Climate Change and Malnutrition Among Under-5 Children in Guatemala from 2000 to 2017 Restricted; Files Only

Abstract

In Guatemala, malnutrition prevalence rates are among the highest in Latin America and the world. Malnutrition drivers are highly complex and intertwined, including socioeconomic, agricultural, and climatic factors. Though Guatemala is highly vulnerable to the effects of climate change, the connection between climate and malnutrition is thus far under-explored. In this thesis, we conduct an exploratory study of the relationship between climate and under-5 child malnutrition in Guatemala from 2000-2017 to better understand the importance of climate variables in determining malnutrition. To do so, regression and random forest analyses were performed to uncover the significance of the climate-malnutrition relationship and determine how climatic factors compare to non-climatic factors in determining malnutrition. Results demonstrate the most significant relationships are between climate and stunting malnutrition, especially in the highlands region, with a positive relationship between annual soil moisture (drought proxy) (p<0.01) and stunting. We also find a negative relationship between growing season temperature and stunting (p<0.01). Similar results were found for underweight malnutrition (p<0.01), though with lower effect size, indicating other non-climatic factors may be more important in predicting underweight malnutrition in Guatemala. Therefore, this thesis highlights the significance of some climate variables as contributing factors to malnutrition prevalence in Guatemala. 

Table of Contents

INTRODUCTION............................................................................................................................... 1

METHODS........................................................................................................................................ 7

Climate Data................................................................................................................................ 7

Malnutrition Data........................................................................................................................ 8

Control Variable Data.................................................................................................................. 9

Descriptive Analysis................................................................................................................... 10

Regression Analysis ................................................................................................................... 11

Random Forest Machine Learning Models ............................................................................... 14

RESULTS......................................................................................................................................... 16

Descriptive Analysis................................................................................................................... 16

Regression Analysis ................................................................................................................... 26

Random Forest Machine Learning Models ............................................................................... 31

DISCUSSION................................................................................................................................... 32

REFERENCES .................................................................................................................................. 40 

About this Honors Thesis

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School	Emory College
Department	Quantitative Science
Degree	B.S.
Submission	Honors Thesis
Language	English
Research Field	Health Sciences, Epidemiology Health Sciences, Public Health Statistics
Palabra Clave	Guatemala Malnutrition Climate
Committee Chair / Thesis Advisor	Rho, Seunghwa , Emory University Hall-Clifford, Rachel, Emory University
Committee Members	Luber, George, Emory University

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