Factors determining the serum 25-hydroxyvitamin D response to vitamin D supplementation: data mining approach

Amiri, Zahra, Nosrati, Mina, Sharifan, Payam, Saffar Soflaei, Sara, Darroudi, Susan, Ghazizadeh, Hamideh, Mohammadi Bajgiran, Maryam, Moafian, Fahimeh, Tayefi, Maryam, Hasanzade, Elahe, Rafiee, Mahdi, Ferns, Gordon A, Esmaily, Habibollah, Amini, Mahnaz and Ghayour-Mobarhan, Majid (2021) Factors determining the serum 25-hydroxyvitamin D response to vitamin D supplementation: data mining approach. BioFactors. ISSN 0951-6433

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Abstract

Vitamin D supplementation has been shown to prevent vitamin D deficiency, but various factors can affect the response to supplementation. Data mining is a statistical method for pulling out information from large databases. We aimed to evaluate the factors influencing serum 25-hydroxyvitamin D levels in response to supplementation of vitamin D using a random forest (RF) model. Data were extracted from the survey of ultraviolet intake by nutritional approach study. Vitamin D levels were measured at baseline and at the end of study to evaluate the responsiveness. We examined the relationship between 76 potential influencing factors on vitamin D response using RF. We found several features that were highly correlated to the serum vitamin D response to supplementation by RF including anthropometric factors (body mass index [BMI], free fat mass [FFM], fat percentage, waist-to-hip ratio [WHR]), liver function tests (serum gamma-glutamyl transferase [GGT], total bilirubin, total protein), hematological parameters (mean corpuscular volume [MCV], mean corpuscular hemoglobin concentration [MCHC], hematocrit), and measurement of insulin sensitivity (homeostatic model assessment of insulin resistance). BMI, total bilirubin, FFM, and GGT were found to have a positive relationship and homeostatic model assessment for insulin resistance, MCV, MCHC, fat percentage, total protein, and WHR were found to have a negative correlation to vitamin D concentration in response to supplementation. The accuracy of RF in predicting the response was 93% compared to logistic regression, for which the accuracy was 40%, in the evaluation of the correlation of the components of the data set to serum vitamin D.

Item Type: Article
Schools and Departments: Brighton and Sussex Medical School > Division of Medical Education
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 13 Aug 2021 09:29
Last Modified: 18 Jul 2022 01:00
URI: http://sro.sussex.ac.uk/id/eprint/101107

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