Title

What Causes Childhood Stunting among Children of San Vicente, Guatemala: Employing Complimentary, System-Analysis Approaches

Abstract

Guatemala has the sixth worst stunting rate with 48% of children under five years of age classified as stunted according to World Health Organization standards. This study utilizes two different yet complimentary system-analysis approaches to analyze correlations among environmental and demographic variables, environmental enteric dysfunction (EED), and child height-for-age (stunting metric) in Guatemala. Two descriptive models constructed around applicable environmental and demographic factors on child height-for-age and EED were analyzed using Network Analysis (NA) and Structural Equation Modeling (SEM). Data from two populations of children between the age of three months and five years were used. The first population (n = 2103) was drawn from the Food for Peace Baseline Survey conducted by the US Agency for International Development (USAID) in 2012, and the second population (n = 372) was drawn from an independent survey conducted by the San Vicente Health Center in 2016. The results from the NA of the height-for-age model confirmed pathogen exposure, nutrition, and prenatal health as important, and the results from the NA of the EED model confirmed water source, water treatment, and type of sanitation as important. The results from the SEM of the height-for-age model confirmed a statistically significant correlation among child height-for-age and child-mother interaction (-0.092, p = 0.076) while the SEM of the EED model confirmed the statistically significant correlation among EED and type of water treatment (-0.115, p = 0.013). Our approach supports important efforts to understand the complex set of factors associated with child stunting among communities sharing similarities with San Vicente.

Department(s)

Civil, Architectural and Environmental Engineering

Keywords and Phrases

Child stunting; Environmental enteric dysfunction; Guatemala; Network analysis; Structural equation modeling

International Standard Serial Number (ISSN)

1438-4639

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2018 Elsevier, All rights reserved.

PubMed ID

29325698

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