Association of air pollution and depressive symptoms with cardiometabolic Multimorbidity in middle-aged and older adults: an analysis based on the China health and retirement longitudinal study (CHARLS).

OBJECTIVE: Long-term exposure to air pollution and the presence of depressive symptoms have been associated with an increased prevalence of cardio-metabolic multimorbidity (CMM). However, their associations with CMM among middle-aged and older adults in China remain underexplored. This study aimed to examine the associations of air pollution exposure and depressive symptoms with CMM, and test for potential interactions between these factors, providing evidence to inform public health strategies.

METHODS: This cross-sectional study analyzes health data from 8,192 residents aged 45 and older from the 2015 China Health and Retirement Longitudinal Study (CHARLS). CMM is defined as the presence of multiple conditions, including heart disease, diabetes, hypertension, and stroke. Depressive symptoms were assessed using a standardized self-report scale, and air pollution exposure was estimated using satellite-based spatiotemporal models, including PM1, PM2.5, PM10, SO2, NO2, and O3. Generalized Linear Models (GLM) were used to examine the relationship between air pollution, depressive symptoms, and CMM. Interaction analysis tested whether depressive symptoms modified the association between air pollution and CMM. Sensitivity analysis was conducted using air pollution data from different time windows to validate the robustness of the results, and multiple imputation was employed to handle missing data.

RESULTS: The prevalence of CMM in this study was 15.82%. PM2.5, PM10, and SO2 significantly increased the risk of CMM, with ORs of 1.140 (95% CI: 1.073, 1.211, P < 0.01), 1.192 (95% CI: 1.124, 1.265, P < 0.01), and 1.154 (95% CI: 1.089, 1.223, P < 0.01), respectively. After adjusting for sociodemographic and lifestyle factors, these associations remained statistically significant. Depressive symptoms were independently associated with an increased risk of CMM (P < 0.01). No statistically significant interaction between depressive symptoms and air pollutants was observed (all P-interaction > 0.05), indicating that these two factors exert independent effects on CMM risk.

CONCLUSION: Long-term exposure to air pollution, particularly PM2.5, PM10, and SO2, was significantly associated with a higher risk of CMM. Depressive symptoms were also independently linked to increased CMM risk. Although we hypothesized potential synergistic effects, statistical analyses revealed no significant interaction between depressive symptoms and air pollutants (all P-interaction > 0.05), indicating that these factors operate through independent pathways. Integrating both air quality control and mental health interventions into chronic disease prevention strategies could help reduce the overall CMM burden.