Bayesian Weighted Sums: A Flexible Approach to Estimate Summed Mixture Effects
Open Access
- 3 February 2021
- journal article
- research article
- Published by MDPI AG in International Journal of Environmental Research and Public Health
- Vol. 18 (4), 1373
- https://doi.org/10.3390/ijerph18041373
Abstract
Objectives: Methods exist to study exposure mixtures, but each is distinct in the research question it aims to address. We propose a new approach focused on estimating both the summed effect and individual weights of one or multiple exposure mixtures: Bayesian Weighted Sums (BWS). Methods: We applied BWS to simulated and real datasets with correlated exposures. The analytic context in our real-world example is an estimation of the association between polybrominated diphenyl ether (PBDE) congeners (28, 47, 99, 100, and 153) and Autism Spectrum Disorder (ASD) diagnosis and Social Responsiveness Scores (SRS). Results: Simulations demonstrate that BWS performs reliably. In adjusted models using Early Autism Risk Longitudinal Investigation (EARLI) data, the odds of ASD for a 1-unit increase in the weighted sum of PBDEs were 1.41 (95% highest posterior density 0.82, 2.50) times the odds of ASD for the unexposed and the change in z-score standardized SRS per 1 unit increase in the weighted sum of PBDEs is 0.15 (95% highest posterior density −0.08, 0.38). Conclusions: BWS provides a means of estimating the summed effect and weights for individual components of a mixture. This approach is distinct from other exposure mixture tools. BWS may be more flexible than existing approaches and can be specified to allow multiple exposure groups based on a priori knowledge from epidemiology or toxicology.This publication has 17 references indexed in Scilit:
- Complex Mixtures, Complex Analyses: an Emphasis on Interpretable ResultsCurrent Environmental Health Reports, 2019
- Environmental Exposure Mixtures: Questions and Methods to Address ThemCurrent Epidemiology Reports, 2018
- Bayesian Analysis of Silica Exposure and Lung Cancer Using Human and Animal StudiesEpidemiology, 2017
- What Can Epidemiological Studies Tell Us about the Impact of Chemical Mixtures on Human Health?Environmental Health Perspectives, 2016
- Characterization of Weighted Quantile Sum Regression for Highly Correlated Data in a Risk Analysis SettingJournal of Agricultural, Biological and Environmental Statistics, 2015
- Bayesian kernel machine regression for estimating the health effects of multi-pollutant mixturesBiostatistics, 2014
- Modelling complex mixtures in epidemiologic analysis: additive versus relative measures for differential effectivenessOccupational and Environmental Medicine, 2013
- Contrasting Theories of Interaction in Epidemiology and ToxicologyEnvironmental Health Perspectives, 2013
- Integrating Informative Priors from Experimental Research with Bayesian MethodsEpidemiology, 2013
- Beyond Autism: A Baby Siblings Research Consortium Study of High-Risk Children at Three Years of AgeJournal of the American Academy of Child & Adolescent Psychiatry, 2012