Geospatial analysis of neighborhood characteristics and psychosocial outcomes among older adults: a cross-sectional community cohort study

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OBJECTIVE: To assess whether neighborhood poverty, income, crime, and walkability are associated with psychosocial outcomes in older adults. METHODS: We analyzed 198 of 301 participants from the Collaborative Aging Research Using Technology study in Oregon and Washington. Geocoded addresses were linked to census block-group and ½-mile buffer indicators. Single-exposure regression models, adjusted for age, gender, education, and neighborhood healthcare infrastructure, examined loneliness (UCLA Loneliness Scale), weekly lonely mood, anxiety (GAD-7), depressive symptoms (Geriatric Depression Scale), and weekly blue mood. RESULTS: Lower median household income was associated with greater loneliness (p=.023). Higher crime risk was associated with increased weekly loneliness (p=.001), anxiety (OR=1.007; 95% CI: 1.001-1.013), and blue mood (p=.002). Greater walkability was also linked to blue mood (p=.035). No associations emerged for depressive symptoms. Indicators overlapped substantially (walkability-crime ρ≈0.78). CONCLUSIONS: Lower income was linked to chronic loneliness, while higher crime was consistently associated with weekly lonely mood, anxiety, and blue mood, suggesting safety-related exposures may be particularly salient for momentary emotional states. The absence of associations with depressive symptoms suggests trait-level depression may be less responsive to proximate environmental conditions than state-sensitive mood. These findings support community-level interventions targeting neighborhood safety among older adults aging in place.

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