The Association Between Metabolic Syndrome and Frailty in Healthy Community-Dwelling Older Adults

Abstract This study examined the association between metabolic syndrome (MetS) and frailty status in relatively healthy community-dwelling older adults. Participants included 19,114 individuals from the “ASPirin in Reducing Events in the Elderly” (ASPREE) trial. The diagnostic criteria for MetS were according to the International Diabetes Federation Task Force on Epidemiology and Prevention and the American Heart Association/National Heart, Lung, and Blood Institute (2009); and comprised any three of five parameters: waist circumference, triglycerides, fasting blood glucose, high-density lipoprotein cholesterol or hypertension. Frailty and prefrailty were defined using a modified Fried phenotype (FP) comprising exhaustion, body mass index, grip strength, gait speed and physical activity and a deficit accumulation frailty index (FI) of 66 items. The association between MetS and frailty was examined using multinomial logistic regression. At baseline, 51.1% of participants met the criteria of MetS; of those, 41.8% and 2.5 % were prefrail and frail, respectively, according to Fried phenotype, while 49.6% and 11.8 % were prefrail and frail, respectively, according to FI. MetS at baseline was associated with an increased likelihood of prefrailty (RRR: 1.25; 95% CI: 1.17, 1.33) and frailty (RRR: 1.60; 95% CI: 1.28, 2.01) compared to no frailty after adjustment for potential confounders according to Fried phenotype, while the association was stronger for prefrailty (RRR: 2.74; 95% CI: 2.55, 2.94) and frailty (RRR: 5.30; 95% CI: 4.60, 6.11) according to FI. Overall, at baseline, more than half of the participants had MetS, and the presence of MetS was significantly associated with pre-frailty and frailty.

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Identifying Frail-Related Biomarkers among Community-Dwelling Older Adults in Japan: A Research Example from the Japanese Gerontological Evaluation Study

BioMed Research International ◽

10.1155/2018/5362948 ◽

2018 ◽

Vol 2018 ◽

pp. 1-8 ◽

Cited By ~ 5

Author(s):

N. Cable ◽

A. Hiyoshi ◽

N. Kondo ◽

J. Aida ◽

H. Sjöqvist ◽

...

Keyword(s):

Older Adults ◽

Logistic Regression ◽

Multinomial Logistic Regression ◽

Frailty Index ◽

Evaluation Study ◽

Community Dwelling ◽

Physical Aspect ◽

Clinical Biomarkers ◽

Community Dwelling Older Adults ◽

Normal Albumin

We examined correlating clinical biomarkers for the physical aspect of frailty among community-dwelling older adults in Japan, using Japanese Gerontological Evaluation Study (JAGES). We used information from the JAGES participants (N = 3,128) who also participated in the community health screening in 2010. We grouped participants’ response to the Study of Osteoporotic Fracture (SOF) Frailty Index into robust (=0), intermediate frail (=1), and frail (=2+) ones to indicate physical aspect of frailty. Independent of sex and age, results from multinomial logistic regression showed above normal albumin and below normal HDL and haemoglobin levels were positively associated with intermediate frail (RRR = 1.99, 95% CI = 1.22–3.23; RRR = 1.36, 95% CI = 1.33–1.39; RRR = 1.36, 95% CI = 1.23–1.51, resp.) and frail cases (RRR = 2.27, 95% CI = 1.91–2.70; RRR = 1.59, 95% CI = 1.51–1.68; RRR = 1.40, 95% CI = 1.28–1.52, resp.). Limited to women, above normal Hb1Ac level was similarly associated with intermediate frail and frail cases (RRR = 1.18, 95% CI = 1.02, 1.38; RRR = 2.56, 95% CI = 2.23–2.95, resp.). Use of relevant clinical biomarkers can help in assessment of older adults’ physical aspect of frailty.

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Bedside Ultrasound Measures of Muscle Mass and Frailty Measures in Community-Dwelling Older Adults

Innovation in Aging ◽

10.1093/geroni/igaa057.861 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 269-269

Author(s):

Kenneth Madden ◽

Boris Feldman ◽

Shane Arishenkoff ◽

Graydon Meneilly

Keyword(s):

Older Adults ◽

Muscle Mass ◽

Frailty Index ◽

Geriatric Medicine ◽

Muscle Thickness ◽

Vancouver General Hospital ◽

Community Dwelling ◽

Point Of Care Ultrasound ◽

Clinical Frailty Scale ◽

Community Dwelling Older Adults

Abstract The age-associated loss of muscle mass and strength in older adults is called sarcopenia, and it is associated with increased rates of falls, fractures, hospitalizations and death. Sarcopenia is one of the most common physical etiologies for increased frailty in older adults, and some recent work has suggested the use of Point-of care ultrasound (PoCUS) measures as a potential measure of muscle mass. The objective of this study was to examine the association of PoCUS measures of muscle thickness (MT) with measures of frailty in community-dwelling older adults. We recruited 150 older adults (age >= 65; mean age 80.0±0.5 years, 66 women, 84 men) sequentially from 5 geriatric medicine clinics (Vancouver General Hospital). We measured lean muscle mass (LMM, by bioimpedance assay) and an ultrasonic measure of muscle quantity (MT, vastus medialis muscle thickness) in all subjects, as well as two outcome measures of frailty (FFI, Fried Frailty Index; RCFS, Rockwood Clinical Frailty Scale). In our models, MT showed an inverse correlation with the FFI (Standardized β=-0.2320±0.107, p=0.032) but no significant correlation with the RCFS (Standardized β = -0.025±0.086, p=0.776). LMM showed no significant association with either FFI (Standardized β=-0.232±0.120, p=0.055) or RCFS (Standardized β = -0.043±0.119, p=0.719). Our findings indicate that PoCUS measures show potential as a way to screen for physical manifestations of frailty and might be superior to other bedside methods such as bioimpedance assay. However, PoCUS measures of muscle thickness will likely miss patients showing frailty in the much broader context captured by the RCFS.

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Corrigendum to “Oral Frailty Index-8 in the risk assessment of new-onset oral frailty and functional disability among community-dwelling older adults” Archives of Gerontology and Geriatrics, Volume 94 (2021) 104340

Archives of Gerontology and Geriatrics ◽

10.1016/j.archger.2021.104466 ◽

2021 ◽

Vol 96 ◽

pp. 104466

Author(s):

Tomoki Tanaka ◽

Hirohiko Hirano ◽

Yuki Ohara ◽

Misa Nishimoto ◽

Katsuya Iijima

Keyword(s):

Older Adults ◽

Risk Assessment ◽

Functional Disability ◽

Frailty Index ◽

Community Dwelling ◽

Community Dwelling Older Adults ◽

Oral Frailty ◽

New Onset

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Oral Frailty Index-8 in the risk assessment of new-onset oral frailty and functional disability among community-dwelling older adults

Archives of Gerontology and Geriatrics ◽

10.1016/j.archger.2021.104340 ◽

2021 ◽

Vol 94 ◽

pp. 104340

Author(s):

Tomoki Tanaka ◽

Hirohiko Hirano ◽

Yuki Ohara ◽

Misa Nishimoto ◽

Katsuya Iijima

Keyword(s):

Older Adults ◽

Risk Assessment ◽

Functional Disability ◽

Frailty Index ◽

Community Dwelling ◽

Community Dwelling Older Adults ◽

Oral Frailty ◽

New Onset

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Diagnostic Power of Circulatory Metabolic Biomarkers as Metabolic Syndrome Risk Predictors in Community-Dwelling Older Adults in Northwest of England (A Feasibility Study)

Nutrients ◽

10.3390/nu13072275 ◽

2021 ◽

Vol 13 (7) ◽

pp. 2275

Author(s):

Razieh Hassannejad ◽

Hamsa Sharrouf ◽

Fahimeh Haghighatdoost ◽

Ben Kirk ◽

Farzad Amirabdollahian

Keyword(s):

Risk Factors ◽

Older Adults ◽

Metabolic Syndrome ◽

Roc Analysis ◽

Cross Validation ◽

Community Dwelling ◽

Tnf Α ◽

Diagnostic Power ◽

Metabolic Biomarkers ◽

Community Dwelling Older Adults

Background: Metabolic Syndrome (MetS) is a cluster of risk factors for diabetes and cardiovascular diseases with pathophysiology strongly linked to aging. A range of circulatory metabolic biomarkers such as inflammatory adipokines have been associated with MetS; however, the diagnostic power of these markers as MetS risk correlates in elderly has yet to be elucidated. This cross-sectional study investigated the diagnostic power of circulatory metabolic biomarkers as MetS risk correlates in older adults. Methods: Hundred community dwelling older adults (mean age: 68.7 years) were recruited in a study, where their blood pressure, body composition and Pulse Wave Velocity (PWV) were measured; and their fasting capillary and venous blood were collected. The components of the MetS; and the serum concentrations of Interleukin-6 (IL-6), Tumor Necrosis Factor-α (TNF-α), Plasminogen Activator Inhibitor-I (PAI-I), Leptin, Adiponectin, Resistin, Cystatin-C, C-Reactive Protein (CRP), insulin and ferritin were measured within the laboratory, and the HOMA1-IR and Atherogenic Index of Plasma (AIP) were calculated. Results: Apart from other markers which were related with some cardiometabolic (CM) risk, after Bonferroni correction insulin had significant association with all components of Mets and AIP. These associations also remained significant in multivariate regression. The multivariate odds ratio (OR with 95% confidence interval (CI)) showed a statistically significant association between IL-6 (OR: 1.32 (1.06–1.64)), TNF-α (OR: 1.37 (1.02–1.84)), Resistin (OR: 1.27 (1.04–1.54)) and CRP (OR: 1.29 (1.09–1.54)) with MetS risk; however, these associations were not found when the model was adjusted for age, dietary intake and adiposity. In unadjusted models, insulin was consistently statistically associated with at least two CM risk factors (OR: 1.33 (1.16–1.53)) and MetS risk (OR: 1.24 (1.12–1.37)) and in adjusted models it was found to be associated with at least two CM risk factors and MetS risk (OR: 1.87 (1.24–2.83) and OR: 1.25 (1.09–1.43)) respectively. Area under curve (AUC) for receiver operating characteristics (ROC) demonstrated a good discriminatory diagnostics power of insulin with AUC: 0.775 (0.683–0.866) and 0.785 by cross validation and bootstrapping samples for at least two CM risk factors and AUC: 0.773 (0.653–0.893) and 0.783 by cross validation and bootstrapping samples for MetS risk. This was superior to all other AUC reported from the ROC analysis of other biomarkers. Area under precision-recall curve for insulin was also superior to all other markers (0.839 and 0.586 for at least two CM risk factors and MetS, respectively). Conclusion: Fasting serum insulin concentration was statistically linked with MetS and its risk, and this link is stronger than all other biomarkers. Our ROC analysis confirmed the discriminatory diagnostic power of insulin as CM and MetS risk correlate in older adults.

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Patterns and predictive factors of loss of the independence trajectory among community-dwelling older adults

BMC Geriatrics ◽

10.1186/s12877-021-02063-7 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Charlotte Bimou ◽

Michel Harel ◽

Cécile Laubarie-Mouret ◽

Noëlle Cardinaud ◽

Marion Charenton-Blavignac ◽

...

Keyword(s):

Older Adults ◽

Predictive Factors ◽

Multinomial Logistic Regression ◽

Cognitive Disorder ◽

Community Dwelling ◽

Functional Autonomy ◽

Process Loss ◽

Associated Risk Factors ◽

Study Participants ◽

Community Dwelling Older Adults

Abstract Background Independence is related to the aging process. Loss of independence is defined as the inability to make decisions and participate in activities of daily living (ADLs). Independence is related to physical, psychological, biological, and socioeconomic factors. An enhanced understanding of older people’s independence trajectories and associated risk factors would enable the develop early intervention strategies. Methods Independence trajectory analysis was performed on patients identified in the Unité de Prévention de Suivi et d’Analyse du Vieillissement (UPSAV) database. UPSAV cohort is a prospective observational study. Participants were 221 community-dwelling persons aged ≥75 years followed for 24 months between July 2011–November 2013 and benefits from a prevention strategy. Data were collected prospectively using a questionnaire. Independence was assessed using the “Functional Autonomy Measurement System (Système de Mesure de l’Autonomie Fonctionnelle (SMAF))”. Group-based trajectory modeling (GBTM) was performed to identify independence trajectories, and the results were compared with those of k-means and hierarchical ascending classifications. A multinomial logistic regression was performed to identify predictive factors of the independence trajectory. Results Three distinct trajectories of independence were identified including a “Stable functional autonomy (SFA) trajectory” (53% of patients), a “Stable then decline functional autonomy decline (SDFA) trajectory” (33% of patients) and a “Constantly functional autonomy decline (CFAD) trajectory” (14% of patients). Not being a member of an association, and previous fall were significantly associated of a SDFA trajectory (P < 0.01). Absence of financial and human assistance, no hobbies, and cognitive disorder were significantly associated with a CFAD trajectory (P < 0.01). Previous occupation and multiple pathologies were predictive factors of both declining trajectories SDFA and CFAD. Conclusions Community-living older persons exhibit distinct independence trajectories and the predictive factors. The evidence from this study suggests that the prevention and screening for the loss of independence of the older adults should be anticipated to maintaining autonomy.

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