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Journal of Food Security. 2015, 3(1), 11-24
DOI: 10.12691/JFS-3-1-3
Original Research

Spatial Distribution of Food Poverty Incidence in Juba Town: A geo-statistical Assessment

David Lomeling1, and Rita Nyoka Wani2

1Department of Agricultural Sciences, CNRES, University of Juba, P.O. Box 82 Juba, South Sudan

2Graduate Student, Department of Agricultural Sciences, University of Juba, P.O Box 82 Juba, South Sudan

Pub. Date: February 27, 2015
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David Lomeling and Rita Nyoka Wani. Spatial Distribution of Food Poverty Incidence in Juba Town: A geo-statistical Assessment. Journal of Food Security. 2015; 3(1):11-24. doi: 10.12691/JFS-3-1-3

Abstract

Food and nutrition security survey based on a representative sample of the population of Juba Town was conducted from October to November 2010. The survey covered four localities: Gudele, Juba na Bari, Kator and Munuki. Daily calorie intake using a one day 24-hour diet recall varied between 500 to 3,500 Kcal as a function of monthly income. Spatial distribution of food poverty incidence as well as daily calorific values were geo-statistically analyzed using a GS+TM Version 9 software. Results showed that about 13.2% of the households with incomes less than 500 SDG/month were severely food insecure with constant hunger,41.5% of the households with incomes between 350-800 SDG/month were food insecure with moderate hunger; 35.8% of the households with incomes between 850-1850 SDG/month were food insecure but without hunger; and 9.4% of the households with incomes between 1,850 and 4,000 SDG/month were food secure. Isotropic variogram of food poverty incidence showed a 46.6% moderate spatial dependency with a relatively low correlation coefficient of r2=0.15 and a range A0 of 8.8 km suggesting a wide radius of even food poverty levels across much of Juba Town. Meanwhile the estimated daily per capita calorific values also showed moderate spatial dependency of 60.3% and a small range A0at 2.3 km. Food poverty incidence at low correlation coefficient r2=0.02 positively correlated with family size and negatively correlated at r2=0.17 with the per capita food consumption. Monetary indicator was used to assess food poverty with the Gini coefficient at 0.32. This unequal income distribution suggested the vulnerability of most households to food insecurity. However, most low income households with less freedom of choice easily compensated their dietary diversity and calorific values through appropriate food preparation methods.

Keywords

daily calorie intake, dietary diversity, food security, food poverty mapping, Gini coefficient, isotropic variogram

Copyright

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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