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

BackgroundDepression 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. MethodsThis 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. ResultsLiving 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. ConclusionsOur 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.