Using an External Exposome Framework to Examine Pregnancy-Related Morbidities and Mortalities: Implications for Health Disparities Research

International Journal of Environmental Research and Public Health

Tonny J. Oyana²  Patricia Matthews-Juarez¹  Stephania A. Cormier¹  Xiaoran Xu¹  Paul D. Juarez¹  Mark Edberg³  Barbara E. Hayes³  Valerie Montgomery Rice³ 

[1] Pediatrics, Infectious Disease and Microbiology, Immunology & Biochemistry, University of Tennessee Health Science Center, Le Bonheur Children’s Medical Center, Memphis, TN 36163, USA;;Research Center on Health Disparities, Equity & the Exposome, Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN 38163, USA;id="af1-ijerph-13-00013">1Research Center on Health Disparities, Equity & the Exposome, Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN 38163, U

关键词: external exposome;    health disparities;    pregnancy outcomes;    maternal mortality;    infant mortality;    premature birth;    low birthweight;    geographic information systems;    discrete Poisson model;   

DOI  :  10.3390/ijerph13010013

来源: mdpi

【 摘 要 】

Objective: We have conducted a study to assess the role of environment on the burden of maternal morbidities and mortalities among women using an external exposome approach for the purpose of developing targeted public health interventions to decrease disparities. Methods: We identified counties in the 48 contiguous USA where observed low birthweight (LBW) rates were higher than expected during a five-year study period. The identification was conducted using a retrospective space-time analysis scan for statistically significant clusters with high or low rates by a Discrete Poisson Model. Results: We observed statistically significant associations of LBW rate with a set of predictive variables. However, in one of the two spatiotemporal models we discovered LBW to be associated with five predictive variables (teen birth rate, adult obesity, uninsured adults, physically unhealthy days, and percent of adults who smoke) in two counties situated in Alabama after adjusting for location changes. Counties with higher than expected LBW rates were similarly associated with two environmental variables (ozone and fine particulate matter). Conclusions: The county-level predictive measures of LBW offer new insights into spatiotemporal patterns relative to key contributory factors. An external framework provides a promising place-based approach for identifying “hotspots” with implications for designing targeted interventions and control measures to reduce and eliminate health disparities.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.