Statistical package for social science spss software version 25

Descriptive statistics were used to summarise the data. Data were presented as frequency distribution tables, consisting of frequencies, percentages and 95% confidence intervals. The chi-square (χ²) test was used to test for statistical relationship between independent and dependent variables (prevalence of diarrhoeal disease). The researcher applied logistic regression analysis to identify significant factors associated with the prevalence of diarrheal disease in children aged under 5, and to determine the likelihood of factors that have an impact on the prevalence of diarrhoea. The model containing all the predictors was statistically significant (χ² [16, N = 530] = 58.44, p ˂ 0.001); this is an indication that the model was able to distinguish between respondents who reported children suffering from diarrhoea and those who did not report the incidence of diarrhoea. We used the International Business Machines (IBM) Statistical Package for Social Science (SPSS) software version 25 to perform this analysis. Variables with statistical significance (p < 0.05) in the bivariate analysis were included in the logistic regression to determine factors associated with the prevalence of diarrhoeal disease.

IBM Statistical Package for Social Science (SPSS) software version 25 was used for the statistical analysis. Differences were considered statistically significant at P < .05. Data were presented as frequency and percentages for binary and categorical variables, and median values were calculated for nonnormally distributed continuous variables. Mann-Whitney U tests were used for nonparametric variables and Fisher exact tests for categorical variables for CPA and non-CPA. Distributions of CPA were compared according to age and sex, using χ² tests for categorical and Wilcoxon rank sum test for continuous variables; for the significance of associations, 95% confidence intervals were used, and significance was set at a probability of 5% (P < .05).