The Predictability of Frailty Associated with Musculoskeletal Deficits: A Longitudinal Study

Exploring causality between bone mineral density and frailty: A bidirectional Mendelian randomization study

OBJECTIVE

The bidirectional correlation between low bone mineral density (BMD) and frailty, despite its extensive documentation, still lacks a conclusive understanding. The objective of this Mendelian randomization (MR) study is to investigate the bidirectional causal relationship between BMD and frailty.

METHODS

We utilized summary statistics data for BMD at different skeletal sites-including heel BMD (e-BMD, N = 40,613), forearm BMD (FA-BMD, N = 8,143), femoral neck BMD (FN-BMD, N = 32,735), and lumbar spine BMD (LS-BMD, N = 28,489), alongside frailty index (FI, N = 175,226) data in participants of European ancestry. MR analysis in our study was conducted using well-established analytical methods, including inverse variance weighted (IVW), weighted median (WM), and MR-Egger approaches.

RESULTS

We observed negative causal estimates between genetically predicted e-BMD (IVW β = - 0.020, 95% confidence interval (CI) = - 0.038, - 0.002, P = 0.029) and FA-BMD (IVW β = -0.035, 95% CI = -0.066, -0.004, P = 0.028) with FI. However, the results did not reach statistical significance after applying the Bonferroni correction, with a significance threshold set at P < 0.0125 (0.05/4). There was no causal effect of FN-BMD (IVW β = - 0.024, 95% CI = -0.052, 0.004, P = 0.088) and LS-BMD (IVW β = - 0.005, 95% CI = -0.034, 0.024, P = 0.749) on FI. In the reverse Mendelian randomization (MR) analysis, we observed no causal effect of FI on BMD at various skeletal sites.

CONCLUSION

Our study provides support for the hypothesis that low BMD may be a potential causal risk factor for frailty, but further research is needed to confirm this relationship. However, our findings did not confirm reverse causality.

Frailty syndrome in women with osteoporosis, should physicians consider screening? A cross-sectional study

Despite its high prevalence and profound impact, frailty syndrome often goes undiagnosed. The study revealed a significant correlation between osteoporosis and frailty syndrome, with predictive accuracy exceeding 75 %. Given these findings and the existing recommendation for osteoporosis screening in older women, we underscore the importance of concurrently screening osteoporotic women for frailty.

Introduction

Frailty syndrome, a prevalent and significant geriatric condition, impacts healthcare costs and quality of life. Previous reviews have associated frailty syndrome with osteoporosis, but original research on this link is limited and has produced conflicting results. This study aims to investigate the relationship between frailty syndrome, osteoporosis, bone mineral densitometry T-score, and other influencing factors.

Methods

In this cross-sectional study, post-menopausal women underwent screening for osteoporosis and frailty syndrome using bone mineral densitometry and the Fried phenotype. Exclusion criteria included a history of diseases related to bone loss or medications affecting bone metabolism. Bivariate and multivariable tests were used to examine the correlation between frailty syndrome and various covariates, including the diagnosis of osteoporosis.

Results

A total of 272 women aged 60 to 89 years (mean age 68.57 ± 6.22) were evaluated. Osteoporosis was prevalent in 44.9 % of participants, and frailty syndrome was identified in 36.4 %. The regression model identified age, menopausal age, and the diagnosis of osteoporosis as variables significantly and independently associated with frailty syndrome. A T-score lower than -2.5 in the femur neck or lumbar spine exhibited a sensitivity of 86.6 % and specificity of 76.5 % in predicting frailty syndrome.

Conclusion

Older adults with osteoporosis face an increased risk of frailty syndrome. Therefore, we recommend that primary care providers screen osteoporotic women for frailty syndrome and, when appropriate, refer this group to geriatric specialists for further evaluation.

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.

The Assessment of Muscle Mass and Function in Patients with Long-Standing Rheumatoid Arthritis

Muscular dysfunction in rheumatoid arthritis (RA) can affect the quality of life and comorbidities. We enrolled 320 patients with RA, and evaluated their muscle mass, grip strength, and physical performance. Seven (2.2%) and 21 RA patients (6.6%) had sarcopenia, as defined by the European and Asian Working Group for Sarcopenia (EWGS and AWGS), respectively; 54 patients (16.9%) were determined to have low muscle mass with normal muscle function, as defined by the EWGS; 38 patients (11.9%) reported sarcopenia by SARC-F questionnaire. Male sex (odds ratio (OR) 140.65), low body mass index (BMI) (OR 0.41), and use of tumor necrosis factor (TNF) inhibitors (OR 4.84) were associated with a low muscle mass as defined by the EWGS, while male sex, old age, and low BMI were associated with sarcopenia as defined by the AWGS. Old age (OR 1.11), high BMI (OR 1.13), and a high Disease Activity Score 28 (OR 1.95) were associated with sarcopenia as reported on the SARC-F. Male, low BMI, and use of TNF inhibitors were associated with a low muscle mass, while male sex, old age, and low BMI were associated with sarcopenia in patients with long-standing RA.