It is well-documented that low birth weight (LBW) is the most significant factor influencing Neonatal mortality rate (NMR). Over recent decades, accumulating evidence around the world has suggested that LBW may be associated with an increased risk of subsequent development of a variety of complications in adulthood including cardiovascular disease, non-insulin-dependent diabetes mellitus, hypertension, and dyslipidemia. Neonatal birth weight is determined by several criteria such as, maternal age, pre-pregnancy Body Mass Index (BMI), gestation age and neonatal gender. This paper deploys regression analysis to explore the effect of pre-pregnancy BMI and other characteristics on the weight of low birth weight babies. The results indicate that the inclusion of the BMI in the regression model can improve the coefficient of the determination significantly.
History
Start page
567
End page
572
Total pages
6
Outlet
Proceeding of the Tenth International Conference on Information Technology: New Generations