Exposure to extreme temperatures may increase the risk of preterm birth in a dose-response manner

Elizabeth A. DeVilbiss Co-Author
Division of Population Health Research, Division of Intramural Research, NICHD
 
Elizabeth H. Scholl Co-Author
Sciome, LLC
 
Taylor Petty Co-Author
Sciome, LLC
 
Brian Kidd Co-Author
Sciome, LLC
 
Deepak Mav Co-Author
Sciome, LLC
 
Shyamal Peddada Co-Author
NIEHS
 
Jagteshwar Grewal Co-Author
Division of Population Health Research, Division of Intramural Research, NICHD, NIH
 
Neil Perkins Co-Author
NIH/NICHS
 
Siddharth Rawat First Author
 
Siddharth Rawat Presenting Author
 
Wednesday, Aug 6: 2:50 PM - 3:05 PM
1719 
Contributed Papers 
Music City Center 
The frequency and severity of extreme temperatures have been increasing and are expected to continue to escalate in the coming decades. Relationships between extreme temperatures and early deliveries are not well understood. This study explores these relationships among 203,691 pregnant women in the Consortium on Safe Labor (CSL) study (2002-2008) with a novel spatially diverse extreme temperature exposure metric. Both extreme cold and heat were meaningfully associated with increased risks of early delivery, with relationships especially pronounced for third-trimester exposures. The strongest observed association was between extreme cold and early preterm birth (gestational age < 34 weeks), with the odds of these births over five times as likely relative to unexposed pregnancies. The likelihood of early delivery increased monotonically with higher proportions of days of exposure to extreme temperatures. We develop a novel constrained statistical inference-based methodology to test the hypothesis, which is statistically significant (p-value < 0.0001). Future work should seek to clarify underlying mechanisms and extend to recent data from the U.S. and other countries.

Keywords

Extreme temperature exposures

Early deliveries

Pregnancy outcomes

Constrained statistical inference

Hypothesis testing

Matrix ordering 

Main Sponsor

Section on Statistics in Epidemiology