ArticleBiostatistics (Oxford, England)2017
Bayesian distributed lag interaction models to identify perinatal windows of vulnerability in children's health.
Article in Biostatistics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.
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Who cites it
57 citing papers in PubMed, 76 citations in OpenAlex.
- Multi-Tree Model for Precision Environmental Health with Longitudinally Assessed Mixture Exposure.Journal of the Royal Statistical Society. Series C, Applied statistics · 2026Article
- Prenatal exposure to heat stress and postpartum depressive symptoms in the MADRES cohort in urban Los Angeles.Environmental research · 2026Article
- Susceptible windows of long-term childhood exposure to air pollution on adult self-reported bronchitic symptoms.International journal of epidemiology · 2026Article
- Distributed lag interaction model with index modification.Biostatistics (Oxford, England) · 2025Article
- Time-activity and daily mobility patterns during pregnancy and inequalities in air pollution exposure in perinatal outcomes: a cohort study.International journal of health geographics · 2025Article
- Identifying critical windows of susceptibility to perinatal lead exposure on child serum vaccine antibody levels.American journal of epidemiology · 2025Article
- Air Pollution Exposure and Birth Weight in the ECHO Cohort.JAMA network open · 2025Article
- Broad Applications of Distributed Lag Non-Linear Model in Public Health: A Comprehensive Review.GeoHealth · 2025Review
- Association between prenatal ambient particulate matter and childhood asthma is modified by community safety and child sex.Scientific reports · 2025Article
- Structured Bayesian Regression Tree Models for Estimating Distributed Lag Effects: The R Package dlmtree.The R journal · 2025Article
- Distributed lag models for retrospective cohort data with application to a study of built environment and body weight.Biometrics · 2025Article
- Flexible Distributed Lag Models for Count Data Using mgcv.The American statistician · 2025Article
- Prenatal exposure to ambient fine particulate matter and child lung function in the CANDLE cohort.Annals of medicine · 2024Article
- Penalized distributed lag interaction model: Air pollution, birth weight, and neighborhood vulnerability.Environmetrics · 2024Article
- Increased Risk of Gestational Hypertension by Periconceptional Exposure to Ambient Air Pollution and Effect Modification by Prenatal Depression.Hypertension (Dallas, Tex. : 1979) · 2024Article
- Sensitive development windows of prenatal air pollution and cognitive functioning in preschool age Mexican children.Environmental epidemiology (Philadelphia, Pa.) · 2024Article
- Heterogeneous Distributed Lag Models to Estimate Personalized Effects of Maternal Exposures to Air Pollution.Journal of the American Statistical Association · 2024Article
- Multiple exposure distributed lag models with variable selection.Biostatistics (Oxford, England) · 2023Article
- Prenatal ambient air pollutant mixture exposure and neurodevelopment in urban children in the Northeastern United States.Environmental research · 2023Article
- Preconceptional and prenatal exposure to air pollutants and risk of gestational diabetes in the MADRES prospective pregnancy cohort study.Lancet regional health. Americas · 2023Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
Abstract
Epidemiological research supports an association between maternal exposure to air pollution during pregnancy and adverse children's health outcomes. Advances in exposure assessment and statistics allow for estimation of both critical windows of vulnerability and exposure effect heterogeneity. Simultaneous estimation of windows of vulnerability and effect heterogeneity can be accomplished by fitting a distributed lag model (DLM) stratified by subgroup. However, this can provide an incomplete picture of how effects vary across subgroups because it does not allow for subgroups to have the same window but different within-window effects or to have different windows but the same within-window effect. Because the timing of some developmental processes are common across subpopulations of infants while for others the timing differs across subgroups, both scenarios are important to consider when evaluating health risks of prenatal exposures. We propose a new approach that partitions the DLM into a constrained functional predictor that estimates windows of vulnerability and a scalar effect representing the within-window effect directly. The proposed method allows for heterogeneity in only the window, only the within-window effect, or both. In a simulation study we show that a model assuming a shared component across groups results in lower bias and mean squared error for the estimated windows and effects when that component is in fact constant across groups. We apply the proposed method to estimate windows of vulnerability in the association between prenatal exposures to fine particulate matter and each of birth weight and asthma incidence, and estimate how these associations vary by sex and maternal obesity status in a Boston-area prospective pre-birth cohort study.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.