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Harmonized food consumption dataset by food category and acquisition source for Sub-Saharan African countries
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  • Published: 21 January 2026

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

  • Amaka P. Nnaji  ORCID: orcid.org/0000-0002-4156-89251,
  • Didier Yelognisse Alia1,
  • Ahana Raina1 &
  • …
  • C. Leigh Anderson1 

Scientific Data , Article number:  (2026) Cite this article

  • 939 Accesses

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Agriculture
  • Economics

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.

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Data availability

The entire dataset is available online in a Figshare repository. The following URL provides access to the dataset25: https://doi.org/10.6084/m9.figshare.29874011.

Code availability

The Stata codes used to process the raw data, generate standardized food consumption indicators, and append different survey waves for each country into a combined dataset are available on GitHub (https://github.com/EvansSchoolPolicyAnalysisAndResearch/Household-Consumption-Data). Each survey data processed has its own Stata dofile. Additionally, we include a dofile used to append individual datasets into a combined dataset. The do files are annotated to describe and guide the user through the different stages of data processing. This ensures full reproducibility of the data harmonization process and enables users to trace each indicator back to its original source. An interactive and more comprehensive visualization of the data is accessible on the Tableau visualization platform. Table S4 in the Supplementary Information lists the names of Stata code files available in the GitHub repository.

References

  1. World Bank. Poverty and Shared Prosperity 2018: Piecing Together the Poverty Puzzle. http://hdl.handle.net/10986/30418 (2018).

  2. Deaton, A. Income, health, and well-being around the world: Evidence from the Gallup World Poll. Journal of Economic perspectives 22, 53–72 (2008).

    Google Scholar 

  3. Ravallion, M. The Economics of Poverty: History, Measurement, and Policy. (Oxford University Press, 2015).

  4. Baah, S. K. T. et al. March 2023 global poverty update from the World Bank: the challenge of estimating poverty in the pandemic. Diakses pada 9 (2023).

  5. Kharas, H. & Dooley, M. The Evolution of Global Poverty, 1990–2030: Trends and Projections. (Brookings Institution. United States of America, 2022).

  6. Debucquet, D. L. & Martin, W. Implications of the global growth slowdown for rural poverty. Agricultural Economics 49, 325–338 (2018).

    Google Scholar 

  7. Damari, Y. & Kissinger, M. Quantity-based analysis of household food consumption patterns and drivers: The case of Israel. Appetite 127, 373–385 (2018).

    Google Scholar 

  8. Otero, G., Gürcan, E. C., Pechlaner, G. & Liberman, G. Food security, obesity, and inequality: Measuring the risk of exposure to the neoliberal diet. Journal of Agrarian Change 18, 536–554 (2018).

    Google Scholar 

  9. Regmi, A. & Meade, B. Demand side drivers of global food security. Global Food Security 2, 166–171 (2013).

    Google Scholar 

  10. Chen, C., Chaudhary, A. & Mathys, A. Dietary Change and Global Sustainable Development Goals. Front. Sustain. Food Syst. 6 (2022).

  11. Pingali, P., Aiyar, A., Abraham, M. & Rahman, A. Diet Diversity and the Declining Importance of Staple Grains. in Transforming Food Systems for a Rising India (eds Pingali, P., Aiyar, A., Abraham, M. & Rahman, A.) 73–91, https://doi.org/10.1007/978-3-030-14409-8_4 (Springer International Publishing, Cham, 2019).

  12. Elzaki, R., Yunus Sisman, M. & Al-Mahish, M. Rural Sudanese household food consumption patterns. Journal of the Saudi Society of Agricultural Sciences 20, 58–65 (2021).

    Google Scholar 

  13. Hayat, N., Mustafa, G., Alotaibi, B. A., Nayak, R. K. & Naeem, M. Households food consumption pattern in Pakistan: Evidence from recent household integrated economic survey. Heliyon 9 (2023).

  14. Mekonnen, D. A. et al. Food consumption patterns, nutrient adequacy, and the food systems in Nigeria. Agric Econ 9, 16 (2021).

    Google Scholar 

  15. Wolle, A., Hirvonen, K., de Brauw, A., Baye, K. & Abate, G. T. Household Food Consumption Patterns in Addis Ababa, Ethiopia. https://doi.org/10.2499/P15738COLL2.133654 (2020).

  16. Waha, K., Zipf, B., Kurukulasuriya, P. & Hassan, R. M. An agricultural survey for more than 9,500 African households. Scientific data 3, 1–8 (2016).

    Google Scholar 

  17. van Wijk, M. et al. The Rural Household Multiple Indicator Survey, data from 13,310 farm households in 21 countries. Scientific Data 7, 46 (2020).

    Google Scholar 

  18. Belmin, C., Hoffmann, R., Elkasabi, M. & Pichler, P.-P. LivWell: a sub-national Dataset on the Living Conditions of Women and their Well-being for 52 Countries. Scientific data 9, 719 (2022).

    Google Scholar 

  19. Chemura, A., Gleixner, S. & Gornott, C. Dataset of the suitability of major food crops in Africa under climate change. Scientific Data 11, 294 (2024).

    Google Scholar 

  20. Machefer, M. et al. A monthly sub-national Harmonized Food Insecurity Dataset for comprehensive analysis and predictive modeling. Scientific Data 12, 741 (2025).

    Google Scholar 

  21. Lee, D. et al. HarvestStat Africa–harmonized subnational crop statistics for sub-Saharan Africa. Scientific Data 12, 690 (2025).

    Google Scholar 

  22. World Bank. World Development Indicators. World Bank, DataBank, https://databank.worldbank.org/source/world-development-indicators.

  23. McKelvey, C. Price, unit value, and quality demanded. Journal of Development Economics 95, 157–169 (2011).

    Google Scholar 

  24. Evans School Policy Analysis and Research (EPAR). EPAR GitHub Code Repository. GitHub (2025).

  25. Nnaji, A. P., Alia, D. Y., Raina, A., & Anderson, C. L. Harmonized food consumption dataset by food category and acquisition source for Sub-Saharan African countries figshare, https://doi.org/10.6084/m9.figshare.29874011 (2025).

  26. Institut National de la Statistique et de l’Analyse Économique (INSAE). Enquête Harmonisée sur le Conditions de Vie des Ménages 2018-2019 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/rn3k-z374 (2022).

  27. Institut National de la Statistique et de la Démographie (INSD). Enquête Harmonisée sur le Conditions de Vie des Ménages 2018-2019 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/wv88-j486 (2022).

  28. Institut National de la Statistique et de la Démographie (INSD). Enquête Harmonisée sur le Conditions de Vie des Ménages, Panel Survey 2021-2022 [Data set]. World Bank, Development Data Group, https://microdata.worldbank.org/index.php/catalog/6224 (2024).

  29. Institut National de la Statistique (INS). Enquête Harmonisée sur le Conditions de Vie des Ménages 2018-2019 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/8wh3-bf40 (2022).

  30. Central Statistical Agency of Ethiopia. Socioeconomic Survey 2015-2016, Wave 3 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/ampf-7988 (2017).

  31. Central Statistics Agency of Ethiopia. Socioeconomic Survey 2018-2019, Wave 4 [Data set]. World Bank, Development Data Group, https://microdata.worldbank.org/index.php/catalog/3823 (2021).

  32. Ethiopian Statistical Service (ESS). Socioeconomic Panel Survey 2021-2022 Wave 5 [Data set]. World Bank, Development Data Group, https://microdata.worldbank.org/index.php/catalog/6161 (2024).

  33. Institute of Statistical, Social and Economic Research & Economic Growth Center. Socioeconomic Panel Survey: 2009-2010 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/851p-b825 (2016).

  34. Instituto Nacional de Estatística (INE). Inquérito Harmonizado sobre as Condiçöes de vide dos Agreagados Familiares 2018-2019 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/1ekb-m086 (2022).

  35. Kenya National Bureau of Statistics. Kenya Integrated Household Budget Survey 2015-2016 [Data set]. Kenya National Data Archive, https://statistics.knbs.or.ke/nada/index.php/catalog/13 (2018).

  36. National Statistical Office (NSO). Third Integrated Household Survey 2010-2011 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/w1jq-qh85 (2012).

  37. National Statistical Office (NSO). Integrated Household Panel Survey 2010-2013 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/4q9f-2288 (2015).

  38. National Statistical Office (NSO). Fourth Integrated Household Survey 2016-2017 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/g2p9-9r19 (2017).

  39. National Statistical Office (NSO). Fifth Integrated Household Survey 2019-2020 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/mpyk-ds48 (2021).

  40. Planning and Statistics Unit, National Institute of Statistics, & National Directorate of Agriculture. 2014 Integrated Agricultural Economic Survey [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/qqam-mn86 (2016).

  41. Institut National de la Statistique (INSTAT). Enquête Harmonisée sur le Conditions de Vie des Ménages 2018-2019 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/90e9-4e91 (2022).

  42. Institut National de la Statistique (INS). Enquête Harmonisée sur le Conditions de Vie des Ménages 2018-2019 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/ggam-ax39 (2022).

  43. National Bureau of Statistics (NBS). General Household Survey, Panel 2010-2011, Wave 1 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/y9e2-b753 (2012).

  44. National Bureau of Statistics (NBS). General Household Survey, Panel 2012-2013, Wave 2 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/kxpy-aa72 (2014).

  45. National Bureau of Statistics (NBS). General Household Survey, Panel 2015-2016, Wave 3 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/7xmj-q133 (2016).

  46. National Bureau of Statistics (NBS). General Household Survey, Panel 2018-2019, Wave 4 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/1hgw-dq47 (2019).

  47. Agence National de la Statistique et de la Démographie (ANSD). Enquête Harmonisée sur le Conditions de Vie des Ménages 2018-2019 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/hhhx-j012 (2022).

  48. Statistics Sierra Leone, & The World Bank. Integrated Household Survey 2018 Dataset. International Household Survey Network (IHSN) Data Catalog, https://catalog.ihsn.org/catalog/9246 (2020).

  49. National Bureau of Statistics. National Panel Survey 2008-2009, Wave 1 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/hz8s-3489 (2011).

  50. National Bureau of Statistics. National Panel Survey 2010-2011, Wave 2 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/jm20-c742 (2012).

  51. National Bureau of Statistics. National Panel Survey 2012-2013, Wave 3 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/7vqv-5f71 (2015).

  52. National Bureau of Statistics. National Panel Survey 2014-2015, Wave 4 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/y3qj-d018 (2017).

  53. World Bank. National Panel Survey 2019-2020 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/0y7d-1v78 (2021).

  54. Institut National de la Statistique et des Etudes Economiques et Démographiques (INSEED). Enquête Harmonisée sur le Conditions de Vie des Ménages 2018-2019 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/ww9z-d865 (2022).

  55. Uganda Bureau of Statistics (UBOS). National Panel Survey 2005-2009 Wave I [Dataset]. World Bank, Development Data Group, https://doi.org/10.48529/9vep-e461 (2012).

  56. Uganda Bureau of Statistics (UBOS). National Panel Survey 2010-2011 Wave II [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/w2d8-t244 (2014).

  57. Uganda Bureau of Statistics (UBOS). National Panel Survey 2011-2012 Wave III [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/wjg5-bg56 (2014).

  58. Uganda Bureau of Statistics (UBOS). National Panel Survey 2013-2014 [Data set]. World Bank, Development Data Group, https://microdata.worldbank.org/index.php/catalog/2663 (2016).

  59. Uganda Bureau of Statistics (UBOS). National Panel Survey 2015-2016 [Data set]. World Bank, Development Data Group, https://microdata.worldbank.org/index.php/catalog/3460 (2018).

  60. Uganda Bureau of Statistics (UBOS). National Panel Survey 2018-2019 [Data set]. World Bank, Development Data Group, https://microdata.worldbank.org/index.php/catalog/3795 (2021).

  61. Uganda Bureau of Statistics (UBOS). National Panel Survey 2019-2020 [Data set]. World Bank, Development Data Group, https://doi.org/10.48529/nqzx-f196 (2021).

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Author information

Authors and Affiliations

  1. Evans School Policy Analysis Research (EPAR) group, Daniel J. Evans School of Public Policy and Governance, University of Washington, Seattle, WA, USA

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

Authors
  1. Amaka P. Nnaji
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  2. Didier Yelognisse Alia
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  3. Ahana Raina
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  4. C. Leigh Anderson
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Contributions

A.P.N.: Conceptualization, Methodology, Data Curation, Formal Analysis, Validation, Visualization, Writing - Original Draft, Review and Editing. D.Y.A.: Conceptualization, Methodology, Data Curation, Formal Analysis, Validation, Visualization, Writing - Review and Editing. A.R.: Visualization, Writing - Review and Editing. C.L.A.: Conceptualization, Writing - Review and Editing, Supervision, Funding Acquisition.

Corresponding author

Correspondence to Amaka P. Nnaji.

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Nnaji, A.P., Alia, D.Y., Raina, A. et al. Harmonized food consumption dataset by food category and acquisition source for Sub-Saharan African countries. Sci Data (2026). https://doi.org/10.1038/s41597-026-06548-1

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  • Received: 11 August 2025

  • Accepted: 29 December 2025

  • Published: 21 January 2026

  • DOI: https://doi.org/10.1038/s41597-026-06548-1

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