Metabolic abnormalities identified by anthropometric measures in elderly men

Endocrine Research Center
Shaheed Beheshti University of Medical Sciences
PO Box 19395-4763
Tehran
Iran
E-mail: azizi{at}erc.ac.ir

Dear Sir:

In a recent issue of the Journal, Wannamethee et al (1) described the results of an interesting cross-sectional study on the association between anthropometric measures and metabolic abnormalities in 2924 men aged 60–79 y. They showed that body mass index and waist circumference had similar associations with cardiovascular disease risk factors, whereas the waist-to-hip ratio showed weaker correlations. We think that this conclusion could be misleading for several reasons. First, the authors' definition of the metabolic syndrome is flawed; in their study, waist circumference was not included, and hypertension [blood pressure 140 (systolic)/90 (diastolic) mm Hg] was considered as one of the components of the metabolic syndrome phenotype, whereas the Adult Treatment Panel III definition of the metabolic syndrome includes elevated blood pressure [130 (systolic)/85 (diastolic) mm Hg], not hypertension (2). Therefore, the prevalence rate is not the true prevalence of the metabolic syndrome in this age category. This is why the prevalence of the metabolic syndrome was 14% by their definition, which is lower than that shown in elderly groups (3, 4). Second, the authors did not state that they had excluded subjects who were taking antihypertensive or lipid-lowering drugs. This could confound the findings. Third, the authors did not control for the effect of hip circumference in their analyses, but studies have shown that larger hip circumferences independently contribute to a reduced risk of metabolic abnormalities in adult and elderly men (5). Fourth, the odds ratio estimated from logistic regression models is a valid estimator of the rate ratio only when the outcome variable has a low prevalence in the sample (generally defined as 10% or less); this is not the case for the metabolic abnormalities in this study, and, as the outcome condition becomes common, the odds ratio highly overestimates the rate ratio (6, 7). Fifth, a comparison of odds ratios is not a suitable method for judgments about the predictive ability of screening tools; a comparison of sensitivity, specificity, and accuracy between screening tools is recommended to reach this objective (8). Sixth, it is possible that the relation between each anthropometric measure and cardiovascular disease risk factors is mediated by another measure. Because the investigators did not control for the simultaneous effects of anthropometric measures, it is not clear which anthropometric measure has a higher correlation coefficient with metabolic risks. Seventh, the use of cutoffs for defining metabolic disorders implies a loss of information; therefore, the authors should have also assessed the relations between anthropometric variables and continuous metabolic variables by using a multiple linear regression.

The recognition of adiposity measures associated with metabolic abnormalities is extremely important, because the prevention of these risk factors is of public health importance for the prevention of noncommunicable diseases. However, careful epidemiologic and statistical methods should be adopted to avoid any incorrect conclusions.

ACKNOWLEDGMENTS

None of the authors had any conflicts of interest.

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