Statistical analysis
FM
Descriptive statistics, including measures of central tendency (mean) and variability (standard deviation), were used to describe baseline characteristics of the control group, MICT, and HIIT. A one-way ANOVA with a Bonferroni adjustment for multiple comparisons was used to test differences in descriptive characteristics between the three groups and a chi-square test was used to assess differences in gender among the groups.Generalized estimating equations were used to assess group by time interactions in NEPA and estimated NEAT on non-exercise days between the controls and exercise groups at 6-months and 1-year while using sex, age, wear time, and total number of trainings as covariates. Baseline NEPA and estimated NEAT were also included in their respective models as covariates given the significant difference between the groups at baseline. A least significant difference post hoc test was used to estimate the between and within-group effects on NEPA and estimated NEAT. A linear distribution for the response was assumed and an autoregressive correlation matrix was set to the data. Similarly, generalized estimating equations were used to assess group by time interactions in NEPA and estimated NEAT between the controls, low responders, and high responders for both FM and BW loss at 6 months and 1-year, while adjusting for sex, age, total number of trainings, wear time, and baseline NEPA or estimated NEAT.A 