Maternal Characteristics and Newborn Birth Weight: A Comprehensive Statistical Analysis
Prithwiraj Chatterjee, Abhinav Tanwar, Devadharshini Udayakumar

TL;DR
This study uses statistical analysis on real-world data to identify key maternal factors affecting newborn birth weight, highlighting the negative impact of smoking and the importance of gestation period as a predictor.
Contribution
It provides a comprehensive statistical evaluation of maternal characteristics' effects on birth weight using advanced tests within SAS, emphasizing public health implications.
Findings
Maternal smoking significantly reduces birth weight.
Gestation period is the strongest positive predictor.
No significant differences found for broad age and parity categories.
Abstract
This report presents a statistical analysis of the impact of key maternal characteristics, including age, smoking status, parity, height, weight, and gestation period, on newborn birth weight. A realworld dataset comprising 1,236 observations was utilized for this investigation. The methodology involved comprehensive data cleaning, exploratory data analysis (EDA), and a series of parametric statistical tests, specifically the One-Sample t-test, Two-Sample t-test, Chi-Square tests, and Analysis of Variance (ANOVA). All analyses were conducted within the SAS programming environment. The study's findings indicate a statistically significant negative impact of maternal smoking on birth weight, a finding consistent with broader public health literature. Gestation period emerged as the strongest positive predictor of birth weight within this dataset. While the analyses using broad categories…
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Taxonomy
TopicsGestational Diabetes Research and Management · COVID-19 Impact on Reproduction · Pregnancy and preeclampsia studies
