Despite US air quality improvements since the 1990 Clean Air Act Amendments, disparities in air pollution between communities persist. We studied whether persistent within-city geospatial disparities in pollution continued over time in historically minoritized and under-resourced areas codified as “redlined” in 1930’s government mapping. We evaluated how longitudinal demographic patterns and disparities in community wealth and resources related to historical redlining score category in three US urban areas: Boston, MA, Nashville, TN, and Detroit, MI. We then examined longitudinal associations of redlining with changing levels of the air pollutants PM2.5 and NO2 between 2000 and 2016 in these cities. Our approach utilized daily estimates of air pollution levels from models with high spatiotemporal resolution, digitized redlining maps, and census data to evaluate temporal trends by redlining categories at the census tract level. Demographic and socioeconomic changes over time differed by city, but for each city, historically redlined areas continued to have a greater proportion of Black residents, higher poverty rates, lower income and home values, and a higher social vulnerability index (SVI). Over all areas, air pollution levels declined markedly over time, but for annual averaged NO2, redlining-area-associated exposure disparities persisted in Boston and widened in Nashville. In contrast, by 2016, regardless of redlining history, areas in Detroit had similar NO2 pollution levels. Our results highlight the lasting social, economic, and environmental effects of urban discriminatory practices, also showing that in some cities, areas may be equally exposed to specific criteria pollutants, regardless of area wealth.

Children are uniquely vulnerable to the neurotoxic effects of air pollution because their brains continue to develop throughout childhood. Indoor air pollution comprises a mixture of several pollutants and is influenced by both indoor and outdoor air pollutant sources. Growing evidence from animal models and epidemiological studies illustrates the adverse effects of air pollutants, especially particulate matter ≤2.5 μm (PM2.5), on cognitive function and academic performance due to its ability to generate oxidative stress and elicit neuroinflammation. Interventions such as air filtration can meaningfully reduce indoor concentrations of pollutants such as PM2.5. Given the significant time children spend indoors in home, school, and childcare settings, indoor air quality interventions are apotential tool to mitigate adverse health effects of indoor air pollutants in children. However, most interventional studies of indoor air pollution focus on improving respiratory outcomes, such as asthma. Here, we conducted a narrative review to collate studies on indoor air pollution interventions that assess neurobehavioral outcomes. Ultimately, our goal was to highlight potential future directions for additional interventional studies that may contribute to public health efforts to optimize neurobehavioral outcomes in children. IMPACT: Mounting evidence suggests indoor air pollution presents a public health concern for neurobehavioral outcomes. Children are particularly vulnerable to the adverse effects of indoor air pollution and subsequent neurobehavioral outcomes. While studies illustrate potential benefits of indoor air pollution interventions on respiratory outcomes, less is known about neurobehavioral outcomes. This narrative review adds to existing literature by summarizing studies of indoor air pollution interventions and neurobehavioral outcomes published in the past 20 years. This review discusses potential next steps for future interventional studies on indoor air quality and child neurobehavior.

BACKGROUND:Social and environmental exposures, typically characterized at residential locations, are linked to adverse respiratory outcomes in children; yet, children spend a significant amount of time in school. Little is known about how socio-demographic and environmental exposures vary between home and school settings. OBJECTIVES:The objectives of this study were to compare home and school exposures and to assess whether these differences were consistent across cities and varied by home-school distance. METHODS:Home and school addresses were geocoded for 6-13 year olds (n = 923) from the Environmental influences on Child Health Outcomes (ECHO) consortium. Children were drawn from cohorts located in New York City (NYC), Boston, Cincinnati, Baltimore, and St. Louis. Four categories of exposures were assessed: neighborhood socio-demographics (assigned at the census-tract level), ambient pollution (fine particulate matter (PM2.5); 1 × 1 km grids), traffic-exposure (primary/secondary road proximity, traffic/truck density; 400 m-buffer), and green-space (Enhanced Vegetation Index; 500-m, 1500-m, and 2500-m buffer). RESULTS:Overall, neighborhood socio-demographic characteristics were less favorable near home vs school including median household income ($58,125 vs $63,315), poverty (7.8% vs 5.9%), percentage of residents with less than high school education attainment (9.8% vs 8.4%), households receiving public assistance (7.6% vs 6.0%; p < 0.002 for all). Home-school differences were greatest for poverty and receiving public assistance in Baltimore (median: 48.9% and 39.3%) and St. Louis (15.8% and 15.7%), whereas the other cities showed no differences (median values of 0). Overall, children who lived farther from school (≥3.4 km), had greater differences in neighborhood socio-demographics (near vs far median percent difference: 0 vs 16.8% less than high school education, 0 vs 43.1% receiving public assistance) with the largest distance-related percent differences observed in NYC and Baltimore. No meaningful home-school differences were observed in particulate pollution, traffic-exposure, green-space (e.g., home vs school PM2.5: 9.8 vs 9.9 μg/m3) regardless of the distance between home and school. IMPACT:Children within our longitudinal birth cohorts experienced less optimal socio-demographic conditions at home compared to school, particularly those from low-income families and those traveling further to go to school; however, outdoor exposures such as PM2.5, traffic, and green-space were similar. Our findings suggest that interventions to reduce environmental health inequities may need to address social and structural disparities at home, such as housing quality and neighborhood socioeconomic status (SES). Additionally, schools may offer an opportunity to provide beneficial exposures, potentially buffering some of the adverse SES-related exposures experienced at home. Overall, our findings provide rationale for a holistic assessment of the social and environmental exposure profile in future environmental health research.

Background:Children encounter multiple indoor and outdoor environmental exposures in early life. We assessed the independent effects of indoor home exposures and ambient particulate matter with an aerodynamic diameter ≤2.5 µm (PM2.5) on early childhood asthma diagnosis. Methods:We included 6,413 children born 1987-2016 from nine United States prospective birth cohorts from the Environmental Influences on Child Health Outcomes consortium, with complete covariate and outcome data. Exposures were (1) average ambient PM2.5 levels during the first 3 years of life, and (2) indoor home exposures, including water damage/home dampness during infancy/childhood, dogs/cats at home during infancy, dust mite allergen during infancy/childhood. Asthma was defined as caregiver-reported or doctor-diagnosed asthma anytime from birth to age 5. We applied Cox proportional hazards models, adjusting for individual-level and neighborhood-level confounders. Cohort-specific effects were implemented as fixed effects. Results:By age 5 years, 10.3%-50.3% of children had developed asthma across general-risk and high-risk cohorts. We found a significant detrimental association of PM2.5 and water damage/home dampness, and a protective association of dogs in the home with risk of childhood asthma, regardless of PM2.5 adjustment. The effect of having both water damage/home dampness and high PM2.5 on asthma diagnosis was greater than that of no water damage/home dampness and having low PM2.5 (hazard ratio: 1.95 [95% confidence interval = 1.19, 3.20]). There were no significant associations with household cats or dust mites. Conclusion:Multiple early exposures, such as PM2.5, home dampness, and absence of dogs in the home, should be considered together as risk factors for childhood asthma.

BACKGROUND:Early childhood wheeze is characterized by heterogeneous trajectories having differential associations with later-life asthma development. OBJECTIVE:We sought to determine how early-life wheeze trajectories impact later life asthma gene expression. METHODS:The Children's Respiratory Environmental Workgroup is a collective of 12 birth cohorts, 7 of which conducted an additional visit with a nasal lavage collected and subjected to bulk RNA-sequencing. Early-life wheeze trajectories were defined using latent class analysis of longitudinal early-life wheezing data. Weighted gene correlation network analysis was used to associate gene expression patterns and current asthma with early-life wheeze trajectories. RESULTS:We investigated 743 children (mean age, 17 ± 5.1 years; 360 [48.5%] male). Four patterns of early-life wheeze were identified: infrequent, transient, late-onset, and persistent. Early-life transient wheeze was associated with gene expression patterns related to increased antiviral response, and late-onset wheeze was associated with decreased insulin signaling and glucose metabolism. Early-life persistent wheeze was associated with gene expression modules of type 2 inflammation and epithelial development, but these modules did not distinguish those with current asthma. Children who had persistent wheeze in early life and current asthma displayed a unique increase in expression of genes enriched for neuronal processes and ciliated epithelial function compared with those without asthma. CONCLUSIONS:Early-life longitudinal wheeze trajectories are associated with specific asthma transcriptomes later in life. These data suggest that early-life asthma prevention strategies may be most beneficial when tailored to the specific wheeze pattern.

Rationale: Race-based estimates of pulmonary function in children could influence the evaluation of asthma in children from racial and ethnic minoritized backgrounds. Objectives: To determine if race-neutral (Global Lung Function Initiative [GLI]-Global) versus race-specific (GLI-Race-Specific) reference equations differentially impact spirometry evaluation of childhood asthma. Methods: The analysis included 8,719 children aged 5 to <12 years from 27 cohorts across the United States grouped by parent-reported race and ethnicity. We analyzed how the equations affected FEV1, FVC, and FEV1/FVC z-scores. We used multivariable logistic models to evaluate associations between z-scores calculated with different equations and asthma diagnosis, emergency department visits, and hospitalization. Measurements and Main Results: For Black children, the GLI-Global versus GLI-Race-Specific equations estimated significantly lower z-scores for FEV1 and FVC but similar values for FEV1/FVC, thus increasing the proportion of children classified with low FEV1 by 14%. Although both equations yielded strong inverse relationships between FEV1 and FEV1/FVC z-scores and asthma outcomes, these relationships varied across racial and ethnic groups (P < 0.05). For any given FEV1 or FEV1/FVC z-score, asthma diagnosis and emergency department visits were higher among Black and Hispanic than among White children (P < 0.05). For FEV1, GLI-Global equations estimated asthma outcomes that were more uniform across racial and ethnic groups. Conclusions: Parent-reported race and ethnicity influenced relationships between lung function and asthma outcomes. Our data show no advantage to race-specific equations for evaluating childhood asthma, and the potential for race-specific equations to obscure lung impairment in disadvantaged children strongly supports using race-neutral equations.

IMPORTANCE:Access to healthy and affordable foods may play a role in reducing inflammation and in healthy pulmonary immune system development. OBJECTIVE:To investigate the association between residing in a low-income and low-food-access (LILA) neighbourhood and risk of childhood asthma. A positive association was hypothesised. DESIGN, SETTING AND PARTICIPANTS:This prospective cohort study consists of 16 012 children from 35 longitudinal studies in the Environmental influences on Child Health Outcomes programme (children born 1998-2021) from across the contiguous USA. We conducted survival analyses adjusted for child sex, race/ethnicity, maternal education, gestational smoking, and parental history of asthma. EXPOSURES:Several commonly used geospatial food access metrics were linked to residential locations including: LILA census tracts where the nearest supermarket is >1 mile in urban and >10 miles in rural areas (LILA1 and 10), >1 mile in urban and >20 miles in rural areas (LILA1 and 20), >0.5 mile in urban and >10 miles in rural areas (LILA0.5 and 10), and >0.5 mile without a vehicle or >20 miles (LILAvehicle). Each metric was linked to lifetime residential history timelines then dichotomised according to whether the child had spent at least 75% of their life living in a LILA area separately for birth through age 5 years (cumulative early childhood) and birth through age 11 years (cumulative middle childhood). MAIN OUTCOMESS AND MEASURES:Asthma incidence in cumulative early and middle childhood. RESULTS:Residing in a LILA0.5 and 10 and LILAvehicleneighbourhood was associated with a higher asthma incidence in cumulative early and middle childhood. The LILA0.5 and 10 and LILAvehicle associations were stronger for asthma during cumulative early childhood, where we observed hazard ratios of 1.13 (95% CI 1.02 to 1.24) and 1.13 (95% CI 1.01 to 1.27), respectively. The associations were higher among children who were Hispanic, were female and had lower maternal education. CONCLUSION AND RELEVANCE:Limited residential food access was associated with higher childhood asthma incidence, especially among female and Hispanic children and those with lower maternal education. Our findings support multipronged efforts to increase access to healthy and affordable food options and lower food insecurity in LILA neighbourhoods.

IntroductionFine particulate matter (PM2.5) air pollution is associated with increased internalizing symptoms (e.g. depressive and anxiety symptoms), particularly during adolescence—a critical period for the emergence of anxiety disorders and vulnerability to neurotoxicants. Preclinical studies suggest that inflammation, including cytokines, reactive proteins, and lipid mediators, may explain the link between PM2.5 and psychiatric risk. However, growing evidence suggests that these relationships may differ by sex, with females potentially more vulnerable to the effects of air pollution on psychiatric symptoms, though the underlying mechanisms remain unclear.MethodsThis study examined the relationships among recent (past-month) PM2.5 exposure, peripheral inflammatory markers, and anxiety and depressive symptoms in 78 adolescents (M ± SD = 13.3 ± 2.3 years, 48.7% female) from the Detroit, MI area.ResultsHigher PM2.5 concentrations were significantly associated with elevated levels of inflammatory lipid mediators: PGE2, 12(S)-HETE, 12(S)-HEPE, and 15(S)-HETE. A significant PM2.5-by-sex interaction was observed for IL-6, with higher PM2.5 exposure associated with higher IL-6 concentrations in females but not males. Additionally, higher PM2.5 concentrations were significantly associated with greater total anxiety, generalized anxiety, and social anxiety symptoms, but only in females. Higher IL-8 concentrations were associated with greater depressive symptoms, and a significant TNF-α-by-sex interaction was observed for total and social anxiety symptoms, with higher TNF-α concentrations linked to greater symptoms in females but not males.DiscussionThese findings suggest that PM2.5 exposure is associated with inflammation and anxiety symptoms in adolescence, with notable sex differences. As a modifiable risk factor, reducing outdoor air pollution exposure may help mitigate psychiatric symptoms in youth.

Prior research has shown that place-based environmental exposures and community characteristics, known as geomarkers, are associated with accelerated lung function decline and increased mortality in individuals with cystic fibrosis (CF). Although geomarkers have been linked to pulmonary outcomes in other respiratory diseases, it is unknown which have the greatest predictive power for rapid lung function decline in CF. We adapted an existing statistical procedure, which arranges candidate variables in a k-dimensional hypercube, where the hypercube forms a set of variables for a multi-stage selection process involving complex longitudinal data. We embedded the hypercube within a dynamic prediction model of rapid lung function decline, in order to accommodate complexity in lung function trajectories. This practical approach simultaneously selects a handful of genuinely predictive markers among candidates and accounts for complex correlations in longitudinal marker data. Our method is applied to actual geomarker and lung-function outcomes data from the existing Cystic Fibrosis Patient Registry and Cincinnati Cystic Fibrosis Center datasets. We applied a 4 × 4 × 4 3-D hypercube to the national and local datasets and selected a subset of geomarkers using p-values from testing coefficients of the association between each geomarker and lung function decline in the dynamic prediction model. Based on the national data analyses, some road density–related geomarkers were selected, including some air pollution–related and greenspace-related variables. Simulations showed the proposed method’s variable selection efficacy and robust performance in identifying true predictors, particularly under weak correlation (ρ≤0.6), although performance dipped with stronger correlations (ρ=0.9). The proposed method is a useful approach for selecting a small set of truly relevant demographic, clinical, and place-based predictors of rapid lung function decline while accounting for the complex correlations inherent in longitudinal lung-function data. We found that selection results differed according to spatial resolution of the geomarkers. Our findings have potential to improve care decisions for people with CF.

Background:Characterization of US sociodemographic disparities in air pollution respiratory effects has often been limited by lack of participant diversity, geography, exposure characterization, and small sample size. Methods:We included 34 sites comprising 23,234 children (born 1981-2021) from the Environmental influences on Child Health Outcomes (ECHO) Program with data on asthma diagnosis until age 10 (182,008 person-years). Predicted annual exposure to fine particulate matter (1988-2021), nitrogen dioxide (2000-2016), and ground ozone (2000-2016) were assigned based on residential histories. For each pollutant, we fitted time-varying Cox models adjusted for time trend, site, and several area- and individual-level sociodemographic features that were separately considered as modifiers via an interaction with exposure. Results:The hazard ratio of incident asthma by age 10 years was 1.19 (95% CI = 1.10, 1.28), 1.19 (95% CI = 1.05, 1.34), and 1.11 (95% CI = 1.01, 1.22) of an interquartile range increase in prior-year exposure to fine particulate matter (6.17 µg/m3), nitrogen dioxide (15.37 ppb), and ozone (6.87 ppb), respectively. For both fine particulate and nitrogen dioxide, children from areas with a higher proportion of Black residents or with a higher population density had greater pollution-associated risks of incident asthma. For ozone, asthma risks were enhanced in less dense areas. Conclusions:US efforts to mitigate childhood asthma risk by reducing air pollution would benefit from addressing root structural causes of vulnerability and susceptibility, including spatial patterning in air pollution sources and exposures as well as social and economic disadvantage.

Prenatal exposure to air pollution is an important risk factor for child health outcomes, including asthma. Identification of DNA methylation changes associated with air pollutant exposure can provide new intervention targets to improve children’s health. The aim of this study is to test the association between prenatal air pollutant exposure and DNA methylation in developmental and asthma-/allergy-relevant biospecimens (placenta, buccal, cord blood, nasal mucosa, and lavage). A subset of 2294 biospecimens collected from 1906 child participants enrolled in the Environmental Influences on Child Health Outcomes program with prenatal air pollutant and high-quality Illumina Asthma&Allergy DNA methylation array measures (n = 37 197 probes) were included. Prenatal ozone, nitrogen dioxide, and fine particulate matter were derived using residential history during pregnancy and spatiotemporal models. For each pollutant, biospecimen type, and prenatal exposure window, we estimated the effects of air pollution on gene DNA methylation levels. We compared results across pollutants, biospecimen types, and trimesters and tested for critical months of exposure using distributed lag models. DNA methylation levels at 154 out of 4746 tested genes were associated with air pollution; over 95% were exposure window, pollutant, and biospecimen-type specific. The fewest gene associations were detected in trimester 2, relative to other exposure windows. A variety of trends in methylation patterns were observed in response to lagged monthly pollution levels. Child DNA methylation changes at specific respiratory- and immune-relevant genes are associated with prenatal air pollutant exposures. Future studies should examine the relationship between these pollution-sensitive genes and child health.

Place-based measures of environmental exposures, climate, neighborhood characteristics, housing, and other social determinants of health are powerful predictors of health outcomes, including asthma. In addition, social determinants of health are likely causes of the persistent racial and ethnic disparities in asthma prevalence and morbidity. The objectives of this commentary are to (1) provide an overview of geospatial data and resources available to researchers to incorporate into studies of asthma-related outcomes, (2) provide a general approach to consider geospatial data in birth cohorts, (3) demonstrate the use of geospatial data in asthma-related research, and (4) highlight challenges and future opportunities for the use of geospatial data in asthma-related research and birth cohort studies. By integrating place-based data into longitudinal studies, researchers may identify critical drivers of asthma and asthma-related disparities and develop strategies to mitigate their impact.

The study objective was to examine how the changes in outdoor concentration of traffic-related aerosol at schools occurring due to an anti-idling campaign affect the indoor aerosol concentration. Four urban public schools featuring different average numbers of school buses and cars and located at different distances from major urban traffic arteries were selected in Cincinnati (Ohio, USA). For each school, the indoor and outdoor air monitoring was conducted before and after the implementation of anti-idling campaign. Additionally, the ambient air was monitored at four "community" sites representing the background aerosol. The PM2.5 samples were collected and subjected to gravimetric, carbon and elemental analysis. The outdoor concentrations of PM2.5 and its relevant elemental constituents were consistent with the data reported in previous studies. Following the anti-idling campaign, the outdoor concentration of most elements decreased at two schools although only a fraction showed statistically significant changes. After accounting for the background aerosol changes, the positive impact of the anti-idling campaign was demonstrated only for one school – with the most intense local traffic. For this school, reduction of the outdoor elemental concentrations was followed by a decrease in the corresponding indoor concentrations (R2 = 0.47, p < 0.05). The data suggests that in cases when traffic emission is the dominant pollution source in the school vicinity, the changes in outdoor air quality associated with the anti-idling campaign are capable of reducing the children exposure to traffic aerosols inside the schools.

BACKGROUND:The goal of treatment of hepatitis B virus (HBV) and human immunodeficiency virus (HIV) coinfection is suppression of both viruses; yet incomplete HBV suppression on tenofovir (TFV) disoproxil fumarate (TDF)-based antiretroviral therapy (ART) is common. This study investigated TFV resistance-associated mutations (RAMs) in individuals with HBV/HIV coinfection with viremia on TDF/lamivudine (3TC)-containing ART. METHODS:Samples from individuals with HBV DNA levels ≥20 IU/mL in a cross-sectional study of 138 persons with HBV/HIV coinfection in Ghana were analyzed in the present study. HBV was sequenced for RAM analysis. TFV-diphosphate (TFV-DP) concentration in peripheral blood mononuclear cells (PBMCs) was used to assess ART adherence level. RESULTS:Nine of 138 participants (6.5 %) had detectable HBV DNA levels ≥20 IU/mL while on ART. Seven of the nine participants had TFV-DP concentrations commensurate with 7 doses per week, and six had suppressed HIV RNA. Phylogenetic analysis revealed that eight sequences were HBV genotype E, with one genotype E/A recombinant. Ten previously-reported TFV RAMs were present in the study samples; eight were wild-type for HBV genotype E. The non-genotype-E-wild-type point mutations M267L and K333Q were found in two and one patients, respectively. No 3TC RAMs were found. CONCLUSION:HBV viremia despite high adherence to TDF/3TC-based ART may be associated with the presence of TFV RAMs. These findings highlight the need for enhanced resistance monitoring and further research to examine the clinical significance of reported TFV RAMs. Individuals with HBV/HIV coinfection and TFV resistance on TDF-based ART may need alternative treatment strategies.

Few studies have addressed the potential changes in particulate matter (PM) exposure occurring in major metropolitan areas over substantial time periods, e.g., 5 or 10 years. The present study examined changes in the PM2.5 concentration and elemental composition between two monitoring campaigns carried out in 2002–2005 and 2010–2011 within the Greater Cincinnati area (USA). This area is recognized for high volume of diesel truck traffic (about 10 million trucks annually on regional freeways). The 24-hour filter samples were collected at four sites. General linear models were used to examine differences between the two data sets for elemental carbon (EC), organic carbon (OC), and EC/OC. The comparison was extended to the concentrations of PM2.5 and its relevant elemental constituents. At one site, which was previously identified as a particularly hot spot for traffic/diesel air pollution, the concentrations of most traffic related elements as well as EC and EC/OC ratio significantly decreased (p < 0.05) between the two campaigns. No significant differences between carbon data generated in the two campaigns were observed at the other three monitoring stations. These findings did not depend on whether the comparison model accounted for wind speed and direction. The EC/OC determined in the recent campaign across all sites showed no significant differences between the Summer and Fall data but Winter values were significantly lower. The site with the highest traffic influence revealed no significant seasonal difference in PM2.5 but essentially all relevant elements showed significant seasonal variations between the Fall (higher) and Winter (lower). The findings suggest that air quality and engine exhaust control policies implemented between 2005 and 2010 have not produced significant changes in metropolitan traffic air pollution levels. However, the decreasing trends in PM2.5, Ti, V, Mn, Fe, Zn, Br, and Pb, EC, OC, and EC/OC may become sustainable over a longer time.

Scholarly activity is a key component of most residency programmes. To establish fundamental research skills and fill gaps within training curricula, we developed an online, asynchronous set of modules called Research 101 to introduce trainees to various topics that are germane to the conduct of research and evaluated its effectiveness in resident research education. Research 101 was utilised by residents at One Brooklyn Health in Brooklyn, NY. Resident knowledge, confidence, and satisfaction were assessed using pre- and post-module surveys with 5-point Likert scaled questions, open-ended text responses, and a multiple-choice quiz. Pre-module survey results indicated that residents were most confident with the Aligning expectations, Introduction to research, and Study design and data analysis basics modules and least confident with the Submitting an Institutional Review Board protocol and Presenting your summer research modules. Post-module survey responses demonstrated increased learning compared to pre-module results for all modules and learning objectives (p < 0.0001). “This module met my needs” was endorsed 91.4% of the time. The median score for the final quiz that consisted of 25 multiple-choice questions was 23. Thematic analysis of open-ended post-module survey responses identified multiple strengths and opportunities for improvement in course content and instructional methods. These data demonstrate that residents benefit from completion of Research 101, as post-module survey scores were significantly higher than pre-module survey scores for all modules and questions, final quiz scores were high, and open-ended responses highlighted opportunities for additional resident learning.

Importance:Exposure to outdoor air pollution contributes to childhood asthma development, but many studies lack the geographic, racial and ethnic, and socioeconomic diversity to evaluate susceptibility by individual-level and community-level contextual factors. Objective:To examine early life exposure to fine particulate matter (PM2.5) and nitrogen oxide (NO2) air pollution and asthma risk by early and middle childhood, and whether individual and community-level characteristics modify associations between air pollution exposure and asthma. Design, Setting, and Participants:This cohort study included children enrolled in cohorts participating in the Children's Respiratory and Environmental Workgroup consortium. The birth cohorts were located throughout the US, recruited between 1987 and 2007, and followed up through age 11 years. The survival analysis was adjusted for mother's education, parental asthma, smoking during pregnancy, child's race and ethnicity, sex, neighborhood characteristics, and cohort. Statistical analysis was performed from February 2022 to December 2023. Exposure:Early-life exposures to PM2.5 and NO2 according to participants' birth address. Main Outcomes and Measures:Caregiver report of physician-diagnosed asthma through early (age 4 years) and middle (age 11 years) childhood. Results:Among 5279 children included, 1659 (31.4%) were Black, 835 (15.8%) were Hispanic, 2555 (48.4%) where White, and 229 (4.3%) were other race or ethnicity; 2721 (51.5%) were male and 2596 (49.2%) were female; 1305 children (24.7%) had asthma by 11 years of age and 954 (18.1%) had asthma by 4 years of age. Mean values of pollutants over the first 3 years of life were associated with asthma incidence. A 1 IQR increase in NO2 (6.1 μg/m3) was associated with increased asthma incidence among children younger than 5 years (HR, 1.25 [95% CI, 1.03-1.52]) and children younger than 11 years (HR, 1.22 [95% CI, 1.04-1.44]). A 1 IQR increase in PM2.5 (3.4 μg/m3) was associated with increased asthma incidence among children younger than 5 years (HR, 1.31 [95% CI, 1.04-1.66]) and children younger than 11 years (OR, 1.23 [95% CI, 1.01-1.50]). Associations of PM2.5 or NO2 with asthma were increased when mothers had less than a high school diploma, among Black children, in communities with fewer child opportunities, and in census tracts with higher percentage Black population and population density; for example, there was a significantly higher association between PM2.5 and asthma incidence by younger than 5 years of age in Black children (HR, 1.60 [95% CI, 1.15-2.22]) compared with White children (HR, 1.17 [95% CI, 0.90-1.52]). Conclusions and Relevance:In this cohort study, early life air pollution was associated with increased asthma incidence by early and middle childhood, with higher risk among minoritized families living in urban communities characterized by fewer opportunities and resources and multiple environmental coexposures. Reducing asthma risk in the US requires air pollution regulation and reduction combined with greater environmental, educational, and health equity at the community level.

Environmental exposures and community characteristics have been linked to accelerated lung function decline in people with cystic fibrosis (CF), but geomarkers, the measurements of these exposures, have not been comprehensively evaluated in a single study. To determine which geomarkers have the greatest predictive potential for lung function decline and pulmonary exacerbation (PEx), a retrospective longitudinal cohort study was performed using novel Bayesian joint covariate selection methods, which were compared with respect to PEx predictive accuracy. Non-stationary Gaussian linear mixed effects models were fitted to data from 151 CF patients aged 6-20 receiving care at a CF Center in the midwestern US (2007-2017). The outcome was forced expiratory volume in 1 s of percent predicted (FEV1pp). Target functions were used to predict PEx from established criteria. Covariates included 11 routinely collected clinical/demographic characteristics and 45 geomarkers comprising 8 categories. Unique covariate selections via four Bayesian penalized regression models (elastic-net, adaptive lasso, ridge, and lasso) were evaluated at both 95 % and 90 % credible intervals (CIs). Resultant models included one to 6 geomarkers (air temperature, percentage of tertiary roads outside urban areas, percentage of impervious nonroad outside urban areas, fine atmospheric particulate matter, fraction achieving high school graduation, and motor vehicle theft) representing weather, impervious descriptor, air pollution, socioeconomic status, and crime categories. Adaptive lasso had the lowest information criteria. For PEx predictive accuracy, covariate selection from the 95 % CI elastic-net had the highest area under the receiver-operating characteristic curve (mean ± standard deviation; 0.780 ± 0.026) along with the 95 % CI ridge and lasso methods (0.780 ± 0.027). The 95 % CI elastic-net had the highest sensitivity (0.773 ± 0.083) while the 95 % CI adaptive lasso had the highest specificity (0.691 ± 0.087), suggesting the need for different geomarker sets depending on monitoring goals. Surveillance of certain geomarkers embedded in prediction algorithms can be used in real-time warning systems for PEx onset.