The association between extreme weather events and depression risk in postmenopausal women: cross-sectional and longitudinal evidence from the China Health and Retirement Longitudinal Study (CHARLS)

OBJECTIVE: Investigating the association between different types of extreme weather events and the risk of depression in postmenopausal women. METHODS: This study used data from the China Health and Retirement Longitudinal Study (CHARLS) covering four waves from 2011 to 2018, with a focus on postmenopausal women aged 45 and older. Depression symptoms were assessed using the Center for Epidemiologic Studies Depression Scale (CESD-10). Based on baseline data from 2011, five types of extreme weather exposure indicators (extreme low temperature [LTD], extreme high temperature [HTD], extreme rainfall [ERD], extreme drought [EDD], and the climate physical risk index [CPRI]) were used to construct generalized linear models to analyze the associations between these five extreme weather exposures and the baseline (2011) prevalence of depression among postmenopausal women. Cox proportional hazards models were employed to assess the relationship between baseline extreme weather exposures and the incidence of new depression (2013-2018). Restrictive cubic splines (RCS) were used to test the nonlinear relationship between exposure and depression, and quantile g-computation was used to examine the joint effects of multiple extreme weather exposures. RESULTS: In the cross-sectional analysis of 5,986 participants, the depression prevalence was 35.9% (2,147 cases). After adjusting for confounding factors, HTD (OR=1.007, 95% CI: 1.005-1.011, P