2.6. Data Analyses
anxiety, depressive, MDD, depression, diabetes
REGRESSION, DIABETES
For descriptive analyses, mean and standard deviation (SD) for continuous data and frequency (and percentage) for categorical data were calculated.The Shapiro–Wilk test for normality indicated that the PHQ-9 and GAD-7 scores did not follow a normal distribution at any recorded time point (Multilevel mixed-effects ordered logistic regression models were constructed for consumption of each beverage (carbonated/soft drink with sugar, carbonated/soft drink with NNSs, coffee, and tea) with the three repeated measures (baseline, 6 and 12 months) on depressive and anxiety symptomatology severity groups as outcome variables. In these models, the random effects refer to the subject level. Marginal effects analysis allowed us to study the association between each level of consumption and each level of depression and anxiety. To fit the association of the consumption of different beverages to depression and anxiety symptoms, a set of covariates were included. The following continuous variables were age, alcohol use, physical activity, BMI, and MooDFOOD diet score. Categorical variables were coded as dummy variables: sex (male vs. female); site (Germany vs. Spain vs. the United Kingdom vs. The Netherlands); level of education (intermediate vs. high vs. low); group intervention (Placebo plus F-BA vs. Supplements without FB-A vs. Supplements plus FB-A vs. Placebo without FB-A); history of MDD diagnosis (yes vs. no); and diabetes (yes vs. no). Beverage consumption was coded as time-dependent variables at all three measurements (baseline, 6 and 12 months): soft drink consumption was classified as <1 unit a week, 1 to 6 units a week, and 1 or more units a day; coffee and tea consumption was classified as <1 cup a day, 1 to 3 cups a day, and >3 cups a day. Although the FFQ scale is composed of 8 categories of consumption, we grouped it into these 3 categories for statistical reasons. Finally, analyses were performed using STATA 16 [