Abstrak: Although prevalence and incidence of type 2 diabetes mellitus (T2DM) are reportedly increasing among adolescents, national data are lacking, particularly in regard to undiagnosed T2DM. To estimate the prevalence of diagnosed and undiagnosed T2DM among US adolescents, we analyzed a nationally representative cross-section of 11,888 adolescents aged 12-19 years who received a diabetes interview in the Continuous National Health and Nutrition Examination Survey during 1999-2010. Among them, a random subsample of 4,661 adolescents also had fasting blood samples collected. Persons who reported a previous diabetes diagnosis and were either taking no medication or taking an oral hypoglycemic agent (with or without insulin) were classified as having T2DM; persons who reported using insulin alone were classified as having type 1 diabetes. Undiagnosed diabetes was defined as a fasting plasma glucose concentration of ≥126 mg/dL and was assumed to be type 2. In the fasting subsample, 31 diabetes cases (types 1 and 2) were identified, representing a prevalence of 0.84% (weighted 95% confidence interval (CI): 0.51, 1.40) (276,638 cases; 95% CI: 134,255, 419,020). Estimates of the prevalences of type 1 and type 2 diabetes were 0.48% (95% CI: 0.23, 1.02) and 0.36% (95% CI: 0.20, 0.67), respectively, indicating that T2DM accounted for 43% of all cases. Further, undiagnosed T2DM prevalence was 0.12% (95% CI: 0.05, 0.31), representing 34% of T2DM cases (40,611 cases; 95% CI: 2,850, 78,373). T2DM accounts for approximately half of adolescent diabetes in the United States, and one-third of these cases are undiagnosed.

Abstrak: Tujuan: Penelitian ini bertujuan untuk menemukan faktor risiko dominandan membuat skor risiko diabetes tidak terdiagnosis (UDDM) dan prediabetes.Metode: Pembuatan skor risiko berdasarkan data yang tersedia hasil RisetKesehatan Dasar 2013, dengan kriteria ≥ 18 tahun, baru terdiagnosis saat Riskesdas,tidak menderita penyakit kronis/menular lainnya. Nilai koefisien β hasil analisisregresi logistik multinomial model prediksi digunakan untuk mengenmbangkan skor.Keakuratan skor prediksi diabetes dan prediabetes dinilai dengan ROC (ReceiverOperating Characteristic). Hasil: Dua model prediksi dikembangkan menjadi skorrisiko. Model 1 prediksi diabetes tidak terdiagnosis dengan 7 prediktor AUC 73,5%,sen 62,2%, spes 70,8%, PPV 12,8%, NPV 96,5%, titik potong ≥22, model 2 prediksidiabetes tidak terdiagnosis dengan 5 prediktor AUC 72,4%, sen 68,3%, spes 64,7%,PPV 11,8%, NPV 96,7%, titik potong ≥20. Prediksi prediabetes tidak dikembangkanmenjadi skor karena tidak akurat, tetapi dapat diketahui faktor dominannya.Kesimpulan: Indonesia dapat memiliki perhitungan skor risiko guna memprediksidiabetes yang tidak terdiagnosis berdasarkan data Riset Kesehatan Dasar yangtersedia. Skor Risiko tersebut dapat digunakan tenaga kesehatan untukmengidentifikasi individu dengan risiko tinggi dan masyarakat awam mampumenggunakan skor tersebut.Kata kunci : Prediabetes, Diabetes tidak terdiagnosis (UDDM), faktor risiko, skor

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Objective: This studi aims to find the risk factors and develop risk scorefor undiagnosed diabetes and prediabetes. Method: Risk score madebased on available data from Basic Health Research 2013 in Indonesia,with criteria 18-55 years old, newly diagnosed diabetes, and not affectedby chronic /infectious diseases before.β coeff value from multinomiallogistic regression analysis results of predictive models are used todevelop risk score. The accuracy of risk score assessed with ROC(Receiver Operating Characteristic). Result: 2 prediction models are useto develop risk score. The accuracy form 7 predictors for undiagnoseddiabetes in model 1 are AUC 73.5%, sen 62.2%, spes 70.8%, PPV 12.8%,NPV 96.5%, cut off ≥22. The accuracy form 5 predictors for undiagnoseddiabetes in model 2 are AUC 72.4%, sen 68.3%, spes 64.7%, PPV 11.8%,NPV 96.7%, cut off ≥20 . Score predikction for diabetes not developed,because of poor accuray, but the result of analysis can showed prediabetesdominant risk factors. Conclusion: Indonesia may have a risk scorecalculation for predicting undiagnosed diabetes based on data from HealthResearch provided. The risk score can be used by health workers toindentified individuals with high-risk and the general public are able touse these scores.Keyword : prediabetes, undiagnosed diabetes, risk factor, score