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Predictors of Infant Mortality

 

 

   Infant mortality rates represent an essential indicator of health in any population.  The United States has experienced a significant improvement in infant mortality rates over the last decade.  A large portion of this improvement is attributed to advances in medical treatment of very low birth weight infants, which illustrates U.S. health care reliance on costly medical interventions rather than on preventive measures.  Greater improvement is possible if health officials focused more on prevention of risk factors contributing to infant mortality.  The literature review suggests that numerous risk factors contribute to infant mortality in the United States.  Community health indicators, such as low birth weight, lack of health insurance, mother’s education level, and other preventable variables, can improve infant mortality and reduce the reliance on expensive clinical interventions.  These represent preventive measures, but the literature is not conclusive regarding which indicators have the greatest potential to identify the greatest risks associated with infant mortality.

 

   Many researchers and public health officials agree that aggressive preventive measures are required to improve infant mortality rates, but not all agree on what indicators most accurately identify those who are at highest risk.  This study hypothesized that infant mortality is a function of seven selected independent variables:

 

• Low birth weight
• Births to unmarried mothers
• Births to adolescent mothers
• People below the poverty level
• People without health insurance
• Children without health insurance
• Per capita income

 

Which of these variables do YOU believe correlates most to infant mortality in the U.S.?

 

   Multivariate regression analysis was applied to examine the relationship between infant mortality and the seven variables.  This methodology is consistent with analysis techniques used by other researchers.  The independent variables that correlated closest to infant mortality were treated as the most reliable predictors, or contributing risk factors, of infant mortality in the U.S.

 

   Results of this study clearly indicated that low birth weight, a broad outcome indicator, was a strong and reliable predictor of infant mortality, which is consistent with findings from the literature review.  However, births to adolescent mothers were equally as predictive of infant mortality, yet the available literature does not emphasize the degree to which this indicator predicts the dependent outcome (infant mortality).

 

   This finding has important implications for community health planning, prevention, and programming for outcome improvements.  Adolescent pregnancies represent a very specific population within a community.  Many interventions associated with improvements in today’s infant mortality rates relate to high cost clinical treatments, such as neonatal intensive care of very low birth weight infants.  This study demonstrates that a high-risk population (adolescent pregnancies) has a high likelihood of contributing to infant mortality.  Community health programs that target this high-risk population for prevention can contribute to lower infant mortality and prevent the costs associated with intensive clinical interventions.

 

   Reliability of these results is based on the data used for analysis.  Secondary data was obtained from the 1999 Statistical Abstract of the United States, which is based on U.S. Census Bureau compilations for each of the U.S states.  This is population-based data, which produces a more accurate representation compared to sample data.  Reliability, however, is also subject to the accuracy of U.S. Census Bureau data collection methods.

 

   This study is certainly open to improvements.  One limitation is based on the data used for analysis, which is based on entire state populations.  For evaluators interested in specific community analysis, this methodology can be replicated at the community level using population data produced by local health needs assessments.  This effort would provide a specific community with insight regarding the degree to which adolescent pregnancies (and other indicators) contribute to infant mortality in that community.

 

   The study also introduces the concept of “aggregate” predictors of infant mortality.  Aggregate outcome predictors may be described as those indicators having the capacity to include multiple risk factors while employing a single, or all-inclusive, predictor of a given outcome.  This concept of aggregate predictors may be useful to quantify the magnitude of multiple risks associated with a population under study; however, the concept is only introduced and requires further evaluation.

 

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