Variables Affecting the Mothers Access to Quality Care during Childbirth using the Neural Networks and Logistic Regression Models

Authors

H. E. Semary, Mathematics and Statistics Department, Faculty of Science, Imam Mohammed Ibn Saud Islamic University (IMSIU), Riyadh, Box 11432, Saudi ArabiaFollow
I. M. Abd El-Fatah, Statistics and Insurance Department, Faculty of Commerce, Zagazig University, Box 44511, Zagazig, EgyptFollow
S. E. El-Desouky, Statistics and Insurance Department, Faculty of Commerce, Zagazig University, Box 44511, Zagazig, EgyptFollow
M. M. El-madawye, Statistics and Insurance Department, Faculty of Commerce, Zagazig University, Box 44511, Zagazig, EgyptFollow

Author Country (or Countries)

Saudi Arabia

Abstract

Quality pregnancy and birth care is crucial in reducing maternal and child mortality in Egypt, requiring both supply and demand interventions. Using data from the Egypt Demographic Health Survey 2014, a neural networks and logistic regression models were built to determine demographic, social, and economic determinants affecting mothers access to care during childbirth. The study found that mothers working status had a significant impact on access to care, with an inverse relationship. Logistic regression outperformed neural networks in analyzing the relationship between explanatory variables and mothers access to care during childbirth.

Digital Object Identifier (DOI)

http://dx.doi.org/10.18576/jsap/120314

Recommended Citation

E. Semary, H.; M. Abd El-Fatah, I.; E. El-Desouky, S.; and M. El-madawye, M. (2023) "Variables Affecting the Mothers Access to Quality Care during Childbirth using the Neural Networks and Logistic Regression Models," Journal of Statistics Applications & Probability: Vol. 12: Iss. 3, Article 14.
DOI: http://dx.doi.org/10.18576/jsap/120314
Available at: https://digitalcommons.aaru.edu.jo/jsap/vol12/iss3/14