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The feasibility of establishing correction factors to adjust self-reported estimates of obesity

by Sarah Connor Gorber, Margot Shields, Mark S. Tremblay and Ian McDowell

Abstract
Keywords
Findings
Authors
Acknowledgements

Abstract

Background

This study examines the feasibility of developing correction factors to adjust self-reported measures of body mass index (BMI) to more closely approximate measured values. 

Data and methods

Data are from the 2005 Canadian Community Health Survey (subsample 2), in which respondents were asked to report their height and weight, and were subsequently measured. Regression analyses were used to determine which socio-demographic and health characteristics were associated with the discrepancies between self-reported and measured values. The sample was then split into two groups. In the first, self-reported BMI and the predictors of the discrepancies were regressed on measured BMI. Correction equations were generated using all predictor variables that were significant at the p<0.05 level. These correction equations were then tested in the second group to derive estimates of sensitivity, specificity and obesity prevalence. Logistic regression was used to examine relationships between self-reported, measured and corrected BMI and obesity-related health conditions.   

Results

Corrected estimates provide more accurate measures of obesity prevalence, mean BMI and sensitivity levels (percentage correctly classified). In almost all cases, associations between BMI and health conditions are more accurate when based on corrected versus self-reported values.

Keywords

Bias, body mass index, direct measure, measurement error, obesity, overweight, prevalence, self-report

Findings

Obesity is a public health problem in both the developed and developing world. Globally, an estimated 400 million people are obese. In Canada, the prevalence is estimated to be 23% in adults and 8% in children, with rates expected to rise in coming years. The costs associated with obesity represent approximately 2% of Canada's total health care expenditures. [Full text]

Authors

Sarah Connor Gorber (613-951-1193; Sarah.ConnorGorber@statcan.gc.ca) and Margot Shields (613-951-4177; Margot.Shields@statcan.gc.ca) are with the Health Information and Research Division at Statistics Canada, Ottawa, Ontario, K1A 0T6. Mark S. Tremblay is with the Children's Hospital of Eastern Ontario Research Institute. Ian McDowell is with the Department of Epidemiology and Community Medicine, University of Ottawa.

Acknowledgements

The authors thank Julie Bernier for her methodological assistance and members of the Health Information and Research Division at Statistics Canada for their input on this research.