OBJECTIVES:Emerging evidence suggests an association between ambient air pollution and severe coronavirus disease 2019 (COVID-19) outcomes. We aimed to assess whether long-term exposure to fine particulate matter (PM2.5) is associated with acute hospitalization after COVID-19 infection and whether this association is modified by COVID-19 vaccination. STUDY DESIGN:Retrospective nationwide cohort study of confirmed COVID-19 cases in the Republic of Korea, with municipality-level PM2.5 exposure assigned and time to emergency admission modeled using a Cox's proportional hazards model. METHODS:Using national health insurance data in the Republic of Korea, we enrolled 556,767 individuals confirmed with COVID-19 infection from October 8, 2020, to December 31, 2021. Municipality-level annual average PM2.5 estimates for 2019 were linked to each COVID-19 case based on their residence. The outcome was defined as hospital admission via an emergency department visit. We employed the Cox's proportional hazards model to assess the association between PM2.5 exposure and the risk of COVID-19 hospitalization after adjusting for potential individual- and municipality-level confounders. RESULTS:Higher exposure to PM2.5 was associated with an increased risk of COVID-19 hospitalization. In the overall population, an increase in PM2.5 of 5 μg/m3 was associated with a 10% (95% confidence interval [CI], 3-17%) increase in the risk of hospitalization. In the unvaccinated group, a 5 μg/m3 increase was associated with a 21% increase in hospitalizations (95% CI, 13-30%). However, we found no association among vaccinated individuals (one vaccine dose or more). CONCLUSIONS:We found evidence that long-term exposure to fine particulates was associated with the increased risk of acute hospitalization from COVID-19 among unvaccinated individuals.

Background:The hazardous impact of heat on health has been extensively reported, with many studies showing long-term adaptation to heat. However, short-term acclimatization, particularly within a season, remains unclear. Methods:Using a two-stage time-series approach and nationwide medical claims data (2011-2019, May-September) for South Korea, we estimated the association between ambient temperature and emergency department (ED) visits as well as its within-summer variation, focusing on individuals aged ≥65 years. Findings:Within the study period, 4,637,075 ED visits were recorded. For the overall population, the relative risk (RR) comparing the 95th versus the 50th percentile of summer temperature was 1·076 (95% confidence interval [CI]: 1·070-1·082). Individuals aged ≥75 years, females, low-income groups, and those with renal-related ED visits exhibited greater vulnerability to extreme heat. RRs for heat were higher in early summer (RR: 1·124 [95% CI: 1·098-1·150]) than in late summer (RR: 1·054 [95% CI: 1·043-1·066]). This within-summer variation was generally consistent across sex, age, income level, and renal- and mental disorders or neurological diseases-related ED visits. However, groups more vulnerable to extreme heat, such as individuals aged ≥75 years, females, low-income groups, and those with renal-related ED visits, showed smaller variation, suggesting persistent vulnerability throughout the summer period. Interpretation:Heat-related ED visits for extreme heat were generally higher in early summer than in late summer, suggesting the necessity to consider temporal changes in heat risk when developing nuanced and targeted national heat adaptation policies. Funding:Korea Environment Industry & Technology Institute.

BACKGROUND:Climate change threatens global health, particularly among vulnerable populations such as pregnant individuals and their newborns. Evidence linking heat to premature birth is largely based on single-location studies or heterogeneous meta-analyses, leaving important gaps regarding underrepresented regions, preterm subgroups, and the role of maternal and infant characteristics. OBJECTIVES:To quantify the association between heat and preterm birth (PTB) across multiple countries, assess gestational-age-specific effects, and identify maternal vulnerability factors. METHODS:We analysed 36.6 million births occurring during the warm season from 250 locations in 13 countries to assess heat effects on PTB. Distributed lag non-linear models (DLNM) with quasi-Poisson regression estimated heat-PTB associations and the fraction of PTB attributable to heat. Gestational-age subcategories (extreme, very, late, and at-term) and socio-economic vulnerability profiles were also examined. RESULTS:Overall, 1.4% (95% CI: 1.3-1.5) of PTB were attributable to heat (855 PTB per million births), with national burdens from 628 to 1,347 PTB per million. Higher susceptibility was suggested for younger, single, non-primiparous, less-educated, and socio-economically deprived mothers, and among female fetuses. Late PTB showed the largest risk; at-term births also displayed a small but consistent heat-related increase. CONCLUSIONS:This large analysis of heat-related PTB using harmonized individual-level data indicates that heat increases PTB risk, with variations across countries and climates. It also shows that heat can trigger labour beyond the typical PTB window, affecting pregnancies not usually considered clinically vulnerable. Overall, these findings underscore the need for strategies to mitigate heat-related risks during pregnancy, particularly among socio-economically vulnerable populations.

BACKGROUND:The impacts of extreme ambient temperatures on mental health may vary by type of disorders, age and sex. We examined the association between extreme ambient temperatures and emergency department (ED) visits for prevalent mental disorders, stratified by age and sex. METHODS:We analyzed the National Emergency Department Information System data in 2015-2021, Korea. Using a case-time series design, we calculated relative risks (RRs) of ED visits for prevalent mental disorders at extremely high (97.5th percentile) and low (2.5th) ambient temperatures, stratified by age (0-19, 20-39, 40-64, and ≥ 65) and sex. A lag period of 0-5 days was considered for ambient temperature and air pollution. RESULTS:Of 1,351,463 ED visits due to mental disorders, neurotic, stress-related and somatoform disorder (anxiety disorder, 31.5%), organic mental disorder (OMD, 25.2%), substance use disorder (SUD, 24.5%) and mood disorder (MD, 15.2%) were common. At extreme high temperatures, the RR of anxiety-related visits was 2.25 (95% confidence interval [CI], 1.87-2.71), with men 20-39 years at higher risk (4.02; 95% CI, 2.77-5.85) than women (1.65; 95% CI, 1.17-2.32, P for difference < 0.001), versus minimum-risk ambient temperature. Extreme heat also raised RR for OMD in men 40-64 years (1.49; 95% CI, 1.01-2.21), SUD in women 20-39 years (2.72; 95% CI, 1.85-3.99) and MD in women ≥ 65 years (2.00; 95% CI, 1.42-2.80). Risk estimates at extreme low temperatures were generally imprecise, except for anxiety in men 20-64 years. These associations were not replicated among children and adolescents (0-19 years). CONCLUSION:Our findings emphasize the need for more tailored climate change adaptation strategies considering the varying vulnerabilities of populations to mental disorders.

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.

Numerous studies have established a U- or J-shaped association between ambient temperature and human mortality by analyzing time-series data collected from multiple locations. However, this association has changed over time owing to climate change and adaptive behaviors, such as the increased use of air conditioning. Temporal changes have been examined using a conventional two-stage modeling framework, which typically assumes a linear change over time. Our preliminary analysis of Japanese data suggests that these temporal changes may not be linear or gradual, challenging the common assumption adopted in the conventional two-stage modeling approach. Moreover, the assumption of normality in the existing second-stage mixed-effects models can make the estimates highly sensitive to outliers. To address these limitations, we propose a two-stage modeling framework with a novel second stage model: a nonparametric Bayesian meta-analysis model with change-point detection. In the first stage, we divide the full study period into non-overlapping one-year sub-periods to capture fine-scale temporal variation and estimate temperature-mortality associations for each location and sub-period using distributed lag nonlinear models. In the second stage, we pool the associations across locations and sub-periods simultaneously applying our novel nonparametric Bayesian meta-analytic model, which is formulated based on the Probit Stick-Breaking Process to facilitate flexible segmentation of time regimes. The model also incorporates a mixture of Gaussian and t-distributed errors to account for potential outliers and ensure robust estimation. The proposed modeling framework is validated through simulation studies and illustrated through an application to the study for time-varying temperature-mortality association in Japan.

Rising temperatures have raised concerns about impacts on mental health, including suicide. However, how climate change will affect global temperature-related suicide remains unclear. Using data from 751 locations across 26 countries, combined with climate projections under 3 emissions scenarios, we estimated temperature-suicide associations and projected temperature-related suicide mortality through the 2050s, assuming no adaptation, demographic shifts or changes in suicide rate. Here we show that climate change is projected to increase suicide mortality attributable to temperature across all studied regions, with the magnitude depending on both the emissions scenario and geographic location. Warmer regions-including Central and South America, South Europe, Southeast Asia and South Africa-show larger increases, while temperate and colder regions such as North America, North Europe, East Asia and Australia show smaller but meaningful rises. These findings highlight the potential of climate change to exacerbate suicide and underscore the importance of adaptive mitigation strategies.

Pollen is a biogenic pollutant of growing concern due to rising temperatures under climate change. Previous studies suggest an exacerbating effect of pollen on allergenicity-related adverse health outcomes but remains inconclusive. This study aimed to examine whether pollen modifies the relationship between particulate matter air pollutant and mortality. We collected daily data on pollen, suspended particulate matter (SPM), and mortality from eight cities across Kyushu, Japan, during the pollen season (February to April) between 1989 and 2014. A two-stage time-series study was conducted, incorporating an interaction term between SPM and pollen levels to quantify effect modification by pollen in the first stage, followed by pooling the city-specific estimates in the second stage. A total of 262,288 all-cause deaths occurred during the study period. SPM was associated with respiratory mortality one day after exposure (lag 1) with a relative risk (RR) of 1.011 and corresponding 95% confidence interval (CI) of 0.997 to 1.025. Days were stratified into binary, lower or higher pollen days based on pollen concentration. A pattern of effect modification of SPM by pollen on respiratory mortality was observed. The risk of respiratory mortality associated with SPM at lag 1 during higher pollen days above the 75th percentile (RR: 1.021, 95% CI: 1.005-1.037) was larger than that during lower pollen days (RR: 1.003, 95% CI: 0.987-1.018). This pattern of effect modification remains regardless of variation in pollen day cutoffs. Targeted adaptive strategies should be developed according to specific pollen concentrations expected to elevate the health burden of air pollution during spring seasons in western Japan.

Minimum mortality temperature (MMT) is an important feature of temperature-mortality relationship, defined as the temperature at which mortality risk is lowest. Although numerous studies have estimated MMT for all-cause mortality, few have explored differences by age or cause of death. We analyzed daily mean temperature and mortality data from 667 communities across 39 countries. Mortality was classified by age and cause of death (cardiovascular, respiratory, or non-cardiorespiratory). A two-stage meta-analytic approach was applied to estimate the MMT and its corresponding percentile (MMTP) by age and cause of death. In the overall population, MMT was the highest for cardiovascular mortality (22.1 °C, 95% CI: 20.9-23.4 °C), whereas respiratory and non-cardiorespiratory causes were 0.87 °C and 0.66 °C lower, respectively, than that for cardiovascular causes. Similar patterns were observed for MMTP, which was highest for cardiovascular mortality (75%, 95% CI: 73-78%) and lower by 5% and 4% for respiratory and non-cardiorespiratory causes, respectively. MMT increased with age for cardiovascular (0.19 °C per 10 years, 95% CI: 0.14-0.23) and non-cardiorespiratory causes (0.13 °C per 10 years, 95% CI: 0.09-0.16). These patterns were generally consistent across geographical regions. Overall, both MMT and MMTP differed by cause of death and age, indicating that the optimal temperature varies across population subgroups.

The potential compounding effect between high temperature and air pollution is critical. However, the evidence is limited in tropical climate areas where temperatures hit record highs year after year. This study aimed to examine whether the heat-related mortality is modified by particulate matter (PM) in five urban or industrial provinces of Thailand. We used a two-stage time-series design and collected daily data of temperature, humidity, PM and mortality (non-accidental, cardiovascular and respiratory) from 2015 to 2019. We fitted a generalized linear model with a Poisson distribution and incorporated an interaction term between PM <= 10 mu m (PM10), PM <= 2.5 mu m (PM2.5) in aerodynamic diameter and temperature to examine the effect modification of PM on heat-related mortality during the six warmest months for each province, adjusting for time-varying confounders, such as day of week, relative humidity, long-term and seasonal trend. Relative risks (RR) of mortality for heat were estimated between the 99th and 50th percentiles of temperature. A random-effects meta-analysis was used in second stage to combine the province-level estimates. Causes of death, sex, and age groups (<65, 65-79, and >= 80 years) were stratified for subgroup analysis. A total of 177 006 deaths were included. We observed a pattern of effect modification, where the risk of mortality for heat increased on days with higher levels of PM. This pattern was more pronounced for respiratory mortality, with the RRs for heat rising from 1.38 (95%CI: 1.05, 1.82) to 1.81 (95%CI: 1.44, 2.28), as PM2.5 levels increased from 20 mu g m(-3) to 55 mu g m(-3). We found that PM air pollution elevated the heat-related mortality. These results underscore the critical need to address the compounding effects of extreme heat and air pollution in mitigation and adaptation strategies to protect public health.

Social health-our ability to access and maintain meaningful human relationships-is recognized as a critical determinant of population health and climate change resilience, yet it is poorly integrated into climate change policy and research. This narrative Review synthesizes interdisciplinary evidence of the bidirectional and nuanced relationship between climate change and social health: climate change disrupts key social conditions (including housing stability and community cohesion), while widespread social disconnection limits our collective capacity to address the climate crisis. We unpack how social health can function as both a climate vulnerability and a lever for climate action. We present a new conceptual framework, describing the pathways through which social health and climate outcomes interact. Finally, we highlight existing evidence gaps and opportunities for public policy development and call for climate and health governance to centre social health as a key pillar of resilience in a changing world.

PURPOSE:We examined the changes in the risk of heat-associated suicide during the summer in Japan from 1973 to 2020. METHODS:A two-stage time-series analysis was conducted separately for daily maximum, mean, and minimum temperatures to examine the association between heat and suicide. In the first stage, we performed prefecture-specific analyses using a distributed lag non-linear model (DLNM) to estimate the exposure-lag-response association between temperature and suicide mortality and its within-summer variation. In the second stage, we used multivariate meta-regression to combine temperature-suicide associations across 47 prefectures and estimated the relative risks (RRs) for the 90th percentile of temperature compared with the minimum value. RESULTS:A total of 383,115 suicides were included. The RRs of suicide for maximum, mean, and minimum temperatures were 1.23 (95% confidence interval (CI) 1.14-1.31), 1.18 (95% CI 1.10-1.27), and 1.10 (95% CI 1.03-1.17), respectively. When comparing early and late summer, the RRs for maximum temperatures did not differ between the two periods (RR = 1.24 [95% CI = 1.15-1.33] and RR = 1.24 [95% CI = 1.09-1.39], respectively). However, the RR for minimum temperatures was higher in early summer (RR = 1.14 [95% CI = 1.07-1.22]) and lower in late summer (RR = 1.05 [95% CI = 0.94-1.17]). CONCLUSIONS:We found a modest late-summer decline in susceptibility to heat-associated suicide from minimum temperatures, suggesting adaptation to nighttime heat, whereas the risk associated with maximum temperatures, reflecting daytime heat, remained stable across summer.

In environmental epidemiology, the short-term association between temperature and suicide has been examined by analyzing daily time-series data on suicide and temperature collected from multiple locations. A two-stage meta-analytic approach has been conventionally used. A Poisson regression with splines is fitted for each location in the first stage, and location-specific association parameter estimates are pooled, adjusted, and regressed onto location-specific variables using meta-regressions in the second stage. However, several limitations of the conventional two-stage approaches have been reported. First, the Poisson distribution assumption may be inappropriate because the daily number of suicides is often zero. Second, the normal assumption in the second-stage meta-regression is not sufficiently flexible to describe between-location heterogeneity when subgroups exist. Third, the two-stage approach does not properly account for the statistical uncertainty associated with first-stage estimates. In this study, we propose a nonparametric Bayesian Poisson hurdle random effects model to investigate heterogeneity in the temperature–suicide association across multiple locations. The proposed model consists of two parts, binary and positive, with random coefficients specified to describe heterogeneity. Furthermore, random coefficients combined with location-specific indicators were assumed to follow a Dirichlet process mixture of normals to identify the subgroups. The proposed methodology was validated through a simulation study and applied to data from a nationwide temperature–suicide association study in Japan.

Heat-related diseases have become a significant public health concern. Studies have shown that susceptibility to heat varies among regions; however, most studies used aggregated data on emergency transport in the regions. The present study used a nationwide inpatient database in Japan and examined the association between regional differences in Wet Bulb Globe Temperature (WBGT) and in-hospital mortality in patients with a heat-related disease, with adjustment for individual-level characteristics. We retrospectively identified participants from the Japanese Diagnosis Procedure Combination inpatient database during the five warmest months of the year (May 1 to September 30) from 2011 to 2019. We calculated the long-term average daily maximum WBGT for the prefectures and categorized the prefectures into three areas (low-, middle-, and high-WBGT). We conduced multivariable logistic regression analyses to compare in-hospital mortality between the WBGT areas, adjusting for individual-level covariates (including age, sex, body mass index, and comorbidities). A total of 82,250 patients were admitted for heat-related diseases. The mean age was 63.2 (standard deviation, 25.0) years, and 63.7% were male. In the multivariable logistic regression analysis, the low-WBGT area had a higher in-hospital mortality than that had by the high-WBGT area (odds ratio, 1.32; 95% confidence interval, 1.15-1.52), whereas no significant difference was observed between the middle- and high-WBGT areas (odds ratio, 1.00; 95% confidence interval, 0.89-1.12). After adjusting for individual-level risk factors, in-hospital death was more likely to occur in patients with heat-related diseases in lower WBGT areas compared with those in higher WBGT areas.

Background: There is growing recognition of the physical and mental health impacts of climate change and the attendant burden on health care systems, including from the World Health Organisation, the United Nations, and national governments. However, the repercussions on 'social health'— our access to meaningful social connections and the health and quality of these relationships — is largely missing from this discourse. Social health is an important factor underpinning physical and mental health. Moreover, the quality of our social connections determines our collective ability to both adapt to and mitigate climate change, enabling us to navigate and transform our world in a response to this crisis.Methods: In this article, we propose a new framework for understanding the bidirectional relationship between climate change and poor social health. Drawing on a wide review of peer-reviewed literature, this position paper and accompanying framework underscores the importance of social health for surviving and thriving amid climate change and its necessity for effective climate change mitigation and adaptation. Findings: We posit that failure to consider social health in the context of climate policy may undermine global health efforts and climate change action. Interpretation: We highlight the diverse pathways by which climate change affects social (ill)health and provide examples of how social health considerations could be integrated into climate mitigation and adaptation strategies.

Climate change increasingly threatens global health as more frequent extreme heat events, combined with varying humidity levels, exacerbate both direct and indirect health risks, strain energy resources, and lead to economic loss. Vulnerable populations, including the elderly, young children, and those with preexisting health conditions, face greater risks due to lower physiological adaptive capacity. Those from socioeconomically disadvantaged communities are also vulnerable because of increased exposure and reduced capacity. While research has expanded our understanding of the physiological effects of extreme heat and humidity, challenges persist, including inconsistent data, lack of unified heat wave definitions, and limited knowledge of their impact on mortality and morbidity especially in specific populations. Addressing these challenges requires enhanced data and a comprehensive evaluation of humidity's modifying effects. Global collaboration to strengthen heat health action plans is essential, with future efforts focusing on enhancing the accessibility and effectiveness of interventions, especially in underresourced regions.

Suicide is a critical public health issue with rates varying across regions and demographic groups.Recent evidence suggests that ambient temperature may influence suicide risk.This study examines the association between temperature and suicide in Thailand's tropical climate,focusing on Chiang Mai and Bangkok provinces,and quantifies the attributable burden.Daily suicide and meteorological data from 2002 to 2021 were analyzed using a time-stratified case-crossover approach with a distributed lag nonlinear model,adjusted for relative humidity.Province-specific estimates were pooled through a multivariate meta-regression model.The study found a positive,mostly linear association between temperature and suicide risk,with a relative risk(RR)of 1.70(95％CI:1.35,2.15)across the temperature range.Approximately 24.61％of suicides were attributable to temperature,with 12.05％due to hot temperatures above the 66th percentile.The pooled attributable fractions were higher in the 0-64 age group compared to those aged ≥65,while differences between sexes were not statistically significant.This study highlights the significant association between higher ambient temperatures and increased suicide risks in Thailand,emphasizing the need to integrate climate considerations into mental health and suicide prevention policies.Further research across diverse climatic zones is essential for understanding climate influences on mental health globally.