2.5. Statistical Analysis
The sample size was calculated using the G*Power 3.1.9.7 program, considering body weight as the main variable. Assuming a statistical power of 80%, a level of statistical significance of 5%, a two-tailed hypothesis and a standard deviation of 6.5 and aiming to detect a difference of 2.5 kg, the sample size was calculated to be 38 subjects. The statistical analysis was performed using SPSS software (version 27.0; SPSS, Inc., IBM Company, Armonk, NY, USA). Values were expressed as mean ± standard deviation in the case of dietary data and mean ± standard error of the mean in the case of blood pressure and all the different biochemical and hormonal parameters. The level of statistical significance was set at Based on the results of the normality test, a general linear model of repeated measures was used to assess the evolution of the different parameters of energy, macronutrient and micronutrient intake at different time points throughout the study. The order of intake of the nutraceuticals did not matter for the purposes of the dietary analysis since it would not affect the overall dietary pattern of the volunteers. In contrast, with the other parameters, a linear mixed model was used, as this model allows the determination of the correlated variability and the study of the effects of the product consumed, taking into account the order of ingestion. For each variable studied, apart from statistically analysing the baseline values from the start of each intervention and the end values of each intervention, the rates of change were calculated [(end value − baseline value)/baseline value] to better estimate the effects produced by the treatment, evaluating how much the variable increased or decreased with respect to the baseline value. When statistical differences were observed, a Bonferroni post hoc test was used in order to conduct pairwise comparisons between the groups’ means. 