ReviewCurrent opinion in pediatrics2020
Environmental mixtures and children's health: identifying appropriate statistical approaches.
Review in Current opinion in pediatrics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed.
- Workflow for Statistical Analysis of Environmental Mixtures.Environmental health perspectives · 2026Review
- Pregnancy exposure to individual phthalate concentrations and their mixtures in relation to pediatric serum antibody response.European journal of epidemiology · 2026Article
- Exposure to phthalate and phenol mixtures and obesity in children and adolescents: the dominant role of bisphenol A.Lipids in health and disease · 2026Article
- Per and polyfluoroalkyl substances affect thyroid hormones for people with a history of exposure from drinking water.Scientific reports · 2025Article
- Exposure to a mixture of four metals and associations with urinary oxidative stress biomarkers in Uruguayan adolescents.Journal of environmental exposure assessment · 2025Article
- Associations of multiple trace elements with bipolar disorder in adolescents: A case-control study.PloS one · 2025Article
- Environmental Mixtures Analysis (E-MIX) Workflow and Methods Repository.medRxiv : the preprint server for health sciences · 2024Article
- Cross-Cohort Mixture Analysis: A Data Integration Approach With Applications on Gestational Age and DNA-Methylation-Derived Gestational Age Acceleration Metrics.Biometrical journal. Biometrische Zeitschrift · 2024Article
- Accommodating detection limits of multiple exposures in environmental mixture analyses: an overview of statistical approaches.Environmental health : a global access science source · 2024Article
- Prenatal exposure to air pollutant mixtures and birthweight in the upstate KIDS cohort.Environment international · 2024Article
- Integrating Data Across Multiple Sites in the Northeastern United States to Examine Associations Between a Prenatal Metal Mixture and Child Cognition.American journal of epidemiology · 2024Article
- A State-of-the-Science Review on Metal Biomarkers.Current environmental health reports · 2023Review
- Bayesian multiple index models for environmental mixtures.Biometrics · 2023Article
- Combined exposure to multiple essential elements and cadmium at early pregnancy on gestational diabetes mellitus: a prospective cohort study.Frontiers in nutrition · 2023Article
- Prenatal exposure to multiple organochlorine compounds and childhood body mass index.Environmental epidemiology (Philadelphia, Pa.) · 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
- Prenatal urinary concentrations of phthalate metabolites and behavioral problems in Mexican children: The Programming Research in Obesity, Growth Environment and Social Stress (PROGRESS) study.Environmental research · 2021Article
- Advancing tools for human early lifecourse exposome research and translation (ATHLETE): Project overview.Environmental epidemiology (Philadelphia, Pa.) · 2021Review
- Invited Perspective: Metal Mixtures and Child Health: The Complex Interplay of Essential and Toxic Elements.Environmental health perspectives · 2021Article
- Microplastics, environment and child health.Italian journal of pediatrics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
purpose of reviewBiomonitoring studies have shown that children are constantly exposed to complex patterns of chemical and nonchemical exposures. Here, we briefly summarize the rationale for studying multiple exposures, also called mixture, in relation to child health and key statistical approaches that can be used. We discuss advantages over traditional methods, limitations and appropriateness of the context. RECENT
findingsNew approaches allow pediatric researchers to answer increasingly complex questions related to environmental mixtures. We present methods to identify the most relevant exposures among a high-multitude of variables, via shrinkage and variable selection techniques, and identify the overall mixture effect, via Weighted Quantile Sum and Bayesian Kernel Machine regressions. We then describe novel extensions that handle high-dimensional exposure data and allow identification of critical exposure windows. SUMMARY: Recent advances in statistics and machine learning enable researchers to identify important mixture components, estimate joint mixture effects and pinpoint critical windows of exposure. Despite many advantages over single chemical approaches, measurement error and biases may be amplified in mixtures research, requiring careful study planning and design. Future research requires increased collaboration between epidemiologists, statisticians and data scientists, and further integration with causal inference methods.
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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.