JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES) ›› 2016, Vol. 54 ›› Issue (9): 69-72.doi: 10.6040/j.issn.1671-7554.0.2016.074

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A prediction model for type 2 diabetes risks: a cohort study based on health examination

YANG Yang1, ZHANG Guang2, ZHANG Chengqi2, SONG Xinhong3, XUE Fuzhong1, WANG Ping4, WANG Li5, LIU Yanxun1   

  1. 1. Department of Biostatistics, School of Public Health, Shandong University, Jinan 250012, Shandong, China;
    2. Health Examiwation Center, Qianfoshan Hospital Affiliated to Shandong University, Jinan 250014, Shandong, China;
    3. Health Examination Center, Shandong Provincial Hospital Affiliated to Shandong University, Jinan 250021, Shandong, China;
    4. Outpatient Operating Room, Qilu Hospital of Shandong University, Jinan 250012, Shandong, China;
    5. Department of Cardiology, Shandong Electric Power Central Hospital, Jinan 250001, Shandong, China
  • Received:2016-01-21 Online:2016-09-10 Published:2016-09-10

Abstract: Objective To establish a model to evaluate the risks of type 2 diabetes among Han population in mainland China. Methods A total of 16,715 non-diabetic people who underwent routine health check-up at the Center for Health Management of Qianfoshan Hospital Affiliated to Shandong University and Shandong Provincial Hospital Affiliated to Shandong University during Jan. 2005 and Dec. 2010 were enrolled in the study. These people were randomly divided into the training group (n=11 700, 70%)and testing group(n=5 015, 30%). Cox regression was used to construct a simple risk model among the training group by stepwise selection method, and risk classification was drawn up according to the prognostic index. Ten-fold cross validation was used to test the stability of the model in the testing group. Discriminatory ability was determined by the area under the ROC curve. Results Altogether 858 new diabetic cases were observed over the five-year follow-up, resulting in a cumulative incidence of 15.14/1000 person years. The risk factors included age, body mass index, fasting blood-glucose, triglyceride, hypertension status and leukocyte logarithm. The estimated AUC for the model was 0.742(95%CI: 0.732-0.752)in the training group and 0.760(95%CI: 山 东 大 学 学 报 (医 学 版)54卷9期 -杨洋,等.基于体检队列的2型糖尿病风险预测模型 \=-0.748-0.772)in the testing group. Conclusion We have constructed a risk model that could be useful for identifying individuals at high risk of diabetes in health examination population.

Key words: Type 2 diabetes, Cohort study, Predictive model, Health check-up

CLC Number: 

  • R587.1
[1] Yang W, Lu J. Prevalence of diabetes among men and women in China[J]. N Engl J Med, 2010, 12(362):1090-1101.
[2] Dong JJ, Lou NJ, Zhao JJ, et al. Evaluation of a risk factor scoring model in screening for undiagnosed diabetes in China population[J]. J Zhejiang Univ Sci B, 2011, 12(10):846-852.
[3] Phillips CM, Kearney PM, Mccarthy VJ, et al. Comparison of diabetes risk score estimates and cardiometabolic risk profiles in a middle-aged Irish population[J]. PLoS One, 2013, 8(11): e78950. doi: 10.1371/journal.pone.0078950.
[4] Lu C, Sun W. Prevalence of diabetes in Chinese adults[J]. JAMA, 2014, 311(2):199-200.
[5] Sun K, Li F, Qi Y, et al. Sex difference in the association between habitual daytime napping and prevalence of diabetes: a population-based study[J]. Endocrine, 2016, 52(2):263-270.
[6] 中国2型糖尿病防治指南(2010年版)[J]. 中国糖尿病杂志, 2012(1):81-117.
[7] 中国高血压防治指南(2010年版)[J]. 中华高血压杂志,2011(8):701-743.
[8] Barber SL, Yao L. Health insurance systems in China: A briefing note: The path to universal coverage [Z]. World Health Organization, 2010.
[9] Lindström J, Tuomilehto J. The diabetes risk score: a practical tool to predict type 2 diabetes risk[J]. Diabetes Care, 2003, 3(26):725-731.
[10] Aekplakorn W, Bunnag P, Woodward M, et al. A risk score for predicting incident diabetes in the Thai population[J]. Diabetes Care, 2006, 29(8):1872-1877.
[11] Balkau B, Lange C, Fezeu L, et al. Predicting diabetes: clinical, biological, and genetic approaches: data from the epidemiological study on the insulin resistance syndrome(DESIR)[J]. Diabetes Care, 2008, 31(10):2056-2061.
[12] Lindstrom J, Tuomilehto J. The diabetes risk score: a practical tool to predict type 2 diabetes risk[J]. Diabetes Care, 2003, 26(3):725-731.
[13] Vassy JL, Hivert MF, Porneala B, et al. Polygenic type 2 diabetes prediction at the limit of common variant detection[J]. Diabetes, 2014, 63(6):2172-2182.
[14] Noto D, Cefalù AB, Barbagallo CM, et al. Prediction of incident type 2 diabetes mellitus based on a twenty-year follow-up of the Ventimiglia heart study[J]. Acta Diabetol, 2012, 49(2):145-151.
[15] Lim N, Park S, Choi S, et al. A risk score for predicting the incidence of type 2 diabetes in a middle-aged Korean cohort[J]. Circ J, 2012, 76(8):1904-1910.
[16] Demmer RT, Jacobs DR, Desvarieux M. Periodontal disease and incident type 2 diabetes: results from the First National Health and Nutrition Examination Survey and its epidemiologic follow-up study[J]. Diabetes Care, 2008, 31(7):1373-1379.
[17] Heianza Y, Arase Y, Saito K, et al. Development of a screening score for undiagnosed diabetes and its application in estimating absolute risk of future type 2 diabetes in Japan: Toranomon Hospital Health Management Center Study 10(TOPICS 10)[J]. J Clin Endocrinol Metab, 2013, 98(3):1051-1060.
[18] Xu L, Jiang CQ, Schooling CM, et al. Prediction of 4-year incident diabetes in older Chinese: recalibration of the Framingham diabetes score on Guangzhou Biobank Cohort Study[J]. Prev Med, 2014, 69:63-68. doi:10.1016/j.ypmed.2014.09.004. Epub 2014 Sep 17.
[19] Gupta AK, Dahlof B, Dobson J, et al. Determinants of new-onset diabetes among 19,257 hypertensive patients randomized in the Anglo-Scandinavian cardiac outcomes trial-blood pressure lowering arm and the relative influence of antihypertensive medication[J]. Diabetes Care, 2008, 31(5):982-988.
[20] 王孝勇. 无症状2型糖尿病及糖尿病前期人群社区筛查策略研究[D]. 山东大学, 2011.
[21] 师正坤, 郭佳, Monica Parry, 等. 中国糖尿病风险评估工具的研究现状与进展[J]. 中国全科医学, 2015(20):2368-2372. SHI Zhengkun, GUO Jia, Monica Parry, et al. Research status and progress of Chinese risk assessment tools for diabetes mellitus[J]. Chinese General Practice, 2015, 18(20):2368-2372.
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