TYPE 2 DIABETES MELLITUS PREDICTION IN MALAYSIA USING MODIFIED DIABETES RISK ASSESSMENT TOOL

  • Aung Myo Oo Biochemistry Unit, Faculty of Medicine and Health Sciences, University Sultan Zainal Abidin, Jalan Sultan Mahmud,20400, Kuala Terengganu, Malaysia
  • Al-abed Ali Ahmed Al-abed Community Medicine Unit, Faculty of Medicine, Lincoln University College, 47301, Petaling Jaya, Selangor, Malaysia
  • Ohn Mar Lwin Physiology Unit, Faculty of Medicine, Lincoln University College, 47301, Petaling Jaya, Selangor, Malaysia
  • Sowmya Sham Kanneppady Department of Pharmacology, Srinivas institute of Medical sciences and Research Centre, Mukka Surathkal, India
  • Tee Yee Sim Department of Pharmacology, Faculty of Medicine and Health Sciences, Management and Science University, Malaysia
  • Nor Ashikeen Mukti Department of Biochemistry, Faculty of Medicine and Health Sciences, Management and Science University, Malaysia
  • Anis Safirah Zahariluddin Department of Microbiology, Faculty of Medicine, University Kebangsaan Malaysia, Pekan Bangi, 43600 Bangi, Selangor, Malaysia.
  • Faizul Jaffar Department of Biochemistry, Faculty of Medicine, University Kebangsaan Malaysia, Pekan Bangi, 43600 Bangi, Selangor, Malaysia
Keywords: Type 2 diabetes mellitus, assessment tool, health screening, prevention

Abstract

Type 2 diabetes mellitus (DM) is becoming major health threat worldwide and it is extremely common in clinical setting. Malaysia is one of the highest diabetic populations among Asian countries and the new cases are increasing day to day. Early detection of people with high risk of Type 2 DM by using simple, easy and cost-effective assessment tool is the better way to identify and prevent the community from this non-communicable disease. The objectives of the study were to identify those are high risk to become type 2DM among Malaysians by using risk scoring form and to educate them how to prevent it. Total 591 subjects were recruited from the health screening programs carried out by the collaboration of Petaling Jaya Development Council (MBPJ) and Lincoln University College, Malaysia. Modified form of Finnish Type 2 Diabetes Risk Assessment Tool was used to identify people at risk of becoming type 2 DM. Descriptive analysis was performed for all included variables in this study by using SPSS version 21. The study found out that almost half of the participants were found to have family history of DM, 60% of them were overweight and obese and 47% were having above normal waist circumference. We observed that nearly 60 % of participants in the study were having moderate to high risk of becoming type 2 DM in next 10 years. To conclude, the result of our study would be helpful in implementation of cost-effective, convenient Type 2 DM risk assessment tool which has yet to be implemented in Malaysia.

References

Mathers CD and Loncar D: Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med, 2006, 3(11): e442.

International Diabetes Federation One adult in ten will have diabetes by 2030. November 14, 2011. Available from http://www.idf.org/media-events/press-releases/2011/diabetes-atlas-5th-edition

The Sun daily. Malaysia has fourth highest diabetics in Asia. November 2016, Available from http://www.thesundaily.my/news/2057274

The Star online. Alarming increase in diabetes among Malaysians., April 2016, Available from http://www.thestar.com.my/news/nation/2016/04/08/hilmi-alarming-increase-in-diabetes-among-malaysians/#HHxWJkelbyj5HBJy.99

"Population by States and Ethnic Group". Department of Information, Ministry of Communications and Multimedia, Malaysia. 2015. Archived from the original on 12 February 2016. Available from https://web.archive.org/web/20160212125740/http:/pmr.penerangan.gov.my/index.php/info-terkini/19463-unjuran-populasi-penduduk-2015.html

Non-Communicable Disease Section Disease Control Division Ministry of Health Malaysia National Diabetes Registry Report Volume 1 2009-2012

Hariri S, Yoon PW, Moonesinghe R, Valdez R and Khoury MJ. Evaluation of family history as a risk factor and screening tool for detecting undiagnosed diabetes in a nationally representative survey population. Genet Med. 2006 Dec; 8(12):752-9.

Das M, Pal S, and Ghosh A. Family history of type 2 diabetes and prevalence of metabolic syndrome in adult Asian Indians. Journal of Cardiovascular Disease Research, 2012, 3(2), 104–108.

Awasthi A, Rao CR, Hegde DS, et al. Association between type 2 diabetes mellitus and anthropometric measurements – a case control study in South India. Journal of Preventive Medicine and Hygiene, 2017, 58(1), E56–E62.

Gray N, Picone G, Sloan F, et al. The Relationship between BMI and Onset of Diabetes Mellitus and its Complications. Southern Medical Journal, 2015,108(1), 29–36.

Hartwig S, Kluttig A, Tiller D, et al. Anthropometric markers and their association with incident type 2 diabetes mellitus. Which marker is best for prediction? BMJ Open. 2016 Jan 20; 6(1): e009266. Epub 2016 Jan 20.

Malik VS, Popkin BM, Bray GA, et al. Sugar-sweetened beverages and risk of metabolic syndrome and type 2 diabetes: a meta-analysis. Diabetes Care. 2010;33:2477-83.

Bazian: High blood pressure: does it lead to diabetes? NHS Choices Thursday October 1 2015. https://www.nhs.uk/news/diabetes/high-blood-pressure-does-it-lead-to-diabetes/

Centers for Disease Control and Prevention. National diabetes fact sheet: national estimates and general information on diabetes and prediabetes in the United States, 2011. Atlanta:U.S. Department of Health and Human Services, Centers for Disease Control andPrevention.

Suastika K, Dwipayana P, Saraswati IMR, et al. Relationship between age and metabolic disorder in the population of Bali. J Clin Gerontol Geriatrics 2011, 30: 1-6.

Lindstrom J and Tuomilehto J. The diabetes risk score: a practical tool to predict type 2 diabetes risk. Diabetes Care 2003. 26:725-731.

Australian type 2DM risk assessment tool (AUSDRISK) Available from https://static.diabetesaustralia.com.au/s/fileassets/diabetes-australia/6d252140-1ff0-47b2-a83f-3cc3db348131.pdf

Clinical practice guidelines management of type 2 diabetes mellitus,2015 (5th Edition). Available from http://www.moh.gov.my/penerbitan/CPG/CPG%20T2DM%202015.pdf

Clinical practice guideline for obesity, Malaysia 2004. Available from http://www.moh.gov.my/penerbitan/CPG2017/3932.pdf

Waist Circumference and Waist–Hip Ratio: Report of a WHO Expert Consultation Geneva, 8–11 December 2008.Available from http://apps.who.int/iris/bitstream/10665/44583/1/9789241501491_eng.pdf

Obesity, A growing problem. The Star News, May 2016. Available from http://www.thestar.com.my/news/nation/2016/05/02/obesity-a-growing problem/#dGLjcZqWQ216fgK0.99

Scott1RA, Langenberg1C, Sharp SJ, et al: The link between Family History and risk of Type 2 Diabetes is Not Explained by Anthropometric, Lifestyle or Genetic Risk Factors: the EPIC-InterAct Study; Diabetologia. 2013 January; 56(1): 60–69. doi:10.1007/s00125-012-2715-x.

Hussein Z, Taher SW, Singh HKG and Swee WCS: Diabetes Care in Malaysia: Problems, New Models, and Solutions; Annals of Global Health,2015; vol. 81, no. 6, 2015.

Chan YY, Lim KK, Lim KH, Teh CH, Kee CC, Cheong SM, et al. Physical activity and overweight/obesity among Malaysian adults: findings from the 2015 National Health and morbidity survey (NHMS). BMC Public Health,2017, 17, 733. http://doi.org/10.1186/s12889-017-4772-z

Malaysia at risk of becoming a chubby nation. The News Strait Times; May 2016. Available from http://www.nst.com.my/news/2016/05/143258/malaysia-risk-becoming-chubby-nation

Jelic K, Luzio SD, Dunseath G, Colding-Jorgsensen M and Owens DR. A cross-sectional analysis of NEFA levels following standard mixed meal in a population of persons with newly diagnosed type 2 diabetes mellitus across a spectrum of glycemic control: American Diabetes Association; 2007. Available from: http://professional.diabetes.org/Abstracts_Display.aspx?

Kahn SE, Hull RL and Utzschneider KM. Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature. 2006 Dec 14; 444(7121):840-6.

D’ Souza MS, Amirtharaj A, Venkatesaperumal R, et al : Risk-assessment score for screening diabetes mellitus among Omani adults; SAGE Open Med. 2013; 1: 2050312113508390

Ishaque A, Shahzad F, Muhammad F, et al. Diabetes risk assessment among squatter settlements in Pakistan: A cross-sectional study. Malaysian Family Physician: The Official Journal of the Academy of Family Physicians of Malaysia, 2016; 11(2-3), 9–15.

Aekplakorn W, Bunnag P, Woodward M, et al.: A risk score for predicting incident diabetes in the Thai population. Diabetes Care. 2006 Aug;29(8):1872-7.

Published
2020-05-01
How to Cite
Aung Myo Oo, Al-abed Ali Ahmed Al-abed, Ohn Mar Lwin, Sowmya Sham Kanneppady, Tee Yee Sim, Nor Ashikeen Mukti, Anis Safirah Zahariluddin, & Faizul Jaffar. (2020). TYPE 2 DIABETES MELLITUS PREDICTION IN MALAYSIA USING MODIFIED DIABETES RISK ASSESSMENT TOOL . Malaysian Journal of Public Health Medicine, 20(1), 15-21. https://doi.org/10.37268/mjphm/vol.20/no.1/art.442