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<p>Household consumption is a key measure of well-being in low- and middle-income countries (LMICs) where agriculture remains the primary livelihood, and food represents a substantial share of household total consumption expenditures. This paper introduces a new harmonized dataset of food consumption value by food categories and acquisition sources for 16 sub-Saharan African countries from 2008 to 2021. The dataset is constructed from consumption modules of large-scale, nationally representative household surveys collected by the World Bank and each country’s National Statistical Office. It adds value to these surveys by standardizing indicators, including monetizing non-market consumption, generating food item-level estimates, and making the processing code and record-level microdata publicly available for replication and use by researchers. The dataset facilitates valid cross-country comparisons of food consumption over time and can be merged with other satellite and climate data datasets for additional analysis of the drivers and impacts of food consumption in LMICs. Additionally, an indicator dashboard and visualizations have been created to make the estimates accessible to policymakers and the public.</p>

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Harmonized food consumption dataset by food category and acquisition source for Sub-Saharan African countries

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月21日

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  • Amaka P. Nnaji,
  • Didier Yelognisse Alia,
  • Ahana Raina,
  • C. Leigh Anderson

摘要

Household consumption is a key measure of well-being in low- and middle-income countries (LMICs) where agriculture remains the primary livelihood, and food represents a substantial share of household total consumption expenditures. This paper introduces a new harmonized dataset of food consumption value by food categories and acquisition sources for 16 sub-Saharan African countries from 2008 to 2021. The dataset is constructed from consumption modules of large-scale, nationally representative household surveys collected by the World Bank and each country’s National Statistical Office. It adds value to these surveys by standardizing indicators, including monetizing non-market consumption, generating food item-level estimates, and making the processing code and record-level microdata publicly available for replication and use by researchers. The dataset facilitates valid cross-country comparisons of food consumption over time and can be merged with other satellite and climate data datasets for additional analysis of the drivers and impacts of food consumption in LMICs. Additionally, an indicator dashboard and visualizations have been created to make the estimates accessible to policymakers and the public.