Predicting sarcopenia from functional measures among community-dwelling older adults.

Abstract

Sarcopenia is defined as age-related lean tissue mass (LTM) loss resulting in reduced muscular strength, physical function, and mobility. Up to 33% of older adults currently are sarcopenic, with likely many more undiagnosed. The purpose of this investigation was to predict sarcopenia status from easily accessible functional measures of community-dwelling older adults. Forty-three community-dwelling older adults (n = 32 females and n = 11 males) participated in the present investigation. Inclusion criteria included ≥65years of age, mini-mental state examination score ≥24, and no falls within previous 12months. All subjects completed their appendicular skeletal mass (ASM) assessment via dual-energy X-ray absorptiometry (DXA) and were categorized as either sarcopenic or non-sarcopenic. Physical assessments included 10-m usual walk, hand-grip (HG) strength, 6-min walk, 8-ft up-and-go, 30-s chair stand, 30-s arm curl, and sit-to-stand muscular power. A forward, stepwise multiple regression analysis revealed that age, sex, weight, height, 10-m walk, HG, and sit-to-stand muscular power account for 96.1% of the variance in ASM. The area under the curve was 0.92 for correctly identifying sarcopenic participants compared to their actual classification. This is the first prediction model used to identify sarcopenia based on parameters of demographic and functional fitness measures in community-dwelling older adults. The ability to accurately identify sarcopenia in older adults is imperative to their quality of life and ability to perform activities of daily living.