# Environmental Data Integration to Assess Impacts of Shale Gas Development on Perinatal Health Outcomes and Childhood Cancers

> **NIH NIH F31** · OREGON STATE UNIVERSITY · 2020 · $14,377

## Abstract

PROJECT SUMMARY
While ambient air pollution is a well-recognized risk factor for adverse infant and childhood health outcomes,
inadequate research exists on the health impacts of air emissions from emerging industries such as shale gas
development (SGD). The SGD industry rapidly expanded from under 30,000 sites in 2000 to over 300,000 sites
in 2016, so now approximately 17.6 million Americans now live within one mile of a drilling site. Given this
substantial population exposure, there is an immediate need to determine the health risks associated with SGD
air emissions and develop effective methods to evaluate and reduce exposure to emerging hazards. This study
will use data science and big data techniques to integrate environmental data with health information to assess
the impact of SGD on infants and children who are exposed to the SGD industry in utero. Specific health data
will be derived from a large retrospective birth cohort (n=5,275,799) with full maternal addresses with linkages
to birth defect and childhood cancer registries from 1996 through 2009, which corresponds to the rapid increase
in Texas SGD activity. Texas is the largest shale gas producer in the country and 16% of its population (4.5
million people) lives within 1 mile of drilling, thus this is the ideal cohort to study this exposure. Aim 1 builds novel
spatial-temporal exposure metrics from administrative and proprietary data sources to capture multiple pathways
by which SGD may affect local populations, including specific SGD processes (e.g. production, flaring), traffic
from the industry, and wind direction between homes and drilling. To date, these sources have not been used in
large-scale data integration projects. By assessing policy-relevant SGD exposures, these metrics represent a
substantial advancement over previous exposure assessments used in epidemiology and risk assessment
studies, which can be applied to SGD as well as future threats. Aim 2 applies these spatial-temporal metrics to
the geocoded birth cohort to quantify the impact of specific SGD processes and related exposures on adverse
birth outcomes, birth defects, and childhood cancers. This analysis uses a unique causal-inference framework
that leverages cross-disciplinary epidemiological, economic, and ontological methods. The results of the health
analyses will provide further insights into which SGD exposures influence perinatal health outcomes as well as
the policy guidelines that can help reduce risks for local communities. The proposed research will synthesize
spatial exposure assessment methods, advance environmental health data science techniques, and develop
causal-inference models to produce robust risk estimates for SGD exposures. Findings from the proposed study
will provide a better understanding of how SGD is affecting local communities by providing the foundational
evidence for the effects of SGD exposure on infant and children’s health. Beyond the risks associated with SGD,
this project wi...

## Key facts

- **NIH application ID:** 10025379
- **Project number:** 5F31ES029801-02
- **Recipient organization:** OREGON STATE UNIVERSITY
- **Principal Investigator:** Mary D Willis
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $14,377
- **Award type:** 5
- **Project period:** 2019-09-01 → 2020-09-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10025379

## Citation

> US National Institutes of Health, RePORTER application 10025379, Environmental Data Integration to Assess Impacts of Shale Gas Development on Perinatal Health Outcomes and Childhood Cancers (5F31ES029801-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10025379. Licensed CC0.

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