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, Accredited official statistics

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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

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• 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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• Volume 11, Issue 6
• Changing the narrative around obesity in the UK: a survey of people with obesity and healthcare professionals from the ACTION-IO study
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• http://orcid.org/0000-0001-9560-7873 Carly A Hughes 1 , 2 ,
• Amy L Ahern 3 ,
• Harsha Kasetty 4 ,
• Barbara M McGowan 5 ,
• Helen M Parretti 2 ,
• Ann Vincent 6 ,
• Jason C G Halford 7
• 1 Fakenham Weight Management Service, Fakenham Medical Practice , Fakenham , UK
• 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
• Correspondence to Dr Carly A Hughes; carly.hughes{at}nhs.net

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 .

• general medicine (see internal medicine)
• public health
• epidemiology
• medical education & training

Data availability statement

Data are available upon reasonable request. De-identified participant data will be made available for this article on a specialised SAS data platform. Datasets from Novo Nordisk will be available permanently after completion of data analysis. Access to data can be made through a request proposal form and the access criteria can be found online (novonordisk-trials.com). Data will be shared with bona fide researchers submitting a research proposal requesting access to data. Data use is subject to approval by the independent review board.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjopen-2020-045616

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Strengths and limitations of this study

Strengths include the scientific rigour in the study design and implementation.

The large number of UK respondents and the ability to directly compare the UK data to the equivalent global dataset is an additional strength.

Limitations of this study include possible response bias from the population sampled and recall bias.

The causes of obesity are complex and multifaceted, encompassing biological, genetic, environmental, economic, social and psychological factors. 1–3 The chronic and relapsing nature of obesity is associated with many serious physical and psychological comorbidities, reduced quality of life and increased healthcare costs. 2 4–8 The WHO has recognised obesity as a disease, and the National Institute for Health and Care Excellence provides guidance on its assessment and treatment. 9 More recently, it has been recognised as a risk factor for severity of COVID-19 infection. 5 6 The prevalence of overweight and obesity among adults in the UK has been increasing and was 63% in 2018. 7 This increase is thought to be primarily caused by people’s latent biological susceptibility interacting with a changing environment that includes more sedentary lifestyles and increased dietary abundance. 1 The prevalence of adiposity in the UK population is approaching similar levels to those reported in the US (71%), Chile (74%) and Mexico (75%), which are among the highest recorded adult overweight and obesity levels in the world. 8 The number of people with obesity (PwO) in the UK continues to rise, and severe and complex obesity (body mass index (BMI) ≥40 kg/m 2 ) increased from less than 1% of the total population in 1993 to nearly 4% in 2017. 10 The UK-wide National Health Service (NHS) costs attributable to overweight and obesity are projected to reach £9.7 billion by 2050, with wider societal costs estimated to reach £49.9 billion per year. 11 The significant increase in the prevalence of obesity has not been matched by a proportionate expansion of continuing education on the biological basis and clinical management of obesity and training provision for healthcare professionals (HCPs), irrespective of their discipline. 12 Moreover, little effort has been made to address weight stigma and societal effects of weight bias, which continue to be experienced in a consistently negative way by those who have excess weight or obesity. Current evidence demonstrates that weight stigma is widespread in the UK, 13 that weight stigma is experienced in many settings 14 15 and that experience of stigma is associated with negative psychosocial outcomes, increased eating, reduced engagement with physical activity and weight gain. 16

The variability of causal pathways of weight gain is inherently unsuited to a ‘one size fits all’ treatment approach. 1 There is a range of existing guidance to support practice and care throughout the obesity care pathway in the UK. 9 17 However, the extent and range of the provision of weight management services is inconsistent and geographically dependent. 18 The obesity care pathway has an important role within the whole systems approach to tackling obesity, as outlined in the Foresight’s report, 1 and endorsed in the Department of Health and Social Care’s (DHSC) Call to Action 19 and the Public Health England’s paper on a whole systems approach to obesity. 20 The DHSC clinical policy outlines a tiered system of obesity care with a focus on public health and community advice in tier 1; primary care, community interventions and pharmacotherapy in tier 2; multi-disciplinary weight management service in tier 3 and secondary care and bariatric surgery in tier 4. 21

Despite its wide global prevalence, obesity remains poorly understood by the general public and HCPs, and this contributes to the high levels of stigma associated with obesity. 22 Society is continually informed through intense media coverage that obesity is simple and easily manipulated. 23 This attitude contributes to greater perceptions of individual responsibility, contrary to evidence that suggests that many factors outside a person’s control influence obesity. 22 23 To improve the quality and accessibility of obesity care, a better understanding of the disease and the gaps between current and optimal obesity management strategies is required. The Awareness, Care, and Treatment In Obesity maNagement–International Observation (ACTION-IO) study assessed the perceptions, attitudes and behaviours of PwO and HCPs. 24 The global dataset 24 revealed a need to increase understanding of obesity and improve education concerning its aetiology. The aim of this subanalysis was to identify the perceptions, attitudes, behaviours and potential barriers to effective obesity care in the UK.

Study design and participants

The ACTION-IO study was a cross-sectional, non-interventional study that collected data via an online survey in Australia, Chile, Israel, Italy, Japan, Mexico, Saudi Arabia, South Korea, Spain, the UK and the United Arab Emirates. The full methods for the ACTION-IO study have been reported previously. 24 Eligible PwO in the UK were 18 years or older, with a current BMI of at least 30 kg/m 2 based on self-reported height and weight. The PwO sample was targeted for demographic representativeness based on gender, age, income, race/ethnicity and region. Therefore, PwO were excluded if they declined to provide any of these variables. Respondents were also excluded for non-obesity reasons, for high BMI or for dramatic weight loss, that is, if they were pregnant, participated in intense fitness or body building programmes, or had significant, unintentional weight loss in the past 6 months. Eligible UK’s HCPs were in practice for 2 years or more, with at least 70% of their time spent in direct patient care, and who had seen 100 or more patients in the past month, at least 10 of whom had a BMI of at least 30 kg/m 2 . HCPs specialising in general, plastic or bariatric surgery were excluded. Respondents were recruited via online panel companies (via email) to whom they had given permission to be contacted for research purposes, and completed the survey in English. All respondents provided electronic informed consent prior to initiation of the screening questions and survey. Preceding participation, PwO were only informed of the purpose of the study, and were blinded to the specific study goals.

Survey development and procedures

The study was designed by an international steering committee of obesity experts (representing primary care, endocrinology and psychology, and including three medical doctors employed by Novo Nordisk), with support from KJT Group (Honeoye Falls, New York, USA), and based on the ACTION US and Canada questionnaires. 25 26 KJT Group managed the acquisition and analysis of data; UK responses were collected between September 2018 and October 2018. Questionnaire items were carefully phrased and presented in identical order for each respondent. Items in a list were displayed in alphabetical, categorical, chronological or random order as relevant for each response. Respondents accessed the survey using a unique web link, details regarding the digital fingerprinting system used to assess unique site visitors has been previously described. 24 To prevent duplicate survey entries, unique site visitors were recorded via a user ID that was passed along the unique web link that respondents used to access the site. The system checked every respondent entering the survey against previous user IDs logged in its database. Respondents who began the survey and suspended were able to re-enter the survey while it was still open and finish the survey where they left off. Respondents who had already received a terminal status (complete, over-quota or terminate) were blocked from re-entering the survey. Following closure of the survey, no users were able to gain access. The user ID and data of suspended respondents were stored until the survey was closed and were then eliminated from the data analysis. The study was conducted in accordance with the Guidelines for Good Pharmacoepidemiology Practices. 27

To ensure representativeness to the general population, the final PwO sample was weighted to demographic targets within each country for age, gender, income, race/ethnicity and region. The HCP data were not weighted. Only data from those who completed the survey were included in the analyses.

Patient and public involvement

No patients or members of the public were involved in the design or conduct of the study. A patient representative was involved in the analysis and interpretation of the UK data and is an author on this article. She will also be involved in disseminating these findings to a wider audience.

Demographics

A total of 69 676 PwO and 2508 HCPs, in the UK, were invited. The response rate to the survey was 14% (9786/69 676) for PwO and 35% (886/2508) for HCPs, as expected for this type of study and in line with the target sample size. 24 Of those who completed the screening questions, the eligibility rate was 22% (2146/9779) for PwO and 53% (387/737) for HCPs. The final UK sample for the ACTION-IO survey was 1500 PwO and 306 HCPs, of whom 156 were primary care professionals (PCPs) and 150 were secondary care professionals (SCPs) ( table 1 ). Some differences were observed in the survey outcomes between PCPs and SCPs, which will be reported in full at a later date.

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Sample demographics and characteristics

Pre-consultation and initiation of weight management discussion

People with obesity.

Only about half (47%) of all PwO had discussed excess weight or losing weight with an HCP in the past 5 years. It took a median of 6 years and mean of 9 years (range: 0.0–56.0 years; IQR: 13 years) between the time when PwO said that they first started struggling with excess weight or obesity and when they first had a weight management conversation with an HCP ( figure 1A ). In comparison, globally it took a median of 3 years and a mean of 6 years (range: 0.0–68.0 years; IQR: 8 years ( figure 1A )). 24 Forty-seven per cent of PwO who discussed weight with an HCP reported that they initiated the conversation themselves. When PwO were asked to name the top five reasons why they may not discuss weight management with their HCP, the most common reason was the belief that it was their own responsibility to manage their weight (51% of PwO) ( figure 1B ). Indeed, when asked whether they agreed with the statement ‘my weight loss is completely my responsibility’, 85% of PwO agreed with the statement. Thirty-four per cent of PwO said that they were motivated to lose weight, and 36% provided a neutral response (neither agreed nor disagreed that they were motivated). Only 4% of PwO reported an indifference to losing weight as a reason for not discussing managing their weight with an HCP. Sixty-five per cent of PwO who previously had a weight conversation with their HCP liked that their HCP discussed their weight with them, and 58% who not previously had a conversation would have liked their HCP to bring up weight during their appointments. Most PwO (81%) believed that obesity has a large impact on overall health, similar to other chronic diseases such as diabetes (82%), stroke (88%), cancer (82%) or chronic obstructive pulmonary disease (COPD; 84%). The internet was cited as a source of information used by 31% of PwO for managing weight ( figure 2A ). Other sources of information were reported as family and friends (27%), weight loss programmes (26%), information from an HCP (23%) and media (books/magazines: 21%, television programmes: 20%) ( figure 2A ).

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Number of years between when struggle with weight began and first discussed with an HCP and PwO/HCP reasons for not discussing weight management. (A) Approximate number of years reported by the UK and global PwO (ACTION-IO study steering committee, personal communication) between the beginning of their struggle with weight and first discussion with an HCP. Calculated at respondent level from questions, ‘Approximately how old were you when you first remember struggling with excess weight or obesity?’ and ‘Approximately how old were you when a healthcare provider first discussed your excess weight or recommended that you lose weight?’. (B) Reasons reported by the UK’s PwO for not discussing managing their weight with an HCP. (C) Reasons reported by the UK’s HCPs for not discussing weight management with their patients. ACTION-IO, Awareness, Care, and Treatment In Obesity maNagement–International Observation; HCP, healthcare professional; PwO, people with obesity.

Sources of information and feelings after a weight discussion. (A) Sources of information most frequently used by the UK’s PwO for managing weight (reported by PwO). (B) Feelings reported by the UK’s PwO after their most recent weight or weight loss discussion with an HCP in the past 5 years. HCP, healthcare professional; PwO, people with obesity.

Healthcare professionals

Those HCPs who discussed weight with their patients reported that 35% of the time the patient initiated the conversation. Compared with PwO (85%), a smaller proportion of HCPs (33%) placed the responsibility for weight loss on PwO. Only 13% of HCPs thought that their patients were motivated to lose weight, and 42% provided a neutral response (neither agreed nor disagreed that their patients were motivated). The most commonly selected reason for not discussing weight management with a patient (selected by 72% of HCPs) was the perception that the patient was not interested in losing weight, and 61% of HCPs selected lack of patient motivation ( figure 1C ). Other reasons provided for not discussing obesity with a patient were that the appointments were not long enough and that they felt rushed (selected by 68% of HCPs), and that more important health issues/concerns were an impediment to discussing obesity with a patient (selected by 58% of HCPs). In addition, almost one-third of HCPs (31%) reported that the good health of a patient and the absence of weight-related comorbidities would be a reason for not discussing weight management. The most important criterion for initiating weight management conversations with a patient was the presence of obesity-related comorbidities, cited by 76% of HCPs. Only 68% of the UK’s HCPs (vs 76% of global HCPs 24 ) recognised the impact of obesity on health, and it was rated as less serious than diabetes, cancer, stroke or COPD by 40%, 65%, 62% and 43% of the UK’s HCPs, respectively.

Consultation

Eighty-one per cent of the PwO who had discussed weight with an HCP had had a discussion with a PCP, 42% with a nurse, 18% with a dietitian/nutritionist and 17% with a diabetes educator. PwO reported a complex mixture of feelings following a weight loss conversation with an HCP ( figure 2B ). PwO cited a combination of feelings such as supported 36%, hopeful 31%, motivated 23%, embarrassed 17%, indifferent 16%, discouraged 11%, relieved 10%, blamed 10%, rushed 10%, offended 4% and confused 4% ( figure 2B ).

Fifty-nine per cent of HCPs reported that they were extremely or very comfortable discussing weight, 30% were neither comfortable nor uncomfortable and 11% were a little or not at all comfortable discussing weight. On average, HCPs reported that they spent 10 min interacting with their patients when discussing weight (range: 1–20 min).

Consultation outcomes and follow-up

Among the 47% of PwO who had discussed their weight with an HCP in the past 5 years, 49% reported that they had been diagnosed with obesity in the past by an HCP (24% of all PwO, figure 3 ). Only 19% of PwO who had discussed their weight with an HCP had a follow-up appointment scheduled (9% of all PwO) ( figure 3 ). However, 62% of PwO would have liked a follow-up appointment and 96% reported attending or planning to attend a follow-up appointment if scheduled. The most frequent methods for managing weight tried by PwO were general improvements in eating habits/reducing calories (reported by 61% of PwO) and general increases in physical activity (55%), which were reported at a greater frequency than by global PwO (51% and 39% for general eating habits and physical activity, respectively; ACTION-IO study steering committee, personal communication). Bariatric surgery and behavioural therapy referral rates were reported in small numbers by the UK’s PwO (1% and 2%, respectively). Visits to a nutritionist/dietician and obesity specialist were reported less frequently by the UK’s PwO than global PwO (nutritionist/dietician: 11% UK, 24% global; obesity specialist: 2% UK, 9% global; ACTION-IO study steering committee, personal communication).

Obesity diagnoses and follow-up appointments with an HCP. Proportion of the UK’s PwO who discussed weight or weight loss with an HCP in the past 5 years and the frequency of obesity diagnoses and follow-up appointments. HCP, healthcare professional; PwO, people with obesity.

On average, HCPs scheduled follow-up appointments with 33% of their patients for obesity and 46% of HCPs said that patients kept these follow-up appointments always or most of the time. HCPs most frequently recommended general improvements in eating habits/reducing calories (reported by 61% of HCPs) and general increases in physical activity (65%). Referrals to obesity specialists were recommended less frequently by UK HCPs (12%) compared with the global dataset (23%). 24

PwO are faced with biological predispositions, and societal and environmental conditions that contribute to obesity, weight stigma and discrimination. Obesity prevention and management are key health priorities and require a whole systems approach. However, the national response for obesity focuses on individual responsibility regarding nutrition and lack of physical activity. In this study, multiple barriers to effective weight management were identified, which are summarised in figure 4 and discussed below.

A conceptual model of the obesity treatment pathway and barriers to obesity care in the UK. BMI, body mass index; HCP, healthcare professional; PwO, people with obesity.

Initiation of weight management discussion with HCPs

Fewer than half of PwO in the UK (47%) had a discussion with an HCP about their weight in the past 5 years, despite HCPs being the gateway to weight management care in the NHS. Moreover, for the PwO who did have a weight discussion, it took a mean of 9 years after they first started struggling with their weight before having the discussion (compared with 6 years globally). 24 This delay is particularly important as it may create an opportunity for significant obesity-related complications to develop. This long delay may also reflect a higher degree of obesity stigma in the UK 28 and a culture of individual responsibility for obesity. 29 30 Indeed, a focus on individual responsibility is reflected in UK government policy on obesity. 31 Reducing the time gap by initiating earlier weight management discussions may be an effective strategy for improving obesity treatment and preventing the development of comorbidities.

From the PwO perspective, a delay in seeking help could be linked to the high percentage (85%) of PwO who perceived their weight loss as completely their responsibility. From the HCP perspective, a delay in discussing obesity with a patient could be linked to reported perceptions that the patient was not interested or motivated in losing weight, consistent with previous research. 32 33 Other impediments to the discussion were HCPs’ views that there were more important health issues to discuss and that a weight management discussion is only required when weight-related comorbidities are present, as supported by other studies. 33 34 Moreover, HCPs in the UK underestimated the effect of obesity on health to a greater extent than the UK’s PwO and global HCPs. 24 For PwO, this will likely require a change in the narrative around obesity to lessen focus on individual responsibility, and for HCPs a need to increase the understanding of the health consequences of obesity and the desire of PwO for help and support. The internet, media, and family and friends formed a substantial source of information for PwO for managing weight. We need to change this from personal responsibility to recognising the aetiology of obesity and its implications for PwO.

Primary care is the gateway to obesity treatment, and most weight management discussions were held with a primary care physician or nurse. While many PwO welcomed weight discussions with HCPs, they also reported experiencing complex and varied emotions after these discussions. It is important to acknowledge the complexity of the experience for PwO. Studies have previously reported patients feeling that their obesity had been ignored, dismissed, distorted or attributed as the explanation of all their health problems by HCPs. 35–37 Negative experiences can contribute to depression, anxiety, low self-esteem and body dissatisfaction. 38 39 Dissatisfactory conversations with an HCP may discourage PwO from seeking further weight management help in the future and reinforce feelings of personal responsibility for weight management. The attitudes of health professionals towards obesity and its management have been generally reported to be negative, and knowledge and skills in managing obesity have been noted to be inconsistent. 40–45 Even well-intended acts can cause offence and humiliation, 46 and PwO often experience their weight in profoundly negative ways as a result of the pervasive stigmatisation of obesity. Patient experiences are valid indications of the strengths and shortcomings of the services they receive. 47 It is important to ensure that the narrative around obesity resonates with the lived experiences of those affected by it and encourages patients to engage with an HCP. 47 HCPs in turn should aim to provide compassionate care that is free of bias and use supportive communication and language to facilitate successful and meaningful conversations. 47

HCPs often have limited time and resources, and lack of time has previously been reported as a barrier to discussing obesity. 48 49 More HCPs in the UK (68%) than globally (54%) indicated that the limited appointment time would be a factor in not having a weight loss conversation. 24 This may be a reflection of the average primary care consultation time in the UK, which is 10 min and considerably shorter than in many other countries. 50 51 Other potential barriers described in the literature have included uncertainty about appropriate language, 48 concerns about compromising rapport 9 and concerns discussing a potentially upsetting and stigmatising topic. 22 50 52 However, in this study, relatively few HCPs reported discomfort with weight discussions.

Obesity diagnoses, follow-up appointments and referrals to specialists were infrequently reported by PwO, which could incorrectly reinforce the feeling of individual responsibility. Indeed, methods for managing weight reported by PwO, which relied largely on general improvements in eating habits and physical activity, suggest a lack of knowledge of effective treatment methods and/or a consequence of the availability of therapeutic options (see below).

The data from HCPs on the frequency of follow-up appointments and methods for obesity management largely aligned with the data from PwO. Barriers to effective weight management cited in the literature have included lack of effective and individualised treatment and/or referral options. 40 41 50 53 Weight management services in the UK exist as part of fragmented health and social care systems, which are geographically dependent. 49 54 55 The range of services and treatments, including pharmacotherapy and bariatric surgery, is limited in the UK, which may restrict HCPs in what they can offer patients. Indeed, HCPs report insufficient management options and scepticism about their efficacy. 56 57 This is further compounded by limited consultation times for the UK’s general practitioners. 50 51 The limited availability of weight management services, effective treatments and coherent, joined-up strategies in the UK health system are significant barriers to providing effective obesity care. 55

Strengths and limitations

Strengths of this study include scientific rigour in the study design (including carefully phrased and ordered questions to prevent biased responses, blinded purpose of the survey for PwO and determination of eligibility by initial screening questions to eradicate bias during recruitment) and implementation (including stratified sampling to provide a representative cohort of the general population and rigorous data analysis). Other strengths include the large number of UK’s PwO and HCP respondents and the ability to directly compare the UK data to the equivalent global dataset. Limitations include the cross-sectional design and reliance on accurate reporting from the PwO and HCP respondents, which could be perceived as recall bias. The self-reported height and weight could underestimate the BMI of the PwO. A higher proportion of HCPs than might be expected self-identified as obesity specialists using the broad criteria specified in table 1 . The low response rates could affect sample representativeness and is a known limitation for this type of study. Response bias from the population sampled cannot be ruled out. However, the PwO sample was representative of the demographics of the general population.

This study demonstrates the need to change the narrative around obesity, with less stigmatising focus on individual responsibility, for the government, commissioners, general public, PwO and HCPs. The findings identified areas that prevent PwO from seeking help and receiving appropriate care. In addition, the attitudes of HCPs prevent them from offering the support PwO require for obesity management. The consultation about weight with an HCP is the gateway to treatment in the NHS and improving the frequency and quality of PwO–HCP conversations is essential. Sufficient time should be given to HCPs to approach the topic of overweight and obesity sensitively and effectively. The current survey did not have high numbers of people with a BMI of over 40 kg/m 2 ; further research is required to understand whether people with higher BMIs have distinct experiences in the management of their obesity.

To conclude, a whole systems approach is required to address and eliminate weight bias and stigmatisation, to change the narrative around obesity in the UK, and to improve provision of NHS services. Educating the whole population, including PwO and HCPs, about the aetiology and psychology of obesity and the interaction with the obesogenic environment should help to ensure that patients access and receive quality care and effective weight treatment and management. Changing the narrative around obesity will allow for a more effective delivery framework for health service providers and greater access to effective treatment pathways and weight management services for PwO.

Ethics statements

Patient consent for publication.

Not required.

Ethics approval

The National Health Service Health Research Authority (Central Research Ethics Committee, London) advised that ethical approval was not needed in the UK.

Acknowledgments

We thank the participants of the study. Medical editorial assistance was provided by Anna Bacon from Articulate Science, and was funded by Novo Nordisk.

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Contributors CAH and JCGH are members of the ACTION-IO study steering committee and contributed to the design of the study. CAH, ALA, HK, BMM, HMP, AV and JCGH participated in the interpretation of data, and drafting and revision of the manuscript. All authors reviewed and approved the final, submitted version.

Funding This work and ACTION-IO was supported by Novo Nordisk. ALA is funded by the Medical Research Council through grant MC_UU_00006/6.

Competing interests CAH reports financial support from Novo Nordisk to attend an obesity conference during the conduct of the study, grants from the Rona Marsden Fund at Fakenham Medical Practice and personal fees from Orexigen Therapeutics, Consilient Health, Nestlé, Ethicon and Alva outside the submitted work. ALA reports grants from UKRI Medical Research Council and National Institute for Health Research, and non-financial support from WW (formerly Weight Watchers). HK is an employee of Novo Nordisk and owns shares in Novo Nordisk. BMM reports grants paid to her institution from Novo Nordisk and personal fees (consultancy and advisory board) from Novo Nordisk, Boehringer Ingelheim and Orexigen Therapeutics; and has received speaker fees for Eli Lilly, Novo Nordisk, Boehringer Ingelheim, Janssen, MSD and Sanofi. HMP reports grants from the National Institute for Health Research and Public Health England and an honorarium from Novo Nordisk (educational grant) outside the submitted work. AV acted as a speaker for Obesity Empowerment Network and is a board member of the Clinical Advisory Committee on the All Wales Obesity Strategy. JCGH reports fees (honoraria) paid to the University of Liverpool from Novo Nordisk, Orexigen and Boehringer Ingelheim during the conduct of the study.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

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Original research

Changing the narrative around obesity in the uk: a survey of people with obesity and healthcare professionals from the action-io study, carly a hughes.

1 Fakenham Weight Management Service, Fakenham Medical Practice, Fakenham, UK

2 Norwich Medical School, University of East Anglia, Norwich, UK

Amy L Ahern

3 MRC Epidemiology Unit, University of Cambridge, Cambridge, UK

Harsha Kasetty

4 Novo Nordisk Ltd, Gatwick, UK

Barbara M McGowan

5 Institute of Diabetes, Endocrinology and Obesity, Guy’s and St Thomas’ NHS Foundation Trust, London, UK

Helen M Parretti

Ann vincent.

6 Department of Medicine, University College London, London, UK

Jason C G Halford

7 School of Psychology, University of Leeds, Leeds, UK

Associated Data

Data are available upon reasonable request. De-identified participant data will be made available for this article on a specialised SAS data platform. Datasets from Novo Nordisk will be available permanently after completion of data analysis. Access to data can be made through a request proposal form and the access criteria can be found online (novonordisk-trials.com). Data will be shared with bona fide researchers submitting a research proposal requesting access to data. Data use is subject to approval by the independent review board.

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.

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.

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

{"type":"clinical-trial","attrs":{"text":"NCT03584191","term_id":"NCT03584191"}} NCT03584191 .

Strengths and limitations of this study

• Strengths include the scientific rigour in the study design and implementation.
• The large number of UK respondents and the ability to directly compare the UK data to the equivalent global dataset is an additional strength.
• Limitations of this study include possible response bias from the population sampled and recall bias.

The causes of obesity are complex and multifaceted, encompassing biological, genetic, environmental, economic, social and psychological factors. 1–3 The chronic and relapsing nature of obesity is associated with many serious physical and psychological comorbidities, reduced quality of life and increased healthcare costs. 2 4–8 The WHO has recognised obesity as a disease, and the National Institute for Health and Care Excellence provides guidance on its assessment and treatment. 9 More recently, it has been recognised as a risk factor for severity of COVID-19 infection. 5 6 The prevalence of overweight and obesity among adults in the UK has been increasing and was 63% in 2018. 7 This increase is thought to be primarily caused by people’s latent biological susceptibility interacting with a changing environment that includes more sedentary lifestyles and increased dietary abundance. 1 The prevalence of adiposity in the UK population is approaching similar levels to those reported in the US (71%), Chile (74%) and Mexico (75%), which are among the highest recorded adult overweight and obesity levels in the world. 8 The number of people with obesity (PwO) in the UK continues to rise, and severe and complex obesity (body mass index (BMI) ≥40 kg/m 2 ) increased from less than 1% of the total population in 1993 to nearly 4% in 2017. 10 The UK-wide National Health Service (NHS) costs attributable to overweight and obesity are projected to reach £9.7 billion by 2050, with wider societal costs estimated to reach £49.9 billion per year. 11 The significant increase in the prevalence of obesity has not been matched by a proportionate expansion of continuing education on the biological basis and clinical management of obesity and training provision for healthcare professionals (HCPs), irrespective of their discipline. 12 Moreover, little effort has been made to address weight stigma and societal effects of weight bias, which continue to be experienced in a consistently negative way by those who have excess weight or obesity. Current evidence demonstrates that weight stigma is widespread in the UK, 13 that weight stigma is experienced in many settings 14 15 and that experience of stigma is associated with negative psychosocial outcomes, increased eating, reduced engagement with physical activity and weight gain. 16

The variability of causal pathways of weight gain is inherently unsuited to a ‘one size fits all’ treatment approach. 1 There is a range of existing guidance to support practice and care throughout the obesity care pathway in the UK. 9 17 However, the extent and range of the provision of weight management services is inconsistent and geographically dependent. 18 The obesity care pathway has an important role within the whole systems approach to tackling obesity, as outlined in the Foresight’s report, 1 and endorsed in the Department of Health and Social Care’s (DHSC) Call to Action 19 and the Public Health England’s paper on a whole systems approach to obesity. 20 The DHSC clinical policy outlines a tiered system of obesity care with a focus on public health and community advice in tier 1; primary care, community interventions and pharmacotherapy in tier 2; multi-disciplinary weight management service in tier 3 and secondary care and bariatric surgery in tier 4. 21

Despite its wide global prevalence, obesity remains poorly understood by the general public and HCPs, and this contributes to the high levels of stigma associated with obesity. 22 Society is continually informed through intense media coverage that obesity is simple and easily manipulated. 23 This attitude contributes to greater perceptions of individual responsibility, contrary to evidence that suggests that many factors outside a person’s control influence obesity. 22 23 To improve the quality and accessibility of obesity care, a better understanding of the disease and the gaps between current and optimal obesity management strategies is required. The Awareness, Care, and Treatment In Obesity maNagement–International Observation (ACTION-IO) study assessed the perceptions, attitudes and behaviours of PwO and HCPs. 24 The global dataset 24 revealed a need to increase understanding of obesity and improve education concerning its aetiology. The aim of this subanalysis was to identify the perceptions, attitudes, behaviours and potential barriers to effective obesity care in the UK.

Study design and participants

The ACTION-IO study was a cross-sectional, non-interventional study that collected data via an online survey in Australia, Chile, Israel, Italy, Japan, Mexico, Saudi Arabia, South Korea, Spain, the UK and the United Arab Emirates. The full methods for the ACTION-IO study have been reported previously. 24 Eligible PwO in the UK were 18 years or older, with a current BMI of at least 30 kg/m 2 based on self-reported height and weight. The PwO sample was targeted for demographic representativeness based on gender, age, income, race/ethnicity and region. Therefore, PwO were excluded if they declined to provide any of these variables. Respondents were also excluded for non-obesity reasons, for high BMI or for dramatic weight loss, that is, if they were pregnant, participated in intense fitness or body building programmes, or had significant, unintentional weight loss in the past 6 months. Eligible UK’s HCPs were in practice for 2 years or more, with at least 70% of their time spent in direct patient care, and who had seen 100 or more patients in the past month, at least 10 of whom had a BMI of at least 30 kg/m 2 . HCPs specialising in general, plastic or bariatric surgery were excluded. Respondents were recruited via online panel companies (via email) to whom they had given permission to be contacted for research purposes, and completed the survey in English. All respondents provided electronic informed consent prior to initiation of the screening questions and survey. Preceding participation, PwO were only informed of the purpose of the study, and were blinded to the specific study goals.

Survey development and procedures

The study was designed by an international steering committee of obesity experts (representing primary care, endocrinology and psychology, and including three medical doctors employed by Novo Nordisk), with support from KJT Group (Honeoye Falls, New York, USA), and based on the ACTION US and Canada questionnaires. 25 26 KJT Group managed the acquisition and analysis of data; UK responses were collected between September 2018 and October 2018. Questionnaire items were carefully phrased and presented in identical order for each respondent. Items in a list were displayed in alphabetical, categorical, chronological or random order as relevant for each response. Respondents accessed the survey using a unique web link, details regarding the digital fingerprinting system used to assess unique site visitors has been previously described. 24 To prevent duplicate survey entries, unique site visitors were recorded via a user ID that was passed along the unique web link that respondents used to access the site. The system checked every respondent entering the survey against previous user IDs logged in its database. Respondents who began the survey and suspended were able to re-enter the survey while it was still open and finish the survey where they left off. Respondents who had already received a terminal status (complete, over-quota or terminate) were blocked from re-entering the survey. Following closure of the survey, no users were able to gain access. The user ID and data of suspended respondents were stored until the survey was closed and were then eliminated from the data analysis. The study was conducted in accordance with the Guidelines for Good Pharmacoepidemiology Practices. 27

To ensure representativeness to the general population, the final PwO sample was weighted to demographic targets within each country for age, gender, income, race/ethnicity and region. The HCP data were not weighted. Only data from those who completed the survey were included in the analyses.

Patient and public involvement

No patients or members of the public were involved in the design or conduct of the study. A patient representative was involved in the analysis and interpretation of the UK data and is an author on this article. She will also be involved in disseminating these findings to a wider audience.

Demographics

A total of 69 676 PwO and 2508 HCPs, in the UK, were invited. The response rate to the survey was 14% (9786/69 676) for PwO and 35% (886/2508) for HCPs, as expected for this type of study and in line with the target sample size. 24 Of those who completed the screening questions, the eligibility rate was 22% (2146/9779) for PwO and 53% (387/737) for HCPs. The final UK sample for the ACTION-IO survey was 1500 PwO and 306 HCPs, of whom 156 were primary care professionals (PCPs) and 150 were secondary care professionals (SCPs) ( table 1 ). Some differences were observed in the survey outcomes between PCPs and SCPs, which will be reported in full at a later date.

Sample demographics and characteristics

All ‘n’ sizes for PwO are from unweighted data. Demographic percentages (age and gender) are also from unweighted data. All non-demographic percentage results are for PwO weighted data. HCP data were not weighted; therefore, n sizes and percentages are all unweighted data.

*Participation rate (those who completed the screener) was 99.9% for PwO and 84.7% for HCPs; completion rate was 100% for PwO and 85.8% for HCPs.

†Disclosure of height and weight was optional for HCPs. The percentages for the BMI categories were calculated using the number of respondents to this question as the denominator.

‡A physician who meets at least one of the following criteria: at least 50% of their patients are seen for obesity/weight management; or has advanced/formal training in treatment of obesity/weight management beyond medical school; or considers themselves to be an expert in obesity/weight loss management or works in an obesity service clinic. 24

BMI, body mass index; HCP, healthcare professional; PCP, primary care professional; PwO, people with obesity; SCP, secondary care professional.

Pre-consultation and initiation of weight management discussion

People with obesity.

Only about half (47%) of all PwO had discussed excess weight or losing weight with an HCP in the past 5 years. It took a median of 6 years and mean of 9 years (range: 0.0–56.0 years; IQR: 13 years) between the time when PwO said that they first started struggling with excess weight or obesity and when they first had a weight management conversation with an HCP ( figure 1A ). In comparison, globally it took a median of 3 years and a mean of 6 years (range: 0.0–68.0 years; IQR: 8 years ( figure 1A )). 24 Forty-seven per cent of PwO who discussed weight with an HCP reported that they initiated the conversation themselves. When PwO were asked to name the top five reasons why they may not discuss weight management with their HCP, the most common reason was the belief that it was their own responsibility to manage their weight (51% of PwO) ( figure 1B ). Indeed, when asked whether they agreed with the statement ‘my weight loss is completely my responsibility’, 85% of PwO agreed with the statement. Thirty-four per cent of PwO said that they were motivated to lose weight, and 36% provided a neutral response (neither agreed nor disagreed that they were motivated). Only 4% of PwO reported an indifference to losing weight as a reason for not discussing managing their weight with an HCP. Sixty-five per cent of PwO who previously had a weight conversation with their HCP liked that their HCP discussed their weight with them, and 58% who not previously had a conversation would have liked their HCP to bring up weight during their appointments. Most PwO (81%) believed that obesity has a large impact on overall health, similar to other chronic diseases such as diabetes (82%), stroke (88%), cancer (82%) or chronic obstructive pulmonary disease (COPD; 84%). The internet was cited as a source of information used by 31% of PwO for managing weight ( figure 2A ). Other sources of information were reported as family and friends (27%), weight loss programmes (26%), information from an HCP (23%) and media (books/magazines: 21%, television programmes: 20%) ( figure 2A ).

Number of years between when struggle with weight began and first discussed with an HCP and PwO/HCP reasons for not discussing weight management. (A) Approximate number of years reported by the UK and global PwO (ACTION-IO study steering committee, personal communication) between the beginning of their struggle with weight and first discussion with an HCP. Calculated at respondent level from questions, ‘Approximately how old were you when you first remember struggling with excess weight or obesity?’ and ‘Approximately how old were you when a healthcare provider first discussed your excess weight or recommended that you lose weight?’. (B) Reasons reported by the UK’s PwO for not discussing managing their weight with an HCP. (C) Reasons reported by the UK’s HCPs for not discussing weight management with their patients. ACTION-IO, Awareness, Care, and Treatment In Obesity maNagement–International Observation; HCP, healthcare professional; PwO, people with obesity.

Sources of information and feelings after a weight discussion. (A) Sources of information most frequently used by the UK’s PwO for managing weight (reported by PwO). (B) Feelings reported by the UK’s PwO after their most recent weight or weight loss discussion with an HCP in the past 5 years. HCP, healthcare professional; PwO, people with obesity.

Healthcare professionals

Those HCPs who discussed weight with their patients reported that 35% of the time the patient initiated the conversation. Compared with PwO (85%), a smaller proportion of HCPs (33%) placed the responsibility for weight loss on PwO. Only 13% of HCPs thought that their patients were motivated to lose weight, and 42% provided a neutral response (neither agreed nor disagreed that their patients were motivated). The most commonly selected reason for not discussing weight management with a patient (selected by 72% of HCPs) was the perception that the patient was not interested in losing weight, and 61% of HCPs selected lack of patient motivation ( figure 1C ). Other reasons provided for not discussing obesity with a patient were that the appointments were not long enough and that they felt rushed (selected by 68% of HCPs), and that more important health issues/concerns were an impediment to discussing obesity with a patient (selected by 58% of HCPs). In addition, almost one-third of HCPs (31%) reported that the good health of a patient and the absence of weight-related comorbidities would be a reason for not discussing weight management. The most important criterion for initiating weight management conversations with a patient was the presence of obesity-related comorbidities, cited by 76% of HCPs. Only 68% of the UK’s HCPs (vs 76% of global HCPs 24 ) recognised the impact of obesity on health, and it was rated as less serious than diabetes, cancer, stroke or COPD by 40%, 65%, 62% and 43% of the UK’s HCPs, respectively.

Consultation

Eighty-one per cent of the PwO who had discussed weight with an HCP had had a discussion with a PCP, 42% with a nurse, 18% with a dietitian/nutritionist and 17% with a diabetes educator. PwO reported a complex mixture of feelings following a weight loss conversation with an HCP ( figure 2B ). PwO cited a combination of feelings such as supported 36%, hopeful 31%, motivated 23%, embarrassed 17%, indifferent 16%, discouraged 11%, relieved 10%, blamed 10%, rushed 10%, offended 4% and confused 4% ( figure 2B ).

Fifty-nine per cent of HCPs reported that they were extremely or very comfortable discussing weight, 30% were neither comfortable nor uncomfortable and 11% were a little or not at all comfortable discussing weight. On average, HCPs reported that they spent 10 min interacting with their patients when discussing weight (range: 1–20 min).

Consultation outcomes and follow-up

Among the 47% of PwO who had discussed their weight with an HCP in the past 5 years, 49% reported that they had been diagnosed with obesity in the past by an HCP (24% of all PwO, figure 3 ). Only 19% of PwO who had discussed their weight with an HCP had a follow-up appointment scheduled (9% of all PwO) ( figure 3 ). However, 62% of PwO would have liked a follow-up appointment and 96% reported attending or planning to attend a follow-up appointment if scheduled. The most frequent methods for managing weight tried by PwO were general improvements in eating habits/reducing calories (reported by 61% of PwO) and general increases in physical activity (55%), which were reported at a greater frequency than by global PwO (51% and 39% for general eating habits and physical activity, respectively; ACTION-IO study steering committee, personal communication). Bariatric surgery and behavioural therapy referral rates were reported in small numbers by the UK’s PwO (1% and 2%, respectively). Visits to a nutritionist/dietician and obesity specialist were reported less frequently by the UK’s PwO than global PwO (nutritionist/dietician: 11% UK, 24% global; obesity specialist: 2% UK, 9% global; ACTION-IO study steering committee, personal communication).

Obesity diagnoses and follow-up appointments with an HCP. Proportion of the UK’s PwO who discussed weight or weight loss with an HCP in the past 5 years and the frequency of obesity diagnoses and follow-up appointments. HCP, healthcare professional; PwO, people with obesity.

On average, HCPs scheduled follow-up appointments with 33% of their patients for obesity and 46% of HCPs said that patients kept these follow-up appointments always or most of the time. HCPs most frequently recommended general improvements in eating habits/reducing calories (reported by 61% of HCPs) and general increases in physical activity (65%). Referrals to obesity specialists were recommended less frequently by UK HCPs (12%) compared with the global dataset (23%). 24

PwO are faced with biological predispositions, and societal and environmental conditions that contribute to obesity, weight stigma and discrimination. Obesity prevention and management are key health priorities and require a whole systems approach. However, the national response for obesity focuses on individual responsibility regarding nutrition and lack of physical activity. In this study, multiple barriers to effective weight management were identified, which are summarised in figure 4 and discussed below.

A conceptual model of the obesity treatment pathway and barriers to obesity care in the UK. BMI, body mass index; HCP, healthcare professional; PwO, people with obesity.

Initiation of weight management discussion with HCPs

Fewer than half of PwO in the UK (47%) had a discussion with an HCP about their weight in the past 5 years, despite HCPs being the gateway to weight management care in the NHS. Moreover, for the PwO who did have a weight discussion, it took a mean of 9 years after they first started struggling with their weight before having the discussion (compared with 6 years globally). 24 This delay is particularly important as it may create an opportunity for significant obesity-related complications to develop. This long delay may also reflect a higher degree of obesity stigma in the UK 28 and a culture of individual responsibility for obesity. 29 30 Indeed, a focus on individual responsibility is reflected in UK government policy on obesity. 31 Reducing the time gap by initiating earlier weight management discussions may be an effective strategy for improving obesity treatment and preventing the development of comorbidities.

From the PwO perspective, a delay in seeking help could be linked to the high percentage (85%) of PwO who perceived their weight loss as completely their responsibility. From the HCP perspective, a delay in discussing obesity with a patient could be linked to reported perceptions that the patient was not interested or motivated in losing weight, consistent with previous research. 32 33 Other impediments to the discussion were HCPs’ views that there were more important health issues to discuss and that a weight management discussion is only required when weight-related comorbidities are present, as supported by other studies. 33 34 Moreover, HCPs in the UK underestimated the effect of obesity on health to a greater extent than the UK’s PwO and global HCPs. 24 For PwO, this will likely require a change in the narrative around obesity to lessen focus on individual responsibility, and for HCPs a need to increase the understanding of the health consequences of obesity and the desire of PwO for help and support. The internet, media, and family and friends formed a substantial source of information for PwO for managing weight. We need to change this from personal responsibility to recognising the aetiology of obesity and its implications for PwO.

Primary care is the gateway to obesity treatment, and most weight management discussions were held with a primary care physician or nurse. While many PwO welcomed weight discussions with HCPs, they also reported experiencing complex and varied emotions after these discussions. It is important to acknowledge the complexity of the experience for PwO. Studies have previously reported patients feeling that their obesity had been ignored, dismissed, distorted or attributed as the explanation of all their health problems by HCPs. 35–37 Negative experiences can contribute to depression, anxiety, low self-esteem and body dissatisfaction. 38 39 Dissatisfactory conversations with an HCP may discourage PwO from seeking further weight management help in the future and reinforce feelings of personal responsibility for weight management. The attitudes of health professionals towards obesity and its management have been generally reported to be negative, and knowledge and skills in managing obesity have been noted to be inconsistent. 40–45 Even well-intended acts can cause offence and humiliation, 46 and PwO often experience their weight in profoundly negative ways as a result of the pervasive stigmatisation of obesity. Patient experiences are valid indications of the strengths and shortcomings of the services they receive. 47 It is important to ensure that the narrative around obesity resonates with the lived experiences of those affected by it and encourages patients to engage with an HCP. 47 HCPs in turn should aim to provide compassionate care that is free of bias and use supportive communication and language to facilitate successful and meaningful conversations. 47

HCPs often have limited time and resources, and lack of time has previously been reported as a barrier to discussing obesity. 48 49 More HCPs in the UK (68%) than globally (54%) indicated that the limited appointment time would be a factor in not having a weight loss conversation. 24 This may be a reflection of the average primary care consultation time in the UK, which is 10 min and considerably shorter than in many other countries. 50 51 Other potential barriers described in the literature have included uncertainty about appropriate language, 48 concerns about compromising rapport 9 and concerns discussing a potentially upsetting and stigmatising topic. 22 50 52 However, in this study, relatively few HCPs reported discomfort with weight discussions.

Obesity diagnoses, follow-up appointments and referrals to specialists were infrequently reported by PwO, which could incorrectly reinforce the feeling of individual responsibility. Indeed, methods for managing weight reported by PwO, which relied largely on general improvements in eating habits and physical activity, suggest a lack of knowledge of effective treatment methods and/or a consequence of the availability of therapeutic options (see below).

The data from HCPs on the frequency of follow-up appointments and methods for obesity management largely aligned with the data from PwO. Barriers to effective weight management cited in the literature have included lack of effective and individualised treatment and/or referral options. 40 41 50 53 Weight management services in the UK exist as part of fragmented health and social care systems, which are geographically dependent. 49 54 55 The range of services and treatments, including pharmacotherapy and bariatric surgery, is limited in the UK, which may restrict HCPs in what they can offer patients. Indeed, HCPs report insufficient management options and scepticism about their efficacy. 56 57 This is further compounded by limited consultation times for the UK’s general practitioners. 50 51 The limited availability of weight management services, effective treatments and coherent, joined-up strategies in the UK health system are significant barriers to providing effective obesity care. 55

Strengths and limitations

Strengths of this study include scientific rigour in the study design (including carefully phrased and ordered questions to prevent biased responses, blinded purpose of the survey for PwO and determination of eligibility by initial screening questions to eradicate bias during recruitment) and implementation (including stratified sampling to provide a representative cohort of the general population and rigorous data analysis). Other strengths include the large number of UK’s PwO and HCP respondents and the ability to directly compare the UK data to the equivalent global dataset. Limitations include the cross-sectional design and reliance on accurate reporting from the PwO and HCP respondents, which could be perceived as recall bias. The self-reported height and weight could underestimate the BMI of the PwO. A higher proportion of HCPs than might be expected self-identified as obesity specialists using the broad criteria specified in table 1 . The low response rates could affect sample representativeness and is a known limitation for this type of study. Response bias from the population sampled cannot be ruled out. However, the PwO sample was representative of the demographics of the general population.

This study demonstrates the need to change the narrative around obesity, with less stigmatising focus on individual responsibility, for the government, commissioners, general public, PwO and HCPs. The findings identified areas that prevent PwO from seeking help and receiving appropriate care. In addition, the attitudes of HCPs prevent them from offering the support PwO require for obesity management. The consultation about weight with an HCP is the gateway to treatment in the NHS and improving the frequency and quality of PwO–HCP conversations is essential. Sufficient time should be given to HCPs to approach the topic of overweight and obesity sensitively and effectively. The current survey did not have high numbers of people with a BMI of over 40 kg/m 2 ; further research is required to understand whether people with higher BMIs have distinct experiences in the management of their obesity.

To conclude, a whole systems approach is required to address and eliminate weight bias and stigmatisation, to change the narrative around obesity in the UK, and to improve provision of NHS services. Educating the whole population, including PwO and HCPs, about the aetiology and psychology of obesity and the interaction with the obesogenic environment should help to ensure that patients access and receive quality care and effective weight treatment and management. Changing the narrative around obesity will allow for a more effective delivery framework for health service providers and greater access to effective treatment pathways and weight management services for PwO.

Supplementary Material

Acknowledgments.

We thank the participants of the study. Medical editorial assistance was provided by Anna Bacon from Articulate Science, and was funded by Novo Nordisk.

Contributors: CAH and JCGH are members of the ACTION-IO study steering committee and contributed to the design of the study. CAH, ALA, HK, BMM, HMP, AV and JCGH participated in the interpretation of data, and drafting and revision of the manuscript. All authors reviewed and approved the final, submitted version.

Funding: This work and ACTION-IO was supported by Novo Nordisk. ALA is funded by the Medical Research Council through grant MC_UU_00006/6.

Competing interests: CAH reports financial support from Novo Nordisk to attend an obesity conference during the conduct of the study, grants from the Rona Marsden Fund at Fakenham Medical Practice and personal fees from Orexigen Therapeutics, Consilient Health, Nestlé, Ethicon and Alva outside the submitted work. ALA reports grants from UKRI Medical Research Council and National Institute for Health Research, and non-financial support from WW (formerly Weight Watchers). HK is an employee of Novo Nordisk and owns shares in Novo Nordisk. BMM reports grants paid to her institution from Novo Nordisk and personal fees (consultancy and advisory board) from Novo Nordisk, Boehringer Ingelheim and Orexigen Therapeutics; and has received speaker fees for Eli Lilly, Novo Nordisk, Boehringer Ingelheim, Janssen, MSD and Sanofi. HMP reports grants from the National Institute for Health Research and Public Health England and an honorarium from Novo Nordisk (educational grant) outside the submitted work. AV acted as a speaker for Obesity Empowerment Network and is a board member of the Clinical Advisory Committee on the All Wales Obesity Strategy. JCGH reports fees (honoraria) paid to the University of Liverpool from Novo Nordisk, Orexigen and Boehringer Ingelheim during the conduct of the study.

Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review: Not commissioned; externally peer reviewed.

Data availability statement

Ethics statements, patient consent for publication.

Not required.

Ethics approval

The National Health Service Health Research Authority (Central Research Ethics Committee, London) advised that ethical approval was not needed in the UK.

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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.

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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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Obesity: the biggest public health challenge facing nursing this century

Rita Newland

Nurse Advisor, Research, Public Health England

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Jamie Blackshaw

National Lead for Physical Activity and Healthy Weight, Public Health England

Jamie Waterall

Deputy Chief Nurse, Public Health England

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Obesity and overweight is arguably the largest and most complex non-communicable disease of the 21st century, threatening future progress in reducing preventable ill health, premature death and addressing unacceptable health inequalities in the UK. Around two-thirds (63%) of adults are above a healthy weight and, of these, half are living with obesity. In England, one in three children leaving primary school are overweight or living with obesity. Living with overweight or obesity is linked to a wide range of diseases, most commonly type 2 diabetes, hypertension, some cancers, heart disease, stroke and liver disease ( Department of Health and Social Care (DHSC), 2020 ; Hancock, 2021 ). Overweight and obesity terms and body mass index (BMI) ranges are set out in Table 1 and Table 2 .

Source: NICE, 2014

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• Health and social care
• Public health
• Health conditions
• Update to the Obesity Profile on Fingertips
• Office for Health Improvement & Disparities

Obesity Profile: short statistical commentary May 2024

Published 8 May 2024

Applies to England

© Crown copyright 2024

This publication is licensed under the terms of the Open Government Licence v3.0 except where otherwise stated. To view this licence, visit nationalarchives.gov.uk/doc/open-government-licence/version/3 or write to the Information Policy Team, The National Archives, Kew, London TW9 4DU, or email: [email protected] .

Where we have identified any third party copyright information you will need to obtain permission from the copyright holders concerned.

This publication is available at https://www.gov.uk/government/statistics/update-to-the-obesity-profile-on-fingertips/obesity-profile-short-statistical-commentary-may-2024

The following indicators have been updated:

overweight (including obesity) prevalence in adults (aged 18 and over)

obesity prevalence in adults (aged 18 and over)

percentage of physically active adults (aged 19 and over)

percentage of physically inactive adults (aged 19 and over)

percentage of adults aged 16 and over meeting the ‘5-a-day’ fruit and vegetable consumption recommendations (new method)

Data has been added for local authority boundaries created in April 2023.

Introduction

This statistical commentary provides background information on the updated indicators for adults on:

• overweight and obesity prevalence
• physical activity and inactivity
• consumption of 5 or more portions of fruit and vegetables per day

in the  Obesity Profile on Fingertips . It presents data for England.

Obesity is a global and complex public health concern. It is associated with reduced life expectancy and is a risk factor for a range of chronic diseases, including cardiovascular disease, type 2 diabetes, cancer, liver, and respiratory disease, and can also impact on mental health.

Regular physical activity is associated with a reduced risk of diabetes, obesity, osteoporosis, colon and breast cancer, and improved mental health.  In older adults, physical activity is associated with increased functional capacities.  Inactivity is doing less than 30 moderate intensity equivalent ( MIE ) minutes per week. Being physically active is doing at least 150 MIE minutes physical activity per week.

Fruit and vegetables are part of a healthy, balanced diet and can help the public stay healthy. Evidence shows there are significant health benefits to getting at least 5 portions of a variety of fruit and vegetables every day. Understanding the data, the trends and patterns enables us to make the case for national and local action, and approaches to create health-promoting environments.

The  Obesity Profile  also includes data on inequalities in these indicators, displaying data by index of multiple deprivation decile, ethnic group, working status, disability, level of education, socioeconomic class, age and sex.

Main findings

Prevalence of overweight and obesity in adults (aged 18 years and over).

In 2022 to 2023, 64.0% of adults aged 18 years and over in England were estimated to be overweight or living with obesity. This is similar to 2021 to 2022 (63.8%) but there has been an upward trend since 2015 to 2016 (61.2%) (Figure 1). In 2022 to 2023 26.2% of adults were estimated to be living with obesity. This is similar to 2021 to 2022 (25.9%) but, as with the prevalence of overweight (including obesity), there has been an upward trend since 2015 to 2016 (22.6%).

Figure 1: prevalence of overweight and obesity in adults (aged 18 years and over)

In 2022 to 2023, the prevalence of overweight (including obesity) was higher among men (69.2%) than women (58.6%), however the prevalence of obesity in adults was similar among men (26.4%) and women (26.2%).

Prevalence of overweight (including obesity), and obesity increases with age up to age 64, reaching the peak in the 55 to 64 years group (72.8% and 32.4% respectively) then decreasing in the 65 to 74 years and older groups.

Prevalence of overweight and obesity in adults by deprivation and ethnicity

Prevalence of overweight (including obesity), and obesity is highest in those living in the most deprived areas (71.5% and 35.9% respectively) and lowest in those living in the least deprived areas (59.6% and 20.5% respectively).

When looking at different ethnic groups, the prevalence of overweight (including obesity) and obesity in adults remains highest amongst those who identified as black (74.8% and 34.8% respectively) or white British (65.3% and 27.6% respectively).

Physical activity and inactivity in adults (aged 19 years and over)

In England in 2022 to 2023, 67.1% of adults were physically active. This is similar to 2021 to 2022 (67.3%) and the pre-pandemic level in 2018 to 2019 (67.2%), but higher than 2015 to 2016 (66.1%). 22.6% of adults were inactive in 2022 to 2023 which is similar to 2021 to 2022 (22.3%) and 2015 to 2016 (22.3%).

Women are less likely to be physically active than men (64.9% compared to 69.6%) and are more likely than men to be inactive (24.0% compared to 21.0%).

The proportion of physically active adults decreases with age; adults aged 19 to 24 years have the highest percentage of physically active adults (73.2%) decreasing to 56.0% and 30.7% in adults aged 75 to 84 years and 85 and over respectively. The proportion of adults who are physically inactive is highest in the 75 to 84 (33.2%) and 85 and over (57.3%) age groups and much lower among adults aged between 19 and 64 where the range is from 17.7% to 21.7%.

Figure 2: percentage of physically active and inactive adults (aged 19 years and over)

Physical activity and inactivity in adults by deprivation and ethnicity

53.9% of adults living in the most deprived areas are physically active compared to 74.0% of adults living in the least deprived areas, while 35.3% are inactive in the most deprived areas compared to 16.1% in the least deprived areas.

Physical activity is highest in white British (69.3%), white other (68.6%) and mixed (71.9%) ethnic groups and lowest in black (55.2%) and Asian (56.1%) ethnic groups. Inactivity is highest in Asian (32.0%), other (31.5%) and black (31.2) ethnic groups and lowest in white British (20.8%), white other (21.2%) and mixed (19.0%) ethnic groups.

Adults (aged 16 years and over) eating at least 5 portions of fruit and vegetables a day

In England in 2022 to 2023, 31.0% of adults reported eating at least 5 portions of fruit and vegetables a day. This is less than in 2021 to 2022 when 32.5% of adults reported eating at least 5 portions, and 2020 to 2021 when 34.9% of adults reported eating at least 5 portions. Comparable data is not available prior to 2020 to 2021.

Figure 3: percentage of adults eating at least 5 portions of fruit and vegetables a day, by sex

Women are more likely than men to eat at least 5 portions of fruit and vegetables a day (34.2% compared with 27.6%). Adults aged 55 and over are more likely to eat at least 5 portions of fruit and vegetables (35.3% and higher) than those aged under 55 years old.

Adults eating at least 5 portions of fruit and vegetables a day by deprivation and ethnicity

More adults living in the least deprived areas eat at least 5 portions of fruit and vegetables a day compared to any other deprivation group (37.2%). The proportion decreases as level of deprivation increases down to 20.3% of adults living in the most deprived areas.

Lower proportions of Asian and black adults eat at least 5 portions of fruit and vegetables a day (19.2% and 21.0% respectively). The proportion is highest among white British adults (32.9%).

Further information

The indicators published in the Obesity Profile present local authority estimates from Sport England’s Active Lives Adult Survey ( ALAS ) data to help inform local action to improve the health of the population now and into the future. A detailed description of the methods used to produce the indicators can be found in the definitions data view of the indicators in the  Obesity Profile .

Data on adult overweight and obesity prevalence

The best indicator of obesity prevalence for adults at a national level comes from the Health Survey for England , which uses measured height and weight to calculate body mass index ( BMI ). However, the survey sample size is not sufficient to produce robust estimates at local level.

The indicators presented in the Obesity Profile use self-reported height and weight from the ALAS which are adjusted so that they more accurately predicted measured values.

The 2022 to 2023 obesity prevalence of 26.2% is similar to the latest available estimates from the 2021 Health Survey for England ( HSE ) (25.9%) which also used adjusted self-reported measurements due to the COVID-19 social distancing restrictions in place at the time. 2022 data from HSE will be available later in 2024 and this will be the first estimate of obesity prevalence since the pandemic to use measured heights and weights making it comparable with pre-pandemic HSE data.

Data on physical activity

The Health Survey for England is the best source for physical activity data at a national level. The HSE allows for comparison over a longer time period, providing data for 2012, 2016 and 2021. The HSE also provides a more complete summary of activity levels as it includes physical activity while at work and other non-occupational activities such as housework, manual work and DIY activities, in addition to activities covered by ALAS such as gardening, walking, and sports and exercise.

More information and the physical activity data from the HSE is published in the adult physical activity chapter of the HSE 2021 report.

Data on fruit and vegetable consumption

National estimates of fruit and vegetable consumption are available from the Health Survey for England , and the National Diet and Nutrition Survey ( NDNS ), which are both much more comprehensive in their questions than the ALAS . But the survey sample sizes for these surveys are not sufficient to provide local authority level estimates.

For the HSE , participants are asked numerous questions, including separate questions about fruits, vegetables and pulses, and portion sizes rather than a single-item question in the ALAS .

For the NDNS , data are collected using food diaries. Foods are then broken down to their component parts and fruit and vegetable portions are calculated.

These differences are included in the indicator source section of the Public Health Outcomes Framework.

For queries relating to this document, please contact: [email protected]

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Home — Essay Samples — Nursing & Health — Obesity — Obesity And Its Effects In The United Kingdom

Obesity and Its Effects in The United Kingdom

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