Associations between storm exposure patterns and metabolic syndrome risk in Chinese adults: a CHARLS-based prospective cohort study

To assess the nonlinear association between city-scale storm events and incident metabolic syndrome (MetS) in the China Health and Retirement Longitudinal Study (CHARLS) cohort of middle-aged and older adults, and to examine the effect modification and mediating effects of PM₂.₅, as well as spatial heterogeneity. Based on CHARLS data from the 2011 baseline survey followed up to 2015, 4,085 participants without pre-existing MetS at baseline were included, with 512 incident MetS cases identified. Cox proportional hazards models were used to estimate risks; natural cubic splines (RCS) were applied to characterize the exposure–response relationship. RCS×RCS interactions was “storm peak rainfall × PM₂.₅,” with simple slope curves estimated at the 10th, 50th, and 90th percentiles (P10, P50, P90) of pollution levels. Parallel multiple mediation analysis assessed the indirect effects of PM₂.₅, and psychosocial factors. Global/local spatial autocorrelation and multiscale geographically weighted regression (MGWR) were employed to evaluate spatial clustering and non-stationarity. In quantile-based Cox models, compared with Q1 (lowest rainfall), participants in Q2–Q4 showed lower MetS risks (Model 2: HR_Q2 = 0.67, HR_Q3 = 0.61, HR_Q4 = 0.58; all significant). After full adjustment, associations attenuated but remained directionally consistent (Model 3: HR_Q2 = 0.76, HR_Q3 = 0.74, HR_Q4 = 0.81). PM₂.₅ was positively associated with MetS (HR ≈ 1.01 per unit), while annual mean temperature was protective (HR ≈ 0.96 per unit). The RCS revealed a U-shaped curve: in low storm peak rainfall areas (≈ 0–25 units), HR was slightly above 1; minimal risk occurred at moderate storm peak rainfall (≈ 50–150 units, HR ≈ 0.5–0.7); beyond 175 units, risk increased sharply (HR > 8 at ≈ 200 units). Significant effect modifications were observed in RCS×RCS analyses: PM₂.₅ stratification: At low pollution (P10 ≈ 37.1 µg/m³), the association increased with storm peak rainfall intensity; neutral at median (P50 ≈ 55.2 µg/m³); protective at high pollution (P90 ≈ 79.6 µg/m³). Mediation analysis indicated a significant indirect effect through PM₂.₅, and nonsignificant psychosocial pathways. Spatial analysis revealed clustering of MetS incidence and non-stationary storm effects—predominantly negative in northern/northeastern China, but neutral or positive in parts of central/southern coastal regions. City-scale storm peak rainfall exhibited a nonlinear association with incident MetS, where moderate intensity may be protective but extreme intensity harmful. PM2.5 served as the primary modifying and mediating pathway and marked regional variability. Health risk assessments of storm peak rainfall must consider both exposure ranges and geographic heterogeneity.