Residential Greenness and Depression in Older U.S. Adults: Evidence from The Health and Retirement Study

BACKGROUND AND AIM: The physical environment influences mental health. In this study, we investigated residential greenness in relation to major depressive disorder (MDD), a leading cause of disability. We also tested effect modification by climate and urbanicity given that vegetation types and human interaction with vegetation differs across these settings. METHODS: We used biennial survey data from 2008 through 2016 from a cohort of older U.S. adults. We calculated greenness at participant home addresses as the maximum normalized difference vegetation index (NDVI) for the year preceding each survey, averaged within 250m and 1km buffers. A score of ≥5 on the Composite International Diagnostic Interview Short Form indicated MDD. We used Köppen-Geiger classifications, which identify vegetation biomes, to characterize climate, and Beale codes for urbanicity. To estimate prevalence ratios, we used Poisson regression accounting for repeated measures and incorporated survey weights. Our models adjusted for individual and neighborhood socio-demographics, geography, sunshine, and bluespace. RESULTS: We included 27,829 participants who contributed 91,479 observations to our analysis. Participants were 66 (±11) years old on average, 83% White, and 28% completed college, with a 12-month prevalence of MDD of 8%. In fully adjusted models, an interquartile range higher NDVI within 250m was associated with a 12% lower prevalence of MDD (PR:0.88, 95% CI:0.81-0.96). This association was stronger in cold (PR:0.82, 95% CI:0.73-0.92) climates (p-interaction: 0.091), and urban (PR:0.84, 95% CI:0.76-0.93) areas (p-interaction: 0.222). We found similar results for 1km NDVI. CONCLUSIONS: More residential greenness was associated with less MDD, suggesting greening interventions could improve mental health. Since we found evidence of effect modification by climate and urbanicity, those planning interventions should consider vegetation types and prioritize areas where they may be particularly beneficial. Future studies could better identify vegetation types and communities most in need of greening interventions. KEYWORDS: Mental health, greenspace, built environment