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Direct and spillover hospitalisation patterns during climate hazards across regions of different health-system resilience levels in China: a nationwide retrospective analysis.

BACKGROUND: Health-system resilience serves as a key contributor in mitigating adverse health impacts during climate hazards. However, quantitative insights into resilience-associated health-care utilisation patterns and targeted adaptation policies remain scarce. We aimed to capture the spatiotemporal health impacts in disaster-exposed counties and their neighbouring counties in China during storms, floods, tropical cyclones, and blizzards or winter storms; understand the association between health-system resilience metrics and hazard-attributable hospitalisations; and develop evidence-based adaptation policies towards climate extremes. METHODS: In this retrospective, observational analysis of county-level aggregated hospitalisation data, we used a propensity score matching-difference-in-differences framework to assess the spatiotemporal changes of nine types of disease-specific hospitalisations in both disaster-exposed and neighbouring regions during storms, floods, tropical cyclones, and blizzards in China. We quantified the relative importance and health gains of health-system metrics during such hazards through random forest approach with interpretable partial dependence plots to derive evidence-based adaptation recommendations. FINDINGS: We included hospitalisation data from Jan 1, 2016 to Dec 31, 2023. In this period, 3241 county-hazard event combinations and 41 747 482 hospitalisations were recorded across 955 Chinese counties. The disaster-exposed regions experienced an initial decline in hospitalisation rates, followed by admission surges after disasters. For example, infectious disease admissions decreased by 11·92% (95% CI -10·53 to -13·31) during the flood-active period but increased by 7·68% (6·46-8·91) after 1-2 weeks of floods. Neighbouring zones were also affected through spillover effects, with infectious disease admissions increasing by 3·18% (1·76-4·61) after 1-2 weeks of the floods. Cardiovascular disease, injuries, infectious, respiratory, and mental disorders were more sensitive across all regions. Particularly for disaster-exposed counties, cardiovascular hospitalisations increased by 14·31% (7·34-21·29) during the tropical cyclone-active period. Notably, compared with low-resilience counties, high-resilience counties were associated with 19·48-30·03% smaller hazard-related relative changes in hospitalisation rates during the hazard-active period and 27·07-31·08% smaller hazard-related relative changes in hospitalisation rates in post-hazard periods. For instance, during the storm-active period, the increase in respiratory hospitalisations was 7·21% (0·67-13·75) in high-resilience counties versus 12·13% (5·20-19·05) in low-resilience counties. Health workforce (relative importance 14·58% during the hazard-active period and 13·80% during the post-hazard period) and service delivery (14·10% during the hazard-active period and 14·17% during the post-hazard period) were identified as key contributors of health-system resilience. Empirical synergistic effects were observed when combining interventions during the post-hazard period, with the combined effect of service delivery (individual contribution 8%) and workforce (individual contribution 4%) exceeding the sum of their individual contributions (16% reduction in cumulative excess admissions) by 33%. INTERPRETATION: Climate hazards are associated with substantial changes in hospitalisation rates in both disaster-exposed and neighbouring regions. Health-system resilience is essential in addressing disaster-health challenges. Targeted adaptation interventions should be context-appropriate and threshold-aware, thereby maximising the public health benefits relative to resilience-oriented investments in health systems. FUNDING: Gates Foundation and the National Natural Science Foundation of China.

Journal Article

Epigenome-wide analysis of DNA-methylation signatures following climate-related disasters.

BACKGROUND: Floods and tropical cyclones (TCs), two of the most frequent and costliest climate-related disasters worldwide, have been linked to sustained health risks extending beyond acute hazards. However, evidence on the underlying epigenetic mechanisms remains scarce. We aimed to characterize DNA methylation patterns associated with exposure to floods and TCs of varying intensities. METHODS: We collected peripheral blood samples from 479 women (132 twin pairs and 215 of their sisters) across Australia. Blood-derived DNA methylation profiles were assessed using the Illumina HumanMethylation450 BeadChip array. Daily flood and TC exposure data for the 6&#xa0;years preceding each blood draw were obtained from the Dartmouth Flood Observatory and the International Best Track Archive for Climate Stewardship, respectively, and linked to participants based on residential addresses. Using a within-sibship analytical framework that accounted for shared familial factors and other relevant covariates, we examined associations between flood and TC exposures of varying intensities and site-specific methylation at each cytosine-guanine dinucleotide (CpG). Differentially methylated regions (DMRs) were identified using a combination of the comb-p and DMRcate algorithms. RESULTS: There were 164 CpGs and 219 DMRs associated with flood and TC exposures (Bonferroni-adjusted p value&#x2009;<&#x2009;0.05), mapping to 242 genes enriched in pathways related to inflammation and immune regulation. These genes have been implicated in a wide range of human diseases or phenotypes. The number of differentially methylated CpGs increased with more recent and higher-intensity exposures. Intensity-dependent gene regulation was observed, with genes such as AMT and C22orf45 consistently implicated across various exposure levels, whereas RNF39 and ACY3 emerged only at higher intensities. CONCLUSIONS: Exposures to floods and TCs were associated with differentially DNA methylated signals across the human genome, exhibiting intensity-dependent patterns. The identified signals and related gene pathways may shed light on the biological mechanism underlying the profound health effects of climate-related disasters.

Humans