文章基本信息

标题：Using Correction Equations Based on Measured Height and Weight Weakens Associations between Obesity Based on Self-Reports and Chronic Diseases
本地全文：下载
作者：Cynthia L. Murray ; Gordon W. Walsh ; Sarah Connor Gorber 等
期刊名称：Epidemiology Research International
印刷版ISSN：2090-2972
电子版ISSN：2090-2980
出版年度：2013
卷号：2013
DOI：10.1155/2013/890762
出版社：Hindawi Publishing Corporation
摘要：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.