Undernutrition in children aged 0-59 months by region and over time: secondary analysis of the Burkina Faso 2012-2018 National Nutrition Surveys

Abstract

The global burden of undernutrition remains high, responsible for significant under-five mortality in resource-limited settings. Numerous sustainable development goals (SDGs) are linked to nutrition, and nationally representative nutrition surveillance is a key activity to track progress towards SDGs and guide efficient programmes.

Objectives: the aim of this study is to look at spatial and temporal trends in undernutrition in children under 5 years age in Burkina Faso.

Setting: we used data from annual National Nutrition Surveys using Standardised Monitoring and Assessment of Relief and Transitions methodology (anthropometry, morbidity) over 7 years (2012-2018) in Burkina Faso.

Participants: children of under 5 years from households selected through systemic sampling at countrywide level.

Main outcome measures: prevalence of stunting (height-for-age z-score, <-2), underweight (weight-for-age z-score, <-2) and wasting (weight-for-height z-score, <-2) at regional and national. We used general linear mixed models, adjusted by age, survey year, sex, presence of fever and/or diarrhoea, and poverty index to quantify the risk of undernutrition over time and by region of residence.

Results: between 2012 and 2018, decreases were observed overall in the prevalence of growth retardation (stunting) decreased from 33.0% (95% CI 32.3 to 33.8) in 2012 to 26.7% (95% CI 26.2 to 27.3) in 2018. Underweight reduced from 24.4% (95% CI 23.7 to 25.1) to 18.7% (95% CI 18.2 to 19.2) for the same period and wasting decreased from 10.8% (95% CI 10.3 to 11.3) in 2012 to 8.4% (95% CI 8.1 to 8.8) in 2018. However, there was substantial variation across the country, with increased risk of undernutrition in the regions of Sahel, East and Cascades primarily. High-risk regions were characterised by a lower poverty index and limited access to healthcare services.

Conclusions: our findings could inform national policymakers in refining and optimising resource allocation based on the identification of high-risk areas.

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