ArticleEnvironmental epidemiology (Philadelphia, Pa.)2019
A quantile regression approach to examine fine particles, term low birth weight, and racial/ethnic disparities.
Article in Environmental epidemiology (Philadelphia, Pa.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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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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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Application of the navigation guide systematic review methodology to evaluate prenatal exposure to particulate matter air pollution and infant birth weight.Environment international · 2021Pooled it
- SARS-CoV-2 and climate factors: a study between linear regression and quantile regression model using longitudinal count data.BMC public health · 2026Article
- Performance of quantile regression methods with discrete outcomes: A simulation study with applications to environmental epidemiology.Environmental epidemiology (Philadelphia, Pa.) · 2025Article
- Association of PMPaediatric and perinatal epidemiology · 2025Article
- On function-on-function linear quantile regression.Journal of applied statistics · 2025Article
- Challenges and opportunities in perinatal public health: the utility of perinatal health inequality dashboards in addressing disparities in maternal and neonatal outcomes.BMC pregnancy and childbirth · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundExposure to fine particulate matter (PM
methodsData for singleton births in California from October 24, 2005 to February 27, 2010 were collected from the birth records accessed from the California Department of Public Health. Air pollution monitoring data collected by the California Air Resources Board and interpolated for each zip code using an inverse-distance weighting approach, and linked to maternal zip code of residence reported on the birth certificate. Multilevel linear regression models were conducted with mother's residential zip code tabulation area as a random effect. Multilevel quantile regression models were used to analyze the association at different percentiles of birth weight (5th, 10th, 25th, 50th, 75th, 90th, 95th), as well as examine the heterogeneity in this association between racial/ethnic groups.
resultsLinear regression revealed that a 10 μg/m
conclusionResults of the quantile regression revealed greater disparities, particularly for infants with the lowest birth weight. By identifying vulnerable populations, we can promote and implement policies to confront these health disparities.
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