Prediabetes Screening with American Diabetes Association (ADA) Scoring in the Primary Health Care Yogyakarta (Development And Validation Of Scoring Systems)

https://doi.org/10.22146/rpcpe.50503

Yaltafit Abror Jeem(1*), Hari Koesnanto(2), Muhammad Robikhul Ikhsan(3)

(1) Clinical Medicine Department of Family and Community Medicine, Faculty of Medicine, Public Health, and Nursing Universitas Gadjah Mada
(2) Department of Family and Community Medicine, Faculty of Medicine, Public Health, and Nursing Universitas Gadjah Mada
(3) Department of Internal Medicine, Diabetic Endocrine Sub Part Faculty of Medicine, Public Health, and Nursing Universitas Gadjah Mada
(*) Corresponding Author

Abstract


Background: Numerous studies have shown  the increasing of prediabetes incidence from the time being. Some of the prediabetes screening methods that can be performed at primary health care were American Diabetes Association (ADA) scoring for prediabetes. However, there was no data that describes the validity and applicability of the ADA scoring on prediabetes patients in Indonesia. Objective: To discribe prediabetes screening and to find out the applicability of the ADA scoring method in Yogyakarta primary health care. Method: The diagnostic test by scoring system of the ADA questionnaire was compared with OGTT (oral glucose tolerance test) as the gold standard. The subjects were patients of primary health care in Yogyakarta who fulfill the inclusion and exclusion criteria. Result: The subjects were 279 respondents with 227 female  (81.4%) and 52 male patients (18.6%). The mean age of the study subjects was 50.4 years (SD 12.81). The sensitivity and specificity of the scoring method of ADA was 61% and 71%. This could be influenced by the difference in BMI standard as one of the scoring items. Conclusion: Prediabetes prevalence was 11.1% in the study population. The sensitivity and specificity of the scoring method of ADA is 61% and 71%. The scoring method of ADA could not be used in primary health care.

Keywords


ADA; prediabetes; primary health care; risk factor scoring; screening

Full Text:

PDF


References

1. Tabák AG, Herder C, Rathmann W, Brunner EJ, Kivimäki M. Prediabetes: a high-risk state for diabetes development. The Lancet. 2012; 379(9833): 2279-90.

2. International Diabetes Federation. IDF diabetes atlas sixth edition. 2013. Tersedia dari: www.idf.org/diabetesatlas

3. Soewondo P, Pramono LA. Prevalence, characteristics, and predictors of pre-diabetes in Indonesia. Medical Journal of Indonesia. 2011; 20(4): 283-94.

4. Agency for Health Research and Development. Basic health research 2013. Jakarta: Ministry of Health Republic of Indonesia; 2013.

5. Yunir E. Presentation of the results of internal medicine research: the prevalence of pre-diabetes in the general population aged 25-64 years in five regions of DKI Jakarta. 2013.

6. Yunir E, Waspadji S, Rahajeng E. The pre-diabetic epidemiological study in Depok, West Java. Acta Med Indones. 2009; 41(4): 181-5.

7. Serrano R, García-Soidán FJ, Diaz-Redondo A, Artola S, Franch J, Diez J, Carrillo L, Ezkurra P, Millaruelo JM, Segui M, Sangrós FJ. Cohort study in primary health care on the evolution of patients with prediabetes (PREDAPS): basis and methodology. Revista espanola de salud publica. 2013; 87(2): 121-35.

8. Gerstein HC, Santaguida P, Raina P, Morrison KM, Balion C, Hunt D, Yazdi H, Booker L. Annual incidence and relative risk of diabetes in people with various categories of dysglycemia: a systematic overview and meta-analysis of prospective studies. Diabetes research and clinical practice. 2007; 78(3): 305-12.

9. Nathan DM, Davidson MB, DeFronzo RA, Heine RJ, Henry RR, Pratley R, Zinman B. Impaired fasting glucose and impaired glucose tolerance: implications for care. Diabetes care. 2007; 30(3): 753-9.

10. Rydén L, Standl E, Bartnik M, Van den Berghe G, Betteridge J, De Boer MJ, Cosentino F, Jönsson B, Laakso M, Malmberg K, Priori S. Guidelines on diabetes, pre-diabetes, and cardiovascular diseases: executive summary: The Task Force on Diabetes and Cardiovascular Diseases of the European Society of Cardiology (ESC) and of the European Association for the Study of Diabetes (EASD). European heart journal. 2007; 28(1): 88-136.

11. Waugh N, Scotland G, Gillet M, Brennan A, Goyder E, Williams R, John A. Screening for type 2 diabetes: literature review and economic modelling. Health technology assessment. 2007; 11(17): 1-143.

12. Zhang P, Engelgau MM, Valdez R, Benjamin SM, Cadwell B, Narayan KV. Costs of screening for pre-diabetes among US adults: a comparison of different screening strategies. Diabetes Care. 2003; 26(9): 2536-42.

13. Poltavskiy E, Kim DJ, Bang H. Comparison of screening scores for diabetes and prediabetes. Diabetes research and clinical practice. 2016; 118: 146-53.

14. Norris SL, Kansagara D, Bougatsos C, Fu R. Screening adults for type 2 diabetes: a review of the evidence for the US Preventive Services Task Force. Annals of Internal Medicine. 2008; 148(11): 855-68.

15. Stentz FB, Brewer A, Wan J, Garber C, Daniels B, Sands C, Kitabchi AE. Remission of pre-diabetes to normal glucose tolerance in obese adults with high protein versus high carbohydrate diet: randomized control trial. BMJ Open Diabetes Research and Care. 2016; 4(1): 1-9.

16. Bang H, Edwards AM, Bomback AS, Ballantyne CM, Brillon D, Callahan MA, Teutsch SM, Mushlin AI, Kern LM. Development and validation of a patient self-assessment score for diabetes risk. Annals of internal medicine. 2009; 151(11): 775-83.

17. WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet (London, England). 2004; 363(9403): 157.

18. Hsia DS, Larrivee S, Cefalu WT, Johnson WD. Impact of lowering BMI cut points as recommended in the revised American Diabetes Association’s Standards of Medical Care in Diabetes—2015 on diabetes screening in Asian Americans. Diabetes care. 2015; 38(11): 2166-8.

19. Zeng Q, He Y, Dong S, Zhao X, Chen Z, Song Z, Chang G, Yang F, Wang Y. Optimal cut-off values of BMI, waist circumference and waist: height ratio for defining obesity in Chinese adults. British Journal of Nutrition. 2014; 112(10): 1735-44.

20. Ouyang P, Guo X, Shen Y, Lu N, Ma C. A simple score model to assess prediabetes risk status based on the medical examination data. Canadian journal of diabetes. 2016; 40(5): 419-23.

21. Hutabarat YHN. Central obesity as a risk factor for prediabetes in Cimahi City [Ph.D Thesis]. Yogyakarta: Universitas Gadjah Mada; 2012.



DOI: https://doi.org/10.22146/rpcpe.50503

Article Metrics

Abstract views : 2201 | views : 1802

Refbacks

  • There are currently no refbacks.


Copyright (c) 2020 Yaltafit Abror Jeem, Hari Koesnanto, Muhammad Robikhul Ikhsan

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.


View My Stats