Abstract

BackgroundMany 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.MethodsThe 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.ResultsIn 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).ConclusionsBiological age could be used to predict future risk of death, and its effect size varied according to gender, chronological age, and cause of death.

Highlights

  • Many studies have been conducted to quantitatively estimate biological age using measurable biomarkers

  • Some biomarkers were commonly found in these studies: body mass index (BMI), blood pressure (BP), waist circumference (WC), forced expiratory volume in 1 s (FEV1), body muscle percentage (BMP), body fat percentage (BFP), blood urea nitrogen (BUN), albumin, globulin, high density lipoprotein (HDL), low density lipoprotein (LDL), and/ or triglyceride (TG), which are all relatively obtainable in a general health check-up

  • The proportions of the data which were used for the analysis excluding missing data were between 4.6% and 99.8%; 14.4% (WC), 99.8% (SBP), 92.4% (FEV1), 94.9% (G-GTP), 98.8% (BUN), 90.4%(HDL), 98.7% (TG), 99.7% (FBS), 90.7% (LDL), 21.2% (BFP), 0% (BMP), and 94.3% (AGR) for male data, and 16.5% (WC), 99.3% (DBP), 92.1% (FEV1), 93.5% (G-GTP), 98.6% (BUN), 88.6% (HDL), 98.5% (TG), 99.7% (FBS), 4.6% (ESR), 88.9% (LDL), 99.8% (BMI), 20.2% (BFP), 0% (BMP), and 93.0% (AGR) for female data

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Summary

Introduction

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. 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. Some biomarkers were commonly found in these studies: body mass index (BMI), blood pressure (BP), waist circumference (WC), forced expiratory volume in 1 s (FEV1), body muscle percentage (BMP), body fat percentage (BFP), blood urea nitrogen (BUN), albumin, globulin, high density lipoprotein (HDL), low density lipoprotein (LDL), and/ or triglyceride (TG), which are all relatively obtainable in a general health check-up. BUN, albumin, globulin, HDL, LDL, and TG are associated with biochemical factors

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