A simple Chinese risk score for undiagnosed diabetes

被引:111
作者
Gao, W. G. [1 ,2 ,5 ]
Dong, Y. H. [2 ]
Pang, Z. C. [3 ]
Nan, H. R. [4 ]
Wang, S. J. [3 ]
Ren, J. [3 ]
Zhang, L. [1 ,2 ,5 ]
Tuomilehto, J. [1 ,5 ]
Qiao, Q. [1 ,5 ]
机构
[1] Univ Helsinki, Dept Publ Hlth, Helsinki, Finland
[2] Qingdao Endocrinol & Diabet Hosp, Qingdao, Peoples R China
[3] Qingdao Municipal Ctr Dis Control & Prevent, Dept Noncommunicable Dis Prevent, Qingdao, Peoples R China
[4] Hong Kong Inst Diabet & Obes, Hong Kong, Hong Kong, Peoples R China
[5] Natl Inst Hlth & Welf, Diabet Unit, Dept Chron Dis Prevent, Helsinki, Finland
关键词
risk assessment; score; undiagnosed diabetes; IMPAIRED FASTING GLUCOSE; ADULT-POPULATION; MELLITUS; PREVALENCE; URBAN; RECLASSIFICATION; PERFORMANCE; VALIDATION; DERIVATION; PREDICT;
D O I
10.1111/j.1464-5491.2010.02943.x
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
P>Aims A diabetes risk score for screening undiagnosed diabetes was constructed and validated in Chinese adults. Methods Two consecutive population-based diabetes surveys among Chinese adults aged 20-74 years were conducted in 2002 (n = 1986) and 2006 (n = 4336). Demographic and anthropometric measures were collected following similar procedures. Standard 2-h 75-g oral glucose tolerance tests (OGTTs) were performed to diagnose diabetes in both surveys. Fasting capillary plasma glucose (FCG) and glycated haemoglobin (HbA(1c)) were also measured together with the OGTTs on the same day of the 2006 survey. Beta coefficients estimated using logistic regression analysis derived from data of the 2002 survey were used to develop the risk assessment algorithm. The performance of the algorithm was validated in the study population of the 2006 survey. Results Of all the variables tested, waist circumference, age and family history of diabetes were significant predictors of diabetes and were used to construct the risk assessment score. The score, ranging from 3 to 32, performed well when applied to the study population of the 2006 survey. The area under the receiver operating characteristic curve was 67.3% (95% CI, 64.9-69.7%) for the score, while it was 76.3% (73.5-79.0%) for FCG alone and 67.8% (64.9-70.8%) for HbA(1c) alone. At a cut-off point of 14, the sensitivity and specificity of the risk score were 84.2% (81.0-87.5%) and 39.8% (38.2-41.3%). Conclusions The risk score based on age, waist circumference and family history of diabetes is efficient as a layperson-oriented diabetes screening tool for health promotion and for population-based screening programmes.
引用
收藏
页码:274 / 281
页数:8
相关论文
共 24 条
  • [1] A risk score for predicting incident diabetes in the Thai population
    Aekplakorn, Wichai
    Bunnag, Pongamorn
    Woodward, Mark
    Sritara, Piyamitr
    Cheepudomwit, Sayan
    Yamwong, Sukit
    Yipintsoi, Tada
    Rajatanavin, Rajata
    [J]. DIABETES CARE, 2006, 29 (08) : 1872 - 1877
  • [2] Diabetes risk score in Oman: A tool to identify prevalent type 2 diabetes among Arabs of the Middle East
    Al-Lawati, J. A.
    Tuomilehto, J.
    [J]. DIABETES RESEARCH AND CLINICAL PRACTICE, 2007, 77 (03) : 438 - 444
  • [3] [Anonymous], 2006, Definition and diagnosis of diabetes mellitus and intermediate hyperglycemia : report of a WHO/IDF consultation, P21
  • [4] [Anonymous], 2000, Diabetes Care, V23, pS20
  • [5] [Anonymous], 2009, BMJ
  • [6] Performance at a predictive model to identity undiagnosed diabetes in a health care setting
    Baan, CA
    Ruige, JB
    Stolk, RP
    Witteman, JCM
    Dekker, JM
    Heine, RJ
    Feskens, EJM
    [J]. DIABETES CARE, 1999, 22 (02) : 213 - 219
  • [7] Predicting Diabetes: Clinical, Biological, and Genetic Approaches Data from the Epidemiological Study on the Insulin Resistance Syndrome (DESIR)
    Balkau, Beverley
    Lange, Celine
    Fezeu, Leopold
    Tichet, Jean
    De Lauzon-Guillain, Blandine
    Cernichow, Sebastien
    Fumeron, Frederic
    Froguel, Philippe
    Vaxillaire, Martine
    Cauchi, Stephane
    Ducimetiere, Pierre
    Eschwege, Eveline
    [J]. DIABETES CARE, 2008, 31 (10) : 2056 - 2061
  • [8] Prevalence of diabetes mellitus and the performance of a risk score among Hindustani Surinamese, African Surinamese and ethnic Dutch: a cross-sectional population-based study
    Bindraban, Navin R.
    van Valkengoed, Irene G. M.
    Mairuhu, Gideon
    Holleman, Frits
    Hoekstra, Joost B. L.
    Michels, Bob P. J.
    Koopmans, Richard P.
    Stronks, Karien
    [J]. BMC PUBLIC HEALTH, 2008, 8 (1)
  • [9] A simple clinical scare for type 2 diabetes mellitus screening in the Canary Wands
    Cabrera de Leon, Antonio
    Dominguez Coello, Santiago
    del Cristo Rodriguez Perez, Maria
    Batista Medina, Marta
    Almeida Gonzalez, Delia
    Brito Diaz, Buenaventura
    Muros de Fuentes, Mercedes
    Aguirre-Jaime, Armando
    [J]. DIABETES RESEARCH AND CLINICAL PRACTICE, 2008, 80 (01) : 128 - 133
  • [10] Prevalence of Type 2 diabetes in urban and rural Chinese populations in Qingdao, China
    Dong, Y
    Gao, W
    Nan, H
    Yu, H
    Li, F
    Duan, W
    Wang, Y
    Sun, B
    Qian, R
    Tuomilehto, J
    Qiao, Q
    [J]. DIABETIC MEDICINE, 2005, 22 (10) : 1427 - 1433