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Stunted linear growth continues to be a public health problem that overwhelms the entire world and, particularly, developing countries. Despite several interventions designed and implemented to reduce stunting, the rate of 33.1% is still high for the proposed target of 19% in 2024. This study investigated the prevalence and associated factors of stunting among children aged 6–23 months from poor households in Rwanda. A cross-sectional study was conducted among 817 mother–child dyads (two individuals from one home) living in low-income families in five districts with a high prevalence of stunting. Descriptive statistics were used to determine the prevalence of stunting. In addition, we used bivariate analysis and a multivariate logistic regression model to measure the strength of the association between childhood stunting and exposure variables. The prevalence of stunting was 34.1%. Children from households without a vegetable garden (AOR = 2.165, p-value < 0.01), children aged 19–23 months (AOR = 4.410, p-value = 0.01), and children aged 13–18 months (AOR = 2.788, p-value = 0.08) showed increased likelihood of stunting. On the other hand, children whose mothers were not exposed to physical violence (AOR = 0.145, p-value < 0.001), those whose fathers were working (AOR = 0.036, p-value = 0.001), those whose parents were both working (AOR = 0.208, p-value = 0.029), and children whose mothers demonstrated good hand washing practice (AOR = 0.181, p-value < 0.001) were less likely to be stunted. Our findings underscore the importance of integrating the promotion of handwashing practices, owning vegetable gardens, and intimate partner violence prevention in the interventions to fight child stunting.
A quantitative cross-sectional survey was conducted in the Rutsiro, Burera, Nyaruguru, Kayonza, and Gasabo districts from the Western, Northern, Southern, and Eastern Provinces and Kigali City, respectively. These districts were purposively chosen for their high stunting rates in their respective provinces and Kigali City based on the data from Rwanda Comprehensive Food Security & Vulnerability Analysis 2018 [23]. This study’s target population was children aged 6 to 23 months. In addition, we included mother–children dyads that belong to the family that has been identified as poor (Category 1 and 2 of Ubudehe) [24], children born full-term (between 38 weeks and 40 weeks), and singleton children (a child that is the only one born at one birth) in the study. Otherwise, eligible people who were very sick to the extent that there were not able to participate were excluded from the study. A multi-stage cluster sampling approach was applied where the primary sampling unit was the administrative Village, followed by households. One mother–child dyad was selected from each household fulfilling the inclusion criteria of the survey. From each village, we selected five households systematically. A total sample of 877 mother–child dyads were recruited to take part in this study based on the formula for estimation of single population proportion n=Z2pqd2 [25] where n is the desired sample size if the population is higher than 10,000, z is the x-coordinate of the standard curve that truncates a range at the ends if the confidence level is 95%, z = 1.96 p is the prevalence, and q = 1 − p. In this case, the prevalence was 33.1% at an accuracy of 5%. n=1.9620.331∗1−0.3310.052=340.2. We used a design effect of 2 and 20% to account for the non-response rate. The primary outcome variable of this study was stunting, where children were categorized into stunted or not stunted. Explanatory variables included variables related to child characteristics such as age, sex, deworming status, Vitamin A supplementation, micronutrient powder supplementation, and minimum dietary diversity. Those variables were selected, referred to the existing literature, and considered for their socioeconomic and biological plausibility with stunting. Household characteristics included the father’s employment status, household hunger status [26], household food insecurity access (HFIA) [27], household size, and owning a vegetable garden. Maternal characteristics included depressive syndrome [28], maternal employment status, maternal disability status, maternal literacy, maternal education, family planning type, breast discomfort during lactation, antenatal care visits, and mode of delivery. Other variables included intimate partner violence (IPV), which involves exposure to controlling behavior, emotional violence, physical violence, sexual violence, and any violence. The survey also included questions related to Water, Sanitation, and Hygiene (WASH), including a source of drinking water, toilet facility, child stool disposal, handwashing facility, and observation of handwashing practice. In addition, we considered good handwashing practices, those who cut their nails and washed their hands with clean water and soap. WASH indicators were grouped and classified into improved and unimproved, following the WHO guidelines [29]. To determine the prevalence of stunting among children aged 6–23 months from poor households, we calculated length-for-age z-scores using the WHO Anthro computer application. We then exported them in the Statistical Package for Social Science (SPSS) version 25.0 used for data analysis. Indices were categorized into stunted and not stunted based on the WHO 2010 Child Growth Standards, where stunting was defined as a Z-score less than −2SD and not stunted as a Z-score more than −2SD [30]. To calculate the prevalence of stunting, we divided the number of stunted children by the total number of children measured multiplied by a hundred. In descriptive statistics, we calculated frequencies and percentages for all variables. Additionally, we performed a bivariate analysis between stunting status and predicting variables. Due to the possible collinearity between independent variables, backward stepwise logistic regression was conducted to determine the final models. We included significant variables from bivariate analysis with p 0.05) and those which correlated with others were excluded automatically from the model, starting with the highest and stopping when all remaining variables were statistically significant (p ≤ 0.05). We reported the results as odds ratios (OR) with a 95% confidence interval (CI).
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