research paper nicotine addiction

Vaping: The new wave of nicotine addiction

Affiliations.

• 1 Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH.
• 2 Head, Center for Adolescent Medicine, Department of General Pediatrics, Cleveland Clinic; Professor, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH [email protected].
• PMID: 31821136
• DOI: 10.3949/ccjm.86a.19118

Vaping devices, introduced to the US market in 2007 as aids for smoking cessation, have become popular among youth and young adults because of their enticing flavors and perceived lack of negative health effects. However, evidence is emerging that vaping may introduce high levels of dangerous chemicals into the body and cause severe lung injury and death. This article reviews the history and prevalence of vaping and available research on its health effects and efficacy in smoking cessation, and proposes recommendations for clinicians and legislators to reduce harms associated with vaping.

Copyright © 2019 Cleveland Clinic.

Publication types

• Adolescent Behavior
• Behavior, Addictive* / etiology
• Behavior, Addictive* / prevention & control
• Behavior, Addictive* / psychology
• Electronic Nicotine Delivery Systems*
• United States
• Vaping* / adverse effects
• Vaping* / epidemiology
• Vaping* / prevention & control
• Vaping* / psychology

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Published: 24 March 2022

Tobacco and nicotine use

• Bernard Le Foll 1 , 2 ,
• Megan E. Piper 3 , 4 ,
• Christie D. Fowler 5 ,
• Serena Tonstad 6 ,
• Laura Bierut 7 ,
• Lin Lu   ORCID: orcid.org/0000-0003-0742-9072 8 , 9 ,
• Prabhat Jha 10 &
• Wayne D. Hall 11 , 12  

Nature Reviews Disease Primers volume  8 , Article number:  19 ( 2022 ) Cite this article

43k Accesses

101 Citations

107 Altmetric

Metrics details

• Disease genetics
• Experimental models of disease
• Preventive medicine

Tobacco smoking is a major determinant of preventable morbidity and mortality worldwide. More than a billion people smoke, and without major increases in cessation, at least half will die prematurely from tobacco-related complications. In addition, people who smoke have a significant reduction in their quality of life. Neurobiological findings have identified the mechanisms by which nicotine in tobacco affects the brain reward system and causes addiction. These brain changes contribute to the maintenance of nicotine or tobacco use despite knowledge of its negative consequences, a hallmark of addiction. Effective approaches to screen, prevent and treat tobacco use can be widely implemented to limit tobacco’s effect on individuals and society. The effectiveness of psychosocial and pharmacological interventions in helping people quit smoking has been demonstrated. As the majority of people who smoke ultimately relapse, it is important to enhance the reach of available interventions and to continue to develop novel interventions. These efforts associated with innovative policy regulations (aimed at reducing nicotine content or eliminating tobacco products) have the potential to reduce the prevalence of tobacco and nicotine use and their enormous adverse impact on population health.

Similar content being viewed by others

Associations between classic psychedelics and nicotine dependence in a nationally representative sample

Nicotine dependence and incident psychiatric disorders: prospective evidence from us national study, use of electronic cigarettes and heated tobacco products during the covid-19 pandemic, introduction.

Tobacco is the second most commonly used psychoactive substance worldwide, with more than one billion smokers globally 1 . Although smoking prevalence has reduced in many high-income countries (HICs), tobacco use is still very prevalent in low-income and middle-income countries (LMICs). The majority of smokers are addicted to nicotine delivered by cigarettes (defined as tobacco dependence in the International Classification of Diseases, Tenth Revision (ICD-10) or tobacco use disorder in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5)). As a result of the neuro-adaptations and psychological mechanisms caused by repeated exposure to nicotine delivered rapidly by cigarettes, cessation can also lead to a well-characterized withdrawal syndrome, typically manifesting as irritability, anxiety, low mood, difficulty concentrating, increased appetite, insomnia and restlessness, that contributes to the difficulty in quitting tobacco use 2 , 3 , 4 .

Historically, tobacco was used in some cultures as part of traditional ceremonies, but its use was infrequent and not widely disseminated in the population. However, since the early twentieth century, the use of commercial cigarettes has increased dramatically 5 because of automated manufacturing practices that enable large-scale production of inexpensive products that are heavily promoted by media and advertising. Tobacco use became highly prevalent in the past century and was followed by substantial increases in the prevalence of tobacco-induced diseases decades later 5 . It took decades to establish the relationship between tobacco use and associated health effects 6 , 7 and to discover the addictive role of nicotine in maintaining tobacco smoking 8 , 9 , and also to educate people about these effects. It should be noted that the tobacco industry disputed this evidence to allow continuing tobacco sales 10 . The expansion of public health campaigns to reduce smoking has gradually decreased the use of tobacco in HICs, with marked increases in adult cessation, but less progress has been achieved in LMICs 1 .

Nicotine is the addictive compound in tobacco and is responsible for continued use of tobacco despite harms and a desire to quit, but nicotine is not directly responsible for the harmful effects of using tobacco products (Box  1 ). Other components in tobacco may modulate the addictive potential of tobacco (for example, flavours and non-nicotine compounds) 11 . The major harms related to tobacco use, which are well covered elsewhere 5 , are linked to a multitude of compounds present in tobacco smoke (such as carcinogens, toxicants, particulate matter and carbon monoxide). In adults, adverse health outcomes of tobacco use include cancer in virtually all peripheral organs exposed to tobacco smoke and chronic diseases such as eye disease, periodontal disease, cardiovascular diseases, chronic obstructive pulmonary disease, stroke, diabetes mellitus, rheumatoid arthritis and disorders affecting immune function 5 . Moreover, smoking during pregnancy can increase the risk of adverse reproductive effects, such as ectopic pregnancy, low birthweight and preterm birth 5 . Exposure to secondhand cigarette smoke in children has been linked to sudden infant death syndrome, impaired lung function and respiratory illnesses, in addition to cognitive and behavioural impairments 5 . The long-term developmental effects of nicotine are probably due to structural and functional changes in the brain during this early developmental period 12 , 13 .

Nicotine administered alone in various nicotine replacement formulations (such as patches, gum and lozenges) is safe and effective as an evidence-based smoking cessation aid. Novel forms of nicotine delivery systems have also emerged (called electronic nicotine delivery systems (ENDS) or e-cigarettes), which can potentially reduce the harmful effects of tobacco smoking for those who switch completely from combustible to e-cigarettes 14 , 15 .

This Primer focuses on the determinants of nicotine and tobacco use, and reviews the neurobiology of nicotine effects on the brain reward circuitry and the functioning of brain networks in ways that contribute to the difficulty in stopping smoking. This Primer also discusses how to prevent tobacco use, screen for smoking, and offer people who smoke tobacco psychosocial and pharmacological interventions to assist in quitting. Moreover, this Primer presents emerging pharmacological and novel brain interventions that could improve rates of successful smoking cessation, in addition to public health approaches that could be beneficial.

Box 1 Tobacco products

Conventional tobacco products include combustible products that produce inhaled smoke (most commonly cigarettes, bidis (small domestically manufactured cigarettes used in South Asia) or cigars) and those that deliver nicotine without using combustion (chewing or dipping tobacco and snuff). Newer alternative products that do not involve combustion include nicotine-containing e-cigarettes and heat-not-burn tobacco devices. Although non-combustion and alternative products may constitute a lesser risk than burned ones 14 , 15 , 194 , no form of tobacco is entirely risk-free.

Epidemiology

Prevalence and burden of disease.

The Global Burden of Disease Project (GBDP) estimated that around 1.14 billion people smoked in 2019, worldwide, increasing from just under a billion in 1990 (ref. 1 ). Of note, the prevalence of smoking decreased significantly between 1990 and 2019, but increases in the adult population meant that the total number of global smokers increased. One smoking-associated death occurs for approximately every 0.8–1.1 million cigarettes smoked 16 , suggesting that the estimated worldwide consumption of about 7.4 trillion cigarettes in 2019 has led to around 7 million deaths 1 .

In most populations, smoking prevalence is much higher among groups with lower levels of education or income 17 and among those with mental health disorders and other co-addictions 18 , 19 . Smoking is also more frequent among men than women (Figs  1 – 3 ). Sexual and/or gender minority individuals have disproportionately high rates of smoking and other addictions 17 , 20 . In addition, the prevalence of smoking varies substantially between regions and ethnicities; smoking rates are high in some regions of Asia, such as China and India, but are lower in North America and Australia. Of note, the prevalence of mental health disorders and other co-addictions is higher in individuals who smoke compared with non-smokers 18 , 19 , 21 . For example, the odds of smoking in people with any substance use disorder is more than five times higher than the odds in people without a substance use disorder 19 . Similarly, the odds of smoking in people with any psychiatric disorder is more than three times higher than the odds of smoking in those without a psychiatric diagnosis 22 . In a study in the USA, compared with a population of smokers with no psychiatric diagnosis, subjects with anxiety, depression and phobia showed an approximately twofold higher prevalence of smoking, and subjects with agoraphobia, mania or hypomania, psychosis and antisocial personality or conduct disorders showed at least a threefold higher prevalence of smoking 22 . Comorbid disorders are also associated with higher rates of smoking 22 , 23 .

a | Number of current male smokers aged 15 years or older per country expressed in millions. b | Former male smokers aged 45–59 years per country expressed in millions. c | Former male smokers aged 45–59 years per country expressed as the percentage of smokers who stopped. The data shown are for male smokers for the period 2015–2019 from countries with direct smoking surveys. The prevalence of smoking among males is less variable than among females. Data from ref. 1 .

a | Number of current female smokers aged 15 years or older per country expressed in millions. b | Former female smokers aged 45–59 years per country expressed in millions. c | Former female smokers aged 45–59 years per country expressed as the percentage of smokers who stopped. The data shown are for female smokers for the period 2015–2019 from countries with direct smoking surveys. The prevalence of smoking among females is much lower in East and South Asia than in Latin America or Eastern Europe. Data from ref. 1 .

a | Number of current male and female smokers aged 15 years or older per country expressed in millions. b | Former male and female smokers aged 45–59 years per country expressed in millions. c | Former male and female smokers aged 45–59 years per country expressed as the percentage of smokers who stopped. The data shown are for the period 2015–2019 from countries with direct smoking surveys. Cessation rates are higher in high-income countries, but also notably high in Brazil. Cessation is far less common in South and East Asia and Russia and other Eastern European countries, and also low in South Africa. Data from ref. 1 .

Age at onset

Most smokers start smoking during adolescence, with almost 90% of smokers beginning between 15 and 25 years of age 24 . The prevalence of tobacco smoking among youths substantially declined in multiple HICs between 1990 and 2019 (ref. 25 ). More recently, the widespread uptake of ENDS in some regions such as Canada and the USA has raised concerns about the long-term effects of prolonged nicotine use among adolescents, including the possible notion that ENDS will increase the use of combustible smoking products 25 , 26 (although some studies have not found much aggregate effect at the population level) 27 .

Smoking that commences in early adolescence or young adulthood and persists throughout life has a more severe effect on health than smoking that starts later in life and/or that is not persistent 16 , 28 , 29 . Over 640 million adults under 30 years of age smoke in 22 jurisdictions alone (including 27 countries in the European Union where central efforts to reduce tobacco dependence might be possible) 30 . In those younger than 30 years of age, at least 320 million smoking-related deaths will occur unless they quit smoking 31 . The actual number of smoking-related deaths might be greater than one in two, and perhaps as high as two in three, long-term smokers 5 , 16 , 29 , 32 , 33 . At least half of these deaths are likely to occur in middle age (30–69 years) 16 , 29 , leading to a loss of two or more decades of life. People who smoke can expect to lose an average of at least a decade of life versus otherwise similar non-smokers 16 , 28 , 29 .

Direct epidemiological studies in several countries paired with model-based estimates have estimated that smoking tobacco accounted for 7.7 million deaths globally in 2020, of which 80% were in men and 87% were current smokers 1 . In HICs, the major causes of tobacco deaths are lung cancer, emphysema, heart attack, stroke, cancer of the upper aerodigestive areas and bladder cancer 28 , 29 . In some lower income countries, tuberculosis is an additional important cause of tobacco-related death 29 , 34 , which could be related to, for example, increased prevalence of infection, more severe tuberculosis/mortality and higher prevalence of treatment-resistant tuberculosis in smokers than in non-smokers in low-income countries 35 , 36 .

Despite substantial reductions in the prevalence of smoking, there were 34 million smokers in the USA, 7 million in the UK and 5 million in Canada in 2017 (ref. 16 ), and cigarette smoking remains the largest cause of premature death before 70 years of age in much of Europe and North America 1 , 16 , 28 , 29 . Smoking-associated diseases accounted for around 41 million deaths in the USA, UK and Canada from 1960 to 2020 (ref. 16 ). Moreover, as smoking-associated diseases are more prevalent among groups with lower levels of education and income, smoking accounts for at least half of the difference in overall mortality between these social groups 37 . Any reduction in smoking prevalence reduces the absolute mortality gap between these groups 38 .

Smoking cessation has become common in HICs with good tobacco control interventions. For example, in France, the number of ex-smokers is four times the number of current smokers among those aged 50 years or more 30 . By contrast, smoking cessation in LMICs remains uncommon before smokers develop tobacco-related diseases 39 . Smoking cessation greatly reduces the risks of smoking-related diseases. Indeed, smokers who quit smoking before 40 years of age avoid nearly all the increased mortality risks 31 , 33 . Moreover, individuals who quit smoking by 50 years of age reduce the risk of death from lung cancer by about two-thirds 40 . More modest hazards persist for deaths from lung cancer and emphysema 16 , 28 ; however, the risks among former smokers are an order of magnitude lower than among those who continue to smoke 33 .

Mechanisms/pathophysiology

Nicotine is the main psychoactive agent in tobacco and e-cigarettes. Nicotine acts as an agonist at nicotinic acetylcholine receptors (nAChRs), which are localized throughout the brain and peripheral nervous system 41 . nAChRs are pentameric ion channels that consist of varying combinations of α 2 –α 7 and β 2 –β 4 subunits, and for which acetylcholine (ACh) is the endogenous ligand 42 , 43 , 44 . When activated by nicotine binding, nAChR undergoes a conformational change that opens the internal pore, allowing an influx of sodium and calcium ions 45 . At postsynaptic membranes, nAChR activation can lead to action potential firing and downstream modulation of gene expression through calcium-mediated second messenger systems 46 . nAChRs are also localized to presynaptic membranes, where they modulate neurotransmitter release 47 . nAChRs become desensitized after activation, during which ligand binding will not open the channel 45 .

nAChRs with varying combinations of α-subunits and β-subunits have differences in nicotine binding affinity, efficacy and desensitization rate, and have differential expression depending on the brain region and cell type 48 , 49 , 50 . For instance, at nicotine concentrations found in human smokers, β 2 -containing nAChRs desensitize relatively quickly after activation, whereas α 7 -containing nAChRs have a slower desensitization profile 48 . Chronic nicotine exposure in experimental animal models or in humans induces an increase in cortical expression of α 4 β 2 -containing nAChRs 51 , 52 , 53 , 54 , 55 , but also increases the expression of β 3 and β 4 nAChR subunits in the medial habenula (MHb)–interpeduncular nucleus (IPN) pathway 56 , 57 . It is clear that both the brain localization and the type of nAChR are critical elements in mediating the various effects of nicotine, but other factors such as rate of nicotine delivery may also modulate addictive effects of nicotine 58 .

Neurocircuitry of nicotine addiction

Nicotine has both rewarding effects (such as a ‘buzz’ or ‘high’) and aversive effects (such as nausea and dizziness), with the net outcome dependent on dose and others factors such as interindividual sensitivity and presence of tolerance 59 . Thus, the addictive properties of nicotine involve integration of contrasting signals from multiple brain regions that process reward and aversion (Fig.  4 ).

During initial use, nicotine exerts both reinforcing and aversive effects, which together determine the likelihood of continued use. As the individual transitions to more frequent patterns of chronic use, nicotine induces pharmacodynamic changes in brain circuits, which is thought to lead to a reduction in sensitivity to the aversive properties of the drug. Nicotine is also a powerful reinforcer that leads to the conditioning of secondary cues associated with the drug-taking experience (such as cigarette pack, sensory properties of cigarette smoke and feel of the cigarette in the hand or mouth), which serves to enhance the incentive salience of these environmental factors and drive further drug intake. When the individual enters into states of abstinence (such as daily during sleep at night or during quit attempts), withdrawal symptomology is experienced, which may include irritability, restlessness, learning or memory deficits, difficulty concentrating, anxiety and hunger. These negative affective and cognitive symptoms lead to an intensification of the individual’s preoccupation to obtain and use the tobacco/nicotine product, and subsequently such intense craving can lead to relapse.

The rewarding actions of nicotine have largely been attributed to the mesolimbic pathway, which consists of dopaminergic neurons in the ventral tegmental area (VTA) that project to the nucleus accumbens and prefrontal cortex 60 , 61 , 62 (Fig.  5 ). VTA integrating circuits and projection regions express several nAChR subtypes on dopaminergic, GABAergic, and glutamatergic neurons 63 , 64 . Ultimately, administration of nicotine increases dopamine levels through increased dopaminergic neuron firing in striatal and extrastriatal areas (such as the ventral pallidum) 65 (Fig.  6 ). This effect is involved in reward and is believed to be primarily mediated by the action of nicotine on α 4 -containing and β 2 -containing nAChRs in the VTA 66 , 67 .

Multiple lines of research have demonstrated that nicotine reinforcement is mainly controlled by two brain pathways, which relay predominantly reward-related or aversion-related signals. The rewarding properties of nicotine that promote drug intake involve the mesolimbic dopamine projection from the ventral tegmental area (VTA) to the nucleus accumbens (NAc). By contrast, the aversive properties of nicotine that limit drug intake and mitigate withdrawal symptoms involve the fasciculus retroflexus projection from the medial habenula (MHb) to the interpeduncular nucleus (IPN). Additional brain regions have also been implicated in various aspects of nicotine dependence, such as the prefrontal cortex (PFC), ventral pallidum (VP), nucleus tractus solitarius (NTS) and insula (not shown here for clarity). All of these brain regions are directly or indirectly interconnected as integrative circuits to drive drug-seeking and drug-taking behaviours.

Smokers received brain PET scans with [ 11 C]PHNO, a dopamine D 2/3 PET tracer that has high sensitivity in detecting fluctuations of dopamine. PET scans were performed during abstinence or after smoking a cigarette. Reduced binding potential (BP ND ) was observed after smoking, indicating increased dopamine levels in the ventral striatum and in the area that corresponds to the ventral pallidum. The images show clusters with statistically significant decreases of [ 11 C]PHNO BP ND after smoking a cigarette versus abstinence condition. Those clusters have been superimposed on structural T1 MRI images of the brain. Reprinted from ref. 65 , Springer Nature Limited.

The aversive properties of nicotine are mediated by neurons in the MHb, which project to the IPN. Studies in rodents using genetic knockdown and knockout strategies demonstrated that the α 5 -containing, α 3 -containing and β 4 -containing nAChRs in the MHb–IPN pathway mediate the aversive properties of nicotine that limit drug intake, especially when animals are given the opportunity to consume higher nicotine doses 68 , 69 , 70 , 71 , 72 . In addition to nAChRs, other signalling factors acting on the MHb terminals in the IPN also regulate the actions of nicotine. For instance, under conditions of chronic nicotine exposure or with optogenetic activation of IPN neurons, a subtype of IPN neurons co-expressing Chrna5 (encoding the α 5 nAChR subunit) and Amigo1 (encoding adhesion molecule with immunoglobulin-like domain 1) release nitric oxide from the cell body that retrogradely inhibits MHb axon terminals 70 . In addition, nicotine activates α 5 -containing nAChR-expressing neurons that project from the nucleus tractus solitarius to the IPN, leading to release of glucagon-like peptide-1 that binds to GLP receptors on habenular axon terminals, which subsequently increases IPN neuron activation and decreases nicotine self-administration 73 . Taken together, these findings suggest a dynamic signalling process at MHb axonal terminals in the IPN, which regulates the addictive properties of nicotine and determines the amount of nicotine that is self-administered.

Nicotine withdrawal in animal models can be assessed by examining somatic signs (such as shaking, scratching, head nods and chewing) and affective signs (such as increased anxiety-related behaviours and conditioned place aversion). Interestingly, few nicotine withdrawal somatic signs are found in mice with genetic knockout of the α 2 , α 5 or β 4 nAChR subunits 74 , 75 . By contrast, β 2 nAChR-knockout mice have fewer anxiety-related behaviours during nicotine withdrawal, with no differences in somatic symptoms compared with wild-type mice 74 , 76 .

In addition to the VTA (mediating reward) and the MHb–IPN pathway (mediating aversion), other brain areas are involved in nicotine addiction (Fig.  5 ). In animals, the insular cortex controls nicotine taking and nicotine seeking 77 . Moreover, humans with lesions of the insular cortex can quit smoking easily without relapse 78 . This finding led to the development of a novel therapeutic intervention modulating insula function (see Management, below) 79 , 80 . Various brain areas (shell of nucleus accumbens, basolateral amygdala and prelimbic cortex) expressing cannabinoid CB 1 receptors are also critical in controlling rewarding effects and relapse 81 , 82 . The α 1 -adrenergic receptor expressed in the cortex also control these effects, probably through glutamatergic afferents to the nucleus accumbens 83 .

Individual differences in nicotine addiction risk

Vulnerability to nicotine dependence varies between individuals, and the reasons for these differences are multidimensional. Many social factors (such as education level and income) play a role 84 . Broad psychological and social factors also modulate this risk. For example, peer smoking status, knowledge on effect of tobacco, expectation on social acceptance, exposure to passive smoking modulate the risk of initiating tobacco use 85 , 86 .

Genetic factors have a role in smoking initiation, the development of nicotine addiction and the likelihood of smoking cessation. Indeed, heritability has been estimated to contribute to approximatively half of the variability in nicotine dependence 87 , 88 , 89 , 90 . Important advances in our understanding of such genetic contributions have evolved with large-scale genome-wide association studies of smokers and non-smokers. One of the most striking findings has been that allelic variation in the CHRNA5 – CHRNA3 – CHRNB4 gene cluster, which encodes α 5 , α 3 and β 4 nAChR subunits, correlates with an increased vulnerability for nicotine addiction, indicated by a higher likelihood of becoming dependent on nicotine and smoking a greater number of cigarettes per day 91 , 92 , 93 , 94 , 95 . The most significant effect has been found for a single-nucleotide polymorphism in CHRNA5 (rs16969968), which results in an amino acid change and reduced function of α 5 -containing nAChRs 92 .

Allelic variation in CYP2A6 (encoding the CYP2A6 enzyme, which metabolizes nicotine) has also been associated with differential vulnerability to nicotine dependence 96 , 97 , 98 . CYP2A6 is highly polymorphic, resulting in variable enzymatic activity 96 , 99 , 100 . Individuals with allelic variation that results in slow nicotine metabolism consume less nicotine per day, experience less-severe withdrawal symptoms and are more successful at quitting smoking than individuals with normal or fast metabolism 101 , 102 , 103 , 104 . Moreover, individuals with slow nicotine metabolism have lower dopaminergic receptor expression in the dopamine D2 regions of the associative striatum and sensorimotor striatum in PET studies 105 and take fewer puffs of nicotine-containing cigarettes (compared with de-nicotinized cigarettes) in a forced choice task 106 . Slower nicotine metabolism is thought to increase the duration of action of nicotine, allowing nicotine levels to accumulate over time, therefore enabling lower levels of intake to sustain activation of nAChRs 107 .

Large-scale genetic studies have identified hundreds of other genetic loci that influence smoking initiation, age of smoking initiation, cigarettes smoked per day and successful smoking cessation 108 . The strongest genetic contributions to smoking through the nicotinic receptors and nicotine metabolism are among the strongest genetic contributors to lung cancer 109 . Other genetic variations (such as those related to cannabinoid, dopamine receptors or other neurotransmitters) may affect certain phenotypes related to smoking (such as nicotine preference and cue-reactivity) 110 , 111 , 112 , 113 , 114 , 115 .

Diagnosis, screening and prevention

Screening for cigarette smoking.

Screening for cigarette smoking should happen at every doctor’s visit 116 . In this regard, a simple and direct question about a person’s tobacco use can provide an opportunity to offer information about its potential risks and treatments to assist in quitting. All smokers should be offered assistance in quitting because even low levels of smoking present a significant health risk 33 , 117 , 118 . Smoking status can be assessed by self-categorization or self-reported assessment of smoking behaviour (Table  1 ). In people who smoke, smoking frequency can be assessed 119 and a combined quantity frequency measure such as pack-year history (that is, average number of cigarettes smoked per day multiplied by the number of years, divided by 20), can be used to estimate cumulative risk of adverse health outcomes. The Association for the Treatment of Tobacco Use and Dependence recommends that all electronic health records should document smoking status using the self-report categories listed in Table  1 .

Owing to the advent of e-cigarettes and heat-not-burn products, and the popularity of little cigars in the US that mimic combustible cigarettes, people who use tobacco may use multiple products concurrently 120 , 121 . Thus, screening for other nicotine and tobacco product use is important in clinical practice. The self-categorization approach can also be used to describe the use of these other products.

Traditionally tobacco use has been classified according to whether the smoker meets criteria for nicotine dependence in one of the two main diagnostic classifications: the DSM 122 (tobacco use disorder) and the ICD (tobacco dependence) 123 . The diagnosis of tobacco use disorder according to DSM-5 criteria requires the presence of at least 2 of 11 symptoms that have produced marked clinical impairment or distress within a 12-month period (Box  2 ). Of note, these symptoms are similar for all substance use disorder diagnoses and may not all be relevant to tobacco use disorder (such as failure to complete life roles). In the ICD-10, codes allow the identification of specific tobacco products used (cigarettes, chewing tobacco and other tobacco products).

Dependence can also be assessed as a continuous construct associated with higher levels of use, greater withdrawal and reduced likelihood of quitting. The level of dependence can be assessed with the Fagerström Test for Nicotine Dependence, a short questionnaire comprising six questions 124 (Box  2 ). A score of ≥4 indicates moderate to high dependence. As very limited time may be available in clinical consultations, the Heaviness of Smoking Index (HSI) was developed, which comprises two questions on the number of cigarettes smoked per day and how soon after waking the first cigarette is smoked 125 . The HSI can guide dosing for nicotine replacement therapy (NRT).

Other measures of cigarette dependence have been developed but are not used in the clinical setting, such as the Cigarette Dependence Scale 126 , Hooked on Nicotine Checklist 127 , Nicotine Dependence Syndrome Scale 128 , the Wisconsin Inventory of Smoking Dependence Motives (Brief) 129 and the Penn State Cigarette Dependence Index 130 . However, in practice, these are not often used, as the most important aspect is to screen for smoking and encourage all smokers to quit smoking regardless of their dependence status.

Box 2 DSM-5 criteria for tobacco use disorder and items of the Fagerström Test for nicotine dependence

DSM-5 (ref. 122 )

Taxonomic and diagnostic tool for tobacco use disorder published by the American Psychiatric Association.

A problematic pattern of tobacco use leading to clinically significant impairment or distress as manifested by at least two of the following, occurring within a 12-month period.

Tobacco often used in larger amounts or over a longer period of time than intended

A persistent desire or unsuccessful efforts to reduce or control tobacco use

A great deal of time spent in activities necessary to obtain or use tobacco

Craving, or a strong desire or urge to use tobacco

Recurrent tobacco use resulting in a failure to fulfil major role obligations at work, school or home

Continued tobacco use despite having persistent or recurrent social or interpersonal problems caused or exacerbated by the effects of tobacco (for example, arguments with others about tobacco use)

Important social, occupational or recreational activities given up or reduced because of tobacco use

Recurrent tobacco use in hazardous situations (such as smoking in bed)

Tobacco use continued despite knowledge of having a persistent or recurrent physical or psychological problem that is likely to have been caused or exacerbated by tobacco use

Tolerance, defined by either of the following.

A need for markedly increased amounts of tobacco to achieve the desired effect

A markedly diminished effect with continued use of the same amount of tobacco

Withdrawal, manifesting as either of the following.

Withdrawal syndrome for tobacco

Tobacco (or a closely related substance, such as nicotine) taken to relieve or avoid withdrawal symptoms

Fagerström Test for Nicotine Dependence 124

A standard instrument for assessing the intensity of physical addiction to nicotine.

How soon after you wake up do you smoke your first cigarette?

Within 5 min (scores 3 points)

5 to 30 min (scores 2 points)

31 to 60 min (scores 1 point)

After 60 min (scores 0 points)

Do you find it difficult not to smoke in places where you should not, such as in church or school, in a movie, at the library, on a bus, in court or in a hospital?

Yes (scores 1 point)

No (scores 0 points)

Which cigarette would you most hate to give up; which cigarette do you treasure the most?

The first one in the morning (scores 1 point)

Any other one (scores 0 points)

How many cigarettes do you smoke each day?

10 or fewer (scores 0 points)

11 to 20 (scores 1 point)

21 to 30 (scores 2 points)

31 or more (scores 3 points)

Do you smoke more during the first few hours after waking up than during the rest of the day?

Do you still smoke if you are so sick that you are in bed most of the day or if you have a cold or the flu and have trouble breathing?

A score of 7–10 points is classified as highly dependent; 4–6 points is classified as moderately dependent; <4 points is classified as minimally dependent.

DSM-5, Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition.

Young people who do not start smoking cigarettes between 15 and 25 years of age have a very low risk of ever smoking 24 , 131 , 132 . This age group provides a critical opportunity to prevent cigarette smoking using effective, evidence-based strategies to prevent smoking initiation and reduce escalation from experimentation to regular use 131 , 132 , 133 , 134 , 135 .

Effective prevention of cigarette uptake requires a comprehensive package of cost-effective policies 134 , 136 , 137 to synergistically reduce the population prevalence of cigarette smoking 131 , 135 . These policies include high rates of tobacco taxation 30 , 134 , 137 , 138 , widespread and rigorously enforced smoke-free policies 139 , bans on tobacco advertising and promotions 140 , use of plain packaging and graphic warnings about the health risks of smoking 135 , 141 , mass media and peer-based education programmes to discourage smoking, and enforcement of laws against the sale of cigarettes to young people below the minimum legal purchase age 131 , 135 . These policies make cigarettes less available and affordable to young people. Moreover, these policies make it more difficult for young people to purchase cigarettes and make smoking a much less socially acceptable practice. Of note, these policies are typically mostly enacted in HICs, which may be related to the declining prevalence of smoking in these countries, compared with the prevalence in LMICs.

Pharmacotherapy

Three evidence-based classes of pharmacotherapy are available for smoking cessation: NRT (using nicotine-based patches, gum, lozenges, mini-lozenges, nasal sprays and inhalers), varenicline (a nAChR partial agonist), and bupropion (a noradrenaline/dopamine reuptake inhibitor that also inhibits nAChR function and is also used as an antidepressant). These FDA-approved and EMA-approved pharmacotherapies are cost-effective smoking cessation treatments that double or triple successful abstinence rates compared with no treatment or placebo controls 116 , 142 .

Combinations of pharmacotherapies are also effective for smoking cessation 116 , 142 . For example, combining NRTs (such as the steady-state nicotine patch and as-needed NRT such as gum or mini-lozenge) is more effective than a single form of NRT 116 , 142 , 143 . Combining NRT and varenicline is the most effective smoking cessation pharmacotherapy 116 , 142 , 143 . Combining FDA-approved pharmacotherapy with behavioural counselling further increases the likelihood of successful cessation 142 . Second-line pharmacotherapies (for example, nortriptyline) have some potential for smoking cessation, but their use is limited due to their tolerability profile.

All smokers should receive pharmacotherapy to help them quit smoking, except those in whom pharmacotherapy has insufficient evidence of effectiveness (among adolescents, smokeless tobacco users, pregnant women or light smokers) or those in whom pharmacotherapy is medically contraindicated 144 . Table  2 provides specific information regarding dosing and duration for each FDA-approved pharmacotherapy. Extended use of pharmacotherapy beyond the standard 12-week regimen after cessation is effective and should be considered 116 . Moreover, preloading pharmacotherapy (that is, initiating cessation medication in advance of a quit attempt), especially with the nicotine patch, is a promising treatment, although further studies are required to confirm efficacy.

Cytisine has been used for smoking cessation in Eastern Europe for a long time and is available in some countries (such as Canada) without prescription 145 . Cytisine is a partial agonist of nAChRs and its structure was the precursor for the development of varenicline 145 . Cytisine is at least as effective as some approved pharmacotherapies for smoking cessation, such as NRT 146 , 147 , 148 , and the role of cytisine in smoking cessation is likely to expand in the future, notably owing to its much lower cost than traditional pharmacotherapies. E-cigarettes also have the potential to be useful as smoking cessation devices 149 , 150 . The 2020 US Surgeon General’s Report concluded that there was insufficient evidence to promote cytisine or e-cigarettes as effective smoking cessation treatments, but in the UK its use is recommended for smoking cessation (see ref. 15 for regularly updated review).

Counselling and behavioural treatments

Psychosocial counselling significantly increases the likelihood of successful cessation, especially when combined with pharmacotherapy. Even a counselling session lasting only 3 minutes can help smokers quit 116 , although the 2008 US Public Health Service guidelines and the Preventive Services Task Force 151 each concluded that more intensive counselling (≥20 min per session) is more effective than less intensive counselling (<20 min per session). Higher smoking cessation rates are obtained by using behavioural change techniques that target associative and self-regulatory processes 152 . In addition, behavioural change techniques that will favour commitment, social reward and identity associated with changed behaviour seems associated with higher success rates 152 . Evidence-based counselling focuses on providing social support during treatment, building skills to cope with withdrawal and cessation, and problem-solving in challenging situations 116 , 153 . Effective counselling can be delivered by diverse providers (such as physicians, nurses, pharmacists, social workers, psychologists and certified tobacco treatment specialists) 116 .

Counselling can be delivered in a variety of modalities. In-person individual and group counselling are effective, as is telephone counselling (quit lines) 142 . Internet and text-based intervention seem to be effective in smoking cessation, especially when they are interactive and tailored to a smoker’s specific circumstances 142 . Over the past several years, the number of smoking cessation smartphone apps has increased, but there the evidence that the use of these apps significantly increases smoking cessation rates is not sufficient.

Contingency management (providing financial incentives for abstinence or engagement in treatment) has shown promising results 154 , 155 but its effects are not sustained once the contingencies are removed 155 , 156 . Other treatments such as hypnosis, acupuncture and laser treatment have not been shown to improve smoking cessation rates compared with placebo treatments 116 . Moreover, no solid evidence supports the use of conventional transcranial magnetic stimulation (TMS) for long-term smoking cessation 157 , 158 .

Although a variety of empirically supported smoking cessation interventions are available, more than two-thirds of adult smokers who made quit attempts in the USA during the past year did not use an evidence-based treatment and the rate is likely to be lower in many other countries 142 . This speaks to the need to increase awareness of, and access to, effective cessation aids among all smokers.

Brain stimulation

The insula (part of the frontal cortex) is a critical brain structure involved in cigarette craving and relapse 78 , 79 . The activity of the insula can be modulated using an innovative approach called deep insula/prefrontal cortex TMS (deep TMS), which is effective in helping people quit smoking 80 , 159 . This approach has now been approved by the FDA as an effective smoking cessation intervention 80 . However, although this intervention was developed and is effective for smoking cessation, the number of people with access to it is limited owing to the limited number of sites equipped and with trained personnel, and the cost of this intervention.

Quality of life

Generic instruments (such as the Short-Form (SF-36) Health Survey) can be used to evaluate quality of life (QOL) in smokers. People who smoke rate their QOL lower than people who do not smoke both before and after they become smokers 160 , 161 . QOL improves when smokers quit 162 . Mental health may also improve on quitting smoking 163 . Moreover, QOL is much poorer in smokers with tobacco-related diseases, such as chronic respiratory diseases and cancers, than in individuals without tobacco-related diseases 161 , 164 . The dimensions of QOL that show the largest decrements in people who smoke are those related to physical health, day-to-day activities and mental health such as depression 160 . Smoking also increases the risk of diabetes mellitus 165 , 166 , which is a major determinant of poor QOL for a wide range of conditions.

The high toll of premature death from cigarette smoking can obscure the fact that many of the diseases that cause these deaths also produce substantial disability in the years before death 1 . Indeed, death in smokers is typically preceded by several years of living with the serious disability and impairment of everyday activities caused by chronic respiratory disease, heart disease and cancer 2 . Smokers’ QOL in these years may also be adversely affected by the adverse effects of the medical treatments that they receive for these smoking-related diseases (such as major surgery and radiotherapy).

Expanding cessation worldwide

The major global challenge is to consider individual and population-based strategies that could increase the substantially low rates of adult cessation in most LMICs and indeed strategies to ensure that even in HICs, cessation continues to increase. In general, the most effective tools recommended by WHO to expand cessation are the same tools that can prevent smoking initiation, notably higher tobacco taxes, bans on advertising and promotion, prominent warning labels or plain packaging, bans on public smoking, and mass media and educational efforts 29 , 167 . The effective use of these policies, particularly taxation, lags behind in most LMICs compared with most HICs, with important exceptions such as Brazil 167 . Access to effective pharmacotherapies and counselling as well as support for co-existing mental health conditions would also be required to accelerate cessation in LMICs. This is particularly important as smokers living in LMICs often have no access to the full range of effective treatment options.

Regulating access to e-cigarettes

How e-cigarettes should be used is debated within the tobacco control field. In some countries (for example, the UK), the use of e-cigarettes as a cigarette smoking cessation aid and as a harm reduction strategy is supported, based on the idea that e-cigarette use will lead to much less exposure to toxic compounds than tobacco use, therefore reducing global harm. In other countries (for example, the USA), there is more concern with preventing the increased use of e-cigarettes by youths that may subsequently lead to smoking 25 , 26 . Regulating e-cigarettes in nuanced ways that enable smokers to access those products whilst preventing their uptake among youths is critical.

Regulating nicotine content in tobacco products

Reducing the nicotine content of cigarettes could potentially produce less addictive products that would allow a gradual reduction in the population prevalence of smoking. Some clinical studies have found no compensatory increase in smoking whilst providing access to low nicotine tobacco 168 . Future regulation may be implemented to gradually decrease the nicotine content of combustible tobacco and other nicotine products 169 , 170 , 171 .

Tobacco end games

Some individuals have proposed getting rid of commercial tobacco products this century or using the major economic disruption arising from the COVID-19 pandemic to accelerate the demise of the tobacco industry 172 , 173 . Some tobacco producers have even proposed this strategy as an internal goal, with the idea of switching to nicotine delivery systems that are less harmful ( Philip Morris International ). Some countries are moving towards such an objective; for example, in New Zealand, the goal that fewer than 5% of New Zealanders will be smokers in 2025 has been set (ref. 174 ). The tobacco end-game approach would overall be the best approach to reduce the burden of tobacco use on society, but it would require coordination of multiple countries and strong public and private consensus on the strategy to avoid a major expansion of the existing illicit market in tobacco products in some countries.

Innovative interventions

The COVID-19 pandemic has shown that large-scale investment in research can lead to rapid development of successful therapeutic interventions. By contrast, smoking cessation has been underfunded compared with the contribution that it makes to the global burden of disease. In addition, there is limited coordination between research teams and most studies are small-scale and often underpowered 79 . It is time to fund an ambitious, coordinated programme of research to test the most promising therapies based on an increased understanding of the neurobiological basis of smoking and nicotine addiction (Table  3 ). Many of those ideas have not yet been tested properly and this could be carried out by a coordinated programme of research at the international level.

GBD 2019 Tobacco Collaborators. Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and attributable disease burden in 204 countries and territories, 1990-2019: a systematic analysis from the Global Burden of Disease Study 2019. Lancet 397 , 2337–2360 (2021). This study summarizes the burden of disease induced by tobacco worldwide .

Google Scholar  

West, R. Tobacco smoking: health impact, prevalence, correlates and interventions. Psychol. Health 32 , 1018–1036 (2017).

PubMed   PubMed Central   Google Scholar  

West, R. The multiple facets of cigarette addiction and what they mean for encouraging and helping smokers to stop. COPD 6 , 277–283 (2009).

PubMed   Google Scholar  

Fagerström, K. Determinants of tobacco use and renaming the FTND to the Fagerström test for cigarette dependence. Nicotine Tob. Res. 14 , 75–78 (2012).

National Center for Chronic Disease Prevention and Health Promotion (US) Office on Smoking and Health. The Health Consequences of Smoking: 50 Years of Progress. A Report of the Surgeon General (Centers for Disease Control and Prevention, 2014).

Doll, R. & Hill, A. B. Smoking and carcinoma of the lung; preliminary report. Br. Med. J. 2 , 739–748 (1950).

CAS   PubMed   PubMed Central   Google Scholar  

Royal College of Physicians. Smoking and health. Summary of a report of the Royal College of Physicians of London on smoking in relation to cancer of the lung and other diseases (Pitman Medical Publishing, 1962).

Henningfield, J. E., Smith, T. T., Kleykamp, B. A., Fant, R. V. & Donny, E. C. Nicotine self-administration research: the legacy of Steven R. Goldberg and implications for regulation, health policy, and research. Psychopharmacology 233 , 3829–3848 (2016).

Le Foll, B. & Goldberg, S. R. Effects of nicotine in experimental animals and humans: an update on addictive properties. Hand. Exp. Pharmacol. https://doi.org/10.1007/978-3-540-69248-5_12 (2009).

Article   Google Scholar  

Proctor, R. N. The history of the discovery of the cigarette–lung cancer link: evidentiary traditions, corporate denial, global toll. Tob. Control. 21 , 87–91 (2012).

Hall, B. J. et al. Differential effects of non-nicotine tobacco constituent compounds on nicotine self-administration in rats. Pharmacol. Biochem. Behav. 120 , 103–108 (2014).

Musso, F. et al. Smoking impacts on prefrontal attentional network function in young adult brains. Psychopharmacology 191 , 159–169 (2007).

CAS   PubMed   Google Scholar  

Goriounova, N. A. & Mansvelder, H. D. Short- and long-term consequences of nicotine exposure during adolescence for prefrontal cortex neuronal network function. Cold Spring Harb. Perspect. Med. 2 , a012120 (2012).

Fagerström, K. O. & Bridgman, K. Tobacco harm reduction: the need for new products that can compete with cigarettes. Addictive Behav. 39 , 507–511 (2014).

Hartmann-Boyce, J. et al. Electronic cigarettes for smoking cessation. Cochrane Database Syst. Rev. 9 , CD010216 (2021).

Jha, P. The hazards of smoking and the benefits of cessation: a critical summation of the epidemiological evidence in high-income countries. eLife https://doi.org/10.7554/eLife.49979 (2020).

Article   PubMed   PubMed Central   Google Scholar  

Palipudi, K. M. et al. Social determinants of health and tobacco use in thirteen low and middle income countries: evidence from Global Adult Tobacco Survey. PLoS ONE 7 , e33466 (2012).

Goodwin, R. D., Pagura, J., Spiwak, R., Lemeshow, A. R. & Sareen, J. Predictors of persistent nicotine dependence among adults in the United States. Drug Alcohol. Depend. 118 , 127–133 (2011).

Weinberger, A. H. et al. Cigarette use is increasing among people with illicit substance use disorders in the United States, 2002-14: emerging disparities in vulnerable populations. Addiction 113 , 719–728 (2018).

Evans-Polce, R. J., Kcomt, L., Veliz, P. T., Boyd, C. J. & McCabe, S. E. Alcohol, tobacco, and comorbid psychiatric disorders and associations with sexual identity and stress-related correlates. Am. J. Psychiatry 177 , 1073–1081 (2020).

Hassan, A. N. & Le Foll, B. Survival probabilities and predictors of major depressive episode incidence among individuals with various types of substance use disorders. J. Clin. Psychiatry https://doi.org/10.4088/JCP.20m13637 (2021).

Article   PubMed   Google Scholar  

Smith, P. H., Mazure, C. M. & McKee, S. A. Smoking and mental illness in the U.S. population. Tob. Control. 23 , e147–e153 (2014).

Bourgault, Z., Rubin-Kahana, D. S., Hassan, A. N., Sanches, M. & Le Foll, B. Multiple substance use disorders and self-reported cognitive function in U.S. adults: associations and sex-differences in a nationally representative sample. Front. Psychiatry https://doi.org/10.3389/fpsyt.2021.797578 (2022).

Reitsma, M. B. et al. Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and initiation among young people in 204 countries and territories, 1990-2019. Lancet Public Health 6 , e472–e481 (2021).

Warner, K. E. How to think–not feel–about tobacco harm reduction. Nicotine Tob. Res. 21 , 1299–1309 (2019).

Soneji, S. et al. Association between initial use of e-cigarettes and subsequent cigarette smoking among adolescents and young adults: a systematic review and meta-analysis. JAMA Pediatr. 171 , 788–797 (2017).

Levy, D. T. et al. Examining the relationship of vaping to smoking initiation among US youth and young adults: a reality check. Tob. Control. 28 , 629–635 (2019).

National Center for Chronic Disease Prevention and Health Promotion (US) Office on Smoking and Health. The health consequences of smoking — 50 years of progress: a report of the Surgeon General (Centers for Disease Control and Prevention, 2014).

Jha, P. & Peto, R. Global effects of smoking, of quitting, and of taxing tobacco. N. Engl. J. Med. 370 , 60–68 (2014). This review covers the impact of tobacco, of quitting smoking and the importance of taxation to impact prevalence of smoking .

Jha, P. & Peto., R. in Tobacco Tax Reform: At the Crossroads of Health and Development . (eds Marquez, P. V. & Moreno-Dodson, B.) 55–72 (World Bank Group, 2017).

Jha, P. et al. 21st-century hazards of smoking and benefits of cessation in the United States. N. Engl. J. Med. 368 , 341–350 (2013).

Banks, E. et al. Tobacco smoking and all-cause mortality in a large Australian cohort study: findings from a mature epidemic with current low smoking prevalence. BMC Med. 13 , 38 (2015).

Pirie, K. et al. The 21st century hazards of smoking and benefits of stopping: a prospective study of one million women in the UK. Lancet 381 , 133–141 (2013).

Jha, P. et al. A nationally representative case-control study of smoking and death in India. N. Engl. J. Med. 358 , 1137–1147 (2008).

Chan, E. D. et al. Tobacco exposure and susceptibility to tuberculosis: is there a smoking gun? Tuberculosis 94 , 544–550 (2014).

Wang, M. G. et al. Association between tobacco smoking and drug-resistant tuberculosis. Infect. Drug Resist. 11 , 873–887 (2018).

Jha, P. et al. Social inequalities in male mortality, and in male mortality from smoking: indirect estimation from national death rates in England and Wales, Poland, and North America. Lancet 368 , 367–370 (2006).

Jha, P., Gelband, H, Irving, H. & Mishra, S. in Reducing Social Inequalities in Cancer: Evidence and Priorities for Research (eds Vaccarella, S et al.) 161–166 (IARC, 2018).

Jha, P. Expanding smoking cessation world-wide. Addiction 113 , 1392–1393 (2018).

Jha, P. Avoidable global cancer deaths and total deaths from smoking. Nat. Rev. Cancer 9 , 655–664 (2009).

Wittenberg, R. E., Wolfman, S. L., De Biasi, M. & Dani, J. A. Nicotinic acetylcholine receptors and nicotine addiction: a brief introduction. Neuropharmacology 177 , 108256 (2020).

Boulter, J. et al. Functional expression of two neuronal nicotinic acetylcholine receptors from cDNA clones identifies a gene family. Proc. Natl Acad. Sci. USA 84 , 7763–7767 (1987).

Couturier, S. et al. A neuronal nicotinic acetylcholine receptor subunit (α7) is developmentally regulated and forms a homo-oligomeric channel blocked by α-BTX. Neuron 5 , 847–856 (1990).

Picciotto, M. R., Addy, N. A., Mineur, Y. S. & Brunzell, D. H. It is not “either/or”: activation and desensitization of nicotinic acetylcholine receptors both contribute to behaviors related to nicotine addiction and mood. Prog. Neurobiol. 84 , 329–342 (2008).

Changeux, J. P. Structural identification of the nicotinic receptor ion channel. Trends Neurosci. 41 , 67–70 (2018).

McKay, B. E., Placzek, A. N. & Dani, J. A. Regulation of synaptic transmission and plasticity by neuronal nicotinic acetylcholine receptors. Biochem. Pharmacol. 74 , 1120–1133 (2007).

Wonnacott, S. Presynaptic nicotinic ACh receptors. Trends Neurosci. 20 , 92–98 (1997).

Wooltorton, J. R., Pidoplichko, V. I., Broide, R. S. & Dani, J. A. Differential desensitization and distribution of nicotinic acetylcholine receptor subtypes in midbrain dopamine areas. J. Neurosci. 23 , 3176–3185 (2003).

Gipson, C. D. & Fowler, C. D. Nicotinic receptors underlying nicotine dependence: evidence from transgenic mouse models. Curr. Top. Behav. Neurosci. 45 , 101–121 (2020).

Hamouda, A. K. et al. Potentiation of (α4)2(β2)3, but not (α4)3(β2)2, nicotinic acetylcholine receptors reduces nicotine self-administration and withdrawal symptoms. Neuropharmacology 190 , 108568 (2021).

Lallai, V. et al. Nicotine acts on cholinergic signaling mechanisms to directly modulate choroid plexus function. eNeuro https://doi.org/10.1523/ENEURO.0051-19.2019 (2019).

Benwell, M. E., Balfour, D. J. & Anderson, J. M. Evidence that tobacco smoking increases the density of (-)-[3H]nicotine binding sites in human brain. J. Neurochem. 50 , 1243–1247 (1988).

Perry, D. C., Davila-Garcia, M. I., Stockmeier, C. A. & Kellar, K. J. Increased nicotinic receptors in brains from smokers: membrane binding and autoradiography studies. J. Pharmacol. Exp. Ther. 289 , 1545–1552 (1999).

Marks, M. J. et al. Nicotine binding and nicotinic receptor subunit RNA after chronic nicotine treatment. J. Neurosci. 12 , 2765–2784 (1992).

Le Foll, B. et al. Impact of short access nicotine self-administration on expression of α4β2* nicotinic acetylcholine receptors in non-human primates. Psychopharmacology 233 , 1829–1835 (2016).

Meyers, E. E., Loetz, E. C. & Marks, M. J. Differential expression of the beta4 neuronal nicotinic receptor subunit affects tolerance development and nicotinic binding sites following chronic nicotine treatment. Pharmacol. Biochem. Behav. 130 , 1–8 (2015).

Zhao-Shea, R., Liu, L., Pang, X., Gardner, P. D. & Tapper, A. R. Activation of GABAergic neurons in the interpeduncular nucleus triggers physical nicotine withdrawal symptoms. Curr. Biol. 23 , 2327–2335 (2013).

Jensen, K. P., Valentine, G., Gueorguieva, R. & Sofuoglu, M. Differential effects of nicotine delivery rate on subjective drug effects, urges to smoke, heart rate and blood pressure in tobacco smokers. Psychopharmacology 237 , 1359–1369 (2020).

Villanueva, H. F., James, J. R. & Rosecrans, J. A. Evidence of pharmacological tolerance to nicotine. NIDA Res. Monogr. 95 , 349–350 (1989).

Corrigall, W. A., Coen, K. M. & Adamson, K. L. Self-administered nicotine activates the mesolimbic dopamine system through the ventral tegmental area. Brain Res. 653 , 278–284 (1994).

Nisell, M., Nomikos, G. G., Hertel, P., Panagis, G. & Svensson, T. H. Condition-independent sensitization of locomotor stimulation and mesocortical dopamine release following chronic nicotine treatment in the rat. Synapse 22 , 369–381 (1996).

Rice, M. E. & Cragg, S. J. Nicotine amplifies reward-related dopamine signals in striatum. Nat. Neurosci. 7 , 583–584 (2004).

Mameli-Engvall, M. et al. Hierarchical control of dopamine neuron-firing patterns by nicotinic receptors. Neuron 50 , 911–921 (2006).

Picciotto, M. R., Higley, M. J. & Mineur, Y. S. Acetylcholine as a neuromodulator: cholinergic signaling shapes nervous system function and behavior. Neuron 76 , 116–129 (2012).

Le Foll, B. et al. Elevation of dopamine induced by cigarette smoking: novel insights from a [11C]-+-PHNO PET study in humans. Neuropsychopharmacology 39 , 415–424 (2014). This brain imaging study identified the brain areas in which smoking elevates dopamine levels .

Maskos, U. et al. Nicotine reinforcement and cognition restored by targeted expression of nicotinic receptors. Nature 436 , 103–107 (2005). This article discusses the implication of the β 2 - containing nAChRs in the VTA in mammalian cognitive function .

Picciotto, M. R. et al. Acetylcholine receptors containing the beta2 subunit are involved in the reinforcing properties of nicotine. Nature 391 , 173–177 (1998). This article discusses the implication of the β 2 - containing nAChRs in addictive effects of nicotine .

Fowler, C. D., Lu, Q., Johnson, P. M., Marks, M. J. & Kenny, P. J. Habenular alpha5 nicotinic receptor subunit signalling controls nicotine intake. Nature 471 , 597–601 (2011). This article discusses the implication of the α5 nicotinic receptor located in the MHb in a mechanism mediating the aversive effects of nicotine .

Elayouby, K. S. et al. α3* Nicotinic acetylcholine receptors in the habenula-interpeduncular nucleus circuit regulate nicotine intake. J. Neurosci. https://doi.org/10.1523/JNEUROSCI.0127-19.2020 (2020).

Ables, J. L. et al. Retrograde inhibition by a specific subset of interpeduncular α5 nicotinic neurons regulates nicotine preference. Proc. Natl Acad. Sci. USA 114 , 13012–13017 (2017).

Frahm, S. et al. Aversion to nicotine is regulated by the balanced activity of β4 and α5 nicotinic receptor subunits in the medial habenula. Neuron 70 , 522–535 (2011).

Jackson, K. J. et al. Role of α5 nicotinic acetylcholine receptors in pharmacological and behavioral effects of nicotine in mice. J. Pharmacol. Exp. Ther. 334 , 137–146 (2010).

Tuesta, L. M. et al. GLP-1 acts on habenular avoidance circuits to control nicotine intake. Nat. Neurosci. 20 , 708–716 (2017).

Salas, R., Pieri, F. & De Biasi, M. Decreased signs of nicotine withdrawal in mice null for the β4 nicotinic acetylcholine receptor subunit. J. Neurosci. 24 , 10035–10039 (2004).

Salas, R., Sturm, R., Boulter, J. & De Biasi, M. Nicotinic receptors in the habenulo-interpeduncular system are necessary for nicotine withdrawal in mice. J. Neurosci. 29 , 3014–3018 (2009).

Jackson, K. J., Martin, B. R., Changeux, J. P. & Damaj, M. I. Differential role of nicotinic acetylcholine receptor subunits in physical and affective nicotine withdrawal signs. J. Pharmacol. Exp. Ther. 325 , 302–312 (2008).

Le Foll, B. et al. Translational strategies for therapeutic development in nicotine addiction: rethinking the conventional bench to bedside approach. Prog. Neuropsychopharmacol. Biol. Psychiatry 52 , 86–93 (2014).

Naqvi, N. H., Rudrauf, D., Damasio, H. & Bechara, A. Damage to the insula disrupts addiction to cigarette smoking. Science 315 , 531–534 (2007). This article discusses the implication of the insular cortex in tobacco addiction .

Ibrahim, C. et al. The insula: a brain stimulation target for the treatment of addiction. Front. Pharmacol. 10 , 720 (2019).

Zangen, A. et al. Repetitive transcranial magnetic stimulation for smoking cessation: a pivotal multicenter double-blind randomized controlled trial. World Psychiatry 20 , 397–404 (2021). This study validated the utility of deep insula/prefrontal cortex rTMS for smoking cessation .

Le Foll, B., Forget, B., Aubin, H. J. & Goldberg, S. R. Blocking cannabinoid CB1 receptors for the treatment of nicotine dependence: insights from pre-clinical and clinical studies. Addict. Biol. 13 , 239–252 (2008).

Kodas, E., Cohen, C., Louis, C. & Griebel, G. Cortico-limbic circuitry for conditioned nicotine-seeking behavior in rats involves endocannabinoid signaling. Psychopharmacology 194 , 161–171 (2007).

Forget, B. et al. Noradrenergic α1 receptors as a novel target for the treatment of nicotine addiction. Neuropsychopharmacology 35 , 1751–1760 (2010).

Garrett, B. E., Dube, S. R., Babb, S. & McAfee, T. Addressing the social determinants of health to reduce tobacco-related disparities. Nicotine Tob. Res. 17 , 892–897 (2015).

Polanska, K., Znyk, M. & Kaleta, D. Susceptibility to tobacco use and associated factors among youth in five central and eastern European countries. BMC Public Health 22 , 72 (2022).

Volkow, N. D. Personalizing the treatment of substance use disorders. Am. J. Psychiatry 177 , 113–116 (2020).

Li, M. D., Cheng, R., Ma, J. Z. & Swan, G. E. A meta-analysis of estimated genetic and environmental effects on smoking behavior in male and female adult twins. Addiction 98 , 23–31 (2003).

Carmelli, D., Swan, G. E., Robinette, D. & Fabsitz, R. Genetic influence on smoking–a study of male twins. N. Engl. J. Med. 327 , 829–833 (1992).

Broms, U., Silventoinen, K., Madden, P. A. F., Heath, A. C. & Kaprio, J. Genetic architecture of smoking behavior: a study of Finnish adult twins. Twin Res. Hum. Genet. 9 , 64–72 (2006).

Kendler, K. S., Thornton, L. M. & Pedersen, N. L. Tobacco consumption in Swedish twins reared apart and reared together. Arch. Gen. Psychiat 57 , 886–892 (2000).

Saccone, N. L. et al. The CHRNA5-CHRNA3-CHRNB4 nicotinic receptor subunit gene cluster affects risk for nicotine dependence in African-Americans and in European-Americans. Cancer Res. 69 , 6848–6856 (2009).

Bierut, L. J. et al. Variants in nicotinic receptors and risk for nicotine dependence. Am. J. Psychiatry 165 , 1163–1171 (2008). This study demonstrates that nAChR gene variants are important in nicotine addiction .

Bierut, L. J. et al. Novel genes identified in a high-density genome wide association study for nicotine dependence. Hum. Mol. Genet. 16 , 24–35 (2007).

Berrettini, W. et al. α-5/α-3 nicotinic receptor subunit alleles increase risk for heavy smoking. Mol. Psychiatry 13 , 368–373 (2008).

Sherva, R. et al. Association of a single nucleotide polymorphism in neuronal acetylcholine receptor subunit alpha 5 (CHRNA5) with smoking status and with ‘pleasurable buzz’ during early experimentation with smoking. Addiction 103 , 1544–1552 (2008).

Thorgeirsson, T. E. et al. Sequence variants at CHRNB3-CHRNA6 and CYP2A6 affect smoking behavior. Nat. Genet. 42 , 448–453 (2010).

Ray, R., Tyndale, R. F. & Lerman, C. Nicotine dependence pharmacogenetics: role of genetic variation in nicotine-metabolizing enzymes. J. Neurogenet. 23 , 252–261 (2009).

Bergen, A. W. et al. Drug metabolizing enzyme and transporter gene variation, nicotine metabolism, prospective abstinence, and cigarette consumption. PLoS ONE 10 , e0126113 (2015).

Mwenifumbo, J. C. et al. Identification of novel CYP2A6*1B variants: the CYP2A6*1B allele is associated with faster in vivo nicotine metabolism. Clin. Pharmacol. Ther. 83 , 115–121 (2008).

Raunio, H. & Rahnasto-Rilla, M. CYP2A6: genetics, structure, regulation, and function. Drug Metab. Drug Interact. 27 , 73–88 (2012).

CAS   Google Scholar  

Patterson, F. et al. Toward personalized therapy for smoking cessation: a randomized placebo-controlled trial of bupropion. Clin. Pharmacol. Ther. 84 , 320–325 (2008).

Rodriguez, S. et al. Combined analysis of CHRNA5, CHRNA3 and CYP2A6 in relation to adolescent smoking behaviour. J. Psychopharmacol. 25 , 915–923 (2011).

Strasser, A. A., Malaiyandi, V., Hoffmann, E., Tyndale, R. F. & Lerman, C. An association of CYP2A6 genotype and smoking topography. Nicotine Tob. Res. 9 , 511–518 (2007).

Liakoni, E. et al. Effects of nicotine metabolic rate on withdrawal symptoms and response to cigarette smoking after abstinence. Clin. Pharmacol. Ther. 105 , 641–651 (2019).

Di Ciano, P. et al. Influence of nicotine metabolism ratio on [11C]-(+)-PHNO PET binding in tobacco smokers. Int. J. Neuropsychopharmacol. 21 , 503–512 (2018).

Butler, K. et al. Impact of Cyp2a6 activity on nicotine reinforcement and cue-reactivity in daily smokers. Nicotine Tob. Res. https://doi.org/10.1093/ntr/ntab064 (2021).

Benowitz, N. L., Swan, G. E., Jacob, P. 3rd, Lessov-Schlaggar, C. N. & Tyndale, R. F. CYP2A6 genotype and the metabolism and disposition kinetics of nicotine. Clin. Pharmacol. Ther. 80 , 457–467 (2006).

Liu, M. et al. Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use. Nat. Genet. 51 , 237–244 (2019).

McKay, J. D. et al. Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes. Nat. Genet. 49 , 1126–1132 (2017).

Chukwueke, C. C. et al. The CB1R rs2023239 receptor gene variant significantly affects the reinforcing effects of nicotine, but not cue reactivity, in human smokers. Brain Behav. 11 , e01982 (2021).

Ahrens, S. et al. Modulation of nicotine effects on selective attention by DRD2 and CHRNA4 gene polymorphisms. Psychopharmacology 232 , 2323–2331 (2015).

Harrell, P. T. et al. Dopaminergic genetic variation moderates the effect of nicotine on cigarette reward. Psychopharmacology 233 , 351–360 (2016).

Lerman, C. et al. Role of functional genetic variation in the dopamine D2 receptor (DRD2) in response to bupropion and nicotine replacement therapy for tobacco dependence: results of two randomized clinical trials. Neuropsychopharmacology 31 , 231–242 (2006).

Le Foll, B., Gallo, A., Le Strat, Y., Lu, L. & Gorwood, P. Genetics of dopamine receptors and drug addiction: a comprehensive review. Behav. Pharmacol. 20 , 1–17 (2009).

Chukwueke, C. C. et al. Exploring the role of the Ser9Gly (rs6280) dopamine D3 receptor polymorphism in nicotine reinforcement and cue-elicited craving. Sci. Rep. 10 , 4085 (2020).

The Clinical Practice Guideline Treating Tobacco Use and Dependence 2008 Update Panel, Liaisons, and Staff A clinical practice guideline for treating tobacco use and dependence: 2008 update: a U.S. Public Health Service report. Am. J. Prev. Med. 35 , 158–176 (2008).

Hackshaw, A., Morris, J. K., Boniface, S., Tang, J. L. & Milenković, D. Low cigarette consumption and risk of coronary heart disease and stroke: meta-analysis of 141 cohort studies in 55 study reports. BMJ 360 , j5855 (2018).

Qin, W. et al. Light cigarette smoking increases risk of all-cause and cause-specific mortality: findings from the NHIS cohort study. Int. J. Env. Res. Public Health https://doi.org/10.3390/ijerph17145122 (2020).

Rodu, B. & Plurphanswat, N. Mortality among male smokers and smokeless tobacco users in the USA. Harm Reduct. J. 16 , 50 (2019).

Kasza, K. A. et al. Tobacco-product use by adults and youths in the United States in 2013 and 2014. N. Engl. J. Med. 376 , 342–353 (2017).

Richardson, A., Xiao, H. & Vallone, D. M. Primary and dual users of cigars and cigarettes: profiles, tobacco use patterns and relevance to policy. Nicotine Tob. Res. 14 , 927–932 (2012).

American Psychiatric Association. Diagnostic and Statistical Manual of Mental disorders 5th edn (American Psychiatric Association, 2013).

World Health Organization. Tobacco fact sheet. WHO https://www.who.int/news-room/fact-sheets/detail/tobacco (2021).

Heatherton, T. F., Kozlowski, L. T., Frecker, R. C. & Fagerström, K. O. The Fagerström test for nicotine dependence: a revision of the Fagerström tolerance questionnaire. Br. J. Addict. 86 , 1119–1127 (1991).

Heatherton, T. F., Kozlowski, L. T., Frecker, R. C., Rickert, W. & Robinson, J. Measuring the heaviness of smoking: using self-reported time to the first cigarette of the day and number of cigarettes smoked per day. Br. J. Addict. 84 , 791–799 (1989).

Etter, J. F., Le Houezec, J. & Perneger, T. V. A self-administered questionnaire to measure dependence on cigarettes: the cigarette dependence scale. Neuropsychopharmacology 28 , 359–370 (2003).

DiFranza, J. R. et al. Measuring the loss of autonomy over nicotine use in adolescents: the DANDY (Development and Assessment of Nicotine Dependence in Youths) study. Arch. Pediatr. Adolesc. Med. 156 , 397–403 (2002).

Shiffman, S., Waters, A. & Hickcox, M. The Nicotine Dependence Syndrome Scale: a multidimensional measure of nicotine dependence. Nicotine Tob. Res. 6 , 327–348 (2004).

Smith, S. S. et al. Development of the Brief Wisconsin Inventory of Smoking Dependence Motives. Nicotine Tob. Res. 12 , 489–499 (2010).

Foulds, J. et al. Development of a questionnaire for assessing dependence on electronic cigarettes among a large sample of ex-smoking E-cigarette users. Nicotine Tob. Res. 17 , 186–192 (2015).

National Center for Chronic Disease Prevention and Health Promotion (US) Office on Smoking and Health. Preventing tobacco use among youth and young adults: a report of the Surgeon General (Centers for Disease Control and Prevention, 2012).

World Health Organization. Tobacco control to improve child health and development. Thematic brief (WHO, 2021).

Lantz, P. M. et al. Investing in youth tobacco control: a review of smoking prevention and control strategies. Tob. Control. 9 , 47–63 (2000).

Leão, T., Kunst, A. E. & Perelman, J. Cost-effectiveness of tobacco control policies and programmes targeting adolescents: a systematic review. Eur. J. Public Health 28 , 39–43 (2018).

Royal College of Physicians. Smoking and health 2021: a coming of age for tobacco control? (RCP, 2021).

Higashi, H. et al. Cost effectiveness of tobacco control policies in Vietnam: the case of population-level interventions. Appl. Health Econ. Health Policy 9 , 183–196 (2011).

Ranson, M. K., Jha, P., Chaloupka, F. J. & Nguyen, S. N. Global and regional estimates of the effectiveness and cost-effectiveness of price increases and other tobacco control policies. Nicotine Tob. Res. 4 , 311–319 (2002).

International Agency for Research on Cancer. I ARC Handbooks of Cancer Prevention: Tobacco control Vol. 14 (IARC, 2011).

Frazer, K. et al. Legislative smoking bans for reducing harms from secondhand smoke exposure, smoking prevalence and tobacco consumption. Cochrane Database Syst. Rev. 2 , CD005992 (2016).

Hoffman, S. J. & Tan, C. Overview of systematic reviews on the health-related effects of government tobacco control policies. BMC Public Health 15 , 744 (2015).

McNeill, A. et al. Tobacco packaging design for reducing tobacco use. Cochrane Database Syst. Rev. 4 , CD011244 (2017).

National Center for Chronic Disease Prevention and Health Promotion (US) Office on Smoking and Health. Smoking cessation: a report of the Surgeon General (Department of Health and Human Services, 2020).

Lindson, N. et al. Different doses, durations and modes of delivery of nicotine replacement therapy for smoking cessation. Cochrane Database Syst. Rev. 4 , CD013308 (2019).

Krist, A. H. et al. Interventions for tobacco smoking cessation in adults, including pregnant persons: US Preventive Services Task Force recommendation statement. JAMA 325 , 265–279 (2021).

Tutka, P. & Zatonski, W. Cytisine for the treatment of nicotine addiction: from a molecule to therapeutic efficacy. Pharmacol. Rep. 58 , 777–798 (2006).

Courtney, R. J. et al. Effect of cytisine vs varenicline on smoking cessation: a randomized clinical trial. JAMA 326 , 56–64 (2021).

Walker, N. et al. Cytisine versus nicotine for smoking cessation. N. Engl. J. Med. 371 , 2353–2362 (2014). This study validated the utility of cytisine for smoking cessation .

West, R. et al. Placebo-controlled trial of cytisine for smoking cessation. N. Engl. J. Med. 365 , 1193–1200 (2011).

Hajek, P. et al. E-cigarettes compared with nicotine replacement therapy within the UK Stop Smoking Services: the TEC RCT. Health Technol. Assess. 23 , 1–82 (2019).

Walker, N. et al. Nicotine patches used in combination with e-cigarettes (with and without nicotine) for smoking cessation: a pragmatic, randomised trial. Lancet Respir. Med. 8 , 54–64 (2020).

Siu, A. L., U.S. Preventive Services Task Force. Behavioral and pharmacotherapy interventions for tobacco smoking cessation in adults, including pregnant women: U.S. Preventive Services Task Force recommendation statement. Ann. Intern. Med. 163 , 622–634 (2015).

Black, N. et al. Behaviour change techniques associated with smoking cessation in intervention and comparator groups of randomized controlled trials: a systematic review and meta-regression. Addiction 115 , 2008–2020 (2020).

Center for Substance Abuse and Treatment. Detoxification and Substance Abuse Treatment (Center for Substance Abuse and Treatment, 2006).

Cahill, K., Hartmann-Boyce, J. & Perera, R. Incentives for smoking cessation. Cochrane Database Syst. Rev. https://doi.org/10.1002/14651858.CD004307.pub5 (2015).

Secades-Villa, R., Aonso-Diego, G., García-Pérez, Á. & González-Roz, A. Effectiveness of contingency management for smoking cessation in substance users: a systematic review and meta-analysis. J. Consult. Clin. Psychol. 88 , 951–964 (2020).

Cahill, K. & Perera, R. Competitions and incentives for smoking cessation. Cochrane Database Syst. Rev. https://doi.org/10.1002/14651858.CD004307.pub4 (2011).

Trojak, B. et al. Transcranial magnetic stimulation combined with nicotine replacement therapy for smoking cessation: a randomized controlled trial. Brain Stimul. 8 , 1168–1174 (2015).

Wing, V. C. et al. Brain stimulation methods to treat tobacco addiction. Brain Stimul. 6 , 221–230 (2013).

Dinur-Klein, L. et al. Smoking cessation induced by deep repetitive transcranial magnetic stimulation of the prefrontal and insular cortices: a prospective, randomized controlled trial. Biol. Psychiatry 76 , 742–749 (2014).

Goldenberg, M., Danovitch, I. & IsHak, W. W. Quality of life and smoking. Am. J. Addict. 23 , 540–562 (2014).

Heikkinen, H., Jallinoja, P., Saarni, S. I. & Patja, K. The impact of smoking on health-related and overall quality of life: a general population survey in Finland. Nicotine Tob. Res. 10 , 1199–1207 (2008).

Moayeri, F., Hsueh, Y. A., Dunt, D. & Clarke, P. Smoking cessation and quality of life: insights from analysis of longitudinal Australian data, an application for economic evaluations. Value Health 24 , 724–732 (2021).

Taylor, G. M. et al. Smoking cessation for improving mental health. Cochrane Database Syst. Rev. 3 , CD013522 (2021).

López-Nicolás, Á., Trapero-Bertran, M. & Muñoz, C. Smoking, health-related quality of life and economic evaluation. Eur. J. Health Econ. 19 , 747–756 (2018).

Morris, A. Linking nicotine addiction and T2DM. Nat. Rev. Endocrinol. 16 , 6 (2020).

Willi, C., Bodenmann, P., Ghali, W. A., Faris, P. D. & Cornuz, J. Active smoking and the risk of type 2 diabetes: a systematic review and meta-analysis. Jama 298 , 2654–2664 (2007).

World Health Organization. WHO report on the global tobacco epidemic (WHO, 2019).

Donny, E. C. et al. Randomized trial of reduced-nicotine standards for cigarettes. N. Engl. J. Med. 373 , 1340–1349 (2015). This study tested the impact of reducing the quantity of nicotine present in cigarettes on smoking .

Benowitz, N. L. & Henningfield, J. E. Establishing a nicotine threshold for addiction. The implications for tobacco regulation. N. Engl. J. Med. 331 , 123–125 (1994).

Benowitz, N. L. & Henningfield, J. E. Reducing the nicotine content to make cigarettes less addictive. Tob. Control. 22 , i14–i17 (2013).

Gottlieb, S. & Zeller, M. A nicotine-focused framework for public health. N. Engl. J. Med. 377 , 1111–1114 (2017).

Hall, W. & West, R. Thinking about the unthinkable: a de facto prohibition on smoked tobacco products. Addiction 103 , 873–874 (2008).

Ioannidis, J. P. A. & Jha, P. Does the COVID-19 pandemic provide an opportunity to eliminate the tobacco industry? Lancet Glob. Health 9 , e12–e13 (2021).

Smokefree. Smokefree 2025. Smokefree https://www.smokefree.org.nz/smokefree-in-action/smokefree-aotearoa-2025 (2021).

Morgan, C. J., Das, R. K., Joye, A., Curran, H. V. & Kamboj, S. K. Cannabidiol reduces cigarette consumption in tobacco smokers: preliminary findings. Addict. Behav. 38 , 2433–2436 (2013).

Elsaid, S., Kloiber, S. & Le Foll, B. Effects of cannabidiol (CBD) in neuropsychiatric disorders: a review of pre-clinical and clinical findings. Prog. Mol. Biol. Transl. Sci. 167 , 25–75 (2019).

Butler, K. & Le Foll, B. Novel therapeutic and drug development strategies for tobacco use disorder: endocannabinoid modulation. Expert Opin. Drug Discov. 15 , 1065–1080 (2020).

D’Souza, D. C. et al. Efficacy and safety of a fatty acid amide hydrolase inhibitor (PF-04457845) in the treatment of cannabis withdrawal and dependence in men: a double-blind, placebo-controlled, parallel group, phase 2a single-site randomised controlled trial. Lancet Psychiatry 6 , 35–45 (2019).

Robinson, J. D. et al. Pooled analysis of three randomized, double-blind, placebo controlled trials with rimonabant for smoking cessation. Addict. Biol. 23 , 291–303 (2018).

Gueye, A. B. et al. The CB1 neutral antagonist AM4113 retains the therapeutic efficacy of the inverse agonist rimonabant for nicotine dependence and weight loss with better psychiatric tolerability. Int. J. Neuropsychopharmacol. https://doi.org/10.1093/ijnp/pyw068 (2016).

Yammine, L. et al. Exenatide adjunct to nicotine patch facilitates smoking cessation and may reduce post-cessation weight gain: a pilot randomized controlled trial. Nicotine Tob. Res. 23 , 1682–1690 (2021).

Eren-Yazicioglu, C. Y., Yigit, A., Dogruoz, R. E. & Yapici-Eser, H. Can GLP-1 be a target for reward system related disorders? A qualitative synthesis and systematic review analysis of studies on palatable food, drugs of abuse, and alcohol. Front. Behav. Neurosci. 14 , 614884 (2020).

Vanderkam, P. et al. Effectiveness of drugs acting on adrenergic receptors in the treatment for tobacco or alcohol use disorders: systematic review and meta-analysis. Addiction 116 , 1011–1020 (2021).

Sokoloff, P. & Le Foll, B. The dopamine D3 receptor, a quarter century later. Eur. J. Neurosci. 45 , 2–19 (2017).

David, S. P., Lancaster, T., Stead, L. F., Evins, A. E. & Prochaska, J. J. Opioid antagonists for smoking cessation. Cochrane Database Syst. Rev. https://doi.org/10.1002/14651858.CD003086.pub3 (2013).

Ray, L. A. et al. Efficacy of combining varenicline and naltrexone for smoking cessation and drinking reduction: a randomized clinical trial. Am. J. Psychiatry 178 , 818–828 (2021).

Mooney, M. E. et al. Bupropion and naltrexone for smoking cessation: a double-blind randomized placebo-controlled clinical trial. Clin. Pharmacol. Ther. 100 , 344–352 (2016).

Justinova, Z., Le Foll, B., Redhi, G. H., Markou, A. & Goldberg, S. R. Differential effects of the metabotropic glutamate 2/3 receptor agonist LY379268 on nicotine versus cocaine self-administration and relapse in squirrel monkeys. Psychopharmacology 233 , 1791–1800 (2016).

Le Foll, B., Wertheim, C. E. & Goldberg, S. R. Effects of baclofen on conditioned rewarding and discriminative stimulus effects of nicotine in rats. Neurosci. Lett. 443 , 236–240 (2008).

Franklin, T. R. et al. The GABA B agonist baclofen reduces cigarette consumption in a preliminary double-blind placebo-controlled smoking reduction study. Drug Alcohol. Depend. 103 , 30–36 (2009).

Lotfy, N., Elsawah, H. & Hassan, M. Topiramate for smoking cessation: systematic review and meta-analysis. Tob. Prev. Cessat. 6 , 14 (2020).

Shanahan, W. R., Rose, J. E., Glicklich, A., Stubbe, S. & Sanchez-Kam, M. Lorcaserin for smoking cessation and associated weight gain: a randomized 12-week clinical trial. Nicotine Tob. Res. 19 , 944–951 (2017).

Higgins, G. A., Fletcher, P. J. & Shanahan, W. R. Lorcaserin: a review of its preclinical and clinical pharmacology and therapeutic potential. Pharmacol. Ther. 205 , 107417 (2020).

Stead, L. F. & Lancaster, T. Interventions to reduce harm from continued tobacco use. Cochrane Database Syst. Rev. https://doi.org/10.1002/14651858.CD005231.pub2 (2007).

Download references

Acknowledgements

B.Le F. is supported by a clinician-scientist award from the Department of Family and Community Medicine at the University of Toronto and the Addiction Psychiatry Chair from the University of Toronto. The funding bodies had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication. The authors thank H. Fu (University of Toronto) for assistance with Figs 1–3.

Author information

Authors and affiliations.

Translational Addiction Research Laboratory, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada

Bernard Le Foll

Departments of Family and Community Medicine, Psychiatry, Pharmacology and Toxicology, University of Toronto, Toronto, Ontario, Canada

Department of Medicine, University of Wisconsin, Madison, WI, USA

Megan E. Piper

University of Wisconsin Center for Tobacco Research and Intervention, Madison, WI, USA

Department of Neurobiology and Behaviour, University of California Irvine, Irvine, CA, USA

Christie D. Fowler

Section for Preventive Cardiology, Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway

Serena Tonstad

Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA

Laura Bierut

Institute of Mental Health, Peking University Sixth Hospital, Peking University, Beijing, China

National Institute on Drug Dependence, Peking University Health Science Center, Beijing, China

Centre for Global Health Research, Unity Health Toronto, University of Toronto, Toronto, Ontario, Canada

• Prabhat Jha

National Centre for Youth Substance Use Research, The University of Queensland, St Lucia, Queensland, Australia

Wayne D. Hall

Queensland Alliance for Environmental Health Sciences, The University of Queensland, Woolloongabba, Queensland, Australia

You can also search for this author in PubMed   Google Scholar

Contributions

Introduction (B.Le F.); Epidemiology (P.J. and W.D.H.); Mechanisms/pathophysiology (C.D.F., L.B., L.L. and B.Le F.); Diagnosis, screening and prevention (P.J., M.E.P., S.T. and B.Le F.); Management (M.E.P., S.T., W.D.H., L.L. and B.Le F.); Quality of life (P.J. and W.D.H.); Outlook (all); Conclusions (all). All authors contributed substantially to the review and editing of the manuscript.

Corresponding author

Correspondence to Bernard Le Foll .

Ethics declarations

Competing interests.

B.Le F. has obtained funding from Pfizer (GRAND Awards, including salary support) for investigator-initiated projects. B.Le F. has received some in-kind donations of cannabis product from Aurora and medication donation from Pfizer and Bioprojet and was provided a coil for TMS study from Brainsway. B.Le F. has obtained industry funding from Canopy (through research grants handled by CAMH or the University of Toronto), Bioprojet, ACS, Indivior and Alkermes. B.Le F. has received in-kind donations of nabiximols from GW Pharma for past studies funded by CIHR and NIH. B.Le F. has been an advisor to Shinoghi. S.T. has received honoraria from Pfizer the manufacturer of varenicline for lectures and advice. All other authors declare no competing interests.

Peer review

Peer reviewer information.

Nature Reviews Disease Primers thanks Jamie Brown, Elisardo Iglesias and Ming Li for their contribution to the peer review of this work.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related links

CTRI website: https://d3futrf33lk36a.cloudfront.net/wp-content/uploads/sites/240/2019/04/Meds-Chart.pdf

Philip Morris International: https://www.pmi.com/

Rights and permissions

Reprints and permissions

About this article

Cite this article.

Le Foll, B., Piper, M.E., Fowler, C.D. et al. Tobacco and nicotine use. Nat Rev Dis Primers 8 , 19 (2022). https://doi.org/10.1038/s41572-022-00346-w

Download citation

Accepted : 07 February 2022

Published : 24 March 2022

DOI : https://doi.org/10.1038/s41572-022-00346-w

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

This article is cited by

Integrated mrna- and mirna-sequencing analyses unveil the underlying mechanism of tobacco pollutant-induced developmental toxicity in zebrafish embryos.

• Jiasheng Chen
• Xiaoping Zhong

Journal of Translational Medicine (2024)

Reductions in smoking due to ratification of the Framework Convention for Tobacco Control in 171 countries

• Guillermo Paraje
• Mauricio Flores Muñoz

Nature Medicine (2024)

Impact of benzoic acid and 2,2’-methylenebis (6-tert-butyl-4-methylphenol) on the metabolome of flue-cured tobacco and rhizosphere microbial communities: implications for continuous cropping obstacles

• Qiulian Peng
• Jiayan Zhang

Plant and Soil (2024)

Nicotinic regulation of microglia: potential contributions to addiction

• Alexa R. Soares
• Marina R. Picciotto

Journal of Neural Transmission (2024)

Improving the Quality of Low-grade Tobacco by Enzymatic Treatment and Co-fermentation with Yeast and Lactic Acid Bacteria

Applied Biochemistry and Biotechnology (2024)

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

• Search Menu
• Sign in through your institution
• Supplements
• Advance articles
• Editor's Choice
• Special Issues
• Author Guidelines
• Submission Site
• Why Publish With Us?
• Open Access
• About Nicotine & Tobacco Research
• About Society for Nicotine & Tobacco Research
• Editorial Board
• Advertising and Corporate Services
• Journals Career Network
• Self-Archiving Policy
• Dispatch Dates
• Journals on Oxford Academic
• Books on Oxford Academic

Article Contents

Introduction, supplementary material, declaration of interests.

• < Previous

Smokers’ Understandings of Addiction to Nicotine and Tobacco: A Systematic Review and Interpretive Synthesis of Quantitative and Qualitative Research

• Article contents
• Figures & tables
• Supplementary Data

Daniel Pfeffer, Britta Wigginton, Coral Gartner, Kylie Morphett, Smokers’ Understandings of Addiction to Nicotine and Tobacco: A Systematic Review and Interpretive Synthesis of Quantitative and Qualitative Research, Nicotine & Tobacco Research , Volume 20, Issue 9, September 2018, Pages 1038–1046, https://doi.org/10.1093/ntr/ntx186

• Permissions Icon Permissions

Despite the centrality of addiction in academic accounts of smoking, there is little research on smokers’ beliefs about addiction to smoking, and the role of nicotine in tobacco dependence. Smokers’ perspectives on nicotine’s role in addiction are important given the increasing prevalence of nontobacco nicotine products such as e-cigarettes. We conducted a systematic review of studies investigating smokers’ understandings and lay beliefs about addiction to smoking and nicotine.

We searched PubMed, Embase, CINAHL, and PsycINFO for studies investigating lay beliefs about addiction to smoking. Twenty-two quantitative and 24 qualitative studies met inclusion criteria. Critical interpretive synthesis was used to analyze the results.

Very few studies asked about addiction to nicotine. Quantitative studies that asked about addiction to smoking showed that most smokers believe that cigarettes are an addictive product, and that they are addicted to smoking. Across qualitative studies, nicotine was not often mentioned by participants. Addiction to smoking was most often characterized as a feeling of “need” for cigarettes resulting from an interplay between physical, mental, and social processes. Overall, we found that understandings of smoking were more consistent with the biopsychosocial model of addiction than with more recent models that emphasize the biological aspects of addiction.

Researchers should not treat perceptions of addiction to smoking interchangeably with perceptions of addiction to nicotine. More research on lay beliefs about nicotine is required, particularly considering the increasing use of e-cigarettes and their potential for long-term nicotine maintenance for harm reduction.

Quantitative studies show that most smokers believe that smoking is addictive and that they are addicted. A feeling of “need” for cigarettes was central to qualitative accounts of addiction, but nicotine was not often discussed. Overall, smokers’ understandings of addiction reflect a biopsychosocial model rather than a neurobiological one. Given the growing market for e-cigarettes and therapeutic nicotine, more research is required on lay beliefs about nicotine and addiction.

Nicotine was declared addictive by the US Surgeon General in 1988, 1 and it is increasingly recommended that nicotine addiction be approached as a disorder requiring medical treatment. 2–4 Various measures of nicotine dependence have been developed, validated and are in regular use in both research and clinical applications. 5–8 The constellation of features included in such measures include continued smoking despite known harms, difficulty quitting, feelings of craving or compulsion, and how long after waking someone smokes their first cigarette. An example of a commonly used measure of dependence is the Fagerstrom Test for Nicotine Dependence (FTND). 6 In 2012, this test was renamed the Fagerstrom Test for Cigarette Dependence, in acknowledgement of the fact that dependence on cigarettes encompasses more than an addiction to nicotine. 9 In a similar vein, the DSM-IV labeled addictive smoking as “nicotine dependence,” 10 however, was labeled “tobacco use disorder” in the DSM 5. 5 The complexity of the relationship between tobacco dependence and nicotine dependence has largely focused on academic arguments about the role of nicotine replacement therapy (NRT), and the neurobiology of nicotine and cigarette smoking. 9 The distinction between nicotine and tobacco dependence has become very relevant to contemporary legal and public health arguments about the potential for dependence on nontobacco forms of nicotine such as e-cigarettes. 11 , 12

Unlike other psychoactive substances such as opiates and alcohol that have long been associated with addiction, nicotine has relatively recently joined the realms of substances defined as addictive. Historically, smoking has been more closely associated with a public health approach than an addiction medicine approach. 13 The increasing recommendation for health professionals to identify smokers and to provide them with pharmacological treatments such as NRT or prescription medications has medicalized smoking to some extent. 14 Also contributing to the medicalization of smoking is the increasing emphasis on the neurobiological aspects of smoking that create and maintain addiction. 15–17 Tobacco dependence is increasingly defined in terms of “nicotine addiction” and is beginning to be labeled a “chronic brain disorder” and a “chronic disease.” 3 , 18

However, whether smokers view themselves as addicted to nicotine, and the role they ascribe to nicotine in their smoking, is less clear. The answer to this question is important for two current public health debates: (1) the amount of emphasis that should be given to therapeutic nicotine (NRT) for quitting smoking, given the limited population impact of cessation medicines despite widespread availability and public subsidization in high income countries; and (2) what contribution nontherapeutic nicotine products (eg, e-cigarettes) will play in reducing the burden of tobacco-related disease. The marketing of NRT a medicinal smoking cessation product, and the recommendation to use it for only a limited period of time, meant that long-term dependence on NRT products has not been a big concern. E-cigarettes have been controversial in the tobacco control field because they are marketed as consumer products that are much safer alternatives to conventional cigarettes. Their potential to foster long-term nicotine dependence and their appeal as a recreational form of nicotine delivery has brought to the fore arguments about how nicotine should be conceptualized and regulated. 11 , 19 , 20

It is important to investigate whether smokers see themselves as addicted to smoking and what meanings they associate with this term. The role that smokers ascribe to nicotine in their understandings of smoking is likely to influence their views about cessation methods and also switching to alternative nicotine products such as NRT or e-cigarettes.

Only one previous systematic review has examined lay perceptions of addiction to smoking. 21 This review focused on youth perceptions of addiction and the health harms of smoking. The authors found that young people were optimistic about their ability to quit before their smoking became problematic, and many did not believe that they were addicted to smoking. However, this review excluded the views of older and more established smokers. Also, the search strategy may have excluded relevant studies because it only included publications that contained one of the following terms: “invincibility, in denial, denial, invulnerable, optimism.” Although a stated aim was to examine perceptions of addiction, no search terms about addiction were used.

Our systematic review aimed to examine smokers’ subjective assessment of tobacco addiction in both adolescent and adult smokers, with an emphasis on investigating beliefs about nicotine. We collated data on smokers’ perceptions, beliefs, and understandings of addiction to smoking in general, or to nicotine specifically where available. We applied critical interpretive synthesis (CIS) 22 to analyze smokers’ understandings of addiction, and the methods by which they have been studied. PRISMA guidelines, which were developed to encourage standardized reporting of systematic reviews, were used to report the method and findings wherever appropriate. 23

Search Strategy

We searched PubMed, Embase, CINAHL, and PsycINFO using broad search terms to capture all relevant studies. While search strategies were adjusted for each database’s features, the key search terms were (cigarette OR tobacco OR nicotine OR smoking) AND (addiction OR habit OR dependence OR “tobacco use disorder”) AND (attitude OR belief OR understanding OR perception OR awareness OR “health belief”). Supplementary File 1 includes the full search strategy for each database.

Searches were conducted in June 2015, restricting results to English language articles published in peer-reviewed journals in or after 1988, to coincide with the publication of the US Surgeon General’s report that declared that nicotine was addictive. 1 The reference lists of relevant studies were manually searched for additional publications that met the selection criteria.

Inclusion/Exclusion Criteria

Figure 1 illustrates the process for identifying studies. After excluding 1087 duplicates, 2424 articles were screened by title and abstract, retaining those that involved current or ex-smokers and investigated beliefs, attitudes, or self-assessment regarding addiction to tobacco or nicotine. Studies that did not report participants’ understandings of “addiction” or “dependence” were excluded. Qualitative studies were included if they explored the meanings that smokers associate with addiction. Quantitative studies were included if they provided smokers’ ratings of their own addiction, or their ratings on the general addictiveness of smoking. Two authors (KM and DP) screened the full texts of 97 publications. Five of these studies were identified from the manual searching of reference lists of relevant articles. Where KM and DP disagreed over inclusion, third author (BW) independently reviewed the article and inclusion was based on majority judgment. Forty-six articles were deemed to meet the selection criteria.

Process of study inclusion.

Data Extraction

Separate data extraction forms were used for qualitative and quantitative articles ( Supplementary File 2 ). One mixed-methods article 24 was included as qualitative because the quantitative component did not address perceptions of addiction. For each study, BW and DP extracted information on research aims, context and methodology, key findings, conclusions, and study quality. Where studies included data from both smokers and nonsmokers, only data from smokers and ex-smokers was extracted. For qualitative studies, all text relating to addiction were imported into NVivo10 25 to enable further analysis.

While formal quality appraisal is common in conventional systematic reviews, many quality appraisal criteria for clinical trials are not applicable to observational studies, and quality appraisal is a contentious exercise for qualitative research. 22 , 26 , 27 For this review, formal quality appraisal in the form of scoring or ranking studies was not appropriate because it predominantly included qualitative or cross-sectional survey studies. Instead, we integrated reporting criteria from the NICE guidelines (quantitative and qualitative) 28 , 29 and STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklists 30 into our extraction forms and quality concerns informed our interpretation of these studies. These reporting guidelines include many items which assist researchers in judging the quality of a study such as details about selection of participants, validity, and generalizability of the results, how the study was explained to participants, and the explicitness of data analysis methods. No articles were excluded based on judgments about quality.

Quantitative studies ( n = 22) varied in aims, methodology, and survey items; therefore meta-analysis was not possible. For qualitative studies ( n = 24), DP conducted a secondary analysis of extracted results (ie, participant quotes and authors’ interpretations) using Nvivo 10. KM independently coded eight randomly chosen studies and differences were discussed until a consensus was reached. Codes were organized into themes, and then further into overarching thematic domains.

We drew on the approach of CIS to interpret the identified literature. 22 CIS has been applied to a wide range of research areas and is particularly useful when reviewing a methodologically diverse body of literature. 22 , 26 , 31 A CIS approach goes beyond the aggregation of data and aims to interpret the findings. The process of CIS includes an evolving research question; a pragmatic approach to quality appraisal based strongly on relevance rather than specific criteria of methodological rigor; and a critical approach to key concepts and assumptions. 22

Quantitative Studies

Key characteristics and results of the 22 quantitative studies (20 research articles and 2 research letters) 32–53 are provided in Supplementary File 3 . These were published between 1990 and 2012 and were cross-sectional designs, with the exception of one prospective cohort study. 39 The study target populations varied, with some focused exclusively on smokers ( n = 12), while others also included nonsmokers for comparison ( n = 10). Most focused on adults ( n = 14), while a number recruited adolescents only ( n = 6), and a minority included both age groups ( n = 2). Some included subgroup analysis based on age ( n = 2), sex ( n = 2), smoking status ( n = 11), and/or ethnicity ( n = 3).

There were substantial differences between studies in the way perceptions of the addictiveness of smoking were measured. Some studies asked about perceptions of personal addiction, for example, “Are you [not at all, somewhat, or very] addicted to cigarettes?” 39 Others used more general questions about the addictiveness of smoking, particularly when comparing smoker and nonsmoker ratings. For example, one study asked participants “How much of a risk is it for someone to get addicted if they try smoking cigarettes even once?” 37 Several studies asked participants to provide ratings of both their own addiction to cigarettes, and the general addictiveness of tobacco/cigarettes. 40 , 49 , 52 , 53

Other aspects of smoking included the ease/difficulty of quitting 38 , 41 , 43 , 44 , 46 ; the addictiveness of tobacco compared to other drugs 34 , 40 , 49 ; and the extent to which they believed addiction was a reason for their smoking. 42 , 45 In many cases, participants’ perceptions of addiction were not the major focus of the study, however, ratings of addiction were included as a relevant variable.

Another important difference between studies was whether participants were asked about addiction to “cigarettes”, “smoking”, “tobacco”, or “nicotine”. Most items asked about the addictiveness of “tobacco”, “cigarettes” or “smoking”. Only two articles contained items that specifically questioned participants about addiction to nicotine. 52 , 53 Weinstein et al. 52 asked “If a teenager starts smoking half a pack of cigarettes a day, how long do you think it takes them to show signs of nicotine addiction?” However, they switched to asking about addiction to cigarettes when questioning participants about their own addiction: “Do you consider yourself addicted to cigarettes?” The survey administered by Zinser et al. 53 included the item “People who smoke cigarettes regularly are addicted to nicotine.” No quantitative studies asked if participants personally felt they were addicted to nicotine.

The included studies consistently found that the majority of smokers agreed that smoking is addictive 32 , 34 , 36 , 37 or that “smokers” in general are addicted. 33 , 40 , 42 , 53 The single study that asked whether people who smoke are addicted to nicotine found that 89% Latino participants and 94% non-Latino Whites agreed with the statement. 53 When asked whether they personally were addicted, most adult daily smokers reported that they were. 39 , 52 , 53 Adolescent smokers were less likely than adults to agree that they personally were addicted, 32 , 52 but most agreed that smoking was addictive, 34 , 36 , 41 and that quitting would be difficult. 35 Other groups who were less likely to report being addicted to smoking were Hispanics in US studies 46 , 49 , 53 and lighter or “occasional” smokers. 39 , 40 , 48

While most studies did not ask about different aspects of addiction to smoking, there were exceptions. Four studies presented more than one explanation for smoking, for example, asking to what extent participants agreed that smoking was a habit and/or an addiction, or that addiction to smoking was physical and/or mental. 42–44 , 48 Where participants were given the option to rate their agreement with each item separately, both smoking as a habit and an addiction were endorsed in adults. 42 One study found that smokers reported psychological addiction to be more of a motive for smoking than physical addiction, but the difference was not large. 44 Three further studies suggested that smokers tend to agree that smoking tobacco is as addictive as other drugs (eg, cocaine or heroin). 34 , 40 , 49

Common methodological limitations included the absence of reporting on response rates; a lack of descriptive statistics on addiction-related variables; information about ethical clearance not being provided; and a lack of clarity about how participants were categorized in relation to smoking status.

Qualitative Studies

Twenty-three qualitative studies were included from 24 articles (one study was reported in two separate articles) published between 1997 and 2015. 24 , 54–76 Details of the studies are included in Supplementary File 4 . Data collection methods were primarily focus groups, individual interviews, or a combination of both. One study used Q-methodology. 61 Sampling strategies varied, with most articles including current smokers ( n = 12) or a combination of current smokers and ex-smokers ( n = 8). Three articles included data from never smokers in their sample. 64 , 69 , 73 Fourteen articles focused on adults and 10 on adolescents.

Similar to the quantitative studies, exploring smokers’ understandings of addiction was not the explicit aim for many studies. However, addiction often arose as a major theme as it was closely tied to discussions around starting and stopping smoking. Although some studies did not report their interview questions, and the results presented were not always linked to specific questions, discussions of addiction appeared to arise from a range of questions about quitting, reasons for smoking, and thoughts about smoking in general. This shows that addiction is a central concern of smokers.

Many studies did not provide sufficient information to allow judgments on study quality. There was often limited reporting on the role of the researcher in the analysis, including whether multiple team members coded the data, and how researcher beliefs and practices may have influenced the results (reflexivity); details about interview questions; recruitment methods or the study’s context; evidence to support claims (eg, few participant quotes); and the analytic approach. These issues are not uncommon in the reporting of qualitative research, particularly in journals with tight word count restrictions, where methodological detail is often sacrificed to allow more room for the reporting of results.

Qualitative findings across studies revealed smokers attach a range of meanings to their addiction. We first discuss common ways in which smokers described addiction to smoking. We then delineate the ways in which these “signs” of addiction were used by some participants to separate themselves from “addicted smokers” or to downplay their own addiction. Last, we explore instances where discussions around nicotine arose, and draw preliminary conclusions about the role of nicotine in smokers’ understandings of addiction.

What Does Addiction Look Like to Smokers?

The most commonly reported sign of addiction to smoking was a feeling of “need” for cigarettes that was seen to set apart addicted smokers from nonaddicted smokers. 55 , 56 , 59 , 63–69 , 73 The feeling of need was often associated with the sensation of craving, such as “sweating at the bit for a fag,” 55 “not satisfied until I have one,” 67 and “twitching ... aching for a cigarette.” 65 Smokers described having emotional withdrawal symptoms, such as “you get these mood swings and temper and everything,” 76 and “you feel more nervous.” 66 Frequent reference to physical withdrawal symptoms occurred across studies including headaches, 58 insomnia, 54 nausea, 59 concentration difficulties, 54 , 59 shakiness, 63 , 68 cold sweats, and dry mouth. 63 Smoking cigarettes relieved these symptoms, but was also associated with pleasure in the form of “a tingly feeling,” 69 a “buzz,” 70 a pleasurable smell and taste, 74 or an enjoyable feeling “going down my throat.” 65 Smoking was often portrayed as necessary to enable “normal” functioning. In some studies, participants described “tanking up” before periods of enforced abstinence 56 and exaggerated reactions to running out of cigarettes, such as willingness to walk for two hours to buy more. 63

Another key aspect of addiction according to smokers was diminished control over smoking, and an associated difficulty in quitting. Addiction was seen as, “trying and trying to give up”, 56 “want to quit, but can’t” 64 or “if it controls you.” 58 Control was tied to notions of choice and those who denied that they were addicted to smoking asserted their autonomy in statements such as “I feel like I’m not addicted because I can stop myself at any time. I choose to smoke that cigarette,” 58 and “Every time it is my own decision to smoke.” 54 The themes of need and control are closely linked, as demonstrated by one participant who stressed that her smoking was not a need, but a “want.” She reflected on times when she had said no to a cigarette as evidence that her addiction is “not too bad.”

I mean the amount of times I’ve said no when people have offered me and I say no and they say go on have one, but I go no it’s alright (laughs), yeah so I’d say you know I’m not too bad really ’cos some people just smoke for the sake of it, I try and just smoke when I want one. 62

A number of factors were offered to explain why only some people become addicted, with frequent references to “overdoing smoking.” 59 In particular, some smokers were viewed as being very controlled and constrained, while others were thought to smoke excessively. Views that, “a cigarette every so often doesn’t get you addicted” 65 ; “the more that somebody smokes for a while, the greater the chance of them getting addicted” 59 ; or “if I was addicted to smoking then I’d be smoking every day” 55 reveal how notions of excess and addiction are intertwined.

Some studies noted a highly physical conception of the process of addiction, employing ideas of tolerance in regards to the development of addiction. Tolerance was seen as a gradual progression toward addiction: “they just need a little bit and then they need more and then they need more” 59 ; “It’s a boring feeling after a while. It doesn’t feel the same anymore. You have to like smoke more to get that feeling—to get that like little high.” 69 Inherent in these descriptions was the identification of subtypes of smoking behavior, based on varying criteria. These included the “in control social smoker” versus the “habitual smoker” versus the “full-fledged addicted smoker” 55 ; light versus moderate versus heavy degrees of addiction 59 ; and “wanting/enjoying” versus “needing” cigarettes. 63 In each case, the process of becoming addicted was associated with progression and moving up a ladder of smoking typologies. This comparison between different smoker “types” was common across studies.

Ambivalence About Addiction to Smoking

Many participants expressed uncertainty about whether they were addicted to smoking, or as to the nature or strength of their addiction. This was particularly the case for adolescent smokers. 54 , 59 , 70 , 71 While an acknowledgement of addiction in some form was common, views on what this meant varied widely. Where addiction was challenged, alternative discourses of smoking were often employed, commonly that it was primarily a social activity. ‘Social smoking’ was presented as an alternative to addiction, for example, “I do have a craving like other people, but it’s more a social thing really” 55 or as a precursor to addiction from which smoking progresses to become “more than just sitting with friends.” 55 One participant stated that the social aspects were as addictive as nicotine: “it is a social aspect of their life that they have become dependent on, as much as the nicotine, you know. I think the social setting of it all is something that is somewhat addictive itself.” 63 Adolescents in particular frequently referenced the social aspects of smoking.

“Habit” was another frequently employed term across studies. While its meaning was not often elaborated on, several studies suggested that smokers associated it with regular and repeated smoking. Yet, how this relates to “addiction” was often unclear due to the varied use of the term both within and across studies. Phrases such as, “I think it’s a habit, it’s not really an addiction …”; “probably an addiction now, it used to be a habit, but now it’s not” 55 ; and “not a habit, it’s an addiction,” 56 seem to suggest a dichotomy, in which “habit” is conceived as a distinctly different phenomenon to “addiction.” 56 , 63 However, other examples reveal less simplistic conceptualizations of the addiction/habit divide.

(. . .) It’s like it’s a drug, it’s er addictive, er I do enjoy it sometimes um, I suppose really it’s become part of my life, it’s a habit really . . . I think if you haven’t had a fag for a long time the first fag you have is like a stimulant, it’s um goes straight into the bloodstream and goes to the brain . . . I think it relaxes people um and I think then it just becomes a habit, a habit-forming er er thing really (. . .). It’s just a habit it’s just a just a really nasty horrible bad habit and I just don’t think I can break out (. . .) 62

Taken together, smokers appear to use the term “habit” to refer to the routine nature to their smoking behavior. While it is sometimes framed as being in contrast to addiction, others refer to it being a sign of addiction.

Across studies there was recognition of the stigma associated with being an addicted smoker. Resisting addiction was seen as a matter of being “strong enough,” 66 revealing a negative perception that “they are weak if they are addicted because they don’t have the willpower to quit.” 59 This conceptualization of addiction more closely aligns with a moral rather than neurobiological framing of addiction.

There was a tendency across studies for participants to use depersonalized language to distance themselves from discussions of their own smoking or addiction. Bottorff et al. 59 explicitly observed this in their interviews with adolescent smokers, and we also found this depersonalization to be common across studies. One example is the limited use of personal pronouns in accounts of addiction, with references to smoking’s effect on “ the body,” “ the brain,” or “ the bloodstream.” 59 , 62 For example, “Your body says you need one at that time; you just can’t ignore what your body says.” 59 Similarly, when discussing addiction, many participants discussed smoking in general terms rather than reflecting on their own smoking. If they did refer to their own smoking, it was often in comparison to “other” smokers who they considered heavier smokers, and more addicted. For example, Farrimond et al. 61 , p.995 stated that some participants made “positive comparisons between themselves as ‘social smokers’ and addicted smokers, for example, by emphasizing their high self-control and external ‘social’ motivation.” Young people used this strategy of distancing themselves from addiction by comparing themselves to older and heavier smokers. 55 , 59

How Do Smokers Understand the Role of Nicotine in Addiction to Smoking?

As described above, feeling a need to smoke was seen as a sign of addiction to smoking. But what aspect of smoking was “needed” was often not clarified. While some participants specifically discussed the role of nicotine, it was uncommon for researchers to probe about nicotine, and many of the discussions about smoking and addiction did not mention it. The chemical composition of cigarettes in general was seen as playing a role in promoting addiction, but participants rarely elaborated on how nicotine contributed to their addiction to cigarettes, and some displayed misunderstandings. For example, one participant implicated the tobacco industry in adding an addictive ingredient to cigarettes, suggesting they were unaware that nicotine is naturally found in tobacco: “If the cigarette manufacturers are putting stuff in the cigarettes that make your body addicted to ‘em, then how are you going to quit?” 57

While nicotine was only occasionally discussed, the physical nature of addiction to smoking was often acknowledged. Cravings were described as when the body “needs the stuff” 62 ; and “is basically crying out for a fag.” 56 Others referred specifically to the brain in describing this physical process, claiming the “brain tricks you” 63 and “forces you to think you need a cigarette.” 59 One participant explained that the brain “is already addicted to it, and the thinking just can’t go away.” 57 These participants often used such physical descriptions to attribute responsibility and development of addiction to the “the body” or “the brain,” situating them as entities external to themselves over which they had little or no control.

Where discussions about the role of nicotine did arise, it was often in the context of comparing tobacco dependence to other drug addictions. For example, “it’s like it’s a drug,” 62 “we’re just junkies, we need nicotine,” 56 “it’s worse than heroin,” 57 or “smokers are preoccupied with where the next nicotine fix is, the nicotine monkey on their backs.” 61 Although, others denied this relationship, claiming they don’t view their relationship to smoking like that of “a heroin addict.” 55

Accounts of addiction that refer to nicotine in the “bloodstream,” 57 , 62 a “chemical dependency” 57 , 62 ; and “tolerance,” 59 reflect—with varying degrees of sophistication—a biomedical understanding of “nicotine dependence.” Participants across studies often presented addiction as a “physical need,” however, we found that physical descriptions of addiction were rarely discussed in isolation from other factors such as family and peer influence. These influences were seen to act at a young age either through access to cigarettes, 59 , 65 children “getting used” to the idea of smoking, 59 , 62 or direct pressure to smoke. 69 A further psychosocial influence that arose was one’s personality, with some mentioning an “addictive personality” 74 or “inner weakness.” 59 , 73 Such a personality was attributed to genetics, immaturity, 59 or one’s mental health status. 73 These discussions implicated a complex web of factors that are seen to mediate addiction, illustrating a common view that tobacco dependence is not caused solely by the brain’s exposure to nicotine.

DiFranza 77 , p.1 has written that “Those who claim to have the power to define nicotine addiction are burdened to provide that they can identify it more accurately than those who live with it every day of their lives.” In this research, we reviewed studies examining smokers’ perceptions and understandings of addiction to smoking. By prioritizing participants’ own views and interpretations, theoretical debates surrounding the nature of addiction to smoking can become grounded in the daily lives and realities of cigarette smokers. The quantitative findings summarized here suggest that most smokers agree that smoking is addictive and that they themselves are addicted to cigarettes. However, when smokers are asked open-ended questions about what addiction means to them, a complex and multidimensional picture emerges. Moreover, there remains a considerable number of smokers who express ambivalence about their own addiction or reject the “addicted” label entirely, even if they believe smoking is addictive for others.

Our qualitative analysis shows that addiction is perceived as a complex process involving relationships between physical processes and sensations, behavioral patterns and the social contexts in which these occur. A feeling of “need” and lack of control over smoking were identified by smokers as the most common signs of addiction, and these align with the “craving” and “loss of control” criteria of the DSM 5. 5 These symptoms that smokers recognize are also consistent with other self-reported data on nicotine addiction, where a developmental sequence of “wanting, craving, needing” was identified during quit attempts. 78 However, smokers often distanced themselves from these symptoms of addiction by referring to addiction in a general way, and using depersonalized terms. Descriptions of smoking as a social practice or habit were sometimes invoked as an alternative to addiction. While the difficulty of quitting was often acknowledged, it was also common for smokers to maintain some sense of autonomy over their smoking. Overall, we found that subjective understandings of smoking were more consistent with the biopsychosocial model of addiction than with more recent models that emphasize the neurobiological or genetic aspects of addiction. 79–81

Largely absent from this literature was a thorough investigation of smokers’ understandings of “nicotine addiction”—as most studies neglected to ask participants specifically about nicotine. It was more common to ask about addiction to smoking, tobacco or cigarettes. Before the emergence of e-cigarettes, nicotine and tobacco were by and large interchangeable since the vast majority of long-term nicotine consumption was in the form of smoking cigarettes. Previous studies may not have specifically explored nicotine separately from other aspects of addiction because addiction to nicotine separated from smoking tobacco was less common. It is important to ask about smoking and cigarettes, as addiction to smoking cannot be reduced to nicotine dependence. However, understanding how smokers conceptualize the role of nicotine in their smoking is more and more important in light of increasing recommendation for smokers to use NRT, and because of the growing market for e-cigarettes, which offer nicotine in a form that could induce and sustain addiction, but without smoking tobacco. Smokers’ attitudes to, and ideas about, nicotine addiction, may influence the uptake and use of nontobacco nicotine products as substitutes for tobacco cigarettes. More specifically, if people do not believe that nicotine plays a central role in their smoking, they may be less likely to use NRT to assist quitting and be less interested in switching to e-cigarettes.

The qualitative studies we reviewed show that smoking is rarely understood primarily through the lens of nicotine addiction. This suggests that a biomedical understanding of addiction to smoking, where nicotine induces neurochemical changes to the brain, which make it very difficult to stop, does not dominate lay beliefs about addiction to cigarettes. These findings are consistent with previous research on how addicted individuals understand the biological basis of their addiction. 15 , 82–84 While the physical aspects of addiction are often acknowledged, smokers’ explanations of addiction are much broader, referring to the role of peers, routine, emotions, habits, inner strength or weakness, and contextual cues. These aforementioned aspects of smoking are not often linked with the mechanisms of nicotine dependence. The role of nicotine in addiction, where it was discussed, was often glossed over, rather than considered in detail. These findings suggest that promises of effective nicotine delivery may not provide sufficient motivation for many smokers to switch from combustible cigarettes to reduced harm alternatives such as NRT or e-cigarettes. Other factors, such as the extent to which e-cigarette use satisfies the social factors that smokers believe contribute to their addiction (eg, the smoking “routine” and sociability) 85 could influence its acceptability as a substitute for smoking. Therefore, the use of e-cigarettes (vaping) as a social practice may be just as important as it’s more functional role of relieving nicotine withdrawal symptoms.

These findings may partly explain the limited uptake of medicinal cessation aids, despite evidence of efficacy from clinical trials, wide availability, promotional advertising and public subsidization to make them more affordable. Cessation medicines may be viewed as addressing only one aspect of addiction (nicotine dependence), which smokers may not consider to be the most important factor driving their addiction. Furthermore, many have written of the increasing stigmatization of smokers that has occurred as tobacco use has become denormalized. 11 , 86–89 The extent to which medicinal cessation aids are associated with notions of substance (nicotine) addiction and the identity of a nicotine addict may make them unattractive to smokers given the techniques used by smokers to distance themselves from “addiction.” 90 This strong association between cigarettes and nicotine, and negative perceptions of being addicted, may also deter some smokers from experimenting with nicotine containing e-cigarettes. 91 Further research on how attitudes toward addiction influence smokers’ choices in relation to quitting smoking would be helpful.

These findings have a number of methodological implications. In limiting our review to literature on smokers’ understandings, the question arose—‘ who is a smoker ?’ How should we classify those who have recently taken up, or stopped smoking, or who smoke regularly but do not classify themselves as smokers? Our approach was to include any studies that claimed to include smokers or ex-smokers and to explicitly report the criteria used to identify and classify their participants. In doing so, we found there was significant diversity in the way that smoking status was classified across the reviewed studies. A number of studies provided either no information on how smokers were classified, or very vague descriptions of smoking status such as ‘known smokers’ 66 or ‘those with recent smoking experience.’ 65 Furthermore, very few studies discussed the rationale or implications of their chosen classifications.

This has a number of implications for interpretations of the above findings. First, adding these disparate classifications to the existing variation between study populations and context resulted in a sample of studies representing a very heterogeneous body of ‘smokers.’ Hence, the reported findings should be interpreted as providing an overall indication of the range of ways in which smokers conceptualize addiction. Further research in this area should ensure that methods for selecting and classifying smokers are reported. This is crucial both for reporting and analytical purposes.

A second methodological issue surrounds variation in the questions used to investigate addiction to smoking. It is likely that the framing of these questions significantly constrained the possible range of responses. For example, studies asking both “is tobacco physically addictive?” and “is tobacco mentally addictive?” presuppose that these are the ways in which addiction is experienced and preclude consideration of other explanations of addiction. While it is necessary to limit responses among large samples of smokers, qualitative literature can inform the most pertinent and useful questions to ask when there is limited scope. Finally, although investigations of addiction were not the primary aim of many studies, addiction consistently arose as a central theme. In the qualitative studies, detailed discussions of addiction sometimes arose from questions exploring smoking in general. This illustrates the significance of the concept of addiction both within smokers’ relationship with smoking as well as smoking research more broadly.

Based on these results, we recommend that researchers should not treat perceptions of addiction to smoking interchangeably with perceptions of addiction to nicotine. There is little research on perceptions of nicotine addiction, and more is needed, particularly considering the increasing use of nontobacco nicotine products and the potential for long-term nicotine maintenance. 19 Researchers should be deliberate in their choice of terms used in surveys and interviews to examine understandings of addiction to smoking and nicotine to improve the clarity of their research findings.

Supplementary data are available at Nicotine and Tobacco Research online.

DP received a UQ Winter Research Scholarship from the UQ School of Public Health to work on this project. KM was supported by an Australian Government Australian Postgraduate Award (APA) scholarship, as well as a top up scholarship from the University of Queensland. CG was supported by a National Health and Medical Research Council Career Development Fellowship (GNT1061978).

None declared.

US Surgeon General . The Health Consequences of Smoking: Nicotine Addiction . Washington, DC : Department of Health and Human Services ; 1988 .

Google Scholar

Google Preview

Aveyard P , Raw M . Improving smoking cessation approaches at the individual level . Tob Control . 2012 ; 21 ( 2 ): 252 – 257 .

Fiore MC , Jaen CR , Baker TB , et al.  Treating Tobacco Use and Dependence: 2008 Update . Rockville, MD : Department of Health and Human Services ; 2008 .

Wolff F , Hughes JR , Woods SS . New terminology for the treatment of tobacco dependence: a proposal for debate . J Smok Cessat . 2013 ; 8 : 71 – 5 .

American Psychiatric Association . Diagnostic and Statistical Manual of Mental Disorders (5th ed.). Arlington, VA : American Psychiatric Association ; 2013 .

Heatherton TF , Kozlowski LT , Frecker RC , Fagerström KO . The Fagerström Test for Nicotine Dependence: a revision of the Fagerström Tolerance Questionnaire . Br J Addict . 1991 ; 86 ( 9 ): 1119 – 1127 .

Heatherton TF , Kozlowski LT , Frecker RC , Rickert W , Robinson J . Measuring the heaviness of smoking: using self-reported time to the first cigarette of the day and number of cigarettes smoked per day . Br J Addict . 1989 ; 84 ( 7 ): 791 – 799 .

Wellman RJ , DiFranza JR , Savageau JA , Godiwala S , Friedman K , Hazelton J . Measuring adults’ loss of autonomy over nicotine use: the Hooked on Nicotine Checklist . Nicotine Tob Res . 2005 ; 7 ( 1 ): 157 – 161 .

Fagerström K . Determinants of tobacco use and renaming the FTND to the Fagerstrom Test for Cigarette Dependence . Nicotine Tob Res . 2012 ; 14 ( 1 ): 75 – 78 .

American Psychiatric Association . Diagnostic and Statistical Manual of Mental Disorders . 4th ed. Arlington, VA : American Psychiatric Association ; 1994 .

Bell K , Keane H . Nicotine control: e-cigarettes, smoking and addiction . Int J Drug Policy . 2012 ; 23 ( 3 ): 242 – 247 .

Elam MJ . Nicorette reborn? E-cigarettes in light of the history of nicotine replacement technology . Int J Drug Policy . 2015 ; 26 ( 6 ): 536 – 542 .

Berridge V . Two tales of addiction; opium and nicotine . Hum Psychopharm Clin . 1997 ; 12 : S45 – S52 .

Morphett K , Carter A , Hall W , Gartner C . Medicalisation, smoking and e-cigarettes: evidence and implications [published online ahead of print November 30, 2016]. Tob Control . 2016 . doi: 10.1136/tobaccocontrol-2016–053348 .

Morphett K , Carter A , Hall W , Gartner C . Framing tobacco dependence as a “brain disease”: implications for policy and practice . Nicotine Tob Res . 2017 ; 19 ( 7 ): 774 – 780 .

Picciotto MR , Mineur YS . Molecules and circuits involved in nicotine addiction: the many faces of smoking . Neuropharmacology . 2014 ; 76(pt B) : 545 – 553 .

D’Souza MS , Markou A . Neuronal mechanisms underlying development of nicotine dependence: implications for novel smoking-cessation treatments . Addict Sci Clin Pract . 2011 ; 6 ( 1 ): 4 – 16 .

Prochaska JJ , Benowitz NL . The past, present, and future of nicotine addiction therapy . Annu Rev Med . 2016 ; 67 : 467 – 486 .

Borland R . Paying more attention to the ‘elephant in the room’ . Tob Control . 2017 ; 26 ( e1 ): e35 – e36 .

Gartner C , Malone RE . Duelling letters: which one would you sign ? Tob Control . 2014 ; 23 ( 5 ): 369 – 370 .

Mantler T . A systematic review of smoking youths’ perceptions of addiction and health risks associated with smoking: utilizing the framework of the health belief model . Addict Res Theory . 2013 ; 21 : 306 – 317 .

Dixon-Woods M , Cavers D , Agarwal S , et al.  Conducting a critical interpretive synthesis of the literature on access to healthcare by vulnerable groups . BMC Med Res Methodol . 2006 ; 6 : 35 .

Moher D , Liberati A , Tetzlaff J , Altman DG ; PRISMA Group . Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement . PLoS Med . 2009 ; 6 ( 7 ): e1000097 .

Peretti-Watel P , Constance J . “It’s all we got left”. Why poor smokers are less sensitive to cigarette price increases . Int J Environ Res Public Health . 2009 ; 6 ( 2 ): 608 – 621 .

QSR International Pty Ltd . NVivo 10. 2010.

Flemming K . The use of morphine to treat cancer-related pain: a synthesis of quantitative and qualitative research . J Pain Symptom Manage . 2010 ; 39 ( 1 ): 139 – 154 .

Notley C , Blyth A , Craig J , Edwards A , Holland R . Postpartum smoking relapse—a thematic synthesis of qualitative studies . Addiction . 2015 ; 110 ( 11 ): 1712 – 1723 .

National Institute for Health and Care Excellence . Methods for the Development of NICE Public Health Guidance (third edition): Appendix H Quality Appraisal Checklist—Qualitative Studies . 2012 . www.nice.org.uk/process/pmg4/chapter/appendix-h-quality-appraisal-checklist-qualitative-studies . Accessed July 21, 2017 .

National Institute for Health and Care Excellence . Methods for the Development of NICE Public Health Guidance (third edition): Appendix G Quality Appraisal Checklist—Quantitative Studies Reporting Correlations and Associations . 2012 . www.nice.org.uk/process/pmg4/chapter/appendix-g-quality-appraisal-checklist-quantitative-studies-reporting-correlations-and . Accessed July 21, 2017 .

Vandenbroucke JP , von Elm E , Altman DG , et al.  ; STROBE Initiative . Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration . Int J Surg . 2014 ; 12 ( 12 ): 1500 – 1524 .

Morrison LG , Yardley L , Powell J , Michie S . What design features are used in effective e-health interventions? A review using techniques from Critical Interpretive Synthesis . Telemed J E Health . 2012 ; 18 ( 2 ): 137 – 144 .

Arnett JJ . Optimistic bias in adolescent and adult smokers and nonsmokers . Addict Behav . 2000 ; 25 ( 4 ): 625 – 632 .

Ashley MJ , Cohen J , Bull S , et al.  Knowledge about tobacco and attitudes toward tobacco control: how different are smokers and nonsmokers ? Can J Public Health . 2000 ; 91 ( 5 ): 376 – 380 .

Carpenter MJ , Garrett-Mayer E , Vitoc C , Cartmell K , Biggers S , Alberg AJ . Adolescent nondaily smokers: favorable views of tobacco yet receptive to cessation . Nicotine Tob Res . 2009 ; 11 ( 4 ): 348 – 355 .

Chabrol H , Faury R , Callahan S . French adolescent smoking and perception of quitting . J Am Acad Child Adolesc Psychiatry . 1999 ; 38 ( 6 ): 640 – 641 .

Chalela P , Velez LF , Ramirez AG . Social influences, and attitudes and beliefs associated with smoking among border Latino youth . J Sch Health . 2007 ; 77 ( 4 ): 187 – 195 .

Cunningham JA . Smokers and non-smokers differ in their beliefs about their addiction: public health implications . Can J Public Health . 2012 ; 103 ( 2 ): 159 .

Daughton JM , Daughton DM , Patil KD . Self-recognition of alcohol and cigarette dependency among high school seniors . Percept Mot Skills . 1997 ; 85 ( 1 ): 115 – 120 .

Edwards SA , Bondy SJ , Kowgier M , McDonald PW , Cohen JE . Are occasional smokers a heterogeneous group? An exploratory study . Nicotine Tob Res . 2010 ; 12 ( 12 ): 1195 – 1202 .

Gilpin E , Cavin SW , Pierce JP . Adult smokers who do not smoke daily . Addiction . 1997 ; 92 ( 4 ): 473 – 480 .

Halpern-Felsher BL , Biehl M , Kropp RY , Rubinstein ML . Perceived risks and benefits of smoking: differences among adolescents with different smoking experiences and intentions . Prev Med . 2004 ; 39 ( 3 ): 559 – 567 .

Hughes JR . Smokers’ beliefs about the inability to stop smoking . Addict Behav . 2009 ; 34 ( 12 ): 1005 – 1009 .

Jenks RJ . Attitudes, perceptions, and risk-taking behaviors of smokers, ex-smokers, and nonsmokers . J Soc Psychol . 1992 ; 132 ( 5 ): 569 – 575 .

Jenks RJ . Attitudes and perceptions toward smoking: smokers’ views of themselves and other smokers . J Soc Psychol . 1994 ; 134 ( 3 ): 355 – 361 .

Levinson AH , Campo S , Gascoigne J , Jolly O , Zakharyan A , Tran ZV . Smoking, but not smokers: identity among college students who smoke cigarettes . Nicotine Tob Res . 2007 ; 9 ( 8 ): 845 – 852 .

Marin BV , Perez-Stable EJ , Marin G , Sabogal F , Otero-Sabogal R . Attitudes and behaviors of Hispanic smokers: implications for cessation interventions . Health Educ Q . 1990 ; 17 ( 3 ): 287 – 297 .

Martin DS . Physical dependence and attributions of addiction among cigarette smokers . Addict Behav . 1990 ; 15 ( 1 ): 69 – 72 .

Okoli CT , Richardson CG , Ratner PA , Johnson JL . Adolescents’ self-defined tobacco use status, marijuana use, and tobacco dependence . Addict Behav . 2008 ; 33 ( 11 ): 1491 – 1499 .

Palinkas LA , Pierce J , Rosbrook BP , Pickwell S , Johnson M , Bal DG . Cigarette smoking behavior and beliefs of Hispanics in California . Am J Prev Med . 1993 ; 9 ( 6 ): 331 – 337 .

Stippekohl B , Winkler MH , Walter B , et al.  Neural responses to smoking stimuli are influenced by smokers’ attitudes towards their own smoking behaviour . PLoS One . 2012 ; 7 ( 11 ): e46782 .

Torchalla I , Okoli CT , Malchy L , Johnson JL . Nicotine dependence and gender differences in smokers accessing community mental health services . J Psychiatr Ment Health Nurs . 2011 ; 18 ( 4 ): 349 – 358 .

Weinstein ND , Slovic P , Gibson G . Accuracy and optimism in smokers’ beliefs about quitting . Nicotine Tob Res . 2004 ; 6(suppl 3) : S375 – S380 .

Zinser MC , Pampel FC , Flores E . Distinct beliefs, attitudes, and experiences of Latino smokers: relevance for cessation interventions . Am J Health Promot . 2011 ; 25 ( 5 suppl ): eS1 – e15 .

Abdullah AS , Ho WW . What Chinese adolescents think about quitting smoking: a qualitative study . Subst Use Misuse . 2006 ; 41 ( 13 ): 1735 – 1743 .

Amos A , Wiltshire S , Haw S , McNeill A . Ambivalence and uncertainty: experiences of and attitudes towards addiction and smoking cessation in the mid-to-late teens . Health Educ Res . 2006 ; 21 ( 2 ): 181 – 191 .

Bancroft A , Wiltshire S , Parry O , Amos A . “It’s like an addiction first thing.afterwards it’s like a habit”: daily smoking behaviour among people living in areas of deprivation . Soc Sci Med . 2003 ; 56 ( 6 ): 1261 – 1267 .

Battle RS , Cunradi CB , Moore RS , Yerger VB . Smoking cessation among transit workers: beliefs and perceptions among an at-risk occupational group . Subst Abuse Treat Prev Policy . 2015 ; 10 : 19 .

Berg CJ , Schauer GL , Buchanan TS , et al.  Perceptions of addiction, attempts to quit, and successful quitting in nondaily and daily smokers . Psychol Addict Behav . 2013 ; 27 ( 4 ): 1059 – 1067 .

Bottorff JL , Johnson JL , Moffat B , Grewal J , Ratner PA , Kalaw C . Adolescent constructions of nicotine addiction . Can J Nurs Res . 2004 ; 36 ( 1 ): 22 – 39 .

Carter-Pokras OD , Feldman RH , Kanamori M , et al.  Barriers and facilitators to smoking cessation among Latino adults . J Natl Med Assoc . 2011 ; 103 ( 5 ): 423 – 431 .

Farrimond H , Joffe H , Stenner P . A Q-methodological study of smoking identities . Psychol Health . 2010 ; 25 ( 8 ): 979 – 998 .

Gillies V , Willig C . “You get the nicotine and that in your blood”: constructions of addiction and control in women’s accounts of cigarette smoking . J Community Appl Soc Psychol . 1997 ; 7 : 285 – 301 .

Johnson JL , Bottorff JL , Moffat B , Ratner PA , Shoveller JA , Lovato CY . Tobacco dependence: adolescents’ perspectives on the need to smoke . Soc Sci Med . 2003 ; 56 ( 7 ): 1481 – 1492 .

Leavy J , Wood L , Phillips F , Rosenberg M . Try and try again—qualitative insights into adolescent smoking experimentation and notions of addiction . Health Promot J Austr . 2010 ; 21 ( 3 ): 208 – 214 .

Moffat BM , Johnson JL . Through the haze of cigarettes: teenage girls’ stories about cigarette addiction . Qual Health Res . 2001 ; 11 ( 5 ): 668 – 681 .

O’Loughlin J , Kishchuk N , DiFranza J , Tremblay M , Paradis G . The hardest thing is the habit: a qualitative investigation of adolescent smokers’ experience of nicotine dependence . Nicotine Tob Res . 2002 ; 4 ( 2 ): 201 – 209 .

Parry O , Thomson C , Fowkes FG . Dependent behaviours and beliefs: a qualitative study of older long-term smokers with arterial disease . Addiction . 2001 ; 96 ( 9 ): 1337 – 1347 .

Peters RJ Jr , Kelder SH , Prokhorov AV , et al.  Beliefs and social norms about smoking onset and addictions among urban adolescent cigarette smokers . J Psychoactive Drugs . 2005 ; 37 ( 4 ): 449 – 453 .

Quintero G , Davis S . Why do teens smoke? American Indian and Hispanic adolescents’ perspectives on functional values and addiction . Med Anthropol Q . 2002 ; 16 ( 4 ): 439 – 457 .

Rothwell E , Lamarque J . The use of focus groups to compare tobacco attitudes and behaviors between youth in urban and rural settings . Health Promot Pract . 2011 ; 12 ( 4 ): 551 – 560 .

Scheffels J , Schou KC . To be one who continues to smoke: construction of legitimacy and meaning in young adults’ accounts of smoking . Addict Res Theory . 2007 ; 15 : 161 – 76 .

Schultz AS , Temple B , Gibbons C , Preston J , Ronson G . Listening to those who are living with HIV and tobacco dependence and exploring their health care context . J Assoc Nurses AIDS Care . 2014 ; 25 ( 1 ): 46 – 59 .

Solivay ES . The lived experiences of tobacco use, dependence, and cessation: insights and perspectives of people with mental illness . Health Soc Work . 2011 ; 36 : 19 – 32 .

Thompson B , Thompson LA , Thompson J , Fredickson C , Bishop S . Heavy smokers: a qualitative analysis of attitudes and beliefs concerning cessation and continued smoking . Nicotine Tob Res . 2003 ; 5 ( 6 ): 923 – 933 .

Uppal N , Shahab L , Britton J , Ratschen E . The forgotten smoker: a qualitative study of attitudes towards smoking, quitting, and tobacco control policies among continuing smokers . BMC Public Health . 2013 ; 13 : 432 .

Wiltshire S , Bancroft A , Parry O , Amos A . ‘I came back here and started smoking again’: perceptions and experiences of quitting among disadvantaged smokers . Health Educ Res . 2003 ; 18 ( 3 ): 292 – 303 .

DiFranza JR . Who are you going to believe? Adolescents and nicotine addiction . J Adolesc Health . 2011 ; 48 ( 1 ): 1 – 2 .

DiFranza JR , Ursprung WW , Biller L . The developmental sequence of tobacco withdrawal symptoms of wanting, craving and needing . Pharmacol Biochem Behav . 2012 ; 100 ( 3 ): 494 – 497 .

American Society for Addiction Medicine . Definition of Addiction . 2015 . www.asam.org/for-the-public/definition-of-addiction . Accessed July 21, 2017 .

Leshner AI . Addiction is a brain disease, and it matters . Science . 1997 ; 278 ( 5335 ): 45 – 47 .

Volkow ND , Koob G . Brain disease model of addiction: why is it so controversial ? Lancet Psychiatry . 2015 ; 2 ( 8 ): 677 – 679 .

Meurk C , Morphett K , Carter A , Weier M , Lucke J , Hall W . Scepticism and hope in a complex predicament: people with addictions deliberate about neuroscience . Int J Drug Policy . 2016 ; 32 : 34 – 43 .

Meurk C , Partridge B , Carter A , Hall W , Morphett K , Lucke J . Public attitudes in Australia towards the claim that addiction is a (brain) disease . Drug Alcohol Rev . 2014 ; 33 ( 3 ): 272 – 279 .

Netherland J . “We haven’t sliced open anyone’s brain yet”: neuroscience, embodiment and the governance of addiction . In: Pickersgill M , Van Keulan I , eds. Sociological Reflections on the Neurosciences (Advances in Medical Sociology) . Emerald Group Publishing Ltd ; 2011 .

Keane H , Weier M , Fraser D , Gartner C . ‘Anytime, anywhere’: vaping as social practice . Crit Public Health . 2016 ;27: 1 – 12 .

Bayer R . Stigma and the ethics of public health: not can we but should we . Soc Sci Med . 2008 ; 67 ( 3 ): 463 – 472 .

Stuber J , Galea S , Link BG . Smoking and the emergence of a stigmatized social status . Soc Sci Med . 2008 ; 67 ( 3 ): 420 – 430 .

Thompson L , Pearce J , Barnett JR . Moralising geographies: stigma, smoking islands and responsible subjects . Area . 2007 ; 39 : 508 – 517 .

Wigginton B , Morphett K , Gartner C . Differential access to health care and support? A qualitative analysis of how Australian smokers conceptualise and respond to stigma . Crit Public Health . 2016 : 1 – 14 . doi:10.1080/09581596.2016.1266298

Wigginton B , Morphett K , Gartner C . Is it the nicotine? Australian smokers’ accounts of nicotine addiction . Addict Res Theory . 2016 ; 24 : 293 – 301 .

Rooke C , Cunningham-Burley S , Amos A . Smokers’ and ex-smokers’ understanding of electronic cigarettes: a qualitative study . Tob Control . 2016 ; 25 ( e1 ): e60 – e66 .

• addictive behavior

Supplementary data

Email alerts, citing articles via.

• About Nicotine & Tobacco Research
• X (formerly Twitter)
• Recommend to your Library

Affiliations

• Online ISSN 1469-994X
• Copyright © 2024 Society for Research on Nicotine and Tobacco
• About Oxford Academic
• Publish journals with us
• University press partners
• What we publish
• New features  
• Open access
• Institutional account management
• Rights and permissions
• Get help with access
• Accessibility
• Advertising
• Media enquiries
• Oxford University Press
• Oxford Languages
• University of Oxford

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide

• Copyright © 2024 Oxford University Press
• Cookie settings
• Cookie policy
• Privacy policy
• Legal notice

This Feature Is Available To Subscribers Only

Sign In or Create an Account

This PDF is available to Subscribers Only

For full access to this pdf, sign in to an existing account, or purchase an annual subscription.

An official website of the United States government

Official websites use .gov A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS A lock ( Lock Locked padlock icon ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

• Publications
• Account settings
• Advanced Search
• Journal List

Nicotine Chemistry, Metabolism, Kinetics and Biomarkers

Neal l benowitz, janne hukkanen, peyton jacob iii.

• Author information
• Copyright and License information

Corresponding author.

Nicotine underlies tobacco addiction, influences tobacco use patterns, and is used as a pharmacological aid to smoking cessation. The absorption, distribution and disposition characteristics of nicotine from tobacco and medicinal products are reviewed. Nicotine is metabolized primarily by the liver enzymes CYP2A6, UDP-glucuronosyltransfease (UGT), and flavin-containing monooxygenase (FMO). In addition to genetic factors, nicotine metabolism is influenced by diet and meals, age, sex, use of estrogen-containing hormone preparations, pregnancy and kidney disease, other medications, and smoking itself. Substantial racial/ethnic differences are observed in nicotine metabolism, which are likely influenced by both genetic and environmental factors. The most widely used biomarker of nicotine intake is cotinine, which may be measured in blood, urine, saliva, hair, or nails. The current optimal plasma cotinine cut-point to distinguish smokers from non-smokers in the general US population is 3 ng ml −1 . This cut-point is much lower than that established 20 years ago, reflecting less secondhand smoke exposure due to clear air policies and more light or occasional smoking.

1 Introduction

An understanding of the pharmacology of nicotine and how nicotine produces addiction and influences smoking behavior provides a necessary basis for therapeutic advances in smoking cessation interventions. This chapter provides a review of several aspects of the human pharmacology of nicotine. These include the presence and levels of nicotine and related alkaloids in tobacco products, the absorption of nicotine from tobacco products and nicotine medications, the distribution of nicotine in body tissues, the metabolism and renal excretion of nicotine, nicotine and cotinine blood levels during tobacco use or nicotine replacement therapy, and biomarkers of nicotine exposure. For more details and references on the pharmacokinetics and metabolism of nicotine, the reader is referred to Hukkanen et al. (2005c) .

2 Nicotine and Related Alkaloids in Tobacco Products

Nicotine ( Fig. 1 ) is a natural ingredient acting as a botanical insecticide in tobacco leaves. It is the principal tobacco alkaloid, occurring to the extent of about 1.5% by weight in commercial cigarette tobacco and comprising about 95% of the total alkaloid content. Oral snuff and pipe tobacco contain concentrations of nicotine similar to cigarette tobacco, whereas cigar and chewing tobacco have only about half the nicotine concentration of cigarette tobacco. An average tobacco rod contains 10–14 mg of nicotine ( Kozlowski et al. 1998 ), and on average about 1–1.5 mg of nicotine is absorbed systemically during smoking ( Benowitz and Jacob 1984 ). Nicotine in tobacco is largely the levorotary ( S )-isomer; only 0.1–0.6% of total nicotine content is ( R )-nicotine ( Armstrong et al. 1998 ). Chemical reagents and pharmaceutical formulations of ( S )-nicotine have a similar content of ( R )-nicotine (0.1–1.2%) as impurity since plant-derived nicotine is used for their manufacture.

Structures of tobacco alkaloids. Reprinted from Benowitz and Jacob (1998) with permission of Wiley-Liss, a subsidiary of Wiley

In most tobacco strains, nornicotine and anatabine are the most abundant of minor alkaloids, followed by anabasine ( Fig. 1 ). This order of abundance is the same in cigarette tobacco and oral snuff, chewing, pipe, and cigar tobacco ( Jacob et al. 1999 ). However, nornicotine levels are highest in cigar tobacco, anatabine levels are lowest in chewing tobacco and oral snuff, and anabasine levels are lowest in chewing tobacco ( Jacob et al. 1999 ). Small amounts of the N′ -methyl derivatives of anabasine and anatabine are found in tobacco and tobacco smoke. Several of the minor alkaloids are thought to arise by bacterial action or oxidation during tobacco processing rather than by biosynthetic processes in the living plant ( Leete 1983 ). These include myosmine, N′ -methylmyosmine, cotinine, nicotyrine, nornicotyrine, nicotine N′ -oxide, 2, 3′-bipyridyl, and metanicotine ( Fig. 1 ). Myosmine is found not only in tobacco but also in a variety of foods including nuts, cereals, milk, and potatoes ( Tyroller et al. 2002 ). Also, nicotine is found in low levels in vegetables such as potatoes, tomatoes, and eggplants ( Siegmund et al. 1999 ).

3 Absorption of Nicotine

Nicotine is distilled from burning tobacco and carried proximally on tar droplets (also called particulate matter), which are inhaled. Absorption of nicotine across biological membranes depends on pH. Nicotine is a weak base with a p K a of 8.0. In its ionized state, such as in acidic environments, nicotine does not rapidly cross membranes. The pH of smoke from flue-cured tobaccos, found in most cigarettes, is acidic (pH 5.5–6.0). At this pH, nicotine is primarily ionized. As a consequence, there is little buccal absorption of nicotine from flue-cured tobacco smoke, even when it is held in the mouth ( Gori et al. 1986 ). Smoke from air-cured tobaccos, the predominant tobacco used in pipes, cigars, and some European cigarettes, is more alkaline (pH 6.5 or higher) and, considerable nicotine is unionized. Smoke from these products is well absorbed through the mouth ( Armitage et al. 1978 ). It has recently been proposed that the pH of cigarette smoke particulate matter is higher than previously thought, and thus, a larger portion of nicotine would be in the unionized form, facilitating rapid pulmonary absorption ( Pankow 2001 ).

When tobacco smoke reaches the small airways and alveoli of the lung, nicotine is rapidly absorbed. Blood concentrations of nicotine rise quickly during a smoke and peak at the completion of smoking ( Fig. 2 ). The rapid absorption of nicotine from cigarette smoke through the lungs, presumably because of the huge surface area of the alveoli and small airways, and dissolution of nicotine in the fluid of pH 7.4 in the human lung facilitate transfer across membranes. After a puff, high levels of nicotine reach the brain in 10–20 s, faster than with intravenous administration, producing rapid behavioral reinforcement ( Benowitz 1990 ). The rapidity of rise in nicotine levels permits the smoker to titrate the level of nicotine and related effects during smoking, and makes smoking the most reinforcing and dependence-producing form of nicotine administration ( Henningfield and Keenan 1993 ).

Blood nicotine concentrations during and after cigarette smoking for 9 min, oral snuff (2.5 g), chewing tobacco (average 7.9 g), and nicotine gum (two 2-mg pieces). Average values for 10 subjects (±SEM). Reprinted from Benowitz et al. (1988) with permission from American Society for Clinical Pharmacology and Therapeutics

The process of cigarette smoking is complex and, as mentioned above, the smoker can manipulate the dose of nicotine and nicotine brain levels on a puff-by-puff basis. Intake of nicotine during smoking depends on puff volume, depth of inhalation, the extent of dilution with room air, and the rate and intensity of puffing ( USDHHS 2001 ). For this reason, machine-determined nicotine yields of cigarettes cannot be used to estimate the dose of nicotine by a smoker ( Jarvis et al. 2001 ). In general, cigarette smokers switching from a higher to a lower-yield cigarette will compensate, i.e., will change their smoking pattern to gain more nicotine ( USDHHS 2001 ).

Chewing tobacco and snuff are buffered to alkaline pH to facilitate absorption of nicotine through oral mucosa. Although absorption through cell membranes is rapid for these more alkaline tobacco products, the rise in the brain nicotine level is slower than with smoking ( Fig. 2 ). Concentrations of nicotine in the blood rise gradually with the use of smokeless tobacco and plateau at about 30 min, with levels persisting and declining only slowly over 2 h or more ( Benowitz et al. 1988 ).

Various formulations of nicotine replacement therapy (NRT), such as nicotine gum, transdermal patch, nasal spray, inhaler, sublingual tablets, and lozenges, are buffered to alkaline pH to facilitate absorption of nicotine through cell membranes. Absorption of nicotine from all NRTs is slower and the increase in nicotine blood levels is more gradual than from smoking. This slow increase in blood and especially in brain levels results in low abuse liability of NRTs ( West et al. 2000 ). Only nasal spray provides a rapid delivery of nicotine that is closer to the rate of nicotine delivery achieved with smoking ( Gourlay and Benowitz 1997 ; Guthrie et al. 1999 ). The absolute dose of nicotine absorbed systemically from nicotine gum is much less than the nicotine content of the gum, in part, because considerable nicotine is swallowed with subsequent first-pass metabolism ( Benowitz et al. 1987 ). Some nicotine is also retained in chewed gum. A portion of the nicotine dose is swallowed and subjected to first-pass metabolism when using other NRTs, inhaler, sublingual tablets, nasal spray, and lozenges. Bioavailability for these products with absorption mainly through the mucosa of the oral cavity and a considerable swallowed portion is about 50–80%.

Nicotine base is well absorbed through skin. That is the reason for the occupational risk of nicotine poisoning (green tobacco sickness) in tobacco harvesters who are exposed to wet tobacco leaves ( McBride et al. 1998 ). That is also the basis for transdermal delivery technology. Currently in the United States several different nicotine transdermal systems are marketed. All are multilayer patches. The rate of release of nicotine into the skin is controlled by the permeability of the skin, rate of diffusion through a polymer matrix, and/or rate of passage through a membrane in the various patches. Rates of nicotine delivery and plasma nicotine concentrations vary among different transdermal systems ( Fant et al. 2000 ). In all cases, there is an initial lag time of about 1 h before nicotine appears in the bloodstream, and there is continued systemic absorption (about 10% of the total dose) after the patch is removed, the latter due to residual nicotine in the skin.

4 Distribution of Nicotine in Body Tissues

After absorption, nicotine enters the bloodstream where, at pH 7.4, it is about 69% ionized and 31% unionized. Binding to plasma proteins is less than 5% ( Benowitz et al. 1982a ). The drug is distributed extensively to body tissues with a steady-state volume of distribution averaging 2.6 L/Kg. Based on human autopsy samples from smokers, the highest affinity for nicotine is in the liver, kidney, spleen, and lung and lowest in adipose tissue. In skeletal muscle, concentrations of nicotine and cotinine are close to that of whole blood. Nicotine binds to brain tissues with high affinity, and the receptor binding capacity is increased in smokers compared with nonsmokers ( Breese et al. 1997 ; Perry et al. 1999 ). Increase in the binding is caused by a higher number of nicotinic cholinergic receptors in the brain of the smokers. Nicotine accumulates markedly in gastric juice and saliva ( Lindell et al. 1996 ). Gastric juice/plasma and saliva/plasma concentration ratios are 61 and 11 with transdermal nicotine administration, and 53 and 87 with smoking, respectively ( Lindell et al. 1996 ). Accumulation is caused by ion-trapping of nicotine in gastric juice and saliva. Nicotine also accumulates in breast milk (milk/plasma ratio 2.9) ( Dahlstrom et al. 1990 ). Nicotine crosses the placental barrier easily, and there is evidence for accumulation of nicotine in fetal serum and amnionic fluid in slightly higher concentrations than in maternal serum ( Dempsey and Benowitz 2001 ).

The time course of nicotine accumulation in the brain and in other body organs and the resultant pharmacologic effects are highly dependent on the route and rate of dosing. Smoking a cigarette delivers nicotine rapidly to the pulmonary venous circulation, from which it moves quickly to the left ventricle of the heart and to the systemic arterial circulation and brain. The lag time between a puff of a cigarette and nicotine reaching the brain is 10–20 s. Although delivery of nicotine to the brain is rapid, there is nevertheless significant pulmonary uptake and some delayed release of nicotine as evidenced by pulmonary positron emission tomography data and the slow decrease in arterial concentrations of nicotine between puffs. ( Rose et al. 1999 ) Nicotine concentrations in arterial blood after smoking a cigarette can be quite high, reaching up to 100 ng ml −1 , but usually ranging between 20 and 60 ng ml −1 ( Gourlay and Benowitz 1997 ; Henningfield and Keenan 1993 ; Lunell et al. 2000 ; Rose et al. 1999 ). The usual peak arterial nicotine concentration after the first puff is lower, averaging 7 ng ml −1 . As high as tenfold arterial/venous nicotine concentration ratios have been measured ( Henningfield et al. 1993 ), but the mean ratio is typically around 2.3–2.8 ( Gourlay and Benowitz 1997 ; Rose et al. 1999 ). The rapid rate of delivery of nicotine by smoking (or intravenous injection, which presents similar distribution kinetics) results in high levels of nicotine in the central nervous system with little time for development of tolerance. The result is a more intense pharmacologic action. The short time interval between puffing and nicotine entering the brain also allows the smoker to titrate the dose of nicotine to a desired pharmacologic effect, further reinforcing drug self-administration and facilitating the development of addiction.

5 Metabolism of Nicotine

5.1 pathways of nicotine and cotinine metabolism.

Nicotine is extensively metabolized to a number of metabolites ( Fig. 3 ) by the liver. Six primary metabolites of nicotine have been identified. Quantitatively, the most important metabolite of nicotine in most mammalian species is the lactam derivative, cotinine. In humans, about 70–80% of nicotine is converted to cotinine. This transformation involves two steps. The first is mediated primarily by CYP2A6 to produce nicotine-Δ 1′ (5′) -iminium ion, which is in equilibrium with 5′-hydroxynicotine. The second step is catalyzed by a cytoplasmic aldehyde oxidase. Nicotine iminium ion has received considerable interest since it is an alkylating agent and, as such, could play a role in the pharmacology of nicotine ( Shigenaga et al. 1988 ).

Pathways of nicotine metabolism. Reprinted with permission from Hukkanen et al. 2005c

Nicotine N′ -oxide is another primary metabolite of nicotine, although only about 4–7% of nicotine absorbed by smokers is metabolized via this route ( Benowitz et al. 1994 ). The conversion of nicotine to nicotine N′ -oxide involves a flavin-containing monooxygenase 3 (FMO3), which results in formation of both possible diasteriomers, the 1′-( R )-2′-( S )- cis and 1′-( S )-2′-( S )- trans -isomers in animals ( Cashman et al. 1992 ; Park et al. 1993 ). In humans, this pathway is highly selective for the trans -isomer ( Cashman et al. 1992 ). Only the trans -isomer of nicotine N′ -oxide was detected in urine after administration of nicotine by intravenous infusion, trans-dermal patch or smoking ( Park et al. 1993 ). It appears that nicotine N′ -oxide is not further metabolized to any significant extent, except by reduction back to nicotine in the intestines, which may lead to recycling nicotine in the body.

In addition to oxidation of the pyrrolidine ring, nicotine is metabolized by two nonoxidative pathways, methylation of the pyridine nitrogen giving nicotine isomethonium ion (also called N -methylnicotinium ion) and glucuronidation.

Nicotine glucuronidation results in an N -quaternary glucuronide in humans ( Benowitz et al. 1994 ). This reaction is catalyzed by uridine diphosphate-glucuronosyltransferase (UGT) enzyme(s) producing ( S )-nicotine- N -β-glucuronide. About 3–5% of nicotine is converted to nicotine glucuronide and excreted in urine in humans.

Oxidative N -demethylation is frequently an important pathway in the metabolism of xenobiotics, but this route is, in most species, a minor pathway in the metabolism of nicotine. Conversion of nicotine to nornicotine in humans has been demonstrated. We found that small amounts of deuterium-labeled nornicotine are excreted in the urine of smokers administered deuterium-labeled nicotine ( Jacob and Benowitz 1991 ). Metabolic formation of nornicotine from nicotine has also been reported ( Neurath et al. 1991 ). Nornicotine is a constituent of tobacco leaves. However, most urine nornicotine is derived from metabolism of nicotine with less than 40% coming directly from tobacco, as estimated from the difference in nornicotine excretion in smokers during smoking and transdermal nicotine treatment (0.65 and 0.41%, respectively) ( Benowitz et al. 1994 ). A new cytochrome P450-mediated metabolic pathway for nicotine metabolism was reported by Hecht et al. (2000) . 2′-Hydroxylation of nicotine was shown to produce 4-(methylamino)-1-(3-pyridyl)-1-butanone with 2′-hydroxynicotine as an intermediate. 2′-Hydroxynicotine also yields nicotine-Δ 1′(2′) -iminium ion. 4-(methylamino)-1-(3-pyridyl)-1-butanone is further metabolized to 4-oxo-4-(3-pyridyl)butanoic acid and 4-hydroxy-4-(3-pyridyl)butanoic acid. The new pathway is potentially significant since 4-(methylamino)-1-(3-pyridyl)-1-butanone can be converted to carcinogenic NNK. However, endogenous production of NNK from nicotine has not been detected in humans or rats ( Hecht et al. 1999a ).

Although on average about 70–80% of nicotine is metabolized via the cotinine pathway in humans, only 10–15% of nicotine absorbed by smokers appears in the urine as unchanged cotinine ( Benowitz et al. 1994 ). Six primary metabolites of cotinine have been reported in humans: 3′-hydroxycotinine ( McKennis et al. 1963 ; Neurath et al. 1987 ), 5′-hydroxycotinine (also called allohydroxycotinine) ( Neurath 1994 ), which exists in tautomeric equilibrium with the open chain derivative 4-oxo-4-(3-pyridyl)- N -methylbutanamide, cotinine N -oxide, cotinine methonium ion, cotinine glucuronide, and norcotinine (also called demethylcotinine).

3′-Hydroxycotinine is the main nicotine metabolite detected in smokers’ urine. It is also excreted as a glucuronide conjugate ( Benowitz et al. 1994 ). 3′-Hydroxycotinine and its glucuronide conjugate account for 40–60% of the nicotine dose in urine ( Benowitz et al. 1994 ; Byrd et al. 1992 ). The conversion of cotinine to 3′-hydroxycotinine in humans is highly stereoselective for the trans -isomer, as less than 5% is detected as cis -3′-hydroxycotinine in urine ( Jacob et al. 1990 ; Voncken et al. 1990 ). While nicotine and cotinine conjugates are N -glucuronides, the only 3′-hydroxycotinine conjugate detected in urine is O -glucuronide ( Byrd et al. 1994 ).

Quantitative aspects of the pattern of nicotine metabolism have been elucidated fairly well in people ( Fig. 4 ). Approximately 90% of a systemic dose of nicotine can be accounted for as nicotine and metabolites in urine ( Benowitz et al. 1994 ). Based on studies with simultaneous infusion of labeled nicotine and cotinine, it has been determined that 70–80% of nicotine is converted to cotinine ( Benowitz and Jacob 1994 ). About 4–7% of nicotine is excreted as nicotine N′ –oxide and 3–5% as nicotine glucuronide ( Benowitz et al. 1994 ; Byrd et al. 1992 ). Cotinine is excreted unchanged in urine to a small degree (10–15% of the nicotine and metabolites in urine). The remainder is converted to metabolites, primarily trans –3′–hydroxycotinine (33–40%), cotinine glucuronide (12–17%), and trans –3′–hydroxycotinine glucuronide (7–9%).

Quantitative scheme of nicotine metabolism, based on estimates of average excretion of metabolites as percent of total urinary nicotine. Reprinted with permission from Hukkanen et al. 2005c

5.2 Rates of Nicotine and Cotinine Metabolism

The rate of metabolism of nicotine can be determined by measuring blood levels after administration of a known dose of nicotine ( Table 1 ) ( Hukkanen et al. 2005c ). Total clearance of nicotine averages about 1200 ml min −1 . Nonrenal clearance represents about 70% of liver blood flow. Assuming most nicotine is metabolized by the liver, this means that about 70% of the drug is extracted from blood in each pass through the liver.

Nicotine absorption pharmacokinetics of different forms of nicotine administration in single doses (modified from Hukkanen et al. 2005c )

Products in italics are currently marketed in the United States

C max and T max values are for peripheral venous blood unless otherwise indicated

T max values are measured from the start of the administration

Estimated dose of 2 mg of nicotine per cigarette is higher than the usual 1–1.5 mg per cigarette since nicotine absorption from smoking a single cigarette was studied after at least overnight abstinence from smoking in these studies

The metabolism of cotinine is much slower than that of nicotine. Cotinine clearance averages about 45 ml min −1 . Clearance of (3′ R , 5′ S )- trans -3′-hydroxycotinine is also quite slow – about 82 ml min −1 .

5.3 Use of the Nicotine Metabolite Ratio

The 3′-hydroxycotinine/cotinine ratio (3HC/cotinine) in plasma and saliva has been evaluated as a non-invasive probe for CYP2A6 activity ( Dempsey et al. 2004 ). The ratio was highly correlated with oral clearance of nicotine and the oral clearance and half-life of cotinine. Correlation coefficients of oral nicotine and cotinine clearances with plasma 3′-hydroxycotinine/cotinine ratios were 0.78 and 0.63, respectively, at 6 h after oral nicotine dosing.

The availability of a phenotypic marker of CYP2A6 activity is important because there is wide variability in nicotine clearance among people with wild-type CYP2A6 genes and only a small proportion of the genetic variability in nicotine clearance can be explained by known CYP2A6 gene variants, at least in whites ( Swan et al. 2005 ). The 3′-hydroxycotinine/cotinine ratio can be used to phenotype nicotine metabolism and CYP2A6 enzyme in smokers while smoking their usual cigarettes ( Johnstone et al. 2006 ; Kandel et al. 2007 ; Lerman et al. 2006 ; Patterson et al. 2008 ). The 3HC/cotinine ratio has been studied as predictor of response to pharmacotherapy.

In one trial, where transdermal nicotine and nicotine nasal spray were compared, the nicotine metabolite ratio (derived from nicotine taken in from tobacco) was shown to be a strong predictor of smoking cessation, both at the end of treatment and in 6 months, in people treated with transdermal nicotine but not nicotine nasal spray ( Lerman et al. 2006 ). In patients treated with transdermal nicotine, slow metabolizers had better cessation response and higher plasma nicotine concentration while using the patch than faster metabolizers, suggesting that higher nicotine levels might be responsible for a better cessation outcome. In contrast, smokers treated with nicotine nasal spray showed no difference in plasma nicotine concentration as a function of the rate of nicotine metabolism, consistent with the idea that nicotine taken in from the spray is titrated by the smoker to the desired effect. However, another recent trial examined the association between the nicotine metabolite ratio and response to bupropion therapy ( Patterson et al. 2008 ). Faster metabolism of nicotine was associated with lower success rate in quitting in a placebo-treated group; but among smokers receiving bupropion, the rate of nicotine metabolism had no differential effect. Bupropion is not metabolized by CYP2A6. Therefore, the findings of the Patterson study are consistent with the idea that rapid metabolizers of nicotine are generally more dependent and have a harder time quitting than do slow metabolizers. The mechanisms of such a relationship have not been proven, but may include more severe withdrawal symptoms and/or a different type of nicotine reinforcement related to more rapid loss of tolerance in fast metabolizers.

Various enzymes involved in nicotine metabolism and their genetics are described in detail in the chapter by Mwenifumbo and Tyndale in this volume.

6 Factors Influencing Nicotine Metabolism

There is considerable inter individual variability in the rate of elimination of nicotine and cotinine in people ( Swan et al. 2005 ). Besides genetic variations discussed by Mwenifumbo and Tyndale, a number of factors that might explain individual variability have been studied.

6.1 Physiological Influences

6.1.1 diet and meals.

An implication of the high degree of hepatic extraction is that clearance of nicotine should be dependent on liver blood flow. Thus, physiological events, such as meals, posture, exercise, or drugs perturbing hepatic blood flow, are predicted to affect the rate of nicotine metabolism. Meals consumed during a steady state infusion of nicotine result in a consistent decline in nicotine concentrations, the maximal effect seen 30–60 min after the end of a meal ( Gries et al. 1996 ; Lee et al. 1989 ). Hepatic blood flow increases about 30% and nicotine clearance increases about 40% after a meal.

Menthol is widely used as a flavorant in foods, mouthwash, toothpaste, and cigarettes. A moderate inhibition of CYP2A6-mediated nicotine metabolism in human liver microsomes by menthol and various related compounds has been reported ( MacDougall et al. 2003 ). This is supported by a crossover study in people, showing that mentholated cigarette smoking significantly inhibits metabolism of nicotine to cotinine and nicotine glucuronidation when compared to smoking nonmentholated cigarettes ( Benowitz et al. 2004 ).

Grapefruit juice inhibits CYP2A6, as evidenced by inhibition of coumarin metabolism in people ( Runkel et al. 1997 ). Grapefruit juice has been shown to inhibit the metabolism of nicotine to cotinine in nonsmokers who were given nicotine orally, with evidence of a greater effect with larger doses of grapefruit juice ( Hukkanen et al. 2006 ). Grapefruit juice also increased renal clearance of nicotine and cotinine by an unknown mechanism. Grapefruit juice had no significant effect on overall exposure to nicotine (area under the plasma concentration–time curve) because the effects of slowed metabolism were offset by the effects on increased renal clearance. Whether the effects of grapefruit juice on nicotine levels in users of tobacco are significant has not been investigated. Consumption of watercress enhances the formation of nicotine glucuronide, cotinine glucuronide, and 3′-hydroxycotinine glucuronide in smokers ( Hecht et al. 1999b ). Watercress has no effect on the excretion of nicotine, cotinine, and 3′-hydroxycotinine in smokers. Thus, watercress may induce some UGT enzymes involved in nicotine metabolism, but has no effect on CYP2A6-mediated nicotine metabolism.

Clearance of nicotine is decreased in the elderly (age >65) compared to adults ( Molander et al. 2001 ). Total clearance was lower by 23%, and renal clearance lower by 49% in the elderly compared to young adults. Lower nicotine metabolism in the elderly may be contributed to by reduced liver blood flow, since no decrease in CYP2A6 protein levels or nicotine metabolism in liver microsomes due to age has been detected ( Messina et al. 1997 ). No differences in steady-state nicotine plasma levels or estimated plasma clearance values were detected in three age groups (18–39, 40–59, and 60–69 years) using patches with the same nicotine content ( Gourlay and Benowitz 1996 ). The volume of distribution of nicotine is lower in older subjects due to a decrease in lean body mass ( Molander et al. 2001 ).

Neonates have diminished nicotine metabolism, as demonstrated by a nicotine half-life of three to four times longer in newborns exposed to tobacco smoke than in adults ( Dempsey et al. 2000 ). Cotinine half-life is reported to be similar in neonates, older children, and adults in two studies ( Dempsey et al. 2000 ; Leong et al. 1998 ). Other studies found that the half-life of urine cotinine was about three times longer in children less than one year old than to the cotinine half-life in adults ( Collier et al. 1994 ). Urine cotinine half-life can be influenced by variations in urine volume and excretion of creatinine. The study by Dempsey et al. was the only one in which the half-life of cotinine was calculated based on both the blood and urine cotinine concentrations ( Dempsey et al. 2000 ). In that study, both the blood and urine half-lives were similar to adult values, supporting the notion that neonates have the same cotinine half-life as older children and adults.

Why nicotine has a much longer half-life in neonates than in adults, whereas the cotinine half-life is essentially the same in newborns and adults, might partially be explained by differing sensitivities of nicotine and cotinine clearances to changes in hepatic blood flow. As a drug with a high extraction ratio, the clearance of nicotine is influenced by changes in hepatic blood flow, whereas clearance of cotinine with low extraction ratio is more dependent on changes in intrinsic clearance, i.e., amount and activity of metabolic enzymes. Studies in newborn animals, mainly sheep, have shown that hepatic blood flow is low immediately after delivery because of the loss of the umbilical venous blood supply and the patency of ductus venosus ( Gow et al. 2001 ). Hepatic blood flow (ml −1 min −1 mg of liver) rises to adult levels within the first week, due to increased blood flow in the portal vein and gradual closure of ductus venosus, which is complete by the eighteenth day in human neonates. This would mean that nicotine clearance should rise and the nicotine half-life shorten within the first couple of weeks as hepatic blood flow increases. Another explanation could be that nicotine and cotinine are metabolized mainly by enzymes other than CYP2A6 in neonates. However, neonates have only slightly lower amounts of CYP2A6, CYP2D6, and CYP2E1 protein in liver microsomes, whereas the CYP2B6 amount is clearly diminished in neonates compared to adults and older children ( Tateishi et al. 1997 ).

6.1.3 Chronopharmacokinetics of Nicotine

During sleep, hepatic blood flow declines and nicotine clearance falls correspondingly. Blood nicotine levels rise during constant infusion at night. Nicotine clearance varies by approximately 17% (from peak to trough) with a minimum between 6 p.m. and 3 a.m. Thus, the day/night variation and meal effects of nicotine clearance result in circadian variations in plasma concentrations during constant dosing of nicotine ( Gries et al. 1996 ).

6.1.4 Gender Related Differences in Nicotine Metabolism

Differences between men and women.

A twin study with intravenous infusions of both nicotine and cotinine clearly shows that nicotine and cotinine clearances are higher in women than in men; oral contraceptive use further accelerates nicotine and cotinine clearances in women ( Benowitz et al. 2006 ). Nicotine clearance and cotinine clearance were 13 and 24% higher, respectively, in women not using oral contraceptives than in men. Oral contraceptive use induced increases in nicotine and cotinine clearance by 28 and 30%, respectively, compared to women not using oral contraceptives. The gender difference was also detected in recent studies on smokers, showing that the ratio of 3HC/cotinine in blood or urine is significantly higher in women indicating faster metabolism in women than men ( Johnstone et al. 2006 ; Kandel et al. 2007 ).

Pregnancy and Menstrual Cycle

Pregnancy has a marked inducing effect in nicotine and especially cotinine clearance. Clearance is increased by 60 and 140% for nicotine and cotinine, respectively, in pregnancy compared to postpartum ( Dempsey et al. 2002 ). Nicotine is a rapidly cleared drug with a high affinity for CYP2A6 and its rate of clearance is primarily controlled by hepatic blood flow, while the rate of cotinine clearance is primarily determined by the activity of metabolizing enzymes in the liver. The finding that in pregnancy cotinine clearance is increased more than nicotine clearance indicates that the increase in clearance is most likely caused by induction of CYP2A6, and not by an increase in hepatic blood flow. A study comparing women during pregnancy and again postpartum, found that the mean salivary cotinine concentration per cigarette was higher when not pregnant (3.5 ng ml −1 vs. 9.9 ng ml −1 ), consistent with higher cotinine clearance during pregnancy ( Rebagliato et al. 1998 ). Pregnant smokers had substantially lower levels of serum nicotine than expected when standardized for their nicotine intake compared to population-based values ( Selby et al. 2001 ). Nicotine and cotinine glucuronidation is induced by pregnancy, while 3′-hydroxycotinine glucuronidation is not ( Dempsey et al. 2002 ). Menstrual cycle (follicular phase vs. luteal phase) has no effect on nicotine and cotinine pharmacokinetics in healthy nonsmoking women ( Hukkanen et al. 2005b ). Pregnancy also increases the rate of formation of nicotine N′ -oxide, indicating induction of the enzyme, flavin-containing monooxygenase 3 ( Hukkanen et al. 2005a ).

The above-mentioned results show that gender has substantial effects on nicotine and cotinine metabolism. Higher metabolism of nicotine and cotinine is detected in women than in men, in users of oral contraceptives than in women not using oral contraceptives, and in pregnant women than in the same subjects postpartum. Furthermore, the inducing effect has a dose–response relationship; gender differences are relatively small, oral contraceptive use further induces metabolism in women, and pregnancy shows the most striking induction compared to postpartum. Changes in clearance appear to be related to the amount of sex hormones present; women have higher concentrations of estrogens and progesterone than men do, oral contraceptive users have higher concentrations of these hormones than women not using oral contraceptives, and pregnancy results in the highest concentrations of circulating sex hormones. These results suggest that CYP2A6 activity is induced by sex hormones and there is recent in-vitro evidence for the induction of human CYP2A6 by estrogen acting on the estrogen receptor ( Higashi et al. 2007 ).

Kidney Disease

Kidney failure not only decreases renal clearance of nicotine and cotinine, but also metabolic clearance of nicotine ( Molander et al. 2000 ). Metabolic clearance of nicotine is reduced by 50% in subjects with severe renal impairment compared to healthy subjects. It is speculated that accumulation of uremic toxins may inhibit CYP2A6 activity or downregulate CYP2A6 expression in liver. Hepatic metabolism of several drugs is reduced in kidney failure, mainly via downregulation of CYP enzymes and/or inhibition of transporters ( Nolin et al. 2003 ).

6.2 Medications

6.2.1 inducers.

A few drugs have been shown to induce CYP2A6 in human primary hepatocyte culture. These include prototypical inducers rifampicin, dexamethasone, and phenobarbital, although there is wide interindividual variability in response ( Madan et al. 2003 ; Meunier et al. 2000 ; Rae et al. 2001 ). Rifampicin was also shown to inhibit CYP2A6 activity as measured by coumarin 7-hydroxylase ( Xia et al. 2002 ). Thus the presence of rifampin may inhibit while chronic administration of rifampin may induce CYP2A6. That might explain the highly variable effects on CYP2A6 induction seen in studies with rifampicin.

There is evidence for the induction of CYP2A6 in vivo by phenobarbital and other anticonvulsant drugs. Two-day treatment with phenobarbital (100 mg per day p.o.) prior to a liver biopsy resulted in induction of metabolism of nicotine to cotinine in hepatocytes ( Kyerematen et al. 1990 ). Liver microsomes from phenobarbital-treated patients have higher amounts of CYP2A6 protein than microsomes from untreated patients ( Cashman et al. 1992 ). A recent study showed that the antimalarial drug artemisinin significantly altered the pharmacokinetics of both nicotine and coumarin, suggesting induction of CYP2A6. ( Asimus et al. 2008 ).

As mentioned earlier, nicotine and cotinine clearances are higher in women using oral contraceptives than in women not using oral contraceptives ( Benowitz et al. 2006 ). Oral contraceptive use induced nicotine and cotinine clearances by 28 and 30%, respectively. A previous small-scale study with caffeine phenotyping of CYP2A6 activity showed a 22% increase in CYP2A6 activity in oral contraceptive users compared to women not using contraceptives ( Krul and Hageman 1998 ).

6.2.2 Inhibitors

Several compounds are inhibitors of CYP2A6-mediated nicotine metabolism in vitro, including methoxsalen (8-methoxypsoralen), tranylcypromine, tryptamine and coumarin ( Le Gal et al. 2003 ; MacDougall et al. 2003 ; Nakajima et al. 1996 ; Zhang et al. 2001 ). Raloxifene is a potent inhibitor of aldehyde oxidase and it has been shown to inhibit the formation of cotinine from nicotine-Δ 1′ (5′) -iminium ion in human liver cytosol ( Obach 2004 ).

Only methoxsalen (used in the photochemotherapy of psoriasis) and tranyl-cypromine (a monoamine oxidase inhibitor) have been demonstrated to inhibit nicotine metabolism in people ( Sellers et al. 2000 , 2003 ). These compounds are only moderately specific for CYP2A6; methoxsalen is also a potent inhibitor of CYP1A2, and tranylcypromine inhibits CYP2B6 and CYP2E1 ( Taavitsainen et al. 2001 ; Zhang et al. 2001 ). Methoxsalen reduces first-pass metabolism of oral nicotine, decreases clearance of subcutaneously administered nicotine, and decreases urinary levels of 3′-hydroxycotinine in smokers ( Sellers et al. 2000 , 2003 ). Tranyl-cypromine has been shown to reduce first-pass metabolism of oral nicotine ( Tyndale and Sellers 2001 ). As smokers smoke at least in part to maintain desired levels of nicotine in the brain, decreased metabolism and higher concentration of nicotine result in a reduction in the number of cigarettes smoked ( Sellers et al. 2000 ). Also, as CYP2A6 is involved in the activation of carcinogenic NNK, inhibition of CYP2A6 routes the metabolism of NNK towards the inactive NNAL-glucuronide ( Sellers et al. 2003 ). Thus, CYP2A6 inhibitors might be of use in reduction of smoking, thereby decreasing the exposure to carcinogenic metabolites, possibly reducing the risk of cancer, and enhancing the efficacy of nicotine replacement therapies.

6.3 Smoking

6.3.1 inhibiting effect of smoking on nicotine clearance.

Cigarette smoking itself influences the rate of metabolism of nicotine. Cigarette smoking is known to accelerate the metabolism of some drugs, especially the ones primarily metabolized by CYP1A2 ( Zevin and Benowitz 1999 ). However, we found that the clearance of nicotine was significantly slower in cigarette smokers than in nonsmokers ( Benowitz and Jacob 1993 ). In support of this observation are crossover studies comparing the clearance of nicotine in the same subjects when smoking compared to when not smoking. After 4 days of smoking abstinence, nicotine clearance was increased by 14% ( Benowitz and Jacob 2000 ), and after 7 days of abstinence, nicotine clearance was 36% higher ( Lee et al. 1987 ), when compared to overnight abstinence from cigarettes.

These studies suggest that there are substance(s) in tobacco smoke, as yet unidentified, that inhibit the metabolism of nicotine. Because nicotine and cotinine are metabolized by the same enzyme, the possibility that cotinine might be responsible for the slowed metabolism of nicotine in smokers was examined. In a study in which nonsmokers received an intravenous infusion of nicotine with and without pretreatment with high doses of cotinine, there was no effect of cotinine on the clearance of nicotine ( Zevin et al. 1997 ). Also, carbon monoxide at levels and in patterns similar to those experienced during smoking had no effect on nicotine and cotinine clearance ( Benowitz and Jacob 2000 ).

Recently, β-nicotyrine, a minor tobacco alkaloid, was shown to effectively inhibit CYP2A6 in vitro ( Denton et al. 2004 ). Thus, β-nicotyrine is one candidate in the search for the inhibiting compound in tobacco smoke. Another possibility is that reduced nicotine clearance is due to downregulation of CYP2A6 expression, and not due to inhibition. Tyndale and coworkers have demonstrated that administration of nicotine for 21 days to monkeys in vivo decreases CYP2A6 activity (nicotine metabolism) by downregulating CYP2A6 mRNA and protein in liver ( Schoedel et al. 2003 ). Interestingly, expression of both CYP2A and CYP3A5 mRNAs are markedly reduced in human pulmonary tissues in smokers compared to nonsmokers ( Crawford et al. 1998 ; Hukkanen et al. 2003 ). The mechanisms of the downregulation are currently unknown.

6.3.2 Inducing Effect of Smoking on Glucuronidation

The excretion of 3′-hydroxycotinine O -glucuronide is induced by smoking, when compared to not smoking studied with a crossover design ( Benowitz and Jacob 2000 ). The extent of nicotine and cotinine N-glucuronidation was not significantly affected by smoking. Smoking is known to induce glucuronidation of some drugs, such as propranolol and oxazepam ( Liston et al. 2001 ). Urinary excretion of 3′-hydroxycotinine O -glucuronide is correlated with the excretion of NNAL- O -glucuronide ( Hecht et al. 1999b ), which is formed by UGT1A9 and UGT2B7 ( Ren et al. 2000 ). TCDD (2,3,7,8-tetrachlorodibenzo-p-dioxin), an AHR (arylhydrocarbon receptor) agonist, induces UGT1A9 but does not induce UGT2B7 in human Caco-2 cells ( Munzel et al. 1999 ). Thus, UGT1A9 could be the inducible component of 3′-hydroxycotinine O-glucuronidation.

6.4 Racial and Ethnic Differences

Racial differences in nicotine and cotinine metabolism have been observed. We compared nicotine and cotinine metabolism in blacks and whites ( Benowitz et al. 1999 ; Perez-Stable et al. 1998 ). The total and nonrenal clearance of cotinine was significantly lower in blacks than in whites (total clearance 0.57 vs. 0.76 ml min −1 kg −1 ). Also, the fractional clearance of nicotine to cotinine, and the metabolic clearance of nicotine to cotinine were lower in blacks. The clearance of nicotine tended to be lower in blacks than in whites (18.1 vs. 20.5 ml min −1 kg −1 ), but this difference was not significant. Excretion of nicotine and cotinine glucuronides was lower in blacks, while excretion of 3′-hydroxycotinine glucuronide was similar in both groups. Nicotine and cotinine glucuronidation appeared to be polymorphic in blacks, with evidence of slow and fast N-glucuronide formers. The distribution of glucuronidation was unimodal in whites. Polymorphic patterns of cotinine glucuronidation in blacks has been detected in other studies ( de Leon et al. 2002 ). Slower metabolism of cotinine explains in part the higher cotinine levels per cigarette detected in blacks than in whites ( Caraballo et al. 1998 ; English et al. 1994 ; Wagenknecht et al. 1990 ). One possible explanation for the slower cotinine metabolism in blacks is the significantly higher proportion of menthol cigarette smokers in blacks than in whites (69% vs. 22% in the general US population, 76% vs. 9% in our study) ( Benowitz et al. 1999 ; Giovino et al. 2004 ). As discussed earlier, menthol cigarette smoking inhibits nicotine oxidation and glucuronidation ( Benowitz et al. 2004 ).

Nicotine and cotinine metabolism among Chinese–Americans, Latinos, and whites has been compared ( Benowitz et al. 2002b ). Chinese–Americans had the lowest total and nonrenal clearance of nicotine and cotinine, and lowest metabolic clearance of nicotine via the cotinine pathway. Also, nicotine intake per cigarette was lower in Chinese–Americans than in Latinos and whites. No significant differences in nicotine and cotinine metabolism or nicotine intake were detected between Latinos and whites. Glucuronidation of nicotine and metabolites did not differ between the groups. Consistent with the findings in experimental studies, Kandel et al. found in an epidemiologic study that the 3HC/cotinine ratio in the urine of young adult smokers, reflecting CYP2A6 activity, was higher in whites and Hispanics than in blacks and Asians ( Kandel et al. 2007 ).

7 Renal Excretion

Nicotine is excreted by glomerular filtration and tubular secretion, with variable reabsorption depending on urinary pH. With uncontrolled urine pH, renal clearance averages about 35–90 ml min −1 , accounting for the elimination of about 5% of total clearance. In acid urine, nicotine is mostly ionized and tubular reabsorption is minimized; renal clearance may be as high as 600 ml min −1 (urinary pH 4.4), depending on urinary flow rate ( Benowitz and Jacob 1985 ). In alkaline urine, a larger fraction of nicotine is unionized, allowing net tubular reabsorption with a renal clearance as low as 17 ml min −1 (urine pH 7.0).

In vitro studies have shown that there are distinct transport systems for both basolateral and apical uptake of nicotine ( Takami et al. 1998 ). Nicotine has been shown to be actively transported by kidney cells, most likely by the organic ion transporter OCT2 ( Zevin et al. 1998 ; Urakami et al. 1998 ). Cimetidine decreases renal clearance of nicotine by 47% in nonsmoking volunteers ( Bendayan et al. 1990 ). This is consistent with the inhibition of basolateral uptake by cimetidine detected in vitro. Mecamylamine reduces renal clearance of nicotine in smokers dosed with intravenous nicotine when urine is alkalinized, but not when urine is acidified ( Zevin et al. 2000 ).

Renal clearance of cotinine is much less than the glomerular filtration rate ( Benowitz et al. 2008b ). Since cotinine is not appreciably protein bound, this indicates extensive tubular reabsorption. Renal clearance of cotinine can be enhanced by up to 50% with extreme urinary acidification. Cotinine excretion is less influenced by urinary pH than nicotine because it is less basic and, therefore, is primarily in the unionized form within the physiological pH range. As is the case for nicotine, the rate of excretion of cotinine is influenced by urinary flow rate. Renal excretion of cotinine is a minor route of elimination, averaging about 12% of total clearance. In contrast, 100% of nicotine N′ -oxide and 63% of 3′-hydroxycotinine are excreted unchanged in the urine ( Benowitz and Jacob 2001 ; Park et al. 1993 ).

The genetic contributions to nicotine and cotinine renal clearances have been estimated in a twin study ( Benowitz et al. 2008b ). This study found a substantial contribution of genetic factors to the net secretory/reabsorbtive clearances of nicotine and cotinine. These findings suggest either that the reabsorption of nicotine and cotinine are active processes and are influenced by the genetics of reabsorptive transporters, or that the active secretory component of renal clearance exerts a substantial effect on the clearance, even in the presence of net reabsorption. It is plausible that the genetic component of the variation in the reabsorbtive clearance of nicotine is determined by the corresponding variation in reabsorptive transporters.

As mentioned previously, renal failure markedly reduces total renal clearance, as well as metabolic clearance of nicotine and cotinine ( Molander et al. 2000 ). Reduction of renal clearance is correlated with the severity of kidney failure; renal clearance is reduced by half in mild renal failure, and by 94% in severe renal impairment. Markedly elevated levels of serum nicotine have been detected in smoking patients with end-stage renal disease undergoing hemodialysis ( Perry et al. 1984 ). This is explained not only by reduced renal clearance, but also by lower metabolic clearance of nicotine in renal disease. It is speculated that accumulation of uremic toxins inhibits CYP2A6 activity or downregulates CYP2A6 expression in liver.

8 Nicotine and Cotinine Blood Levels During Tobacco Use and Nicotine Replacement Therapy

Blood or plasma nicotine concentrations sampled in the afternoon in smokers generally range from 10 to 50 ng ml −1 . Typical trough concentrations during daily smoking range between 10 and 37 ng ml −1 and typical peak concentrations range between 19 and 50 ng ml −1 . The increment in venous blood nicotine concentration after smoking a single cigarette varies from 5 to 30 ng ml −1 , depending on how a cigarette is smoked. In a recent study, the mean nicotine boost after smoking a cigarette was 10.9 ng ml −1 in smokers with no smoking abstinence on the study day ( Patterson et al. 2003 ).

Blood levels peak at the end of smoking a cigarette and decline rapidly over the next 20 min due to tissue distribution. The distribution half-life averages about 8 min. Although the rate of rise of nicotine is slower for cigar smokers and users of snuff and chewing tobacco than for cigarette smokers, peak venous blood levels of nicotine are similar ( Benowitz et al. 1988 ). Pipe smokers, particularly those who have previously smoked cigarettes, may have blood and urine levels of nicotine and cotinine as high as cigarette smokers ( McCusker et al. 1982 ; Wald et al. 1981 ). Primary pipe smokers who have not previously smoked cigarettes tend to have lower nicotine levels. Likewise, cigar smokers who have previously smoked cigarettes may inhale more deeply and achieve higher blood levels of nicotine than primary cigar smokers, although on average, based on urinary cotinine levels, daily nicotine intake appears to be less for cigar smokers compared with cigarette or pipe smokers ( Wald et al. 1984 ).

The plasma half-life of nicotine after intravenous infusion or cigarette smoking averages about 2 h. However, when half-life is determined using the time course of urinary excretion of nicotine, which is more sensitive in detecting lower levels of nicotine in the body, the terminal half-life averages 11 h ( Jacob et al. 1999 ). The longer half-life detected at lower concentrations of nicotine is most likely a consequence of slow release of nicotine from body tissues. Based on a half-life of 2 h for nicotine, one would predict accumulation over 6–8 h (3–4 half-lives) of regular smoking and persistence of significant levels for 6–8 h after cessation of smoking. If a smoker smokes until bedtime, significant levels should persist all night. Studies of blood levels in regular cigarette smokers confirm these predictions ( Benowitz et al. 1982b ). Peak and trough levels follow each cigarette, but as the day progresses, trough levels rise and the influence of peak levels become less important. Thus, nicotine is not a drug to which smokers are exposed intermittently and which is eliminated rapidly from the body. On the contrary, smoking represents a multiple dosing situation with considerable accumulation while smoking and persistent levels for 24 h of each day.

Plasma levels of nicotine from nicotine replacement therapies tend to be in the range of low-level cigarette smokers. Thus, typical steady-state plasma nicotine concentrations with nicotine patches range from 10 to 20 ng ml −1 , and for nicotine gum, inhaler, sublingual tablet, and nasal spray from 5 to 15 ng ml −1 ( Benowitz et al. 1987 ; Schneider et al. 2001 ). Usually ad libitum use of NRTs results in one-third to two-thirds the concentration of nicotine that is achieved by cigarette smoking ( Schneider et al. 2001 ). However, users of 4-mg nicotine gum may sometimes reach or even exceed the nicotine levels associated with smoking ( McNabb 1984 ; McNabb et al. 1982 ). For the sake of comparison, systemic doses from various nicotine delivery systems are as follows: cigarette smoking, 1–1.5 mg per cigarette ( Benowitz and Jacob 1984 ; Jarvis et al. 2001 ); nicotine gum, 2 mg for a 4-mg gum ( Benowitz et al. 1988 ); transdermal nicotine, 5–21 mg per day, depending on the patch; nicotine nasal spray, 0.7 mg per 1-mg dose of one spray in each nostril ( Gourlay and Benowitz 1997 ; Johansson et al. 1991 ); nicotine inhaler, 2 mg for a 4-mg dose released from the 10-mg inhaler ( Molander et al. 1996 ); nicotine lozenge, 1 mg for a 2-mg lozenge ( Choi et al. 2003 ); oral snuff, 3.6 mg for 2.5 g held in the mouth for 30 min ( Benowitz et al. 1988 ); and chewing tobacco, 4.5 mg for 7.9 g chewed for 30 min ( Benowitz et al. 1988 ).

Cotinine is present in the blood of smokers in much higher concentrations than those of nicotine. Cotinine blood concentrations average about 250–300 ng ml −1 in groups of cigarette smokers. We have seen levels in tobacco users ranging up to 900 ng ml −1 . After stopping smoking, levels decline in a log linear fashion with an average half-life of about 16 h. The half-life of cotinine derived from nicotine is longer than the half-life of cotinine administered as cotinine ( Zevin et al. 1997 ). This is caused by slow release of nicotine from tissues. Because of the long half-life there is much less fluctuation in cotinine concentrations throughout the day than in nicotine concentrations. As expected, there is a gradual rise in cotinine levels throughout the day, peaking at the end of smoking and persisting at high concentrations overnight. Cotinine levels produced by NRTs are usually 30–70% of the levels detected while smoking ( Hurt et al. 1994 ; Schneider et al. 1995 ).

9 Biomarkers of Nicotine Exposure

Biomarkers are desirable for quantifying the systemic exposure of smokers to toxic constituents of smoke derived from tobacco use or from potential reduced harm products. Measures such as cigarettes per day are imprecise indicators of tobacco smoke exposure because of variability in how smokers smoke their cigarettes. There is considerable individual variability in smoke intake, even by people smoking the same brand of cigarettes ( USDHHS 2001 ). Cigarette design and how the cigarette is smoked influence toxic exposures. For example, light cigarettes are smoked on average more intensely than are regular cigarettes. The optimal assessment of exposure to tobacco smoke would be the analysis of concentrations of chemicals of pathogenetic concern in body fluids of the exposed individual – termed a biological marker or biomarker. A variety of biomarkers of tobacco smoke exposure have been proposed, as summarized in Table 2 and reviewed in detail previously ( Hatsukami et al. 2003 ).

Biomarkers of tobacco exposure

NNAL 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol; NNAL-gluc 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol glucuronide; NNK 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone; TSNA tobacco-specific nitrosamines; PAH polycylcic aromatic hydrocarbons

In studies of smoking cessation, anatabine is recommended as nicotine replacement therapies will lead to the presence of nicotine and cotinine without any tobacco exposure

This section focuses on the use of nicotine and cotinine and other tobacco alkaloids as biomarkers of tobacco exposure. Other potential biomarkers of exposure to the particulate or gas phase of tobacco smoke are described in the review papers cited above.

Nicotine measurement is highly specific for tobacco use or exposure (in the absence of nicotine medication use), but because of nicotine’s short half-life (2 h) the method is not recommended for general use. Cotinine is a highly specific and sensitive marker for tobacco use (in the absence nicotine medication use) and has the advantages of a fairly long half-life (16 h). When NRT is not being used, cotinine appears to be the best biomarker for tobacco use. When NRT is used, the minor tobacco alkaloids are useful biomarkers, as described below. A limitation of using cotinine is that it indicates ongoing exposure but not long-term exposure to tobacco smoke. Approaches to longer term monitoring include measurement of nicotine in hair or nails, as discussed below, or measurement of the tobacco-specific nitrosamine 4-(methylnitrosamine)-1-(3-pyridyl)-1-butanol (NNAL) in urine, as described by ( Hecht 2003 ).

9.1 Cotinine as a Biomarker for Intake of Nicotine

The presence of cotinine in biological fluids indicates exposure to nicotine. Because of the long half-life of cotinine it has been used as a biomarker for daily intake, both in cigarette smokers and in those exposed to secondhand tobacco smoke ( Benowitz 1996 ). There is a high correlation among cotinine concentrations measured in plasma, saliva, and urine, and measurements in any one of these fluids can be used as a marker of nicotine intake. There is, however, individual variability in the quantitative relationship between steady state cotinine levels and intake of nicotine. This is because different people convert different percentages of nicotine to cotinine (usual range 50–90%), and because different people metabolize cotinine differently at different rates (usual clearance range 20–75 ml min −1 ) ( Benowitz 1996 ).

The relationship between nicotine intake and steady state cotinine blood levels can be expressed in the following way, based on steady state exposure conditions: D nic = CL COT × C COT ÷ f, where D nic is the intake (dose) of nicotine, CL COT is the clearance of cotinine, C COT is the steady state blood concentration of cotinine and f is the fraction of nicotine converted to cotinine. On rearranging the equation, D nic = (CL COT ÷ f) × C COT = K × C COT where K is a constant that converts a given blood level of cotinine to nicotine intake. On average, K = 0.08 mg 24 h −1 ng −1 ml −1 (range 0.05–1.1, CV = 21.9%). Thus, a cotinine level of 30 ng ml −1 in blood corresponds on average to a nicotine intake of 24 mg per day.

While cotinine functions fairly well as a marker of nicotine intake, it is not perfect due to individual variation in metabolism as discussed previously. As described earlier in this chapter, cotinine metabolism is affected by factors such as race, gender, age, genetic variation in the liver enzyme CYP2A6, and/or by the presence of pregnancy, liver or kidney disease. Another limitation to the use of cotinine is that, given an average half-life of 16 h, cotinine levels reflect relatively short-term exposure to tobacco (that is, over the past 3–4 days).

9.2 Nicotine and Cotinine in Hair and Nails

The use of hair as a material in which to measure nicotine and cotinine has been proposed as a way to assess long-term exposure to nicotine from tobacco products. Nicotine and cotinine are incorporated into hair as it grows over time. The average rate of hair growth is 1 cm per month. Thus, measurements of levels of nicotine may provide a way of assessing exposure of a person to nicotine over several months ( Al-Delaimy et al. 2002 ; Florescu et al. 2007 ).

Potentials problems with the use of hair include a strong influence of hair pigmentation on nicotine and cotinine binding and uptake ( Dehn et al. 2001 ). Nicotine and cotinine are bound to melanin. As a result, dark hair binds much more nicotine than does blond or white hair. This makes comparison across individuals difficult. Also, hair is exposed to nicotine and cotinine from sweat and from sebaceous gland secretions, and to nicotine from environmental tobacco smoke exposure. Washing the hair before analysis may reduce this problem of environmental contamination, but it is not likely to remove all environmental nicotine and cotinine.

Nicotine and cotinine, as well as NNAL, can be measured in nail clippings ( Stepanov et al. 2007 ). Toenail clippings are easy to collect and store and represent cumulative exposure as nails grow at a rate of about 0.1 cm per month. In a group of smokers, the average toenail biomarker concentrations were 5.4 ng nicotine and 0.67 ng cotinine per mg toenail. Plasma levels of nicotine and cotinine were significantly but moderately correlated with toenail levels. Thus, hair or toenail measurements of nicotine or cotinine (or NNAL) are promising biomarkers of long-term tobacco exposure.

9.3 Dietary Sources

Dietary sources of nicotine have been alleged to be a potential confounder of cotinine levels used in measurement of secondhand smoke exposure. Several foods contain small amounts of nicotine ( Siegmund et al. 1999 ). However, the levels of nicotine in foods are quite low. Based on nicotine levels in foods and the usual daily consumption of various nicotine-containing foods, it has been determined that the levels of cotinine produced by even a diet high in nicotine-containing foods is lower than that seen in individuals exposed to moderate levels of secondhand smoke ( Benowitz 1996 ).

9.4 Minor Tobacco Alkaloids

The primary alkaloid in tobacco is nicotine, but tobacco also contains small amounts of minor alkaloids such as anabasine, anatabine, myosmine, and others. The minor alkaloids are absorbed systemically and can be measured in the urine of smokers and users of smokeless tobacco ( Jacob et al. 1999 ). The measurement of minor alkaloids is a way to quantitate tobacco use when a person is also taking in pure nicotine from a nicotine medication or a nontobacco nicotine delivery system. This method has been used to assess tobacco abstinence in clinical trials of smoking cessation with treatment by nicotine medications ( Jacob et al. 2002 ).

9.5 Optimal Cotinine Cut-Points to Distinguish Tobacco Use From No Tobacco Use

Based on the work of Jarvis and coworkers, who measured cotinine levels in individuals attending outpatient clinics in the United Kingdom in the early 1980s, an optimal plasma or saliva cotinine cut-point of 15 ng ml −1 or a urine cotinine of 50 ng ml −1 were determined to discriminate smokers from nonsmokers (some of whom are exposed to secondhand smoke) ( Benowitz et al. 2002a ). The optimal cut-point depends on the smoking behavior of the smokers and the magnitude of exposure to secondhand smoke. Data from the National Health and Nutrition Examination Surveys (NHANES) from 1999 to 2004 were recently analyzed to assess the optimal serum cotinine in the US population at present ( Benowitz et al. 2008a ). Using receiver operator characteristic curve analysis, the optimal cotinine cut-points were 3.08 ng ml −1 for adults (sensitivity 96.3%, specificity 97.4%) and 2.99 ng ml −1 for adolescents (sensitivity 86.5%, specificity 93.1%). The decline in the optimal cut-point since 1980 is likely due to the marked reduction in secondhand smoke exposure in the general US population. Of note is that the cut-points are much lower for Mexican Americans than for whites or African Americans, most likely due to both more occasional smoking and lower exposure to secondhand smoke.

Acknowledgments

We thank Marc Olmsted for his excellent editorial assistance. Much of the research described in this chapter was supported by US Public Health Service grants DA02277 and DA12393 from the National Institute on Drug Abuse, National Institutes of Health, and carried out at the General Clinical Research Center at San Francisco General Hospital Medical Center with support of the Division of Research Resources, National Institutes of Health (RR-00083).

• Al-Delaimy WK, Crane J, Woodward A. Is the hair nicotine level a more accurate biomarker of environmental tobacco smoke exposure than urine cotinine? J Epidemiol Community Health. 2002;56(1):66–71. doi: 10.1136/jech.56.1.66. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Armitage A, Dollery C, Houseman T, Kohner E, Lewis PJ, Turner D. Absorption of nicotine from small cigars. Clin Pharmacol Ther. 1978;23(2):143–151. doi: 10.1002/cpt1978232143. [ DOI ] [ PubMed ] [ Google Scholar ]
• Armstrong DW, Wang X, Ercal N. Enantiomeric composition of nicotine in smokeless tobacco, medicinal products, and commercial reagents. Chirality. 1998;10:587–591. [ Google Scholar ]
• Asimus S, Hai TN, Van Huong N, Ashton M. Artemisin and CYP2A6 activity in healthy subjects. Eur J Clin Pharmacol. 2008;64:283–292. doi: 10.1007/s00228-007-0406-1. [ DOI ] [ PubMed ] [ Google Scholar ]
• Bendayan R, Sullivan JT, Shaw C, Frecker RC, Sellers EM. Effect of cimetidine and ranitidine on the hepatic and renal elimination of nicotine in humans. Eur J Clin Pharmacol. 1990;38(2):165–169. doi: 10.1007/BF00265978. [ DOI ] [ PubMed ] [ Google Scholar ]
• Benowitz NL. Clinical pharmacology of inhaled drugs of abuse: implications in understanding nicotine dependence. NIDA Res Monogr. 1990;99:12–29. [ PubMed ] [ Google Scholar ]
• Benowitz NL. Cotinine as a biomarker of environmental tobacco smoke exposure. Epidemiol Rev. 1996;18(2):188–204. doi: 10.1093/oxfordjournals.epirev.a017925. [ DOI ] [ PubMed ] [ Google Scholar ]
• Benowitz NL, Jacob P., 3rd Daily intake of nicotine during cigarette smoking. Clin Pharmacol Ther. 1984;35(4):499–504. doi: 10.1038/clpt.1984.67. [ DOI ] [ PubMed ] [ Google Scholar ]
• Benowitz NL, Jacob P., 3rd Nicotine renal excretion rate influences nicotine intake during cigarette smoking. J Pharmacol Exp Ther. 1985;234(1):153–155. [ PubMed ] [ Google Scholar ]
• Benowitz NL, Jacob P., 3rd Nicotine and cotinine elimination pharmacokinetics in smokers and nonsmokers. Clin Pharmacol Ther. 1993;53(3):316–323. doi: 10.1038/clpt.1993.27. [ DOI ] [ PubMed ] [ Google Scholar ]
• Benowitz NL, Jacob P., 3rd Metabolism of nicotine to cotinine studied by a dual stable isotope method. Clin Pharmacol Ther. 1994;56(5):483–493. doi: 10.1038/clpt.1994.169. [ DOI ] [ PubMed ] [ Google Scholar ]
• Benowitz NL, Jacob P., 3rd Effects of cigarette smoking and carbon monoxide on nicotine and cotinine metabolism. Clin Pharmacol Ther. 2000;67(6):653–659. doi: 10.1067/mcp.2000.107086. [ DOI ] [ PubMed ] [ Google Scholar ]
• Benowitz NL, Jacob P., 3rd Trans-3′-hydroxycotinine: disposition kinetics, effects and plasma levels during cigarette smoking. Br J Clin Pharmacol. 2001;51(1):53–59. doi: 10.1046/j.1365-2125.2001.01309.x. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Benowitz NL, Jacob P, 3rd, Jones RT, Rosenberg J. Interindividual variability in the metabolism and cardiovascular effects of nicotine in man. J Pharmacol Exp Ther. 1982a;221(2):368–372. [ PubMed ] [ Google Scholar ]
• Benowitz NL, Kuyt F, Jacob P., 3rd Circadian blood nicotine concentrations during cigarette smoking. Clin Pharmacol Ther. 1982b;32(6):758–764. doi: 10.1038/clpt.1982.233. [ DOI ] [ PubMed ] [ Google Scholar ]
• Benowitz NL, Jacob P, 3rd, Savanapridi C. Determinants of nicotine intake while chewing nicotine polacrilex gum. Clin Pharmacol Ther. 1987;41(4):467–473. doi: 10.1038/clpt.1987.58. [ DOI ] [ PubMed ] [ Google Scholar ]
• Benowitz NL, Porchet H, Sheiner L, Jacob P., 3rd Nicotine absorption and cardiovascular effects with smokeless tobacco use: comparison with cigarettes and nicotine gum. Clin Pharmacol Ther. 1988;44(1):23–28. doi: 10.1038/clpt.1988.107. [ DOI ] [ PubMed ] [ Google Scholar ]
• Benowitz NL, Jacob P, 3rd, Fong I, Gupta S. Nicotine metabolic profile in man: comparison of cigarette smoking and transdermal nicotine. J Pharmacol Exp Ther. 1994;268(1):296–303. [ PubMed ] [ Google Scholar ]
• Benowitz NL, Perez-Stable EJ, Fong I, Modin G, Herrera B, Jacob P., 3rd Ethnic differences in N-glucuronidation of nicotine and cotinine. J Pharmacol Exp Ther. 1999;291(3):1196–1203. [ PubMed ] [ Google Scholar ]
• Benowitz NL, Jacob P, 3rd, Ahijevych K, Jarvis MJ, Hall S, LeHouezec J, Hansson A, Lichtenstein E, Henningfield J, Tsoh J, Hurt RD, Velicer W. Biochemical verification of tobacco use and cessation. Nicotine and Tobacco Research. 2002a;4:149–159. [ Google Scholar ]
• Benowitz NL, Perez-Stable EJ, Herrera B, Jacob P., 3rd Slower metabolism and reduced intake of nicotine from cigarette smoking in Chinese-Americans. J Natl Cancer Inst. 2002b;94(2):108–115. doi: 10.1093/jnci/94.2.108. [ DOI ] [ PubMed ] [ Google Scholar ]
• Benowitz NL, Herrera B, Jacob P., 3rd Mentholated cigarette smoking inhibits nicotine metabolism. J Pharmacol Exp Ther. 2004;310:1208–1215. doi: 10.1124/jpet.104.066902. [ DOI ] [ PubMed ] [ Google Scholar ]
• Benowitz NL, Lessov-Schlaggar CN, Swan GE, Jacob P., 3rd Female sex and oral contraceptive use accelerate nicotine metabolism. Clin Pharmacol Ther. 2006;79(5):480–488. doi: 10.1016/j.clpt.2006.01.008. [ DOI ] [ PubMed ] [ Google Scholar ]
• Benowitz N, Bernert JT, Caraballo RS, Holiday DB, Wang J. Optimal Serum Cotinine Levels to Distinguish Cigarette Smokers and Non-Smokers within Different Racial/Ethnic Groups in the United States Between 1999–2004. Am J Epidemiol. 2008a doi: 10.1093/aje/kwn301. (in press) [ DOI ] [ PubMed ] [ Google Scholar ]
• Benowitz N, Lessov-Schlaggar C, Swan G. Genetic Influences in the Variation in Renal Clearance of Nicotine and Cotinine. Clin Pharmacol Ther. 2008b;84(2):243–247. doi: 10.1038/clpt.2008.54. [ DOI ] [ PubMed ] [ Google Scholar ]
• Breese CR, Marks MJ, Logel J, Adams CE, Sullivan B, Collins AC, Leonard S. Effect of smoking history on [3H]nicotine binding in human postmortem brain. J Pharmacol Exp Ther. 1997;282(1):7–13. [ PubMed ] [ Google Scholar ]
• Byrd GD, Chang KM, Greene JM, deBethizy JD. Evidence for urinary excretion of glucuronide conjugates of nicotine, cotinine, and trans-3′-hydroxycotinine in smokers. Drug Metab Dispos. 1992;20(2):192–197. [ PubMed ] [ Google Scholar ]
• Byrd GD, Uhrig MS, deBethizy JD, Caldwell WS, Crooks PA, Ravard A, Riggs R. Direct determination of cotinine-N-glucuronide in urine using thermospray liquid chromatography/mass spectrometry. Biol Mass Spectrom. 1994;23(2):103–107. doi: 10.1002/bms.1200230210. [ DOI ] [ PubMed ] [ Google Scholar ]
• Caraballo RS, Giovino GA, Pechacek TF, Mowery PD, Richter PA, Strauss WJ, Sharp DJ, Eriksen MP, Pirkle JL, Maurer KR. Racial and ethnic differences in serum cotinine levels of cigarette smokers: Third National Health and Nutrition Examination Survey, 1988–1991. JAMA. 1998;280(2):135–139. doi: 10.1001/jama.280.2.135. [ DOI ] [ PubMed ] [ Google Scholar ]
• Cashman JR, Park SB, Yang ZC, Wrighton SA, Jacob P, Benowitz NL. Metabolism of nicotine by human liver microsomes: stereoselective formation of trans-nicotine N′-oxide. Chem Res Toxicol. 1992;5(5):639–646. doi: 10.1021/tx00029a008. [ DOI ] [ PubMed ] [ Google Scholar ]
• Choi JH, Dresler CM, Norton MR, Strahs KR. Pharmacokinetics of a nicotine polacrilex lozenge. Nicotine Tob Res. 2003;5(5):635–644. doi: 10.1080/1462220031000158690. [ DOI ] [ PubMed ] [ Google Scholar ]
• Collier AM, Goldstein GM, Shrewsbury RP, Davis SM, Koch GG, Zhang C-A, Benowitz NL, Lewtas J, Williams RW. Cotinine elimination and its use as a biomarker in young children involuntarily exposed to environmental tobacco smoke. Indoor Environ. 1994;3:353–359. [ Google Scholar ]
• Crawford EL, Weaver DA, DeMuth JP, Jackson CM, Khuder SA, Frampton MW, Utell MJ, Thilly WG, Willey JC. Measurement of cytochrome P450 2A6 and 2E1 gene expression in primary human bronchial epithelial cells. Carcinogenesis. 1998;19(10):1867–1871. doi: 10.1093/carcin/19.10.1867. [ DOI ] [ PubMed ] [ Google Scholar ]
• Dahlstrom A, Lundell B, Curvall M, Thapper L. Nicotine and cotinine concentrations in the nursing mother and her infant. Acta Paediatr Scand. 1990;79(2):142–147. doi: 10.1111/j.1651-2227.1990.tb11430.x. [ DOI ] [ PubMed ] [ Google Scholar ]
• de Leon J, Diaz FJ, Rogers T, Browne D, Dinsmore L, Ghosheh OH, Dwoskin LP, Crooks PA. Total cotinine in plasma: a stable biomarker for exposure to tobacco smoke. J Clin Psychopharmacol. 2002;22(5):496–501. doi: 10.1097/00004714-200210000-00009. [ DOI ] [ PubMed ] [ Google Scholar ]
• Dehn DL, Claffey DJ, Duncan MW, Ruth JA. Nicotine and cotinine adducts of a melanin intermediate demonstrated by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Chem Res Toxicol. 2001;14(3):275–279. doi: 10.1021/tx000205l. [ DOI ] [ PubMed ] [ Google Scholar ]
• Dempsey DA, Benowitz NL. Risks and benefits of nicotine to aid smoking cessation in pregnancy. Drug Saf. 2001;24(4):277–322. doi: 10.2165/00002018-200124040-00005. [ DOI ] [ PubMed ] [ Google Scholar ]
• Dempsey D, Jacob P, Benowitz NL. Nicotine metabolism and elimination kinetics in newborns. Clin Pharmacol Ther. 2000;67(5):458–465. doi: 10.1067/mcp.2000.106129. [ DOI ] [ PubMed ] [ Google Scholar ]
• Dempsey D, Jacob P, Benowitz NL. Accelerated metabolism of nicotine and cotinine in pregnant smokers. J Pharmacol Exp Ther. 2002;301(2):594–598. doi: 10.1124/jpet.301.2.594. [ DOI ] [ PubMed ] [ Google Scholar ]
• Dempsey D, Tutka P, Jacob P, Allen F, Schoedel K, Tyndale RF, Benowitz NL. Nicotine metabolite ratio as an index of cytochrome P450 2A6 metabolic activity. Clin Pharmacol Ther. 2004;76:64–72. doi: 10.1016/j.clpt.2004.02.011. [ DOI ] [ PubMed ] [ Google Scholar ]
• Denton TT, Zhang X, Cashman JR. Nicotine-related alkaloids and metabolites as inhibitors of human cytochrome P-450 2A6. Biochem Pharmacol. 2004;67(4):751–756. doi: 10.1016/j.bcp.2003.10.022. [ DOI ] [ PubMed ] [ Google Scholar ]
• English PB, Eskenazi B, Christianson RE. Black-white differences in serum cotinine levels among pregnant women and subsequent effects on infant birthweight. Am J Public Health. 1994;84(9):1439–1443. doi: 10.2105/ajph.84.9.1439. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Fant RV, Henningfield JE, Shiffman S, Strahs KR, Reitberg DP. A pharmacokinetic crossover study to compare the absorption characteristics of three transdermal nicotine patches. Pharmacol Biochem Behav. 2000;67(3):479–482. doi: 10.1016/s0091-3057(00)00399-3. [ DOI ] [ PubMed ] [ Google Scholar ]
• Florescu A, Ferrence R, Einarson TR, Selby P, Kramer M, Woodruff S, Grossman L, Rankin A, Jacqz-Aigrain E, Koren G. Reference values for hair cotinine as a biomarker of active and passive smoking in women of reproductive age, pregnant women, children, and neonates: systematic review and meta-analysis. Ther Drug Monit. 2007;29(4):437–446. doi: 10.1097/FTD.0b013e318074df6e. [ DOI ] [ PubMed ] [ Google Scholar ]
• Giovino G, Sidney S, Gfroerer J, O’Malley P, Allen J, Richter P, Ph DK. Epidemiology of menthol cigarette use. Nicotine Tob Res. 2004;6(Suppl 1):S67–81. doi: 10.1080/14622203710001649696. [ DOI ] [ PubMed ] [ Google Scholar ]
• Gori GB, Benowitz NL, Lynch CJ. Mouth versus deep airways absorption of nicotine in cigarette smokers. Pharmacol Biochem Behav. 1986;25(6):1181–1184. doi: 10.1016/0091-3057(86)90108-5. [ DOI ] [ PubMed ] [ Google Scholar ]
• Gourlay SG, Benowitz NL. The benefits of stopping smoking and the role of nicotine replacement therapy in older patients. Drugs Aging. 1996;9(1):8–23. doi: 10.2165/00002512-199609010-00002. [ DOI ] [ PubMed ] [ Google Scholar ]
• Gourlay SG, Benowitz NL. Arteriovenous differences in plasma concentration of nicotine and catecholamines and related cardiovascular effects after smoking, nicotine nasal spray, and intravenous nicotine. Clin Pharmacol Ther. 1997;62(4):453–463. doi: 10.1016/S0009-9236(97)90124-7. [ DOI ] [ PubMed ] [ Google Scholar ]
• Gow PJ, Ghabrial H, Smallwood RA, Morgan DJ, Ching MS. Neonatal hepatic drug elimination. Pharmacol Toxicol. 2001;88(1):3–15. doi: 10.1034/j.1600-0773.2001.088001003.x. [ DOI ] [ PubMed ] [ Google Scholar ]
• Gries JM, Benowitz N, Verotta D. Chronopharmacokinetics of nicotine. Clin Pharmacol Ther. 1996;60(4):385–395. doi: 10.1016/S0009-9236(96)90195-2. [ DOI ] [ PubMed ] [ Google Scholar ]
• Guthrie SK, Zubieta JK, Ohl L, Ni L, Koeppe RA, Minoshima S, Domino EF. Arterial/venous plasma nicotine concentrations following nicotine nasal spray. Eur J Clin Pharmacol. 1999;55(9):639–643. doi: 10.1007/s002280050686. [ DOI ] [ PubMed ] [ Google Scholar ]
• Hatsukami DK, Hecht SS, Hennrikus DJ, Joseph AM, Pentel PR. Biomarkers of tobacco exposure or harm: application to clinical and epidemiological studies. 25–26 October 2001, Minneapolis, Minnesota. Nicotine Tob Res. 2003;5(3):387–396. doi: 10.1080/1462220031000094222. [ DOI ] [ PubMed ] [ Google Scholar ]
• Hecht SS. Tobacco carcinogens, their biomarkers and tobacco-induced cancer. Nat Rev Cancer. 2003;3(10):733–744. doi: 10.1038/nrc1190. [ DOI ] [ PubMed ] [ Google Scholar ]
• Hecht SS, Carmella SG, Chen M, Dor Koch JF, Miller AT, Murphy SE, Jensen JA, Zimmerman CL, Hatsukami DK. Quantitation of urinary metabolites of a tobacco-specific lung carcinogen after smoking cessation. Cancer Res. 1999a;59(3):590–596. [ PubMed ] [ Google Scholar ]
• Hecht SS, Carmella SG, Murphy SE. Effects of watercress consumption on urinary metabolites of nicotine in smokers. Cancer Epidemiol Biomarkers Prev. 1999b;8(10):907–913. [ PubMed ] [ Google Scholar ]
• Hecht SS, Hochalter JB, Villalta PW, Murphy SE. 2′-Hydroxylation of nicotine by cytochrome P450 2A6 and human liver microsomes: formation of a lung carcinogen precursor. Proc Natl Acad Sci U S A. 2000;97(23):12493–12497. doi: 10.1073/pnas.220207697. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Henningfield JE, Keenan RM. Nicotine delivery kinetics and abuse liability. J Consult Clin Psychol. 1993;61(5):743–750. doi: 10.1037//0022-006x.61.5.743. [ DOI ] [ PubMed ] [ Google Scholar ]
• Henningfield JE, Stapleton JM, Benowitz NL, Grayson RF, London ED. Higher levels of nicotine in arterial than in venous blood after cigarette smoking. Drug Alcohol Depend. 1993;33(1):23–29. doi: 10.1016/0376-8716(93)90030-t. [ DOI ] [ PubMed ] [ Google Scholar ]
• Higashi E, Fukami T, Itoh M, Kyo S, Inoue M, Yokoi T, Nakajima M. Human CYP2A6 is induced by estrogen via estrogen receptor. Drug Metab Dispos. 2007;35:1935–1941. doi: 10.1124/dmd.107.016568. [ DOI ] [ PubMed ] [ Google Scholar ]
• Hukkanen J, Vaisanen T, Lassila A, Piipari R, Anttila S, Pelkonen O, Raunio H, Hakkola J. Regulation of CYP3A5 by glucocorticoids and cigarette smoke in human lung-derived cells. J Pharmacol Exp Ther. 2003;304(2):745–752. doi: 10.1124/jpet.102.038208. [ DOI ] [ PubMed ] [ Google Scholar ]
• Hukkanen J, Dempsey D, Jacob P, Benowitz NL. Effect of pregnancy on a measure of FMO3 activity. Br J Clin Pharmacol. 2005a;60(2):224–226. doi: 10.1111/j.1365-2125.2005.02406.x. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Hukkanen J, Gourlay SG, Kenkare S, Benowitz NL. Influence of menstrual cycle on cytochrome P450 2A6 activity and cardiovascular effects of nicotine. Clin Pharmacol Ther. 2005b;77(3):159–169. doi: 10.1016/j.clpt.2004.10.012. [ DOI ] [ PubMed ] [ Google Scholar ]
• Hukkanen J, Jacob P, 3rd, Benowitz NL. Metabolism and disposition kinetics of nicotine. Pharmacol Rev. 2005c;57(1):79–115. doi: 10.1124/pr.57.1.3. [ DOI ] [ PubMed ] [ Google Scholar ]
• Hukkanen J, Jacob P, 3rd, Benowitz NL. Effect of grapefruit juice on cytochrome P450 2A6 and nicotine renal clearance. Clin Pharmacol Ther. 2006;80(5):522–530. doi: 10.1016/j.clpt.2006.08.006. [ DOI ] [ PubMed ] [ Google Scholar ]
• Hurt RD, Dale LC, Fredrickson PA, Caldwell CC, Lee GA, Offord KP, Lauger GG, Marusic Z, Neese LW, Lundberg TG. Nicotine patch therapy for smoking cessation combined with physician advice and nurse follow-up. One-year outcome and percentage of nicotine replacement. JAMA. 1994;271(8):595–600. [ PubMed ] [ Google Scholar ]
• Jacob P, 3rd, Benowitz NL. Oxidative metabolism of nicotine in vivo. In: Adlkofer F, Thurau K, editors. Effects of nicotine on biological systems. Birkhauser Verlag; Basel: 1991. pp. 35–44. [ Google Scholar ]
• Jacob P, Shulgin AT, Benowitz NL. Synthesis of (3′R, 5′S)-trans-3′-hydroxycotinine, a major metabolite of nicotine. Metabolic formation of 3′-hydroxycotinine in humans is highly stereoselective. J Med Chem. 1990;33(7):1888–1891. doi: 10.1021/jm00169a009. [ DOI ] [ PubMed ] [ Google Scholar ]
• Jacob P, Yu L, Shulgin AT, Benowitz NL. Minor tobacco alkaloids as biomarkers for tobacco use: comparison of users of cigarettes, smokeless tobacco, cigars, and pipes. Am J Public Health. 1999;89(5):731–736. doi: 10.2105/ajph.89.5.731. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Jacob P, Hatsukami D, Severson H, Hall S, Yu L, Benowitz NL. Anabasine and anatabine as biomarkers for tobacco use during nicotine replacement therapy. Cancer Epidemiol Biomarkers Prev. 2002;11(12):1668–1673. [ PubMed ] [ Google Scholar ]
• Jarvis MJ, Boreham R, Primatesta P, Feyerabend C, Bryant A. Nicotine yield from machine-smoked cigarettes and nicotine intakes in smokers: evidence from a representative population survey. J Natl Cancer Inst. 2001;93(2):134–138. doi: 10.1093/jnci/93.2.134. [ DOI ] [ PubMed ] [ Google Scholar ]
• Johansson CJ, Olsson P, Bende M, Carlsson T, Gunnarsson PO. Absolute bioavailability of nicotine applied to different nasal regions. Eur J Clin Pharmacol. 1991;41(6):585–588. doi: 10.1007/BF00314989. [ DOI ] [ PubMed ] [ Google Scholar ]
• Johnstone E, Benowitz N, Cargill A, Jacob R, Hinks L, Day I, Murphy M, Walton R. Determinants of the rate of nicotine metabolism and effects on smoking behavior. Clin Pharmacol Ther. 2006;80(4):319–330. doi: 10.1016/j.clpt.2006.06.011. [ DOI ] [ PubMed ] [ Google Scholar ]
• Kandel DB, Hu MC, Schaffran C, Udry JR, Benowitz NL. Urine nicotine metabolites and smoking behavior in a multiracial/multiethnic national sample of young adults. Am J Epidemiol. 2007;165(8):901–910. doi: 10.1093/aje/kwm010. [ DOI ] [ PubMed ] [ Google Scholar ]
• Kozlowski LT, Mehta NY, Sweeney CT, Schwartz SS, Vogler GP, Jarvis MJ, West RJ. Filter ventilation and nicotine content of tobacco in cigarettes from Canada, the United Kingdom, and the United States. Tob Control. 1998;7(4):369–375. doi: 10.1136/tc.7.4.369. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Krul C, Hageman G. Analysis of urinary caffeine metabolites to assess biotransformation enzyme activities by reversed-phase high-performance liquid chromatography. J Chromatogr B Biomed Sci Appl. 1998;709(1):27–34. doi: 10.1016/s0378-4347(98)00016-4. [ DOI ] [ PubMed ] [ Google Scholar ]
• Kyerematen GA, Morgan M, Warner G, Martin LF, Vesell ES. Metabolism of nicotine by hepatocytes. Biochem Pharmacol. 1990;40(8):1747–1756. doi: 10.1016/0006-2952(90)90351-k. [ DOI ] [ PubMed ] [ Google Scholar ]
• Le Gal A, Dreano Y, Lucas D, Berthou F. Diversity of selective environmental substrates for human cytochrome P450 2A6: alkoxyethers, nicotine, coumarin, N-nitrosodiethylamine, and N-nitrosobenzylmethylamine. Toxicol Lett. 2003;144(1):77–91. doi: 10.1016/s0378-4274(03)00229-7. [ DOI ] [ PubMed ] [ Google Scholar ]
• Lee BL, Benowitz NL, Jacob P., 3rd Influence of tobacco abstinence on the disposition kinetics and effects of nicotine. Clin Pharmacol Ther. 1987;41(4):474–479. doi: 10.1038/clpt.1987.59. [ DOI ] [ PubMed ] [ Google Scholar ]
• Lee BL, Jacob P, 3rd, Jarvik ME, Benowitz NL. Food and nicotine metabolism. Pharmacol Biochem Behav. 1989;33(3):621–625. doi: 10.1016/0091-3057(89)90398-5. [ DOI ] [ PubMed ] [ Google Scholar ]
• Leete E. Biosynthesis and metabolism of the tobacco alkaloids. In: Pelletier SW, editor. Alkaloids: chemical and biological perspectives. Wiley; New York: 1983. pp. 85–152. [ Google Scholar ]
• Leong JW, Dore ND, Shelley K, Holt EJ, Laing IA, Palmer LJ, LeSouef PN. The elimination half-life of urinary cotinine in children of tobacco-smoking mothers. Pulm Pharmacol Ther. 1998;11(4):287–290. doi: 10.1006/pupt.1998.0153. [ DOI ] [ PubMed ] [ Google Scholar ]
• Lerman C, Tyndale R, Patterson F, Wileyto EP, Shields PG, Pinto A, Benowitz N. Nicotine metabolite ratio predicts efficacy of transdermal nicotine for smoking cessation. Clin Pharmacol Ther. 2006;79(6):600–608. doi: 10.1016/j.clpt.2006.02.006. [ DOI ] [ PubMed ] [ Google Scholar ]
• Lindell G, Lunell E, Graffner H. Transdermally administered nicotine accumulates in gastric juice. Eur J Clin Pharmacol. 1996;51(3–4):315–318. doi: 10.1007/s002280050204. [ DOI ] [ PubMed ] [ Google Scholar ]
• Liston HL, Markowitz JS, DeVane CL. Drug glucuronidation in clinical psychopharmacology. J Clin Psychopharmacol. 2001;21(5):500–515. doi: 10.1097/00004714-200110000-00008. [ DOI ] [ PubMed ] [ Google Scholar ]
• Lunell E, Molander L, Ekberg K, Wahren J. Site of nicotine absorption from a vapour inhaler–comparison with cigarette smoking. Eur J Clin Pharmacol. 2000;55(10):737–741. doi: 10.1007/s002280050007. [ DOI ] [ PubMed ] [ Google Scholar ]
• MacDougall JM, Fandrick K, Zhang X, Serafin SV, Cashman JR. Inhibition of human liver microsomal (S)-nicotine oxidation by (−)-menthol and analogues. Chem Res Toxicol. 2003;16(8):988–993. doi: 10.1021/tx0340551. [ DOI ] [ PubMed ] [ Google Scholar ]
• Madan A, Graham RA, Carroll KM, Mudra DR, Burton LA, Krueger LA, Downey AD, Czerwinski M, Forster J, Ribadeneira MD, Gan LS, LeCluyse EL, Zech K, Robertson P, Jr, Koch P, Antonian L, Wagner G, Yu L, Parkinson A. Effects of prototypical microsomal enzyme inducers on cytochrome P450 expression in cultured human hepatocytes. Drug Metab Dispos. 2003;31(4):421–431. doi: 10.1124/dmd.31.4.421. [ DOI ] [ PubMed ] [ Google Scholar ]
• McBride JS, Altman DG, Klein M, White W. Green tobacco sickness. Tob Control. 1998;7(3):294–298. doi: 10.1136/tc.7.3.294. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• McCusker K, McNabb E, Bone R. Plasma nicotine levels in pipe smokers. JAMA. 1982;248(5):577–578. [ PubMed ] [ Google Scholar ]
• McKennis H, Jr, Turnbull LB, Bowman ER, Tamaki E. The synthesis of hydroxycotinine and studies on its structure. J Org Chem. 1963;28:383–387. [ Google Scholar ]
• McNabb ME. Chewing nicotine gum for 3 months: what happens to plasma nicotine levels? Can Med Assoc J. 1984;131(6):589–592. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• McNabb ME, Ebert RV, McCusker K. Plasma nicotine levels produced by chewing nicotine gum. JAMA. 1982;248(7):865–868. [ PubMed ] [ Google Scholar ]
• Messina ES, Tyndale RF, Sellers EM. A major role for CYP2A6 in nicotine C-oxidation by human liver microsomes. J Pharmacol Exp Ther. 1997;282(3):1608–1614. [ PubMed ] [ Google Scholar ]
• Meunier V, Bourrie M, Julian B, Marti E, Guillou F, Berger Y, Fabre G. Expression and induction of CYP1A1/1A2, CYP2A6 and CYP3A4 in primary cultures of human hepatocytes: a 10-year follow-up. Xenobiotica. 2000;30(6):589–607. doi: 10.1080/004982500406426. [ DOI ] [ PubMed ] [ Google Scholar ]
• Molander L, Lunell E, Andersson SB, Kuylenstierna F. Dose released and absolute bioavailability of nicotine from a nicotine vapor inhaler. Clin Pharmacol Ther. 1996;59(4):394–400. doi: 10.1016/S0009-9236(96)90107-1. [ DOI ] [ PubMed ] [ Google Scholar ]
• Molander L, Hansson A, Lunell E, Alainentalo L, Hoffmann M, Larsson R. Pharmacokinetics of nicotine in kidney failure. Clin Pharmacol Ther. 2000;68(3):250–260. doi: 10.1067/mcp.2000.109006. [ DOI ] [ PubMed ] [ Google Scholar ]
• Molander L, Hansson A, Lunell E. Pharmacokinetics of nicotine in healthy elderly people. Clin Pharmacol Ther. 2001;69(1):57–65. doi: 10.1067/mcp.2001.113181. [ DOI ] [ PubMed ] [ Google Scholar ]
• Munzel PA, Schmohl S, Heel H, Kalberer K, Bock-Hennig BS, Bock KW. Induction of human UDP glucuronosyltransferases (UGT1A6, UGT1A9, and UGT2B7) by t-butylhydroquinone and 2,3,7,8-tetrachlorodibenzo-p-dioxin in Caco-2 cells. Drug Metab Dispos. 1999;27(5):569–573. [ PubMed ] [ Google Scholar ]
• Nakajima M, Yamamoto T, Nunoya K, Yokoi T, Nagashima K, Inoue K, Funae Y, Shimada N, Kamataki T, Kuroiwa Y. Role of human cytochrome P4502A6 in C-oxidation of nicotine. Drug Metab Dispos. 1996;24(11):1212–1217. [ PubMed ] [ Google Scholar ]
• Neurath GB. Aspects of the oxidative metabolism of nicotine. Clin Investig. 1994;72(3):190–195. doi: 10.1007/BF00189309. [ DOI ] [ PubMed ] [ Google Scholar ]
• Neurath GB, Dunger M, Orth D, Pein FG. Trans-3′-hydroxycotinine as a main metabolite in urine of smokers. Int Arch Occup Environ Health. 1987;59(2):199–201. doi: 10.1007/BF00378497. [ DOI ] [ PubMed ] [ Google Scholar ]
• Neurath GB, Orth D, Pein FG. Detection of nornicotine in human urine after infusion of nicotine. In: Adlkofer F, Thurau K, editors. Effects of nicotine on biological systems. Birkhauser Verlag; Basel: 1991. pp. 45–49. [ Google Scholar ]
• Nolin TD, Frye RF, Matzke GR. Hepatic drug metabolism and transport in patients with kidney disease. Am J Kidney Dis. 2003;42(5):906–925. doi: 10.1016/j.ajkd.2003.07.019. [ DOI ] [ PubMed ] [ Google Scholar ]
• Obach RS. Potent inhibition of human liver aldehyde oxidase by raloxifene. Drug Metab Dispos. 2004;32(1):89–97. doi: 10.1124/dmd.32.1.89. [ DOI ] [ PubMed ] [ Google Scholar ]
• Pankow JF. A consideration of the role of gas/particle partitioning in the deposition of nicotine and other tobacco smoke compounds in the respiratory tract. Chem Res Toxicol. 2001;14(11):1465–1481. doi: 10.1021/tx0100901. [ DOI ] [ PubMed ] [ Google Scholar ]
• Park SB, Jacob P, Benowitz NL, Cashman JR. Stereoselective metabolism of (S)-(−)-nicotine in humans: formation of trans-(S)-(−)-nicotine N-1′-oxide. Chem Res Toxicol. 1993;6(6):880–888. doi: 10.1021/tx00036a019. [ DOI ] [ PubMed ] [ Google Scholar ]
• Patterson F, Benowitz N, Shields P, Kaufmann V, Jepson C, Wileyto P, Kucharski S, Lerman C. Individual differences in nicotine intake per cigarette. Cancer Epidemiol Biomarkers Prev. 2003;12(5):468–471. [ PubMed ] [ Google Scholar ]
• Patterson F, Schnoll R, Wileyto E, Pinto A, Epstein L, Shields P, Hawk L, Tyndale R, Benowitz N, Lerman C. Toward Personalized Therapy for Smoking Cessation: A Randomized Placebo-controlled Trial of Bupropion. Clin Pharmacol Ther. 2008;84(3):320–325. doi: 10.1038/clpt.2008.57. [ DOI ] [ PubMed ] [ Google Scholar ]
• Perez-Stable EJ, Herrera B, Jacob P, 3rd, Benowitz NL. Nicotine metabolism and intake in black and white smokers. JAMA. 1998;280(2):152–156. doi: 10.1001/jama.280.2.152. [ DOI ] [ PubMed ] [ Google Scholar ]
• Perry RJ, Griffiths W, Dextraze P, Solomon RJ, Trebbin WM. Elevated nicotine levels in patients undergoing hemodialysis. A role in cardiovascular mortality and morbidity? Am J Med. 1984;76(2):241–246. doi: 10.1016/0002-9343(84)90780-0. [ DOI ] [ PubMed ] [ Google Scholar ]
• Perry DC, Davila-Garcia MI, Stockmeier CA, Kellar KJ. Increased nicotinic receptors in brains from smokers: membrane binding and autoradiography studies. J Pharmacol Exp Ther. 1999;289(3):1545–1552. [ PubMed ] [ Google Scholar ]
• Rae JM, Johnson MD, Lippman ME, Flockhart DA. Rifampin is a selective, pleiotropic inducer of drug metabolism genes in human hepatocytes: studies with cDNA and oligonucleotide expression arrays. J Pharmacol Exp Ther. 2001;299(3):849–857. [ PubMed ] [ Google Scholar ]
• Rebagliato M, Bolumar F, Florey Cdu V, Jarvis MJ, Perez-Hoyos S, Hernandez-Aguado I, Avino MJ. Variations in cotinine levels in smokers during and after pregnancy. Am J Obstet Gynecol. 1998;178(3):568–571. doi: 10.1016/s0002-9378(98)70440-5. [ DOI ] [ PubMed ] [ Google Scholar ]
• Ren Q, Murphy SE, Zheng Z, Lazarus P. O-Glucuronidation of the lung carcinogen 4-(methylnitrosamino)-1- (3-pyridyl)-1-butanol (NNAL) by human UDP-glucuronosyltransferases 2B7 and 1A9. Drug Metab Dispos. 2000;28(11):1352–1360. [ PubMed ] [ Google Scholar ]
• Rose JE, Behm FM, Westman EC, Coleman RE. Arterial nicotine kinetics during cigarette smoking and intravenous nicotine administration: implications for addiction. Drug Alcohol Depend. 1999;56(2):99–107. doi: 10.1016/s0376-8716(99)00025-3. [ DOI ] [ PubMed ] [ Google Scholar ]
• Runkel M, Bourian M, Tegtmeier M, Legrum W. The character of inhibition of the metabolism of 1,2-benzopyrone (coumarin) by grapefruit juice in human. Eur J Clin Pharmacol. 1997;53(3–4):265–269. doi: 10.1007/s002280050374. [ DOI ] [ PubMed ] [ Google Scholar ]
• Schneider NG, Olmstead R, Mody FV, Doan K, Franzon M, Jarvik ME, Steinberg C. Efficacy of a nicotine nasal spray in smoking cessation: a placebo-controlled, double-blind trial. Addiction. 1995;90(12):1671–1682. doi: 10.1046/j.1360-0443.1995.901216719.x. [ DOI ] [ PubMed ] [ Google Scholar ]
• Schneider NG, Olmstead RE, Franzon MA, Lunell E. The nicotine inhaler: clinical pharmacokinetics and comparison with other nicotine treatments. Clin Pharmacokinet. 2001;40(9):661–684. doi: 10.2165/00003088-200140090-00003. [ DOI ] [ PubMed ] [ Google Scholar ]
• Schoedel KA, Sellers EM, Palmour R, Tyndale RF. Down-regulation of hepatic nicotine metabolism and a CYP2A6-like enzyme in African green monkeys after long-term nicotine administration. Mol Pharmacol. 2003;63(1):96–104. doi: 10.1124/mol.63.1.96. [ DOI ] [ PubMed ] [ Google Scholar ]
• Selby P, Hackman R, Kapur B, Klein J, Koren G. Heavily smoking women who cannot quit in pregnancy: evidence of pharmacokinetic predisposition. Ther Drug Monit. 2001;23(3):189–191. doi: 10.1097/00007691-200106000-00001. [ DOI ] [ PubMed ] [ Google Scholar ]
• Sellers EM, Kaplan HL, Tyndale RF. Inhibition of cytochrome P450 2A6 increases nicotine’s oral bioavailability and decreases smoking. Clin Pharmacol Ther. 2000;68(1):35–43. doi: 10.1067/mcp.2000.107651. [ DOI ] [ PubMed ] [ Google Scholar ]
• Sellers EM, Ramamoorthy Y, Zeman MV, Djordjevic MV, Tyndale RF. The effect of methoxsalen on nicotine and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) metabolism in vivo. Nicotine Tob Res. 2003;5(6):891–899. doi: 10.1080/14622200310001615231. [ DOI ] [ PubMed ] [ Google Scholar ]
• Shigenaga MK, Trevor AJ, Castagnoli N., Jr Metabolism-dependent covalent binding of (S)-[5–3H]nicotine to liver and lung microsomal macromolecules. Drug Metab Dispos. 1988;16(3):397–402. [ PubMed ] [ Google Scholar ]
• Siegmund B, Leitner E, Pfannhauser W. Determination of the nicotine content of various edible nightshades (Solanaceae) and their products and estimation of the associated dietary nicotine intake. J Agric Food Chem. 1999;47(8):3113–3120. doi: 10.1021/jf990089w. [ DOI ] [ PubMed ] [ Google Scholar ]
• Stepanov I, Hecht SS, Lindgren B, Jacob P, 3rd, Wilson M, Benowitz NL. Relationship of human toenail nicotine, cotinine, and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol to levels of these biomarkers in plasma and urine. Cancer Epidemiol Biomarkers Prev. 2007;16(7):1382–1386. doi: 10.1158/1055-9965.EPI-07-0145. [ DOI ] [ PubMed ] [ Google Scholar ]
• Swan GE, Benowitz NL, Lessov CN, Jacob P, Tyndale RF, Wilhelmsen K. Nicotine metabolism: the impact of CYP2A6 on estimates of additive genetic influence. Pharmacogenet Genomics. 2005;15(2):115–125. doi: 10.1097/01213011-200502000-00007. [ DOI ] [ PubMed ] [ Google Scholar ]
• Taavitsainen P, Juvonen R, Pelkonen O. In vitro inhibition of cytochrome P450 enzymes in human liver microsomes by a potent CYP2A6 inhibitor, trans-2-phenylcyclopropylamine (tranylcypromine), and its nonamine analog, cyclopropylbenzene. Drug Metab Dispos. 2001;29(3):217–222. [ PubMed ] [ Google Scholar ]
• Takami K, Saito H, Okuda M, Takano M, Inui KI. Distinct characteristics of transcellular transport between nicotine and tetraethylammonium in LLC-PK1 cells. J Pharmacol Exp Ther. 1998;286(2):676–680. [ PubMed ] [ Google Scholar ]
• Tateishi T, Nakura H, Asoh M, Watanabe M, Tanaka M, Kumai T, Takashima S, Imaoka S, Funae Y, Yabusaki Y, Kamataki T, Kobayashi S. A comparison of hepatic cytochrome P450 protein expression between infancy and postinfancy. Life Sci. 1997;61(26):2567–2574. doi: 10.1016/s0024-3205(97)01011-4. [ DOI ] [ PubMed ] [ Google Scholar ]
• Tyndale RF, Sellers EM. Variable CYP2A6-mediated nicotine metabolism alters smoking behavior and risk. Drug Metab Dispos. 2001;29(4 Pt 2):548–552. [ PubMed ] [ Google Scholar ]
• Tyroller S, Zwickenpflug W, Richter E. New sources of dietary myosmine uptake from cereals, fruits, vegetables, and milk. J Agric Food Chem. 2002;50(17):4909–4915. doi: 10.1021/jf020281p. [ DOI ] [ PubMed ] [ Google Scholar ]
• Urakami Y, Okuda M, Maasuda S, Saito H, Inui KI. Functional characteristics and membrane locatlization of rat multispecific organic cation transporters, OCT1 and OCT2, mediating tubular secretion of cationic drugs. J Pharmacol Ther. 1998;287:800–805. [ PubMed ] [ Google Scholar ]
• USDHHS. Risks associated with smoking cigarettes with low machine-measured yields of tar and nicotine. Smoking and Tobacco Control Monographs, U.S. Department of Health and Human Services, Public Health Service, National Institutes of Health, National Cancer Institute; 2001. [ Google Scholar ]
• Voncken P, Rustemeier K, Schepers G. Identification of cis-3′-hydroxycotinine as a urinary nicotine metabolite. Xenobiotica. 1990;20(12):1353–1356. doi: 10.3109/00498259009046633. [ DOI ] [ PubMed ] [ Google Scholar ]
• Wagenknecht LE, Cutter GR, Haley NJ, Sidney S, Manolio TA, Hughes GH, Jacobs DR. Racial differences in serum cotinine levels among smokers in the coronary artery risk development in (young) adults study. Am J Public Health. 1990;80(9):1053–1056. doi: 10.2105/ajph.80.9.1053. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Wald NJ, Idle M, Boreham J, Bailey A. Serum cotinine levels in pipe smokers: evidence against nicotine as cause of coronary heart disease. Lancet. 1981;2(8250):775–777. doi: 10.1016/s0140-6736(81)90187-2. [ DOI ] [ PubMed ] [ Google Scholar ]
• Wald NJ, Idle M, Boreham J, Bailey A, Van Vunakis H. Urinary nicotine concentrations in cigarette and pipe smokers. Thorax. 1984;39(5):365–368. doi: 10.1136/thx.39.5.365. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• West R, Hajek P, Foulds J, Nilsson F, May S, Meadows A. A comparison of the abuse liability and dependence potential of nicotine patch, gum, spray and inhaler. Psychopharmacology (Berl) 2000;149(3):198–202. doi: 10.1007/s002130000382. [ DOI ] [ PubMed ] [ Google Scholar ]
• Xia XY, Peng RX, Yu JP, Wang H, Wang J. In vitro metabolic characteristics of cytochrome P-450 2A6 in Chinese liver microsomes. Acta Pharmacol Sin. 2002;23(5):471–476. [ PubMed ] [ Google Scholar ]
• Zevin S, Benowitz NL. Drug interactions with tobacco smoking. An update. Clin Pharmacokinet. 1999;36(6):425–438. doi: 10.2165/00003088-199936060-00004. [ DOI ] [ PubMed ] [ Google Scholar ]
• Zevin S, Jacob P, 3rd, Benowitz N. Cotinine effects on nicotine metabolism. Clin Pharmacol Ther. 1997;61(6):649–654. doi: 10.1016/S0009-9236(97)90099-0. [ DOI ] [ PubMed ] [ Google Scholar ]
• Zevin S, Schaner ME, Giacomini KM. Nicotine transport in a human choriocarcinoma cell line (JAR) J Pharm Sci. 1998;87:702–706. doi: 10.1021/js970455v. [ DOI ] [ PubMed ] [ Google Scholar ]
• Zevin S, Jacob P, 3rd, Benowitz NL. Nicotine-mecamylamine interactions. Clin Pharmacol Ther. 2000;68(1):58–66. doi: 10.1067/mcp.2000.108066. [ DOI ] [ PubMed ] [ Google Scholar ]
• Zhang W, Kilicarslan T, Tyndale RF, Sellers EM. Evaluation of methoxsalen, tranyl-cypromine, and tryptamine as specific and selective CYP2A6 inhibitors in vitro. Drug Metab Dispos. 2001;29(6):897–902. [ PubMed ] [ Google Scholar ]
• View on publisher site
• PDF (1.1 MB)
• Collections

Similar articles

Cited by other articles, links to ncbi databases.

• Download .nbib .nbib
• Format: AMA APA MLA NLM

Add to Collections

• Introduction
• Conclusions
• Article Information

Among adolescents who were currently using any tobacco product, the proportion who initiated use with e-cigarettes increased over time, becoming the dominant first product in 2017. Percentages do not add up to 100% because some users initiated with more than 1 tobacco product at the same age. SLT indicates smokeless tobacco.

Mean age at first use decreased over time for e-cigarettes but remained stable for other tobacco products. Regression analyses are shown in eTable 2 in the Supplement . CCLC indicates cigar, cigarillo, and little cigar; SLT, smokeless tobacco.

Between 2014 and 2021, days of e-cigarette use per month shifted from light use to heavier use. Statistical results are shown in eTable 3 in the Supplement .

Includes e-cigarette users who used no other tobacco products. After remaining stable from 2014 to 2017 ( P = .74 by interrupted time series analysis), the proportion of users who consumed their first e-cigarette within 5 minutes of waking rapidly increased more than 10-fold ( P  = .002 for slope change following 2017 by interrupted time series analysis). Error bars indicate SEs.

A, The estimated number of adolescents with high levels of nicotine dependence and who were sole users of e-cigarettes diverged from the numbers for other products in 2018, exceeding the sum of use of cigarettes and all other products combined. B, Considering dual-product users with the other products confirms that e-cigarette users began to exceed use of all other tobacco products among adolescents with high levels of nicotine dependence. The 2021 numbers may underestimate tobacco use compared with earlier years, as discussed in the Limitations subsection of the Discussion section. SLT indicates smokeless tobacco.

eFigure 1. Number of Adolescents Using Different Tobacco Products

eFigure 2. Current e-Cigarette and Cigarette Use, Separating Out Dual Use (Reporting Current Use of Both e-Cigarettes and Cigarettes in the Same Survey)

eFigure 3. Days per Month Adolescents Used Cigarette, Cigars, and Smokeless Tobacco

eTable 1. NYTS Variables Used in the Analysis

eTable 2. Age of Tobacco Product Initiation Among Ever Users

eTable 3. Metaregressions for Changes in Tobacco Product Use Intensity Over Time, 2014-2021

eTable 4. Use Within 5 Minutes of Waking Among Sole Product Users

eMethods. YRBSS Supplemental Analysis

eAppendix. YRBSS Supplemental Analysis

eTable 5. Current Tobacco Product Use in YRBSS and NYTS (High School Students)

eFigure 4. e-Cigarette and Cigarette Use in YRBSS

eFigure 5. Percentage of e-Cigarette and Cigarette Users Who Used Product ≥20 d/mo

See More About

Sign up for emails based on your interests, select your interests.

Customize your JAMA Network experience by selecting one or more topics from the list below.

• Academic Medicine
• Acid Base, Electrolytes, Fluids
• Allergy and Clinical Immunology
• American Indian or Alaska Natives
• Anesthesiology
• Anticoagulation
• Art and Images in Psychiatry
• Artificial Intelligence
• Assisted Reproduction
• Bleeding and Transfusion
• Caring for the Critically Ill Patient
• Challenges in Clinical Electrocardiography
• Climate and Health
• Climate Change
• Clinical Challenge
• Clinical Decision Support
• Clinical Implications of Basic Neuroscience
• Clinical Pharmacy and Pharmacology
• Complementary and Alternative Medicine
• Consensus Statements
• Coronavirus (COVID-19)
• Critical Care Medicine
• Cultural Competency
• Dental Medicine
• Dermatology
• Diabetes and Endocrinology
• Diagnostic Test Interpretation
• Digital Health
• Drug Development
• Electronic Health Records
• Emergency Medicine
• End of Life, Hospice, Palliative Care
• Environmental Health
• Equity, Diversity, and Inclusion
• Facial Plastic Surgery
• Gastroenterology and Hepatology
• Genetics and Genomics
• Genomics and Precision Health
• Global Health
• Guide to Statistics and Methods
• Hair Disorders
• Health Care Delivery Models
• Health Care Economics, Insurance, Payment
• Health Care Quality
• Health Care Reform
• Health Care Safety
• Health Care Workforce
• Health Disparities
• Health Inequities
• Health Policy
• Health Systems Science
• History of Medicine
• Hypertension
• Images in Neurology
• Implementation Science
• Infectious Diseases
• Innovations in Health Care Delivery
• JAMA Infographic
• Law and Medicine
• Leading Change
• Less is More
• LGBTQIA Medicine
• Lifestyle Behaviors
• Medical Coding
• Medical Devices and Equipment
• Medical Education
• Medical Education and Training
• Medical Journals and Publishing
• Mobile Health and Telemedicine
• Narrative Medicine
• Neuroscience and Psychiatry
• Notable Notes
• Nutrition, Obesity, Exercise
• Obstetrics and Gynecology
• Occupational Health
• Ophthalmology
• Orthopedics
• Otolaryngology
• Pain Medicine
• Palliative Care
• Pathology and Laboratory Medicine
• Patient Care
• Patient Information
• Performance Improvement
• Performance Measures
• Perioperative Care and Consultation
• Pharmacoeconomics
• Pharmacoepidemiology
• Pharmacogenetics
• Pharmacy and Clinical Pharmacology
• Physical Medicine and Rehabilitation
• Physical Therapy
• Physician Leadership
• Population Health
• Primary Care
• Professional Well-being
• Professionalism
• Psychiatry and Behavioral Health
• Public Health
• Pulmonary Medicine
• Regulatory Agencies
• Reproductive Health
• Research, Methods, Statistics
• Resuscitation
• Rheumatology
• Risk Management
• Scientific Discovery and the Future of Medicine
• Sexual Health
• Shared Decision Making and Communication
• Sleep Medicine
• Sports Medicine
• Stem Cell Transplantation
• Substance Use and Addiction Medicine
• Surgical Innovation
• Surgical Pearls
• Teachable Moment
• Technology and Finance
• The Art of JAMA
• The Arts and Medicine
• The Rational Clinical Examination
• Tobacco and e-Cigarettes
• Translational Medicine
• Trauma and Injury
• Treatment Adherence
• Ultrasonography
• Users' Guide to the Medical Literature
• Vaccination
• Venous Thromboembolism
• Veterans Health
• Women's Health
• Workflow and Process
• Wound Care, Infection, Healing

Get the latest research based on your areas of interest.

Others also liked.

• Download PDF
• X Facebook More LinkedIn

Glantz S , Jeffers A , Winickoff JP. Nicotine Addiction and Intensity of e-Cigarette Use by Adolescents in the US, 2014 to 2021. JAMA Netw Open. 2022;5(11):e2240671. doi:10.1001/jamanetworkopen.2022.40671

Manage citations:

© 2024

• Permissions

Nicotine Addiction and Intensity of e-Cigarette Use by Adolescents in the US, 2014 to 2021

• 1 Retired, San Francisco, California
• 2 Division of General Academic Pediatrics, Massachusetts General Hospital for Children, Boston
• 3 Tobacco Research and Treatment Center, Massachusetts General Hospital, Boston
• 4 Julius B. Richmond Center, American Academy of Pediatrics, Itasca, Illinois

Question   How are e-cigarettes associated with nicotine addiction among US adolescents?

Findings   In this survey study of 151 573 respondents, age at initiation of e-cigarette use decreased and intensity of use and addiction increased between 2014 and 2021. By 2019, more e-cigarette users were using their first tobacco product within 5 minutes of waking than users of cigarettes and all other tobacco products combined.

Meaning   These findings suggest that clinicians need to be ready to address youth addiction to these new highly addictive nicotine products during many clinical encounters, and stronger regulation is needed, including comprehensive bans on the sale of flavored tobacco products.

Importance   As e-cigarettes have become more effective at delivering the addictive drug nicotine, they have become the dominant form of tobacco use by US adolescents.

Objective   To measure intensity of use of e-cigarettes, cigarettes, and other tobacco products among US adolescents and their dependence level over time.

Design, Setting, and Participants   This survey study analyzed the cross-sectional National Youth Tobacco Surveys from 2014 to 2021. Confirmatory analysis was conducted using Youth Behavioral Risk Factor Surveillance System from 2015 to 2019. The surveys were administered to national probability samples of US students in grades 6 to 12.

Exposures   Use of e-cigarettes and other tobacco products before and after the introduction of e-cigarettes delivering high levels of nicotine.

Main Outcomes and Measures   First tobacco product used, age at initiation of use, intensity of use (days per month), and nicotine addiction (measured as time after waking to first use of any tobacco product).

Results   A total of 151 573 respondents were included in the analysis (51.1% male and 48.9% female; mean [SEM] age, 14.57 [0.03] years). Prevalence of e-cigarette use peaked in 2019 and then declined. Between 2014 and 2021, the age at initiation of e-cigarette use decreased, and intensity of use and addiction increased. By 2017, e-cigarettes became the most common first product used (77.0%). Age at initiation of use did not change for cigarettes or other tobacco products, and changes in intensity of use were minimal. By 2019, more e-cigarette users were using their first tobacco product within 5 minutes of waking than for cigarettes and all other products combined. Median e-cigarette use also increased from 3 to 5 d/mo in 2014 to 2018 to 6 to 9 d/mo in 2019 to 2020 and 10 to 19 d/mo in 2021.

Conclusions and Relevance   The changes detected in this survey study may reflect the higher levels of nicotine delivery and addiction liability of modern e-cigarettes that use protonated nicotine to make nicotine easier to inhale. The increasing intensity of use of modern e-cigarettes highlights the clinical need to address youth addiction to these new high-nicotine products over the course of many clinical encounters. In addition, stronger regulation, including comprehensive bans on the sale of flavored tobacco products, should be implemented.

Electronic cigarettes (e-cigarettes) are highly engineered drug delivery devices that create and sustain addiction. Early e-cigarettes did not deliver nicotine as efficiently as cigarettes because they delivered freebase nicotine that was hard to inhale. This situation changed with the 2015 introduction of Juul products (Juul Labs Inc), 1 which added benzoic acid to the nicotine e-liquid to lower the pH level and form protonated nicotine. Protonated nicotine increases addictive potential by making it easier to inhale quantities of nicotine that are difficult for naive users to achieve with cigarettes or earlier e-cigarettes. 2 By 2018, Juul held 75% of the market. 3 After the US Food and Drug Administration partially banned cartridge-based flavored products in 2020, 4 disposable flavored protonated nicotine e-cigarettes rapidly gained adolescent market share 3 , 5 ; in 2021 middle and high school students used Puff Bar (Puff Bar [26.8%]), Vuse (R. J. Reynolds Vapor Company [10.5%]), SMOK (Shenzhen IVPS Technology Co Ltd [8.6%]), and Juul (6.8%). 6

In the brain, nicotine attaches to acetylcholine receptors and releases dopamine, which causes feelings of pleasure, 7 - 9 upregulates acetylcholine receptors, 10 and alters brain circuitry involved in learning, stress, and self-control, resulting in addiction and dependence. 11 - 13 Adolescents and young adults are particularly susceptible to nicotine receptor upregulation and addiction because of enhanced brain plasticity. 14 - 16

Prior studies reported changing prevalence of e-cigarette use among middle and high school students. 6 , 17 - 24 By 2019, the Centers for Disease Control and Prevention (CDC) National Youth Tobacco Survey (NYTS) estimated that 5.3 million middle and high school students were using e-cigarettes. 22 This number dropped to 3.6 million in 2020 23 and again to 2.1 million in 2021 during the COVID-19 pandemic. 6

One prior study 25 assessed changes in nicotine dependence after the introduction of Juul. Population Assessment of Tobacco and Health data for individuals aged 12 to 34 years from 2014 to 2016 and 2017 to 2019 revealed increased daily use and nicotine dependence among adolescents aged 14 to 17 years from 2017 to 2019, after the introduction of Juul, with no change in the 2014 to 2016 cohort. Another study 26 using NYTS data from 2015 to 2018 showed that high-frequency use of e-cigarettes and cigarettes was associated with higher odds of nicotine dependence (using tobacco products within 5 minutes of waking). Neither study tracked intensity of e-cigarette use, age at initiation, or dependence over time. This study moves beyond population prevalence as a measure of the changing e-cigarette use patterns among US adolescents over time to capture changes in measures of dependence and intensity of e-cigarette use among adolescents on an annual basis, during an 8-year period from 2014 through 2021.

In this survey study, we analyzed data from the NYTS, a nationally representative survey of middle and high school students. 27 We used 2014 through 2021, all years in which the NYTS provided information on number of days per month that respondents used e-cigarettes, cigarettes, cigars (including cigarillos and little cigars), and smokeless tobacco (ie, chewing tobacco, snuff, or dip). This was a secondary analysis of 2 deidentified public use data sets released by the CDC and was therefore deemed exempt from human participant research per the Massachusetts General Brigham Human Research Committee. This study followed the American Association for Public Opinion Research ( AAPOR ) reporting guideline.

Because of COVID-19, the 2021 NYTS transitioned from an in-person, tablet-based administration to a fully online administration where students could participate in classrooms, at home, or in another remote learning environment. Because of these differences in data collection, the CDC recommended that 2021 NYTS not be compared with earlier years. 6 Indeed, the NYTS 2021 data demonstrate higher prevalence of e-cigarette use in those who took the survey at school (15.0%) vs at home (8.1%). 6 To clarify behavioral reporting in different learning environments, the CDC performed the Adolescent Behaviors and Experiences Survey between January and June 2021, reporting current e-cigarette use rates of 25.2% among in-person, 17.2% among hybrid, and 9.1% among home-based high school students. 28 These results are consistent with data from the 1990s and early 2000s showing that in-home surveys report lower prevalence of smoking than in-school surveys. 29 - 31 Nevertheless, with these cautions and caveats in mind, and because this study focused on changes in consumption patterns within self-reported ever and current users of tobacco products, we have included the 2021 data for these users in our analysis. We reasoned that students who reported that they use tobacco products are less likely to be concerned about reporting details of their use patterns.

eTable 1 in the Supplement lists all the specific questions and variable definitions used in the analysis. Ever use of a tobacco product was coded as “yes” if the respondent reported ever using the product, even 1 or 2 times. Current use was coded as “yes” if the respondent reported using the product 1 or more of the past 30 days. There was no required threshold of lifetime use (such as 100 cigarettes in their lifetime) for current use. Dual use was coded “yes” if respondents reported current use of 2 or more tobacco products in the same survey year. We used the CDC’s categorization of days used for each product in the past 30 days established in 2014: 0, 1 to 2, 3 to 5, 6 to 9, 10 to 19, 20 to 29, and 30. The days used for each product among current users are tabulated separately, so each one includes users of that product as well as dual users and polyusers of other products.

We determined first tobacco product used with the question, “How old were you when you first smoked a cigarette, even 1 or 2 puffs?” and equivalent questions for other products. Respondents who gave the same age for multiple products were treated as having started using those products in the same year.

We assessed respondents’ level of tobacco dependence using the standard question 32 : “How soon after you wake up do you want to use a tobacco product of any kind?” The responses were coded as 0 for “I do not want to use tobacco products”; 1 for “I rarely want to use tobacco products”; 2 for “after more than 1 hour but less than 24 hours”; 3 for “from more than 30 minutes to 1 hour”; 4 for “from 6 to 30 minutes”; and 5 for “within 5 minutes.” The time to first cigarette is a commonly used measure of nicotine dependence in tobacco control research because it is a strong and consistent factor associated with smoking cessation success. 33

We repeated our primary analyses with the CDC Youth Behavioral Risk Surveillance System 34 (YRBSS) data, a nationally representative in-school survey of high school students. We used 2015, 2017, and 2019, all years in which the YRBSS provided information on the number of days per month that respondents used e-cigarettes, cigarettes, cigars, and smokeless tobacco. Details of the YRBSS analysis are provided in the eMethods in the Supplement .

We used CDC-provided weights and stratification variables to adjust for clustering and nonresponse and to match sample characteristics to national estimates. Results were tabulated for each year accounting for the complex survey design and weights for each year using Stata, version 15.0 (StataCorp LLC), commands syv, subpop():proportion, svy, subpop():regress, and svy, subpop():logistic. To test for trends over time while accounting for the uncertainties in each year’s estimates, metaregressions 35 were computed for trends in proportion of adolescents in each intensity of use group (days per month) across years based on point estimates and SEs for each year using the Stata command metareg .

A total of 151 573 respondents were included in the analysis (mean [SEM] age, 14.57 [0.03] years). Because all respondents were in middle or high school, 99% of respondents were between 11 and 18 years of age, with 86% between 12 and 17 years of age. A total of 51.1% of the sample were male and 48.9% were female (weighted numbers).

Among adolescents who currently use any tobacco product, the proportion whose first tobacco product used was e-cigarettes increased from 27.2% in 2014 to 78.3% in 2019 and remained at 77.0% in 2021 ( Figure 1 ). By 2017, e-cigarettes were the most popular initial tobacco product. For each year from 2019 to 2021, more current tobacco users were initiating use with e-cigarettes than all other products combined ( Figure 1 and eFigure 1 in the Supplement ).

Age at first use for e-cigarettes decreased by −0.159 (95% CI, −0.176 to 0.143) years (1.9 months) per calendar year ( P  < .001), controlling for respondent age at the time they completed the survey ( Figure 2 and eTable 2 in the Supplement ). In contrast, change in age at first use for cigarettes (0.017 [95% CI, −0.011 to 0.045] years; P = .24), cigars (0.015 [95% CI, −0.011 to 0.041] years; P = .25), and smokeless tobacco (−0.036 [95% CI, −0.074 to 0.0002] years; P = .64) was not significant.

Intensity of e-cigarette use shifted from using 9 or fewer days a month to 10 or more days a month ( Figure 3 and eTable 3 in the Supplement ). This shift in e-cigarette use intensity is also reflected in median number of days used, which increased from 3 to 5 d/mo in 2014 to 2018 to 6 to 9 d/mo in 2019 to 2020 and 10 to 19 d/mo in 2021. Intensity of use of cigarettes, cigars, and smokeless tobacco generally did not shift over time (eFigure 3 and eTable 3 in the Supplement ).

Addiction to e-cigarette nicotine, measured as the odds of having use of first tobacco product within 5 minutes of waking, increased over time for sole e-cigarette users (eTable 4 in the Supplement ). These changes over time were not uniform. From 2014 to 2017, the percentage of sole e-cigarette users who used e-cigarettes within 5 minutes of waking was less than 1% ( Figure 4 and eTable 4 in the Supplement ). However, beginning in 2017 through 2021, a shift occurred, with 10.3% using their first e-cigarette within 5 minutes of waking by 2021. During this same time, addiction did not change for sole cigarette smokers (odds ratio [OR] per year, 0.99 [95% CI, 0.85-1.16]; P  = .92) or smokeless tobacco users (OR per year, 0.97 [95% CI, 0.81-1.16]; P  = .73), but did increase among sole cigar users (OR per year, 1.49 [95% CI, 1.16-1.90]; P  = .002) (eTable 4 in the Supplement ). For comparison, between 2014 and 2021, a mean (SE) of 6.1% (0.8%) of smokers with sole use of cigarettes first used cigarettes within 5 minutes of waking and 5.2% (1.0%) of smokeless tobacco users used the product within 5 minutes of waking. The highest mean (SE) percentage for sole cigar users was 6.3% (2.4%) in 2020.

To isolate the population effect of addictiveness of different product types, we considered those adolescents who used only 1 product type and measured use of the product within 5 minutes of waking ( Figure 5 ). Beginning in 2019, the number of addicted e-cigarette users (n = 177 000) exceeded the numbers of all other tobacco product users (n = 23 000) on this high-addiction measure.

Results from the YRBSS were similar to those of the NYTS (eAppendix, eTable 5, and eFigures 4 and 5 in the Supplement ), showing a shift in e-cigarette use to more days per month with minimal changes in patterns of cigarette use. The frequent use of e-cigarettes (≥20 days in the past month) increased between 2017 and 2019 to the point where it was 700% higher than frequent use of cigarettes by 2019.

In 2017, e-cigarettes became the most common first tobacco product used, with the proportion of adolescents who initiated tobacco product use with e-cigarettes increasing over time ( Figure 1 ) and the age at initiation of e-cigarette use decreasing ( Figure 2 ). In addition, measures of addiction increased: days per month ( Figure 3 ) and the fraction of users who used their first product within 5 minutes of waking ( Figure 4 ) increased, and e-cigarette addiction surpassed that for all other forms of tobacco products combined ( Figure 5 ). Age at initiation of use did not change for cigarettes and other products, and changes in intensity of use for them were minimal.

As has been reported elsewhere, 6 , 17 - 24 the historic decline in use of tobacco products by US adolescents reversed after the advent of e-cigarettes, with e-cigarette use peaking in 2019 at a higher level than cigarette smoking in 2006 (eFigure 2 in the Supplement ). The shift to e-cigarettes being the first tobacco product used is consistent with Monitoring the Future data from 8th and 10th grade students in 2015 to 2017. 36 , 37 Likewise, the decrease in age at initiation of e-cigarette use but not use of other tobacco products is consistent with earlier NYTS results 38 : the 8.8% of ever users of e-cigarettes aged 16 to 17 years who initiated use at 14 years or younger in 2014 increased to 28.6% in 2018, whereas initiation age did not change for cigarettes, cigars, and smokeless tobacco products. Our results are consistent with the prior Population Assessment of Tobacco and Health study that showed increased intensity of use and nicotine dependence among adolescents through 2019 after the introduction of Juul and the diffusion of protonated nicotine technology in e-cigarettes 25 ; our results also show that the shift toward increased e-cigarette use and higher levels of addiction continued through 2021. In addition, the 2022 NYTS reported that 2.6 million adolescents used e-cigarettes and 27.6% of them used e-cigarettes daily; the comparable numbers reported herein for 2021 are 2.1 million and 24.7%. 39 Our findings are also consistent with the finding that using e-cigarettes on more days per month is associated with higher levels of nicotine dependence. 26

The decrease in e-cigarette use from 2019 levels may be attributable to a variety of factors, including local, state, and national strategies to address e-cigarette use among adolescents and enacting comprehensive restrictions on the sale of flavored tobacco products, 40 - 42 as well as raising the federal minimum age for tobacco product sale to 21 years. 43 Heightened health concerns because of e-cigarette– or vaping–associated lung injury 44 may also have contributed to this decrease. The effects of COVID-19 on the 2021 results are likely more reflected in the prevalence estimates than in the measures of behavior among self-identified tobacco product users. The fact that adolescents were predominately at home and outside social environments may have affected tobacco use. A national online survey in May 2020, during the COVID-19 pandemic, found that 36.5% of adolescents and young adults (aged 13 to 20 years) who used e-cigarettes reported quitting and another 2.2% switched to other nicotine products. 45

The extent to which decreases in tobacco product use for the 2021 NYTS data may reflect a long-term trend, owing perhaps to education about e-cigarettes, increased concern about the health risks of e-cigarettes, 44 restrictions on available products such as the US Food and Drug Administration’s 2020 partial ban on flavored products, 4 short-term lack of access to products and stimuli for use among peers, biases in the data collection, or some combination of these factors is unknown. Some of this decrease may be an artifact due to NYTS being administered at home as well as in school. Although adolescent prevalence of e-cigarette use appeared to decrease in the NYTS, data from the CDC’s Adolescent Behaviors and Experiences Survey from January to June 2021 suggested that the in-person high school student respondents in 2021 had rates of current e-cigarette use of 25.2% (95% CI, 13.9%-41.2%), 28 similar to the 2019 NYTS levels of 27.5% (95% CI, 23.5%-29.7%) 22 measured among in-person high school student respondents. It will be important to determine to what degree prevalence of e-cigarette use among adolescents rebounds as the return to school and contact with their peers and society generally proceeds.

Regardless of falling prevalence, e-cigarette users were initiating use at younger ages, use became more intensive (in days per month), and a higher percentage used them within 5 minutes of waking. These changes may reflect the increased addictive potential of protonated nicotine delivery products that make it easier to inhale nicotine than from cigarettes or other combustible tobacco products. 1 , 2 The fact that e-cigarette addiction trends are continuing to increase despite the 2019 federal legislation raising the tobacco sales age to 21 years suggests that tighter regulation, additional legislative action, or both may be necessary to protect adolescents.

Despite the COVID-19 pandemic leading to people being socially isolated, students being out of school, and the increased risk of adolescents and young adults contracting COVID-19 with e-cigarette use, 46 intensity of use among adolescents continued to increase. This increase in intensity may reflect increasing use of nicotine for self-medication in response to increases in adolescent depression, anxiety, tic disorders, and suicidality that occurred during the COVID-19 pandemic. 28 The pandemic has also been a lost year for school-based prevention and treatment efforts, meaning that abatement plans will need to be intensified to address the nicotine addiction in those adolescents who missed a year of contact with adults who might have otherwise helped them get treatment. 47

The change in e-cigarette use and intensity of use among adolescents contrasts with what was happening in the adult e-cigarette market at the same time. 48 - 50 The prevalence of current adult e-cigarette use in the Tobacco Use Supplement to the Current Population Survey showed an upward trend from 2010 until 2014, 51 followed by a decline to the 2019 rate of 2.3%, 52 less than one-tenth of the 27.5% prevalence among high school respondents in the NYTS that year. 22 High-dose concealable nicotine e-cigarettes entered the market as a product targeting adolescents, as shown by the fact that by 2018, only 2% of adults used a flash drive–shaped e-cigarette regularly. 53 Despite several years of intensive adolescent e-cigarette users becoming 18 years of age and therefore part of a different category, the 2020 National Health Interview Survey found only 3.7% prevalence of adult e-cigarette use, 54 compared with 19.6% among high school students. 23 These findings suggest that the primary effect of the modern e-cigarette has been to addict adolescents to nicotine. Clinicians should be vigilant for new tobacco products that may come into the youth tobacco product market.

The primary limitation of this study is that it was based on the NYTS, which is a cross-sectional survey. The NYTS collects self-reported data from respondents without biochemical verification of tobacco use behavior, which could lead to recall bias.

In addition to the changes in how the NYTS was administered in 2021, the NYTS was conducted via paper-and-pencil questionnaires until 2019, when it shifted to electronic data collection. In 1 study, 30 paper-administered questionnaires tended to result in nonsignificantly lower prevalence reporting. Beginning in 2019, the electronic survey contained skip patterns and tobacco product images, which may limit comparability with data collected via paper-and-pencil surveys, in which respondents were asked to answer all questions (regardless of tobacco product use) and did not have any images to aid with product recall. In addition, owing to COVID-19, 2020 NYTS data collection ended early, in March, yielding a smaller sample size and lower response rate than usual. The CDC performed additional nonresponse bias analysis assessing differences in responding and nonresponding schools for 2020 and concluded that they were able to create survey weights that compensated for these problems. 23

Use of e-cigarettes reversed the long-term decline in US youth tobacco use and expanded the tobacco epidemic by attracting many adolescents at low risk of initiating nicotine use with cigarettes. 55 - 57 This survey study found that between 2014 and 2021, although prevalence of e-cigarette use among adolescents peaked in 2019 and then declined, the age of initiation among ever users continued to decrease and the intensity of use and level of addiction among adolescents who are current e-cigarette users increased. This increasing intensity of use may reflect the higher nicotine delivery and addiction liability of e-cigarettes that use protonated nicotine. 1 , 2 Clinicians should question all their patients about nicotine and tobacco product use, including e-cigarettes and other new nicotine products. Because tobacco addiction is a chronic disease, clinicians should be ready to address youth addiction to these new high-nicotine products during the course of many clinical encounters. The increasing intensity of use of modern e-cigarettes highlights the need for local, state, and federal comprehensive bans on the sale of flavored tobacco products and consideration of ending the sale of these products on the open retail market, as has been done in 47 countries as of 2021. 58

Accepted for Publication: September 11, 2022.

Published: November 7, 2022. doi:10.1001/jamanetworkopen.2022.40671

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2022 Glantz S et al. JAMA Network Open .

Corresponding Author: Jonathan P. Winickoff, MD, MPH, Division of General Academic Pediatrics, Massachusetts General Hospital for Children, 55 Fruit St, Yawkey Room 6D, Boston, MA 02114 ( [email protected] ).

Author Contributions: Drs Glantz and Jeffers had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Glantz, Winickoff.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Glantz, Winickoff.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: All authors.

Obtained funding: Winickoff.

Administrative, technical, or material support: Winickoff.

Supervision: Winickoff.

Conflict of Interest Disclosures: Dr Glantz reported receiving personal fees from the World Health Organization outside the submitted work. Dr Winickoff reported receiving grant funding from the National Institutes of Health (NIH) during the conduct of the study and serving as a paid expert witness against the tobacco industry outside the submitted work. No other disclosures were reported.

Funding/Support: This study was supported in part by grants R01CA248742 and R01CA245145 from the National Cancer Institute (Dr Winickoff).

Role of the Funder/Sponsor: The sponsor had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

• Register for email alerts with links to free full-text articles
• Access PDFs of free articles
• Manage your interests
• Save searches and receive search alerts

An official website of the United States government

Official websites use .gov A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS A lock ( Lock Locked padlock icon ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

• Publications
• Account settings
• Advanced Search
• Journal List

Addicted to smoking or addicted to nicotine?: A focus group study on perceptions of nicotine and addiction among US adult current smokers, former smokers, non-smokers, and dual users of cigarettes and e-cigarettes

Emily e loud , mph, hue trong duong , phd, katherine c henderson , mph, reed m reynolds , phd, david l ashley , phd, james f thrasher , phd, lucy popova , phd.

• Author information
• Article notes
• Copyright and License information

Corresponding author: Lucy Popova, School of Public Health, Georgia State University, P.O. Box 3995, Atlanta, GA, 30302, USA. [email protected]

Author Contributions

EL: Formal Analysis, Writing – original draft

HD: Formal Analysis, Writing – original draft

KH: Formal Analysis, Writing – review & editing

RR: Formal Analysis, Writing – review & editing

DA: Conceptualization, Writing – review & editing

JT: Conceptualization, Funding acquisition, Writing – review & editing

LP: Conceptualization, Funding acquisition, Supervision, Writing – review & editing

Issue date 2022 Feb.

Background and Aims:

In 2017, the U.S. Food and Drug Administration (FDA) proposed to reduce nicotine in cigarettes to minimally or non-addictive levels. This study qualitatively explored perceptions of nicotine and addiction, both independently and in response to messages communicating about nicotine reduction.

Qualitative study using focus groups. Participants described their perceptions of nicotine and addiction and their responses to messages about the nicotine reduction.

Atlanta, GA and San Francisco, CA, USA. Semi-structured focus groups were conducted virtually in Spring 2020.

Participants:

Exclusive smokers (n=27), dual users (of cigarettes and electronic cigarettes) (n=25), former smokers (n=32), and young adult non-smokers (n=31).

Measurement:

Inductive thematic analysis of transcripts was conducted, and results were compared across smoking status groups.

Participants across all smoking status groups associated nicotine with tobacco products, but consistently misperceived that nicotine caused disease. Perceptions of addiction were largely negative and varied by smoking status. Experienced smokers (exclusive smokers, former smokers, and dual users) differentiated tobacco use from other addictions and minimized their own experiences of addiction. Perceptions of addiction across experienced smokers included not only the chemical properties of nicotine, but also the behavioral aspects of tobacco use, including oral fixation, having a smoking routine, and response to internal and external cues. In response to messages, many believed that removing the nicotine would not make cigarettes less addictive because of the multi-factorial nature of smoking addiction that includes nonpharmacological cues.

Conclusions:

Perceptions of nicotine and addiction among nonsmokers, former smokers, exclusive smokers and dual users of cigarettes and e-cigarettes vary based on smoking status, but there is a common tendency to believe that nicotine is addictive, that addiction results from more than just nicotine, and that very low nicotine cigarettes will not necessarily reduce the addictiveness of cigarettes.

Keywords: Nicotine, addiction, perceptions, smokers, dual users, former smokers, non-smokers, qualitative

Introduction

Most of the death and disease caused by tobacco ( 1 ) is due to combustible tobacco products, particularly cigarettes, because combustion produces most of the toxic and carcinogenic chemicals that cause the cardiovascular and respiratory conditions ( 2 ). Tobacco products also contain nicotine, the addictive chemical that keeps people smoking ( 3 ). Around the world, different “endgame” approaches are discussed to end the tobacco epidemic, such as phasing out the sales of tobacco products, banning combustibles, and licensing smokers ( 4 ). One of the most discussed tobacco “endgame” strategies is reducing nicotine in combusted tobacco products to make them non-addictive ( 5 ). In 2017, the U.S. Food and Drug Administration (FDA) proposed a policy to reduce the amount of nicotine in cigarettes, and possibly other combusted tobacco products, to minimally or non-addictive levels ( 6 ). Although this policy has potential to save millions of lives, there are challenges, including the public’s misperceptions of nicotine ( 7 ) that, if addressed, would increase the efficacy of this policy. Effectively communicating very low nicotine cigarettes (VLNC) policies to the public requires understanding how the public perceives nicotine and addiction.

Approximately 80% of adults in the U.S. mistakenly believe that nicotine causes the diseases associated with smoking ( 8 ). If VLNCs were mandated by FDA, smokers may believe these products are less harmful than regular cigarettes and continue to smoke instead of quitting. Many adult smokers and non-smokers believe that lower nicotine content does not reduce addictiveness, that less nicotine content does not make it easier to quit smoking, and that nicotine causes cancer ( 9 – 11 ). These misperceptions may cause misunderstanding of the intended purpose of the policy, potentially impeding its desired effects (e.g., deterring quitting).

Existing research on perceptions of nicotine addiction is limited. Most quantitative studies have focused on perceptions of whether smoking is addictive rather than investigating if and how smokers view nicotine in cigarettes as an agent that causes addiction to smoking ( 12 ). Similarly, qualitative studies have focused on addiction to smoking ( 13 – 15 ) or other tobacco products ( 16 , 17 ) rather than nicotine’s role in addiction. To our knowledge, qualitative studies of beliefs about nicotine have only involved adolescents ( 18 , 19 , 20 ), and qualitative studies of nicotine beliefs among adults are lacking.

More research is needed to inform effective communication strategies that support implementation of the VLNC policy. Key population segments might have different responses to this policy. For example, nicotine reduction may drive exclusive smokers to believe that they need to smoke more intensively to satisfy their desire for nicotine, dual users to switch to alternative nicotine products they already use, and former smokers or nonsmokers to re-initiate or initiate smoking, respectively. Based on the potentially distinct responses from these population segments, the current study used a behavioral segmentation approach to qualitatively explore the perceptions of nicotine and nicotine addiction that exist within these groups ( 21 – 23 ). Also, to inform future communication efforts around VLNC policy, we examine how their perceptions of nicotine and addiction might be affected by the messages communicating about VLNC policy.

Participants were recruited in Atlanta and San Francisco from a marketing research panel in February-March 2020 ( 24 ). We screened 1,685 respondents (including by phone to confirm age and tobacco use status) and recruited 165, resulting in 115 participants. Those not meeting the enrollment criteria (e.g., non-smokers over the age of 30), not interested in participating, or without the technology to participate in an online focus group (virtual due to COVID-19) were excluded. We conducted two groups per smoking status per city following the recommendation that 2–4 groups per category is sufficient to achieve saturation ( 25 ). Participants provided informed consent online.

Four types of participants were targeted: 1. exclusive smokers were currently smoking every day or some days and had smoked at least 100 cigarettes in their lifetime (n=27); 2. dual users were currently smoking and using e-cigarettes every day or some days (n=25); 3. former smokers had previously smoked 100 cigarettes in their lifetime but were not currently smoking (n=32); 4. young adult non-smokers were 18–30 years old and had not smoked 100 cigarettes in their lifetime (n=31). We excluded non-smokers over 30 because initiation of tobacco use is very low in this population ( 26 ).

In each city, we held two focus groups for each smoking status group (n=16 focus groups). All focus groups were conducted virtually by an experienced moderator who encouraged active participation from everybody and called on more reserved participants. The moderator followed the focus group guide developed based on the literature on nicotine perceptions and our experience with developing and testing messages by integrating different strategies to elicit perceptions (i.e., free association, semi-structured probing, individual and group evaluations of different messages). The first part of the guide included open-ended questions on participants’ perceptions about nicotine, such as participants’ first associations with the terms “nicotine” and “addiction” and the immediate and long-term health effects of nicotine. Exclusive smokers and dual users were also asked about their own perceived addiction.

In the second part of the focus group, participants viewed eight messages the research team developed to communicate about the VLNC policy. These eight messages were grouped into four types: efficacy messages, risk messages, an alternative product message, and a compensation misperception message (see Appendix ). Despite different core themes, all messages provided general information about the FDA policy, including that the nicotine content of all cigarettes would be reduced. Message reactions are reported elsewhere ( 27 ); in this paper we include only the discussion concerning nicotine and addiction that participants raised in response to the messages.

The focus groups lasted 75–90 minutes, and the number of participants ranged from four to nine (median=7.5). All focus groups were audio-recorded and transcribed. Participants received $50 as compensation for their time. The Georgia State University IRB approved this study.

Data analysis

Transcripts were analyzed in NVivo 12.0 using inductive thematic analysis ( 22 ). The first two authors (E.L. & H.D.) independently read all transcripts and developed the initial codes. The codes were then shared with the research team, who discussed and developed the initial codebook. Two transcripts were randomly selected and independently coded by the first two authors. Discrepancies in coding were resolved with the last author (L.P). A master codebook was then created, and the remaining transcripts were divided and coded independently by the two first authors. Transcript extracts for particular codes were distributed among research team members who wrote memos on salient themes that were discussed with the team. Transcripts for each population segment (i.e. exclusive smokers, dual users, former smokers, and non-smokers) were described separately and were compared with other segments. The first author then read the memos, corresponding transcripts, and synthesized the results.

Participant characteristics are shown in Table 1 below. Among dual users, median number of days out of past 30 days participants reported smoking cigarettes was 20 (IQR: 30–5.25) and using e-cigarettes was 25 (IQR: 25.75–11.5).

Participant Characteristics

Free Associations with Nicotine

When prompted to describe the first things that come to mind when considering the word “nicotine”, participants consistently mentioned tobacco products, such as cigarettes, e-cigarettes, rolling tobacco, and cigars. However, they assigned different valence to the term depending on their smoking status: mostly negative for exclusive smokers, former smokers, and non-smokers, and neutral or positive for dual users. Several exclusive smokers said that nicotine is a “necessary evil” and a “bad habit.” Former smokers associated nicotine with being a “danger.” For several non-smokers, the word “nicotine” triggered thoughts about the bad smell of cigarettes. In contrast, dual users focused more on products containing nicotine and “quitting products” and it made them think of “relaxing.” For each smoking status type, members of at least one focus group associated nicotine with “addiction.” Only a couple of participants brought up tobacco-related diseases (“cancer”) as the first thing that they associated with “nicotine.”

Free Associations with Addiction

Free associations with “addiction” were largely negative but were much more nuanced compared to associations with “nicotine.” Common across focus groups were mentions of addiction to other substances, including sugary snacks, soda, coffee, alcohol, drugs, and even watching television and exercising. But overall, free associations with addiction differed greatly based on experience with tobacco. Experienced smokers (i.e. exclusive smokers, dual users, and former smokers) related addiction to the feeling of losing control, referencing their own experience with addiction. For example, they mentioned “helpless,” “compulsion,” and “lack of discipline.” Many exclusive smokers described how addiction resulted in their inability to control responses when internally cued to smoke, such as when “you don’t know what to do with your hands”; that it “pushes you to an action that you may not or may want to do” and feels like “a human jail …it consumes you and there’s no way out…” Dual users had similar responses, speaking from their own experiences, “You almost organically link to it and if you go a few hours without it, it feels like another organ that you’re missing.”

Former smokers did not refer to their own experience with addiction. Rather, they defined addiction as “dependency on a product,” “an uncontrollable urge,” and “the silent killer.” Non-smokers expressed criticism of addicts as their first thought about addiction, referring to addicts being in denial, or stating that addiction starts as a choice. One participant stated, “I think it’s a choice to an extent. I mean, once you get past the normal usage of things and you cross that addiction border, at that point it becomes a disease.” Indeed, many nonsmokers mentioned that addiction is a disease or mental illness that requires treatment and some focused on the consequences of addiction, referring to its impact on friends or family of tobacco users.

Perceived Effects of Nicotine

Participants were asked to discuss the effects of nicotine, both immediately after inhalation and the long-term diseases nicotine causes. Participants across focus groups conflated the various smoking-related diseases with the effects of nicotine but differed in describing benign effects. Across groups, participants believed that the health effects of nicotine included lung cancer, emphysema, COPD, and heart disease.

Exclusive smokers discussed physiological effects from nicotine inhalation based on their personal experiences, describing how nicotine stimulates the nervous system, increases the heart rate, and releases endorphins. They listed psychoactive effects, including feelings of euphoria and a buzz, rush, or high, and intensifying the current moods, “If I’m feeling anxious, smoking a cigarette would make me more anxious.” Unlike other groups, exclusive smokers mentioned benefits of nicotine, such as “a calming sensation.” When asked about diseases caused by nicotine, the discussion among exclusive smokers progressed from talking about different diseases associated with smoking to an assertion that nicotine is not the primary cause of these diseases. One exclusive smoker said, “I don’t know that it’s the nicotine that causes the cancer. I think it’s more the smoke, it’s the actual smoke that you’re inhaling [that] does the damage to your lungs.”

Dual users overwhelmingly began by mentioning neutral health effects, such as “relaxes my muscles,” “constricts the blood vessels,” and “makes your heart rate speed up.” Similar to exclusive smokers, dual users then describe the positive effects of nicotine, such as nicotine “makes you focus,” and “gives you a good buzz.” With the exception of one dual user who suggested a positive psychoactive effect (enjoyment), other dual users also discussed that smoking-related diseases are caused by nicotine.

Former smokers tended to talk about the negative effects of nicotine, including that it “coats the inside of your lungs” and “reduces your lungs’ ability to take in oxygen.” Some former smokers mentioned psychoactive effects, such as causing an adrenaline rush or triggering addiction. Others discussed mixed effects, such as comfort, relaxation, and feeling nauseous. Additionally, some former smokers suggested that nicotine “elevates blood pressure.” In contrast, non-smokers mostly discussed the health effects of smoking rather than nicotine, but one asserted that “the health risks that are associated with smoking don’t exactly come from nicotine itself.” Several non-smokers said that nicotine’s main effect is that it “satisfies addiction.”

Acknowledgement of Own Addiction to Nicotine

Experienced smokers were asked whether they thought they were addicted to nicotine and responses differed by smoking status. Exclusive smokers who identified themselves as addicted said that they “tried to stop several times to no avail” or that if they refrain from smoking, they become “irritable” and have “no patience.” Others described their responses to internal and external cues to smoke as signs of addiction, including the need to smoke “after every meal,” smoking when experiencing emotions including “when I’m bored, when I’m stressed, when I’m sad, when I’m drinking coffee, drinking alcohol, if I’m on the phone.”

Dual users who believed that they were addicted referred to it as “a way to escape my reality.” Others stated that they are “dependent, but I think I could stop it if I really wanted to.” Some referenced using e-cigarettes or nicotine replacement therapy as a sign of addiction: “If I don’t have a vape or a cig, I always chew nicotine gum.” Experiencing withdrawal symptoms was also associated with addiction, including when using e-cigarettes: “So, I switched to vaping last May and the vaping definitely helped with all of the withdrawals.” Dual users also identified the need to smoke when exposed to external cues as being indicative of addiction. One dual user said, “You wake up in the morning, that’s the first thing you do, like before you brush your teeth and you’re continuously doing it throughout the day.” Some also referenced continuing to smoke or vape despite being aware of adverse effects: “you’re still doing it even when you know it’s affecting different parts of your life.”

Former smokers acknowledged that they had been addicted due to their first-hand experience with cessation. For many, quitting smoking was “probably the hardest thing that I ever really did.” Several referred to moments of desperation that revealed their addiction, such as “when I’m sitting on the edge of the bed coughing my lungs out and I still want another one” or “when you are going through the ash tray and seeing if there’s any piece left that you could get a hit off.”

Denial of Own Addiction to Nicotine

When asked about their own experiences with addiction, many experienced smokers denied that they were addicted to nicotine. Exclusive smokers who believed they were not addicted said that addicts would have a schedule of smoking, and smoking only occasionally in certain circumstances is a sign that a person is not addicted. One exclusive smoker stated,

“I think of those people, those friends that get up in the morning and have to have a cigarette, before he goes to bed at night he has to have a cigarette… he’s driving and he’s smoking… So, I think of that when I think of addiction, I don’t think of it like every once in a while or like it won’t kill me to go a couple of days. I’m not dying for to get a pack of cigarettes… I’m not (a) freak.”

Dual users who did not believe they were addicted said they knew this because they could “stop if I really wanted to,” and because they had once been able to quit cigarettes. Some dual users classified their smoking as a “habit” or a “vice”, which they perceived as different from addiction, “I wouldn’t consider myself addicted to cigarettes, but I do indulge in a lot of vices… I wouldn’t consider myself I guess diagnosed as addicted.”

Defining Addiction to Nicotine

Regardless of whether they believed they were addicted, exclusive smokers tended to minimize the negative associations with their own addiction and differentiated tobacco use from other addictions. For instance, one exclusive smoker commented, “Cigarette addiction doesn’t seem as bad as some other drug addiction. You know, it’s just so much more accepted.” Other exclusive smokers acknowledged their own addiction but suggested that it had been normalized, “Sometimes, I just think of it as a bad habit. That’s how I grew up.”

Many exclusive smokers identified their addiction as specifically tied to nicotine, “You’re not addicted to the tobacco, you’re addicted to the nicotine. That’s what gives you the high, the rush.” Some dual users also responded that nicotine is “the drug you’re addicted to,” while others showed reluctance to admit they were addicted to a chemical and felt that their addiction was more complex. One dual user said, “there’s a combination of nicotine and other things within a cigarette or a vape that causes addiction.” Some dual users also cited ‘flavors’ or the action of using a product as being a component of addiction, stating, “I think that active like vaping or like the oral fixation is as addictive in and of itself.” Dual users also believed that “it’s a physical addiction as well as an emotional.” Several former smokers mentioned that addiction involves the habit of smoking and response to external cues to smoke. One former smoker stated, “smoking becomes a habit in your social situation, for example around other people that smoke and that also makes it really hard to quit when you’re addicted.”

Responses to Messages

When exposed to the messages about the VLNC policy, participants across focus groups found it difficult to understand how nicotine addiction works in relation to the policy, or why this type of policy would be considered. Participants in all focus groups expressed uncertainty about whether reducing nicotine content would actually remove the addictiveness, or if other factors would also contribute to addiction.

Exposure to the messages allowed the focus groups to consider how a reduction in nicotine would impact addiction. Dual users were mostly skeptical that the policy would lead to reduction of smoking, with one stating, “I think it’s going to be harder to become addicted. But once you’re addicted, I don’t think it’s gonna make it any easier to quit.” Former smokers said the messages benefited their understanding of how nicotine addiction works. One former smoker said: “Nicotine is basically the one thing that makes smoking pleasurable and without that, it’s not as fun to smoke anymore.”

The complex beliefs that participants had about addiction to smoking also arose in response to the messages. Some dual users understood that “less nicotine equals less addiction.” Others argued that addiction is caused by multiple factors, saying that the policy’s focus on nicotine oversimplifies addiction. Many dual users understood nicotine to be “the thing that gets people hooked on cigarettes” but some were “under the impression that there’s other chemicals that they add as well that keep you addicted” and thought, “we’re getting addicted to the chemicals that are in the nicotine, but they’re not telling us how the other chemicals are also affecting us.”

Exclusive smokers and former smokers mostly supported this position. One exclusive smoker stated, “if there are other reasons why they’re smoking other than being physically addicted to nicotine, then it’s not going to affect those people.” Another exclusive smoker said, “everybody has their own story when it comes to cigarettes. It’s a stress reliever for some people. It’s a habit for other people. And some people just want to be with the in crowd to be cool.” One former smoker added, “The nicotine is where the addiction comes from. But it’s also just a habit.”

One specific message that elicited conversation across focus groups encouraged smokers to ‘consider the alternatives’ and try switching to lower-harm products, such as e-cigarettes. Non-smokers had a difficult time understanding the rationale of the policy through this lens, identifying that it “keeps the addiction going, just in a different vice or form.” Nearly all non-smokers felt that encouraging smokers to switch to e-cigarettes would just promote addiction to nicotine through other products. Exclusive smokers and former smokers also rejected that message, criticizing the recommendation to switch from one nicotine source to another. Not surprisingly, dual users responded favorably to the messages by stating that “if you still need nicotine, you can still get it from less harmful alternatives but still you’re going to maintain an addiction.”

Our focus group study with key tobacco use behavioral segments suggests that personal experience with tobacco products may shape how people talk about nicotine and addiction. Exclusive smokers and former smokers expressed strong negative perspectives about nicotine, dual users were more positive or neutral, and non-smokers had varying levels of understanding, likely due to their lack of experience with nicotine. Participants tended to believe that nicotine is addictive, but that addiction results from more than just nicotine (e.g., oral fixation, routine, cravings brought on by internal and external cues). After showing messages about VLNC policy, participants across all groups discussed that reducing nicotine will not necessarily reduce the addictiveness of cigarettes because of the multi-factorial nature of smoking addiction. They believed that a VLNC policy would not address this broader conceptualization.

By asking about the immediate thoughts or images that arise when hearing the word “nicotine” or “addiction”, we aimed to tap into participants’ experiential mode of thinking ( 28 ). This experiential mode is affective, associative, and intuitive, in contrast with the logical, conscious, and effortful analytic mode. These “gut” feelings that drive people’s decisions and behavior consistently predict smoking behaviors ( 29 , 30 ). Across smoker types, the most common immediate association participants had with nicotine was nicotine-containing products, and the valence was largely neutral; however, some former and exclusive smokers and non-smokers tended to respond with more negative emotions than dual users. Future studies should examine whether reducing nicotine through a VLNC policy may lower the negative affect these groups experience toward nicotine in general ( 31 ) and, consistent with dual system theories that identify the key role of the affect heuristic in shaping risk perceptions ( 32 ), thereby lower risk perceptions of VLNCs compared to regular cigarettes.

When probed on what nicotine does once inside the body, participants identified many negative effects. Across focus groups, participants believed that nicotine caused several diseases attributed to smoking, consistent with research showing that many people falsely believe that nicotine causes cancer ( 8 ). However, in some groups, particularly among exclusive smokers and dual users, participants mentioned the positive psychoactive effects of nicotine. This likely perpetuates their rationale for continuing to smoke. Prior research found that describing VLNCs as no longer providing these positive psychoactive effects (relieving cravings) caused smokers to indicate that they would quit smoking in response to this policy ( 33 ); however, in a real-world environment, these responses may differ.

Exclusive smokers were aware of the addictiveness of nicotine; however, some believed that the term ‘addiction’ was inappropriate, expressing that, compared to illicit drug use, smoking is more publicly acceptable, and that ‘addiction’ better describes drug use. They described addiction to nicotine as the inability to quit and a need to smoke when exposed to internal and external cues. Dual users tended to be less direct when describing their addiction and used more positive language. They talked about using e-cigarettes to satisfy cravings from nicotine addiction. Some exclusive smokers and dual users denied or downplayed whether they were “addicted” to nicotine. Because addiction might be negatively perceived when linked to smokers’ self-concept, we suspect that these participants might be motivated to rationalize their smoking behavior by minimizing negative beliefs about addiction and inflating their sense of self-efficacy to control their behavior ( 34 ). Indeed, research on optimistic bias and smoking risk has consistently found that smokers tend to underestimate their own addiction ( 35 , 36 ).

Former smokers mostly focused on experiences with overcoming addiction, concluding that addiction can be strong, but that quitting is possible. These conceptualizations are in line with that of the Wisconsin Inventory of Smoking Dependence Motives (WISDM) ( 37 ), a frequently used measure of nicotine dependence that is based on the traditional conceptualizations of nicotine dependence: classifications from the early Diagnostic and Statistical Manual of Mental Disorders (DSM) from the American Psychiatric Association (APA) and the physical dependence classification initially conceptualized by Fagerstrӧm. Early DSM classifications of nicotine dependence center around symptomology of dependence, including cravings, compulsion, and withdrawal ( 38 ). Meanwhile, the Fagerstrӧm conceptualization uses self-reported behaviors to measure the extent to which individuals are dependent on nicotine ( 39 ). WISDM builds upon these conceptualizations, encompassing thirteen distinct drives that characterize dependence 37). We found that experienced smokers mostly referred to motives around cue exposure-associated processes (i.e. smoking in response to nonsocial cues), automaticity (i.e. smoking without awareness), and loss of control. Motives around behavioral-choice melioration (i.e. smoking despite negative consequences), tolerance, and social-environmental goads (i.e. exposure to social stimuli or contexts that invite smoking) were mentioned, but less often. Perhaps because many of these participants viewed addiction negatively, they explained their smoking as not an addiction, but in more benign terms, such as habit or dependence. This type of rationalization has been reported before in studies of nicotine beliefs among adolescents ( 18 – 20 ).

As in their free-associations, participant responses to the messages about VLNC policy differentiated between addiction to nicotine and addiction to smoking. Many felt that removing nicotine from cigarettes would not eliminate their addictiveness, citing that the hand-to-mouth movement or oral fixation, routine, and social or environmental cues would keep a smoker addicted. Some also believed that other chemicals in cigarettes cause addiction and that removing only nicotine would not eliminate their addictiveness. A growing literature indicates that pharmacological effects of nicotine are not the only drivers of substance use and addiction ( 40 ) and that neuropharmacological model of addiction is too narrow and does not fully explain the human behavior ( 41 , 42 ). Non-pharmacological influences on drug use and addiction incorporate multiple dimensions, such as a person’s mental state, environmental conditions (such as settings and stressors), and instrumental use of drugs (to achieve a specific task, such as increased concentration) ( 40 ). In our study, statements by experienced nicotine users that cigarettes are addictive only in part because of nicotine reflect this stance, resulting in skepticism and reactance towards the VLNC policy among some participants.

Implications for Regulation

A federal mandate to reduce nicotine in cigarettes and possibly other combusted tobacco products represents a critical opportunity to communicate the rationale for these measures, how consumers will experience them, and what this implies for their health. Substantial misunderstanding of the relationship between nicotine, addiction, and health should be addressed to maximize the potential health benefits of this policy. Our results suggest that it will likely be important to persuade consumers that nicotine reduction would result in less addictive tobacco products, protecting non-smokers and future generations. Communications that accompany a VLNC policy should consider acknowledging the belief that addiction not only involves nicotine, but also encompasses a variety of cues and motivations that encourage continued smoking. Communications must also include messaging to counteract the misunderstanding that nicotine is the primary source of the adverse health outcomes that result from smoking. Additionally, it will be critical to help consumers understand that continuing to smoke VLNCs will result in the same adverse health effects as from current cigarettes.

Should FDA adopt a VLNC policy, effective communication strategies may need to target the varied assumptions we found for exclusive smokers, dual users, former users and nonsmokers to maximize the public health benefits of this regulatory action. For example, exclusive smokers may benefit from messages focusing on the reduction of cravings or psychoactive effects of nicotine, and emphasizing that the health risks of smoking would not be ameliorated by removing nicotine. Based on their acceptance of the message encouraging smokers to ‘consider the alternatives’, dual users may be most receptive of messages that encourage smokers to switch to non-combustible tobacco products to obtain nicotine. To avoid promoting relapse for former smokers or initiation of smoking for non-smokers, it is important that messages do not portray VLNCs in a positive light. Rather, messages should emphasize that VLNCs are not less harmful than cigarettes and that a reduction in nicotine will only reduce the addictiveness. Other countries considering a VLNC policy may also need to address the similarities and differences in key consumer groups.

Limitations

Generalizability is limited due to the purposive recruitment from two different cities with contrasting tobacco control environments. San Francisco’s restrictions on e-cigarettes may be associated with different perceptions of nicotine than in areas with fewer restrictions; however, we found responses were generally similar across cities. Our participants were from urban areas, which have lower smoking rates (18.3%) compared to rural areas (28.5%) ( 43 ). The virtual format of the focus groups restricted participation to those with internet access and equipment and may have limited communicative cues (eye contact, turn taking), but allowed for participants with difficulty in transportation to participate and may have reduced normative pressures common in face-to-face focus group ( 44 ). Although 89% of all US households have internet access ( 45 ), future research should examine these issues among smokers from disadvantaged communities. Additionally, we did not examine the social or cultural factors that may account for participant beliefs and responses to VLNC policy, which may be important to consider in future research on why people believe what they do about nicotine. Nevertheless, the results from our focus on individual perceptions across key behavioral segments provides insights around and potential linkage to theories and concepts that should be explored in more systematic fashion.

In conclusion, our findings show that discussions of nicotine and addiction were nuanced and varied based on the smoking status, although all groups shared some degree of misunderstandings of the risks of nicotine and potentially underestimating their addiction to nicotine. For example, participants across all smoking statuses did not clearly understand the relationship between nicotine and addiction, which may lead to confusion in interpreting the purpose of the VLNC policy. While general messages to address these misunderstanding would be useful, FDA would likely benefit from tailoring the messages to specific groups.

Supplementary Material

Acknowledgements.

We wish to thank all participants for participating in this study. We also to wish to thank The Research Associates for aiding in message creation and conducting the focus groups. Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number R01CA239308. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Declaration of interest: None

• 1. World Health Organization. WHO global report on trends in prevalence of tobacco smoking, 2015. Geneva, Switzerland: World Health Organization; 2015. Retrieved from http://apps.who.int/iris/bitstream/10665/156262/1/9789241564922_eng.pdf [ Google Scholar ]
• 2. American Cancer Society. Harmful Chemicals in Tobacco Products. American Cancer Society; 2017. Retrieved from https://www.cancer.org/cancer/cancer-causes/tobacco-and-cancer/carcinogens-found-in-tobacco-products.html [ Google Scholar ]
• 3. Benowitz NL. Nicotine addiction. New England Journal of Medicine. 2010;362(24): 2295–2303. 10.1056/NEJMra0809890 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 4. McDaniel PA, Smith EA, Malone RE. The tobacco endgame: A qualitative review and synthesis. Tobacco Control. 2016;25(5):594–604. 10.1136/tobaccocontrol-2015-052356 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 5. Benowitz NL, Henningfield JE. Reducing the nicotine content to make cigarettes less addictive. Tobacco Control. 2013;22(1):i14–i17. 10.1136/tobaccocontrol-2012-050860 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 6. Gottlieb S, Zeller M. A nicotine-focused framework for public health. New England Journal of Medicine. 2017:377(12);1111–1114. 10.1056/NEJMp1707409 [ DOI ] [ PubMed ] [ Google Scholar ]
• 7. Villanti AC, Byron MJ, Mercincavage M, Pacek LR. Misperceptions of nicotine and nicotine reduction: The importance of public education to maximize the benefits of a nicotine reduction standard. Nicotine and Tobacco Research, 2019:21(Supplement_1), S88–S90. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 8. Mumford EA, Pearson JL, Villanti AC, Evans WD. Nicotine and e-cigarette beliefs and policy support among US Smokers and Nonsmokers. Tobacco Regulatory Science. 2017:3(3);293–305. 10.18001/TRS.3.3.5 [ DOI ] [ Google Scholar ]
• 9. Mercincavage M, Lochbuehler K, Villanti AC, Wileyto EP, Audrain-McGovern J, Strasser AA. Examining risk perceptions among daily smokers naïve to reduced nicotine content cigarettes. Nicotine & Tobacco Research. 2018:21(7);985–990. 10.1093/ntr/nty082 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 10. Nguyen AB, Zhao X, Hoffman L, Morse AL, Delahanty J. Nicotine and addiction beliefs and perceptions among the US-born and foreign-born populations. Preventive Medicine. 2018:114;107–114. 10.1016/j.ypmed.2018.06.018 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 11. O’Brien EK, Nguyen AB, Persoskie A, Hoffman AC. U.S. adults’ addiction and harm beliefs about nicotine and low nicotine cigarettes. Preventive Medicine. 2017:96;94–100. 10.1016/j.ypmed.2016.12.048 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 12. Pfeffer D, Wigginton B, Gartner C, Morphett K. Smokers’ Understandings of Addiction to Nicotine and Tobacco: A Systematic Review and Interpretive Synthesis of Quantitative and Qualitative Research. Nicotine & Tobacco Research. 2018:20(9);1038–1046. 10.1093/ntr/ntx186 [ DOI ] [ PubMed ] [ Google Scholar ]
• 13. Abdullah ASM, Ho WWN. What Chinese Adolescents Think About Quitting Smoking: A Qualitative Study. Substance Use & Misuse. 2006:41(13);1735–1743. 10.1080/10826080601006433 [ DOI ] [ PubMed ] [ Google Scholar ]
• 14. Berg CJ, Schauer GL, Buchanan TS, Sterling K, DeSisto C, Pinsker EA, Ahluwalia JS. Perceptions of addiction, attempts to quit, and successful quitting in nondaily and daily smokers. Psychology of Addictive Behaviors. 2013:27(4);1059–1067. 10.1037/a0033790 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 15. Gillies V, Willig C. ‘You get the nicotine and that in your blood’—Constructions of addiction and control in women’s accounts of cigarette smoking. Journal of Community & Applied Social Psychology. 1997:7(4);285–301. [ Google Scholar ]
• 16. Harrell PT, Brandon TH, England KJ, Barnett TE, Brockenberry LO, Simmons VN, Quinn GP Vaping Expectancies: A Qualitative Study among Young Adult Nonusers, Smokers, Vapers, and Dual Users. Substance Abuse: Research and Treatment. 2019:13. 10.1177/1178221819866210 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 17. Kaufman AR, Grenen E, Grady M, Bryan L, Ferrer RA. Perceptions of Harm and Addiction of Snus: An Exploratory Study. Psychol Addict Behav. 2016:30(8);895–903. 10.1037/adb0000230 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 18. Bottorff JL, Johnson JL, Moffat B, Grewal J, Ratner PA, Kalaw C. Adolescent constructions of nicotine addiction. The Canadian Journal of Nursing Research = Revue Canadienne De Recherche En Sciences Infirmieres. 2004:36(1);22–39. [ PubMed ] [ Google Scholar ]
• 19. O’Loughlin J, Kishchuk N, DiFranza J, Tremblay M, Paradis G. The hardest thing is the habit: A qualitative investigation of adolescent smokers’ experience of nicotine dependence. Nicotine & Tobacco Research: Official Journal of the Society for Research on Nicotine and Tobacco. 2002:4(2);201–209. 10.1080/14622200210123000 [ DOI ] [ PubMed ] [ Google Scholar ]
• 20. Roditis M, Lee J, Halpern-Felsher BL. Adolescent (Mis)Perceptions About Nicotine Addiction: Results From a Mixed-Methods Study. Health Education & Behavior. 2016:43(2);156–164. 10.1177/1090198115598985 [ DOI ] [ PubMed ] [ Google Scholar ]
• 21. Philip K (2017). Principles of marketing. Pearson higher education. [ Google Scholar ]
• 22. Dewhirst T, & Lee WB (2011). Social Marketing and Tobacco Control. The SAGE handbook of social marketing, 391–404. [ Google Scholar ]
• 23. Sun S An analysis on the conditions and methods of market segmentation. International Journal of Business and Management. 2009:4(2);63–70. [ Google Scholar ]
• 24. The Research Associates. The Research Associates – Corporate Website; 2017. Retrieved from https://www.theresearch.com/
• 25. Hennink M, Hutter I, Bailey A. Qualitative research methods. London, UK: SAGE Publications Ltd; 2011. [ Google Scholar ]
• 26. United States Department of Health and Human Services. The Health Consequences of Smoking—50 Years of Progress: A Report of the Surgeon General Atlanta, GA: US Department of Health and Human Services, Center for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office of Smoking and Health; 2014. [ Google Scholar ]
• 27. Duong HT, Loud EE, Henderson K, Ashley D, Thrasher JF, Popova L. “It Brings Light to What You Really Put into Your Body”: A Focus Group Study of Reactions to Messages about Nicotine Reduction in Cigarettes. Tobacco Control. In press. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 28. Braun V, Clarke V. Using thematic analysis in psychology. Qualitative Research in Psychology. 2006:3(2);77–101. 10.1191/1478088706qp063oa [ DOI ] [ Google Scholar ]
• 29. Lawton R, Conner M, McEachan R. Desire or reason: predicting health behaviors from affective and cognitive attitudes. Health Psychology. 2009:28(1);56. 10.1037/a0013424 [ DOI ] [ PubMed ] [ Google Scholar ]
• 30. Trafimow D, Sheeran P, Lombardo B, Finlay KA, Brown J, Armitage CJ. Affective and cognitive control of persons and behaviours. British Journal of Social Psychology. 2004:43(2);207–224. 10.1348/0144666041501642 [ DOI ] [ PubMed ] [ Google Scholar ]
• 31. Popova L, Owusu D, Weaver SR, Kemp CB, Mertz CK, Pechacek TF, Slovic P. Affect, risk perception, and the use of cigarettes and e-cigarettes: A population study of U.S. adults. BMC Public Health. 2018:18;395. 10.1186/s12889-018-5306-z [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 32. Slovic P, Finucane ML, Peters E, McGregor DG. Risk as analysis and risk as feelings: Some thoughts about affect, reasons, risk, and rationality. Risk Analysis. 2004:24(2);311–322. [ DOI ] [ PubMed ] [ Google Scholar ]
• 33. Popova L, Owusu D, Nyman AL, Weaver SR, Yang B, Huang J, Ashley DL. Effects of framing nicotine reduction in cigarettes on anticipated tobacco product use intentions and risk perceptions among US adult smokers. Nicotine & Tobacco Research. 2019:21(1); S108–S116. 10.1093/ntr/ntz146 [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 34. Fotuhi O, Fong GT, Zanna MP, Borland R, Yong HH, Cummings KM. “Patterns of cognitive dissonance-reducing beliefs among smokers: a longitudinal analysis from the International Tobacco Control (ITC) Four Country Survey.” Tobacco control. 2013:22(1);52–58. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 35. Arnett JJ. Optimistic bias in adolescent and adult smokers and nonsmokers. Addictive behaviors. 2000:25(4);625–632 [ DOI ] [ PubMed ] [ Google Scholar ]
• 36. Popova Lucy, and Bonnie L Halpern-Felsher. “A longitudinal study of adolescents’ optimistic bias about risks and benefits of cigarette smoking.” American journal of health behavior. 2016:40(3);341–351. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 37. Piper ME, Piasecki TM, Federman EB, Bolt DM, Smith SS, Fiore MC, Baker TB. A multiple motives approach to tobacco dependence: The Wisconsin inventory of smoking dependence motives (WISDM-68). Journal of Consulting and Clinical Psychology. 2004:72(2);139–154. 10.1037/0022-006X.72.2.139 [ DOI ] [ PubMed ] [ Google Scholar ]
• 38. American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC. [ Google Scholar ]
• 39. Heatherton TF, Kozlowski LT, Frecker RC, & Fagerstrom KO The Fagerström test for nicotine dependence: a revision of the Fagerstrom Tolerance Questionnaire. British journal of addiction. 1991:86(9);1119–1127. [ DOI ] [ PubMed ] [ Google Scholar ]
• 40. Ahmed SH, Badiani A, Miczek KA, & Müller CP Non-pharmacological factors that determine drug use and addiction. Neuroscience and Biobehavioral Reviews. 2020:110;3–27. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 41. Hall W, Carter A, & Forlini C The brain disease model of addiction: is it supported by the evidence and has it delivered on its promises? The Lancet Psychiatry/ 2015:2(1);105–110. [ DOI ] [ PubMed ] [ Google Scholar ]
• 42. Badiani A, Berridge KC, Heilig M, Nutt DJ, & Robinson TE (2018). Addiction research and theory: a commentary on the Surgeon General’s Report on alcohol, drugs, and health. Addiction biology. 2018:23(1);3–5. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ]
• 43. Centers for Disease Control and Prevention. Tobacco use by geographic region. Office on Smoking and Health, National Center for Chronic Disease Prevention and Health Promotion; 2019. Retrieved from https://www.cdc.gov/tobacco/disparities/geographic/index.htm [ Google Scholar ]
• 44. Morgan D Focus Groups as Qualitative Research. SAGE Publications, Inc. 1997. 10.4135/9781412984287 [ DOI ] [ Google Scholar ]
• 45. PEW Research Center. Internet penetration rates are high in North America, Europe and parts of the Asia-Pacific. PEW Research Center; 2018. Retrieved from http://www.pewglobal.org/2018/06/19/social-media-use-continues-to-rise-in-developing-countries-but-plateaus-across-developed-ones/pg_2018-06-19_global-tech_0-01/ . [ Google Scholar ]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

• View on publisher site
• PDF (333.2 KB)
• Collections

Similar articles

Cited by other articles, links to ncbi databases.

• Download .nbib .nbib
• Format: AMA APA MLA NLM

Add to Collections

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

•  We're Hiring!
•  Help Center

Nicotine Addiction

• Most Cited Papers
• Most Downloaded Papers
• Newest Papers
• Nicotine Follow Following
• Nicotine Dependence Follow Following
• Adolescent Risk Taking Follow Following
• Selective Attention (Psychology) Follow Following
• Noradrenaline Follow Following
• Striatum Follow Following
• Implicit measures Follow Following
• Internet addiction, cyberpsychology, gaming, gambling, sex, social networks Follow Following
• Canine behaviour Follow Following
• Glutamate receptors Follow Following

Enter the email address you signed up with and we'll email you a reset link.

• Academia.edu Journals
•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

An official website of the United States government

Here’s how you know

Official websites use .gov A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS A lock ( Lock Locked padlock icon ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Parents & Educators

Find the latest science-based information about drug use, health, and the developing brain. Designed for young people and those who influence them—parents, guardians, teachers, and other educators—these resources inspire learning and encourage critical thinking so teens can make informed decisions about drug use and their health.  Information provided by NIDA is not a substitute for professional medical care.

Looking for Treatment?

Use the  SAMHSA Treatment Locator  or call  1-800-662-HELP (4357) .

Lesson Plans and Activities

Educate teens about drugs, drug use, and life skills with activities and lessons from Scholastic.

National Drug and Alcohol Facts Week (NDAFW)

NDAFW is an annual health observance that teaches teens the science of drug use and addiction among youth. Join NIDA by...

Parents: Conversation Starters

Get information to help you talk with your teens about drugs and their effects, and learn where to go to get help.

Mind Matters Series

Take a scientific journey to learn about the brain’s complex responses to specific drugs.

What Is the Worst Drug?

Scientists from the National Institute on Drug Abuse answer common questions teens ask about drug use and addiction. The...

What Is Addiction?

What Happens When Drugs Are Combined?

Can Using Drugs Help Me Deal With Anxiety and Depression?

Mind Matters: How do Drugs Affect Your Life?

This video for middle school students describes the effects of addiction and how getting high can take over your life.

Mind Matters: How do Drugs Work on the Brain?

This video for middle school students explains how the brain develops and how drugs affect the brain. Check out the Mind...

Mind Matters: The Body’s Response to Inhalants

This video for middle school students identifies common household items that are used as inhalants and explains how they...

Mind Matters: The Body’s Response to Bath Salts

This video for middle school students explains how synthetic cathinones, commonly known as bath salts, affect the brain...

Mind Matters: How do Vaping Devices Work?

This video explains what vaping devices are and how they work.

Mind Matters: How do You Become Addicted to Nicotine?

This video for middle school students describes cigarettes, e-cigarettes, vapes, and other tobacco products and provides...

Mind Matters: What are Opioids?

This video for middle school students describes what Opioids are, why doctors prescribe them, and how they can be...

Mind Matters: The Body’s Response to K2/Spice

This video for middle school students describes how synthetic cannabinoids, called K2 or Spice, affect the brain and the...

Mind Matters: The Body’s Response to Prescription Stimulants

This video for middle school students describes prescription stimulants, why they are prescribed, and how they can...

Mind Matters: How Does Marijuana Affect Your Brain and Body?

This video for middle school students describes the short and long term effects of Marijuana on the brain and body.

Mind Matters: What if someone I know needs help?

This video for middle school students describes the steps needed to help someone recover from drug abuse and addiction

Monitoring the Future 2021 Survey Results

The percentage of adolescents reporting substance use decreased significantly in 2021

The Human Brain: Major Structures and Functions

This video explains the human brain and its major structures and functions. Your brain is who you are. It’s what allows...

More on this Topic

Innovative projects answer nida’s challenge to implement substance use prevention in primary care, fentanyl drugfacts, vaping devices (electronic cigarettes) drugfacts, more than 321,000 u.s. children lost a parent to drug overdose from 2011 to 2021, related resources, get the facts.

• College-Age and Young Adult NIDA Resources
• Commonly Used Drugs Chart
• Medical School Resources
• Mind Matters Series - Provides resources for those in grades K–9.
• National Drug and Alcohol Facts Week ®
• Prevention Resources
• Treatment Resources  

Additional Resources

• Keeping Youth Drug Free  (SAMHSA)
• Guide to Reducing Vaping Among Youth and Young Adults to Vaping  (SAMHSA)
• Opioids and Adolescents  (Office of Adolescent Health)
• Presentation for Youth - Know the Risks: A Youth Guide to E-cigarettes  (Centers for Disease Control and Prevention)

Other Resources

• MEDLINEplus Health Information on Substance Use Disorders  (National Library of Medicine, NIH)
• Healthfinder.gov  (U.S. Department of Health and Human Services)

Clinical Trials

Clinical trials are research studies in human volunteers conducted to answer specific health questions. Learn about the NIDA-sponsored clinical trials available to you

• Skip to main content
• Skip to FDA Search
• Skip to in this section menu
• Skip to footer links

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

On Oct. 1, 2024, the FDA began implementing a reorganization impacting many parts of the agency. We are in the process of updating FDA.gov content to reflect these changes.

U.S. Food and Drug Administration

•   Search
•   Menu
• Tobacco Products
• Products, Guidance & Regulations
• Products, Ingredients & Components

E-Cigarettes, Vapes, and other Electronic Nicotine Delivery Systems (ENDS)

On this page:

• What Are E-Cigarettes, Vapes, and Other Electronic Nicotine Delivery System (ENDS) products?

Are E-Cigarettes a Lower-Risk Alternative to Cigarettes?

• Youth Use and Prevention

E-Cigarette Problems and Potential Violations

Safe disposal of e-cigarettes.

• Vape Shops that Mix E-Liquids or Modify Products
• Importing ENDS and E-Liquids

Are You a Retailer of ENDS Products?

What are e-cigarettes, vapes, and other electronic nicotine delivery system (ends) products.

Vapes, vaporizers, vape pens, hookah pens, electronic cigarettes (e-cigarettes or e-cigs), e-cigars, and e-pipes are some of the many tobacco product terms used to describe electronic nicotine delivery systems (ENDS). 

These products use an “e-liquid” that usually contains nicotine derived from tobacco, as well as flavorings, propylene glycol, vegetable glycerin, and other ingredients. The liquid is heated to create an aerosol that is inhaled.

ENDS may be manufactured to look like conventional combusted cigarettes, cigars, or pipes. Some resemble pens or USB flash drives. Larger devices, such as tank systems or mods, bear little or no resemblance to cigarettes. These products may have reusable parts, or they may be disposable and only used once before they are thrown away.

Are You Looking for General Health and Safety Information Related to E-Cigarettes, Vapes, or Other ENDS?

The longer ENDS and other e-cigarettes are on the market, the more information we know about their impacts on health. This includes data on youth use of these products, which has led to development of several educational programs designed to prevent adolescents and teens from using these products. Through tobacco product problem reports and tobacco product violation reports , the FDA also knows much more about many safety and health hazards they may pose.

While e-cigarettes can generally be a lower-risk alternative for adults who smoke cigarettes, the use of e-cigarettes is not risk-free. These products deliver harmful chemicals and contain nicotine, which is highly addictive. Moreover, given the harmful chemicals found in e-cigarettes, further high-quality research on both short- and long-term health outcomes is needed.

Given that there is no safe tobacco product, youth and adults who do not use tobacco products should not start using e-cigarettes.

For adults who smoke, switching completely from cigarettes to e-cigarettes may reduce exposure to many harmful chemicals present in cigarettes. However, it is important that they switch completely from cigarettes to e-cigarettes to get the full health benefit. Long periods of dual use of cigarettes and e-cigarettes can result in harms to health similar to, or in addition to, the harms from exclusive use of cigarettes.

To date, FDA has authorized 34 tobacco- and menthol-flavored e-cigarette products and devices . These products have undergone rigorous scientific review, including toxicologic assessments, and have been found by FDA to meet the statutory public health standard.

Learn more at FDA’s “ Facts About E-Cigarettes ” webpage.

Youth Use and Prevention 

The FDA monitors the national usage rates for all tobacco products, including an annual youth survey, and has seen a drastic increase in youth use of e-cigarette products in recent years. Due to what has been called an ‘epidemic’ of youth use of these products, FDA has prioritized prevention efforts. The agency has taken a multitude of actions to keep ENDS out of the hands of youth, from policy making to enforcement to education. 

Learn about public education efforts and resources that have been created to reach youth who are at higher risk of or more vulnerable to cigarette use and nicotine addiction. FDA created a toolkit, Resources for Professionals About Vaping & E-Cigarettes , for adults and professionals who work with youth. This FREE resource provides fast facts about youth vaping and e-cigarettes.

The Real Cost

“The Real Cost” E-Cigarette Prevention Campaign 

FDA’s award-winning public education campaign, “ The Real Cost ,” continues to prevent youth from tobacco initiation and use. In 2017, the campaign began prioritizing e-cigarette prevention messaging to combat increasing youth vaping rates. “The Real Cost” campaign also educates teens on the health consequences of smoking cigarettes.  

Resources in the FDA Tobacco Education Resource Library

The FDA Tobacco Education Resource Library, from FDA's Center for Tobacco Products, provides tobacco education resources. This site offers digital and print content for state and local health officials, nonprofit organizations, and schools to support public outreach efforts and includes the Vaping Prevention and Education Resource Center , an online resource center with science-based, standards-mapped materials teachers can use to help students understand the dangers associated with vaping and nicotine addiction. The resource center features numerous age-appropriate, cross-curricular resources for teachers to promote learning and begin having open conversations with youth about vaping.

In addition to content designed for teachers, there are also materials for parents and teens. All content on the resource center is free, easy to navigate, and optimized for each audience.  These resources are also available in Spanish.

Visit the Vaping Resource Center

There are no safe tobacco products, including ENDS. In addition to exposing people to risks of tobacco-related disease and death, FDA has received reports from the public about safety problems associated with vaping products including:

• Overheating, fires, and explosions
• Lung injuries
• Seizures and other neurological symptoms

These problems can seriously hurt the person using the ENDS product and others around them. There may be added dangers, for example if a vape battery catches fire near an oxygen tank, a propane tank (such as used in backyard grills), or a gas pump, or if a person has a vape-related seizure while driving. FDA has a webpage with tips to help avoid vape fires or explosions .

If you have experienced undesired health or quality problems with any tobacco product, including ENDS, you can report it to FDA . Knowing more about adverse experiences can help FDA identify concerning trends and causes or contributors for particular incidents or health or quality problems beyond those normally associated with tobacco product use. You can read some tobacco-related adverse experience reports on the Tobacco Product Problem Reports page.

If you think ENDS or other tobacco products are being sold to people who are underage, or you see another potential violation of the FD&C Act or FDA’s tobacco regulations, please report the potential tobacco product violation .

The United States Environmental Protection Agency’s How to Safely Dispose of E-Cigarettes: Information for Individuals includes important information and a printable fact sheet about proper and safe disposal of e-cigarettes. Most important:   

• Do NOT put e-cigarettes in your household trash or recycling
• Take e-cigarettes to your household hazardous waste collection site

Are You a Manufacturer of E-Cigarettes, Vapes, or other ENDS?

FDA regulates the manufacture, import, packaging, labeling, advertising, promotion, sale, and distribution of ENDS, including components and parts of ENDS but excluding accessories.

Examples of regulated components and parts of ENDS include:

• A glass or plastic vial container of e-liquid
• Atomizers, the part of the ENDS that turns e-liquid into vapor for inhalation
• Cartomizers and clearomizers, which, similar to atomizers also deliver e-liquid in vapor form
• Certain batteries
• Digital display or lights to adjust settings
• Tank systems
• Drip tips or mouthpieces
• Flavorings for ENDS
• Programmable software

Products marketed for therapeutic purposes (for example, marketed as a product to help people quit smoking) are regulated by FDA’s Center for Drug Evaluation and Research (CDER) . FDA published a rule clarifying when products made or derived from tobacco are regulated as tobacco products, drugs, and/ or devices.

If you make, modify, mix, manufacture, fabricate, assemble, process, label, repack, relabel, or import ENDS, you must comply with the requirements for manufacturers .

CTP's Office of Small Business Assistance can answer specific questions about requirements for small businesses and how to comply with the law. This office also provides online educational resources to help regulated industry understand FDA regulations and policies.

Tools for Retailers

“ This is Our Watch ” is a voluntary education program with resources to help tobacco retailers better understand and comply with FDA tobacco regulations. Tobacco retailers play a direct role in protecting kids from nicotine addiction and the deadly effects of tobacco use. Learn what tobacco retailers need to do to comply with the rules designed to prevent our nation's youth from becoming the next generation of Americans to die prematurely from tobacco-related disease.

Retail Sales of Tobacco Products offers more information about federal rules that retailers must follow as well as information on regulations, guidance, and webinars for retailers.

Did You Know? It is illegal for a retailer to sell any tobacco product – including cigarettes, cigars, smokeless tobacco, and e-cigarettes – to anyone under 21 .

Vape Shops That Mix E-Liquids or Modify Products

If you operate a vape shop that mixes or prepares liquid nicotine or nicotine-containing e-liquids, or creates or modifies any type of ENDS, in addition to product sales, you may be considered a manufacturer and have to comply with the requirements for manufacturers linked above. 

Some vape shops may have legal responsibilities as both manufacturers and retailers of tobacco products.

For information about ENDS products that are authorized  for marketing in the U.S., view FDA’s “ Searchable Tobacco Products Database ."

Note: This page does not provide a comprehensive list of all ENDS products that may be marketed in the U.S. Retailers should discuss with their suppliers about the current status of any particular tobacco product’s application or any product’s marketing authorization.  

Subscribe to CTPConnect

Get regular updates on the health effects of tobacco, public health educational resources, and highlights on current tobacco issues and regulations.

A .gov website belongs to an official government organization in the United States.

A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

• Cigarette Smoking
• Secondhand Smoke
• E-cigarettes (Vapes)
• Menthol Tobacco Products
• Nicotine Pouches
• Morbidity and Mortality Weekly Reports (MMWR)
• About Surveys
• Other Tobacco Products
• Patient Care Settings and Smoking Cessation
• Patient Care
• Funding Opportunity Announcements
• Scientific Evidence Briefs
• Current Cigarette Smoking Among Adults in the United States
• Youth and Tobacco Use
• Smoking Cessation: Fast Facts
• Economic Trends in Tobacco
• State and Community Work
• National and State Tobacco Control Program

Related Topics:

• View All Home
• Tobacco - Health Equity
• Tobacco - Surgeon General's Reports
• State Tobacco Activities Tracking and Evaluation (STATE) System
• Global Tobacco Control

How to Quit Smoking

What to know.

• There are proven treatments to help people quit smoking.
• Using counseling and medication together gives people who smoke the best chance of quitting for good.

You can quit smoking: here's how

Quitting smoking is one of the most important steps you can take to improve your health. This is true no matter how old you are or how long you have smoked. The good news is there are proven treatments that can help you quit.

Many people who smoke become addicted to nicotine, a drug that is found naturally in tobacco. This can make it hard to quit smoking. But the good news is there are proven treatments that can help you quit.

Download and print the infographic

You can quit smoking: here’s how infographic

Usted puede dejar de fumar: sepa cómo hacerlo

Counseling can help you make a plan to quit smoking. Counseling can also prepare you to cope with stress, urges to smoke, and other issues when trying to quit.

Seek counseling

• Talk to a quit smoking counselor individually or in a group.
• Get free confidential coaching through a quitline ( 1-800-QUIT-NOW ).
• Use free online resources like CDC.gov/quit and Smokefree.gov .
• Sign up for free texting program .
• Use a mobile app like quitSTART .

Medications

Medications can help you manage nicotine withdrawal symptoms and cravings, which helps you stay confident and motivated to quit.

You can use Nicotine Replacement Therapy (NRT)

Nicotine Replacement Therapy (NRT) includes several options.

• Over-the-counter forms: patch , gum , lozenge .
• Prescription forms: inhaler , nasal spray .

You can talk to your health care provider about using a pill prescription medication

Varenicline and buproprion are pill prescription medications you can discuss with your doctor.

You can combine quit medications

Use a long-acting form of NRT (nicotine patch) together with a short-acting form (nicotine gum or lozenge) . Compared to using one form of NRT, this combination can further increase your chances of quitting.

Counseling plus medications

Using counseling and medication together gives you the best chance of quitting for good.

Many treatments and resources may be available to you for free of charge or may be covered by your insurance.

Get help quitting today

If you are ready to quit:

• Call a quitline coach ( 1-800-QUIT-NOW ) or
• Talk to a health care professional

They can help you decide what treatment is best for you and can connect you to quit smoking programs and resources .

Remember, even if you've tried before, the key to success is to keep trying and not give up. More than half of U.S. adults who smoked have quit.

For more information about quitting smoking, visit CDC.gov/quit .

Smoking and Tobacco Use

Commercial tobacco use is the leading cause of preventable disease, disability, and death in the United States.

For Everyone

Health care providers, public health.