316
Views
1
CrossRef citations to date
0
Altmetric
ORIGINAL RESEARCH

ModAsian FINDRISC as a Screening Tool for People with Undiagnosed Type 2 Diabetes Mellitus in Vietnam: A Community-Based Cross-Sectional Study

ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon show all
Pages 439-449 | Received 24 Nov 2022, Accepted 02 Feb 2023, Published online: 17 Feb 2023

References

  • Bramlage P, Rey A, Thoenes M. Diabetes prevalence and metabolic risk profile in an unselected population visiting pharmacies in Switzerland. Vasc Health Risk Manag. 2012;541. doi:10.2147/VHRM.S35896
  • Liu M, Pan C, Jin M; Chinese Diabetes A. Risk score for screening of undiagnosed diabetes and abnormal glucose tolerance. Diabetes Technol Ther. 2011;13(5):501–507. doi:10.1089/dia.2010.0106
  • Ogurtsova K, da Rocha Fernandes JD, Huang Y, et al. IDF diabetes atlas: global estimates for the prevalence of diabetes for 2015 and 2040. Diabetes Res Clin Pract. 2017;128:40–50. doi:10.1016/j.diabres.2017.03.024
  • Nnamudi AC, Orhue NEJ, Ijeh II. Assessment of the FINDRISC tool in predicting the risk of developing type 2 diabetes mellitus in a young adult Nigerian population. Bull Natl Res Cent. 2020;44(1):186. doi:10.1186/s42269-020-00440-7
  • Levitt NS. Diabetes in Africa: epidemiology, management, and healthcare challenges. Heart. 2008;94(11):1376–1382. doi:10.1136/hrt.2008.147306
  • Selph S, Dana T, Blazina I, Bougatsos C, Patel H, Chou R. Screening for type 2 diabetes mellitus: a systematic review for the U.S. Preventive services task force. Ann Intern Med. 2015;162(11):765–776. doi:10.7326/M14-2221
  • Brown N, Critchley J, Bogowicz P, Mayige M, Unwin N. Risk scores based on self-reported or available clinical data to detect undiagnosed Type 2 Diabetes: a systematic review. Diabetes Res Clin Pract. 2012;98(3):369–385. doi:10.1016/j.diabres.2012.09.005
  • Paulweber B, Valensi P, Lindström J, et al. A European evidence-based guideline for the prevention of type 2 diabetes. Horm Metab Res. 2010;42(S 01):S3–S36. doi:10.1055/s-0029-1240928
  • Glümer C, Carstensen B, Sandbæk A, et al. Risk Score for Targeted Screening. Diabetes Care. 2004;27(3):727–733. doi:10.2337/diacare.27.3.727
  • Lindström J, Tuomilehto J. The diabetes risk score: a practical tool to predict type 2 diabetes risk. Diabetes Care. 2003;26(3):725–731. doi:10.2337/diacare.26.3.725
  • Zhou X, Qiao Q, Ji L, et al. Nonlaboratory-based risk assessment algorithm for undiagnosed type 2 diabetes developed on a nation-wide diabetes survey. Diabetes Care. 2013;36(12):3944–3952. doi:10.2337/dc13-0593
  • Hippisley-Cox J, Coupland C. Development and validation of QDiabetes-2018 risk prediction algorithm to estimate future risk of type 2 diabetes: cohort study. BMJ. 2017;j5019. doi:10.1136/bmj.j5019
  • Lindström J, Louheranta A, Mannelin M, et al. The Finnish Diabetes Prevention Study (DPS): lifestyle intervention and 3-year results on diet and physical activity. Diabetes Care. 2003;26(12):3230–3236. doi:10.2337/diacare.26.12.3230
  • Janghorbani M, Adineh H, Amini M. Evaluation of the Finnish Diabetes Risk Score (FINDRISC) as a screening tool for the metabolic syndrome. Rev Diabet Stud RDS. 2013;10(4):283–292. doi:10.1900/RDS.2013.10.283
  • Rodríguez MG, Saldaña MR, Leyva JMA, Rojas RM, Molina-Recio G. The FINDRISC questionnaire capacity to predict diabetes mellitus II, arterial hypertension and comorbidity in women from low-and-middle-income countries. Health Care Women Int. 2020;41(2):205–226. doi:10.1080/07399332.2019.1680678
  • Muñoz-González MC, Lima-Martínez MM, Nava A, et al. FINDRISC modified for Latin America as a screening tool for persons with impaired glucose metabolism in Ciudad Bolívar, Venezuela. Med Princ Pract. 2019;28(4):324–332. doi:10.1159/000499468
  • Alberti KGMM, Zimmet P, Shaw J. International Diabetes Federation: a consensus on Type 2 diabetes prevention. Diabet Med J Br Diabet Assoc. 2007;24(5):451–463. doi:10.1111/j.1464-5491.2007.02157.x
  • Roglic G. WHO Global report on diabetes: a summary. Int J Noncommunicable Dis. 2016;1(1):3. doi:10.4103/2468-8827.184853
  • 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
  • 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
  • Châu LM, Cảnh ĐX. The prediction of type 2 diabetes for next years in 3 districts in Hung Yen province using the FINDRISC tool (Dự báo bệnh đái tháo đường typ 2 tại 3 huyện tỉnh Hưng Yên 10 năm theo thang điểm FINDRISC). Vietnam J Prev Med. 2019;29(2):52–59.
  • Mai VQ, Đạt NV, Thiệu LH, et al. Prediction of undiagnosed diabetes and prediabetes by Findrisc scale in subjects over 45 years old in Khanh Hoa province (Dự báo tiền đái tháo đường và đái tháo đường không được chẩn đoán ở đối tượng trên 45 tuổi tại tỉnh Khánh Hòa theo thang điểm FINDRISC). Vietnam J Prev Med. 2017;28(8):95–102.
  • Trần HD, Nguyễn ĐK. Study on the risk of diabetes by FINDRISC scale in hypertension patients (Nghiên cứu nguy cơ đái tháo đường theo thang điểm FINDRISC trên bệnh nhân tăng huyết áp). Vietnam J Diabetes Endocrinol. 2020;39:23–27. doi:10.47122/vjde.2020.39.3
  • Vinh NT. Using FINDRISC in screening for type 2 diabetes (Sử dụng thang điểm FINDRISC trong sàng lọc đái tháo đường tuýp 2). Vietnam J Health Policy. 2020;30:69–75.
  • Hajian-Tilaki K. Sample size estimation in diagnostic test studies of biomedical informatics. J Biomed Inform. 2014;48:193–204. doi:10.1016/j.jbi.2014.02.013
  • The Lancet Infectious Diseases. COVID-19: endgames. Lancet Infect Dis. 2020;20(5):511. doi:10.1016/S1473-3099(20)30298-X
  • Vietnamese Ministry of Health. Coronavirus disease (COVID-19) outbreak in Vietnam; 2020. Available from: https://ncov.moh.gov.vn/. Accessed April 5, 2022.
  • World Health Organization. Novel coronavirus (2019-nCoV) technical guidance; 2021. Available from: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/technicalguidance. Accessed April 5, 2022.
  • Bui TV, Blizzard CL, Luong KN, et al. National survey of risk factors for non-communicable disease in Vietnam: prevalence estimates and an assessment of their validity. BMC Public Health. 2016;16:498. doi:10.1186/s12889-016-3160-4
  • World Health Organization, Regional Office for the Western Pacific, International Association for the Study of Obesity, International Obesity TaskForce. The Asia-Pacific Perspective: redefining Obesity and Its Treatment; 2002.
  • Jølle A, Midthjell K, Holmen J, et al. Validity of the FINDRISC as a prediction tool for diabetes in a contemporary Norwegian population: a 10-year follow-up of the HUNT study. BMJ Open Diabetes Res Care. 2019;7(1):e000769. doi:10.1136/bmjdrc-2019-000769
  • Do IT, Tran HD, Ton TT, et al. Risk prediction model for type 2 diabetes mellitus using Finnish diabetes risk score (FINDRISC) among adult population in Da Nang city. Vietnam J Prev Med. 2017;2:137–141.
  • Hageman S, Pennells L, Ojeda F; SCORE2 working group and ESC Cardiovascular risk collaboration. SCORE2 risk prediction algorithms: new models to estimate 10-year risk of cardiovascular disease in Europe. Eur Heart J. 2021;42(25):2439–2454. doi:10.1093/eurheartj/ehab309
  • de Vries TI, Cooney MT, Selmer RM; SCORE2-OP working group and ESC Cardiovascular risk collaboration. SCORE2-OP risk prediction algorithms: estimating incident cardiovascular event risk in older persons in four geographical risk regions. Eur Heart J. 2021;42(25):2455–2467. doi:10.1093/eurheartj/ehab312
  • Chen D, Zhang H, Cui N, et al. Development of a behavior change intervention to improve physical activity adherence in individuals with metabolic syndrome using the behavior change wheel. BMC Public Health. 2022;22(1):1740. doi:10.1186/s12889-022-14129-1
  • Lemstra M, Bird Y, Nwankwo C, Rogers M, Moraros J. Weight-loss intervention adherence and factors promoting adherence: a meta-analysis. Patient Prefer Adherence. 2016;10:1547–1559. doi:10.2147/PPA.S103649
  • Akinosun AS, Polson R, Diaz-Skeete Y, et al. Digital technology interventions for risk factor modification in patients with cardiovascular disease: systematic review and meta-analysis. JMIR MHealth UHealth. 2021;9(3):e21061. doi:10.2196/21061
  • Hinchliffe N, Capehorn MS, Bewick M, Feenie J. The potential role of digital health in obesity care. Adv Ther. 2022;39(10):4397–4412. doi:10.1007/s12325-022-02265-4