Statistical analysis
infection
INFECTION, DISEASES
Continuous variables are summarized as means with ± standard deviations (± SD) or medians with interquartile range. Continuous outcomes with repeated measures were analyzed using a mixed linear model in the per-protocol population (i.e., the 130 participants adherent to the prescribed interventions), which might provide a better mechanistic understanding of the interventions, and in the intention-to-treat population (i.e., all 195 participants randomized). Significance testing was performed using α = 0.05 on MetS-Z, android fat percentage, and hsCRP outcomes. The following fixed effects were included in the model: time (factorial), group, age group (< / ≥ 40 years), sex, a time-group interaction, and a repeated effect for visit. A supplementary analysis further adjusting for blood pressure or lipid-lowering medication, smoking, and alcohol consumption at inclusion was also performed. All missing data were assumed to be missing at random. The analyses were unadjusted for multiplicity; therefore, definite inferences cannot be made. Results are reported as estimated changes with 95% confidence intervals (95% CI). Statistical sample size power analysis has previously been published and was based on body weight change (a 4 kg difference between the four groups was estimated to require at least 30 participants per group) [Regarding hsCRP, the non-normal distributed results were log-transformed before analysis and back-transformed as ratios with 95% CI. Three samples were excluded before analysis due to sample dilution error or hsCRP values consistent with concurrent infection or other diseases.