SSM: Population Health (Sep 2023)

Heterogenous trajectories in physical, mental and cognitive health among older Americans: Roles of genetics and life course contextual factors

  • Cung Truong Hoang,
  • Vikesh Amin,
  • Jere R. Behrman,
  • Hans-Peter Kohler,
  • Illiana V. Kohler

Journal volume & issue
Vol. 23
p. 101448

Abstract

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We investigate the roles of genetic predispositions, childhood SES and adult educational attainment in shaping trajectories for three important components of the overall health of older adults -- BMI, depressive symptoms and cognition. We use the Health & Retirement Study (HRS) and group-based trajectory modeling (GBTM) to identify subgroups of people who share the same underlying trajectories ages 51–94 years. After identifying common underlying health trajectories, we use fractional multinomial logit models to estimate associations of (1) polygenic scores for BMI, depression, ever-smoked, education, cognition and subjective wellbeing, (2) childhood SES and (3) educational attainment with the probabilities of trajectory group memberships. While genetic predispositions do play a part in predicting trajectory group memberships, our results highlight the long arm of socioeconomic factors. Educational attainment is the most robust predictor—it predicts increased probabilities of belonging to trajectories with BMI in the normal range, low depressive symptoms and very-high initial cognition. Childhood circumstances are manifested in trajectories to a lesser extent, with childhood SES predicting higher likelihood of being on the low depressive symptoms and very-high initial cognition trajectories. We also find suggestive evidence that associations of educational attainment on the probabilities of being on trajectories with BMI in the normal range, low depressive symptoms and very-high initial cognition vary with genetic predispositions. Our results suggest that policies to increase educational attainment may improve population health by increasing the likelihood of belonging to “good” aging trajectories.

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