Statistica 13 package

All statistical analyses were performed using Excel (MS Office, Redmond, WA, USA) and Statistica 13 Package (StatSoft, Cracow, Poland). The average filter mass was calculated as the arithmetic mean from two subsequent filter’s weighing (after 24 and 48 h). The difference in filter weight (a total of five filters of each type) between the first and second weighing was calculated as the standard deviation (SD) value from the averaged filter mass. Differences in the total filter mass between all weighing sessions within the batch of filter of one type was calculated as standard deviation (SD) of repeatability (µg). To check whether the average mass of filter blanks was positively correlated with the change in humidity/temperature, a one-way ANOVA was performed (p < 0.05).

All statistical analyses were performed using Statistica 13 Package (StatSoft, Poland). Pearson’s correlation coefficients (r) were calculated to determine the relationships between the different heavy metals and physicochemical parameters of the sludge samples. A similar analysis was also performed in relation to the levels of risk, calculated for different heavy metals in the sludge samples. Cluster Analysis (CA) was applied to group the heavy metals from the different WWTPs into meaningful groups (clusters), and the Ward method was used for data agglomeration. Factor Analysis (FA) was applied to obtain more reliable information about the relationships between the different heavy metals in the sludge samples. To extract the significant components and identify the possible sources of heavy metals, a Principle Component Analysis (PCA) along with a Varimax rotation (with Kaiser normalization) was carried out. All statistical analyses were performed at a 95% confidence interval (p < 0.05). Data analysis also included calculating the mean ( $\overline{x})$ and standard deviation (SD).

The distribution of results for the analysed variables was checked using the Shapiro–Wilk test, and the equality of variance with the Levene test. For single measurements, the significance of group-related differences was assessed using independent-sample tests, Student’s t-test or the Mann–Whitney U test. Pearson or Spearman correlations were calculated.
Comparing the impact of WBC treatments on changes in the analysed variables among the compared groups, analysis of variance with repeated measures (ANOVA) was used, examining the influence of the main factors, i.e., Group (MetS and Healthy), Treatment (influence of WBC) and Group × Treatment interaction. Effect sizes for ANOVA analysis were calculated using partial eta squared (η²) and interpreted as 0.010–0.059 = small, 0.060–0.139 = medium, ≥0.14 = large. For changes in the level of specific variables after WBC, confidence intervals were determined (95% CI). When significant influence of the main factors was found, post-hoc analysis was performed using the Fisher LSD test. The statistical significance of differences was assumed for the level of p < 0.05. The statistical power of the test was also calculated (1-β). The STATISTICA 13 package (StatSoft, Inc., Tulsa, OK, USA) was used for calculations.