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The multiple roles of life stress in metabolic disorders

Abstract

The activation of stress-related neuroendocrine systems helps to maintain homeostasis, but excessive stress can damage body functions. We review current evidence from basic sciences and epidemiology linking stress to the development and progression of metabolic disorders throughout life. Findings from rodents demonstrate that stress can affect features of metabolic dysfunction, such as insulin resistance, glucose and lipid homeostasis, as well as ageing processes such as cellular senescence and telomere length shortening. In human studies, stressors in the home, workplace and neighbourhood are associated with accelerated ageing and metabolic and immune alterations, both directly and indirectly via behavioural risks. The likelihood of developing clinical conditions, such as diabetes mellitus and hepatic steatosis is increased in individuals with adverse childhood experiences or long-term (years) or severe stress at work or in private life. The increased risk of metabolic disorders is often associated with other stress-related conditions, such as mental health disorders, cardiovascular disease and increased susceptibility to infections. Equally, stress can worsen prognosis in metabolic diseases. As favourable modifications in stressors are associated with reductions in incidence of metabolic disorders, further investigation of the therapeutic value of targeting stress in personalized medicine is warranted.

Key points

  • Both animal and human research suggests that stress and related changes in sympathetic–parasympathetic balance and the hypothalamic–pituitary–adrenal axis can accelerate biological ageing, including unfavourable changes in metabolism and immune function.

  • The adverse impact on metabolic disease risk in adults with a history of childhood adversity is potentiated by mental disorders and behavioural risks and the risk of metabolic disease can be more than twofold higher than in adults without childhood adversity.

  • In adults, stress is associated with a 1.1-fold to 1.4-fold excess risk of obesity, diabetes mellitus and liver disease.

  • The excess risk for mental disorders, such as depression, and cardiovascular disease among individuals with stress in adulthood is slightly higher than that for obesity, diabetes mellitus and liver disease.

  • Life stress is also a prognostic factor in patients, accelerating the transition of metabolic diseases towards multimorbidity, frailty and death.

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Fig. 1: Mechanisms of stress-induced metabolic changes.
Fig. 2: Preclinical metabolic changes from childhood to adulthood in individuals exposed to stressors at the individual and community levels and with stress appraisal.
Fig. 3: Disease trajectories, multimorbidity and death in individuals exposed to socioeconomic stressors at the individual and community levels.

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References

  1. GBD 2019 Diseases and Injuries Collaborators. Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet 396, 1204–1222 (2020).

    Article  Google Scholar 

  2. Paik, J. M. et al. The growing burden of disability related to nonalcoholic fatty liver disease: data from the Global Burden of Disease 2007–2017. Hepatol. Commun. 4, 1769–1780 (2020).

    Article  Google Scholar 

  3. Dai, H. et al. The global burden of disease attributable to high body mass index in 195 countries and territories, 1990–2017: an analysis of the Global Burden of Disease Study. PLoS Med. 17, e1003198 (2020).

    Article  Google Scholar 

  4. McEwen, B. S. Protective and damaging effects of stress mediators. N. Engl. J. Med. 338, 171–179 (1998).

    Article  CAS  Google Scholar 

  5. Koolhaas, J. M. et al. Stress revisited: a critical evaluation of the stress concept. Neurosci. Biobehav. Rev. 35, 1291–1301 (2011). This review of animal models and human studies suggests that stress is characterized by the absence of an anticipatory response (unpredictable) or a reduced recovery (uncontrollable) of the neuroendocrine reaction, and proposes a definition for the term ‘stress’ as a condition where environmental demands exceed the natural regulatory capacity of an organism.

    Article  CAS  Google Scholar 

  6. Epel, E. S. et al. More than a feeling: a unified view of stress measurement for population science. Front. Neuroendocrinol. 49, 146–169 (2018).

    Article  Google Scholar 

  7. Snyder-Mackler, N. et al. Social determinants of health and survival in humans and other animals. Science 368, eaax9553 (2020). This paper demonstrates strong parallels in the consequences of social adversity between humans and other social mammals, and reviews studies in experimental animal models that show socially induced stress is, by itself, sufficient to damage health and shorten lifespan.

    Article  CAS  Google Scholar 

  8. Bartolomucci, A. Social stress, immune functions and disease in rodents. Front. Neuroendocrinol. 28, 28–49 (2007).

    Article  CAS  Google Scholar 

  9. Kirschbaum, C., Pirke, K. M. & Hellhammer, D. H. The ‘Trier Social Stress Test’–a tool for investigating psychobiological stress responses in a laboratory setting. Neuropsychobiol 28, 76–81 (1993).

    Article  CAS  Google Scholar 

  10. Harkness, K. L. & Monroe, S. M. The assessment and measurement of adult life stress: basic premises, operational principles, and design requirements. J. Abnorm. Psychol. 125, 727–745 (2016).

    Article  Google Scholar 

  11. Kivimaki, M. & Steptoe, A. Effects of stress on the development and progression of cardiovascular disease. Nat. Rev. Cardiol. 15, 215–229 (2018).

    Article  CAS  Google Scholar 

  12. Cohen, S., Janicki-Deverts, D. & Miller, G. E. Psychological stress and disease. JAMA 298, 1685–1687 (2007).

    Article  CAS  Google Scholar 

  13. Lampert, R. et al. Triggering of symptomatic atrial fibrillation by negative emotion. J. Am. Coll. Cardiol. 64, 1533–1534 (2014).

    Article  Google Scholar 

  14. Gunnar, M. & Quevedo, K. The neurobiology of stress and development. Annu. Rev. Psychol. 58, 145–173 (2007).

    Article  Google Scholar 

  15. Russell, G. & Lightman, S. The human stress response. Nat. Rev. Endocrinol. 15, 525–534 (2019). A review of evidence on the human stress response, the cortisol ultradian rhythmicity under basal and stressful conditions and their relevance for cardiovascular, immunological and metabolic function.

    Article  Google Scholar 

  16. Ulrich-Lai, Y. M. & Herman, J. P. Neural regulation of endocrine and autonomic stress responses. Nat. Rev. Neurosci. 10, 397–409 (2009).

    Article  CAS  Google Scholar 

  17. Tawakol, A. et al. Relation between resting amygdalar activity and cardiovascular events: a longitudinal and cohort study. Lancet 389, 834–884 (2017).

    Article  Google Scholar 

  18. Lightman, S. L., Birnie, M. T. & Conway-Campbell, B. L. Dynamics of ACTH and cortisol secretion and implications for disease. Endocr. Rev. 41, bnaa002 (2020).

    Article  Google Scholar 

  19. Russell, E., Koren, G., Rieder, M. & Van Uum, S. Hair cortisol as a biological marker of chronic stress: current status, future directions and unanswered questions. Psychoneuroendocrinology 37, 589–601 (2012).

    Article  CAS  Google Scholar 

  20. Sara, J. D. S. et al. Mental stress and its effects on vascular health. Mayo Clin. Proc. 97, 951–990 (2022).

    Article  Google Scholar 

  21. Razzoli, M. et al. Social stress shortens lifespan in mice. Aging Cell 17, e12778 (2018). A mouse model that demonstrates the adverse effect of subordinate social status on lifespan, implicating cellular senescence in ageing-associated diseases.

    Article  Google Scholar 

  22. Koert, A. et al. The social instability stress paradigm in rat and mouse: a systematic review of protocols, limitations, and recommendations. Neurobiol. Stress. 5, 100410 (2021).

    Article  Google Scholar 

  23. Lacroix, A., Feelders, R. A., Stratakis, C. A. & Nieman, L. K. Cushing’s syndrome. Lancet 386, 913–927 (2015).

    Article  CAS  Google Scholar 

  24. Ferrau, F. & Korbonits, M. Metabolic comorbidities in Cushing’s syndrome. Eur. J. Endocrinol. 173, M133–M157 (2015).

    Article  CAS  Google Scholar 

  25. Constantinescu, G. et al. Glucocorticoid excess in patients with pheochromocytoma compared with paraganglioma and other forms of hypertension. J. Clin. Endocrinol. Metab. 105, dgaa423 (2020).

    Article  Google Scholar 

  26. O’Donnell, C. J. et al. Posttraumatic stress disorder and cardiovascular disease: state of the science, knowledge gaps, and research opportunities. JAMA Cardiol. 6, 1207–1216 (2021).

    Article  Google Scholar 

  27. Wingenfeld, K., Whooley, M. A., Neylan, T. C., Otte, C. & Cohen, B. E. Effect of current and lifetime posttraumatic stress disorder on 24-h urinary catecholamines and cortisol: results from the Mind Your Heart Study. Psychoneuroendocrinology 52, 83–91 (2015).

    Article  CAS  Google Scholar 

  28. Kwok, M. K., Kawachi, I., Rehkopf, D. & Schooling, C. M. The role of cortisol in ischemic heart disease, ischemic stroke, type 2 diabetes, and cardiovascular disease risk factors: a bi-directional Mendelian randomization study. BMC Med. 18, 363 (2020).

    Article  CAS  Google Scholar 

  29. Pan, X., Wang, Z., Wu, X., Wen, S. W. & Liu, A. Salivary cortisol in post-traumatic stress disorder: a systematic review and meta-analysis. BMC Psychiatry 18, 324 (2018).

    Article  CAS  Google Scholar 

  30. Meewisse, M. L., Reitsma, J. B., de Vries, G. J., Gersons, B. P. & Olff, M. Cortisol and post-traumatic stress disorder in adults: systematic review and meta-analysis. Br. J. Psychiatry 191, 387–392 (2007).

    Article  Google Scholar 

  31. Stalder, T. et al. Stress-related and basic determinants of hair cortisol in humans: a meta-analysis. Psychoneuroendocrinology 77, 261–274 (2017).

    Article  CAS  Google Scholar 

  32. Oster, H. et al. The functional and clinical significance of the 24-hour rhythm of circulating glucocorticoids. Endocr. Rev. 38, 3–45 (2017).

    Article  Google Scholar 

  33. Chrousos, G. P. Stress, chronic inflammation, and emotional and physical well-being: concurrent effects and chronic sequelae. J. Allergy Clin. Immunol. 106, S275–S291 (2000).

    Article  CAS  Google Scholar 

  34. Ramamoorthy, S. & Cidlowski, J. A. Corticosteroids: mechanisms of action in health and disease. Rheum. Dis. Clin. North Am. 42, 15–31 (2016).

    Article  Google Scholar 

  35. Bartolomucci, A. et al. The extended granin family: structure, function, and biomedical implications. Endocr. Rev. 32, 755–797 (2011).

    Article  CAS  Google Scholar 

  36. Hirsch, D. & Zukowska, Z. NPY and stress 30 years later: the peripheral view. Cell Mol. Neurobiol. 32, 645–659 (2012).

    Article  CAS  Google Scholar 

  37. Possenti, R. et al. Characterization of a novel peripheral pro-lipolytic mechanism in mice: role of VGF-derived peptide TLQP-21. Biochem. J. 441, 511–522 (2012).

    Article  CAS  Google Scholar 

  38. Berger, J. M. et al. Mediation of the acute stress response by the skeleton. Cell Metab. 30, 890–902 (2019). This paper describes the role of osteoblasts and osteocalcin in the body’s metabolic regulation and modulation of the acute stress response and parasympathetic tone.

    Article  CAS  Google Scholar 

  39. Rentscher, K. E. et al. Chronic stress exposure and daily stress appraisals relate to biological aging marker p16(INK4a). Psychoneuroendocrinology 102, 139–148 (2019).

    Article  CAS  Google Scholar 

  40. Belsky, D. W. et al. Quantification of the pace of biological aging in humans through a blood test, the DunedinPoAm DNA methylation algorithm. eLife 9, 54870 (2020).

    Article  Google Scholar 

  41. Noren Hooten, N., Pacheco, N. L., Smith, J. T. & Evans, M. K. The accelerated aging phenotype: the role of race and social determinants of health on aging. Ageing Res. Rev. 73, 101536 (2022).

    Article  Google Scholar 

  42. Snyder-Mackler, N. et al. Social status alters immune regulation and response to infection in macaques. Science 354, 1041–1045 (2016). By manipulating the social status of individual macaques this animal study examined how stress affects immune function, demonstrating that social status influences the immune system at multiple levels, from immune cell numbers to gene expression and signalling pathways.

    Article  CAS  Google Scholar 

  43. de Kloet, E. R., Meijer, O. C., de Nicola, A. F., de Rijk, R. H. & Joels, M. Importance of the brain corticosteroid receptor balance in metaplasticity, cognitive performance and neuro-inflammation. Front. Neuroendocrinol. 49, 124–145 (2018).

    Article  Google Scholar 

  44. Sapolsky, R. M., Romero, L. M. & Munck, A. U. How do glucocorticoids influence stress responses? Integrating permissive, suppressive, stimulatory, and preparative actions. Endocr. Rev. 21, 55–89 (2000).

    CAS  Google Scholar 

  45. Ogawa, A. et al. Roles of insulin resistance and beta-cell dysfunction in dexamethasone-induced diabetes. J. Clin. Invest. 90, 497–504 (1992).

    Article  CAS  Google Scholar 

  46. Wiesner, T. D., Bluher, M., Windgassen, M. & Paschke, R. Improvement of insulin sensitivity after adrenalectomy in patients with pheochromocytoma. J. Clin. Endocrinol. Metab. 88, 3632–3636 (2003).

    Article  CAS  Google Scholar 

  47. Utzschneider, K. M. & Kahn, S. E. Review: the role of insulin resistance in nonalcoholic fatty liver disease. J. Clin. Endocrinol. Metab. 91, 4753–4761 (2006).

    Article  CAS  Google Scholar 

  48. Kivimaki, M. et al. Neighbourhood socioeconomic disadvantage, risk factors, and diabetes: a cohort study from childhood to middle age. Lancet Public Health 3, e365–e373 (2018).

    Article  Google Scholar 

  49. Surwit, R. S. et al. Stress management improves long-term glycemic control in type 2 diabetes. Diabetes Care 25, 30–34 (2002).

    Article  Google Scholar 

  50. Takahashi, A., Flanigan, M. E., McEwen, B. S. & Russo, S. J. Aggression, social stress, and the immune system in humans and animal models. Front. Behav. Neurosci. 12, 56 (2018).

    Article  Google Scholar 

  51. Cohen, S. et al. Chronic stress, glucocorticoid receptor resistance, inflammation, and disease risk. Proc. Natl. Acad. Sci. U. S. A. 109, 5995–5999 (2012). The paper describes two viral challenge studies among people with and without stress, and provides support for the concept that prolonged exposure to a stressor can result in glucocorticoid receptor resistance and dysregulation of immune function, potentially contributing to the onset and progression of a wide range of diseases.

    Article  CAS  Google Scholar 

  52. Winning, A., Glymour, M. M., McCormick, M. C., Gilsanz, P. & Kubzansky, L. D. Psychological distress across the life course and cardiometabolic risk: findings from the 1958 British Birth Cohort study. J. Am. Coll. Cardiol. 66, 1577–1586 (2015). This longitudinal analysis of the of the 1958 British Birth Cohort Study showed that psychological distress at any point in the life course is associated with higher cardiometabolic risk, the highest risk being evident among those with distress in both childhood and adulthood.

    Article  Google Scholar 

  53. Deighton, S., Neville, A., Pusch, D. & Dobson, K. Biomarkers of adverse childhood experiences: a scoping review. Psychiatry Res. 269, 719–732 (2018).

    Article  CAS  Google Scholar 

  54. Crick, D. C. P. et al. Associations between adverse childhood experiences and the novel inflammatory marker glycoprotein acetyls in two generations of the Avon Longitudinal Study of Parents and Children Birth Cohort. Brain Behav. Immun. 100, 112–120 (2022).

    Article  CAS  Google Scholar 

  55. Berger, E. et al. Multi-cohort study identifies social determinants of systemic inflammation over the life course. Nat. Commun. 10, 773 (2019).

    Article  CAS  Google Scholar 

  56. Danese, A. & McEwen, B. S. Adverse childhood experiences, allostasis, allostatic load, and age-related disease. Physiol. Behav. 106, 29–39 (2012).

    Article  CAS  Google Scholar 

  57. Ribeiro, A. I. et al. Neighbourhood socioeconomic deprivation and allostatic load: a multi-cohort study. Sci. Rep. 9, 8790 (2019).

    Article  Google Scholar 

  58. Pivonello, R. et al. Complications of Cushing’s syndrome: state of the art. Lancet Diabetes Endocrinol. 4, 611–629 (2016).

    Article  CAS  Google Scholar 

  59. Hasenmajer, V. et al. The immune system in Cushing’s syndrome. Trends Endocrinol. Metab. 31, 655–669 (2020).

    Article  CAS  Google Scholar 

  60. Passos, I. C. et al. Inflammatory markers in post-traumatic stress disorder: a systematic review, meta-analysis, and meta-regression. Lancet Psychiatry 2, 1002–1012 (2015).

    Article  Google Scholar 

  61. Olff, M. & van Zuiden, M. Neuroendocrine and neuroimmune markers in PTSD: pre-, peri- and post-trauma glucocorticoid and inflammatory dysregulation. Curr. Opin. Psychol. 14, 132–137 (2017).

    Article  Google Scholar 

  62. Sumner, J. A. et al. Post-traumatic stress disorder symptoms and risk of hypertension over 22 years in a large cohort of younger and middle-aged women. Psychol. Med. 46, 3105–3116 (2016).

    Article  CAS  Google Scholar 

  63. Shalev, A., Liberzon, I. & Marmar, C. Post-traumatic stress disorder. N. Engl. J. Med. 376, 2459–2469 (2017).

    Article  Google Scholar 

  64. Zelinka, T. et al. Elevated inflammation markers in pheochromocytoma compared to other forms of hypertension. Neuroimmunomodulation 14, 57–64 (2007).

    Article  CAS  Google Scholar 

  65. Liu, Z. et al. Associations of genetics, behaviors, and life course circumstances with a novel aging and healthspan measure: evidence from the Health and Retirement Study. PLoS Med. 16, e1002827 (2019).

    Article  Google Scholar 

  66. Barzilai, N., Huffman, D. M., Muzumdar, R. H. & Bartke, A. The critical role of metabolic pathways in aging. Diabetes 61, 1315–1322 (2012).

    Article  CAS  Google Scholar 

  67. Alpert, A. et al. A clinically meaningful metric of immune age derived from high-dimensional longitudinal monitoring. Nat. Med. 25, 487–495 (2019).

    Article  CAS  Google Scholar 

  68. Ferrucci, L. & Fabbri, E. Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty. Nat. Rev. Cardiol. 15, 505–522 (2018).

    Article  CAS  Google Scholar 

  69. Crimmins, E. M. Social hallmarks of aging: suggestions for geroscience research. Ageing Res. Rev. 63, 101136 (2020).

    Article  Google Scholar 

  70. Epel, E. S. The geroscience agenda: toxic stress, hormetic stress, and the rate of aging. Ageing Res. Rev. 63, 101167 (2020).

    Article  CAS  Google Scholar 

  71. Lopez-Otin, C., Blasco, M. A., Partridge, L., Serrano, M. & Kroemer, G. The hallmarks of aging. Cell 153, 1194–1217 (2013).

    Article  CAS  Google Scholar 

  72. Childs, B. G., Durik, M., Baker, D. J. & van Deursen, J. M. Cellular senescence in aging and age-related disease: from mechanisms to therapy. Nat. Med. 21, 1424–1435 (2015).

    Article  CAS  Google Scholar 

  73. Lin, J. & Epel, E. S. Stress and telomere shortening: insights from cellular mechanisms. Ageing Res. Rev. 73, 101507 (2022).

    Article  CAS  Google Scholar 

  74. Colich, N. L., Rosen, M. L., Williams, E. S. & McLaughlin, K. A. Biological aging in childhood and adolescence following experiences of threat and deprivation: a systematic review and meta-analysis. Psychol. Bull. 146, 721–764 (2020). A review and meta-analysis of 54 studies and over 116,010 participants synthesizing the evidence on the associations of early life adversity with pubertal timing and cellular ageing indicated by telomere length and DNA methylation age.

    Article  Google Scholar 

  75. Epel, E. S. et al. Accelerated telomere shortening in response to life stress. Proc. Natl. Acad. Sci. USA 101, 17312–17315 (2004).

    Article  CAS  Google Scholar 

  76. Wolf, E. J. et al. Traumatic stress and accelerated DNA methylation age: a meta-analysis. Psychoneuroendocrinology 92, 123–134 (2018).

    Article  CAS  Google Scholar 

  77. Reuben, A. et al. Association of neighborhood disadvantage in childhood with DNA methylation in young adulthood. JAMA Netw. Open 3, e206095 (2020).

    Article  Google Scholar 

  78. Raffington, L. & Belsky, D. W. Integrating DNA methylation measures of biological aging into social determinants of health research. Curr. Environ. Health Rep. 9, 196–210 (2022).

    Article  Google Scholar 

  79. Freni-Sterrantino, A. et al. Work-related stress and well-being in association with epigenetic age acceleration: a Northern Finland Birth Cohort 1966 Study. Aging 14, 1128–1156 (2022).

    Article  CAS  Google Scholar 

  80. Turecki, G. & Meaney, M. J. Effects of the social environment and stress on glucocorticoid receptor gene methylation: a systematic review. Biol. Psychiatry 79, 87–96 (2016).

    Article  CAS  Google Scholar 

  81. Zheng, Y., Ley, S. H. & Hu, F. B. Global aetiology and epidemiology of type 2 diabetes mellitus and its complications. Nat. Rev. Endocrinol. 14, 88–98 (2018).

    Article  Google Scholar 

  82. Carlsson, L. M. et al. Bariatric surgery and prevention of type 2 diabetes in Swedish obese subjects. N. Engl. J. Med. 367, 695–704 (2012).

    Article  CAS  Google Scholar 

  83. Pontzer, H. et al. Daily energy expenditure through the human life course. Science 373, 808–812 (2021).

    Article  CAS  Google Scholar 

  84. Stefanaki, C., Pervanidou, P., Boschiero, D. & Chrousos, G. P. Chronic stress and body composition disorders: implications for health and disease. Hormones 17, 33–43 (2018).

    Article  Google Scholar 

  85. Santosa, A. et al. Psychosocial risk factors and cardiovascular disease and death in a population-based cohort from 21 low-, middle-, and high-income countries. JAMA Netw. Open 4, e2138920 (2021).

    Article  Google Scholar 

  86. Rautava, S. et al. Neighborhood socioeconomic disadvantage and childhood body mass index trajectories from birth to 7 years of age. Epidemiol 33, 121–130 (2022).

    Article  Google Scholar 

  87. Ochoa, L. B. et al. Association of neighbourhood socioeconomic trajectories with preterm birth and small-for-gestational-age in the Netherlands: a nationwide population-based study. Lancet Reg. Health Eur. 10, 100205 (2021).

    Article  Google Scholar 

  88. Razzoli, M. & Bartolomucci, A. The dichotomous effect of chronic stress on obesity. Trends Endocrinol. Metab. 27, 504–515 (2016).

    Article  CAS  Google Scholar 

  89. Rosengren, A. et al. Psychosocial factors and obesity in 17 high-, middle- and low-income countries: the Prospective Urban Rural Epidemiologic (PURE) study. Int. J. Obes. 39, 1217–1223 (2015).

    Article  CAS  Google Scholar 

  90. Oliver, G. & Wardle, J. Perceived effects of stress on food choice. Physiol. Behav. 66, 511–515 (1999).

    Article  CAS  Google Scholar 

  91. Kivimäki, M. et al. Work stress, weight gain and weight loss: evidence for bidirectional effects of job strain on body mass index in the Whitehall II study. Int. J. Obes. 30, 982–987 (2006).

    Article  Google Scholar 

  92. Nyberg, S. T. et al. Job strain in relation to body mass index: pooled analysis of 160 000 adults from 13 cohort studies. J. Int. Med. 272, 65–73 (2012).

    Article  CAS  Google Scholar 

  93. Razzoli, M., Pearson, C., Crow, S. & Bartolomucci, A. Stress, overeating, and obesity: insights from human studies and preclinical models. Neurosci. Biobehav. Rev. 76, 154–162 (2017).

    Article  Google Scholar 

  94. Virtanen, M. et al. Long working hours and alcohol use: systematic review and meta-analysis of published studies and unpublished individual participant data. BMJ 350, g7772 (2015).

    Article  Google Scholar 

  95. Magnusson-Hanson, L. et al. Work stress, anthropometry, lung function, blood pressure, and blood-based biomarkers: a cross-sectional study of 43,593 French men and women. Sci. Rep. 7, 9282 (2017).

    Article  Google Scholar 

  96. Fransson, E. I. et al. Job strain as a risk factor for leisure-time physical inactivity: an individual-participant meta-analysis of up to 170 000 men and women – The IPD-Work Consortium. Am. J. Epidemiol. 176, 1078–1089 (2012).

    Article  Google Scholar 

  97. van den Berk-Clark, C. et al. Association between posttraumatic stress disorder and lack of exercise, poor diet, obesity, and co-occuring smoking: a systematic review and meta-analysis. Health Psychol. 37, 407–416 (2018).

    Article  Google Scholar 

  98. Zhang, Y. et al. Sleep in posttraumatic stress disorder: a systematic review and meta-analysis of polysomnographic findings. Sleep. Med. Rev. 48, 101210 (2019).

    Article  Google Scholar 

  99. Kim, E. J. & Dimsdale, J. E. The effect of psychosocial stress on sleep: a review of polysomnographic evidence. Behav. Sleep. Med. 5, 256–278 (2007).

    Article  Google Scholar 

  100. Kalmbach, D. A., Anderson, J. R. & Drake, C. L. The impact of stress on sleep: pathogenic sleep reactivity as a vulnerability to insomnia and circadian disorders. J. Sleep. Res. 27, e12710 (2018).

    Article  Google Scholar 

  101. Geiker, N. R. W. et al. Does stress influence sleep patterns, food intake, weight gain, abdominal obesity and weight loss interventions and vice versa? Obes. Rev. 19, 81–97 (2018).

    Article  CAS  Google Scholar 

  102. Meier-Ewert, H. K. et al. Effect of sleep loss on C-reactive protein, an inflammatory marker of cardiovascular risk. J. Am. Coll. Cardiol. 43, 678–683 (2004).

    Article  CAS  Google Scholar 

  103. Kumari, M., Shipley, M., Stafford, M. & Kivimaki, M. Association of diurnal patterns in salivary cortisol with all-cause and cardiovascular mortality: findings from the Whitehall II study. J. Clin. Endocrinol. Metab. 96, 1478–1485 (2011).

    Article  CAS  Google Scholar 

  104. Hackett, R. A., Kivimaki, M., Kumari, M. & Steptoe, A. Diurnal cortisol patterns, future diabetes, and impaired glucose metabolism in the Whitehall II Cohort Study. J. Clin. Endocrinol. Metab. 101, 619–625 (2016).

    Article  CAS  Google Scholar 

  105. Briancon-Marjollet, A. et al. The impact of sleep disorders on glucose metabolism: endocrine and molecular mechanisms. Diabetol. Metab. Syndr. 7, 25 (2015).

    Article  Google Scholar 

  106. Iyegha, I. D., Chieh, A. Y., Bryant, B. M. & Li, L. Associations between poor sleep and glucose intolerance in prediabetes. Psychoneuroendocrinol 110, 104444 (2019).

    Article  CAS  Google Scholar 

  107. Iob, E., Baldwin, J. R., Plomin, R. & Steptoe, A. Adverse childhood experiences, daytime salivary cortisol, and depressive symptoms in early adulthood: a longitudinal genetically informed twin study. Transl. Psychiatry 11, 420 (2021).

    Article  Google Scholar 

  108. Lorant, V. et al. Socioeconomic inequalities in depression: a meta-analysis. Am. J. Epidemiol. 157, 98–112 (2003).

    Article  CAS  Google Scholar 

  109. Richardson, R., Westley, T., Gariepy, G., Austin, N. & Nandi, A. Neighborhood socioeconomic conditions and depression: a systematic review and meta-analysis. Soc. Psychiatry Psychiatr. Epidemiol. 50, 1641–1656 (2015).

    Article  Google Scholar 

  110. Madsen, I. E. H. et al. Job strain as a risk factor for clinical depression: systematic review and meta-analysis with additional individual participant data. Psychol. Med. 47, 1342–1356 (2017).

    Article  CAS  Google Scholar 

  111. Tsirlin, A. et al. Pheochromocytoma: a review. Maturitas 77, 229–238 (2014).

    Article  CAS  Google Scholar 

  112. Hashemian, F. et al. Anxiety, depression, and posttraumatic stress in Iranian survivors of chemical warfare. JAMA 296, 560–566 (2006).

    Article  CAS  Google Scholar 

  113. Kawachi, I., Aida, J., Hikichi, H. & Kondo, K. Disaster resilience in aging populations: lessons from the 2011 Great East Japan earthquake and tsunami. J. R. Soc. N. Z. 50, 263–278 (2020).

    Article  Google Scholar 

  114. Milaneschi, Y., Simmons, W. K., van Rossum, E. F. C. & Penninx, B. W. Depression and obesity: evidence of shared biological mechanisms. Mol. Psychiatry 24, 18–33 (2019).

    Article  CAS  Google Scholar 

  115. Ulrich-Lai, Y. M. & Ryan, K. K. Neuroendocrine circuits governing energy balance and stress regulation: functional overlap and therapeutic implications. Cell Metab. 19, 910–925 (2014).

    Article  CAS  Google Scholar 

  116. Momen, N. C. et al. Association between mental disorders and subsequent medical conditions. N. Engl. J. Med. 382, 1721–1731 (2020).

    Article  Google Scholar 

  117. Tabak, A. G., Akbaraly, T. N., Batty, G. D. & Kivimaki, M. Depression and type 2 diabetes: a causal association? Lancet Diabetes Endocrinol. 2, 236–245 (2014).

    Article  Google Scholar 

  118. Moulton, C. D., Pickup, J. C. & Ismail, K. The link between depression and diabetes: the search for shared mechanisms. Lancet Diabetes Endocrinol. 3, 461–471 (2015).

    Article  Google Scholar 

  119. Lindekilde, N. et al. Prevalence of type 2 diabetes in psychiatric disorders: an umbrella review with meta-analysis of 245 observational studies from 32 systematic reviews. Diabetol 65, 440–456 (2022).

    Article  Google Scholar 

  120. Soto-Angona, O. et al. Non-alcoholic fatty liver disease (NAFLD) as a neglected metabolic companion of psychiatric disorders: common pathways and future approaches. BMC Med. 18, 261 (2020).

    Article  Google Scholar 

  121. Warrier, V. et al. Gene–environment correlations and causal effects of childhood maltreatment on physical and mental health: a genetically informed approach. Lancet Psychiat 8, 373–386 (2021).

    Article  Google Scholar 

  122. Laitinen, T. T. et al. Childhood socioeconomic disadvantage and risk of fatty liver in adulthood: the Cardiovascular Risk in Young Finns Study. Hepatology 71, 67–75 (2019).

    Article  Google Scholar 

  123. Rahimi, L., Rajpal, A. & Ismail-Beigi, F. Glucocorticoid-induced fatty liver disease. Diabetes Metab. Syndr. Obes. 13, 1133–1145 (2020).

    Article  CAS  Google Scholar 

  124. Crowe, C. L. et al. Associations of loneliness and social isolation with health span and life span in the U.S. Health and Retirement Study. J. Gerontol. A Biol. Sci. Med. Sci. 76, 1997–2006 (2021).

    Article  Google Scholar 

  125. Hughes, K. et al. The effect of multiple adverse childhood experiences on health: a systematic review and meta-analysis. Lancet Public Health 2, e356–366 (2017). A systematic review and meta-analysis highlighting the pervasive and strong association between adverse childhood experiences and a wide range of diseases throughout the life course with emphasis on the importance of addressing the various stressors that can occur in children’s lives.

    Article  Google Scholar 

  126. Kivimaki, M. et al. Association between socioeconomic status and the development of mental and physical health conditions in adulthood: a multi-cohort study. Lancet Public Health 5, e140–e149 (2020). This outcome-wide study links socioeconomic adversity to increased risks of mental and behavioural disorders as well as a life-long cascade of diseases of the pancreas, liver, kidney, and vascular and respiratory systems and dementia.

    Article  Google Scholar 

  127. Heikkila, K. et al. Job strain and COPD exacerbations: an individual-participant meta-analysis. Eur. Resp. J. 44, 247–251 (2014).

    Article  Google Scholar 

  128. Heikkila, K. et al. Job strain and the risk of severe asthma exacerbations: a meta-analysis of individual-participant data from 100 000 European men and women. Allergy 69, 775–783 (2014).

    Article  CAS  Google Scholar 

  129. Heikkila, K. et al. Work stress and risk of cancer: meta-analysis of 5700 incident cancer events in 116,000 European men and women. BMJ 346, f165 (2013).

    Article  Google Scholar 

  130. Nyberg, S. T. et al. Job strain as a risk factor for type 2 diabetes: a pooled analysis of 124 808 men and women. Diabetes Care 37, 2268–2275 (2014). In this individual participant meta-analysis of 124,808 adults without diabetes mellitus from 13 European cohort studies, job strain was associated with a 1.15-fold increased risk of incident T2DM, with no evidence of differences in the association by sex.

    Article  Google Scholar 

  131. Fransson, E. I. et al. Job strain and the risk of stroke: an individual-participant data meta-analysis. Stroke 46, 557–559 (2015).

    Article  Google Scholar 

  132. Kivimaki, M. et al. Job strain as a risk factor for coronary heart disease: a collaborative meta-analysis of individual participant data. Lancet 380, 1491–1497 (2012).

    Article  Google Scholar 

  133. Ervasti, J. et al. Long working hours and risk of 50 health conditions and mortality outcomes: a multicohort study in four European countries. Lancet Reg. Health Eur. 11, 100212 (2021).

    Article  Google Scholar 

  134. Virtanen, M. et al. Long working hours and change in body weight: analysis of individual-participant data from 19 cohort studies. Int. J. Obes. 44, 1368–1375 (2020).

    Article  Google Scholar 

  135. Liu, D. et al. A practical guide to the monitoring and management of the complications of systemic corticosteroid therapy. Allergy Asthma Clin. Immun. 9, 30 (2013).

    Article  Google Scholar 

  136. Daley-Yates, P. T. Inhaled corticosteroids: potency, dose equivalence and therapeutic index. Br. J. Clin. Pharmacol. 80, 372–380 (2015).

    Article  CAS  Google Scholar 

  137. Sharma, S. T., Nieman, L. K. & Feelders, R. A. Comorbidities in Cushing’s disease. Pituitary 18, 188–194 (2015).

    Article  CAS  Google Scholar 

  138. Dekkers, O. M. et al. Multisystem morbidity and mortality in Cushing’s syndrome: a cohort study. J. Clin. Endocrinol. Metab. 98, 2277–2284 (2013).

    Article  CAS  Google Scholar 

  139. Pigeyre, M. et al. How obesity relates to socio-economic status: identification of eating behavior mediators. Int. J. Obes. 40, 1794–1801 (2016).

    Article  CAS  Google Scholar 

  140. Agardh, E. E. et al. Burden of type 2 diabetes attributed to lower educational levels in Sweden. Popul. Health Metr. 9, 60 (2011).

    Article  Google Scholar 

  141. Vancampfort, D. et al. Type 2 diabetes among people with posttraumatic stress disorder: systematic review and meta-analysis. Psychosom. Med. 78, 465–473 (2016).

    Article  Google Scholar 

  142. Xu, T. et al. Onset of workplace bullying and risk of weight gain: a multicohort longitudinal study. Obesity 28, 2216–2223 (2020).

    Article  Google Scholar 

  143. Xu, T. et al. Workplace bullying and violence as risk factors for type 2 diabetes: a multicohort study and meta-analysis. Diabetologia 61, 75–83 (2018).

    Article  CAS  Google Scholar 

  144. Ul-Haq, Z., Mackay, D. F., Fenwick, E. & Pell, J. P. Meta-analysis of the association between body mass index and health-related quality of life among adults, assessed by the SF-36. Obesity 21, E322–E327 (2013).

    Article  Google Scholar 

  145. Mommersteeg, P. M., Herr, R., Zijlstra, W. P., Schneider, S. & Pouwer, F. Higher levels of psychological distress are associated with a higher risk of incident diabetes during 18 year follow-up: results from the British Household Panel Survey. BMC Public Health 12, 1109 (2012).

    Article  Google Scholar 

  146. Russ, T. C. et al. Association between psychological distress and liver disease mortality: a meta-analysis of individual study participants. Gastroenterol 148, 958–966 (2015).

    Article  Google Scholar 

  147. Pena-Gralle, A. P. B. et al. Job strain and effort–reward imbalance as risk factors for type 2 diabetes mellitus: a systematic review and meta-analysis of prospective studies. Scand. J. Work. Environ. Health 48, 5–20 (2022).

    Article  CAS  Google Scholar 

  148. Li, D. & Zou, Y. Causal effects of life course adiposity on chronic kidney disease: a Mendelian randomization study. Ann. Palliat. Med. 10, 10861–10869 (2021).

    Article  Google Scholar 

  149. Cuevas, A. G. et al. Stressful life events and obesity in the United States: the role of nativity and length of residence. Am. J. Health Promot. 36, 190–193 (2022).

    Article  Google Scholar 

  150. Wang, M. et al. Associations between stressful life events and diabetes: findings from the China Kadoorie Biobank study of 500,000 adults. J. Diabetes Investig. 10, 1215–1222 (2019).

    Article  CAS  Google Scholar 

  151. Nordentoft, M. et al. Effort–reward imbalance at work and weight changes in a nationwide cohort of workers in Denmark. Am. J. Ind. Med. 63, 634–643 (2020).

    Article  Google Scholar 

  152. Kouvonen, A., Kivimäki, M., Cox, S. J., Cox, T. & Vahtera, J. Relationship between work stress and body mass index among 45,810 female and male employees. Psychosom. Med. 67, 577–583 (2005).

    Article  Google Scholar 

  153. Abdullah, A., Peeters, A., de Courten, M. & Stoelwinder, J. The magnitude of association between overweight and obesity and the risk of diabetes: a meta-analysis of prospective cohort studies. Diabetes Res. Clin. Pract. 89, 309–319 (2010).

    Article  Google Scholar 

  154. Aune, D., Norat, T., Leitzmann, M., Tonstad, S. & Vatten, L. J. Physical activity and the risk of type 2 diabetes: a systematic review and dose-response meta-analysis. Eur. J. Epidemiol. 30, 529–542 (2015).

    Article  Google Scholar 

  155. Zhao, J. et al. Triglyceride is an independent predictor of type 2 diabetes among middle-aged and older adults: a prospective study with 8-year follow-ups in two cohorts. J. Transl. Med. 17, 403 (2019).

    Article  CAS  Google Scholar 

  156. Khera, R. et al. Cost-related medication nonadherence in adults with atherosclerotic cardiovascular disease in the United States, 2013 to 2017. Circulation 140, 2067–2075 (2019).

    Article  Google Scholar 

  157. Steptoe, A. et al. Disruption of multisystem responses to stress in type 2 diabetes: investigating the dynamics of allostatic load. Proc. Natl. Acad. Sci. U. S. A. 111, 15693–15698 (2014).

    Article  CAS  Google Scholar 

  158. Kivimaki, M. et al. Work stress and risk of death in men and women with and without cardiometabolic disease: a multicohort study. Lancet Diabetes Endocrinol. 6, 705–713 (2018).

    Article  Google Scholar 

  159. Huang, W. et al. Psychological distress and all-cause, cardiovascular disease, cancer mortality among adults with and without diabetes. Clin. Epidemiol. 13, 555–565 (2021).

    Article  Google Scholar 

  160. Dalsgaard, E. M. et al. Psychological distress, cardiovascular complications and mortality among people with screen-detected type 2 diabetes: follow-up of the ADDITION-Denmark trial. Diabetologia 57, 710–717 (2014).

    Article  CAS  Google Scholar 

  161. Livingston, G. et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet 396, 413–446 (2020).

    Article  Google Scholar 

  162. Fratiglioni, L., Marseglia, A. & Dekhtyar, S. Ageing without dementia: can stimulating psychosocial and lifestyle experiences make a difference? Lancet Neurol. 19, 533–543 (2020).

    Article  Google Scholar 

  163. Tung, J., Archie, E. A., Altmann, J. & Alberts, S. C. Cumulative early life adversity predicts longevity in wild baboons. Nat. Commun. 7, 11181 (2016).

    Article  CAS  Google Scholar 

  164. Bellis, M. A. et al. Measuring mortality and the burden of adult disease associated with adverse childhood experiences in England: a national survey. J. Public Health 37, 445–454 (2015).

    Article  CAS  Google Scholar 

  165. Stringhini, S. et al. Socioeconomic status and the 25×25 risk factors as determinants of premature mortality: a multicohort study and meta-analysis of 1.7 million men and women. Lancet 389, 1229–1237 (2017).

    Article  Google Scholar 

  166. Prior, A. et al. Bereavement, multimorbidity and mortality: a population-based study using bereavement as an indicator of mental stress. Psychol. Med. 48, 1437–1443 (2018).

    Article  CAS  Google Scholar 

  167. Rutters, F. et al. The association between psychosocial stress and mortality is mediated by lifestyle and chronic diseases: the Hoorn Study. Soc. Sci. Med. 118, 166–172 (2014).

    Article  Google Scholar 

  168. Falvey, J. R., Hajduk, A. M., Keys, C. R. & Chaudhry, S. I. Association of financial strain with mortality among older US adults recovering from an acute myocardial infarction. JAMA Intern. Med. 182, 445–448 (2022).

    Article  Google Scholar 

  169. Prior, A. et al. The association between perceived stress and mortality among people with multimorbidity: a prospective population-based cohort study. Am. J. Epidemiol. 184, 199–210 (2016).

    Article  Google Scholar 

  170. Batty, G. D., Hamer, M. & Gale, C. R. Life-course psychological distress and total mortality by middle age: the 1970 Birth Cohort Study. Epidemiology 32, 740–743 (2021).

    Article  Google Scholar 

  171. Emerging Risk Factors Collaboration Association of cardiometabolic multimorbidity with mortality. JAMA 314, 52–60 (2015).

    Article  Google Scholar 

  172. Singh-Manoux, A. et al. Clinical, socioeconomic, and behavioural factors at age 50 years and risk of cardiometabolic multimorbidity and mortality: a cohort study. PLoS Med. 15, e1002571 (2018). This cohort study with a 24-year follow-up examined transitions between health states and found that clinical risk factors (hypertension, obesity, high cholesterol and family history of diabetes mellitus or cardiovascular disease) are important predictors of first cardiometabolic disease, but socioeconomic disadvantage and unhealthy behaviours determine progression to multimorbidity.

    Article  Google Scholar 

  173. Brunner, E. J. et al. Midlife contributors to socioeconomic differences in frailty during later life: a prospective cohort study. Lancet Public Health 3, e313–e322 (2018).

    Article  Google Scholar 

  174. Courtin, E., Kim, S., Song, S., Yu, W. & Muennig, P. Can social policies improve health? A systematic review and meta-analysis of 38 randomized trials. Milbank Q. 98, 297–371 (2020).

    Article  Google Scholar 

  175. Ludwig, J. et al. Neighborhoods, obesity, and diabetes – a randomized social experiment. N. Engl. J. Med. 365, 1509–1519 (2011). This real-life social experiment showed that moving from a socioeconomically disadvantaged neighbourhood to one with less socioeconomic disadvantage is associated with modest but potentially important reductions in the prevalence of severe obesity and T2DM.

    Article  CAS  Google Scholar 

  176. Kivimaki, M. et al. Modifications to residential neighbourhood characteristics and risk of 79 common health conditions: a prospective cohort study. Lancet Public Health 6, e396–e407 (2021).

    Article  Google Scholar 

  177. White, J. S. et al. Long-term effects of neighbourhood deprivation on diabetes risk: quasi-experimental evidence from a refugee dispersal policy in Sweden. Lancet Diabetes Endocrinol. 4, 517–524 (2016).

    Article  Google Scholar 

  178. Chew, B. H., Vos, R. C., Metzendorf, M. I., Scholten, R. J. & Rutten, G. E. Psychological interventions for diabetes-related distress in adults with type 2 diabetes mellitus. Cochrane Database Syst. Rev. 9, CD011469 (2017).

    Google Scholar 

  179. Winkley, K. et al. Psychological interventions to improve glycemic control in adults with type 2 diabetes: a systematic review and meta-analysis. BMJ Open. Diabetes Res. Care 8, 001150 (2020).

    Article  Google Scholar 

  180. Crabb, D. W., Im, G. Y., Szabo, G., Mellinger, J. L. & Lucey, M. R. Diagnosis and treatment of alcohol-associated liver diseases: 2019 practice guidance from the American Association for the Study of Liver Diseases. Hepatology 71, 306–333 (2020).

    Article  Google Scholar 

  181. International Diabetes Federation. Global Guideline for Type 2 Diabetes. International Diabetes Federation https://www.idf.org/our-activities/advocacy-awareness/resources-and-tools/79:global-guideline-for-type-2-diabetes.html (2012).

  182. International Diabetes Federation. Recommendations For Managing Type 2 Diabetes In Primary Care. International Diabetes Federation www.idf.org/managing-type2-diabetes (2017).

  183. American Diabetes Association. 3. Prevention or delay of type 2 diabetes: Standards of Medical Care in Diabetes-2021. Diabetes Care 44, S34–S39 (2021).

    Article  Google Scholar 

  184. Chatterjee, S., Khunti, K. & Davies, M. J. Type 2 diabetes. Lancet 389, 2239–2251 (2017).

    Article  CAS  Google Scholar 

  185. Young, C., Majolo, B., Heistermann, M., Schulke, O. & Ostner, J. Responses to social and environmental stress are attenuated by strong male bonds in wild macaques. Proc. Natl. Acad. Sci. U. S. A. 111, 18195–18200 (2014).

    Article  CAS  Google Scholar 

  186. Fraser, O. N., Stahl, D. & Aureli, F. Stress reduction through consolation in chimpanzees. Proc. Natl. Acad. Sci. U. S. A. 105, 8557–8562 (2008).

    Article  CAS  Google Scholar 

  187. Ruis, M. A. et al. Housing familiar male wildtype rats together reduces the long-term adverse behavioural and physiological effects of social defeat. Psychoneuroendocrinology 24, 285–300 (1999).

    Article  CAS  Google Scholar 

  188. Carrillo-Alvarez, E., Kawachi, I. & Riera-Romani, J. Neighbourhood social capital and obesity: a systematic review of the literature. Obes. Rev. 20, 119–141 (2019).

    Article  CAS  Google Scholar 

  189. Perez, E. et al. Neighbourhood community life and health: a systematic review of reviews. Health Place 61, 102238 (2020).

    Article  Google Scholar 

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Acknowledgements

M.K. was supported by the UK Medical Research Council (S011676), Wellcome Trust, UK (221854/Z/20/Z), National Institute on Aging (NIH), US (R01AG056477), and the Academy of Finland (350426). A.B. was supported by NIH/NIDDK (DK117504, DK118150, DK102496), NIH/NHLBI (HL151740), NIH/NIA (AG043972) and MN Partnership for Biotechnology and Molecular Genomic #18.4. I.K. was supported by National Institute on Aging (R01 AG042463).

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Glossary

Allostatic states

An allostatic state is a state in which there is a chronic deviation of regulatory systems away from their normal state of operation.

Burnout

A syndrome resulting from excessive or prolonged stress and characterized by feelings of energy depletion or exhaustion, increased mental distancing, or feelings of negativism or cynicism related to one’s job and reduced professional efficacy.

Ultradian

A rhythm with a period of recurrence shorter than 24 h.

Polysomnography

A test protocol monitoring multiple physiological changes that occur during sleep (such as brain waves, eye and leg movement, heart rate and breathing) to study sleep and diagnose sleep disorders.

Stroop colour–word interference task

A neuropsychological test to assess the ability to inhibit cognitive inference (a mismatch between the name of a colour and the colour it is printed on) used in the laboratory to induce stress in a study participant.

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Kivimäki, M., Bartolomucci, A. & Kawachi, I. The multiple roles of life stress in metabolic disorders. Nat Rev Endocrinol 19, 10–27 (2023). https://doi.org/10.1038/s41574-022-00746-8

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