DOI QR코드

DOI QR Code

The Distribution and Characteristics of Abnormal Findings Regarding Fasting Plasma Glucose and HbA1c - Based on Adults Except for Known Diabetes

공복혈당과 당화혈색소를 적용한 당뇨병 이상소견자의 분포 및 특성 - 당뇨병 기진단자를 제외한 성인을 대상으로

  • Kwon, Seyoung (Department of Biomedical Laboratory Science, Daegu Health College) ;
  • Na, Youngak (Department of Biomedical Laboratory Science, Daegu Health College)
  • 권세영 (대구보건대학교 임상병리과) ;
  • 나영악 (대구보건대학교 임상병리과)
  • Received : 2017.07.29
  • Accepted : 2017.08.14
  • Published : 2017.09.30

Abstract

Among the commonly known tools to diagnose diabetes are fasting plasma glucose (FPG), HbA1c., and OGTT known as gold standard. However, there can be many disagreements on the ways to diagnose diabetes. In this study, we examined the differences of the types of diabetes according to the applicability of FPG and HbA1c. Moreover, we evaluated the concordance of diagnosis. We excluded subjects with missing glucose and HbA1c data, as well as those previously diagnosed with diabetes, and those who fasted less than 8 hours. The data of 4,502 subjects (1,956 men and 2,546 women) from the 2015 KNHNES were analyzed. We divided these patients into three categories which are normal, prediabetes, and diabetes, based on the FPG and HbA1c. In men, the number of subjects with FPG ranging from 100 to 125 mg/dL and HbA1c ${\geq}6.5%$ was 23 out of 664, and the number of subjects with FPG < 126 mg/dL and HbA1c ${\geq}6.5%$ was 39 out of 86 newly diagnosed diabetes patients. The concordance rate was as follows: Normal 80.3%, prediabetes 44.9%, and diabetes 54.7%. The coefficient of Cohen's Kappa was 0.322 in men and 0.362 in women; this suggests that both gender showed a low concordance rate. However, when we divided them into two categories (nondiabetes and diabetes), Kappa was 0.582 in men and 0.637 in women, showing a relatively high concordance rate. While all subjects with FPG ${\geq}126mg/dL$ showed a significantly high HOMA IR, all subjects with FPG < 126 mg/dL showed a significantly high QUICKI. Considering the low concordance rate for the diagnosis of diabetes and characteristic of diagnostic tests, it is necessary to combine the related tests for diagnosing diabetes.

현재 임상에서 적용되고 있는 대표적인 당뇨 진단 기준에는 표준검사법인 경구당부하검사, 공복혈당, 당화혈색소가 있다. 그러나, 검사별로 판정이 일치하지 않는 경우가 많다. 본 연구에서는 선별검사에서 행해지는 공복혈당과 당화혈색소를 이용하여 당뇨병 판정의 일치도를 구해보고, 유형별로 그 특성을 살펴 보았다. 국민건강영양조사 데이터(2015) 중 측정치 누락자, 당뇨병 기진단자, 공복 8시간 미만인 자를 제외한 20세 이상 대상자 4,502명(남성 1,956명, 여성 2,546명)의 자료를 이용하였다. 공복혈당과 당화혈색소 농도를 당뇨병 진단기준의 세 범주(정상, 당뇨병 전단계, 당뇨병)로 나누어 살펴본 남성 대상자의 분포에서 공복혈당 100 mg/dL~125 mg/dL이면서 HbA1c ${\geq}6.5%$인 대상자는 664명 중 23명, 새롭게 진단된 당뇨군 86명 중 39명은 공복혈당 ${\geq}126mg/dL$ 이면서 HbA1c < 6.5%로 나타났다. 판정의 일치율은 비당뇨군 80.3% 당뇨군 54.7%, 당뇨병 전단계에서 44.9%로 가장 낮았다. 코헨의 kappa 값은 남성의 경우 0.322, 여성의 경우 0.362로 일치도가 낮게 나타났고, 두 범주(비당뇨병, 당뇨병)로 나누었을 때 남성의 경우 0.582, 여성의 경우 0.637로 나타나 더 높은 일치도를 보였다. 공복혈당 <126 mg/dL이며 HbA1c < 6.5%인 군에서 연령도 낮고 대부분의 혈액 측정치도 낮게 나타났으며, 공복혈당 ${\geq}126mg/dL$ 이면서 HbA1c ${\geq}6.5%$인 군에서 남성의 경우 허리둘레, 혈압, 총 콜레스테롤, 중성지방의 수치가 높고 여성의 경우 ALT, hsCRP가 높게 나타났다. 남녀 모두 공복혈당 ${\geq}126mg/dL$인 군에서 인슐린저항성 지표인 HOMA IR값이 유의하게 높았고, <126 mg/dL인 군에서 인슐린감수성 지표인 QUICKI 값이 유의하게 높았다. 당뇨병 판정의 낮은 일치도 및 진단검사의 특성을 고려하여 관련검사의 병행 해석이 필요하다.

Keywords

References

  1. Salmasi AM, Dancy M. The glucose tolerance test, but not HbA(1c), remains the gold standard in identifying unrecognized diabetes mellitus and impaired glucose tolerance in hypertensive subjects. Angiology. 2005;56(5):571-579. https://doi.org/10.1177/000331970505600508
  2. Phillips PJ. Oral glucose tolerance testing. Australian Family Physician. 2012;41(6):391-393.
  3. Sacks DB. A1C versus glucose testing: a comparison. Diabetes Care. 2011;34(2):518-523. https://doi.org/10.2337/dc10-1546
  4. International Expert Committee. International expert committee report on the role of the A1c assay in the diagnosis of diabetes. Diabetes Care. 2009;32(7):1327-1334. https://doi.org/10.2337/dc09-9033
  5. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2010;33(Suppl 1):62-69. https://doi.org/10.2337/dc10-S062
  6. Carson AP, Reynolds K, Fonseca VA, Muntner P. Comparison of A1C and fasting glucose criteria to diagnose diabetes among U.S. adults. Diabetes Care 2010;33(1):95-97. https://doi.org/10.2337/dc09-1227
  7. Korea Centers for Disease Control and Prevention. The Sixth Korea National Health and Nutrition Examination Survey (KNHANES VI-3) [Internet]. Cheongju: Korea Centers for Disease Control and Prevention; 2015 [cited 2017 June 26]. Available from: https://knhanes.cdc.go.kr/knhanes/index.do
  8. The DECODE Study Group: Is fasting glucose sufficient to define diabetes? Epidemiological data from 20 European studies. Diabetologia. 1999;42(6):647-654. https://doi.org/10.1007/s001250051211
  9. The DECODA Study Group: The fasting plasma glucose cut-point predicting a diabetic 2-h OGTT glucose level depends on the phenotype. Diab Res Clin Pract. 2002;55(1):35-43. https://doi.org/10.1016/S0168-8227(01)00270-4
  10. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and ${\beta}$-cell function from fasting plasma glucose and insulin concentration in man. Diabetologia. 1985;28(7):412-419. https://doi.org/10.1007/BF00280883
  11. Katz A, Nambi SS, Mather K, Baron AD, Follmann DA, Sullivan G, et al. Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans. J Clin Endocrinol Metab. 2000;85(7):2402-2410. https://doi.org/10.1210/jcem.85.7.6661
  12. Barr RG, Nathan DM, Meigs JB, Singer DE. Tests of glycemia for the diagnosis of type 2 diabetes mellitus. Ann Intern Med. 2002;137(4):263-272. https://doi.org/10.7326/0003-4819-137-4-200208200-00011
  13. Sato KK, Hayashi T, Harita N, Yoneda T, Nakamura Y, Endo G, et al. Combined measurement of fasting plasma glucose and A1c is effective for the prediction of type 2 diabetes. Diabetes Care. 2009;32(4):644-646. https://doi.org/10.2337/dc08-1631
  14. Wang W, Lee ET, Fabsitz R, Welty TK, Howard BV. Using HbA1c to improve efficacy of the American Diabetes Association fasting plasma glucose criterion in screening for new type 2 diabetes in American Indians. Diabetes Care. 2002;25(8):1365-1370. https://doi.org/10.2337/diacare.25.8.1365
  15. Lee CH, Chang WJ, Chung HH, Kim HJ, Park SH, Moon JS, et al. The combination of fasting plasma glucose and glycosylated hemoglobin as a predictor for type 2 diabetes in Korean adults. Korean Diabetes J. 2009;33(4):306-314. https://doi.org/10.4093/kdj.2009.33.4.306
  16. Kim JH, Han MA, Park CJ, Park IG, Shin JH, Kim SY, et al. Evaluation of fasting plasma glucose as a screening for diabetes mellitus in middle-aged adults of Naju country. Korean Diabetes J. 2008;32(4):328-337. https://doi.org/10.4093/kdj.2008.32.4.328
  17. Baik SH, Choi KM, Cho YJ, Kim KO, Kim DR, Kim NH, et al. Prevalence of diabetes mellitus in elderly Korean in southwest Seoul (SWS study)-comparison of 1997 ADA & 1985 WHO criteria in elderly Korean. Korean Diabetes J. 2001;25(2):125-132.
  18. Kwon PS, Rheem IS. The assessment of blood glucose distribution according to the fasting state and glycemic control indicators for diabetes screening. Korean J Clin Lab Sci. 2016; 48(4):312-320. https://doi.org/10.15324/kjcls.2016.48.4.312
  19. Kwon SY, Na YA. The cutoff value of HbA1c in predicting diabetes and impaired fasting glucose. Korean J Clin Lab Sci. 2017;49(2):114-120. https://doi.org/10.15324/kjcls.2017.49.2.114
  20. Choi YH, Ahn YB, Yoon KH, Kang MI, Cha BY, Lee KW, et al. New ADA criteria in the Korean population : Fasting blood glucose is not enough for diagnosis of mild diabetes especially in the elderly. Korean J Int Med. 2000;15(3):211-217. https://doi.org/10.3904/kjim.2000.15.3.211
  21. Angulo P. Nonalcoholic fatty liver disease. N Engl J Med. 2002;346(16):1221-1231. https://doi.org/10.1056/NEJMra011775
  22. Esteghamati A, Noshad S, Khalilzadeh O, Khalili M, Zandieh A, Nakhjavani M. Insulin resistance is independently associated with liver aminotransferases in diabetic patients without ultrasound signs of nonalcoholic fatty liver disease. Metab Syndr Relat Disord. 2011;9(2):111-117. https://doi.org/10.1089/met.2010.0066
  23. Gao F, Pan JM, Hou XH, Fang QC, Lu HJ, Tang JL, et al. Liver enzymes concentrations are closely related to prediabetes: findings of the Shanghai Diabetes Study II (SHDS II). Biomed Environ Sci. 2012;25(1):30-37. https://doi.org/10.3967/0895-3988.2012.01.005
  24. Danesh J, Whincup P, Walker M, Lennon L, Thomson A, Appleby P, et al. Low grade inflammation and coronary heart disease: prospective study and updated meta-analyses. BMJ. 2000;321(7255):199-204. https://doi.org/10.1136/bmj.321.7255.199
  25. Ridker PM. C-reactive protein and the prediction of cardiovascular events among those at intermediate risk: moving an inflammatory hypothesis toward consensus. J Am Coll Cardiol. 2007;49(21):2129-2138. https://doi.org/10.1016/j.jacc.2007.02.052
  26. Choi ES, Rhee EJ, Kim JH, Won JC, Park CY, Lee WY, et al. Insulin sensitivity and insulin secretion determined by homeostasis model assessment and future risk of diabetes mellitus in Korean men. Korean Diabetes J. 2008;32(6):498-505. https://doi.org/10.4093/kdj.2008.32.6.498

Cited by

  1. Relationships between Blood Profiles and Physical Activity in Pre-Diabetic Adults: Based on the 6th-7th (2014-2016) Korean National Health and Nutrition Examination Survey (KNHANES) vol.30, pp.4, 2017, https://doi.org/10.7856/kjcls.2019.30.4.529