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How Seasonality of Malnutrition Is Measured and Analyzed

Author

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  • Anastasia Marshak

    (Feinstein International Center, Tufts University, Boston, MA 02111, USA
    Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA 02111, USA)

  • Aishwarya Venkat

    (Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA 02111, USA)

  • Helen Young

    (Feinstein International Center, Tufts University, Boston, MA 02111, USA
    Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA 02111, USA)

  • Elena N. Naumova

    (Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA 02111, USA)

Abstract

Seasonality is a critical source of vulnerability across most human activities and natural processes, including the underlying and immediate drivers of acute malnutrition. However, while there is general agreement that acute malnutrition is highly variable within and across years, the evidence base is limited, resulting in an overreliance on assumptions of seasonal peaks. We review the design and analysis of 24 studies exploring the seasonality of nutrition outcomes in Africa’s drylands, providing a summary of approaches and their advantages and disadvantages. Over half of the studies rely on two to four time points within the year and/or the inclusion of time as a categorical variable in the analysis. While such approaches simplify interpretation, they do not correspond to the climatic variability characteristic of drylands or the relationship between climatic variability and human activities. To better ground our understanding of the seasonality of acute malnutrition in a robust evidence base, we offer recommendations for study design and analysis, including drawing on participatory methods to identify community perceptions of seasonality, use of longitudinal data and panel analysis with approaches borrowed from the field of infectious diseases, and linking oscillations in nutrition data with climatic data.

Suggested Citation

  • Anastasia Marshak & Aishwarya Venkat & Helen Young & Elena N. Naumova, 2021. "How Seasonality of Malnutrition Is Measured and Analyzed," IJERPH, MDPI, vol. 18(4), pages 1-12, February.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:4:p:1828-:d:498811
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    References listed on IDEAS

    as
    1. Kavitha Ramanathan & Mani Thenmozhi & Sebastian George & Shalini Anandan & Balaji Veeraraghavan & Elena N. Naumova & Lakshmanan Jeyaseelan, 2020. "Assessing Seasonality Variation with Harmonic Regression: Accommodations for Sharp Peaks," IJERPH, MDPI, vol. 17(4), pages 1-14, February.
    2. Olga K. Alsova & Valery B. Loktev & Elena N. Naumova, 2019. "Rotavirus Seasonality: An Application of Singular Spectrum Analysis and Polyharmonic Modeling," IJERPH, MDPI, vol. 16(22), pages 1-20, November.
    3. Aishwarya Venkat & Tania M. Alarcon Falconi & Melissa Cruz & Meghan A. Hartwick & Shalini Anandan & Naveen Kumar & Honorine Ward & Balaji Veeraraghavan & Elena N. Naumova, 2019. "Spatiotemporal Patterns of Cholera Hospitalization in Vellore, India," IJERPH, MDPI, vol. 16(21), pages 1-14, November.
    4. Katarina Ureña-Castro & Silvia Ávila & Mariela Gutierrez & Elena N. Naumova & Rolando Ulloa-Gutierrez & Alfredo Mora-Guevara, 2019. "Seasonality of Rotavirus Hospitalizations at Costa Rica’s National Children’s Hospital in 2010–2015," IJERPH, MDPI, vol. 16(13), pages 1-13, June.
    5. Pelletier, David L. & Deneke, Kassahun & Kidane, Yemane & Haile, Beyenne & Negussie, Fikre, 1995. "The food-first bias and nutrition policy: lessons from Ethiopia," Food Policy, Elsevier, vol. 20(4), pages 279-298, August.
    6. Tania M. Alarcon Falconi & Bertha Estrella & Fernando Sempértegui & Elena N. Naumova, 2020. "Effects of Data Aggregation on Time Series Analysis of Seasonal Infections," IJERPH, MDPI, vol. 17(16), pages 1-21, August.
    7. Pavel S. Stashevsky & Irina N. Yakovina & Tania M. Alarcon Falconi & Elena N. Naumova, 2019. "Agglomerative Clustering of Enteric Infections and Weather Parameters to Identify Seasonal Outbreaks in Cold Climates," IJERPH, MDPI, vol. 16(12), pages 1-19, June.
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