Adjusting Divergences between Self-reported and Measured Height and Weight in an Adult Canadian Population
Abstract:Objective: To develop algorithm equations that could be used to adjust self-reported height and weight to elicit better estimates of actual BMI. Methods: Linear regression analyses were performed to generate equations that could predict actual height and weight from self-reported data collected through telephone interviews on a representative sample of Canadians aged 18 years or older. Results: There were systematic biases in self-reported height and weight, leading to an underestimation of BMI. The application of our calibration equations to self-reported data produced closer estimates to actual rates of overweight and obesity. Discussion: We advocate the use of our correction equation whenever dealing with self-reported height and weight from telephone surveys to avoid potential distortions in estimating obesity prevalence.
Document Type: Research Article
Affiliations: 1: University of Alberta, School of Public Health, Edmonton, AB, Canada. firstname.lastname@example.org 2: The University of Alberta, School of Public Health, Edmonton, AB, Canada 3: University of Newcastle, Australia
Publication date: November 1, 2013
The American Journal of Health Behavior seeks to improve the quality of life through multidisciplinary health efforts in fostering a better understanding of the multidimensional nature of both individuals and social systems as they relate to health behaviors.
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