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Sources of Variation of Commonly Measured Serum Analytes in 6 Asian Cities and Consideration of Common Reference Intervals

¹ Faculty of Health Sciences, Yamaguchi University, Ube, Japan; ² Department of Laboratory Medicine, Asahikawa Medical College, Asahikawa, Japan; ³ Department of Chemical Pathology, Chinese University of Hong Kong, Hong Kong; ⁴ Department of Laboratory Medicine, Yonsei University, Seoul, Korea; ⁵ Yuan Ching Clinical Laboratory, Taipei, Taiwan; ⁶ Prodia Clinical Laboratory, Jakarta, Indonesia.

^aAddress correspondence to this author at: Department of Laboratory Sciences, Faculty of Health Sciences, Yamaguchi University Graduate School of Medicine, Minami-Kogushi 1–1-1, Ube, 755-8505 Japan. Fax +81-836-35-5213; e-mail ichihara{at}yamaguchi-u.ac.jp.

Background: In a previous study to determine the feasibility of common reference intervals in Asia, we found significant differences among populations from 6 cities. In this study, we attempted to define the sources of these differences.

Methods: We enrolled 580 healthy volunteers (279 men, 301 women, 20–62 years old), after a selection process that was based on the Clinical and Laboratory Standards Institute guidelines, and used a lifestyle questionnaire. All sera were obtained at a basal state and frozen at –80 °C until the collective assay was done. We measured 21 basic chemical analytes and 10 serum proteins.

Results: We used 3-level nested ANOVA to separate the variation (SD) into between-city (SD-city), between-sex (SD-sex), between-age (SD-age), and between-individual (SD-indiv) components. SD-indiv corresponds to one-quarter of the "pure" reference interval obtained after removing variations due to city, sex, and age. The SD-sex to SD-indiv ratio was >0.8 for creatinine, urate, retinol-binding protein, and transthyretin. We observed high SD-city to SD-indiv ratios, ranging from 0.4 to 0.7, for 11 analytes including lactate dehydrogenase (LDH), electrolytes, IgG, and complement components and SD-age to SD-indiv ratios >0.4 for LDH, alkaline phosphatase, and total cholesterol. Multiple regression analysis demonstrated several other relevant sources of variation, including body mass index, alcohol consumption, and cigarette smoking, although their contributions were generally smaller than those for sex, region, or age.

Conclusion: We observed unacceptably large regional differences in measured values of some analytes even after adjustment for age, sex, and lifestyle variables. Genetic and environmental factors may account for the residual differences.

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