JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES) ›› 2017, Vol. 55 ›› Issue (6): 82-86.doi: 10.6040/j.issn.1671-7554.0.2017.347

Previous Articles     Next Articles

Prediction models on the onset risks of type 2 diabetes among the health management population

SU Ping1,2, YANG Yachao3, YANG Yang1,2, JI Jiadong1,2, DAYIMU Alimu1,2, LI Min1,2, XUE Fuzhong1,2, LIU Yanxun1,2   

  1. 1. Department of Biostatistics, School of Public Health, Shandong University, Jinan 250012, Shandong, China;
    2. Cheeloo Research Center for Biomedical Big Data, Shandong University, Jinan 250012, Shandong, China;
    3. Physical Examination Department, Weihai Municipal Hospital, Weihai 264200, Shandong, China
  • Received:2017-04-20 Online:2017-06-10 Published:2017-06-10

PDF (PC)

381

Abstract: Objective To construct prediction models to estimate the risks of developing type 2 diabetes mellitus(T2DM)in 3 years among the health management population in mainland China. Methods Non-diabetic people aged 20 to 75 years at the baseline were chosen from Shandong Multi-center Longitudinal Cohort for Health Management to compose our cohort. Coxs proportional hazards regression model was adopted to build T2DM prediction model. The area under the receiver operating characteristic(ROC)curve(AUC)was used to evaluate the predictability of the model. Ten-fold cross-validation was adopted to test the stability of the model. Results During the follow-up of 3.68±2.8 years, 1,624 cases of new-onset diabetes occurred. The incidence density of male and female was 15.00‰ and 10.83‰, respectively. The risk factors for the male model included age, body mass index(BMI), fasting plasma glucose(FPG), triglyceride, alanine aminotransferase(ALT), and white blood cell(WBC)count. The risk factors 山 东 大 学 学 报 (医 学 版)55卷6期 -苏萍,等.健康管理人群2型糖尿病发病风险预测模型 \=-for the female model included age, FPG, triglyceride, high density lipoprotein cholesterol(HDL-C), and ALT. The AUC of the male model and female model was 0.795(95% CI: 0.764-0.827)and 0.707(95%CI: 0.654-0.759), respectively. Conclusion The male and female prediction models we constructed have high predictability and reliability among the health management population.

Key words: Cohort study, Coxs proportional hazards regression, Type 2 diabetes, Risk prediction model

CLC Number: 

  • R587.1
[1] Lu C, Sun W. Prevalence of diabetes in Chinese adults[J]. JAMA, 2014, 311(2): 199-200.
[2] Yang W, Lu J, Weng J, et al. Prevalence of diabetes among men and women in China[J]. N Engl J Med, 2010, 362(12): 1090-1101.
[3] Bhushan R, Elkindhirsch KE, Bhushan M, et al. Improved glycemic control and reduction of cardiometabolic risk factors in subjects with type 2 diabetes and metabolic syndrome treated with exenatide in a clinical practice setting[J]. Diabetes Technol Ther, 2009, 11(6): 353-359.
[4] Tuomilehto J, Lindstro MJ, Eriksson J, et al. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance[J]. N Engl J Med, 2001, 344: 1343-1350.
[5] Park PJ, Griffin SJ, Sargeant L, et al. The performance of a risk score in predicting undiagnosed hyperglycemia[J]. Diabetes Care, 2002, 25: 984-988.
[6] Lindström J, Tuomilehto J. The Diabetes risk score: a practical tool to predict type 2 diabetes risk[J]. Diabetes Care, 2003, 26(3): 725-731.
[7] 江慧, 徐慧兰, 肖水源, 等. 3种糖尿病筛查问卷在农村居民中应用的效果评价[J]. 中南大学学报(医学版), 2012, 37(11): 1108-1111. JIANG Hui, XU Huilan, XIAO Shuiyuan, et al. Performance of 3 diabetes screening questionnaires for a rural sample in China[J]. Journal of Central South University(Medical Sciences), 2012, 37(11): 1108-1111.
[8] Glümer C, Carstensen B, Sandbæk A, et al. A danish diabetes risk score for targeted screening the inter99 study[J]. Diabetes Care, 2004, 27(3): 727-733.
[9] 董建军, 娄能俊, 辛颖, 等. 不同糖尿病筛查问卷在中国人群糖尿病普查中的价值评估[J]. 中华内分泌代谢杂志, 2009, 25(1): 64-65.
[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(29): 1872-1877.
[11] Gao WG, Dong YH, Pang ZC, et al. A simple Chinese risk score for undiagnosed diabetes[J]. Diabetic Medicine, 2010, 27(3): 274-281.
[12] 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.
[13] 中国高血压防治指南修订委员会. 中国高血压防治指南(2010年修订版)[J]. 中国实用乡村医生杂志, 2012, 19(10): 1-15.
[14] 黎衍云, 李锐, 张胜年. 无症状糖尿病不同筛查方法效果评价[J]. 中国公共卫生, 2006, 22(6): 687-689. LI Yanyun, LI Rui, ZHANG Shengnian, et al. Evaluation on effect of screening method for undiagnosed diabetes[J]. Chinese Journal of Public Health, 2006, 22(6): 687-689.
[15] 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]. 济南: 山东大学, 2011.
[16] 沈洪兵, 俞顺章, 徐耀初, 等. 危险因素记分法筛检无症状糖尿病及其评价[J]. 中华流行病学杂志, 1999, 20(2): 114-117.
[17] 雷先阳. 农村社区2型糖尿病筛查及初步干预研究[D]. 长沙: 中南大学, 2013.
[18] Lim NK, Park SH, Choi SJ, et al. A risk score for predicting the incidence of type 2 diabetes in a middle-aged Korean cohort: the Korean genome and epidemiology study[J]. Circ J, 2012, 76(8): 1904-1910.
[19] Demmer RT, Jr JD, 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.
[20] Yoriko H, Yasuji A, Kazumi S, 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.
[21] 王忠东. 谷丙转氨酶和尿酸等指标检测在2型糖尿病中的意义分析[J]. 糖尿病新世界, 2016, 19(12): 67-68.
[22] 米生权. 中国成人个体糖尿病发病风险预测模型的建立及验证[D]. 北京: 中国疾病预防控制中心, 2011.
[23] Xie J, Hu D, Yu D, et al. A quick self-assessment tool to identify individuals at high risk of type 2 diabetes in the Chinese general population[J]. J Epidemiol Community Health, 2010, 64(3): 236-242.
[24] Xin Z, Yuan J, Hua L, et al. A simple tool detected diabetes and prediabetes in rural Chinese[J]. J Clin Epidemiol, 2010, 63(9): 1030-1035.
[1] CAO Jin, JI Xiaokang, SUN Xiubin, JIANG Zheng, XUE Fuzhong. The relationship between γ-glutamyltransferase and hyperuricemia: a cohort study [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2017, 55(6): 124-128.
[2] LI Jiqing, ZHAO Huanzong, SONG Binghong, ZHANG Lichun, LI Xiangyi, CHEN Yafei, WANG Ping, XUE Fuzhong. Risk prediction model of cardiovascular disease based on health management cohort [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2017, 55(6): 56-60.
[3] WANG Chunxia, XU Yibo, YANG Ning, XIA Bing, WANG Ping, XUE Fuzhong. A prediction model for coronary heart disease risks based on health management cohort [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2017, 55(6): 66-71.
[4] ZHANG Guang, WANG Guangyin, WU Hongyan, ZHANG Hongyu, WANG Tingting, LI Jiqing, LI Min, KANG Fengling, LIU Yanxun, XUE Fuzhong. A prediction model of hyperlipidemia risk based on the health management population [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2017, 55(6): 72-76.
[5] LI Jiangbing, SONG Xinhong, LIN Haiyan, ZHANG Dongzhi, LI Xiangyi, XU Yibo, WANG Li, XUE Fuzhong. The influencing factors of ischemic ECG abnormalities in a large health check-up population [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2017, 55(6): 77-81.
[6] ZHOU Miao, XIA Tongyao, SUN Ailing, LI Ming, SHEN Zhenwei, BIAN Weiwei, JIANG Zheng, KANG Fengling, LIU Xiaojuan, XUE Fuzhong, LIU Jing. Risk prediction model of chronic kidney disease in health management population [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2017, 55(6): 98-103.
[7] YU Yuanyuan, WANG Chunxia, SU Ping, SUN Yuanying, XUE Fuzhong, LIU Yanxun. A prediction model to estimate risks of cataract based on health management cohort [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2017, 55(6): 104-107.
[8] LIU Xiaojuan, JIANG Zheng, KANG Fengling, ZHOU Miao, LIN Weiqiang, XUE Fuzhong. Association between neutrophil count and nonalcoholic fatty liver disease:a prospective cohort study [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2017, 55(6): 119-123.
[9] LI Shuai, WANG Yalin, SUN Zhongwen, ZHU Meijia. Expression changes and mechanism of Nod-like receptor protein 3 inflammasome in the cerebral microvascular endothelial cells in type 2 diabetes mellitus [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2017, 55(3): 6-11.
[10] YANG Yang, ZHANG Guang, ZHANG Chengqi, SONG Xinhong, XUE Fuzhong, WANG Ping, WANG Li, LIU Yanxun. A prediction model for type 2 diabetes risks: a cohort study based on health examination [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2016, 54(9): 69-72.
[11] PENG Li, QIANG Ye, ZHAO Huichen, CHEN Shihong, YAO Weidong, LIU Yuantao. Clinical studies on type 2 diabetic patients treated with sitagliptin [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2016, 54(8): 60-63.
[12] LIN Dong, GUAN Qingbo. Association of serum testosterone level and non-alcoholic fatty liver disease in male patients with T2DM [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2016, 54(7): 33-37.
[13] Muhadasi TUERXUNYIMING, Patamu MOHEMAITI, Tuolanguli MAIMAITIKUERBAN. Association of CDKAL1 rs10946398 C/A polymorphism with type 2 diabetes [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2016, 54(2): 75-85.
[14] YU Ning, GAO Yanyan, XIAN Yuxin, NIU Jiapeng, LI Li, WANG Jing, CAO Caixia. Effect of exenatide on serum chemerin level and liver fat contents in type 2 diabetes mellitus combined with non-alcoholic fatty liver disease patients [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2016, 54(11): 51-55.
[15] ZHANG Li, ZHU Huiming, WANG Yanmei, JIANG Di, SUN Xianjiu, LE Youlin. Relationship between abdominal distension and small intestine bacterial overgrowth in type 2 diabetic patients [J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2016, 54(1): 45-47.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright 2018 © Editorial office of Journal of Shandong University (Health Sciences)
Supported by Beijing Magtech Co.Ltd