Associations Between Aldosterone-Renin-Ratio and Bone Parameters Derived from Peripheral Quantitative Computed Tomography and Impact Microindentation in Men.

Components of the renin-angiotensin-aldosterone system (RAAS) are present on bone cells. One measure of RAAS activity, the aldosterone-renin-ratio (ARR), is used to screen for primary aldosteronism. Associations between ARR and bone mineral density are conflicting. This study investigated associations between ARR and peripheral quantitative computed tomography (pQCT) and impact microindentation (IMI). Male participants (n = 431) were from the Geelong Osteoporosis Study. "Likely" primary aldosteronism was defined as ARR ≥ 70 pmol/mIU. Another group, "possible" primary aldosteronism, was defined as either ARR ≥ 70 pmol/mIU or taking a medication that affects the RAAS, but not a beta blocker, and renin < 15 mU/L. Using pQCT, images at 4% and 66% of radial (n = 365) and tibial (n = 356) length were obtained. Using IMI measurements, bone material strength index (BMSi; n = 332) was determined. Associations between ARR or likely/possible primary aldosteronism and IMI or pQCT-derived bone parameters were tested using median regression. ARR and aldosterone values were not associated with any of the pQCT-derived bone variables in either unadjusted or adjusted analyses. Men with likely primary aldosteronism (n = 16), had lower adjusted total bone area (radial 66% site, - 12.5%). No associations were observed for men with possible primary aldosteronism (unadjusted or adjusted). No associations with BMSi were observed (p > 0.05). There were no associations between ARR or aldosterone and pQCT-derived bone parameters. Men with likely primary aldosteronism had lower bone area, suggesting clinically high levels of ARR may have a negative impact on bone health.

A cross-sectional health literacy profile of Australian regional adults using the Health Literacy Questionnaire©.

OBJECTIVE: Health literacy is the resources and abilities required to make and enact health decisions. This study aimed to describe the health literacy of a diverse cross-section of adults in regional Victoria. METHODS: Participants were recruited from two primary care clinics differing in socioeconomic scope and through non-clinical recruitment via the town's largest football club. Health Literacy Questionnaire© measured nine distinct scales, and comprehensive demographic data were also collected. Effect-sizes and regression were used for health literacy comparison between groups. RESULTS: In this sample of 351 adults, health literacy strengths were observed in Scale 1: 'Feeling understood and supported by healthcare providers' (mean 3.29/4 ±0.5) and Scale 9: 'Understanding health information well enough to know what to do' (mean 4.10/5 ±0.6). Challenging areas were Scale 5: 'Appraising health information' (mean 2.88/4 ±0.5) and Scale 7: 'Navigating the healthcare system' (mean 3.84/5 ±0.6). After adjustment, living alone predicted lower scores across most scales. CONCLUSIONS: This study showed greater health literacy barriers experienced by certain groups, particularly those who live alone and those who weren't clinically recruited. IMPLICATIONS FOR PUBLIC HEALTH: These findings have implications for further research into addressing health literacy barriers in marginalised individuals and non-clinical settings. Results from this study may inform interventions which address identified barriers.

Peripheral quantitative computed tomography-derived bone parameters in men with impaired fasting glucose and diabetes.

INTRODUCTION: Individuals with type 2 diabetes mellitus (T2DM) are at higher risk of fracture, but paradoxically do not have reduced bone mineral density. We investigated associations between peripheral quantitative computed tomography (pQCT) and glycaemia status. MATERIALS AND METHODS: Participants were men (n = 354, age 33-92 year) from the Geelong Osteoporosis Study. Diabetes was defined by fasting plasma glucose (FPG) ≥ 7.0 mmol/L, self-report of diabetes and/or antihyperglycaemic medication use and impaired fasting glucose (IFG) as FPG 5.6-6.9 mmol/L. Bone measures were derived using pQCT (XCT2000) at 4% and 66% radial and tibial sites. Linear regression was used, adjusting for age, body mass index and socio-economic status. RESULTS: At the 4% site, men with T2DM had lower adjusted bone total area, trabecular area and cortical area at the radius (all - 6.2%) and tibia (all - 6.4%) compared to normoglycaemia. Cortical density was higher for T2DM at the radius (+ 5.8%) and tibia (+ 8.0%), as well as adjusted total bone density at the tibial site (+ 6.1%). At the 66% site, adjusted total bone area and polar stress strain index were lower for T2DM at the radius (- 4.3% and - 8.0%). Total density was also higher for T2DM (+ 1.2%). Only cortical density at the 4% tibial site was different between IFG and normoglycaemia in adjusted analyses (+ 4.5%). CONCLUSION: Men with T2DM had lower total bone area, trabecular area, cortical area and polar stress strain index than the other two groups; however, total density and cortical density were higher. Only one difference was observed between IFG and normoglycaemia; increased tibial cortical density.

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.

Evaluating telehealth lifestyle therapy versus telehealth psychotherapy for reducing depression in adults with COVID-19 related distress: the curbing anxiety and depression using lifestyle medicine (CALM) randomised non-inferiority trial protocol.

BACKGROUND: There is increasing recognition of the substantial burden of mental health disorders at an individual and population level, including consequent demand on mental health services. Lifestyle-based mental healthcare offers an additional approach to existing services with potential to help alleviate system burden. Despite the latest Royal Australian New Zealand College of Psychiatrists guidelines recommending that lifestyle is a 'first-line', 'non-negotiable' treatment for mood disorders, few such programs exist within clinical practice. Additionally, there are limited data to determine whether lifestyle approaches are equivalent to established treatments. Using an individually randomised group treatment design, we aim to address this gap by evaluating an integrated lifestyle program (CALM) compared to an established therapy (psychotherapy), both delivered via telehealth. It is hypothesised that the CALM program will not be inferior to psychotherapy with respect to depressive symptoms at 8 weeks. METHODS: The study is being conducted in partnership with Barwon Health's Mental Health, Drugs & Alcohol Service (Geelong, Victoria), from which 184 participants from its service and surrounding regions are being recruited. Eligible participants with elevated psychological distress are being randomised to CALM or psychotherapy. Each takes a trans-diagnostic approach, and comprises four weekly (weeks 1-4) and two fortnightly (weeks 6 and 8) 90-min, group-based sessions delivered via Zoom (digital video conferencing platform). CALM focuses on enhancing knowledge, behavioural skills and support for improving dietary and physical activity behaviours, delivered by an Accredited Exercise Physiologist and Accredited Practising Dietitian. Psychotherapy uses cognitive behavioural therapy (CBT) delivered by a Psychologist or Clinical Psychologist, and Provisional Psychologist. Data collection occurs at baseline and 8 weeks. The primary outcome is depressive symptoms (assessed via the Patient Health Questionnaire-9) at 8 weeks. Societal and healthcare costs will be estimated to determine the cost-effectiveness of the CALM program. A process evaluation will determine its reach, adoption, implementation and maintenance. DISCUSSION: If the CALM program is non-inferior to psychotherapy, this study will provide the first evidence to support lifestyle-based mental healthcare as an additional care model to support individuals experiencing psychological distress. TRIAL REGISTRATION: Australia and New Zealand Clinical Trials Register (ANZCTR): ACTRN12621000387820 , Registered 8 April 2021.

Fatty Liver Index and Skeletal Muscle Density.

Accumulation of fat in the liver and skeletal muscle is associated with obesity and poor health outcomes. Liver steatosis is a characteristic of non-alcoholic fatty liver disease (NAFLD) and myosteatosis, of poor muscle quality in sarcopenia. In this study of 403 men (33-96 years), we investigated associations between the fatty liver index (FLI) and muscle density, as markers of fat accumulation in these organs. We also investigated associations between the FLI and parameters of sarcopenia, including DXA-derived appendicular lean mass (ALM) and handgrip strength by dynamometry. Muscle density was measured using pQCT at the radius and tibia. FLI was calculated from BMI, waist circumference, and levels of triglycerides and gamma-glutamyltransferase. There was a pattern of decreasing muscle density across increasing quartiles of FLI. After adjusting for age and lifestyle, mean radial muscle density in Q4 was 2.1% lower than Q1 (p < 0.001) and mean tibial muscle density was 1.8% lower in Q3 and 3.0% lower in Q4, compared to Q1 (p = 0.022 and < 0.001, respectively). After adjusting for age and sedentary lifestyle, participants in the highest FLI quartile were sixfold more likely to have sarcopenia. In conclusion, our results suggest that fat accumulation in the liver co-exists with fat infiltration into skeletal muscle.

Associations between parameters of peripheral quantitative computed tomography and bone material strength index.

BACKGROUND: Bone material strength index (BMSi) is measured in vivo using impact microindentation (IMI). However, the associations between BMSi and other bone measures are not clear. This study investigated whether bone parameters derived by peripheral quantitative computed tomography (pQCT) are associated with BMSi. METHODS: Participants were men (n = 373, ages 34-96 yr) from the Geelong Osteoporosis Study. BMSi was measured using an OsteoProbe (Active Life Scientific, USA). Bone measures were obtained at both the radius (n = 348) and tibia (n = 342) using pQCT (XCT 2000 Stratec Medizintechnik, Germany). Images were obtained at 4% and 66% of radial and tibial length. Associations between pQCT parameters and BMSi were tested using Spearman's correlation and multivariable regression used to determine independent associations after adjustment for potential confounders. Models were checked for interaction terms. RESULTS: Weak associations were observed between total bone density (radius 4%; r = +0.108, p = 0.046, tibia 4%; r = +0.115, p = 0.035), cortical density (tibia 4%; r = +0.123, p = 0.023) and BMSi. The associations were independent of weight, height, and glucocorticoid use (total bone density: radius 4%; ß = 0.020, p = 0.006, tibia 4%; ß = 0.020, p = 0.027 and cortical density: radius 4%; ß = 4.160, p = 0.006, tibia 4%; ß = 0.038, p = 0.010). Associations with bone mass were also observed at the 66% radial and tibial site, independent of age, weight, and glucocorticoid use (ß = 4.160, p = 0.053, ß = 1.458, p = 0.027 respectively). Total area at the 66% tibial site was also associated with BMSi (ß = 0.010, p = 0.012), independent of weight and glucocorticoid use. No interaction terms were identified. CONCLUSION: There were weak associations detected between some pQCT-derived bone parameters and BMSi.

Frailty associations with socioeconomic status, healthcare utilisation and quality of life among older women residing in regional Australia.

OBJECTIVES: The health and well-being of older women may be influenced by frailty and low socioeconomic status (SES). This study examined the association between frailty and SES, healthcare utilisation and quality of life (QOL) among older women in regional Australia. METHODS: Cross-sectional analysis of the Geelong Osteoporosis Study was conducted on 360 women (ages ≥60yr) in the 15-year follow up. Frailty was identified using modified Fried's phenotype. Individual SES measures and healthcare utilisation were documented by questionnaire. Area-based SES was determined by cross-referencing residential addresses with the Australian Bureau of Statistics Index of Relative Socio-economic Advantage and Disadvantage (IRSAD). QOL was measured using the Australian World Health Organisation Quality of Life Instrument (WHOQoL-Bref). Multinomial logistic regression was conducted with frailty groupings as outcome. RESULTS: Sixty-two (17.2%) participants were frail, 199 (55.3%) pre-frail and 99 (27.5%) robust. Frail participants were older with higher body mass index. Frailty was associated with lower education but not marital status, occupation or IRSAD. Strong associations with frailty were demonstrated for all WHOQoL-Bref domains. Frailty was associated with more primary care doctor visits (p<0.001). CONCLUSIONS: This population-based study highlights the significant impact of frailty on older women, indicating reduced QOL and increased primary care doctor visits.

The contribution of musculoskeletal factors to physical frailty: a cross-sectional study.

BACKGROUND: Musculoskeletal conditions and physical frailty have overlapping constructs. We aimed to quantify individual contributions of musculoskeletal factors to frailty. METHODS: Participants included 347 men and 360 women aged ≥60 yr (median ages; 70.8 (66.1-78.6) and 71.0 (65.2-77.5), respectively) from the Geelong Osteoporosis Study. Frailty was defined as ≥3, pre-frail 1-2, and robust 0, of the following; unintentional weight loss, weakness, low physical activity, exhaustion, and slowness. Measures were made of femoral neck BMD, appendicular lean mass index (ALMI, kg/m2) and whole-body fat mass index (FMI, kg/m2) by DXA (Lunar), SOS, BUA and SI at the calcaneus (Lunar Achilles Insight) and handgrip strength by dynamometers. Binary and ordinal logistic regression models and AUROC curves were used to quantify the contribution of musculoskeletal parameters to frailty. Potential confounders included anthropometry, smoking, alcohol, prior fracture, FMI, SES and comorbidities. RESULTS: Overall, 54(15.6%) men and 62(17.2%) women were frail. In adjusted-binary logistic models, SI, ALMI and HGS were associated with frailty in men (OR = 0.73, 95%CI 0.53-1.01; OR=0.48, 0.34-0.68; and OR = 0.11, 0.06-0.22; respectively). Muscle measures (ALMI and HGS) contributed more to this association than did bone (SI) (AUROCs 0.77, 0.85 vs 0.71, respectively). In women, only HGS was associated with frailty in adjusted models (OR = 0.30 95%CI 0.20-0.45, AUROC = 0.83). In adjusted ordinal models, similar results were observed in men; for women, HGS and ALMI were associated with frailty (ordered OR = 0.30 95%CI 0.20-0.45; OR = 0.56, 0.40-0.80, respectively). CONCLUSION: Muscle deficits appeared to contribute more than bone deficits to frailty. This may have implications for identifying potential musculoskeletal targets for preventing or managing the progression of frailty.

Peripheral quantitative computed tomography (pQCT) measures are associated with prior low trauma fracture in men.

Peripheral quantitative computed tomography (pQCT) assesses bone quantity and quality, complementary to current standard practice, and has potential to improve prediction of fracture risk. This study explored whether pQCT parameters were associated with prior fracture in men and found a number of parameters to be associated, particularly at the radius. PURPOSE: Peripheral quantitative computed tomography (pQCT) provides information about bone structure and density complementary to dual x-ray absorptiometry. This study aimed to determine which pQCT parameters are associated with prior fracture. METHODS: Participants were men (n = 508, age 33-96 years) from the Geelong Osteoporosis Study. Parameters at 4% (n = 469) and 66% (n = 436) of radial length, and 4% (n = 449) and 66% (n = 437) of tibial length were acquired (pQCT XCT 2000, Stratec Medizintechnik, Pforzheim, Germany), and mean standardised. Low trauma prior fractures in adulthood (≥ age 20 years) were radiologically confirmed when possible. Cross-sectional associations between pQCT and fracture were tested using logistic regression adjusting for confounders. RESULTS: Prior low trauma fractures were identified for 106 participants. Fracture was negatively associated with parameters at the 4% radius site: bone mass (adjusted OR = 0.67; 95%CI = 0.52-0.86), total density (OR = 0.61; 95%CI = 0.47-0.78), trabecular density (OR = 0.62; 95%CI = 0.48-0.79) and cortical subdensity (OR = 0.61; 95%CI = 0.47-0.77). At the 66% radius site, fracture was associated with total density (OR = 0.69; 95%CI = 0.55-0.87) and cortical thickness (OR = 0.68; 95%CI = 0.54-0.86). Fracture was associated with the ratio of the cortical area at the 66% site to the total area at the 4% site (OR = 0.74; 95%CI = 0.58-0.94). Prior fracture was negatively associated with parameters at the 4% tibial site: total density (OR = 0.67; 95%CI = 0.52-0.86), trabecular density (OR = 0.64; 95%CI = 0.50-0.82) and cortical subdensity (OR = 0.72; 95%CI = 0.56-0.92). Fracture was negatively associated with cortical density at the 66% site (OR = 0.74; 95%CI = 0.58-0.94), and the ratio of the cortical area at the 66% site to the total area at the 4% site (OR = 0.65; 95%CI = 0.46-0.91), but were attenuated in adjusted models. No other associations were identified. CONCLUSION: Prior fracture was associated with parameters at both the radius and tibia. This study highlights key pQCT parameters that may aid in the prediction of fracture risk.

Normative data for peripheral quantitative computed tomography (pQCT) bone parameters in Australian men.

BACKGROUND: Peripheral quantitative computed tomography (pQCT) can provide information complementary to dual x-ray absorptiometry (DXA), however, there is sparse normative data to enable meaningful clinical interpretation and comparison. This study aimed to develop age-stratified normative data for pQCT-derived bone parameters in Australian men. METHODS: Participants were men (n = 508, age 33-96 yr) from the Geelong Osteoporosis Study. Bone parameters at 4% (n = 469) and 66% (n = 436) of radial length, and 4% (n = 449) and 66% (n = 438) of tibial length were acquired using pQCT (XCT 2000, Stratec Medizintechnik, Pforzheim, Germany). Best models of age, height and weight for each parameter were developed and where parameters exhibited variation with age, age decade mean (±SD) values were determined. Scatterplots were used to visualise the relationships between each of the parameters and age, height and weight. RESULTS: Thirteen parameters at tibial and radial sites were correlated with age, height and weight, allowing for their inclusion in multiple linear regression models. A positive association with age was found for total area of the tibia or radius (as appropriate) (mm2) at all sites, trabecular bone area (mm2) at 4% sites, and total bone area (both long bones) (mm2) at 66% sites. A negative association with age was found for cortical density (mg/cm3) and cortical thickness (mm) at both radial and tibial 66% sites, but total density (mg/cm3) at the 66% radial site and total cortical density of both long bones (mg/cm3) at the 66% tibial site only. CONCLUSION: This study presents normative data for pQCT-derived bone parameters and describes age related associations in a number of these variables. Broadly, parameters of bone area were positively associated with age, whereas parameters associated with bone density and structure were negatively associated with age. These data have the potential to be used in clinical settings when assessing age-related decline in bone health. MINI ABSTRACT: Normative data for pQCT parameters in Australian men are presented, adjusted for age, height and weight.

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

We investigated and quantified the predictability of frailty associated with musculoskeletal parameters. This longitudinal study included 287 men aged ≥ 50 yr at baseline (2001-2006) from the Geelong Osteoporosis Study. Baseline musculoskeletal measures included femoral neck bone mineral density (BMD), appendicular lean mass index (ALMI, kg/m2) and whole-body fat mass index (FMI, kg/m2) and lower-limb strength. Frailty at the 15 yr-follow-up (2016-2019) was defined as ≥ 3 and non-frail as < 3, of the following: unintentional weight loss, weakness, low physical activity, exhaustion, and slowness. Binary regression models and AUROC curves quantified the attributable risk of musculoskeletal factors to frailty and their predictive ability. Potential confounders included anthropometry, smoking, alcohol, FMI, socioeconomic status and comorbidities. Forty-eight (16.7%) men were frail at 15 yr-follow-up. Musculoskeletal models were better predictors of frailty compared to the referent (confounders only) model (AUROC for musculoskeletal factors 0.74 vs 0.67 for the referent model). The model with the highest AUROC (0.74; 95% CI 0.66-0.82) included BMD, ALMI and muscle strength (hip abductors) and was better than the referent model that included only lifestyle factors (p = 0.046). Musculoskeletal parameters improved the predictability model as measured by AUROC for frailty after 15 years. In general, muscle models performed better compared to bone models. Musculoskeletal parameters improved the predictability of frailty of the referent model that included lifestyle factors. Muscle deficits accounted for a greater proportion of the risk for frailty than did bone deficits. Targeting musculoskeletal health could be a possible avenue of intervention in regards to frailty.

Association between serum interleukin-6 and frailty in older men: cross-sectional data.

PURPOSE: To investigate the association between serum interleukin-6 (IL-6) and frailty. METHODS: Participants were 581 men aged 60-90 yr (median (IQR): 74 yr (67-83 yr)) from the Geelong Osteoporosis Study. Tallies of ≥ 3, 1-2 and 0 for weight loss/exhaustion/physical-inactivity/slowness/weakness indicated frailty, pre-frailty and robustness, respectively. Anthropometry, lower-limb muscle strength and physical performance were measured and health behaviours self-reported. Serum IL-6 was measured using an enzyme-linked immunosorbent assay and log-transformed (ln-IL-6). Total antioxidant capacity (TAC) was also measured using quantitative colorimetric determination. Multivariable ordinal logistic regression models tested associations between ln-IL-6 and frailty while considering age, anthropometry, comorbidities, TAC, medications that affect inflammatory processes, lifestyle and socioeconomic status. RESULTS: There were 49(8.4%) frail and 315(54.2%) pre-fail men. A relationship was evident between ln-IL-6 and frailty before and after accounting for age (adjusted OR = 1.24, 95%CI 1.01-1.53). Adjusting for medications attenuated the association (OR = 1.20, 95%CI 0.98-1.48). No other confounders were identified. CONCLUSION: These data suggest that IL-6 is positively associated with frailty in men, partly explained by advancing age and medications known to affect inflammation.

Prevalence of Sarcopenia Employing Population-Specific Cut-Points: Cross-Sectional Data from the Geelong Osteoporosis Study, Australia.

BACKGROUND: Prevalence estimates for sarcopenia vary depending on the ascertainment criteria and thresholds applied. We aimed to estimate the prevalence of sarcopenia using two international definitions but employing Australian population-specific cut-points. METHODS: Participants (n = 665; 323 women) aged 60-96 years old were from the Geelong Osteoporosis Study. Handgrip strength (HGS) was measured by dynamometers and appendicular lean mass (ALM) by whole-body dual-energy X-ray absorptiometry. Physical performance was assessed using gait speed (GS, men only) and/or the timed up-and-go (TUG) test. Using cut-points equivalent to two standard deviations (SDs) below the mean young reference range from the same population and recommendations from the European Working Group on Sarcopenia in Older People (EWGSOP), sarcopenia was identified by low ALM/height2 (<5.30 kg for women; <6.94 kg for men) + low HGS (<16 kg women; <31 kg men); low ALM/height2 + slow TUG (>9.3 s); low ALM/height2 + slow GS (<0.8 m/s). For the Foundation for the National Institutes of Health (FNIH) equivalent, sarcopenia was identified as low ALM/BMI (<0.512 m2 women, <0.827 m2 men) + low HGS (<16 kg women, <31 kg men). Receiver Operating Characteristic curves were also applied to determine optimal cut-points for ALM/BMI (<0.579 m2 women, <0.913 m2 men) that discriminated poor physical performance. Prevalence estimates were standardized to the Australian population and compared to estimates using international thresholds. RESULTS: Using population-specific cut-points and low ALM/height2 + HGS, point-estimates for sarcopenia prevalence were 0.9% for women and 2.9% for men. Using ALM/height2 + TUG, prevalence was 2.5% for women and 4.1% for men, and using ALM/height2 + GS, sarcopenia was identified for 1.6% of men. Using ALM/BMI + HGS, prevalence estimates were 5.5-10.4% for women and 11.6-18.4% for men. CONCLUSIONS: This study highlights the range of prevalence estimates that result from employing different criteria for sarcopenia. While population-specific criteria could be pertinent for some populations, a consensus is needed to identify which deficits in skeletal muscle health are important for establishing an operational definition for sarcopenia.

Dynapenia and Low Cognition: A Cross-Sectional Association in Postmenopausal Women.

Dynapenia is a key contributor to physical frailty. Cognitive impairment and dementia accompany frailty, yet links between skeletal muscle and neurocognition are poorly understood. We examined the cross-sectional relationship between lower limb muscle strength and global cognitive function. Participants were 127 women aged 51-87 years, from the Geelong Osteoporosis Study. Peak eccentric strength of the hip-flexors and hip abductors was determined using a hand-held dynamometer, and dynapenia identified as muscle strength t-scores < -1. Cognition was assessed using the Mini-Mental State Examination (MMSE), and MMSE scores below the median were rated as low. Associations between dynapenia and low cognition were examined using logistic regression models. Hip-flexor dynapenia was detected in 38 (71.7%) women with low cognition and 36 (48.7%) with good cognition (p = 0.009); for hip abductor dynapenia, the pattern was similar (21 (39.6%) vs. 9 (12.2%); p < 0.001). While the observed difference for hip-flexor strength was attenuated after adjusting for age and height (adjusted Odds Ratio (OR) 1.95, 95%CI 0.86-4.41), low cognition was nearly 4-fold more likely in association with hip abductor dynapenia (adjusted OR 3.76, 95%CI 1.44-9.83). No other confounders were identified. Our data suggest that low strength of the hip abductors and low cognition are associated and this could be a consequence of poor muscle function contributing to cognitive decline or vice versa. As muscle weakness is responsive to physical interventions, this warrants further investigation.

Skeletal Muscle Density and Cognitive Function: A Cross-Sectional Study in Men.

We aimed to investigate cross-sectional associations between skeletal muscle density, a proxy measure for fatty infiltration into muscle, and cognition. Contributions from body fat mass, systemic inflammation and lifestyle were explored, as these factors have been identified in both muscle and cognitive deterioration. For 281 men (60-95 year) from the Geelong Osteoporosis Study, radial and tibial muscle density were measured using peripheral quantitative computed tomography. Body fat and appendicular lean mass were measured using dual-energy X-ray absorptiometry. Cognitive function was assessed for psychomotor function (DET), visual identification/attention (IDN), visual learning (OCL) and working memory (OBK) (CogState Brief Battery). Composite scores signified overall cognitive function (OCF). Higher scores represent poorer performance except for OCL and OCF. Regression analyses examined associations between muscle density and cognition; potential confounders included age, muscle cross-sectional area (CSA), body composition, lifestyle and serum markers of inflammation. Negative associations with age were evident for muscle density, all cognitive domains and OCF. Muscle density at both sites was positively associated with DET, OCL and OCF. After adjustment for age, the association persisted for DET (radius: B = - 0.006, p = 0.02; tibia: B = - 0.003, p = 0.04) and OCL (radius B = + 0.004, p = 0.02; tibia: B = + 0.005, p < 0.001). At the radius, further adjustment for serum TNF-α explained the association between muscle density (B = - 0.002, p = 0.66) and DET. Education and physical activity contributed to the model for radial muscle density and DET. There were no contributions from muscle CSA, appendicular lean mass, body fat mass, other markers of inflammation or other potential confounders. At the tibia, the association between muscle density and DET (B = - 0.003, p = 0.04) was independent of TNF-α. There was an age-adjusted association between muscle density and OCL at both sites (radius: B = + 0.004, p = 0.02; tibia: B = + 0.005, p < 0.001). None of the potential confounders contributed to the models. Muscle density was associated with cognitive function in the DET and OCL domains. However, there was little evidence that this was explained by inflammation or body fat mass. No associations were identified between muscle density and IDN or OBK.

Total Antioxidant Capacity and Frailty in Older Men.

Frailty, a clinical syndrome characterized by multisystem dysregulation, has been associated with high levels of oxidative stress. We investigated the association between serum total antioxidant capacity (TAC) and frailty in older men. This cross-sectional study included 581 men (age 60-90 years) enrolled in the Geelong Osteoporosis Study. Frailty comprised at least three of unintentional weight loss, exhaustion, low physical activity, slowness, and weakness. Serum TAC was measured by quantitative colorimetric determination and expressed as uric acid equivalents (mM). Relationships between TAC (in SD units) and frailty were explored using multivariable logistic regression models. Sociodemographic, anthropometric, and lifestyle variables were tested as potential confounders and effect modifiers. A sensitivity analysis excluded participants (n = 145) in the upper quartile of TAC, who were likely to have hyperuricemia. Fifty (8.6%) men were frail. There was evidence that higher TAC levels were associated with increased likelihood of frailty (OR 1.34, 95% confidence interval [CI; 0.99, 1.80]), and this was attenuated after adjustment for age and body mass index (BMI; OR 1.26, 95% CI [0.93,1.71]). No effect modifiers or other confounders were identified. The sensitivity analysis revealed a positive association between TAC and frailty, before and after accounting for age and BMI (adjusted OR 1.79, 95% CI [1.01, 3.17] p = .038). These results suggest a positive association between TAC levels and frailty, supporting the hypothesis that this biomarker could be useful in identifying individuals at risk of frailty. We speculate that a milieu of heightened oxidative stress in frailty may elevate the oxidative stress regulatory set point, raising antioxidant activity. This warrants further investigation.

Prevalence of Frailty in Older Men and Women: Cross-Sectional Data from the Geelong Osteoporosis Study.

Few studies have investigated the prevalence of frailty in the Australian general population. This study determined the prevalence of frailty in a population-based sample of older adults and examined the relationship between frailty and comorbid conditions. Men (n = 347) and women (n = 360) aged ≥ 60 year from the Geelong Osteoporosis Study (GOS) were assessed between 2016-2019 and 2011-2014, respectively. Frailty was identified using a modified Fried frailty phenotype. Prevalence estimates were standardised to the 2011 Australian population. Kruskal-Wallis test and χ2 test were used to analyse data. For women, mean standardised prevalence estimates were 18.3% (14.1-22.5) for frail, 54.1% (47.3-60.8) pre-frail and 22.9% (18.9-26.8) robust. Corresponding estimates for men were 13.1% (9.8-16.3) frail, 47.8% (42.0-53.6) pre-frail and 27.3% (22.7-31.8) robust. Women who were frail were older, shorter, tended to have a higher body mass index (BMI) and used more medications compared to other groups. Compared to robust women, those who were frail were more likely to have cardio-metabolic (OR 3.5 (0.7-20.0)), pulmonary (OR 3.5 (1.5-8.4)) and musculoskeletal (OR 10.1 (2.1-48.0)) conditions. Frail men were older, had a higher BMI and were more likely to have musculoskeletal conditions (OR 5.8 (2.8-12.3)) and tended to be from a lower SES. No further associations were observed. This study reported the prevalence of frail and pre-frail individuals in a population-based sample of Australian men and women. Frailty was associated with musculoskeletal conditions for both men and women; however, associations with cardio-metabolic and pulmonary comorbidities were evident in women only.

The association between a fracture risk tool and frailty: Geelong Osteoporosis Study.

BACKGROUND: Frailty is characterised by age-related declines in physical, psychological and social functioning. Features of frailty overlap with risk factors for fragility fractures. The aim of this study was to investigate the association between the fracture risk assessment tool (FRAX®) and frailty. METHODS: In cross-sectional analysis, frailty status was determined for participants aged 60-90 yr at 15-year follow-up of the Geelong Osteoporosis Study, using a modified Fried frailty phenotype. Using the FRAX on-line tool, scores for hip and major osteoporotic fracture (MOF) were calculated with and without bone mineral density (BMD). Using the area under Receiver Operating Characteristic (AUROC) curves, and FRAX scores calculated at the baseline visit for these participants, we investigated the association of FRAX and frailty 15 years later. RESULTS: Forty-seven of 303 women (15.5%) and 41 of 282 men (14.5%) were frail at the 15-year visit. There was a gradient of increasing median FRAX scores from robust to frail. For example, for women, median MOF-FRAX without BMD increased from 5.9 for the robust to 7.5 for the pre-frail and 14.0 for the frail (p < 0.001). In secondary analyses, an association was observed between FRAX and frailty over 15 years, with the highest AUROC for women being 0.72 for MOF-FRAX with BMD, and for men, 0.76 hip-FRAX without BMD. CONCLUSION: An association was observed between FRAX and frailty where frail men and women had higher FRAX-scores compared to the other groups. Preliminary data suggest that FRAX, with or without BMD, may be useful in enhancing the information on frailty. Further research using larger datasets will be required to explore this.

Lower-limb muscle strength: normative data from an observational population-based study.

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.