Identifying and Estimating Frailty Phenotypes by Vocal Biomarkers: Cross-Sectional Study.

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.