COMPARATIVE STUDY
JOURNAL ARTICLE

Predicting insulin resistance using the triglyceride-to-high-density lipoprotein cholesterol ratio in Taiwanese adults

Jui-Kun Chiang, Ning-Sheng Lai, Jiunn-Kae Chang, Malcolm Koo
Cardiovascular Diabetology 2011, 10: 93
22004541

BACKGROUND: The triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C) has been advocated as a simple clinical indicator of insulin resistance. Thresholds of TG/HDL-C appeared to depend on ethnicity. However, no studies have specifically compared the accuracy of TG/HDL-C with and without other clinical and demographic factors in predicting insulin resistance in Taiwanese adults. The aim of the present investigation was to use TG/HDL-C and other clinical available factors to predict insulin resistance in Taiwanese adults.

METHODS: A total of 812 subjects were recruited from at the time of their general health examination at the Buddhist Dalin Tzu Chi General Hospital, Taiwan. Demographic information and clinical characteristics were obtained. Insulin resistance was defined by the homeostasis model assessment for insulin resistance (HOMA-IR). Simple and multiple logistic regression analyses were used to obtain probabilities of insulin resistance (HOMA-IR > 2) using TG/HDL-C with (Model 2) and without (Model 1) other clinical variables. A receiver operating characteristic (ROC) analysis was conducted to evaluate the ability of the two models to correctly discriminate between subjects of low and elevated HOMA-IR.

RESULTS: Female sex, greater waist circumferences, and higher ALT levels were significantly associated with the risk of elevated HOMA-IR in addition to TG/HDL-C in the multiple logistic regression (Model 2). The area under the ROC curve (AUC) of Model 2 was 0.71 [95% CI = 0.67-0.75] and was significantly higher (P = 0.007) than the AUC 0.66 [95% CI = 0.62-0.71] of Model 1.

CONCLUSIONS: The diagnostic accuracy of insulin resistance, defined by HOMA-IR, using TG/HDL-C can be significantly enhanced by including three additional clinically available factors - sex, waist circumferences, and ALT levels.

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