ArticleEnvironmental health perspectives2019
Using Birth Cohort Data to Estimate Prenatal Chemical Exposures for All Births around the New Bedford Harbor Superfund Site in Massachusetts.
Article in Environmental health perspectives, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Multiple prenatal exposures and acute-care clinical encounters for asthma among children born to mothers living near a Superfund site.American journal of epidemiology · 2024Article
- Prenatal environmental exposures and associations with teen births.Journal of exposure science & environmental epidemiology · 2021Article
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Authors and funding
6 authors.
Funding
Abstract
backgroundChildren born near New Bedford, Massachusetts, have been prenatally exposed to multiple environmental chemicals, in part due to an older housing stock, maternal diet, and proximity to the New Bedford Harbor (NBH) Superfund site. Chemical exposure measures are not available for all births, limiting epidemiologic investigations and potential interventions.
objectiveWe linked biomonitoring data from the New Bedford Cohort (NBC) and birth record data to predict prenatal exposures for all contemporaneous area births.
methodsWe used prenatal exposure biomarker data from the NBC, a population-based cohort of 788 mother-infant pairs born during 1993–1998 to mothers living near the NBH, linked to their corresponding Massachusetts birth record data, to build predictive models for cord serum polychlorinated biphenyls (expressed as a sum, [Formula: see text]), [Formula: see text] (DDE), hexachlorobenzene (HCB), cord blood lead (Pb), and maternal hair mercury (Hg). We applied the best fit models (highest pseudo [Formula: see text]), with multivariable smooths of continuous variables, to predict exposure biomarkers for all 10,270 births during 1993–1998 around the NBH. We used 10-fold cross validation to validate the exposure models and the bootstrap method to characterize sampling variability in the exposure predictions.
resultsThe 10-fold cross-validated [Formula: see text] for the [Formula: see text], DDE, HCB, Pb, and Hg exposure models were 0.54, 0.40, 0.34, 0.46, and 0.40, respectively. For each exposure model, multivariable smooths of continuous variables improved the fit compared with linear models. Other variables with significant effects on exposure estimates were paternal education, maternal race/ethnicity, and maternal ancestry. The resulting exposure predictions for all births had variability consistent with the NBC measured exposures.
conclusionsPredictive models using multivariable smoothing explained reasonable amounts of variance in prenatal exposure biomarkers. Our analyses suggest that prenatal chemical exposures can be predicted for all contemporaneous births in the same geographic area by modeling available biomarker data for a subset of that population. https://doi.org/10.1289/EHP4849.
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