Exploration of preterm birth rates using the public health exposome database and computational analysis methods.

Anne D Kershebaum, Micheal A Langston, Robert S Levine, Arnold M Saxton, A M Oyana, Barbara J Kilbourne, Gary L Rogers, LisaAnn Gittner, Susanne H Baktash, Patricia Matthews-Juarez, Paul D Juarez

Research output: Other contributionpeer-review

Abstract

Recent advances in informatics technology has made it possible to integrate, manipulate, and analyze variables from a wide range of scientific disciplines allowing for the examination of complex social problems such as health disparities. This study used 589 county-level variables to identify and compare geographical variation of high and low preterm birth rates. Data were collected from a number of publically available sources, bringing together natality outcomes with attributes of the natural, built, social, and policy environments. Singleton early premature county birth rate, in counties with population size over 100,000 persons provided the dependent variable. Graph theoretical techniques were used to identify a wide range of predictor variables from various domains, including black proportion, obesity and diabetes, sexually transmitted infection rates, mother’s age, income, marriage rates, pollution and temperature among others. Dense subgraphs (paracliques) representing groups o
Original languageEnglish
Publisher. International Journal of Environmental Research and Public Health
Volume11
StatePublished - Nov 2014

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