*2.5. Statistical Analysis*

Several variables derived from the online survey were re-coded for further statistical analyses. The following categories were used to categorize participants based on their body mass index (BMI) levels: underweight (UW) (BMI < 18.5), normal weight (NW) (18.5 < BMI < 25), and overweight (OW) (BMI > 25) [25,39]. Participants were grouped into five different age categories: young (≤ 25 years), young adults (25 < years ≤ 35), adults (35 < years ≤ 55), senior adults (55 < years ≤ 65), and elderly (>65 years) [25,40]. The Shapiro–Wilk test was used to test the normality of the distribution for all variables. Data are computed and presented as means, standard deviation, and percentages.

To test the difference in the total energy expenditure (MET-min/week) before and during COVID-19 confinement, the Wilcoxon signed-rank test for dependent groups was used. The Mann–Whitney U test was chosen to analyze the differences in responses before

and during for type of PA, gender, and living area (urban vs. rural living environment). To assess pre- and during COVID-19 confinement differences between categories assigned based on BMI and age, the Kruskal–Wallis rank-sum test was employed, with the Mann– Whitney U test chosen for pairwise comparisons. Non-parametric tests have been used because the normality assumption of the distribution, tested by the Shapiro–Wilks test, was violated.

The level of significance was set at *p* < 0.05. All of the statistical analyses were performed using the Statistical Package for Social Sciences (SPSS), version 21.0 (SPSS Inc., Chicago, IL, USA). GraphPad Prism version 8.4.3 was used to design graphs and figures.
