obesity in the uk essay

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Publication, Part of Health Survey for England

Health Survey for England, 2021 part 1

Official statistics, National statistics, Survey

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• Part 3: Drinking alcohol

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• Overweight and obesity in adults

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• Part 1: Methods and definitions

This report examines the prevalence of overweight and obesity among adults in 2021. The estimates were produced using prediction equations that adjusted self-reported values of height and weight in order to predict measured values of height and weight. 

Detailed tables accompanying this report can be accessed here .  

Key findings for 2021

• In 2021, 26% of adults in England were obese. 
• A higher proportion of men than women were either overweight or obese (69% compared with 59%). 
• Obesity prevalence was lowest among adults living in the least deprived areas (20%) and highest in the most deprived areas (34%).
• 11% of obese adults reported that they had had a diagnosis of diabetes from a doctor, compared with 5% of overweight adults and 3% of those who were neither overweight nor obese.  
• Introduction

Obesity is a major public health problem in England and globally (Source: World Health Organization ). In adults, overweight and obesity are associated with life-limiting conditions, such as Type 2 diabetes, cardiovascular disease, and some cancers. 

The burden on the National Health Service (NHS) due to obesity and related illnesses is well recognised. The monetary cost each year, uplifted for inflation, was estimated at £6.1 billion in 2019 (Source: Department of Health and Social Care ). 

The COVID-19 pandemic has had a disproportionate effect on people with obesity, who are at increased risk of being hospitalised, admitted to intensive care, and of dying from COVID-19 (Public Health England, 2020; Saul, Gursul and Piernas, 2022). 

The Health Survey for England (HSE) is the main data source for monitoring overweight and obesity in the general population in England. Between 1993 and 2019, height and weight were directly measured during the interviewer visit in each year of the HSE series, and these values were used to calculate body mass index (BMI). 

For most of 2021 it was not possible to directly measure participants’ height and weight because of COVID-19 pandemic precautions. Instead, participants were asked about their height and weight during the telephone interview. This report presents findings on the prevalence of overweight (including obesity) and obesity for adults after applying adjustments to these self-reported heights and weights. 

Last edited: 15 December 2022 5:13 pm

Pages in this publication

• Adults' health-related behaviours
• Part 1: Smoking
• Part 2: E-cigarette use
• Part 2: Overweight and obesity
• Part 3: Overweight, obesity and health
• Part 4: Trends
• Part 5: References
• Part 6: Technical appendix
• Data Quality Statement

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Article Contents

1. why is rising obesity a problem, 2. what determines food choices, 3. what can governments do to reduce obesity, 4. final comments, obesity, poverty and public policy.

• Article contents
• Figures & tables
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Rachel Griffith, Obesity, Poverty and Public Policy, The Economic Journal , Volume 132, Issue 644, May 2022, Pages 1235–1258, https://doi.org/10.1093/ej/ueac013

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Obesity rates in the United Kingdom, and around the world, are high and rising. They are higher, and rising faster, amongst people growing up and living in deprivation. These patterns raise potential concerns about both market failures and equity. There is much that policy can do to address these concerns. However, policy can also do harm if it is poorly targeted or has unintended consequences. In order to design effective policies we need an understanding of who we are trying to target, and for what reasons. This paper provides an overview of some of the evidence, and some recent policy initiatives.

Obesity rates in the UK, and around the world, are high and rising. They are higher, and rising faster, amongst people growing up and living in deprivation. Rising obesity is a concern because it suggests that there are potential market failures that are leading people to make suboptimal choices about the foods they eat and the activities they engage in. These choices are potentially suboptimal in the sense that they may lead to higher than anticipated costs for the person themselves in the future and for wider society. Even if markets are functioning well, obesity may also potentially be a concern for equity reasons. If some children, for example those from disadvantaged backgrounds, are not able to access sufficient nourishment for healthy development, then there might be a role for policy intervention to provide greater equality of opportunity by ensuring access to a nutritious diet.

This paper provides an overview of the main evidence (and lack of evidence) on why obesity is an issue of public policy concern, what are some of the factors that might be driving rising obesity and its association with deprivation, and where policy might be most effective at improving welfare. There is much that public policy can do in terms of changing market signals, such as relative prices, and changing the choice environment to encourage people to make choices that better align with their own long-term interests. However, policy can also do harm if it is poorly targeted or has unintended consequences. In order to design effective policies we need an understanding of who we are trying to target, and for what reasons.

Obesity has risen dramatically in recent years in the UK and around the world. 1 Obesity is defined using the ‘body mass index’ (BMI), which is the ratio of weight to height squared (kilograms per |${\rm metre}^2$|⁠ ). BMI is a simple summary statistic used by medical professionals as an indicator of whether an individual is overweight (or underweight) and how overweight they are. An adult is obese when their BMI is over 30, they are morbid or severely obese when their BMI is over 40. BMI is not a perfect indicator, nor is it the only indicator that medical professionals care about. 2 For example, excess fat around the waist is another indicator. However, BMI is relatively easy to measure and track across time and locations, it is correlated with other measures, and it is seen as useful as a broad and relatively easy to measure indicator.

In England in 2018 nearly one in three adults was obese, and around one in twenty-five were morbidly obese. The rate of obesity in adults has doubled since 1993, shown in Figure  1 . Obesity rates are higher in more deprived areas (see Table 5 of NHSDigital, 2019 ). The statistics show similar trends in Scotland, Wales and Northern Ireland and other parts of the world.

Adult Obesity Rate in England.

Notes: Obese is defined as a BMI over 30; morbid or severely obese is defined as a BMI over 40.

Source . Table 6 of NHSDigital ( 2019 ).

Obesity in children is also high, for example, around one in five 10–11 year olds in England were obese in 2019. Worryingly, children are becoming obese at younger ages and are staying obese into adulthood (Johnson et al ., 2015 ). Obesity is more prevalent in more deprived areas, with children living in the most deprived regions being nearly twice as likely to be obese as those living in the least deprived regions. If we focus on children that are severely obese, the rate in the most deprived regions is over four times the least deprived areas (NHSDigital, 2020 ). 3

The gap in obesity rates between children growing up in the least and most deprived areas has widened over the last decade, as shown in Figure  2 . Panel (a) shows that in 2006 the gap was 8.5 percentage points; by 2019, it had grown to 13.3. Panel (b) shows that, for severely obese children, the gap between the share of children in the least and most deprived areas grew from 3.1 percentage points in 2006 to 5.3 in 2019.

Child Obesity Rate in England, by Deprivation.

Notes: Location is measured by the postcode of the child’s school. The dashed lines show 95% confidence intervals. See footnote 3 for definitions of the least and most deprived regions. Details on how obesity in children is measured is available in NHS ( 2011 ).

Source . Tables 13(a) and 14(b) of NHSDigital ( 2020 ).

Rising obesity is a concern because it suggests that there might be market failures that are leading people to make suboptimal choices. These market failures could arise if people do not fully account for the costs that obesity imposes on wider society, and on themselves, in the future when they make consumption choices. While there are many good papers that try to estimate the extent of these social costs, 4 the magnitude and nature of these costs (and in particular how they vary across different people), and what market failures are causing them, is still not fully understood. 5 However, policy-makers (and many others) believe that these costs are large, particularly amongst children, and especially amongst those growing up in deprivation.

Even if markets are functioning well, obesity may also potentially be a concern for equity reasons. Ensuring that all children, including those from disadvantaged backgrounds, are well nourished seems a corner stone of the provision of equality of opportunity. It is well established that child nutrition has important impacts on later life outcomes (see, among others, Currie, 2009 ; Almond et al ., 2018 and Lundborg et al ., 2021 ). Higher and growing rates of obesity amongst children from disadvantaged backgrounds might indicate that these children are not able to access sufficient nourishment, and suggest a role for policy intervention to provide greater equality of opportunity.

Obesity is associated with, and potentially causes, a number of adverse health, social and economic outcomes. Obesity arises due to a caloric imbalance (too many calories consumed relative to expended) leading to excess weight. It is also associated with, and might be an indicator of, a potentially unhealthy balance of nutrients, for example, a diet with too many sugars and carbohydrates. Obesity can also be associated with food insecurity (the inability to regularly access a healthy diet) if, when people do have the resources and ability to obtain food, they choose low-cost calorie-dense foods with a low nutritional value.

The main medical concern about excess weight is that it indicates an excess of fat (too much bone or muscle is not a problem). Excess fat is thought to increase an individual’s risk factor for a number of diseases, including metabolic syndrome, high blood pressure, atherosclerosis, heart disease, diabetes, high blood cholesterol, cancers and sleep disorders (NIH, 2021 ). The increased risk of these diseases likely increases costs to the healthcare system, both through an increase in the prevalence or severity of these diseases, and also because the costs of treating obese patients can be higher than normal weight individuals. Hospital admissions either directly attributable to obesity, or where obesity was a factor, are more prevalent amongst individuals from more deprived areas (NHS, 2020 ).

Obesity in childhood can have significant impacts on physical and psychological health (Sahoo et al ., 2015 ). The widening gap in obesity rates between children growing up in the least and most deprived areas raises the concern that obesity, and associated poor nutrition, may be important drivers of long-term inequalities. There is no strong causal evidence on the impact of obesity and poor nutrition on outcomes, but Public Health England (PHE) and the Centers for Disease Control and Prevention (CDC) in the United States highlight being obese as at least correlated with long-term harms in children, for example, through increased school absences and behavioural problems. We do not have good evidence on whether these effects are all driven by poor health, which feeds through to poor social and educational outcomes, or whether other factors are also at play. But at least amongst public health officials there is a concern that as well as affecting health, childhood obesity can have potentially important consequences for children’s long-term social and economic outcomes. 6 Economists have formalised the costs and related effects that fall on the person themselves in the future as ‘internalities’ . 7 For children, they are likely too young to understand the long-term consequences of eating an unhealthy diet, and so it is not factored into their decision-making, and for some children at least, their parents may also not fully account for these effects either.

Obesity is the result of an imbalance in energy consumed and energy expended. A common question is whether it matters what type of calories you eat, or is it only calories (net of energy expended on activities) that matter? Many governments give advice on the ‘optimal’ combination of foods; 8 however, the evidence seems to suggest that many different combinations of foods can yield healthy outcomes. 9 Recently, attention has focused on processed foods as leading to poor health outcomes, rather than foods containing any particular macro nutrients. 10

Excess consumption of some types of foods is also associated, and possibly causally so, with specific diseases. For example, high consumption of foods that have a lot of ‘free sugars’ (sugars added in manufacturing) can cause insulin resistance, which can cause diabetes (Ludwig, 2002 ; Kalra and Gupta, 2014 ; Imamura et al ., 2015 ). High consumption of salt can harden your arteries, leading to high blood pressure and cardiovascular disease (Trieu et al ., 2015 ).

Excess sugar consumption has been a particular target of policy-makers around the world. To see one reason why, consider Figure  3 . The horizontal axis shows age, and the vertical access shows grams of added sugar per day. Added sugar does not include naturally occurring sugars, for example in fruit or milk. The red dashed line is the UK government’s recommended maximum daily consumption based on medical advice. The solid black line shows the mean daily consumption reported in the National Diet and Nutrition Survey (NDNS); the dashed black lines show 95% confidence intervals. The NDNS is a continuous, cross-sectional survey. It is designed to collect detailed, quantitative information on food consumption, nutrient intake and nutritional status of the general population aged 1.5 years and over. The survey covers a representative sample of around 1,000 people per year. Respondents are asked to record consumption of all foods over two days. What is clear from panel (a) is that consumption is way above the recommended maximum at all ages, but particularly at younger ages. Panels (b)–(d) show that in fact almost all young children consume more than the medically recommended amounts of added sugar.

Sugar Consumption by Age.

Source . Panel (a) is Figure  1 , panels (b)–(d) are Figure  2 of Griffith et al . ( 2020 ), using National Diet and Nutrition Survey (NDNS).

Another common question is—if weight gain results from eating more calories than you burn in activity, is it only calories that matter, or does increasing activity through exercise lead to weight loss? In principle yes, but the relationship between exercise and weight loss is complicated. Exercise is good for you for all sorts of reasons, but some evidence suggests that on its own it might not lead to a lot of weight loss. This is partly because you would have to increase the amount of exercise you do by quite a lot, and also because the body responds in complicated ways that might mitigate some of the effects of increasing exercise on weight loss (see, for example, Prentice and Jebb, 2004 and Jebb, 2015 ). On the other hand, the analysis in Griffith et al . (2016a ) suggests that a reduction in the strenuousness of daily life may be at least partially responsible for the increase in obesity in adults over the 1980s and 1990s in the UK.

In this section we discuss some of the important factors that determine food choices. If markets are functioning well then consumers’ choices will be determined by market prices, income and the attributes of consumption that yield (positive or negative) utility. For markets to function well requires that consumers have good information about these attributes and about the utility they generate, and that consumers can and do act on this information appropriately; it also requires that consumers can access the foods they want to buy and that prices reflect costs.

We highlight some of the possible reasons that people might be making suboptimal choices, due to market failures or resource constraints. This is important because in order to design good policy we need to understand why some people are making bad choices. In the next section we consider how some specific policies might encourage people to make better choices, or to otherwise mitigate the negative consequences of their suboptimal choices, and whether they might also have other unintended consequences.

2.1. Food Prices

The price of foods is obviously an important determinant of consumers’ choices, and many policies aim to change relatives prices of different food products or food groups in order to incentivise producers and consumers to account for the excess social costs of consumption. In this section we highlight some of the main recent trends in food prices.

2.1.1. Price levels

From the 1980s until the mid-2000s, food prices have fallen in OECD countries; see OECD ( 2020 ). In the UK, this was particularly the case (Griffith et al ., 2015 ). The reduction in food prices benefited poorer households, for whom foods represent a significant share of their budget, and a much higher proportion than for richer households. While access to cheaper food could have contributed to people eating more, increasing the overall price of food seems unlikely to be an effective way to reduce obesity or improve diet quality. It will hit the poorest hardest, and the increase would likely have to be very large to have an appreciable impact. Food prices in the UK increased dramatically in the mid-2000s due to the depreciation of the sterling, though fell back below the OECD average reasonably quickly, but now look likely to rise again due to increased trade costs due to Brexit. There is so far no indication that these large price rises are having a positive impact on health or reducing obesity.

2.1.2. Relative prices

Changing the relative prices of different foods is a policy that many governments are pursuing, for example by introducing taxes on sugar sweetened beverages. The National Food Strategy (Dimbleby, 2021 ) has recommended expanding this to a more general tax on added sugar.

How do the prices of different food products and food groups vary with the healthiness of that product? This is not a simple question to answer. One common approach is to show that the average price per calorie of more healthy products is higher than that of less healthy products. 11

However, this comparison of prices misses the key point. Why do some foods cost more than others? The price of a product depends on the interaction of supply and demand factors. If something costs more to make or grow then this will typically be reflected in a higher price. However, if there are social costs to the consumption of some foods—that is, if the costs of production do not fully reflect the costs to society of that product being consumed—then the price might be ‘too low’, in the sense that there may be a benefit (in terms of higher social welfare) if government intervened to raise the price above the market price. It is the existence of these social costs that provide a rationale for taxes on unhealthy foods, such as sugary drinks. The appropriate level of these taxes does not depend on the differences in price between healthy and unhealthy products, but on the magnitude of the social costs that are associated with the consumption of unhealthy foods.

Another reason why the price of two products that cost the same to produce might differ is if firms have market power that enables them to mark prices up above marginal cost. If one product is much more popular, and has fewer substitutes, than another, then the firm can markup the price by more. Processed foods are typically produced and sold in more concentrated markets with more advertising, so if anything, we would expect the price of these products to be marked up above marginal costs by more than products where producers have less market power.

If healthy foods are more expensive to produce, there may also be equity reasons to provide targeted subsidies to low-income households to reduce the costs of healthy foods. For example, Healthy Start Vouchers and Free School Meals (discussed further in Subsection  3.4 ) do that in the UK.

2.1.3. Time use and prices

Some foods take time to prepare, and both the technology of food product and the opportunity cost of time can affect the costs of doing this. Households may increase their time spent searching for lower prices or in home production in order to reduce the costs of consumption at some points in time (Stigler, 1961 ; Becker, 1965 ; Aguiar and Hurst, 2007 ). They may also change the composition of their shopping basket (e.g., switching from a preferred brand to a cheaper generic product) to maintain its nutritional quality for a given cost.

Several papers study the ways that households reduced the prices they paid in response to the adverse shocks to incomes and food prices over the 2007–8 recession. Unlike during previous recessions in the UK the amount that households spent on food did not keep pace with rising food prices, and this led some to infer a substantial reduction in the size and nutritional quality of households’ food baskets (see, for example, Lock et al ., 2009 ; Taylor-Robinson et al ., 2013 ), with similar concerns in the United States (US Department of Agriculture, 2010 ; US Department of Agriculture, 2013 ). Griffith et al . ( 2016b ) showed that in the UK households were able to exploit various mechanisms to smooth, or ‘insure’, the quantity and nutritional quality of their food basket in the face of these adverse shocks. Evidence from the United States suggests that, as economic conditions worsened, households spent more time shopping and thus paid lower prices (Kaplan and Menzio, 2015 ), increased their use of sales, switched to generic products (Nevo and Wong, 2019 ) and switched to low-price retailers (Coibion et al ., 2014 ).

The costs of making and eating nutritious foods is not just the money spent on buying the ingredients, but also the time spent in preparation. Griffith et al . ( 2022 ) showed that over the last several decades the share of the food budget that goes on ingredients fell, while the share on processed foods increased. This is surprising because they also showed that the market prices of ingredients declined most. The distinction between ingredients and prepared foods is particularly relevant due to the recent attention on processed foods as leading to poor health outcomes, discussed above.

Griffith et al . ( 2022 ) documented that time spent on food management, which includes shopping and cooking, declined between 1974 and 2000; Cutler et al . ( 2003 ) showed the same is true in the United States. Mean hours on food management have fallen, with women reducing time spent and men increasing time spent on these activities, but not by enough to compensate for the reduction by women. Women are spending more time in the labour market; labour force participation has increased, hours worked conditional on participation have increased and wage offers have increased. Putting these together, Griffith et al . ( 2022 ) constructed a shadow price of a home cooked meal. The shadow price reflects both the costs of purchasing the ingredients and the time needed to prepare it for consumption, where the cost of time is estimated and has increased due to outside labour market opportunities for women. Figure  4 shows that, while market prices have fallen, the shadow price—the cost of home cooked food—has increased.

Market and Shadow Prices of Foods.

Notes : The shadow price incorporates the observed wage for labour market participants, and the maximum of the estimated market wage or the estimated reservation wage for non-participants.

Source . Figure 4.2 of Griffith et al . ( 2022 ).

2.2. Income

There is clearly a strong correlation between deprivation and obesity (see Figure  2 for example), and more generally there are strong intergenerational correlations in health and income (see, for example, Case et al ., 2002 ). However, convincingly identifying the causal impacts of income on obesity and nutrition in a developed countries context remains a challenge.

A large and growing literature suggests that even relatively mild negative economic shocks in childhood can have long lasting negative impacts, although these are heterogeneous (see the survey in Almond et al ., 2018 ). For example, Hoynes et al . ( 2016 ) used the roll out of the Food Stamp Program in the United States in the 1960s and early 1970s to show that access to food stamps in childhood leads to a significant reduction in the incidence of metabolic syndrome (conditions that include obesity, high blood pressure, heart disease and diabetes) and, for women, an increase in economic self-sufficiency. However, a literature that looks at the short-run impacts of economic shocks suggests that diet quality is either not affected by, or is improved by, adverse economic conditions, 12 and Adda et al . ( 2009 ) showed that permanent income shocks have little effect on a range of health outcomes.

Another way that income and deprivation might affect the nutritional quality of individuals’ diets is through the availability of healthy foods. Many papers have documented that healthy foods are less available, or cost more, in lower income neighbourhoods—what is referred to as ‘food deserts’. 13

One important question, on which there is still limited evidence, is what is the direction of causation in this observed relationship. The food offering in any location is a result of supply and demand factors. Is the supply of healthy foods driven by restrictions to supply, or by differences in demand preferences by consumers in those locations? Allcott et al . ( 2019a ) provided evidence for the United States that it is largely differences in preferences, and not supply constraints. The answer to this is important for policy design; either response might merit policy intervention, but the effective policy will differ. Even where differences in the food offering are driven by differences in the market demand curve, it might be that individuals within a market with a restricted offering have preferences that differ from the mean, and they are affected by supply constraints.

In the next section we discuss some of the ways that income might interact with other factors to affect the way that people make decisions, and that might lead to market failures and suboptimal outcomes.

2.3. Information, Cognition, Self-Control and Advertising

In addition to prices and incomes economists have long studied the importance of information, and the ways that information is processed, in determining consumer choices (see, for example, Stigler, 1961 ; Nelson, 1970 ; Loewenstein et al ., 2014 ), and the role of information in promoting healthier food choices (see, for example, Schofield and Mullainathan, 2008 ; Wisdom et al ., 2010 ; Reutskaja et al ., 2011 ).

There is a long history of government policies that aim at providing information and education, for example, on the safety benefits of wearing seat belts and the health consequences of smoking. There have been many information campaigns on food and nutrition; in the UK these have included the Eatwell Guide, the five-a-day campaign, Change4life and nutrient labelling regulations, amongst many others.

Information campaigns will be most effective where people want, but lack, information. One important reason that some campaigns might not be that successful is if people already have the information they need (people probably already know that vegetables are good for them). However, work by behavioural economists suggests that people do not always fully pay attention to the information they have when making decisions (Bordalo et al ., 2013 ), for example, some people may group products into categories in order to reduce ‘cognitive overload’ (Mullainathan et al ., 2008 ). Work by Sendhil Mullainathan and colleagues 14 has looked at the impact of poverty on cognition. The poor often behave in less capable ways, which can perpetuate them staying in poverty. This body of work argues that poverty directly impedes cognitive function, because poverty-related concerns consume mental resources, leaving less for other tasks. The fact of being poor means that you have to cope not only with a shortfall of money, but also with many other calls on cognitive resources. This view suggests that the poor are less capable not because of inherent traits, but because the very context of poverty imposes a load of concerns on people that impedes cognitive capacity.

Another reason that people might not fully take account of all of the information available to them is that they might succumb to temptation due to self-control problems. Read and Van Leeuwen ( 1998 ) and Sadoff et al . ( 2020 ) provided some of the most direct evidence (based on experiments in the field) of self-control problems in diet. Cherchye et al . ( 2017 ) showed that, as well as some people eating a healthier diet than others, there is considerable variation in the quality of most individuals’ diets over time that cannot be explained by standard factors such as prices and incomes, and which is likely to be at least partially driven by self-control problems in food choice.

An extensive psychological literature shows that individual choice behaviour varies with context and time, and that individuals sometimes use self-regulation and behaviour modification in an attempt to mitigate these influences (see the references and discussion in Rabin, 1998 and DellaVigna, 2009 ). For example, experimental evidence suggests that individuals may be willing to impose (sometimes costly) commitments on themselves. 15 New Years’ resolutions to eat a more healthy diet are an example of a common form of self-regulation and behaviour modification with regards to diet (Dai et al ., 2014 ; 2015 ).

Figure  5 shows an example of these fluctuations in diet quality over the calendar year. Panel (a) shows variation in the nutritional quality of food purchased by a large sample of UK households. 16 This suggests a clear ‘reset’ in January of each year to a healthier diet, with a decline over the year. Panel (b) shows the same trend in Google searches for the term ‘healthy foods’.

Variation in Diet Quality.

Source . Figures 1(b) and 2(a) in Cherchye et al . ( 2017 ).

Cherchye et al . ( 2017 ) used information on individuals’ stated preferences and attitudes to investigate whether greater fluctuations in the share of calories from healthy food reflect impulsive behaviour. Their findings suggest that fluctuations are larger for individuals who state that they are more impulsive (e.g., spend money without thinking). They relate their findings to the literature that finds empirical evidence of considerable within-individual variation in choice behaviour in other settings, 17 as well as in grocery purchases using alternative identification strategies. 18 They formalise this behaviour in a two-selves model of food purchasing behaviour in the spirit of this literature, in which individuals’ food choices are the outcome of an intra-personal bargaining process between a healthy and an unhealthy self. 19

What affects might advertising have on food choices? In the economics literature advertising is modelled as either informative (it gives consumers information about a characteristic of the product) or distortionary (it gives consumers misleading information, or distracts them from information they have). 20 Informative advertising will improve the choices that consumers make, while distortionary advertising will lead to worse choices. Another important distinction for our purposes here is whether the impact of advertising is to expand the market, or whether it is largely rivalrous, leading to shifts in market share between firms within a market. If advertising expands a market then it is more likely to have adverse impacts on nutrition (if the products being advertised are less nutritious), whereas if advertising largely leads consumers to switch between products that have similar nutrient value (e.g., between Coca Cola and Pepsi) then its impact on nutrition will likely be smaller. We return to discuss this further in Subsection  3.3 .

Advertising might amplify problems of temptation and self-control; the products that are advertised most heavily are also those that are the least healthy (see, for example, the figure on UK advertising expenditure by food group in Abi-Rafeh et al ., 2021 ). Experimental evidence shows that children exposed to food advertising ate more and were more likely to be obese. 21 Advertisers can frame a consumers’ view of a product using a desirable product category, or transfer desirable attributes from other products in the same category in the consumers’ mind. For example, in the context of food advertising, a kind of chewing gum can be viewed as healthy by ‘coarse’ thinking consumers if it is advertised as low-fat (Schofield and Mullainathan, 2008 ). This may be particularly true for people living in poverty who have a lot of other things to worry about and so experience cognitive overload (Mani et al ., 2013 ).

Griffith et al . ( 2018a ) attempted to measure exposure of consumers to food advertising in the UK, and estimated that households in the lowest income quartile see something like 20% more adverts for unhealthy foods than households in the highest income quartile; this is because they watch more TV, and they watch at a time and watch TV shows on which these adverts are more likely to be shown.

Governments are considering, and have implemented, a large range of policies that change relative prices, alter the choice environment, provide information and education to consumers, incentivise firms to reformulate, encourage a more active lifestyle and more. Policies that are aimed at correcting market failures should reduce externalities (costs imposed on wider society) and internalities (costs imposed on the person themselves in the future), while minimising any unintended adverse consequences. Policies that are aimed at alleviating equity concerns should be well targeted and minimise deadweight costs.

Designing and implementing policies that meet these ambitions is difficult. 22 That does not mean that it is not worth trying, but it is important to recognise that policies can (inadvertently) do harm as well as good. For example, poorly designed taxes might fail to improve outcomes if people with high externalities or internalities do not respond, yet could impose additional costs on exactly those people it is intended to help.

3.1. Corrective Taxes

Corrective taxes are a common approach to tackle externalities. 23 Increasing the overall price of food seems unlikely to be an effective way to reduce obesity. It will hit the poorest hardest, and the increase would likely have to be very large to have an appreciable impact. Instead, corrective taxes generally aim to change relative prices , i.e., to increase the price of less healthy foods relative to more healthy foods.

To date, one of the most popular corrective taxes aimed at reducing obesity and improving nutrition is taxes on sugary soft drinks. 24 The UK introduced the Soft Drinks Industry Levy in 2018, and Dimbleby ( 2021 ) is recommending broader taxes on added sugar and salt in the UK. Griffith et al . ( 2020 ) reviewed twenty-seven studies of taxes in eleven jurisdictions—all studies find that taxes lead to increased prices—pass-through is lower in smaller jurisdictions; in settings like the UK, taxes are fully passed through to prices. Most studies find that taxes led to substantial reductions in purchases of soda. Allcott et al . ( 2019b ) provided further discussion of the evidence.

One key ingredient to understanding whether soda taxes are effective is to know whether they lead to reductions in consumption in those individuals who generate the largest externalities and internalities. Unfortunately, we do not have good estimates of the scale or distribution of externalities and internalities; this is a key piece of missing evidence. Policy-makers in the UK and elsewhere have targeted some specific groups more than others, including the young, poor and heavy sugar consumers. One question is whether these groups are responsive to taxes. If they are, and if policy-makers are right that they suffer higher internalities, then they gain in the long run due to reduced internalities, which compensates them for the loss from higher prices. However, if they are not responsive to taxes then they do not benefit from reduction in internalities, and they are made worse off because they pay higher prices.

Dubois et al . ( 2020 ) used UK data to study how well targeted taxes on sugary drinks are, and in doing so tackle a number of methodological challenges. It is important to capture heterogeneity in preferences and in responses across people, and in order to study how well targeted the policy is, to be able to relate this heterogeneity to demographics of interest. They focused on the young, poor and heavy sugar consumers because policy-makers have focused on these groups, for which they believe consumption leads to high internalities. Dubois et al . ( 2020 ) exploited longitudinal data and relaxed some of the parametric assumptions imposed by traditional methods for estimating demand in differentiated product markets. Their results show that high sugar consumers would be less responsive to a tax than low sugar consumers, but that the young are more responsive than the old, so this form of tax is well targeted in one dimension, but not the other.

O’Connell and Smith ( 2020 ) considered the design of taxes on sugar-sweetened beverages, accounting for the fact that firms have market power, showing how optimal policy depends on the relative size of price-cost margins among externality generating goods and alternative products, and the degree of consumer switching across these product sets. They showed that taking these factors into account can substantially increase the welfare improvements achieved by these taxes.

3.2. Incentivising Reformulation

Consumer information campaigns, such as those to promote greater consumption of fruit and vegetables (Stables et al ., 2002 ; Capacci and Mazzocchi, 2011 ) and reduce salt consumption (PHE, 2020b ), have been a favoured policy of governments. However, changing the behaviour of a large number of consumers can be challenging, for many of the reasons discussed above, and strong evidence on their effectiveness has been limited. Because of this, many governments have focused instead on encouraging and incentivising firms to reformulate (see, for example, Vagnoni and Prpa, 2021 ).

Griffith et al . ( 2017 ) showed that following a large public health campaign in the UK resulted in a decline in dietary salt intake but that this was entirely attributable to product reformulation; consumer switching between products worked in the opposite direction and led to a slight increase in the salt intensity of grocery products purchased.

When the UK soft drinks industry levy was introduced, an explicit aim was to encourage reformulation. The tax has two rates. Products that contain between 5–8 g of sugar per 100 mL are taxed at the rate of 18p per litre of drink, and those that contains 8 g of sugar per 100 mL or more are taxed at 24p per litre of drink. Because the tax is based on volume, not directly on sugar, the tax rate within a band declines in sugar intensity; see the dashed line in Figure  6 . The idea behind this design was to give producers incentives to reformulate to just below 8 g and just below 5 g. These points were chosen with detailed knowledge of the industry, and the technological feasibility of reformulation.

Reformulation Following the SDIL.

Notes: The dashed line shows the tax per gram of sugar under the UK Soft Drinks Industry Levy (SDIL), which was introduced on April 6, 2018. The bars are based on the Kantar (FMCG) Purchase Panel (Take Home) 2016–9 (Kantar UK, 2020 ). The figure was created in Stata using three lines of code: ‘replace sugars=sugars/100’ to make the variable gram of sugar per 100 g, ‘collapse (mean) sugars,by(rf prodcode)’ to make the data at the product (rather than transaction) level, and ‘twoway histogram sugars if (lowsugarcaloriefat==‘Regular’ |$|$| lowsugarcaloriefat==‘Standard’) & sugars |$\lt $| =20, width(0.25) lc(black) fc(black) frac |$||$| line taxpersugar sugars if (lowsugarcaloriefat==‘Regular’ |$|$| lowsugarcaloriefat==‘Standard’) & sugars |$\lt $| =20, lc(black) lp(dash) lw(thick) yaxis(2) legend(off)’ to draw the figure.

The different panels in Figure  6 show the evolution of the distribution of soft drinks available in the market by sugar intensity. Prior to the introduction of the tax (panels (a) and (b)) there was a mass point of products with around 10 g of sugar per 100 g; this is approximately the sugar intensity of a standard can of Coca Cola. After the tax (panels (c) and (d)) we see a shift towards lower sugar intensity, with a pronounced shifting to reformulate below 5 g per 100 g, the lower tax threshold, and by 2019 we see considerable bunching just below this point. 25

This result is somewhat surprising, as standard models do not suggest that the optimal tax design is tiered in this way. Nonetheless, it seems in this case that the introduction of the tax was at least associated with reformulation. However, more work is needed to understand whether this design was what caused the reformulation. What would a more standard linear corrective tax on sugar have achieved? If, for some reason, this banded design was more effective, what does it require in terms of information about the technology of production to know where to position the bands if it was to be extended to other products.

3.3. Changing the Choice Environment

A large number of policies aim to change the choice environment in which consumers make decisions, by altering the products that consumers perceive to be in their choice set, removing temptation and changing the way that information is presented. These types of policies (sometimes called ‘nudge’ policies) are attractive because they are often low cost to the policy-maker and might be less regressive than taxes (Farhi and Gabaix, 2020 ).

Regulations specify how nutritional information is presented to consumers (for example, through simpler front-of-package labelling 26 and standards of measurement), how and when products can be advertised (for example, the UK bans online advertising of products that are high in fat, sugar or salt (DCMS and DHSC, 2021 ), where products can be sold (for example, fast food outlets are restricted near schools, 27 and sugary treats are discouraged from being placed near the check out counter), amongst others.

Above we raised the possibility that advertising distorts choices, and we saw that unhealthy foods, and particularly very sugary products, are the most advertised. Dubois et al . ( 2018 ) studied the impact of banning advertising for junk food (using the market for crisps, or potato chips, as an example). They modelled consumer choice and firm behaviour, in a model where firms compete in prices and advertising. They showed that advertising affects the choices that consumers make, and affects firms’ strategic behaviours. However, in order to interpret the welfare impacts of this ban, we have to take a stance on whether advertising is informative of distortionary. 28 Dubois et al . ( 2018 ) did not have a strategy for identifying whether advertising for crisps is informative or persuasive, so they calculated the welfare impact of banning advertising in both situations.

Subjectively looking at adverts for junk food, which show sports stars and models eating crisps, it seems likely that they distract people from characteristics of the product that people do not like (for example, price and the bad health consequences of eating crisps), and lead people to choose to buy more junk food (than they would in the absence of adverts). In the case where adverts are persuasive and distort consumers’ decision-making the impact of banning junk food adverts is to lead consumers to pay more attention to the unattractive characteristics (price and unhealthiness). Because firms can no longer compete in advertising, and because consumers pay more attention to prices, price competition increases, and this leads prices to fall. So while banning persuasive advertising reduces purchases of junk foods, it also leads to a reduction in prices, which partially mitigates that impact.

In 2007 adverts for food and drink that are high in fat, salt or sugar (HFSS)—junk foods—were banned from children’s TV in the UK (see Section 8 of Conway, 2021 ). This led to a reduction in the number of adverts for HFSS that children viewed, but firms' response to the advertising restrictions partially mitigated this (Ofcom, 2010 ). Firms adapted their advertising strategies in a number of ways, such as shifting the timing of adverts to avoid showing them during children’s programs, and changed the nature of the adverts they showed. Despite the ban, most adverts that children see on TV are for junk foods (Griffith et al ., 2018a ), and because of this the UK government is currently legislating to extend restrictions to adverts for high in fat, salt or sugar (see Griffith et al ., 2019 and DHSC and DCMS, 2021 ).

3.4. Cash and In-Kind Benefits

Above we have cited evidence that poor nutrition is clearly associated with poverty, and argued that it is likely that this at least partially represents a causal relationship (although conclusive scientific evidence on this is still lacking). For example, it may be that poverty impedes cognitive functioning. Even in the absence of market failures associated with poverty, it might be that households living in poverty might not be able to obtain as nutritious of a diet as households with higher incomes. Society might take the view, particularly for children, that this is not the level of inequality we prefer, and want policies that improve the diet quality of children growing up in poverty.

Child poverty in the UK increased from 2011–2 to 2016–7, the first increase sustained over such a substantial period since the 1990s (Bourquin et al ., 2020 ). Out-of-work households are more likely to be in poverty—about 60% are in poverty, with the poverty rate in working households more like 20%. However, the share of households who are workless is reasonably low in the UK, or at least it was prior to the pandemic, so more children living in poverty are living in households with at least some work. We do not yet know the full impact of the COVID-19 pandemic, but it looks likely to be worse in households in poverty, and it may increase worklessness and poverty amongst some groups. The UK government introduced increases in benefits to help people through the pandemic; however, these were temporary (Waters and Wernham, 2021 ), and there have been large real-term cuts in the generosity of out-of-work benefits over the decade before the pandemic (Bourquin et al ., 2020 ). 29

The main policies in the UK that target children in poverty and/or child nutrition include cash benefits (such as the child credit component of universal credit), and in-kind and conditional benefits, such as Free School Meals and Healthy Start Vouchers.

Reforms to universal credit are the most direct way to lift households out of income poverty. A household on benefits currently gets around £3,000 per year for an extra child. However, increasing this would be expensive, and possibly not that well targeted at the poorest children or at improving nutrition. The value of Free School Meals and Healthy Start Vouchers is much lower, but they are targeted at out-of-work families or families with very low earnings. That means that boosting these benefits would benefit, on average, the very poorest households, compared to say raising Universal Credit standard allowances or the child elements.

Healthy Start Vouchers have been shown to be effective at improving nutritional outcomes (see, for example, Griffith et al ., 2018b ); however, take-up varies across these benefits. Figure  7 shows that it is lower for Healthy Start Vouchers, and has declined in recent years. Addressing this would need to be a priority to make this a more effective policy. Healthy Start vouchers are also available for low-income pregnant women before they give birth to their child; this is one of the few benefits that is available to (low-income) pregnant women, a time that is thought to be important for later life health outcomes (see, among others, Case et al ., 2002 ; Currie 2009 ; Almond and Currie, 2011 ; Almond et al ., 2018 ).

Take-Up Rates of Different Child-Related Benefits, 2011–8.

Notes: The decline in take-up of child benefit is related to the introduction of the high income child benefit charge in 2013.

Source . Figure  2 of Augsburg et al . ( 2021 ) from Crawley and Dodds ( 2018 ), HMRC ( 2019 ; 2020 ) and Holford and Rabe ( 2020 ).

Free School Meals provide food directly to children, so are likely to be particularly effective if we think that an important problem is that parents are able or do not provide sufficient nutritional foods (for any of the reasons discussed above). There may be challenges in expanding Free School Meals depending how it was expanded. For example, in April 2020 the government introduced the COVID Summer Food Fund, which aimed to provide Free School Meals to children when they were not in school; however, half of children eligible for free school meals were not able to access this programme (Crawford et al ., 2020 ). Children who attended school were almost six times more likely to get a free school meal than children who did not. Families of children who had a free school meal were more likely to use a food bank than families who could not. Augsburg et al . ( 2021 ) provided further discussion of these policies.

There is growing concern about the impacts that arise from people making suboptimal choices regarding food consumption. Market failures related to information, cognition and a lack of self-control potentially lead to high costs on wider society and on the person themselves in the future. In addition, obesity and poor nutrition seem likely to be important constraints on the opportunities of children, particularly those growing up in deprivation, raising equity concerns.

There is much that policy can potentially do in terms of changing market signals, such as relative prices, and policies that change the choice environment to encourage people to make choices that better align with their own long-term interests. But to design these policies well we need a better understanding of who we are trying to target, and for what reasons.

We do not know enough about the magnitude and distributions of the market failures: what are the major externalities and who generates most of them, and what are the unanticipated future costs that are caused by obesity and poor nutrition and how do the vary across people? There is a growing body of evidence on these issues, but much of it is still anecdotal or based on correlations. A better evidence base on this is not simply of academic interest, it is essential to design a well-targeted policy. Poorly targeted and poorly designed policies can do harm to the individuals they are aiming to help.

Many of these policies will also interact in important ways. For example, soda taxes increase the prices of sugary drinks and reduce consumption through the price channel, but taxes may also change firms’ other strategic choices, such as advertising. Advertising itself can shape demand, affecting price elasticities, and has long-term effects on demand, leading to dynamic considerations. Careful consideration needs to be given to designing policies that are robust to these concerns. More work needs to be done to understand these interactions, and to understand how dynamic firm and consumer responses affect our evaluation of how effective and well targeted different policies will be.

It is also important to remember that there are potential equity as well as efficiency concerns. If poverty is an important factor driving the growth in obesity then it is also important to look at policies that directly lift people out of deprivation. The long-term decline (until recent rises) in food prices has had important welfare benefits for low-income households. Policies that lead to increased prices without improving nutritional outcomes will have adverse consequences for these households.

This paper draws heavily on joint work with a number of people who I have had the privilege to work with, in particular Pierre Dubois, Martin O’Connell and Kate Smith. I gratefully acknowledge financial support from the European Research Council (ERC) under ERC-2015-AdG-694822, the Economic and Social Research Council (ESRC) under the Centre for the Microeconomic Analysis of Public Policy (CPP), grant number RES-544-28-0001. Data supplied by TNS UK Limited. The use of TNS UK Ltd. data in this work does not imply the endorsement of TNS UK Ltd. in relation to the interpretation or analysis of the data. All errors and omissions remain the responsibility of the author.

This paper was originally delivered as the Past President’s Address at the RES 2021 Annual Conference.

See, for example, Ritchie and Roser ( 2017 ), NHS ( 2020 ), WHO ( 2021 ).

See Harvard School of Public Policy ( 2012 ) for a discussion of why BMI is used, and NHS ( 2019 ).

These statistics are based on the index of multiple deprivation (IMD), which is the official measure of relative deprivation for small areas (lower super output areas) in England. IMD deciles are calculated by ranking the 32,844 small areas in England from most deprived to least deprived and dividing them into ten equal groups. The most deprived line in the figure shows the mean for children living in the 10% of most deprived small areas nationally (decile 1), the least deprived are those living in the 10% of least deprived small areas nationally (decile 10). Further details are available at: https://www.gov.uk/government/statistics/english-indices-of-deprivation-2019 .

I will not attempt to survey this literature here, but see, for example, Bhattacharya and Sood ( 2011 ) and Allcott et al . ( 2019b ), both of whom discuss this issue in the US context.

See the useful articulation of what compelling evidence for suboptimal choices would look like in Bernheim and Taubinsky ( 2018 ).

See the summary in CDC ( 2021 ) and the references therein, including Vaidya ( 2006 ), Lloyd et al . ( 2012 ), Narang and Mathew ( 2012 ), Cote et al . ( 2013 ), Halfon et al . ( 2013 ), Mohanan et al . ( 2014 ), Pollock ( 2015 ), Morrison et al . ( 2015 ), Lundborg et al . ( 2021 ). See also PHE ( 2020a ).

See, for example, https://en.wikipedia.org/wiki/Internality and Herrnstein et al . ( 1993 ).

For example, many countries publish dietary reference intakes (Trumbo et al ., 2002 or public guidance such as the UK Eatwell Guide ( https://www.nhs.uk/live-well/eat-well/the-eatwell-guide/ ).

See, Venn ( 2020 ), and the systematic literature review in Fogelholm et al . ( 2012 ), which suggests that the combination of macro nutrients is not important for weight loss.

See, for example, Monteiro et al . ( 2019 ), WHO ( 2020 ).

One problem with this approach is that on the vertical axis (price per calorie) calories appear as the denominator and the measure on the horizontal axis is increasing in calorie density. This creates a mechanical relationship in the two variables. An alternative way to measure the cost of a product is price per kilogram. However, weight is often not a particularly useful unit of comparison across different food products.

Some examples include the following. Studying variation over time across US states, Ruhm (2000) showed that diets become less healthy and obesity increases when the economic situation improves. Dehejia and Lleras-Muney (2004) found that babies conceived in recessions have a lower probability of bad outcomes, such as low birth weight, congenital malformations and post-neonatal mortality. Griffith et al . ( 2016b ) and the papers cited above showed that, when households experienced negative income shocks over the 2007–8 recession, they were largely able to maintain the quality of their diet by adjusting shopping effort (searching out products on sale, visiting more stores to find cheaper offers) and compromising on non-nutritional characteristics (e.g., switching from branded to store brand products, buying in bulk).

This literature is mainly from the United States—see the references in Allcott et al . ( 2019a )—however, it has also been put forward by public health researchers in the UK—see, for example, https://www.sheffield.ac.uk/social-sciences/news/12-million-living-uk-food-deserts-studys-shows .

See, among others, Banerjee and Mullainathan ( 2010 ), Shah et al . ( 2012 ; 2018 ), Mani et al . ( 2013 ; 2020 ), Schilbach et al . ( 2016 ).

See Read and Van Leeuwen ( 1998 ), Read et al . ( 1999 ), Trope and Fishbach ( 2000 ), Ariely and Wertenbroch ( 2002 ) and Gilbert et al . ( 2002 ).

The figure is based on data on households’ shopping baskets. Each food product is categorised based on the Nutritional Profile Model (NPM). The NPM is the measure used in the UK to categorise foods for regulatory purposes (DHSC, 2011 ). It combines measures of ‘unhealthy’ characteristics (energy, saturated fat, sugars and sodium) and ‘healthy’ characteristics (fruit, vegetable and nut content, fibre and protein) into a single index. Products are assigned a score between −15 and 30: a higher NPS indicates a less healthy food product. For example, fruits and vegetables mostly have NPS scores less than zero, while chocolate bars, sweets and crisps tend to have NPS scores that are above 5.

See Oster and Morton ( 2005 ), Ashraf et al . ( 2006 ), DellaVigna and Malmendier ( 2006 ), Bucciol ( 2012 ) and Hinnosaar ( 2016 ).

See Shapiro ( 2005 ), Milkman et al . ( 2010 ) and Sadoff et al . ( 2020 ).

The model draws on insights from the literature on collective household models; see Chiappori ( 1988 ; 1992 ), Browning and Chiappori ( 1998 ), Chiappori and Ekeland ( 2009 ), Dunbar et al . ( 2013 ) and Browning et al . ( 2013 ).

Bagwell ( 2007 ) provided a comprehensive discussion about the impact of advertising on consumer choice.

See a review of the epidemiology and public health literatures in Boyland et al . ( 2016 ), Norman et al . ( 2018 ) and Russell et al . ( 2019 ) showed that children exposed to TV adverts for less healthy foods consume more food in the immediate period after watching them; Boyland et al . ( 2016 ) and Norman et al . ( 2018 ) showed that exposure to advertising for less healthy foods also influences food preferences and purchasing patterns.

One indicator of this difficulty is the fact that there is a large industry of diet and exercise programs on which many people spend a lot of time and money, with limited success.

Subsidies for healthy foods is another potential policy; see, for example, DHSC ( 2021 ). Price floors are another policy that has been advocated by the World Health Organisation; see the evaluation of the introduction of a price floor on alcohol in Scotland in Griffith et al . ( 2022 ).

As of April 2021, over fifty jurisdictions had implemented taxes on sugary soft drinks (GFRP, 2021 ).

Dickson et al . ( 2021 ) showed evidence of reformulation in response to the UK sugar tax include; Barahona et al . ( 2020 ) showed evidence that breakfast cereal producers in Chile reformulated in response to the introduction of new labelling regulations.

A number of studies show that front-of-package labels are effective in shifting consumption towards healthier products; see, among others, Rudd Center for Food Policy & Obesity ( 2008 ), Allais et al . ( 2015 ), Barahona et al . ( 2020 ), Fichera and von Hinke ( 2020 ).

Currie et al . ( 2010 ) showed that proximity to fast food outlets increase the probability of gaining weight amongst US teenagers.

These cuts were partly due to relatively high inflation combined with the cash-terms freeze to many benefits claimed by workless households, as well as to reductions in generosity due to the introduction of universal credit. The temporary increases only unwind these cuts by a small proportion.

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Home Essay Examples Health Obesity

The Issue Of Obesity In

• Category Health
• Subcategory Disease
• Topic Obesity

In this essay, I will discuss obesity in adults and the effect it has on their health and lifestyles. The focus of this essay will be on United Kingdom (UK) population. Obesity is known as the fat that is present in the body which is extra and can be harmful in a way of causing disability, cardiovascular disease, diabetes, cancer, high cholesterol, or death (Agha, 2017). Body Mass Index (BMI) is used to calculate obesity. BMI can be calculated by using a person’s weight in kilograms, divided by person height in meters (Bhaskaran et al., 2014). If the BMI of a person is above 30, it is classified as obese, below 25 is said to be overweight (Khorgami et al., 2015). In the past, it is observed that obesity is only present in the countries with high income but now the countries with low income are also facing this problem (El-Sayed, 2012).

In Europe, UK has the highest obesity rate with 26.9%. One person in every four is suffering from obesity in the UK. Among the 100% population of the UK, it is said that 61.7% of the people are either obese or overweight (Ogden, et al. 2015). Scarborough et al. (2011) stated that UK’s highest obesity rate is mostly due to poor diet and lack of exercise. Managing the weight of patients is the most leading practice for nurses. Nurses play an important role in identifying if a patient is obese or at risk to become obese and should be able to support this patient by giving them advice (McKee, 2017). This discussion is about the leading problem like obesity and socio-economic factors that are affecting it, like education, environment, or green space. Also, the impact on gender and ethnicity along with physiological factors like depression and stress will be discussed. The policies to tackle this health issue will also be discussed.

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There are a few signs, which are estimated to find out the inequalities of obesity. The factors that are listed up to define the estimation of obesity, relate to logical regressions and overweight rate for every group that is social or economic. These copies are used for the scope of categories in which gender, age, ethnicity, occupation status, and the status of health are included. Many socioeconomic factors affect obesity, such as housing, education, environment or Green spaces, health literacy, and income (Ogden et al., 2015).

Three possible types of relationships are built between education and obesity. The first one is the random relation that is formed to improve obesity to increase the number of education, the second one is a reverse random relationship that demonstrates, a better education leads to a healthy life and thirdly, the relationship is the absence of the random link between health and education by which education and obesity both are ignored (Bodor et al., 2010). Scrivano et al. (2017) said many factors are unobserved and have a major effect on obesity which may include the background of the family, their genetics, or the differences that individuals have. The above factors are also used to elaborate the fact that educated people are healthier. The people who are educated have use of the information related to health in a better way than the people who are less educated or not educated (Scrivano et al., 2017). Through education, the person has the ability to improve their thinking skills and access useful information. Patterson (2018) stated that people who have less education about the content of energy of food may lead their life towards obesity. Studies have shown that in lower social class, non-obese people have better food knowledge as compared to obese people of the same group (Kim, 2018). There is a possibility that people with high education can healthily set their lifestyles and have more knowledge about the risk that can make a person obese (Patterson et al., 2018). Although studies have shown that, educated groups are most likely to eat healthier than non-educated groups, it is also likely they will eat unhealthy due to time factors (Mann, 2013). Educated groups can have a very busy schedule, that time will not permit them to cook healthy food at home. So, although they are aware that it will be healthier to cook a meal at home than to buy, they will still order meals from restaurants to save time. This type of habit can also increase obesity in educated groups. It is known that there are several methods by which the effect of education obesity is driven out. This link is important as it results in many policies related to education, to set trends in education-based policies.

The interaction between genetics and the environment is considered as the midway to regulate balanced energy and the weight of the body (Choquet, 2011). However, genetic have impacts on the weight of the body and has gained attention in the past years. There is a noticeable increase in the popularity of obesity in the last 30 years. Mayne (2015) said that environmental change is known to be the biggest factor of obesity. Interaction of the environment that is said to be gene-environment interaction, is the one in which the genetically capable individuals had a major risk to develop obesity. Such an environment has a facility of high energy intake and the expenditure of energy is low (Mayne & Auchincloss, 2015). Environment goes towards weight gain when there is the absence of energy-dense foods and decrement in the demand for physical activities (Mayne et al., 2015).

Gretebeck et al. (2017) demonstrated that in the past years, there have been several studies that were done, and these studies resulted in the rate of health-related quality of life in women are lower than the men. This is not only figured out in the people who are healthy but also figured in the people that are under medical treatment (Gretebeck et al., 2017). Whereas the health-related quality of life for individuals that are suffering from severe diseases is less in females as compared to males. Jonikas et al. (2016) by studying the relationship between health and obesity, it is concluded that obesity is directly proportional to the health rate. It takes place among the people who have low health-rate. The direct cause of obesity is not clear, yet it is a reason for many major health issues (Jonikas et al., 2016). Women who are suffering from obesity have lower health rates as compared to men. In the UK, obesity is high in women as compared to men. There are 25% of men who are obese and 30% of women who are suffering from obesity in the UK (Jonikas et al., 2016). There are more obese women than men because women are more susceptible to obesity due to physiological features. However, the difference between women and men is not much.

Obesity is one of the main challenges that are faced by people all over the world. Obesity affects the countries that are developed or the countries that are still developing. Around 244 million people in the world are migrating from the countries they were born in and living in other countries. Ethnically, there are structured patterns that occur in the commonness of obesity. The most important thing is to understand the nature of these relationships in the formation of the policy for the prevention of obesity. Khorgami (2015) said in the UK, the rate of obesity of black people is higher than white people, 51% of black people are suffering from obesity. These obesity problems in different ethnicities can be avoided by making efforts in creating a better and healthy environment for living. There are three factors on which obesity in different ethnicities depends (Khorgami et al., 2015). First are the differences in behaviors of different ethnic groups directs towards obesity. Second the differences between the attitudes of the individual and the cultural norms that are related to how the weight of the body affects obesity. Lastly, the factor that affects obesity is the affordability of healthy food. Healthy foods tend to be very expensive and working families with low income may not be able to afford expensive foods. They will be limited with time and therefore will not be able to do the constant shopping for cheap healthy foods. So, they will rather go for cheap and unhealthy foods or whatever is available to eat. A great public response is needed to reduce the effects of obesity in different races and ethnicities. Moreover, the policies, programs, effort from the government, and the environment that plays supportive roles are also needed to overcome obesity (Khorgami et al., 2015).

Mannan et al. (2016) state that the connection between obesity and depression is not a one-way connection. It is observed from the studies that both obesity and depression feed each other. It is a self-destructive act. According to the researches, it is said that obese people are suffering more from disorders that are related to moods like depression, as compared to those who are not suffering from obesity (Mannan et al., 2016). There are many negative causes of obesity such as low self-esteem, poor self-image, and social isolation, these all factors are known as the main contributors for causing depression. People suffering from obesity found themselves stereotyped and discriminated against. Obesity also leads to many chronic diseases like diabetes or hypertension that has a great link with obesity (Mannan et al., 2016).

Stress and obesity has also a dual relationship with each other. The impact of stress and the health of people vary from person to person. Tomiyama (2018) many people gain weight during stress. People suffering from stress usually prefer comfort food that contains a great amount of fat and sugar. Which act as the stress releaser to the brain (Tomiyama, 2018). This is also observed that the people who are suffering from stress usually eat more snacks and that meals and intake of vegetables are fewer, this leads a person to be obese. These people also do not get themselves involved in physical exercises as stress is the main cause to promote physical inactivity. Workplace stress causes a person towards consuming fast food which results in obesity (Tomiyama, 2018).

Our Health guidance was mainly set to target obesity in adults and the health risk involved. Health professionals, including nurses, have a duty of care to educate themselves with resources and services available in their community or at their workplaces. Health care professionals must build a good relationship with their patients to advise them on health risks concerning obesity and the right path to take to help them in gaining a healthy diet, a healthy weight, and a healthy lifestyle. This advice includes physical activities and even psychological help if needed. Our Health guidance was also set to improve health and wellbeing in communities or societies to make them aware of the importance of physical activities, like exercise.

According to the NMC (Nursing and Midwifery Council) code of conduct, nurses must avoid bias and everyone should be treated with respect (NMC, 2015). Obese people stay longer in the hospital because they take a long time in recovery, so the nurses should particularly act polite to obese people (Jonikas et al., 2016). It is likely for some obese patients to stay longer in hospitals, depending on how effective the medications are. An example of this could be an obese patient with diabetes. They will have to stay in hospital even after their treatment to ensure their blood sugar is stable.

A nurse plays a leading role in the reduction of obesity. As is stated by Lineberry and Ickes (2015) that nurses should have to prevent illness and work for the betterment of the health of the individuals. A nurse plays a major role when it comes to obesity, as the doctors are not always present with the patient, but nurses do. So, the patient listens to them as they take care of them during their stay at the hospital (Lineberry & Ickes, 2015). A nurse can prevent a patient from being obese by giving the patient a proper diet chart and by keeping the check and balance that either the patient is following the diet or not. A nurse is also capable of referring obese patients or patients at risk of obesity to dietitians for help. The motivational sessions of nurses with the patients will have a great impact on them and they will be able to recover soon. Legally nurses owe the patients who are obese, and the nurses are responsible for their actions. Nurses should provide primary care to obese patients, the care like self-referral, GP referral, and the referral to acute care with the guidelines to lose the weight before the procedure is started (Lineberry & Ickes, 2015).

A great part of the people with low education is the one who is suffering from obesity. In the UK, a few people of the higher socioeconomic group are the victims of obesity. The people who have low education suffer more than the people from high education because they can build an understanding about the food that is harmful to them or the food that can cause obesity. Nurses play a role in preventing obesity as they are the one who stays 24/7 with the patients, patients’ starts listening to them more. Many physiological factors affect obesity. These factors are all related to obesity. With physiological factors, there are some socio-economic factors as well which majorly affect obesity.

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• Research article
• Open access
• Published: 15 January 2010

Analysis of the UK recommendations on obesity based on a proposed implementation framework

• Amudha S Poobalan 1 ,
• Lorna S Aucott 1 ,
• Sheraz Ahmed 2 &
• W Cairns S Smith 1  

BMC Public Health volume  10 , Article number:  17 ( 2010 ) Cite this article

10k Accesses

9 Citations

Metrics details

There is considerable expertise in the obesity field in identifying, appraising, and synthesising evidence to develop guidelines and recommendations for policy and practice. The recommendations, while based on evidence, are not formulated in a way that readily leads to implementation. This paper analyses the recent UK recommendations on obesity using a proposed implementation framework.

Two bibliographic databases (Medline and Embase) and various health related and government websites were systematically searched for obesity recommendations published between 1996 and 2007. All the documents published on recommendations for either prevention or treatment of obesity in the UK were assessed. A proposed implementation framework was developed for the purpose of this review. All the UK recommendations were critically appraised and results summarised according to the criteria used within the framework. Cross-country applicability of the proposed framework was assessed using the Swedish policy recommendations on obesity.

Most recommendations on obesity while demonstrating their basis in evidence, fail to meet the implementation standards. They tend to be non-specific in identifying who is responsible for implementation and monitoring, and often no timescale is indicated. The costs of implementation are rarely estimated and those responsible for such funding are not specified. There are some notable exemptions to the general pattern emanating from more operational and locally based groups. The Swedish policy details 79 proposals with responsibility clearly identified and costs are presented for 20 of them. This policy satisfied most of the framework criteria but failed to give details on evaluation, monitoring and the timeframe for implementation.

Conclusions

Public health has developed skills in appraising evidence and formulating recommendations based on appropriate evidence but these are often not implemented. Different skills are required to translate these recommendations into actions. Public health clearly needs to develop the implementation skills to a level comparable to the ability to synthesise evidence.

Peer Review reports

The UK adult overweight/obesity prevalence has increased steadily in the past three decades [ 1 – 3 ], despite targets set by the government [ 4 ] to reduce obesity levels. A review conducted by National Audit Office (NAO) in 1996 [ 5 ] showed no evidence of reduction. The Health Survey for England [ 6 ] in 2005 reported two thirds of adults and a third of children as overweight/obese. The recent obesity Foresight document [ 7 ] suggests that if current trends continue that by 2015, 36% of males and 28% of females will be obese, increasing to 60% and 50% respectively by 2050. This increase in obesity has consequences for individuals with increased risk of co-morbidities and costs, and for society with the current total cost (including NHS) at £7 billion rising to £50 billion per year by 2050 [ 7 ].

Systematic reviews and reviews of reviews [ 8 ] have investigated the evidence on prevention and treatment of obesity. These give various recommendations from which policies and strategies have been published with the common aim to reduce the rise in obesity. The aim of this assessment is to critically appraise all published UK obesity recommendations (1996-2007) for implementation criteria using a proposed implementation framework. An additional aim is to assess the cross-country applicability of the developed framework using the Swedish action plan for healthy dietary habits and increased physical activity [ 9 ]. This document has been identified as one of the most detailed documents on obesity policies [ 10 ] and provides an opportunity to evaluate the framework.

An initial scoping exercise was conducted to identify any implementation framework to assess guidelines on obesity. One framework was identified for monitoring and evaluating implementation of the global strategy on diet, physical activity and health published by the WHO in 2008 [ 11 ]. This framework suggested that process, outcome and output indicators should be identified by each member state. The literature was also searched for recurrent themes within various recommendations that were relevant to implementation. The proposed framework with critical items was developed based on these recurrent common themes which were: specificity of the target population, responsibility for implementation, monitoring, evaluation, time frame, priorities and cost estimation.

The electronic bibliographic databases, Medline and Embase, were then systematically searched for articles published from 1996 to December 2007. Mesh terms and key words for 'obesity', 'obesity guidelines', 'recommendations' were combined using Boolean operators to identify the relevant articles and reports. The search strategy used in Medline is detailed in the additional file, which was modified for use in Embase (see Additional file 1 ). A structured search of the internet was undertaken to identify the other guidelines and recommendations not indexed in the electronic bibliographic databases. The sources accessed were Science Direct, Blackwell Synergy, National Electronic Library for Health (Guidelines Finder), University of York Centre for Reviews and Dissemination, Public Health Electronic Library, The National Electronic Library for Health, Scottish Intercollegiate Guidelines Network (SIGN), The National Institute of Clinical Excellence (NICE), Health Development Agency (HDA), Department of Health (DoH), and The Stationery Office site. The key words used for the website searches were 'obesity', 'guidelines' and 'recommendations'. All the identified abstracts were scanned by two reviewers and full texts of potentially eligible documents were obtained and assessed according to the inclusion criteria.

All the included UK recommendations were appraised using the proposed framework. The relevant details were extracted from all the documents included. The assessment of the obesity recommendation documents are summarised according to this framework. The Swedish action plan for healthy dietary habits and increased physical activity [ 9 , 10 ] was critically appraised using the same criteria to assess the cross-country applicability of the developed framework.

The systematic search identified 4275 abstracts, of which 133 were potentially eligible. The full texts of these were critically appraised and 21 articles were included in the review. The results of the literature search and the selection process are presented in Figure 1 .

Selection process of the review . Flow diagram of the selection process of the review for the appraisal.

Key recommendations for obesity identified in selected UK reports

The reports identified key nutritional recommendations. These were to replace energy dense snacks and drinks with healthier alternatives from vending machines in school and fast food outlets [ 12 – 14 ]; to train teachers in healthy food advice and physical activity [ 12 ]; to shift consumer demand from high fat, high calorie diets to healthier alternatives [ 12 , 15 ] with the Government and Food Standard Agency (FSA) working together; to simplify food labelling for easy interpretation by the general population [ 16 ]; to ban marketing of unhealthy foods targeting children [ 17 , 18 ]; and to provide healthy diet and physical activity advice to pregnant and/or breast feeding women to promote weight control [ 14 , 15 ].

The reports identified key recommendations for physical activity. These were that schools and local authorities should improve physical activity levels by allocating ≥ 3 hours per week for physical activity among school children; make safer pedestrian routes [ 12 – 14 ]; provide information about pedometers for all age groups [ 12 , 14 ] and to consider single sex physical education classes to improve participation of girls and ethnic minority groups [ 12 – 14 ].

The recommendations for obesity management were that physicians should maintain databases for patients at risk of developing obesity [ 19 ] and for those receiving obesity treatment (drugs and surgery) [ 20 – 22 ]; that the Government should provide sufficient funds for the NHS for at least one specialist primary care obesity clinic within each Primary Care Trust area and to expand obesity services in secondary care to include bariatric surgery for morbidly obese people [ 12 , 23 ]; that easy access to specialist treatment for obese children and young people should be provided [ 24 ] and funds should be made available for doctors and nurses to train in obesity management [ 15 , 23 ].

These reports recommended that the Government should initiate a health education campaign specifically for tackling obesity [ 12 , 15 ]. Guidelines for drugs and obesity management should be constantly evaluated [ 25 ] with information about effectiveness of obesity treatment and preventative interventions being disseminated to appropriate health care professionals [ 26 ].

Analysis of UK obesity recommendations using the Implementation Framework

The 21 selected reports were analysed using the proposed implementation framework based on 7 criteria (see Additional file 2 ). The findings are summarized in Table 1 . All 21 studies [ 12 – 32 ] clearly define the target population and prioritise in terms of either prevention and/or treatment. Sub-groups of the community vulnerable to obesity are specifically targeted within recommendations. The organisations responsible for implementation [ 12 – 26 , 28 – 32 ] was considered by 20 of the studies. The Government, Department of Health, Cabinet Task Force, NHS and physicians were identified as having responsibility for monitoring of implementation, but 5 out of the 21 articles did not report on how the implementation progress should be monitored or evaluated. Achieving set milestones, conducting regular audits and maintaining databases on progress were tools suggested for monitoring and evaluating the progress of implementation. Although stated, there was no evidence of ownership of these published recommendations.

Only four reports considered an implementation timeframe [ 13 , 14 , 23 , 31 ]. The report by the Faculty of Public Health [ 13 ] set the time for achieving targets to be within 3 years of their report with goals set for the 1 st , 2 nd and 3 rd year whereas the Tayside report [ 14 ] set a 10 year timeframe with goals set at the 1 st and 5 th year. The other two reports mentioning timeframes gave no details. Two reports by NICE [ 20 , 21 ] predicted the uncertainty in implementation due to lack of expertise and resources plus training of doctors. Two other reports [ 12 , 24 ] merely stated that the implementation of recommendations was urgent.

Seven reports gave estimated implementation costs [ 14 , 20 – 23 , 28 , 32 ]. NICE gave NHS estimated costs for orlistat, sibutramine and bariatric surgery recommendations [ 15 – 17 ]. The Tayside local strategy for obesity report [ 14 ] gave costing for the extension of their weight management service to all Tayside GP practices, child obesity services and their food "dudes" programme [ 14 ]. One report [ 28 ] identified resources along with skills required for interventions. Of the remaining, eleven gave no costing, two others [ 13 , 19 ] suggested that their recommendations should be implemented after considering the available resources and the "Toolkit for obesity" by the Public Health Faculty [ 31 ] recommended that the NICE costing templates [ 32 ] for adult and childhood obesity management should be used.

Cross-country applicability of the developed framework

The Swedish action plan [ 9 ] has been identified as one of the most detailed documents [ 10 ] addressing obesity as part of the action plan for healthy dietary habits and increased physical activity. It has 79 proposals (called measures) in 12 specified policy areas (see Additional file 3 ) with detailed descriptions of the justification for each measure. It clearly identifies the people responsible for implementing all the 79 proposals highlighted. Only 20 out of the 79 proposals gave cost estimates, with one proposal indicating the split between development and implementation. However, the action plan did not provide adequate information in terms of monitoring, evaluation and time frames. Some of the proposals highlight the importance of evaluation but details of how this might be achieved or who would be responsible for the evaluation was not clear. The breakdown of the costing in 4 of the proposals gave an indication of time frame (e.g. EUR 8.5 million over 7 yr period or EUR 210.000 per year for 3 years and EUR 53.000 per year for 5 years), but was otherwise not clearly stated. Within the proposals, gaps and limitations which need to be addressed were identified, for example the lack of health information to ethnic minorities, lack of evaluation of organisational measures, and shortage of intervention research in Sweden.

Main findings of this review

This critical appraisal of obesity prevention/treatment recommendations in the UK using implementation criteria indicates that some aspects such as priorities and target populations are generally well laid out. However, important factors such as timeframes and cost estimations are not adequately addressed. The responsible organisations are often identified but actual ownership of the recommendations is unclear. Treatment recommendations for drugs and surgery were more specific with projections of cost and future eligible populations. However, prevention recommendations tended to lack clarity for timeframes and costings.

What is known and what this review adds

There is considerable expertise in the process of identifying, critically appraising, and synthesising the evidence to develop guidelines and recommendations for obesity policy and practice. However, there are indications that these recommendations are failing to be implemented despite being evidence based, which may be due to their formulation and presentation.

This assessment is the first to systematically appraise recommendations for obesity treatment/prevention in terms of the criteria for their implementation. All the recommendations within UK and one action plan from Sweden were appraised using an implementation framework. Another framework recently proposed by Sacks et al [ 33 ] has analysis grids for a comprehensive policy approach to reducing obesity hence identify areas for obesity policy action. Our review leads on from this by proposing criteria within such policies to be addressed for easier implementation.

Recommendations need to be framed in a manner to facilitate their implementation and this includes targeting, ownership, monitoring and evaluation, time frame and resource implications. This approach is generalisable and can be used to assess other strategy documents and their recommendations. It is worth noting that evidence based guidelines/action plans do not always give the essential elements for implementation at the initial stage but may be extended as formal implementation plans at a later date.

The NHS Modernisation Agency [ 34 ] with 24 Primary Care Trusts (PCTs) conducted a review to identify obesity strategies developed by the Trusts as a response to recommendations issued by the Faculty of Public Health [ 13 ]. This review found that the Trusts were at the early stages of development and implementation, and highlighted the evidence of current best practices by various Trusts. Since this review, two strategies have been published in England [ 35 ] and Scotland [ 36 ] which move away from focusing on the individual and instead consider broader holistic integrated approaches to obesity prevention such as healthy lifestyle adoption at all levels of society, but these still do not address the issues if implementation highlighted in this paper. The Swedish action plan identified as one of the most complete documents [ 9 ] provides detailed descriptions of 79 proposals and addresses most of the criteria identified in this framework but it does not address the issues of monitoring, evaluation or the setting of time frames. The essential elements identified in this proposed framework encompass issues at the level of recommendation/guideline formation that will facilitate implementation. Successful implementation of guidelines (in whole or in part) will result in various interventions being developed which can be assessed using a Health Impact Assessment [ 37 ] which reflects some of the broader issues covered by the proposed framework.

The literature search used a comprehensive strategy but many of the recommendation documents were not electronically indexed in databases and available only on websites. Efforts were made to identify all documents from various sources but recommendations by various groups, charities and local authorities may not be readily in the public domain.

The implementation framework was developed through a scoping exercise and was based on the recurring themes within guidelines and may require modification in light of experience with its use. The proposed framework thus provides a first step in assessing the obesity guidelines to emphasise the importance of addressing the essential elements contained within them for successful implementation.

Obesity recommendations in UK clearly define the target population and are well prioritized in terms of either prevention and/or treatment. Sub-groups of the community vulnerable to obesity are specifically targeted within recommendations with most identifying the organisations responsible for implementation. However, for recommendations to be successfully implemented, it is essential that they also have clear timeframes, costings and identify ownership, training and coordination within local organisations. Clinicians and academics involved in producing recommendations and policies should consult public health professionals who are more familiar with actual implementation of the proposed actions to ensure that their proposals are realistic for successful implementation. The proposed framework could be used as a basis and adapted for wider use in other countries, for other topics and for different target groups. Every effort should be taken to formulate evidence based recommendations that facilitate their effective implementation in view of the rapidly increasing obesity epidemic.

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Acknowledgements

We would like to thank the staff at Medical School Library, University of Aberdeen and secretarial staff in the Section of Population Health for their help with obtaining the full texts of the articles and documents. AP, LA and WCS were funded by the University of Aberdeen and SA was a student who was self funded. This study was funded by the Section of Population Health within the University of Aberdeen.

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Amudha S Poobalan, Lorna S Aucott & W Cairns S Smith

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Authors' contributions

The study was designed and planned by WCS. AP and SA carried out the systematic review. LA, AP and WCS contributed to the development of the implementation framework. AP and SA drafted the manuscript with the contribution from all authors. All authors read and approved the final manuscript.

Amudha S Poobalan, Lorna S Aucott and W Cairns S Smith contributed equally to this work.

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Additional file 1: Search Strategy. Search Strategy used in Medline which was modified for the other databases. (DOC 24 KB)

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Additional file 2: Analysis based on proposed framework. Analysis of articles on obesity recommendations based on the proposed implementation framework. (DOC 78 KB)

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Additional file 3: Cross-country applicability of the proposed framework. Analysis of the Swedish Action Plan based on the proposed framework. (DOC 32 KB)

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Poobalan, A.S., Aucott, L.S., Ahmed, S. et al. Analysis of the UK recommendations on obesity based on a proposed implementation framework. BMC Public Health 10 , 17 (2010). https://doi.org/10.1186/1471-2458-10-17

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Changing the narrative around obesity in the UK: a survey of people with obesity and healthcare professionals from the ACTION-IO study

Affiliations.

• 1 Fakenham Weight Management Service, Fakenham Medical Practice, Fakenham, UK [email protected].
• 2 Norwich Medical School, University of East Anglia, Norwich, UK.
• 3 MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
• 4 Novo Nordisk Ltd, Gatwick, UK.
• 5 Institute of Diabetes, Endocrinology and Obesity, Guy's and St Thomas' NHS Foundation Trust, London, UK.
• 6 Department of Medicine, University College London, London, UK.
• 7 School of Psychology, University of Leeds, Leeds, UK.
• PMID: 34193488
• PMCID: PMC8246368
• DOI: 10.1136/bmjopen-2020-045616

Objectives: To investigate the perceptions, attitudes, behaviours and potential barriers to effective obesity care in the UK using data collected from people with obesity (PwO) and healthcare professionals (HCPs) in the Awareness, Care, and Treatment In Obesity maNagement-International Observation (ACTION-IO) study.

Design: UK's PwO (body mass index of ≥30 kg/m 2 based on self-reported height and weight) and HCPs who manage patients with obesity completed an online survey.

Results: In the UK, 1500 PwO and 306 HCPs completed the survey. Among the 47% of PwO who discussed weight with an HCP in the past 5 years, it took a mean of 9 years from the start of their struggles with weight until a discussion occurred. HCPs reported that PwO initiated 35% of weight-related discussions; PwO reported that they initiated 47% of discussions. Most PwO (85%) assumed full responsibility for their own weight loss. The presence of obesity-related comorbidities was cited by 76% of HCPs as a top criterion for initiating weight management conversations. The perception of lack of interest (72%) and motivation (61%) in losing weight was reported as top reasons by HCPs for not discussing weight with a patient. Sixty-five per cent of PwO liked their HCP bringing up weight during appointments. PwO reported complex and varied emotions following a weight loss conversation with an HCP, including supported (36%), hopeful (31%), motivated (23%) and embarrassed (17%). Follow-up appointments were scheduled for 19% of PwO after a weight discussion despite 62% wanting follow-up.

Conclusions: The current narrative around obesity requires a paradigm shift in the UK to address the delay between PwO struggling with their weight and discussing weight with their HCP. Perceptions of lack of patient interest and motivation in weight management must be challenged along with the blame culture of individual responsibility that is prevalent throughout society. While PwO may welcome weight-related conversations with an HCP, they evoke complex feelings, demonstrating the need for sensitivity and respect in these conversations.

Trial registration number: NCT03584191 .

Keywords: epidemiology; general medicine (see internal medicine); medical education & training; public health.

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

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Obesity: Risk factors, complications, and strategies for sustainable long‐term weight management

Sharon m. fruh.

1 College of Nursing, University of South Alabama, Mobile, Alabama

Background and Purpose

The aims of this article are to review the effects of obesity on health and well‐being and the evidence indicating they can be ameliorated by weight loss, and consider weight‐management strategies that may help patients achieve and maintain weight loss.

Narrative review based on literature searches of PubMed up to May 2016 with no date limits imposed. Search included terms such as “obesity,” “overweight,” “weight loss,” “comorbidity,” “diabetes,” cardiovascular,” “cancer,” “depression,” “management,” and “intervention.”

Conclusions

Over one third of U.S. adults have obesity. Obesity is associated with a range of comorbidities, including diabetes, cardiovascular disease, obstructive sleep apnea, and cancer; however, modest weight loss in the 5%–10% range, and above, can significantly improve health‐related outcomes. Many individuals struggle to maintain weight loss, although strategies such as realistic goal‐setting and increased consultation frequency can greatly improve the success of weight‐management programs. Nurse practitioners have key roles in establishing weight‐loss targets, providing motivation and support, and implementing weight‐loss programs.

Implications for Practice

With their in‐depth understanding of the research in the field of obesity and weight management, nurse practitioners are well placed to effect meaningful changes in weight‐management strategies deployed in clinical practice.

Introduction

Obesity is an increasing, global public health issue. Patients with obesity are at major risk for developing a range of comorbid conditions, including cardiovascular disease (CVD), gastrointestinal disorders, type 2 diabetes (T2D), joint and muscular disorders, respiratory problems, and psychological issues, which may significantly affect their daily lives as well as increasing mortality risks. Obesity‐associated conditions are manifold; however, even modest weight reduction may enable patients to reduce their risk for CVD, diabetes, obstructive sleep apnea (OSA), and hypertension among many other comorbidities (Cefalu et al., 2015 ). A relatively small and simple reduction in weight, for example, of around 5%, can improve patient outcomes and may act as a catalyst for further change, with sustainable weight loss achieved through a series of incremental weight loss steps. In facilitating the process of losing weight for patients, nurse practitioners play an essential role. Through assessing the patient's risk, establishing realistic weight‐loss targets, providing motivation and support, and supplying patients with the necessary knowledge and treatment tools to help achieve weight loss, followed by tools for structured lifestyle support to maintain weight lost, the nurse practitioner is ideally positioned to help patient's achieve their weight‐loss—and overall health—targets.

The obesity epidemic

The World Health Organization (WHO) defines overweight and obesity as abnormal or excessive fat accumulation that presents a risk to health (WHO, 2016a ). A body mass index (BMI) ≥25 kg/m 2 is generally considered overweight, while obesity is considered to be a BMI ≥ 30 kg/m 2 . It is well known that obesity and overweight are a growing problem globally with high rates in both developed and developing countries (Capodaglio & Liuzzi, 2013 ; WHO, 2016a , 2016b ).

In the United States in 2015, all states had an obesity prevalence more than 20%, 25 states and Guam had obesity rates >30% and four of those 25 states (Alabama, Louisiana, Mississippi, and West Virginia) had rates >35% (Centres for Disease Control and Prevention, 2016 ; Figure ​ Figure1). 1 ). Approximately 35% and 37% of adult men and women, respectively, in the United States have obesity (Yang & Colditz, 2015 ). Adult obesity is most common in non‐Hispanic black Americans, followed by Mexican Americans, and non‐Hispanic white Americans (Yang & Colditz, 2015 ). Individuals are also getting heavier at a younger age; birth cohorts from 1966 to 1975 and 1976 to 1985 reached an obesity prevalence of ≥20% by 20–29 years of age, while the 1956–1965 cohort only reached this prevalence by age 30–39 years (Lee et al., 2010 ). Additionally, the prevalence of childhood obesity in 2‐ to 17‐year‐olds in the United States has increased from 14.6% in 1999–2000 to 17.4% in 2013–2014 (Skinner & Skelton, 2014 ). Childhood obesity is an increasing health issue because of the early onset of comorbidities that have major adverse health impacts, and the increased likelihood of children with obesity going on to become adults with obesity (50% risk vs. 10% for children without obesity; Whitaker, Wright, Pepe, Seidel, & Dietz, 1997 ).

U.S. obesity epidemic 2015.

Source . Figure adapted from Centers for Disease Control and Prevention (CDC). Retrieved from https://www.cdc.gov/obesity/data/prevalence-maps.html .

Association of obesity with mortality and comorbid disease

Obesity is associated with a significant increase in mortality, with a life expectancy decrease of 5–10 years (Berrington de Gonzalez et al., 2010 ; Kuk et al., 2011 ; Prospective Studies Collaboration et al., 2009 ). There is evidence to indicate that all‐cause, CVD‐associated, and cancer‐associated mortalities are significantly increased in individuals with obesity, specifically those at Stages 2 or 3 of the Edmonton Obesity Staging System (EOSS; Kuk et al., 2011 ; Figure ​ Figure2). 2 ). Mortality related to cancer is, however, also increased at Stage 1, when the physical symptoms of obesity are marginal (Figure ​ (Figure2). 2 ). Recently, a large‐scale meta‐analysis that included studies that had enrolled over 10 million individuals, indicated that, relative to the reference category of 22.5 to <25 kg/m 2 , the hazard ratio (HR) for all‐cause mortality rose sharply with increasing BMI (The Global BMI Mortality Collaboration, 2016 ). For a BMI of 25.0 to <30.0 kg/m 2 , the HR was 1.11 (95% confidence interval [CI] 1.10, 1.11), and this increased to 1.44 (1.41, 1.47), 1.92 (1.86, 1.98), and 2.71 (2.55, 2.86) for a BMI of 30.0 to <35.0, 35.0 to <40.0, and 40.0 to <60.0 kg/m 2 , respectively.

Association between EOSS stage and risk of all‐cause (A), CVD (B), cancer (C), and non‐CVD or noncancer mortality (D) in men and women. © 2011.

Source . Reproduced with permission from NRC Research Press, from Kuk et al. ( 2011 ). CVD, cardiovascular disease; NW, normal weight.

Comorbidities

Obesity is a chronic disease that is associated with a wide range of complications affecting many different aspects of physiology (Dobbins, Decorby, & Choi, 2013 ; Guh et al., 2009 ; Martin‐Rodriguez, Guillen‐Grima, Marti, & Brugos‐Larumbe, 2015 ; summarized in Table ​ Table1). 1 ). To examine these obesity‐related morbidities in detail is beyond the scope of this review and therefore only a brief overview of some of the key pathophysiological processes is included next.

Morbidities associated with obesity (Hamdy, 2016 ; Petry, Barry, Pietrzak, & Wagner, 2008 ; Pi‐Sunyer, 2009 ; Sakai et al., 2005 ; Smith, Hulsey, & Goodnight, 2008 ; Yosipovitch, DeVore, & Dawn, 2007 )

The progression from lean state to obesity brings with it a phenotypic change in adipose tissue and the development of chronic low‐grade inflammation (Wensveen, Valentic, Sestan, Turk Wensveen, & Polic, 2015 ). This is characterized by increased levels of circulating free‐fatty acids, soluble pro‐inflammatory factors (such as interleukin [IL] 1β, IL‐6, tumor necrosis factor [TNF] α, and monocyte chemoattractant protein [MCP] 1) and the activation and infiltration of immune cells into sites of inflammation (Hursting & Dunlap, 2012 ). Obesity is also usually allied to a specific dyslipidemia profile (atherogenic dyslipidemia) that includes small, dense low‐density lipoprotein (LDL) particles, decreased levels of high‐density lipoprotein (HDL) particles, and raised triglyceride levels (Musunuru, 2010 ). This chronic, low‐grade inflammation and dyslipidemia profile leads to vascular dysfunction, including atherosclerosis formation, and impaired fibrinolysis. These, in turn, increase the risk for CVD, including stroke and venous thromboembolism (Blokhin & Lentz, 2013 ).

The metabolic and cardiovascular aspects of obesity are closely linked. The chronic inflammatory state associated with obesity is established as a major contributing factor for insulin resistance, which itself is one of the key pathophysiologies of T2D (Johnson, Milner, & Makowski, 2012 ). Furthermore, central obesity defined by waist circumference is the essential component of the International Diabetes Federation (IDF) definition of the metabolic syndrome (raised triglycerides, reduced HDL cholesterol, raised blood pressure, and raised fasting plasma glucose; International Diabetes Federation, 2006 ).

Obesity is also closely associated with OSA. To start, a number of the conditions associated with obesity such as insulin resistance (Ip et al., 2002 ), systemic inflammation, and dyslipidemia are themselves closely associated with OSA, and concurrently, the obesity‐associated deposition of fat around the upper airway and thorax may affect lumen size and reduce chest compliance that contributes to OSA (Romero‐Corral, Caples, Lopez‐Jimenez, & Somers, 2010 ).

The development of certain cancers, including colorectal, pancreatic, kidney, endometrial, postmenopausal breast, and adenocarcinoma of the esophagus to name a few, have also been shown to be related to excess levels of fat and the metabolically active nature of this excess adipose tissue (Booth, Magnuson, Fouts, & Foster, 2015 ; Eheman et al., 2012 ). Cancers have shown to be impacted by the complex interactions between obesity‐related insulin resistance, hyperinsulinemia, sustained hyperglycemia, oxidative stress, inflammation, and the production of adipokines (Booth et al., 2015 ). The wide range of morbidities associated with obesity represents a significant clinical issue for individuals with obesity. However, as significant as this array of risk factors is for patient health, the risk factors can be positively modified with weight loss.

Obesity‐related morbidities in children and adolescents

As was referred to earlier, children and adolescents are becoming increasingly affected by obesity. This is particularly concerning because of the long‐term adverse consequences of early obesity. Obesity adversely affects the metabolic health of young people and can result in impaired glucose tolerance, T2D, and early‐onset metabolic syndrome (Pulgaron, 2013 ).There is also strong support in the literature for relationships between childhood obesity and asthma, poor dental health (caries), nonalcoholic fatty liver disease (NAFLD), and gastroesophageal reflux disease (GERD; Pulgaron, 2013 ). Obesity can also affect growth and sexual development and may delay puberty in boys and advance puberty in some girls (Burt Solorzano & McCartney, 2010 ). Childhood obesity is also associated with hyperandrogenism and polycystic ovary syndrome (PCOS) in girls (Burt Solorzano & McCartney, 2010 ). Additionally, obesity is associated with psychological problems in young people including attention deficit hyperactivity disorder (ADHD), anxiety, depression, poor self‐esteem, and problems with sleeping (Pulgaron, 2013 ).

Modest weight loss and its long‐term maintenance: Benefits and risks

Guidelines endorse weight‐loss targets of 5%–10% in individuals with obesity or overweight with associated comorbidities, as this has been shown to significantly improve health‐related outcomes for many obesity‐related comorbidities (Cefalu et al., 2015 ; Figure ​ Figure3), 3 ), including T2D prevention, and improvements in dyslipidemia, hyperglycemia, osteoarthritis, stress incontinence, GERD, hypertension, and PCOS. Further benefits may be evident with greater weight loss, particularly for dyslipidemia, hyperglycemia, and hypertension. For NAFLD and OSA, at least 10% weight loss is required to observe clinical improvements (Cefalu et al., 2015 ).

Benefits of modest weight loss. Lines demonstrate the ranges in which weight loss has been investigated and shown to have clinical benefits. Arrows indicate that additional benefits may be seen with further weight loss.

Source . Figure adapted from Cefalu et al. ( 2015 ).

Importantly, the weight‐loss benefits in terms of comorbidities are also reflected in improved all‐cause mortality. A recent meta‐analysis of 15 studies demonstrated that relatively small amounts of weight loss, on average 5.5 kg in the treatment arm versus 0.2 kg with placebo from an average baseline BMI of 35 kg/m 2 , resulted in a substantial 15% reduction in all‐cause mortality (Kritchevsky et al., 2015 ).

Cardiovascular health

Weight loss is associated with beneficial changes in several cardiovascular risk markers, including dyslipidemia, pro‐inflammatory/pro‐thrombotic mediators, arterial stiffness, and hypertension (Dattilo & Kris‐Etherton, 1992 ; Dengo et al., 2010 ; Goldberg et al., 2014 ; Haffner et al., 2005 ; Ratner et al., 2005 ). Importantly, weight loss was found to reduce the risk for CVD mortality by 41% up to 23 years after the original weight‐loss intervention (Li et al., 2014 ; Figure ​ Figure4). 4 ). Evidence including the biological effects of obesity and weight loss, and the increased risk for stroke with obesity indicates that weight loss may be effective for primary‐ and secondary‐stroke prevention (Kernan, Inzucchi, Sawan, Macko, & Furie, 2013 ).

Reduction in cardiovascular mortality with modest weight reduction. Cumulative incidence of CVD mortality during 23 years of follow‐up in the Da Qing study (Li et al., 2014 ). Figure © 2014 Elsevier.

Source . Reproduced with permission from Li et al. ( 2014 ).

Type 2 diabetes

Three major long‐term studies, the Diabetes Prevention Program (DPP), the Diabetes Prevention Study (DPS), and the Da Qing IGT and Diabetes (Da Qing) study, have demonstrated that modest weight loss through short‐term lifestyle or pharmacologic interventions can reduce the risk for developing T2D by 58%, 58%, and 31%, respectively, in individuals with obesity and prediabetes (DPP Research Group et al., 2009 ; Pan et al., 1997 ; Tuomilehto et al., 2001 ). Long‐term benefits were maintained following the interventions; for example, in the DPP, the risk reduction of developing T2D versus placebo was 34% at 10 years and 27% at 15 years following the initial weight‐loss intervention (DPP Research Group, 2015 ; DPP Research Group et al., 2009 ). Weight loss increased the likelihood of individuals reverting from prediabetes to normoglycemia (DPP Research Group et al., 2009 ; Li et al., 2008 ; Lindstrom et al., 2003 , 2006 ; Tuomilehto et al., 2001 ), and also improved other aspects of glycemic control including fasting and postprandial glucose, and insulin sensitivity (Haufe et al., 2013 ; Li et al., 2008 ).

Sleep apnea

Data indicate that weight loss is beneficial, although not curative, in patients with obesity who experience OSA. Meta‐analyses of patients who underwent treatment with either intensive lifestyle intervention (Araghi et al., 2013 ) or bariatric surgery (Greenburg, Lettieri, & Eliasson, 2009 ) demonstrated improvements in apnea‐hypopnea index (AHI) following treatment. In the first of these meta‐analyses, in randomized controlled trials, lifestyle intervention lead to a mean reduction in BMI of 2.3 kg/m 2 , which was associated with a decrease in mean AHI of 6.0 events/h. As expected, weight loss was much higher in the second meta‐analysis that investigated the effect of bariatric surgery on measures of OSA, and this was associated with greater reductions in AHI; the mean BMI reduction of 17.9 kg/m 2 resulted in AHI events being reduced by a mean of 38.2 events/h. Once these improvements in AHI have occurred, they seem to persist for some time, irrespective of a certain degree of weight regain. In one study, an initial mean weight loss of 10.7 kg resulted in a persistent improvement in AHI over a 4‐year period despite weight regain of approximately 50% by Year 4 (Kuna et al., 2013 ).

Intentional weight loss of >9 kg reduced the risk for a range of cancers including breast, endometrium, and colon in the large‐scale Iowa Women's Health Study (Parker & Folsom, 2003 ). The overall reduction in the incidence rate of any cancer was 11% (relative risk, 0.89; 95% CI 0.79, 1.00) for participants who lost more than 9 kg compared with those who did not achieve a more than 9 kg weight loss episode. Additionally, weight loss in participants with obesity has been established to be associated with reductions in cancer biomarkers including soluble E‐selectin and IL‐6 (Linkov et al., 2012 ).

Additional health benefits

The substantial weight loss associated with bariatric surgery has been shown to improve asthma with a 48%–100% improvement in symptoms and reduction in medication use (Juel, Ali, Nilas, & Ulrik, 2012 ); however, there is a potential threshold effect so that modest weight loss of 5%–10% may lead to clinical improvement (Lv, Xiao, & Ma, 2015 ). Similarly, modest weight loss of 5%–10% improves GERD (Singh et al., 2013 ) and liver function (Haufe et al., 2013 ). A study utilizing MRI scanning to examine the effects of weight loss on NAFLD has reported a reduction in liver fat from 18.3% to 13.6% ( p = .03), a relative reduction of 25% (Patel et al., 2015 ). Taking an active role in addressing obesity through behavioral modifications or exercise can also reduce the symptoms of depression (Fabricatore et al., 2011 ), improve urinary incontinence in men and women (Breyer et al., 2014 ; Brown et al., 2006 ), and improve fertility outcomes in women (Kort, Winget, Kim, & Lathi, 2014 ). Additionally, weight loss can reduce the joint‐pain symptoms and disability caused by weight‐related osteoarthritis (Felson, Zhang, Anthony, Naimark, & Anderson, 1992 ; Foy et al., 2011 ).

Mitigating risks

Despite the array of benefits, weight loss can also be linked with certain risks that may need to be managed. One such example is the risk for gallstones with rapid weight loss, which is associated with gallstone formation in 30%–71% of individuals. Gallstone formation is particularly associated with bariatric surgery when weight loss exceeds 1.5 kg/week and occurs particularly within the first 6 weeks following surgery when weight loss is greatest. Slower rates of weight loss appear to mitigate the risk for gallstone formation compared to the general population but may not eliminate it entirely; as was noted in the year‐long, weight‐loss, SCALE trial that compared liraglutide 3.0 mg daily use to placebo and resulted in gallstone formation in 2.5% of treated subjects compared to 1% of subjects taking placebo. For this reason, the risk for cholethiasis should be considered when formulating weight‐loss programs (Weinsier & Ullmann, 1993 ).

Strategies to help individuals achieve and maintain weight loss

Rogge and Gautam have covered the biology of obesity and weight regain within another section of this supplement (Rogge & Gautam, 2017 ), so here we focus on some of the clinical strategies for delivering weight loss and weight loss maintenance lifestyle programs. Structured lifestyle support plays an important role in successful weight management. A total of 34% of participants receiving structured lifestyle support from trained‐nursing staff achieved weight loss of ≥5% over 12 weeks compared with approximately 19% with usual care (Nanchahal et al., 2009 ). This particular structured program, delivered in a primary healthcare setting, included initial assessment and goal setting, an eating plan and specific lifestyle goals, personalized activity program, and advice about managing obstacles to weight loss. Additionally, data from the National Weight Control Registry (NWCR), which is the longest prospective compilation of data from individuals who have successfully lost weight and maintained their weight loss, confirm expectations that sustained changes to both diet and activity levels are central to successful weight management (Table ​ (Table2). 2 ). Therefore, an understanding of different clinical strategies for delivery‐structured support is essential for the nurse practitioner.

Lifestyle factors associated with achieving and maintaining weight loss

Note . Data from (NWCR, 2016 ).

a Walking was the most common activity undertaken.

Realistic weight‐loss targets

From the outset, a patient's estimate of their achievable weight loss may be unrealistic. Setting realistic weight‐loss goals is often difficult because of misinformation from a variety of sources, including friends, media, and other healthcare professionals (Osunlana et al., 2015 ). Many individuals with obesity or overweight have unrealistic goals of 20%–30% weight loss, whereas a more realistic goal would be the loss of 5%–15% of the initial body weight (Fabricatore et al., 2007 ). Promoting realistic weight‐loss expectations for patients was identified as a key difficulty for nurse practitioners, primary care nurses, dieticians, and mental health workers (Osunlana et al., 2015 ). Visual resources showing the health and wellness benefit of modest weight loss may thus be helpful (Osunlana et al., 2015 ). Healthcare practitioners should focus on open discussion about, and re‐enforcement of, realistic weight‐loss goals and assess outcomes consistently according to those goals (Bray, Look, & Ryan, 2013 ).

Maintaining a food diary

The 2013 White Paper from the American Nurse Practitioners Foundation on the Prevention and Treatment of Obesity considers a food diary as an important evidence‐based nutritional intervention in aiding weight loss (ANPF). Consistent and regular recording in a food diary was significantly associated with long‐term weight‐loss success in a group of 220 women (Peterson et al., 2014 ). This group lost a mean of 10.4% of their initial body weight through a 6‐month group‐based weight‐management program and then regained a mean of 2.3% over a 12‐month follow‐up period, during which participants received bimonthly support in person, by telephone, or by e‐mail (Peterson et al., 2014 ). Over the 12‐month follow‐up, women who self‐monitored consistently (≥50% of the extended‐care year) had a mean weight loss of 0.98%, while those who were less consistent (<50%) gained weight (5.1%; p < .01). Therefore, frequent and consistent food monitoring should be encouraged, particularly in the weight‐maintenance phase of any program.

Motivating and supporting patients

Motivational interviewing is a technique that focuses on enhancing intrinsic motivation and behavioral changes by addressing ambivalence (Barnes & Ivezaj, 2015 ). Interviews focus on “change talk,” including the reasons for change and optimism about the intent for change in a supportive and nonconfrontational setting, and may help individuals maintain behavioral changes.

For patients that have achieved weight loss, the behavioral factors associated with maintaining weight loss include strong social support networks, limiting/avoiding disinhibited eating, avoiding binge eating, avoiding eating in response to stress or emotional issues, being accountable for one's decisions, having a strong sense of autonomy, internal motivation, and self‐efficacy (Grief & Miranda, 2010 ). Therefore, encouraging feelings of “self‐worth” or “self‐efficacy” can help individuals to view weight loss as being within their own control and achievable (Cochrane, 2008 ).

Strengthening relationships with patients with overweight or obesity to enhance trust may also improve adherence with weight‐loss programs. Patients with hypertension who reported having “complete trust” in their healthcare practitioner were more than twice as likely to engage in lifestyle changes to lose weight than those who lacked “complete trust” (Jones, Carson, Bleich, & Cooper, 2012 ). It may be prudent to ensure the healthcare staff implementing weight‐loss programs have sufficient time to foster trust with their patients.

Continued support from healthcare staff may help patients sustain the necessary motivation for lifestyle changes. A retrospective analysis of 14,256 patients in primary care identified consultation frequency as a factor that can predict the success of weight‐management programs (Lenoir, Maillot, Guilbot, & Ritz, 2015 ). Individuals who successfully maintained ≥10% weight loss over 12 months visited the healthcare provider on average 0.65 times monthly compared with an average of 0.48 visits/month in those who did not maintain ≥10% weight loss, and 0.39 visits/month in those who failed to achieve the initial ≥10% weight loss ( p < .001; Lenoir et al., 2015 ).

Educational and environmental factors

It is important to consider a patient's education and environment when formulating a weight loss strategy as environmental factors may need to be challenged to help facilitate weight loss. A family history of obesity and childhood obesity are strongly linked to adult obesity, which is likely to be because of both genetic and behavioral factors (Kral & Rauh, 2010 ). Parents create their child's early food experiences and influence their child's attitudes to eating through learned eating habits and food choices (Kral & Rauh, 2010 ). Families can also impart cultural preferences for less healthy food choices and family food choices may be affected by community factors, such as the local availability and cost of healthy food options (Castro, Shaibi, & Boehm‐Smith, 2009 ). Alongside this, genetic variation in taste sensation may influence the dietary palate and influence food choices (Loper, La Sala, Dotson, & Steinle, 2015 ). For example, sensitivity to 6‐n‐propylthiouracil (PROP) is genetically determined, and PROP‐tasting ability ranges from super taster to nontaster. When offered buffet‐style meals over 3 days, PROP nontasters consumed more energy, and a greater proportion of energy from fat compared with super tasters. So it is possible that a family's genetic profile could contribute to eating choices. To address behavioral factors, it is important to ensure that families have appropriate support and information and that any early signs of weight gain are dealt with promptly.

A healthy home food environment can help individuals improve their diet. In children, key factors are availability of fresh fruit and vegetables at home and parental influence through their own fresh fruit and vegetable intake (Wyse, Wolfenden, & Bisquera, 2015 ). In adults, unhealthy home food environment factors include less healthy food in the home and reliance on fast food ( p = .01) are all predictors of obesity (Emery et al., 2015 ).

Family mealtimes are strongly associated with better dietary intake and a randomized controlled trial to encourage healthy family meals showed a promising reduction in excess weight gain in prepubescent children (Fulkerson et al., 2015 ). Another study showed that adolescents with any level of baseline family meal frequency, 1–2, 3–4, and ≥5 family meals/week, had reduced odds of being affected by overweight or obesity 10 years later than adolescents who never ate family meals (Berge et al., 2015 ). Community health advocates have identified the failure of many families to plan meals or prepare food as a barrier to healthy family eating patterns (Fruh, Mulekar, Hall, Fulkerson et al., 2013 ). Meal planning allows healthy meals to be prepared in advance and frozen for later consumption (Fruh, Mulekar, Hall, Adams et al., 2013 ) and is associated with increased consumption of vegetables and healthier meals compared with meals prepared on impulse (Crawford, Ball, Mishra, Salmon, & Timperio, 2007 ; Hersey et al., 2001 ).

The role of the nurse practitioner

The initial and ongoing interactions between patient and nurse practitioner are keys for the determination of an effective approach and implementation of a weight loss program and subsequent weight maintenance. The initial interaction can be instigated by either the nurse practitioner or the patient and once the decision has been made to manage the patient's weight, the evaluation includes a risk assessment, a discussion about the patient's weight, and treatment goal recommendations (American Nurse Practitioner Foundation, 2013 ). Across this process, it may be advantageous to approach this using objective data and language that is motivational and/or nonjudgmental. Patients may struggle with motivation, and therefore, ongoing discussions around the health benefits and improvements to quality of life as a result of weight loss may be required (American Nurse Practitioner Foundation, 2013 ). It may be valuable to allocate personalized benefits to the weight loss such as playing with children/grandchildren (American Nurse Practitioner Foundation, 2013 ). Treatment approaches encompass nonpharmacological and pharmacological strategies; however, it is important to remember that any pharmacological agent used should be used as an adjunct to nutritional and physical activity strategies (American Nurse Practitioner Foundation, 2013 ). Pharmacotherapy options for weight management are discussed further in the article by Golden in this supplement.

Conclusions/summary

The importance of obesity management is underscored both by the serious health consequences for individuals, but also by its increasing prevalence globally, and across age groups in particular. Obesity promotes a chronic, low‐grade, inflammatory state, which is associated with vascular dysfunction, thrombotic disorders, multiple organ damage, and metabolic dysfunction. These physiological effects ultimately lead to the development of a range of morbidities, including CVD, T2D, OSA, and certain cancers along with many others, as well as causing a significant impact on mortality.

However, even modest weight loss of 5%–10% of total body weight can significantly improve health and well‐being, and further benefits are possible with greater weight loss. Weight loss can help to prevent development of T2D in individuals with obesity and prediabetes and has a positive long‐term impact on cardiovascular mortality. Beneficial, although not curative, effects have also been noted on OSA following >10% weight loss. In addition, weight loss reduces the risk for certain cancer types and has positive effects on most comorbidities including asthma, GERD, liver function, urinary incontinence, fertility, joint pain, and depression.

Weight‐loss programs that include realistic weight loss goals, frequent check‐in, and meal/activity diaries may help individuals to lose weight. Setting realistic weight‐loss goals can be difficult; however, visual resources showing the health and wellness benefit of weight loss may be helpful in discussing realistic goals, and help motivate the patient in maintaining the weight loss. Techniques such as motivational interviewing that focus on addressing resistance to behavioral change in a supportive and optimistic manner may help individuals in integrating these changes to allow them to become part of normal everyday life and thus help with maintaining the weight loss. Positive reinforcement in terms of marked early‐weight loss may also assist in improving adherence, so this should be a key goal for weight‐loss programs. Encouraging feelings of “self‐worth” or “self‐efficacy” can help individuals to view weight loss as being within their own control.

Nurse practitioners play a major role in helping patients achieve weight loss through all aspects of the process including assessment, support, motivation, goal‐setting, management, and treatment. With their in‐depth understanding of the research in the field of obesity and weight management, nurse practitioners are well placed to effect meaningful changes in the weight‐management strategies deployed in clinical practice.

List of helpful resources

Acknowledgments.

The authors are grateful to Watermeadow Medical for writing assistance in the development of this manuscript. This assistance was funded by Novo Nordisk, who also had a role in the review of the manuscript for scientific accuracy. The author discussed the concept, drafted the outline, commented in detail on the first iteration, made critical revision of later drafts, and has revised and approved the final version for submission.

Dr. Sharon Fruh serves on the Novo Nordisk Obesity Speakers Bureau. In compliance with national ethical guidelines, the author reports no relationship with business or industry that would post a conflict of interest.

Writing and editorial support was provided by Watermeadow Medical, and funded by Novo Nordisk.

The copyright line in this article was changed on 9 August 2018 after online publication.

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Home — Essay Samples — Government & Politics — Policy — Critical Analysis of the UK Policy on Childhood Obesity

Critical Analysis of The UK Policy on Childhood Obesity

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