Predicting type 2 diabetes risk among adults aged 40 - 79 and determining the optimal findrisc threshold in the population of Kon Tum province
Main Article Content
Abstract
The burden of type 2 diabetes mellitus (T2DM) is increasing in Vietnam, particularly in resource-limited areas. This cross-sectional study assessed T2DM risk among 1,071 individuals aged 40-79 in Kon Tum province using the Modified Asian FINDRISC tool and identified the optimal cut-off score. Logistic regression and receiver operating characteristics (ROC) curve analysis were used to determine risk factors and the optimal cut-off threshold. The mean FINDRISC score was 7.3 ± 3.4, with a projected 10-year T2DM risk of 4.44%. Key risk factors included age ≥ 60, history of hypertension, BMI ≥ 23, central obesity, and low physical activity. The optimal cut-off point was 9.5 for the Kinh ethnic group (sensitivity 46.7%, specificity 74.2%) and 12.5 for ethnic minorities (sensitivity 18.8%, specificity 97.2%). This study highlights the necessity of integrating FINDRISC into routine diabetes screening at the primary care level, with cut-off points adjusted for risk factors and population characteristics to enhance early type 2 diabetes detection.
Article Details
Keywords
Type 2 diabetes mellitus, risk prediction, diabetes screening, ModAsian FINDRISC, primary care
References
2. Nguyen TP, Gilmour S, Le PM, et al. Trends in, projections of, and inequalities in non-communicable disease management indicators in Vietnam 2010-2030 and progress toward universal health coverage: A Bayesian analysis at national and sub-national levels. EClinicalMedicine. 2022; 51: 101550. doi:10.1016/j.eclinm.2022.101550.
3. Lim HM, Chia YC, Koay ZL. Performance of the Finnish Diabetes Risk Score (FINDRISC) and Modified Asian FINDRISC (ModAsian FINDRISC) for screening of undiagnosed type 2 diabetes mellitus and dysglycaemia in primary care. Prim Care Diabetes. 2020; 14(5): 494-500. doi:10.1016/j.pcd.2020.02.008.
4. Cahyaningsih I, Rokhman MR, Sudikno, Postma MJ, van der Schans J. Accuracy of the Modified Finnish Diabetes Risk Score (Modified FINDRISC) for detecting metabolic syndrome: Findings from the Indonesian national health survey. PLoS One. 2025; 20(2): e0314824. doi:10.1371/journal.pone.0314824.
5. Gabriel R, Acosta T, Florez K, et al. Validation of the Finnish Type 2 Diabetes Risk Score (FINDRISC) with the OGTT in Health Care Practices in Europe. Diabetes Res Clin Pract. 2021; 178: 108976. doi:10.1016/j.diabres.2021.108976.
6. Rokhman MR, Arifin B, Zulkarnain Z, et al. Translation and performance of the Finnish Diabetes Risk Score for detecting undiagnosed diabetes and dysglycaemia in the Indonesian population. PLoS One. 2022; 17(7): e0269853. doi:10.1371/journal.pone.0269853.
7. Trần Hữu Dàng, Nguyễn Đức Kiên. Nghiên cứu nguy cơ đái tháo đường theo thang điểm FINDRISC trên bệnh nhân tăng huyết áp. Tạp chí Nội tiết và Đái tháo đường. 2020;39(1):24-27. doi:10.47122/vjde.2020.39.3.
8. Hồ Thị Dung, Nguyễn Thị Linh. Đánh giá nguy cơ đái tháo đường theo thang điểm FINDRISC trên bệnh nhân tăng huyết áp tại bệnh viện đa khoa 115 Nghệ An năm 2022. Tạp chí Y học Việt Nam. 2023; 527(2): 32-36. doi: 10.51298/vmj.v527i2.5840.
9. Doan PPL, Nguyen TH, Nguyen TPT, Phan TTL, Le DH, Nguyen TTH, Doan PT. ModAsian FINDRISC as a Screening Tool for People with Undiagnosed Type 2 Diabetes Mellitus in Vietnam: A Community-Based Cross-Sectional Study. Journal of Multidisciplinary Healthcare. 2023; 16: 439-449. doi:10.2147/JMDH.S398455.
10. Lê Nguyễn Trí Nhân, Võ Duy Nhàn, Lê Trung Khả và cộng sự. Tính giá trị của thang đo findrisc trong phát hiện bệnh đái tháo đường týp 2 trên người trưởng thành tại huyện Phong Điền, thành phố Cần Thơ năm 2021. Tạp chí Y dược học Cần Thơ. 2022; 50: 33-40. doi:10.58490/ctump.2022i50.119.
11. Babor TF, Higgins-Biddle JC, Saunders JB, Monteiro MG. AUDIT: The Alcohol Use Disorders Identification Test: Guidelines for Use in Primary Health Care. 2nd ed. World Health Organization; 2001.
12. Traoré S, Paré BC, Dabourou DL. Performance of the Finnish diabetes risk score (FINDRISC) in the identification of Dysglycemia in an urban population in Ouagadougou (Burkina Faso). Open Journal of Internal Medicine. 2021; 11(02): 39-54. doi:10.4236/ojim.2021.112003.
13. Ismail L, Materwala H, Al Kaabi J. Association of risk factors with type 2 diabetes: A systematic review. Comput Struct Biotechnol J. 2021; 19:1759-1785. doi: 10.1016/j.csbj.2021.03.003.
14. Hayashi T, Tsumura K, Suematsu C, Endo G, Fujii S, Okada K. High normal blood pressure, hypertension, and the risk of type 2 diabetes in Japanese men. The Osaka Health Survey. Diabetes Care. 1999; 22(10): 1683-7. doi: 10.2337/diacare.22.10.1683. PMID: 10526735.
15. Kyrou I, Tsigos C, Mavrogianni C, et al. Sociodemographic and lifestyle-related risk factors for identifying vulnerable groups for type 2 diabetes: a narrative review with emphasis on data from Europe. BMC Endocr Disord. 2020; 20 (Suppl 1): 134. doi:10.1186/s12902-019-0463-3.
16. Hemmingsen B, Gimenez-Perez G, Mauricio D, et al. Diet, physical activity or both for prevention or delay of type 2 diabetes mellitus and its associated complications in people at increased risk of developing type 2 diabetes mellitus. Cochrane Database of Systematic Reviews. 2017; 12(12):CD003054. doi:10.1002/14651858.CD003054.pub4.
17. Bennet L, Groop L, Lindblad U, Agardh CD, Franks PW. Ethnicity is an independent risk indicator when estimating diabetes risk with FINDRISC scores: a cross sectional study comparing immigrants from the Middle East and native Swedes. Prim Care Diabetes. 2014; 8(3): 231-238. doi:10.1016/j.pcd.2014.01.002.