Global population exposure to landscape fire air pollution from 2000 to 2019.

Wildfires are thought to be increasing in severity and frequency as a result of climate change1-5. Air pollution from landscape fires can negatively affect human health4-6, but human exposure to landscape fire-sourced (LFS) air pollution has not been well characterized at the global scale7-23. Here, we estimate global daily LFS outdoor fine particulate matter (PM2.5) and surface ozone concentrations at 0.25° × 0.25° resolution during the period 2000-2019 with the help of machine learning and chemical transport models. We found that overall population-weighted average LFS PM2.5 and ozone concentrations were 2.5 µg m-3 (6.1% of all-source PM2.5) and 3.2 µg m-3 (3.6% of all-source ozone), respectively, in 2010-2019, with a slight increase for PM2.5, but not for ozone, compared with 2000-2009. Central Africa, Southeast Asia, South America and Siberia experienced the highest LFS PM2.5 and ozone concentrations. The concentrations of LFS PM2.5 and ozone were about four times higher in low-income countries than in high-income countries. During the period 2010-2019, 2.18 billion people were exposed to at least 1 day of substantial LFS air pollution per year, with each person in the world having, on average, 9.9 days of exposure per year. These two metrics increased by 6.8% and 2.1%, respectively, compared with 2000-2009. Overall, we find that the global population is increasingly exposed to LFS air pollution, with socioeconomic disparities.

Associations Between Extreme Temperatures and Cardiovascular Cause-Specific Mortality: Results From 27 Countries.

BACKGROUND: Cardiovascular disease is the leading cause of death worldwide. Existing studies on the association between temperatures and cardiovascular deaths have been limited in geographic zones and have generally considered associations with total cardiovascular deaths rather than cause-specific cardiovascular deaths. METHODS: We used unified data collection protocols within the Multi-Country Multi-City Collaborative Network to assemble a database of daily counts of specific cardiovascular causes of death from 567 cities in 27 countries across 5 continents in overlapping periods ranging from 1979 to 2019. City-specific daily ambient temperatures were obtained from weather stations and climate reanalysis models. To investigate cardiovascular mortality associations with extreme hot and cold temperatures, we fit case-crossover models in each city and then used a mixed-effects meta-analytic framework to pool individual city estimates. Extreme temperature percentiles were compared with the minimum mortality temperature in each location. Excess deaths were calculated for a range of extreme temperature days. RESULTS: The analyses included deaths from any cardiovascular cause (32 154 935), ischemic heart disease (11 745 880), stroke (9 351 312), heart failure (3 673 723), and arrhythmia (670 859). At extreme temperature percentiles, heat (99th percentile) and cold (1st percentile) were associated with higher risk of dying from any cardiovascular cause, ischemic heart disease, stroke, and heart failure as compared to the minimum mortality temperature, which is the temperature associated with least mortality. Across a range of extreme temperatures, hot days (above 97.5th percentile) and cold days (below 2.5th percentile) accounted for 2.2 (95% empirical CI [eCI], 2.1-2.3) and 9.1 (95% eCI, 8.9-9.2) excess deaths for every 1000 cardiovascular deaths, respectively. Heart failure was associated with the highest excess deaths proportion from extreme hot and cold days with 2.6 (95% eCI, 2.4-2.8) and 12.8 (95% eCI, 12.2-13.1) for every 1000 heart failure deaths, respectively. CONCLUSIONS: Across a large, multinational sample, exposure to extreme hot and cold temperatures was associated with a greater risk of mortality from multiple common cardiovascular conditions. The intersections between extreme temperatures and cardiovascular health need to be thoroughly characterized in the present day-and especially under a changing climate.

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.

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.

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.

Wildfire smoke exposure during pregnancy and perinatal, obstetric, and early childhood health outcomes: A systematic review and meta-analysis.

BACKGROUND: Maternal exposure to air pollution during pregnancy is associated with adverse birth outcomes, although less is known for wildfire smoke. This systematic review evaluated the association between maternal exposure to wildfire smoke during pregnancy and the risk of perinatal, obstetric, and early childhood health outcomes. METHODS: We searched CINAHL Complete, Ovid/EMBASE, Ovid/MEDLINE, ProQuest, PubMed, Scopus, Web of Science, and Google Scholar to identify relevant epidemiological observational studies indexed through September 2023. The screening of titles, abstracts, and full-texts, data extraction, and risk of bias assessment was performed by pairs of independent reviewers. RESULTS: Our systematic search yielded 28,549 records. After duplicate removal, we screened 14,009 studies, identifying 31 for inclusion in the present review. Data extraction highlighted high methodological heterogeneity between studies, including a lack of geographic variation. Approximately 56.5% and 16% originated in the United States and Brazil, respectively, and fewer in other countries. Among the studies, wildfire smoke exposure during pregnancy was assessed using distance of residence from wildfire-affected areas (n = 15), measurement of air pollutant concentration during wildfires (n = 11), number of wildfire records (n = 3), aerosol index (n = 1), and geographic hot spots (n = 1). Pooled meta-analysis for birthweight and low birthweight were inconclusive, likely due to low number of methodologically homogenous studies. However, the reviewed studies provided suggestive evidence for an increased risk of birthweight reduction, low birthweight, preterm birth, and other adverse health outcomes. CONCLUSIONS: This review identified 31 studies evaluating the impacts of maternal wildfire smoke exposure on maternal, infant, and child health. Although we found suggestive evidence of harm from exposure to wildfire smoke during pregnancy, more methodologically homogenous studies are required to enable future meta-analysis with greater statistical power to more accurately evaluate the association between maternal wildfire smoke and adverse birth outcomes and other health outcomes.

Is residential exposure to oil refineries a novel contextual risk factor for coronary heart disease?

Despite a multi-decade decrease in cardiovascular disease, geographic disparities have widened, with excess mortality concentrated within the United States (U.S.) South. Petroleum production and refining, a major contributor to climate change, is concentrated within the U.S. South and emits multiple classes of atherogenic pollutants. We investigated whether residential exposure to oil refineries could explain variation in self-reported coronary heart disease (CHD) prevalence among adults in southern states for the year 2018, where the majority of oil refinery activity occurs (Alabama, Mississippi, Louisiana, Arkansas, Texas, New Mexico, and Oklahoma). We examined census tract-level association between oil refineries and CHD prevalence. We used a double matching method to adjust for measured and unmeasured spatial confounders: one-to-n distance matching and one-to-one generalized propensity score matching. Exposure metrics were constructed based on proximity to refineries, activities of refineries, and wind speed/direction. For all census tracts within 10 km of refineries, self-reported CHD prevalence ranged from 1.2% to 17.6%. Compared to census tracts located at ≥5 km and <10 km, one standard deviation increase in the exposure within 5 km of refineries was associated with a 0.33 (95% confidence interval: 0.04, 0.63) percentage point increase in the prevalence. A total of 1119.0 (123.5, 2114.2) prevalent cases or 1.6% (0.2, 3.1) of CHD prevalence in areas within 5 km from refineries were potentially explained by exposure to oil refineries. At the census tract-level, the prevalence of CHD explained by exposure to oil refineries ranged from 0.02% (0.00, 0.05) to 47.4% (5.2, 89.5). Thus, although we cannot rule out potential confounding by other personal risk factors, CHD prevalence was found to be higher in populations living nearer to oil refineries, which may suggest that exposure to oil refineries can increase CHD risk, warranting further investigation.

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.

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.

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.

Hourly Air Pollutants and Acute Coronary Syndrome Onset in 1.29 Million Patients.

BACKGROUND: Short-term exposure to ambient air pollution has been linked with daily hospitalization and mortality from acute coronary syndrome (ACS); however, the associations of subdaily (hourly) levels of criteria air pollutants with the onset of ACS and its subtypes have rarely been evaluated. METHODS: We conducted a time-stratified case-crossover study among 1 292 880 patients with ACS from 2239 hospitals in 318 Chinese cities between January 1, 2015, and September 30, 2020. Hourly concentrations of fine particulate matter (PM2.5), coarse particulate matter (PM2.5-10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3) were collected. Hourly onset data of ACS and its subtypes, including ST-segment-elevation myocardial infarction, non-ST-segment-elevation myocardial infarction, and unstable angina, were also obtained. Conditional logistic regressions combined with polynomial distributed lag models were applied. RESULTS: Acute exposures to PM2.5, NO2, SO2, and CO were each associated with the onset of ACS and its subtypes. These associations were strongest in the concurrent hour of exposure and were attenuated thereafter, with the weakest effects observed after 15 to 29 hours. There were no apparent thresholds in the concentration-response curves. An interquartile range increase in concentrations of PM2.5 (36.0 µg/m3), NO2 (29.0 µg/m3), SO2 (9.0 µg/m3), and CO (0.6 mg/m3) over the 0 to 24 hours before onset was significantly associated with 1.32%, 3.89%, 0.67%, and 1.55% higher risks of ACS onset, respectively. For a given pollutant, the associations were comparable in magnitude across different subtypes of ACS. NO2 showed the strongest associations with all 3 subtypes, followed by PM2.5, CO, and SO2. Greater magnitude of associations was observed among patients older than 65 years and in the cold season. Null associations of exposure to either PM2.5-10 or O3 with ACS onset were observed. CONCLUSIONS: The results suggest that transient exposure to the air pollutants PM2.5, NO2, SO2, or CO, but not PM2.5-10 or O3, may trigger the onset of ACS, even at concentrations below the World Health Organization air quality guidelines.

Drought and ozone air quality in California: Identifying susceptible regions in the preparedness of future drought.

California experienced extreme and prolonged drought conditions during the early 2010s. To date, little is known regarding the influence of drought on air quality. Our study quantified site-specific associations between drought (defined by the Standardized Precipitation-Evapotranspiration Index; SPEI) and daily maximum 8-h ozone (O3) concentrations for California, USA, and then pooled these associations for the years 2009-2015. Overall, ambient O3 concentration was higher during droughts by 1.18 ppb (95% confidence interval (CI) = 1.00-1.36). The sensitivity of O3 to drought was greater during the warm season than during the cool season (1.73 ppb versus 0.79 ppb higher O3 during droughts) with substantial regional variation. In a pooled analysis with meteorological parameters as potential effect modifiers, the spatial heterogeneity of drought-O3 associations was explained strongly by average relative humidity for each season (71.9% (warm season) and 73.4% (cool season) of the drought-O3 associations explained), followed by the drought-related changes in relative humidity (47.6% (warm season)) and temperature (53.6% (cool season)). The pooled regression further identified regions susceptible for drought-related O3 increases as those with relatively low average relative humidity (10-25th percentiles or 44.3-47.3%) and larger drought-related decrease in relative humidity and increase in temperature. As the drought events are projected to occur with increased frequency and intensity in the era of climate change, the excess health burdens from O3 exposures attributed to the projected drought events need to be taken into account when allocating air quality and health resources. The impacts of O3 on health during droughts would confound the health burdens from the drought itself.

Exposures to ambient particulate matter are associated with reduced adult earnings potential.

The societal costs of air pollution have historically been measured in terms of premature deaths (including the corresponding values of statistical lives lost), disability-adjusted life years, and medical costs. Emerging research, however, demonstrated potential impacts of air pollution on human capital formation. Extended contact with pollutants such as airborne particulate matter among young persons whose biological systems are still developing can result in pulmonary, neurobehavioral, and birth complications, hindering academic performance as well as skills and knowledge acquisition. Using a dataset that tracks 2014-2015 incomes for 96.2% of Americans born between 1979 and 1983, we assessed the association between childhood exposure to fine particulate matter (PM2.5) and adult earnings outcomes across U.S. Census tracts. After accounting for pertinent economic covariates and regional random effects, our regression models indicate that early-life exposure to PM2.5 is associated with lower predicted income percentiles by mid-adulthood; all else equal, children raised in high pollution tracts (at the 75th percentile of PM2.5) are estimated to have approximately a 0.51 decrease in income percentile relative to children raised in low pollution tracts (at the 25th percentile of PM2.5). For a person earning the median income, this difference corresponds to a $436 lower annual income (in 2015 USD). We estimate that 2014-2015 earnings for the 1978-1983 birth cohort would have been ∼$7.18 billion higher had their childhood exposure met U.S. air quality standards for PM2.5. Stratified models show that the relationship between PM2.5 and diminished earnings is more pronounced for low-income children and for children living in rural environments. These findings raise concerns about long-term environmental and economic justice for children living in areas with poor air quality where air pollution could act as a barrier to intergenerational class equity.

Hospital admission risks and excess costs for neurological symptoms attributable to long-term exposure to fine particulate matter in New York State, USA.

BACKGROUND: Although emerging evidence suggests that PM2.5 is linked to neurological symptoms (NSs) via neuroinflammation, relevant studies are scarce. This study aimed to investigate the risks and excess costs of hospital admission for five NSs-fatigue, headache, dizziness, convulsion, and paralysis-attributable to long-term exposure to PM2.5 in New York State, USA. METHODS: We analyzed the New York Statewide Planning and Research Cooperative System (SPARCS) from 2010 to 2016. A Bayesian hierarchical model with integrated nested Laplace approximations was performed to estimate the risks and excess costs of hospital admission for NSs due to long-term exposure to PM2.5 at the county level. RESULTS: A 1 µg/m3 increase in lag 0-1 years PM2.5 was associated with an increased risk of headache and convulsion by 1.06 (1.01, 1.11) and 1.04 (1.01, 1.06), respectively. The excess hospital admission cost for five NSs attributable to lag 0-1 years PM2.5 above the new World Health Organization guideline (annual standard: 5 µg/m3) was $200.24 (95% CI: 6.00, 376.96) million during 2011-2016, recording the highest for convulsion ($153.73 [95% CI: 63.61, 244.19] million). CONCLUSIONS: This study provides quantitative estimates of risks and excess costs for NSs attributable to long-term PM2.5 and suggests that policies that reduce long-term PM2.5 concentration in accordance with the new WHO air quality guidelines can yield substantial health and economic benefits related to NSs in the New York State population.

Coarse Particulate Air Pollution and Daily Mortality: A Global Study in 205 Cities.

Rationale: The associations between ambient coarse particulate matter (PM2.5-10) and daily mortality are not fully understood on a global scale. Objectives: To evaluate the short-term associations between PM2.5-10 and total, cardiovascular, and respiratory mortality across multiple countries/regions worldwide. Methods: We collected daily mortality (total, cardiovascular, and respiratory) and air pollution data from 205 cities in 20 countries/regions. Concentrations of PM2.5-10 were computed as the difference between inhalable and fine PM. A two-stage time-series analytic approach was applied, with overdispersed generalized linear models and multilevel meta-analysis. We fitted two-pollutant models to test the independent effect of PM2.5-10 from copollutants (fine PM, nitrogen dioxide, sulfur dioxide, ozone, and carbon monoxide). Exposure-response relationship curves were pooled, and regional analyses were conducted. Measurements and Main Results: A 10 µg/m3 increase in PM2.5-10 concentration on lag 0-1 day was associated with increments of 0.51% (95% confidence interval [CI], 0.18%-0.84%), 0.43% (95% CI, 0.15%-0.71%), and 0.41% (95% CI, 0.06%-0.77%) in total, cardiovascular, and respiratory mortality, respectively. The associations varied by country and region. These associations were robust to adjustment by all copollutants in two-pollutant models, especially for PM2.5. The exposure-response curves for total, cardiovascular, and respiratory mortality were positive, with steeper slopes at lower exposure ranges and without discernible thresholds. Conclusions: This study provides novel global evidence on the robust and independent associations between short-term exposure to ambient PM2.5-10 and total, cardiovascular, and respiratory mortality, suggesting the need to establish a unique guideline or regulatory limit for daily concentrations of PM2.5-10.

Where Is Air Quality Improving, and Who Benefits? A Study of PM2.5 and Ozone Over 15 Years.

In the United States, concentrations of criteria air pollutants have declined in recent decades. Questions remain regarding whether improvements in air quality are equitably distributed across subpopulations. We assessed spatial variability and temporal trends in concentrations of particulate matter with an aerodynamic diameter ≤2.5 µm (PM2.5) and ozone (O3) across North Carolina from 2002-2016, and associations with community characteristics. Estimated daily PM2.5 and O3 concentrations at 2010 Census tracts were obtained from the Fused Air Quality Surface Using Downscaling archive and averaged to create tract-level annual PM2.5 and O3 estimates. We calculated tract-level measures of: racial isolation of non-Hispanic Black individuals, educational isolation of non-college educated individuals, the neighborhood deprivation index (NDI), and percentage of the population in urban areas. We fitted hierarchical Bayesian space-time models to estimate baseline concentrations of and time trends in PM2.5 and O3 for each tract, accounting for spatial between-tract correlation. Concentrations of PM2.5 and O3 declined by 6.4 µg/m3 and 13.5 ppb, respectively. Tracts with lower educational isolation and higher urbanicity had higher PM2.5 and more pronounced declines in PM2.5. Racial isolation was associated with higher PM2.5 but not with the rate of decline in PM2.5. Despite declines in pollutant concentrations, over time, disparities in exposure increased for racially and educationally isolated communities.

Ambient Particulate Air Pollution and Daily Mortality in 652 Cities.

BACKGROUND: The systematic evaluation of the results of time-series studies of air pollution is challenged by differences in model specification and publication bias. METHODS: We evaluated the associations of inhalable particulate matter (PM) with an aerodynamic diameter of 10 µm or less (PM10) and fine PM with an aerodynamic diameter of 2.5 µm or less (PM2.5) with daily all-cause, cardiovascular, and respiratory mortality across multiple countries or regions. Daily data on mortality and air pollution were collected from 652 cities in 24 countries or regions. We used overdispersed generalized additive models with random-effects meta-analysis to investigate the associations. Two-pollutant models were fitted to test the robustness of the associations. Concentration-response curves from each city were pooled to allow global estimates to be derived. RESULTS: On average, an increase of 10 µg per cubic meter in the 2-day moving average of PM10 concentration, which represents the average over the current and previous day, was associated with increases of 0.44% (95% confidence interval [CI], 0.39 to 0.50) in daily all-cause mortality, 0.36% (95% CI, 0.30 to 0.43) in daily cardiovascular mortality, and 0.47% (95% CI, 0.35 to 0.58) in daily respiratory mortality. The corresponding increases in daily mortality for the same change in PM2.5 concentration were 0.68% (95% CI, 0.59 to 0.77), 0.55% (95% CI, 0.45 to 0.66), and 0.74% (95% CI, 0.53 to 0.95). These associations remained significant after adjustment for gaseous pollutants. Associations were stronger in locations with lower annual mean PM concentrations and higher annual mean temperatures. The pooled concentration-response curves showed a consistent increase in daily mortality with increasing PM concentration, with steeper slopes at lower PM concentrations. CONCLUSIONS: Our data show independent associations between short-term exposure to PM10 and PM2.5 and daily all-cause, cardiovascular, and respiratory mortality in more than 600 cities across the globe. These data reinforce the evidence of a link between mortality and PM concentration established in regional and local studies. (Funded by the National Natural Science Foundation of China and others.).

Short-term Exposure to Air Pollution and Attributable Risk of Kidney Diseases: A Nationwide Time-series Study.

BACKGROUND: Several studies have shown that long-term exposure to air pollution is associated with reduced kidney function. However, less is known about effects of short-term exposure to air pollution on kidney disease aggravation and resultant emergency room (ER) burden. This study aimed to estimate excess ER visits attributable to short-term air pollution and to provide evidence relevant to air pollution standards to protect kidney patients. METHODS: We conducted time-series analysis using National Health Insurance data covering all persons in South Korea (2003-2013). We collected daily data for air pollutants (particulate matter ≤10 µm [PM10], ozone [O3], carbon monoxide [CO], and sulfur dioxide [SO2]) and ER visits for total kidney and urinary system disease, acute kidney injury (AKI), and chronic kidney disease (CKD). We performed a two-stage time-series analysis to estimate excess ER visits attributable to air pollution by first calculating estimates for each of 16 regions, and then generating an overall estimate. RESULTS: For all kidney and urinary disease (902,043 cases), excess ER visits attributable to air pollution existed for all pollutants studied. For AKI (76,330 cases), we estimated the highest impact on excess ER visits from O3, while for CKD (210,929 cases), the impacts of CO and SO2 were the highest. The associations between air pollution and kidney ER visits existed for days with air pollution concentrations below current World Health Organization guidelines. CONCLUSION: This study provides quantitative estimates of ER burdens attributable to air pollution. Results are consistent with the hypothesis that stricter air quality standards benefit kidney patients.