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Background Attributes defining the Social Determinants of Health (SDoH) are associated with disproportionate exposures to environmental hazards and differential health outcomes among communities. The dynamics between SDoH, disproportionate environmental exposures, and differential health outcomes are often specific to micro-geographic areas. Methods This study focused on children less than 20 years of age who lived in Douglas County, Nebraska, during 2016–2019. To assess the role of SDoH in differential exposures, we evaluated the association between SDoH metrics and criteria pollutant concentrations and the association between SDoH and pediatric asthma exacerbations to quantify the role of SDoH in differential pediatric asthma outcomes. The Bayesian Poisson regression model with spatial random effects was used to evaluate associations. Results We identified significant positive associations between the annual mean concentration of criteria pollutants (carbon monoxide, particulate matter 2.5 , nitrogen dioxide, sulfur dioxide) with race (Non-Hispanic Black and Hispanic/Latino), financial stability, and literacy. Additionally, there were significant positive associations between higher rates of pediatric asthma emergency department visits and neighborhoods with more Non-Hispanic Black children, children without health insurance coverage, and households without access to a vehicle. Conclusions Non-Hispanic Black and Hispanic/Latino children living in Douglas County, NE experience disproportionately higher exposure to criteria pollutant concentrations. Additionally, higher rates of asthma exacerbations among Non-Hispanic Black children could be due to reduced access to respiratory care that is potentially the result of financial instability and vehicle access. These results could inform city planners and health care providers to mitigate respiratory risks among these higher at-risk populations.

The year 2012 marks a decade of observations undertaken by the U.S. Climate Reference Network (USCRN) under the auspices of NOAA's National Climatic Data Center and Atmospheric Turbulence and Diffusion Division. The network consists of 114 sites across the conterminous 48 states, with additional sites in Alaska and Hawaii. Stations are installed in open (where possible), rural sites very likely to have stable land-cover/use conditions for several decades to come. At each site a suite of meteorological parameters are monitored, including triple redundancy for the primary air temperature and precipitation variables and for soil moisture/temperature. Instrumentation is regularly calibrated to National Institute for Standards and Technology (NIST) standards and maintained by a staff of expert engineers. This attention to detail in USCRN is intended to ensure the creation of an unimpeachable record of changes in surface climate over the United States for decades to come. Data are made available without restriction for all public, private, and government use. This article describes the rationale for the USCRN, its implementation, and some of the highlights of the first decade of operations. One critical use of these observations is as an independent data source to verify the existing U.S. temperature record derived from networks corrected for nonhomogenous histories. Future directions for the network are also discussed, including the applicability of USCRN approaches for networks monitoring climate at scales from regional to global. Constructive feedback from end users will allow for continued improvement of USCRN in the future and ensure that it continues to meet stakeholder requirements for precise climate measurements.

A more comprehensive understanding of the role of irrigation in coupled natural–human systems is needed to minimize the negative consequences for climate, ecosystems and public health.

Irrigation plays a crucial role in agricultural production across the US Great Plains. Meanwhile, it is a key driver of local and regional climate due to its influence on energy and water exchange between land surface and atmosphere. Despite the irrigation-induced evaporative cooling on temperature alone, how irrigation affects summer heat stress—a combination of temperature and humidity can become a concern to public health—is not well understood. This study examines the potential impacts of irrigation practices on summer temperature and heat extremes in the Great Plains using a set of sensitivity experiments conducted with the Weather Research & Forecasting (WRF) model for 10 growing seasons. Results show that intensive irrigation lowers the ambient temperature, but the increased humidity from enhanced evapotranspiration, especially during the extreme hot and dry summers, can possibly elevate the risks of heat stress in the heavily irrigated area and its surroundings. The response of humid heat extremes to irrigation depends on the heat metrics used in the assessment. For variables like wet-bulb temperature, wet-bulb globe temperature, and equivalent temperature, irrigation leads to significantly intensified humid heat extremes by up to 5 °C and increased heatwave frequency by 3 events year−1. In contrast, metrics like the heat index and environmental stress index suggest that irrigation mitigates heat intensity by decreasing the temperature metrics by up to 1 °C. Given the importance of irrigation in Great Plains agriculture in a changing climate, these uncertainties underscore the urgent need to connect heat metrics with health outcomes to better address heat mitigation in rural communities.

Background A United States ethanol company used pesticide-coated seed corn for fuel ethanol production, resulting in highly contaminated byproducts. Improper storage and disposal of the waste led to widespread environmental contamination. Detectable levels of neonicotinoids have been found in soil, water, and air samples, raising questions about the potential impacts to the environment and human health. The study objective was to evaluate the community’s perceived physical and mental health impacts and needs resulting from the contamination linked to bioenergy production by a single company. Methods A 54-question survey was administered to households located within a 10-mile radius of the facility. Respondents could complete the paper survey and return it by mail or electronically. The general topics were household members’ awareness, concerns, and perceptions of environmental and health impacts. Quantitative data were presented as frequencies and percentages, while qualitative data were grouped into themes based on keywords and summarized as counts. Results A total of 459 respondents completed the survey, a 38% response rate. The average household size was 2.7 (SD = 1.4). Responding households were primarily single-family homes (89%) that were owned (85%), and were long-time residents (mean = 18.4 years, SD = 15.5). A total of 36% of households included children aged 18 or younger. Respondents were concerned about contaminants affecting water (82%), soil (79%), and air (72%) quality. Most respondents (74%) felt some or a lot of stress related to potentially compromised health; however, 51% did not believe they had health symptoms resulting from the contamination. The most common self-reported symptoms among primary respondents were sinus ( n  = 17), respiratory ( n  = 22), cognitive/neurological symptoms ( n  = 15), and allergies ( n  = 17). Depression and anxiety were the primary mental health symptoms reported with 31 mentions. The top community need was wanting the environment cleaned-up, including proper removal of waste and land restoration. Conclusions This study evaluated community-level perceived impacts of environmental contamination directly related to an ethanol plant’s improper handling of production waste containing pesticides. Findings can support immediate actions by state officials and community leaders and serve as a baseline for future health and environmental monitoring.

Background Little is known about the effect of drought on all-cause mortality, especially in higher income countries such as the United States. As the frequency and severity of droughts are likely to increase, understanding the connections between drought and mortality becomes increasingly important. Methods Our exposure variable was an annual cumulative drought severity score based on the 1-month, county-level Standardized Precipitation Evapotranspiration Index. The outcome variables of demographic subgroup-specific all-cause mortality count data per year were obtained from the National Vital Statistics System. Any counts below 10 deaths were censored in that demographic group per county. We modeled county-stratum-year mortality using interval-censored negative binomial regression with county-level random intercepts, for each combined age-race-sex stratum either with or without further stratification by climate regions. Fixed effects meta-regression was used to test the associations between age, race, sex, and region with the drought-mortality regression coefficients. Predictive margins were then calculated from the meta-regression model to estimate larger subgroup (e.g., ‘race’ or ‘sex’) associations of drought with mortality. Results Most of the results were null for associations between drought severity and mortality, across joint strata of race, age, sex and region, but incidence rate ratios (IRRs) for 17 subgroups were significant after accounting for the multiple testing; ten were < 1 indicating a possible protective effect of drought on mortality for that particular subpopulation. The meta-regression indicated heterogeneity in the association of drought with mortality according to race, climate region, and age, but not by sex. Marginal means of the estimated log-incidence rate ratios differed significantly from zero for age groups 25–34, 35–44, 45–54 and 55–64; for the white race group; and for the South, West and Southwest regions, in the analysis that included wet county-years. The margin of the meta-regression model suggested a slightly negative, but not statistically significant, association of drought with same-year mortality in the overall population. Conclusions There were significant, heterogeneous-direction associations in subpopulation-stratified models, after controlling for multiple comparisons, suggesting that the impacts of drought on mortality may not be monolithic across the United States. Meta-regression identified systematic differences in the associations of drought severity with all-cause mortality according to climate region, race, and age. These findings suggest there may be important contextual differences in the effects of drought severity on mortality, motivating further work focused on local mechanisms. We speculate that some of the estimated negative associations of drought severity with same-year mortality could be consistent with either a protective effect of drought on total mortality in the same year, or with a delayed health effect of drought beyond the same year. Further research is needed to clarify associations of drought with more specific causes of death and with sublethal health outcomes, for specific subpopulations, and considering lagged effects occurring beyond the same year as the drought.

Background Emissions from wildfire plumes are composed of modified biomass combustion by-products, including carcinogens. However, studies of the association between wildland fires (WF; includes wildfires, prescribed burns, and resource management fires) exposure and lung cancer are scant. We evaluated geographic patterns in these exposures and their association with lung cancer mortality (LCM) rates across the conterminous United States (US). Methods We extracted data from the Monitoring Trends in Burn Severity program (1997–2003) and derived county-level exposure metrics: WF density by area, WF density by population, the ratio between total burned land area and county area, and the ratio between total burned land area by population. We obtained sex-specific, county-level LCM rates for 2016–2020 from the National Center for Health Statistics. Counties with fewer than 10 cases were suppressed. To account for cigarette smoking, we first modeled residual values from a Poisson regression between cigarette smoking prevalence and sex-specific, age-adjusted LCM rates. We then used Lee’s L statistic for bivariate spatial association to identify counties with statistically significant ( p  < 0.05) associations between WF exposures and these residuals. In a sensitivity analysis, we applied a false discovery rate correction to adjust for multiple comparisons. Results We observed geographic variation in bivariate associations between large WFs and subsequent LCM rates across US counties while accounting for ever cigarette smoking prevalence. There were positive (high WF exposures and high LCM rate) clusters for males and females in counties within the mid-Appalachian region and Florida, and modest differences across WF metrics in the cluster patterns were observed across the Western US and Central regions. The most positive clusters were seen between WF density by area and LCM rates among women ( n  = 82 counties) and a similar geographic pattern among men ( n  = 75 counties). Similar patterns were observed for males and females in the western US, with clusters of high WF exposures and low LCM rates. After adjusting for multiple comparisons, a positive cluster pattern among both sexes persisted in Kentucky and Florida with area-based exposure metrics. Discussion Our analysis identified counties outside the western US with wildfires associated with lung cancer mortality. Studies with individual-level exposure-response assessments are needed to evaluate this relationship further.

Coccidioidomycosis (Valley fever, VF) is a climate‐sensitive infectious disease caused by inhaling soil‐dwelling fungus Coccidioides, mostly reported in southwestern USA. Although soil moisture (SM) and soil temperature (ST) are known to shape the fungal lifecycle, their effects on coccidioidomycosis remain understudied. Most prior studies have relied on their proxies—precipitation and air temperature—that might not accurately capture soil hydrothermal dynamics. We conducted multivariable negative binomial regressions to estimate seasonal associations between incidence and climate drivers—including SM, ST, and wind speed from the North American Land Data Assimilation Phase 2 (NLDAS‐2), and PM10‐based dusty‐day counts—in Arizona's hyperendemic counties (Maricopa, Pima, and Pinal) from 2000 to 2022. We found higher incidence in areas with hotter, drier soils and more seasonal dusty days. Multi‐year soil hydrothermal cycles—alternating wet–dry and cool–hot periods along with concurrent dry, dusty conditions—significantly influenced incidence. Notably, no antecedent dry–cool seasons were linked to increased incidence, indicating moisture and/or heat are prerequisites for fungal growth and dispersal. SM showed more consistent and widespread effects than ST across seasons and lags, with winter and spring soils most influential. Higher incidence followed wetter winters and monsoons, and dry, hot springs and falls. Our models using NLDAS‐2 SM and ST data showed robust performance and generalizability across exposure seasons. Our results support adding multi‐year soil indicators—with up to 3‐year lead times—into early‐warning systems to enhance VF forecasting and better prepare endemic regions for the challenges of a warming, drying, and increasingly variable climate. Plain Language Summary Coccidioidomycosis is a fungal disease caused by inhaling Coccidioides spores from soils, most commonly in southwestern USA. Soil moisture and temperature likely shape the fungus's lifecycle, but their roles remain poorly understood because most studies used their proxies—precipitation and air temperature—that might not accurately reflect soil water‐temperature patterns. We examined how current wind, dusty days, and both current and past soil moisture and soil temperature influenced incidence. We found more cases in Arizona regions with drier, hotter soils and more seasonal dusty days. Importantly, alternating wet–dry and cool–hot soil cycles over the past 0–3 years significantly influenced disease occurrence. No past dry–cool conditions were linked to higher incidence, suggesting moisture and/or heat is needed for fungal proliferation and dispersal. Soil moisture had more consistent and extensive seasonal effects than soil temperature. Higher incidence was linked to wetter soils in prior winters and monsoons, and hotter, drier soils in falls and springs, with winter and spring soil hydrothermal conditions most influential. Our models using reanalysis‐based soil data showed robust performance across seasons. Our findings support adding soil data with up to 3‐year lead times into early‐warning systems to improve public health actions in endemic regions. Key Points Multi‐year soil wet–dry and cool–hot cycles along with concurrent dry, dusty conditions, are linked to higher Valley fever incidence across exposure seasons Higher incidence is linked to prior wetter winters and monsoons, and hotter, drier falls and springs, with winter and spring soil conditions most influential Results call for adding soil indicators with up to 3‐year lead time into early‐warning systems to enhance public health actions in endemic regions

Heatwaves cause excess mortality and physiological impacts on humans throughout the world, and climate change will intensify and increase the frequency of heat events. Many adaptation and mitigation studies use spatial distribution of highly vulnerable local populations to inform heat reduction and response plans. However, most available heat vulnerability studies focus on urban areas with high heat intensification by Urban Heat Islands (UHIs). Rural areas encompass different environmental and socioeconomic issues that require alternate analyses of vulnerability. We categorized Nebraska census tracts into four urbanization levels, then conducted factor analyses on each group and captured different patterns of socioeconomic vulnerabilities among resultant Heat Vulnerability Indices (HVIs). While disability is the major component of HVI in two urbanized classes, lower education, and races other than white have higher contributions in HVI for the two rural classes. To account for environmental vulnerability of HVI, we considered different land type combinations for each urban class based on their percentage areas and their differences in heat intensifications. Our results demonstrate different combinations of initial variables in heat vulnerability among urban classes of Nebraska and clustering of high and low heat vulnerable areas within the highest urbanized sections. Less urbanized areas show no spatial clustering of HVI. More studies with separation on urbanization level of residence can give insights into different socioeconomic vulnerability patterns in rural and urban areas, while also identifying changes in environmental variables that better capture heat intensification in rural settings. Plain Language Summary Heat waves are known as periods of abnormally high temperatures that can cause health problems, even deaths. The 2003 heat wave in Europe and the Chicago heat wave of 1995 are well known examples that are well‐documented and caused thousands of mortalities and morbidities. Scientific studies show that climate change will cause more frequent, more extreme, and longer lasting heat waves in the future all over the world. Additionally, more people are expected to live in urban areas in the future, that are known to experience higher temperatures compared to their surrounding non‐urban areas, because of concrete, asphalt, steel, and similar materials that absorb energy and return it as heat. Because of this issue, known as the Urban Heat Island (UHI) effect, and because more people live in urban areas, most studies tracking the most heat‐threatened people are focused on urban areas, or use the same findings for rural areas, too. In this study, we separate the state of Nebraska into four levels of urbanizations from highest metropolitan to most rural and found that the socioeconomic variables combined differently based on urbanization. Key Points Despite similar incidence rates, Heat Vulnerability Index (HVI) in rural areas is under studied in comparison to urban areas The environmental vulnerability variables in rural areas are dissimilar to urban areas, so we applied different variables to calculate them We found different organization of socioeconomic variables in calculated HVIs, suggesting separate heat strategies for urbanization levels

Climate change is known to increase the frequency and intensity of hot days (daily maximum temperature ≥30°C), both globally and locally. Exposure to extreme heat is associated with numerous adverse human health outcomes. This study estimated the burden of heat‐related illness (HRI) attributable to anthropogenic climate change in North Carolina physiographic divisions (Coastal and Piedmont) during the summer months from 2011 to 2016. Additionally, assuming intermediate and high greenhouse gas emission scenarios, future HRI morbidity burden attributable to climate change was estimated. The association between daily maximum temperature and the rate of HRI was evaluated using the Generalized Additive Model. The rate of HRI assuming natural simulations (i.e., absence of greenhouse gas emissions) and future greenhouse gas emission scenarios were predicted to estimate the HRI attributable to climate change. Over 4 years (2011, 2012, 2014, and 2015), we observed a significant decrease in the rate of HRI assuming natural simulations compared to the observed. About 3 out of 20 HRI visits are attributable to anthropogenic climate change in Coastal (13.40% [IQR: −34.90,95.52]) and Piedmont (16.39% [IQR: −35.18,148.26]) regions. During the future periods, the median rate of HRI was significantly higher (78.65%: Coastal and 65.85%: Piedmont), assuming a higher emission scenario than the intermediate emission scenario. We observed significant associations between anthropogenic climate change and adverse human health outcomes. Our findings indicate the need for evidence‐based public health interventions to protect human health from climate‐related exposures, like extreme heat, while minimizing greenhouse gas emissions. Plain Language Summary We conducted this study to understand how current and future changes in temperature caused by human‐caused climate change impacts human health. To complete this work, we developed a statistical model to estimate the heat‐related emergency room visits for two regions of North Carolina. We applied this statistical model to changes in temperature that have occurred during the last century that are attributed to human‐caused changes in greenhouse gases. We also used this model to look at future changes in temperature over the next century based on different greenhouse gas emission scenarios. Using the statistical model that we trained using the actual observations during 2011–2016, we estimated the HRI risk attributable to climate change during 2011, 2012, 2014, 2015, and for the future. Our results suggest that about 3 out of 20 heat‐related emergency room visits during 2011–2016 were attributable to human‐caused climate change. In addition, the rate of heat‐related emergency room visits with a higher greenhouse gas emission scenario in the future was significantly greater. Our results show that human‐caused climate change is currently impacting heat‐related hospitalizations, and these impacts are projected to continue in the future. Key Points Quantified the association between daily maximum temperature and heat‐related illness (HRI) emergency room visits During 2011–2016, 15% of the HRI emergency room visits in North Carolina were attributable to anthropogenic climate change HRI emergencies are projected to increase by 32% during 2036–2065 and 79% during 2070–2099, assuming RCP8.5 emissions compared to RCP4.5