# Extreme heat events and pregnancy duration: a national study

> **NIH NIH R01** · EMORY UNIVERSITY · 2020 · $531,577

## Abstract

PROJECT SUMMARY/ABSTRACT
Recent studies suggest high ambient temperatures increase the risk of preterm birth (<37 completed weeks of
gestation), a leading cause of infant mortality and long-term neurological disabilities. Infants born early term
(37-38 weeks) also have more morbidity compared to full term births. Under climate projections, heat waves
are expected to increase in frequency, intensity, and duration, and many will cause increases in ambient air
pollutant concentrations. The proposed research seeks to use large existing databases and robust
methodological approaches at multiple spatial scales to test the overarching hypothesis that extreme heat
events increase the risk of preterm birth and early term birth, with stronger associations hypothesized to be
observed following heat events of longer duration and greater intensity. Using national birth record data from
the National Center for Health Statistics, we will assess these relationships in 114 large U.S. cities (covering
54% of the population) at a county-level spatial resolution over a 36-year period (1981-2016). We will
additionally obtain birth record data from eight populous and geographically representative U.S. states
(covering 40% of the population) over the period 1990-2016 to assess relationships at ZIP code or finer
resolution and to examine possible mediation of heat wave associations by accompanying changes in air
pollution levels. Meteorology will be characterized by integrating hourly data from multiple weather station
networks and satellite-resources, harnessing the strengths of each dataset to maximize spatial and temporal
coverage and minimize exposure prediction error. Ambient concentrations of 12 pollutants for the eight
selected states will be also characterized by combining Community Multiscale Air Quality Model (CMAQ)
outputs with monitor measurements. The statistical models for preterm and early term birth will account for
seasonal patterns of conception (a possible source of bias in previous studies), and two-stage analyses using
Bayesian hierarchical models will be used to combine information across study locations and assess
heterogeneity by climate region, timing of the heat event (within season or across decades), maternal
characteristics (educational attainment, race/ethnicity), and location-specific attributes (e.g., contextual
socioeconomic indicators, air conditioning prevalence, urbanicity). Precise estimation of this heterogeneity is
possible due to the exceptionally large sample, which also allows for examination of heat events defined using
higher intensity and duration thresholds than previously assessed. The multi-scale approach facilitates
assessment and propagation of uncertainty due to exposure prediction errors, spatial aggregation, and
residential mobility during pregnancy. Results can be used to inform local public health warning systems such
as heat advisories that target pregnant women with the ultimate goal of reducing early birth and it...

## Key facts

- **NIH application ID:** 9914101
- **Project number:** 5R01ES028346-03
- **Recipient organization:** EMORY UNIVERSITY
- **Principal Investigator:** Howard H Chang
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $531,577
- **Award type:** 5
- **Project period:** 2018-05-01 → 2023-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9914101

## Citation

> US National Institutes of Health, RePORTER application 9914101, Extreme heat events and pregnancy duration: a national study (5R01ES028346-03). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/9914101. Licensed CC0.

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