Skip to main content

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

Obesity: global epidemiology and pathogenesis


The prevalence of obesity has increased worldwide in the past ~50 years, reaching pandemic levels. Obesity represents a major health challenge because it substantially increases the risk of diseases such as type 2 diabetes mellitus, fatty liver disease, hypertension, myocardial infarction, stroke, dementia, osteoarthritis, obstructive sleep apnoea and several cancers, thereby contributing to a decline in both quality of life and life expectancy. Obesity is also associated with unemployment, social disadvantages and reduced socio-economic productivity, thus increasingly creating an economic burden. Thus far, obesity prevention and treatment strategies — both at the individual and population level — have not been successful in the long term. Lifestyle and behavioural interventions aimed at reducing calorie intake and increasing energy expenditure have limited effectiveness because complex and persistent hormonal, metabolic and neurochemical adaptations defend against weight loss and promote weight regain. Reducing the obesity burden requires approaches that combine individual interventions with changes in the environment and society. Therefore, a better understanding of the remarkable regional differences in obesity prevalence and trends might help to identify societal causes of obesity and provide guidance on which are the most promising intervention strategies.

Key points

  • Obesity prevalence has increased in pandemic dimensions over the past 50 years.

  • Obesity is a disease that can cause premature disability and death by increasing the risk of cardiometabolic diseases, osteoarthritis, dementia, depression and some types of cancers.

  • Obesity prevention and treatments frequently fail in the long term (for example, behavioural interventions aiming at reducing energy intake and increasing energy expenditure) or are not available or suitable (bariatric surgery) for the majority of people affected.

  • Although obesity prevalence increased in every single country in the world, regional differences exist in both obesity prevalence and trends; understanding the drivers of these regional differences might help to provide guidance for the most promising intervention strategies.

  • Changes in the global food system together with increased sedentary behaviour seem to be the main drivers of the obesity pandemic.

  • The major challenge is to translate our knowledge of the main causes of increased obesity prevalence into effective actions; such actions might include policy changes that facilitate individual choices for foods that have reduced fat, sugar and salt content.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Factors that can influence the chronic positive energy balance, thus subsequently causing obesity.
Fig. 2: Complex biological, environmental and societal factors contributing to obesity.
Fig. 3: Worldwide prevalence of obesity.
Fig. 4: Increase in prevalence of obesity over time.
Fig. 5: The energy flipping point.


  1. 1.

    World Health Organization. Noncommunicable diseases progress monitor, 2017. WHO (2017).

  2. 2.

    Fontaine, K. R., Redden, D. T., Wang, C., Westfall, A. O. & Allison, D. B. Years of life lost due to obesity. JAMA 289, 187–193 (2003).

    PubMed  Google Scholar 

  3. 3.

    Berrington de Gonzalez, A. et al. Body-mass index and mortality among 1.46 million white adults. N. Engl. J. Med. 363, 2211–2219 (2010).

    CAS  PubMed  Google Scholar 

  4. 4.

    Prospective Studies Collaboration. Body-mass index and cause-specific mortality in 900000 adults: collaborative analyses of 57 prospective studies. Lancet 373, 1083–1096 (2009).

    PubMed Central  Google Scholar 

  5. 5.

    Woolf, A. D. & Pfleger, B. Burden of major musculoskeletal conditions. Bull. World Health Organ. 81, 646–656 (2003).

    PubMed  PubMed Central  Google Scholar 

  6. 6.

    Bray, G. A. et al. Obesity: a chronic relapsing progressive disease process. A position statement of the World Obesity Federation. Obes. Rev. 18, 715–723 (2017).

    CAS  PubMed  Google Scholar 

  7. 7.

    World Health Organization. Obesity and overweight. WHO (2016).

  8. 8.

    World Health Organization. Political declaration of the high-level meeting of the general assembly on the prevention and control of non-communicable diseases. WHO (2012).

  9. 9.

    Franco, M. et al. Population-wide weight loss and regain in relation to diabetes burden and cardiovascular mortality in Cuba 1980-2010: repeated cross sectional surveys and ecological comparison of secular trends. BMJ 346, f1515 (2013).

    PubMed  Google Scholar 

  10. 10.

    Swinburn, B. A. et al. The global obesity pandemic: shaped by global drivers and local environments. Lancet 378, 804–814 (2011).

    PubMed  Google Scholar 

  11. 11.

    Yanovski, J. A. Obesity: Trends in underweight and obesity — scale of the problem. Nat. Rev. Endocrinol. 14, 5–6 (2018).

    PubMed  Google Scholar 

  12. 12.

    Heymsfield, S. B. & Wadden, T. A. Mechanisms, pathophysiology, and management of obesity. N. Engl. J. Med. 376, 254–266 (2017).

    CAS  PubMed  Google Scholar 

  13. 13.

    Murray, S., Tulloch, A., Gold, M. S. & Avena, N. M. Hormonal and neural mechanisms of food reward, eating behaviour and obesity. Nat. Rev. Endocrinol. 10, 540–552 (2014).

    CAS  PubMed  Google Scholar 

  14. 14.

    Farooqi, I. S. Defining the neural basis of appetite and obesity: from genes to behaviour. Clin. Med. 14, 286–289 (2014).

    Google Scholar 

  15. 15.

    Anand, B. K. & Brobeck, J. R. Hypothalamic control of food intake in rats and cats. Yale J. Biol. Med. 24, 123–140 (1951).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Zhang, Y. et al. Positional cloning of the mouse obese gene and its human homologue. Nature 372, 425–432 (1994).

    CAS  PubMed  Google Scholar 

  17. 17.

    Coleman, D. L. & Hummel, K. P. Effects of parabiosis of normal with genetically diabetic mice. Am. J. Physiol. 217, 1298–1304 (1969).

    CAS  PubMed  Google Scholar 

  18. 18.

    Farooqi, I. S. & O’Rahilly, S. 20 years of leptin: human disorders of leptin action. J. Endocrinol. 223, T63–T70 (2014).

    CAS  PubMed  Google Scholar 

  19. 19.

    Börjeson, M. The aetiology of obesity in children. A study of 101 twin pairs. Acta Paediatr. Scand. 65, 279–287 (1976).

    PubMed  Google Scholar 

  20. 20.

    Stunkard, A. J., Harris, J. R., Pedersen, N. L. & McClearn, G. E. The body-mass index of twins who have been reared apart. N. Engl. J. Med. 322, 1483–1487 (1990).

    CAS  PubMed  Google Scholar 

  21. 21.

    Montague, C. T. et al. Congenital leptin deficiency is associated with severe early-onset obesity in humans. Nature 387, 903–908 (1997).

    CAS  PubMed  Google Scholar 

  22. 22.

    Farooqi, I. S. et al. Effects of recombinant leptin therapy in a child with congenital leptin deficiency. N. Engl. J. Med. 341, 879–884 (1999).

    CAS  PubMed  Google Scholar 

  23. 23.

    Clément, K. et al. A mutation in the human leptin receptor gene causes obesity and pituitary dysfunction. Nature 392, 398–401 (1998).

    PubMed  Google Scholar 

  24. 24.

    Farooqi, I. S. et al. Dominant and recessive inheritance of morbid obesity associated with melanocortin 4 receptor deficiency. J. Clin. Invest. 106, 271–279 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. 25.

    Krude, H. et al. Severe early-onset obesity, adrenal insufficiency and red hair pigmentation caused by POMC mutations in humans. Nat. Genet. 19, 155–157 (1998).

    CAS  PubMed  Google Scholar 

  26. 26.

    Hebebrand, J., Volckmar, A. L., Knoll, N. & Hinney, A. Chipping away the ‘missing heritability’: GIANT steps forward in the molecular elucidation of obesity - but still lots to go. Obes. Facts 3, 294–303 (2010).

    PubMed  PubMed Central  Google Scholar 

  27. 27.

    Speliotes, E. K. et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat. Genet. 42, 937–948 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. 28.

    Sharma, A. M. & Padwal, R. Obesity is a sign - over-eating is a symptom: an aetiological framework for the assessment and management of obesity. Obes. Rev. 11, 362–370 (2010).

    CAS  PubMed  Google Scholar 

  29. 29.

    Berthoud, H. R., Münzberg, H. & Morrison, C. D. Blaming the brain for obesity: integration of hedonic and homeostatic mechanisms. Gastroenterology 152, 1728–1738 (2017).

    PubMed  PubMed Central  Google Scholar 

  30. 30.

    Government Office for Science. Foresight. Tackling obesities: future choices – project report. GOV.UK (2007).

  31. 31.

    World Health Organization. International Statistical Classification of Diseases and Related Health Problems 10th revision. WHO (2010).

  32. 32.

    Hebebrand, J. et al. A proposal of the European Association for the Study of Obesity to improve the ICD-11 diagnostic criteria for obesity based on the three dimensions. Obes. Facts 10, 284–307 (2017).

    PubMed  PubMed Central  Google Scholar 

  33. 33.

    Ramos Salas, X. et al. Addressing weight bias and discrimination: moving beyond raising awareness to creating change. Obes. Rev. 18, 1323–1335 (2017).

    CAS  PubMed  Google Scholar 

  34. 34.

    Sharma, A. M. et al. Conceptualizing obesity as a chronic disease: an interview with Dr. Arya Sharma. Adapt. Phys. Activ Q. 35, 285–292 (2018).

    PubMed  Google Scholar 

  35. 35.

    Hebebrand, J. et al. “Eating addiction”, rather than “food addiction”, better captures addictive-like eating behavior. Neurosci. Biobehav. Rev. 47, 295–306 (2014).

    PubMed  Google Scholar 

  36. 36.

    Phelan, S. M. et al. Impact of weight bias and stigma on quality of care and outcomes for patients with obesity. Obes. Rev. 16, 319–326 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Kushner, R. F. et al. Obesity coverage on medical licensing examinations in the United States. What is being tested? Teach Learn. Med. 29, 123–128 (2017).

    PubMed  Google Scholar 

  38. 38.

    NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128.9 million children, adolescents, and adults. Lancet 390, 2627–2642 (2017).

    Google Scholar 

  39. 39.

    NCD Risk Factor Collaboration (NCD-RisC). Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19.2 million participants. Lancet 387, 1377–1396 (2016).

    Google Scholar 

  40. 40.

    Organisation for Economic Co-operation and Development. Obesity update 2017. OECD (2017).

  41. 41.

    Geserick, M. et al. BMI acceleration in early childhood and risk of sustained obesity. N. Engl. J. Med. 379, 1303–1312 (2018).

    PubMed  Google Scholar 

  42. 42.

    Ezzati, M. & Riboli, E. Behavioral and dietary risk factors for noncommunicable diseases. N. Engl. J. Med. 369, 954–964 (2013).

    CAS  PubMed  Google Scholar 

  43. 43.

    Kleinert, S. & Horton, R. Rethinking and reframing obesity. Lancet 385, 2326–2328 (2015).

    PubMed  Google Scholar 

  44. 44.

    Roberto, C. A. et al. Patchy progress on obesity prevention: emerging examples, entrenched barriers, and new thinking. Lancet 385, 2400–2409 (2015).

    PubMed  Google Scholar 

  45. 45.

    Lundborg, P., Nystedt, P. & Lindgren, B. Getting ready for the marriage market? The association between divorce risks and investments in attractive body mass among married Europeans. J. Biosoc. Sci. 39, 531–544 (2007).

    PubMed  Google Scholar 

  46. 46.

    McCabe, M. P. et al. Socio-cultural agents and their impact on body image and body change strategies among adolescents in Fiji, Tonga, Tongans in New Zealand and Australia. Obes. Rev. 12, 61–67 (2011).

    PubMed  Google Scholar 

  47. 47.

    Hayashi, F., Takimoto, H., Yoshita, K. & Yoshiike, N. Perceived body size and desire for thinness of young Japanese women: a population-based survey. Br. J. Nutr. 96, 1154–1162 (2006).

    CAS  PubMed  Google Scholar 

  48. 48.

    Hardin, J., McLennan, A. K. & Brewis, A. Body size, body norms and some unintended consequences of obesity intervention in the Pacific islands. Ann. Hum. Biol. 45, 285–294 (2018).

    PubMed  Google Scholar 

  49. 49.

    Monteiro, C. A., Conde, W. L. & Popkin, B. M. Income-specific trends in obesity in Brazil: 1975–2003. Am. J. Public Health 97, 1808–1812 (2007).

    PubMed  PubMed Central  Google Scholar 

  50. 50.

    Mariapun, J., Ng, C. W. & Hairi, N. N. The gradual shift of overweight, obesity, and abdominal obesity towards the poor in a multi-ethnic developing country: findings from the Malaysian National Health and Morbidity Surveys. J. Epidemiol. 28, 279–286 (2018).

    PubMed  PubMed Central  Google Scholar 

  51. 51.

    Gebrie, A., Alebel, A., Zegeye, A., Tesfaye, B. & Ferede, A. Prevalence and associated factors of overweight/ obesity among children and adolescents in Ethiopia: a systematic review and meta-analysis. BMC Obes. 5, 19 (2018).

    PubMed  PubMed Central  Google Scholar 

  52. 52.

    Rokholm, B., Baker, J. L. & Sørensen, T. I. The levelling off of the obesity epidemic since the year 1999 — a review of evidence and perspectives. Obes. Rev. 11, 835–846 (2010).

    CAS  PubMed  Google Scholar 

  53. 53.

    Hauner, H. et al. Overweight, obesity and high waist circumference: regional differences in prevalence in primary medical care. Dtsch. Arztebl. Int. 105, 827–833 (2008).

    PubMed  PubMed Central  Google Scholar 

  54. 54.

    Myers, C. A. et al. Regional disparities in obesity prevalence in the United States: a spatial regime analysis. Obesity 23, 481–487 (2015).

    PubMed  Google Scholar 

  55. 55.

    Wilkinson, R. G. & Pickett, K. The Spirit Level: Why More Equal Societies Almost Always Do Better 89–102 (Bloomsbury Press London, 2009).

  56. 56.

    Sarget, M. Why inequality is fatal. Nature 458, 1109–1110 (2009).

    Google Scholar 

  57. 57.

    Plachta-Danielzik, S. et al. Determinants of the prevalence and incidence of overweight in children and adolescents. Public Health Nutr. 13, 1870–1881 (2010).

    PubMed  Google Scholar 

  58. 58.

    Bell, A. C., Ge, K. & Popkin, B. M. The road to obesity or the path to prevention: motorized transportation and obesity in China. Obes. Res. 10, 277–283 (2002).

    PubMed  Google Scholar 

  59. 59.

    Ludwig, J. et al. Neighborhoods, obesity, and diabetes — a randomized social experiment. N. Engl. J. Med. 365, 1509–1519 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. 60.

    Beyerlein, A., Kusian, D., Ziegler, A. G., Schaffrath-Rosario, A. & von Kries, R. Classification tree analyses reveal limited potential for early targeted prevention against childhood overweight. Obesity 22, 512–517 (2014).

    PubMed  Google Scholar 

  61. 61.

    Reilly, J. J. et al. Early life risk factors for obesity in childhood: cohort study. BMJ 330, 1357 (2005).

    PubMed  PubMed Central  Google Scholar 

  62. 62.

    Kopelman, P. G. Obesity as a medical problem. Nature 404, 635–643 (2000).

    CAS  Google Scholar 

  63. 63.

    Bouchard, C. et al. The response to long-term overfeeding in identical twins. N. Engl. J. Med. 322, 1477–1482 (1990).

    CAS  PubMed  Google Scholar 

  64. 64.

    Sadeghirad, B., Duhaney, T., Motaghipisheh, S., Campbell, N. R. & Johnston, B. C. Influence of unhealthy food and beverage marketing on children’s dietary intake and preference: a systematic review and meta-analysis of randomized trials. Obes. Rev. 17, 945–959 (2016).

    CAS  PubMed  Google Scholar 

  65. 65.

    Gilbert-Diamond, D. et al. Television food advertisement exposure and FTO rs9939609 genotype in relation to excess consumption in children. Int. J. Obes. 41, 23–29 (2017).

    CAS  Google Scholar 

  66. 66.

    Frayling, T. M. et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 316, 889–894 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. 67.

    Loos, R. J. F. & Yeo, G. S. H. The bigger picture of FTO-the first GWAS-identified obesity gene. Nat. Rev. Endocrinol. 10, 51–61 (2014).

    CAS  PubMed  Google Scholar 

  68. 68.

    Wardle, J. et al. Obesity associated genetic variation in FTO is associated with diminished satiety. J. Clin. Endocrinol. Metab. 93, 3640–3643 (2008).

    CAS  PubMed  Google Scholar 

  69. 69.

    Tanofsky-Kraff, M. et al. The FTO gene rs9939609 obesity-risk allele and loss of control over eating. Am. J. Clin. Nutr. 90, 1483–1488 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  70. 70.

    Hess, M. E. et al. The fat mass and obesity associated gene (Fto) regulates activity of the dopaminergic midbrain circuitry. Nat. Neurosci. 16, 1042–1048 (2013).

    CAS  PubMed  Google Scholar 

  71. 71.

    Fredriksson, R. et al. The obesity gene, FTO, is of ancient origin, up-regulated during food deprivation and expressed in neurons of feeding-related nuclei of the brain. Endocrinology 149, 2062–2071 (2008).

    CAS  PubMed  Google Scholar 

  72. 72.

    Cohen, D. A. Neurophysiological pathways to obesity: below awareness and beyond individual control. Diabetes 57, 1768–1773 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  73. 73.

    Richard, D. Cognitive and autonomic determinants of energy homeostasis in obesity. Nat. Rev. Endocrinol. 11, 489–501 (2015).

    PubMed  Google Scholar 

  74. 74.

    Clemmensen, C. et al. Gut-brain cross-talk in metabolic control. Cell 168, 758–774 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  75. 75.

    Timper, K. & Brüning, J. C. Hypothalamic circuits regulating appetite and energy homeostasis: pathways to obesity. Dis. Model. Mech. 10, 679–689 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  76. 76.

    Kim, K. S., Seeley, R. J. & Sandoval, D. A. Signalling from the periphery to the brain that regulates energy homeostasis. Nat. Rev. Neurosci. 19, 185–196 (2018).

    CAS  PubMed  Google Scholar 

  77. 77.

    Cutler, D. M., Glaeser, E. L. & Shapiro, J. M. Why have Americans become more obese? J. Econ. Perspect. 17, 93–118 (2003).

    Google Scholar 

  78. 78.

    Löffler, A. et al. Effects of psychological eating behaviour domains on the association between socio-economic status and BMI. Public Health Nutr. 20, 2706–2712 (2017).

    PubMed  Google Scholar 

  79. 79.

    Chan, R. S. & Woo, J. Prevention of overweight and obesity: how effective is the current public health approach. Int. J. Environ. Res. Public Health 7, 765–783 (2010).

    PubMed  PubMed Central  Google Scholar 

  80. 80.

    Hsueh, W. C. et al. Analysis of type 2 diabetes and obesity genetic variants in Mexican Pima Indians: marked allelic differentiation among Amerindians at HLA. Ann. Hum. Genet. 82, 287–299 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  81. 81.

    Schulz, L. O. et al. Effects of traditional and western environments on prevalence of type 2 diabetes in Pima Indians in Mexico and the US. Diabetes Care 29, 1866–1871 (2006).

    PubMed  Google Scholar 

  82. 82.

    Rotimi, C. N. et al. Distribution of anthropometric variables and the prevalence of obesity in populations of west African origin: the International Collaborative Study on Hypertension in Blacks (ICSHIB). Obes. Res. 3, 95–105 (1995).

    Google Scholar 

  83. 83.

    Durazo-Arvizu, R. A. et al. Rapid increases in obesity in Jamaica, compared to Nigeria and the United States. BMC Public Health 8, 133 (2008).

    PubMed  PubMed Central  Google Scholar 

  84. 84.

    Hu, F. B., Li, T. Y., Colditz, G. A., Willett, W. C. & Manson, J. E. Television watching and other sedentary behaviors in relation to risk of obesity and type 2 diabetes mellitus in women. JAMA 289, 1785–1791 (2003).

    PubMed  Google Scholar 

  85. 85.

    Rissanen, A. M., Heliövaara, M., Knekt, P., Reunanen, A. & Aromaa, A. Determinants of weight gain and overweight in adult Finns. Eur. J. Clin. Nutr. 45, 419–430 (1991).

    CAS  PubMed  Google Scholar 

  86. 86.

    Zimmet, P. Z., Arblaster, M. & Thoma, K. The effect of westernization on native populations. Studies on a Micronesian community with a high diabetes prevalence. Aust. NZ J. Med. 8, 141–146 (1978).

    CAS  Google Scholar 

  87. 87.

    Ulijaszek, S. J. Increasing body size among adult Cook Islanders between 1966 and 1996. Ann. Hum. Biol. 28, 363–373 (2001).

    CAS  PubMed  Google Scholar 

  88. 88.

    Snowdon, W. & Thow, A. M. Trade policy and obesity prevention: challenges and innovation in the Pacific Islands. Obes. Rev. 14, 150–158 (2013).

    PubMed  Google Scholar 

  89. 89.

    McLennan, A. K. & Ulijaszek, S. J. Obesity emergence in the Pacific islands: why understanding colonial history and social change is important. Public Health Nutr. 18, 1499–1505 (2015).

    PubMed  Google Scholar 

  90. 90.

    Becker, A. E., Gilman, S. E. & Burwell, R. A. Changes in prevalence of overweight and in body image among Fijian women between 1989 and 1998. Obes. Res. 13, 110–117 (2005).

    PubMed  Google Scholar 

  91. 91.

    Swinburn, B., Sacks, G. & Ravussin, E. Increased food energy supply is more than sufficient to explain the US epidemic of obesity. Am. J. Clin. Nutr. 90, 1453–1456 (2009).

    CAS  PubMed  Google Scholar 

  92. 92.

    Swinburn, B. A. et al. Estimating the changes in energy flux that characterize the rise in obesity prevalence. Am. J. Clin. Nutr. 89, 1723–1728 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  93. 93.

    US Department of Agriculture. Food availability (per capita) data system. USDA (updated 29 Oct 2018).

  94. 94.

    Carden, T. J. & Carr, T. P. Food availability of glucose and fat, but not fructose, increased in the U.S. between 1970 and 2009: analysis of the USDA food availability data system. Nutr. J. 12, 130 (2013).

    PubMed  PubMed Central  Google Scholar 

  95. 95.

    Hall, K. D., Guo, J., Dore, M. & Chow, C. C. The progressive increase of food waste in America and its environmental impact. PLOS ONE 4, e7940 (2009).

    PubMed  PubMed Central  Google Scholar 

  96. 96.

    Scarborough, P. et al. Increased energy intake entirely accounts for increase in body weight in women but not in men in the UK between 1986 and 2000. Br. J. Nutr. 105, 1399–1404 (2011).

    CAS  PubMed  Google Scholar 

  97. 97.

    McGinnis, J. M. & Nestle, M. The Surgeon General’s report on nutrition and health: policy implications and implementation strategies. Am. J. Clin. Nutr. 49, 23–28 (1989).

    CAS  PubMed  Google Scholar 

  98. 98.

    Krebs-Smith, S. M., Reedy, J. & Bosire, C. Healthfulness of the U.S. food supply: little improvement despite decades of dietary guidance. Am. J. Prev. Med. 38, 472–477 (2010).

    PubMed  PubMed Central  Google Scholar 

  99. 99.

    Malik, V. S., Popkin, B. M., Bray, G. A., Després, J. P. & Hu, F. B. Sugar-sweetened beverages, obesity, type 2 diabetes mellitus, and cardiovascular disease risk. Circulation 121, 1356–1364 (2010).

    PubMed  PubMed Central  Google Scholar 

  100. 100.

    Schulze, M. B. et al. Sugar-sweetened beverages, weight gain, and incidence of type 2 diabetes in young and middle-aged women. JAMA 292, 927–934 (2004).

    CAS  PubMed  Google Scholar 

  101. 101.

    Mozaffarian, D., Hao, T., Rimm, E. B., Willett, W. C. & Hu, F. B. Changes in diet and lifestyle and long-term weight gain in women and men. N. Engl. J. Med. 364, 2392–2404 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  102. 102.

    Malik, V. S. & Hu, F. B. Sugar-sweetened beverages and health: where does the evidence stand? Am. J. Clin. Nutr. 94, 1161–1162 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  103. 103.

    Qi, Q. et al. Sugar-sweetened beverages and genetic risk of obesity. N. Engl. J. Med. 367, 1387–1396 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  104. 104.

    Heiker, J. T. et al. Identification of genetic loci associated with different responses to high-fat diet-induced obesity in C57BL/6N and C57BL/6J substrains. Physiol. Genomics 46, 377–384 (2014).

    CAS  PubMed  Google Scholar 

  105. 105.

    Wahlqvist, M. L. et al. Early-life influences on obesity: from preconception to adolescence. Ann. NY Acad. Sci. 1347, 1–28 (2015).

    PubMed  Google Scholar 

  106. 106.

    Rohde, K. et al. Genetics and epigenetics in obesity. Metabolism. (2018).

    Article  PubMed  Google Scholar 

  107. 107.

    Panzeri, I. & Pospisilik, J. A. Epigenetic control of variation and stochasticity in metabolic disease. Mol. Metab. 14, 26–38 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  108. 108.

    Ruiz-Hernandez, A. et al. Environmental chemicals and DNA methylation in adults: a systematic review of the epidemiologic evidence. Clin. Epigenet. 7, 55 (2015).

    Google Scholar 

  109. 109.

    Quarta, C., Schneider, R. & Tschöp, M. H. Epigenetic ON/OFF switches for obesity. Cell 164, 341–342 (2016).

    CAS  PubMed  Google Scholar 

  110. 110.

    Dalgaard, K. et al. Trim28 haploinsufficiency triggers bi-stable epigenetic obesity. Cell 164, 353–364 (2015).

    Google Scholar 

  111. 111.

    Michaelides, M. et al. Striatal Rgs4 regulates feeding and susceptibility to diet-induced obesity. Mol. Psychiatry. (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  112. 112.

    Weihrauch-Blüher, S. et al. Current guidelines for obesity prevention in childhood and adolescence. Obes. Facts 11, 263–276 (2018).

    PubMed  PubMed Central  Google Scholar 

  113. 113.

    Nakamura, R. et al. Evaluating the 2014 sugar-sweetened beverage tax in Chile: An observational study in urban areas. PLOS Med. 15, e1002596 (2018).

    PubMed  PubMed Central  Google Scholar 

  114. 114.

    Colchero, M. A., Molina, M. & Guerrero-López, C. M. After Mexico implemented a tax, purchases of sugar-sweetened beverages decreased and water increased: difference by place of residence, household composition, and income level. J. Nutr. 147, 1552–1557 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  115. 115.

    Brownell, K. D. & Warner, K. E. The perils of ignoring history: Big Tobacco played dirty and millions died. How similar is Big Food? Milbank Q. 87, 259–294 (2009).

    PubMed  PubMed Central  Google Scholar 

  116. 116.

    Mialon, M., Swinburn, B., Allender, S. & Sacks, G. ‘Maximising shareholder value’: a detailed insight into the corporate political activity of the Australian food industry. Aust. NZ J. Public Health 41, 165–171 (2017).

    Google Scholar 

  117. 117.

    Peeters, A. Obesity and the future of food policies that promote healthy diets. Nat. Rev. Endocrinol. 14, 430–437 (2018).

    PubMed  Google Scholar 

  118. 118.

    Hawkes, C., Jewell, J. & Allen, K. A food policy package for healthy diets and the prevention of obesity and diet-related non-communicable diseases: the NOURISHING framework. Obes. Rev. 14 (Suppl. 2), 159–168 (2013).

    PubMed  Google Scholar 

  119. 119.

    World Health Organisation. Global database on the Implementation of Nutrition Action (GINA). WHO (2012).

  120. 120.

    Popkin, B., Monteiro, C. & Swinburn, B. Overview: Bellagio Conference on program and policy options for preventing obesity in the low- and middle-income countries. Obes. Rev. 14 (Suppl. 2), 1–8 (2013).

    PubMed  Google Scholar 

Download references

Reviewer information

Nature Reviews Endocrinology thanks G. Bray, A. Sharma and H. Toplak for their contribution to the peer review of this work.

Author information



Corresponding author

Correspondence to Matthias Blüher.

Ethics declarations

Competing interests

The author declares no competing interests.

Additional information

Publisher’s note

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

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Blüher, M. Obesity: global epidemiology and pathogenesis. Nat Rev Endocrinol 15, 288–298 (2019).

Download citation

Further reading


Quick links

Nature Briefing

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

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing