Exploring the Association between Elevated Anxiety Symptoms and Low Skeletal Muscle Mass among Asymptomatic Adults: A Population-Based Study in Republic of Korea

Individuals with mental health problems are at higher risk of musculoskeletal diseases. However, the association between low muscle mass (LMM) and anxiety symptoms remains uninvestigated. This cross-sectional study enrolled 174,262 adults (73,833 women, 100,429 men), aged 18 to 89, who completed the anxiety scale and body composition analyses. Using bio-electrical impedance analysis, skeletal muscle mass index (SMI) was calculated based on appendicular skeletal muscle mass (ASM) (kg)/height (m2). LMM was defined as SMI < 7.0 kg/m2 in men and <5.4 kg/m2 in women. Anxiety symptoms were screened using the Clinical Useful Anxiety Outcome Scale (CUXOS) with cut-off scores of 20, 30, and 40. Multivariable logistic regression analyses were performed. LMM prevalence was 20.17% in women, 3.86% in men (p < 0.001). The prevalence of anxiety symptoms in LMM group decreased from mild (CUXOS > 20: women, 32.74%, men, 21.17%) to moderate (CUXOS > 30: 13.34%, 7.32%), to severe anxiety symptoms (CUXOS > 40: 4.00%, 1.73%). In multivariable-adjusted models, LMM was associated with mild (aOR (95% confidence interval)), women, 1.13 (1.08-1.17); men, 1.17 (1.08-1.27)), moderate (1.17 (1.11-1.24); 1.35 (1.19-1.53) and severe anxiety symptoms (1.18 (1.07-1.3), 1.36 (1.06-1.74)), demonstrating an increased risk of ORs with escalating anxiety severity. LMM was independently associated with a higher prevalence of anxiety symptoms.

How Well Do Low Population-Specific Values for Muscle Parameters Associate with Indices of Poor Physical Health? Cross-Sectional Data from the Geelong Osteoporosis Study

We aimed to examine associations between skeletal muscle deficits and indices of poor health. Cut-points for skeletal muscle deficits were derived using data from the Geelong Osteoporosis Study and definitions from the revised European Consensus on Definition and Diagnosis and the Foundation for the National Institutes of Health. Participants (n = 665; 323 women) aged 60–96 year had handgrip strength measured by dynamometry and appendicular lean mass by whole-body dual-energy X-ray absorptiometry. Physical performance was assessed using the Timed Up and Go test. Sex-specific cut-points were equivalent to two standard deviations below the mean young reference range from the Geelong Osteoporosis Study. Indices of poor health included fractures, falls, and hospitalisations. Low trauma fractures since age 50 year (excluding skull, face, digits) were self-reported and confirmed using radiological reports. Falls (≥1 in the past 12 months) and hospitalisations (past month) were self-reported. Logistic regression models (age- and sex-adjusted) were used to examine associations. Receiver Operating Characteristic curves were applied to determine optimal cut-points for handgrip strength, Timed Up and Go, appendicular lean mass/height2, and appendicular lean mass/body mass index that discriminated poor health outcomes. There were 48 participants (6.9%) with hospitalisations, 94 (13.4%) with fractures, and 177 (25.3%) with at least one fall (≥1). For all cut-points, low handgrip strength was consistently associated with falls. There was little evidence to support an association between low appendicular lean mass, using any cut-point, and indices of poor health. Optimal cut-offs for predicting falls (≥1) were: handgrip strength 17.5 kg for women and 33.5 kg for men; Timed Up and Go 8.6 s for women and 9.9 s for men; appendicular lean mass/height2 6.2 kg/m2 for women and 7.46 kg/m2 for men; and appendicular lean mass/body mass index 0.6 m2 for women and 0.9 m2 for men. In conclusion, muscle strength and function performed better than lean mass to indicate poor health. These findings add to the growing evidence base to inform decisions regarding the selection of skeletal muscle parameters and their optimal cut-points for identifying sarcopenia.

Associations Between Muscle Quality and Cognitive Function in Older Men: Cross-Sectional Data From the Geelong Osteoporosis Study

Sarcopenia-related declines appear to be adversely associated with cognition in the elderly. Poor muscle quality is a marker for sarcopenia, yet little research has examined the concurrence of poor muscle quality and poor cognition. The aim of this study was to investigate the association between muscle quality and cognitive function, overall and in specific domains, in older men. This study involved 342 men from the Geelong Osteoporosis Study (ages 60-96 years). Handgrip strength (HGS, kg) was measured by dynamometry (Vernier, LoggerPro3), and lean mass of arms (kg) and appendicular lean mass (ALM, kg) by dual-energy X-ray absorptiometry (Lunar). Muscle quality was expressed as HGS/(arm lean mass) (kg/kg) as well as HGS/ALM (kg/kg). Cognitive function was assessed in 4 domains: visual attention, psychomotor function, working memory and visual learning. Overall cognitive function scores were calculated. Higher scores represent poorer cognitive performance in attention, psychomotor function and working memory, but better performance for visual memory/learning and overall cognitive function. Additionally, cognitive impairment was determined by the mini-mental state exam (score ≤ 24). Linear regression analyses and logistic regression were performed. There were age-related declines observed for all measures relating to muscle and cognition. Muscle quality (HGS/arm lean mass) was associated with all cognition assessments before and after adjusting for age, except for age-adjusted working memory. Muscle quality (HGS/arm lean mass) was associated with psychomotor function (B -0.01, 95% CI -0.02, -0.005) and overall cognitive function (b + 0.07, 95% CI 0.03, 0.11) after adjusting for age and education. Greater muscle quality was also associated with the likelihood of cognitive impairment OR 0.64 (95%CI 0.46-0.88) after adjusting for age; associations with attention and visual memory/learning were attenuated after further adjustment for confounders. Similar patterns were observed when muscle quality was determined as HGS/ALM. Our data support an association between muscle quality and cognitive function. Further research is needed to examine temporal changes between the Two.