JMIR Publications

ABSTRACT

Background:

Anthropometric indexes represent a promising, simple diagnostic tool for metabolic syndrome (MetS) in areas with limited healthcare resources.

Objective:

This study aimed to examine the association between eight easy-to-collect anthropometric indexes and MetS, and determine the most appropriate indexes to identify the presence of MetS for adults in less developed areas.

Methods:

10520 participants aged 18-85 years from NingXia were included in this cross-sectional study. Logistic regression analysis was used to determine the odds ratios (ORs) of each index. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were applied to examine the predictive power of each anthropometric index.

Results:

Under the International Diabetes Federation criteria, the highest odds ratios for MetS risk were found in waist-to-height ratio (WHtR) and lipid accumulation products (LAP). WHtR was the strongest predictor of MetS for males (AUC=0.91, 95%CI: 0.90-0.92, optimal cutoff 0.53) and overall (AUC=0.89, 95%CI: 0.89-0.90, optimal cutoff 0.52). LAP was the strongest predictor of MetS for females (AUC= 0.89, 95%CI: 0.89-0.90, optimal cutoff 28.67).

Conclusions:

WHtR and LAP are more advantageous anthropometric indexes for predicting MetS among adults in less developed areas. We suggest to accommodate the optimal thresholds of them from different regions when formulating standardised diagnosis criteria.