Browsing by Author "Bravo, Mercedes A."

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    Disparities in air quality downscaler model uncertainty across socioeconomic and demographic indicators in North Carolina
    (Elsevier, 2022) Zhou, Shan; Griffin, Robert J.; Bui, Alexander; Lilienfeld Asbun, Aaron; Bravo, Mercedes A.; Osgood, Claire; Miranda, Marie Lynn
    Studies increasingly use output from the Environmental Protection Agency's Fused Air Quality Surface Downscaler (“downscaler”) model, which provides spatial predictions of daily concentrations of fine particulate matter (PM2.5) and ozone (O3) at the census tract level, to study the health and societal impacts of exposure to air pollution. Downscaler outputs have been used to show that lower income and higher minority neighborhoods are exposed to higher levels of PM2.5 and lower levels of O3. However, the uncertainty of the downscaler estimates remains poorly characterized, and it is not known if all subpopulations are benefiting equally from reliable predictions. We examined how the percent errors (PEs) of daily concentrations of PM2.5 and O3 between 2002 and 2016 at the 2010 census tract centroids across North Carolina were associated with measures of racial and educational isolation, neighborhood disadvantage, and urbanicity. Results suggest that there were socioeconomic and demographic disparities in surface concentrations of PM2.5 and O3, as well as their prediction uncertainties. Neighborhoods characterized by less reliable downscaler predictions (i.e., higher PEPM2.5 and PEO3) exhibited greater levels of aerial deprivation as well as educational isolation, and were often non-urban areas (i.e., suburban, or rural). Between 2002 and 2016, predicted PM2.5 and O3 levels decreased and O3 predictions became more reliable. However, the predictive uncertainty for PM2.5 has increased since 2010. Substantial spatial variability was observed in the temporal changes in the predictive uncertainties; educational isolation and neighborhood deprivation levels were associated with smaller increases in predictive uncertainty of PM2.5. In contrast, racial isolation was associated with a greater decline in the reliability of PM2.5 predictions between 2002 and 2016; it was associated with a greater improvement in the predictive reliability of O3 within the same time frame.
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    Racial residential segregation shapes the relationship between early childhood lead exposure and fourth-grade standardized test scores
    (National Academy of Sciences, 2022) Bravo, Mercedes A.; Zephyr, Dominique; Kowal, Daniel; Ensor, Katherine; Miranda, Marie Lynn
    Racial/ethnic disparities in academic performance may result from a confluence of adverse exposures that arise from structural racism and accrue to specific subpopulations. This study investigates childhood lead exposure, racial residential segregation, and early educational outcomes. Geocoded North Carolina birth data is linked to blood lead surveillance data and fourth-grade standardized test scores (n = 25,699). We constructed a census tract-level measure of racial isolation (RI) of the non-Hispanic Black (NHB) population. We fit generalized additive models of reading and mathematics test scores regressed on individual-level blood lead level (BLL) and neighborhood RI of NHB (RINHB). Models included an interaction term between BLL and RINHB. BLL and RINHB were associated with lower reading scores; among NHB children, an interaction was observed between BLL and RINHB. Reading scores for NHB children with BLLs of 1 to 3 µg/dL were similar across the range of RINHB values. For NHB children with BLLs of 4 µg/dL, reading scores were similar to those of NHB children with BLLs of 1 to 3 µg/dL at lower RINHB values (less racial isolation/segregation). At higher RINHB levels (greater racial isolation/segregation), children with BLLs of 4 µg/dL had lower reading scores than children with BLLs of 1 to 3 µg/dL. This pattern becomes more marked at higher BLLs. Higher BLL was associated with lower mathematics test scores among NHB and non-Hispanic White (NHW) children, but there was no evidence of an interaction. In conclusion, NHB children with high BLLs residing in high RINHB neighborhoods had worse reading scores.
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    Spatial Variability in Relationships between Early Childhood Lead Exposure and Standardized Test Scores in Fourth Grade North Carolina Public School Students (2013–2016)
    (National Institute of Environmental Health Sciences, National Institutes of Health, 2024) Bravo, Mercedes A.; Kowal, Daniel R.; Zephyr, Dominique; Feldman, Joseph; Ensor, Katherine; Miranda, Marie Lynn
    Background:Exposure to lead during childhood is detrimental to children’s health. The extent to which the association between lead exposure and elementary school academic outcomes varies across geography is not known.Objective:Estimate associations between blood lead levels (BLLs) and fourth grade standardized test scores in reading and mathematics in North Carolina using models that allow associations between BLL and test scores to vary spatially across communities.Methods:We link geocoded, individual-level, standardized test score data for North Carolina public school students in fourth grade (2013–2016) with detailed birth records and blood lead testing data retrieved from the North Carolina childhood blood lead state registry on samples typically collected at 1–6 y of age. BLLs were categorized as: 1μ⁢g/dL (reference), 2μ⁢g/dL, 3–4μ⁢g/dL and ≥5μ⁢g/dL. We then fit spatially varying coefficient models that incorporate information sharing (smoothness), across neighboring communities via a Gaussian Markov random field to provide a global estimate of the association between BLL and test scores, as well as census tract–specific estimates (i.e., spatial coefficients). Models adjusted for maternal- and child-level covariates and were fit separately for reading and math.Results:The average BLL across the 91,706 individuals in the analysis dataset was 2.84μ⁢g/dL. Individuals were distributed across 2,002 (out of 2,195) census tracts in North Carolina. In models adjusting for child sex, birth weight percentile for gestational age, and Medicaid participation as well as maternal race/ethnicity, educational attainment, marital status, and tobacco use, BLLs of 2μ⁢g/dL, 3–4μ⁢g/dL and ≥5μ⁢g/dL were associated with overall lower reading test scores of −0.28 [95% confidence interval (CI): −0.43, −0.12], −0.53 (−0.69, −0.38), and −0.79 (−0.99, −0.604), respectively. For BLLs of 1μ⁢g/dL, 2μ⁢g/dL, 3–4μ⁢g/dL and ≥5μ⁢g/dL, spatial coefficients—that is, tract-specific adjustments in reading test score relative to the “global” coefficient—ranged from −9.70 to 2.52, −3.19 to 3.90, −11.14 to 7.85, and −4.73 to 4.33, respectively. Results for mathematics were similar to those for reading.Conclusion:The association between lead exposure and reading and mathematics test scores exhibits considerable heterogeneity across North Carolina communities. These results emphasize the need for prevention and mitigation efforts with respect to lead exposures everywhere, with special attention to locations where the cognitive impact is elevated. https://doi.org/10.1289/EHP13898
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    Toll-like Receptor 4 Pathway Polymorphisms Interact with Pollution to Influence Asthma Diagnosis and Severity
    (Springer Nature, 2018) Schurman, Shepherd H.; Bravo, Mercedes A.; Innes, Cynthia L.; Jackson, W. Braxton II; McGrath, John A.; Miranda, Marie Lynn; Garantziotis, Stavros
    Asthma is a common chronic lung disease, the incidence and severity of which may be influenced by gene-environment interactions. Our objective was to examine associations between single nucleotide polymorphisms (SNPs) and combinations of SNPs in the toll-like receptor 4 (TLR4) pathway, residential distance to roadway as a proxy for traffic-related air pollution exposure, and asthma diagnosis and exacerbations. We obtained individual-level data on genotype, residential address, and asthma diagnosis and exacerbations from the Environmental Polymorphisms Registry. Subjects (n = 2,704) were divided into three groups (hyper-responders, hypo-responders, and neither) based on SNP combinations in genes along the TLR4 pathway. We geocoded subjects and calculated distance, classified as <250 m or ≥250 m, between residence and nearest major road. Relationships between genotype, distance to road, and odds of asthma diagnosis and exacerbations were examined using logistic regression. Odds of an asthma diagnosis among hyper-responders <250 m from a major road was 2.37(0.97, 6.01) compared to the reference group (p < 0.10). Hypo-responders ≥250 m from the nearest road had lower odds of activity limitations (0.46 [0.21, 0.95]) and sleeplessness (0.36 [0.12, 0.91]) compared to neither-responders (p < 0.05). Specific genotype combinations when combined with an individual's proximity to roadways, possibly due to traffic-related air pollution exposure, may affect the likelihood of asthma diagnosis and exacerbations.