Prenatal black carbon exposure and DNA methylation in umbilical cord blood.

BACKGROUND/OBJECTIVES: Prenatal exposure to ambient air pollution is associated with adverse cardiometabolic outcomes in childhood. We previously observed that prenatal black carbon (BC) was inversely associated with adiponectin, a hormone secreted by adipocytes, in early childhood. Changes to DNA methylation have been proposed as a potential mediator linking in utero exposures to lasting health impacts. METHODS: Among 532 mother-child pairs enrolled in the Colorado-based Healthy Start study, we performed an epigenome-wide association study of the relationship between prenatal exposure to a component of air pollution, BC, and DNA methylation in cord blood. Average pregnancy ambient BC was estimated at the mother's residence using a spatiotemporal prediction model. DNA methylation was measured using the Illumina 450K array. We used multiple linear regression to estimate associations between prenatal ambient BC and 429,246 cysteine-phosphate-guanine sites (CpGs), adjusting for potential confounders. We identified differentially methylated regions (DMRs) using DMRff and ENmix-combp. In a subset of participants (n = 243), we investigated DNA methylation as a potential mediator of the association between prenatal ambient BC and lower adiponectin in childhood. RESULTS: We identified 44 CpGs associated with average prenatal ambient BC after correcting for multiple testing. Several genes annotated to the top CpGs had reported functions in the immune system. There were 24 DMRs identified by both DMRff and ENmix-combp. One CpG (cg01123250), located on chromosome 2 and annotated to the UNC80 gene, was found to mediate approximately 20% of the effect of prenatal BC on childhood adiponectin, though the confidence interval was wide (95% CI: 3, 84). CONCLUSIONS: Prenatal BC was associated with DNA methylation in cord blood at several sites and regions in the genome. DNA methylation may partially mediate associations between prenatal BC and childhood cardiometabolic outcomes.

Redlining in New York City: impacts on particulate matter exposure during pregnancy and birth outcomes.

BACKGROUND: Evidence suggests historical redlining shaped the built environment and health outcomes in urban areas. Only a handful of studies have examined redlining's association with air pollution and adverse birth outcomes in New York City (NYC). Additionally, no NYC-specific studies have examined the impact of redlining on birth weight. METHODS: This longitudinal cohort study analysed data from the National Institute of Health Environmental Influences on Child Health Outcomes Programme to investigate the extent to which maternal residence in a historically redlined neighbourhood is associated with fine particulate matter (PM2.5) exposure during pregnancy using multivariable regression models. Additionally, we examined how maternal residence in a historically redlined neighbourhood during pregnancy influenced birth weight z-score, preterm birth and low birth weight. RESULTS: Our air pollution model showed that living in a historically redlined census tract or an ungraded census tract was associated with increased PM2.5 exposure during pregnancy. We also found living in a historically redlined census tract or an ungraded census tract was associated with a lower birth weight z-score. This finding remained significant when controlling for individual and census tract-level race, ethnicity and income. When we controlled PM2.5 in our models assessing the relationship between redlining grade and birth outcome, our results did not change. DISCUSSION: Our study supports the literature linking redlining to contemporary outcomes. However, our research in ungraded tracts suggests redlining alone is insufficient to fully explain inequality in birth outcomes and PM2.5 levels today.

The effects of ambient air pollution exposure on Thoroughbred racehorse performance.

BACKGROUND: Limited research exists on impacts of air pollution on non-human mammals, particularly animal athletes such as Thoroughbred racehorses. Athletes have a greater risk of exposure as heightened exertion and increased airflow carry more pollutants deeper into the respiratory tract. OBJECTIVES: To provide insights into the impact of ambient air pollution, particularly fine particulate matter (PM2.5), on race speed. STUDY DESIGN: Retrospective observational study. METHODS: Data were obtained from The Jockey Club Information Systems, covering 31 407 winning races by Thoroughbred horses in California spanning 10 years (2011-2020) and evaluated the association between air pollution and winning race speeds. For race days, we collected PM2.5 data from the nearest U.S. Environmental Protection Agency (EPA) monitoring site within 100 km of each racetrack (n = 12). We assessed the associations between daily average PM2.5 concentrations and speed of winning horses with linear mixed effects regression. We adjusted for horse characteristics, race-related covariates, temporal indicators (e.g., year), other air pollutants and temperature. We conducted sensitivity analyses by adjusting extreme air pollution days by reassigning values to the 95th percentile value and conducting linear mixed effects regression on series of datasets with incremental cutpoints of PM2.5. RESULTS: In the cutpoint analysis, we found that for PM2.5 between 4 and 23.6 µg/m3, speed decreased 0.0008 m/s (95% CI: -0.0014562 to -0.00018) for every 1 µg/m3 increase of PM2.5. MAIN LIMITATIONS: Limitations include the use of offsite monitors leading to imprecise exposure measurements, not using training practice data, and generalisability as the study focuses on California racetracks. CONCLUSION: This study highlights the need to create advisories to safeguard the performance of horses during periods of poor air quality. Further research is recommended to explore additional factors influencing the relationship between air pollution and equine welfare.

Association of ambient air pollution and pesticide mixtures on respiratory inflammatory markers in agricultural communities.

Air pollution exposure is associated with adverse respiratory health outcomes. Evidence from occupational and community-based studies also suggests agricultural pesticides have negative health impacts on respiratory health. Although populations are exposed to multiple inhalation hazards simultaneously, multidomain mixtures (e.g. environmental and chemical pollutants of different classes) are rarely studied. We investigated the association of ambient air pollution-pesticide exposure mixtures with urinary leukotriene E4 (LTE4), a respiratory inflammation biomarker, for 75 participants in four Central California communities over two seasons. Exposures included three criteria air pollutants estimated via the Community Multiscale Air Quality model (fine particulate matter, ozone, and nitrogen dioxide) and urinary metabolites of organophosphate (OP) pesticides (total dialkyl phosphates (DAPs), total diethyl phosphates (DE), and total dimethyl phosphates (DM)). We implemented multiple linear regression models to examine associations in single pollutant models adjusted for age, sex, asthma status, occupational status, household member occupational status, temperature, and relative humidity, and evaluated whether associations changed seasonally. We then implemented Bayesian kernel machine regression (BKMR) to analyse these criteria air pollutants, DE, and DM as a mixture. Our multiple linear regression models indicated an interquartile range (IQR) increase in total DAPs was associated with an increase in urinary LTE4 in winter (ß: 0.04, 95% CI: [0.01, 0.07]). Similarly, an IQR increase in total DM was associated with an increase in urinary LTE4 in winter (ß:0.03, 95% CI: [0.004, 0.06]). Confidence intervals for all criteria air pollutant effect estimates included the null value. BKMR analysis revealed potential non-linear interactions between exposures in our air pollution-pesticide mixture, but all confidence intervals contained the null value. Our analysis demonstrated a positive association between OP pesticide metabolites and urinary LTE4 in a low asthma prevalence population and adds to the limited research on the joint effects of ambient air pollution and pesticides mixtures on respiratory health.

Impact of the 2022 New Mexico, US wildfires on air quality and health.

The 2022 wildfires in New Mexico, United States, were unparalleled compared to past wildfires in the state in both their scale and intensity, resulting in poor air quality and a catastrophic loss of habitat and livelihood. Among all wildfires in New Mexico in 2022, six wildfires were selected for our study based on the size of the burn area and their proximity to populated areas. These fires accounted for approximately 90 % of the total burn area in New Mexico in 2022. We used a regional chemical transport model and data-fusion technique to quantify the contribution of these six wildfires (April 6 to August 22) on particulate matter (PM2.5: diameter ≤ 2.5 µm) and ozone (O3) concentrations, as well as the associated health impacts from short-term exposure. We estimated that these six wildfires emitted 152 thousand tons of PM2.5 and 287 thousand tons of volatile organic compounds to the atmosphere. We estimated that the average daily wildfire smoke PM2.5 across New Mexico was 0.3 µg/m3, though 1 h maximum exceeded 120 µg/m3 near Santa Fe. Average wildfire smoke maximum daily average 8-h O3 (MDA8-O3) contribution was 0.2 ppb during the study period over New Mexico. However, over the state 1 h maximum smoke O3 exceeded 60 ppb in some locations near Santa Fe. Estimated all-cause excess mortality attributable to short term exposure to wildfire PM2.5 and MDA8-O3 from these six wildfires were 18 (95 % Confidence Interval (CI), 15-21) and 4 (95 % CI: 3-6) deaths. Additionally, we estimate that wildfire PM2.5 was responsible for 171 (95 %: 124-217) excess cases of asthma emergency department visits. Our findings underscore the impact of wildfires on air quality and human health risks, which are anticipated to intensify with global warming, even as local anthropogenic emissions decline.

Cumulative Exposures to Environmental and Socioeconomic Risk Factors in Milwaukee County, Wisconsin.

The environmental justice literature demonstrates consistently that low-income and minority communities are disproportionately exposed to environmental hazards. In this case study, we examined cumulative multipollutant, multidomain, and multimatrix environmental exposures in Milwaukee County, Wisconsin for the year 2015. We identified spatial hot spots in Milwaukee County both individually (using local Moran's I) and through clusters (using K-means clustering) across a profile of environmental pollutants that span regulatory domains and matrices of exposure, as well as socioeconomic indicators. The cluster with the highest exposures within the urban area was largely characterized by low socioeconomic status and an overrepresentation of the Non-Hispanic Black population relative to the county as a whole. In this cluster, average pollutant concentrations were equivalent to the 78th percentile in county-level blood lead levels, 67th percentile in county-level NO2, 79th percentile in county-level CO, and 78th percentile in county-level air toxics. Simultaneously, this cluster had an average equivalent to the 62nd percentile in county-level unemployment, 70th percentile in county-level population rate lacking a high school diploma, 73rd percentile in county-level poverty rate, and 28th percentile in county-level median household income. The spatial patterns of pollutant exposure and SES indicators suggested that these disparities were not random but were instead structured by socioeconomic and racial factors. Our case study, which combines environmental pollutant exposures, sociodemographic data, and clustering analysis, provides a roadmap to identify and target overburdened communities for interventions that reduce environmental exposures and consequently improve public health.

Bridging Differences in Cohort Analyses of the Relationship between Secondhand Smoke Exposure during Pregnancy and Birth Weight: The Transportability Framework in the ECHO Program.

BACKGROUND: Estimates for the effects of environmental exposures on health outcomes, including secondhand smoke (SHS) exposure, often present considerable variability across studies. Knowledge of the reasons behind these differences can aid our understanding of effects in specific populations as well as inform practices of combining data from multiple studies. OBJECTIVES: This study aimed to assess the presence of effect modification by measured sociodemographic characteristics on the effect of SHS exposure during pregnancy on birth weights that may drive differences observed across cohorts. We also aimed to quantify the extent to which differences in the cohort mean effects observed across cohorts in the Environmental influences on Child Health Outcomes (ECHO) consortium are due to differing distributions of these characteristics. METHODS: We assessed the presence of effect modification and transportability of effect estimates across five ECHO cohorts in a total of 6,771 mother-offspring dyads. We assessed the presence of effect modification via gradient boosting of regression trees based on the H-statistic. We estimated individual cohort effects using linear models and targeted maximum likelihood estimation (TMLE). We then estimated transported effects from one cohort to each of the remaining cohorts using a robust nonparametric estimation approach relying on TMLE estimators and compared them to the original effect estimates for these cohorts. RESULTS: Observed effect estimates varied across the five cohorts, ranging from significantly lower birth weight associated with exposure [-167.3g; 95% confidence interval (CI): -270.4, -64.1] to higher birth weight with wide CIs, including the null (42.4g; 95% CI: -15.0, 99.8). Transported effect estimates only minimally explained differences in the point estimates for two out of the four cohort pairs. DISCUSSION: Our findings of weak to moderate evidence of effect modification and transportability indicate that unmeasured individual-level and contextual factors and sources of bias may be responsible for differences in the effect estimates observed across ECHO cohorts. https://doi.org/10.1289/EHP13961.

Independent and joint effects of neighborhood-level environmental and socioeconomic exposures on body mass index in early childhood: The environmental influences on child health outcomes (ECHO) cohort.

Past studies support the hypothesis that the prenatal period influences childhood growth. However, few studies explore the joint effects of exposures that occur simultaneously during pregnancy. To explore the feasibility of using mixtures methods with neighborhood-level environmental exposures, we assessed the effects of multiple prenatal exposures on body mass index (BMI) from birth to age 24 months. We used data from two cohorts: Healthy Start (n = 977) and Maternal and Developmental Risks from Environmental and Social Stressors (MADRES; n = 303). BMI was measured at delivery and 6, 12, and 24 months and standardized as z-scores. We included variables for air pollutants, built and natural environments, food access, and neighborhood socioeconomic status (SES). We used two complementary statistical approaches: single-exposure linear regression and quantile-based g-computation. Models were fit separately for each cohort and time point and were adjusted for relevant covariates. Single-exposure models identified negative associations between NO2 and distance to parks and positive associations between low neighborhood SES and BMI z-scores for Healthy Start participants; for MADRES participants, we observed negative associations between O3 and distance to parks and BMI z-scores. G-computations models produced comparable results for each cohort: higher exposures were generally associated with lower BMI, although results were not significant. Results from the g-computation models, which do not require a priori knowledge of the direction of associations, indicated that the direction of associations between mixture components and BMI varied by cohort and time point. Our study highlights challenges in assessing mixtures effects at the neighborhood level and in harmonizing exposure data across cohorts. For example, geospatial data of neighborhood-level exposures may not fully capture the qualities that might influence health behavior. Studies aiming to harmonize geospatial data from different geographical regions should consider contextual factors when operationalizing exposure variables.

Quantifying Prescribed-Fire Smoke Exposure Using Low-Cost Sensors and Satellites: Springtime Burning in Eastern Kansas.

Prescribed fires (fires intentionally set for mitigation purposes) produce pollutants, which have negative effects on human and animal health. One of the pollutants produced from fires is fine particulate matter (PM2.5). The Flint Hills (FH) region of Kansas experiences extensive prescribed burning each spring (March-May). Smoke from prescribed fires is often understudied due to a lack of monitoring in the rural regions where prescribed burning occurs, as well as the short duration and small size of the fires. Our goal was to attribute PM2.5 concentrations to the prescribed burning in the FH. To determine PM2.5 increases from local burning, we used low-cost PM2.5 sensors (PurpleAir) and satellite observations. The FH were also affected by smoke transported from fires in other regions during 2022. We separated the transported smoke from smoke from fires in eastern Kansas. Based on data from the PurpleAir sensors, we found the 24-hr median PM2.5 to increase by 3.0-5.3 µg m-3 (based on different estimates) on days impacted by smoke from fires in the eastern Kansas region compared to days unimpacted by smoke. The FH region was the most impacted by smoke PM2.5 compared to other regions of Kansas, as observed in satellite products and in situ measurements. Additionally, our study found that hourly PM2.5 estimates from a satellite-derived product aligned with our ground-based measurements. Satellite-derived products are useful in rural areas like the FH, where monitors are scarce, providing important PM2.5 estimates.

Early-life exposure to residential black carbon and childhood cardiometabolic health.

BACKGROUND: Early life exposure to air pollution, such as particulate matter ≤2.5 µm (PM2.5), may be associated with obesity and adverse cardiometabolic health outcomes in childhood. However, the toxicity of PM2.5 varies according to its chemical composition. Black carbon (BC) is a constituent of PM2.5, but few studies have examined its impact on childhood cardiometabolic health. Therefore, we examined relationships between prenatal and early childhood exposure to BC and markers of adiposity and cardiometabolic health in early childhood. METHODS: This study included 578 mother-child pairs enrolled in the Healthy Start study (2009-2014) living in the Denver-metro area. Using a spatiotemporal prediction model, we assessed average residential black carbon levels during pregnancy and in the year prior to the early childhood follow-up visit at approximately 5 years old. We estimated associations between prenatal and early childhood BC and indicators of adiposity and cardiometabolic biomarkers in early childhood (mean 4.8 years; range, 4.0, 8.3), using linear regression. RESULTS: We found higher early childhood BC was associated with higher percent fat mass, fat mass index, insulin, and homeostatic model assessment for insulin resistance (HOMA-IR), and lower leptin and waist circumference at approximately 5 years old, after adjusting for covariates. For example, per interquartile range (IQR) increase in early childhood BC (IQR, 0.49 µg/m3) there was 3.32% higher fat mass (95% CI; 2.05, 4.49). Generally, we did not find consistent evidence of associations between prenatal BC and cardiometabolic health outcomes in early childhood, except for an inverse association between prenatal BC and adiponectin, an adipocyte-secreted hormone typically inversely associated with adiposity. CONCLUSIONS: Higher early childhood, but not in utero, ambient concentrations of black carbon, a component of air pollution, were associated with greater adiposity and altered insulin homeostasis at approximately 5 years old. Future studies should examine whether these changes persist later in life.

Environmental risk factors for UV-induced cutaneous neoplasia in horses: A GIS approach.

Objective: Ultraviolet light (UV) is a risk factor for the development of cutaneous neoplasia in many mammalian species. This study evaluated UV exposure as a risk factor of concern for the development of cutaneous neoplasia in equine species due to the significant UV exposure that may accrue over their lifetimes. Animals and samples: Neoplastic biopsy specimens from 3272 horses that were submitted over a 10-year period to the Colorado State University Diagnostic Medicine Center and to the University of Saskatchewan Western College of Veterinary Medicine and Prairie Diagnostic Services were evaluated. Procedure: This retrospective study assessed the spatial relationships between altitude, latitude, longitude, and UV maximum value and the probability of UV-induced cutaneous neoplasia. Results: Cases from areas at high altitude proved to have a higher prevalence of UV-induced cutaneous neoplasia than those from areas at lower elevations. A multivariable regression analysis demonstrated that altitude was the only factor significantly and positively associated with the diagnosis of UV-induced neoplasia. Conclusion and clinical relevance: Evidence of cutaneous neoplasia in horses and environmental factors that influence the degree of UV exposure in a geographic location may aid in diagnosis and suggest preventive measures from UV overexposure.

Facteurs de risque environnementaux des néoplasies cutanées induites par les UV chez le cheval : une approche SIG. Objectif: La lumière ultraviolette (UV) est un facteur de risque pour le développement de néoplasies cutanées chez de nombreuses espèces de mammifères. Cette étude a évalué l'exposition aux UV en tant que facteur de risque préoccupant pour le développement de néoplasies cutanées chez les équidés en raison de l'exposition importante aux UV qui peut s'accumuler au cours de leur vie. Animaux et échantillons: Des échantillons de biopsie néoplasique de 3272 chevaux qui ont été soumis sur une période de 10 ans au Colorado State University Diagnostic Medicine Center et au University of Saskatchewan Western College of Veterinary Medicine and Prairie Diagnostic Services ont été évalués. Procédure: Cette étude rétrospective a évalué les relations spatiales entre l'altitude, la latitude, la longitude et la valeur maximale des UV et la probabilité de néoplasie cutanée induite par les UV. Résultats: Les cas des régions de haute altitude se sont avérés avoir une prévalence plus élevée de néoplasie cutanée induite par les UV que ceux des régions de basse altitude. Une analyse de régression multivariée a démontré que l'altitude était le seul facteur significativement et positivement associé au diagnostic de néoplasie induite par les UV. Conclusion et pertinence clinique: Les preuves de néoplasie cutanée chez les chevaux et les facteurs environnementaux qui influencent le degré d'exposition aux UV dans un lieu géographique peuvent aider au diagnostic et suggérer des mesures préventives contre la surexposition aux UV.(Traduit par Dr Serge Messier).

Pathways framework identifies wildfire impacts on agriculture.

Wildfires are a growing concern to society and the environment in many parts of the world. Within the United States, the land area burned by wildfires has steadily increased over the past 40 years. Agricultural land management is widely understood as a force that alters fire regimes, but less is known about how wildfires, in turn, impact the agriculture sector. Based on an extensive literature review, we identify three pathways of impact-direct, downwind and downstream-through which wildfires influence agricultural resources (soil, water, air and photosynthetically active radiation), labour (agricultural workers) and products (crops and livestock). Through our pathways framework, we highlight the complexity of wildfire-agriculture interactions and the need for collaborative, systems-oriented research to better quantify the magnitude of wildfire impacts and inform the adaptation of agricultural systems to an increasingly fire-prone future.

Developing a National-Scale Exposure Index for Combined Environmental Hazards and Social Stressors and Applications to the Environmental Influences on Child Health Outcomes (ECHO) Cohort.

Tools for assessing multiple exposures across several domains (e.g., physical, chemical, and social) are of growing importance in social and environmental epidemiology because of their value in uncovering disparities and their impact on health outcomes. Here we describe work done within the Environmental influences on Child Health Outcomes (ECHO)-wide Cohort Study to build a combined exposure index. Our index considered both environmental hazards and social stressors simultaneously with national coverage for a 10-year period. Our goal was to build this index and demonstrate its utility for assessing differences in exposure for pregnancies enrolled in the ECHO-wide Cohort Study. Our unitless combined exposure index, which collapses census-tract level data into a single relative measure of exposure ranging from 0-1 (where higher values indicate higher exposure to hazards), includes indicators for major air pollutants and air toxics, features of the built environment, traffic exposures, and social determinants of health (e.g., lower educational attainment) drawn from existing data sources. We observed temporal and geographic variations in index values, with exposures being highest among participants living in the West and Northeast regions. Pregnant people who identified as Black or Hispanic (of any race) were at higher risk of living in a "high" exposure census tract (defined as an index value above 0.5) relative to those who identified as White or non-Hispanic. Index values were also higher for pregnant people with lower educational attainment. Several recommendations follow from our work, including that environmental and social stressor datasets with higher spatial and temporal resolutions are needed to ensure index-based tools fully capture the total environmental context.

Health Research in the Wake of Disasters: Challenges and Opportunities for Sensor Science.

BACKGROUND: Disaster events adversely affect the health of millions of individuals each year. They create exposure to physical, chemical, biological, and psychosocial hazards while simultaneously exploiting community and individual-level vulnerabilities that allow such exposures to exert harm. Since 2013, the National Institute of Environmental Health Sciences (NIEHS) has led the development of the Disaster Research Response (DR2) program and infrastructure; however, research exploring the nature and effects of disasters on human health is lacking. One reason for this research gap is the challenge of developing and deploying cost-effective sensors for exposure assessment during disaster events. OBJECTIVES: The objective of this commentary is to synergize the consensus findings and recommendations from a panel of experts on sensor science in support of DR2. METHODS: The NIEHS convened the workshop, "Getting Smart about Sensors for Disaster Response Research" on 28 and 29 July 2021 to discuss current gaps and recommendations for moving the field forward. The workshop invited full discussion from multiple viewpoints, with the goal of identifying recommendations and opportunities for further development of this area of research. The panel of experts included leaders in engineering, epidemiology, social and physical sciences, and community engagement, many of whom had firsthand experience with DR2. DISCUSSION: The primary finding of this workshop is that exposure science in support of DR2 is severely lacking. We highlight unique barriers to DR2, such as the need for time-sensitive exposure data, the chaos and logistical challenges that ensue from a disaster event, and the lack of a robust market for sensor technologies in support of environmental health science. We highlight a need for sensor technologies that are more scalable, reliable, and versatile than those currently available to the research community. We also recommend that the environmental health community renew efforts in support of DR2 facilitation, collaboration, and preparedness. https://doi.org/10.1289/EHP12270.

Global rural health disparities in Alzheimer's disease and related dementias: State of the science.

INTRODUCTION: Individuals living in rural communities are at heightened risk for Alzheimer's disease and related dementias (ADRD), which parallels other persistent place-based health disparities. Identifying multiple potentially modifiable risk factors specific to rural areas that contribute to ADRD is an essential first step in understanding the complex interplay between various barriers and facilitators. METHODS: An interdisciplinary, international group of ADRD researchers convened to address the overarching question of: "What can be done to begin minimizing the rural health disparities that contribute uniquely to ADRD?" In this state of the science appraisal, we explore what is known about the biological, behavioral, sociocultural, and environmental influences on ADRD disparities in rural settings. RESULTS: A range of individual, interpersonal, and community factors were identified, including strengths of rural residents in facilitating healthy aging lifestyle interventions. DISCUSSION: A location dynamics model and ADRD-focused future directions are offered for guiding rural practitioners, researchers, and policymakers in mitigating rural disparities. HIGHLIGHTS: Rural residents face heightened Alzheimer's disease and related dementia (ADRD) risks and burdens due to health disparities. Defining the unique rural barriers and facilitators to cognitive health yields insight. The strengths and resilience of rural residents can mitigate ADRD-related challenges. A novel "location dynamics" model guides assessment of rural-specific ADRD issues.

Association of Temperature Thresholds with Heat Illness- and Cardiorespiratory-Related Emergency Visits during Summer Months in Alaska.

BACKGROUND: Recent record-breaking hot temperatures in Alaska have raised concerns about the potential human health implications of heat exposure among this unacclimated population. OBJECTIVES: We estimated cardiorespiratory morbidity associated with days above summer (June-August) heat index (HI, apparent temperature) thresholds in three major population centers (Anchorage, Fairbanks, and the Matanuska-Susitna Valley) for the years 2015-2019. METHODS: We implemented time-stratified case-crossover analyses of emergency department (ED) visits for International Classification of Diseases, 10th Revision codes indicative of heat illness and major cardiorespiratory diagnostic codes using data from the Alaska Health Facilities Data Reporting Program. Using conditional logistic regression models, we tested maximum hourly HI temperature thresholds between 21.1°C (70°F) and 30°C (86°F) for a single day, 2 consecutive days, and the absolute number of previous consecutive days above the threshold, adjusting for the daily average concentration of particulate matter ≤2.5µg. RESULTS: There were increased odds of ED visits for heat illness above a HI threshold as low as 21.1°C (70°F) [odds ratio (OR)=13.84; 95% confidence interval (CI): 4.05, 47.29], and this increased risk continued for up to 4 d (OR=2.43; 95% CI: 1.15, 5.10). Asthma and pneumonia were the only respiratory outcomes positively associated with the HI: ED visits for both were highest the day after a heat event (Asthma: HI>27°C(80°F) OR=1.18; 95% CI: 1.00, 1.39; Pneumonia: HI>28°C(82°F) OR=1.40; 95% CI: 1.06, 1.84). There was a decreased odds of bronchitis-related ED visits when the HI was above thresholds of 21.1-28°C (70-82°F) across all lag days. We found stronger effects for ischemia and myocardial infarction (MI) than for respiratory outcomes. Multiple days of warm weather were associated with an increased risk of health impacts. For each additional preceding day above a HI of 22°C (72°F), the odds of ED visits related to ischemia increased 6% (95% CI: 1%, 12%); for each additional preceding day above a HI of 21.1°C (70°F), the odds of ED visits related to MI increased 7% (95% CI: 1%, 14%). DISCUSSION: This study demonstrates the importance of planning for extreme heat events and developing local guidance for heat warnings, even in areas with historically mild summertime climates. https://doi.org/10.1289/EHP11363.

Factors affecting urinary organophosphate pesticide metabolite levels among Californian agricultural community members.

Organophosphate (OP) pesticides are widely used in California for agricultural pest and weed control despite their well-documented adverse health effects among infants, children, and adults. We sought to identify factors affecting urinary OP metabolites among families living in high-exposure communities. Our study included 80 children and adults who lived within 61 m (200 ft) of agricultural fields in the Central Valley of California in January and June 2019, which are pesticide non-spraying and spraying seasons, respectively. We collected one urine sample per participant during each visit to measure dialkyl phosphate (DAP) metabolites; these were coupled with in-person surveys to identify health, household, sociodemographic, pesticide exposure, and occupational risk factors. We used a data-driven, best subsets regression approach to identify key factors that influenced urinary DAPs. Participants were mostly Hispanic/Latino(a) (97.5 %), over half were female (57.5 %), and most households reported having a member who worked in agriculture (70.6 %). Among the 149 urine samples suitable for analysis, DAP metabolites were detected in 48.0 % and 40.5 % of samples during January and June, respectively. Total diethyl alkylphosphates (EDE) were only detected in 4.7 % (n = 7) of samples, but total dimethyl alkylphosphates (EDM) were detected in 41.6 % (n = 62) of samples. No differences were observed in urinary DAP levels by visit month or by occupational exposure to pesticides. Best subsets regression identified several individual- and household-level variables that influenced both urinary EDM and total DAPs: the number of years spent living at the current address, household use of chemical products to control mice/rodents, and seasonal employment status. Among adults only, we identified educational attainment (for total DAPs) and age category (for EDM) as significant factors. Our study found consistent urinary DAP metabolites among participants, regardless of spraying season, and identified potential mitigating factors that members of vulnerable populations can implement to protect their health against OP exposure.

The COVID-19-wildfire smoke paradox: Reduced risk of all-cause mortality due to wildfire smoke in Colorado during the first year of the COVID-19 pandemic.

BACKGROUND: In 2020, the American West faced two competing challenges: the COVID-19 pandemic and the worst wildfire season on record. Several studies have investigated the impact of wildfire smoke (WFS) on COVID-19 morbidity and mortality, but little is known about how these two public health challenges impact mortality risk for other causes. OBJECTIVES: Using a time-series design, we evaluated how daily risk of mortality due to WFS exposure differed for periods before and during the COVID-19 pandemic. METHODS: Our study included daily data for 11 counties in the Front Range region of Colorado (2010-2020). We assessed WFS exposure using data from the National Oceanic and Atmospheric Administration and used mortality counts from the Colorado Department of Public Health and Environment. We estimated the interaction between WFS and the pandemic (an indicator variable) on mortality risk using generalized additive models adjusted for year, day of week, fine particulate matter, ozone, temperature, and a smoothed term for day of year. RESULTS: WFS impacted the study area on 10% of county-days. We observed a positive association between the presence of WFS and all-cause mortality risk (incidence rate ratio (IRR) = 1.03, 95%CI: 1.01-1.04 for same-day exposures) during the period before the pandemic; however, WFS exposure during the pandemic resulted in decreased risk of all-cause mortality (IRR = 0.90, 95%CI: 0.87-0.93 for same-day exposures). DISCUSSION: We hypothesize that mitigation efforts during the first year of the pandemic, e.g., mask mandates, along with high ambient WFS levels encouraged health behaviors that reduced exposure to WFS and reduced risk of all-cause mortality. Our results suggest a need to examine how associations between WFS and mortality are impacted by pandemic-related factors and that there may be lessons from the pandemic that could be translated into health-protective policies during future wildfire events.

Neighborhood Walkability, Historical Redlining, and Childhood Obesity in Denver, Colorado.

Childhood obesity is a precursor to future health complications. In adults, neighborhood walkability is inversely associated with obesity prevalence. Recently, it has been shown that current urban walkability has been influenced by historical discriminatory neighborhood disinvestment. However, the relationship between this systemic racism and obesity has not been extensively studied. The objective of this study was to evaluate the association of neighborhood walkability and redlining, a historical practice of denying home loans to communities of color, with childhood obesity. We evaluated neighborhood walkability and walkable destinations for 250 participants of the Healthy Start cohort, based in the Denver metropolitan region. Eligible participants attended an examination between ages 4 and 8. Walkable destinations and redlining geolocations were determined based on residential addresses, and a weighting system for destination types was developed. Sidewalks and trails in Denver were included in the network analyst tool in ArcMap to calculate the precise walkable environment for each child. We implemented linear regression models to estimate associations between neighborhood characteristics and child body mass index (BMI) z-scores and fat mass percent. There was a significant association between child BMI and redlining (ß: 1.36, 95% CI: 0.106, 2.620). We did not find an association between walkability measures and childhood obesity outcomes. We propose that cities such as Denver pursue built environment policies, such as inclusionary zoning and direct investments in neighborhoods that have been historically neglected, to reduce the childhood health impacts of segregated poverty, and suggest further studies on the influences that redlining and urban built environment factors have on childhood obesity.