At a Glance
Social and Economic Determinants of Hospital Use, Morbidity, and Mortality over the Life Course
Kieron Barclay, Yaoyue Hu, Karen van Hedel, Mikko Myrskylä, Rasmus Hoffmann, Pekka Martikainen (MPIDR / University of Helsinki, Finland)
Social and economic characteristics and conditions are key determinants of health and mortality, and one of the most consistent findings in the social sciences is that socially disadvantaged groups have worse health and higher rates of mortality than socially advantaged groups. This pattern holds true across countries, among men and women, across practically all age groups, and almost no matter what measure of social status is used.
In this project, we address questions such as how social and economic factors influence older adults’ hospital use. This is particularly important as older adults are disproportionately heavy users of health-care services because of health vulnerabilities related to the aging process. We also seek to gain new and deeper insights into how social disparities in hospital usage change across later life, i.e., whether social disparities continue to grow, start to diminish, or remain stable with increasing age. Other key questions are whether certain living arrangements, such as living alone, are more closely related to higher levels of hospital use than living with a spouse or partner and how the relationship between living arrangements and hospital use differs with increasing age, net of individual heterogeneity. We also examine the effects of socioeconomic status on health, and health itself, on socioeconomic attainment.
To address these questions, we use data from a wide range of countries, including Austria, Belgium, China, Denmark, England, Finland, France, Germany, Italy, the Netherlands, Spain, Sweden, and Switzerland. Our data sources are nationally representative longitudinal datasets, such as the Survey of Healthy Aging and Retirement in Europe, the China Health and Retirement Longitudinal Study , the English Longitudinal Study of Ageing , and Finnish population register data. By using such a wide range of countries, which differ on population health metrics as well as on the levels of social and economic developments and national welfare systems, we are able to build a broad understanding of the extent to which social and economic determinants of hospital use, morbidity, and mortality vary across institutional settings.
Using a cross-national comparative approach, we have found that middle-aged and older Chinese and English adults with wealth and university degrees have a lower risk of depression onset. English adults who do not own their current residence and Chinese adults who experienced deprivation in childhood are at higher risk of mid-late-life depression. These consistent findings from China and England demonstrate that socioeconomic status is a pervasive determinant of mid-late-life depression in very diverse social contexts. However, patterns of depression by age do vary between China and Europe. For Europe, the data suggest that there is a U-shaped pattern where the depression level declines with age until about age 65 and then increases again. In China, however, depression levels continuously increase with age. This may reveal the importance of differences in the provision of mental health services between China and many countries in Western Europe.
Aging, Mortality and Longevity, Health Care, Public Health, Medicine, and Epidemiology
Longitudinal and Life Course Studies, 1–17. (2021)
Journals of Gerontology, Series B: Psychological Sciences and Social Sciences 75:6, 1336–1347. (2020)
American Journal of Epidemiology, 1–21. (2020)
OSF preprints. unpublished. (2020)
Aging and Mental Health 24:6, 923–931. (2020)
Social Indicators Research 141:3, 1341–1367. (2019)
Social Indicators Research 145:1, 349–365. (2019)
BMC Public Health 19:1011, 1–13. (2019)
Journal of Epidemiology and Community Health 73:9, 817–824. (2019)
Rotterdam: Erasmus University Rotterdam. (2019)
European Journal of Ageing 15:4, 379–391. (2018)
Advances in Life Course Research 36, 23–36. (2018)
Journal of Epidemiology and Community Health 72:11, 971–972. (2018)
PLoS One 13:6, e0199551–e0199551. (2018)
Social Science and Medicine 217, 106–111. (2018)
BMC Public Health 18:1105, 1–14. (2018)
European Journal of Epidemiology 32:1, 77–85. (2017)
Social Science and Medicine 177, 100–109. (2017)
European Journal of Public Health 26:2, 260–266. (2016)