IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0283627.html
   My bibliography  Save this article

Multivariate analysis of food consumption profiles in crisis settings

Author

Listed:
  • Aleksandra Gorzycka-Sikora
  • Nancy Mock
  • Michelle Lacey

Abstract

Preventing malnutrition is one of the primary objectives of many humanitarian agencies, and household surveys are regularly employed to monitor food insecurity caused by political, economic, or environmental crises. Consumption frequencies for standard food groups are often collected to characterize the depth of food insecurity in a community and measure the impact of food assistance programs, producing a vector of bounded, correlated counts for each household. While aggregate indicators are typically used to summarize these results with a single statistic, they can be difficult to interpret and provide insufficient detail to judge the effectiveness of assistance programs. To address these limitations, we have developed a multivariate modeling framework for consumption frequency data. We introduce methods to update baseline models for the analysis of the smaller and more variable surveys typically collected in crisis settings, and we present an application of our approach to national consumption data collected in Yemen in 2014 and 2016 by the World Food Programme. The approach provides more nuanced and interpretable information about consumption changes in response to shocks and the effectiveness of humanitarian assistance.

Suggested Citation

  • Aleksandra Gorzycka-Sikora & Nancy Mock & Michelle Lacey, 2023. "Multivariate analysis of food consumption profiles in crisis settings," PLOS ONE, Public Library of Science, vol. 18(3), pages 1-22, March.
    • Handle: RePEc:plo:pone00:0283627
    DOI: 10.1371/journal.pone.0283627
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0283627
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0283627&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0283627?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
    ---><---

    References listed on IDEAS

    as
    1. Lewandowski, Daniel & Kurowicka, Dorota & Joe, Harry, 2009. "Generating random correlation matrices based on vines and extended onion method," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 1989-2001, October.
    2. Molenberghs, Geert & Verbeke, Geert & Iddi, Samuel & Demétrio, Clarice G.B., 2012. "A combined beta and normal random-effects model for repeated, overdispersed binary and binomial data," Journal of Multivariate Analysis, Elsevier, vol. 111(C), pages 94-109.
    3. Wim Marivoet & Elodie Becquey & Bjorn Campenhout, 2019. "How well does the Food Consumption Score capture diet quantity, quality and adequacy across regions in the Democratic Republic of the Congo (DRC)?," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 11(5), pages 1029-1049, October.
    4. Hoddinott, John F. & Yohannes, Yisehac, 2002. "Dietary diversity as a food security indicator," FCND discussion papers 136, International Food Policy Research Institute (IFPRI).
    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. Zhang, Yixiao & Yu, Cindy L. & Li, Haitao, 2022. "Nowcasting GDP Using Dynamic Factor Model with Unknown Number of Factors and Stochastic Volatility: A Bayesian Approach," Econometrics and Statistics, Elsevier, vol. 24(C), pages 75-93.
    2. Thottappilly, Anna, 2021. "Identifying the Income Effect on Nutrition for Agricultural Households: Separability of Production and Consumption," 2021 Conference, August 17-31, 2021, Virtual 315335, International Association of Agricultural Economists.
    3. Anna D'Souza & Dean Jolliffe, 2012. "Rising Food Prices and Coping Strategies: Household-level Evidence from Afghanistan," Journal of Development Studies, Taylor & Francis Journals, vol. 48(2), pages 282-299, August.
    4. Fander Falconí & Juan Cadillo Benalcazar & Freddy Llive Cóndor & Jesus Ramos-Martin & Belén Liger, 2015. "Pérdida de autosuficiencia alimentaria y posibilidades de complementariedad agrícola en los países de UNASUR," Documentos de Trabajo CEPROEC 2015_06, Instituto de Altos Estudios Nacionales, Centro de Prospectiva Estratégica.
    5. Alejandro Plastina & Sergio H. Lence & Ariel Ortiz‐Bobea, 2021. "How weather affects the decomposition of total factor productivity in U.S. agriculture," Agricultural Economics, International Association of Agricultural Economists, vol. 52(2), pages 215-234, March.
    6. Matthias Breuer & Harm H. Schütt, 2023. "Accounting for uncertainty: an application of Bayesian methods to accruals models," Review of Accounting Studies, Springer, vol. 28(2), pages 726-768, June.
    7. JD Opdyke, 2025. "Beating the Correlation Breakdown: Robust Inference, Flexible Scenarios, and Stress Testing for Financial Portfolios," Papers 2504.15268, arXiv.org, revised Jun 2025.
    8. Flórez, Alvaro J. & Molenberghs, Geert & Van der Elst, Wim & Alonso Abad, Ariel, 2022. "An efficient algorithm to assess multivariate surrogate endpoints in a causal inference framework," Computational Statistics & Data Analysis, Elsevier, vol. 172(C).
    9. Finaret, A.B. & Miller, L.C. & Joshi, N. & Mahato, S. & Lohani, M. & Drozdowsky, J. & Rogers, B.L., 2018. "Longitudinal analysis of the intrahousehold distribution of foods in rural Nepal: Relative variability of child dietary quality across age and sex cohorts," Food Policy, Elsevier, vol. 79(C), pages 101-110.
    10. Paramita Bhattacharya & Siddhartha Mitra & Md. Zakaria Siddiqui, 2016. "Dynamics of Foodgrain Deficiency in India," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 10(4), pages 465-498, November.
    11. Giuseppe Brandi & Ruggero Gramatica & Tiziana Di Matteo, 2019. "Unveil stock correlation via a new tensor-based decomposition method," Papers 1911.06126, arXiv.org, revised Apr 2020.
    12. Andrew Y. Chen & Jack McCoy, 2022. "Missing Values Handling for Machine Learning Portfolios," Papers 2207.13071, arXiv.org, revised Jan 2024.
    13. Abera Demeke & Alwin Keil & Manfred Zeller, 2011. "Using panel data to estimate the effect of rainfall shocks on smallholders food security and vulnerability in rural Ethiopia," Climatic Change, Springer, vol. 108(1), pages 185-206, September.
    14. Gregory Benton & Wesley J. Maddox & Andrew Gordon Wilson, 2022. "Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes," Papers 2207.06544, arXiv.org.
    15. Juho Kettunen & Lauri Mehtätalo & Eeva‐Stiina Tuittila & Aino Korrensalo & Jarno Vanhatalo, 2024. "Joint species distribution modeling with competition for space," Environmetrics, John Wiley & Sons, Ltd., vol. 35(2), March.
    16. Larochelle, Catherine & Alwang, Jeffrey Roger, 2014. "Impacts of Improved Bean Varieties on Food Security in Rwanda," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170567, Agricultural and Applied Economics Association.
    17. Orkhan Sariyev & Tim K. Loos & Ling Yee Khor, 2021. "Intra-household decision-making, production diversity, and dietary quality: a panel data analysis of Ethiopian rural households," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 13(1), pages 181-197, February.
    18. Maluccio, John A. & Flores, Rafael, 2004. "Impact evaluation of a conditional cash transfer program: the Nicaraguan Red de Protección Social," FCND discussion papers 184, International Food Policy Research Institute (IFPRI).
    19. Alison Misselhorn, 2009. "Is a focus on social capital useful in considering food security interventions? Insights from KwaZulu-Natal," Development Southern Africa, Taylor & Francis Journals, vol. 26(2), pages 189-208.
    20. Sharimakin Akinwumi & Dada James Temitope, 2020. "Access to Finance, Indigenous Technology and Food Security in Nigeria: Case Study of Ondo Central Senatorial District," Economics and Culture, Sciendo, vol. 17(2), pages 75-87, December.

    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:plo:pone00:0283627. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.