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Statistical Methods for Precision Environmental Health with Mixture Exposures

Award Number: R01ES035735
ORGANIZATION: NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 07/06/2024
PERIOD OF PERFORMANCE END DATE: 04/30/2029

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Statistical Methods for Precision Environmental Health with Mixture Exposures - Project Summary/Abstract Precision environmental health focuses on individual risk assessment to inform targeted disease prevention strate gies. Identifying individuals with increased sensitivity to environmental exposures is especially challenging with mixture exposures. The health effects of exposure to mixtures are likely to depend on the composition of the mixture, characteristics specific to the espoused individual including individual and neighborhoodlevel factors, and the developmental stage at which an individual is exposed. We propose to develop statistical methods for precision environmental health with mixture exposures. The proposed methods will estimate mixtureexposure response relationships that are individualized based on multiple candidate modifying factors. The framework we develop will allow for datadriven discovery of novel combinations of individual and neighborhoodlevel factors that define susceptible subgroups. We will address three specific data settings. In Aim 1 we propose a general framework for effect heterogeneity using established mixture methods including Bayesian multiple index models. This will include heterogeneous versions of Bayesian kernel machine regression and linear index models. In Aim 2 we develop methods to identify critical windows of susceptibility to mixtures that are assessed longitudinally. The methods will allow for identification of individualized windows of susceptibility to a mixture and estimation of individualized mixtureexposuretimeresponse functions. In Aim 3 we develop heterogeneous mixture methods for multiple outcomes. The multiple outcome methods will apply to trajectories defined by repeated measures of common endpoint or pathway as well as shared information across multiple related endpoints, such as multiple measures of a common pathway. In Aim 4 we will develop software to implement the methods, along with vignettes and tutorials. We will use the methods developed to analyze air pollution mixtures in a large administrative birth cohort and in a Northeastern United States longitudinal perinatal cohort drawing from multiple source populations. We will estimate individualized mixtureexposureresponse functions for birth weight and multiple neurodevelop mental endpoints assessed at multiple times. The methods we develop will allow for new avenues of precision environmental health to better identify individuals at increased risk of adverse effects of the environment, which will better inform targeted disease prevention strategies.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2025 ( Subtotal = $498,576 )
2025	2025	COLORADO STATE UNIVERSITY	601 S HOWES ST	FORT COLLINS	CO	80521	LARIMER	USA	Environmental Health	000	2	8/14/2025	NON-COMPETING CONTINUATION	$498,576
														Subtotal = $498,576

Issue Date FY: 2024 ( Subtotal = $528,194 )
2024	2024	COLORADO STATE UNIVERSITY	601 S HOWES ST	FORT COLLINS	CO	80521	LARIMER	USA	Environmental Health	000	1	7/5/2024	NEW	$528,194
														Subtotal = $528,194

Grand Total All Awards = $1,026,770

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Statistical Methods for Precision Environmental Health with Mixture Exposures

Award Number: R01ES035735

ORGANIZATION: NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 07/06/2024

PERIOD OF PERFORMANCE END DATE: 04/30/2029

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