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Using Metrics of a Mixture Effect and Nutrition from an Observational Study for Consideration towards Causal Inference

Gennings, Chris ; Svensson, Katherine ; Wolk, Alicja ; Lindh, Christian LU orcid ; Kiviranta, Hannu and Bornehag, Carl Gustaf LU (2022) In International Journal of Environmental Research and Public Health 19(4).
Abstract

Environmental exposures to a myriad of chemicals are associated with adverse health effects in humans, while good nutrition is associated with improved health. Single chemical in vivo and in vitro studies demonstrate causal links between the chemicals and outcomes, but such studies do not represent human exposure to environmental mixtures. One way of summarizing the effect of the joint action of chemical mixtures is through an empirically weighted index using weighted quantile sum (WQS) regression. My Nutrition Index (MNI) is a metric of overall dietary nutrition based on guideline values, including for pregnant women. Our objective is to demonstrate the use of an index as a metric for more causally linking human exposure to health... (More)

Environmental exposures to a myriad of chemicals are associated with adverse health effects in humans, while good nutrition is associated with improved health. Single chemical in vivo and in vitro studies demonstrate causal links between the chemicals and outcomes, but such studies do not represent human exposure to environmental mixtures. One way of summarizing the effect of the joint action of chemical mixtures is through an empirically weighted index using weighted quantile sum (WQS) regression. My Nutrition Index (MNI) is a metric of overall dietary nutrition based on guideline values, including for pregnant women. Our objective is to demonstrate the use of an index as a metric for more causally linking human exposure to health outcomes using observational data. We use both a WQS index of 26 endocrine-disrupting chemicals (EDCs) and MNI using data from the SELMA pregnancy cohort to conduct causal inference using g-computation with counterfactuals for assumed either reduced prenatal EDC exposures or improved prenatal nu-trition. Reducing the EDC exposure using the WQS index as a metric or improving dietary nutrition using MNI as a metric, the counterfactuals in a causal inference with one SD change indicate significant improvement in cognitive function. Evaluation of such a strategy may support decision mak-ers for risk management of EDCs and individual choices for improving dietary nutrition.

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author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Endocrine disruptors, G-computation, Nutritional status, WQS regression
in
International Journal of Environmental Research and Public Health
volume
19
issue
4
article number
2273
publisher
MDPI AG
external identifiers
  • scopus:85124595330
  • pmid:35206461
ISSN
1661-7827
DOI
10.3390/ijerph19042273
language
English
LU publication?
yes
id
e86ad1fd-1bd5-407c-b3d9-f85aa4e2662e
date added to LUP
2022-04-13 10:26:51
date last changed
2024-06-18 15:48:44
@article{e86ad1fd-1bd5-407c-b3d9-f85aa4e2662e,
  abstract     = {{<p>Environmental exposures to a myriad of chemicals are associated with adverse health effects in humans, while good nutrition is associated with improved health. Single chemical in vivo and in vitro studies demonstrate causal links between the chemicals and outcomes, but such studies do not represent human exposure to environmental mixtures. One way of summarizing the effect of the joint action of chemical mixtures is through an empirically weighted index using weighted quantile sum (WQS) regression. My Nutrition Index (MNI) is a metric of overall dietary nutrition based on guideline values, including for pregnant women. Our objective is to demonstrate the use of an index as a metric for more causally linking human exposure to health outcomes using observational data. We use both a WQS index of 26 endocrine-disrupting chemicals (EDCs) and MNI using data from the SELMA pregnancy cohort to conduct causal inference using g-computation with counterfactuals for assumed either reduced prenatal EDC exposures or improved prenatal nu-trition. Reducing the EDC exposure using the WQS index as a metric or improving dietary nutrition using MNI as a metric, the counterfactuals in a causal inference with one SD change indicate significant improvement in cognitive function. Evaluation of such a strategy may support decision mak-ers for risk management of EDCs and individual choices for improving dietary nutrition.</p>}},
  author       = {{Gennings, Chris and Svensson, Katherine and Wolk, Alicja and Lindh, Christian and Kiviranta, Hannu and Bornehag, Carl Gustaf}},
  issn         = {{1661-7827}},
  keywords     = {{Endocrine disruptors; G-computation; Nutritional status; WQS regression}},
  language     = {{eng}},
  number       = {{4}},
  publisher    = {{MDPI AG}},
  series       = {{International Journal of Environmental Research and Public Health}},
  title        = {{Using Metrics of a Mixture Effect and Nutrition from an Observational Study for Consideration towards Causal Inference}},
  url          = {{http://dx.doi.org/10.3390/ijerph19042273}},
  doi          = {{10.3390/ijerph19042273}},
  volume       = {{19}},
  year         = {{2022}},
}