IDEAS home Printed from https://ideas.repec.org/a/wly/jintdv/v37y2025i2p554-569.html
   My bibliography  Save this article

Malnourished but Not Destitute: The Spatial Interplay Between Nutrition and Poverty in Madagascar

Author

Listed:
  • Dunstan Matekenya
  • Francis Mulangu
  • David Newhouse

Abstract

Hidden hunger is a global issue that affects an astounding 2 billion people, demanding targeted interventions for better resource allocation. However, conventional methods for identifying high‐prevalence areas often prove impractical in developing countries. This study introduces a cost‐effective and practical approach to detecting hidden hunger, combining household budget data with health surveys and applying these methods to Madagascar. By using small‐area estimation techniques, the study achieves precise commune‐level estimates, addressing the limitations of survey data representativeness. The findings challenge poverty‐based targeting, revealing that 17.9% of stunted children belong to non‐poor households. Additionally, 21.3% of non‐stunted children are found in impoverished households, supporting Sen's argument that malnutrition extends beyond destitution. The analysis further highlights key commune‐level determinants of hidden hunger, including access to healthcare, improved roads, telecommunication networks and productive agricultural activities.

Suggested Citation

  • Dunstan Matekenya & Francis Mulangu & David Newhouse, 2025. "Malnourished but Not Destitute: The Spatial Interplay Between Nutrition and Poverty in Madagascar," Journal of International Development, John Wiley & Sons, Ltd., vol. 37(2), pages 554-569, March.
  • Handle: RePEc:wly:jintdv:v:37:y:2025:i:2:p:554-569
    DOI: 10.1002/jid.3975
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/jid.3975
    Download Restriction: no

    File URL: https://libkey.io/10.1002/jid.3975?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Nikos Tzavidis & Li‐Chun Zhang & Angela Luna & Timo Schmid & Natalia Rojas‐Perilla, 2018. "From start to finish: a framework for the production of small area official statistics," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(4), pages 927-979, October.
    2. D. Pfeffermann & C. J. Skinner & D. J. Holmes & H. Goldstein & J. Rasbash, 1998. "Weighting for unequal selection probabilities in multilevel models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(1), pages 23-40.
    3. Thomas Pave Sohnesen & Alemayehu Azeze Ambel & Peter Fisker & Colin Andrews & Qaiser Khan, 2017. "Small area estimation of child undernutrition in Ethiopian woredas," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-17, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nora Würz & Timo Schmid & Nikos Tzavidis, 2022. "Estimating regional income indicators under transformations and access to limited population auxiliary information," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1679-1706, October.
    2. Patrick Krennmair & Timo Schmid, 2022. "Flexible domain prediction using mixed effects random forests," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1865-1894, November.
    3. Takaaki Masaki & David Newhouse & Ani Rudra Silwal & Adane Bedada & Ryan Engstrom, 2020. "Small Area Estimation of Non-Monetary Poverty with Geospatial Data," World Bank Publications - Reports 34469, The World Bank Group.
    4. Carrington C. J. Shepherd & Holly D. Clifford & Francis Mitrou & Shannon M. Melody & Ellen J. Bennett & Fay H. Johnston & Luke D. Knibbs & Gavin Pereira & Janessa L. Pickering & Teck H. Teo & Lea-Ann , 2019. "The Contribution of Geogenic Particulate Matter to Lung Disease in Indigenous Children," IJERPH, MDPI, vol. 16(15), pages 1-12, July.
    5. Natascha Hainbach & Christoph Halbmeier & Timo Schmid & Carsten Schröder, 2019. "A Practical Guide for the Computation of Domain-Level Estimates with the Socio-Economic Panel (and Other Household Surveys)," SOEPpapers on Multidisciplinary Panel Data Research 1055, DIW Berlin, The German Socio-Economic Panel (SOEP).
    6. Gianni Betti & Federico Crescenzi & Vasco Molini & Lorenzo Mori, 2024. "Estimation of Multidimensional Poverty in Morocco: A Small Area Estimation Approach Using Meteorological and Socio-economic Covariates," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 175(2), pages 545-575, November.
    7. Patricia Dörr & Jan Pablo Burgard, 2019. "Data-driven transformations and survey-weighting for linear mixed models," Research Papers in Economics 2019-16, University of Trier, Department of Economics.
    8. Shepherd, Carrington CJ & Li, Jianghong & Mitrou, Francis & Zubrick, Stephen R., 2012. "Socioeconomic disparities in the mental health of Indigenous children in Western Australia," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 12, pages 1-1.
    9. Jorge Walter & Daniel Z. Levin & J. Keith Murnighan, 2015. "Reconnection Choices: Selecting the Most Valuable (vs. Most Preferred) Dormant Ties," Organization Science, INFORMS, vol. 26(5), pages 1447-1465, October.
    10. Jennings, Jacky M. & Hensel, Devon J. & Tanner, Amanda E. & Reilly, Meredith L. & Ellen, Jonathan M., 2014. "Are social organizational factors independently associated with a current bacterial sexually transmitted infection among urban adolescents and young adults?," Social Science & Medicine, Elsevier, vol. 118(C), pages 52-60.
    11. Marchetti Stefano & Tzavidis Nikos, 2021. "Robust Estimation of the Theil Index and the Gini Coeffient for Small Areas," Journal of Official Statistics, Sciendo, vol. 37(4), pages 955-979, December.
    12. Joseph L Dieleman & Tara Templin, 2014. "Random-Effects, Fixed-Effects and the within-between Specification for Clustered Data in Observational Health Studies: A Simulation Study," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-17, October.
    13. Jan Pablo Burgard & Ralf Münnich & Martin Rupp, 2020. "Qualitätszielfunktionen für stark variierende Gemeindegrößen im Zensus 2021 [Quality measures respecting highly varying community sizes within the 2021 German Census]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 14(1), pages 5-65, March.
    14. Paul A. Smith & Chiara Bocci & Nikos Tzavidis & Sabine Krieg & Marc J. E. Smeets, 2021. "Robust estimation for small domains in business surveys," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(2), pages 312-334, March.
    15. Laura M. Stapleton & Yoonjeong Kang, 2018. "Design Effects of Multilevel Estimates From National Probability Samples," Sociological Methods & Research, , vol. 47(3), pages 430-457, August.
    16. Woojin Chung & Roeul Kim, 2020. "Which Occupation is Highly Associated with Cognitive Impairment? A Gender-Specific Longitudinal Study of Paid and Unpaid Occupations in South Korea," IJERPH, MDPI, vol. 17(21), pages 1-17, October.
    17. Batterham, Deb & Nygaard, Christian & reynolds, margaret & De Vries, Jacqueline, 2021. "Estimating the population at-risk of homelessness in small areas," SocArXiv hkc7y_v1, Center for Open Science.
    18. Sophia Rabe‐Hesketh & Anders Skrondal, 2006. "Multilevel modelling of complex survey data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(4), pages 805-827, October.
    19. Robert G. Clark & David G. Steel, 2022. "Sample design for analysis using high‐influence probability sampling," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1733-1756, October.
    20. Francesco Schirripa Spagnolo & Nicola Salvati & Antonella D’Agostino & Ides Nicaise, 2020. "The use of sampling weights in M‐quantile random‐effects regression: an application to Programme for International Student Assessment mathematics scores," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(4), pages 991-1012, August.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:jintdv:v:37:y:2025:i:2:p:554-569. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www3.interscience.wiley.com/journal/5102/home .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.