Introduction
Obesity (body mass index ≥ 30 kg/m2) is a growing public health crisis across the world. The available data suggest that the global burden of obesity has more than tripled since 1975 (1). It is particularly high in some first world countries. However, recent data show that obesity is spreading very fast in low-and middle-income countries (LIMICs), and has reached world record level in some of them (2). At the country level, around 42% of adults in the US are obese, compared to estimates four decades earlier of about 13%. Similarly, in the United Kingdom, prevalence has increased to about 25%. In the LMICs, high obesity is apparent in Brazil, China, Egypt, South Africa, India, Indonesia, Mexico, Pakistan and Russia, while prevalence is more than 75% in countries such as Tonga, Samoa, and Kiribati (3). Obesity forecasts (4) are for continuing growth, with the study (Nianogo and Arah) proposing a micro-simulation model for forecasting cohort obesity.
In racial and ethnic minority sub-groups, such as non-Hispanic blacks in the US, obesity has reached half the adult population. There is also considerable variation between socio-economic groups and geographic areas in the obesity burden: for example, the prevalence of adult obesity varies widely across upper tier local authorities in England, ranging from 11 to 40%.
Obesity is a major cause of premature death, is implicated in recent slowing in improved life expectancy (5), and increases the risk of a range of chronic diseases. There is a seven times greater risk of diabetes in the obese as against those of healthy weight, with a three-fold increase in risk for overweight people (6). Elevated body mass index (BMI) is thought to account for 20% of hypertension and coronary-heart disease (6).
There are many contributing factors to obesity in individual behavior patterns, such as poor food choices and over-eating, sedentary lifestyles, and genetic disposition (with heritability estimates of 40–70%). Adverse trends are apparent in both food consumption patterns and activity levels (7). However, the responsible factors extend far beyond individual behavior (8).
Adverse trends show not only in food consumption and activity levels in higher income countries, but in the geographic diffusion of obesity and overweight. The “nutrition transition” characterizes changing food consumption in low and middle income countries, with many facing a “double burden” of obesity and undernutrition, as well as an upturn in non-communicable disease linked to obesity and overweight (9). For example, the special issue paper by Reddy et al. highlights the nutrition transition and its impacts in South Africa.
Causes: Proximal influences
Excess consumption of less healthy foods and inadequate activity (surplus of energy intake compared to energy expenditure) can be seen as the proximate cause of obesity (8, 10). There is considerable debate around the dietary patterns implicated, whether overall calories intake (the energy balance model) or processed carbohydrates (11, 12).
Distinct dietary pattern subtypes have been identified, such as Western vs. prudent (13). Kopp (14) characterizes the Western diet as containing “large amounts of high-glycemic/high-insulinemic carbohydrate foodstuff like refined cereals, corn, potatoes and sugars (in particular sucrose and fructose), dairy products, as well as high amounts of fat and substantial amounts of protein”. In LMICs, urbanization typically is associated with adoption of Western diet, and associated declines in cardiometabolic health (15).
The Global Burden of Disease study tracking trends in food consumption between 1990 and 2017 in 195 countries estimates that one in five deaths globally are associated with poor diet, with diet contributing to obesity and a range of chronic diseases.
Reduced activity levels are the other main immediate driving factor for increased obesity. In line with many studies looking beyond individual behaviors, the review (16) argues that “a systems approach that focuses on populations and the complex interactions among the correlates of physical inactivity, rather than solely a behavioral science approach focusing on individuals, is the way forward to increase physical activity worldwide”.
Contextual influences on obesity
The broader distal context to increased obesity is set by policy, and structural “obesogens” of the built, food and social environments. The broader obesogenic context is multifactorial, with the relevance of particular features varying between countries and between subpopulations (17).
Obesity is associated with the emergence of a food industry producing, and marketing (e.g., through advertising), convenient, highly-processed foods. Food advertising content has been linked to growing child obesity (18), and may provide a misleading perspective on nutritional value (19). Food outlets are also increasingly diverse, providing convenience or fast food, with less need for preparing meals at home (20, 21).
A system perspective emphasizes the role of the capitalism in shaping dietary behavior and consumption. Thus, Wells (22) argues that the key to understanding obesity is an “obesogenic niche” caused by the logic of capitalism. Thus, “historically, capitalism contributed to the under-nutrition of many populations through demand for cheap labor. As the limiting factor for economic growth switched to consumption, capitalism has increasingly driven consumer behavior inducing widespread over-nutrition”.
The global food system interacts with local environmental characteristics to create wide variation in obesity levels between populations, and in the obesogenic context (17). For example, obesity, especially through reduced activity, has been linked to urban sprawl. This type of residential dispersal to low density suburban settings—especially in North America and Australasia—is linked to reduced walkability, disconnected street networks, and greater reliance on car use (23, 24).
Influence on activity levels is also the relevant mechanism for studies into green space access and obesity (25), and research into obesity and access to exercise opportunities (26). The Australian study (Jayasinghe et al.) exemplifies research into access to physical activity infrastructure using a seven category breakdown based on the work of Lee et al. (27).
By contrast, access to healthy food and hence dietary influences on obesity are paramount in studies of the food environment (28). Food store type and location is one aspect of the food environment: supermarkets, and fruit and vegetable markets, are associated with improved access to healthy food, as opposed to fast-food restaurants or outlets, small groceries and convenience stores.
Obesity context and population sub-groups
US studies find population subgroups (income and ethnic groups) differing considerably in access to healthy food outlets (29), while in the UK there are more fast food outlets in deprived areas than in more affluent areas (30). Food deserts have been designated to describe neighborhoods where poverty, poor public transport, and lack of large supermarkets nearby, limit access to affordable fresh fruit and vegetables (31).
Lesser activity levels have also been reported among females than males (32, 33). For example, the Ethiopian study (Biadgilign et al.) investigates gender differences in physical activity among adolescents.
Obesity prevention
Many interventions to reduce obesity focus on individual behaviors, for example to promote healthy diets (34) or physical activity (35). Most often such interventions involve face-to-face counseling or group therapy combined with recording of dietary intake and physical activity. For example, the study (Yang et al.) considers a longitudinal weight management program in China.
However, advances in technology provide opportunities to deliver eHealth interventions using the web, phone apps and other digital media (36). For example, the systematic review (37) showed that eHealth intervention had potential to effectively promote physical activity in obese adults, while the Research Topic paper (Reddy et al.) mentioned the benefits of eHealth interventions in sub-Saharan contexts as these can reach large populations at low cost.
There is a growing recognition of the importance of population-level interventions and market interventions (38), though the potential for these remains to be fully explored. Thus, the study (39) mentioned that although early child education settings are often an untapped opportunity for supportive nutrition and physical activity changes, while for older children suitable interventions include comprehensive school-based physical activity programs and improved school nutrition environments. Similarly the study (40) estimated that a 20% tax on sugar sweetened drinks would lead to a reduction in the obesity in the UK of 1.3% (around 180,000 people). Studies of the impact of such taxes, where implemented, indicate significant effects on consumption (41).
Often prior consultation with the relevant community will indicate an appropriate design for an intervention. The Saudi study (Almughamisi et al.) is an example of co-identifying actionable priorities for interventions. The importance of the degree of agency in groups targeted by population interventions has also been emphasized (42).
Author contributions
Text written initially by PC. Subsequent amendments by DA included. Both authors contributed to the article and approved the submitted version.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
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References
- 1.World Health Organization . Obesity and Overweight. Available online at: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight (accessed August 1, 2022).
- 2.Goryakin Y, Lobstein T, James WP, Suhrcke M. The impact of economic, political and social globalization on overweight and obesity in the 56 low and middle income countries. Soc Sci Med. (2015) 133:67–76. 10.1016/j.socscimed.2015.03.030 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Ng M, Fleming T, Robinson M, Thomson B, Graetz N, et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. (2014) 384:766–81. 10.1016/S0140-6736(14)60460-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Finkelstein EA, Khavjou OA, Thompson H, Trogdon JG, Pan L, Sherry B, et al. Obesity and severe obesity forecasts through 2030. Am J Prev Med. (2012) 42:563–70. 10.1016/j.amepre.2011.10.026 [DOI] [PubMed] [Google Scholar]
- 5.Preston S, Vierboom Y, Stokes A. The role of obesity in exceptionally slow US mortality improvement. Proc Nat Acad Sci. (2018) 115:957–61. 10.1073/pnas.1716802115 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Public Health England . Adult Obesity and Type 2 Diabetes. London: Public Health England; (2014). [Google Scholar]
- 7.Hills A, King N, Armstrong T. The contribution of physical activity and sedentary behaviours to the growth and development of children and adolescents. Sports Med. (2007) 37:533–45. 10.2165/00007256-200737060-00006 [DOI] [PubMed] [Google Scholar]
- 8.Candib L. Obesity and diabetes in vulnerable populations: reflection on proximal and distal causes. Ann Fam Med. (2007) 5:547–56. 10.1370/afm.754 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Adeboye B, Bermano G, Rolland C. Obesity and its health impact in Africa: a systematic review. Cardiovasc J Afr. (2012) 23:512–21. 10.5830/CVJA-2012-040 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Sansbury B, Hill B. Regulation of obesity and insulin resistance by nitric oxide. Free Rad Biol Med. (2014) 73:383–99. 10.1016/j.freeradbiomed.2014.05.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Ludwig D, Aronne L, Astrup A, de Cabo R, Cantley L, Friedman M, et al. The carbohydrate-insulin model: a physiological perspective on the obesity pandemic. Am J Clin Nutr. (2021) 114:1873–85. 10.1093/ajcn/nqab270 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Barlow P, Serôdio P, Ruskin G, McKee M, Stuckler D. Science organisations and Coca-Cola's ‘war' with the public health community: insights from an internal industry document. J Epidemiol Community Health. (2018) 72:761–3. 10.1136/jech-2017-210375 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Walsh E, Jacka F, Butterworth P, Anstey K, Cherbuin N. The association between Western and Prudent dietary patterns and fasting blood glucose levels in type 2 diabetes and normal glucose metabolism in older Australian adults. Heliyon. (2017) 3:e00315. 10.1016/j.heliyon.2017.e00315 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Kopp W. How western diet and lifestyle drive the pandemic of obesity and civilization diseases. Diabetes Metab Syndrome Obes Targets Therapy. (2019) 12: 2221 10.2147/DMSO.S216791 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Howard A, Attard S, Herring A, Wang H, Du S, Gordon-Larsen P. Socioeconomic gradients in the Westernization of diet in China over 20 years. SSM Population Health. (2021) 16:100943. 10.1016/j.ssmph.2021.100943 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Kohl H, Craig C, Lambert E, Inoue S, Alkandari J, Leetongin G, et al. The pandemic of physical inactivity: global action for public health. Lancet. (2012) 380:294–305. 10.1016/S0140-6736(12)60898-8 [DOI] [PubMed] [Google Scholar]
- 17.Swinburn B, Sacks G, Hall K, McPherson K, Finegood D, Moodie M, et al. The global obesity pandemic: shaped by global drivers and local environments. Lancet. (2011) 378:804–14. 10.1016/S0140-6736(11)60813-1 [DOI] [PubMed] [Google Scholar]
- 18.Ashton D. Food advertising and childhood obesity. J R Soc Med. (2004) 97:51–2. 10.1177/014107680409700201 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Karnani A, McFerran B, Mukhopadhyay A. Leanwashing: a hidden factor in the obesity crisis. Calif Manage Rev. (2014) 56:5–3. 10.1525/cmr.2014.56.4.5 [DOI] [Google Scholar]
- 20.Jeffery R, Baxter J, McGuire M, Linde J. Are fast food restaurants an environmental risk factor for obesity? Int J Behav Nutr Phys Act. (2006) 3:1–6. 10.1186/1479-5868-3-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Currie J, DellaVigna S, Moretti E, Pathania V. The effect of fast food restaurants on obesity and weight gain. Am Econ J Econ Policy. (2010) 2:32–63. 10.1257/pol.2.3.32 [DOI] [Google Scholar]
- 22.Wells J. Obesity as malnutrition: the role of capitalism in the obesity global epidemic. Am J Hum Biol. (2012) 24:261–76. 10.1002/ajhb.22253 [DOI] [PubMed] [Google Scholar]
- 23.Ewing R, Meakins G, Hamidi S, Nelson A. Relationship between urban sprawl and physical activity, obesity, and morbidity - update and refinement. Health Place. (2014) 26:118–26. 10.1016/j.healthplace.2013.12.008 [DOI] [PubMed] [Google Scholar]
- 24.Barrington-Leigh C, Millard-Ball A. A global assessment of street-network sprawl. PLoS ONE. (2019) 14:e022307. 10.1371/journal.pone.0223078 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Jia P, Cao X, Yang H, Dai S, He P, Huang G, et al. Green space access in the neighbourhood and childhood obesity. Obesity Rev. (2021) 22:e13100. 10.1111/obr.13100 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Mason K, Pearce N, Cummins S. Associations between fast food and physical activity environments and adiposity in mid-life: cross-sectional, observational evidence from UK Biobank. Lancet Public Health. (2018) 3:e24–33. 10.1016/S2468-2667(17)30212-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Lee R, Booth K, Reese-Smith J, Regan G, Howard HH. The Physical Activity Resource Assessment (PARA) instrument: evaluating features, amenities and incivilities of physical activity resources in urban neighbourhoods. Int J Behav Nutr Phys Act. (2005) 2:13. 10.1186/1479-5868-2-13 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Public Health England (PHE) . Health Matters: Obesity and the Food Environment. London: Public Health England; (2017). [Google Scholar]
- 29.Hilmers A, Hilmers D, Dave J. Neighborhood disparities in access to healthy foods and their effects on environmental justice. Am J Public Health. (2012) 102:1644–54. 10.2105/AJPH.2012.300865 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Maguire E, Burgoine T, Monsivais P. Area deprivation and the food environment over time: a repeated cross-sectional study on takeaway outlet density and supermarket presence in Norfolk, UK, 1990–2008. Health Place. (2015) 33:142–7. 10.1016/j.healthplace.2015.02.012 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Whelan A, Wrigley N, Warm D, Cannings E. Life in a 'food desert'. Urban Stud. (2002) 39:2083–100. 10.1080/0042098022000011371 [DOI] [Google Scholar]
- 32.Brazo-Sayavera J, Aubert S, Barnes JD, González SA, Tremblay MS. Gender differences in physical activity and sedentary behavior: results from over 200,000 Latin-American children and adolescents. PLoS ONE. (2021) 16:e0255353. 10.1371/journal.pone.0255353 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Sfm C, Van Cauwenberg J, Maenhout L, Cardon G, Lambert EV, Van Dyck D. Inequality in physical activity, global trends by income inequality and gender in adults. Int J Behav Nutr Phys Act. (2020) 17:1–8. 10.1186/s12966-020-01039-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Muscogiuri G, El Ghoch M, Colao A, Hassapidou M, Yumuk V, Busetto L. European guidelines for obesity management in adults with a very low-calorie ketogenic diet: a systematic review and meta-analysis. Obes Facts. (2021) 14:222–45. 10.1159/000515381 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Foster C, Hillsdon M, Thorogood M, Kaur A, Wedatilake T. Interventions for promoting physical activity. Cochrane Database Syst Rev. (2005) 1:CD003180. 10.1002/14651858.CD003180.pub2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Okorodudu D, Bosworth H, Corsino L. Innovative interventions to promote behavioral change in overweight or obese individuals: a review of the literature. Ann Med. (2015) 47:179–85. 10.3109/07853890.2014.931102 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Lee S, Patel P, Myers ND, Pfeiffer KA, Smith AL, Kelly KS. A systematic review of eHealth interventions to promote physical activity in adults with obesity or overweight. Behav Med. (2022) 38:1–8. 10.1080/08964289.2022.2065239 [DOI] [PubMed] [Google Scholar]
- 38.Mytton O, Gray A, Rayner M, Rutter H. Could targeted food taxes improve health? J Epidemiol Commun Health. (2007) 61:689–94. 10.1136/jech.2006.047746 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Foltz J, May AL, Belay B, Nihiser AJ, Dooyema CA, Blanck HM. Population-level intervention strategies and examples for obesity prevention in children. Annu Rev Nutr. (2012) 32:391–415. 10.1146/annurev-nutr-071811-150646 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Briggs A, Mytton O, Kehlbacher A, Tiffin R, Rayner M, Scarborough P. Overall and income specific effect on prevalence of overweight and obesity of 20% sugar sweetened drink tax in UK: econometric and comparative risk assessment modelling study. Brit Med J. (2013) 347:f6189. 10.1136/bmj.f6189 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Powell LM, Leider J. Impact of a sugar-sweetened beverage tax two-year post-tax implementation in Seattle, Washington, United States. J Public Health Policy. (2021) 42:574–88. 10.1057/s41271-021-00308-8 [DOI] [PubMed] [Google Scholar]
- 42.Adams J, Mytton O, White M, Monsivais P. Why are some population interventions for diet and obesity more equitable and effective than others? The role of individual agency. PLoS Med. (2016) 13:e1001990. 10.1371/journal.pmed.1001990 [DOI] [PMC free article] [PubMed] [Google Scholar]