Statistical Analysis
obesity, overweight
OBESITY, REGRESSION, SECONDARY
Our analyses excluded participants with missing or extreme baseline BMI (BMI<12.0 or ≥60.0). Participants’ baseline characteristics, demographic characteristics, and health status at trial baseline were stratified by baseline BMI categories of underweight (<18.5), normal weight (18.5-24.9), overweight (25.0-29.9), obesity class I (30.0-34.9), and obesity class II (≥35.0). For analyses including repeated biomarkers at 2 years, we combined the underweight and normal weight categories due to an insufficient sample size for BMI less than 18.5.To minimize outliers, we winsorized biomarker values at the bottom and top 0.5%, then inspected the biomarker distributions for normality. BioD, VDBP, PTH, and calcium were log transformed for analysis to improve normal distribution. We performed multivariable-adjusted generalized linear regression models with biomarkers as the continuous dependent variable to calculate the least square mean (SEM) or geometric mean and 95% CI for log-transformed biomarkers, stratified by baseline BMI category. We modeled continuous BMI to calculate the We generated waterfall plots to visualize the variability among participants for changes in total serum 25-OHD concentration at 2 years. Means and SEM (or geometric means and 95% CI for log-transformed biomarkers) of the continuous biomarkers were estimated from multivariable linear mixed-effects models with maximum likelihood estimation of the covariance parameters with an unstructured covariance matrix. The treatment effects per BMI category were calculated as the mean change difference in biomarkers, plus additional adjustment for the baseline biomarker value in an analysis of covariance.In secondary analyses, we estimated the treatment effect at 2 years according to categories of central obesity restricted to the subset of participants with in-person technician measurements. Classification of central obesity was defined based on the World Health Organization waist circumference (WC) for minimal risk (category I) including women less than 80.0 cm and men less than 94.0; moderate risk (category II) including women 80.0 to 87.9 cm and men 94.0 to 101.9 cm; and high risk (category III) including women, 88.0 cm or more and men, 102.0 cm or more. We also performed a sensitivity analysis among participants with baseline total 25-OHD levels less than 20.0 ng/mL to estimate whether effect modification by BMI persisted among those with initially insufficient vitamin D levels. We used SAS, version 9.4 (TS1M5) statistical software (SAS Institute Inc) to perform the analysis, with an a priori level of significance set as 