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On-line Access: 2011-10-08

Received: 2010-11-08

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Journal of Zhejiang University SCIENCE B 2011 Vol.12 No.10 P.846-852

http://doi.org/10.1631/jzus.B1000390


Evaluation of a risk factor scoring model in screening for undiagnosed diabetes in China population


Author(s):  Jian-jun Dong, Neng-jun Lou, Jia-jun Zhao, Zhong-wen Zhang, Lu-lu Qiu, Ying Zhou, Lin Liao

Affiliation(s):  Division of Endocrinology, Department of Medicine, Qilu Hospital of Shandong University, Jinan 250012, China, Division of Endocrinology, Department of Medicine, the Second Hospital of Shandong University, Jinan 250033, China, Division of Endocrinology, Department of Medicine, Shandong Provincial Qianfoshan Hospital, Jinan 250014, China, Division of Endocrinology, Department of Medicine, Provincial Hospital Affiliated to Shandong University, Jinan 250021, China

Corresponding email(s):   liaolin@medmail.com.cn

Key Words:  Diabetes mellitus, Screening, Questionnaire, Risk factor score


Jian-jun Dong, Neng-jun Lou, Jia-jun Zhao, Zhong-wen Zhang, Lu-lu Qiu, Ying Zhou, Lin Liao. Evaluation of a risk factor scoring model in screening for undiagnosed diabetes in China population[J]. Journal of Zhejiang University Science B, 2011, 12(10): 846-852.

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author="Jian-jun Dong, Neng-jun Lou, Jia-jun Zhao, Zhong-wen Zhang, Lu-lu Qiu, Ying Zhou, Lin Liao",
journal="Journal of Zhejiang University Science B",
volume="12",
number="10",
pages="846-852",
year="2011",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.B1000390"
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%A Jia-jun Zhao
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T1 - Evaluation of a risk factor scoring model in screening for undiagnosed diabetes in China population
A1 - Jian-jun Dong
A1 - Neng-jun Lou
A1 - Jia-jun Zhao
A1 - Zhong-wen Zhang
A1 - Lu-lu Qiu
A1 - Ying Zhou
A1 - Lin Liao
J0 - Journal of Zhejiang University Science B
VL - 12
IS - 10
SP - 846
EP - 852
%@ 1673-1581
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DOI - 10.1631/jzus.B1000390


Abstract: 
Objective: To develop a risk scoring model for screening for undiagnosed type 2 diabetes in Chinese population. Methods: A total of 5348 subjects from two districts of Jinan City, Shandong Province, China were enrolled. Group A (2985) included individuals from east of the city and Group B (2363) from west of the city. screening questionnaires and a standard oral glucose tolerance test (OGTT) were completed by all subjects. Based on the stepwise logistic regression analysis of Group A, variables were selected to establish the risk scoring model. The validity and effectiveness of this model were evaluated in Group B. Results: Based on stepwise logistic regression analysis performed with data of Group A, variables including age, body mass index (BMI), waist-to-hip ratio (WHR), systolic pressure, diastolic pressure, heart rate, family history of diabetes, and history of high glucose were accepted into the risk scoring model. The risk for having diabetes increased along with aggregate scores. When Youden index was closest to 1, the optimal cutoff value was set up at 51. At this point, the diabetes risk scoring model could identify diabetes patients with a sensitivity of 83.3% and a specificity of 66.5%, making the positive predictive value 12.83% and negative predictive value 98.53%. We compared our model with the Finnish and Danish model and concluded that our model has superior validity in Chinese population. Conclusions: Our diabetes risk scoring model has satisfactory sensitivity and specificity for identifying undiagnosed diabetes in our population, which might be a simple and practical tool suitable for massive diabetes screening.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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