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Exploration of Preterm Birth Rates Using the Public Health Exposome Database and Computational Analysis Methods

Author

Listed:
  • Anne D. Kershenbaum

    (Department of Public Health, University of Tennessee, Knoxville, TN 37996, USA)

  • Michael A. Langston

    (Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN 37996, USA)

  • Robert S. Levine

    (Department of Family and Community Medicine, Meharry Medical College, Nashville, TN 37208, USA)

  • Arnold M. Saxton

    (Department of Animal Science, Institute of Agriculture, University of Tennessee, Knoxville, TN 37996, USA)

  • Tonny J. Oyana

    (Research Center on Health Disparities, Equity, and the Exposome, University of Tennessee Health Science Center, Memphis, TN 38163, USA)

  • Barbara J. Kilbourne

    (Department of Family and Community Medicine, Meharry Medical College, Nashville, TN 37208, USA)

  • Gary L. Rogers

    (National Institute for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA)

  • Lisaann S. Gittner

    (Department of Political Sciences, Texas Tech University, Lubbock, TX 79409, USA)

  • Suzanne H. Baktash

    (Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN 37996, USA)

  • Patricia Matthews-Juarez

    (Research Center on Health Disparities, Equity, and the Exposome, University of Tennessee Health Science Center, Memphis, TN 38163, USA)

  • Paul D. Juarez

    (Research Center on Health Disparities, Equity, and the Exposome, University of Tennessee Health Science Center, Memphis, TN 38163, USA)

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 of highly correlated variables were resolved into latent factors, which were then used to build a regression model explaining prematurity (R-squared = 76.7%). Two lists of counties with large positive and large negative residuals, indicating unusual prematurity rates given their circumstances, may serve as a starting point for ways to intervene and reduce health disparities for preterm births.

Suggested Citation

  • Anne D. Kershenbaum & Michael A. Langston & Robert S. Levine & Arnold M. Saxton & Tonny J. Oyana & Barbara J. Kilbourne & Gary L. Rogers & Lisaann S. Gittner & Suzanne H. Baktash & Patricia Matthews-J, 2014. "Exploration of Preterm Birth Rates Using the Public Health Exposome Database and Computational Analysis Methods," IJERPH, MDPI, vol. 11(12), pages 1-21, November.
    • Handle: RePEc:gam:jijerp:v:11:y:2014:i:12:p:12346-12366:d:42883
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    References listed on IDEAS

    as
    1. Michael A. Langston & Robert S. Levine & Barbara J. Kilbourne & Gary L. Rogers & Anne D. Kershenbaum & Suzanne H. Baktash & Steven S. Coughlin & Arnold M. Saxton & Vincent K. Agboto & Darryl B. Hood &, 2014. "Scalable Combinatorial Tools for Health Disparities Research," IJERPH, MDPI, vol. 11(10), pages 1-25, October.
    2. Levine, R.S. & Briggs, N.C. & Kilbourne, B.S. & King, W.D. & Fry-Johnson, Y. & Baltrus, P.T. & Husaini, B.A. & Rust, G.S., 2007. "Black-white mortality from HIV in the United States before and after introduction of highly active antiretroviral therapy in 1996," American Journal of Public Health, American Public Health Association, vol. 97(10), pages 1884-1892.
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    Citations

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    Cited by:

    1. Tonny J. Oyana & Patricia Matthews-Juarez & Stephania A. Cormier & Xiaoran Xu & Paul D. Juarez, 2015. "Using an External Exposome Framework to Examine Pregnancy-Related Morbidities and Mortalities: Implications for Health Disparities Research," IJERPH, MDPI, vol. 13(1), pages 1-14, December.
    2. Paul D. Juarez & Patricia Matthews-Juarez & Darryl B. Hood & Wansoo Im & Robert S. Levine & Barbara J. Kilbourne & Michael A. Langston & Mohammad Z. Al-Hamdan & William L. Crosson & Maurice G. Estes &, 2014. "The Public Health Exposome: A Population-Based, Exposure Science Approach to Health Disparities Research," IJERPH, MDPI, vol. 11(12), pages 1-30, December.
    3. Michael A. Langston & Robert S. Levine & Barbara J. Kilbourne & Gary L. Rogers & Anne D. Kershenbaum & Suzanne H. Baktash & Steven S. Coughlin & Arnold M. Saxton & Vincent K. Agboto & Darryl B. Hood &, 2014. "Scalable Combinatorial Tools for Health Disparities Research," IJERPH, MDPI, vol. 11(10), pages 1-25, October.

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