IDEAS home Printed from https://ideas.repec.org/p/ags/uerstb/338949.html
   My bibliography  Save this paper

Assessment and Adjustment of Body Weight Measures in Scanner Data

Author

Listed:
  • Young, Sabrina K.
  • Page, Elina T.
  • Okrent, Abigail
  • Sweitzer, Megan

Abstract

Household scanner data are a rich resource for understanding food purchasing habits in the United States. The IRI Consumer Network provides a detailed account of the retail food purchases for a large, nationally representative sample. These data further include self-reported height and weight for a subset of households that complete the MedProfiler survey. Together, the Consumer Network and MedProfiler surveys provide a unique opportunity to study the relationship between diet and obesity. This report includes an assessment of the MedProfiler height and weight data in determining body mass index (BMI) for children and adults, using MedProfiler data from 2012 to 2018 and National Health and Nutrition Examination Survey data from 2011–2012 to 2017–2018. In addition, because self-reported height and weight may often be misreported in survey data, the report explores adjustment methods to account for any self-reporting measurement bias. Finally, since food-purchase data are collected at the household level, the report includes a comparison of methods for defining the obesity status of a household.

Suggested Citation

  • Young, Sabrina K. & Page, Elina T. & Okrent, Abigail & Sweitzer, Megan, 2023. "Assessment and Adjustment of Body Weight Measures in Scanner Data," Technical Bulletins 338949, United States Department of Agriculture, Economic Research Service.
    • Handle: RePEc:ags:uerstb:338949
    DOI: 10.22004/ag.econ.338949
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/338949/files/tb-1960.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.338949?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. Mancino, Lisa & Guthrie, Joanne & Ver Ploeg, Michele & Lin, Biing-Hwan, 2018. "Nutritional Quality of Foods Acquired by Americans: Findings From USDA's National Household Food Acquisition and Purchase Survey," Economic Information Bulletin 276248, United States Department of Agriculture, Economic Research Service.
    2. Carlson, Andrea C. & Page, Elina Tselepidakis & Zimmerman, Thea Palmer & Tornow, Carina E. & Hermansen, Sigurd, 2019. "Linking USDA Nutrition Databases to IRI Household-Based and Store-Based Scanner Data," Technical Bulletins 291970, United States Department of Agriculture, Economic Research Service.
    3. Volpe, Richard & Kuhns, Annemarie & Jaenicke, Ted, 2017. "Store Formats and Patterns in Household Grocery Purchases," Economic Information Bulletin 256712, United States Department of Agriculture, Economic Research Service.
    4. Matthias Staudigel, 2012. "How do obese people afford to be obese? Consumption strategies of Russian households," Agricultural Economics, International Association of Agricultural Economists, vol. 43(6), pages 701-714, November.
    5. Sweitzer, Megan & Brown, Derick & Karns, Shawn & Muth, Mary K. & Siegel, Peter & Zhen, Chen, 2017. "Food-at-Home Expenditures: Comparing Commercial Household Scanner Data From IRI and Government Survey Data," Technical Bulletins 291969, United States Department of Agriculture, Economic Research Service.
    6. Chen Zhen & Eric A. Finkelstein & James M. Nonnemaker & Shawn A. Karns & Jessica E. Todd, 2014. "Predicting the Effects of Sugar-Sweetened Beverage Taxes on Food and Beverage Demand in a Large Demand System," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(1), pages 1-25.
    7. Kuhns, Annemarie & Saksena, Michelle, 2017. "Food Purchase Decisions of Millennial Households Compared to Other Generations," Economic Information Bulletin 291931, United States Department of Agriculture, Economic Research Service.
    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. Cleary, Rebecca & Liu, Yizao & Carlson, Andrea C., 2022. "Differences in the Distribution of Nutrition Between Households Above and Below Poverty," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322267, Agricultural and Applied Economics Association.
    2. Hayden Stewart & Fred Kuchler & William Hahn, 2021. "Is competition among soft drinks, juices, and other major beverage categories responsible for reducing Americans' milk consumption?," Agribusiness, John Wiley & Sons, Ltd., vol. 37(4), pages 731-748, October.
    3. Chen Zhen & Mary Muth & Abigail Okrent & Shawn Karns & Derick Brown & Peter Siegel, 2019. "Do differences in reported expenditures between household scanner data and expenditure surveys matter in health policy research?," Health Economics, John Wiley & Sons, Ltd., vol. 28(6), pages 782-800, June.
    4. Alyssa J. Moran & Yuxuan Gu & Sasha Clynes & Attia Goheer & Christina A. Roberto & Anne Palmer, 2020. "Associations between Governmental Policies to Improve the Nutritional Quality of Supermarket Purchases and Individual, Retailer, and Community Health Outcomes: An Integrative Review," IJERPH, MDPI, vol. 17(20), pages 1-23, October.
    5. Joey Blumberg & Gary Thompson, 2022. "Nonparametric segmentation methods: Applications of unsupervised machine learning and revealed preference," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(3), pages 976-998, May.
    6. Zach Conrad & Alexandra Stern & David C. Love & Meredith Salesses & Ashley Cyril & Acree McDowell & Nicole Tichenor Blackstone, 2021. "Data Integration for Diet Sustainability Analyses," Sustainability, MDPI, vol. 13(14), pages 1-22, July.
    7. Allais, Olivier & Etilé, Fabrice & Lecocq, Sébastien, 2015. "Mandatory labels, taxes and market forces: An empirical evaluation of fat policies," Journal of Health Economics, Elsevier, vol. 43(C), pages 27-44.
    8. Yu Chen & Chen Zhen, 2022. "The potential impact of reducing sodium in packaged food: The case of the Chinese instant noodles market," Agribusiness, John Wiley & Sons, Ltd., vol. 38(1), pages 3-20, January.
    9. Abay, Kibrom A. & Ibrahim, Hosam & Breisinger, Clemens, 2022. "Food policies and obesity in low- and middle-income countries," World Development, Elsevier, vol. 151(C).
    10. Jakina Debnam, 2017. "Selection Effects and Heterogeneous Demand Responses to the Berkeley Soda Tax Vote," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(5), pages 1172-1187.
    11. Bonnet, Céline & Réquillart, Vincent, 2023. "The effects of taxation on the individual consumption of sugar-sweetened beverages," Economics & Human Biology, Elsevier, vol. 51(C).
    12. Laura Cornelsen & Rosemary Green & Rachel Turner & Alan D. Dangour & Bhavani Shankar & Mario Mazzocchi & Richard D. Smith, 2015. "What Happens to Patterns of Food Consumption when Food Prices Change? Evidence from A Systematic Review and Meta‐Analysis of Food Price Elasticities Globally," Health Economics, John Wiley & Sons, Ltd., vol. 24(12), pages 1548-1559, December.
    13. Zarko Kalamov, 2020. "A sales tax is better at promoting healthy diets than the fat tax and the thin subsidy," Health Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 353-366, March.
    14. Boonsaeng, Tullaya & Carpio, Carlos E., 2017. "Budget Allocation Patterns of American Household across Income Level in the 21 Century," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258245, Agricultural and Applied Economics Association.
    15. J Alai Quiroz-Reyes & Jesús Enrique Morales-Ríos & Adriana Vargas-Flores & Néstor A Sánchez-Ortiz & M Arantxa Colchero, 2025. "Are taxes to sugar-sweetened beverages and non-essential energy dense food implemented in Mexico regressive?," PLOS ONE, Public Library of Science, vol. 20(3), pages 1-13, March.
    16. Violeta Chacon & Guillermo Paraje & Joaquin Barnoya & Frank J Chaloupka, 2018. "Own-price, cross-price, and expenditure elasticities on sugar-sweetened beverages in Guatemala," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-12, October.
    17. Hovhannisyan, Vardges, 2016. "New Evidence On The Structure Of Food Demand In China: An Easi Demand Model Estimated Via Panel Data Techniques," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236889, Agricultural and Applied Economics Association.
    18. Zarko Kalamov, 2021. "Evaluating Marginal Internalities: A New Approach," CESifo Working Paper Series 9476, CESifo.
    19. Okrent, Abigail & Sweitzer, Megan, 2016. "Obesity as a Modifier of Price Sensitivity in the United States," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236251, Agricultural and Applied Economics Association.
    20. Zeballos, Eliana & Dong, Xiao & Islamaj, Ergys, 2023. "A Disaggregated View of Market Concentration in the Food Retail Industry," USDA Miscellaneous 333546, United States Department of Agriculture.

    More about this item

    Keywords

    ;
    ;
    ;

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ags:uerstb:338949. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/ersgvus.html .

    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.