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A method for estimating physical and economic food access at high spatial resolution

Author

Listed:
  • Florencio Campomanes

    (University of Twente)

  • Michael Marshall

    (University of Twente)

  • Andrew Nelson

    (University of Twente)

Abstract

Physical and economic access to food vary spatially. Methods to map that variability at high levels of spatial detail over large areas are scarce, even though suitable datasets and methods exist. Using open-access data for Ethiopia, we developed a method to map the disparities in physical and economic food access at 1-km resolution. We selected 25 access-related variables for 486 geo-located communities from the 2018 Ethiopian Living Standards Measurement Study to create a food access index (FAI). The index was based on a weighted summation of the 25 variables from a principal component analysis (PCA). We then extrapolated the FAI to the rest of Ethiopia using a generalized additive model (GAM) to produce a 1-km resolution FAI map and used that to describe the spatial variability of food access. Economic access had a heavier weight than physical access in the FAI reflecting the fact that proximity to food markets alone is insufficient if one cannot afford food. The GAM had an R2 of 0.57 and a normalized root mean square error of 22.2% which are comparable to measures of model performance in studies that provided micro-level estimates of relative wealth. Peri-urban areas, representing 67% of the population, had relatively low food access, suggesting that these areas should be a priority for infrastructure or economic intervention. The scarcity of detailed spatial information on food access may limit the effectiveness of targeted policymaking to improve food security. The methodology developed in this study uses widely available and carefully selected datasets and can contribute to more spatially detailed estimates of food access in other countries.

Suggested Citation

  • Florencio Campomanes & Michael Marshall & Andrew Nelson, 2024. "A method for estimating physical and economic food access at high spatial resolution," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 16(1), pages 47-64, February.
    • Handle: RePEc:spr:ssefpa:v:16:y:2024:i:1:d:10.1007_s12571-023-01404-1
    DOI: 10.1007/s12571-023-01404-1
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    1. Maria Adam Nyangasa & Christoph Buck & Soerge Kelm & Mohammed Sheikh & Antje Hebestreit, 2019. "Exploring Food Access and Sociodemographic Correlates of Food Consumption and Food Insecurity in Zanzibari Households," IJERPH, MDPI, vol. 16(9), pages 1-15, May.
    2. Quynh Lê & Stuart Auckland & Hoang Boi Nguyen & Sandra Murray & Gretchen Long & Daniel R. Terry, 2015. "The Socio-Economic and Physical Contributors to Food Insecurity in a Rural Community," SAGE Open, , vol. 5(1), pages 21582440145, January.
    3. Wantchekon, Leonard & Riaz, Zara, 2019. "Mobile technology and food access," World Development, Elsevier, vol. 117(C), pages 344-356.
    4. Sven Bergau & Tim K. Loos & Orkhan Sariyev, 2022. "On- and Off-Farm Diversification and Travel Time to Markets: Linkages to Food Security in Rural Ethiopia," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 34(5), pages 2543-2560, October.
    5. Mu, Yunming & He, Xuming, 2007. "Power Transformation Toward a Linear Regression Quantile," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 269-279, March.
    6. Amin, Modhurima Dey & Badruddoza, Syed & McCluskey, Jill J., 2021. "Predicting access to healthful food retailers with machine learning," Food Policy, Elsevier, vol. 99(C).
    7. Trang Nguyen & Huong Pham Thi Mai & Marrit van den Berg & Tuyen Huynh Thi Thanh & Christophe Béné, 2021. "Interactions between Food Environment and (Un)healthy Consumption: Evidence along a Rural-Urban Transect in Viet Nam," Agriculture, MDPI, vol. 11(8), pages 1-31, August.
    8. Michele Ver Ploeg & Paula Dutko & Vince Breneman, 2015. "Measuring Food Access and Food Deserts for Policy Purposes," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 37(2), pages 205-225.
    9. Lentz, E.C. & Michelson, H. & Baylis, K. & Zhou, Y., 2019. "A data-driven approach improves food insecurity crisis prediction," World Development, Elsevier, vol. 122(C), pages 399-409.
    10. Miwa Yamaguchi & Katsuya Takahashi & Masamichi Hanazato & Norimichi Suzuki & Katsunori Kondo & Naoki Kondo, 2019. "Comparison of Objective and Perceived Access to Food Stores Associated with Intake Frequencies of Vegetables/Fruits and Meat/Fish among Community-Dwelling Older Japanese," IJERPH, MDPI, vol. 16(5), pages 1-13, March.
    11. Simon N. Wood, 2003. "Thin plate regression splines," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 95-114, February.
    12. Simon N. Wood, 2011. "Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 73(1), pages 3-36, January.
    13. Deon Filmer & Lant Pritchett, 2001. "Estimating Wealth Effects Without Expenditure Data—Or Tears: An Application To Educational Enrollments In States Of India," Demography, Springer;Population Association of America (PAA), vol. 38(1), pages 115-132, February.
    14. Jiao, J. & Moudon, A.V. & Ulmer, J. & Hurvitz, P.M. & Drewnowski, A., 2012. "How to identify food deserts: Measuring physical and economic access to supermarkets in King County, Washington," American Journal of Public Health, American Public Health Association, vol. 102(10), pages 32-39.
    15. Paulo De Marco Júnior & Caroline Corrêa Nóbrega, 2018. "Evaluating collinearity effects on species distribution models: An approach based on virtual species simulation," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-25, September.
    16. Steven Deller & Amber Canto & Laura Brown, 2015. "Rural poverty, health and food access," Regional Science Policy & Practice, Wiley Blackwell, vol. 7(2), pages 61-74, June.
    17. Liu, Jing & Shively, Gerald E. & Binkley, James K., 2014. "Access to variety contributes to dietary diversity in China," Food Policy, Elsevier, vol. 49(P1), pages 323-331.
    18. Keumseok Koh & Rebecca Reno & Ayaz Hyder, 2019. "Examining disparities in food accessibility among households in Columbus, Ohio: an agent-based model," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 11(2), pages 317-331, April.
    19. Junjie Hong & Zhaofang Chu & Qiang Wang, 2011. "Transport infrastructure and regional economic growth: evidence from China," Transportation, Springer, vol. 38(5), pages 737-752, September.
    20. Christopher Yeh & Anthony Perez & Anne Driscoll & George Azzari & Zhongyi Tang & David Lobell & Stefano Ermon & Marshall Burke, 2020. "Using publicly available satellite imagery and deep learning to understand economic well-being in Africa," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
    21. Lin, Biing-Hwan & Ver Ploeg, Michele & Kasteridis, Panagiotis & Yen, Steven T., 2014. "The roles of food prices and food access in determining food purchases of low-income households," Journal of Policy Modeling, Elsevier, vol. 36(5), pages 938-952.
    22. Candelise, Chiara & Saccone, Donatella & Vallino, Elena, 2021. "An empirical assessment of the effects of electricity access on food security," World Development, Elsevier, vol. 141(C).
    23. Bondemark, Anders, 2020. "The relationship between accessibility and price – The case of Swedish food stores," Journal of Transport Geography, Elsevier, vol. 82(C).
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