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BMI, Waist-to-hip ratio, waist circumference, waist-to-height ratio – how should we define obesity?

Dr. med. Harald Jörn Schneider

Max Planck Insitute of Psychiatry

Internal Medicine/Endocrinology and Clinical Chemistry

Kraepelinstr. 10

80804 Munich, Germany

email: schneider@mpipsykl.mpg.de

fax: +49 89 30622 605

phone: +49 89 30622 270

It has long been known that excess body fat is associated with increased cardiovascular risk. The WHO recommends the use of the body mass index (BMI) to define overweight and obesity, even though it also encourages measures of abdominal obesity. In the recent years it has become clear that mainly visceral, rather than subcutanuous fat, is associated with cardiovascular risk. Thus, it seems obvious that measures of abdominal obesity should be more accurate in determining the amount of dangerous excess body fat than simple BMI. But is this really the case, and if so, which measure should we use?

Evidence from the literature

The National Cholesterol Education Program (NCEP) has adopted waist circumference for definition of the metabolic syndrome [1], based on the data from Lean et al. [2]. A recent, international case-control study found that the waist-to-hip ratio (WHR) predicts myocardial infarction better than BMI or other anthropometric parameters [3] and an accompanying article already recommended to universally replace the BMI with the WHR [4]. Other studies found that waist-to height ratio (WHtR) shows the best association with cardiovascular risk factors [5,6].

Thus, to better understand the subject, we wanted to compare the ability of several anthropometric measures of obesity to predict prevalent cardiovascular risk.

Findings from our studies

In one analysis, we studied 5,377 subjects without artherosclerotic disease, aged 20-79 years, from the DETECT study [7]. The DETECT study is a nationally representative cross-sectional study in primary care in Germany with a prospective substudy (detect-studie.de). It focuses on cardiovascular risk factors and diabetes. In all patients, the treating primary care physicians took a detailed patient history, sampled blood, and measured blood pressure, weight, height, and waist and hip circumferences according to standardized, written instructions. We calculated BMI, WHR (waist circumference divided by hip circumference), and WHtR (waist circumference divided by body height) from the obtained measurements. In addition to these, we also compared waist and hip circumference. We used receiver operating characterstics (ROC) analysis to assess how well the five different anthopometric parameters separated between subjects affected by several cardiovascular risk factors and those without. ROC analysis is used to compare the accuracy of a diagnostic test to separate between affected and non-affected subjects. A ROC curve can be drawn on a diagram displaying sensitivity on the Y-axis and 1-specifity on the X-axis. The higher the area under the ROC curve is, the better the test separates between affected and non-affected subjects. Thus, an area under the ROC curve of 1 indicates perfect separation and 0.5 indicates no separation at all. With this method we compared which anthropometric parameter was best associated to type 2 diabetes, dyslipidemia, and the presence of at least two of five criteria constituting the metabolic syndrome [1].

We found that WHtR was significantly better than the other parameters in predicting metabolic syndrome, type 2 diabetes, and dyslipidemia in women and type 2 diabetes and dyslipidemia in men. No other anthropometric was significantly better for any other cardiovascular risk factor. We repeated these analysis in the age groups of 20-44, 45-65, and 66-79 years. There were no significant findings in these age subgroups. Interestingly however, in the age groups that were described to be at particular risk for new onset of cardiovascular events by the NCEP [1] (35-65 years for men and 45-75 years for women), we also found significantly better prediction of the WHtR for dyslipidemia in both sexes [7].

Additionally, we used another method to allow for adjustment of confounding factors: we calculated the adjusted odds ratios for the above mentioned risk factors with an increase of the respective anthropometric parameter of 1 standard deviation. With this method, we also found the odds ratios of the WHtR slightly higher than other parameters in men and the waist circumference slightly better than the other measures in women [7].

To find out if these findings also hold true in larger sample, we also performed a similar analysis in the total sample of the DETECT study, including 48,353 subjects [8]. In this study, all assessments mentioned above, apart from blood sampling, were performed. We analyzed the same anthropometric parameters and the health conditions coronary artery disease, type 2 diabetes, dyslipidemia, and hypertension as indicated by the treating primary care physicians. We divided the anthropometric parameters in quintiles and calculated the odds ratios for these health conditions in the fifth quintile of the respective parameter, compared to the first quintile. In this analysis, apart from hypertension, which was best predicted by BMI, waist-to-height ratio also predicted all other disorders slightly better than BMI and other anthropometric measures [8]. In all analyses, the WHR showed the weakest association with all cardiovascular risk conditions [7,8].

Conclusions

In our studies we have shown that WHtR, and to some degree waist circumference, are better predictors of most cardiovascular risk conditions than other parameters, including BMI. Even though, most of these differences are rather small, our findings show that WHtR and waist circumference are clearly superior to WHR in predicting cardiovascular risk. This is in line with the findings of Ashwell et al. and Ho et al. [5,6] but contradiction to the findings of Yusuf et al. [3]. Differences in study design might play a role in these diverging findings. We studied unselected primary care patients, whereas in the latter study, a case-control design was used. Controls were recruited mainly from other hospital wards. It cannot be ruled out that other diseases might have affected the anthropometric measures in controls, leading to potential bias.

Clearly, however, data from the literature and from our studies indicate that measures of abdominal obesity predict cardiovascular risk better than BMI. Yet , the question on what parameter to use is still matter of debate and large-scale, prospective studies are needed to give a final answer.

References

1. Anonymous 2001 Executive summary of the third report of the national cholesterol education program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III). JAMA 285:2486 – 2497

2. Lean MEJ, Han TS, Morrison CE 1995 Waist circumference as a measure for indicating need for weight management. BMJ 311:158-161

3. Yusuf S, Hawken S, Ounpuu S, et al.; INTERHEART Study Investigators 2005 Obesity and the risk of myocardial infarction in 27,000 participants from 52 countries: a case-control study. Lancet 366:1640-1649

4. Kragelund C, Omland T. A farewell to body-mass index? Lancet. 2005 366:1589-91

5. Ashwell M, Lejeune S, McPherson K. Ratio of waist circumference to height may be better indicator of need for weight management. BMJ. 1996 Feb 10;312(7027):377

6. Ho, S, Lam T, Janus ED; for the Hong Kong Cardiovascular Risk Factor Prevalence Study Steering Committee 2003 Waist to stature ratio is more strongly associated with cardiovascular risk factors than other simple anthropometric indices. Ann Epidemiol 13:683-691

7. Schneider HJ, Glaesmer H, Klotsche J, et al. Accuracy of anthropometric indicators of obesity to predict cardiovascular risk. J Clin Endocrinol Metab. 2006 Nov 14; [Epub ahead of print]

8. Schneider HJ, Klotsche J, Stalla GK, Wittchen HU. 2006 Obesity and risk of myocardial infarction: the INTERHEART study. Lancet 367:1052

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