effects of smoking essay

Essay on Smoking

500 words essay on  smoking.

One of the most common problems we are facing in today’s world which is killing people is smoking. A lot of people pick up this habit because of stress , personal issues and more. In fact, some even begin showing it off. When someone smokes a cigarette, they not only hurt themselves but everyone around them. It has many ill-effects on the human body which we will go through in the essay on smoking.

Ill-Effects of Smoking

Tobacco can have a disastrous impact on our health. Nonetheless, people consume it daily for a long period of time till it’s too late. Nearly one billion people in the whole world smoke. It is a shocking figure as that 1 billion puts millions of people at risk along with themselves.

Cigarettes have a major impact on the lungs. Around a third of all cancer cases happen due to smoking. For instance, it can affect breathing and causes shortness of breath and coughing. Further, it also increases the risk of respiratory tract infection which ultimately reduces the quality of life.

In addition to these serious health consequences, smoking impacts the well-being of a person as well. It alters the sense of smell and taste. Further, it also reduces the ability to perform physical exercises.

It also hampers your physical appearances like giving yellow teeth and aged skin. You also get a greater risk of depression or anxiety . Smoking also affects our relationship with our family, friends and colleagues.

Most importantly, it is also an expensive habit. In other words, it entails heavy financial costs. Even though some people don’t have money to get by, they waste it on cigarettes because of their addiction.

How to Quit Smoking?

There are many ways through which one can quit smoking. The first one is preparing for the day when you will quit. It is not easy to quit a habit abruptly, so set a date to give yourself time to prepare mentally.

Further, you can also use NRTs for your nicotine dependence. They can reduce your craving and withdrawal symptoms. NRTs like skin patches, chewing gums, lozenges, nasal spray and inhalers can help greatly.

Moreover, you can also consider non-nicotine medications. They require a prescription so it is essential to talk to your doctor to get access to it. Most importantly, seek behavioural support. To tackle your dependence on nicotine, it is essential to get counselling services, self-materials or more to get through this phase.

One can also try alternative therapies if they want to try them. There is no harm in trying as long as you are determined to quit smoking. For instance, filters, smoking deterrents, e-cigarettes, acupuncture, cold laser therapy, yoga and more can work for some people.

Always remember that you cannot quit smoking instantly as it will be bad for you as well. Try cutting down on it and then slowly and steadily give it up altogether.

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Conclusion of the Essay on Smoking

Thus, if anyone is a slave to cigarettes, it is essential for them to understand that it is never too late to stop smoking. With the help and a good action plan, anyone can quit it for good. Moreover, the benefits will be evident within a few days of quitting.

FAQ of Essay on Smoking

Question 1: What are the effects of smoking?

Answer 1: Smoking has major effects like cancer, heart disease, stroke, lung diseases, diabetes, and more. It also increases the risk for tuberculosis, certain eye diseases, and problems with the immune system .

Question 2: Why should we avoid smoking?

Answer 2: We must avoid smoking as it can lengthen your life expectancy. Moreover, by not smoking, you decrease your risk of disease which includes lung cancer, throat cancer, heart disease, high blood pressure, and more.

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Health Effects of Cigarette Smoking

Smoking and death, smoking and increased health risks, smoking and cardiovascular disease, smoking and respiratory disease, smoking and cancer, smoking and other health risks, quitting and reduced risks.

Cigarette smoking harms nearly every organ of the body, causes many diseases, and reduces the health of smokers in general. 1,2

Quitting smoking lowers your risk for smoking-related diseases and can add years to your life. 1,2

Cigarette smoking is the leading cause of preventable death in the United States. 1

• Cigarette smoking causes more than 480,000 deaths each year in the United States. This is nearly one in five deaths. 1,2,3
• Human immunodeficiency virus (HIV)
• Illegal drug use
• Alcohol use
• Motor vehicle injuries
• Firearm-related incidents
• More than 10 times as many U.S. citizens have died prematurely from cigarette smoking than have died in all the wars fought by the United States. 1
• Smoking causes about 90% (or 9 out of 10) of all lung cancer deaths. 1,2  More women die from lung cancer each year than from breast cancer. 5
• Smoking causes about 80% (or 8 out of 10) of all deaths from chronic obstructive pulmonary disease (COPD). 1
• Cigarette smoking increases risk for death from all causes in men and women. 1
• The risk of dying from cigarette smoking has increased over the last 50 years in the U.S. 1

Smokers are more likely than nonsmokers to develop heart disease, stroke, and lung cancer. 1

• For coronary heart disease by 2 to 4 times 1,6
• For stroke by 2 to 4 times 1
• Of men developing lung cancer by 25 times 1
• Of women developing lung cancer by 25.7 times 1
• Smoking causes diminished overall health, increased absenteeism from work, and increased health care utilization and cost. 1

Smokers are at greater risk for diseases that affect the heart and blood vessels (cardiovascular disease). 1,2

• Smoking causes stroke and coronary heart disease, which are among the leading causes of death in the United States. 1,3
• Even people who smoke fewer than five cigarettes a day can have early signs of cardiovascular disease. 1
• Smoking damages blood vessels and can make them thicken and grow narrower. This makes your heart beat faster and your blood pressure go up. Clots can also form. 1,2
• A clot blocks the blood flow to part of your brain;
• A blood vessel in or around your brain bursts. 1,2
• Blockages caused by smoking can also reduce blood flow to your legs and skin. 1,2

Smoking can cause lung disease by damaging your airways and the small air sacs (alveoli) found in your lungs. 1,2

• Lung diseases caused by smoking include COPD, which includes emphysema and chronic bronchitis. 1,2
• Cigarette smoking causes most cases of lung cancer. 1,2
• If you have asthma, tobacco smoke can trigger an attack or make an attack worse. 1,2
• Smokers are 12 to 13 times more likely to die from COPD than nonsmokers. 1

Smoking can cause cancer almost anywhere in your body: 1,2

• Blood (acute myeloid leukemia)
• Colon and rectum (colorectal)
• Kidney and ureter
• Oropharynx (includes parts of the throat, tongue, soft palate, and the tonsils)
• Trachea, bronchus, and lung

Smoking also increases the risk of dying from cancer and other diseases in cancer patients and survivors. 1

If nobody smoked, one of every three cancer deaths in the United States would not happen. 1,2

Smoking harms nearly every organ of the body and affects a person’s overall health. 1,2

• Preterm (early) delivery
• Stillbirth (death of the baby before birth)
• Low birth weight
• Sudden infant death syndrome (known as SIDS or crib death)
• Ectopic pregnancy
• Orofacial clefts in infants
• Smoking can also affect men’s sperm, which can reduce fertility and also increase risks for birth defects and miscarriage. 2
• Women past childbearing years who smoke have weaker bones than women who never smoked. They are also at greater risk for broken bones.
• Smoking affects the health of your teeth and gums and can cause tooth loss. 1
• Smoking can increase your risk for cataracts (clouding of the eye’s lens that makes it hard for you to see). It can also cause age-related macular degeneration (AMD). AMD is damage to a small spot near the center of the retina, the part of the eye needed for central vision. 1
• Smoking is a cause of type 2 diabetes mellitus and can make it harder to control. The risk of developing diabetes is 30–40% higher for active smokers than nonsmokers. 1,2
• Smoking causes general adverse effects on the body, including inflammation and decreased immune function. 1
• Smoking is a cause of rheumatoid arthritis. 1
• Quitting smoking is one of the most important actions people can take to improve their health. This is true regardless of their age or how long they have been smoking. Visit the Benefits of Quitting  page for more information about how quitting smoking can improve your health.
• U.S. Department of Health and Human Services. The Health Consequences of Smoking—50 Years of Progress: A Report of the Surgeon General . Atlanta: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2014 [accessed 2017 Apr 20].
• U.S. Department of Health and Human Services. How Tobacco Smoke Causes Disease: What It Means to You . Atlanta: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2010 [accessed 2017 Apr 20].
• Centers for Disease Control and Prevention. QuickStats: Number of Deaths from 10 Leading Causes—National Vital Statistics System, United States, 2010 . Morbidity and Mortality Weekly Report 2013:62(08);155. [accessed 2017 Apr 20].
• Mokdad AH, Marks JS, Stroup DF, Gerberding JL. Actual Causes of Death in the United States . JAMA: Journal of the American Medical Association 2004;291(10):1238–45 [cited 2017 Apr 20].
• U.S. Department of Health and Human Services. Women and Smoking: A Report of the Surgeon General . Rockville (MD): U.S. Department of Health and Human Services, Public Health Service, Office of the Surgeon General, 2001 [accessed 2017 Apr 20].
• U.S. Department of Health and Human Services. Reducing the Health Consequences of Smoking: 25 Years of Progress. A Report of the Surgeon General . Rockville (MD): U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 1989 [accessed 2017 Apr 20].

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• Open access
• Published: 10 October 2022

Health effects associated with smoking: a Burden of Proof study

• Xiaochen Dai   ORCID: orcid.org/0000-0002-0289-7814 1 , 2 ,
• Gabriela F. Gil 1 ,
• Marissa B. Reitsma 1 ,
• Noah S. Ahmad 1 ,
• Jason A. Anderson 1 ,
• Catherine Bisignano 1 ,
• Sinclair Carr 1 ,
• Rachel Feldman 1 ,
• Simon I. Hay   ORCID: orcid.org/0000-0002-0611-7272 1 , 2 ,
• Jiawei He 1 , 2 ,
• Vincent Iannucci 1 ,
• Hilary R. Lawlor 1 ,
• Matthew J. Malloy 1 ,
• Laurie B. Marczak 1 ,
• Susan A. McLaughlin 1 ,
• Larissa Morikawa   ORCID: orcid.org/0000-0001-9749-8033 1 ,
• Erin C. Mullany 1 ,
• Sneha I. Nicholson 1 ,
• Erin M. O’Connell 1 ,
• Chukwuma Okereke 1 ,
• Reed J. D. Sorensen 1 ,
• Joanna Whisnant 1 ,
• Aleksandr Y. Aravkin 1 , 3 ,
• Peng Zheng 1 , 2 ,
• Christopher J. L. Murray   ORCID: orcid.org/0000-0002-4930-9450 1 , 2 &
• Emmanuela Gakidou   ORCID: orcid.org/0000-0002-8992-591X 1 , 2  

Nature Medicine volume  28 ,  pages 2045–2055 ( 2022 ) Cite this article

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• Risk factors

Matters Arising to this article was published on 14 April 2023

As a leading behavioral risk factor for numerous health outcomes, smoking is a major ongoing public health challenge. Although evidence on the health effects of smoking has been widely reported, few attempts have evaluated the dose–response relationship between smoking and a diverse range of health outcomes systematically and comprehensively. In the present study, we re-estimated the dose–response relationships between current smoking and 36 health outcomes by conducting systematic reviews up to 31 May 2022, employing a meta-analytic method that incorporates between-study heterogeneity into estimates of uncertainty. Among the 36 selected outcomes, 8 had strong-to-very-strong evidence of an association with smoking, 21 had weak-to-moderate evidence of association and 7 had no evidence of association. By overcoming many of the limitations of traditional meta-analyses, our approach provides comprehensive, up-to-date and easy-to-use estimates of the evidence on the health effects of smoking. These estimates provide important information for tobacco control advocates, policy makers, researchers, physicians, smokers and the public.

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Among both the public and the health experts, smoking is recognized as a major behavioral risk factor with a leading attributable health burden worldwide. The health risks of smoking were clearly outlined in a canonical study of disease rates (including lung cancer) and smoking habits in British doctors in 1950 and have been further elaborated in detail over the following seven decades 1 , 2 . In 2005, evidence of the health consequences of smoking galvanized the adoption of the first World Health Organization (WHO) treaty, the Framework Convention on Tobacco Control, in an attempt to drive reductions in global tobacco use and second-hand smoke exposure 3 . However, as of 2020, an estimated 1.18 billion individuals globally were current smokers and 7 million deaths and 177 million disability-adjusted life-years were attributed to smoking, reflecting a persistent public health challenge 4 . Quantifying the relationship between smoking and various important health outcomes—in particular, highlighting any significant dose–response relationships—is crucial to understanding the attributable health risk experienced by these individuals and informing responsive public policy.

Existing literature on the relationship between smoking and specific health outcomes is prolific, including meta-analyses, cohort studies and case–control studies analyzing the risk of outcomes such as lung cancer 5 , 6 , 7 , chronic obstructive pulmonary disease (COPD) 8 , 9 , 10 and ischemic heart disease 11 , 12 , 13 , 14 due to smoking. There are few if any attempts, however, to systematically and comprehensively evaluate the landscape of evidence on smoking risk across a diverse range of health outcomes, with most current research focusing on risk or attributable burden of smoking for a specific condition 7 , 15 , thereby missing the opportunity to provide a comprehensive picture of the health risk experienced by smokers. Furthermore, although evidence surrounding specific health outcomes, such as lung cancer, has generated widespread consensus, findings about the attributable risk of other outcomes are much more heterogeneous and inconclusive 16 , 17 , 18 . These studies also vary in their risk definitions, with many comparing dichotomous exposure measures of ever smokers versus nonsmokers 19 , 20 . Others examine the distinct risks of current smokers and former smokers compared with never smokers 21 , 22 , 23 . Among the studies that do analyze dose–response relationships, there is large variation in the units and dose categories used in reporting their findings (for example, the use of pack-years or cigarettes per day) 24 , 25 , which complicates the comparability and consolidation of evidence. This, in turn, can obscure data that could inform personal health choices, public health practices and policy measures. Guidance on the health risks of smoking, such as the Surgeon General’s Reports on smoking 26 , 27 , is often based on experts’ evaluation of heterogenous evidence, which, although extremely useful and well suited to carefully consider nuances in the evidence, is fundamentally subjective.

The present study, as part of the Global Burden of Diseases, Risk Factors, and Injuries Study (GBD) 2020, re-estimated the continuous dose–response relationships (the mean risk functions and associated uncertainty estimates) between current smoking and 36 health outcomes (Supplementary Table 1 ) by identifying input studies using a systematic review approach and employing a meta-analytic method 28 . The 36 health outcomes that were selected based on existing evidence of a relationship included 16 cancers (lung cancer, esophageal cancer, stomach cancer, leukemia, liver cancer, laryngeal cancer, breast cancer, cervical cancer, colorectal cancer, lip and oral cavity cancer, nasopharyngeal cancer, other pharynx cancer (excluding nasopharynx cancer), pancreatic cancer, bladder cancer, kidney cancer and prostate cancer), 5 cardiovascular diseases (CVDs: ischemic heart disease, stroke, atrial fibrillation and flutter, aortic aneurysm and peripheral artery disease) and 15 other diseases (COPD, lower respiratory tract infections, tuberculosis, asthma, type 2 diabetes, Alzheimer’s disease and related dementias, Parkinson’s disease, multiple sclerosis, cataracts, gallbladder diseases, low back pain, peptic ulcer disease, rheumatoid arthritis, macular degeneration and fractures). Definitions of the outcomes are described in Supplementary Table 1 . We conducted a separate systematic review for each risk–outcome pair with the exception of cancers, which were done together in a single systematic review. This approach allowed us to systematically identify all relevant studies indexed in PubMed up to 31 May 2022, and we extracted relevant data on risk of smoking, including study characteristics, following a pre-specified template (Supplementary Table 2 ). The meta-analytic tool overcomes many of the limitations of traditional meta-analyses by incorporating between-study heterogeneity into the uncertainty of risk estimates, accounting for small numbers of studies, relaxing the assumption of log(linearity) applied to the risk functions, handling differences in exposure ranges between comparison groups, and systematically testing and adjusting for bias due to study designs and characteristics. We then estimated the burden-of-proof risk function (BPRF) for each risk–outcome pair, as proposed by Zheng et al. 29 ; the BPRF is a conservative risk function defined as the 5th quantile curve (for harmful risks) that reflects the smallest harmful effect at each level of exposure consistent with the available evidence. Given all available data for each outcome, the risk of smoking is at least as harmful as the BPRF indicates.

We used the BPRF for each risk–outcome pair to calculate risk–outcome scores (ROSs) and categorize the strength of evidence for the association between smoking and each health outcome using a star rating from 1 to 5. The interpretation of the star ratings is as follows: 1 star (*) indicates no evidence of association; 2 stars (**) correspond to a 0–15% increase in risk across average range of exposures for harmful risks; 3 stars (***) represent a 15–50% increase in risk; 4 stars (****) refer to >50–85% increase in risk; and 5 stars (*****) equal >85% increase in risk. The thresholds for each star rating were developed in consultation with collaborators and other stakeholders.

The increasing disease burden attributable to current smoking, particularly in low- and middle-income countries 4 , demonstrates the relevance of the present study, which quantifies the strength of the evidence using an objective, quantitative, comprehensive and comparative framework. Findings from the present study can be used to support policy makers in making informed smoking recommendations and regulations focusing on the associations for which the evidence is strongest (that is, the 4- and 5-star associations). However, associations with a lower star rating cannot be ignored, especially when the outcome has high prevalence or severity. A summary of the main findings, limitations and policy implications of the study is presented in Table 1 .

We evaluated the mean risk functions and the BPRFs for 36 health outcomes that are associated with current smoking 30 (Table 2 ). Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines 31 for each of our systematic reviews, we identified studies reporting relative risk (RR) of incidence or mortality from each of the 36 selected outcomes for smokers compared with nonsmokers. We reviewed 21,108 records, which were identified to have been published between 1 May 2018 and 31 May 2022; this represents the most recent time period since the last systematic review of the available evidence for the GBD at the time of publication. The meta-analyses reported in the present study for each of the 36 health outcomes are based on evidence from a total of 793 studies published between 1970 and 2022 (Extended Data Fig. 1 – 5 and Supplementary Information 1.5 show the PRISMA diagrams for each outcome). Only prospective cohort and case–control studies were included for estimating dose–response risk curves, but cross-sectional studies were also included for estimating the age pattern of smoking risk on cardiovascular and circulatory disease (CVD) outcomes. Details on each, including the study’s design, data sources, number of participants, length of follow-up, confounders adjusted for in the input data and bias covariates included in the dose–response risk model, can be found in Supplementary Information 2 and 3 . The theoretical minimum risk exposure level used for current smoking was never smoking or zero 30 .

Five-star associations

When the most conservative interpretation of the evidence, that is, the BPRF, suggests that the average exposure (15th–85th percentiles of exposure) of smoking increases the risk of a health outcome by >85% (that is, ROS > 0.62), smoking and that outcome are categorized as a 5-star pair. Among the 36 outcomes, there are 5 that have a 5-star association with current smoking: laryngeal cancer (375% increase in risk based on the BPRF, 1.56 ROS), aortic aneurysm (150%, 0.92), peripheral artery disease (137%, 0.86), lung cancer (107%, 0.73) and other pharynx cancer (excluding nasopharynx cancer) (92%, 0.65).

Results for all 5-star risk–outcome pairs are available in Table 2 and Supplementary Information 4.1 . In the present study, we provide detailed results for one example 5-star association: current smoking and lung cancer. We extracted 371 observations from 25 prospective cohort studies and 53 case–control studies across 25 locations (Supplementary Table 3 ) 5 , 6 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 . Exposure ranged from 1 pack-year to >112 pack-years, with the 85th percentile of exposure being 50.88 pack-years (Fig. 1a ).

a , The log(RR) function. b , RR function. c , A modified funnel plot showing the residuals (relative to 0) on the x axis and the estimated s.d. that includes reported s.d. and between-study heterogeneity on the y axis.

We found a very strong and significant harmful relationship between pack-years of current smoking and the RR of lung cancer (Fig. 1b ). The mean RR of lung cancer at 20 pack-years of smoking was 5.11 (95% uncertainty interval (UI) inclusive of between-study heterogeneity = 1.84–14.99). At 50.88 pack-years (85th percentile of exposure), the mean RR of lung cancer was 13.42 (2.63–74.59). See Table 2 for mean RRs at other exposure levels. The BPRF, which represents the most conservative interpretation of the evidence (Fig. 1a ), suggests that smoking in the 15th–85th percentiles of exposure increases the risk of lung cancer by an average of 107%, yielding an ROS of 0.73.

The relationship between pack-years of current smoking and RR of lung cancer is nonlinear, with diminishing impact of further pack-years of smoking, particularly for middle-to-high exposure levels (Fig. 1b ). To reduce the effect of bias, we adjusted observations that did not account for more than five confounders, including age and sex, because they were the significant bias covariates identified by the bias covariate selection algorithm 29 (Supplementary Table 7 ). The reported RRs across studies were very heterogeneous. Our meta-analytic method, which accounts for the reported uncertainty in both the data and between-study heterogeneity, fit the data and covered the estimated residuals well (Fig. 1c ). After trimming 10% of outliers, we still detected publication bias in the results for lung cancer. See Supplementary Tables 4 and 7 for study bias characteristics and selected bias covariates, Supplementary Fig. 5 for results without 10% trimming and Supplementary Table 8 for observed RR data and alternative exposures across studies for the remaining 5-star pairs.

Four-star associations

When the BPRF suggests that the average exposure of smoking increases the risk of a health outcome by 50–85% (that is, ROS > 0.41–0.62), smoking is categorized as having a 4-star association with that outcome. We identified three outcomes with a 4-star association with smoking: COPD (72% increase in risk based on the BPRF, 0.54 ROS), lower respiratory tract infection (54%, 0.43) and pancreatic cancer (52%, 0.42).

In the present study, we provide detailed results for one example 4-star association: current smoking and COPD. We extracted 51 observations from 11 prospective cohort studies and 4 case–control studies across 36 locations (Supplementary Table 3 ) 6 , 8 , 9 , 10 , 78 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 . Exposure ranged from 1 pack-year to 100 pack-years, with the 85th percentile of exposure in the exposed group being 49.75 pack-years.

We found a strong and significant harmful relationship between pack-years of current smoking and RR of COPD (Fig. 2b ). The mean RR of COPD at 20 pack-years was 3.17 (1.60–6.55; Table 2 reports RRs at other exposure levels). At the 85th percentile of exposure, the mean RR of COPD was 6.01 (2.08–18.58). The BPRF suggests that average smoking exposure raises the risk of COPD by an average of 72%, yielding an ROS of 0.54. The results for the other health outcomes that have an association with smoking rated as 4 stars are shown in Table 2 and Supplementary Information 4.2 .

a , The log(RR) function. b , RR function. c , A modified funnel plot showing the residuals (relative to 0) on th e x axis and the estimated s.d. that includes the reported s.d. and between-study heterogeneity on the y axis.

The relationship between smoking and COPD is nonlinear, with diminishing impact of further pack-years of current smoking on risk of COPD, particularly for middle-to-high exposure levels (Fig. 2a ). To reduce the effect of bias, we adjusted observations that did not account for age and sex and/or were generated for individuals aged >65 years 116 , because they were the two significant bias covariates identified by the bias covariate selection algorithm (Supplementary Table 7 ). There was large heterogeneity in the reported RRs across studies, and our meta-analytic method fit the data and covered the estimated residuals well (Fig. 2b ). Although we trimmed 10% of outliers, publication bias was still detected in the results for COPD. See Supplementary Tables 4 and 7 for study bias characteristics and selected bias covariates, Supplementary Fig. 5 for results without 10% trimming and Supplementary Table 8 for reported RR data and alternative exposures across studies for the remaining health outcomes that have a 4-star association with smoking.

Three-star associations

When the BPRF suggests that the average exposure of smoking increases the risk of a health outcome by 15–50% (or, when protective, decreases the risk of an outcome by 13–34%; that is, ROS >0.14–0.41), the association between smoking and that outcome is categorized as having a 3-star rating. We identified 15 outcomes with a 3-star association: bladder cancer (40% increase in risk, 0.34 ROS); tuberculosis (31%, 0.27); esophageal cancer (29%, 0.26); cervical cancer, multiple sclerosis and rheumatoid arthritis (each 23–24%, 0.21); lower back pain (22%, 0.20); ischemic heart disease (20%, 0.19); peptic ulcer and macular degeneration (each 19–20%, 0.18); Parkinson's disease (protective risk, 15% decrease in risk, 0.16); and stomach cancer, stroke, type 2 diabetes and cataracts (each 15–17%, 0.14–0.16).

We present the findings on smoking and type 2 diabetes as an example of a 3-star risk association. We extracted 102 observations from 24 prospective cohort studies and 4 case–control studies across 15 locations (Supplementary Table 3 ) 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 . The exposure ranged from 1 cigarette to 60 cigarettes smoked per day, with the 85th percentile of exposure in the exposed group being 26.25 cigarettes smoked per day.

We found a moderate and significant harmful relationship between cigarettes smoked per day and the RR of type 2 diabetes (Fig. 3b ). The mean RR of type 2 diabetes at 20 cigarettes smoked per day was 1.49 (1.18–1.90; see Table 2 for other exposure levels). At the 85th percentile of exposure, the mean RR of type 2 diabetes was 1.54 (1.20–2.01). The BPRF suggests that average smoking exposure raises the risk of type 2 diabetes by an average of 16%, yielding an ROS of 0.15. See Table 2 and Supplementary Information 4.3 for results for the additional health outcomes with an association with smoking rated as 3 stars.

a , The log(RR) function. b , RR function. c , A modified funnel plot showing the residuals (relative to 0) on the x axis and the estimated s.d. that includes the reported s.d. and between-study heterogeneity on the y axis.

The relationship between smoking and type 2 diabetes is nonlinear, particularly for high exposure levels where the mean risk curve becomes flat (Fig. 3a ). We adjusted observations that were generated in subpopulations, because it was the only significant bias covariate identified by the bias covariate selection algorithm (Supplementary Table 7 ). There was moderate heterogeneity in the observed RR data across studies and our meta-analytic method fit the data and covered the estimated residuals extremely well (Fig. 3b,c ). After trimming 10% of outliers, we still detected publication bias in the results for type 2 diabetes. See Supplementary Tables 4 and 7 for study bias characteristics and selected bias covariates, Supplementary Fig. 5 for results without 10% trimming and Supplementary Table 8 for observed RR data and alternative exposures across studies for the remaining 3-star pairs.

Two-star associations

When the BPRF suggests that the average exposure of smoking increases the risk of an outcome by 0–15% (that is, ROS 0.0–0.14), the association between smoking and that outcome is categorized as a 2-star rating. We identified six 2-star outcomes: nasopharyngeal cancer (14% increase in risk, 0.13 ROS); Alzheimer’s and other dementia (10%, 0.09); gallbladder diseases and atrial fibrillation and flutter (each 6%, 0.06); lip and oral cavity cancer (5%, 0.05); and breast cancer (4%, 0.04).

We present the findings on smoking and breast cancer as an example of a 2-star association. We extracted 93 observations from 14 prospective cohort studies and 9 case–control studies across 14 locations (Supplementary Table 3 ) 84 , 87 , 145 , 146 , 147 , 148 , 149 , 150 , 151 , 152 , 153 , 154 , 155 , 156 , 157 , 158 , 159 , 160 , 161 , 162 , 163 , 164 , 165 . The exposure ranged from 1 cigarette to >76 cigarettes smoked per day, with the 85th percentile of exposure in the exposed group being 34.10 cigarettes smoked per day.

We found a weak but significant relationship between pack-years of current smoking and RR of breast cancer (Extended Data Fig. 6 ). The mean RR of breast cancer at 20 pack-years was 1.17 (1.04–1.31; Table 2 reports other exposure levels). The BPRF suggests that average smoking exposure raises the risk of breast cancer by an average of 4%, yielding an ROS of 0.04. See Table 2 and Supplementary Information 4.4 for results on the additional health outcomes for which the association with smoking has been categorized as 2 stars.

The relationship between smoking and breast cancer is nonlinear, particularly for high exposure levels where the mean risk curve becomes flat (Extended Data Fig. 6a ). To reduce the effect of bias, we adjusted observations that were generated in subpopulations, because it was the only significant bias covariate identified by the bias covariate selection algorithm (Supplementary Table 7 ). There was heterogeneity in the reported RRs across studies, but our meta-analytic method fit the data and covered the estimated residuals (Extended Data Fig. 6b ). After trimming 10% of outliers, we did not detect publication bias in the results for breast cancer. See Supplementary Tables 4 and 7 for study bias characteristics and selected bias covariates, Supplementary Fig. 5 for results without 10% trimming and Supplementary Table 8 for observed RR data and alternative exposures across studies for the remaining 2-star pairs.

One-star associations

When average exposure to smoking does not significantly increase (or decrease) the risk of an outcome, once between-study heterogeneity and other sources of uncertainty are accounted for (that is, ROS < 0), the association between smoking and that outcome is categorized as 1 star, indicating that there is not sufficient evidence for the effect of smoking on the outcome to reject the null (that is, there may be no association). There were seven outcomes with an association with smoking that rated as 1 star: colorectal and kidney cancer (each –0.01 ROS); leukemia (−0.04); fractures (−0.05); prostate cancer (−0.06); liver cancer (−0.32); and asthma (−0.64).

We use smoking and prostate cancer as examples of a 1-star association. We extracted 78 observations from 21 prospective cohort studies and 1 nested case–control study across 15 locations (Supplementary Table 3 ) 157 , 160 , 166 , 167 , 168 , 169 , 170 , 171 , 172 , 173 , 174 , 175 , 176 , 177 , 178 , 179 , 180 , 181 , 182 , 183 , 184 , 185 . The exposure among the exposed group ranged from 1 cigarette to 90 cigarettes smoked per day, with the 85th percentile of exposure in the exposed group being 29.73 cigarettes smoked per day.

Based on our conservative interpretation of the data, we did not find a significant relationship between cigarettes smoked per day and the RR of prostate cancer (Fig. 4B ). The exposure-averaged BPRF for prostate cancer was 0.94, which was opposite null from the full range of mean RRs, such as 1.16 (0.89–1.53) at 20 cigarettes smoked per day. The corresponding ROS was −0.06, which is consistent with no evidence of an association between smoking and increased risk of prostate cancer. See Table 2 and Supplementary Information 4.5 for results for the additional outcomes that have a 1-star association with smoking.

The relationship between smoking and prostate cancer is nonlinear, particularly for middle-to-high exposure levels where the mean risk curve becomes flat (Fig. 4a ). We did not adjust for any bias covariate because no significant bias covariates were selected by the algorithm (Supplementary Table 7 ). The RRs reported across studies were very heterogeneous, but our meta-analytic method fit the data and covered the estimated residuals well (Fig. 4b,c ). The ROS associated with the BPRF is −0.05, suggesting that the most conservative interpretation of all evidence, after accounting for between-study heterogeneity, indicates an inconclusive relationship between smoking exposure and the risk of prostate cancer. After trimming 10% of outliers, we still detected publication bias in the results for prostate cancer, which warrants further studies using sample populations. See Supplementary Tables 4 and 7 for study bias characteristics and selected bias covariates, Supplementary Fig. 5 for results without 10% trimming and Supplementary Table 8 for observed RR data and alternative exposures across studies for the remaining 1-star pairs.

Age-specific dose–response risk for CVD outcomes

We produced age-specific dose–response risk curves for the five selected CVD outcomes ( Methods ). The ROS associated with each smoking–CVD pair was calculated based on the reference risk curve estimated using all risk data regardless of age information. Estimation of the BPRF, calculation of the associated ROS and star rating of the smoking–CVD pairs follow the same rules as the other non-CVD smoking–outcome pairs (Table 1 and Supplementary Figs. 2 – 4 ). Once we had estimated the reference dose–response risk curve for each CVD outcome, we determined the age group of the reference risk curve. The reference age group is 55–59 years for all CVD outcomes, except for peripheral artery disease, the reference age group for which is 60–64 years. We then estimated the age pattern of smoking on all CVD outcomes (Supplementary Fig. 2 ) and calculated age attenuation factors of the risk for each age group by comparing the risk of each age group with that of the reference age group, using the estimated age pattern (Supplementary Fig. 3 ). Last, we applied the draws of age attenuation factors of each age group to the dose–response risk curve for the reference age group to produce the age group-specific dose–response risk curves for each CVD outcome (Supplementary Fig. 4 ).

Using our burden-of-proof meta-analytic methods, we re-estimated the dose–response risk of smoking on 36 health outcomes that had previously been demonstrated to be associated with smoking 30 , 186 . Using these methods, which account for both the reported uncertainty of the data and the between-study heterogeneity, we found that 29 of the 36 smoking–outcome pairs are supported by evidence that suggests a significant dose–response relationship between smoking and the given outcome (28 with a harmful association and 1 with a protective association). Conversely, after accounting for between-study heterogeneity, the available evidence of smoking risk on seven outcomes (that is, colon and rectum cancer, kidney cancer, leukemia, prostate cancer, fractures, liver cancer and asthma) was insufficient to reject the null or draw definitive conclusions on their relationship to smoking. Among the 29 outcomes that have evidence supporting a significant relationship to smoking, 8 had strong-to-very-strong evidence of a relationship, meaning that, given all the available data on smoking risk, we estimate that average exposure to smoking increases the risk of those outcomes by >50% (4- and 5-star outcomes). The currently available evidence for the remaining 21 outcomes with a significant association with current smoking was weak to moderate, indicating that smoking increases the risk of those outcomes by at least >0–50% (2- and 3-star associations).

Even under our conservative interpretation of the data, smoking is irrefutably harmful to human health, with the greatest increases in risk occurring for laryngeal cancer, aortic aneurysm, peripheral artery disease, lung cancer and other pharynx cancer (excluding nasopharynx cancer), which collectively represent large causes of death and ill-health. The magnitude of and evidence for the associations between smoking and its leading health outcomes are among the highest currently analyzed in the burden-of-proof framework 29 . The star ratings assigned to each smoking–outcome pair offer policy makers a way of categorizing and comparing the evidence for a relationship between smoking and its potential health outcomes ( https://vizhub.healthdata.org/burden-of-proof ). We found that, for seven outcomes in our analysis, there was insufficient or inconsistent evidence to demonstrate a significant association with smoking. This is a key finding because it demonstrates the need for more high-quality data for these particular outcomes; availability of more data should improve the strength of evidence for whether or not there is an association between smoking and these health outcomes.

Our systematic review approach and meta-analytic methods have numerous benefits over existing systematic reviews and meta-analyses on the same topic that use traditional random effects models. First, our approach relaxes the log(linear) assumption, using a spline ensemble to estimate the risk 29 . Second, our approach allows variable reference groups and exposure ranges, allowing for more accurate estimates regardless of whether or not the underlying relative risk is log(linear). Furthermore, it can detect outliers in the data automatically. Finally, it quantifies uncertainty due to between-study heterogeneity while accounting for small numbers of studies, minimizing the risk that conclusions will be drawn based on spurious findings.

We believe that the results for the association between smoking and each of the 36 health outcomes generated by the present study, including the mean risk function, BPRF, ROS, average excess risk and star rating, could be useful to a range of stakeholders. Policy makers can formulate their decisions on smoking control priorities and resource allocation based on the magnitude of the effect and the consistency of the evidence relating smoking to each of the 36 outcomes, as represented by the ROS and star rating for each smoking–outcome association 187 . Physicians and public health practitioners can use the estimates of average increased risk and the star rating to educate patients and the general public about the risk of smoking and to promote smoking cessation 188 . Researchers can use the estimated mean risk function or BPRF to obtain the risk of an outcome at a given smoking exposure level, as well as uncertainty surrounding that estimate of risk. The results can also be used in the estimation of risk-attributable burden, that is, the deaths and disability-adjusted life-years due to each outcome that are attributable to smoking 30 , 186 . For the general public, these results could help them to better understand the risk of smoking and manage their health 189 .

Although our meta-analysis was comprehensive and carefully conducted, there are limitations to acknowledge. First, the bias covariates used, although carefully extracted and evaluated, were based on observable study characteristics and thus may not fully capture unobserved characteristics such as study quality or context, which might be major sources of bias. Second, if multiple risk estimates with different adjustment levels were reported in a given study, we included only the fully adjusted risk estimate and modeled the adjustment level according to the number of covariates adjusted for (rather than which covariates were adjusted for) and whether a standard adjustment for age and sex had been applied. This approach limited our ability to make full use of all available risk estimates in the literature. Third, although we evaluated the potential for publication bias in the data, we did not test for other forms of bias such as when studies are more consistent with each other than expected by chance 29 . Fourth, our analysis assumes that the relationships between smoking and health outcomes are similar across geographical regions and over time. We do not have sufficient evidence to quantify how the relationships may have evolved over time because the composition of smoking products has also changed over time. Perhaps some of the heterogeneity of the effect sizes in published studies reflects this; however, this cannot be discerned with the currently available information.

In the future, we plan to include crude and partially adjusted risk estimates in our analyses to fully incorporate all available risk estimates, to model the adjusted covariates in a more comprehensive way by mapping the adjusted covariates across all studies comprehensively and systematically, and to develop methods to evaluate additional forms of potential bias. We plan to update our results on a regular basis to provide timely and up-to-date evidence to stakeholders.

To conclude, we have re-estimated the dose–response risk of smoking on 36 health outcomes while synthesizing all the available evidence up to 31 May 2022. We found that, even after factoring in the heterogeneity between studies and other sources of uncertainty, smoking has a strong-to-very-strong association with a range of health outcomes and confirmed that smoking is irrefutably highly harmful to human health. We found that, due to small numbers of studies, inconsistency in the data, small effect sizes or a combination of these reasons, seven outcomes for which some previous research had found an association with smoking did not—under our meta-analytic framework and conservative approach to interpreting the data—have evidence of an association. Our estimates of the evidence for risk of smoking on 36 selected health outcomes have the potential to inform the many stakeholders of smoking control, including policy makers, researchers, public health professionals, physicians, smokers and the general public.

For the present study, we used a meta-analytic tool, MR-BRT (metaregression—Bayesian, regularized, trimmed), to estimate the dose–response risk curves of the risk of a health outcome across the range of current smoking levels along with uncertainty estimates 28 . Compared with traditional meta-analysis using linear mixed effect models, MR-BRT relaxes the assumption of a log(linear) relationship between exposure and risk, incorporates between-study heterogeneity into the uncertainty of risk estimates, handles estimates reported across different exposure categories, automatically identifies and trims outliers, and systematically tests and adjusts for bias due to study designs and characteristics. The meta-analytic methods employed by the present study followed the six main steps proposed by Zheng et al. 28 , 29 , namely: (1) enacting a systematic review approach and data extraction following a pre-specified and standardized protocol; (2) estimating the shape of the relationship between exposure and RR; (3) evaluating and adjusting for systematic bias as a function of study characteristics and risk estimation; (4) quantifying between-study heterogeneity while adjusting for within-study correlation and the number of studies; (5) evaluating potential publication or reporting biases; and (6) estimating the mean risk function and the BPRF, calculating the ROS and categorizing smoking–outcome pairs using a star-rating scheme from 1 to 5.

The estimates for our primary indicators of this work—mean RRs across a range of exposures, BRPFs, ROSs and star ratings for each risk–outcome pair—are not specific to or disaggregated by specific populations. We did not estimate RRs separately for different locations, sexes (although the RR of prostate cancer was estimated only for males and of cervical and breast cancer only for females) or age groups (although this analysis was applied to disease endpoints in adults aged ≥30 years only and, as detailed below, age-specific estimates were produced for the five CVD outcomes).

The present study complies with the PRISMA guidelines 190 (Supplementary Tables 9 and 10 and Supplementary Information 1.5 ) and Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) recommendations 191 (Supplementary Table 11 ). The study was approved by the University of Washington Institutional Review Board (study no. 9060). The systematic review approach was not registered.

Selecting health outcomes

In the present study, current smoking is defined as the current use of any smoked tobacco product on a daily or occasional basis. Health outcomes were initially selected using the World Cancer Research Fund criteria for convincing or probable evidence as described in Murray et al. 186 . The 36 health outcomes that were selected based on existing evidence of a relationship included 16 cancers (lung cancer, esophageal cancer, stomach cancer, leukemia, liver cancer, laryngeal cancer, breast cancer, cervical cancer, colorectal cancer, lip and oral cavity cancer, nasopharyngeal cancer, other pharynx cancer (excluding nasopharynx cancer), pancreatic cancer, bladder cancer, kidney cancer and prostate cancer), 5 CVDs (ischemic heart disease, stroke, atrial fibrillation and flutter, aortic aneurysm and peripheral artery disease) and 15 other diseases (COPD, lower respiratory tract infections, tuberculosis, asthma, type 2 diabetes, Alzheimer’s disease and related dementias, Parkinson’s disease, multiple sclerosis, cataracts, gallbladder diseases, low back pain, peptic ulcer disease, rheumatoid arthritis, macular degeneration and fracture). Definitions of the outcomes are described in Supplementary Table 1 .

Step 1: systematic review approach to literature search and data extraction

Informed by the systematic review approach we took for the GBD 2019 (ref. 30 ), for the present study we identified input studies in the literature using a systematic review approach for all 36 smoking–outcome pairs using updated search strings to identify all relevant studies indexed in PubMed up to 31 May 2022 and extracted data on smoking risk estimates. Briefly, the studies that were extracted represented several types of study design (for example, cohort and case–control studies), measured exposure in several different ways and varied in their choice of reference categories (where some compared current smokers with never smokers, whereas others compared current smokers with nonsmokers or former smokers). All these study characteristics were catalogued systematically and taken into consideration during the modeling part of the analysis.

In addition, for CVD outcomes, we also estimated the age pattern of risk associated with smoking. We applied a systematic review of literature approach for smoking risk for the five CVD outcomes. We developed a search string to search for studies reporting any association between binary smoking status (that is, current, former and ever smokers) and the five CVD outcomes from 1 January 1970 to 31 May 2022, and included only studies reporting age-specific risk (RR, odds ratio (OR), hazard ratio (HR)) of smoking status. The inclusion criteria and results of the systematic review approach are reported in accordance with PRISMA guidelines 31 . Details for each outcome on the search string used in the systematic review approach, refined inclusion and exclusion criteria, data extraction template and PRISMA diagram are given in Supplementary Information 1 . Title and/or abstract screening, full text screening and data extraction were conducted by 14 members of the research team and extracted data underwent manual quality assurance by the research team to verify accuracy.

Selecting exposure categories

Cumulative exposure in pack-years was the measure of exposure used for COPD and all cancer outcomes except for prostate cancer, to reflect the risk of both duration and intensity of current smoking on these outcomes. For prostate cancer, CVDs and all the other outcomes except for fractures, we used cigarette-equivalents smoked per day as the exposure for current smoking, because smoking intensity is generally thought to be more important than duration for these outcomes. For fractures, we used binary exposure, because there were few studies examining intensity or duration of smoking on fractures. The smoking–outcome pairs and the corresponding exposures are summarized in Supplementary Table 4 and are congruent with the GBD 2019 (refs. 30 , 186 ).

Steps 2–5: modeling dose–response RR of smoking on the selected health outcomes

Of the six steps proposed by Zheng et al. 29 , steps 2–5 cover the process of modeling dose–response risk curves. In step 2, we estimated the shape (or the ‘signal’) of the dose–response risk curves, integrating over different exposure ranges. To relax the log(linear) assumption usually applied to continuous dose–response risk and make the estimates robust to the placement of spline knots, we used an ensemble spline approach to fit the functional form of the dose–response relationship. The final ensemble model was a weighted combination of 50 models with random knot placement, with the weight of each model proportional to measures of model fit and total variation. To avoid the influence of extreme data and reduce publication bias, we trimmed 10% of data for each outcome as outliers. We also applied a monotonicity constraint to ensure that the mean risk curves were nondecreasing (or nonincreasing in the case of Parkinson’s disease).

In step 3, following the GRADE approach 192 , 193 , we quantified risk of bias across six domains, namely, representativeness of the study population, exposure, outcome, reverse causation, control for confounding and selection bias. Details about the bias covariates are provided in Supplementary Table 4 . We systematically tested for the effect of bias covariates using metaregression, selected significant bias covariates using the Lasso approach 194 , 195 and adjusted for the selected bias covariates in the final risk curve.

In step 4, we quantified between-study heterogeneity accounting for within-study correlation, uncertainty of the heterogeneity, as well as small number of studies. Specifically, we used a random intercept in the mixed-effects model to account for the within-study correlation and used a study-specific random slope with respect to the ‘signal’ to capture between-study heterogeneity. As between-study heterogeneity can be underestimated or even zero when the number of studies is small 196 , 197 , we used Fisher’s information matrix to estimate the uncertainty of the heterogeneity 198 and incorporated that uncertainty into the final results.

In step 5, in addition to generating funnel plots and visually inspecting for asymmetry (Figs. 1c , 2c , 3c and 4c and Extended Data Fig. 6c ) to identify potential publication bias, we also statistically tested for potential publication or reporting bias using Egger’s regression 199 . We flagged potential publication bias in the data but did not correct for it, which is in line with the general literature 10 , 200 , 201 . Full details about the modeling process have been published elsewhere 29 and model specifications for each outcome are in Supplementary Table 6 .

Step 6: estimating the mean risk function and the BPRF

In the final step, step 6, the metaregression model inclusive of the selected bias covariates from step 3 (for example, the highest adjustment level) was used to predict the mean risk function and its 95% UI, which incorporated the uncertainty of the mean effect, between-study heterogeneity and the uncertainty in the heterogeneity estimate accounting for small numbers of studies. Specifically, 1,000 draws were created for each 0.1 level of doses from 0 pack-years to 100 pack-years or cigarette-equivalents smoked per day using the Bayesian metaregression model. The mean of the 1,000 draws was used to estimate the mean risk at each exposure level, and the 25th and 95th draws were used to estimate the 95% UIs for the mean risk at each exposure level.

The BPRF 29 is a conservative estimate of risk function consistent with the available evidence, correcting for both between-study heterogeneity and systemic biases related to study characteristics. The BPRF is defined as either the 5th (if harmful) or 95th (if protective) quantile curve closest to the line of log(RR) of 0, which defines the null (Figs. 1a , 2b , 3a and 4a ). The BPRF represents the smallest harmful (or protective) effect of smoking on the corresponding outcome at each level of exposure that is consistent with the available evidence. A BPRF opposite null from the mean risk function indicates that insufficient evidence is available to reject null, that is, that there may not be an association between risk and outcome. Likewise, the further the BPRF is from null on the same side of null as the mean risk function, the higher the magnitude and evidence for the relationship. The BPRF can be interpreted as indicating that, even accounting for between-study heterogeneity and its uncertainty, the log(RR) across the studied smoking range is at least as high as the BPRF (or at least as low as the BPRF for a protective risk).

To quantify the strength of the evidence, we calculated the ROS for each smoking–outcome association as the signed value of the log(BPRF) averaged between the 15th and 85th percentiles of observed exposure levels for each outcome. The ROS is a single summary of the effect of smoking on the outcome, with higher positive ROSs corresponding to stronger and more consistent evidence and a higher average effect size of smoking and a negative ROS, suggesting that, based on the available evidence, there is no significant effect of smoking on the outcome after accounting for between-study heterogeneity.

For ease of communication, we further classified each smoking–outcome association into a star rating from 1 to 5. Briefly, 1-star associations have an ROS <0, indicating that there is insufficient evidence to find a significant association between smoking and the selected outcome. We divided the positive ROSs into ranges 0.0–0.14 (2-star), >0.14–0.41 (3-star), >0.41–0.62 (4-star) and >0.62 (5-star). These categories correspond to excess risk ranges for harmful risks of 0–15%, >15–50%, >50–85% and >85%. For protective risks, the ranges of exposure-averaged decreases in risk by star rating are 0–13% (2 stars), >13–34% (3 stars), >34–46% (4 stars) and >46% (5 stars).

Among the 36 smoking–outcome pairs analyzed, smoking fracture was the only binary risk–outcome pair, which was due to limited data on the dose–response risk of smoking on fracture 202 . The estimation of binary risk was simplified because the RR was merely a comparison between current smokers and nonsmokers or never smokers. The concept of ROS for continuous risk can naturally extend to binary risk because the BPRF is still defined as the 5th percentile of the effect size accounting for data uncertainty and between-study heterogeneity. However, binary ROSs must be divided by 2 to make them comparable with continuous ROSs, which were calculated by averaging the risk over the range between the 15th and the 85th percentiles of observed exposure levels. Full details about estimating mean risk functions, BPRFs and ROSs for both continuous and binary risk–outcome pairs can be found elsewhere 29 .

Estimating the age-specific risk function for CVD outcomes

For non-CVD outcomes, we assumed that the risk function was the same for all ages and all sexes, except for breast, cervical and prostate cancer, which were assumed to apply only to females or males, respectively. As the risk of smoking on CVD outcomes is known to attenuate with increasing age 203 , 204 , 205 , 206 , we adopted a four-step approach for GBD 2020 to produce age-specific dose–response risk curves for CVD outcomes.

First, we estimated the reference dose–response risk of smoking for each CVD outcome using dose-specific RR data for each outcome regardless of the age group information. This step was identical to that implemented for the other non-CVD outcomes. Once we had generated the reference curve, we determined the age group associated with it by calculating the weighted mean age across all dose-specific RR data (weighted by the reciprocal of the s.e.m. of each datum). For example, if the weighted mean age of all dose-specific RR data was 56.5, we estimated the age group associated with the reference risk curve to be aged 55–59 years. For cohort studies, the age range associated with the RR estimate was calculated as a mean age at baseline plus the mean/median years of follow-up (if only the maximum years of follow-up were reported, we would halve this value and add it to the mean age at baseline). For case–control studies, the age range associated with the OR estimate was simply the reported mean age at baseline (if mean age was not reported, we used the midpoint of the age range instead).

In the third step, we extracted age group-specific RR data and relevant bias covariates from the studies identified in our systematic review approach of age-specific smoking risk on CVD outcomes, and used MR-BRT to model the age pattern of excess risk (that is, RR-1) of smoking on CVD outcomes with age group-specific excess RR data for all CVD outcomes. We modeled the age pattern of smoking risk on CVDs following the same steps we implemented for modeling dose–response risk curves. In the final model, we included a spline on age, random slope on age by study and the bias covariate encoding exposure definition (that is, current, former and ever smokers), which was picked by the variable selection algorithm 28 , 29 . When predicting the age pattern of the excess risk of smoking on CVD outcomes using the fitted model, we did not include between-study heterogeneity to reduce uncertainty in the prediction.

In the fourth step, we calculated the age attenuation factors of excess risk compared with the reference age group for each CVD outcome as the ratio of the estimated excess risk for each age group to the excess risk for the reference age group. We performed the calculation at the draw level to obtain 1,000 draws of the age attenuation factors for each age group. Once we had estimated the age attenuation factors, we carried out the last step, which consisted of adjusting the risk curve for the reference age group from step 1 using equation (1) to produce the age group-specific risk curves for each CVD outcome:

We implemented the age adjustment at the draw level so that the uncertainty of the age attenuation factors could be naturally incorporated into the final adjusted age-specific RR curves. A PRISMA diagram detailing the systematic review approach, a description of the studies included and the full details about the methods are in Supplementary Information 1.5 and 5.2 .

Estimating the theoretical minimum risk exposure level

The theoretical minimum risk exposure level for smoking was 0, that is, no individuals in the population are current or former smokers.

Model validation

The validity of the meta-analytic tool has been extensively evaluated by Zheng and colleagues using simulation experiments 28 , 29 . For the present study, we conducted two additional sensitivity analyses to examine how the shape of the risk curves was impacted by applying a monotonicity constraint and trimming 10% of data. We present the results of these sensitivity analyses in Supplementary Information 6 . In addition to the sensitivity analyses, the dose–response risk estimates were also validated by plotting the mean risk function along with its 95% UI against both the extracted dose-specific RR data from the studies included and our previous dose–response risk estimates from the GBD 2019 (ref. 30 ). The mean risk functions along with the 95% UIs were validated based on data fit and the level, shape and plausibility of the dose–response risk curves. All curves were validated by all authors and reviewed by an external expert panel, comprising professors with relevant experience from universities including Johns Hopkins University, Karolinska Institute and University of Barcelona; senior scientists working in relevant departments at the WHO and the Center for Disease Control and Prevention (CDC) and directors of nongovernmental organizations such as the Campaign for Tobacco-Free Kids.

Statistical analysis

Analyses were carried out using R v.3.6.3, Python v.3.8 and Stata v.16.

Statistics and reproducibility

The study was a secondary analysis of existing data involving systematic reviews and meta-analyses. No statistical method was used to predetermine sample size. As the study did not involve primary data collection, randomization and blinding, data exclusions were not relevant to the present study, and, as such, no data were excluded and we performed no randomization or blinding. We have made our data and code available to foster reproducibility.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

The findings from the present study are supported by data available in the published literature. Data sources and citations for each risk–outcome pair can be downloaded using the ‘download’ button on each risk curve page currently available at https://vizhub.healthdata.org/burden-of-proof . Study characteristics and citations for all input data used in the analyses are also provided in Supplementary Table 3 , and Supplementary Table 2 provides a template of the data collection form.

Code availability

All code used for these analyses is publicly available online ( https://github.com/ihmeuw-msca/burden-of-proof ).

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Acknowledgements

Research reported in this publication was supported by the Bill & Melinda Gates Foundation and Bloomberg Philanthropies. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders. The study funders had no role in study design, data collection, data analysis, data interpretation, writing of the final report or the decision to publish.

We thank the Tobacco Metrics Team Advisory Group for their valuable input and review of the work. The members of the Advisory Group are: P. Allebeck, R. Chandora, J. Drope, M. Eriksen, E. Fernández, H. Gouda, R. Kennedy, D. McGoldrick, L. Pan, K. Schotte, E. Sebrie, J. Soriano, M. Tynan and K. Welding.

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Xiaochen Dai, Gabriela F. Gil, Marissa B. Reitsma, Noah S. Ahmad, Jason A. Anderson, Catherine Bisignano, Sinclair Carr, Rachel Feldman, Simon I. Hay, Jiawei He, Vincent Iannucci, Hilary R. Lawlor, Matthew J. Malloy, Laurie B. Marczak, Susan A. McLaughlin, Larissa Morikawa, Erin C. Mullany, Sneha I. Nicholson, Erin M. O’Connell, Chukwuma Okereke, Reed J. D. Sorensen, Joanna Whisnant, Aleksandr Y. Aravkin, Peng Zheng, Christopher J. L. Murray & Emmanuela Gakidou

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X.D., S.I.H., S.A.M., E.C.M., E.M.O., C.J.L.M. and E.G. managed the estimation or publications process. X.D. and G.F.G. wrote the first draft of the manuscript. X.D. and P.Z. had primary responsibility for applying analytical methods to produce estimates. X.D., G.F.G., N.S.A., J.A.A., S.C., R.F., V.I., M.J.M., L.M., S.I.N., C.O., M.B.R. and J.W. had primary responsibility for seeking, cataloguing, extracting or cleaning data, and for designing or coding figures and tables. X.D., G.F.G., M.B.R., N.S.A., H.R.L., C.O. and J.W. provided data or critical feedback on data sources. X.D., J.H., R.J.D.S., A.Y.A., P.Z., C.J.L.M. and E.G. developed methods or computational machinery. X.D., G.F.G., M.B.R., S.I.H., J.H., R.J.D.S., A.Y.A., P.Z., C.J.L.M. and E.G. provided critical feedback on methods or results. X.D., G.F.G., M.B.R., C.B., S.I.H., L.B.M., S.A.M., A.Y.A. and E.G. drafted the work or revised it critically for important intellectual content. X.D., S.I.H., L.B.M., E.C.M., E.M.O. and E.G. managed the overall research enterprise.

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Extended data

Extended data fig. 1 prisma 2020 flow diagram for an updated systematic review of the smoking and tracheal, bronchus, and lung cancer risk-outcome pair..

The PRISMA flow diagram of an updated systematic review on the relationship between smoking and lung cancer conducted on PubMed to update historical review from previous cycles of the Global Burden of Disease Study. Template is from: Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. doi: 10.1136/bmj.n71. For more information, visit: http://www.prisma-statement.org/ .

Extended Data Fig. 2 PRISMA 2020 flow diagram for an updated systematic review of the Smoking and Chronic obstructive pulmonary disease risk-outcome pair.

The PRISMA flow diagram of an updated systematic review on the relationship between smoking and chronic obstructive pulmonary disease conducted on PubMed to update historical review from previous cycles of the Global Burden of Disease Study. Template is from: Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. doi: 10.1136/bmj.n71. For more information, visit: http://www.prisma-statement.org/ .

Extended Data Fig. 3 PRISMA 2020 flow diagram for an updated systematic review of the Smoking and Diabetes mellitus type 2 risk- outcome pair.

The PRISMA flow diagram of an updated systematic review on the relationship between smoking and type 2 diabetes conducted on PubMed to update historical review from previous cycles of the Global Burden of Disease Study. Template is from: Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. doi: 10.1136/bmj.n71. For more information, visit: http://www.prisma-statement.org/ .

Extended Data Fig. 4 PRISMA 2020 flow diagram for an updated systematic review of the Smoking and Breast cancer risk-outcome pair.

The PRISMA flow diagram of an updated systematic review on the relationship between smoking and breast cancer conducted on PubMed to update historical review from previous cycles of the Global Burden of Disease Study. Template is from: Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. doi: 10.1136/bmj.n71. For more information, visit: http://www.prisma-statement.org/ .

Extended Data Fig. 5 PRISMA 2020 flow diagram for an updated systematic review of the Smoking and Prostate cancer risk-outcome pair.

The PRISMA flow diagram of an updated systematic review on the relationship between smoking and prostate cancer conducted on PubMed to update historical review from previous cycles of the Global Burden of Disease Study. Template is from: Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. doi: 10.1136/bmj.n71. For more information, visit: http://www.prisma-statement.org/ .

Extended Data Fig. 6 Smoking and Breast Cancer.

a , log-relative risk function. b , relative risk function. c , A modified funnel plot showing the residuals (relative to 0) on the x-axis and the estimated standard deviation (SD) that includes reported SD and between-study heterogeneity on the y-axis.

Supplementary information

Supplementary information.

Supplementary Information 1: Data source identification and assessment. Supplementary Information 2: Data inputs. Supplementary Information 3: Study quality and bias assessment. Supplementary Information 4: The dose–response RR curves and their 95% UIs for all smoking–outcome pairs. Supplementary Information 5: Supplementary methods. Supplementary Information 6: Sensitivity analysis. Supplementary Information 7: Binary smoking–outcome pair. Supplementary Information 8: Risk curve details. Supplementary Information 9: GATHER and PRISMA checklists.

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Dai, X., Gil, G.F., Reitsma, M.B. et al. Health effects associated with smoking: a Burden of Proof study. Nat Med 28 , 2045–2055 (2022). https://doi.org/10.1038/s41591-022-01978-x

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Persuasive Essay About Smoking

Persuasive Essay About Smoking - Making a Powerful Argument with Examples

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Are you wondering how to write your next persuasive essay about smoking?

Smoking has been one of the most controversial topics in our society for years. It is associated with many health risks and can be seen as a danger to both individuals and communities.

Writing an effective persuasive essay about smoking can help sway public opinion. It can also encourage people to make healthier choices and stop smoking. 

But where do you begin?

In this blog, we’ll provide some examples to get you started. So read on to get inspired!

• 1. What You Need To Know About Persuasive Essay
• 2. Persuasive Essay Examples About Smoking
• 3. Argumentative Essay About Smoking Examples
• 4. Tips for Writing a Persuasive Essay About Smoking

What You Need To Know About Persuasive Essay

A persuasive essay is a type of writing that aims to convince its readers to take a certain stance or action. It often uses logical arguments and evidence to back up its argument in order to persuade readers.

It also utilizes rhetorical techniques such as ethos, pathos, and logos to make the argument more convincing. In other words, persuasive essays use facts and evidence as well as emotion to make their points.

A persuasive essay about smoking would use these techniques to convince its readers about any point about smoking. Check out an example below:

Simple persuasive essay about smoking

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Persuasive Essay Examples About Smoking

Smoking is one of the leading causes of preventable death in the world. It leads to adverse health effects, including lung cancer, heart disease, and damage to the respiratory tract. However, the number of people who smoke cigarettes has been on the rise globally.

A lot has been written on topics related to the effects of smoking. Reading essays about it can help you get an idea of what makes a good persuasive essay.

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Persuasive speech on smoking outline

Persuasive essay about smoking should be banned

Persuasive essay about smoking pdf

Persuasive essay about smoking cannot relieve stress

Persuasive essay about smoking in public places

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Persuasive Essay About Smoking Introduction

Persuasive Essay About Stop Smoking

Short Persuasive Essay About Smoking

Stop Smoking Persuasive Speech

Check out some more persuasive essay examples on various other topics.

Argumentative Essay About Smoking Examples

An argumentative essay is a type of essay that uses facts and logical arguments to back up a point. It is similar to a persuasive essay but differs in that it utilizes more evidence than emotion.

If you’re looking to write an argumentative essay about smoking, here are some examples to get you started on the arguments of why you should not smoke.

Argumentative essay about smoking pdf

Argumentative essay about smoking in public places

Argumentative essay about smoking introduction

Check out the video below to find useful arguments against smoking:

Tips for Writing a Persuasive Essay About Smoking

You have read some examples of persuasive and argumentative essays about smoking. Now here are some tips that will help you craft a powerful essay on this topic.

Choose a Specific Angle

Select a particular perspective on the issue that you can use to form your argument. When talking about smoking, you can focus on any aspect such as the health risks, economic costs, or environmental impact.

Think about how you want to approach the topic. For instance, you could write about why smoking should be banned. 

Check out the list of persuasive essay topics to help you while you are thinking of an angle to choose!

Research the Facts

Before writing your essay, make sure to research the facts about smoking. This will give you reliable information to use in your arguments and evidence for why people should avoid smoking.

You can find and use credible data and information from reputable sources such as government websites, health organizations, and scientific studies. 

For instance, you should gather facts about health issues and negative effects of tobacco if arguing against smoking. Moreover, you should use and cite sources carefully.

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Make an Outline

The next step is to create an outline for your essay. This will help you organize your thoughts and make sure that all the points in your essay flow together logically.

Your outline should include the introduction, body paragraphs, and conclusion. This will help ensure that your essay has a clear structure and argument.

Use Persuasive Language

When writing your essay, make sure to use persuasive language such as “it is necessary” or “people must be aware”. This will help you convey your message more effectively and emphasize the importance of your point.

Also, don’t forget to use rhetorical devices such as ethos, pathos, and logos to make your arguments more convincing. That is, you should incorporate emotion, personal experience, and logic into your arguments.

Introduce Opposing Arguments

Another important tip when writing a persuasive essay on smoking is to introduce opposing arguments. It will show that you are aware of the counterarguments and can provide evidence to refute them. This will help you strengthen your argument.

By doing this, your essay will come off as more balanced and objective, making it more convincing.

Finish Strong

Finally, make sure to finish your essay with a powerful conclusion. This will help you leave a lasting impression on your readers and reinforce the main points of your argument. You can end by summarizing the key points or giving some advice to the reader.

A powerful conclusion could either include food for thought or a call to action. So be sure to use persuasive language and make your conclusion strong.

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Office on Smoking and Health (US). The Health Consequences of Involuntary Exposure to Tobacco Smoke: A Report of the Surgeon General. Atlanta (GA): Centers for Disease Control and Prevention (US); 2006.

The Health Consequences of Involuntary Exposure to Tobacco Smoke: A Report of the Surgeon General.

1 introduction, summary, and conclusions.

• Introduction

The topic of passive or involuntary smoking was first addressed in the 1972 U.S. Surgeon General’s report ( The Health Consequences of Smoking , U.S. Department of Health, Education, and Welfare [USDHEW] 1972 ), only eight years after the first Surgeon General’s report on the health consequences of active smoking ( USDHEW 1964 ). Surgeon General Dr. Jesse Steinfeld had raised concerns about this topic, leading to its inclusion in that report. According to the 1972 report, nonsmokers inhale the mixture of sidestream smoke given off by a smoldering cigarette and mainstream smoke exhaled by a smoker, a mixture now referred to as “secondhand smoke” or “environmental tobacco smoke.” Cited experimental studies showed that smoking in enclosed spaces could lead to high levels of cigarette smoke components in the air. For carbon monoxide ( CO ) specifically, levels in enclosed spaces could exceed levels then permitted in outdoor air. The studies supported a conclusion that “an atmosphere contaminated with tobacco smoke can contribute to the discomfort of many individuals” ( USDHEW 1972 , p. 7). The possibility that CO emitted from cigarettes could harm persons with chronic heart or lung disease was also mentioned.

Secondhand tobacco smoke was then addressed in greater depth in Chapter 4 (Involuntary Smoking) of the 1975 Surgeon General’s report, The Health Consequences of Smoking ( USDHEW 1975 ). The chapter noted that involuntary smoking takes place when nonsmokers inhale both sidestream and exhaled mainstream smoke and that this “smoking” is “involuntary” when “the exposure occurs as an unavoidable consequence of breathing in a smoke-filled environment” (p. 87). The report covered exposures and potential health consequences of involuntary smoking, and the researchers concluded that smoking on buses and airplanes was annoying to nonsmokers and that involuntary smoking had potentially adverse consequences for persons with heart and lung diseases. Two studies on nicotine concentrations in nonsmokers raised concerns about nicotine as a contributing factor to atherosclerotic cardiovascular disease in nonsmokers.

The 1979 Surgeon General’s report, Smoking and Health: A Report of the Surgeon General ( USDHEW 1979 ), also contained a chapter entitled “Involuntary Smoking.” The chapter stressed that “attention to involuntary smoking is of recent vintage, and only limited information regarding the health effects of such exposure upon the nonsmoker is available” (p. 11–35). The chapter concluded with recommendations for research including epidemiologic and clinical studies. The 1982 Surgeon General’s report specifically addressed smoking and cancer ( U.S. Department of Health and Human Services [USDHHS] 1982 ). By 1982, there were three published epidemiologic studies on involuntary smoking and lung cancer, and the 1982 Surgeon General’s report included a brief chapter on this topic. That chapter commented on the methodologic difficulties inherent in such studies, including exposure assessment, the lengthy interval during which exposures are likely to be relevant, and accounting for exposures to other carcinogens. Nonetheless, the report concluded that “Although the currently available evidence is not sufficient to conclude that passive or involuntary smoking causes lung cancer in nonsmokers, the evidence does raise concern about a possible serious public health problem” (p. 251).

Involuntary smoking was also reviewed in the 1984 report, which focused on chronic obstructive pulmonary disease and smoking ( USDHHS 1984 ). Chapter 7 (Passive Smoking) of that report included a comprehensive review of the mounting information on smoking by parents and the effects on respiratory health of their children, data on irritation of the eye, and the more limited evidence on pulmonary effects of involuntary smoking on adults. The chapter began with a compilation of measurements of tobacco smoke components in various indoor environments. The extent of the data had increased substantially since 1972. By 1984, the data included measurements of more specific indicators such as acrolein and nicotine, and less specific indicators such as particulate matter ( PM ), nitrogen oxides, and CO . The report reviewed new evidence on exposures of nonsmokers using bio-markers, with substantial information on levels of cotinine, a major nicotine metabolite. The report anticipated future conclusions with regard to respiratory effects of parental smoking on child respiratory health ( Table 1.1 ).

Conclusions from previous Surgeon General’s reports on the health effects of secondhand smoke exposure

Involuntary smoking was the topic for the entire 1986 Surgeon General’s report, The Health Consequences of Involuntary Smoking ( USDHHS 1986 ). In its 359 pages, the report covered the full breadth of the topic, addressing toxicology and dosimetry of tobacco smoke; the relevant evidence on active smoking; patterns of exposure of nonsmokers to tobacco smoke; the epidemiologic evidence on involuntary smoking and disease risks for infants, children, and adults; and policies to control involuntary exposure to tobacco smoke. That report concluded that involuntary smoking caused lung cancer in lifetime nonsmoking adults and was associated with adverse effects on respiratory health in children. The report also stated that simply separating smokers and nonsmokers within the same airspace reduced but did not eliminate exposure to secondhand smoke. All of these findings are relevant to public health and public policy ( Table 1.1 ). The lung cancer conclusion was based on extensive information already available on the carcinogenicity of active smoking, the qualitative similarities between secondhand and mainstream smoke, the uptake of tobacco smoke components by nonsmokers, and the epidemiologic data on involuntary smoking. The three major conclusions of the report ( Table 1.2 ), led Dr. C. Everett Koop, Surgeon General at the time, to comment in his preface that “the right of smokers to smoke ends where their behavior affects the health and well-being of others; furthermore, it is the smokers’ responsibility to ensure that they do not expose nonsmokers to the potential [ sic ] harmful effects of tobacco smoke” ( USDHHS 1986 , p. xii).

Major conclusions of the 1986 Surgeon General’s report, The Health Consequences of Involuntary Smoking

Two other reports published in 1986 also reached the conclusion that involuntary smoking increased the risk for lung cancer. The International Agency for Research on Cancer ( IARC ) of the World Health Organization concluded that “passive smoking gives rise to some risk of cancer” ( IARC 1986 , p. 314). In its monograph on tobacco smoking, the agency supported this conclusion on the basis of the characteristics of sidestream and mainstream smoke, the absorption of tobacco smoke materials during an involuntary exposure, and the nature of dose-response relationships for carcinogenesis. In the same year, the National Research Council ( NRC ) also concluded that involuntary smoking increases the incidence of lung cancer in nonsmokers ( NRC 1986 ). In reaching this conclusion, the NRC report cited the biologic plausibility of the association between exposure to secondhand smoke and lung cancer and the supporting epidemiologic evidence. On the basis of a pooled analysis of the epidemiologic data adjusted for bias, the report concluded that the best estimate for the excess risk of lung cancer in nonsmokers married to smokers was 25 percent, compared with nonsmokers married to nonsmokers. With regard to the effects of involuntary smoking on children, the NRC report commented on the literature linking secondhand smoke exposures from parental smoking to increased risks for respiratory symptoms and infections and to a slightly diminished rate of lung growth.

Since 1986, the conclusions with regard to both the carcinogenicity of secondhand smoke and the adverse effects of parental smoking on the health of children have been echoed and expanded ( Table 1.3 ). In 1992, the U.S. Environmental Protection Agency ( EPA ) published its risk assessment of secondhand smoke as a carcinogen ( USEPA 1992 ). The agency’s evaluation drew on toxicologic information on secondhand smoke and the extensive literature on active smoking. A comprehensive meta-analysis of the 31 epidemiologic studies of secondhand smoke and lung cancer published up to that time was central to the decision to classify secondhand smoke as a group A carcinogen—namely, a known human carcinogen. Estimates of approximately 3,000 U.S. lung cancer deaths per year in non-smokers were attributed to secondhand smoke. The report also covered other respiratory health effects in children and adults and concluded that involuntary smoking is causally associated with several adverse respiratory effects in children. There was also a quantitative risk assessment for the impact of involuntary smoking on childhood asthma and lower respiratory tract infections in young children.

Selected major reports, other than those of the U.S. Surgeon General, addressing adverse effects from exposure to tobacco smoke

In the decade since the 1992 EPA report, scientific panels continued to evaluate the mounting evidence linking involuntary smoking to adverse health effects ( Table 1.3 ). The most recent was the 2005 report of the California EPA ( Cal/EPA 2005 ). Over time, research has repeatedly affirmed the conclusions of the 1986 Surgeon General’s reports and studies have further identified causal associations of involuntary smoking with diseases and other health disorders. The epidemiologic evidence on involuntary smoking has markedly expanded since 1986, as have the data on exposure to tobacco smoke in the many environments where people spend time. An understanding of the mechanisms by which involuntary smoking causes disease has also deepened.

As part of the environmental health hazard assessment, Cal/EPA identified specific health effects causally associated with exposure to secondhand smoke. The agency estimated the annual excess deaths in the United States that are attributable to secondhand smoke exposure for specific disorders: sudden infant death syndrome ( SIDS ), cardiac-related illnesses (ischemic heart disease), and lung cancer ( Cal/EPA 2005 ). For the excess incidence of other health outcomes, either new estimates were provided or estimates from the 1997 health hazard assessment were used without any revisions ( Cal/EPA 1997 ). Overall, Cal/EPA estimated that about 50,000 excess deaths result annually from exposure to secondhand smoke ( Cal/EPA 2005 ). Estimated annual excess deaths for the total U.S. population are about 3,400 (a range of 3,423 to 8,866) from lung cancer, 46,000 (a range of 22,700 to 69,600) from cardiac-related illnesses, and 430 from SIDS. The agency also estimated that between 24,300 and 71,900 low birth weight or pre-term deliveries, about 202,300 episodes of childhood asthma (new cases and exacerbations), between 150,000 and 300,000 cases of lower respiratory illness in children, and about 789,700 cases of middle ear infections in children occur each year in the United States as a result of exposure to secondhand smoke.

This new 2006 Surgeon General’s report returns to the topic of involuntary smoking. The health effects of involuntary smoking have not received comprehensive coverage in this series of reports since 1986. Reports since then have touched on selected aspects of the topic: the 1994 report on tobacco use among young people ( USDHHS 1994 ), the 1998 report on tobacco use among U.S. racial and ethnic minorities ( USDHHS 1998 ), and the 2001 report on women and smoking ( USDHHS 2001 ). As involuntary smoking remains widespread in the United States and elsewhere, the preparation of this report was motivated by the persistence of involuntary smoking as a public health problem and the need to evaluate the substantial new evidence reported since 1986. This report substantially expands the list of topics that were included in the 1986 report. Additional topics include SIDS , developmental effects, and other reproductive effects; heart disease in adults; and cancer sites beyond the lung. For some associations of involuntary smoking with adverse health effects, only a few studies were reviewed in 1986 (e. g ., ear disease in children); now, the relevant literature is substantial. Consequently, this report uses meta-analysis to quantitatively summarize evidence as appropriate. Following the approach used in the 2004 report ( The Health Consequences of Smoking , USDHHS 2004 ), this 2006 report also systematically evaluates the evidence for causality, judging the extent of the evidence available and then making an inference as to the nature of the association.

Organization of the Report

This twenty-ninth report of the Surgeon General examines the topics of toxicology of secondhand smoke, assessment and prevalence of exposure to secondhand smoke, reproductive and developmental health effects, respiratory effects of exposure to secondhand smoke in children and adults, cancer among adults, cardiovascular diseases, and the control of secondhand smoke exposure.

This introductory chapter (Chapter 1) includes a discussion of the concept of causation and introduces concepts of causality that are used throughout this report; this chapter also summarizes the major conclusions of the report. Chapter 2 (Toxicology of Secondhand Smoke) sets out a foundation for interpreting the observational evidence that is the focus of most of the following chapters. The discussion details the mechanisms that enable tobacco smoke components to injure the respiratory tract and cause nonmalignant and malignant diseases and other adverse effects. Chapter 3 (Assessment of Exposure to Secondhand Smoke) provides a perspective on key factors that determine exposures of people to secondhand smoke in indoor environments, including building designs and operations, atmospheric markers of secondhand smoke, exposure models, and biomarkers of exposure to secondhand smoke. Chapter 4 (Prevalence of Exposure to Secondhand Smoke) summarizes findings that focus on nicotine measurements in the air and cotinine measurements in biologic materials. The chapter includes exposures in the home, workplace, public places, and special populations. Chapter 5 (Reproductive and Developmental Effects from Exposure to Secondhand Smoke) reviews the health effects on reproduction, on infants, and on child development. Chapter 6 (Respiratory Effects in Children from Exposure to Secondhand Smoke) examines the effects of parental smoking on the respiratory health of children. Chapter 7 (Cancer Among Adults from Exposure to Secondhand Smoke) summarizes the evidence on cancer of the lung, breast, nasal sinuses, and the cervix. Chapter 8 (Cardiovascular Diseases from Exposure to Secondhand Smoke) discusses coronary heart disease ( CHD ), stroke, and subclinical vascular disease. Chapter 9 (Respiratory Effects in Adults from Exposure to Secondhand Smoke) examines odor and irritation, respiratory symptoms, lung function, and respiratory diseases such as asthma and chronic obstructive pulmonary disease. Chapter 10 (Control of Secondhand Smoke Exposure) considers measures used to control exposure to secondhand smoke in public places, including legislation, education, and approaches based on building designs and operations. The report concludes with “A Vision for the Future.” Major conclusions of the report were distilled from the chapter conclusions and appear later in this chapter.

Preparation of the Report

This report of the Surgeon General was prepared by the Office on Smoking and Health, National Center for Chronic Disease Prevention and Health Promotion, Coordinating Center for Health Promotion, Centers for Disease Control and Prevention ( CDC ), and U.S. DHHS. Initial chapters were written by 22 experts who were selected because of their knowledge of a particular topic. The contributions of the initial experts were consolidated into 10 major chapters that were then reviewed by more than 40 peer reviewers. The entire manuscript was then sent to more than 30 scientists and experts who reviewed it for its scientific integrity. After each review cycle, the drafts were revised by the scientific editors on the basis of the experts’ comments. Subsequently, the report was reviewed by various institutes and agencies within U.S. DHHS. Publication lags, even short ones, prevent an up-to-the-minute inclusion of all recently published articles and data. Therefore, by the time the public reads this report, there may be additional published studies or data. To provide published information as current as possible, this report includes an Appendix of more recent studies that represent major additions to the literature.

This report is also accompanied by a companion database of key evidence that is accessible through the Internet ( http://www.cdc.gov/tobacco ). The database includes a uniform description of the studies and results on the health effects of exposure to secondhand smoke that were presented in a format compatible with abstraction into standardized tables. Readers of the report may access these data for additional analyses, tables, or figures.

• Definitions and Terminology

The inhalation of tobacco smoke by nonsmokers has been variably referred to as “passive smoking” or “involuntary smoking.” Smokers, of course, also inhale secondhand smoke. Cigarette smoke contains both particles and gases generated by the combustion at high temperatures of tobacco, paper, and additives. The smoke inhaled by nonsmokers that contaminates indoor spaces and outdoor environments has often been referred to as “secondhand smoke” or “environmental tobacco smoke.” This inhaled smoke is the mixture of sidestream smoke released by the smoldering cigarette and the mainstream smoke that is exhaled by a smoker. Sidestream smoke, generated at lower temperatures and under somewhat different combustion conditions than mainstream smoke, tends to have higher concentrations of many of the toxins found in cigarette smoke ( USDHHS 1986 ). However, it is rapidly diluted as it travels away from the burning cigarette.

Secondhand smoke is an inherently dynamic mixture that changes in characteristics and concentration with the time since it was formed and the distance it has traveled. The smoke particles change in size and composition as gaseous components are volatilized and moisture content changes; gaseous elements of secondhand smoke may be adsorbed onto materials, and particle concentrations drop with both dilution in the air or environment and impaction on surfaces, including the lungs or on the body. Because of its dynamic nature, a specific quantitative definition of secondhand smoke cannot be offered.

This report uses the term secondhand smoke in preference to environmental tobacco smoke, even though the latter may have been used more frequently in previous reports. The descriptor “secondhand” captures the involuntary nature of the exposure, while “environmental” does not. This report also refers to the inhalation of secondhand smoke as involuntary smoking, acknowledging that most nonsmokers do not want to inhale tobacco smoke. The exposure of the fetus to tobacco smoke, whether from active smoking by the mother or from her exposure to secondhand smoke, also constitutes involuntary smoking.

• Evidence Evaluation

Following the model of the 1964 report, the Surgeon General’s reports on smoking have included comprehensive compilations of the evidence on the health effects of smoking. The evidence is analyzed to identify causal associations between smoking and disease according to enunciated principles, sometimes referred to as the “Surgeon General’s criteria” or the “Hill” criteria (after Sir Austin Bradford Hill) for causality ( USDHEW 1964 ; USDHHS 2004 ). Application of these criteria involves covering all relevant observational and experimental evidence. The criteria, offered in a brief chapter of the 1964 report entitled “Criteria for Judgment,” included (1) the consistency of the association, (2) the strength of the association, (3) the specificity of the association, (4) the temporal relationship of the association, and (5) the coherence of the association. Although these criteria have been criticized (e. g ., Rothman and Greenland 1998 ), they have proved useful as a framework for interpreting evidence on smoking and other postulated causes of disease, and for judging whether causality can be inferred.

In the 2004 report of the Surgeon General, The Health Consequences of Smoking , the framework for interpreting evidence on smoking and health was revisited in depth for the first time since the 1964 report ( USDHHS 2004 ). The 2004 report provided a four-level hierarchy for interpreting evidence ( Table 1.4 ). The categories acknowledge that evidence can be “suggestive” but not adequate to infer a causal relationship, and also allows for evidence that is “suggestive of no causal relationship.” Since the 2004 report, the individual chapter conclusions have consistently used this four-level hierarchy ( Table 1.4 ), but evidence syntheses and other summary statements may use either the term “increased risk” or “cause” to describe instances in which there is sufficient evidence to conclude that active or involuntary smoking causes a disease or condition. This four-level framework also sharply and completely separates conclusions regarding causality from the implications of such conclusions.

Four-level hierarchy for classifying the strength of causal inferences based on available evidence

That same framework was used in this report on involuntary smoking and health. The criteria dating back to the 1964 Surgeon General’s report remain useful as guidelines for evaluating evidence ( USDHEW 1964 ), but they were not intended to be applied strictly or as a “checklist” that needed to be met before the designation of “causal” could be applied to an association. In fact, for involuntary smoking and health, several of the criteria will not be met for some associations. Specificity, referring to a unique exposure-disease relationship (e. g ., the association between thalidomide use during pregnancy and unusual birth defects), can be set aside as not relevant, as all of the health effects considered in this report have causes other than involuntary smoking. Associations are considered more likely to be causal as the strength of an association increases because competing explanations become less plausible alternatives. However, based on knowledge of dosimetry and mechanisms of injury and disease causation, the risk is anticipated to be only slightly or modestly increased for some associations of involuntary smoking with disease, such as lung cancer, particularly when the very strong relative risks found for active smokers are compared with those for lifetime nonsmokers. The finding of only a small elevation in risk, as in the example of spousal smoking and lung cancer risk in lifetime nonsmokers, does not weigh against a causal association; however, alternative explanations for a risk of a small magnitude need full exploration and cannot be so easily set aside as alternative explanations for a stronger association. Consistency, coherence, and the temporal relationship of involuntary smoking with disease are central to the interpretations in this report. To address coherence, the report draws not only on the evidence for involuntary smoking, but on the even more extensive literature on active smoking and disease.

Although the evidence reviewed in this report comes largely from investigations of secondhand smoke specifically, the larger body of evidence on active smoking is also relevant to many of the associations that were evaluated. The 1986 report found secondhand smoke to be qualitatively similar to mainstream smoke inhaled by the smoker and concluded that secondhand smoke would be expected to have “a toxic and carcinogenic potential that would not be expected to be qualitatively different from that of MS [mainstream smoke]” ( USDHHS 1986 , p. 23). The 2004 report of the Surgeon General revisited the health consequences of active smoking ( USDHHS 2004 ), and the conclusions substantially expanded the list of diseases and conditions caused by smoking. Chapters in the present report consider the evidence on active smoking that is relevant to biologic plausibility for causal associations between involuntary smoking and disease. The reviews included in this report cover evidence identified through search strategies set out in each chapter. Of necessity, the evidence on mechanisms was selectively reviewed. However, an attempt was made to cover all health studies through specified target dates. Because of the substantial amount of time involved in preparing this report, lists of new key references published after these cut-off dates are included in an Appendix . Literature reviews were extended when new evidence was sufficient to possibly change the level of a causal conclusion.

• Major Conclusions

This report returns to involuntary smoking, the topic of the 1986 Surgeon General’s report. Since then, there have been many advances in the research on secondhand smoke, and substantial evidence has been reported over the ensuing 20 years. This report uses the revised language for causal conclusions that was implemented in the 2004 Surgeon General’s report ( USDHHS 2004 ). Each chapter provides a comprehensive review of the evidence, a quantitative synthesis of the evidence if appropriate, and a rigorous assessment of sources of bias that may affect interpretations of the findings. The reviews in this report reaffirm and strengthen the findings of the 1986 report. With regard to the involuntary exposure of nonsmokers to tobacco smoke, the scientific evidence now supports the following major conclusions:

• Secondhand smoke causes premature death and disease in children and in adults who do not smoke.
• Children exposed to secondhand smoke are at an increased risk for sudden infant death syndrome ( SIDS ), acute respiratory infections, ear problems, and more severe asthma. Smoking by parents causes respiratory symptoms and slows lung growth in their children.
• Exposure of adults to secondhand smoke has immediate adverse effects on the cardiovascular system and causes coronary heart disease and lung cancer.
• The scientific evidence indicates that there is no risk-free level of exposure to secondhand smoke.
• Many millions of Americans, both children and adults, are still exposed to secondhand smoke in their homes and workplaces despite substantial progress in tobacco control.
• Eliminating smoking in indoor spaces fully protects nonsmokers from exposure to secondhand smoke. Separating smokers from nonsmokers, cleaning the air, and ventilating buildings cannot eliminate exposures of nonsmokers to secondhand smoke.
• Chapter Conclusions

Chapter 2 Toxicology of Secondhand Smoke

Evidence of carcinogenic effects from secondhand smoke exposure.

• 1. More than 50 carcinogens have been identified in sidestream and secondhand smoke.
• 2. The evidence is sufficient to infer a causal relationship between exposure to secondhand smoke and its condensates and tumors in laboratory animals.
• 3. The evidence is sufficient to infer that exposure of nonsmokers to secondhand smoke causes a significant increase in urinary levels of metabolites of the tobacco-specific lung carcinogen 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone ( NNK ). The presence of these metabolites links exposure to secondhand smoke with an increased risk for lung cancer.
• 4. The mechanisms by which secondhand smoke causes lung cancer are probably similar to those observed in smokers. The overall risk of secondhand smoke exposure, compared with active smoking, is diminished by a substantially lower carcinogenic dose.

Mechanisms of Respiratory Tract Injury and Disease Caused by Secondhand Smoke Exposure

• 5. The evidence indicates multiple mechanisms by which secondhand smoke exposure causes injury to the respiratory tract.
• 6. The evidence indicates mechanisms by which secondhand smoke exposure could increase the risk for sudden infant death syndrome.

Mechanisms of Secondhand Smoke Exposure and Heart Disease

• 7. The evidence is sufficient to infer that exposure to secondhand smoke has a prothrombotic effect.
• 8. The evidence is sufficient to infer that exposure to secondhand smoke causes endothelial cell dysfunctions.
• 9. The evidence is sufficient to infer that exposure to secondhand smoke causes atherosclerosis in animal models.

Chapter 3. Assessment of Exposure to Secondhand Smoke

Building designs and operations.

• 1. Current heating, ventilating, and air conditioning systems alone cannot control exposure to secondhand smoke.
• 2. The operation of a heating, ventilating, and air conditioning system can distribute secondhand smoke throughout a building.

Exposure Models

• 3. Atmospheric concentration of nicotine is a sensitive and specific indicator for secondhand smoke.
• 4. Smoking increases indoor particle concentrations.
• 5. Models can be used to estimate concentrations of secondhand smoke.

Biomarkers of Exposure to Secondhand Smoke

• 6. Biomarkers suitable for assessing recent exposures to secondhand smoke are available.
• 7. At this time, cotinine, the primary proximate metabolite of nicotine, remains the biomarker of choice for assessing secondhand smoke exposure.
• 8. Individual biomarkers of exposure to secondhand smoke represent only one component of a complex mixture, and measurements of one marker may not wholly reflect an exposure to other components of concern as a result of involuntary smoking.

Chapter 4. Prevalence of Exposure to Secondhand Smoke

• The evidence is sufficient to infer that large numbers of nonsmokers are still exposed to secondhand smoke.
• Exposure of nonsmokers to secondhand smoke has declined in the United States since the 1986 Surgeon General’s report, The Health Consequences of Involuntary Smoking .
• The evidence indicates that the extent of secondhand smoke exposure varies across the country.
• Homes and workplaces are the predominant locations for exposure to secondhand smoke.
• Exposure to secondhand smoke tends to be greater for persons with lower incomes.
• Exposure to secondhand smoke continues in restaurants, bars, casinos, gaming halls, and vehicles.

Chapter 5. Reproductive and Developmental Effects from Exposure to Secondhand Smoke

• 1. The evidence is inadequate to infer the presence or absence of a causal relationship between maternal exposure to secondhand smoke and female fertility or fecundability. No data were found on paternal exposure to secondhand smoke and male fertility or fecundability.

Pregnancy (Spontaneous Abortion and Perinatal Death)

• 2. The evidence is inadequate to infer the presence or absence of a causal relationship between maternal exposure to secondhand smoke during pregnancy and spontaneous abortion.

Infant Deaths

• 3. The evidence is inadequate to infer the presence or absence of a causal relationship between exposure to secondhand smoke and neonatal mortality.

Sudden Infant Death Syndrome

• 4. The evidence is sufficient to infer a causal relationship between exposure to secondhand smoke and sudden infant death syndrome.

Preterm Delivery

• 5. The evidence is suggestive but not sufficient to infer a causal relationship between maternal exposure to secondhand smoke during pregnancy and preterm delivery.

Low Birth Weight

• 6. The evidence is sufficient to infer a causal relationship between maternal exposure to secondhand smoke during pregnancy and a small reduction in birth weight.

Congenital Malformations

• 7. The evidence is inadequate to infer the presence or absence of a causal relationship between exposure to secondhand smoke and congenital malformations.

Cognitive Development

• 8. The evidence is inadequate to infer the presence or absence of a causal relationship between exposure to secondhand smoke and cognitive functioning among children.

Behavioral Development

• 9. The evidence is inadequate to infer the presence or absence of a causal relationship between exposure to secondhand smoke and behavioral problems among children.

Height/Growth

• 10. The evidence is inadequate to infer the presence or absence of a causal relationship between exposure to secondhand smoke and children’s height/growth.

Childhood Cancer

• 11. The evidence is suggestive but not sufficient to infer a causal relationship between prenatal and postnatal exposure to secondhand smoke and childhood cancer.
• 12. The evidence is inadequate to infer the presence or absence of a causal relationship between maternal exposure to secondhand smoke during pregnancy and childhood cancer.
• 13. The evidence is inadequate to infer the presence or absence of a causal relationship between exposure to secondhand smoke during infancy and childhood cancer.
• 14. The evidence is suggestive but not sufficient to infer a causal relationship between prenatal and postnatal exposure to secondhand smoke and childhood leukemias.
• 15. The evidence is suggestive but not sufficient to infer a causal relationship between prenatal and postnatal exposure to secondhand smoke and childhood lymphomas.
• 16. The evidence is suggestive but not sufficient to infer a causal relationship between prenatal and postnatal exposure to secondhand smoke and childhood brain tumors.
• 17. The evidence is inadequate to infer the presence or absence of a causal relationship between prenatal and postnatal exposure to secondhand smoke and other childhood cancer types.

Chapter 6. Respiratory Effects in Children from Exposure to Secondhand Smoke

Lower respiratory illnesses in infancy and early childhood.

• 1. The evidence is sufficient to infer a causal relationship between secondhand smoke exposure from parental smoking and lower respiratory illnesses in infants and children.
• 2. The increased risk for lower respiratory illnesses is greatest from smoking by the mother.

Middle Ear Disease and Adenotonsillectomy

• 3. The evidence is sufficient to infer a causal relationship between parental smoking and middle ear disease in children, including acute and recurrent otitis media and chronic middle ear effusion.
• 4. The evidence is suggestive but not sufficient to infer a causal relationship between parental smoking and the natural history of middle ear effusion.
• 5. The evidence is inadequate to infer the presence or absence of a causal relationship between parental smoking and an increase in the risk of adenoidectomy or tonsillectomy among children.

Respiratory Symptoms and Prevalent Asthma in School-Age Children

• 6. The evidence is sufficient to infer a causal relationship between parental smoking and cough, phlegm, wheeze, and breathlessness among children of school age.
• 7. The evidence is sufficient to infer a causal relationship between parental smoking and ever having asthma among children of school age.

Childhood Asthma Onset

• 8. The evidence is sufficient to infer a causal relationship between secondhand smoke exposure from parental smoking and the onset of wheeze illnesses in early childhood.
• 9. The evidence is suggestive but not sufficient to infer a causal relationship between secondhand smoke exposure from parental smoking and the onset of childhood asthma.
• 10. The evidence is inadequate to infer the presence or absence of a causal relationship between parental smoking and the risk of immunoglobulin E-mediated allergy in their children.

Lung Growth and Pulmonary Function

• 11. The evidence is sufficient to infer a causal relationship between maternal smoking during pregnancy and persistent adverse effects on lung function across childhood.
• 12. The evidence is sufficient to infer a causal relationship between exposure to secondhand smoke after birth and a lower level of lung function during childhood.

Chapter 7. Cancer Among Adults from Exposure to Secondhand Smoke

Lung cancer.

• 1. The evidence is sufficient to infer a causal relationship between secondhand smoke exposure and lung cancer among lifetime nonsmokers. This conclusion extends to all secondhand smoke exposure, regardless of location.
• 2. The pooled evidence indicates a 20 to 30 percent increase in the risk of lung cancer from secondhand smoke exposure associated with living with a smoker.

Breast Cancer

• 3. The evidence is suggestive but not sufficient to infer a causal relationship between secondhand smoke and breast cancer.

Nasal Sinus Cavity and Nasopharyngeal Carcinoma

• 4. The evidence is suggestive but not sufficient to infer a causal relationship between secondhand smoke exposure and a risk of nasal sinus cancer among nonsmokers.
• 5. The evidence is inadequate to infer the presence or absence of a causal relationship between secondhand smoke exposure and a risk of nasopharyngeal carcinoma among nonsmokers.

Cervical Cancer

• 6. The evidence is inadequate to infer the presence or absence of a causal relationship between secondhand smoke exposure and the risk of cervical cancer among lifetime nonsmokers.

Chapter 8. Cardiovascular Diseases from Exposure to Secondhand Smoke

• The evidence is sufficient to infer a causal relationship between exposure to secondhand smoke and increased risks of coronary heart disease morbidity and mortality among both men and women.
• Pooled relative risks from meta-analyses indicate a 25 to 30 percent increase in the risk of coronary heart disease from exposure to secondhand smoke.
• The evidence is suggestive but not sufficient to infer a causal relationship between exposure to secondhand smoke and an increased risk of stroke.
• Studies of secondhand smoke and subclinical vascular disease, particularly carotid arterial wall thickening, are suggestive but not sufficient to infer a causal relationship between exposure to secondhand smoke and atherosclerosis.

Chapter 9. Respiratory Effects in Adults from Exposure to Secondhand Smoke

Odor and irritation.

• 1. The evidence is sufficient to infer a causal relationship between secondhand smoke exposure and odor annoyance.
• 2. The evidence is sufficient to infer a causal relationship between secondhand smoke exposure and nasal irritation.
• 3. The evidence is suggestive but not sufficient to conclude that persons with nasal allergies or a history of respiratory illnesses are more susceptible to developing nasal irritation from secondhand smoke exposure.

Respiratory Symptoms

• 4. The evidence is suggestive but not sufficient to infer a causal relationship between secondhand smoke exposure and acute respiratory symptoms including cough, wheeze, chest tightness, and difficulty breathing among persons with asthma.
• 5. The evidence is suggestive but not sufficient to infer a causal relationship between secondhand smoke exposure and acute respiratory symptoms including cough, wheeze, chest tightness, and difficulty breathing among healthy persons.
• 6. The evidence is suggestive but not sufficient to infer a causal relationship between secondhand smoke exposure and chronic respiratory symptoms.

Lung Function

• 7. The evidence is suggestive but not sufficient to infer a causal relationship between short-term secondhand smoke exposure and an acute decline in lung function in persons with asthma.
• 8. The evidence is inadequate to infer the presence or absence of a causal relationship between short-term secondhand smoke exposure and an acute decline in lung function in healthy persons.
• 9. The evidence is suggestive but not sufficient to infer a causal relationship between chronic secondhand smoke exposure and a small decrement in lung function in the general population.
• 10. The evidence is inadequate to infer the presence or absence of a causal relationship between chronic secondhand smoke exposure and an accelerated decline in lung function.
• 11. The evidence is suggestive but not sufficient to infer a causal relationship between secondhand smoke exposure and adult-onset asthma.
• 12. The evidence is suggestive but not sufficient to infer a causal relationship between secondhand smoke exposure and a worsening of asthma control.

Chronic Obstructive Pulmonary Disease

• 13. The evidence is suggestive but not sufficient to infer a causal relationship between secondhand smoke exposure and risk for chronic obstructive pulmonary disease.
• 14. The evidence is inadequate to infer the presence or absence of a causal relationship between secondhand smoke exposure and morbidity in persons with chronic obstructive pulmonary disease.

Chapter 10. Control of Secondhand Smoke Exposure

• Workplace smoking restrictions are effective in reducing secondhand smoke exposure.
• Workplace smoking restrictions lead to less smoking among covered workers.
• Establishing smoke-free workplaces is the only effective way to ensure that secondhand smoke exposure does not occur in the workplace.
• The majority of workers in the United States are now covered by smoke-free policies.
• The extent to which workplaces are covered by smoke-free policies varies among worker groups, across states, and by sociodemographic factors. Workplaces related to the entertainment and hospitality industries have notably high potential for secondhand smoke exposure.
• Evidence from peer-reviewed studies shows that smoke-free policies and regulations do not have an adverse economic impact on the hospitality industry.
• Evidence suggests that exposure to secondhand smoke varies by ethnicity and gender.
• In the United States, the home is now becoming the predominant location for exposure of children and adults to secondhand smoke.
• Total bans on indoor smoking in hospitals, restaurants, bars, and offices substantially reduce secondhand smoke exposure, up to several orders of magnitude with incomplete compliance, and with full compliance, exposures are eliminated.
• Exposures of nonsmokers to secondhand smoke cannot be controlled by air cleaning or mechanical air exchange.
• Methodologic Issues

Much of the evidence on the health effects of involuntary smoking comes from observational epidemiologic studies that were carried out to test hypotheses related to secondhand smoke and risk for diseases and other adverse health effects. The challenges faced in carrying out these studies reflect those of observational research generally: assessment of the relevant exposures and outcomes with sufficient validity and precision, selection of an appropriate study design, identification of an appropriate and sufficiently large study population, and collection of information on other relevant factors that may confound or modify the association being studied. The challenge of accurately classifying secondhand smoke exposures confronts all studies of such exposures, and consequently the literature on approaches to and limitations of exposure classification is substantial. Sources of bias that can affect the findings of epidemiologic studies have been widely discussed ( Rothman and Greenland 1998 ), both in general and in relation to studies of involuntary smoking. Concerns about bias apply to any study of an environmental agent and disease risk: misclassification of exposures or outcomes, confounding effect modification, and proper selection of study participants. In addition, the generalizability of findings from one population to another (external validity) further determines the value of evidence from a study. Another methodologic concern affecting secondhand smoke literature comes from the use of meta-analysis to combine the findings of epidemiologic studies; general concerns related to the use of meta-analysis for observational data and more specific concerns related to involuntary smoking have also been raised. This chapter considers these methodologic issues in anticipation of more specific treatment in the following chapters.

Classification of Secondhand Smoke Exposure

For secondhand smoke, as for any environmental factor that may be a cause of disease, the exposure assessment might encompass the time and place of the exposure, cumulative exposures, exposure during a particular time, or a recent exposure ( Jaakkola and Jaakkola 1997 ; Jaakkola and Samet 1999 ). For example, exposures to secondhand smoke across the full life span may be of interest for lung cancer, while only more recent exposures may be relevant to the exacerbation of asthma. For CHD , both temporally remote and current exposures may affect risk. Assessments of exposures are further complicated by the multiplicity of environments where exposures take place and the difficulty of characterizing the exposure in some locations, such as public places or workplaces. Additionally, exposures probably vary qualitatively and quantitatively over time and across locations because of temporal changes and geographic differences in smoking patterns.

Nonetheless, researchers have used a variety of approaches for exposure assessments in epidemiologic studies of adverse health effects from involuntary smoking. Several core concepts that are fundamental to these approaches are illustrated in Figure 1.1 ( Samet and Jaakkola 1999 ). Cigarette smoking is, of course, the source of most secondhand smoke in the United States, followed by pipes, cigars, and other products. Epidemiologic studies generally focus on assessing the exposure, which is the contact with secondhand smoke. The concentrations of secondhand smoke components in a space depend on the number of smokers and the rate at which they are smoking, the volume into which the smoke is distributed, the rate at which the air in the space exchanges with uncontaminated air, and the rate at which the secondhand smoke is removed from the air. Concentration, exposure, and dose differ in their definitions, although the terms are sometimes used without sharp distinctions. However, surrogate indicators that generally describe a source of exposure may also be used to assess the exposure, such as marriage to a smoker or the number of cigarettes smoked in the home. Biomarkers can provide an indication of an exposure or possibly the dose, but for secondhand smoke they are used for recent exposure only.

The determinants of exposure, dose, and biologically effective dose that underlie the development of health effects from smoking. Source: Samet and Jaakkola (more...)

People are exposed to secondhand smoke in a number of different places, often referred to as “microenvironments” ( NRC 1991 ). A microenvironment is a definable location that has a constant concentration of the contaminant of interest, such as secondhand smoke, during the time that a person is there. Some key microenvironments for secondhand smoke include the home, the workplace, public places, and transportation environments ( Klepeis 1999 ). Based on the microenvironmental model, total exposure can be estimated as the weighted average of the concentrations of secondhand smoke or indicator compounds, such as nicotine, in the microenvironments where time is spent; the weights are the time spent in each microenvironment. Klepeis (1999) illustrates the application of the microenvironmental model with national data from the National Human Activity Pattern Survey conducted by the EPA . His calculations yield an overall estimate of exposure to airborne particles from smoking and of the contributions to this exposure from various microenvironments.

Much of the epidemiologic evidence addresses the consequences of an exposure in a particular microenvironment, such as the home (spousal smoking and lung cancer risk or maternal smoking and risk for asthma exacerbation), or the workplace (exacerbation of asthma by the presence of smokers). Some studies have attempted to cover multiple microenvironments and to characterize exposures over time. For example, in the multicenter study of secondhand smoke exposure and lung cancer carried out in the United States, Fontham and colleagues (1994) assessed exposures during childhood, in workplaces, and at home during adulthood. Questionnaires that assess exposures have been the primary tool used in epidemiologic studies of secondhand smoke and disease. Measurement of biomarkers has been added in some studies, either as an additional and complementary exposure assessment approach or for validating questionnaire responses. Some studies have also measured components of secondhand smoke in the air.

Questionnaires generally address sources of exposure in microenvironments and can be tailored to address the time period of interest. Questionnaires represent the only approach that can be used to assess exposures retrospectively over a life span, because available biomarkers only reflect exposures over recent days or, at most, weeks. Questionnaires on secondhand smoke exposure have been assessed for their reliability and validity, generally based on comparisons with either biomarker or air monitoring data as the “gold” standard ( Jaakkola and Jaakkola 1997 ). Two studies evaluated the reliability of questionnaires on lifetime exposures ( Pron et al. 1988 ; Coultas et al. 1989 ). Both showed a high degree of repeatability for questions concerning whether a spouse had smoked, but a lower reliability for responses concerning the quantitative aspects of an exposure. Emerson and colleagues (1995) evaluated the repeatability of information from parents of children with asthma. They found a high reliability for parent-reported tobacco use and for the number of cigarettes to which the child was exposed in the home during the past week.

To assess validity, questionnaire reports of current or recent exposures have been compared with levels of cotinine and other biomarkers. These studies tend to show a moderate correlation between levels of cotinine and questionnaire indicators of exposures ( Kawachi and Colditz 1996 ; Cal/EPA 1997 ; Jaakkola and Jaakkola 1997 ). However, cotinine levels reflect not only exposure but metabolism and excretion ( Benowitz 1999 ). Consequently, exposure is only one determinant of variation in cotinine levels among persons; there also are individual variations in metabolism and excretion rates. In spite of these sources of variability, mean levels of cotinine vary as anticipated across categories of self-reported exposures ( Cal/EPA 1997 ; Jaakkola and Jaakkola 1997 ), and self-reported exposures are moderately associated with measured levels of markers ( Cal/EPA 1997 ; Jaakkola and Jaakkola 1997 ).

Biomarkers are also used for assessing exposures to secondhand smoke. A number of biomarkers are available, but they vary in their specificity and in the dynamics of the temporal relationship between the exposure and the marker level ( Cal/EPA 1997 ; Benowitz 1999 ). These markers include specific tobacco smoke components (nicotine) or metabolites (cotinine and tobacco-specific nitrosamines), nonspecific biomarkers (thiocyanate and CO ), adducts with tobacco smoke components or metabolites (4-amino-biphenyl hemoglobin adducts, benzo[ a ]pyrene DNA adducts, and polycyclic aromatic hydrocarbon albumin adducts), and nonspecific assays (urinary mutagenicity). Cotinine has been the most widely used biomarker, primarily because of its specificity, half-life, and ease of measurement in body fluids (e. g ., urine, blood, and saliva). Biomarkers are discussed in detail in Chapter 3 (Assessment of Exposure to Secondhand Smoke).

Some epidemiologic studies have also incorporated air monitoring, either direct personal sampling or the indirect approach based on the microenvironmental model. Nicotine, present in the gas phase of secondhand smoke, can be monitored passively with a special filter or actively using a pump and a sorbent. Hammond and Leaderer (1987) first described a diffusion monitor for the passive sampling of nicotine in 1987; this device has now been widely used to assess concentrations in different environments and to study health effects. Airborne particles have also been measured using active monitoring devices.

Each of these approaches for assessing exposures has strengths and limitations, and preference for one over another will depend on the research question and its context ( Jaakkola and Jaakkola 1997 ; Jaakkola and Samet 1999 ). Questionnaires can be used to characterize sources of exposures, such as smoking by parents. With air concentrations of markers and time-activity information, estimates of secondhand smoke exposures can be made with the microenvironmental model. Biomarkers provide exposure measures that reflect the patterns of exposure and the kinetics of the marker; the cotinine level in body fluids, for example, reflects an exposure during several days. Air monitoring may be useful for validating measurements of exposure. Exposure assessment strategies are matched to the research question and often employ a mixture of approaches determined by feasibility and cost constraints.

Misclassification of Secondhand Smoke Exposure

Misclassification may occur when classifying exposures, outcomes, confounding factors, or modifying factors. Misclassification may be differential on either exposure or outcome, or it may be random ( Armstrong et al. 1992 ). Differential or nonrandom misclassification may either increase or decrease estimates of effect, while random misclassification tends to reduce the apparent effect and weaken the relationship of exposure with disease risk. In studies of secondhand smoke and disease risk, exposure misclassification has been a major consideration in the interpretation of the evidence, although misclassification of health outcome measures has not been a substantial issue in this research. The consequences for epidemiologic studies of misclassification in general are well established ( Rothman and Greenland 1998 ).

An extensive body of literature on the classification of exposures to secondhand smoke is reviewed in this and other chapters, as well as in some publications on the consequences of misclassification ( Wu 1999 ). Two general patterns of exposure misclassification are of concern to secondhand smoke: (1) random misclassification that is not differential by the presence or absence of the health outcome and (2) systematic misclassification that is differential by the health outcome. In studying the health effects of secondhand smoke in adults, there is a further concern as to the classification of the active smoking status (never, current, or former smoking); in studies of children, the accuracy of secondhand smoke exposure classification is the primary methodologic issue around exposure assessment, but unreported active smoking by adolescents is also a concern.

With regard to random misclassification of secondhand smoke exposures, there is an inherent degree of unavoidable measurement error in the exposure measures used in epidemiologic studies. Questionnaires generally assess contact with sources of an exposure (e. g ., smoking in the home or work-place) and cannot capture all exposures nor the intensity of exposures; biomarkers provide an exposure index for a particular time window and have intrinsic variability. Some building-related factors that determine an exposure cannot be assessed accurately by a questionnaire, such as the rate of air exchange and the size of the microenvironment where time is spent, nor can concentrations be assessed accurately by subjective reports of the perceived level of tobacco smoke. In general, random misclassification of exposures tends to reduce the likelihood that studies of secondhand smoke exposure will find an effect. This type of misclassification lessens the contrast between exposure groups, because some truly exposed persons are placed in the unexposed group and some truly unexposed persons are placed in the exposed group. Differential misclassification, also a concern, may increase or decrease associations, depending on the pattern of misreporting.

One particular form of misclassification has been raised with regard to secondhand smoke exposure and lung cancer: the classification of some current or former smokers as lifetime nonsmokers ( USEPA 1992 ; Lee and Forey 1995 ; Hackshaw et al. 1997 ; Wu 1999 ). The resulting bias would tend to increase the apparent association of secondhand smoke with lung cancer, if the misclassified active smokers are also more likely to be classified as involuntary smokers. Most studies of lung cancer and secondhand smoke have used spousal smoking as a main exposure variable. As smoking tends to aggregate between spouses (smokers are more likely to marry smokers), misclassification of active smoking would tend to be differential on the basis of spousal smoking (the exposure under investigation). Because active smoking is strongly associated with increased disease risk, greater misclassification of an actively smoking spouse as a non-smoker among spouses of smokers compared with spouses of nonsmokers would lead to risk estimates for spousal smoking that are biased upward by the effect of active smoking. This type of misclassification is also relevant to studies of spousal exposure and CHD risk or other diseases also caused by active smoking, although the potential for bias is less because the association of active smoking with CHD is not as strong as with lung cancer.

There have been a number of publications on this form of misclassification. Wu (1999) provides a review, and Lee and colleagues (2001) offer an assessment of potential consequences. A number of models have been developed to assess the extent of bias resulting from the misclassification of active smokers as lifetime nonsmokers ( USEPA 1992 ; Hackshaw et al. 1997 ). These models incorporate estimates of the rate of misclassification, the degree of aggregation of smokers by marriage, the prevalence of smoking in the population, and the risk of lung cancer in misclassified smokers ( Wu 1999 ). Although debate about this issue continues, analyses show that estimates of upward bias from misclassifying active smokers as lifetime nonsmokers cannot fully explain the observed increase in risk for lung cancer among lifetime non-smokers married to smokers ( Hackshaw et al. 1997 ; Wu 1999 ).

There is one additional issue related to exposure misclassification. During the time the epidemiologic studies of secondhand smoke have been carried out, exposure has been widespread and almost unavoidable. Therefore, the risk estimates may be biased downward because there are no truly unexposed persons. The 1986 Surgeon General’s report recognized this methodologic issue and noted the need for further data on population exposures to secondhand smoke ( USDHHS 1986 ). This bias was also recognized in the 1986 report of the NRC , and an adjustment for this misclassification was made to the lung cancer estimate ( NRC 1986 ). Similarly, the 1992 report of the EPA commented on background exposure and made an adjustment ( USEPA 1992 ). Some later studies have attempted to address this issue; for example, in a case-control study of active and involuntary smoking and breast cancer in Switzerland, Morabia and colleagues (2000) used a questionnaire to assess exposure and identified a small group of lifetime nonsmokers who also reported no exposure to secondhand smoke. With this subgroup of controls as the reference population, the risks of secondhand smoke exposure were substantially greater for active smoking than when the full control population was used.

This Surgeon General’s report further addresses specific issues of exposure misclassification when they are relevant to the health outcome under consideration.

Use of Meta-Analysis

Meta-analysis refers to the process of evaluating and combining a body of research literature that addresses a common question. Meta-analysis is composed of qualitative and quantitative components. The qualitative component involves the systematic identification of all relevant investigations, a systematic assessment of their characteristics and quality, and the decision to include or exclude studies based on predetermined criteria. Consideration can be directed toward sources of bias that might affect the findings. The quantitative component involves the calculation and display of study results on common scales and, if appropriate, the statistical combination of these results across studies and an exploration of the reasons for any heterogeneity of findings. Viewing the findings of all studies as a single plot provides insights into the consistency of results and the precision of the studies considered. Most meta-analyses are based on published summary results, although they are most powerful when applied to data at the level of individual participants. Meta-analysis is most widely used to synthesize evidence from randomized clinical trials, sometimes yielding findings that were not evident from the results of individual studies. Meta-analysis also has been used extensively to examine bodies of observational evidence.

Beginning with the 1986 NRC report, meta-analysis has been used to summarize the evidence on involuntary smoking and health. Meta-analysis was central to the 1992 EPA risk assessment of secondhand smoke, and a series of meta-analyses supported the conclusions of the 1998 report of the Scientific Committee on Tobacco and Health in the United Kingdom. The central role of meta-analysis in interpreting and applying the evidence related to involuntary smoking and disease has led to focused criticisms of the use of meta-analysis in this context. Several papers that acknowledged support from the tobacco industry have addressed the epidemiologic findings for lung cancer, including the selection and quality of the studies, the methods for meta-analysis, and dose-response associations ( Fleiss and Gross 1991 ; Tweedie and Mengersen 1995 ; Lee 1998 , 1999 ). In a lawsuit brought by the tobacco industry against the EPA, the 1998 decision handed down by Judge William L . Osteen, Sr., in the North Carolina Federal District Court criticized the approach EPA had used to select studies for its meta-analysis and criticized the use of 90 percent rather than 95 percent confidence intervals for the summary estimates ( Flue-Cured Tobacco Cooperative Stabilization Corp. v. United States Environmental Protection Agency , 857 F. Supp. 1137 [M.D.N.C. 1993]). In December 2002, the 4th U.S. Circuit Court of Appeals threw out the lawsuit on the basis that tobacco companies cannot sue the EPA over its secondhand smoke report because the report was not a final agency action and therefore not subject to court review ( Flue-Cured Tobacco Cooperative Stabilization Corp. v. The United States Environmental Protection Agency , No. 98–2407 [4th Cir., December 11, 2002], cited in 17.7 TPLR 2.472 [2003]).

Recognizing that there is still an active discussion around the use of meta-analysis to pool data from observational studies (versus clinical trials), the authors of this Surgeon General’s report used this methodology to summarize the available data when deemed appropriate and useful, even while recognizing that the uncertainty around the meta-analytic estimates may exceed the uncertainty indicated by conventional statistical indices, because of biases either within the observational studies or produced by the manner of their selection. However, a decision to not combine estimates might have produced conclusions that are far more uncertain than the data warrant because the review would have focused on individual study results without considering their overall pattern, and without allowing for a full accounting of different sample sizes and effect estimates.

The possibility of publication bias has been raised as a potential limitation to the interpretation of evidence on involuntary smoking and disease in general, and on lung cancer and secondhand smoke exposure specifically. A 1988 paper by Vandenbroucke used a descriptive approach, called a “funnel plot,” to assess the possibility that publication bias affected the 13 studies considered in a review by Wald and colleagues (1986) . This type of plot characterizes the relationship between the magnitude of estimates and their precision. Vandenbroucke suggested the possibility of publication bias only in reference to the studies of men. Bero and colleagues (1994) concluded that there had not been a publication bias against studies with statistically significant findings, nor against the publication of studies with nonsignificant or mixed findings in the research literature. The researchers were able to identify only five unpublished “negative” studies, of which two were dissertations that tend to be delayed in publication. A subsequent study by Misakian and Bero (1998) did find a delay in the publication of studies with nonsignificant results in comparison with studies having significant results; whether this pattern has varied over the several decades of research on secondhand smoke was not addressed. More recently, Copas and Shi (2000) assessed the 37 studies considered in the meta-analysis by Hackshaw and colleagues (1997) for publication bias. Copas and Shi (2000) found a significant correlation between the estimated risk of exposure and sample size, such that smaller studies tended to have higher values. This pattern suggests the possibility of publication bias. However, using a funnel plot of the same studies, Lubin (1999) found little evidence for publication bias.

On this issue of publication bias, it is critical to distinguish between indirect statistical arguments and arguments based on actual identification of previously unidentified research. The strongest case against substantive publication bias has been made by researchers who mounted intensive efforts to find the possibly missing studies; these efforts have yielded little nothing that would alter published conclusions ( Bero et al. 1994 ; Glantz 2000 ). Presumably because this exposure is a great public health concern, the findings of studies that do not have statistically significant outcomes continue to be published ( Kawachi and Colditz 1996 ).

The quantitative results of the meta-analyses, however, were not determinate in making causal inferences in this Surgeon General’s report. In particular, the level of statistical significance of estimates from the meta-analyses was not a predominant factor in making a causal conclusion. For that purpose, this report relied on the approach and criteria set out in the 1964 and 2004 reports of the Surgeon General, which involved judgments based on an array of quantitative and qualitative considerations that included the degree of heterogeneity in the designs of the studies that were examined. Sometimes this heterogeneity limits the inference from meta-analysis by weakening the rationale for pooling the study results. However, the availability of consistent evidence from heterogenous designs can strengthen the meta-analytic findings by making it unlikely that a common bias could persist across different study designs and populations.

Confounding

Confounding, which refers in this context to the mixing of the effect of another factor with that of secondhand smoke, has been proposed as an explanation for associations of secondhand smoke with adverse health consequences. Confounding occurs when the factor of interest (secondhand smoke) is associated in the data under consideration with another factor (the confounder) that, by itself, increases the risk for the disease ( Rothman and Greenland 1998 ). Correlates of secondhand smoke exposures are not confounding factors unless an exposure to them increases the risk of disease. A factor proposed as a potential confounder is not necessarily an actual confounder unless it fulfills the two elements of the definition. Although lengthy lists of potential confounding factors have been offered as alternatives to direct associations of secondhand smoke exposures with the risk for disease, the factors on these lists generally have not been shown to be confounding in the particular data of interest.

The term confounding also conveys an implicit conceptualization as to the causal pathways that link secondhand smoke and the confounding factor to disease risk. Confounding implies that the confounding factor has an effect on risk that is independent of secondhand smoke exposure. Some factors considered as potential confounders may, however, be in the same causal pathway as a secondhand smoke exposure. Although socioeconomic status ( SES ) is often cited as a potential confounding factor, it may not have an independent effect but can affect disease risk through its association with secondhand smoke exposure ( Figure 1.2 ). This figure shows general alternative relationships among SES, secondhand smoke exposure, and risk for an adverse effect. SES may have a direct effect, or it may indirectly exert its effect through an association with secondhand smoke exposure, or it may confound the relationship between secondhand smoke exposure and disease risk. To control for SES as a potential confounding factor without considering underlying relationships may lead to incorrect risk estimates. For example, controlling for SES would not be appropriate if it is a determinant of secondhand smoke exposure but has no direct effect.

Model for socioeconomic status (SES) and secondhand smoke (SHS) exposure. Arrows indicate directionality of association.

Nonetheless, because the health effects of involuntary smoking have other causes, the possibility of confounding needs careful exploration when assessing associations of secondhand smoke exposure with adverse health effects. In addition, survey data from the last several decades show that secondhand smoke exposure is associated with correlates of lifestyle that may influence the risk for some health effects, thus increasing concerns for the possibility of confounding ( Kawachi and Colditz 1996 ). Survey data from the United States ( Matanoski et al. 1995 ) and the United Kingdom ( Thornton et al. 1994 ) show that adults with secondhand smoke exposures generally tend to have less healthful lifestyles. However, the extent to which these patterns of association can be generalized, either to other countries or to the past, is uncertain.

The potential bias from confounding varies with the association of the confounder to secondhand smoke exposures in a particular study and to the strength of the confounder as a risk factor. The importance of confounding to the interpretation of evidence depends further on the magnitude of the effect of secondhand smoke on disease. As the strength of an association lessens, confounding as an alternative explanation for an association becomes an increasing concern. In prior reviews, confounding has been addressed either quantitatively ( Hackshaw et al. 1997 ) or qualitatively ( Cal/EPA 1997 ; Thun et al. 1999 ). In the chapters in this report that focus on specific diseases, confounding is specifically addressed in the context of potential confounding factors for the particular diseases.

• Tobacco Industry Activities

The evidence on secondhand smoke and disease risk, given the public health and public policy implications, has been reviewed extensively in the published peer-reviewed literature and in evaluations by a number of expert panels. In addition, the evidence has been criticized repeatedly by the tobacco industry and its consultants in venues that have included the peer-reviewed literature, public meetings and hearings, and scientific symposia that included symposia sponsored by the industry. Open criticism in the peer-reviewed literature can strengthen the credibility of scientific evidence by challenging researchers to consider the arguments proposed by critics and to rebut them.

Industry documents indicate that the tobacco industry has engaged in widespread activities, however, that have gone beyond the bounds of accepted scientific practice ( Glantz 1996 ; Ong and Glantz 2000 , 2001 ; Rampton and Stauber 2000 ; Yach and Bialous 2001 ; Hong and Bero 2002 ; Diethelm et al. 2004 ). Through a variety of organized tactics, the industry has attempted to undermine the credibility of the scientific evidence on secondhand smoke. The industry has funded or carried out research that has been judged to be biased, supported scientists to generate letters to editors that criticized research publications, attempted to undermine the findings of key studies, assisted in establishing a scientific society with a journal, and attempted to sustain controversy even as the scientific community reached consensus ( Garne et al. 2005 ). These tactics are not a topic of this report, but to the extent that the scientific literature has been distorted, they are addressed as the evidence is reviewed. This report does not specifically identify tobacco industry sponsorship of publications unless that information is relevant to the interpretation of the findings and conclusions.

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• Wu AH. Exposure misclassification bias in studies of environmental tobacco smoke and lung cancer. Environmental Health Perspectives. 1999; 107 (Suppl 6):873–7. [ PMC free article : PMC1566193 ] [ PubMed : 10592145 ]
• Yach D, Bialous SA. Junking science to promote tobacco. American Journal of Public Health. 2001; 91 (11):1745–8. [ PMC free article : PMC1446867 ] [ PubMed : 11684592 ]
• Cite this Page Office on Smoking and Health (US). The Health Consequences of Involuntary Exposure to Tobacco Smoke: A Report of the Surgeon General. Atlanta (GA): Centers for Disease Control and Prevention (US); 2006. 1, Introduction, Summary, and Conclusions.
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Essay on Negative Effects Of Smoking

Students are often asked to write an essay on Negative Effects Of Smoking in their schools and colleges. And if you’re also looking for the same, we have created 100-word, 250-word, and 500-word essays on the topic.

Let’s take a look…

100 Words Essay on Negative Effects Of Smoking

Introduction to smoking.

Smoking is a bad habit that harms our body. Many people smoke cigarettes, cigars, or pipes. Some people also chew tobacco. These things contain nicotine, a harmful chemical. It’s highly addictive, meaning once you start smoking, it’s very hard to stop.

Health Problems Caused by Smoking

Smoking can cause many health problems. It can lead to lung cancer, heart disease, and stroke. It can also cause other types of cancer, like mouth and throat cancer. Smoking can make it hard to breathe and can cause chronic coughing.

Smoking and Secondhand Smoke

Not only does smoking hurt the smoker, but it also harms others around them. This is called secondhand smoke. It can cause the same health problems in non-smokers. Children exposed to secondhand smoke can get sick more often.

Smoking and Appearance

Smoking can also affect how you look. It can cause yellow teeth and bad breath. It can also cause your skin to age faster, leading to wrinkles. Smoking can even cause hair loss and turn your fingers yellow.

In conclusion, smoking is very harmful. It can cause many health problems and can even harm others around you. It’s best to avoid this bad habit. If you or someone you know smokes, try to quit. Your body will thank you.

250 Words Essay on Negative Effects Of Smoking

Introduction.

Smoking is a harmful habit that many people around the world have. It is bad for our health and the environment. This essay will talk about the negative effects of smoking.

Damages to Health

Smoking hurts our bodies in many ways. It is the main cause of lung cancer. This is a very serious disease that can lead to death. Other than lung cancer, smoking can also cause heart disease. This is because the smoke makes it harder for the heart to pump blood.

Problems for the Environment

Smoking is not just bad for our health, but also for our environment. Cigarette butts are often thrown on the ground, causing pollution. Also, the smoke from cigarettes adds to air pollution. This is bad for all living things, not just humans.

Effects on Others

Smoking is not only harmful to the person who smokes, but also to the people around them. This is called second-hand smoke. It can cause the same health problems as smoking does. This means that even if you do not smoke, you can still get sick from being around someone who does.

In conclusion, smoking is a harmful habit with many negative effects. It causes health problems, harms the environment, and can even make others sick. It is important to avoid smoking for a healthier and safer world.

500 Words Essay on Negative Effects Of Smoking

Smoking is a habit that many people pick up due to various reasons, such as stress, peer pressure, or even out of curiosity. Despite its popularity, smoking has many negative effects on our health and the environment. This essay will discuss these harmful effects in simple terms.

Effects on Personal Health

Firstly, let’s talk about how smoking harms our own health. When you smoke, you inhale many dangerous chemicals. These chemicals can harm nearly every organ in your body. The most commonly known health problem caused by smoking is lung cancer. But that’s not all. Smoking can also lead to other types of cancer, such as mouth cancer and throat cancer.

Apart from cancer, smoking can cause heart disease. The chemicals in smoke make it harder for your heart to work properly. This can lead to heart attacks. Smoking also harms your lungs, making it difficult to breathe. This can lead to diseases like bronchitis and emphysema.

Effects on Others’ Health

Smoking is not only harmful to the smoker but also to those around them. This is called secondhand smoke. When you smoke, the people around you also breathe in the harmful chemicals. This can lead to the same health problems that smokers face. Children are particularly at risk. They can suffer from problems like asthma, ear infections, and even sudden infant death syndrome.

Effects on the Environment

Smoking also hurts our environment. Cigarette butts, which are often thrown away carelessly, are a form of litter. They can take many years to break down and are harmful to wildlife. The smoke from cigarettes also adds to air pollution. This can harm the air we all breathe and contribute to climate change.

Effects on Personal Life

Lastly, smoking can affect your personal life. It can make your clothes and breath smell bad, which can affect your relationships with others. It can also be a costly habit. The money spent on cigarettes could be used for other things like education, hobbies, or saving for the future.

In conclusion, smoking has many negative effects. It harms our health, the health of those around us, our environment, and our personal lives. It’s important to understand these effects and to make healthy choices for ourselves and our communities. Remember, it’s never too late to quit smoking and start living a healthier life.

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Free Cause and Effect Essay on Smoking

Published by gudwriter on May 30, 2018 May 30, 2018

Causes and effects of smoking is a broad application that requires adequate research and knowledge to write and expound on the subject, thus students who doubt their research skills can opt to purchase a research proposal from a legit service like Gudwriter to help them with the homework.

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Smoking Cause and Effect Essay Outline

Introduction  .

Thesis: To understand the social and health implications of smoking it is essential to look into some of its causes and effects.

Paragraph 1:

Peer pressure is the most prevalent cause of smoking.

• Most people start smoking through the influence of their friends,
• Smoking begins when most people are young; that is during adolescence and in their early twenties.
• Quitting smoking due to addiction is difficult.

Paragraph 2:

Parenting style determines whether or not one will be a smoker.

• A child whose parents were smokers is highly likely to become a smoker.
• Children take after their parents’ behaviors.

Paragraph 3:

People are duped into believing that smoking relieves stress.

• People engage in smoking as a way of managing stress.
• Smoking does not relieve stress; instead, it increases it.
• The level of stress in smokers is higher compared to non-smokers.

Paragraph 4:

Smoking is the leading cause of lung cancer in the world.

• Smoking causes cancer both in active and passive smokers.
• Smoking also causes anxiety on the victim.
• Smoking damages the lining of one’s lungs thus causing lung cancer.
• Continued smoking leads to permanent damage to lung tissues.

Paragraph 5:

Smoking causes loss of sight.

• Cataracts are the number one cause of blindness in the world.
• Smokers are twice at the risk of developing cataracts than non-smokers.
• AMD is the leading cause of permanent blindness in people aged 65years and above.
• Smokers are three times likely to develop AMD than non-smokers.

Paragraph 6:

Smoking is one of the major causes of type-2 diabetes.

• 40% of smokers are likely to develop type-2 diabetes.
• Diabetic smokers make it hard to control the disease progress and insulin levels thus increasing their chances of dying from the disease.
• Diabetic smokers are also likely to suffer from other health complications linked to diabetes such as heart failure, kidney problems, high blood pressure, retinopathy, and peripheral neuropathy.

Paragraph 7:

Smoking is the number one cause of death in the US among all the causes of preventable deaths.

• 480,000 deaths in the country are caused by cigarette smoking each year.
• This translates to 20% of the total yearly deaths.

Conclusion:

Smoking is a general lifestyle behavior among young people. People engage in the practice as a way of having fun. Peer pressure is one of the leading factors that drive people to smoke. Parenting style also contributes to the chances of one becoming a smoker. Most people underestimate the health risks associated with smoking. Lung cancer, blindness, and type-2 diabetes are some of the few health effects attributed to smoking.

Learn how to write a cause and effect essay that will get you good grades.

Cause and Effect Essay on Smoking

Introduction.

Smoking is considered a lifestyle behavior. Many people engage in the practice without the awareness of the health risks it is associated with. Smoking is one of the most addictive lifestyle behaviors and has life-changing implications. It has been termed as one of the most significant health challenges that health organizations are facing today (Onor et al., 2017). According to reports by World Health Organization, there were more than 1 billion smokers all over the world in 2014. To understand the social and health implications of smoking, it is essential to look into some of its causes and effects.

Peer pressure is the most prevalent cause of smoking. According to research, most smokers start the smoking habit at a tender age. During adolescence and in the early twenties, most people are infatuated with friendships (Ukwayi, Eja & Unwanede, 2012). At this stage in life, friends hold great value and meaning in individuals. It is at this age that most people are either in their final years in high school or just starting off in college. Most young people particularly those at the college and high school levels engage in various dangerous and life-harming activities, one of which is smoking (Ukwayi, Eja & Unwanede, 2012). Often, their intent is not to become smokers but to enjoy the experience of being young and feel a celebrated status over their peers. If one belongs to a group whose members are smokers, then they too will likely start smoking (Ukwayi, Eja & Unwanede, 2012). Later in life, such people try to drop the smoking behavior, but it becomes challenging due to withdrawal effects.

Parenting style is another factor that may determine whether or not one will become a smoker. The manner in which a child is raised contributes significantly to their behavior as adults (Gilman et al., 2009). Most children look up to their parents and will adopt most of the lifestyle behaviors portrayed by the parents (Gilman et al., 2009). There are parents who have the habit of smoking in the presence of their children, a behavior which is utterly irresponsible (Gilman et al., 2009). Children get the idea that smoking is not unhealthy if their parents do it in their presence (Gilman et al., 2009). Once such children grow up, they develop a liking for tobacco smoking without knowing that it is an unhealthy lifestyle behavior.

There is also a misconception that smoking acts as strain reliever. This delusion blinds most people that smoking helps one relieve stress. Many people therefore find themselves engaging in the habit as a stress management strategy (Choi, Ota & Watanuki, 2015). Noteworthy, continued smoking leads to addiction, thereby making it very difficult for one to do away with the habit once they start it. Research has shown that smoking does not relieve stress, instead it increases it (Choi, Ota & Watanuki, 2015). The level of stress in smokers is twice as high as that in non-smokers.

Smoking is the leading cause of lung cancer in the world, according to research. The practice is likely to cause lung cancer both in active and passive smokers. Passive smokers are people who do not smoke but are exposed to cigarette smoke (Onor et al., 2017). According to medics, smoking damages the lining of one’s lungs thus causing lung cancer. When one inhales cigarette smoke, which consists of cancer-causing carcinogens, lung tissues start changing immediately (Onor et al., 2017). If one smokes for a small period then quits, the lung tissues will repair themselves thus reducing the chances of contracting lung cancer (Onor et al., 2017). However, continued smoking leads to permanent damage of the lung tissues to the extent that they become irreparable. These damages accelerate the development of lung cancer.

Smoking also causes loss of sight. According to medical research, cataracts are the number one cause of blindness in the world. Cataract is the blurring of the eyes standard lens. Studies reveal that smokers are twice at the risk of developing cataracts than non-smokers (Kennedy et al., 2017). Age-related Macular Degeneration (AMD) has an impact on the retina, which is the part of the eye that is responsible for the sharp vision that people use while driving and reading. AMD has been termed as the leading cause of permanent blindness in people aged 65years and above (Kennedy et al., 2017). Research shows that smokers are three times likely to develop AMD than non-smokers (Kennedy et al., 2017). However, if one quits smoking at an early stage, the damage caused to the eyes is repairable, but prolonged smoking leads to increased destruction of the eyes that in turn translates to permanent blindness.

Further, smoking is one of the major causes of type-2 diabetes. Research shows that 40% of smokers are likely to develop type-2 diabetes (Onor et al., 2017). Diabetic people who smoke are likely to experience difficulties in managing insulin levels in their bodies even with prescribed medications. Since increased smoking leads to increased chances of developing type-2 diabetes, diabetic smokers make it hard to control the disease’s progress and insulin levels thus increasing their chances of dying from it (Onor et al., 2017). Diabetic smokers are also likely to suffer from other health complications linked to diabetes such as heart failure, kidney problems, high blood pressure, retinopathy, and peripheral neuropathy (Onor et al., 2017). For a diabetic person, quitting smoking can help control insulin levels in the body.

Even more disheartening is the fact that even though preventable, cigarette smoking is the number one cause of death in the US among all the causes of deaths that are preventable. The same applies to the United Kingdom. In the US alone, 480,000 deaths are caused by cigarette smoking each year, translating to 20% of the total yearly deaths ( Marshall , 2016). The total deaths resulting from a combination of the following causes every year is less than the number of deaths caused by cigarette smoking: firearm-related accidents, motor vehicle injuries, alcohol use, illegal drug use, and HIV. This further shows the seriousness of the effects of smoking on human health.

Smoking is a general lifestyle behavior among young and older people alike. People engage in the practice as a way of having fun. Peer pressure is one of the leading factors that drive people to smoke. Parenting style also contributes to the chances of one becoming a smoker. Many people underestimate the health risks associated with smoking. Lung cancer, blindness, and type-2 diabetes are some of the health effects associated with this habit.

Choi, D., Ota, S., & Watanuki, S. (2015). Does cigarette smoking relieve stress? Evidence from the event-related potential (ERP).  International Journal of Psychophysiology ,  98 (3), 470-476.

Gilman, S. E., Rende, R., Boergers, J., Abrams, D. B., Buka, S. L., Clark, M. A., … & Lloyd-Richardson, E. E. (2009). Parental smoking and adolescent smoking initiation: an intergenerational perspective on tobacco control.  Pediatrics ,  123 (2), e274-e281.

Kennedy, R. D., Hammond, D., Spafford, M. M., Douglas, O., Brûlé, J., Fong, G. T., & Schultz, A. S. (2016). Educating smokers about the risk of blindness–insights to improve tobacco product health warning labels.  Tobacco Induced Diseases ,  14 (1), 30.

Marshall, T. (2016). Public opinion, public policy, and smoking: the transformation of American attitudes and cigarette use, 1890–2016 (1st ed.) . Lanham, MD: Rowman & Littlefield.

Onor, I. O., Stirling, D. L., Williams, S. R., Bediako, D., Borghol, A., Harris, M. B., … & Sarpong, D. F. (2017). Clinical effects of cigarette smoking: epidemiologic impact and review of pharmacotherapy options.  International Journal of Environmental Research and Public Health ,  14 (10), 1147.

Ukwayi, J. K., Eja, O. F., & Unwanede, C. C. (2012). Peer pressure and tobacco smoking among undergraduate students of the University of Calabar, Cross River State.  Higher Education Studies ,  2 (3), 92.

Smoking Essay 2: The Effects of Smoking on Health and Social Care

A sample smoking essay outline.

Thesis:  Smoking is harmful to nearly all body organs and thus quitting has health benefits.

Smoking damages the human heart and interferes with normal blood circulation.

• This increases the risks of such conditions as cerebrovascular disease, peripheral vascular disease, stroke, heart attack, and coronary heart disease.
• The heart is made to work faster and thereby strained.
• The cigarette contents increase the risks of blood clots.
• Smoking leads to furring of the coronary arteries.

Paragraph 2: 

Smoking can cause lung disease.

• Chronic obstructive pulmonary disease (COPD) is one of the lung diseases.
• Most cases of lung cancer are caused by smoking.
• An attack can be triggered or made worse by tobacco smoke in asthmatic people.

Smoking can cause serious damages to the mouth and throat.

• It can cause strained teeth, bad breath and gum disease.
• It causes an increased cancer risk in the gullet, voice box, throat, tongue, and lips.

Smoking can make a woman to experience difficulties in becoming pregnant.

• There are higher risks for a pregnant smoker to miscarry.
• They may have their baby born with a cleft palate and/or cleft lip,
• They may give birth before time to a baby with an abnormally low birth weight,
• They may have an ectopic pregnancy.

Quitting smoking reduces the risk of many diseases caused by the habit.

• Reduced chances of dying from illnesses that are smoking-related
• Quitters have substantial life expectancy gains in comparison to those who continue to smoke.

Paragraph 6: 

It is only through quitting that one would be free from the problems caused by smoking.

• Set the stage to quit by mentally preparing oneself.
• Control cravings of smoking by using nicotine replacement products.
• Apply SmokEnders’ behavioral changes in completely breaking emotional bonds developed between smokers and cigarettes.

Smoking affects almost every organ of the human body and is thus detrimental to health. It causes fatal diseases such as cancer, heart disease, COPD, and can also damage the mouth and throat. Quitting is highly recommendable.

Smoking Essay Sample

The harmful effects of smoking on health and social care essay.

There are many chemicals contained in tobacco smoke that pose health risks both to smokers and nonsmokers. It can be harmful to even breathe a little tobacco smoke. “Of the more than 7,000 chemicals in tobacco smoke, at least 250 are known to be harmful, including hydrogen cyanide, carbon monoxide, and ammonia” (National Cancer Institute, 2017). At least 69 of these 250 known harmful chemicals in tobacco smoke cause cancer. This explains why cigarette smoking is the leading cause of preventable premature deaths in the United States. Overall, smoking is harmful to nearly all body organs and thus quitting has health benefits.

Smoking damages the human heart and interferes with normal blood circulation. This increases the risks of such conditions as cerebrovascular disease (damage to arteries supplying blood to the brain), peripheral vascular disease (damaged blood vessels), stroke, heart attack, and coronary heart disease. The heart is made to work faster by nicotine and carbon monoxide from the smoke thereby straining it. The cigarette contents also increase the risks of one experiencing blood clots in their circulation system. In addition, smoking leads to furring of the coronary arteries as the lining of the arteries are damaged by other chemicals in the cigarette smoke. As a matter of fact, one faces a double risk of having a heart attack by smoking (NHS, 2018). Their risk of dying from coronary heart disease is also twice that of nonsmokers.

According to CDC (2018), “Smoking can cause lung disease by damaging your airways and the small air sacs (alveoli) found in your lungs.” Chronic obstructive pulmonary disease (COPD) is one of the lung diseases caused by smoking and it includes chronic bronchitis and emphysema. It is also noteworthy that most cases of lung cancer are caused by smoking. An attack can be triggered or made worse by tobacco smoke in people who have asthma. Compared to nonsmokers, the chances of smokers dying from COPD are 12 to 13 times higher. Additionally, smoking causes a cancer that forms in the intestines (rectum or colon) known as colorectal cancer and is the second leading contributor to cancer deaths in the U.S. (American Lung Association, 2018). A smoker has higher risks of developing this type of cancer.

Smoking can also cause serious damages to the mouth and throat. It can cause such unattractive problems as strained teeth, bad breath, and gum disease, as well as damage one’s sense of taste. The most serious damage caused by smoking in the throat and mouth is an increased cancer risk in the gullet (esophagus), voice box, throat, tongue, and lips. This risk increases with an increase in the intake of tobacco contents. “More than 93% of oropharyngeal cancers (cancer in part of the throat) are caused by smoking” (NHS, 2018). This implies that nonsmokers have a greatly reduced risk of developing mouth and throat cancers.

Further, smoking can make a woman to experience difficulties in becoming pregnant. Even if they succeed at conceiving, there are higher risks for a pregnant smoker to miscarry. In addition, they may have their baby born with a cleft palate and/or cleft lip, they may give birth before time to a baby with an abnormally low birth weight, and they may also have an ectopic pregnancy. Moreover, if a woman smokes during or after pregnancy, her infant would have higher risks of dying from Sudden Infant Death Syndrome (SIDS) (National Cancer Institute, 2017). This implies that even after birth, a mother’s consumption of tobacco contents is harmful to the baby because the baby feeds from her breasts. Furthermore, according to CDC (2018), a pregnant smoker may likely experience stillbirth whereby her baby may die before birth.

Quitting smoking reduces the risk of many diseases caused by the habit, including COPD, heart disease, and cancer. Data from the U.S. National Health Interview Survey indicate that if one quits smoking, they have reduced chances of dying from illnesses that are smoking-related as compared to those who continues to smoke. “Smokers who quit before age 40 reduce their chance of dying prematurely from smoking-related diseases by about 90%, and those who quit by age 45-54 reduce their chance of dying prematurely by about two-thirds” (National Cancer Institute, 2017). Generally, quitters have substantial life expectancy gains in comparison to those who continue to smoke. According to the U.S. National Health Interview Survey, quitters aged between 25 and 34 live longer for about ten years, 35 and 44 for about nine years, 45 and 54 for about six years, and 55 and 64 for about four years.

It is therefore only through quitting that one would be free from the problems caused by smoking. In this respect, there can never be specific solutions to specific health problems caused by smoking; rather, the problems may be best addressed through solutions whose target would be to make one quit. One of the solutions, as suggested by Usman and Davidson (2016), would be to set the stage to quit by mentally preparing oneself. One may also quit by controlling cravings of smoking by using nicotine replacement products which should be used based on consultations with a doctor. Another solution may be to apply SmokEnders’ behavioral changes in completely breaking emotional bonds developed between smokers and cigarettes.

Smoking affects almost every organ of the human body and is thus detrimental to health. It causes fatal diseases such as cancer, heart disease, COPD, and can also damage the mouth and throat. It results into premature deaths that could otherwise be prevented. It also affects pregnant women who may experience increased risks of orofacial clefts in infants, ectopic pregnancy, sudden infant death syndrome, low birth weight, stillbirth, and preterm delivery. As such, quitting smoking has several health benefits and generally increases one’s life expectancy. This is so irrespective of the age at which one quits the habit.

American Lung Association. (2018). “10 health effects caused by smoking you didn’t know about”.  American Lung Association . Retrieved May 28, 2018 from  http://www.lung.org/our-initiatives/tobacco/reports-resources/sotc/by-the-numbers/10-health-effects-caused-by-smoking.html

CDC. (2018). “Health effects of cigarette smoking”.  Centers for Disease Control and Prevention . Retrieved May 28, 2018 from  https://www.cdc.gov/tobacco/data_statistics/fact_sheets/health_effects/effects_cig_smoking/index.htm

National Cancer Institute. (2017). “Harms of cigarette smoking and health benefits of quitting”.  National Cancer Institute . Retrieved May 28, 2018 from  https://www.cancer.gov/about-cancer/causes-prevention/risk/tobacco/cessation-fact-sheet#q8

NHS. (2018). “How smoking affects your body”.  NHS . Retrieved May 28, 2018 from  https://www.nhs.uk/smokefree/why-quit/smoking-health-problems

Usman, M. & Davidson, J. (2016).  Tips on how to stop smoking . Mendon, MA: Mendon Cottage Books.

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Causes and Effects of Smoking Research Paper

Cultural influences, social influences, psychological causes, effects of smoking, works cited.

Smoking is the habit where burned tobacco or cannabis is inhaled. Smoking is mostly practiced for recreation purposes. Smoking mainly involves smoking of cigarettes. Other methods that are employed for smoking tobacco include use of pipes as well as cigars. Smoking is considered as the most common method of recreation drug use.

Tobacco smoking is considered as the leading method of smoking. Other forms of drugs that are also smoked include cannabis and opium. The habit of smoking is approximated to have started as early as 5000BC and was practiced by different societies across the world. Smoking in early generations was usually being done for religious ceremonies, cleansing rituals as well as offerings to deities.

Nowadays, people smoke mainly for recreation reasons. There are many reasons why people smoke nowadays. However, these reasons can be divided into three main categories; psychological social, physical and cultural reasons. The physical causes that trigger smoking concern the human body. Since nicotine that is contained in cigarette is an addictive substance, the bodies of those who smoke feel the urge to take it in as it has a calming effect. In many cases, such people smoke whenever they feel jaded lonesome or anxious.

Just a little amount of nicotine is known to make the body of the smoker get energized and improve attentiveness when absorbed by the lungs or intestines. The calming as well as the stimulating effect that accompanies smoking tobacco is linked to the nicotine present in tobacco that stimulates the brain and some nerves that increase the heart rate, blood pressure subsequently, increasing respiration.

In many cases, the media which includes the newspapers, television and radio stations has associated smoking to glamour pleasure and adventure. As a matter of fact, most classic movies present smoking as positive and strong cultural images. Moreover, we are all subject to advertising that intentionally upholds the habit of smoking and makes positive relations with brands. Unfortunately, these images do not show the negative effects of smoking (Psychological Effects of Smoking 3).

On the other hand, social influences are highly attributed with peer pressure which is a social ill that is hard to defy. When one has a friend who smokes, he/she is likely to be influenced into the habit if not careful. Consequently, it becomes very hard to quit the habit as it may seem awkward as it may be seen as condemnation of their routine. As a matter of fact, smoking strengthens the friendship between smokers.

There are various psychological reasons that can lead to smoking. For instance, the universal desire for expression is a major reason why some people smoke. Smokers claim that smoking of cigarettes helps in enhancing one’s mood.

Some studies indicate that it is true that smoking of cigarettes causes some calming effects in additional to stimulating effects. The effects of cigarettes smoking varies with the amount of nicotine present in the blood stream. Most smokers have realized that the effects of smoking cigarettes depends on the quantity of nicotine present in the blood stream.

Subsequently, smokers either take shorter or longer puffs in order to realize the desired effects. Smoking is associated with a feeling of euphoria, calmness as well as a perception of performance enhancement. Studies show that smoking really causes improvements in performance. The enhancement in reaction and processing time after smoking cigarettes results because of nicotine that is present in a cigarette which is a psychomotor stimulant.

Unfortunately, the enhancement effects of cigarette smoking is known to last only for a short time, although smokers continue to smoke believing that they will continue receiving the enhancement effects from cigarettes. Some people continue smoking as a result of the psychological addiction that is associated with nicotine that is present in cigarettes. Those people that have smoked for a long period continue their smoking practice as a means of relieving their stressful situations.

When smokers are tired, they opt to smoke in order to receive the stimulating effects from cigarettes. The psychological effects that are associated with smoking are the one that makes smokers to experience a lot of challenge while stopping the smoking habit. Although the physical effects disappears fourteen days after stopping smoking, the psychological smoking effects are known to last for years after quitting smoking (Psychological Effects of Smoking 5).

Despite the high rate of smoking that is witnessed in the contemporary world. Smoking is associated with various adverse effects. For instance, smoking of tobacco is known to cause gum diseases, yellowing of teeth as well as teeth decay. Similarly, the tar that is contained in tobacco is very dangerous.

The tar is known to cause discoursing of teeth as well as triggering throat cancer. Smoking is highly attributed with narrowing of the blood-vessels which subsequently trigger high blood pressure and stroke. Nicotine that is present in tobacco increases the pulse rate of the heart that overworks the heart. Similarly, tobacco smoking is associated with carbon monoxide that results to accumulation of cholesterol deposits in the artery blood vessels that cause blood pressure and eventually stroke.

Equally, lack of blood circulation in limbs as a result of accumulation of cholesterol in the blood vessels can lead to amputation. Smoking of tobacco triggers bronchitis. This is because smoke from tobacco possesses hydrogen cyanide and other dangerous chemicals that attack the lining of the bronchi; consequently, inflaming it’s lining that increase the probability of someone contracting bronchitis (Harmful Effects of Smoking par. 2-4).

Apart from health related issues, smoking is also linked to some negative social effects. Smoking is known to strain social interaction between the smokers and non-smokers. The bad smell that is associated with smoking puts off many non-smokers from establishing close relations with smokers. Similarly, the health effects that are associated with secondary smoking also put off non-smokers.

Nevertheless, the contemporary generation has adapted appropriate smoking habits, nowadays, smokers do not smoke in public areas, but smoke in isolated places in order to prevent exposing non-smokers to the dangerous effects that are associated with secondary smoking.

Moreover, smoking has been noted to make some people to steal. Stealing in order to get money to buy cigarettes happens to those smokers that are already addicted to smoking and are not earning to afford money to buy cigarettes (Harmful Effects of Smoking par.6).

People smoke due to various reasons that range from social; cultural as well as psychological. Smoking is known to have very detrimental health consequences. For instance, smokers are more vulnerable to suffer from cancer, blood pressure, stroke as well as bronchitis. Thus, people ought to be well informed about the dangers of smoking and those that are smoking, but willing to stop smoking being assisted according.

”Harmful Effects of Smoking.” Ciggyfree. n.p., 2011. Web.

“Psychological Effects of Smoking.” Gumactions. n.p., 2004. Web.

• Chicago (A-D)
• Chicago (N-B)

IvyPanda. (2024, February 23). Causes and Effects of Smoking. https://ivypanda.com/essays/causes-and-effects-of-smoking/

"Causes and Effects of Smoking." IvyPanda , 23 Feb. 2024, ivypanda.com/essays/causes-and-effects-of-smoking/.

IvyPanda . (2024) 'Causes and Effects of Smoking'. 23 February.

IvyPanda . 2024. "Causes and Effects of Smoking." February 23, 2024. https://ivypanda.com/essays/causes-and-effects-of-smoking/.

1. IvyPanda . "Causes and Effects of Smoking." February 23, 2024. https://ivypanda.com/essays/causes-and-effects-of-smoking/.

Bibliography

IvyPanda . "Causes and Effects of Smoking." February 23, 2024. https://ivypanda.com/essays/causes-and-effects-of-smoking/.

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