BMC Nutrition (May 2021)
The prevalence and associated factors of undernutrition among under-five children in South Sudan using the standardized monitoring and assessment of relief and transitions (SMART) methodology
Abstract
Abstract Background Conflict regions bear the heaviest brunt of food insecurity and undernutrition. South Sudan is one of the fragile countries following years of conflict that led to large displacements. Moderate to severe undernutrition among under-five children has been associated with elevated morbidity and mortality. This study, therefore, was conducted to assess the magnitude and factors influencing undernutrition (wasting, underweight and stunting) among children aged 6 to 59 months in Yambio County, South Sudan. Methods A cross-sectional study was conducted from 26 October to 6 November 2018 in Yambio County, South Sudan among 630 children aged 6–59 months from the 348 households surveyed in 39 clusters using two-stage cluster sampling design. Data were collected using questionnaires and nutritional anthropometric measurements. The Standardized Monitoring and Assessment of Relief and Transitions (SMART) Methodology was followed to obtain the prevalence of wasting, underweight and stunting based on respective z scores and according to the 2006 world health organization child growth standards. Data were exported to Stata version 16 for further analysis. Bivariate analysis of independent variables and undernutrition was done using binary logistic regression. Mixed effects logistic regression analysis was conducted to control for possible confounders and account for random effects at household and cluster levels. Unadjusted and adjusted odds ratios (cOR and aOR) with 95% confidence intervals (CI) and p-values were computed. P-values of ≤0.05 were considered statistically significant. Results The prevalence of undernutrition explained by wasting (weight-for-height Z-score (WHZ) < − 2), underweight (weight-for-age z-scores (WAZ) < − 2) and stunting (height-for-age z-scores (WHZ) < − 2) were 2.3% (1.3–4.1, 95% CI), 4.8% (3.1–7.5, 95% CI) and 23.8% (19.1–29.2, 95% CI). Male sex (aOR [95% CI], p-value: 5.6 [1.10–30.04], p = 0.038), older child’s age (aOR [95% CI], p-value: 30.4 [2.65–347.60], p = 0.006) and non-residents (cOR [95% CI], p-value: 4.2 [1.4–12.2] p = 0.009) were associated with increased risk of wasting. Household size (cOR [95% CI], p-value: 1.09 [1.01–1.18] p = 0.029) and younger child age (cOR [95% CI], p-value: 4.2 [1.34–13.23] p = 0.014) were significantly associated with underweight. Younger child age (aOR [95% CI], p-value: 5.4 [1.82–16.44] p = 0.003) and agricultural livelihood (aOR [95% CI], p-value: 3.4 [1.61–7.02] p = 0.001) were associated with stunting. Conclusion Based on a cut off of less than − 2 standard deviations for 2006 World Health Organization (WHO) child growth standards, the wasting prevalence was very low, underweight prevalence was low while stunting prevalence was high. The county lies in the only livelihood region in South Sudan with bimodal reliable rainfall pattern and it seems that the impact of the 2016 conflicts that lead to large displacements may not have greatly affected under-five undernutrition. Interventions targeted at improving food diversity, increasing nutrition knowledge and enhancing resilience in male children might reduce undernutrition. In the short-term, investment in continued surveillance of nutritional status should be a main focus.
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