Associations of body composition with incident dementia in older adults: Cardiovascular Health Study-Cognition Study

Comprehensive analysis of molecular, physiological, and functional biomarkers of aging with neurological diseases using Mendelian randomization

An increasing burden of neurological diseases (NDs) has been a public health challenge in an aging society. Age, especially biological age, is the most important risk factor for NDs. Identification of biomarkers of aging to capture NDs might lead to a better understanding of the underlying mechanisms of pathological brain aging and the implementation of effective intervention. We conducted a comprehensive two-sample Mendelian Randomization (MR) study to investigate the association between various biomarkers of aging and three leading causes of NDs: Alzheimer's disease (AD), vascular dementia (VaD), and ischemic stroke. Publicly available GWAS summary statistics on people from European ancestry were obtained for six molecular biomarkers, two physiological biomarkers, and eight functional biomarkers, and three NDs. Genetic variants serving as instrumental variables (IVs) were identified for each biomarker. The MR analysis included inverse variance weighted (IVW), weighted median, MR-Egger, and MR-PRESSO. We found that short telomere length and decrease in appendicular lean mass were associated with an increased risk for AD (OR IVW = 1.12 per 1SD decrease, 95% confidence interval 1.02-1.22, and OR IVW = 1.11, 1.06-1.16, respectively), whereas high frailty index showed a protective effect for AD. Accelerated BioAge appeared to be associated with increased risk for ischemic stroke (OR IVW = 1.3 per year in BioAge acceleration, 95% CI 1.19-1.41). Our findings implied a causal association of short telomere length and a decrease in appendicular lean mass with an increased risk for AD, while BioAge appeared to be a good biomarker for ischemic stroke. Further studies are needed to validate these associations and explore underlying mechanisms.

Association Between Body Composition Patterns, Cardiovascular Disease, and Risk of Neurodegenerative Disease in the UK Biobank

BACKGROUND AND OBJECTIVES

Accumulating evidence connects diverse components of body composition (e.g., fat, muscle, and bone) to neurodegenerative disease risk, yet their interplay remains underexplored. This study examines the associations between patterns of body composition and the risk of neurodegenerative diseases, exploring the mediating role of cardiovascular diseases (CVDs).

METHODS

This retrospective analysis used data from the UK Biobank, a prospective community-based cohort study. We included participants free of neurodegenerative diseases and with requisite body composition measurements at recruitment, who were followed from 5 years after recruitment until April 1, 2023, to identify incident neurodegenerative diseases. We assessed the associations between different components and major patterns of body composition (identified by principal component analysis) with the risk of neurodegenerative diseases, using multivariable Cox models. Analyses were stratified by disease susceptibility, indexed by polygenetic risk scores for Alzheimer and Parkinson diseases, APOE genotype, and family history of neurodegenerative diseases. Furthermore, we performed mediation analysis to estimate the contribution of CVDs to these associations. In addition, in a subcohort of 40,790 participants, we examined the relationship between body composition patterns and brain aging biomarkers (i.e., brain atrophy and cerebral small vessel disease).

RESULTS

Among 412,691 participants (mean age 56.0 years, 55.1% female), 8,224 new cases of neurodegenerative diseases were identified over an average follow-up of 9.1 years. Patterns identified as "fat-to-lean mass," "muscle strength," "bone density," and "leg-dominant fat distribution" were associated with a lower rate of neurodegenerative diseases (hazard ratio [HR] = 0.74-0.94) while "central obesity" and "arm-dominant fat distribution" patterns were associated with a higher rate (HR = 1.13-1.18). Stratification analysis yielded comparable risk estimates across different susceptibility groups. Notably, 10.7%-35.3% of the observed associations were mediated by CVDs, particularly cerebrovascular diseases. The subcohort analysis of brain aging biomarkers corroborated the findings for "central obesity," "muscle strength," and "arm-dominant fat distribution" patterns.

DISCUSSION

Our analyses demonstrated robust associations of body composition patterns featured by "central obesity," "muscle strength," and "arm-dominant fat distribution" with both neurodegenerative diseases and brain aging, which were partially mediated by CVDs. These findings underscore the potential of improving body composition and early CVD management in mitigating risk of neurodegenerative diseases.

DXA-Measured Abdominal Adipose Depots and Structural Brain Integrity in Postmenopausal Women

BACKGROUND

This study extends prior research from the MRI substudy of the Women's Health Initiative Memory Study (WHIMS-MRI) linking BMI to reduced brain atrophy and ischemic lesion load by examining DXA-based measurements of total body fat, total abdominal adipose tissue (TAT), abdominal visceral (VAT) and subcutaneous (SAT) adipose tissue, gynoid fat, and overall leg fat.

METHODS

The analytic sample consisted of 61 postmenopausal women (baseline mean age 69.5 [3.6]) enrolled in WHIMS-MRI who had undergone DXA scans. DXA scans were completed at years 0, 3, and 6, and MRI scans were conducted ~8 years after baseline. Adjusted linear regression models were used to analyze the association between adiposity averaged across the 3-time points and volumes of brain regions previously linked to dementia.

RESULTS

Higher levels of total body fat, TAT, VAT, SAT, gynoid, and overall leg fat were associated with larger hippocampal volume (β 0.02 [95% CI, 0.004-0.04]; 0.11 [0.02-0.21]; 0.26 [0.04-0.47]; 0.18 [0.03-0.33]; 0.18 [0.05-0.30]; 0.07 [0.009-0.12], respectively). No other significant associations were observed.

CONCLUSION

Higher levels of adiposity were positively associated with hippocampal volume. Additional research with larger sample sizes is needed to ascertain the significance of this association.

Mendelian randomization identifies causal effects of major depressive disorder on accelerated aging

BACKGROUND

Evidence links major depressive disorder (MDD) with aging, but it's unclear if MDD accelerates aging and what factors mediate this transition.

METHODS

Two-sample Mendelian randomization (MR) analyses were applied to estimate the causal association between MDD and frailty index (FI), telomere length (TL), and appendicular lean mass (ALM) from available genome-wide association studies in populations of European ancestry. Furthermore, we conducted mediation MR analyses to assess the mediating effects of 31 lifestyle factors or diseases on the causal relationship between MDD and aging.

RESULTS

MDD was significantly causally associated with increased FI (βIVW = 0.23, 95 % CI = 0.18 to 0.28, p = 1.20 × 10-17), shorter TL (βIVW = -0.04, 95 % CI = -0.07 to -0.01, p = 0.01), and decreased ALM (βIVW = -0.07, 95 % CI = -0.11 to -0.03, p = 3.54 × 10-4). The mediation analysis through two-step MR revealed smoking initiation (9.09 %), hypertension (6.67 %) and heart failure (5.36 %) mediated the causal effect of MDD on FI. Additionally, alcohol use disorders and alcohol dependence on the causal relationship between MDD and TL were found to be 17.52 % and 17.13 % respectively.

LIMITATIONS

Confounding, statistical power, and Euro-centric focus limit generalization.

CONCLUSION

Overall, individuals with MDD may be at a higher risk of experiencing premature aging, and this risk is partially influenced by the pathways involving smoking, alcohol use, and cardiovascular health. It underscores the importance of early intervention and comprehensive health management in individuals with MDD to promote healthy aging and overall well-being.

Body Composition, Sarcopenic Obesity, and Cognitive Function in Older Adults: Findings From the National Health and Nutrition Examination Survey (NHANES) 1999-2002 and 2011-2014

OBJECTIVE

Sarcopenic-obesity (SO) is characterized by the concomitant presence of low muscle mass and high adiposity. This study explores the association of body composition and SO phenotypes with cognitive function in older adults.

METHODS

Cross-sectional data in older adults (≥60 years) from NHANES 1999-2002 and 2011-2014 were used. In the 1999-2002 cohort, phenotypes were derived from body mass index (BMI) and dual-X-ray-absorptiometry, and cognition was assessed the by Digit-Symbol-Substitution-Test (DSST). In the 2011-2014 cohort, phenotypes were derived from BMI, waist-circumference (WC), and hand-grip-strength (HGS). Cognition was assessed using four tests: DSST, Animal Fluency, the Consortium-to-Establish-a-Registry-for-Alzheimer's-Disease-Delayed-Recall, and Word Learning. Mediation analysis was conducted to evaluate the contribution of inflammation (C-reactive-protein, CRP) and insulin resistance (Homeostatic-Model-Assessment-for-Insulin-Resistance, HOMA-IR) to the association between body composition and cognitive outcomes.

RESULTS

The SO phenotype had the lowest DSST mean scores (p < 0.05) and was associated with a significant risk of cognitive impairment [Odds Ratio (OR) = 1.9; 95%CI 1.0-3.7, p = 0.027] in the 1999-2002 cohort. A higher ratio of fat mass and fat free mass (FM/FFM) also showed a greater risk of cognitive impairment (OR = 2.0; 95%CI 1.3-3.1, p = 0.004). In the 2011-2014 cohort, the high WC-Low HGS group showed significantly lower scores on all four cognitive tests (p < 0.05) and a higher risk of cognitive impairment. CRP and HOMA-IR were significant partial mediators of the association between FM/FFM and DSST in the 1999-2002 cohort.

CONCLUSIONS

The SO phenotype was associated with a higher risk of cognitive impairment in older adults. Insulin resistance and inflammation may represent key mechanisms linking SO to the development of cognitive impairment.

Comparison of multiple linear regression and machine learning methods in predicting cognitive function in older Chinese type 2 diabetes patients

INTRODUCTION

The prevalence of type 2 diabetes (T2D) has increased dramatically in recent decades, and there are increasing indications that dementia is related to T2D. Previous attempts to analyze such relationships principally relied on traditional multiple linear regression (MLR). However, recently developed machine learning methods (Mach-L) outperform MLR in capturing non-linear relationships. The present study applied four different Mach-L methods to analyze the relationships between risk factors and cognitive function in older T2D patients, seeking to compare the accuracy between MLR and Mach-L in predicting cognitive function and to rank the importance of risks factors for impaired cognitive function in T2D.

METHODS

We recruited older T2D between 60-95 years old without other major comorbidities. Demographic factors and biochemistry data were used as independent variables and cognitive function assessment (CFA) was conducted using the Montreal Cognitive Assessment as an independent variable. In addition to traditional MLR, we applied random forest (RF), stochastic gradient boosting (SGB), Naïve Byer's classifier (NB) and eXtreme gradient boosting (XGBoost).

RESULTS

Totally, the test cohort consisted of 197 T2D (98 men and 99 women). Results showed that all ML methods outperformed MLR, with symmetric mean absolute percentage errors for MLR, RF, SGB, NB and XGBoost respectively of 0.61, 0.599, 0.606, 0.599 and 0.2139. Education level, age, frailty score, fasting plasma glucose and body mass index were identified as key factors in descending order of importance.

CONCLUSION

In conclusion, our study demonstrated that RF, SGB, NB and XGBoost are more accurate than MLR for predicting CFA score, and identify education level, age, frailty score, fasting plasma glucose, body fat and body mass index as important risk factors in an older Chinese T2D cohort.

Body composition and plasma total-tau, neurofilament light chain, and amyloid-β: A population-based study

A higher body mass at older age has been linked to a lower risk of dementia. This unexpected trend may be explained by age-related lean mass depletion, or methodological issues such as the long preclinical phase of dementia or competing risks. Focusing on preclinical markers of dementia may overcome these issues. Between 2002 and 2005, body composition and plasma total-tau, neurofilament light chain (NfL), amyloid-β40, and amyloid-β42 were measured in 3408 dementia-free participants from the population-based Rotterdam Study. The cross-sectional associations between body composition and plasma markers were determined using linear regression models. Whole body and fat mass, but not lean mass, were positively associated with total-tau, while all these measures were inversely associated with NfL. Apart from an inverse association between lean mass and amyloid-β40, body composition measures were not associated with plasma amyloid-β. Our findings suggest distinct effects of body composition on neurodegeneration.

Differential Associations of 6 Adiposity Indices With Dementia in Older Adults: The MIND-China Study

OBJECTIVES

The cross-sectional association between late-life obesity and dementia is often explained by the obesity paradox. We assessed the potential differential associations of various adiposity indices with dementia and subtypes of dementia in rural Chinese older adults.

DESIGN

A population-based cross-sectional study.

SETTING AND PARTICIPANTS

A total of 5277 participants (age ≥60 years; 57.23% female) who were living in rural communities and were examined in March-September 2018 for MIND-China.

METHODS

We used weight, height, and waist circumference (WC) to calculate 6 adiposity indices: body mass index (BMI), waist-to-height ratio (WHtR), weight-adjusted-waist index (WWI), A Body Shape Index (ABSI), body roundness index (BRI), and Conicity Index (ConI). Dementia, Alzheimer's disease (AD), and vascular dementia (VaD) were clinically diagnosed following the international criteria. Data were analyzed with logistic regression models.

RESULTS

Of the 5277 participants, 303 were diagnosed with dementia, including 193 with AD and 99 with VaD. The multivariable-adjusted odds ratio (95% CI) of dementia associated with the highest (vs lowest) quintile of adiposity index was 2.32 (1.40-3.85) for WWI, 1.56 (1.03-2.36) for ABSI, and 1.40 (0.92-2.11) for ConI. Similarly, higher levels of these 3 adiposity indices were significantly associated with an increased likelihood of AD, whereas a higher BMI was associated with a decreased likelihood of AD. None of the 6 examined adiposity indices was significantly associated with VaD when adjusting for multiple confounders.

CONCLUSIONS AND IMPLICATIONS

The adiposity index WWI is linearly associated with the likelihood of dementia and AD. An increased WWI may be a clinical marker for the dementia syndrome and Alzheimer's dementia.

Association of Motoric Cognitive Risk Syndrome with Sarcopenia and Systemic Inflammation in Pre-Frail Older Adults

Motoric cognitive risk syndrome (MCR) is defined by the presence of slow gait and subjective cognitive decline. It is well recognized as a prodrome for dementia, but the biological mechanism and trajectory for MCR are still lacking. The objective of this study was to explore the association of MCR with body composition, including sarcopenia and systemic inflammation, in pre-frail older adults in a cross-sectional study of 397 pre-frail community-dwelling older adults. Data on demographics, physical function, frailty, cognition (Montreal Cognitive Assessment (MoCA)), perceived health and depression were collected. Body composition was measured using a bioelectrical impedance analyzer. Systemic inflammatory biomarkers, such as progranulin, growth differentiation factor-15 (GDF-15), interleukin-10 (IL-10), interleukin-6 and tumor necrosis factor-α (TNF-α), were collected. Univariate and multivariate logistic regression were used to analyze the association between MCR, body composition, sarcopenia and systemic inflammatory biomarkers. The prevalence of MCR was 14.9%. They were significantly older and there were more females, depression, functional impairment, lower education, physical activity and MoCA scores. Body fat percentage (BF%), fat mass index, fat to fat free mass ratio (FM/FFM) and sarcopenia prevalence were significantly higher in MCR. Serum GDF-15 and TNF-α levels were highest with progranulin/TNF-α and IL-10/TNF-α ratio lowest in MCR. Compared to healthy patients, MCR was significantly associated with sarcopenia (aOR 2.62; 95% CI 1.46-3.17), BF% (aOR 1.06; 95% CI 1.01-1.12), FMI (aOR 1.16; 95% CI 1.02-1.30) and FM/FFM (aOR 6.38; 95% CI 1.20-33.98). The association of IL-10 to TNF-α ratio (aOR 0.98, 95% CI 0.97-0.99) and IL-10 (aOR 2.22, 95% CI 0.05-0.98) with MCR were independent of sarcopenia and BF%. Longitudinal population studies are needed to understand the role of body fat indices and IL-10 in pre-frail older adults with MCR and trajectory to dementia.

Adiposity in the older population and the risk of dementia: The Rotterdam Study

INTRODUCTION

We determined associations of total and regional adiposity with incident dementia among older adults.

METHODS

Within the population-based Rotterdam Study, adiposity was measured as total, android, and gynoid fat mass using dual-energy X-ray absorptiometry in 3408 men and 4563 women, every 3 to 6 years between 2002 and 2016. Incident dementia was recorded until 2020.

RESULTS

Higher adiposity measures were associated with a decreased risk of dementia in both sexes. After excluding the first 5 years of follow-up, only the association of gynoid fat among women remained significant (hazard ratio 0.85 [95% confidence interval 0.75-0.97] per standard deviation increase). No major differences in trajectories of adiposity measures were observed between dementia cases and dementia-free controls.

DISCUSSION

Higher total and regional fat mass related to a decreased risk of dementia. These results may be explained by reverse causality, although a protective effect of adiposity cannot be excluded.

HIGHLIGHTS

Total and regional adiposity were assessed using dual-energy X-ray absorptiometry scans in 7971 older adults. All adiposity measures were associated with a decreased risk of dementia. The results suggest a beneficial effect of gynoid fat on the risk of dementia in women. Reverse causation and competing risk may explain these inverse associations.

Total and regional fat-to-muscle mass ratio and risks of incident all-cause dementia, Alzheimer's disease, and vascular dementia

BACKGROUND

The fat-to-muscle mass ratio (FMR), which integrates the antagonistic effects of fat and muscle mass, has been proposed as a useful indicator to assess disease risk independent of overall obesity. However, little is known about the association between FMR and dementia risk. We aimed to prospectively investigate the sex-specific associations between total and regional FMR and incident dementia.

METHODS

A total of 491 420 participants (223 581 men and 267 839 women; mean age 56.7 ± 8.2 and 56.3 ± 8.0 years old, respectively) free of dementia at baseline from the UK Biobank were included. Fat mass and muscle mass were measured using a bioelectrical impedance assessment device. Cox regression analyses were used to examine the associations of total and regional FMR with incident all-cause dementia, Alzheimer's disease (AD) and vascular dementia (VD). The shape of the associations of the continuous scale of FMR and incident dementia were examined using restricted cubic spline analysis.

RESULTS

During a median 8.65 years of follow-up, we documented 2 225 incident all-cause dementia cases, including 836 AD and 468 VD cases. There was an L-shaped association between whole body FMR and all-cause dementia risk in both sexes after adjusting body mass index (BMI) and other covariates (P for non-linear <0.001 in men and women), where all-cause dementia risk decreased steeply with increasing FMR and levelled off at around the medians (0.35 in men, 0.61 in women) with a hazard ratio (HR) of 0.78 (95% CI: 0.64, 0.96; P = 0.019) and 0.60 (0.47, 0.77; <0.001) per 1 standard deviation (SD) increase in men and women, respectively. Compared with other body parts, FMR of the leg showed the strongest inverse associations [HR (95% CI; P) per 1 SD below the medians: 0.60 (0.48, 0.75; <0.001); 0.61 (0.47, 0.79; <0.001) in men and women, respectively]. Specifically, the inverse associations of whole body FMR on all-cause dementia risk were significant only among participants over the age of 60 (P for trend <0.001). Multivariable adjusted Cox models showed inverse associations of whole body FMR with AD in men only (P for trend = 0.003), whereas no statistically significant decrease was detected in VD among men and women.

CONCLUSIONS

Our analyses provide strong evidence for L-shaped associations of total and regional FMR with the development of dementia among participants aged 60 years or older independent of overall obesity.

A training program for researchers in population neuroimaging: Early experiences

Recent advances in neuroimaging create groundbreaking opportunities to better understand human neurological and psychiatric diseases, but also bring new challenges. With the advent of more and more sophisticated and efficient multimodal image processing software, we can now study much larger populations and integrate information from multiple modalities. In consequence, investigators that use neuroimaging techniques must also understand and apply principles of population sampling and contemporary data analytic techniques. The next generation of neuroimaging researchers must be skilled in numerous previously distinct disciplines and so a new integrated model of training is needed. This tutorial presents the rationale for such a new training model and presents the results from the first years of the training program focused on population neuroimaging of Alzheimer's Disease. This approach is applicable to other areas of population neuroimaging.

A Phenome-wide Association and Mendelian Randomization Study for Alzheimer's Disease: A Prospective Cohort Study of 502,493 Participants From the UK Biobank

BACKGROUND

Considerable uncertainty remains regarding associations of multiple risk factors with Alzheimer's disease (AD). We aimed to systematically screen and validate a wide range of potential risk factors for AD.

METHODS

Among 502,493 participants from the UK Biobank, baseline data were extracted for 4171 factors spanning 10 different categories. Phenome-wide association analyses and time-to-event analyses were conducted to identify factors associated with both polygenic risk scores for AD and AD diagnosis at follow-up. We performed two-sample Mendelian randomization analysis to further assess their potential causal relationships with AD and imaging association analysis to discover underlying mechanisms.

RESULTS

We identified 39 factors significantly associated with both AD polygenic risk scores and risk of incident AD, where higher levels of education, body size, basal metabolic rate, fat-free mass, computer use, and cognitive functions were associated with a decreased risk of developing AD, and selective food intake and more outdoor exposures were associated with an increased risk of developing AD. The identified factors were also associated with AD-related brain structures, including the hippocampus, entorhinal cortex, and inferior/middle temporal cortex, and 21 of these factors were further supported by Mendelian randomization evidence.

CONCLUSIONS

To our knowledge, this is the first study to comprehensively and rigorously assess the effects of wide-ranging risk factors on AD. Strong evidence was found for fat-free body mass, basal metabolic rate, computer use, selective food intake, and outdoor exposures as new risk factors for AD. Integration of genetic, clinical, and neuroimaging information may help prioritize risk factors and prevention targets for AD.

Association of life course adiposity with risk of incident dementia: a prospective cohort study of 322,336 participants

Cohort studies report inconsistent associations between body mass index (BMI) and all-cause incident dementia. Furthermore, evidence on fat distribution and body composition measures are scarce and few studies estimated the association between early life adiposity and dementia risk. Here, we included 322,336 participants from UK biobank to investigate the longitudinal association between life course adiposity and risk of all-cause incident dementia and to explore the underlying mechanisms driven by metabolites, inflammatory cells and brain structures. Among the 322,336 individuals (mean (SD) age, 62.24 (5.41) years; 53.9% women) in the study, during a median 8.74 years of follow-up, 5083 all-cause incident dementia events occurred. The risk of dementia was 22% higher with plumper childhood body size (p < 0.001). A strong U-shaped association was observed between adult BMI and dementia. More fat and less fat-free mass distribution on arms were associated with a higher risk of dementia. Interestingly, similar U-shaped associations were found between BMI and four metabolites (i.e., 3-hydroxybutrate, acetone, citrate and polyunsaturated fatty acids), four inflammatory cells (i.e., neutrophil, lymphocyte, monocyte and leukocyte) and abnormalities in brain structure that were also related to dementia. The findings that adiposity is associated with metabolites, inflammatory cells and abnormalities in brain structure that were related to dementia risk might provide clues to underlying biological mechanisms. Interventions to prevent dementia should begin early in life and include not only BMI control but fat distribution and body composition.

Handgrip strength asymmetry is associated with the risk of neurodegenerative disorders among Chinese older adults

BACKGROUND

Neurodegenerative disorders, as the irreversible condition, have a long, silent preclinical period. Recognition of early physical signs of neurodegenerative disorders had important practical implications for identifying at-risk population. The aim of this study was to investigate whether handgrip strength (HGS) asymmetry was associated with the incidence of neurodegenerative disorders among Chinese older adults.

METHODS

This study used the data of participants aged 60 years and over from three waves (2011-2015) of China Health and Retirement Longitudinal Study. HGS asymmetry was measured with HGS ratio (maximal non-dominant HGS/maximal dominant HGS), with the value less than 0.9 or more than 1.1 considered as HGS asymmetry. Physician-diagnosed neurodegenerative disorders were identified by self-reported or proxy-reported information. Competing risk analysis was conducted to examine the association between HGS asymmetry and incident neurodegenerative disorders, with mortality treated as the competing event.

RESULTS

A total of 4925 participants were included in the analysis [mean (SD) age: 68.1(6.68); female: 49.7%]. Eight hundred and eighty-eight (18.0%) participants had low HGS and 2227 (45.2%) had HGS asymmetry. During the 4 years of follow-up, there were 156 cases of neurodegenerative disorders and 422 cases of mortality. The incidence of neurodegenerative disorders was 8.7 per 1000 person-years [95% confidence interval (CI): 7.4-10.2], and the incidence of mortality was 23.5 per 1000 person-years (95% CI: 21.4-25.9). Both the cause-specific model and the Fine-Gray subdistribution hazard model showed that participants with HGS asymmetry had increased hazard of neurodegenerative disorders [hazard ratio (HR) = 1.66, P = 0.002, 95% CI: 1.202-2.297; subdistribution hazard ratio (SHR) = 1.65, P = 0.002, 95% CI: 1.202-2.285]. Low HGS, but not HGS asymmetry, was related to the higher hazard of mortality (HR = 1.61, P < 0.001, 95% CI: 1.297-1.995; SHR = 1.58, P < 0.001, 95% CI: 1.286-1.951).

CONCLUSIONS

Handgrip strength asymmetry was associated with the future risk of neurodegenerative disorders among Chinese older adults. Public healthcare providers could consider examining HGS asymmetry along with the maximal HGS as a way to identify those at elevated risk of neurodegenerative disorders.

Association of body composition with functional capacity and cognitive function in older adults living in nursing homes

BACKGROUND

Older adults living in nursing homes have an increased risk of adverse outcomes. However, the role of body composition in vital health and quality of life parameters such as functional capacity and cognitive function is less studied in this group of older adults compared to community-dwelling counterparts.

OBJECTIVE

The aim of the present study was to examine the association of body composition with functional capacity and cognitive function in nursing home residents.

METHODS

Fifty-three older adults (82.8±7.3 years) were enrolled in this study and they underwent body composition evaluation, functional capacity and cognitive function measurements.

RESULTS

The results showed a high prevalence of obesity accompanied by functional capacity limitations and cognitive impairment in older adults living in nursing homes. Partial correlations, controlling for age, showed that body fat percentage was positively correlated with sit-to-stand-5 (r=0.310, p=0.025) and timed-up-and-go (r=0.331, p=0.017), and negatively correlated with handgrip strength test results (r=-0.431, p<0.001), whereas greater lean body mass was associated with better sit-to-stand-5 (r=-0.410, p=0.003), handgrip strength (r=0.624, p<0.001) and cognitive function performance (r=0.302, p=0.037).

CONCLUSIONS

These important associations reinforce the need to develop effective healthy lifestyle interventions targeting both lean mass and body fat to combat functional and cognitive decline in nursing home residents.

Body composition in patients with rheumatoid arthritis: a narrative literature review

There is growing interest in the alterations in body composition (BC) that accompany rheumatoid arthritis (RA). The purpose of this review is to (i) investigate how BC is currently measured in RA patients, (ii) describe alterations in body composition in RA patients and (iii) evaluate the effect on nutrition, physical training, and treatments; that is, corticosteroids and biologic Disease Modifying Anti-Rheumatic Disease (bDMARDs), on BC in RA patients. The primary-source literature for this review was acquired using PubMed, Scopus and Cochrane database searches for articles published up to March 2021. The Medical Subject Headings (MeSH) terms used were 'Arthritis, Rheumatoid', 'body composition', 'sarcopenia', 'obesity', 'cachexia', 'Absorptiometry, Photon' and 'Electric Impedance'. The titles and abstracts of all articles were reviewed for relevant subjects. Whole-BC measurements were usually performed using dual energy x-ray absorptiometry (DXA) to quantify lean- and fat-mass parameters. In RA patients, lean mass is lower and adiposity is higher than in healthy controls, both in men and women. The prevalence of abnormal BC conditions such as overfat, sarcopenia and sarcopenic obesity is significantly higher in RA patients than in healthy controls; these alterations in BC are observed even at an early stage of the disease. Data on the effect treatments on BC in RA patients are scarce. In the few studies published, (a) creatine supplementation and progressive resistance training induce a slight and temporary increase in lean mass, (b) exposure to corticosteroids induces a gain in fat mass and (c) tumour necrosis factor alpha (TNFα) inhibitors might be associated with a gain in fat mass, while tocilizumab might be associated with a gain in lean mass. The available data clearly demonstrate that alterations in BC occur in RA patients, but data on the effect of treatments, especially bDMARDs, are inconsistent and further studies are needed in this area.