Back

Chronic health conditions and health-related economic inactivity in midlife: Evidence from the 1958 and 1970 British birth cohorts

Gimeno, L.; Bridger Staatz, C.; Goisis, A.; Dowd, J.; Ploubidis, G. B.

2025-06-20 epidemiology
10.1101/2025.06.20.25329982 medRxiv
Show abstract

BackgroundHealth-related economic inactivity is a growing concern in the United Kingdom but little is known about how the relationship between health and work participation has changed across cohorts. MethodsWe used data from two British birth cohorts born in 1958 (National Child Development Study, n = 9,761) and 1970 (British Cohort Study, n = 7,336). We examined how self-reported chronic health conditions at age 42 (longstanding illness, obesity, diabetes, high blood pressure, back pain, and mental ill-health) were associated with economic activity at ages 50-54, focusing on health-related inactivity. Multinomial logistic regression models, adjusted for previous economic activity and sociodemographic characteristics, were used to estimate average marginal effects (AME). ResultsPoor health was more prevalent in the 1970c, including among those still working at age 50-54. Longstanding illness and mental ill-health were associated with a higher risk of health-related inactivity in both cohorts. A longstanding illness at age 42 was associated with a 6 percentage-point increase in health-related inactivity risk a decade later (AME1958 = 5.9 [95% Confidence Interval (CI) 2.7, 9.1], AME1970 = 6.5 [95%CI 3.4, 9.6]), and mental ill-health with a 4.5 percentage-point higher risk (AME1958 = 4.4 [95%CI 0.9, 7.9], AME1970 = 4.5 [95%CI 1.1, 7.8]). The magnitude of associations was similar across cohorts except for high blood pressure. ConclusionsChronic health conditions in early midlife were strongly associated with a health-related inactivity, despite contextual change. Preventing ill-health and supporting employment for those with chronic conditions is key to face the challenges of population ageing.

Published in SSM - Population Health (predicted rank #2) · training set

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.