Background: Children are especially vulnerable to accelerating climate change, particularly in low- and middle-income countries (LMICs). We aimed to assess the spatial distribution, temporal trends, and key factors of child health vulnerability in LMICs. Methods: Using data from 19 LMICs (2008-2022), we constructed a national-level child health vulnerability index through principal component analysis (PCA). Subsequently, we identified vulnerability driving patterns and temporal shifts for each country based on dimensional indices analysis. Finally, we applied machine learning to examine the association between vulnerability factors and under-5 mortality rates (U5MR). Findings: Between 2008 and 2022, the number of moderately to highly vulnerable countries increased from seven to ten. Three vulnerability driving patterns as exposure-driven (e.g., Bangladesh, Pakistan), adaptive‑deficit‑driven (e.g., Mali, Kenya), and adaptive-deficit-exposure-driven (e.g., Guinea, Sierra Leone) emerged. The original vulnerability factors accurately predicted U5MR using random forest models (validation R² up to 80·6%). Key protective factors included improved water sources (threshold 5·3%), full vaccination coverage (38·7%), minimum dietary diversity (22·4-25·9%), and weekly media exposure (34·4%). Key risk factors were financial barriers to healthcare (51·1%), unimproved toilet facilities (38·9-41·1%), and proportion of the population under 5 years (14·8%). Exposure factors had limited direct influence on U5MR. Interpretation: To our knowledge, this study provides the first dynamic, multidimensional framework for assessing child health vulnerability across LMICs. Additionally, the predictive power of vulnerability factors for U5MR underscores the importance of addressing child vulnerability to improve health outcomes, offering an evidence-based foundation for targeted, staged interventions.

Background People in many regions of the world are often affected by blizzards, which are also showing an increasing trend in certain areas due to climate change. This literature review aimed to synthesize evidence on the health impacts of blizzards. Methods This literature review was informed by systematic review principles. PubMed and Web of Science were searched from January 1, 1935, to May 31, 2025. The risk of bias of the included studies was assessed using the Office of Health Assessment and Translation (OHAT) risk of bias rating tool, and findings were synthesized descriptively due to substantial heterogeneity across studies. Results A total of 28 studies were included. Available evidence indicated that blizzards were associated with adverse health outcomes affecting multiple systems and organs, including trauma, cardiovascular diseases, respiratory diseases, neurological diseases, and foodborne and waterborne diseases. However, evidence was geographically concentrated in a limited number of countries, diseases, categories, and subpopulations. Conclusions Blizzards may pose substantial risks to human health, yet important evidence gaps remain. Deepening the understanding and strengthening the prevention of the negative health impacts of blizzards is an integral part of addressing the health threats of climate change globally. This requires joint efforts from government-led policy support, individual coping, education of the population, and scientific research and technological innovation. Registration PROSPERO CRD42024586068.

Climate change poses an escalating threat to global public health. However, the diseases related to climate change have not been fully recognized due to the lack of a direct mechanistic link between nonoptimal ambient temperature exposure and human diseases. Here, we present a multi-scale network framework integrating transient receptor potential ion channel biology with human disease interactome to comprehensively delineate the potential impacts of climate change on 299 human diseases. We find the majority of known diseases are closely linked to ambient temperature exposure at the molecular mechanistic level. Our projections indicate that global warming will directly lead to an increase of over 12% in the risks of non-communicable and non-congenital human diseases across over 95% of the world's inhabited land by the mid-21st century, thereby impacting over 97% of the global population, compared with the early 21st century. Limiting warming to below 2 ℃ this century can effectively control this surge in disease risks. This work uncovers previously unrecognized health risks directly attributable to temperature exposure from climate change, offers a new paradigm for reshaping our understanding of climate-health causality, and provides scalable tools to mitigate climate-driven disease burdens in an increasingly warming world.

Short-term heat exposure has been linked to adverse mental-health outcomes, but its associations with pregnancy-specific maternal anxiety for fetal health (MAFH) remain unclear, and the role of heatwave and climate change risk perception is unknown. Using data from 1746 pregnant women admitted for delivery in Guangzhou, China, we first used restricted cubic splines to characterize the exposure–response relationship between 7-d average ambient temperature before interview and MAFH. Based on a J-shaped relationship, we defined extreme heat exposure as temperatures at or above the 90th percentile and used multivariable linear regression to examine the association between heat and MAFH. Heatwave and climate change risk perception among the participants was measured and potential effect modification was assessed through stratified and interaction analyses. The mean MAFH score was 10.26 (Standard Deviation = 3.68). Extreme heat was associated with a 0.85-point (95% CI: 0.16–1.54) higher MAFH score compared with the reference range (<P50). In stratified analyses, heat was associated with MAFH in the high perception group, whereas no association was observed in the low perception group. However, there was no statistical evidence to support the presence of effect modification. These findings underscore the need to better characterize heat-related health risks in pregnancy and to design communication and adaptation strategies that improve preparedness for extreme heat without exacerbating maternal anxiety.

BACKGROUND:Antimicrobial resistance (AMR) is an escalating global health crisis being worsened by climate change. Studies of temperature-AMR associations remain limited by geographic scope, time frames and linear approaches. We aimed to identify temperature thresholds where AMR dynamics shift across pathogen-drug combinations, periods and socioeconomic contexts. METHODS:We analysed data from 56 countries and territories over 24 years (1999-2022), focusing on six WHO-designated 'critical' antibiotic-resistant pathogens. Using segmented regression models with mean ambient temperature as the primary independent variable, we divided the study period into three intervals (1999-2006, 2007-2014, 2015-2022) and incorporated 16 socioeconomic and environmental covariates. Model robustness was validated through bootstrap cross-validation with 1000 resamples. FINDINGS:We identified distinct temperature association thresholds for each pathogen-drug combination (5.7°C-18.4°C). Below these thresholds, resistance rates consistently decreased with rising temperatures; above thresholds, responses varied by phenotype and time period. For third-generation cephalosporin-resistant Escherichia coli, each 1°C rise above 16.5°C corresponded to a 0.46% increase (95% CI 0.28% to 0.65%; p<0.001) during 1999-2006, a 0.11% decrease (95% CI -0.17% to -0.06%; p<0.001) during 2007-2014 and a 0.18% increase (95% CI 0.11% to 0.25%; p<0.001) during 2015-2022. The Corruption Perception Index showed consistent negative associations with resistance rates, particularly for carbapenem-resistant Acinetobacter baumannii (β=-1.40, p<0.001). INTERPRETATION:Phenotype-specific temperature association thresholds provide descriptive, hypothesis-generating reference points for understanding how AMR burden varies along the global temperature gradient. The observed temporal heterogeneity suggests complex patterns requiring long-term monitoring and climate-adaptive AMR control strategies considering both phenotype-specific temperature sensitivities and socioeconomic contexts.

Amid global warming, China, a climate-vulnerable region, faces escalating complexity and frequency of compound extreme events, posing risks to public health. Using ambulance dispatch data of 13 cities from the Chinese Ambulance Service Center and ERA5 meteorological data (1979–2024), this study investigates the dominant type transition of high-health-risk temperature–humidity compound extremes in China. The results show that hot–wet extremes have surpassed cold–wet ones as the dominant type around 2010. Further investigation into mechanisms reveals that winter warming in the Barents–Kara Sea (shift contribution: 37.59%, the same below) and summer Arctic sea-ice melting (33.37%) trigger circulation anomalies via polar–midlatitude teleconnections. Spring European soil moisture anomalies (15.24%) amplify the initial signal through land–atmosphere interactions. These anomalies propagate eastward to East Asia via Rossby wave trains, driving abnormal atmospheric circulation: the western Pacific subtropical high enhanced by the influence of western Pacific sea surface temperature increases summer moisture transport to the Tibetan Plateau (26.25%) and later affects Northeast China in winter (18.92%). These circulatory adjustments directly cause changes in temperature and humidity: 4.06 percentage point increases in relative humidity on the Tibetan Plateau, and 4.42 percentage point increases in Northeast China. Combined with the nationwide warming of 0.53°C, hot–wet events have significantly increased and emerged as the dominant events, with the Tibetan Plateau and Northeast China contributing the most to this shift. This study reveals a multi-sphere synergistic mechanism, providing a scientific basis for health risk prevention and adaptation under climate change.

Tropical cyclones (TCs) can elevate diarrheal disease risk yet inconsistent definitions and types of diarrheal data being used can obscure important heterogeneity. Here, we used harmonized weekly diarrheal mortality and morbidity data from 10 Asian regions between 2000 and 2021. We applied two-way fixed effects models to estimate TC-diarrhea associations across regions and compare associations across multiple TC definitions. These definitions include wind-based (wind intensity), rainfall-based (percentile threshold), and combined wind-rainfall metrics. We then assessed differences across a range of diarrheal outcomes. We found that mortality associations were generally not statistically significant and had wide confidence intervals across regions. For morbidity, we observed substantial heterogeneity across regions and definitions, with the greatest TC-attributable burden observed in Taiwan. These findings suggest that tailored TC definitions, calibrated to local health burden profiles, represent a promising strategy to improve early warning systems and guide interventions.

Flooding heightens waterborne disease risks, yet evidence on whether nature-based urban adaptation reduces these burdens is limited. Here we analyzed 4.2 million bacillary dysentery (BD) cases across China (2005–2020). We employed a case-crossover design to estimate the acute effect of flood exposure on BD risk, coupled with a quasi-experimental approach to compare changes in flood-related BD risk between cities with and without the sponge city development initiative. Flood exposure, especially severe floods, increased BD risk over a 28-day lag period. School-aged children and elders were most vulnerable to overall and severe floods, respectively. Cities with sponge city development showed lower flood-related BD risk, with the greatest reduction (12.2%) by the third year after the initiative. Protective effects were stronger where pre-existing infrastructure was weaker (for example, fewer public toilets, lower water pipeline density and less favorable industry). These findings suggest that nature-based urban adaptation could yield health co-benefits, particularly in less-developed settings. Flooding exacerbates bacillary dysentery risks, particularly among vulnerable groups. Analysis of 4.2 million cases in China utilized case-crossover and quasi-experimental methods, revealing a 12.2% risk reduction post-sponge city development, especially in areas with weaker infrastructure.

Climate change has amplified the variability and intensity of cold weather, contributing to a growing health burden. Cold exposure serves as a significant, yet preventable, environmental trigger for acute chest pain–related life-threatening cardiovascular diseases (CVDs), such as acute coronary syndrome, acute aortic dissection, and pulmonary embolism. This scientific statement synthesizes multidisciplinary evidence from meteorology, environmental epidemiology, basic science, and clinical research to offer an updated evaluation of the impact of cold exposure on these acute chest pain-related life-threatening CVDs. The evidence consistently demonstrates that cold weather significantly increases the incidence of such events, often with delayed effects lasting several days to weeks. Vulnerable groups, including the elderly, individuals with chronic conditions, and those of lower socioeconomic status, are particularly at risk. Data also suggest that interventions, including central heating, integrated health warning systems, and appropriate personal protective measures, can effectively mitigate the associated risks. Based on this evidence, the statement provides expert consensus recommendations across clinical, policy, and behavioral domains. Strengthening prevention and response to cold-related cardiovascular risks is essential for building climate-resilient health systems and mitigating the health impacts of climate change.

Extreme weather events increasingly threaten human health, yet current weather–health systems often struggle to translate hazard-based forecasts into actionable, impact-oriented guidance. This gap arises primarily from spatiotemporal misalignment between meteorological and health data, reliance on static hazard thresholds, and limited integration of probabilistic risk assessment. Here, we propose a conceptual framework that leverages artificial intelligence (AI) to bridge extreme weather forecasting and health impact prediction. The AI-enabled system aligns heterogeneous data sources, captures nonlinear and lagged exposure–response relationships, and propagates uncertainty throughout the prediction chain. We illustrate the framework using heatwaves, wildfires, and extreme precipitation, and outline key priorities for operational implementation, including model interpretability, privacy-preserving architectures, and institutional governance. Integrating interpretable and uncertainty-aware health impact prediction into operational forecasting systems will be essential for enabling anticipatory public health action in a future of intensifying weather extremes.

Background: Extreme heat exposure is increasing globally due to climate change and poses a growing threat to cardiovascular health. While the short-term effects of heat exposure on acute cardiovascular events are well established, the long-term cardiovascular consequences of sustained extreme heat exposure remain unclear, particularly among older adults. Frailty may represent an important but underexplored pathway linking environmental risk factors to cardiovascular disease (CVD). Methods: We constructed a longitudinal cohort based on the nationally representative data from the China Health and Retirement Longitudinal Study between (2011–2018). Cox proportional hazards models were used to estimate associations between cumulative long-term extreme heat exposure and CVD incidence. Mediation and interaction analyses were performed to assess the role of frailty in the relationship between extreme heat exposure and CVD. Findings: Long-term extreme heat exposure has a stable, cumulative effect on CVD risk, with the effect magnified in pre-frail individuals and those with worsening frailty, who experience elevated risks of 5·9% to 9·8% per additional day. For frail individuals, cumulative exposure exceeding 60 days showed a significant synergistic interaction with frailty, accounting for 28·7% of excess CVD risk. Higher-intensity heat exposure required fewer exposure days to increase risk, decreasing from 50 to 25 days as the exposure threshold increased from the 90th to 95th percentile. Mediation analysis showed that frailty explained 14·6% of the total effect of extreme heat exposure on CVD. Interpretation: Long-term extreme heat exposure and frailty jointly contribute to CVD risk through both mediation and interaction pathways. Individuals in the pre-frailty stage represent a particularly vulnerable group and a potential target for early intervention. These findings highlight the importance of integrating climate adaptation strategies with ageing-focused CVD prevention in the context of rising global temperatures.

High temperature is a major risk factor for kidney injury, and population exposure to nighttime heat is increasing as the climate warms. However, whether renal responses to heat exposure differ between daytime and nighttime remains unclear. Forty-one healthy adults participated in a randomized crossover experiment conducted in a controlled laboratory setting. Participants were exposed to heat (32°C during daytime; 30°C during nighttime) and thermoneutral conditions (26°C) for 8 h. Blood and urine samples were collected before and after each exposure to examine various renal biomarkers reflecting glomerular filtration function, tubular injury, and early kidney stress. Heat exposure affected both blood and urinary biomarkers of kidney function, with notable diurnal differences in renal responses. Daytime heat exposure primarily affected blood markers of glomerular filtration, increasing creatinine by 7.67% (95% CI: 4.73%-10.61%) and cystatin C by 3.05% (95% CI: 0.17%-5.93%), while reducing estimated glomerular filtration rate by 0.05% (95% CI: 0.02%-0.08%). In contrast, nighttime heat exposure predominantly elevated urinary biomarkers of early kidney stress, including insulin-like growth factor-binding protein 7 (58.40%, 95% CI: 27.66%-89.14%), kidney injury molecule-1 (47.25%, 95% CI: 18.91%-75.59%), and tissue inhibitor of metalloproteinases-2 (51.88%, 95% CI: 22.26%-81.51%). Moreover, increases in insulin-like growth factor-binding protein 7 were significantly greater at night than during the day. Sleep-related parameters, including sleep quality, duration, and heart rate variability, partially mediated nighttime heat effects on renal responses. These results indicated that heat exposure induced different diurnal patterns in renal responses.

Climate change has increased the frequency of extreme temperature and humidity events. Although the association between temperature and hand‒foot‒mouth disease (HFMD) is well-established, evidence regarding the synergistic amplification of risk driven by compound temperature‒humidity events remain limited. This study aims to investigate the temperature‒humidity synergistic effects on the HFMD risk and burden across China based on daily HFMD surveillance records and meteorological data from 302 cities during the period 2011–2019. Temperature‒humidity interactions are evaluated using generalized additive models (GAMs). Bivariate compound events are defined based on multiple temperature‒humidity percentile combinations. Exposure‒lag‒response relationships between temperature‒humidity compound events and HFMD risk are quantified using distributed lag nonlinear models (DLNMs) to identify high-risk thresholds with extreme characteristics. The HFMD burden is assessed through attributable case calculations. In over 18 million cases, we identified substantial synergistic effects between high temperature and humidity (S = 1.328, 95% CI: 1.286–1.370). Concurrent exposure above the 70th temperature percentile and 80th humidity percentile constituted high-risk conditions for HFMD (RR: 1.298, 95% CI: 1.222–1.379) at the national level, yet specific thresholds and associated risks exhibited spatial heterogeneity across regions. Subgroup analysis further identified preschool children and regions with economic disadvantages as vulnerable populations. The frequency of high HFMD risk compound events increased by 24% during 2017–2019 compared with 2011–2013. We identified 464,823 HFMD cases attributable to high-risk compound events across China, with the burden increasing most substantially in Northeast and North China. These findings provide a scientific basis for developing climate-adaptive early-warning systems and targeted interventions.

Humidity and temperature may pose joint effects on human health. However, current temperature-related risk assessments generally focus on univariate temperature statistics, leading to inaccurate risk estimation. By combining temperature and humidity intensities as compound temperature-humidity events (hereinafter as compound events), we examined the effects of humidity in temperature-related health risks in the context of climate change in China using ambulance dispatch data, and further determined the high-risk types and thresholds of compound events. After assessing the health risks, compound events are defined as: i) warm and wet event: temperature ≥ 90th, humidity ≥ 55th and 70%; ii) warm and dry event: temperature ≥ 80th, humidity ≤ 10th; iii) cold and wet event: temperature ≤ 15th, humidity ≥ 70th and 70%; iv) cold and dry event: temperature ≤ 5th and humidity ≤ 25th. Results reveal that humidity can amplify the temperature-related health risks. Higher risks were found during cold and dry events and warm and wet events, posing risks as 1.102 (1.045–1.161) and 1.093 (1.068–1.118) respectively. Compound events mainly occurred in Southeast China during 1979–2019, while the frequency and gripped regions are projected to increase by 2100, and climate change will amplify these trends. Since humidity would exacerbate temperature-related health risks, therefore multiple meteorological parameters are needed in defining adverse weather conditions and conducting risk assessment accurately.

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.

BACKGROUND:The effects of early-life exposure to extreme temperatures on adverse neurodevelopmental outcomes have been increasingly investigated. However, less attention has been given to emotional and behavioral problems (EBPs). This study aimed to examine the association between early-life exposure to non-optimal temperature and EBPs among preschool children aged 2 - 6 years. METHODS:We conducted a cross-sectional study among over 4000 preschool children in Guangzhou, China. EBPs were assessed using the parent-reported Strengths and Difficulties Questionnaire (SDQ). Residential daily ambient temperature during early-life period (from conception to the date of the SDQ assessment) were assessed. Heatwave and cold spell days were defined as extreme high- and low-temperature events, respectively, lasting for at least two consecutive days. Gaussian generalized linear models with an identity link were applied to estimate the associations between non-optimal temperature and SDQ scores, adjusting for relevant confounders. Stratified analyses were conducted to identify vulnerable populations. Distributed lag nonlinear models (DLNMs) were applied to explore potential sensitive windows across period spanning pregnancy through 2 years of age. RESULTS:The exposures to cooler temperature (<5th percentile, 23.79 °C) and warmer temperature (>95th percentile, 24.36 °C) were associated with a 0.357 (95% CI: 0.058, 0.656) and 0.487 (95% CI: 0.164, 0.810) higher total difficulties scores compared with the median temperature (24.09 °C) in preschool children. The significant associations were also observed across other SDQ domains and were more pronounced among children from low-income households. Potential sensitive windows for associations of heatwave and cold spell exposure with SDQ scores were identified primarily during the first two postnatal years. CONCLUSION:Early-life exposures to non-optimal temperature were associated with increased risks of EBPs in preschool children. These findings underscore the importance of mitigating the health impacts of early-life exposure to non-optimal temperatures and developing targeted protective strategies for children from low-income households.

Background: Climate-related health risks are rising rapidly in cities, yet it remains unclear whether scientific research reflects the geography and mechanisms of these emerging risks. Methods: We systematically map city-level climate–health research in China using a large language model–based multi-agent framework, analyzing 2,902 Chinese- and English-language publications from 1993 to 2023. The AI agent system performed document appraisal, information extraction, and structured evidence synthesis. Findings: We identify 2,902 studies, including 1,151 city-level analyses covering 2,012 mentions of 408 unique cities in the articles. Research attention is highly concentrated in a small number of metropolitan areas, with strong geographic inequality in research exposure. Across 408 cities, the growth of climate-related health risks is negatively correlated with research attention (r = −0・329), indicating a mismatch between emerging risks and the distribution of scientific evidence. The literature also focuses predominantly on exposure–disease relationships, while vulnerability, socioeconomic determinants, and system-level responses remain underexplored. Interpretation: Structural gaps exist in the climate–health evidence base. Geographically balanced and mechanism-focused research is urgently needed to support urban climate adaptation and public health action.