A quick self-assessment tool to identify individuals at high risk of type 2 diabetes in the Chinese general population

Abstract

Background Currently available tools for identifying individuals at high risk of type 2 diabetes can be invasive, costly and time consuming. This study aims to develop and validate a self-assessment tool for identifying individuals at high risk of type 2 diabetes in the Chinese general population. Methods A cross-sectional survey was conducted from 2000 to 2001 in a nationally representative sample of 15 540 Chinese adults aged 35e74 years. The diabetes risk level (DRL) was assessed by classification and regression tree (CART) analysis using four predictors: age, body mass index, waistehip ratio (WHR) and waist circumference (WC). Results The significant predictors for type 2 diabetes were WHR and age for women and WC and age for men. The categories generated by CART analysis stratified women into eight DRL and men into five DRL. The prevalence of type 2 diabetes increased with the increase in DRL in both women and men. A DRL of 6 or greater predicted type 2 diabetes status with a sensitivity of 0.61 (95% CI 0.55 to 0.67), a specificity of 0.71 (95% CI 0.70 to 0.73) in women, and a DRL of 3 or greater predicted type 2 diabetes status with a sensitivity of 0.59 (95% CI 0.52 to 0.65) and a specificity of 0.63 (95% CI 0.62 to 0.65) in men. Conclusions This study demonstrates that application of the DRL has identified a substantial proportion of individuals with type 2 diabetes in the Chinese general population. It suggests that there is a great potential for applying the self-assessment tool in healthcare-limited settings.The rising prevalence of type 2 diabetes has a become major public health problem worldwide, and it has been predicted to affect 366 million people by the year 2030, of which at least 40 million people would be from China alone.

Developing risk prediction models for type 2 diabetes: a systematic review of methodology and reporting

“…Thirteen studies (33%) were published in Diabetes Care , five studies (13%) were published in Diabetes Research and Clinical Practice , four studies (10%) were published in Diabetic Medicine and three studies (8%) were published in the Annals of Internal Medicine . Four studies reported separate risk prediction models for men and women [23-26], thus our review assesses a total of 43 risk prediction models from 39 articles. Thus the denominator is 39 when reference is made to studies and 43 when reference is made to risk prediction models.…”

“…The outcomes predicted by the models varied because of different definitions of diabetes and patients included (Tables 1, 2 and 3). Seventeen studies (44%) described a model to predict the development of diabetes (incident diabetes) [23,25,27-40], fifteen (38%) described the development of a model to predict the risk of having undiagnosed diabetes [41-53], four described the development of a prediction model for diagnosed and undiagnosed diabetes [24,26,54,55], one described the development of a prediction model for undiagnosed diabetes and prediabetes [56], one described the development of a prediction model for abnormal postchallenge plasma glucose level (defined as ≥ 140 mg/dL) to predict undiagnosed diabetes [57] and one described the development of a model to predict the risk of undiagnosed type 2 diabetes and impaired glucose regulation [58]. …”

“…Eight articles (21%) were from the USA [31,34,36,39,43,56,57,59], thirteen articles (33%) were from Europe [23-25,32,33,35,40,42,46,52,54,55], thirteen articles (33%) were from Asia [26,27,29,37,41,44,45,47-49,51,60], two were from Africa [30,53], one was from Australia [28] and one was from Brazil [50]. …”

“…In the four studies where this was not clearly reported, the number of events was not reported [26,34,49,56]. The median number of participants included in model development was 2,562 (interquartile range (IQR) 1,426 to 4,965).…”

Risk Estimation of Type 2 Diabetes and Dietary Habits among Adult Saudi Non-diabetics in Central Saudi Arabia

“…The earlier detection of individuals at high risk of T2D is a high priority for primary prevention (Xie et al, 2010). Research protocols for estimating a person's future risk for T2D have depended primarily on identifying IGT through a 2-hour oral glucose tolerance test (Kahn et al, 2009).…”