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      Can body mass index, waist circumference, waist-hip ratio and waist-height ratio predict the presence of multiple metabolic risk factors in Chinese subjects?

      research-article
      1 , , 1 , 1 , 1 , 1
      BMC Public Health
      BioMed Central

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          Abstract

          Background

          Obesity is associated with metabolic risk factors. Body mass index (BMI), waist circumference, waist-hip ratio (WHR) and waist-height ratio (WHtR) are used to predict the risk of obesity related diseases. However, it has not been examined whether these four indicators can detect the clustering of metabolic risk factors in Chinese subjects.

          Methods

          There are 772 Chinese subjects in the present study. Metabolic risk factors including high blood pressure, dyslipidemia, and glucose intolerance were identified according to the criteria from WHO. All statistical analyses were performed separately according to sex by using the SPSS 12.0.

          Results

          BMI, waist circumference and WHtR values were all significantly associated with blood pressure, glucose, triglyceride and also with the number of metabolic risk factors in both male and female subjects (all of P < 0.05). According to receiver operating characteristic (ROC) analysis, the area under curve values of BMI, waist circumference and WHtR did not differ in male (0.682 vs. 0.661 vs. 0.651) and female (0.702 vs. 0.671 vs. 0.674) subjects, indicating that the three values could be useful in detecting the occurrence of multiple metabolic risk factors. The appropriate cut-off values of BMI, waist circumference and WHtR to predict the presence of multiple metabolic risk factors were 22.85 and 23.30 kg/m2 in males and females, respectively. Those of waist circumference and WHtR were 91.3cm and 87.1cm, 0.51 and 0.53 in males and females, respectively.

          Conclusion

          The BMI, waist circumference and WHtR values can similarly predict the presence of multiple metabolic risk factors in Chinese subjects.

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          Most cited references28

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          Measuring the accuracy of diagnostic systems.

          J Swets (1988)
          Diagnostic systems of several kinds are used to distinguish between two classes of events, essentially "signals" and "noise". For them, analysis in terms of the "relative operating characteristic" of signal detection theory provides a precise and valid measure of diagnostic accuracy. It is the only measure available that is uninfluenced by decision biases and prior probabilities, and it places the performances of diverse systems on a common, easily interpreted scale. Representative values of this measure are reported here for systems in medical imaging, materials testing, weather forecasting, information retrieval, polygraph lie detection, and aptitude testing. Though the measure itself is sound, the values obtained from tests of diagnostic systems often require qualification because the test data on which they are based are of unsure quality. A common set of problems in testing is faced in all fields. How well these problems are handled, or can be handled in a given field, determines the degree of confidence that can be placed in a measured value of accuracy. Some fields fare much better than others.
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            Waist circumference and not body mass index explains obesity-related health risk.

            The addition of waist circumference (WC) to body mass index (BMI; in kg/m(2)) predicts a greater variance in health risk than does BMI alone; however, whether the reverse is true is not known. We evaluated whether BMI adds to the predictive power of WC in assessing obesity-related comorbidity. Subjects were 14 924 adult participants in the third National Health and Nutrition Examination Survey, grouped into categories of BMI and WC in accordance with the National Institutes of Health cutoffs. Odds ratios for hypertension, dyslipidemia, and the metabolic syndrome were compared for overweight and class I obese BMI categories and the normal-weight category before and after adjustment for WC. BMI and WC were also included in the same regression model as continuous variables for prediction of the metabolic disorders. With few exceptions, overweight and obese subjects were more likely to have hypertension, dyslipidemia, and the metabolic syndrome than were normal-weight subjects. After adjustment for WC category (normal or high), the odds of comorbidity, although attenuated, remained higher in overweight and obese subjects than in normal-weight subjects. However, after adjustment for WC as a continuous variable, the likelihood of hypertension, dyslipidemia, and the metabolic syndrome was similar in all groups. When WC and BMI were used as continuous variables in the same regression model, WC alone was a significant predictor of comorbidity. WC, and not BMI, explains obesity-related health risk. Thus, for a given WC value, overweight and obese persons and normal-weight persons have comparable health risks. However, when WC is dichotomized as normal or high, BMI remains a significant predictor of health risk.
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              How useful is body mass index for comparison of body fatness across age, sex, and ethnic groups?

              This study tested the hypothesis that body mass index (BMI) is representative of body fatness independent of age, sex, and ethnicity. Between 1986 and 1992, the authors studied a total of 202 black and 504 white men and women who resided in or near New York City, were ages 20-94 years, and had BMIs of 18-35 kg/m2. Total body fat, expressed as a percentage of body weight (BF%), was assessed using a four-compartment body composition model that does not rely on assumptions known to be age, sex, or ethnicity dependent. Statistically significant age dependencies were observed in the BF%-BMI relations in all four sex and ethnic groups (p values < 0.05-0.001) with older persons showing a higher BF% compared with younger persons with comparable BMIs. Statistically significant sex effects were also observed in BF%-BMI relations within each ethnic group (p values < 0.001) after controlling first for age. For an equivalent BMI, women have significantly greater amounts of total body fat than do men throughout the entire adult life span. Ethnicity did not significantly influence the BF%-BMI relation after controlling first for age and sex even though both black women and men had longer appendicular bone lengths relative to stature (p values < 0.001 and 0.02, respectively) compared with white women and men. Body mass index alone accounted for 25% of between-individual differences in body fat percentage for the 706 total subjects; adding age and sex as independent variables to the regression model increased the variance (r2) to 67%. These results suggest that BMI is age and sex dependent when used as an indicator of body fatness, but that it is ethnicity independent in black and white adults.
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                Author and article information

                Journal
                BMC Public Health
                BMC Public Health
                BioMed Central
                1471-2458
                2011
                13 January 2011
                : 11
                : 35
                Affiliations
                [1 ]Clinical laboratory, Shengjing Hospital of China Medical University, Shenyang 110004, PR China
                Article
                1471-2458-11-35
                10.1186/1471-2458-11-35
                3032682
                21226967
                1b5f74da-fd9a-473f-b8bc-f3a5b11ca10c
                Copyright ©2011 Liu et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 8 July 2010
                : 13 January 2011
                Categories
                Research Article

                Public health
                Public health

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