Proposal and validation of an equation to identify sarcopenia using bioelectrical impedance analysis-derived parameters

Abstract

Objective

This study aimed to develop a simpler approach for diagnosing sarcopenia by using only bioelectrical impedance vector analysis parameters.

Methods

The study design was a cross-sectional study. The research was conducted based on the Itabashi Longitudinal Study on Aging, a community-based cohort study, with data collected from the 2022 and 2023 surveys in Itabashi Ward, Tokyo, Japan. The development cohort consisted of 1146 participants from the 2022 survey, and the validation cohort included 656 participants from the 2023 survey. Both cohorts were comprised of community-dwelling older adults with similar inclusion criteria. Sarcopenia was defined according to the Asian Working Group for Sarcopenia 2019 criteria. The logistic model utilized height divided by impedance at 50 kHz and phase angle to establish a new regression equation to identify sarcopenia. Regression equations were generated for the development cohort and validated for the validation cohort. Discriminatory ability was assessed using the area under the receiver operating characteristic curve (AUC) for men and women.

Results

The prevalence of sarcopenia was 20.7% and 14.8% in the development and validation cohort, respectively. The AUC (95% confidence interval) of the logistic model in discriminating sarcopenia was 0.92 (0.88, 0.95) for men and 0.82 (0.78, 0.86) for women in the development cohort and 0.85 (0.78, 0.91) for men and 0.90 (0.86, 0.95) for women in the validation cohort.

Conclusion

The study demonstrated that a simple formula using bioelectrical parameters at 50 kHz proved useful in identifying sarcopenia in the older adult population.