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Introduction Children’s feces are thought to pose a greater public health risk than those of adults’ due to higher concentrations of pathogens. The aim of this study was to determine the associated factors of safe child feces disposal among children under two years of age in Sub-Saharan Africa. Methods The most recent demographic and health survey datasets of 34 sub-Saharan countries were used. A total weighted sample of 78, 151 mothers/caregivers of under two children were included in the study. Both bivariable and multivariable multilevel logistic regression were done. The Odds Ratio (OR) with a 95% Confidence Interval (CI) was calculated for each independent variables included in the model. Results Those mothers/caregivers from urban residence (AOR = 1.42; CI: 1.36, 1.48), mothers with primary education (AOR = 1.49; CI: 1.44, 1.56), richer (AOR = 1.78; CI: 1.69, 1.88) and richest wealth quintiles (AOR = 2.17; CI: 2.01, 2.31), family size <5 (AOR = 1.06; CI: 1.02–1.09), access to improved water source (AOR = 1.29; CI: 1.25, 1.34), mothers who owned toilet (AOR = 3.09; 2.99–3.19) and who had media exposure (AOR = 1.19; CI: 1.15, 1.24) had higher odds of practicing safe child feces disposal than their counter parts. However, mothers/care givers who are not currently working (AOR = 0.83; CI: 0.80, 0.86), higher education (AOR = 0.85; CI: 0.76–0.94) and from Western region of Africa (AOR = 0.82; CI: 0.79–0.86) had reduced chance of safe child feces disposal as compared to their counter parts. Conclusion Residence, mothers’ level of education, wealth index, water source, toilet ownership and media exposure were factors associated with safe child feces disposal. It is advisable to implement health promotion and behavioral change intervention measures especially for those women /caregivers from rural residence, poor economic status, who cannot access improved water and for those with no media exposure to improve the practice of safe child feces disposal.
This study was a secondary data analysis from the most recent appended demographic and health surveys (KR data sets) conducted in 34 sub-Saharan countries from 2009 to 2018. The DHS is a nationally representative survey that collects data on basic health indicators like morbidity, mortality, fertility, maternal and child health. The DHS used two stage stratified sampling technique to select the study participants. A pretested and standard DHS questionnaires were used for data collection of the DHS surveys. The questionnaire was conceptualized to the different countries context and the data were collected by trained data collectors. The datasets of each sub- Saharan country were obtained at https://dhsprogram.com/data/dataset_admin/index.cfm.Those countries which have data on feces disposal among under two children were included in the analysis. We removed those cases which were incomplete from the analysis to handle missing data. Each country was given a code and then appended together to create a single data set that represents the SSA countries. In this study, a total weighted sample of 78,151 under-two children were included (Table 1). The dependent variable for this study was safe child feces disposal. Safe child feces disposal is a binary outcome (yes or no) and a child is said to have safe child feces disposal if they used latrine’ and if they ‘put/rinsed child feces into latrine [18]. The independent variables considered for this study were both individual and community level variables. The individual level variables were age of child, age of mothers, education level of mothers, education level of partners, wealth index, occupational status of mothers, family size, number of under five children, water source, toilet ownership and media exposure (a composite variable generated by the aggregation of listening radio, reading newspaper and watching television and it was dichotomized as yes “if the mother had exposure to either of the above three mentioned media sources” and no “if she had no exposure to all of the three media sources). SSA region and residence were considered as the community level variables. Data extraction, recoding and analysis were done using STATA version 14 software. Before the analysis sampling weight was applied to produce reliable estimates by adjusting the over and under-sampled region. Sample weights were calculated to six decimals but are presented in the standard recode files without the decimal point. They need to be divided by 1,000,000 before use to approximate the number of cases. The whole procedure of weighting and its rationale is found on the guide of DHS statistics [24]. Measures of community variation/random effects such as Median Odds Ratio (MOR), Proportional Change in Variance (PCV) and Interclass Correlation Coefficient (ICC) were calculated due to the correlated nature of DHS data. Accordingly, the values of these measures were found to be significant and hence the use of multilevel logistic regression model is more appropriate than ordinary logistic regression. To choose the best fitted model, first we developed four models and compared them with deviance. The first one is the null-model; a model with no independent variable, the second model is model I; a model that has individual-level factors only, model II; a model with community-level factors only and model III; a model that contain both individual and community level independent variables. Of the four models fitted, model III was selected as the best fitted model (it had the lowest deviance). Then after, both bivariable and multivariable multilevel logistic regression was conducted to determine the associated factors of safe child feces disposal in SSA. All variables with a p value < 0.2 at bi-variable analysis were entered into the multivariable logistic regression model. In the final model p value ≤ 0.05 was used to declare statistically significant variables.
