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

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.