Climate-related health risks and payer-specific health expenditure growth: empirical evidence from government, social, and out-of-pocket health expenditure in China.

BACKGROUND: Climate-related health risks may coincide with healthcare needs, service disruptions, and preparedness demands, yet the associated expenditure is distributed across public budgets, collective financing, and households. Evidence rarely shows whether multidimensional climate-risk profiles are associated with expenditure growth across these financing channels. We examined associations between four climate-risk dimensions and real growth in government, social, and out-of-pocket (OOP) health expenditure in China. METHODS: Annual data for 31 provincial-level regions covered 2013-2023; growth models used a balanced panel of 310 province-year observations for 2014-2023. The IPCC framework was operationalized as climate hazard, urban exposure, social vulnerability, and adaptive-capacity deficits. Exploratory and confirmatory factor analyses evaluated the measurement structure. CFA factor scores were entered into two-way fixed-effects models with province and year effects; structural equation modeling (SEM) was supplementary and descriptive. RESULTS: Measurement analyses were consistent with four related but internally distinguishable dimensions within the study sample. In the primary models, each dimension was positively associated with real growth in all three payer-specific expenditure categories. Positive directions generally persisted under annual z-score standardization, 1-year lagging, exclusion of 2020-2022, and log-level outcomes, although magnitudes varied and the social-financing estimates were most sensitive to construct specification. SEM yielded directionally concordant contemporaneous associations but was not used for primary inference. CONCLUSION: The findings are consistent with climate-related health risk as a multidimensional financing context whose statistical footprint is visible across multiple payers, while the study does not establish statistically different effects between payers. They support risk-profile surveillance and targeted hypothesis generation for climate-health adaptation, not causal attribution, contribution rules, or province-specific allocation formulas without claims-based and quasi-experimental evidence.