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Acta Diabetologica

, Volume 55, Issue 1, pp 13–19 | Cite as

Development of a new scoring system to predict 5-year incident diabetes risk in middle-aged and older Chinese

  • Xu Han
  • Jing Wang
  • Yaru Li
  • Hua Hu
  • Xiulou Li
  • Jing Yuan
  • Ping Yao
  • Xiaoping Miao
  • Sheng Wei
  • Youjie Wang
  • Yuan Liang
  • Xiaomin Zhang
  • Huan Guo
  • An Pan
  • Handong Yang
  • Tangchun Wu
  • Meian HeEmail author
Original Article

Abstract

Aims

The aim of this study was to develop a new risk score system to predict 5-year incident diabetes risk among middle-aged and older Chinese population.

Methods

This prospective study included 17,690 individuals derived from the Dongfeng–Tongji cohort. Participants were recruited in 2008 and were followed until October 2013. Incident diabetes was defined as self-reported clinician diagnosed diabetes, fasting glucose ≥7.0 mmol/l, or the use of insulin or oral hypoglycemic agent. A total of 1390 incident diabetic cases were diagnosed during the follow-up period. β-Coefficients were derived from Cox proportional hazard regression model and were used to calculate the risk score.

Results

The diabetes risk score includes BMI, fasting glucose, hypertension, hyperlipidemia, current smoking status, and family history of diabetes. The β-coefficients of these variables ranged from 0.139 to 1.914, and the optimal cutoff value was 1.5. The diabetes risk score was calculated by multiplying the β-coefficients of the significant variables by 10 and rounding to the nearest integer. The score ranges from 0 to 36. The area under the receiver operating curve of the score was 0.751. At the optimal cutoff value of 15, the sensitivity and specificity were 65.6 and 72.9%, respectively. Based upon these risk factors, this model had the highest discrimination compared with several commonly used diabetes prediction models.

Conclusions

The newly established diabetes risk score with six parameters appears to be a reliable screening tool to predict 5-year risk of incident diabetes in a middle-aged and older Chinese population.

Keywords

Incident diabetes Prediction Risk score Cohort study 

Notes

Acknowledgements

The authors would like to thank all study subjects for participating in the present Dongfeng–Tongji cohort study as well as all volunteers for assisting in collecting the sample and questionnaire data. We also acknowledge all the staff for collecting the clinic data.

Funding

This work was supported by the grant from the National Natural Science Foundation (Grants NSFC-81473051, 81522040) and the Program for the New Century Excellent Talents in University (NCET-11-0169) for Meian He; the National Natural Science Foundation (Grant NSFC-81230069) for Tangchun Wu.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The study has been approved by the Ethics and Human Subject Committee of the School of Public Health, Tongji Medical College, and Dongfeng General Hospital, the Dongfeng Motor Corporation (DMC).

Informed consent

All study participants provided written informed consents.

Supplementary material

592_2017_1047_MOESM1_ESM.docx (16 kb)
Supplementary material 1 (DOCX 16 kb)

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Copyright information

© Springer-Verlag Italia S.r.l. 2017

Authors and Affiliations

  • Xu Han
    • 1
  • Jing Wang
    • 1
  • Yaru Li
    • 1
  • Hua Hu
    • 1
  • Xiulou Li
    • 2
  • Jing Yuan
    • 1
  • Ping Yao
    • 1
  • Xiaoping Miao
    • 1
  • Sheng Wei
    • 1
  • Youjie Wang
    • 1
  • Yuan Liang
    • 1
  • Xiaomin Zhang
    • 1
  • Huan Guo
    • 1
  • An Pan
    • 1
  • Handong Yang
    • 2
  • Tangchun Wu
    • 1
  • Meian He
    • 1
    Email author
  1. 1.Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
  2. 2.Dongfeng Central HospitalDongfeng Motor Corporation and Hubei University of MedicineShiyanChina

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