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Multilevel quantile function modeling with application to birth outcomes.

Luke B Smith1, Brian J Reich1, Amy H Herring2

  • 1Department of Statistics, North Carolina State University, Raleigh, North Carolina 27695-8203, U.S.A.

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|March 13, 2015
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Summary
This summary is machine-generated.

Air pollution, specifically ozone, is linked to adverse birth outcomes like lower gestational age and birth weight in Texas infants. This study introduces a novel Bayesian approach to analyze these complex environmental health relationships.

Keywords:
Birth weightDiscreteExtremesGestational AgeGraphics processing unitsOzoneQuantile

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Area of Science:

  • Environmental epidemiology
  • Biostatistics
  • Perinatal health

Background:

  • Infants born preterm or small for gestational age face higher morbidity and mortality risks.
  • Understanding environmental factors influencing birth outcomes is crucial for public health.

Purpose of the Study:

  • To investigate the association between ozone exposure and birth weight and gestational age in Texas infants.
  • To develop and apply a flexible semi-parametric Bayesian quantile model for analyzing environmental health data.

Main Methods:

  • Utilized Texas birth certificate data (2002-2004) and EPA air pollution estimates.
  • Employed a semi-parametric Bayesian multilevel quantile function model to analyze the full distribution of birth weight and gestational age.
  • Incorporated extreme value theory for low birth weight analysis and methods for discrete response data.

Main Results:

  • Ozone exposure was negatively associated with the lower tail of gestational age in South Texas.
  • Ozone exposure showed a negative association with the distribution of birth weight for high gestational ages.
  • The proposed modeling approach demonstrated reduced mean squared error in effect estimation through information pooling.

Conclusions:

  • Environmental factors like ozone can significantly impact infant birth outcomes, particularly at the extremes of the distribution.
  • The developed Bayesian quantile methodology provides a robust framework for analyzing complex environmental health associations.
  • The R package BSquare offers accessible tools for implementing these advanced statistical methods.