Statistica software version 12

Data were presented as a sample percentage (%) for categorical data or mean and standard deviation (SD) for continuous data. The differences between groups were verified with the Pearson Chi² test (categorical data) or the Kruskal–Wallis test (continuous data; for more than two groups) or the Tukey’ test (continuous data; for two groups). Before statistical analysis, the normality of variable distribution was checked with a Kolmogorov–Smirnov test. The logistic regression analysis was performed to assess a chance of higher food consumption in association with an average and lower socioeconomic status, or higher level of limitations related to eating or health conditions, as well as with a one-point increase in SESI, E-LS, and H-LS. The odds ratios (ORs) and 95% confidence intervals (95% CI) were calculated. The lower food consumption, higher socioeconomic status, or lower level of eating- or health-related limitations were used as reference (ref.). ORs were adjusted for age (continuous variable in years) and SESI (continuous variable in points), if applicable. The level of significance of the OR was verified with the Wald’s test [47 ]. For all tests, p < 0.05 was considered significant. The statistical analysis was performed using STATISTICA software version 12.0 (StatSoft Inc., Tulsa, OK, USA; StatSoft, Krakow, Poland).

The STATISTICA software, version 12.0 (StatSoft Corp., Krakow, Poland), was used to determine the differences among treatment groups. Two-way ANOVA was applied to assess the effects of main factors CuNPs dose (L, 6.5 mg/kg and H, 13 mg/kg) and dietary fibre type (cellulose, pectin, inulin and psyllium), followed by Duncan’s multiple range test. Additionally, each experimental group fed CuNPs L dose was compared with the control C group (fed diet with 6.5 mg/kg Cu from CuCO₃ and containing cellulose as the main dietary fibre source) with the aid of a t-test. Similarly, the t-test was used to compare the experimental groups fed diets with CuNPs H dose with the control CH group fed diet with 13 mg/kg Cu from CuCO₃ and containing cellulose as the main dietary fibre source. Differences with p ≤ 0.05 are considered to be significant.

All values were expressed as mean ± s.e. All parameters were subjected either to parametric analysis of variance (ANOVA) or to repeated-measure ANOVA. ANOVA was followed, in cases of significance (P < 0.05), by post hoc comparisons using Duncan’s test. All quantitative analyses were conducted blind to the animal’s experimental group. All statistical analyses were carried out with the help of Statistica software Version 12.0 (StatSoft, Tulsa, OK, USA).

Statistical analyses were performed with Tukey’s and Dunnett’s tests using Statistica software version 12.0 (StatSoft, Tulsa, USA). A value of P≤0.05 was considered to be significant.

STATISTICA software, version 12.0 (StatSoft Corp., Krakow, Poland), was applied to determine whether variables differed among treatment groups. Two-way ANOVA and Student’s t-test were used to analyze the results. Two-way ANOVA was applied to assess the effects of the main factors: diet type (D; low-fat, high-fat/low fiber), additional Cr type (Cr; without, picolinate, nanoparticles), and the interaction between them (Cr×D). When ANOVA indicated significant treatment effects, the means were evaluated using Duncan’s multiple range test. The data were checked for normality before statistical analysis was performed. Differences with p ≤ 0.05 were considered significant.