Assessment of the association between sociodemographic characteristics and response to vitamin D supplementation using artificial neural network

Bahrami, Afsaneh; Allahyari, Elahe; Arzehgar, Afrooz; Sohrabi, Mehdi; Amirzadeh, Elham; Alipour, Soheila; Ferns, Gordon A.; Ghayour, Majid

doi:10.22038/rcm.2022.63204.1394

Assessment of the association between sociodemographic characteristics and response to vitamin D supplementation using artificial neural network

Document Type : Original article

Authors

Afsaneh Bahrami

Elahe Allahyari ¹

Afrooz Arzehgar ²

Mehdi Sohrabi ³

Elham Amirzadeh ³

Soheila Alipour ³

Gordon A. Ferns ⁴

majid Ghayour ⁵

¹ 2Department of Epidemiology and Biostatistics, School of Health, Social Determinants of Health Research Center, Birjand University of Medical Sciences, Birjand, Iran

² Biomedical Engineering Depertment, Islamic Azad University, Iran, Mashhad Branch

³ Faculty of Sport Sciences, Ferdowsi University of Mashhad, Iran

⁴ Department of Medical Education, Brighton and Sussex Medical School, Falmer, Brighton, UK.

⁵ Biochemistry and Nutrition Research Center and Department of clinical biochemistry, Mashhad University of Medical Sciences, Mashhad, Iran

10.22038/rcm.2022.63204.1394

Abstract

Introduction: The serum 25(OH)D response to vitamin D supplementation, differs between individuals. The goal of this study was the evaluation of the relationship between socioeconomic and demographic factors with the hugeness of response to vitamin supplementation, defined by statistical analysis artificial neural network (ANNs).
Methods: The prospective interventional study was conducted on 529 participants aged 19-12 years old. All participants were administrated to receive nine vitamin D capsules (50000IU vitamin D) over nine weeks. The response variables were the following: the differences between the concentrations of vitamin D before and after intervention.
Results: Among various sociodemographic factors which affect the increase in serum vitamin D amounts in response to supplementations, baseline serum vitamin D (%28.1), BMI (%13.8), physical activity (%12.1), age (%7.6), mother›s education (%6.4), and father›s occupation (%5.8) be important variables.
Conclusion: This interventional study provides specific sociodemographicrecommendations to achieve 25(OH)D targets in cases with severe vitamin D deficiency, perhaps indicating that a higher dose is require to obtain optimal Vit D levels in some individuals.

Keywords

lifestyle

socioeconomic

adolescent girls

Artificial Neural Network

vitamin D supplementation