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

**Authors:** Amaka P. Nnaji, Didier Yelognisse Alia, Ahana Raina, C. Leigh Anderson

PMC · DOI: 10.1038/s41597-026-06548-1 · 2026-01-21

## TL;DR

This paper presents a standardized dataset of food consumption in 16 Sub-Saharan African countries from 2008 to 2021, enabling cross-country comparisons and policy insights.

## Contribution

The novel contribution is a harmonized, publicly accessible dataset of food consumption by category and source across 16 Sub-Saharan African countries.

## Key findings

- The dataset includes standardized food consumption indicators from nationally representative surveys.
- It enables valid cross-country comparisons and can be merged with satellite and climate data.
- Public access to processing code and microdata supports replication and further research.

## Abstract

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.

## Full-text entities

- **Diseases:** COVID-19 (MESH:D000086382)
- **Chemicals:** ghee (MESH:D000067048), ITEM (-), margarine (MESH:D008383), oils (MESH:D009821)
- **Species:** Arachis hypogaea (goober, species) [taxon 3818], Oryza sativa (Asian cultivated rice, species) [taxon 4530], Sorghum bicolor (broomcorn, species) [taxon 4558], Solanum tuberosum (potatoes, species) [taxon 4113], Manihot esculenta (cassava, species) [taxon 3983]
- **Mutations:** INSTAT

## Figures

8 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12902005/full.md

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Source: https://tomesphere.com/paper/PMC12902005