The SHARE Frailty Instrument for Primary Care was Associated with Sarcopenia, as Measured by Bioelectrical Impedance, in Falls Clinic Attendees

Objective

This study aimed to assess the association between measures of frailty phenotype (FP) and malnutrition, and sarcopenia measured by bioelectrical impedance analysis (BIA), in individuals aged 50 and above attending an outpatient falls clinic.

Methods

The Survey of Health, Ageing and Retirement in Europe Frailty Instrument (SHARE-FI) gauged FP status, while nutritional assessment relied on the Mini Nutritional Assessment-Short Form (MNA®-SF). Body composition, specifically appendicular skeletal muscle mass (ASMM), was determined through TANITA® DC-430MA BIA. Multivariable binary logistic regression models were used to predict pre-frailty or frailty based on SHARE-FI and at-risk of malnutrition or malnutrition based on MNA®-SF.

Results

Out of the 123 participants (68 women, 55 men), 56.1% were classified as robust, 27.6% as living with pre-frailty, and 16.3% as living with frailty according to SHARE-FI. MNA®-SF results were available for 116 patients, with 54.3% categorised as normal, 39.7% at risk of malnutrition, and 6.0% as malnourished. Among the 118 patients who underwent BIA, ASMM was independently associated with pre-frail/frail status, but there was no significant association between abnormal MNA®-SF and sarcopenia.

Conclusion

SHARE-FI, a modified FP tool, demonstrated an independent association with sarcopenia as measured by BIA.

Investigating the impact of fluid status on the ultrasound assessment of muscle quantity and quality in the diagnosis of sarcopenia - a multidimensional cross-sectional study

BACKGROUND

Sarcopenia is a clinical manifestation of adverse ageing, characterised by progressive loss of muscle mass and function. Diagnosis requires assessment of muscle quantity and quality; ultrasound represents an emerging tool for this. However, ultrasound muscle assessment may be impacted by fluid balance. This is particularly important when assessing for acute sarcopenia in hospitalised patients, where fluid disturbance often occurs. The primary aim of this study was to characterise the impact of fluid status on ultrasound muscle assessment, such that this may be accounted for in sarcopenia diagnostics.

METHODS

This Multidimensional Cross-sectional study involved 80 participants, who were inpatients at QEHB, a large UK tertiary centre. Fluid status was evaluated clinically and quantified using Bioelectrical Impedance Analysis (BIA). Muscle quantity was measured using Bilateral Anterior Thigh Thickness (BATT) with Rectus Femoris (RF) echogenicity used to assesses muscle adiposity and hence provide an inverse measure of muscle quality.

RESULTS

A significant positive correlation was found between fluid status, measured using BIA, and BATT as a measure of muscle quantity, in males (rs = 0.662, p < 0.001) and females (rs = 0.638, p < 0.001). A significant negative correlation was found between fluid status and RF echogenicity (rs=-0.448, p < 0.001).

CONCLUSIONS

These findings demonstrate associations between fluid balance and ultrasound assessment of muscle quantity and quality. Given the emerging use of ultrasound muscle assessment in sarcopenia diagnosis, there is a need to account for this in clinical practice. Future research should focus on the development of a corrective equation allowing assessment of muscle quantity and quality which account for changes in fluid status, hence aiding accurate diagnosis of sarcopenia.

Body composition analysis to determine gender specific physical fitness equations in a cohort of Saudi population

Objective: To determine an association between body composition analysis and physical fitness in the Saudi population and derive gender specific physical fitness equations.

Methods: A total of 530 healthy Saudi adults aged 15-72 years (mean 37.16±14.12 years) were enrolled in this study. Body composition analysis was assessed by bioelectrical impedance analysis (BIA), with a commercially available body analyzer according to standard protocols.

Results: Different body composition parameters, such as age, height, BSA (body surface area), obesity degree, body mass index (BMI), body fat mass (BFM) and percent body fat (% BF) contents were significantly different in males and females except weight which was non-significant (p=0.649). There was significant positive or negative correlation among different body composition parameters except weight with age in males and weight with age, height and BSA in females. In males, all the body composition characteristics contributed to the fitness score except BMI and BFM, while in females, the most significant effect was contributed by weight and BFM. Female body composition characteristics were strongly related to fitness score compared to males (R² = 93.8% vs R² = 78.5%).

Conclusions: Different body composition parameters like BFM and %BF played an important role in determining physical fitness of healthy male individuals instead of BMI, weight and BSA, while in females weight was the best predictor of physical fitness.