@Article{info:doi/10.2196/58466,
author="Lin, Yu-Chun
and Yan, Huang-Ting
and Lin, Chih-Hsueh
and Chang, Hen-Hong",
title="Identifying and Estimating Frailty Phenotypes by Vocal Biomarkers: Cross-Sectional Study",
journal="J Med Internet Res",
year="2024",
month="Nov",
day="8",
volume="26",
pages="e58466",
keywords="frailty phenotypes; older adults; successful aging; vocal biomarkers; frailty; phenotype; vocal biomarker; cross-sectional; gerontology; geriatrics; older adult; Taiwan; energy-based; hybrid-based; sarcopenia",
abstract="Background: Researchers have developed a variety of indices to assess frailty. Recent research indicates that the human voice reflects frailty status. Frailty phenotypes are seldom discussed in the literature on the aging voice. Objective: This study aims to examine potential phenotypes of frail older adults and determine their correlation with vocal biomarkers. Methods: Participants aged ≥60 years who visited the geriatric outpatient clinic of a teaching hospital in central Taiwan between 2020 and 2021 were recruited. We identified 4 frailty phenotypes: energy-based frailty, sarcopenia-based frailty, hybrid-based frailty--energy, and hybrid-based frailty--sarcopenia. Participants were asked to pronounce a sustained vowel ``/a/'' for approximately 1 second. The speech signals were digitized and analyzed. Four voice parameters---the average number of zero crossings (A1), variations in local peaks and valleys (A2), variations in first and second formant frequencies (A3), and spectral energy ratio (A4)---were used for analyzing changes in voice. Logistic regression was used to elucidate the prediction model. Results: Among 277 older adults, an increase in A1 values was associated with a lower likelihood of energy-based frailty (odds ratio [OR] 0.81, 95{\%} CI 0.68-0.96), whereas an increase in A2 values resulted in a higher likelihood of sarcopenia-based frailty (OR 1.34, 95{\%} CI 1.18-1.52). Respondents with larger A3 and A4 values had a higher likelihood of hybrid-based frailty--sarcopenia (OR 1.03, 95{\%} CI 1.002-1.06) and hybrid-based frailty--energy (OR 1.43, 95{\%} CI 1.02-2.01), respectively. Conclusions: Vocal biomarkers might be potentially useful in estimating frailty phenotypes. Clinicians can use 2 crucial acoustic parameters, namely A1 and A2, to diagnose a frailty phenotype that is associated with insufficient energy or reduced muscle function. The assessment of A3 and A4 involves a complex frailty phenotype. ",
issn="1438-8871",
doi="10.2196/58466",
url="https://www.jmir.org/2024/1/e58466",
url="https://doi.org/10.2196/58466"
}