Literature DB >> 16311099

Spectrum of insulin sensitivity in the Korean population.

Seungho Ryu1, Ki Chul Sung, Yoosoo Chang, Won-Young Lee, Eun-Jung Rhee.   

Abstract

The aims of the present study were to (1) examine the range of values for insulin sensitivity measures such as fasting serum insulin, homeostasis model assessment (HOMA), and quantitative insulin sensitivity check index (QUICKI) and (2) to identify cutoffs for indirect indexes of insulin sensitivity such as insulin, HOMA, and QUICKI that confer increased risk of metabolic syndrome in a large sample of Korean adults. The total number of study subjects involved was 83186. All of them presented for a routine health status checkup at the Kangbuk Samsung Hospital between January 2003 and December 2004, and none of them was currently taking medication for hypertension, diabetes, or dyslipidemia. We used 3 measures of insulin sensitivity: the fasting serum insulin, the HOMA, and the QUICKI. The age- and sex-adjusted prevalence of metabolic syndrome was examined by tenths of the distribution of each index of insulin. The fasting serum insulin, HOMA, and QUICKI were compared by using receiver operating characteristic curves. The fasting serum insulin ranged from 1.71 to 70.40 microU/mL, with the 25th percentile = 5.97, the median = 7.69, and the 75th percentile = 9.82. The HOMA ranged from 0.34 to 17.72, with the 25th percentile = 1.33, the median = 1.74, and the 75th percentile = 2.27. The QUICKI ranged from 0.112 to 0.202, with the 25th percentile = 0.146, the median = 0.152, and the 75th percentile = 0.158. The insulin, HOMA, and QUICKI values at the point on the receiver operating characteristic curve closest to the ideal of 100% sensitivity and 100% specificity for detecting the presence of metabolic syndrome were 9.7 microU/mL, 2.43, and 0.145, respectively. In conclusion, these findings describe the spectrum of insulin sensitivity in Korean adults. This study is the first attempt to determine cutoff values for indirect indexes of insulin sensitivity such as insulin, HOMA, and QUICKI that confer an increased risk of metabolic syndrome. These findings may be useful for evaluating insulin resistance, particularly in epidemiological studies.

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Year:  2005        PMID: 16311099     DOI: 10.1016/j.metabol.2005.06.014

Source DB:  PubMed          Journal:  Metabolism        ISSN: 0026-0495            Impact factor:   8.694


  9 in total

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  9 in total

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