Statistics
overweight
REGRESSION, REGRESSION
Continuous variables are presented as mean ± standard deviation (SD), categorical variables as frequencies and valid percent. Normality was tested using the Shapiro–Wilk test and judged by histograms. All data were analysed in accordance with the predefined study plan. All available data were analysed. Missing data were not imputed.To compare intervention group and control group, independent t-test was used for normally distributed continuous variables (e.g. changes of eating behaviour scores) and Mann–Whitney Subgroups were formed to separately analyse the weight reduction effects of the intervention in participants who were overweight and normal-weight and in participants with high and low stress levels.Multiple linear regression modeling (MLR) was used to explore the effect of the intervention on the change of stress eating dimensions, adjusting for sex and the baseline value of the respective variable. Variables found to be associated with change of DEBQ and PSS-10 parameters were also added as covariates (in addition to the group variable) to the multiple regression model using a forward–backward selection approach. Regression models that were statistically relevant (p ≤ 0.05), with the highest corrected Rp-values < 0.05 are considered significant, and are to be understood as exploratoryStatistical analyses were performed using IBM SPSS Statistics for Windows, Version 27.0. Armonk, NY: IBM Corp.
