Estimating Obesity Rates in Europe in the Presence of Self-Reporting Errors

Donal O'Neill and Olive Sweetman

Economics Department Working Paper Series from Department of Economics, National University of Ireland - Maynooth

Abstract: Reliable measures of obesity are essential in order to develop effective policies to tackle the costs of obesity. We examine what, if anything, we can learn about obesity rates using self-reported BMI once we allow for possible measurement error. Existing approaches that correct for self-reporting errors often require strong assumptions. In this paper we combine self-reported data on BMI with estimated misclassification rates obtained from auxiliary data to derive upper and lower bounds for the population obesity rate for ten European countries using minimal assumptions on the error process. For men it is possible to obtain meaningful comparisons across countries even after accounting for measurement error. In particular the self-reported data identifies a set of low obesity countries consisting of Denmark, Ireland, Italy, Greece and Portugal and a set of high obesity countries consisting of Spain and Finland. However, it is more difficult to rank countries by female obesity rates. Meaningful rankings only emerge when the misclassification rate is bounded at a level that is much lower than that observed in auxiliary data. A similar limit on misclassification rates is also needed before we can begin to observe meaningful gender differences in obesity rates within countries.

Keywords: Obesity; Self-Reporting Errors; Bounds (search for similar items in EconPapers)
JEL-codes: C38 I18 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2013
New Economics Papers: this item is included in nep-hea
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Citations: View citations in EconPapers (3)

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Working Paper: Estimating Obesity Rates in the Presence of Measurement Error (2013)
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