- 著者
- Hiroshi Yatsuya Yuanying Li Yoshihisa Hirakawa Atsuhiko Ota Masaaki Matsunaga Hilawe Esayas Haregot Chifa Chiang Yan Zhang Koji Tamakoshi Hideaki Toyoshima Atsuko Aoyama
- 出版者
- Japan Epidemiological Association
- 雑誌
- Journal of Epidemiology (ISSN:09175040)
- 巻号頁・発行日
- pp.JE20170048, (Released:2018-03-17)
- 参考文献数
- 36
- 被引用文献数
- 12
Background: Relatively little evidence exists for type 2 diabetes mellitus (T2DM) prediction models from long-term follow-up studies in East Asians. This study aims to develop a point-based prediction model for 10-year risk of developing T2DM in middle-aged Japanese men.Methods: We followed 3,540 male participants of Aichi Workers’ Cohort Study, who were aged 35–64 years and were free of diabetes in 2002, until March 31, 2015. Baseline age, body mass index (BMI), smoking status, alcohol consumption, regular exercise, medication for dyslipidemia, diabetes family history, and blood levels of triglycerides (TG), high density lipoprotein cholesterol (HDLC) and fasting blood glucose (FBG) were examined using Cox proportional hazard model. Variables significantly associated with T2DM in univariable models were simultaneously entered in a multivariable model for determination of the final model using backward variable selection. Performance of an existing T2DM model when applied to the current dataset was compared to that obtained in the present study’s model.Results: During the median follow-up of 12.2 years, 342 incident T2DM cases were documented. The prediction system using points assigned to age, BMI, smoking status, diabetes family history, and TG and FBG showed reasonable discrimination (c-index: 0.77) and goodness-of-fit (Hosmer-Lemeshow test, P = 0.22). The present model outperformed the previous one in the present subjects.Conclusion: The point system, once validated in the other populations, could be applied to middle-aged Japanese male workers to identify those at high risk of developing T2DM. In addition, further investigation is also required to examine whether the use of this system will reduce incidence.