Should waist circumference be used to identify metabolic disorders than BMI in South Korea?

Indicators of hypertriglyceridemia from anthropometric measures based on data mining

BACKGROUND

The best indicator for the prediction of hypertriglyceridemia derived from anthropometric measures of body shape remains a matter of debate. The objectives are to determine the strongest predictor of hypertriglyceridemia from anthropometric measures and to investigate whether a combination of measures can improve the prediction accuracy compared with individual measures.

METHODS

A total of 5517 subjects aged 20-90 years participated in this study. The numbers of normal and hypertriglyceridemia subjects were 3022 and 653 females, respectively, and 1306 and 536 males, respectively. We evaluated 33 anthropometric measures for the prediction of hypertriglyceridemia using statistical analysis and data mining.

RESULTS

In the 20-90-year-old groups, age in women was the variable that exhibited the highest predictive power; however, this was not the case in men in all age groups. Of the anthropometric measures, the waist-to-height ratio (WHtR) was the best predictor of hypertriglyceridemia in women. In men, the rib-to-forehead circumference ratio (RFcR) was the strongest indicator. The use of a combination of measures provides better predictive power compared with individual measures in both women and men. However, in the subgroups of ages 20-50 and 51-90 years, the strongest indicators for hypertriglyceridemia were rib circumference in the 20-50-year-old group and WHtR in the 51-90-year-old group in women and RFcR in the 20-50-year-old group and BMI in the 51-90-year-old group in men.

CONCLUSIONS

Our results demonstrated that the best predictor of hypertriglyceridemia may differ according to gender and age.

Measurement error of waist circumference: gaps in knowledge

Objective

It is not clear whether measuring waist circumference in clinical practice is problematic because the measurement error is unclear, as well as what constitutes a clinically relevant change. The present study aimed to summarize what is known from state-of-the-art research.

Design

To identify the magnitude of the measurement error of waist circumference measurements from the literature, a search was conducted in PubMed from 1975 to February 2011.

Results

The measurement error may vary between 0·7 cm and 15 cm. Taking a realistic range of measurable waist circumference into account (60–135 cm), we argue that a short-term clinically relevant change in waist circumference of 5 % may lie between 3·0 and 6·8 cm and a maintained clinically relevant change of 3 % between 1·8 and 4·1 cm.

Conclusions

Based on these results, we conclude it may be difficult to distinguish clinically relevant change from measurement error in individual subjects, due to the large measurement error and unclear definition of clinically relevant change. More research is needed to address these gaps in knowledge. To minimize measurement error, we recommend using a uniform measurement protocol, training and repeated measurements.