Related Experiment Video
Updated: Jul 3, 2026

Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Effects of measurement on obesity and morbidity
Margot Shields1, Sarah Connor Gorber, Mark S Tremblay
1Health Information and Research Division, Statistics Canada, Ottawa, Ontario, Canada. Margot.Shields@statcan.ca
Objectives:
This article compares associations between body mass index (BMI) categories based on self-reported vers measured data with selected health conditions. The goal is to see if the misclassifications resulting from the use of self-reported data alters associations between excess body weight and these health conditions.
Methods:
The analysis is based on 2,667 respondents aged 40 years or older from the 2005 Canadian Community Health Survey (CCHS) who, during a face-to-face interview, provided self-reported values for height and weight and were then measured by trained interviewers. Multiple logistic regression analysis was used to examine associations between BMI categories (based on self-reported and measured data) and obesity-related health conditions.
Results:
On average, BMI based on self-reported height and weight was 1.3 kg/m2 lower than BMI based on measured values. Consequently, based on self-reported data, a substantial proportion of individuals with excess body weight were erroneously placed in lower BMI categories. This misclassification resulted in elevated associations between overweight/obesity and morbidity.
More Related Videos
08:30Intraperitoneal Glucose Tolerance Test, Measurement of Lung Function, and Fixation of the Lung to Study the Impact of Obesity and Impaired Metabolism on Pulmonary Outcomes
Published on: March 15, 2018
13:09Segmentation and Measurement of Fat Volumes in Murine Obesity Models Using X-ray Computed Tomography
Published on: April 4, 2012
Related Concept Videos
Obesity
Drug Dosing: Obese Patients
Pharmacokinetics in Obese Patients: Drug Absorption and Distribution
Pharmacokinetics in Obese Patients: Drug Metabolism and Excretion
Regression Toward the Mean
Bias in Epidemiological Studies