Nonlaboratory-Based Risk Assessment Algorithm for Undiagnosed Type 2 Diabetes Developed on a Nation-Wide Diabetes Survey

OBJECTIVE

To develop a New Chinese Diabetes Risk Score for screening undiagnosed type 2 diabetes in China.

RESEARCH DESIGN AND METHODS

Data from the China National Diabetes and Metabolic Disorders Study conducted from June 2007 to May 2008 comprising 16,525 men and 25,284 women aged 20–74 years were analyzed. Undiagnosed type 2 diabetes was detected based on fasting plasma glucose ≥7.0 mmol/L or 2-h plasma glucose ≥11.1 mmol/L in people without a prior history of diabetes. β-Coefficients derived from a multiple logistic regression model predicting the presence of undiagnosed type 2 diabetes were used to calculate the New Chinese Diabetes Risk Score. The performance of the New Chinese Diabetes Risk Score was externally validated in two studies in Qingdao: one is prospective with follow-up from 2006 to 2009 (validation 1) and another cross-sectional conducted in 2009 (validation 2).

RESULTS

The New Chinese Diabetes Risk Score includes age, sex, waist circumference, BMI, systolic blood pressure, and family history of diabetes. The score ranges from 0 to 51. The area under the receiver operating curve of the score for undiagnosed type 2 diabetes was 0.748 (0.739–0.756) in the exploratory population, 0.725 (0.683–0.767) in validation 1, and 0.702 (0.680–0.724) in validation 2. At the optimal cutoff value of 25, the sensitivity and specificity of the score for predicting undiagnosed type 2 diabetes were 92.3 and 35.5%, respectively, in validation 1 and 86.8 and 38.8% in validation 2.

CONCLUSIONS

The New Chinese Diabetes Risk Score based on nonlaboratory data appears to be a reliable screening tool to detect undiagnosed type 2 diabetes in Chinese population.Prevalence of type 2 diabetes is increasing dramatically worldwide. In China, the prevalence of type 2 diabetes increased from 5.5% in 2000–2001 (1) to 9.7% in 2007–2008 (2). Nearly 60% of individuals with type 2 diabetes had not been diagnosed previously (2). Mortality in individuals with previously undiagnosed type 2 diabetes was, however, as high as in those with known type 2 diabetes; both were higher than in people without type 2 diabetes (3). Obesity, hypertension, and dyslipidemia are also frequently clustered in an individual with undiagnosed type 2 diabetes (2,4,5). Early detection of type 2 diabetes and intervention may reduce exposure to long-term hyperglycemia and prevent or delay chronic diabetes complications. The currently used diagnostic tool for type 2 diabetes is 75-g oral glucose tolerance test (OGTT) and A1C (6). The OGTT is, however, time consuming, and the fasting status cannot be assured. The A1C test is less standard and relatively expensive. Consequently, their use in mass screening has been limited. Risk score developed based on demographic, anthropometric, and clinical information without a laboratory test has been proved to be a useful and cheap tool for a stepwise screening strategy for undiagnosed type 2 diabetes (7–17). This approach is particularly useful in China, considering a large population and an already high and still increasing prevalence of undiagnosed type 2 diabetes.A simple Chinese diabetes risk score has been reported based on data collected in Qingdao (7). Considering the diversity in economic development, culture, living environment, and dietary factors in different areas of China, we tried to develop a New Chinese Diabetes Risk Score for undiagnosed type 2 diabetes using the data of the China National Diabetes and Metabolic Disorders Study (exploratory population) that was conducted in 12 provinces and autonomous regions in addition to the municipalities of Beijing and Shanghai from June 2007 to May 2008. The performance of the New Chinese Diabetes Risk Score developed in this study is validated in two external studies in Qingdao. One of the two studies is prospective (validation 1) and the other cross-sectional (validation 2). The results of the validation of the indexed score are also compared with previously published diabetes risk scores that derived from Chinese (7), Caucasian (9,11,13,14,18), and other Asian populations (15,16,19,20).