Contribution of vitamin D status as a determinant of cardiometabolic risk factors: a structural equation model, National Food and Nutrition Surveillance

• Published in: BMC public health Vol. 21; no. 1; pp. 1819 - 7
• Main Authors: Nikooyeh, Bahareh, Neyestani, Tirang R.
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 09.10.2021; BioMed Central; BMC
• Subjects: Adult; Age; Age factors; Aged; Alfacalcidol; Anthropometry; Bivariate analysis; Blood lipid profile; BMI; Body mass index; Calcifediol; Calciferol; Cardiometabolic risk factors; Cardiovascular diseases; Cardiovascular Diseases - epidemiology; Cardiovascular Diseases - etiology; Cholesterol; Cross-Sectional Studies; Data collection; Demographic variables; Diagnosis; Dietary supplements; Female; Food selection; Gender; Health aspects; Health risks; High density lipoprotein; Humans; Lipids; Literature reviews; Male; Mathematical models; Measurement; Metabolic diseases; Metabolism; Middle Aged; Models, Theoretical; Multivariate statistical analysis; Nutrition; Nutrition monitoring; Public health; Risk analysis; Risk Factors; Statistical analysis; Structural equation modeling; Sunscreen; Surveillance; Variables; Vitamin D; Vitamin D Deficiency - epidemiology; Vitamin deficiency; Women; Young Adult; Iran; Structural equation modeling; Surveillance; Vitamin D; Cardiometabolic risk factors; BMI; Blood lipid profile
• ISSN: 1471-2458; 1471-2458
• DOI: 10.1186/s12889-021-11839-w

Structural equation modeling (SEM) is a method used to evaluate linear causal relationships among variables. This study aimed to investigate the direct and indirect effects of serum 25(OH) D on certain cardiovascular risk factors using SEM. An analytical cross-sectional study was conducted in six provinces of Iran. Subjects (n = 922), aged 19-65 years, were selected from National Food and Nutrition Surveillance. The assessments were sun-exposure behavior, anthropometric and biochemical measurements. A series of SEM models were tested and the model with the best fit indices was considered for use in the structural part of the model. Based on the literature review of previous theoretical models and supporting bivariate analyses, an overall SEM examined direct or indirect associations among observed and latent variables. We put the demographic, duration of sun exposure, anthropometric and metabolic variables in our model. The paths between serum 25(OH) D and BMI were inverse and statistically significant, whereas age showed a positive association with BMI (B = 0.06, p < 0.001), both direct (st. effect = 0.11, p = 0.01) and indirect via vitamin D (st. effect = - 0.02, p = 0.01). The results confirmed that serum 25(OH) D concentration is a predictor for latent variable of lipid profile (B = - 0.13, p = 0.01) both through direct (p = 0.02) and indirect effects via BMI (p = 0.01). Serum 25(OH) D concentration is a predictor of BMI and also a latent variable of lipid profile via direct and indirect effects. It can also attenuate the harmful effect of age on BMI and lipid profile particularly in women.