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Internal validity of the Food Access Survey Tool in assessing household food insecurity in rural Zambia

Author

Listed:
  • Muzi Na

    (Johns Hopkins Bloomberg School of Public Health)

  • Alden L. Gross

    (Johns Hopkins Bloomberg School of Public Health)

  • Lee S. F. Wu

    (Johns Hopkins Bloomberg School of Public Health)

  • Bess L. Caswell

    (Johns Hopkins Bloomberg School of Public Health)

  • Sameera A. Talegawkar

    (The George Washington University)

  • Amanda C. Palmer

    (Johns Hopkins Bloomberg School of Public Health)

Abstract

We assessed the internal validity of the Food Access Survey Tool (FAST) using data from households (n = 907) enrolled in an efficacy trial of biofortified maize in rural Zambia. This scale assesses food insecurity over a 6-month recall period. A Rasch partial credit model was used to evaluate item performance. Unidimensionality was assessed by principal component analysis, monotonicity was assessed by non-parametric methods, and differential item functioning (DIF) by several characteristics was assessed by cumulative ordinal logistic regression models. One item (frequency of consuming three square meals) did not fit the partial credit model. The remaining eight items fit in a primary single statistical dimension and item category severity increased monotonically with increasing severity of food insecurity. We identified statistically significant DIF in three subgroup comparisons, but effect sizes of total DIF were considered practically insignificant (

Suggested Citation

  • Muzi Na & Alden L. Gross & Lee S. F. Wu & Bess L. Caswell & Sameera A. Talegawkar & Amanda C. Palmer, 2016. "Internal validity of the Food Access Survey Tool in assessing household food insecurity in rural Zambia," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 8(3), pages 679-688, June.
    • Handle: RePEc:spr:ssefpa:v:8:y:2016:i:3:d:10.1007_s12571-016-0573-y
    DOI: 10.1007/s12571-016-0573-y
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    References listed on IDEAS

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    1. Geoff Masters, 1982. "A rasch model for partial credit scoring," Psychometrika, Springer;The Psychometric Society, vol. 47(2), pages 149-174, June.
    2. Cole, Steven M. & Tembo, Gelson, 2011. "The effect of food insecurity on mental health: Panel evidence from rural Zambia," Social Science & Medicine, Elsevier, vol. 73(7), pages 1071-1079.
    3. Nanama, Siméon & Frongillo, Edward A., 2012. "Altered social cohesion and adverse psychological experiences with chronic food insecurity in the non-market economy and complex households of Burkina Faso," Social Science & Medicine, Elsevier, vol. 74(3), pages 444-451.
    4. Nord, Mark & Bickel, Gary, 2002. "Measuring Children'S Food Security In U.S. Households, 1995-99," Food Assistance and Nutrition Research Reports 33801, United States Department of Agriculture, Economic Research Service.
    5. Maxwell, Daniel & Caldwell, Richard & Langworthy, Mark, 2008. "Measuring food insecurity: Can an indicator based on localized coping behaviors be used to compare across contexts?," Food Policy, Elsevier, vol. 33(6), pages 533-540, December.
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    Cited by:

    1. Vicka Kharisma & Naoya Abe, 2020. "Food Insecurity and Associated Socioeconomic Factors: Application of Rasch and Binary Logistic Models with Household Survey Data in Three Megacities in Indonesia," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 148(2), pages 655-679, April.
    2. Megan Mucioki & Bernard Pelletier & Timothy Johns & Lutta W. Muhammad & Gordon M. Hickey, 2018. "On developing a scale to measure chronic household seed insecurity in semi-arid Kenya and the implications for food security policy," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 10(3), pages 571-587, June.
    3. Ramya Ambikapathi & Jessica D. Rothstein & Pablo Peñataro Yori & Maribel Paredes Olortegui & Gwenyth Lee & Margaret N. Kosek & Laura E. Caulfield, 2018. "Food purchase patterns indicative of household food access insecurity, children’s dietary diversity and intake, and nutritional status using a newly developed and validated tool in the Peruvian Amazon," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 10(4), pages 999-1011, August.

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