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.

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.

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).

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.

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.

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.

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.

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.

Preliminary investigation of a hypertonic saline nasal rinse as a hygienic intervention in dairy workers.

Livestock workers experience an increased burden of bioaerosol-induced respiratory disease including a high prevalence of rhinosinusitis. Dairy operations generate bioaerosols spanning the inhalable size fraction (0-100 µm) containing bacterial constituents such as endotoxin. Particles with an aerodynamic diameter between 10 and 100 µm are known to deposit in the nasopharyngeal region and likely affect the upper respiratory tract. We evaluated the effectiveness of a hypertonic saline nasal lavage in reducing inflammatory responses in dairy workers from a high-volume dairy operation. Inhalable personal breathing zone samples and pre-/post-shift nasal lavage samples from each participant over five consecutive days were collected. The treatment group (n = 5) received hypertonic saline while the control group (n = 5) received normotonic saline. Personal breathing zone samples were analyzed for particulate concentrations and endotoxin using gravimetric and enzymatic methods, respectively. Pro- and anti-inflammatory cytokines (i.e., IL-8, IL-10, and TNF-α) were measured from nasal lavage samples using a multiplex assay. Inhalable dust concentrations ranged from 0.15 to 1.9 mg/m3. Concentrations of both pro- and anti-inflammatory cytokines, specifically IL-6, IL-8, and IL-10, were significantly higher in the treatment group compared to the control group (p < 0.02, p < 0.04, and p < 0.01, respectively). Further analysis of IL-10 anti-inflammatory indicates a positive association between hypertonic saline administration and IL-10 production. This pilot study demonstrates that hypertonic saline nasal lavages were successful in upregulating anti-inflammatory cytokines to support larger interventional studies.

Disparities in Air Pollutants Across Racial, Ethnic, and Poverty Groups at US Public Schools.

We investigate socioeconomic disparities in air quality at public schools in the contiguous US using high resolution estimates of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations. We find that schools with higher proportions of people of color (POC) and students eligible for the federal free or reduced lunch program, a proxy for poverty level, are associated with higher pollutant concentrations. For example, we find that the median annual NO2 concentration for White students, nationally, was 7.7 ppbv, compared to 9.2 ppbv for Black and African American students. Statewide and regional disparities in pollutant concentrations across racial, ethnic, and poverty groups are consistent with nationwide results, where elevated NO2 concentrations were associated with schools with higher proportions of POC and higher levels of poverty. Similar, though smaller, differences were found in PM2.5 across racial and ethnic groups in most states. Racial, ethnic, and economic segregation across the rural-urban divide is likely an important factor in pollution disparities at US public schools. We identify distinct regional patterns of disparities, highlighting differences between California, New York, and Florida. Finally, we highlight that disparities exist not only across urban and non-urban lines but also within urban environments.

Using non-parametric Bayes shrinkage to assess relationships between multiple environmental and social stressors and neonatal size and body composition in the Healthy Start cohort.

BACKGROUND: Both environmental and social factors have been linked to birth weight and adiposity at birth, but few studies consider the effects of exposure mixtures. Our objective was to identify which components of a mixture of neighborhood-level environmental and social exposures were driving associations with birth weight and adiposity at birth in the Healthy Start cohort. METHODS: Exposures were assessed at the census tract level and included air pollution, built environment characteristics, and socioeconomic status. Prenatal exposures were assigned based on address at enrollment. Birth weight was measured at delivery and adiposity was measured using air displacement plethysmography within three days. We used non-parametric Bayes shrinkage (NPB) to identify exposures that were associated with our outcomes of interest. NPB models were compared to single-predictor linear regression. We also included generalized additive models (GAM) to assess nonlinear relationships. All regression models were adjusted for individual-level covariates, including maternal age, pre-pregnancy BMI, and smoking. RESULTS: Results from NPB models showed most exposures were negatively associated with birth weight, though credible intervals were wide and generally contained zero. However, the NPB model identified an interaction between ozone and temperature on birth weight, and the GAM suggested potential non-linear relationships. For associations between ozone or temperature with birth weight, we observed effect modification by maternal race/ethnicity, where effects were stronger for mothers who identified as a race or ethnicity other than non-Hispanic White. No associations with adiposity at birth were observed. CONCLUSIONS: NPB identified prenatal exposures to ozone and temperature as predictors of birth weight, and mothers who identify as a race or ethnicity other than non-Hispanic White might be disproportionately impacted. However, NPB models may have limited applicability when non-linear effects are present. Future work should consider a two-stage approach where NPB is used to reduce dimensionality and alternative approaches examine non-linear effects.

Early-life exposure to tobacco and childhood adiposity: Identifying windows of susceptibility.

BACKGROUND: Early-life exposure to tobacco is associated with obesity, but the most susceptible developmental periods are unknown. OBJECTIVE: To explore windows of susceptibility in a cohort of 568 mother-child pairs. METHODS: We measured seven measures of tobacco exposure (five self-reported and two biomarkers) spanning from pre-conception to age 5 years. Mothers self-reported active smoking (pre-conception, 17 weeks, and delivery) and household smokers (5 and 18 months postnatally). Cotinine was measured in maternal urine (27 weeks) and child urine (5 years). Adiposity (fat mass percentage) was measured at birth and 5 years via air displacement plethysmography. Using a multiple informant approach, we tested whether adiposity (5 years) and changes in adiposity (from birth to 5 years) differed by the seven measures of tobacco exposure. RESULTS: The associations may depend on timing. For example, only pre-conception (ß = 3.1%; 95% CI: 1.0-5.1) and late gestation (ß = 4.0%; 95% CI: 0.4-7.6) exposures influenced adiposity accretion from birth to 5 years (p for interaction = 0.01). Early infancy exposure was also associated with 1.7% higher adiposity at 5 years (95% CI: 0.1-3.2). Mid-pregnancy and early childhood exposures did not influence adiposity. CONCLUSIONS: Pre-conception, late gestation, and early infancy exposures to tobacco may have the greatest impact on childhood adiposity.

Association between air pollution and COVID-19 disease severity via Bayesian multinomial logistic regression with partially missing outcomes.

Recent ecological analyses suggest air pollution exposure may increase susceptibility to and severity of coronavirus disease 2019 (COVID-19). Individual-level studies are needed to clarify the relationship between air pollution exposure and COVID-19 outcomes. We conduct an individual-level analysis of long-term exposure to air pollution and weather on peak COVID-19 severity. We develop a Bayesian multinomial logistic regression model with a multiple imputation approach to impute partially missing health outcomes. Our approach is based on the stick-breaking representation of the multinomial distribution, which offers computational advantages, but presents challenges in interpreting regression coefficients. We propose a novel inferential approach to address these challenges. In a simulation study, we demonstrate our method's ability to impute missing outcome data and improve estimation of regression coefficients compared to a complete case analysis. In our analysis of 55,273 COVID-19 cases in Denver, Colorado, increased annual exposure to fine particulate matter in the year prior to the pandemic was associated with increased risk of severe COVID-19 outcomes. We also found COVID-19 disease severity to be associated with interactions between exposures. Our individual-level analysis fills a gap in the literature and helps to elucidate the association between long-term exposure to air pollution and COVID-19 outcomes.

Associations between combined exposure to environmental hazards and social stressors at the neighborhood level and individual perinatal outcomes in the ECHO-wide cohort.

Limited studies examine how prenatal environmental and social exposures jointly impact perinatal health. Here we investigated relationships between a neighborhood-level combined exposure (CE) index assessed during pregnancy and perinatal outcomes, including birthweight, gestational age, and preterm birth. Across all participants, higher CE index scores were associated with small decreases in birthweight and gestational age. We also observed effect modification by race; infants born to Black pregnant people had a greater risk of preterm birth for higher CE values compared to White infants. Overall, our results suggest that neighborhood social and environmental exposures have a small but measurable joint effect on neonatal indicators of health.

Ambient air pollution during pregnancy and DNA methylation in umbilical cord blood, with potential mediation of associations with infant adiposity: The Healthy Start study.

BACKGROUND: Prenatal exposure to ambient air pollution has been associated with adverse offspring health outcomes. Childhood health effects of prenatal exposures may be mediated through changes to DNA methylation detectable at birth. METHODS: Among 429 non-smoking women in a cohort study of mother-infant pairs in Colorado, USA, we estimated associations between prenatal exposure to ambient fine particulate matter (PM2.5) and ozone (O3), and epigenome-wide DNA methylation of umbilical cord blood cells at delivery (2010-2014). We calculated average PM2.5 and O3 in each trimester of pregnancy and the full pregnancy using inverse-distance-weighted interpolation. We fit linear regression models adjusted for potential confounders and cell proportions to estimate associations between air pollutants and methylation at each of 432,943 CpGs. Differentially methylated regions (DMRs) were identified using comb-p. Previously in this cohort, we reported positive associations between 3rd trimester O3 exposure and infant adiposity at 5 months of age. Here, we quantified the potential for mediation of that association by changes in DNA methylation in cord blood. RESULTS: We identified several DMRs for each pollutant and period of pregnancy. The greatest number of significant DMRs were associated with third trimester PM2.5 (21 DMRs). No single CpGs were associated with air pollutants at a false discovery rate <0.05. We found that up to 8% of the effect of 3rd trimester O3 on 5-month adiposity may be mediated by locus-specific methylation changes, but mediation estimates were not statistically significant. CONCLUSIONS: Differentially methylated regions in cord blood were identified in association with maternal exposure to PM2.5 and O3. Genes annotated to the significant sites played roles in cardiometabolic disease, immune function and inflammation, and neurologic disorders. We found limited evidence of mediation by DNA methylation of associations between third trimester O3 exposure and 5-month infant adiposity.