Estimating quality of life with biomarkers among older Korean adults: A machine-learning approach

Sung Ha Lee, Incheol Choi, Woo Young Ahn, Enyoung Shin, Sung Il Cho, Sunyoung Kim, Bumjo Oh

Research output: Contribution to journalArticle

Abstract

Background: While health-related quality of life (HRQoL) has clinical value, its determinants, particularly objective health-related measurements, have not been fully explored. This study seeks to identify the biological indicators that relate to HRQoL among a group of older Korean adults using a machine-learning approach. Methods: We used physical and mental scores from the 36-item Short Form Health Survey (SF-36) to measure HRQoL among older Korean adults who participated in the Korean Longitudinal Study of Aging (KLoSA) biomarker pilot study (N = 385). The variables for the multivariate penalized regression analysis included demographic factors, medical measurements, physical performance, and health-related behaviors. Results: The multivariate profiles identified several significant biomarkers that relate to quality of life. Among the 20 variables, handgrip strength was the most powerful indicator in both men and women for the SF-36 physical scores, followed by walking speed. Age and total sleep duration exclusively were significantly associated with the SF-36 physical scores only in women, whereas body mass index, blood pressure, and sit-to-stand times were unique elements in men. Conclusions: The present study suggests significant physical indicators that explain quality of life in elderly populations, using a data-driven approach. Based on these findings, maintaining a good level of physical performance is considered a key element of successful aging.

Original languageEnglish
Article number103966
JournalArchives of Gerontology and Geriatrics
Volume87
DOIs
StatePublished - 1 Mar 2020

Fingerprint

quality of life
Biomarkers
Quality of Life
health
learning
Health
Health Surveys
Longitudinal Studies
demographic factors
sleep
Sleep
Body Mass Index
multivariate analysis
performance
Regression Analysis
Demography
Machine Learning
longitudinal study
regression analysis
Blood Pressure

Keywords

  • Elastic net
  • Elderly
  • Handgrip strength
  • HRQoL
  • Penalized regression
  • SF-36

Cite this

Lee, Sung Ha ; Choi, Incheol ; Ahn, Woo Young ; Shin, Enyoung ; Cho, Sung Il ; Kim, Sunyoung ; Oh, Bumjo. / Estimating quality of life with biomarkers among older Korean adults : A machine-learning approach. In: Archives of Gerontology and Geriatrics. 2020 ; Vol. 87.
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Estimating quality of life with biomarkers among older Korean adults : A machine-learning approach. / Lee, Sung Ha; Choi, Incheol; Ahn, Woo Young; Shin, Enyoung; Cho, Sung Il; Kim, Sunyoung; Oh, Bumjo.

In: Archives of Gerontology and Geriatrics, Vol. 87, 103966, 01.03.2020.

Research output: Contribution to journalArticle

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T1 - Estimating quality of life with biomarkers among older Korean adults

T2 - A machine-learning approach

AU - Lee, Sung Ha

AU - Choi, Incheol

AU - Ahn, Woo Young

AU - Shin, Enyoung

AU - Cho, Sung Il

AU - Kim, Sunyoung

AU - Oh, Bumjo

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