Observational studyAmerican journal of epidemiology2021
Bayesian G-Computation for Estimating Impacts of Interventions on Exposure Mixtures: Demonstration With Metals From Coal-Fired Power Plants and Birth Weight.
Observational study in American journal of epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 3 of them syntheses 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.
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
19 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- "We adjusted for race": now what? A systematic review of utilization and reporting of race in American Journal of Epidemiology and Epidemiology, 2020-2021.Epidemiologic reviews · 2023Pooled it
- Reporting of Observational Studies Explicitly Aiming to Emulate Randomized Trials: A Systematic Review.JAMA network open · 2023Pooled it
- Metabolic Signatures of Youth Exposure to Mixtures of Per- and Polyfluoroalkyl Substances: A Multi-Cohort Study.Environmental health perspectives · 2023Pooled it
- Everything All at Once: On Choosing an Estimand for Multi-component Environmental Exposures.Epidemiology (Cambridge, Mass.) · 2026Article
- The potential effects of hypothetical PM2.5 interventions on childhood autism in different neighborhood socioeconomic contexts.American journal of epidemiology · 2026Article
- Robust Statistical Approaches to Understanding the Causal Effect of Air Pollution Mixtures.Research report (Health Effects Institute) · 2025Article
- Harnessing Geospatial Artificial Intelligence (GeoAI) for Environmental Epidemiology: A Narrative Review.Current environmental health reports · 2025Review
- Causal analysis of air pollution mixtures: estimands, positivity, and extrapolation.American journal of epidemiology · 2024Article
- Long-term ambient sulfur dioxide exposure during gestation and preterm birth in North Carolina, 2003-2015.Atmospheric environment (Oxford, England : 1994) · 2024Article
- Quantifying Multipollutant Health Impacts Using the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE): A Case Study in Atlanta, Georgia.Environmental health perspectives · 2024Article
- Exposure to phthalate metabolites, bisphenol A, and psychosocial stress mixtures and pregnancy outcomes in the Atlanta African American maternal-child cohort.Environmental research · 2023Article
- Mixtures of Metals and Micronutrients in Early Pregnancy and Cognition in Early and Mid-Childhood: Findings from the Project Viva Cohort.Environmental health perspectives · 2023Article
- Sulfur dioxide reduction at coal-fired power plants in North Carolina and associations with preterm birth among surrounding residents.Environmental epidemiology (Philadelphia, Pa.) · 2023Article
- Using Parametric g-Computation to Estimate the Effect of Long-Term Exposure to Air Pollution on Mortality Risk and Simulate the Benefits of Hypothetical Policies: The Canadian Community Health Survey Cohort (2005 to 2015).Environmental health perspectives · 2023Article
- Estimating Causal Effects of Interventions on Early-life Environmental Exposures Using Observational Data.Current environmental health reports · 2023Review
- Invited Commentary: The Promise and Pitfalls of Causal Inference With Multivariate Environmental Exposures.American journal of epidemiology · 2021Article
- Keil et al. Respond to "Causal Inference for Environmental Mixtures".American journal of epidemiology · 2021Article
- Invited Perspective: Metal Mixtures and Child Health: The Complex Interplay of Essential and Toxic Elements.Environmental health perspectives · 2021Article
- Response to "Comment on 'A Quantile-Based g-Computation Approach to Addressing the Effects of Exposure Mixtures'".Environmental health perspectives · 2021Article
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3 authors.
Funding
Abstract
The importance of studying the health impacts of exposure mixtures is increasingly being recognized, but such research presents many methodological and interpretation difficulties. We used Bayesian g-computation to estimate effects of a simulated public health action on exposure mixtures and birth weights in Milwaukee, Wisconsin, in 2011-2013. We linked data from birth records with census-tract-level air toxics data from the Environmental Protection Agency's National Air Toxics Assessment model. We estimated the difference between observed and expected birth weights that theoretically would have followed a hypothetical intervention to reduce exposure to 6 airborne metals by decommissioning 3 coal-fired power plants in Milwaukee County prior to 2010. Using Bayesian g-computation, we estimated a 68-g (95% credible interval: 25, 135) increase in birth weight following this hypothetical intervention. This example demonstrates the utility of our approach for using observational data to evaluate and contrast possible public health actions. Additionally, Bayesian g-computation offers a flexible strategy for estimating the effects of highly correlated exposures, addressing statistical issues such as variance inflation, and addressing conceptual issues such as the lack of interpretability of independent effects.
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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.