Causes of Miscarriage: Evidence from Logistic Regression Analysis

Authors

  • Nasir Elmesmari University of Benghazi, Benghazi-Libya

Keywords:

Pregnancy, Miscarriage, maternal age, chronic conditions, Logistic regression, Binary data

Abstract

The unexpected end of a pregnancy before the birth is called Miscarriage. The miscarriage rate among pregnant women is about 15 to 20%. The first step in emotional recovery is to gain a better understanding of miscarriages. Next, it’s important to identify the factors that can elevate the risk of miscarriage. The objective of this study was employing a logistic regression model to evaluate the impact of various factors, including maternal age, embryo weight, chronic conditions, the number of previous miscarriages, and the embryo's gender. Our analysis reveals that when we control for these characteristics, the findings based on the data sample show that maternal age, chronic conditions, and the number of previous miscarriages have statistically significant impact on the incidence of miscarriage.

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Published

2024-12-24

How to Cite

Nasir Elmesmari. (2024). Causes of Miscarriage: Evidence from Logistic Regression Analysis. International Journal of Sciences: Basic and Applied Research (IJSBAR), 75(1), 1–15. Retrieved from https://gssrr.org/index.php/JournalOfBasicAndApplied/article/view/17246

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