2.8. Statistical Analysis
Metabolic syndrome
REGRESSION, METABOLIC SYNDROME
A priori power analysis was based on data from our prior diet intervention cohorts that showed a sample size of 50 completers per group would provide 80% probability to detect a mean difference of ≥2.54 cm in waist circumference, the primary outcome. Metabolic syndrome score (0–5) was calculated for each participant by assigning 1 point for each metabolic risk criteria met (waist circumference, glucose level, HDL-cholesterol level, triglyceride level, and blood pressure). Difference in changes between groups was tested by analysis of covariance (ANCOVA) using general linear models. Within group differences were assessed using the Wilcoxon test. Multivariable linear regression modeling was performed to assess the main effect of the tree nuts snack treatment and the interaction between treatment and sex on MetSx score. Each of the MetSx criteria and insulin level were also investigated as separate outcome variables. Age, BMI, and year of enrollment (the COVID-19 pandemic occurred during the study data collection period) were considered as between-subject factors but showed no main effect on any of the outcomes. Analyses were performed using SPSS