title: Assessment of biological age by principal component analysis.
abstract: A method of assessing biological age by the application of principal component analysis is reported. Healthy individuals (462) randomly selected from about 6000 men who had taken a 2-day health examination were studied. Out of the 30 physiological variables examined in routine check-ups, 11 variables were selected as suitable for the assessment of biological age based on the results of factor analysis and the physiological meaning of each test. This variable set was then submitted to principal component analysis, and the 1st principal component obtained from this analysis was used as an equation for assessing one's biological age. However, the biological age calculated from this equation is expressed as a score, so the estimated score was transformed to years (biological age) using the T-score idea. The biological age estimated by this method is practically useful and theoretically valid in contrast with the multiple regression model, because this approach eliminates and overcomes the following 2 big problems of the multiple regression model: (1) the distortion of the individual biological age at the regression edges; and (2) a theoretical contradiction in that a perfect model will merely be predicting the subject's chronological age, not his biological age.
authors.affiliation: Department of Health and Physical Education, Kyoto University, Japan.
authors.forename: E
authors.initials: E
authors.lastname: Nakamura
authors.forename: K
authors.initials: K
authors.lastname: Miyao
authors.forename: T
authors.initials: T
authors.lastname: Ozeki
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology*; D003627:Data Interpretation, Statistical; D003920:Diabetes Mellitus / Q000503:physiopathology; D006801:Humans; D006973:Hypertension / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D012016:Reference Values; D012044:Regression Analysis