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1.
Diabetes Technol Ther ; 16(12): 853-7, 2014 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-25014878

RESUMO

BACKGROUND: Europeans and Americans are gradually accepting the hemoglobin A1c (HbA1c) threshold of 6.5% for diagnosing diabetes proposed by the American Diabetes Association, but the cutoff of HbA1c for the Chinese population is unclear. We evaluated the diagnostic efficiency of HbA1c for diagnosing newly diagnosed diabetes and prediabetes in community-based Chinese adults 40 years of age or older. SUBJECTS AND METHODS: In this study 8,239 subjects (5,496 women) 40-90 years of age underwent HbA1c and oral glucose tolerance test measurement after an overnight fast. Diabetes and prediabetes were defined by the World Health Organization criteria. The area under the receiver operating characteristic curve (AUC) was used to evaluate the diagnostic efficiency of HbA1c, and the optimal cutoff was defined as the point on the receiver operating characteristic curve with the largest Youden index. Spearman correlation was used for correlation analysis. RESULTS: The prevalence of newly diagnosed diabetes and prediabetes was 10.7% (880/8,239) and 19.0% (1,564/8,239), respectively. Fasting plasma glucose and postprandial plasma glucose were positively correlated with HbA1c level (r=0.725 and r=0.673, both P<0.001, respectively). For diagnosing diabetes, the AUC was 0.857 (95% confidence interval, 0.841-0.873), and the optimal cutoff for HbA1c was 6.3%, with the largest Youden index being 0.581. For diagnosing prediabetes, the AUC was 0.681 (95% confidence interval, 0.666-0.697), and the optimal cutoff for HbA1c was 5.9%, with the largest Youden index being 0.280. CONCLUSIONS: An HbA1c threshold of 6.3% was highly valuable for diagnosing newly diagnosed diabetes, and a value of 5.9% was weakly valuable for diagnosing prediabetes in community-based Chinese adults 40 years of age or older.


Assuntos
Diabetes Mellitus Tipo 2/diagnóstico , Hemoglobinas Glicadas/análise , Estado Pré-Diabético/diagnóstico , Adulto , Idoso , Idoso de 80 Anos ou mais , Glicemia/análise , China/epidemiologia , Estudos Transversais , Diabetes Mellitus Tipo 2/sangue , Diabetes Mellitus Tipo 2/epidemiologia , Diabetes Mellitus Tipo 2/etnologia , Diagnóstico Diferencial , Feminino , Teste de Tolerância a Glucose , Inquéritos Epidemiológicos , Humanos , Masculino , Pessoa de Meia-Idade , Período Pós-Prandial , Guias de Prática Clínica como Assunto , Estado Pré-Diabético/sangue , Estado Pré-Diabético/epidemiologia , Estado Pré-Diabético/etnologia , Prevalência , Sensibilidade e Especificidade
2.
Biomed Environ Sci ; 27(5): 353-9, 2014 May.
Artigo em Inglês | MEDLINE | ID: mdl-24827716

RESUMO

OBJECTIVE: To study the optimal waist circumference (WC) cut-off values for identifying metabolic risk factors in middle-aged and elderly subjects in Shandong Province of China. METHODS: A total of 2,873 men and 5,559 women were included in this cross-sectional study. Metabolic syndrome (MetS) was diagnosed according to the definition of Chinese Diabetes Society in 2004. The relation between WC and MetS was analyzed by multivariate logistic regression analysis. The optimal WC cut-off values were identified using the area under the ROC curve and the different diagnostic criteria for central obesity were compared. RESULTS: The WC was the risk factor for MetS independent of BMI, blood glucose, blood lipid, and blood pressure. The optimal WC cut-off value was 83.8 cm and 91.1 cm for identifying MetS in women and men, respectively. Compared with 80 cm and 85 cm for women and men, 85 cm and 90 cm had a higher Youden index for identifying all metabolic risk factors and MetS in women and men. CONCLUSION: The appropriate WC cut-off value is 85 cm and 90 cm for identifying central obesity and MetS in women and men in Shandong Province of China.


Assuntos
Síndrome Metabólica/diagnóstico , Obesidade Abdominal/diagnóstico , Circunferência da Cintura , Idoso , Área Sob a Curva , Estudos Transversais , Feminino , Humanos , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Valor Preditivo dos Testes
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