R-Based Statistical Evaluation of Micronutrient Deficiencies in Early Pregnancy (1–8 Weeks)
Ejiro Stanley Omokoh. *
Department of Mathematics, University of Benin, Edo State, Nigeria.
Eduiyovwiri Lewis Ejiro
Department of Mathematics, Delta State College of Education Mosogar, Delta State, Nigeria.
Unaegbu Ebenezer Nkemjika
Department of Mathematics, Nnamdi Azikiwe University Awka, Nigeria.
Okogun Augustine Ejiroghene
Department of Mathematics, Delta State College of Education Mosogar, Delta State, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
Early pregnancy (1–8 weeks) is a crucial period in which micronutrient sufficiency directly influences maternal health and fetal development. Deficiencies in essential nutrients such as iron, folate, and vitamin D are major contributors to complications including anemia, neural tube defects, and impaired fetal growth. This study uses R programming to statistically evaluate micronutrient deficiencies in early pregnancy using simulated biomarker data. A dataset of 150 women in early pregnancy was simulated, including biomarkers (hemoglobin, ferritin, folate, and vitamin D). Descriptive statistics, logistic regression, and ROC analysis were performed using R. Iron deficiency prevalence was 30%, anemia 24%, folate deficiency 17%, and vitamin D deficiency 33%. Ferritin showed a strong predictive performance (AUC = 0.85) for iron deficiency. R programming offers a flexible, reproducible, and scalable framework for analyzing nutritional biomarkers and identifying at-risk pregnant women during the first trimester.
Keywords: R programming, micronutrient deficiency, early pregnancy, ferritin, iron deficiency, ROC analysis, statistical modeling