Correlates of Calcidiol Deficiency in Adults-Cross-Sectional, Observational, Population-Based Study.
Massimo CirilloGiancarlo BilancioPierpaolo CavalloSimona CostanzoAmalia De CurtisAugusto Di CastelnuovoLicia IacovielloPublished in: Nutrients (2022)
The prevalence, determinants, and clinical significance of vitamin D deficiency in the population are debated. The population-based study investigated the cross-sectional associations of several variables with serum 25-hydroxyvitamin D (calcidiol) measured using standardized calibrators. The study cohort consisted of 979 persons of the Moli-sani study, both sexes, ages ≥35 years. The correlates in the analyses were sex, age, education, local solar irradiance in the month preceding the visit, physical activity, anthropometry, diabetes, kidney function, albuminuria, blood pressure, serum cholesterol, smoking, alcohol intake, calorie intake, dietary vitamin D intake, and vitamin D supplement. The serum calcidiol was log transformed for linear regression because it was positively skewed (skewness = 1.16). The prevalence of calcidiol deficiency defined as serum calcidiol ≤12 ng/mL was 24.5%. In multi-variable regression, older age, lower solar irradiance, lower leisure physical activity, higher waist/hip ratio, higher systolic pressure, higher serum cholesterol, smoking, lower alcohol intake, and no vitamin D supplement were independent correlates of lower serum calcidiol (95% confidence interval of standardized regression coefficient ≠ 0) and of calcidiol deficiency (95% confidence interval of odds ratio > 1). The data indicate that low serum calcidiol in the population could reflect not only sun exposure, age, and vitamin D supplementation but also leisure physical activity, abdominal obesity, systolic hypertension, hypercholesterolemia, smoking, and alcohol intake.
Keyphrases
- physical activity
- blood pressure
- cross sectional
- body mass index
- weight gain
- type diabetes
- left ventricular
- risk factors
- magnetic resonance imaging
- insulin resistance
- machine learning
- weight loss
- big data
- electronic health record
- adipose tissue
- magnetic resonance
- deep learning
- heart rate
- depressive symptoms
- atomic force microscopy
- high fat diet induced
- community dwelling
- neural network