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. 1998 Jan;46(1):49-57.
doi: 10.1111/j.1532-5415.1998.tb01012.x.

Can money buy happiness? Depressive symptoms in an affluent older population

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Can money buy happiness? Depressive symptoms in an affluent older population

C G West et al. J Am Geriatr Soc. 1998 Jan.

Abstract

Objectives: To determine if the inverse association between depressive symptoms and income reported in predominantly low- and middle-income older populations is present in a more affluent population of older adults and to determine if this pattern is independent of other known correlates of depressive symptoms such as medical problems, physical disability, and social support.

Design: Cross-sectional analysis within a prospective cohort study.

Setting: An ongoing, community-based cohort study conducted by an independent research institution in an affluent Northern California county.

Participants: A total of 1948 randomly selected, noninstitutionalized county residents 55 years of age and older who completed the baseline questionnaire and physical performance tests.

Measurements: The outcome measure was high level of depressive symptoms (score > or = 16) using the Center for Epidemiologic Studies-Depression scale (CES-D).

Results: The prevalence of high levels of depressive symptoms (CES-D score > or = 16) was lower than in most other population-based samples using an identical CES-D scale. In age-adjusted, sex-specific analyses, increasing income level was associated significantly with lower levels of depressive symptoms, but the nature of the relationship appeared quadratic rather than linear (Men: odds ratio (OR) income .80, 95% confidence interval (CI) .68-.94; income2 OR 1.006, 95% CI 1.001-1.011. Women: OR income .80, 95% CI .69-.91; income2 OR 1.007, 95% CI 1.002-1.011). In multivariate regression analyses including potential confounding risk factors, the magnitude of the association between depressive symptoms and income decreased and was not statistically significant when measures of health conditions, physical disability, and social support were included in the model (Men: OR income .90, 95% CI .75-1.06; income2 OR 1.003, 95% CI .998-1.009. Women: OR income .90, 95% CI .78-1.05; income2 OR 1.003, 95% CI .998-1.008).

Conclusion: These findings suggest that poor health, physical disability, and social isolation are the major factors responsible for the observed inverse relationship between income and symptoms of depression in affluent, as well as economically disadvantaged, older populations.

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