Development of a Validated Diabetes Risk Chart as a Simple Tool to Predict the Onset of Diabetes in Bogor, Indonesia

  • Eva Sulistiowati National Institute of Health Research and Development (NIHRD) https://orcid.org/0000-0003-1863-1647
  • Julianty Pradono National Institutes of Health Research and Development (NIHRD)
Keywords: diabetes screening, risk factors, diabetes, cohort study, Bogor

Abstract

Objective. To develop a simple, non-invasive tool for predicting the onset of type 2 diabetes mellitus (T2DM).

Methodology. A total of 4418 nondiabetic respondents living in Bogor were included in this cohort study. Their ages ranged from 25 to 60 years old and were followed for 6 years with interviews, physical examinations and laboratory tests. The investigators used logistic regression to create a tool for diabetes risk determination. 

Results. The cumulative incidence of T2DM was 17.9%. Risk factors significantly associated with T2DM included age, obesity, central obesity, hypertension and lack of physical activity. The Bogor Diabetes Risk Prediction (BDRP) chart had a cut-off of 0.128, with sensitivity of 76.6% and specificity of 50.3%. The Positive Predictive Value (PPV) was 21.6% and Negative Predictive Value (NPV) was 92.3%. The Area under the Curve (AUC) was 0.70 with a 95% confidence interval ranging from 0.675-0.721.

Conclusion: The BDRP chart  is a simple and non-invasive tool to predict T2DM. In addition, the BDRP chart is reliable and can be easily used in primary health care. 

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Author Biographies

Eva Sulistiowati, National Institute of Health Research and Development (NIHRD)

Researcher

Julianty Pradono, National Institutes of Health Research and Development (NIHRD)

Senior Researcher

References

International Diabetes Federation. IDF Diabetes Atlas 2019 , 9th ed. https://www.idf.org/e-library/epidemiology-research/diabetes-atlas/159-idf-diabetes-atlas-ninth-edition-2019.html.

Badan Penelitian dan Pengembangan Kesehatan Kementerian Kesehatan Republik Indonesia. Riset Kesehatan Dasar (Riskesdas) 2013. Jakarta; 2013. https://www.litbang.kemkes.go.id/laporan-riset-nasional/.

Badan Penelitian dan Pengembangan Kesehatan Kementerian Kesehatan RI. Hasil Utama RISKESDAS 2018. Jakarta; 2018. https://www.litbang.kemkes.go.id/laporan-riset-nasional/.

Badan Penelitian dan Pengembangan Kesehatan Kementerian Kesehatan Republik Indonesia. Laporan Provinsi Jawa Barat, Riskesdas 2018. Lembaga Penerbit Badan Penelitian dan Pengembangan Kesehatan. Jakarta: Lembaga Penerbit Badan Penelitian dan Pengembangan Kesehatan; 2019. https://www.litbang.kemkes.go.id/laporan-riset-nasional/.

Leal J, Morrow LM, Khurshid W, Pagano E, Feenstra T. Decision models of prediabetes populations: A systematic review. Diabetes Obes Metab. 2019;21(7):1558–69. https://pubmed.ncbi.nlm.nih.gov/30828927. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6619188. https://doi.org/10.1111/dom.13684.

Noble D, Mathur R, Dent T, Meads C, Greenhalgh T. Risk models and scores for type 2 diabetes: Systematic review. BMJ. 2011;343:d7163. https://pubmed.ncbi.nlm.nih.gov/22123912. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3225074. https://doi.org/10.1136/bmj.d7163.

Lim NK, Park SH, Choi SJ, Lee KS, Park HY. A risk score for predicting the incidence of type 2 diabetes in a middle-aged Korean cohort - The Korean Genome and epidemiology study. Circ J. 2012;76(8):1904–10. https://pubmed.ncbi.nlm.nih.gov/22640983. https://doi.org/10.1253/circj.cj-11-1236.

Sharkia R, Sheikh-Muhammad A, Mahajnah M, Khatib M, Zalan A. Exploration of risk factors for type 2 diabetes among arabs in Israel. Ann Glob Heal. 2019; 85(1):67. https://pubmed.ncbi.nlm.nih.gov/31074599. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6634318. https;//doi.org/10.5334/aogh.2350.

Lindström J, Tuomilehto J. The diabetes risk score: A practical tool to predict type 2 diabetes risk. Diabetes Care. 2003;26(3):725–31.https://pubmed.ncbi.nlm.nih.gov/12610029. https://doi.org/10.2337/diacare.26.3.725.

Zhang H, Wang C, Ren Y, et al. A risk‐score model for predicting risk of type 2 diabetes mellitus in a rural Chinese adult population: A cohort study with a 6‐year follow‐up. Diabetes Metab Res Rev. 2017;33(7). https://pubmed.ncbi.nlm.nih.gov/28608942. https://doi.org/10.1002/dmrr.2911.

Chen X, Wu Z, Chen Y, et al. Risk score model of type 2 diabetes prediction for rural Chinese adults: The Rural Deqing Cohort Study. J Endocrinol Invest. 2017;40(10):1115-23. https://pubmed.ncbi.nlm.nih.gov/28474301. https://doi.org/10.1007/s40618-017-0680-4.

Zhang HY, Shi WH, Zhnag M, et al. Establishing a non-invasive prediction model for type 2 diabetes mellitus based on a rural Chinese population. Zhonghua Yu Fang Yi Xue Za Zhi. 2016;50 (5):397–403. https://pubmed.ncbi.nlm.nih.gov/27141894. https://doi.org/10.3760/cma.j.issn.0253-9624.2016.05.003.

Kementerian Kesehatan Republik Indonesia. Pedoman Pengukuran dan Pemeriksaan Studi Kohor Penyakit Tidak Menular; 2010. https://www.litbang.kemkes.go.id/layanan-perpustakaan/.

American Diabetes Association. 2. Classification and diagnosis of diabetes: Standards of medical care in diabetes-2019. Diabetes Care. 2019;42(Suppl 1):S13–28. https://pubmed.ncbi.nlm.nih.gov/30559228. https://doi.org/10.2337/dc19-S002.

American Diabetes Association. Updates to the standards of medical care in diabetes-2018. Diabetes Care. 2018;41(9):2045–7. https://pubmed.ncbi.nlm.nih.gov/30135199. https://doi.org/10.2337/dc18-su09.

Siswosudarmo R. Tes diagnostik (Diagnostic test). J Metodol Penelit [Internet]. 2017. http://obgin-ugm.com/wp-content/uploads/2017/09/HRS-Kuliah-Tes-Diagnostik.pdf.

Sastroasmoro S, Ismael S. Dasar-dasar metodologi penelitian klinis, 3rd ed. Jakarta: Sagung Seto; 2008.

Putra IWG. Sutarga IM. Kardiwinata MP. Suariyani NLP. Septarini NW, Subrata I. Modul Penelitian Uji Diagnostik dan Skrining [Internet]. 2016. https://simdos.unud.ac.id/uploads/file_pendidikan_1_dir/d204d4a5ad0870a0965416e671a38791.pdf.

Aekplakorn W, Bunnag P, Woodward M, et al. A risk score for predicting incident diabetes in the Thai population. Diabetes Care. 2006;29(8):1872–7. https://pubmed.ncbi.nlm.nih.gov/16873795. https://doi.org/10.2337/dc05-2141.

Sulaiman N, Mahmoud I, Hussein A, et al. Diabetes risk score in the United Arab Emirates: A screening tool for the early detection of type 2 diabetes mellitus. BMJ Open Diabetes Res Care. 2018;6(1):e000489. https://pubmed.ncbi.nlm.nih.gov/29629178. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5884268. https://doi.org/10.1136/bmjdrc-2017-000489.

Bang H, Edwards AM, Bomback AS, et al. Development and validation of a patient self-assessment score for diabetes Risk. Ann Intern Med. 2009;151(11):775-83. https://pubmed.ncbi.nlm.nih.gov/19949143. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3633111. https://doi.org/10.7326/0003-4819-151-11-200912010-00005.

Chen L, Magliano DJ, Balkau B, et al. AUSDRISK: An Australian type 2 diabetes risk assessment tool based on demographic, lifestyle and simple anthropometric measures. Med J Aust. 2010;192(4):197–202. https://pubmed.ncbi.nlm.nih.gov/20170456. https://doi.org/10.5694/j.1326-5377.2010.tb03507.x.

Glümer C, Carstensen B, Sandbaek A, Lauritzen T, Jorgensen T, Borch-Johnsen K. A Danish diabetes risk score for targeted screening. Diabetes Care. 2004;27(3):727–33. https://pubmed.ncbi.nlm.nih.gov/14988293. https://doi.org/10.2337/diacare.27.3.727.

Al-Lawati JA, Tuomilehto J. Diabetes risk score in Oman: A tool to identify prevalent type 2 diabetes among Arabs of the Middle East. Diabetes Res Clin Pract. 2007;77(3):438–44. https://pubmed.ncbi.nlm.nih.gov/17306410. https://doi.org/10.1016/j.diabres.2007.01.013.

Gao WG, Dong YH, Pang ZC, et al. A simple Chinese risk score for undiagnosed diabetes. Diabet Med. 2010;27(3):274–81. https://pubmed.ncbi.nlm.nih.gov/20536489. https://doi.org/10.1111/j.1464-5491.2010.02943.x.

Mohan V, Deepa R, Deepa M, Somannavar S, Datta M. A simplified Indian Diabetes Risk Score for screening for undiagnosed diabetic subjects. J Assoc Physicians India. 2005;53:759–63. https://pubmed.ncbi.nlm.nih.gov/16334618.

American Diabetes Association. Are you at risk for type 2 diabetes? 2009. http://main.diabetes.org/dorg/PDFs/risk-test-paper-version.pdf.

Pertiwi MD. Identifikasi Pengetahuan Ibu Hamil Dalam Manajemen Penyakit Diabetes Mellitus Gestasional Di Puskesmas Minggir Yogyakarta; 2019.

Published
2022-04-27
How to Cite
Sulistiowati, E., & Pradono, J. (2022). Development of a Validated Diabetes Risk Chart as a Simple Tool to Predict the Onset of Diabetes in Bogor, Indonesia. JAFES , 37(1). Retrieved from https://asean-endocrinejournal.org/index.php/JAFES/article/view/1225
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Original Articles