Adjusting divergences between self-reported and measured height and weight in an adult Canadian population

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