ArticleEnvironmental research2017
Extending the Distributed Lag Model framework to handle chemical mixtures.
Article in Environmental research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 38 papers.
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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
38 citing papers in PubMed, 50 citations in OpenAlex.
- Prenatal Household Air Pollution Exposure and Childhood Blood Pressure in Rural Ghana.Environmental health perspectives · 2024Trial
- Perinatal C-Reactive Protein Levels Detected in Deciduous Teeth Are Associated With Autism-Related Traits and Behavior Problems in School-Aged Children.Biological psychiatry global open science · 2026Article
- Multi-Tree Model for Precision Environmental Health with Longitudinally Assessed Mixture Exposure.Journal of the Royal Statistical Society. Series C, Applied statistics · 2026Article
- Fetal and postnatal metal metabolism-related changes in brain function are associated with childhood behavioral deficits.Science advances · 2026Article
- Modeling approaches for estimating the effects of risk factors using longitudinal lifecourse exposure data in dementia research.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Review
- LOW-RANK LONGITUDINAL FACTOR REGRESSION WITH APPLICATION TO CHEMICAL MIXTURES.The annals of applied statistics · 2025Article
- A review of common statistical methods for dealing with multiple pollutant mixtures and multiple exposures.Frontiers in public health · 2024Review
- Multiple exposure distributed lag models with variable selection.Biostatistics (Oxford, England) · 2023Article
- Statistical Approaches to Study Exposome-Health Associations in the Context of Repeated Exposure Data: A Simulation Study.Environmental science & technology · 2023Article
- Semiparametric distributed lag quantile regression for modeling time-dependent exposure mixtures.Biometrics · 2023Article
- The impact of correlated exposures and missing data on multiple informant models used to identify critical exposure windows.Statistics in medicine · 2023Article
- NICU-based stress response and preterm infant neurobehavior: exploring the critical windows for exposure.Pediatric research · 2022Article
- CRITICAL WINDOW VARIABLE SELECTION FOR MIXTURES: ESTIMATING THE IMPACT OF MULTIPLE AIR POLLUTANTS ON STILLBIRTH.The annals of applied statistics · 2022Article
- KERNEL MACHINE AND DISTRIBUTED LAG MODELS FOR ASSESSING WINDOWS OF SUSCEPTIBILITY TO ENVIRONMENTAL MIXTURES IN CHILDREN'S HEALTH STUDIES.The annals of applied statistics · 2022Article
- Prenatal trace elements mixture is associated with learning deficits on a behavioral acquisition task among young children.New directions for child and adolescent development · 2022Article
- Powering Research through Innovative Methods for Mixtures in Epidemiology (PRIME) Program: Novel and Expanded Statistical Methods.International journal of environmental research and public health · 2022Review
- Effects of gestational exposures to chemical mixtures on birth weight using Bayesian factor analysis in the Health Outcome and Measures of Environment (HOME) Study.Environmental epidemiology (Philadelphia, Pa.) · 2021Article
- Human Health Exposure Analysis Resource (HHEAR): A model for incorporating the exposome into health studies.International journal of hygiene and environmental health · 2021Review
- Metal mixtures and neurodevelopment: recent findings and emerging principles.Current opinion in toxicology · 2021Article
- Prenatal air pollution exposure and neurodevelopment: A review and blueprint for a harmonized approach within ECHO.Environmental research · 2021Review
Corrections and comments
- Erratum issued
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Distributed Lag Models (DLMs) are used in environmental health studies to analyze the time-delayed effect of an exposure on an outcome of interest. Given the increasing need for analytical tools for evaluation of the effects of exposure to multi-pollutant mixtures, this study attempts to extend the classical DLM framework to accommodate and evaluate multiple longitudinally observed exposures. We introduce 2 techniques for quantifying the time-varying mixture effect of multiple exposures on an outcome of interest. Lagged WQS, the first technique, is based on Weighted Quantile Sum (WQS) regression, a penalized regression method that estimates mixture effects using a weighted index. We also introduce Tree-based DLMs, a nonparametric alternative for assessment of lagged mixture effects. This technique is based on the Random Forest (RF) algorithm, a nonparametric, tree-based estimation technique that has shown excellent performance in a wide variety of domains. In a simulation study, we tested the feasibility of these techniques and evaluated their performance in comparison to standard methodology. Both methods exhibited relatively robust performance, accurately capturing pre-defined non-linear functional relationships in different simulation settings. Further, we applied these techniques to data on perinatal exposure to environmental metal toxicants, with the goal of evaluating the effects of exposure on neurodevelopment. Our methods identified critical neurodevelopmental windows showing significant sensitivity to metal mixtures.
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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.