Objectives. To determine whether obesity correction equations for the Canadian general population, which are dependent on the prevalence of obesity, are appropriate for use in Atlantic Canada, which has the highest obesity rates in the country. Also, to compare the accuracy of the national equations to equations developed specifically for the Atlantic Canadian population. Methods. The dataset consisted of Canadian Community Health Survey (CCHS) 2007-2008 data collected on 17,126 Atlantic Canadians and a subsample of adults, who provided measured height and weight (MHW) data. Atlantic correction equations were developed in the MHW subsample. Using separate multiple regression models for men and women, self-reported body mass index (BMI) was corrected by multiplying the self-reported estimate by its corresponding model coefficient and adding the model intercept. Paired t-tests were used to determine whether corrected mean BMI values were significantly more accurate (i.e., closer to measured data) than the equivalent means based on self-reported data. The analyses were repeated using the national equations. Results. Both the Atlantic and the national equations yielded corrected obesity estimates that were significantly more accurate than those based on self-report. Conclusion. The results provide some evidence of the generalizability of the national equations to atypical regions of Canada. 1. Introduction Obesity is a major cause of morbidity in Canada and in many parts of the world and it is increasing worldwide . As indicated by a body mass index (BMI) greater than or equal to 30？kg/m2, obesity is a risk factor for cardiovascular disease, type 2 diabetes, several types of cancer, asthma, gallbladder disease, osteoarthritis, and chronic back pain [1, 2]. Class II+ obesity (BMI ≥ 35？kg/m2) is also associated with an increased risk of all-cause mortality . Obesity and its associated comorbidities exact a heavy toll on health care systems and expenditures. In Canada, the 2006 direct medical cost of overweight and obesity was $6.0 billion . Against a global background comprising of 500 million obese adults , obesity has reached a historic high in Canada with one-quarter of adults and 9% of children meeting the definition . Federal government statistical agencies, such as Statistics Canada and the National Center for Health Statistics, use large population-based studies to track nationwide obesity trends. Researchers usually use the BMI as a proxy to gauge obesity in these large national studies. According to Health Canada , although the BMI
D. P. Guh, W. Zhang, N. Bansback, Z. Amarsi, C. L. Birmingham, and A. H. Anis, “The incidence of co-morbidities related to obesity and overweight: a systematic review and meta-analysis,” BMC Public Health, vol. 9, article 88, pp. 1–20, 2009.
H. M. Orpana, J. M. Berthelot, M. S. Kaplan, D. H. Feeny, B. McFarland, and N. A. Ross, “BMI and mortality: results from a national longitudinal study of Canadian adults,” Obesity, vol. 18, no. 1, pp. 214–218, 2010.
Health Canada, “Canadian guidelines for body weight classification in adults: Quick reference tool for professionals,” 2008, http://www.hc-sc.gc.ca/fn-an/nutrition/weights-poids/guide-ld-adult/cg_quick_ref-ldc_rapide_ref-eng.php.
S. Connor Gorber, M. Shields, M. S. Tremblay, and I. McDowell, “The feasibility of establishing correction factors to adjust self-reported estimates of obesity,” Health Reports, vol. 19, no. 3, pp. 71–82, 2008.
A. J. Hayes, P. M. Clarke, and T. W. C. Lung, “Change in bias in self-reported body mass index in Australia between 1995 and 2008 and the evaluation of correction equations,” Population Health Metrics, vol. 9, Article ID 53, 2011.
A. Mozumdar and G. Liguori, “Correction equations to adjust self-reported height and weight for obesity estimates among college students,” Research Quarterly for Exercise and Sport, vol. 82, no. 3, pp. 391–399, 2011.
R. B. Jain, “Regression models to predict corrected weight, height and obesity prevalence from self-reported data: data from BRFSS 1999–2007,” International Journal of Obesity, vol. 34, no. 11, pp. 1655–1664, 2010.
M. Nyholm, B. Gullberg, J. Merlo, C. Lundqvist-Persson, L. R？stam, and U. Lindblad, “The validity of obesity based on self-reported weight and height: implications for population studies,” Obesity, vol. 15, no. 1, pp. 197–208, 2007.
M. Ezzati, H. Martin, S. Skjold, S. Vander Hoorn, and C. J. L. Murray, “Trends in national and state-level obesity in the USA after correction for self-report bias: analysis of health surveys,” Journal of the Royal Society of Medicine, vol. 99, no. 5, pp. 250–257, 2006.
M. Shields, S. Connor Gorber, I. Janssen, and M. S. Tremblay, “Bias in self-reported estimates of obesity in Canadian health surveys: an update on correction equations for adults,” Health Reports, vol. 22, no. 3, pp. 35–45, 2011.
J. Pedro, “Study on the reliability of the weighing scales used in the 2008 Canadian Community Health Survey (CCHS) for the measured height and weight (MHW) module,” 2009, http://www.statcan.gc.ca/imdb-bmdi/document/3226_D63_T9_V1-eng.htm.
A. Chiolero, I. Peytremann-Bridevaux, and F. Paccaud, “Associations between obesity and health conditions may be overestimated if self-reported body mass index is used,” Obesity Reviews, vol. 8, no. 4, pp. 373–374, 2007.
F. J. Elgar and J. M. Stewart, “Validity of self-report screening for overweight and obesity: evidence from the Canadian community health survey,” Canadian Journal of Public Health, vol. 99, no. 5, pp. 423–427, 2008.
J. L. Grant, K. C. MacKay, P. M. Manuel, and T. L. F. McHugh, “Barriers to optimizing investments in the built environment to reduce youth obesity: policy-maker perspectives,” Canadian Journal of Public Health, vol. 101, no. 3, pp. 237–240, 2010.