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.
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.
Your institute does not have access to this article
Open Access articles citing this article.
BMC Endocrine Disorders Open Access 27 July 2022
A systematic review and meta-analysis of weight loss in control group participants of lifestyle randomized trials
Scientific Reports Open Access 18 July 2022
Galectin-4 levels in hospitalized versus non-hospitalized subjects with obesity: the Malmö Preventive Project
Cardiovascular Diabetology Open Access 02 July 2022
Subscribe to Nature+
Get immediate online access to the entire Nature family of 50+ journals
Subscribe to Journal
Get full journal access for 1 year
only $4.92 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Get time limited or full article access on ReadCube.
All prices are NET prices.
World Health Organization. Noncommunicable diseases progress monitor, 2017. WHO https://www.who.int/nmh/publications/ncd-progress-monitor-2017/en/ (2017).
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).
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).
Prospective Studies Collaboration. Body-mass index and cause-specific mortality in 900000 adults: collaborative analyses of 57 prospective studies. Lancet 373, 1083–1096 (2009).
Woolf, A. D. & Pfleger, B. Burden of major musculoskeletal conditions. Bull. World Health Organ. 81, 646–656 (2003).
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).
World Health Organization. Obesity and overweight. WHO https://www.who.int/mediacentre/factsheets/fs311/en/ (2016).
World Health Organization. Political declaration of the high-level meeting of the general assembly on the prevention and control of non-communicable diseases. WHO https://www.who.int/nmh/events/un_ncd_summit2011/political_declaration_en.pdf (2012).
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).
Swinburn, B. A. et al. The global obesity pandemic: shaped by global drivers and local environments. Lancet 378, 804–814 (2011).
Yanovski, J. A. Obesity: Trends in underweight and obesity — scale of the problem. Nat. Rev. Endocrinol. 14, 5–6 (2018).
Heymsfield, S. B. & Wadden, T. A. Mechanisms, pathophysiology, and management of obesity. N. Engl. J. Med. 376, 254–266 (2017).
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).
Farooqi, I. S. Defining the neural basis of appetite and obesity: from genes to behaviour. Clin. Med. 14, 286–289 (2014).
Anand, B. K. & Brobeck, J. R. Hypothalamic control of food intake in rats and cats. Yale J. Biol. Med. 24, 123–140 (1951).
Zhang, Y. et al. Positional cloning of the mouse obese gene and its human homologue. Nature 372, 425–432 (1994).
Coleman, D. L. & Hummel, K. P. Effects of parabiosis of normal with genetically diabetic mice. Am. J. Physiol. 217, 1298–1304 (1969).
Farooqi, I. S. & O’Rahilly, S. 20 years of leptin: human disorders of leptin action. J. Endocrinol. 223, T63–T70 (2014).
Börjeson, M. The aetiology of obesity in children. A study of 101 twin pairs. Acta Paediatr. Scand. 65, 279–287 (1976).
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).
Montague, C. T. et al. Congenital leptin deficiency is associated with severe early-onset obesity in humans. Nature 387, 903–908 (1997).
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).
Clément, K. et al. A mutation in the human leptin receptor gene causes obesity and pituitary dysfunction. Nature 392, 398–401 (1998).
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).
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).
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).
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).
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).
Berthoud, H. R., Münzberg, H. & Morrison, C. D. Blaming the brain for obesity: integration of hedonic and homeostatic mechanisms. Gastroenterology 152, 1728–1738 (2017).
Government Office for Science. Foresight. Tackling obesities: future choices – project report. GOV.UK https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/287937/07-1184x-tackling-obesities-future-choices-report.pdf (2007).
World Health Organization. International Statistical Classification of Diseases and Related Health Problems 10th revision. WHO http://apps.who.int/classifications/icd10/browse/2010/en (2010).
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).
Ramos Salas, X. et al. Addressing weight bias and discrimination: moving beyond raising awareness to creating change. Obes. Rev. 18, 1323–1335 (2017).
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).
Hebebrand, J. et al. “Eating addiction”, rather than “food addiction”, better captures addictive-like eating behavior. Neurosci. Biobehav. Rev. 47, 295–306 (2014).
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).
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).
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).
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).
Organisation for Economic Co-operation and Development. Obesity update 2017. OECD https://www.oecd.org/els/health-systems/Obesity-Update-2017.pdf (2017).
Geserick, M. et al. BMI acceleration in early childhood and risk of sustained obesity. N. Engl. J. Med. 379, 1303–1312 (2018).
Ezzati, M. & Riboli, E. Behavioral and dietary risk factors for noncommunicable diseases. N. Engl. J. Med. 369, 954–964 (2013).
Kleinert, S. & Horton, R. Rethinking and reframing obesity. Lancet 385, 2326–2328 (2015).
Roberto, C. A. et al. Patchy progress on obesity prevention: emerging examples, entrenched barriers, and new thinking. Lancet 385, 2400–2409 (2015).
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).
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).
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).
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).
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).
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).
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).
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).
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).
Myers, C. A. et al. Regional disparities in obesity prevalence in the United States: a spatial regime analysis. Obesity 23, 481–487 (2015).
Wilkinson, R. G. & Pickett, K. The Spirit Level: Why More Equal Societies Almost Always Do Better 89–102 (Bloomsbury Press London, 2009).
Sarget, M. Why inequality is fatal. Nature 458, 1109–1110 (2009).
Plachta-Danielzik, S. et al. Determinants of the prevalence and incidence of overweight in children and adolescents. Public Health Nutr. 13, 1870–1881 (2010).
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).
Ludwig, J. et al. Neighborhoods, obesity, and diabetes — a randomized social experiment. N. Engl. J. Med. 365, 1509–1519 (2011).
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).
Reilly, J. J. et al. Early life risk factors for obesity in childhood: cohort study. BMJ 330, 1357 (2005).
Kopelman, P. G. Obesity as a medical problem. Nature 404, 635–643 (2000).
Bouchard, C. et al. The response to long-term overfeeding in identical twins. N. Engl. J. Med. 322, 1477–1482 (1990).
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).
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).
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).
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).
Wardle, J. et al. Obesity associated genetic variation in FTO is associated with diminished satiety. J. Clin. Endocrinol. Metab. 93, 3640–3643 (2008).
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).
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).
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).
Cohen, D. A. Neurophysiological pathways to obesity: below awareness and beyond individual control. Diabetes 57, 1768–1773 (2008).
Richard, D. Cognitive and autonomic determinants of energy homeostasis in obesity. Nat. Rev. Endocrinol. 11, 489–501 (2015).
Clemmensen, C. et al. Gut-brain cross-talk in metabolic control. Cell 168, 758–774 (2017).
Timper, K. & Brüning, J. C. Hypothalamic circuits regulating appetite and energy homeostasis: pathways to obesity. Dis. Model. Mech. 10, 679–689 (2017).
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).
Cutler, D. M., Glaeser, E. L. & Shapiro, J. M. Why have Americans become more obese? J. Econ. Perspect. 17, 93–118 (2003).
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).
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).
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).
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).
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).
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).
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).
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).
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).
Ulijaszek, S. J. Increasing body size among adult Cook Islanders between 1966 and 1996. Ann. Hum. Biol. 28, 363–373 (2001).
Snowdon, W. & Thow, A. M. Trade policy and obesity prevention: challenges and innovation in the Pacific Islands. Obes. Rev. 14, 150–158 (2013).
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).
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).
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).
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).
US Department of Agriculture. Food availability (per capita) data system. USDA https://www.ers.usda.gov/data-products/food-availability-per-capita-data-system/ (updated 29 Oct 2018).
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).
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).
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).
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).
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).
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).
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).
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).
Malik, V. S. & Hu, F. B. Sugar-sweetened beverages and health: where does the evidence stand? Am. J. Clin. Nutr. 94, 1161–1162 (2011).
Qi, Q. et al. Sugar-sweetened beverages and genetic risk of obesity. N. Engl. J. Med. 367, 1387–1396 (2012).
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).
Wahlqvist, M. L. et al. Early-life influences on obesity: from preconception to adolescence. Ann. NY Acad. Sci. 1347, 1–28 (2015).
Rohde, K. et al. Genetics and epigenetics in obesity. Metabolism. https://doi.org/10.1016/j.metabol.2018.10.007 (2018).
Panzeri, I. & Pospisilik, J. A. Epigenetic control of variation and stochasticity in metabolic disease. Mol. Metab. 14, 26–38 (2018).
Ruiz-Hernandez, A. et al. Environmental chemicals and DNA methylation in adults: a systematic review of the epidemiologic evidence. Clin. Epigenet. 7, 55 (2015).
Quarta, C., Schneider, R. & Tschöp, M. H. Epigenetic ON/OFF switches for obesity. Cell 164, 341–342 (2016).
Dalgaard, K. et al. Trim28 haploinsufficiency triggers bi-stable epigenetic obesity. Cell 164, 353–364 (2015).
Michaelides, M. et al. Striatal Rgs4 regulates feeding and susceptibility to diet-induced obesity. Mol. Psychiatry. https://doi.org/10.1038/s41380-018-0120-7 (2018).
Weihrauch-Blüher, S. et al. Current guidelines for obesity prevention in childhood and adolescence. Obes. Facts 11, 263–276 (2018).
Nakamura, R. et al. Evaluating the 2014 sugar-sweetened beverage tax in Chile: An observational study in urban areas. PLOS Med. 15, e1002596 (2018).
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).
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).
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).
Peeters, A. Obesity and the future of food policies that promote healthy diets. Nat. Rev. Endocrinol. 14, 430–437 (2018).
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).
World Health Organisation. Global database on the Implementation of Nutrition Action (GINA). WHO https://www.who.int/nutrition/gina/en/ (2012).
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).
Nature Reviews Endocrinology thanks G. Bray, A. Sharma and H. Toplak for their contribution to the peer review of this work.
The author declares no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Blüher, M. Obesity: global epidemiology and pathogenesis. Nat Rev Endocrinol 15, 288–298 (2019). https://doi.org/10.1038/s41574-019-0176-8
Child and Adolescent Psychiatry and Mental Health (2022)
Transcriptomic profiling of the telomerase transformed Mesenchymal stromal cells derived adipocytes in response to rosiglitazone
BMC Genomic Data (2022)
Galectin-4 levels in hospitalized versus non-hospitalized subjects with obesity: the Malmö Preventive Project
Cardiovascular Diabetology (2022)
Interplay between fatty acid desaturase2 (FADS2) rs174583 genetic variant and dietary antioxidant capacity: cardio-metabolic risk factors in obese individuals
BMC Endocrine Disorders (2022)
Long noncoding RNA XIST regulates brown preadipocytes differentiation and combats high-fat diet induced obesity by targeting C/EBPα
Molecular Medicine (2022)