Sarcopenia is the loss of skeletal muscle mass and function with advancing age. It involves both complex genetic and modifiable risk factors, such as lack of exercise, malnutrition and reduced neurological drive. Cognitive decline refers to diminished or impaired mental and/or intellectual functioning. Contracting skeletal muscle is a major source of neurotrophic factors, including brain-derived neurotrophic factor, which regulate synapses in the brain. Furthermore, skeletal muscle activity has important immune and redox effects that modify brain function and reduce muscle catabolism. The identification of common risk factors and underlying mechanisms for sarcopenia and cognition may allow the development of targeted interventions that slow or reverse sarcopenia and also certain forms of cognitive decline. However, the links between cognition and skeletal muscle have not been elucidated fully. This review provides a critical appraisal of the literature on the relationship between skeletal muscle health and cognition. The literature suggests that sarcopenia and cognitive decline share pathophysiological pathways. Ageing plays a role in both skeletal muscle deterioration and cognitive decline. Furthermore, lifestyle risk factors, such as physical inactivity, poor diet and smoking, are common to both disorders, so their potential role in the muscle–brain relationship warrants investigation.

We aimed to examine muscle strength, function and mass in relation to cognition in older men. This cross-sectional data-set included 292 men aged ≥60 yr. Handgrip strength (kg) was measured by dynamometry, gait speed by 4-metre walk (m/s) and appendicular lean mass (kg) by dual-energy x-ray absorptiometry. Cognition was assessed across four domains: psychomotor function, attention, visual learning and working memory. Composite scores for overall cognition were calculated. Bivariate analyses indicated that handgrip strength and gait speed were positively associated with cognitive function. After accounting for confounders, positive associations between individual muscle (or physical) measures and cognitive performance were sustained for handgrip strength and psychomotor function, gait speed and psychomotor function, gait speed and attention, handgrip strength and overall cognition, and gait speed and overall cognition. In multivariable models, handgrip strength and gait speed independently predicted psychomotor function and overall cognition. No associations were detected between lean mass and cognition after adjusting for confounders. Thus, low muscle strength and slower gait speed, rather than low lean mass, were associated with poor cognition in older men.

Dementia comprises a wide range of progressive and acquired neurocognitive disorders. Obesity, defined as excessive body fat tissue, is a common health issue world-wide and a risk factor for dementia. The adverse effects of obesity on the brain and the central nervous system have been the subject of considerable research. The aim of this review is to explore the available evidence in the field of body–brain crosstalk focusing on obesity and brain function, to identify the major research measurements and methodologies used in the field, to discuss the potential risk factors and biological mechanisms, and to identify the research gap as a precursor to systematic reviews and empirical studies in more focused topics related to the obesity–brain relationship. To conclude, obesity appears to be associated with reduced brain function. However, obesity is a complex health condition, while the human brain is the most complicated organ, so research in this area is difficult. Inconsistency in definitions and measurement techniques detract from the literature on brain–body relationships. Advanced techniques developed in recent years are capable of improving investigations of this relationship.

Background: The extent of muscle deterioration associated with ageing or disease can be quantified by comparison with appropriate reference data. The objective of this study is to present normative data for lower-limb muscle strength and quality for 573 males and 923 females aged 20-97 yr participating in the Geelong Osteoporosis Study in southeastern Australia. Methods: In this cross-sectional study, measures of muscle strength for hip flexors and hip abductors were obtained using a Nicholas manual muscle tester, a hand-held dynamometer (HHD; kg). Leg lean mass was measured by dual energy x-ray absorptiometry (DXA; kg), and muscle quality calculated as strength/mass (N/kg). Results: For both sexes, muscle strength and quality decreased with advancing age. Age explained 12.9–25.3% of the variance in muscle strength in males, and 20.8–24.6% in females; age explained less of the variance in muscle quality. Means and standard deviations for muscle strength and quality for each muscle group are reported by age-decade for each sex, and cutpoints equivalent to T-scores of − 2.0 and − 1.0 were derived using data from young males (n = 89) and females (n = 148) aged 20–39 years. Conclusions: These data will be useful for quantifying the extent of dynapenia and poor muscle quality among adults in the general population in the face of frailty, sarcopenia and other age-related muscle dysfunction.

Background: Low handgrip strength (HGS) is a measure of poor skeletal muscle performance and a marker of ill health and frailty. Muscle quality (MQ) is a measure of muscle strength relative to muscle mass. We aimed to develop normative data for HGS and MQ, report age‐related prevalence of low HGS and MQ, and determine the relationship with age, anthropometry, and body composition for women in Australia.Methods: This cross‐sectional analysis included data from 792 women (ages 28–95 years) assessed by the Geelong Osteoporosis Study. Duplicate measures of HGS were performed for each hand with a dynamometer (Jamar) and the mean of maximum values used for analyses. Dual energy X‐ray absorptiometry‐derived lean mass for the arms was used to calculate MQ as HGS/lean mass (kg/kg). Body mass index (BMI) was categorized as normal (BMI < 25.0 kg/m²), overweight (25.0–29.9 kg/m²), and obese (>30.0 kg/m²). Fat mass index (FMI) was calculated as whole body fat/height² (kg/m²) and appendicular lean mass index (ALMI) as lean mass of arms and legs/height² (kg/m²).Results: Mean (±SD) of HGS values for normal BMI, overweight, and obese groups were 25 (±7), 24 (±7), and 24 (±7) kg, P = 0.09, and for MQ, 12 (±3), 11 (±3), and 10 (±3) kg/kg, P < 0.001. Our data indicated a quadratic relationship between age and HGS or MQ. Mean HGS and MQ remained stable until the fifth age decade then declined steadily with increasing age; therefore, we used data for women (n = 283) aged 28–49 years as the young adult reference group, with mean (SD) values for HGS 28 (±6) kg and MQ 12 (±3) kg/kg. The prevalence of low (T‐score < −2) HGS and MQ for women 80 years and older was 52.2% and 39.6%, respectively. In multivariable models, age‐adjusted HGS was associated with FMI (B = −0.13, P = 0.004) and ALMI (1.03, <0.001) while age‐adjusted MQ was associated with BMI (−0.15, <0.001) but not with FMI. In a sensitivity analysis, the same pattern remained after the removal of 129 women who reported hand and/or arm pain.Conclusions: Mean HGS and MQ declined with advancing age in older women. Our data suggest that while mean HGS increased with appendicular lean mass and decreased with body fat mass, there was no association with BMI. By contrast, MQ decreased with increasing BMI, but not with increasing adiposity.

Purpose of Review: Cognitive impairment is associated with obesity, sarcopenia, and osteoporosis. However, no critical appraisal of the literature on the relationship between musculoskeletal deficits and cognitive impairment, focusing on the epidemiological evidence and biological mechanisms, has been published to date. Herein, we critically evaluate the literature published over the past 3 years, emphasizing interesting and important new findings, and provide an outline of future directions that will improve our understanding of the connections between the brain and the musculoskeletal system. Recent Findings: Recent literature suggests that musculoskeletal deficits and cognitive impairment share pathophysiological pathways and risk factors. Cytokines and hormones affect both the brain and the musculoskeletal system; yet, lack of unified definitions and standards makes it difficult to compare studies. Summary: Interventions designed to improve musculoskeletal health are plausible means of preventing or slowing cognitive impairment. We highlight several musculoskeletal health interventions that show potential in this regard.