Development and application of an evidence-based directed acyclic graph to evaluate the associations between metal mixtures and cardiometabolic outcomes
Abstract
Objectives
Specifying causal models to assess relationships among metal mixtures and cardiometabolic outcomes requires evidence-based models of the causal structures; however, such models have not been previously published. The objective of this study was to develop and evaluate a directed acyclic graph (DAG) diagraming metal mixture exposure and cardiometabolic outcomes.
Methods
We conducted a literature search to develop the DAG of metal mixtures and cardiometabolic outcomes. To evaluate consistency of the DAG, we tested the suggested conditional independence statements using linear and logistic regression analyses with data from the San Luis Valley Diabetes Study (SLVDS; n=1795). We calculated the proportion of statements supported by the data and compared this to the proportion of conditional independence statements supported by 1,000 DAGs with the same structure but randomly permuted nodes. Next, we used our DAG to identify minimally sufficient adjustment sets needed to estimate the association between metal mixtures and cardiometabolic outcomes (i.e., cardiovascular disease, fasting glucose, and systolic blood pressure). We applied them to the SLVDS using Bayesian kernel machine regression, linear mixed effects, and Cox proportional hazards models.
Results
From the 42 articles included in the review, we developed an evidence-based DAG with 74 testable conditional independence statements (43 % supported by SLVDS data). We observed evidence for an association between As and Mn and fasting glucose.
Conclusions
We developed, tested, and applied an evidence-based approach to analyze associations between metal mixtures and cardiometabolic health.
Funding source: National Institute of Environmental Health Sciences
Award Identifier / Grant number: R00ES027853
Funding source: Tufts Institute of the Environment
Funding source: Tufts University Department of Public Health and Community Medicine
Award Identifier / Grant number: K12HD092535
Acknowledgments
We would like to thank the participants and staff of the San Luis Valley Diabetes Study.
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Research funding: Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD) grant number K12HD092535 (Corlin), Tufts University Department of Public Health and Community Medicine (Corlin and Riseberg), Tufts Institute of the Environment (Riseberg), R00ES027853 (Alderete).
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Author contribution: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Competing interests: Authors state no conflict of interest.
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Informed consent: Informed consent was obtained from all individuals included in this study.
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Ethical approval: The SLVDS was approved by the Colorado Multiple Institutional Review Board. The Tufts University Social, Behavioral & Educational Research Institutional Review Board deemed this study Not Human Subjects Research (study # 00000131).
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Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/em-2022-0133).
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Articles in the same Issue
- Research Articles
- Development and application of an evidence-based directed acyclic graph to evaluate the associations between metal mixtures and cardiometabolic outcomes
- Addressing substantial covariate imbalance with propensity score stratification and balancing weights: connections and recommendations
- Tutorial
- On some pitfalls of the log-linear modeling framework for capture-recapture studies in disease surveillance