Open AccessLogistic Regression Modeling for Maternal Determinants of Low Birth Weight
Author(s) -
S. Sundarabalan,
S. Raguraman
Publication year - 2022
Publication title -
international journal of scientific research in science and technology
Language(s) - English
Resource type - Journals
eISSN - 2395-602X
pISSN - 2395-6011
DOI - 10.32628/ijsrst229131
Subject(s) - logistic regression , low birth weight , birth weight , socioeconomic status , medicine , demography , regression analysis , obstetrics , pregnancy , statistics , environmental health , mathematics , population , biology , genetics , sociology
Low birth weight is a major public health issue in India. Low birth weight leads to an impaired growth of the infant resulting in a higher mortality rate and increased morbidity. In India, nearly 20% of new borns have Low birth weight. Males have less frequency of Low birth weight than females. This study emphasizes the need for improving maternal health, weight gain during pregnancies, prevention and proper management of risk factors along with improving socioeconomic and educational status of mothers. Logistic regression is a statistical model for analyzing a dataset in which one or more independent variables that determine an outcome. The main objective of this paper is to identify the predictors of low birth weight through simple logistic regression model.