title: Biological age as a useful index to predict seventeen-year survival and mortality in Koreans.
abstract: Many studies have been conducted to quantitatively estimate biological age using measurable biomarkers. Biological age should function as a valid proxy for aging, which is closely related with future work ability, frailty, physical fitness, and/or mortality. A validation study using cohort data found biological age to be a superior index for disease-related mortality than chronological age. The purpose of this study is to demonstrate the validity of biological age as a useful index to predict a person's risk of death in the future.
  
  
  
  The data consists of 13,106 cases of death from 557,940 Koreans at 20-93 years old, surveyed from 1994 to 2011. Biological ages were computed using 15 biomarkers measured in general health check-ups using an algorithm based on principal component analysis. The influence of biological age on future mortality was analyzed using Cox proportional hazards regression considering gender, chronological age, and event type.
  
  
  
  In the living subjects, the average biological age was almost the same as the average chronological age. In the deceased, the biological age was larger than the chronological age: largest increment of biological age over chronological age was observed when their baseline chronological age was within 50-59 years. The death rate significantly increased as biological age became larger than chronological age (linear trend test, p value < 0.0001). The largest hazard ratio was observed in subjects whose baseline chronological age was within 50-59 years when the cause was death from non-cancerous diseases (HR = 1.30, 95% confidence intervals = 1.26 - 1.34). The survival probability, over the 17 year term of the study, was significantly decreased in the people whose biological age was larger than chronological age (log rank test, p value < 0.001).
  
  
  
  Biological age could be used to predict future risk of death, and its effect size varied according to gender, chronological age, and cause of death.
authors.affiliation: Bioage Medical Research Institute, Bio-Age Inc., Seoul, Republic of Korea.
authors.forename: Jinho
authors.initials: J
authors.lastname: Yoo
authors.affiliation: Bioage Medical Research Institute, Bio-Age Inc., Seoul, Republic of Korea.|College of Oriental Medicine, Kyung Hee University, Seoul, Republic of Korea.
authors.forename: Yangseok
authors.initials: Y
authors.lastname: Kim
authors.affiliation: Department of Epidemiology and Health Promotion, Institute for Health promotion, Yonsei University Graduate School of Public Health, Seoul, Republic of Korea.
authors.forename: Eo Rin
authors.initials: ER
authors.lastname: Cho
authors.affiliation: Department of Epidemiology and Health Promotion, Institute for Health promotion, Yonsei University Graduate School of Public Health, Seoul, Republic of Korea. jsunha@yuhs.ac.
authors.forename: Sun Ha
authors.identifier: 0000-0001-9519-3068
authors.initials: SH
authors.lastname: Jee
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology*; D015415:Biomarkers / Q000032:analysis*; D005260:Female; D015577:Geriatric Assessment; D006801:Humans; D008297:Male; D008875:Middle Aged; D009026:Mortality; D016016:Proportional Hazards Models; D056910:Republic of Korea / Q000453:epidemiology; D018570:Risk Assessment / Q000379:methods*; D011795:Surveys and Questionnaires; D016019:Survival Analysis
chemical_list: D015415:Biomarkers
keywords: Biological age; Biomarkers; Chronological age; Cox regression; Mortality; Risk of death