Disaggregate level estimates and spatial mapping of food insecurity in Bangladesh by linking survey and census data

Md. Jamal Hossain*, Sumonkanti Das, Hukum Chandra, Mohammad Amirul Islam

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Web of Science)

Abstract

Food insecurity is an important and persistent social issue in Bangladesh. Existing data based on socio-economic surveys produce divisional and nationally representative food insecurity estimates but these surveys cannot be used directly to generate reliable district level estimates. We deliberate small area estimation (SAE) approach for estimating the food insecurity status at district level in Bangladesh by combining Household Income and Expenditure Survey 2010 with the Bangladesh Population and Housing Census 2011. The food insecurity prevalence, gap and severity status have been determined based on per capita calorie intake with a threshold of 2122 kcal per day, as specified by the Bangladesh Bureau of Statistics.The results show that the food insecurity estimates generated from SAE are precise and representative of the spatial heterogeneity in the socioeconomic conditions than do the direct estimates. The maps showing the food insecurity indicators by district indicate that a number of districts in northern and southern parts are more vulnerable in terms of all indicators. These maps will guide the government, international organizations, policy-makers and development partners for efficient resource allocation.

Original languageEnglish
Article number0230906
Number of pages16
JournalPLOS ONE
Volume15
Issue number4
DOIs
Publication statusPublished - 10 Apr 2020

Keywords

  • MEAN-SQUARED ERROR
  • POVERTY
  • MODEL

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