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Calibration of High-Density Lipoprotein Cholesterol Values From the Korea National Health and Nutrition Examination Survey Data, 2008 to 2015

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초록

Background: For correct interpretation of the high-density lipoprotein cholesterol (HDL-C) data from the Korea National Health and Nutrition Examination Survey (KNHANES), the values should be comparable to reference values. We aimed to suggest a way to calibrate KNHANES HDL-C data from 2008 to 2015 to the Centers for Disease Control and Prevention (CDC) reference method values. Methods: We derived three calibration equations based on comparisons between the HDL-C values of the KNHANES laboratory and the CDC reference method values in 2009, 2012, and 2015 using commutable frozen serum samples. The selection of calibration equation for correcting KNHANES HDL-C in each year was determined by the accuracy-based external quality assurance results of the KNHANES laboratory. Results: Significant positive biases of HDL-C values were observed in all years (2.85-9.40%). We created the following calibration equations: standard HDL-C=0.872×[original KNHANES HDL-C]+2.460 for 2008, 2009, and 2010; standard HDL-C=0.952×[original KNHANES HDL-C]+1.096 for 2012, 2013, and 2014; and standard HDL-C=1.01×[original KNHANES HDL-C]-3.172 for 2011 and 2015. We calibrated the biases of KNHANES HDL-C data using the calibration equations. Conclusions: Since the KNHANES HDL-C values (2008-2015) showed substantial positive biases compared with the CDC reference method values, we suggested using calibration equations to correct KNHANES data from these years. Since the necessity for correcting the biases depends on the characteristics of research topics, each researcher should determine whether to calibrate KNHANES HDL-C data or not for each study.

Abstract

Background: For correct interpretation of the high-density lipoprotein cholesterol (HDL-C) data from the Korea National Health and Nutrition Examination Survey (KNHANES), the values should be comparable to reference values. We aimed to suggest a way to calibrate KNHANES HDL-C data from 2008 to 2015 to the Centers for Disease Control and Prevention (CDC) reference method values. Methods: We derived three calibration equations based on comparisons between the HDL-C values of the KNHANES laboratory and the CDC reference method values in 2009, 2012, and 2015 using commutable frozen serum samples. The selection of calibration equation for correcting KNHANES HDL-C in each year was determined by the accuracy-based external quality assurance results of the KNHANES laboratory. Results: Significant positive biases of HDL-C values were observed in all years (2.85-9.40%). We created the following calibration equations: standard HDL-C=0.872×[original KNHANES HDL-C]+2.460 for 2008, 2009, and 2010; standard HDL-C=0.952×[original KNHANES HDL-C]+1.096 for 2012, 2013, and 2014; and standard HDL-C=1.01×[original KNHANES HDL-C]-3.172 for 2011 and 2015. We calibrated the biases of KNHANES HDL-C data using the calibration equations. Conclusions: Since the KNHANES HDL-C values (2008-2015) showed substantial positive biases compared with the CDC reference method values, we suggested using calibration equations to correct KNHANES data from these years. Since the necessity for correcting the biases depends on the characteristics of research topics, each researcher should determine whether to calibrate KNHANES HDL-C data or not for each study.

참고문헌 (11)

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  7. Passing H, "A new biometrical procedure for testing the equality of measurements from two different analytical methods. Application of linear regression procedures for method comparison studies in clinical chemistry, Part I", J Clin Chem Clin Biochem, 21, pp.709~720 (1983)
  8. "Development of trend analysis methods for lipid profile in the KNHANES" (2014)[URL]
  9. Yetley EA, "NHANES monitoring of serum 25-hydroxyvitamin D: a roundtable summary", J Nutr, 140, pp.2030S~2045S (2010)
  10. "National Health and Nutrition Examination Survey 2007 - 2008 Data Documentation, Codebook, and Frequencies; HDL-Cholesterol (HDL_E)" (2010)[URL]
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