The impact of heat exposure on reduced gestational age in pregnant women in North Carolina, 2011–2015
Research on the impact of heat on pregnant women has focused largely on outcomes following extreme temperature events, such as particular heat waves or spells of very cold weather on pregnant women. Consistently, the literature has shown a statistically significant relationship between heat with shortened gestational age with studies concentrated largely in the western states of the USA or other nations. The association between heat and shortened gestational age has not been examined in the Southeastern US where maternal outcomes are some of the most challenging in the nation. Unlike previous studies that focus on the impacts of a single heat wave event, this study seeks to understand the impact of high heat over a 5-year period during the annual warm season (May–September). To achieve this goal, a case-crossover study design is employed to understand the impact of heat on preterm labor across regions in North Carolina (NC). Temperature thresholds for impact and the underlying relationships between preterm labor and heat are investigated using generalized additive models (GAM). Gridded temperature data (PRISM) is used to establish exposure classifications. The results reveal significant impacts to pregnant women exposed to heat with regional variations. The exposure variable with the most stable and significant result was minimum temperature, indicating high overnight temperatures have the most impact on preterm birth. The magnitude of this impact varies across regions from a 1% increase in risk to 6% increase in risk per two-degree increment above established minimum temperature thresholds.
KeywordsClimate-health vulnerabilities Heat-health Southeast Maternal health
The authors would like to acknowledge Jess Rinsky, PhD, MPH, Epidemiologist, Division of Public Health, Occupational and Environmental Epidemiology Branch, NC Department of Health and Human Services for her consultation and guidance on this project.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
- Avalos L, Chen H, De-Kun L, Basu R (2017) The impact of high ambient temperature on spontaneous preterm delivery: a case-crossover study. Environ Health 16(5). https://doi.org/10.1186/s12940-017-0205-5
- Daly C, Halbleib M, Smith JI, Gibson WP, Doggett MK, Taylor GH, Curtis J, Pasteris PP (2008) Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States. Int J Climatol 28(15):2031–2064. https://doi.org/10.1002/joc.1688 CrossRefGoogle Scholar
- Fisher, Sheehan, Colton (2016) Home energy affordability gap. Public Finance and General Economics, Belmont, MassachusettsGoogle Scholar
- Frich P, Alexander LV, Della-Marta P, Gleason B, Haylock M, Klein Tank AMG, Peterson T (2002) Observed coherent changes in climatic extremes during the second half of the twentieth century. Climate Research. 19(3):193–212Google Scholar
- He, J., Liu, Y., Xia, X., Ma., W., Lin, H., Kan, H., Lu, J., Feng, Q., Mo, W., Wang, P., Xia, H., Qiu, X., Muglia, L. (2016). Ambient temperature and the risk of preterm birth in Guangzhou, China (2001-2011). Environ Health Perspect 124(7), 1100–1106Google Scholar
- Li C, West-Strum D (2010) Patient panel of underserved populations and adoption of electronic medical record systems by office–based physicians. Health Services Research. 4:963–84Google Scholar
- Matthew S, Mathur D, Chang A, McDonald E, Singh G, Nur D, Gerristen R (2017) Examining the effects of ambient temperature on pre-term birth in Central Australia. Environ Res Public Health 14(147)Google Scholar
- PRISM Climate Group, Oregon State University, http://prism.oregonstate.edu, created 11 Jul 2012
- Sayres WG Jr (2010) Preterm labor. Am Fam Physician 81:477–484Google Scholar
- Schoen, C., Tabbah, S., Iams, J., Caughey, A., Berghella, V. (2015). Why the United States preterm birth rate is declining. American Journal of Obstetrics and Gynecology. 185-180Google Scholar
- Social Explorer; U.S. Census Bureau; (2016) ACS 1-year and 2012–2016 ACS 5-year Data Releases: Technical DocumentationGoogle Scholar
- United States Department of Health and Human Services (US DHHS), Centers for Disease Control and Prevention (CDC), National Center for Health Statistics (NCHS),2018 Division of Vital Statistics, Natality public-use data on CDC WONDER Online Database, for years 2007–2016 available February 2018Google Scholar
- Weinick RM, Byron SC, Bierman AS, (2005) Who can’t pay for health care? Journal of General Internal Medicine. 20(6):504–509Google Scholar
- xmACIS: Applied Climate Information System (2018). NOAA Regional Climate Centers. http://xmacis.rcc-acis.org. Retrieved 2018