Causal Mediation of Neighborhood-Level Pediatric Hospitalization Inequities.

BACKGROUND AND OBJECTIVES: Population-wide racial inequities in child health outcomes are well documented. Less is known about causal pathways linking inequities and social, economic, and environmental exposures. Here, we sought to estimate the total inequities in population-level hospitalization rates and determine how much is mediated by place-based exposures and community characteristics. METHODS: We employed a population-wide, neighborhood-level study that included youth <18 years hospitalized between July 1, 2016 and June 30, 2022. We defined a causal directed acyclic graph a priori to estimate the mediating pathways by which marginalized population composition causes census tract-level hospitalization rates. We used negative binomial regression models to estimate hospitalization rate inequities and how much of these inequities were mediated indirectly through place-based social, economic, and environmental exposures. RESULTS: We analyzed 50 719 hospitalizations experienced by 28 390 patients. We calculated census tract-level hospitalization rates per 1000 children, which ranged from 10.9 to 143.0 (median 45.1; interquartile range 34.5 to 60.1) across included tracts. For every 10% increase in the marginalized population, the tract-level hospitalization rate increased by 6.2% (95% confidence interval: 4.5 to 8.0). After adjustment for tract-level community material deprivation, crime risk, English usage, housing tenure, family composition, hospital access, greenspace, traffic-related air pollution, and housing conditions, no inequity remained (0.2%, 95% confidence interval: -2.2 to 2.7). Results differed when considering subsets of asthma, type 1 diabetes, sickle cell anemia, and psychiatric disorders. CONCLUSIONS: Our findings provide additional evidence supporting structural racism as a significant root cause of inequities in child health outcomes, including outcomes at the population level.

Early-Life Exposure to Air Pollution and Childhood Asthma Cumulative Incidence in the ECHO CREW Consortium.

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.

Social determinants of health predict health outcomes following pediatric allogeneic hematopoietic stem cell transplant.

BACKGROUND: Pediatric hematopoietic stem cell transplantation (HCT) is an intensive medical procedure that places substantial financial and logistical burdens on families and is associated with significant health risks, such as graft-versus-host disease (GVHD), and infections. The influence of the social determinants of health (SDoH) on outcomes following pediatric HCT is understudied. This study aimed to examine whether SDoH predicts outcomes following pediatric HCT. PROCEDURE: Data were collected from 84 children who received HCT (Mage  = 5.8 years, SD = 3.7) and their primary caregiver. Detailed demographic information was collected from caregivers at baseline, and child health information was extracted from the electronic medical records. Multivariate logistic regression was used to examine the association between SDoH and health outcomes within a 24-month period following pediatric HCT. RESULTS: After controlling for malignancy as reason for transplant and donor type, lower family income predicted the incidence of chronic GVHD. Neighborhood deprivation, total family income, public health insurance, caregiver relationship status, caregiver educational attainment, and perceived family financial difficulties did not predict acute GVHD or the number of infections. CONCLUSIONS: Total family income is a simple family indicator of SDoH that predicts chronic GVHD after pediatric allogeneic HCT. These findings provide further support for the importance of screening of child and family SDoH risks to ensure that fundamental needs can be met to mitigate potential health disparities for up to 2 years following pediatric HCT.

Social-environmental phenotypes of rapid cystic fibrosis lung disease progression in adolescents and young adults living in the United States.

Background: Cystic fibrosis (CF) is a genetic disease but is greatly impacted by non-genetic (social/environmental and stochastic) influences. Some people with CF experience rapid decline, a precipitous drop in lung function relative to patient- and/or center-level norms. Those who experience rapid decline in early adulthood, compared to adolescence, typically exhibit less severe clinical disease but greater loss of lung function. The extent to which timing and degree of rapid decline are informed by social and environmental determinants of health (geomarkers) is unknown. Methods: A longitudinal cohort study was performed (24,228 patients, aged 6-21 years) using the U.S. CF Foundation Patient Registry. Geomarkers at the ZIP Code Tabulation Area level measured air pollution/respiratory hazards, greenspace, crime, and socioeconomic deprivation. A composite score quantifying social-environmental adversity was created and used in covariate-adjusted functional principal component analysis, which was applied to cluster longitudinal lung function trajectories. Results: Social-environmental phenotyping yielded three primary phenotypes that corresponded to early, middle, and late timing of peak decline in lung function over age. Geographic differences were related to distinct cultural and socioeconomic regions. Extent of peak decline, estimated as forced expiratory volume in 1 s of % predicted/year, ranged from 2.8 to 4.1 % predicted/year depending on social-environmental adversity. Middle decliners with increased social-environmental adversity experienced rapid decline 14.2 months earlier than their counterparts with lower social-environmental adversity, while timing was similar within other phenotypes. Early and middle decliners experienced mortality peaks during early adolescence and adulthood, respectively. Conclusion: While early decliners had the most severe CF lung disease, middle and late decliners lost more lung function. Higher social-environmental adversity associated with increased risk of rapid decline and mortality during young adulthood among middle decliners. This sub-phenotype may benefit from enhanced lung-function monitoring and personalized secondary environmental health interventions to mitigate chemical and non-chemical stressors.

Impact of Environmental Exposures on Lung Cancer in Patients Who Never Smoked.

BACKGROUND: Despite the rising incidence of lung cancer in patients who never smoked, environmental risk factors such as ambient air pollution in this group are poorly described. Our objective was to identify the relationship of environmental exposures with lung cancer in patients who never smoked. METHODS: A prospectively collected database was reviewed for all patients with non-small cell lung carcinoma (NSCLC) who underwent resection from 2006 to 2021. Environmental exposures were estimated using the geocoded home address of patients. Logistic regression was used to determine the association of clinical and environmental variables with smoking status. Kaplan-Meier and Cox proportional hazards analyses were used to assess survival. RESULTS: A total of 665 patients underwent resection for NSCLC, of which 67 (10.1%) were patients who never smoked and 598 (89.9%) were current/former smokers. Patients who never smoked were more likely of white race (p = 0.001) and had well-differentiated tumors with carcinoid or adenocarcinoma histology (p < 0.001). Environmental exposures were similar between groups, but patients who never smoked had less community material deprivation (p = 0.002) measured by household income, education, health insurance, and vacancies. They had improved overall survival (p = 0.012) but equivalent cancer recurrence (p = 0.818) as those who smoked. In univariable Cox analyses, fine particulate matter (HR: 1.447 [95% CI 1.197-1.750], p < 0.001), distance to nearest major roadway (HR: 1.067 [1.024-1.111], p = 0.002), and greenspace (HR: 0.253 [0.087-0.737], p = 0.012) were associated with overall survival in patients who never smoked. CONCLUSIONS: Lung cancer patients who never smoked have unique clinical and pathologic characteristics, including higher socioeconomic status. Interventions to reduce environmental exposures may improve lung cancer survival in this population.

High Resolution and Spatiotemporal Place-Based Computable Exposures at Scale.

Place-based exposures, termed "geomarkers", are powerful determinants of health but are often understudied because of a lack of open data and integration tools. Existing DeGAUSS (Decentralized Geomarker Assessment for Multisite Studies) software has been successfully implemented in multi-site studies, ensuring reproducibility and protection of health information. However, DeGAUSS relies on transporting geomarker data, which is not feasible for high-resolution spatiotemporal data too large to store locally or download over the internet. We expanded the DeGAUSS framework for high-resolution spatiotemporal geomarkers. Our approach stores data subsets based on coarsened location and year in an online repository, and appropriate subsets are downloaded to complete exposure assessment locally using exact date and location. We created and validated two free and open-source DeGAUSS containers for estimation of high-resolution, daily ambient air pollutant exposures, transforming published exposure assessment models into computable exposures for geomarker assessment at scale.

Lung function and secondhand smoke exposure among children with cystic fibrosis: A Bayesian meta-analysis.

BACKGROUND: Secondhand smoke exposure, an important environmental health factor in cystic fibrosis (CF), remains uniquely challenging to children with CF as they strive to maintain pulmonary function during early stages of growth and throughout adolescence. Despite various epidemiologic studies among CF populations, little has been done to coalesce estimates of the association between secondhand smoke exposure and lung function decline. METHODS: A systematic review was performed using PRISMA guidelines. A Bayesian random-effects model was employed to estimate the association between secondhand smoke exposure and change in lung function (measured as FEV1% predicted). RESULTS: Quantitative synthesis of study estimates indicated that second-hand smoke exposure corresponded to a significant drop in FEV1 (estimated decrease: -5.11% predicted; 95% CI: -7.20, -3.47). The estimate of between-study heterogeneity was 1.32% predicted (95% CI: 0.05, 4.26). There was moderate heterogeneity between the 6 analyzed studies that met review criteria (degree of heterogeneity: I2=61.9% [95% CI: 7.3-84.4%] and p = 0.022 from the frequentist method.) CONCLUSIONS: Our results quantify the impact at the pediatric population level and corroborate the assertion that secondhand smoke exposure negatively affects pulmonary function in children with CF. Findings highlight challenges and opportunities for future environmental health interventions in pediatric CF care.

Racial Disparities in Pediatric Inflammatory Bowel Disease Care: Differences in Outcomes and Health Service Utilization Between Black and White Children.

OBJECTIVE: To describe racial inequities in pediatric inflammatory bowel disease care and explore potential drivers. METHODS: We undertook a single-center, comparative cohort study of newly diagnosed Black and non-Hispanic White patients with inflammatory bowel disease, aged <21 years, from January 2013 through 2020. Primary outcome was corticosteroid-free remission (CSFR) at 1 year. Other longitudinal outcomes included sustained CSFR, time to anti-tumor necrosis factor therapy, and evaluation of health service utilization. RESULTS: Among 519 children (89% White, 11% Black), 73% presented with Crohn's disease and 27% with ulcerative colitis. Disease phenotype did not differ by race. More patients from Black families had public insurance (58% vs 30%, P < .001). Black patients were less likely to achieve CSFR 1-year post diagnosis (OR: 0.52, 95% CI:0.3-0.9) and less likely to achieve sustained CSFR (OR: 0.48, 95% CI: 0.25-0.92). When adjusted by insurance type, differences by race to 1-year CSFR were no longer significant (aOR: 0.58; 95% CI: 0.33, 1.04; P = .07). Black patients were more likely to transition from remission to a worsened state, and less likely to transition to remission. We found no differences in biologic therapy utilization or surgical outcomes by race. Black patients had fewer gastroenterology clinic visits and 2-fold increased odds for emergency department visits. CONCLUSIONS: We observed no differences by race in phenotypic presentation and medication usage. Black patients had half the odds of achieving clinical remission, but a degree of this was mediated by insurance status. Understanding the cause of such differences will require further exploration of social determinants of health.

Air pollution exposure and social responsiveness in childhood: The cincinnati combined childhood cohorts.

Autism Spectrum Disorder (ASD) affects about 1 in 44 children and environmental exposures may contribute to disease onset. Air pollution has been associated with adverse neurobehavioral outcomes, yet little research has examined its association with autistic-like behaviors. Therefore, our objective was to examine the association between exposure to air pollution, including NO2 and PM2.5, during pregnancy and the first year of life to ASD-like behaviors during childhood. Participants (n = 435) enrolled in the Cincinnati Childhood Allergy and Air Pollution Study and the Health Outcomes and Measures of the Environment Study were included in the analysis. Daily exposures to NO2 and PM2.5 at the residential addresses of participants were estimated using validated spatiotemporal models and averaged to obtain prenatal and first year exposure estimates. ASD-like behaviors were assessed via the Social Responsiveness Scale (SRS) questionnaire at age 12. Linear regression models adjusting for confounders were applied to estimate the association between pollutants and SRS scores. After adjusting for covariates, the association between NO2 and PM2.5 and SRS scores remained positive but were no longer statistically significant. Prenatal and first year exposure to NO2 were associated with total SRS T-scores with an estimated 0.4 point increase (95% CI: -0.7, 1.6) per 5.2 ppb increase in NO2 exposure and 0.7 point (95% CI: -0.3, 1.6) per 4.2 ppb increase in NO2 exposure, respectively. For PM2.5, a 2.6 µg/m3 increase in prenatal exposure was associated with a 0.1 point increase (95% CI: -1.1, 1.4) in SRS Total T-scores and a 1.3 µg/m3 increase first year of life was associated with a 1 point increase (95% CI: -0.2, 2.3). In summary, exposure to NO2 and PM2.5 during pregnancy and the first year of life were not significantly associated with higher autistic-like behaviors measured with SRS scores after adjustment of covariates. Additional research is warranted given prior studies suggesting air pollution contributes to ASD.

Participant engagement to develop report-back materials for personal air monitoring.

Background: Studies that measure environmental exposures in biological samples frequently provide participants their results. In contrast, studies using personal air monitors do not typically provide participants their monitoring results. The objective of this study was to engage adolescents who completed personal air sampling and their caregivers to develop understandable and actionable report-back documents containing the results of their personal air sampling. Methods: Adolescents and their caregivers who previously completed personal air sampling participated in focus groups to guide the development of report-back materials. We conducted thematic analyses of focus group data to guide the design of the report-back document and convened experts in community engagement, reporting study results, and human subjects research to provide feedback. Final revisions to the report-back document were made based on follow-up focus group feedback. Results: Focus groups identified critical components of an air-monitoring report-back document to include an overview of the pollutant being measured, a comparison of individual personal sampling data to the overall study population, a guide to interpreting results, visualization of individual data, and additional information on pollution sources, health risks, and exposure reduction strategies. Participants also indicated their desire to receive study results in an electronic and interactive format. The final report-back document was electronic and included background information, participants' results presented using interactive maps and figures, and additional material regarding pollution sources. Conclusion: Studies using personal air monitoring technology should provide research participants their results in an understandable and meaningful way to empower participants with increased knowledge to guide exposure reduction strategies.

Built environment factors predictive of early rapid lung function decline in cystic fibrosis.

BACKGROUND: The extent to which environmental exposures and community characteristics of the built environment collectively predict rapid lung function decline, during adolescence and early adulthood in cystic fibrosis (CF), has not been examined. OBJECTIVE: To identify built environment characteristics predictive of rapid CF lung function decline. METHODS: We performed a retrospective, single-center, longitudinal cohort study (n = 173 individuals with CF aged 6-20 years, 2012-2017). We used a stochastic model to predict lung function, measured as forced expiratory volume in 1 s (FEV1 ) of % predicted. Traditional demographic/clinical characteristics were evaluated as predictors. Built environmental predictors included exposure to elemental carbon attributable to traffic sources (ECAT), neighborhood material deprivation (poverty, education, housing, and healthcare access), greenspace near the home, and residential drivetime to the CF center. MEASUREMENTS AND MAIN RESULTS: The final model, which included ECAT, material deprivation index, and greenspace, alongside traditional demographic/clinical predictors, significantly improved fit and prediction, compared with only demographic/clinical predictors (Likelihood Ratio Test statistic: 26.78, p < 0.0001; the difference in Akaike Information Criterion: 15). An increase of 0.1 µg/m3 of ECAT was associated with 0.104% predicted/yr (95% confidence interval: 0.024, 0.183) more rapid decline. Although not statistically significant, material deprivation was similarly associated (0.1-unit increase corresponded to additional decline of 0.103% predicted/year [-0.113, 0.319]). High-risk regional areas of rapid decline and age-related heterogeneity were identified from prediction mapping. CONCLUSION: Traffic-related air pollution exposure is an important predictor of rapid pulmonary decline that, coupled with community-level material deprivation and routinely collected demographic/clinical characteristics, enhance CF prognostication and enable personalized environmental health interventions.

Children from disadvantaged neighborhoods experience disproportionate injury from interpersonal violence.

BACKGROUND: Disparities in pediatric injury have been widely documented and are driven, in part, by differential exposures to social determinants of health (SDH). Here, we hypothesized that neighborhood socioeconomic deprivation and specific sociodemographic characteristics would be associated with interpersonal violence-related injury admission. METHODS: We conducted a retrospective cohort study of all patients ≤16 years, residing in Hamilton County, admitted to our level 1 pediatric trauma center. Residential addresses were geocoded to link admissions with a census tract-level socioeconomic deprivation index. Admissions were categorized as resulting from interpersonal violence or not - based on a mechanism of injury (MOI) of abuse or assault. The percentage of interpersonal violence-related injury admissions was compared across patient demographics and neighborhood deprivation index tertiles. These factors were then evaluated with multivariable regression analysis. RESULTS: Interpersonal violence accounted for 6.2% (394 of 6324) of all injury-related admissions. Interpersonal violence-related injury admission was associated with older age, male sex, Black race, public insurance, and living in tertiles of census tracts with higher socioeconomic deprivation. Those living in the most deprived tertile experienced 62.2% of all interpersonal violence-related injury admissions but only 36.9% of non-violence related injury admissions (p < 0.001). After adjustment, insurance and neighborhood deprivation accounted for much of the increase in interpersonal violence-related admissions for Black compared to White children. CONCLUSIONS: Children from higher deprivation neighborhoods, who are also disproportionately Black and publicly insured, experience a higher burden of interpersonal violence-related injury admissions. Level of evidence Level III.

Racial Fairness in Precision Medicine: Pediatric Asthma Prediction Algorithms.

PURPOSE: Quantify and examine the racial fairness of two widely used childhood asthma predictive precision medicine algorithms: the asthma predictive index (API) and the pediatric asthma risk score (PARS). DESIGN: Apply the API and PARS and evaluate model performance overall and when stratified by race. SETTING: Cincinnati, OH, USA. SUBJECTS: A prospective birth cohort of 590 children with clinically measured asthma diagnosis by age seven. MEASURES: Model diagnostic criteria included sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). ANALYSIS: Significant differences in model performance between Black and white children were considered to be present if the P-value associated with a t-test based on 100 bootstrap replications was less than .05. RESULTS: Compared to predictions for white children, predictions for Black children using the PARS had a higher sensitivity (.88 vs .57), lower specificity (.55 vs .83), higher PPV (.42 vs .33), but a similar NPV (.93 vs .93). Within the API and compared to predictions for white children, predictions for Black children had a higher sensitivity (.63 vs .53), similar specificity (.81 vs .80), higher PPV (.54 vs .28), and lower NPV (.86 vs .92). CONCLUSIONS: Overall, racial disparities in model diagnostic criteria were greatest for sensitivity and specificity in the PARS, but racial disparities existed in three of the four criteria for both the PARS and the API.

Use Of Area-Based Socioeconomic Deprivation Indices: A Scoping Review And Qualitative Analysis.

There is considerable interest among researchers, clinicians, and policy makers in understanding the impact of place on health. In this scoping review and qualitative analysis, we sought to assess area-level socioeconomic deprivation indices used in public health and health outcomes research in the US. We conducted a systematic scoping review to identify area-level socioeconomic deprivation indices commonly used in the US since 2015. We then qualitatively compared the indices based on the input-variable domains, data sources, index creation characteristics, index accessibility, the geography over which the index is applied, and the nature of the output measure or measures. We identified fifteen commonly used indices of area-level socioeconomic deprivation. There were notable differences in the characteristics of each index, particularly in how they define socioeconomic deprivation based on input-variable domains, the geography over which they are applied, and their output measures. These characteristics can help guide future index selection and application in clinical care, research, and policy decisions.

Neighbourhood socio-economic environment predicts adiposity and obesity risk in children under two.

BACKGROUND: Neighbourhood socio-economic environment (SEE) is associated with obesity in older children and adults, but little is known about this relationship in younger children. Breastfeeding is an important preventative of adiposity in childhood, but its relationship with neighbourhood SEE is unknown. AIMS: We assessed differences in adiposity and obesity in children before age two by neighbourhood SEE, controlling for family socio-demographics and breastfeeding duration. MATERIALS AND METHODS: Family socio-demographics, child body mass index z scores (BMIz), and breastfeeding duration were collected at periodic study visits from participants in PREVAIL (n = 245), a birth cohort in Cincinnati, OH. Addresses were assigned a Deprivation Index score, a validated measure of SEE, and dichotomized into highest SEE (least deprived quartile of scores) and not highest SEE (remaining quartiles). Longitudinal and Poisson models assessed differences in BMIz by SEE over the second year of life and obesity risk at age two, respectively (highest SEE, reference), while attenuation of obesity risk by breastfeeding duration was tested in mediation models. RESULTS: Residing outside of the highest SEE neighbourhoods was associated with an increased BMIz of 0.04 (95%CI 0.02, 0.06) per month of life and increased obesity risk at age two (aRR: 3.7, 95%CI 1.2, 16.2), controlling for family socio-demographics. Breastfeeding duration attenuated >9% of the obesity risk attributable to SEE (mediated RR: 3.4, 95%CI 1.1, 14.8). DISCUSSION: In the PREVAIL Cohort, residing outside of the highest SEE neighbourhoods predicted a significant increase in BMIz and obesity risk in children before age two, a relationship that was partially mediated by breastfeeding duration. CONCLUSION: Breastfeeding support may play an important role in reducing obesity rates in children in lower SEE neighbourhoods.

Air pollution, depressive and anxiety disorders, and brain effects: A systematic review.

Accumulating data suggest that air pollution increases the risk of internalizing psychopathology, including anxiety and depressive disorders. Moreover, the link between air pollution and poor mental health may relate to neurostructural and neurofunctional changes. We systematically reviewed the MEDLINE database in September 2021 for original articles reporting effects of air pollution on 1) internalizing symptoms and behaviors (anxiety or depression) and 2) frontolimbic brain regions (i.e., hippocampus, amygdala, prefrontal cortex). One hundred and eleven articles on mental health (76% human, 24% animals) and 92 on brain structure and function (11% human, 86% animals) were identified. For literature search 1, the most common pollutants examined were PM2.5 (64.9%), NO2 (37.8%), and PM10 (33.3%). For literature search 2, the most common pollutants examined were PM2.5 (32.6%), O3 (26.1%) and Diesel Exhaust Particles (DEP) (26.1%). The majority of studies (73%) reported higher internalizing symptoms and behaviors with higher air pollution exposure. Air pollution was consistently associated (95% of articles reported significant findings) with neurostructural and neurofunctional effects (e.g., increased inflammation and oxidative stress, changes to neurotransmitters and neuromodulators and their metabolites) within multiple brain regions (24% of articles), or within the hippocampus (66%), PFC (7%), and amygdala (1%). For both literature searches, the most studied exposure time frames were adulthood (48% and 59% for literature searches 1 and 2, respectively) and the prenatal period (26% and 27% for literature searches 1 and 2, respectively). Forty-three percent and 29% of studies assessed more than one exposure window in literature search 1 and 2, respectively. The extant literature suggests that air pollution is associated with increased depressive and anxiety symptoms and behaviors, and alterations in brain regions implicated in risk of psychopathology. However, there are several gaps in the literature, including: limited studies examining the neural consequences of air pollution in humans. Further, a comprehensive developmental approach is needed to examine windows of susceptibility to exposure and track the emergence of psychopathology following air pollution exposure.

Epigenome-wide association of neonatal methylation and trimester-specific prenatal PM2.5 exposure.

Exposure to particulate matter with an aerodynamic diameter smaller than 2.5 microns (PM2.5) can affect birth outcomes through physiological pathways such as inflammation. One potential way PM2.5 affects physiology could be through altering DNA methylation (DNAm). Considering that exposures during specific windows of gestation may have unique effects on DNAm, we hypothesized a timing-specific association between PM2.5 exposure during pregnancy and DNAm in the neonatal epithelial-cell epigenome. Methods: After collecting salivary samples from a cohort of 91 neonates, DNAm was assessed at over 850,000 cytosine-guanine dinucleotide (CpG) methylation sites on the epigenome using the MethylationEPIC array. Daily ambient PM2.5 concentrations were estimated based on the mother's address of primary residence during pregnancy. PM2.5 was averaged over the first two trimesters, separately and combined, and tested for association with DNAm through an epigenome-wide association (EWA) analysis. For each EWA, false discovery rate (FDR)-corrected P < 0.05 constituted a significant finding and every CpG site with uncorrected P < 0.0001 was selected to undergo pathway and network analysis to identify molecular functions enriched by them. Results: Our analysis showed that cg18705808 was associated with the combined average of PM2.5. Pathway and network analysis revealed little similarity between the first two trimesters. Previous studies reported that TMEM184A, the gene regulated by cg18705808, has a putative role in inflammatory pathways. Conclusions: The differences in pathway and network analyses could potentially indicate trimester-specific effects of PM2.5 on DNAm. Further analysis with greater temporal resolution would be valuable to fully characterize the effect of PM2.5 on DNAm and child development.

Understanding racial disparities in childhood asthma using individual- and neighborhood-level risk factors.

BACKGROUND: Racial disparities in childhood asthma outcomes result from a complex interplay of individual- and neighborhood-level factors. OBJECTIVES: We sought to examine racial disparities in asthma-related emergency department (ED) visits between African American (AA) and European American (EA) children. METHODS: This is a retrospective study of patients younger than 18 years who visited the ED at Cincinnati Children's for asthma from 2009 to 2018. The outcome was number of ED visits during a year. We assessed 11 social, economic, and environmental variables. Mediation and mixed-effects analyses were used to assess relationships between race, mediators, and number of ED visits. RESULTS: A total of 31,114 children (46.1% AA, 53.9% EA) had 186,779 asthma-related ED visits. AA children had more visits per year than EA children (2.23 vs 2.15; P < .001). Medicaid insurance was associated with a 7% increase in rate of ED visits compared with commercial insurance (1.07; 95% CI, 1.03-1.1). Neighborhood socioeconomic deprivation was associated with an increased rate of ED visits in AA but not in EA children. Area-level particulate matter with diameter less than 2.5 µm, pollen, and outdoor mold were associated with an increased rate of ED visits for both AA and EA children (all P < .001). Associations between race and number of ED visits were mediated by insurance, area-level deprivation, particulate matter with diameter less than 2.5 µm, and outdoor mold (all P < .001), altogether accounting for 55% of the effect of race on ED visits. Race was not associated with number of ED visits (P = .796) after accounting for mediators. CONCLUSIONS: Racial disparities in asthma-related ED visits are mediated by social, economic, and environmental factors, which may be amenable to interventions aimed at improving outcomes and eliminating inequities.

Using Geomarkers and Sociodemographics to Inform Assessment of Caregiver Adversity and Resilience.

BACKGROUND AND OBJECTIVES: A high level of caregiver adverse childhood experiences (ACEs) and/or low resilience is associated with poor outcomes for both caregivers and their children after hospital discharge. It is unknown if sociodemographic or area-based measures (ie, "geomarkers") can inform the assessment of caregiver ACEs or resilience. Our objective was to determine if caregiver ACEs or resilience can be identified by using any combinations of sociodemographic measures, geomarkers, and/or caregiver-reported household characteristics. METHODS: Eligible participants for this cohort study were English-speaking caregivers of children hospitalized on a hospital medicine team. Caregivers completed the ACE questionnaire, Brief Resilience Scale, and strain surveys. Exposures included sociodemographic characteristics available in the electronic health record (EHR), geomarkers tied to a patient's geocoded home address, and household characteristics that are not present in the EHR (eg, income). Primary outcomes were a high caregiver ACE score (≥4) and/or a low BRS Score (<3). RESULTS: Of the 1272 included caregivers, 543 reported high ACE or low resilience, and 63 reported both. We developed the following regression models: sociodemographic variables in EHR (Model 1), EHR sociodemographics and geomarkers (Model 2), and EHR sociodemographics, geomarkers, and additional survey-reported household characteristics (Model 3). The ability of models to identify the presence of caregiver adversity was poor (all areas under receiver operating characteristics curves were <0.65). CONCLUSIONS: Models using EHR data, geomarkers, and household-level characteristics to identify caregiver adversity had limited utility. Directly asking questions to caregivers or integrating risk and strength assessments during pediatric hospitalization may be a better approach to identifying caregiver adversity.