Association between urbanicity and depressive symptoms among Chinese middle-aged and older adults

Abstract

Background: Depression is a pressing public health issue and may be affected by multifaceted urban living, yet the specific urbanicity elements associated is unclear. Using a multidimensional urbanicity scale, we explored the association between urbanicity and its components with the risk of depressive symptoms. Methods: This study used data from four waves of the China Health and Retirement Longitudinal Study, including 12,515 participants aged ≥45 years at baseline in 2011 in 450 rural and urban communities, and 8,766 with 7 years of follow-up. Multilevel logistics regression and Cox proportional hazards regression models examined the cross-sectional and longitudinal associations between urbanicity and depressive symptoms. Results: Living in areas with the highest tertile of urbanicity was associated with a 61% lower risk of depressive symptoms cross-sectionally (odds ratio (OR): 0.39, 95% confidence interval (CI): 0.30-0.50) and 33% lower risk longitudinally (hazard ratio (HR): 0.67, 95% CI: 0.58-0.77) compared to those living in areas with the lowest tertile of urbanicity. Among components, higher population density (OR: 0.92, 95% CI: 0.87-0.97), better education (OR: 0.94, 95% CI: 0.89-0.99), transportation (OR: 0.95, 95% CI: 0.92-0.98), sanitation (OR: 0.96, 95% CI: 0.93-0.98) was associated with lower odds of depressive symptoms, while greater population educational and socioeconomic diversity (OR, 1.08; 95% CI, 1.03-1.13) had opposite effect. Better economic conditions (HR: 0.94, 95% CI: 0.90-0.98) and availability of social services (HR, 0.96; 95% CI, 0.93-0.99) were longitudinally associated with reduced risk of developing depressive symptoms during 7 years of follow-up. Additionally, differences in associated components were found between urban and rural residents and between midlife and older adults. Conclusions: Our findings underscore the complex links of urban living with depressive symptoms among middle-aged and older adults, highlighting the need to consider a multidimensional urbanicity perspective to understand the urbanicity-mental health nexus. Tailored urban planning policies should consider the associated urbanicity components, along with temporal effectiveness, urban-rural disparities, and age group differences.