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An Assessment of Multisectoral Factors Influencing Global Trends in Neonatal Mortality Rates Open Access (recommended)

Descriptions

Resource type(s)
Masters Thesis
Keyword
neonatal mortality
income
health risks
public health
Rights
Attribution 4.0 International

Creator
Karmazin, Michelle
Abstract
Objective: Neonatal mortality continues to be a global burden on healthcare. Multisectoral factors have been identified that are associated with neonatal mortality rate. The primary objective of this study was to determine the extent of the association between these variables and neonatal mortality rate, and which variables are key in targeting for future public health policy to reduce neonatal death. Methods: Preliminary data analysis revealed variables believed to be associated with neonatal mortality rate. The twenty countries that account for 75% of total global neonatal death were identified. STATA statistical analysis software was used to conduct data analysis from 2000 to 2019, in 5-year intervals, for all countries. Regression analyses and correlation matrices were run for neonatal mortality and variables such as median income, stillbirth rates, healthcare spending, low birth weight, relative number of physicians, relative number of nurses, literacy level, and maternal mortality ratio. The variables were entered into a series of models that accounted for different combinations. Model A included neonatal mortality rate, maternal mortality ratio change, and median income change. Model B included low birth weight instead of maternal mortality ratio. Model C included neonatal mortality rate, low birth weight rate, and healthcare spending. Model D included neonatal mortality rate, median income, and literacy level. Results: The mean change in nation-level median income over the last 20 years was found to be 1.63 times the median income in 2000-2004. The regression analysis revealed that an increase in median income was associated with a decrease in neonatal mortality rate. There was a 2.7-unit change in neonatal mortality rate seen for every 1-unit change in low-birth-weight rate, a 0.24 unit decrease for every 1-unit change in literacy level, a 1.47-point decrease for every 1-unit change of healthcare spending, and a 0.02-unit change for every 1-unit change in maternal mortality ratio from 2000-2004 through 2015-2019. Model A demonstrated that there was a 0.02 change in neonatal mortality rate for every 1-unit change in maternal mortality ratio, and a -1.58-unit change for every 1 unit of median income. Model B demonstrated that there was a 2.39-unit change in neonatal mortality rate for every 1-unit change in low-birth-weight rate, and a -1.46-unit change for every 1 unit of median income. Model C demonstrated that there was a 2.56-unit change in neonatal mortality rate for every 1-unit change in low-birth-weight rate, and a -1.32-unit change for every 1 unit of healthcare spending. Model D demonstrated that there was a -0.23-unit change in neonatal mortality rate for every 1 unit increase in literacy level, and a -1.45-unit change for every 1 unit increase in median income. Discussion: The results of this analysis suggest the highest degree of correlation between neonatal mortality rate, maternal mortality ratio, and median income. There results offer foundational starting points for research in neonatal mortality and associated multisectoral factors. Further research is necessary to determine how these results can be used to target mortality reduction in the twenty countries determined to have the highest neonatal total deaths. Focusing on median income as a strongly correlated factor of neonatal mortality rate may allow for the future creation of targeted public health policies. Creating models that account for a higher percentage of the variance would be useful as well. Future analysis should focus on deriving deeper associations between the variables through further literature review or data collection. In addition, future research should focus on determining why the association between maternal mortality ratio and neonatal mortality rate wasnt as high as anticipated. Eventually, these findings could be used to influence public health programs, policy, or planning by aiding in the creation of a dissemination plan for a best practice training program aimed at reducing neonatal mortality rated globally.
Publisher
DigitalHub. Galter Health Sciences Library & Learning Center
Date Created
2021-05-25
DOI
10.18131/g3-s0pr-jm28

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