Jul 2026· AI Sensors· Vol 2, pp. 8· 0 citations· 31 references
Abstract
Cardiovascular disease (CVD) is the leading cause of mortality in the United States, yet the role of atmospheric exposures as independent predictors of county-level CVD mortality remains poorly characterized. We integrated satellite-derived atmospheric data alongside socioeconomic, demographic, and livestock predictors across 24,487 county-year observations in the contiguous United States (2012–2019) and applied an XGBoost model with SHAP-based interpretability to identify the leading predictors of county-level CVD mortality (Test R2 = 0.706, RMSE = 29.55 per 100,000 persons). Four of the top ten predictors came from CAMS/ERA5. Ambient formaldehyde exposure frequency ranked second among all 43 predictors, exceeded only by educational attainment and surpassing poverty rate. Wet-bulb temperature ranked third, Leaf Area Index for High Vegetation ranked seventh, and sulphate aerosol mixing ratio ranked eighth. These variables added county-level prediction information beyond socioeconomic covariates. Integrating atmospheric exposure monitoring into county-level CVD surveillance alongside socioeconomic indicators may improve the identification of high-risk geographies.
With less decline and greater attributable impact than PM2.5, NO2 is increasingly important for measuring morbidity impacts from local sources (i.e., traffic and buildings) in New York City.
A. Spira-Cohen, Rebecca Goldberg, Sarah Johnson et al.· Environmental Epidemiology· 0 citations
Purpose Chronic kidney disease (CKD) is a major public health concern in the United States, with persistently rising incidence and mortality. This study aimed to quantify geographic and demographic disparities in CKD mortality across the United States and to examine the association between CKD mortality and ambient temperature variation. Patients and Methods CKD deaths and age-adjusted mortality rates (AAMRs) for 1999–2023 were obtained from CDC WONDER and stratified by census region, state, sex, race, age group, and urbanization level. Mortality trends were quantified using joinpoint regression. Primary temperature–mortality analyses used CDC WONDER-linked NLDAS temperature data for 1999–2011, while supplementary descriptive analyses used independently retrieved NLDAS temperature estimates for 2012–2023. Temperature–mortality associations were evaluated using Spearman rank correlations, quasi-Poisson regression models, and distributed lag nonlinear models (DLNMs). Results From 1999 to 2023, 628,937 CKD deaths occurred, with national AAMR increasing steadily. Mortality rates were consistently higher in men and nonmetropolitan areas. AAPC rose fastest in the West and Midwest, though recent AAMR declines were noted in the Northeast and South. Winter mortality exceeded summer across regions. In the primary DLNM analysis, cold exposure at the region-specific 5th percentile was associated with higher cumulative CKD mortality risk, with risk ration (RR) ranging from 1.065 in the Northeast to 1.505 in the Midwest; the association reached statistical significance only in the Midwest (RR 1.505, 95% CI: 1.091–2.075), while hot-exposure estimates at the 95th percentile were generally imprecise and not statistically significant. Conclusion CKD mortality in the United States increased from 1999 to 2023 with marked geographic and demographic disparities. Cold air temperature was associated with higher short-term mortality risk.
Heng Wang, Keyi Fan, Limin Cao et al.· International Journal of Nep...· 0 citations
Long-term exposure to ambient fine particulate matter (PM2.5) is the leading environmental risk factor for premature mortality worldwide, yet comprehensive province-level evidence quantifying its health burden across Türkiye remains limited. This study investigated the spatial relationship between long-term PM2.5 exposure and all-cause attributable mortality across all 81 Turkish provinces in 2022 using province-level annual mean PM2.5 concentrations and World Health Organisation (WHO) AirQ+ estimates of PM2.5-attributable deaths among adults aged ≥30 years, assuming a counterfactual concentration of 5 µg/m3. The association between PM2.5 exposure and mortality was evaluated using Pearson and Spearman correlation analyses, ordinary least squares (OLS) regression, a log–log elasticity model, and population-weighted regional and exposure-quartile comparisons, while national temporal indicators for 2010–2023 were reported solely as supplementary context for the primary single-year 2022 cross-sectional analysis. The population-weighted annual mean PM2.5 concentration was 27.0 µg/m3, exceeding the WHO Air Quality Guideline by a factor of 5.4, and all 81 provinces exceeded the recommended threshold. The bivariate OLS model accounted for 41% of the between-province variation in attributable mortality rates (OLS slope = 3.23 additional deaths per 100,000 population for each 1 µg/m3 increase in PM2.5; 95% CI: 2.37–4.10; R2 = 0.41; p < 0.001), while the log–log elasticity model indicated that a 1% increase in PM2.5 concentration was associated with a 0.80% increase in the attributable mortality rate (95% CI: 0.65–0.95). The attributable fraction of natural-cause mortality increased progressively from 8.8% in the lowest exposure quartile to 24.6% in the highest. Nationwide, an estimated 68,440 premature deaths, representing 14.2% of all natural-cause deaths among adults aged ≥30 years, were attributable to PM2.5 exposure. These findings quantify a steep, spatially graded PM2.5-attributable mortality burden across Türkiye. As the attributable estimates derive from the WHO AirQ+ concentration–response function, the gradient describes the magnitude and spatial distribution of the modelled burden rather than an independently estimated exposure–response relationship, and on that basis the results support the adoption of WHO-aligned air-quality standards and accelerated decarbonization strategies to reduce the national health burden attributable to ambient air pollution.
Extreme heat events (EHEs) are becoming more frequent and severe across the United States, yet the drivers of heat-related mortality remain unevenly understood. This study examines how heat vulnerability and regional heat conditions shape all-cause mortality anomalies across the nine U.S. climate regions. Using a national dataset of EHEs and population-normalized mortality z-scores from 2014–2023, we compared the relative influence of socioeconomic, demographic, environmental, and heat-event characteristics on mortality outcomes. Across regions, socioeconomic and demographic vulnerabilities—particularly poverty, racial/ethnic composition, social isolation, limited green space, and older age—were the strongest predictors of elevated mortality during extreme heat. In contrast, event characteristics such as duration, temperature exceedance, and areal extent contributed comparatively little once socioeconomic and demographic vulnerability was accounted for. Mortality modeling performance varied widely by region, with particularly strong predictive signals in the Southwest, West, and South. These findings suggest that socioeconomic and demographic vulnerabilities, rather than meteorological extremes alone, may be more consistent drivers of heat-related mortality variation across U.S. climate regions. Targeted, region-specific heat-health strategies—especially those addressing social vulnerability and humidity exposure—are essential for reducing mortality risk under a warming climate.
Anuska Narayanan, David Keellings, C. Quintero-López· Environmental Research: Clim...· 0 citations
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