Regional variation in the role of humidity on city-level heat-related mortality.

The rising humid heat is regarded as a severe threat to human survivability, but the proper integration of humid heat into heat-health alerts is still being explored. Using state-of-the-art epidemiological and climatological datasets, we examined the association between multiple heat stress indicators (HSIs) and daily human mortality in 739 cities worldwide. Notable differences were observed in the long-term trends and timing of heat events detected by HSIs. Air temperature (Tair) predicts heat-related mortality well in cities with a robust negative Tair-relative humidity correlation (CT-RH). However, in cities with near-zero or weak positive CT-RH, HSIs considering humidity provide enhanced predictive power compared to Tair. Furthermore, the magnitude and timing of heat-related mortality measured by HSIs could differ largely from those associated with Tair in many cities. Our findings provide important insights into specific regions where humans are vulnerable to humid heat and can facilitate the further enhancement of heat-health alert systems.

Disparities in exposure to concentrated animal feeding operations (CAFOs) and risk of adverse birth outcomes in Pennsylvania, USA.

Background: Previous studies have linked exposure to concentrated animal feeding operations (CAFOs) with various health outcomes. However, relatively few studies evaluated the impacts of CAFOs on adverse birth outcomes, despite significant public health concerns regarding maternal and child health. Objectives: This cross-sectional study investigated the risk of adverse birth outcomes associated with CAFOs exposure and evaluated disparities in exposure to CAFOs and associated health outcomes. Methods: We obtained individual-level birth records from 2003 to 2020 from the Pennsylvania Department of Health. We considered two adverse birth outcomes: (1) preterm birth (PTB); and (2) low birth weight (LBW). Exposure was considered as a binary indicator (presence or absence of CAFO) and as categories based on level of exposure. Logistic regression was applied to estimate the association between CAFOs exposure and adverse birth outcomes. Models were adjusted for infant's sex, maternal demographics (age, race/ethnicity, education), prenatal BMI, prenatal care, smoking status, marital status, plurality, WIC status, and urban/rural indicator. We examined both disparities in exposure and in health response. Results: Presence of CAFOs was associated with higher risk of PTB, with an increasing trend with higher levels of CAFOs exposure. Compared to the no CAFO exposure group, the odds ratios for PTB were 1.022 (95 % confidence interval 1.003, 1.043), 1.066 (1.034, 1.100), 1.069 (1.042, 1.097) for low, medium, and high CAFOs exposure groups, respectively. Some maternal characteristics were associated with a higher CAFO-related risk of PTB. Similar associations were observed for LBW for some characteristics such as mother's race/ethnicity, education, WIC status, and urbanicity, although some findings were not statistically significant. Conclusions: Our findings suggest that presence of CAFOs increases risk of preterm birth. Our results indicate that some maternal characteristics may be associated with higher risk of CAFO-related PTB or LBW. This study can inform future research on disparities in CAFO exposure and associated health burden.

Associations between gestational residential radon exposure and term low birthweight in Connecticut, USA.

BACKGROUND: Studies suggest biologic mechanisms for gestational exposure to radiation and impaired fetal development. We explored associations between gestational radon exposure and term low birthweight, for which evidence is limited. METHODS: We examined data for 68,159 singleton full-term births in Connecticut, USA, 2016-2018. Using a radon spatiotemporal model, we estimated ZIP code-level basement and ground-level exposures during pregnancy and trimesters for each participant's address at birth or delivery. We used logistic regression models, including confounders, to estimate odds ratios (ORs) for term low birth weight in four exposure quartiles (Q1 to Q4) with the lowest exposure group (Q1) as the reference. RESULTS: Exposure levels to basement radon throughout pregnancy (0.27-3.02 pCi/L) were below the guideline level set by the US Environmental Protection Agency (4 pCi/L). The ORs for term low birth weight in the second-highest (Q3; 1.01-1.33 pCi/L) exposure group compared to the reference (<0.79 pCi/L) group for basement radon during the first trimester was 1.22 (95% confidence interval [CI]: 1.02, 1.45). The OR in the highest (Q4; 1.34-4.43 pCi/L) quartile group compared to the reference group during the first trimester was 1.26 (95% CI: 1.05, 1.50). Risks from basement radon were higher for participants with lower income, lower maternal education levels, or living in urban regions. CONCLUSION: This study found increased term low birth weight risks for increases in basement radon. Results have implications for infants' health for exposure to radon at levels below the current national guideline for indoor radon concentrations and building remediations.

All-cause, cardiovascular, and respiratory mortality and wildfire-related ozone: a multicountry two-stage time series analysis.

BACKGROUND: Wildfire activity is an important source of tropospheric ozone (O3) pollution. However, no study to date has systematically examined the associations of wildfire-related O3 exposure with mortality globally. METHODS: We did a multicountry two-stage time series analysis. From the Multi-City Multi-Country (MCC) Collaborative Research Network, data on daily all-cause, cardiovascular, and respiratory deaths were obtained from 749 locations in 43 countries or areas, representing overlapping periods from Jan 1, 2000, to Dec 31, 2016. We estimated the daily concentration of wildfire-related O3 in study locations using a chemical transport model, and then calibrated and downscaled O3 estimates to a resolution of 0·25°â€ˆ× 0·25° (approximately 28 km2 at the equator). Using a random-effects meta-analysis, we examined the associations of short-term wildfire-related O3 exposure (lag period of 0-2 days) with daily mortality, first at the location level and then pooled at the country, regional, and global levels. Annual excess mortality fraction in each location attributable to wildfire-related O3 was calculated with pooled effect estimates and used to obtain excess mortality fractions at country, regional, and global levels. FINDINGS: Between 2000 and 2016, the highest maximum daily wildfire-related O3 concentrations (≥30 µg/m3) were observed in locations in South America, central America, and southeastern Asia, and the country of South Africa. Across all locations, an increase of 1 µg/m3 in the mean daily concentration of wildfire-related O3 during lag 0-2 days was associated with increases of 0·55% (95% CI 0·29 to 0·80) in daily all-cause mortality, 0·44% (-0·10 to 0·99) in daily cardiovascular mortality, and 0·82% (0·18 to 1·47) in daily respiratory mortality. The associations of daily mortality rates with wildfire-related O3 exposure showed substantial geographical heterogeneity at the country and regional levels. Across all locations, estimated annual excess mortality fractions of 0·58% (95% CI 0·31 to 0·85; 31 606 deaths [95% CI 17 038 to 46 027]) for all-cause mortality, 0·41% (-0·10 to 0·91; 5249 [-1244 to 11 620]) for cardiovascular mortality, and 0·86% (0·18 to 1·51; 4657 [999 to 8206]) for respiratory mortality were attributable to short-term exposure to wildfire-related O3. INTERPRETATION: In this study, we observed an increase in all-cause and respiratory mortality associated with short-term wildfire-related O3 exposure. Effective risk and smoke management strategies should be implemented to protect the public from the impacts of wildfires. FUNDING: Australian Research Council and the Australian National Health and Medical Research Council.

A systematic review of animal feeding operations including concentrated animal feeding operations (CAFOs) for exposure, health outcomes, and environmental justice.

BACKGROUND: Despite growing literature on animal feeding operations (AFOs) including concentrated animal feeding operations (CAFOs), research on disproportionate exposure and associated health burden is relatively limited and shows inconclusive findings. OBJECTIVE: We systematically reviewed previous literature on AFOs/CAFOs, focusing on exposure assessment, associated health outcomes, and variables related to environmental justice (EJ) and potentially vulnerable populations. METHODS: We conducted a systematic search of databases (MEDLINE/PubMed and Web of Science) and performed citation screening. Screening of titles, abstracts, and full-text articles and data extraction were performed independently by pairs of reviewers. We summarized information for each study (i.e., study location, study period, study population, study type, study design, statistical methods, and adjusted variables (if health association was examined), and main findings), AFO/CAFO characteristics and exposure assessment (i.e., animal type, data source, measure of exposure, and exposure assessment), health outcomes or symptoms (if health association was examined), and information related to EJ and potentially vulnerable populations (in relation to exposure and/or health associations, vulnerable populations considered, related variables, and main findings in relation to EJ and vulnerable populations). RESULTS: After initial screening of 10,963 papers, we identified 76 eligible studies. This review found that a relatively small number of studies (20 studies) investigated EJ and vulnerability issues related to AFOs/CAFOs exposure and/or associated health outcomes (e.g., respiratory diseases/symptoms, infections). We found differences in findings across studies, populations, the metrics used for AFO/CAFO exposure assessment, and variables related to EJ and vulnerability. The most commonly used metric for AFO/CAFO exposure assessment was presence of or proximity to facilities or animals. The most investigated variables related to disparities were race/ethnicity and socioeconomic status. CONCLUSION: Findings from this review provide suggestive evidence that disparities exist with some subpopulations having higher exposure and/or health response in relation to AFO/CAFO exposure, although results varied across studies.

Air quality modeling in the metropolitan area of São Paulo, Brazil: A review.

Numerous studies have used air quality models to estimate pollutant concentrations in the Metropolitan Area of São Paulo (MASP) by using different inputs and assumptions. Our objectives are to summarize these studies, compare their performance, configurations, and inputs, and recommend areas of further research. We examined 29 air quality modeling studies that focused on ozone (O3) and fine particulate matter (PM2.5) performed over the MASP, published from 2001 to 2023. The California Institute of Technology airshed model (CIT) was the most used offline model, while the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) was the most used online model. Because the main source of air pollution in the MASP is the vehicular fleet, it is commonly used as the only anthropogenic input emissions. Simulation periods were typically the end of winter and during spring, seasons with higher O3 and PM2.5 concentrations. Model performance for hourly ozone is good with half of the studies with Pearson correlation above 0.6 and root mean square error (RMSE) ranging from 7.7 to 27.1 ppb. Fewer studies modeled PM2.5 and their performance is not as good as ozone estimates. Lack of information on emission sources, pollutant measurements, and urban meteorology parameters is the main limitation to perform air quality modeling. Nevertheless, researchers have used measurement campaign data to update emission factors, estimate temporal emission profiles, and estimate volatile organic compounds (VOCs) and aerosol speciation. They also tested different emission spatial disaggregation approaches and transitioned to global meteorological reanalysis with a higher spatial resolution. Areas of research to explore are further evaluation of models' physics and chemical configurations, the impact of climate change on air quality, the use of satellite data, data assimilation techniques, and using model results in health impact studies. This work provides an overview of advancements in air quality modeling within the MASP and offers practical approaches for modeling air quality in other South American cities with limited data, particularly those heavily impacted by vehicle emissions.

Unraveling near real-time spatial dynamics of population using geographical ensemble learning.

Dynamic gridded population data are crucial in fields such as disaster reduction, public health, urban planning, and global change studies. Despite the use of multi-source geospatial data and advanced machine learning models, current frameworks for population spatialization often struggle with spatial non-stationarity, temporal generalizability, and fine temporal resolution. To address these issues, we introduce a framework for dynamic gridded population mapping using open-source geospatial data and machine learning. The framework consists of (i) delineation of human footprint zones, (ii) construction of muliti-scale population prediction models using automated machine learning (AutoML) framework and geographical ensemble learning strategy, and (iii) hierarchical population spatial disaggregation with pycnophylactic constraint-based corrections. Employing this framework, we generated hourly time-series gridded population maps for China in 2016 with a 1-km spatial resolution. The average accuracy evaluated by root mean square deviation (RMSD) is 325, surpassing datasets like LandScan, WorldPop, GPW, and GHSL. The generated seamless maps reveal the temporal dynamic of population distribution at fine spatial scales from hourly to monthly. This framework demonstrates the potential of integrating spatial statistics, machine learning, and geospatial big data in enhancing our understanding of spatio-temporal heterogeneity in population distribution, which is essential for urban planning, environmental management, and public health.

Long-term exposure to PM2.5 and mortality in a national cohort in South Korea: effect modification by community deprivation, medical infrastructure, and greenness.

BACKGROUND: Long-term exposure to PM2.5 has been linked to increased mortality risk. However, limited studies have examined the potential modifying effect of community-level characteristics on this association, particularly in Asian contexts. This study aimed to estimate the effects of long-term exposure to PM2.5 on mortality in South Korea and to examine whether community-level deprivation, medical infrastructure, and greenness modify these associations. METHODS: We conducted a nationwide cohort study using the National Health Insurance Service-National Sample Cohort. A total of 394,701 participants aged 30 years or older in 2006 were followed until 2019. Based on modelled PM2.5 concentrations, 1 to 3-year and 5-year moving averages of PM2.5 concentrations were assigned to each participant at the district level. Time-varying Cox proportional-hazards models were used to estimate the association between PM2.5 and non-accidental, circulatory, and respiratory mortality. We further conducted stratified analysis by community-level deprivation index, medical index, and normalized difference vegetation index to represent greenness. RESULTS: PM2.5 exposure, based on 5-year moving averages, was positively associated with non-accidental (Hazard ratio, HR: 1.10, 95% Confidence Interval, CI: 1.01, 1.20, per 10 µg/m3 increase) and circulatory mortality (HR: 1.22, 95% CI: 1.01, 1.47). The 1-year moving average of PM2.5 was associated with respiratory mortality (HR: 1.33, 95% CI: 1.05, 1.67). We observed higher associations between PM2.5 and mortality in communities with higher deprivation and limited medical infrastructure. Communities with higher greenness showed lower risk for circulatory mortality but higher risk for respiratory mortality in association with PM2.5. CONCLUSIONS: Our study found mortality effects of long-term PM2.5 exposure and underlined the role of community-level factors in modifying these association. These findings highlight the importance of considering socio-environmental contexts in the design of air quality policies to reduce health disparities and enhance overall public health outcomes.

On adjustment for temperature in heatwave epidemiology: a new method and toward clarification of methods to estimate health effects of heatwaves.

Defining the effect of exposure of interest and selecting an appropriate estimation method are prerequisite for causal inference. Understanding the ways in which association between heatwaves (i.e., consecutive days of extreme high temperature) and an outcome depends on whether adjustment was made for temperature and how such adjustment was conducted, is limited. This paper aims to investigate this dependency, demonstrate that temperature is a confounder in heatwave-outcome associations, and introduce a new modeling approach to estimate a new heatwave-outcome relation: E[R(Y)|HW=1, Z]/E[R(Y)|T=OT, Z], where HW is a daily binary variable to indicate the presence of a heatwave; R(Y) is the risk of an outcome, Y; T is a temperature variable; OT is optimal temperature; and Z is a set of confounders including typical confounders but also some types of T as a confounder. We recommend characterization of heatwave-outcome relations and careful selection of modeling approaches to understand the impacts of heatwaves under climate change. We demonstrate our approach using real-world data for Seoul, which suggests that the total effect of heatwaves may be larger than what may be inferred from the extant literature. An R package, HEAT (Heatwave effect Estimation via Adjustment for Temperature), was developed and made publicly available.

Global, regional, and national burden of heatwave-related mortality from 1990 to 2019: A three-stage modelling study.

BACKGROUND: The regional disparity of heatwave-related mortality over a long period has not been sufficiently assessed across the globe, impeding the localisation of adaptation planning and risk management towards climate change. We quantified the global mortality burden associated with heatwaves at a spatial resolution of 0.5°×0.5° and the temporal change from 1990 to 2019. METHODS AND FINDINGS: We collected data on daily deaths and temperature from 750 locations of 43 countries or regions, and 5 meta-predictors in 0.5°×0.5° resolution across the world. Heatwaves were defined as location-specific daily mean temperature ≥95th percentiles of year-round temperature range with duration ≥2 days. We first estimated the location-specific heatwave-mortality association. Secondly, a multivariate meta-regression was fitted between location-specific associations and 5 meta-predictors, which was in the third stage used with grid cell-specific meta-predictors to predict grid cell-specific association. Heatwave-related excess deaths were calculated for each grid and aggregated. During 1990 to 2019, 0.94% (95% CI: 0.68-1.19) of deaths [i.e., 153,078 cases (95% eCI: 109,950-194,227)] per warm season were estimated to be from heatwaves, accounting for 236 (95% eCI: 170-300) deaths per 10 million residents. The ratio between heatwave-related excess deaths and all premature deaths per warm season remained relatively unchanged over the 30 years, while the number of heatwave-related excess deaths per 10 million residents per warm season declined by 7.2% per decade in comparison to the 30-year average. Locations with the highest heatwave-related death ratio and rate were in Southern and Eastern Europe or areas had polar and alpine climates, and/or their residents had high incomes. The temporal change of heatwave-related mortality burden showed geographic disparities, such that locations with tropical climate or low incomes were observed with the greatest decline. The main limitation of this study was the lack of data from certain regions, e.g., Arabian Peninsula and South Asia. CONCLUSIONS: Heatwaves were associated with substantial mortality burden that varied spatiotemporally over the globe in the past 30 years. The findings indicate the potential benefit of governmental actions to enhance health sector adaptation and resilience, accounting for inequalities across communities.

Extreme Temperatures and Stroke Mortality: Evidence From a Multi-Country Analysis.

BACKGROUND: Extreme temperatures contribute significantly to global mortality. While previous studies on temperature and stroke-specific outcomes presented conflicting results, these studies were predominantly limited to single-city or single-country analyses. Their findings are difficult to synthesize due to variations in methodologies and exposure definitions. METHODS: Within the Multi-Country Multi-City Network, we built a new mortality database for ischemic and hemorrhagic stroke. Applying a unified analysis protocol, we conducted a multinational case-crossover study on the relationship between extreme temperatures and stroke. In the first stage, we fitted a conditional quasi-Poisson regression for daily mortality counts with distributed lag nonlinear models for temperature exposure separately for each city. In the second stage, the cumulative risk from each city was pooled using mixed-effect meta-analyses, accounting for clustering of cities with similar features. We compared temperature-stroke associations across country-level gross domestic product per capita. We computed excess deaths in each city that are attributable to the 2.5% hottest and coldest of days based on each city's temperature distribution. RESULTS: We collected data for a total of 3 443 969 ischemic strokes and 2 454 267 hemorrhagic stroke deaths from 522 cities in 25 countries. For every 1000 ischemic stroke deaths, we found that extreme cold and hot days contributed 9.1 (95% empirical CI, 8.6-9.4) and 2.2 (95% empirical CI, 1.9-2.4) excess deaths, respectively. For every 1000 hemorrhagic stroke deaths, extreme cold and hot days contributed 11.2 (95% empirical CI, 10.9-11.4) and 0.7 (95% empirical CI, 0.5-0.8) excess deaths, respectively. We found that countries with low gross domestic product per capita were at higher risk of heat-related hemorrhagic stroke mortality than countries with high gross domestic product per capita (P=0.02). CONCLUSIONS: Both extreme cold and hot temperatures are associated with an increased risk of dying from ischemic and hemorrhagic strokes. As climate change continues to exacerbate these extreme temperatures, interventional strategies are needed to mitigate impacts on stroke mortality, particularly in low-income countries.

Association between heat and hospital admissions in people with disabilities in South Korea: a nationwide, case-crossover study.

BACKGROUND: Despite extensive findings on the hazardous impacts of environmental heat exposure, little is known about the effect on people with disabilities. This study aimed to estimate the association between environmental heat exposure and emergency department admissions for people with disabilities compared with people without disabilities. METHODS: In this nationwide, case-crossover study, we linked data on emergency department admissions (cases) for any cause in the warm season in South Korea from the Korean National Health Insurance Service (NHIS)-National Sample Cohort database (a nationally representative database of 1 million systematically sampled beneficiaries covering all ages) from Jan 1, 2002, to Dec 31, 2019, and short-term daily mean temperature exposure (measured via Google Earth Engine at a 9 km spatial grid, aggregated to district). We defined beneficiaries with disabilities as those who were registered as disabled in the NHIS; disabilities included in our study were physical disability, brain lesion disorders, blindness or vision loss, and deafness or hearing loss. Other types of disability were not included for confidentiality reasons. A time-stratified case-crossover design, in which participants served as their own control, was used with conditional logistic regression to estimate the association between heat and emergency department admissions in people with and without disabilities. FINDINGS: 23 792 emergency department admissions were recorded for 59 527 people with disabilities. Of these 23 792 admissions, 10 234 (43·0%) individuals were female and 13 558 (57·0%) were male. The odds ratio (OR) of emergency department admissions associated with heat (99th temperature percentile vs 75th percentile) was 1·15 (95% CI 1·07-1·24) in people with disabilities and 1·06 (1·04-1·09) in people without disabilities. The annual excess number of emergency department admissions attributable to heat per 100 000 persons-years was 27·81 admissions (95% CI 9·20-45·69) and excess medical costs were US$638 739·47 (95% CI 201 900·12-1 059 641·87) in people with disabilities; these values were more than four times that of the non-disabled population. People with brain lesion disorders, people with severe physical disabilities, female individuals, and those aged 65 years or older showed higher heat risks. The risks of emergency department admissions due to mental disorder (1·89, 95% CI 1·18-3·00) and respiratory diseases (1·34, 1·06-1·70) also showed higher heat risks than for the other two analysed causes of admission (cardiovascular and genitourinary diseases). INTERPRETATION: Heat was associated with increased risk of emergency department admissions for people with and without disabilities, but the risk appeared to be higher for those with disabilities. These results can inform policy makers when establishing action plans for people with disabilities. FUNDING: National Research Foundation of Korea, the South Korean Ministry of Environment, and the South Korean Ministry of Education.

Heat and hospital admission via the emergency department for people with intellectual disability, autism, and mental disorders in South Korea: a nationwide, time-stratified, case-crossover study.

BACKGROUND: Given the anticipated increase in ambient temperature due to climate change, the hazardous effects of heat on health have been extensively studied; however, its impact on people with intellectual disability, autism, and mental illness is largely unknown. We aimed to estimate the association between heat and hospitalisation through the emergency department (ED) among people with these mental disorders. METHODS: In this nationwide study, we used data from the National Health Insurance Database (NHID) of the National Health Insurance Service, the single universal insurer in South Korea, the claims data for which is based on the ICD-10. We included individuals with identified intellectual disability, autism, and mental disorders (including schizophrenia, bipolar disorder, recurrent depressive disorder, schizoaffective disorder and persistent obsessive-compulsive disorder, Tourette's disorder, and narcolepsy) and we established two control groups of people without these disorders: one including 1 million systematically sampled individuals, and one matched to the cohort based on sex, age, and income group. Data on hospital admission via the ED were obtained from the NHID, including the primary cause of admission and corresponding medical costs, for the warm season (June-September) of the period 2006-2021. We used the Google Earth Engine with the ERA5-Land dataset to collect data on the daily mean temperature. We applied a time-stratified case-crossover design using a distributed lag non-linear model and performed a conditional logistic regression. The risk ratio was estimated as the odds ratio (OR) with calculated odds at the 99th percentile temperature compared with that at the local 75th percentile temperature. We did not include people with lived experience of mental illness in this study. FINDINGS: Of the 456 946 people with intellectual disability, autism, or mental disorder in the NHID records, 99 845 were admitted to the ED, including 59 821 (59·9%) males and 40 024 (40·1%) females, and including 29 192 people with intellectual disability, 1428 people with autism, and 69 225 people with mental disorders. We were not able to collect data on ethnicity. The mean age at ED admission was 42·1 years (SD 17·9, range 0-102) for people with intellectual disability, 18·6 years (SD 10·4, range 1-72) for people with autism, and 50·8 years (SD 11·9, range 2-94) for people with mental disorders. The heat OR (odds at the 99th percentile vs 75th percentile of temperature) of ED admission was 1·23 (95% CI 1·11-1·36) for intellectual disability, 1·06 (0·68-1·63) for autism, and 1·20 (1·12-1·29) for mental disorders. People with intellectual disability, female individuals, people living in rural areas, or those with a low-income status were at increased risk of ED admission due to heat. The risk of ED admission due to genitourinary diseases was higher than that from other causes. Annual increase in medical costs attributable to heat among people with intellectual disability, autism, and mental disorders was US$ 224 970 per 100 000 person-years (95% empirical CI 139 784-305 770). INTERPRETATION: People with intellectual disability, autism, and mental disorders should be included in groups considered at a high-risk for heat exposure, and heat adaptation policies should be implemented with consideration of these groups and their needs. FUNDING: The National Research Foundation of Korea, Korean Ministry of Environment, and Korean Ministry of Education. TRANSLATION: For the Korean translation of the abstract see Supplementary Materials section.

Estimates of global mortality burden associated with short-term exposure to fine particulate matter (PM2·5).

BACKGROUND: The acute health effects of short-term (hours to days) exposure to fine particulate matter (PM2·5) have been well documented; however, the global mortality burden attributable to this exposure has not been estimated. We aimed to estimate the global, regional, and urban mortality burden associated with short-term exposure to PM2·5 and the spatiotemporal variations in this burden from 2000 to 2019. METHODS: We combined estimated global daily PM2·5 concentrations, annual population counts, country-level mortality rates, and epidemiologically derived exposure-response functions to estimate the mortality attributable to short-term PM2·5 exposure from 2000 to 2019, in the continental regions and in 13 189 urban centres worldwide at a spatial resolution of 0·1°â€ˆ× 0·1°. We tested the robustness of our mortality estimates with different theoretical minimum risk exposure levels, lag effects, and exposure-response functions. FINDINGS: Approximately 1 million (95% CI 690 000-1·3 million) premature deaths per year from 2000 to 2019 were attributable to short-term PM2·5 exposure, representing 2·08% (1·41-2·75) of total global deaths or 17 (11-22) premature deaths per 100 000 population. Annually, 0·23 million (0·15 million-0·30 million) deaths attributable to short-term PM2·5 exposure were in urban areas, constituting 22·74% of the total global deaths attributable to this cause and accounting for 2·30% (1·56-3·05) of total global deaths in urban areas. The sensitivity analyses showed that our worldwide estimates of mortality attributed to short-term PM2·5 exposure were robust. INTERPRETATION: Short-term exposure to PM2·5 contributes a substantial global mortality burden, particularly in Asia and Africa, as well as in global urban areas. Our results highlight the importance of mitigation strategies to reduce short-term exposure to air pollution and its adverse effects on human health. FUNDING: Australian Research Council and the Australian National Health and Medical Research Council.

Accuracy of self-reported distance to nearest unconventional oil and gas well in Pennsylvania, Ohio, and West Virginia residents and implications for exposure assessment.

Self-reported distances to industrial sources have been used in epidemiology as proxies for exposure to environmental hazards and indicators of awareness and perception of sources. Unconventional oil and gas development (UOG) emits pollutants and has been associated with adverse health outcomes. We compared self-reported distance to the nearest UOG well to the geographic information system-calculated distance for 303 Pennsylvania, Ohio, and West Virginia residents using Cohen's Weighted Kappa. Agreement was low (Kappa = 0.18), and self-reports by Ohioans (39% accuracy) were more accurate than West Virginians (22%) or Pennsylvanians (13%, both p < 0.05). Of the demographic characteristics studied, only educational attainment was related to reporting accuracy; residents with 12-16 years of education were more accurate (31.3% of group) than those with <12 or >16 years (both 16.7%). Understanding differences between objective and subjective measures of UOG proximity could inform studies of perceived exposures or risks and may also be relevant to adverse health effects. IMPACT: We compared objective and self-reported measures of distance to the nearest UOG well for 303 Appalachian Basin residents. We found that residents' self-reported distance to the nearest UOG well had limited agreement with the true calculated distance category. Our results can be used to inform the collection and contextualize the use of self-reported data in communities exposed to UOGD. Self-reported metrics can be used in conjunction with objective assessments and can be informative regarding how potentially exposed populations perceive environmental exposures or risks and could provide insights into awareness of distance-related policies, such as setbacks.

Seasonality of mortality under climate change: a multicountry projection study.

BACKGROUND: Climate change can directly impact temperature-related excess deaths and might subsequently change the seasonal variation in mortality. In this study, we aimed to provide a systematic and comprehensive assessment of potential future changes in the seasonal variation, or seasonality, of mortality across different climate zones. METHODS: In this modelling study, we collected daily time series of mean temperature and mortality (all causes or non-external causes only) via the Multi-Country Multi-City Collaborative (MCC) Research Network. These data were collected during overlapping periods, spanning from Jan 1, 1969 to Dec 31, 2020. We projected daily mortality from Jan 1, 2000 to Dec 31, 2099, under four climate change scenarios corresponding to increasing emissions (Shared Socioeconomic Pathways [SSP] scenarios SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). We compared the seasonality in projected mortality between decades by its shape, timings (the day-of-year) of minimum (trough) and maximum (peak) mortality, and sizes (peak-to-trough ratio and attributable fraction). Attributable fraction was used to measure the burden of seasonality of mortality. The results were summarised by climate zones. FINDINGS: The MCC dataset included 126 809 537 deaths from 707 locations within 43 countries or areas. After excluding the only two polar locations (both high-altitude locations in Peru) from climatic zone assessments, we analysed 126 766 164 deaths in 705 locations aggregated in four climate zones (tropical, arid, temperate, and continental). From the 2000s to the 2090s, our projections showed an increase in mortality during the warm seasons and a decrease in mortality during the cold seasons, albeit with mortality remaining high during the cold seasons, under all four SSP scenarios in the arid, temperate, and continental zones. The magnitude of this changing pattern was more pronounced under the high-emission scenarios (SSP3-7.0 and SSP5-8.5), substantially altering the shape of seasonality of mortality and, under the highest emission scenario (SSP5-8.5), shifting the mortality peak from cold seasons to warm seasons in arid, temperate, and continental zones, and increasing the size of seasonality in all zones except the arid zone by the end of the century. In the 2090s compared with the 2000s, the change in peak-to-trough ratio (relative scale) ranged from 0·96 to 1·11, and the change in attributable fraction ranged from 0·002% to 0·06% under the SSP5-8.5 (highest emission) scenario. INTERPRETATION: A warming climate can substantially change the seasonality of mortality in the future. Our projections suggest that health-care systems should consider preparing for a potentially increased demand during warm seasons and sustained high demand during cold seasons, particularly in regions characterised by arid, temperate, and continental climates. FUNDING: The Environment Research and Technology Development Fund of the Environmental Restoration and Conservation Agency, provided by the Ministry of the Environment of Japan.

Ozone-related acute excess mortality projected to increase in the absence of climate and air quality controls consistent with the Paris Agreement.

Short-term exposure to ground-level ozone in cities is associated with increased mortality and is expected to worsen with climate and emission changes. However, no study has yet comprehensively assessed future ozone-related acute mortality across diverse geographic areas, various climate scenarios, and using CMIP6 multi-model ensembles, limiting our knowledge on future changes in global ozone-related acute mortality and our ability to design targeted health policies. Here, we combine CMIP6 simulations and epidemiological data from 406 cities in 20 countries or regions. We find that ozone-related deaths in 406 cities will increase by 45 to 6,200 deaths/year between 2010 and 2014 and between 2050 and 2054, with attributable fractions increasing in all climate scenarios (from 0.17% to 0.22% total deaths), except the single scenario consistent with the Paris Climate Agreement (declines from 0.17% to 0.15% total deaths). These findings stress the need for more stringent air quality regulations, as current standards in many countries are inadequate.

A nationwide time-series analysis for short-term effects of ambient temperature on violent crime in South Korea.

Psychological theories on heat-aggression relationship have existed for decades and recent models suggest climate change will increase violence through varying pathways. Although observational studies have examined the impact of temperature on violent crime, the evidence for associations is primarily limited to coarse temporal resolution of weather and crime (e.g., yearly/monthly) and results from a few Western communities, warranting studies based on higher temporal resolution data of modern systemic crime statistics for various regions. This observational study examined short-term temperature impacts on violent crime using national crime data for the warm months (Jun.-Sep.) across South Korea (2016-2020). Distributed lag non-linear models assessed relative risks (RRs) of daily violent crime counts at the 70th, 90th, and 99th summer temperature percentiles compared to the reference temperature (10th percentile), with adjustments for long-term trends, seasonality, weather, and air pollution. Results indicate potentially non-linear relationships between daily summer temperature (lag0-lag10) and violent crime counts. Violent crimes consistently increased from the lowest temperature and showed the highest risk at the 70th temperature (~ 28.0 °C). The RR at the 70th and 90th percentiles of daily mean temperature (lag0-lag10), compared to the reference, was 1.11 (95% CI 1.09, 1.15) and 1.04 (95% CI 1.01, 1.07), indicating significant associations. Stratified analysis showed significant increases in assault and domestic violence for increases in temperature. The lagged effects, the influences of heat on subsequent crime incidence, did not persist 21 days after the exposure, possibly due to the displacement phenomenon. We found curvilinear exposure-response relationships, which provide empirical evidence to support the psychological theories for heat and violence. Lower public safety through increased violent crime may be an additional public health harm of climate change.

Impact of green space and built environment on metabolic syndrome: A systematic review with meta-analysis.

Metabolic Syndrome presents a significant public health challenge associated with an increased risk of noncommunicable diseases such as cardiovascular conditions. Evidence shows that green spaces and the built environment may influence metabolic syndrome. We conducted a systematic review and meta-analysis of observational studies published through August 30, 2023, examining the association of green space and built environment with metabolic syndrome. A quality assessment of the included studies was conducted using the Office of Health Assessment and Translation (OHAT) tool. The Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) assessment was used to evaluate the overall quality of evidence. Our search retrieved 18 studies that met the inclusion criteria and were included in our review. Most were from China (n = 5) and the USA (n = 5), and most used a cross-sectional study design (n = 8). Nine studies (50 %) reported only green space exposures, seven (39 %) reported only built environment exposures, and two (11 %) reported both built environment and green space exposures. Studies reported diverse definitions of green space and the built environment, such as availability, accessibility, and quality, particularly around participants' homes. The outcomes focused on metabolic syndrome; however, studies applied different definitions of metabolic syndrome. Meta-analysis results showed that an increase in normalized difference vegetation index (NDVI) within a 500-m buffer was associated with a lower risk of metabolic syndrome (odds ratio [OR] = 0.90, 95%CI = 0.87-0.93, I2 = 22.3 %, n = 4). A substantial number of studies detected bias for exposure classification and residual confounding. Overall, the extant literature shows a 'limited' strength of evidence for green space protecting against metabolic syndrome and an 'inadequate' strength of evidence for the built environment associated with metabolic syndrome. Studies with more robust study designs, better controlled confounding factors, and stronger exposure measures are needed to understand better what types of green spaces and built environment features influence metabolic syndrome.