Estimating Biological Age in the Singapore Longitudinal Aging Study.

Background: Biological age (BA) is a more accurate measure of the rate of human aging than chronological age (CA). However, there is limited consensus regarding measures of BA in life span and healthspan.Methods: This study investigated measurement sets of 68 physiological biomarkers using data from...

Full description

Bibliographic Details
Published in:Journals of Gerontology Series A: Biological Sciences & Medical Sciences Vol. 75; no. 10; pp. 1913 - 1921
Main Authors: Zhong, Xin, Lu, Yanxia, Gao, Qi, Nyunt, Ma Shwe Zin, Fulop, Tamas, Monterola, Christopher Pineda, Tong, Joo Chuan, Larbi, Anis, Ng, Tze Pin
Format: research Journal Article
Published: Oxford University Press / USA Oct2020
Online Access:View this record in EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=146103059&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 146103059
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        10795006
        JGA
      jtl: Journals of Gerontology Series A: Biological Sciences & Medical Sciences
      issn: 10795006
      maglogo: N
    pubinfo:
      dt: Oct2020
      vid: 75
      iid: 10
      pid: 622
      pub: Oxford University Press / USA
    artinfo:
      ui:
        146103059
        146103059
        NLM31179487
        146103059
        10.1093/gerona/glz146
        NLM31179487
        146103059
      ppf: 1913
      ppct: 8
      formats:
      tig:
        atl: Estimating Biological Age in the Singapore Longitudinal Aging Study.
      aug:
        au:
          Zhong, Xin
          Lu, Yanxia
          Gao, Qi
          Nyunt, Ma Shwe Zin
          Fulop, Tamas
          Monterola, Christopher Pineda
          Tong, Joo Chuan
          Larbi, Anis
          Ng, Tze Pin
        affil: Social & Cognitive Computing Department, Institute of High Performance Computing, Agency for Science, Technology and Research (A*STAR) , Fusionopolis, Singapore
      sug:
        subj:
          Aging Physiology
          Risk Factors
          Aged, 80 and Over
          Forced Expiratory Volume
          Longevity
          Mortality Trends
          Glomerular Filtration Rate
          Female
          Middle Age
          Predictive Value of Tests
          Prospective Studies
          Aged
          Algorithms
          Male
          Singapore
          Human
          Validation Studies
          Comparative Studies
          Evaluation Research
          Multicenter Studies
          Aged, 80 & over
          Middle Aged: 45-64 years
          Aged: 65+ years
          Female
          Male
      ab: Background: Biological age (BA) is a more accurate measure of the rate of human aging than chronological age (CA). However, there is limited consensus regarding measures of BA in life span and healthspan.Methods: This study investigated measurement sets of 68 physiological biomarkers using data from 2,844 Chinese Singaporeans in two age subgroups (55-70 and 71-94 years) in the Singapore Longitudinal Aging Study (SLAS-2) with 8-year follow-up frailty and mortality data. We computed BA estimate using three commonly used algorithms: Principal Component Analysis (PCA), Multiple Linear Regression (MLR), and Klemera and Doubal (KD) method, and additionally, explored the use of machine learning methods for prediction of mortality and frailty. The most optimal algorithmic estimate of BA compared to CA was evaluated for their associations with risk factors and health outcome.Results: Stepwise selection procedures resulted in the final selection of 8 biomarkers in males and 10 biomarkers in females. The highest-ranking biomarkers were estimated glomerular filtration rate for both genders, and the forced expiratory volume in 1 second in males and females. The BA estimates robustly predicted frailty and mortality and outperformed CA. The best performing KD measure of BA was notably predictive in the younger group (aged 55-70 years). BA estimates obtained using a machine learning train-test method were not more accurate than conventional BA estimates in predicting mortality and frailty in most situations. Biologically older people with the same CA as biologically younger individuals had higher prevalence of frailty and 8-year mortality, and worse health, behavioral, and functional characteristics.Conclusions: BA is better than CA for measuring life span (mortality) and healthspan (frailty). This measurement set of physiological markers of biological aging among Chinese robustly differentiate biologically old from younger individuals with the same CA.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N