Examining Predictors of Birth Outcomes: Implications for Early Childhood Development and Policy

While the infant mortality rate has improved significantly in the United States in recent years, a Black-White disparity persists. The problem is the high infant mortality rate in the state of Texas. The purpose of this quantitative multiple logistic regression study was to examine disparities in birth outcomes in the state of Texas by race, ethnicity, and other significant predictors related to socioeconomic status. The Mosley-Chen theoretical framework bridges the gap between social science and biomedicine to identify key predictors of infant mortality including socioeconomic factors for studies in child development. The 2 research questions examined if race and ethnicity would predict infant mortality and if any predictor had a statistically significant impact on women and infant mortality. The methodology of this study used sequential multiple logistic regression analysis, with the inclusion criteria of all available linked birth/infant death records from the National Bureau of Economic Research for 2011â2013, to examine the likelihood that the independent variables could predict infant mortality. The sample size was 11,862,780. The results indicated there was a statistically significant likelihood that race and ethnicity would predict infant mortality and that one predictor, prenatal care, had a statistically significant impact on women and infant mortality. This study\u27s findings can inform positive social change by encouraging researchers and policymakers to further examine the role of racial disparities in health. Additionally, study findings may encourage community groups to examine possible changes in policy and educational practices to benefit women and children in Texas by focusing on racial disparities and equity gaps and their effects on children and families