Big Data Meets Public Health: A Logistic Regression Analysis of Vitamin D Deficiency in the U.S. using the National Institutes of Health’s All of Us Database

Abstract

Vitamin D deficiency is a long-standing public health issue associated with various chronic conditions. This study explores how genetic ancestry, specific single nucleotide polymorphisms (SNPs), and solar radiation exposure influence the risk of vitamin D deficiency in the diverse U.S. population using data from the large-scale All of Us project. With a matched case-control study of 16,145 vitamin D-deficient and 16,145 vitamin D-sufficient participants, logistic regression was used to assess these associations. Findings reveal that African ancestry, particular SNP variants, and lower solar radiation exposure are significant predictors of deficiency. The results also show that risk factors differ among racial groups, emphasizing the complexity of gene-environment interactions. This research contributes to a deeper understanding of the biological and environmental drivers of vitamin D deficiency and may support the development of personalized and population-specific public health strategies to address disparities in vitamin D-related health outcomes. Keywords — Genetic Ancestry, Logistic Regression, SNPs, Vitamin D Deficiency.