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The Implications of Self-Reported Body Weight and Height for Measurement Error in BMI

Author

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  • Davillas, Apostolos

    (University of Macedonia)

  • Jones, Andrew M.

    (University of York)

Abstract

We designed an experiment to explore the extent of measurement error in body mass index (BMI), when based on self-reported body weight and height. We find that there is a systematic age gradient in the reporting error in BMI, while there is limited evidence of systematic associations with gender, education and income. This is reassuring evidence for the use of self-reported BMI in studies that use it as an outcome, for example, to analyse socioeconomic gradients in obesity. However, our results suggest a complex structure of non-classical measurement error in BMI, depending on both individuals' and within-household peers' true BMI. This may bias studies that use BMI based on self-reported data as a regressor. Common methods to mitigate reporting error in BMI using predictions from corrective equations do not fully eliminate reporting heterogeneity associated with individual and within-household true BMI. Overall, the presence of non-classical error in BMI highlights the importance of collecting measured body weight and height data in large social science datasets.

Suggested Citation

  • Davillas, Apostolos & Jones, Andrew M., 2021. "The Implications of Self-Reported Body Weight and Height for Measurement Error in BMI," IZA Discussion Papers 14695, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp14695
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    References listed on IDEAS

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    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. Michaela Benzeval & Edith Aguirre & Meena Kumari, 2023. "Understanding Society: health, biomarker and genetic data," Fiscal Studies, John Wiley & Sons, vol. 44(4), pages 399-415, December.
    3. Gensowski, Miriam & Gørtz, Mette, 2024. "The education-health gradient: Revisiting the role of socio-emotional skills," Journal of Health Economics, Elsevier, vol. 97(C).
    4. Donal O’Neill & Olive Sweetman, 2013. "The consequences of measurement error when estimating the impact of obesity on income," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 2(1), pages 1-20, December.
    5. Gil, Joan & Mora, Toni, 2011. "The determinants of misreporting weight and height: The role of social norms," Economics & Human Biology, Elsevier, vol. 9(1), pages 78-91, January.
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    Cited by:

    1. Apostolos Davillas & Victor Hugo Oliveira & Andrew M. Jones, 2024. "A model of errors in BMI based on self-reported and measured anthropometrics with evidence from Brazilian data," Empirical Economics, Springer, vol. 67(5), pages 2371-2410, November.
    2. Olbrich, Lukas & Kosyakova, Yuliya & Sakshaug, Joseph W., 2022. "The reliability of adult self-reported height: The role of interviewers," Economics & Human Biology, Elsevier, vol. 45(C).

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    More about this item

    Keywords

    measurement error; experiment; BMI; reporting bias;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General

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