Skip to main content

Thank you for visiting nature.com. 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.

  • Review Article
  • Published:

Social determinants of health in multiple sclerosis

Abstract

Social determinants of health are the conditions in which people are born, grow, live, work and age. These circumstances are the non-medical factors that influence health outcomes. Evidence indicates that health behaviours, comorbidities and disease-modifying therapies all contribute to multiple sclerosis (MS) outcomes; however, our knowledge of the effects of social determinants — that is, the ‘risks of risks’ — on health has not yet changed our approach to MS. Assessing and addressing social determinants of health could fundamentally improve health and health care in MS; this approach has already been successful in improving outcomes in other chronic diseases. In this narrative Review, we identify and discuss the body of evidence supporting an effect of many social determinants of health, including racial background, employment and social support, on MS outcomes. It must be noted that many of the published studies were subject to bias, and screening tools and/or practical interventions that address these social determinants are, for the most part, lacking. The existing work does not fully explore the potential bidirectional and complex relationships between social determinants of health and MS, and the interpretation of findings is complicated by the interactions and intersections among many of the identified determinants. On the basis of the reviewed literature, we consider that, if effective interventions targeting social determinants of health were available, they could have substantial effects on MS outcomes. Therefore, funding for and focused design of studies to evaluate and address social determinants of health are urgently needed.

Key points

  • Addressing an individual’s social determinants of health — that is, the conditions under which they are born, grow, live, work and age — could provide opportunities to reduce the burden of living with multiple sclerosis (MS).

  • Individual factors that may influence MS-related outcomes include sex, gender and sexuality, race and ethnicity, education and employment, socioeconomic status, and domestic abuse.

  • Societal infrastructures, including access to food, health care and social support, can also affect MS-related outcomes.

  • Awareness of the specific circumstances of a patient with MS might help neurologists deliver better care.

  • Social determinants of health are not static and can change according to wider sociopolitical contexts, as highlighted by the COVID-19 pandemic.

  • Rigorous studies of interventions to ameliorate the effects of poor social determinants on people with MS are urgently needed.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: WHO social determinants of health.
Fig. 2: Potential interactions between selected social determinants of health and multiple sclerosis outcomes.

Similar content being viewed by others

References

  1. Multiple Sclerosis International Federation. Atlas of MS, 3rd edn. MS International Federation https://www.msif.org/wp-content/uploads/2020/12/Atlas-3rd-Edition-Epidemiology-report-EN-updated-30-9-20.pdf (2020).

  2. Dobson, R. & Giovannoni, G. Multiple sclerosis–a review. Eur. J. Neurol. 26, 27–40 (2019).

    CAS  PubMed  Google Scholar 

  3. Beiki, O., Frumento, P., Bottai, M., Manouchehrinia, A. & Hillert, J. Changes in the risk of reaching multiple sclerosis disability milestones in recent decades: A nationwide population-based cohort study in Sweden. JAMA Neurol. 76, 665–671 (2019).

    PubMed  PubMed Central  Google Scholar 

  4. Marshall, C. R., Noyce, A. J., Neligan, A. & Dobson, R. Brain health: the hidden casualty of a humanitarian crisis. Lancet Reg. Health Eur. 15, 100374 (2022).

    PubMed  PubMed Central  Google Scholar 

  5. Krysko, K. M. et al. Sex effects across the lifespan in women with multiple sclerosis. Ther. Adv. Neurol. Disord. 13, 1756286420936166 (2020).

    PubMed  PubMed Central  Google Scholar 

  6. Simmons, S. B., Schippling, S., Giovannoni, G. & Ontaneda, D. Predicting disability worsening in relapsing and progressive multiple sclerosis. Curr. Opin. Neurol. 34, 312–321 (2021).

    PubMed  Google Scholar 

  7. Kister, I., Bacon, T. & Cutter, G. R. How multiple sclerosis symptoms vary by age, sex, and race/ethnicity. Neurol. Clin. Pract. 11, 335–341 (2021).

    PubMed  PubMed Central  Google Scholar 

  8. Miller, A. & Dishon, S. Health-related quality of life in multiple sclerosis: the impact of disability, gender and employment status. Qual. Life Res. 15, 259–271 (2006).

    PubMed  Google Scholar 

  9. Anderson, A. et al. Experiences of sexual and gender minority people living with multiple sclerosis in Northern California: an exploratory study. Mult. Scler. Relat. Disord. 55, 103214 (2021).

    PubMed  Google Scholar 

  10. Khayambashi, S. et al. Gender identity and sexual orientation affect health care satisfaction, but not utilization, in persons with multiple sclerosis. Mult. Scler. Relat. Disord. 37, 101440 (2020).

    PubMed  Google Scholar 

  11. Jacobs, B. M. et al. Towards a global view of multiple sclerosis genetics. Nat. Rev. Neurol. https://doi.org/10.1038/s41582-022-00704-y (2022).

    Article  PubMed  Google Scholar 

  12. Lebrun, L. A. & LaVeist, T. A. Black/white racial disparities in health: a cross-country comparison of Canada and the United States. Arch. Intern. Med. 171, 1591–1593 (2011).

    PubMed  Google Scholar 

  13. Langer-Gould, A. M., Gonzales, E. G., Smith, J. B., Li, B. H. & Nelson, L. M. Racial and ethnic disparities in multiple sclerosis prevalence. Neurology https://doi.org/10.1212/WNL.0000000000200151 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Amezcua, L., Rivera, V. M., Vazquez, T. C., Baezconde-Garbanati, L. & Langer-Gould, A. Health disparities, inequities, and social determinants of health in multiple sclerosis and related disorders in the US: a review. JAMA Neurol. 78, 1515–1524 (2021).

    PubMed  Google Scholar 

  15. Cree, B. A. C. et al. Clinical characteristics of African Americans vs Caucasian Americans with multiple sclerosis. Neurology 63, 2039–2045 (2004).

    CAS  PubMed  Google Scholar 

  16. Caldito, N. G. et al. Brain and retinal atrophy in African-Americans versus Caucasian-Americans with multiple sclerosis: a longitudinal study. Brain 141, 3115–3129 (2018).

    PubMed  PubMed Central  Google Scholar 

  17. Amezcua, L., Rivas, E., Joseph, S., Zhang, J. & Liu, L. Multiple sclerosis mortality by race/ethnicity, age, sex, and time period in the United States, 1999-2015. Neuroepidemiology 50, 35–40 (2018).

    PubMed  Google Scholar 

  18. Bross, M. et al. Cortical surface thickness, subcortical volumes and disability between races in relapsing-remitting multiple sclerosis. Mult. Scler. Relat. Disord. 53, 103025 (2021).

    PubMed  Google Scholar 

  19. Amezcua, L. & McCauley, J. L. Race and ethnicity on MS presentation and disease course. Mult. Scler. 26, 561–567 (2020).

    PubMed  PubMed Central  Google Scholar 

  20. Amezcua, L., Smith, J. B., Gonzales, E. G., Haraszti, S. & Langer-Gould, A. Race, ethnicity, and cognition in persons newly diagnosed with multiple sclerosis. Neurology 94, e1548–e1556 (2020).

    PubMed  PubMed Central  Google Scholar 

  21. US Department of Veterans Affairs. Multiple sclerosis centers of excellence. VA https://www.va.gov/MS/veterans/benefits/index.asp (2022).

  22. Wallin, M. T. et al. The Gulf War era multiple sclerosis cohort: age and incidence rates by race, sex and service. Brain 135, 1778–1785 (2012).

    PubMed  Google Scholar 

  23. Fernandez Turienzo, C. et al. Addressing inequities in maternal health among women living in communities of social disadvantage and ethnic diversity. BMC Public Health 21, 176 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. D’hooghe, M. B., Haentjens, P., Van Remoortel, A., De Keyser, J. & Nagels, G. Self-reported levels of education and disability progression in multiple sclerosis. Acta Neurol. Scand. 134, 414–419 (2016).

    PubMed  Google Scholar 

  25. Rimkus, C. et al. The protective effects of high-education levels on cognition in different stages of multiple sclerosis. Mult. Scler. Relat. Disord. 22, 41–48 (2018).

    PubMed  Google Scholar 

  26. Marrie, R. A. et al. From the prodromal stage of multiple sclerosis to disease prevention. Nat. Rev. Neurol. https://doi.org/10.1038/s41582-022-00686-x (2022).

    Article  PubMed  Google Scholar 

  27. Bacci, S., Pigini, C., Seracini, M. & Minelli, L. Employment condition, economic deprivation and self-evaluated health in Europe: evidence from EU-SILC 2009–2012. Int. J. Environ. Res. Public Health 14, 143 (2017).

    PubMed  PubMed Central  Google Scholar 

  28. Moore, P. et al. Demographic and clinical factors associated with changes in employment in multiple sclerosis. Mult. Scler. 19, 1647–1654 (2013).

    PubMed  Google Scholar 

  29. Pearson, J. F. et al. Multiple sclerosis impact on employment and income in New Zealand. Acta Neurol. Scand. 136, 223–232 (2017).

    CAS  PubMed  Google Scholar 

  30. Van Dijk, P. A., Kirk-Brown, A. K., Taylor, B. & van der Mei, I. Closing the gap: longitudinal changes in employment for Australians with multiple sclerosis. Mult. Scler. 23, 1415–1423 (2017).

    PubMed  Google Scholar 

  31. Forslin, M., Fink, K., Hammar, U., von Koch, L. & Johansson, S. Predictors for employment status in people with multiple sclerosis: a 10-year longitudinal observational study. Arch. Phys. Med. Rehabil. 99, 1483–1490 (2018).

    PubMed  Google Scholar 

  32. D’hooghe, M. B. et al. Perceived neuropsychological impairment inversely related to self-reported health and employment in multiple sclerosis. Eur. J. Neurol. 26, 1447–1454 (2019).

    PubMed  Google Scholar 

  33. van Gorp, D. A. M. et al. Cognitive functioning as a predictor of employment status in relapsing-remitting multiple sclerosis: a 2-year longitudinal study. Neurol. Sci. 40, 2555–2564 (2019).

    PubMed  PubMed Central  Google Scholar 

  34. Chen, J. et al. Risk factors for leaving employment due to multiple sclerosis and changes in risk over the past decades: using competing risk survival analysis. Mult. Scler. 27, 1250–1261 (2021).

    PubMed  Google Scholar 

  35. Chalmer, T. A. et al. Clinically stable disease is associated with a lower risk of both income loss and disability pension for patients with multiple sclerosis. J. Neurol. Neurosurg. Psychiatry 91, 67–74 (2020).

    PubMed  Google Scholar 

  36. Marck, C. H. et al. Predictors of change in employment status and associations with quality of life: a prospective international study of people with multiple sclerosis. J. Occup. Rehabil. 30, 105–114 (2020).

    PubMed  Google Scholar 

  37. Chen, J. et al. Comorbidities are prevalent and detrimental for employment outcomes in people of working age with multiple sclerosis. Mult. Scler. 26, 1550–1559 (2020).

    PubMed  Google Scholar 

  38. Renner, A., Baetge, S. J., Filser, M. & Penner, I.-K. Working ability in individuals with different disease courses of multiple sclerosis: factors beyond physical impairment. Mult. Scler. Relat. Disord. 46, 102559 (2020).

    PubMed  Google Scholar 

  39. Conradsson, D. M. et al. Employment status of people with multiple sclerosis in relation to 10-year changes in functioning and perceived impact of the disease. Mult. Scler. Relat. Disord. 46, 102519 (2020).

    PubMed  Google Scholar 

  40. Beier, M. et al. Relationship of perceived stress and employment status in individuals with multiple sclerosis. Work 62, 243–249 (2019).

    PubMed  Google Scholar 

  41. Krokavcova, M. et al. Employment status and perceived health status in younger and older people with multiple sclerosis. Int. J. Rehabil. Res. 35, 40–47 (2012).

    PubMed  Google Scholar 

  42. Lehmann, A. I. et al. Factors associated with employment and expected work retention among persons with multiple sclerosis: findings of a cross-sectional citizen science study. J. Neurol. 267, 3069–3082 (2020).

    PubMed  PubMed Central  Google Scholar 

  43. Krause, J. S., Rumrill, P., Dismuke-Greer, C. E. & Jarnecke, M. Quality employment outcomes after multiple sclerosis: a comparison of participants from a specialty hospital and the National MS Society. J. Vocat. Rehabil. 48, 177–186 (2018).

    Google Scholar 

  44. Frieden, T. R. The future of public health. N. Engl. J. Med. 373, 1748–1754 (2015).

    CAS  PubMed  Google Scholar 

  45. Cookson, R. et al. Health equity indicators for the English NHS: a longitudinal whole-population study at the small-area level. Health Serv. Deliv. Res. 4, 1–224 (2016).

    Google Scholar 

  46. Harding, K. E. et al. Socioeconomic status and disability progression in multiple sclerosis: a multinational study. Neurology 92, e1497–e1506 (2019).

    PubMed  Google Scholar 

  47. Goulden, R., Ibrahim, T. & Wolfson, C. Is high socioeconomic status a risk factor for multiple sclerosis? A systematic review. Eur. J. Neurol. 22, 899–911 (2015).

    CAS  PubMed  Google Scholar 

  48. Calocer, F. et al. Socioeconomic deprivation increases the risk of disability in multiple sclerosis patients. Mult. Scler. Relat. Disord. 40, 101930 (2020).

    PubMed  Google Scholar 

  49. Vasileiou, E. S. et al. Socioeconomic disparity is associated with faster retinal neurodegeneration in multiple sclerosis. Brain 144, 3664–3673 (2021).

    PubMed  PubMed Central  Google Scholar 

  50. Maldonado, D. A. P. et al. The impact of socioeconomic status on mental health and health-seeking behavior across race and ethnicity in a large multiple sclerosis cohort. Mult. Scler. Relat. Disord. 58, 103451 (2022).

    Google Scholar 

  51. Wang, Y. et al. Socioeconomic status and race are correlated with affective symptoms in multiple sclerosis. Mult. Scler. Relat. Disord. 41, 102010 (2020).

    PubMed  PubMed Central  Google Scholar 

  52. National Multiple Sclerosis Society. Access to high quality MS healthcare principles. National Multiple Sclerosis Society https://www.nationalmssociety.org/Get-Involved/Advocate-for-Change/Take-Action/Access-to-High-Quality-Healthcare/Access-to-High-Quality-MS-Healthcare-Principles (2022).

  53. Leech, M. M., Weiss, J. E., Markey, C. & Loehrer, A. P. Influence of race, insurance, rurality, and socioeconomic status on equity of lung and colorectal cancer care. Ann. Surg. Oncol. 29, 3630–3639 (2022).

    PubMed  Google Scholar 

  54. Calocer, F., Dejardin, O., Droulon, K., Launoy, G. & Defer, G. Socio-economic status influences access to second-line disease modifying treatment in relapsing remitting multiple sclerosis patients. PLoS ONE 13, e0191646 (2018).

    PubMed  PubMed Central  Google Scholar 

  55. Das, J. et al. The association between deprivation and the access to disease modifying therapies for multiple sclerosis: an England wide community-based study in the UK MS Register. Mult. Scler. Relat. Disord. 57, 103474 (2022).

    PubMed  Google Scholar 

  56. Gómez-Figueroa, E. et al. Socioeconomic status and access to multiple sclerosis treatment in Mexico. Mult. Scler. Relat. Disord. 52, 102967 (2021).

    PubMed  Google Scholar 

  57. Reyes, S. et al. Socioeconomic status and disease-modifying therapy prescribing patterns in people with multiple sclerosis. Mult. Scler. Relat. Disord. 41, 102024 (2020).

    PubMed  Google Scholar 

  58. Flemmen, H. Ø. et al. The influence of socioeconomic factors on access to disease modifying treatment in a Norwegian multiple sclerosis cohort. Mult. Scler. Relat. Disord. 61, 103759 (2022).

    PubMed  Google Scholar 

  59. Kivimäki, 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).

    PubMed  Google Scholar 

  60. Salter, A., Kowalec, K., Fitzgerald, K. C., Cutter, G. & Marrie, R. A. Comorbidity is associated with disease activity in MS: findings from the CombiRx trial. Neurology 95, e446–e456 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. Jennum, P., Wanscher, B., Frederiksen, J. & Kjellberg, J. The socioeconomic consequences of multiple sclerosis: a controlled national study. Eur. Neuropsychopharmacol. 22, 36–43 (2012).

    CAS  PubMed  Google Scholar 

  62. United Nations. What is domestic abuse? United Nations https://www.un.org/en/coronavirus/what-is-domestic-abuse (2022).

  63. Public Health England. Disability and domestic abuse: risk, impacts and response. Public Health England https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/480942/Disability_and_domestic_abuse_topic_overview_FINAL.pdf (2015).

  64. Cohen, M., Forte, T., Dumont, J., Hyman, I. & Romans, S. Adding insult to injury: intimate partner violence among women and men reporting activity limitations. Ann. Epidemiol. 16, 644–651 (2006).

    PubMed  Google Scholar 

  65. Morrison, E. H., Sorkin, D., Mosqueda, L. & Ayutyanont, N. Abuse and neglect of people with multiple sclerosis: a survey with the North American Research Committee on Multiple Sclerosis (NARCOMS). Mult. Scler. Relat. Disord. 46, 102530 (2020).

    PubMed  Google Scholar 

  66. World Health Organization. World report on disability. WHO https://www.who.int/teams/noncommunicable-diseases/sensory-functions-disability-and-rehabilitation/world-report-on-disability (2011).

  67. Minden, S. L. et al. Access to and utilization of neurologists by people with multiple sclerosis. Neurology 70, 1141–1149 (2008).

    CAS  PubMed  Google Scholar 

  68. Marrie, R. A., Cutter, G., Tyry, T., Vollmer, T. & Campagnolo, D. Disparities in the management of multiple sclerosis-related bladder symptoms. Neurology 68, 1971–1978 (2007).

    CAS  PubMed  Google Scholar 

  69. Li, P. et al. Disease-modifying therapy adherence and associated factors in a national sample of Medicare patients with multiple sclerosis. Value Health 23, 328–334 (2020).

    PubMed  Google Scholar 

  70. Dobos, K., Healy, B. & Houtchens, M. Access to preventive health care in severely disabled women with multiple sclerosis. Int. J. MS Care 17, 200–205 (2015).

    PubMed  PubMed Central  Google Scholar 

  71. Lonergan, R. et al. Unmet needs of multiple sclerosis patients in the community. Mult. Scler. Relat. Disord. 4, 144–150 (2015).

    PubMed  Google Scholar 

  72. Bo, M. et al. Access to social security benefits among multiple sclerosis patients in Italy: a cross-sectional study. Mult. Scler. Relat. Disord. 24, 107–112 (2018).

    PubMed  Google Scholar 

  73. Department for Environment Food & Rural Affairs. United Kingdom Food Security Report 2021: Theme 4: Food security at household level. GOV.UK https://www.gov.uk/government/statistics/united-kingdom-food-security-report-2021/united-kingdom-food-security-report-2021-theme-4-food-security-at-household-level (2021).

  74. Simpson-Yap, S., Nag, N., Probst, Y., Jelinek, G. & Neate, S. Higher-quality diet and non-consumption of meat are associated with less self-determined disability progression in people with multiple sclerosis: a longitudinal cohort study. Eur. J. Neurol. 29, 225–236 (2022).

    PubMed  Google Scholar 

  75. Marck, C. H., Probst, Y., Chen, J., Taylor, B. & van der Mei, I. Dietary patterns and associations with health outcomes in Australian people with multiple sclerosis. Eur. J. Clin. Nutr. 75, 1506–1514 (2021).

    PubMed  Google Scholar 

  76. Parks, N. E., Jackson-Tarlton, C. S., Vacchi, L., Merdad, R. & Johnston, B. C. Dietary interventions for multiple sclerosis-related outcomes. Cochrane Database Syst. Rev. 5, CD004192 (2020).

    PubMed  Google Scholar 

  77. Erickson, L. D., Gale, S. D., Anderson, J. E., Brown, B. L. & Hedges, D. W. Association between exposure to air pollution and total gray matter and total white matter volumes in adults: a cross-sectional study. Brain Sci. 10, 164 (2020).

    PubMed  PubMed Central  Google Scholar 

  78. Ziaei, A. et al. Gene-environment interactions increase the risk of pediatric-onset multiple sclerosis associated with ozone pollution. Mult. Scler. 28, 1330–1339 (2022).

    CAS  PubMed  PubMed Central  Google Scholar 

  79. Jeanjean, M. et al. Ozone, NO and PM are associated with the occurrence of multiple sclerosis relapses. Evidence from seasonal multi-pollutant analyses. Environ. Res. 163, 43–52 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  80. Roux, J. et al. Air pollution by particulate matter PM10 may trigger multiple sclerosis relapses. Environ. Res. 156, 404–410 (2017).

    CAS  PubMed  Google Scholar 

  81. Ashtari, F. et al. An 8-year study of people with multiple sclerosis in Isfahan, Iran: association between environmental air pollutants and severity of disease. J. Neuroimmunol. 319, 106–111 (2018).

    CAS  PubMed  Google Scholar 

  82. Elgabsi, M. et al. An impact of air pollution on moderate to severe relapses among multiple sclerosis patients. Mult. Scler. Relat. Disord. 53, 103043 (2021).

    CAS  PubMed  Google Scholar 

  83. Angelici, L. et al. Effects of particulate matter exposure on multiple sclerosis hospital admission in Lombardy region, Italy. Environ. Res. 145, 68–73 (2016).

    PubMed  Google Scholar 

  84. Bergamaschi, R. et al. Air pollution is associated to the multiple sclerosis inflammatory activity as measured by brain MRI. Mult. Scler. J. 24, 1578–1584 (2018).

    CAS  Google Scholar 

  85. Tonne, C. et al. Socioeconomic and ethnic inequalities in exposure to air and noise pollution in London. Environ. Int. 115, 170–179 (2018).

    CAS  PubMed  Google Scholar 

  86. Freeman, J., Gorst, T., Gunn, H. & Robens, S. “A non-person to the rest of the world”: experiences of social isolation amongst severely impaired people with multiple sclerosis. Disabil. Rehabil. 42, 2295–2303 (2020).

    PubMed  Google Scholar 

  87. Gallagher, P. & Mulvany, F. Levels of ability and functioning: using the WHODAS II in an Irish context. Disabil. Rehabil. 26, 506–517 (2004).

    PubMed  Google Scholar 

  88. Yorkston, K. M. et al. Measuring participation in people living with multiple sclerosis: a comparison of self-reported frequency, importance and self-efficacy. Disabil. Rehabil. 30, 88–97 (2008).

    PubMed  PubMed Central  Google Scholar 

  89. Tyszka, A. C. & Farber, R. S. Exploring the relation of health-promoting behaviors to role participation and health-related quality of life in women with multiple sclerosis: a pilot study. Am. J. Occup. Ther. 64, 650–659 (2010).

    PubMed  Google Scholar 

  90. Tabuteau-Harrison, S. L., Haslam, C. & Mewse, A. J. Adjusting to living with multiple sclerosis: the role of social groups. Neuropsychol. Rehabil. 26, 36–59 (2016).

    PubMed  Google Scholar 

  91. Moriya, R. & Kutsumi, M. Fatigue in Japanese people with multiple sclerosis. Nurs. Health Sci. 12, 421–428 (2010).

    PubMed  Google Scholar 

  92. Irvine, H., Davidson, C., Hoy, K. & Lowe-Strong, A. Psychosocial adjustment to multiple sclerosis: exploration of identity redefinition. Disabil. Rehabil. 31, 599–606 (2009).

    CAS  PubMed  Google Scholar 

  93. Patti, F. et al. Longitudinal changes in social functioning in mildly disabled patients with relapsing-remitting multiple sclerosis receiving subcutaneous interferon β-1a: results from the COGIMUS (COGnitive Impairment in MUltiple Sclerosis) study (II). Qual. Life Res. 21, 1111–1121 (2012).

    PubMed  Google Scholar 

  94. Koutsogeorgou, E., Chiesi, A. M. & Leonardi, M. Social capital components and social support of persons with multiple sclerosis: a systematic review of the literature from 2000 to 2018. Disabil. Rehabil. 42, 3437–3449 (2020).

    PubMed  Google Scholar 

  95. Feinstein, A. An examination of suicidal intent in patients with multiple sclerosis. Neurology 59, 674–678 (2002).

    PubMed  Google Scholar 

  96. Reyes, S., Suarez, S., Allen-Philbey, K., Thomson, A. & Giovannoni, G. The impact of social capital on patients with multiple sclerosis. Acta Neurol. Scand. 142, 58–65 (2020).

    PubMed  Google Scholar 

  97. Uhr, L., Rice, D. R. & Mateen, F. J. Sociodemographic and clinical factors associated with depression, anxiety, and general mental health in people with multiple sclerosis during the COVID-19 pandemic. Mult. Scler. Relat. Disord. 56, 103327 (2021).

    CAS  PubMed  PubMed Central  Google Scholar 

  98. Bishop, M. & Rumrill, S. P. The employment impact of the COVID-19 pandemic on Americans with MS: preliminary analysis. J. Vocat. Rehabil. 54, 81–87 (2021).

    Google Scholar 

  99. Giménez-Llort, L., Martín-González, J. J. & Maurel, S. Secondary impacts of COVID-19 pandemic in fatigue, self-compassion, physical and mental health of people with multiple sclerosis and caregivers: the Teruel Study. Brain Sci. 11, 1233 (2021).

    PubMed  PubMed Central  Google Scholar 

  100. Learmonth, Y. C. et al. The impact of the Australian Black Summer Bushfires and the COVID-19 pandemic on wellbeing in persons with multiple sclerosis; preparation for future and ongoing crises. Disabil. Rehabil. https://doi.org/10.1080/09638288.2022.2037756 (2022).

    Article  PubMed  Google Scholar 

  101. Bonavita, S., Sparaco, M., Russo, A., Borriello, G. & Lavorgna, L. Perceived stress and social support in a large population of people with multiple sclerosis recruited online through the COVID‐19 pandemic. Eur. J. Neurol. 28, 3396–3402 (2021).

    PubMed  Google Scholar 

  102. Morris-Bankole, H. & Ho, A. K. The COVID-19 pandemic experience in multiple sclerosis: the good, the bad and the neutral. Neurol. Ther. 10, 279–291 (2021).

    PubMed  PubMed Central  Google Scholar 

  103. Marmot, M., Allen, J., Boyce, T., Goldblatt, P. & Morrison, J. Marmot Review 10 years on. Institute of Health Equity https://www.instituteofhealthequity.org/resources-reports/marmot-review-10-years-on (2020).

  104. Moscrop, A., Ziebland, S., Bloch, G. & Iraola, J. R. If social determinants of health are so important, shouldn’t we ask patients about them? BMJ 371, m4150 (2020).

    PubMed  Google Scholar 

  105. Bechtel, N., Jones, A., Kue, J. & Ford, J. L. Evaluation of the core 5 social determinants of health screening tool. Public. Health Nurs. 39, 438–445 (2022).

    PubMed  Google Scholar 

  106. Bradywood, A., Leming-Lee, T. S., Watters, R. & Blackmore, C. Implementing screening for social determinants of health using the Core 5 screening tool. BMJ Open Qual. 10, e001362 (2021).

    PubMed  PubMed Central  Google Scholar 

  107. Dobson, R. et al. Ethnic and socioeconomic associations with multiple sclerosis risk. Ann. Neurol. 87, 599–608 (2020).

    PubMed  Google Scholar 

  108. NHS England. Treatment algorithm for multiple sclerosis disease-modifying therapies. NHS England https://www.england.nhs.uk/commissioning/wp-content/uploads/sites/12/2019/03/Treatment-Algorithm-for-Multiple-Sclerosis-Disease-Modifying-Therapies-08-03-2019-1.pdf (2019).

  109. Wiendl, H. et al. Multiple Sclerosis Therapy Consensus Group (MSTCG): position statement on disease-modifying therapies for multiple sclerosis (white paper). Ther. Adv. Neurol. Disord. 14, 17562864211039648 (2021).

    PubMed  PubMed Central  Google Scholar 

  110. Hoffman, K. M., Trawalter, S., Axt, J. R. & Oliver, M. N. Racial bias in pain assessment and treatment recommendations, and false beliefs about biological differences between blacks and whites. Proc. Natl Acad. Sci. USA 113, 4296–4301 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  111. Kirk, L. & Bezzant, K. What barriers prevent health professionals screening women for domestic abuse? A literature review. Br. J. Nurs. 29, 754–760 (2020).

    PubMed  Google Scholar 

  112. McFadden, E. et al. Screening for the risk of job loss in multiple sclerosis (MS): development of an MS-specific Work Instability Scale (MS-WIS). Mult. Scler. 18, 862–870 (2012).

    PubMed  Google Scholar 

  113. Kordovski, V. M. et al. Identifying employed multiple sclerosis patients at-risk for job loss: when do negative work events pose a threat? Mult. Scler. Relat. Disord. 4, 409–413 (2015).

    PubMed  Google Scholar 

  114. Vanotti, S. et al. Employment status monitoring in an Argentinian population of patients with multiple sclerosis: particularities of a developing country. Work 68, 1121–1131 (2021).

    CAS  PubMed  Google Scholar 

  115. Simmons, R. D., Tribe, K. L. & McDonald, E. A. Living with multiple sclerosis: longitudinal changes in employment and the importance of symptom management. J. Neurol. 257, 926–936 (2010).

    PubMed  Google Scholar 

  116. Honan, C. A., Brown, R. F. & Batchelor, J. Perceived cognitive difficulties and cognitive test performance as predictors of employment outcomes in people with multiple sclerosis. J. Int. Neuropsychol. Soc. 21, 156–168 (2015).

    PubMed  Google Scholar 

  117. Lueckmann, S. L. et al. Socioeconomic inequalities in primary-care and specialist physician visits: a systematic review. Int. J. Equity Health 20, 58 (2021).

    PubMed  PubMed Central  Google Scholar 

  118. Fjær, E. L. et al. Exploring the differences in general practitioner and health care specialist utilization according to education, occupation, income and social networks across Europe: findings from the European Social Survey (2014) special module on the social determinants of health. Eur. J. Public Health 27, 73–81 (2017).

    PubMed  Google Scholar 

  119. Crawshaw, A. F. et al. Defining the determinants of vaccine uptake and undervaccination in migrant populations in Europe to improve routine and COVID-19 vaccine uptake: a systematic review. Lancet Infect. Dis. https://doi.org/10.1016/S1473-3099(22)00066-4 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  120. Morse, D. F. et al. Global developments in social prescribing. BMJ Glob. Health 7, e008524 (2022).

    PubMed  PubMed Central  Google Scholar 

  121. Hoffmeister, L. V. et al. Evaluation of the impact and implementation of social prescribing in primary healthcare units in Lisbon: a mixed-methods study protocol. Int. J. Integr. Care 21, 26 (2021).

    PubMed  PubMed Central  Google Scholar 

  122. Rodriguez, J. A., Shachar, C. & Bates, D. W. Digital inclusion as health care — supporting health care equity with digital-infrastructure initiatives. N. Engl. J. Med. 386, 1101–1103 (2022).

    PubMed  Google Scholar 

  123. Kavaliunas, A., Danylaitė Karrenbauer, V., Binzer, S. & Hillert, J. Systematic review of the socioeconomic consequences in patients with multiple sclerosis with different levels of disability and cognitive function. Front. Neurol. 12, 737211 (2021).

    PubMed  Google Scholar 

Download references

Acknowledgements

This work received no specific funding. R.D. works within the Preventive Neurology Unit, which is part funded by Barts Charity. Y.L. and C.H.M. are funded by MS Australia fellowships.

Author information

Authors and Affiliations

Authors

Contributions

R.D., D.R.R., M.D., R.H., Y.L., F.J.M., S.R., M.J.W., G.G. and H.L.F. researched data for the article. All authors contributed substantially to discussion of the content. R.D., D.R.R., M.D., R.H., Y.L., F.J.M., S.R., M.J.W., G.G. and H.L.F wrote the article. All authors reviewed and/or edited the manuscript before submission.

Corresponding author

Correspondence to Ruth Dobson.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Reviews Neurology thanks A. He, who co-reviewed with J. Hillert; E. Vasileiou, who co-reviewed with K. Fitzgerald; and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

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

Review criteria To ensure an inclusive overview, we searched PubMed, Scopus, CINAHL through EBSCOhost, MEDLINE through OVID, all other Web of Science (BCI OR SciELO OR WoS OR CABI OR RSCI OR CCC) core collection, PsychINFO and Emcare (OVID) using a search strategy based on the WHO social and immediate determinants of health and a wide range of MS terms on 17 January 2022. We considered any original studies examining social determinants of health and MS outcomes from 2004 onwards, and did not restrict based on language, given the wide-reaching effects of social determinants of health. Out of 2,453 papers screened, a total of 194 papers were considered for inclusion, and the final decision was based on relevance to social determinants of health and MS, along with novelty and current relevance.

Related links

Social determinants of health: https://www.who.int/health-topics/social-determinants-of-health#tab=tab_1

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dobson, R., Rice, D.R., D’hooghe, M. et al. Social determinants of health in multiple sclerosis. Nat Rev Neurol 18, 723–734 (2022). https://doi.org/10.1038/s41582-022-00735-5

Download citation

  • Accepted:

  • Published:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41582-022-00735-5

This article is cited by

Search

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