Cognitive Frailty and Incidence of Dementia in Older Persons

Prevalence and Outcomes of Cognitive Frailty Among Community-Dwelling Older Adults: A Systematic Review and Meta-Analysis

PURPOSE

To systematically review the available evidence regarding the prevalence and outcomes of cognitive frailty-a clinical syndrome characterized by the combination of physical frailty and cognitive impairment, without dementia-in community-dwelling older adults.

METHOD

The following databases were searched: PubMed, Web of Science, Embase, EBSCO, Cochrane Central Register of Controlled Trials, ProQuest, CNKI, Wanfang, VIP, and CBMdisc (inception to October 2, 2023).

RESULTS

Twenty-four studies were included (N = 62,169) reporting a median prevalence of cognitive frailty among community-dwelling older adults of 12.2%. Frailty with cognitive impairment was independently associated with increased all-cause mortality (adjusted 8-year hazard ratio [HR] = 2.6, 95% confidence interval [CI] [2.05, 3.30]). There was evidence of increased risk of 3-year mortality for frailty (adjusted HR = 1.92, 95% CI [1.26, 2.93]) and prefrailty (adjusted HR = 1.79, 95% CI [1.33, 2.41]) with cognitive impairment. There was also evidence of increased risk of dementia for frailty (adjusted 24-month HR = 6.19, 95% CI [2.74, 13.99]; adjusted 4-year HR = 4.98, 95% CI [2.17, 11.41]) and prefrailty (adjusted 4-year HR = 5.21, 95% CI [2.95, 9.20]; adjusted 5-year HR = 14.5, 95% CI [1.68, 125.1]) with cognitive impairment. Activities of daily living (ADL) dependence was more frequent in individuals with cognitive impairment and frailty (adjusted 4-year odds ratio = 5.6, 95% CI [2.13, 14.72]).

CONCLUSION

Of community-dwelling older adults, 12.2% have cognitive frailty as well as increased risk of all-cause mortality, dementia, and ADL dependence. Further studies on prevention and treatment of cognitive frailty is warranted. Health care providers should formulate specific interventions to decrease the impact of cognitive frailty. [Research in Gerontological Nursing, 17(4), 202-212.].

Risk factors and a nomogram for predicting cognitive frailty in Chinese patients with lung cancer receiving drug therapy: A single-center cross-sectional study

BACKGROUND

To identify independent factors of cognitive frailty (CF) and construct a nomogram to predict cognitive frailty risk in patients with lung cancer receiving drug therapy.

METHODS

In this cross-sectional study, patients with lung cancer undergoing drug therapy from October 2022 to July 2023 were enrolled. The data collected includes general demographic characteristics, clinical data characteristics and assessment of tools for cognitive frailty and other factors. Logistic regression was harnessed to determine the influencing factors, R software was used to establish a nomogram model to predict the risk of cognitive frailty. The enhanced bootstrap method was employed for internal verification of the model. The performance of the nomogram was evaluated by using calibration curves, the area under the receiver operating characteristic curve, and decision curve analysis.

RESULTS

A total of 372 patients were recruited, with a cognitive frailty prevalence of 56.2%. Age, education background, diabetes mellitus, insomnia, sarcopenia, and nutrition status were identified as independent factors. Then, a nomogram model was constructed and patients were classified into high- and low-risk groups with a cutoff value of 0.552. The internal validation results revealed good concordance, calibration and discrimination. The decision curve analysis presented prominent clinical utility.

CONCLUSIONS

The prevalence of cognitive frailty was higher in lung cancer patients receiving drug therapy. The nomogram could identify the risk of cognitive frailty intuitively and simply in patients with lung cancer, so as to provide references for early screening and intervention for cognitive frailty at the early phases of drug treatment.

Role of Cognitive Frailty in Older Adults With Cardiovascular Disease

As the older adult population expands, an increasing number of patients affected by geriatric syndromes are seen by cardiovascular clinicians. One such syndrome that has been associated with poor outcomes is cognitive frailty: the simultaneous presence of cognitive impairment, without evidence of dementia, and physical frailty, which results in decreased cognitive reserve. Driven by common pathophysiologic underpinnings (eg, inflammation and neurohormonal dysregulation), cardiovascular disease, cognitive impairment, and frailty also share the following risk factors: hypertension, diabetes, obesity, sedentary behavior, and tobacco use. Cardiovascular disease has been associated with the onset and progression of cognitive frailty, which may be reversible in early stages, making it essential for clinicians to diagnose the condition in a timely manner and prescribe appropriate interventions. Additional research is required to elucidate the mechanisms underlying the development of cognitive frailty, establish preventive and therapeutic strategies to address the needs of older patients with cardiovascular disease at risk for cognitive frailty, and ultimately facilitate targeted intervention studies.

Prevalence and related factors of cognitive frailty in diabetic patients in China: a systematic review and meta-analysis

Objective

Cognitive frailty (CF) is characterized by physical frailty and potentially reversible cognitive impairment without Alzheimer's disease and other dementias. Clarifying the prevalence and related factors of cognitive frailty can help researchers understand its epidemiological status and formulate intervention measures. This study aims to conduct a systematic review and meta-analysis of the prevalence and related factors of CF in diabetic patients in Chinas to better understand the current status of CF in diabetic patients in China and develop effective intervention measures for related factors.

Methods

PubMed, Web of Science, Embase, Cochrane Library, CNKI, Weipu(VIP), WANFANG, China Biology Medicine (CBM) and DUXIU were searched to collect epidemiological data on Chinese diabetic patients. Articles published through May 29, 2023, were searched. The number of diabetes with CF and the total number of diabetes in the included studies were extracted to estimate the prevalence of diabetes with CF. For factors related to diabetes with CF, odds ratios (OR) and 95% confidence intervals (CI) were used for estimation.

Results

A total of 248 records were screened, of which 18 met the inclusion criteria. The results of meta-analysis showed that the prevalence of Chinese diabetic patients with CF was 25.8% (95% CI = 19.7 to 31.9%). Subgroup analysis showed that hospital prevalence was higher than in the community and in women than in men. Combined estimates showed that depression, malnutrition, advanced age (≥70, ≥80), combined chronic diseases ≥4 and glycated hemoglobin ≥8.5 were risk factors for CF in diabetics patients in China, with regular exercise and high education level (≥ college) as protective factors.

Conclusion

Cognitive frailty was common in diabetic patients in China. Such populations should be screened early and intervened with relevant factors.Systematic review registration: A systematic review of this study evaluated the registered websites as https://www.crd.york.ac.uk/PROSPERO/, CRD42023431396.

Management of cognitive frailty: A network meta-analysis of randomized controlled trials

OBJECTIVES

We aimed to compare the effectiveness of interventions in cognitive function and frailty status and rank these interventions.

METHODS

Data Sources-We searched PubMed, Embase, CINAHL, PsycINFO, Web of Science, Cochrane Library, Central Register of Controlled Trials (CENTRAL), CNKI, Wanfang, VIP and Google scholar. Data synthesis-The risk of bias was assessed using the Cochrane risk bias assessment tool. Statistical heterogeneity was assessed using the Chi-square test and quantified by I2 . The results were pooled using the standardized mean difference (SMD). The rank probability for each intervention was calculated using the surface under the cumulative ranking curve (SUCRA). Additionally, the quality of the evidence was evaluated using the GRADE approach.

RESULTS

A total of 10 randomized controlled trials (RCTs) involving 1110 patients were included in our analysis. The network map of cognitive function comprised 9 RCTs with 1347 participants, examining eight different interventions. Nutritional support (SUCRA = 99.9%, SMD = 3.02, 95% CI: 2.53, 3.51) may be the most effective intervention to improve cognitive function. The network map of frailty (including 9 RCTs with 1017 participants and 9 interventions) suggested that multicomponent exercises (SUCRA = 96.4%, SMD = -5.10, 95% CI: -5.96, -4.23) tended to have a greater effect.

CONCLUSIONS

Community-based multicomponent exercises have shown significant benefits for improving cognitive function and frailty status in older adults, with moderate certainty. For hospitalized older patients with Cognitive frailty (CF), current evidence suggests that nutritional support yields the most improvement. Additionally, aerobic exercise and dual-task training have proven effective in managing CF. Further studies are needed to validate these preliminary findings and exploring more accessible and effective physical and cognitive interventions to prevent CF in aging.

Prevalence and possible factors of cognitive frailty in the elderly with hypertension and diabetes

BACKGROUND

Cognitive frailty is the coexistence of physical frailty and mild cognitive impairment. Research shows that cognitive frailty is related to an increased risk of hospitalization, mortality, disability, and dementia. Diabetes and hypertension are common risk factors for physical frailty and cognitive impairment. However, the factors influencing cognitive frailty in the elderly with hypertension and diabetes are still unclear. This study aimed to investigate the possible factors influencing cognitive frailty in the elderly with hypertension and diabetes.

METHODS

A cross-sectional study was conducted. We evaluated people over 60 years with hypertension and diabetes who underwent physical examination in Wuxi Xin'an Community Health Service Center. Frail scale, Montreal Cognitive Assessment-Basic and clinical dementia rating were used to assess cognitive frailty. We collected demographic characteristics, hypertension and diabetes-related laboratory indicators of the participants. We also used various scales to assess the overall health status of the elderly.

RESULTS

Approximately 20.8% of the participants were determined to have cognitive frailty in elderly adults with hypertension and diabetes. These participants were older, had a lower monthly income, and included a higher proportion of peasants. They also had a higher level of depression (p = 0.037), higher risk of falls (p = 0.000), higher risk of malnutrition (p = 0.002), poorer ability to perform activities of daily living (ADL) (p = 0.000), and less social support (p = 0.030). Multivariate regression analysis was used to further assess the factors for cognitive frailty. After adjusting for possible confounders, age and ADL score emerged as risk factors, whereas high monthly income decreased the risk of cognitive frailty.

CONCLUSION

Cognitive frailty is correlated with age, income, and ability to perform daily living activities in the elderly with diabetes and hypertension. Closer attention to the elderly who have low income and poor self-care ability may play an important role in the early prevention of cognitive frailty and even dementia.

Impact of frailty, mild cognitive impairment and cognitive frailty on adverse health outcomes among community-dwelling older adults: A systematic review and meta-analysis

Aims

This study analyzes the impact of frailty, mild cognitive impairment, and cognitive frailty on adverse outcomes in community-dwelling older adults.

Methods

This systematic review and meta-analysis were conducted using the PRISMA guidelines and MOOSE statement. We developed a specific search strategy for each electronic database and searched PubMed, Web of Science, MEDLINE, and Embase from initial records to July 2021. The studies on adverse outcomes of frailty, pre-frailty, mild cognitive impairment, and mild cognitive impairment with pre-frailty and cognitive frailty were included. Two researchers independently extracted data based on a spreadsheet and assessed the risk of bias. The primary outcomes were mortality, dementia, disability, and hospitalization. The second outcome included quality of life and falls. All analysis was conducted by using Review Manager (RevMan) 5.3 software.

Results

A total of 22 cohort studies (71,544 older adults with mean age ranging from 65.1 to 93.6 years) were included with a low risk of bias and high methodological quality with a NOS score ≥7. Compared to robust elders, individuals identified as frailty were associated with a higher risk of mortality (RR = 2.11, 95% CI: 1.57–2.83) and disability (RR = 5.91, 95% CI: 2.37–14.74). Mild cognitive impairment with pre-frailty was associated with mortality (RR = 1.74, 95% CI: 1.48–2.05) and dementia (RR = 4.15, 95% CI: 1.87–9.20). Pre-frailty was associated with a higher risk of mortality (RR = 1.29, 95% CI: 1.11–1.50). Cognitive frailty was associated with higher risk of incident mortality (RR = 2.41, 95% CI: 1.97–2.94), dementia (RR = 3.67, 95% CI: 2.81–4.78), disability (RR = 11.32, 95% CI: 4.14–30.97), and hospitalization (RR = 2.30, 95% CI: 1.60–3.32), as well as poor quality of life.

Conclusion

Cognitive frailty could be a comprehensive psychosomatic predictor for adverse outcomes among older people. Interactions between frailty, mild cognitive impairment, and cognitive frailty on adverse outcomes must be further explored.

Systematic review registration

[https://inplasy.com/inplasy-2022-5-0064/], identifier [INPLASY202250064].

Multi-Concept Frailty Predicts the Late-Life Occurrence of Cognitive Decline or Dementia: An Updated Systematic Review and Meta-Analysis of Longitudinal Studies

Background

Frailty is a multidimensional syndrome that increases an individual’s vulnerability for developing adverse health outcomes, which include dementia. It might serve as a promising target for dementia prevention. However, there are currently no studies summarizing the association between multi-concept frailty and the risk of cognitive disorders. This study aims to summarize the evidence of associations between multi-concept frailty and cognitive disorders based on longitudinal studies.

Methods

Scopus, The Cochrane Library, PsycINFO, CINAHL, PubMed, and EMBASE databases were searched from inception to January 2, 2022. Longitudinal studies, which explored the association of frailty with incident risk of cognitive decline or dementia, were included. The multivariable-adjusted effect estimates were pooled by random-effects models. The evidence credibility was depicted according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) method.

Results

A total of 30 longitudinal studies were included. Four types of frailty concepts were involved, including physical, cognitive, social, and biopsychosocial frailty. The meta-analysis comprised 20 studies of 252,571 older adults (mean age: 64.1–80.4 years), among whom 7,388 participants developed cognitive decline or dementia. Physical frailty was associated with higher risk of developing cognitive disorders [pooled relative risk (pRR) = 1.52, 95% confidence interval (CI): 1.28–1.80, I2 = 21.2%, pRR = 1.62 for cognitive decline, 95% CI: 1.07–2.45, I2 = 40.2%, pRR = 1.37 for all-cause dementia (ACD), 95% CI: 1.13–1.66, I2 = 0.0%]. Cognitive frailty (pRR = 2.90, 95% CI: 1.28–6.55, I2 = 78.1%) and pre-frailty (pRR = 4.24, 95% CI: 2.74–6.56, I2 = 30.2%) were linked to higher risk of ACD. Biopsychosocial frailty could predict a 41% (pRR = 1.41, 95% CI: 1.17–1.71) elevated risk of cognitive decline or dementia [pRR = 1.53 (95% CI: 1.19–1.96) for ACD and 1.11 (95% CI: 1.05–1.17) for Alzheimer’s disease (AD)]. In the systematic review, social frailty was associated with a 53% higher risk of AD. Preventing frailty could avoid a maximum of 9.9% cognitive disorders globally. The overall evidence strength is rated as low-to-moderate. Inconsistency and imprecision are major sources of bias.

Conclusion

Frailty in late life is a promising risk factor for cognitive disorders. Frail elderly should be monitored for their cognitive dynamics and initiate early prevention of dementia.

Systematic Review Registration

www.ClinicalTrials.gov, identifier CRD4202127 3434.

Health Care Utilization and Out-of-Pocket Payments among Elderly with Cognitive Frailty in Malaysia

Background: Cognitive frailty (CF) as a potential risk factor for dementia, functional disability, poor quality of life, and mortality. The aim of this study was to explore the health care-related utilization and out-of-pocket (OOP) expenditures, sociodemographic characteristics, and comorbidities among elderly Malaysians with CF. Methods: A cross-sectional study targeting elderly Malaysian aged ≥65 years was conducted. The study included all participants of the fourth phase of the Malaysian representative Long-Term-Research-Grant-Scheme Towards-Useful-Aging (LRGS-TUA) community-based study. A structured and validated interview questionnaire was used. Results: In total, 1006 elderly were interviewed, with a 66.18% response rate. Only 730 respondents met the inclusion criteria. Of the eligible respondents, the CF prevalence was 4.5%. Around 60.6% of the participants with CF had utilized outpatient care at government clinics within the past 6 months. The estimated mean total OOP payments for CF during the past 6 months was 84 Malaysian Ringgit (RM) (SD 96.0). Conclusions: CF among elderly Malaysians is within the internationally recognized range of prevalence. The OOP payments for seeking health care among CF elderly are not different from that of other elderly categories. There is a high possibility of underutilization of the health care services of CF cases while they are still needy.

A systematic review and meta-analysis on cognitive frailty in community-dwelling older adults: risk and associated factors

OBJECTIVES

To identify which factors are associated with cognitive frailty (CF), as well as the impact of CF on the incidence of dementia and mortality.

METHODS

A systematic review with meta-analysis was carried out using papers that enrolled a total of 75,379 participants and were published up to January 2020.

RESULTS

Of the 558 identified records, 28 studies met the inclusion criteria and were included in the review. The meta-analysis of cross-sectional studies showed that CF has a significant association of having an older age and a history of falls. In longitudinal studies, the analysis showed a significant increase in risk of mortality and dementia for those with CF.

DISCUSSION

This is the first systematic review and meta-analysis on CF, which addressed a wide variety of factors associated with the theme and which pointed out some as a potential target for prevention or management with different interventions or treatments, showing the clinical importance of its identification in the most vulnerable and susceptible groups.

Prevalence of cognitive impairment in Chinese older inpatients and its relationship with 1-year adverse health outcomes: a multi-center cohort study

BACKGROUND

Previous studies on the relationship between cognitive impairment and adverse outcomes among geriatric inpatients are not representative of older inpatients in China because of insufficient sample sizes or single-center study designs. The purpose of our study was to examine the prevalence of cognitive impairment and the relationship between cognitive impairment and 1-year adverse health outcomes in older inpatients.

METHODS

This study was a large-scale multi-center cohort study conducted from October 2018 to February 2020. Six tertiary hospitals across China were selected using a two-stage cluster sampling method, and eligible older inpatients were selected for the baseline survey and follow-up. The Mini Cognitive Scale and the FRAIL scale were used to screen for cognitive impairment and frailty, respectively. The EuroQol-5 Dimension-5 Level questionnaire was used to assess health-related quality of life (HRQoL). We used a generalized estimating model to evaluate the relationship between cognitive impairment and adverse outcomes.

RESULTS

The study included 5008 men (58.02%) and 3623 women (41.98%), and 70.64% were aged 65-75 years, and 26.27% were aged 75-85 years. Cognitive impairment was observed in 1756 patients (20.35%). There were significant differences between participants with cognitive impairment and those with normal cognitive function for age, gender, surgery status, frailty, depression, handgrip strength and so on. After adjusting for multiple covariates, compared with patients with normal cognitive function, the odds ratio for 1-year mortality was 1.216 (95% confidence interval [CI]: 1.076-1.375) and for 1-year incidence of frailty was 1.195 (95% CI: 1.037-1.376) in patients with cognitive impairment. Similarly, the regression coefficient of 1-year HRQoL was - 0.013 (95% CI: - 0.024-- 0.002). In the stratified analysis, risk of adverse outcome within 1 year was higher in older patients with cognitive impairment aged over 75 years than those aged 65-74 years.

CONCLUSIONS

We revealed that cognitive impairment was highly correlated with occurrence of 1-year adverse health outcomes (death, frailty, and decreased HRQoL) in older inpatients, which provides a basis for formulating effective intervention measures.

TRIAL REGISTRATION

Chinese Clinical Trial Registry, ChiCTR1800017682 , registered 09 August 2018.

Mental Component Score (MCS) from Health-Related Quality of Life Predicts Incidence of Dementia in U.S. Males

BACKGROUND

The Medical Outcomes Study Questionnaire Short Form 36 health survey (SF-36) measures health-related quality of life (HRQoL) from the individual's point of view and is an indicator of overall health status.

OBJECTIVE

To examine whether HRQoL shows differential changes over time prior to dementia onset and investigate whether HRQoL predicts incidence of dementia.

DESIGN

Prevention of Alzheimer's Disease (AD) by Vitamin E and Selenium (PREADViSE) trial, which recruited 7,547 non-demented men between 2002 and 2009. A subset of 2,746 PREADViSE participants who completed up to five SF-36 assessments at annual visits was included in the current analysis.

SETTING

Secondary data analysis of PREADViSE data.

PARTICIPANTS

A subset of 2,746 PREADViSE participants who completed up to five SF-36 assessments at annual visits was included in the current analysis.

MEASUREMENTS

Two summary T scores were generated for analysis: physical component score (PCS) and mental component score (MCS), each with a mean of 50 (standard deviation of 10); higher scores are better. Linear mixed models (LMM) were applied to determine if mean component scores varied over time or by eventual dementia status. Cox proportional hazards regression was used to determine if the baseline component scores were associated with dementia incidence, adjusting for baseline age, race, APOE-4 carrier status, sleep apnea, and self-reported memory complaint at baseline.

RESULTS

The mean baseline MCS score for participants who later developed dementia (mean± SD: 53.9±9.5) was significantly lower than for those participants who did not develop dementia during the study (mean±SD: 56.4±6.5; p = 0.005). Mean PCS scores at baseline (dementia: 49.3±7.9 vs. non-dementia: 49.8±7.8) were not significantly different (p = 0.5) but LMM analysis showed a significant time effect. For MCS, the indicator for eventual dementia diagnosis was significantly associated with poorer scores after adjusting for baseline age, race, and memory complaint. Adjusted for other baseline risk factors, the Cox model showed that a 10-unit increase in MCS was associated with a 44% decrease in the hazard of a future dementia diagnosis (95% CI: 32%-55%).

CONCLUSION

The SF-36 MCS summary score may serve as a predictor for future dementia and could be prognostic in longitudinal dementia research.

Psychosocial Adjustment of In-Home Caregivers of Family Members with Dementia and Parkinson's Disease: A Comparative Study

Neurodegenerative diseases such as Parkinson's and dementia are highly prevalent worldwide. People who suffer from these disorders often receive in-home care and assistance from family members, who must dedicate a considerable amount of time to the care recipient. The study of family caregivers' psychosocial adjustment to the degenerative processes of both conditions is of interest due to the implications for the quality of life of both the care receiver and the caregiver, as well as other family members. This study compares the psychosocial adjustment of family members who care for people with dementia and Parkinson's disease and identifies the main sociodemographic variables that affect the processes of adjustment to both conditions. To this end, the Psychosocial Adjustment to Illness Scale (PAIS-SR) and a sociodemographic form were administered to 157 family caregivers in Navarre, Spain. The results show that adjustment to the disease in family caregivers of people with Parkinson's disease and dementia is, in general, satisfactory and related to variables such as place of residence, income, and employment status. The illness itself (Parkinson's or dementia), however, is found to be the most influential variable in the level of psychosocial adjustment.

Automatic Detection of Cognitive Impairments through Acoustic Analysis of Speech

Background: Early detection of mild cognitive impairment is crucial in the prevention of Alzheimer’s disease. The aim of the present study was to identify whether acoustic features can help differentiate older, independent community-dwelling individuals with cognitive impairment from healthy controls.

Methods: A total of 8779 participants (mean age 74.2 ± 5.7 in the range of 65-96, 3907 males and 4872 females) with different cognitive profiles, namely healthy controls, mild cognitive impairment, global cognitive impairment (defined as a Mini Mental State Examination score of 20-23), and mild cognitive impairment with global cognitive impairment (a combined status of mild cognitive impairment and global cognitive impairment), were evaluated in short-sentence reading tasks, and their acoustic features, including temporal features (such as duration of utterance, number and length of pauses) and spectral features (F0, F1, and F2), were used to build a machine learning model to predict their cognitive impairments.

Results: The classification metrics from the healthy controls were evaluated through the area under the receiver operating characteristic curve and were found to be 0.61, 0.67, and 0.77 for mild cognitive impairment, global cognitive impairment, and mild cognitive impairment with global cognitive impairment, respectively.

Conclusion: Our machine learning model revealed that individuals’ acoustic features can be employed to discriminate between healthy controls and those with mild cognitive impairment with global cognitive impairment, which is a more severe form of cognitive impairment compared with mild cognitive impairment or global cognitive impairment alone. It is suggested that language impairment increases in severity with cognitive impairment.

Cognitive function in Prefrail and frail community-dwelling older adults in China

Background

Physical frailty, characterized by reduced physiologic complexity and ability to cope with stressors, is closely associated with cognitive impairment, which increases the risk of poor clinical outcomes. To better capture the association between frailty and cognitive impairment, a new construct, cognitive frailty, has been proposed. Cognitive frailty is a clinical condition characterized by the simultaneous presence of physical frailty and cognitive impairment. There is little evidence on the relationship between physical frailty and cognition, as well as cognitive frailty, in Chinese older adults. We aimed to elucidate whether physical frailty is associated with cognitive impairment in an older Chinese population.

Methods

Data were obtained from the China Comprehensive Geriatric Assessment Study. The sample comprised 3202 community-dwelling adults, aged 60 years and older, from seven Chinese cities. Physical frailty was assessed using a modified, four-item version of the Fried criteria, according to frailty phenotype. Cognitive function was assessed using the Mini-Mental State Examination (MMSE).

Results

The prevalence of physical frailty, prefrailty, cognitive impairment, and cognitive frailty was 9.9, 33.9, 7.5, and 2.3%, respectively (weighted: 8.8, 33.8, 6.5, and 2.0%). The prevalence of the combination of prefrail/frail and cognitive impairment was 5.1% (weighted 4.5%). Frail participants performed worse on global cognition and all cognitive domains than robust and prefrail participants. The MMSE total score was positively correlated with walking speed and negatively correlated with age and frailty. A multivariate logistic regression revealed that after adjusting for age, gender, education level, living area, and chronic diseases, frailty, exhaustion, slowness, and inactivity were significantly associated with poor global cognition.

Conclusions

The standard prevalence of physical frailty, prefrailty, cognitive impairment, and cognitive frailty in community-dwelling older adults in China was 8.8, 33.8, 6.5, and 2.0%, respectively. Frailty, exhaustion, slowness, and inactivity were significantly associated with poor global cognition.

Self-Reported Cognitive Frailty Predicts Adverse Health Outcomes for Community-Dwelling Older Adults Based on an Analysis of Sex and Age

OBJECTIVES

The present study examined whether the combination of self-reported mobility decline (SR-MD) and cognitive decline (SR-CD) was associated with mortality and new long-term care insurance (LTCI) service certifications based on sex and age.

DESIGN

A prospective cohort study.

SETTING AND PARTICIPANTS

We analyzed cohort data from a sample of older adult residents in Kami Town, Japan. The response rate was 94.3%, and we followed 5,094 older adults for 3 years. Full analyses were conducted on 5,076 participants.

MEASURES

A total of four groups were determined through self-reported responses on the Kihon Checklist for SR-MD (a score of 3 or more on 5 items) and SR-CD (a score of 1 or more on 3 items): non-SR-cognitive frailty, non-SR-MD and SR-CD, SR-MD and non-SR-CD, and SR-cognitive frailty.

RESULTS

Main outcomes included mortality (n = 262) or new certifications for LTCI services (n = 708) during the 3-year period. Excluding overlapping, this included 845 older adults (16.6%). Among men, prevalence of non-SR-cognitive frailty, non-SR-MD and SR-CD, SR-MD and non-SR-CD, and SR-cognitive frailty (SR-MD and SR-CD) was 48.2%, 26.4%, 11.5%, and 13.8%, respectively. Respective rates for women were 45.7%, 15.5%, 23.1%, and 15.7%. Multivariate analyses revealed that for men, SR-MD and non-SR-CD significantly affected adverse health outcomes, leading to earlier negative outcomes relative to the non-SR-MD and SR-CD group. For women, non-SR-MD and SR-CD and SR-MD and non-SR-CD had similar slopes.

CONCLUSIONS

The impact of SR-MD or SR-CD on adverse health outcomes differed as a function of age and sex. Thus, we need to consider preventive approaches according to these specific target group features.

Instrumented Trail-Making Task: Application of Wearable Sensor to Determine Physical Frailty Phenotypes

BACKGROUND

The physical frailty assessment tools that are currently available are often time consuming to use with limited feasibility.

OBJECTIVE

To address these limitations, an instrumented trail-making task (iTMT) platform was developed using wearable technology to automate quantification of frailty phenotypes without the need of a frailty walking test.

METHODS

Sixty-one older adults (age = 72.8 ± 9.9 years, body mass index [BMI] = 27.4 ± 4.9 kg/m2) were recruited. According to the Fried Frailty Criteria, 39% of participants were determined as robust and 61% as non-robust (pre-frail or frail). In addition, 17 young subjects (age = 29.0 ± 7.2 years, BMI = 26.2 ± 4.6 kg/m2) were recruited to determine the healthy benchmark. The iTMT included reaching 5 indexed circles (including numbers 1-to-3 and letters A&B placed in random orders), which virtually appeared on a computer-screen, by rotating one's ankle-joint while standing. By using an ankle-worn inertial sensor, 3D ankle-rotation was estimated and mapped into navigation of a computer-cursor in real-time (100 Hz), allowing subjects to navigate the computer-cursor to perform the iTMT. The ankle-sensor was also used for quantifying ankle-rotation velocity (representing slowness), its decline during the test (representing exhaustion), and ankle-velocity variability (representing movement inefficiency), as well as the power (representing weakness) generated during the test. Comparative assessments included Fried frailty phenotypes and gait assessment.

RESULTS

All subjects were able to complete the iTMT, with an average completion time of 125 ± 85 s. The iTMT-derived parameters were able to identify the presence and absence of slowness, exhaustion, weakness, and inactivity phenotypes (Cohen's d effect size = 0.90-1.40). The iTMT Velocity was significantly different between groups (d = 0.62-1.47). Significant correlation was observed between the iTMT Velocity and gait speed (r = 0.684 p < 0.001). The iTMT-derived parameters and age together enabled significant distinguishing of non-robust cases with area under curve of 0.834, sensitivity of 83%, and specificity of 67%.

CONCLUSION

This study demonstrated a non-gait-based wearable platform to objectively quantify frailty phenotypes and determine physical frailty, using a quick and practical test. This platform may address the hurdles of conventional physical frailty phenotypes methods by replacing the conventional frailty walking test with an automated and objective process that reduces the time of assessment and is more practical for those with mobility limitations.

Cognitive Frailty Predicts Incident Dementia among Community-Dwelling Older People

Cognitive frailty, defined as the presence of both frailty and cognitive impairment, is a risk factor for adverse events in older adults. However, prevalence rates of cognitive frailty are low (1.1–2.5%), so primary screening is unsuitable in community settings. The aim of the study was to examine whether a new definition of cognitive frailty, which was developed for primary screening, is useful to predict incident dementia in community-dwelling older adults. A total of 4570 older adults participated in the study (2326 women; average age, 71.9 ± 5.5 years). We defined physical frailty as the presence of ≥1 of the following symptoms: slow walking speed and muscle weakness. Cognitive impairment was defined as ≥1 symptom of cognitive impairment, indicated by an age- and education-adjusted score that was ≥1.5 standard deviations below the reference threshold in word list memory, attention, executive function, and processing speed tests. Cognitive frailty was defined as comorbid physical frailty and cognitive impairment. The incidence of dementia was determined using data collected by the Japanese Health Insurance System over 36 months. The prevalence rates of physical frailty, cognitive impairment, and cognitive frailty were 17.5%, 15.3%, and 9.8%, respectively. Cognitive impairment (hazard ratio [HR]: 2.06, 95% confidence interval [95% CI]: 1.41–3.02) and cognitive frailty (HR: 3.43, 95% CI: 2.37–4.97) were found to be significant risk factors for dementia. However, the association between dementia and physical frailty was not significant (HR: 1.13, 95% CI: 0.76–1.69). Individuals with comorbid physical frailty and cognitive impairment could have a higher risk of dementia than healthy older adults or older adults with either physical frailty or cognitive impairment alone.

Motor Planning Error: Toward Measuring Cognitive Frailty in Older Adults Using Wearables

Practical tools which can be quickly administered are needed for measuring subtle changes in cognitive–motor performance over time. Frailty together with cognitive impairment, or ‘cognitive frailty’, are shown to be strong and independent predictors of cognitive decline over time. We have developed an interactive instrumented trail-making task (iTMT) platform, which allows quantification of motor planning error (MPE) through a series of ankle reaching tasks. In this study, we examined the accuracy of MPE in identifying cognitive frailty in older adults. Thirty-two older adults (age = 77.3 ± 9.1 years, body-mass-index = 25.3 ± 4.7 kg/m², female = 38%) were recruited. Using either the Mini-Mental State Examination or Montreal Cognitive Assessment (MoCA), 16 subjects were classified as cognitive-intact and 16 were classified as cognitive-impaired. In addition, 12 young-healthy subjects (age = 26.0 ± 5.2 years, body-mass-index = 25.3 ± 3.9 kg/m², female = 33%) were recruited to establish a healthy benchmark. Subjects completed the iTMT, using an ankle-worn sensor, which transforms ankle motion into navigation of a computer cursor. The iTMT task included reaching five indexed target circles (including numbers 1-to-3 and letters A&B placed in random order) on the computer-screen by moving the ankle-joint while standing. The ankle-sensor quantifies MPE through analysis of the pattern of ankle velocity. MPE was defined as percentage of time deviation between subject’s maximum ankle velocity and the optimal maximum ankle velocity, which is halfway through the reaching pathway. Data from gait tests, including single task and dual task walking, were also collected to determine cognitive–motor performance. The average MPE in young-healthy, elderly cognitive-intact, and elderly cognitive-impaired groups was 11.1 ± 5.7%, 20.3 ± 9.6%, and 34.1 ± 4.2% (p < 0.001), respectively. Large effect sizes (Cohen’s d = 1.17–4.56) were observed for discriminating between groups using MPE. Significant correlations were observed between the MPE and MoCA score (r = −0.670, p < 0.001) as well as between the MPE and dual task stride velocity (r = −0.584, p < 0.001). This study demonstrated feasibility and efficacy of estimating MPE from a practical wearable platform with promising results in identifying cognitive–motor impairment and potential application in assessing cognitive frailty. The proposed platform could be also used as an alternative to dual task walking test, where gait assessment may not be practical. Future studies need to confirm these observations in larger samples.