Estimating obesity rates in the presence of measurement error

Arbeitspapier

Reliable measures of obesity are essential in order to develop effective policies to tackle the costs of obesity. In this paper we examine what, if anything, we can learn about obesity rates using self-reported BMI once we allow for possible measurement error. 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. 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.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: IZA Discussion Papers ; No. 7288

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Estimation: General ; Single Equation Models: Single Variables: Instrumental Variables (IV) Estimation ; Health and Inequality
• Thema: obesity ; measurement error ; bounds

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): O'Neill, Donal ; Sweetman, Olive B.
• Ereignis: Veröffentlichung
• (wer): Institute for the Study of Labor (IZA)
• (wo): Bonn
• (wann): 2013

Weitere Informationen

• Handle: http://hdl.handle.net/10419/71653
• Letzte Aktualisierung: 10.03.2025, 11:44 MEZ