Mind the Gap! Socioeconomic Determinants of the Stunting Urban-Rural Gap for Children in Colombia


Stunting (low height for age) is a crucial indicator for measuring child well-being and economic and social development of a country. Despite a decrease in overall children’s stunting in the last decades, there are still significant geographic disparities between urban and rural areas in Colombia. This paper aims to identify the role of the main determinants of children’s stunting in explaining the urban-rural stunting gap. We use data from the 2015 National Nutritional Situation Survey (the most recent available dataset) and the Yun’s statistical decomposition technique. We find that the urban-rural gap in child stunting is 7.2 percentage points. Three determinants household wealth, maternal education, and health services utilization, explain most of the gap (92%). Each determinant explains 54%, 26%, and 12% of the characteristics effect, respectively. Public health policies aiming to reduce the gap must seek improvements in access to institutional delivery and education services for mothers in rural areas in the short term. In the long term, increasing economic wealth in rural areas is essential.

Child Indicators Research


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This research was chosen as the best work in the research category in the XVIII Edition of “Premio por la Nutrición Infantil 2021 de la Fundación Éxito”. This work was leadered by the research group “Economía, Gestión y Salud (ECGESA)” of the Pontificia Universidad Javeriana Cali, in addition to Economics School of Universidad Sergio Arboleda.

The Éxito Foundation pointed out that the research “also contributes to our national cause, with which it is expected that in 2025 the first generation will be born with zero malnutrition and that by 2030 no child under 5 years of age will have chronic malnutrition in the country.”

A pleasure to work with this team

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Orlando Joaqui Barandica
Orlando Joaqui Barandica
PhD(C) in Industrial Engineering

My research interests include energy markets, asset and liability management, quantitative finance, applied econometrics and statistical, and data visualization.