Determinants of Serum Vitamin D level; A Data Mining Approach
Author(s):
Zahra Amiri , Fahimeh Moafian , Payam Sharifan , Elahe Hasanzadeh , Zahra Khorasanchi , Moniba Bijari , Maryam Mohammadi Bajgiran , Sara Saffar Soflaei , Susan Darroudi , Hamideh Ghazizadeh , Fatemeh Rouhi , Fatemeh Mohseni Nik , Maryam Tayefi , Samira Roohi , Ayad Noor , Abdullah Al Yakobi , Mohammed Hadi Lafta Alboresha , Gordon A. Ferns , Habibollah Esmaily , Majid Ghayour-Mobarhan *
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Introduction
Serum vitamin D levels are related to a wide spectrum of factors including low sunlight exposure, high oxidative stress, low physical activity and sleep disorders. In this paper we are going to investigate the most crucial parameters associated with serum vitamin D levels in survey of ultraviolet intake by nutritional approach (SUVINA) study with a data mining approach.Material and Methods
Data including demographic, anthropometric, clinical and laboratory information were extracted from the SUVINA dataset comprising 289 subjects who were enrolled into our study. The XGBoost algorithm was used to define the most important features related to vitamin D level in our population.Results
Applying XGBoost modeling for vitamin D level showed that the presented scheme can determine the most important determinants of serum vitamin D level with an accuracy of 91%. Pro-oxidant anti-oxidant balance (PAB), body fat percentage, physical activity level (PAL), age, restless leg syndrome (RLS), and dietary inflammatory index (DII) density were the most important variables correlated with vitamin D deficiency.Conclusion
Using XGBoost and with an accuracy of more than 90%, we showed that the six most important risk factors for vitamin D deficiency are PAB, PAL, age, body fat percentage, RLS and DII density, respectively.Keywords:
Language:
English
Published:
Journal of Cardio -Thoracic Medicine, Volume:11 Issue: 3, Summer 2023
Pages:
1207 to 1215
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