Table of Contents
Epidemiology Research International
Volume 2013, Article ID 890762, 7 pages
http://dx.doi.org/10.1155/2013/890762
Research Article

Using Correction Equations Based on Measured Height and Weight Weakens Associations between Obesity Based on Self-Reports and Chronic Diseases

1School of Nursing, Memorial University, St. John’s, NL, Canada A1B 3V6
2Surveillance and Epidemiology Unit, Cancer Care Nova Scotia, Halifax, NS, Canada B3H 2Y9
3Center for Chronic Disease Prevention and Control, Public Health Agency of Canada, Ottawa, ON, Canada K1A OK9

Received 10 November 2012; Revised 26 December 2012; Accepted 28 December 2012

Academic Editor: Michael Leitzmann

Copyright © 2013 Cynthia L. Murray et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Objective. Researchers have established a preponderance of height overestimation among men and weight underestimation among women in self-reported anthropometric data, which skews obesity prevalence data and obscures obesity-chronic disease relationships. The objective of this study was to reevaluate associations between obesity and chronic diseases using body mass index (BMI) correction equations derived from measured data. Methods. Measured height and weight (MHW) data were collected on a subsample of the 17,126 Atlantic Canadians who participated in the 2007-2008 Canadian Community Health Survey (CCHS). To obtain corrected BMI estimates for the 17,126 adults, correction equations were developed in the MHW subsample and multiple regression procedures were used to model BMI. To test obesity-chronic disease relationships, logistic regression models were utilized. Results. The correction procedure eliminated statistically significant relations ( ) between obesity and chronic bronchitis and obesity and stroke. Also, correction attenuated many relationships between adiposity and chronic disease. For example, among obese adults, there was a 13%, 12%, and 7% reduction in the adjusted odds ratios for asthma, urinary incontinence, and cardiovascular disease, respectively. Conclusion. Further research is needed to fully understand how the usage of self-reported data alters our understanding of the relationships between overweight or obesity and chronic diseases.