2.6. Statistical Analyses
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All data were entered into a digital questionnaire and extracted to SPSS 25 and cleaned. Data from 302 enrolled children were included in the analysis. Descriptive analyses were employed to examine the distribution of the full range of variables. All enrolled children were included in the ‘intention to treat’ analysis, while a separate analysis was conducted on the children who finished the 8-week intervention study. Repeated-measurement data were analysed using general linear models (GLM). Normality of data was checked using z-score skewness and kurtosis, and the Kolmogorov-Smirnov test. Data are presented as the mean ± standard deviation (SD) for normally distributed variables, median and interquartile range (IQR) for non-normally distributed variables and as percentages for categorical variables. Non-parametric Kruskal–Wallis test was used to test differences between non-normally distributed variables. Pearson chi-square test was used to compare categorical variables. Mann–Whitney U test was used to compare non-parametric variables between intervention groups. Data were considered significant at Minimum dietary diversity score (MDDS) and minimum acceptable diet (MAD) were calculated using WHO IYCF Practices Indicators 2010 and 2021. A dichotomous variable was created to define whether children met the MDDS (at least 4 food groups) or not (<4 food groups). Household food security was determined by applying the Household Food Insecurity Access Scale.