An appropriate ASMI cutoff value enhances utilization of the CHARLS database for studying sarcopenia

Area of Science:

• Gerontology and Geriatric Medicine
• Nutritional Science
• Biostatistics

Background:

• Sarcopenia research using the China Health and Retirement Longitudinal Study (CHARLS) often relies on an anthropometric equation to estimate appendicular skeletal muscle mass (ASM).
• Recent studies have raised concerns regarding the reliability of this commonly used estimation equation.
• This study aimed to validate the anthropometric equation against bioelectrical impedance analysis (BIA) and assess the impact of different diagnostic criteria for low muscle mass in CHARLS-based research.

Purpose of the Study:

• To validate the anthropometric equation for estimating appendicular skeletal muscle mass (ASM) against bioelectrical impedance analysis (BIA) measurements.
• To evaluate the influence of different cutoff values for defining low muscle mass on sarcopenia classification within the context of CHARLS-based studies.
• To provide recommendations for reliable sarcopenia assessment in aging populations, particularly those with diabetes.

Main Methods:

• Retrospective analysis of bioelectrical impedance analysis (BIA) data from 548 diabetic patients (aged 23-90 years).
• Comparison of appendicular skeletal muscle mass (ASM) measured by BIA (bASM) with ASM calculated using the anthropometric equation (cASM).
• Statistical analyses included Spearman correlation, intraclass correlation coefficient (ICC), Bland-Altman analysis, and Kappa statistics to compare different cutoff sets against the AWGS 2019 standard.

Main Results:

• The calculated ASM (cASM) showed a strong correlation with bioelectrical impedance analysis-measured ASM (bASM) (r=0.94, p<0.001), with excellent agreement indicated by ICC (0.933).
• Bland-Altman analysis revealed acceptable limits of agreement between the two measurement methods.
• One set of height-adjusted ASM (ASM/Ht2) cutoffs (men 7.05, women 5.63 kg/m²) demonstrated near-perfect agreement with the AWGS 2019 criteria (Kappa=0.909), while another set showed only moderate agreement and significant discordance.

Conclusions:

• The anthropometric equation for estimating appendicular skeletal muscle mass (ASM) is validated and remains a reliable tool for sarcopenia research utilizing CHARLS data, including in diabetic populations.
• The choice of cutoff values significantly impacts sarcopenia classification; AWGS 2019-aligned cutoffs are recommended for consistency.
• Adopting standardized, validated cutoffs ensures accurate sarcopenia diagnosis and enhances the comparability of findings across different studies.