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International Journal of Endocrinology
Volume 2015, Article ID 675245, 7 pages
http://dx.doi.org/10.1155/2015/675245
Research Article

The Estimation of First-Phase Insulin Secretion by Using Components of the Metabolic Syndrome in a Chinese Population

1Division of Endocrinology, Department of Internal Medicine, Shuang Ho Hospital, School of Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan
2Department of Family Medicine, Cardinal Tien Hospital, School of Medicine, Fu-Jen Catholic University, New Taipei City 242, Taiwan
3Department of Life-Science, Fu-Jen University, New Taipei City 242, Taiwan
4Division of Endocrinology and Metabolism, Department of Internal Medicine, Buddhist Dalin Tzu Chi General Hospital, School of Medicine, Hualien 970, Taiwan
5Division of Endocrinology and Metabolism, Department of Internal Medicine, Tri-Service General Hospital, Taipei 114, Taiwan
6Division of Endocrinology and Metabolism, Department of Internal Medicine, Cardinal Tien Hospital, Medical School, Fu-Jen Catholic University, New Taipei City 242, Taiwan
7Department of Pathology, Cardinal Tien Hospital, Medical School, Fu-Jen Catholic University, New Taipei City 242, Taiwan

Received 29 April 2014; Revised 14 September 2014; Accepted 26 November 2014

Academic Editor: Tien-Jyun Chang

Copyright © 2015 Jiunn-diann Lin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Aims. There are two phases of insulin secretion, the first (FPIS) and second phase (SPIS). In this study, we built equations to predict FPIS with metabolic syndrome (MetS) components and fasting plasma insulin (FPI). Methods. Totally, 186 participants were enrolled. 75% of participants were randomly selected as the study group to build equations. The remaining 25% of participants were selected as the external validation group. All participants received a frequently sampled intravenous glucose tolerance test, and acute insulin response after the glucose load (AIRg) was obtained. The AIRg was considered as FPIS. Results. When MetS components were only used, the following equation was built: log (FPIS) = 1.477 − 0.119 × fasting plasma glucose (FPG) + 0.079 × body mass index (BMI) − 0.523 × high-density lipoprotein cholesterol (HDL-C). After FPI was added, the second equation was formulated: log (FPIS) = 1.532 − 0.127 × FPG + 0.059 × BMI - 0.511 × HDL-C + 0.375 × log (FPI), which provided a better accuracy than the first one. Conclusions. Using MetS components, the FPIS could be estimated accurately. After adding FPI into the equation, the predictive power increased further. We hope that these equations could be widely used in daily practice.