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Estimating equations to correct self‐reported height and weight: implications for prevalence of overweight and obesity in Australia
Author(s) -
Hayes Alison J.,
Kortt Michael A.,
Clarke Philip M.,
Brandrup Jason D.
Publication year - 2008
Publication title -
australian and new zealand journal of public health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.946
H-Index - 76
eISSN - 1753-6405
pISSN - 1326-0200
DOI - 10.1111/j.1753-6405.2008.00306.x
Subject(s) - overweight , obesity , body mass index , medicine , population , statistics , demography , standard error , mathematics , environmental health , endocrinology , sociology
Objective:To derive correction equations based on nationally representative data, for the error associated with self‐reported height and weight and to apply these to recent estimates of overweight and obesity in the Australian adult population.Methods:Linear regression was used to derive correction equations to predict reporting error on height, weight and body mass index (BMI) for 8,435 adults, aged 20 and over, who had their height and weight accurately measured as participants of the 1995 National Nutrition Survey (NNS) and who had also supplied self‐reported information within the 1995 National Health Survey (NHS).Results:Evaluation of different correction algorithms suggests that simple correction equations for height and weight (each with one independent variable) are the most useful in the prediction of corrected prevalence of overweight and obesity. Applying these equations to nationally representative data suggests that the prevalence of overweight and obesity (BMI>=25) in Australia in 2004/05 was 66% compared with the value of 54% determined from self‐reported data.Conclusion:We present a simple and reliable method for correcting true prevalence of overweight and obesity from self‐reported data.Implications:In order to get realistic estimates of overweight and obesity in Australia, either measured height and weight data should be collected directly, or equations to correct for self report error should be used.

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