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Comparison of Characteristics and Dispersion of Fasting Blood Glucose Data by Administrative Districts and Gender Difference Using the 2017 'Korean Blood Glucose Reference Standard'

2017 '한국인 혈당 참조표준'을 이용한 행정구역별 남녀별 공복 혈당 데이터의 특성 및 산포성 비교

  • Kwon, Young-Il (Department of Biomedical Laboratory Science, Shinhan University)
  • Received : 2020.02.08
  • Accepted : 2020.03.02
  • Published : 2020.03.31

Abstract

This study aimed to investigate the differences in the upper and lower limits of the 95% distribution of fasting blood glucose (FBG) by age groups. We also analyzed the changes in the mean values and dispersion of the data using the Korean Blood Glucose Reference Standard raw data published by the National Health Insurance Service (NHIS). Furthermore, the trends among 16 administrative districts were analyzed and any gender differences were determined. We also assessed whether the study results correlated with the relative standard uncertainty, as published by the NHIS. On the dispersion analysis using the differences between the upper and lower limits of the 95% distribution of FBG by age group, there were significant differences across gender and administrative districts (P<0.05). The gender differences in FBG measurements, as published by the NHIS, were significant across different administrative districts and age groups (P<0.001). This confirmed the need to recalculate the blood glucose reference standards for men and women. No significant correlation was observed between the relative standard uncertainty, as published by NHIS, and the dispersion and number of measurements analyzed in this study. However, it showed a high correlation with the measured mean value (R2=0.95). Therefore, further research on the reference standard and uncertainty is needed.

본 조사의 목적은 국민건강보험공단에서 공개한 '한국인 혈당 참조 표준'의 원자료를 이용하여 나이 그룹별 95% 분포 상한값과 하한값의 차를 조사하고 이 데이터들에 대한 평균값 변화와 산포 정도를 분석하는 것이다. 그리고 이 데이터를 이용하여 16개 행정구역 간 경향과 남녀간 차이를 분석하는 것이다. 또한 본 조사의 결과가 NHIS에서 제시한 상대표준불화도와 관련성이 있는지를 분석하였다. 본 조사에서 분석한 나이 그룹별 공복혈당의 95% 분포 상한값과 하한값의 차이를 이용한 산포성 분석에서는 행정구역별로 의미 있는 차이와 경향을 보여주었고, 남녀 평균치 간에서도 유의한 차이를 보여주었다(P<0.05). NHIS에서 발표한 공복 혈당 측정값의 남녀간 차이는 행정구역별, 나이그룹별 비교에서 모두 유의한 차이(P<0.001)를 보여 주어 남녀 간 혈당 참고치 재산정 필요성이 인정되었다. NHIS가 발표한 행정구역별 상대표준불확도와 본 조사에서 분석한 산포성 그리고 측정수와는 유의한 상관성이 관찰되지 않았다. 그러나 측정 평균치와는 높은 상관성을 보여주었다(R2=0.95). 또한 참조표준의 적용과 불확도 평가에 대한 추가적인 연구가 필요할 것으로 사료된다.

Keywords

References

  1. Cho B, Lee CM. Current situation of national health screening systems in Korea. J Korean Med Assoc. 2011;54:666-669. https://doi.org/10.5124/jkma.2011.54.7.666
  2. National Health Insurance Service. 2017 national health screening statistical yearbook. Wonju: NHIS; 2018 Nov. p54.
  3. Big data operations office. NHIS registered korean blood glucose national reference standard. Wonju: NHIS; 2017 [cited 2020 February 1]. Available from: https://www.nhis.or.kr/bbs7/boards/B0039/25119
  4. National Health Insurance Service. Korean agency for technology and standards. Korean blood glucose national reference standard. Wonju: NHIS; 2017 [cited 2020 February 1]. Available from: https://nhiss.nhis.or.kr/bd/ab/bdabf011cv.do
  5. National Center for Standard Reference Data. Definition and necessity of reference standard. Daejeon: KRISS; 2014 [cited 2020 February 1]. Available from: https://www.srd.re.kr:446/srdintro/definition.do
  6. Bercik Inal B, Koldas M, Inal H, Coskun C, Gumus A, Doventas Y. Evaluation of measurement uncertainty of glucose in clinical chemistry. Ann N Y Acad Sci. 2007;1100:223-226. https://doi.org/10.1196/annals.1395.023
  7. Kallner A, Waldenstrom J. Does the uncertainty of commonly performed glucose measurements allow identification of individuals at high risk for diabetes? Clin Chem Lab Med. 1999;37:907-912. https://doi.org/10.1515/CCLM.1999.134
  8. ISO, IEC. Uncertainty of measurement. Part 3: guide to the expression of uncertainty in measurement (GUM:1995). GUIDE. Geneva: ISO/IEC; 2008. p1-120. ISO/IEC GUIDE 98-3.
  9. Williams A. What can we learn from traceability in physical measurements? Accredit Qual Assur. 2000;5:414-417. https://doi.org/10.1007/s007690000218
  10. Williams A. Traceability and uncertainty a comparison of their application in chemical and physical measurement. Accredit Qual Assur. 2001;6:73-75. https://doi.org/10.1007/s007690000255
  11. Kristiansen J, Christensen JM. Traceability and uncertainty in analytical measurements. Ann Clin Biochem. 1998;35:371-379. https://doi.org/10.1177/000456329803500305
  12. Xavier FA. Uncertainty of measurement in clinical laboratory sciences. Clin Chem. 2000;46:1437-1438. https://doi.org/10.1093/clinchem/46.9.1437
  13. Oosterhuis WP, Bayat H, Armbruster D, Coskun A, Freeman KP, Kallner A, et al. The use of error and uncertainty methods in the medical laboratory. Clin Chem Lab Med. 2018;56:209-219. https://doi.org/10.1515/cclm-2017-0341
  14. Neda M, Svetlana I, Zorica S, Nada MS. Uncertainty of measure ment in laboratory medicine. J Med Biochem. 2018;37:279-288. https://doi.org/10.2478/jomb-2018-0002
  15. Theodorsson E. Uncertainty in measurement and total error: tools for coping with diagnostic uncertainty. Clin Lab Med. 2017;37:15-34. http://dx.doi.org/10.1016/j.cll.2016.09.002
  16. Farrance I, Badrick T, Sikaris KA. Uncertainty in measurement and total error are they so incompatible? Clin Chem Lab Med. 2016;54:1309-1311. https://doi.org/10.1515/cclm-2016-0314
  17. Chen H, Deng XL, Bi XY, Yang P, Zhang LP, Chen HC. Study on measurement uncertainty for total cholesterol in routine clinical laboratory. Chinese Journal of Clinical Laboratory Science. 2010;28:372-374.
  18. Huang HC, Chien CH, Wang CY, Chong FC. Evaluating the uncertainty of measurement on blood's glucose level. Biomed Eng Appl Basis Comm. 2005;17:31-37.