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Reporting error in weight and height among the elderly: Implications and recommendations for estimating healthcare costs

Author

Listed:
  • Johanna Catherine Maclean

    (Department of Economics, Temple University)

  • Asia Sikora Kessler

    (Department of Health Promotion, Social and Economic Behavioral Health, University of Nebraska Medical Center)

Abstract

A large literature has examined the healthcare consequences of obesity. A major barrier to careful study of these consequences is reliance on self-reported measures of weight and height. Previous research has developed algorithms to adjust for such error among working age adults. In this study we consider elderly adults, a group likely to differ in reporting error patterns from working age adults due to involuntary weight loss and changes in cognition, muscle mass, and bone density. We first provide evidence on the degree and type of reporting error in this population. Second, we consider how well standard approaches to adjusting for such error preform in an elderly population in terms of estimating obesity prevalence and regression coefficients. These findings have direct implications for evaluating anti-obesity programs among the elderly and estimating the obesity-related healthcosts to the Medicare program.

Suggested Citation

  • Johanna Catherine Maclean & Asia Sikora Kessler, 2015. "Reporting error in weight and height among the elderly: Implications and recommendations for estimating healthcare costs," DETU Working Papers 1501, Department of Economics, Temple University.
  • Handle: RePEc:tem:wpaper:1501
    as

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    File URL: http://www.cla.temple.edu/RePEc/documents/DETU_15_01.pdf
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    References listed on IDEAS

    as
    1. Cawley, John & Maclean, Johanna Catherine & Hammer, Mette & Wintfeld, Neil, 2015. "Reporting error in weight and its implications for bias in economic models," Economics & Human Biology, Elsevier, vol. 19(C), pages 27-44.
    2. Courtemanche, Charles & Pinkston, Joshua C. & Stewart, Jay, 2015. "Adjusting body mass for measurement error with invalid validation data," Economics & Human Biology, Elsevier, vol. 19(C), pages 275-293.
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    More about this item

    Keywords

    Healthcare costs; Medicare; reporting error; validation data; weight; height; obesity; elderly adults;
    All these keywords.

    JEL classification:

    • I1 - Health, Education, and Welfare - - Health

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