Determination of Factors Affecting Vitamin D Levels in Women at Risk Using Classification and Regression Tree Analysis

Abstract

BACKGROUND: The influence of the factors on Vitamin D as a health indicator in premenopausal and menopausal women is a significant subject to be investigated. AIM: The study uses the potential of classification and regression trees (CART) as a data mining method for medical type samples. METHODS: The data set is built by records of 84 indoor working women at the age of 45 to 67 years from five Bulgarian companies. The data are obtained through laboratory tests of serum concentrations of 25-OH-Vitamin D and a questionnaire, created for the study. Statistical data processing is made by descriptive statistics and the CART method. RESULTS: The results show Vitamin D deficiency in 69% of the studied women at risk from Stara Zagora. For the target variable – Vitamin D (the quantity of 25-OH-Vitamin D), a regression CART tree was built. The calculated percentages of normalized importance for each independent variable reveal that the most important predictors, affecting Vitamin D, are body mass index (100%), alcohol (84.2%), education (70.3%), coffee (70.2%), Са_Vit D (69.8%), and sports frequency (42.4%), while the other variables have much less importance. CONCLUSION: The application of the CART method makes it possible to study the distribution and importance of the factors influencing the state of vitamin D. The presence of such a high percentage of women at risk requires a comprehensive approach, including educational programs and strict application of guidelines for vitamin D supplementation to prevent the effects of hypovitaminosis.