Models for Predicting Five Jang Biological Ages with Clinical Biomarkers

임상 생체지표를 이용한 오장생체나이 추정 모델

  • Received : 2011.07.15
  • Accepted : 2011.08.12
  • Published : 2011.08.31

Abstract

Objectives: Even though there has been no consensus on the concept of viscera organ between the oriental and western medicine, we tried to investigate the correlation between clinical biomarkers of five Jang and chronological age and develop the models for predicting five Jang biological ages by statistical analysis. Methods: We obtained data from about 120,000 subjects who visited health promotion centers for health promotion and disease prevention from January 2004 to June 2009. Participants were included if they were over 20 years old, and excluded if reported to have cardiovascular disease or other serious medical illness such as cancer, malignant hypertension, uncontrolled diabetes, cardiopulmonary insufficiency, liver disease, pancreatic disease or renal disease. Among the clinical biomarkers obtained, we selected the biomarkers which were associated with the function of 5 Jang in previous studies, or showed statistically significant correlation with age. Multiple regression models were used for building prediction models of biological age after adjusting for potential confounders for men and women, respectively. Pearson correlation coefficient was calculated to examine the linear relationship between age and various biomarkers, and multiple regression analysis was used for building the prediction models of five Jang biological ages for men and women, respectively. All statistical data analysis was performed by using SPSS Version 12.0 software and statistical significance was obtained if p<0.05. Results: For males, the best models were developed using 12, 2, 8, 3, and 4 biomarkers for predicting biological ages of heart, lung, liver, pancreas, and kidney, respectively (R2 = 0.57, 0.43, 0.11, 0.24, and 0.93, respectively). Similar to males, for the females, 10, 2, 8, 3, and 4 biomarkers were selected as the models respectively (R2 = 0.76, 0.44, 0.14, 0.38, and 0.89, respectively). Conclusions: As we have developed for the first time the models for predicting five Jang biological ages with common clinical biomarkers, it is expected that these models may be used as clinical supplementary tools in the evaluation of aging status and functional decline of five Jang according to age in health promotion centers and private clinics. At the same time, it is considered that the use as objective tools to evaluate aging status and functional decline of each Jang.

Keywords

References

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