Tracking changes in frailty throughout later life: results from a 17-year longitudinal study in the Netherlands

The Longitudinal Aging Study Amsterdam: design and cohort update 2025

The Longitudinal Aging Study Amsterdam (LASA) is an ongoing prospective cohort study of older adults in the Netherlands, with data on multiple domains of functioning available over a period of more than 30 years of follow-up. The study started in 1992 with a nationally representative sample of older adults aged 55-84 years. Over the years, three refresher cohorts (two cohorts aged 55-64 years in 2002 and in 2012, and one cohort aged 60-86 years in 2024) were added. The main aim of LASA was to describe determinants, trajectories and consequences of (changes in) physical, cognitive, emotional and social functioning. LASA has multiple strengths, including its multidisciplinary character, the very long period of follow-up, and the cohort-sequential design which enables the study of longitudinal changes as well as historical time trends in functioning. So far, findings based on data from LASA have been reported in more than 800 scientific publications (see www.lasa-vu.nl ). In this article, we provide an update of the design and methods of LASA, including a description of several ancillary studies such as the Loneliness study and the COVID-19 study.

Frailty in motion: Amnestic mild cognitive impairment and Alzheimer's disease cohorts display heterogeneity in multimorbidity classification and longitudinal transitions

BackgroundData-driven examination of multiple morbidities and deficits are informative for clinical and research applications in aging and dementia. Resulting profiles may change longitudinally according to dynamic alterations in extent, duration, and pattern of risk accumulation. Do such frailty-related changes include not only progression but also stability and reversion?ObjectiveWith cognitively impaired and dementia cohorts, we employed data-driven analytics to (a) detect the extent of heterogeneity in frailty-related multimorbidity and deficit burden subgroups and (b) identify key person characteristics predicting differential transition patterns.MethodsWe assembled baseline and 2-year follow-up data from the National Alzheimer's Coordinating Center for amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD) cohorts. We applied factor analyses to 43 multimorbidity and deficit indicators. Latent Transition Analysis (LTA) was applied to the resulting domains in order to detect subgroups differing in transition patterns for multimorbidity and deficit burden. We characterized heterogeneity in change patterns by evaluating key person characteristics as differential predictors.ResultsFactor analyses revealed five domains at two time points. LTA showed that two latent burden subgroups at Time 1 (Low, Moderate) differentiated into an additional two subgroups at Time 2 (adding Mild, Severe). Transition analyses detected heterogeneous changes, including progression, stability, and reversion. Baseline classifications and transitions varied according to clinical cohort, global cognition, sex, age, and education.ConclusionsHeterogeneous frailty-related subgroup transitions can be (a) detected in aging adults living with aMCI and AD, (b) characterized as not only progression but also stability and reversion, and (c) predicted by precision characteristics.

Short-term Frailty Index Fluctuations in Older Adults: Noise or Signal?

BACKGROUND

Reversible short-term fluctuations in the frailty index (FI) are often thought of as representing only noise or error. Here, we assess (i) the size and source of short-term FI fluctuations, (ii) variation across sociodemographic characteristics, (iii) association with chronic diseases, (iv) correlation with age, frailty level, frailty change, and mortality, and (v) whether fluctuations reflect discrete health transitions.

METHODS

Nationwide, biweekly longitudinal data from 426 community-dwelling older adults (70+) were collected in the FRequent health Assessment In Later life (FRAIL70+) study using a measurement burst design (5 122 repeated observations, median of 13 repeated observations per person). We calculated the intraindividual standard deviation of the FI and used location-scale mixed regression models.

RESULTS

Mean intraindividual standard deviation was 0.04 (standard deviation = .03). Fluctuations were driven foremost by cognitive problems, somatic symptoms, and limitations in instrumental and mobility-related activities of daily living. Short-term fluctuations correlated with higher FI levels (r = 0.62), 1-year FI change (r = 0.26), and older age (+3% per year). Older adults who took to bed due to a health problem (+50%), those who had an overnight hospital stay (+50%), and those who died during follow-up (+44%) exhibited more FI fluctuations.

CONCLUSIONS

Short-term FI fluctuations were neither small nor random. Instead, as older adults become frailer, their measured health also becomes more unstable; hence, short-term fluctuations in overall health status can be seen as a concomitant phenomenon of the aging process. Researchers and clinicians should be aware of the existence of reversible fluctuations in the FI over weeks and months and its consequences for frailty monitoring.

Delirium and frailty in older adults: Clinical overlap and biological underpinnings

Frailty and delirium are two common geriatric syndromes sharing several clinical characteristics, risk factors, and negative outcomes. Understanding their interdependency is crucial to identify shared mechanisms and implement initiatives to reduce the associated burden. This literature review summarizes scientific evidence on the complex interplay between frailty and delirium; clinical, epidemiological, and pathophysiological commonalities; and current knowledge gaps. We conducted a PubMed systematic search in June 2023, which yielded 118 eligible articles out of 991. The synthesis of the results-carried out by content experts-highlights overlapping risk factors, clinical phenotypes, and outcomes and explores the influence of one syndrome on the onset of the other. Common pathophysiological mechanisms identified include inflammation, neurodegeneration, metabolic insufficiency, and vascular burden. The review suggests that frailty is a risk factor for delirium, with some support for delirium associated with accelerated frailty. The proposed unifying framework supports the integration and measurement of both constructs in research and clinical practice, identifying the geroscience approach as a potential avenue to develop strategies for both conditions. In conclusion, we suggest that frailty and delirium might be alternative-sometimes coexisting-manifestations of accelerated biological aging. Clinically, the concepts addressed in this review can help approach older adults with either frailty or delirium from a different perspective. From a research standpoint, longitudinal studies are needed to explore the hypothesis that specific pathways within the biology of aging may underlie the clinical manifestations of frailty and delirium. Such research will pave the way for future understanding of other geriatric syndromes as well.

Impact of frailty in older people on health care demand: simulation modelling of population dynamics to inform service planning

Background

As populations age, frailty and the associated demand for health care increase. Evidence needed to inform planning and commissioning of services for older people living with frailty is scarce. Accurate information on incidence and prevalence of different levels of frailty and the consequences for health outcomes, service use and costs at population level is needed.

Objectives

To explore the incidence, prevalence, progression and impact of frailty within an ageing general practice population and model the dynamics of frailty-related healthcare demand, outcomes and costs, to inform the development of guidelines and tools to facilitate commissioning and service development.

Study design and methods

A retrospective observational study with statistical modelling to inform simulation (system dynamics) modelling using routine data from primary and secondary health care in England and Wales. Modelling was informed by stakeholder engagement events conducted in Hampshire, England. Data sources included the Royal College of General Practitioners Research and Surveillance Centre databank, and the Secure Anonymised Information Linkage Databank. Population prevalence, incidence and progression of frailty within an ageing cohort were estimated using the electronic Frailty Index tool, and associated service use and costs were calculated. Association of frailty with outcomes, service use and costs was explored with multistate and generalised linear models. Results informed development of a prototype system dynamics simulation model, exploring population impact of frailty and future scenarios over a 10-year time frame. Simulation model population projections were externally validated against retrospective data from Secure Anonymised Information Linkage.

Study population

The Royal College of General Practitioners Research and Surveillance Centre sample comprised an open cohort of the primary care population aged 50 + between 2006 and 2017 (approx. 2.1 million people). Data were linked to Hospital Episode Statistics data and Office for National Statistics death data. A comparable validation data set from Secure Anonymised Information Linkage was generated.

Baseline measures

Electronic Frailty Index score calculated annually and stratified into Fit, Mild, Moderate and Severe frailty categories. Other variables included age, sex, Index of Multiple Deprivation score, ethnicity and Urban/rural.

Outcomes

Frailty transitions, mortality, hospitalisations, emergency department attendances, general practitioner visits and costs.

Findings

Frailty is already present in people aged 50-64. Frailty incidence was 47 cases per 1000 person-years. Frailty prevalence increased from 26.5% (2006) to 38.9% (2017). Older age, higher deprivation, female sex, Asian ethnicity and urban location independently predict frailty onset and progression; 4.8% of 'fit' people aged 50-64 years experienced a transition to a higher frailty state in a year, compared to 21.4% aged 75-84. Individual healthcare use rises with frailty severity, but Mild and Moderate frailty groups have higher overall costs due to larger population numbers. Simulation projections indicate frailty will increase by 7.1%, from 41.5% to 48.7% between 2017 and 2027, and associated costs will rise by £5.8 billion (in England) over an 11-year period.

Conclusions

Simulation modelling indicates that frailty prevalence and associated service use and costs will continue to rise in the future. Scenario analysis indicates reduction of incidence and slowing of progression, particularly before the age of 65, has potential to substantially reduce future service use and costs, but reducing unplanned admissions in frail older people has a more modest impact. Study outputs will be collated into a commissioning toolkit, comprising guidance on drivers of frailty-related demand and simulation model outputs.

Study registration

This study is registered as NCT04139278 www.clinicaltrials.gov.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 16/116/43) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 44. See the NIHR Funding and Awards website for further award information.

Impact of activity limitations due to fear of falling on changes in frailty in Korean older adults: a longitudinal study

This study investigated the frailty change patterns among Korean older adults during 2006-2020 and the effect of activity limitations induced by the fear of falling (FOF) on these patterns. We employed a descriptive longitudinal design utilizing data from Waves 1 to 8 of the Korean Longitudinal Study of Aging. The exclusion criteria were a baseline age < 65 years, frailty index (FI) captured only at baseline, and death or unknown survival status. Multilevel modeling, combining regression equations at two levels, was used to examine the effect of activity limitations due to FOF on frailty, adjusting for other confounding factors. An increase in FI (1.97; p < .001) was demonstrated in participants who had experienced falls versus those who had not in the past 2 years. Notably, those facing activity limitations due to FOF exhibited a more significant increase in FI (4.62; p < .001) compared with those without; frailty progression intensified over time in the former (0.54, p < .001). Activity limitations due to FOF had a more pronounced impact on frailty than falls; moreover, these activity limitations accelerated the progression of frailty. Healthcare providers must prioritize addressing FOF by employing both physical and psychological interventions to mitigate activity limitations and ultimately decelerate frailty.

Secular trends in frailty among community-dwelling 75-95-year-old cohorts over three decades in Helsinki, Finland

BACKGROUND

Frailty Index (FI) reflects health, functioning and well-being of older people. It is valuable to compare how frailty has changed over time in ageing cohorts. This study aims to examine trends in frailty among 75-95-year-old men and women over three decades.

METHODS

The Helsinki Ageing Study started in 1989 and includes repeated cross-sectional postal surveys every 10 years examining community-dwelling cohorts of older people (75, 80, 85, 90 and 95 years). FI comprises the same 36 items in each cohort.

RESULTS

The mean FI was 0.22 (SD 0.12), 0.25 (SD 0.15), 0.26 (SD 0.15) and 0.23 (SD 0.15) in 1989, 1999, 2009 and 2019, respectively (P for linearity for crude values .11). Adjusted for age and sex, the four cohorts differed in their frailty the 2019 cohort having the lowest FI. This sex-adjusted difference was seen among 75-, 80-, 85- and 90-year-olds but not among 95-year-olds. FI decreased more among men than women (P for cohort <.001, P for sex <.01, P for interaction = .19).

CONCLUSIONS

The prevalence of frailty among community-dwelling individuals aged 75, 80, 85 and 90 years-but not among those aged 95 years-has significantly decreased over the last decades. This positive trend may have important implications for health policies in societies with increasing longevity.

Identifying low acuity Emergency Department visits with a machine learning approach: The low acuity visit algorithms (LAVA)

OBJECTIVE

To improve the performance of International Classification of Disease (ICD) code rule-based algorithms for identifying low acuity Emergency Department (ED) visits by using machine learning methods and additional covariates.

DATA SOURCES

We used secondary data on ED visits from the National Hospital Ambulatory Medical Survey (NHAMCS), from 2016 to 2020.

STUDY DESIGN

We established baseline performance metrics with seven published algorithms consisting of International Classification of Disease, Tenth Revision codes used to identify low acuity ED visits. We then trained logistic regression, random forest, and gradient boosting (XGBoost) models to predict low acuity ED visits. Each model was trained on five different covariate sets of demographic and clinical data. Model performance was compared using a separate validation dataset. The primary performance metric was the probability that a visit identified by an algorithm as low acuity did not experience significant testing, treatment, or disposition (positive predictive value, PPV). Subgroup analyses assessed model performance across age, sex, and race/ethnicity.

DATA COLLECTION

We used 2016-2019 NHAMCS data as the training set and 2020 NHAMCS data for validation.

PRINCIPAL FINDINGS

The training and validation data consisted of 53,074 and 9542 observations, respectively. Among seven rule-based algorithms, the highest-performing had a PPV of 0.35 (95% CI [0.33, 0.36]). All model-based algorithms outperformed existing algorithms, with the least effective-random forest using only age and sex-improving PPV by 26% (up to 0.44; 95% CI [0.40, 0.48]). Logistic regression and XGBoost trained on all variables improved PPV by 83% (to 0.64; 95% CI [0.62, 0.66]). Multivariable models also demonstrated higher PPV across all three demographic subgroups.

CONCLUSIONS

Machine learning models substantially outperform existing algorithms based on ICD codes in predicting low acuity ED visits. Variations in model performance across demographic groups highlight the need for further research to ensure their applicability and fairness across diverse populations.

Longitudinal trajectories of frailty are associated with short-term mortality in older people: a joint latent class models analysis using 2 UK primary care databases

OBJECTIVES

Frailty is a dynamic health state that changes over time. Our hypothesis was that there are identifiable subgroups of the older population that have specific patterns of deterioration. The objective of this study was to evaluate the application of joint latent class model in identifying trajectories of frailty progression over time and their group-specific risk of death in older people.

STUDY DESIGN AND SETTING

The primary care records of UK patients, aged over 65 as of January 1, 2010, included in the Clinical Practice Research Datalink: GOLD and AURUM databases, were analyzed and linked to mortality data. The electronic frailty index (eFI) scores were calculated at baseline and annually in subsequent years (2010-2013). Joint latent class model was used to divide the population into clusters with different trajectories and associated mortality hazard ratios. The model was built in GOLD and validated in AURUM.

RESULTS

Five trajectory clusters were identified and characterized based on baseline and speed of progression: low-slow, low-moderate, low-rapid, high-slow, and high-rapid. The high-rapid cluster had the highest average starting eFI score; 7.9, while the low-rapid cluster had the steepest rate of eFI progression; 1.7. Taking the low-slow cluster as reference, low-rapid and high-rapid had the highest hazard ratios: 3.73 (95% CI 3.71, 3.76) and 3.63 (3.57-3.69), respectively. Good validation was found in the AURUM population.

CONCLUSION

Our research found that there are vulnerable subgroups of the older population who are currently frail or have rapid frailty progression. Such groups may be targeted for greater healthcare monitoring.

Frailty, cognitive impairment, and depressive symptoms in Chinese older adults: an eight-year multi-trajectory analysis

BACKGROUND

Frailty, cognitive impairment, and depressive symptoms are closely interrelated conditions in the aging population. However, limited research has longitudinally analyzed the concurrent trajectories of these three prominent conditions in older adults in China. This study aimed to explore the eight-year trajectories of frailty, cognitive impairment, and depressive symptoms, and to identify individual-level and structural-level factors associated with the trajectories.

METHODS

Four waves of data from the China Health and Retirement Longitudinal Study (2011-2018) were used to identify 6,106 eligible older adults. The main measures included frailty by the frailty index constructed using 30 indicators, cognitive impairment by the summary score of immediate and delayed word recall, figure drawing, serial subtraction, and orientation, and depressive symptoms by the Center for Epidemiologic Studies Depression Scale. Multi-trajectory models identified the trajectories of frailty, cognitive impairment, and depressive symptoms over time. Multinomial logistic regression was employed to estimate the associations between individual-level capital factors and one structural factor (hukou and geographic residency) with the identified trajectories, adjusting for demographic characteristics.

RESULTS

Four trajectories emerged: (1) worsening frailty, worsening cognitive impairment, depression (14.0%); (2) declining pre-frailty, declining cognition, borderline depression (20.0%); (3) pre-frailty, worsening cognitive impairment, no depression (29.3%); and (4) physically robust, declining cognition, no depression (36.7%). Using the "physically robust, declining cognition, no depression" as the reference, not working, no social activity participant, worse childhood family financial situation, and poorer adult health were most strongly associated with the "worsening frailty, worsening cognitive impairment, depression" trajectory; worse health during childhood had the highest association with the "declining pre-frailty, declining cognition, borderline depression" trajectory; less education, lower household consumption, and rural hukou had the greatest association with the increased likelihood of the "pre-frailty, worsening cognitive impairment, no depression" trajectory.

CONCLUSIONS

Findings could inform the understanding of the interrelationship of frailty, cognitive impairment, and depressive symptoms in older adults in China and may help practitioners detect adults at risk for adverse trajectories to implement strategies for proper care.

Frailty index trajectories in Chinese older adults with diverse levels of social participation: findings from a national population-based longitudinal study

BACKGROUND

Aging and frailty pose significant challenges globally, placing a substantial burden on healthcare and social services due to their adverse consequences.

AIM

The primary objective of this study was to investigate the relationship between social participation and development of frailty transition and trajectory.

METHODS

This study utilized data from the CLHLS Cohort, a 10-year follow-up study involving 6713 participants, to investigate the association between social participation and development of frailty. Frailty reflects a comprehensive decline in various body functions. The study employed a group-based trajectory model to analyze the development trajectory of the frailty index and used logistic regression to assess the odds ratio (OR) of frailty risk.

RESULTS

We identified two distinct groups of frailty progression trajectories: the "stable development group" and the "rapid growth group." Individuals who engaged in social activities at least once a month, but not daily, exhibited a significant association with an increased risk of transitioning into the "rapid growth group" (OR 1.305, 95% CI 1.032-1.649). Those with social participation less than once a month had an even greater risk (OR 1.872, 95% CI 1.423-2.463). Moreover, low social participation frequency (occasionally/never) has a more pronounced impact on frailty progression in males.

CONCLUSION

A higher frequency of social participation is associated with a lower risk of being classified into the "rapid growth group" and a slower rate of frailty index progression. Preventing the progression of frailty can contribute to enhanced support for healthy aging among older adults.

Exploring fraity and sarcopenia in older adults admitted to acute medical unit, looking at prevalence, trajectory, and outcomes: A protocol testing the feasibility and acceptability of the TYSON study

BACKGROUND

Frailty and sarcopenia are common in older people and are associated with adverse outcomes including increased mortality and morbidity. It is unclear whether screening for frailty and sarcopenia would identify specific populations most at risk of poor outcomes during unplanned hospital admissions, which screening tools should be used and what the trajectory of both conditions are over the course of an admission. The TYSON study is an observational cohort study aiming to determine the prevalence, trajectory and outcomes associated with frailty and sarcopenia in different patient cohorts. This protocol tests the feasibility and acceptability of TYSON processes.

OBJECTIVES

To determine in acutely admitted medical patients who are older adults: Primary: The feasibility and acceptability of frailty and sarcopenia assessments; Secondary: (1) Differences in community and hospital frailty assessments, as assessed by the medical team, the patient and elderly care physicians, (2) The dynamic changes in frailty and sarcopenia during a hospital admission, and patient outcomes; Exploratory: Inflammatory and metabolic mediators associated with frailty and sarcopenia.

METHODS

A single centre, prospective observational study including patients aged ≥ 65 years admitted to an acute medical unit. Frailty assessments include the Rockwood clinical frailty and e-frailty index. Sarcopenia assessments include the Bilateral Anterior Thigh Thickness (BATT) measurement. Each participant will be asked to complete 5 visits, at day 0, day 3, day 7, month 3 and month 6. Blood samples will be collected to explore inflammatory and metabolic markers associated with frailty and sarcopenia. The study and protocol have been ethically approved by the Health Research Authority (REC 20/WA/0263).

DISCUSSION

The study will determine the feasibility and acceptability of frailty and sarcopenia assessments in an acute hospital setting, and inform on the prevalence, trajectory and associated outcomes of frailty and sarcopenia in this group of patients. An inflammatory and metabolic profile will be explored in frailty and sarcopenia.

Frailty transitions and prevalence in an ageing population: longitudinal analysis of primary care data from an open cohort of adults aged 50 and over in England, 2006-2017

INTRODUCTION

frailty is common in older adults and is associated with increased health and social care use. Longitudinal information is needed on population-level incidence, prevalence and frailty progression to plan services to meet future population needs.

METHODS

retrospective open cohort study using electronic health records of adults aged ≥50 from primary care in England, 2006-2017. Frailty was calculated annually using the electronic Frailty Index (eFI). Multistate models estimated transition rates between each frailty category, adjusting for sociodemographic characteristics. Prevalence overall for each eFI category (fit, mild, moderate and severe) was calculated.

RESULTS

the cohort included 2,171,497 patients and 15,514,734 person-years. Frailty prevalence increased from 26.5 (2006) to 38.9% (2017). The average age of frailty onset was 69; however, 10.8% of people aged 50-64 were already frail in 2006. Estimated transitions from fit to any level of frailty were 48/1,000 person-years aged 50-64, 130/1,000 person-years aged 65-74, 214/1,000 person-years aged 75-84 and 380/1,000 person-years aged ≥ 85. Transitions were independently associated with older age, higher deprivation, female sex, Asian ethnicity and urban dwelling. Mean time spent in each frailty category decreased with age, with the longest period spent in severe frailty at all ages.

CONCLUSIONS

frailty is prevalent in adults aged ≥50 and time spent in successive frailty states is longer as frailty progresses, resulting in extended healthcare burden. Larger population numbers and fewer transitions in adults aged 50-64 present an opportunity for earlier identification and intervention. A large increase in frailty over 12 years highlights the urgency of informed service planning in ageing populations.

Genetic and Environmental Influences on Longitudinal Frailty Trajectories From Adulthood into Old Age

BACKGROUND

Frailty is a complex, dynamic geriatric condition, but limited evidence has shown how genes and environment may contribute to its longitudinal changes. We sought to investigate sources of individual differences in the longitudinal trajectories of frailty, considering potential selection bias when including a sample of oldest-old twins.

METHODS

Data were from 2 Swedish twin cohort studies: a younger cohort comprising 1 842 adults aged 29-96 years followed up to 15 waves, and an older cohort comprising 654 adults aged ≥79 years followed up to 5 waves. Frailty was measured using the frailty index (FI). Age-based latent growth curve models were used to examine longitudinal trajectories, and extended to a biometric analysis to decompose variability into genetic and environmental etiologies.

RESULTS

A bilinear model with an inflection point at age 75 best described the data, indicating a fourfold to fivefold faster FI increase after 75 years. Twins from the older cohort had significantly higher mean FI at baseline but slower rate of increase afterward. FI level at age 75 was moderately heritable in both men (42%) and women (55%). Genetic influences were relatively stable across age for men and increasing for women, although the most salient amplification in FI variability after age 75 was due to individual-specific environmental influences for both men and women; conclusions were largely consistent when excluding the older cohort.

CONCLUSION

Increased heterogeneity of frailty in late life is mainly attributable to environmental influences, highlighting the importance of targeting environmental risk factors to mitigate frailty in older adults.

Progression of frailty as measured by a cumulative deficit index: A systematic review

BACKGROUND

Frailty is a risk factor for adverse health outcomes. There is a paucity of literature on frailty progression defined by a cumulative deficit model among community dwelling older people. The objective of this review was to synthesise evidence on these changes in health and mortality among community-dwelling older people.

METHODS

Six databases (Medline, Embase, CINAHL, Cochrane, PsycInfo, Web of Science) and a clinical trials registry were searched in July 2021. The inclusion criteria were studies using a frailty index and providing information on transition between frailty states or to death in community-dwelling older people aged ≥ 50. Exclusion criteria were studies examining specific health conditions, conference abstracts and non-English studies. To standardise the follow-up period and facilitate comparison, we converted the transition probabilities to annual transition rates.

RESULTS

Two reviewers independently screened 5078 studies and 61 studies were included for analysis. Of these, only three used the same frailty state cut-points to facilitate cross-cohort comparison. This review found that frailty tends to increase with time, people who are frail at baseline have greater likelihood to progress in frailty and die, and the main factor that accelerates frailty progression is age. Other risk factors for progression are having chronic disease, smoking, obesity, low-income or/and low-education levels. A frailty index is an accurate predictor of adverse outcomes and death.

DISCUSSION

This systematic review demonstrated that worsening in frailty was a common frailty transition, and older people who are frail at baseline are more likely to die. A frailty index has significant power to predict adverse health outcomes. It is a useful tool for within-cohort comparison but there are challenges comparing different cohorts due to dependence of frailty progression on age and differences in how frailty index is defined and measured.

Frailty trajectories and associated factors in the years prior to death: evidence from 14 countries in the Survey of Health, Aging and Retirement in Europe

BACKGROUND

Age-related changes in frailty have been documented in the literature. However, the evidence regarding changes in frailty prior to death is scarce. Understanding patterns of frailty progression as individuals approach death could inform care and potentially lead to interventions to improve individual's well-being at the end of life. In this paper, we estimate the progression of frailty in the years prior to death.

METHODS

Using data from 8,317 deceased participants of the Survey of Health, Ageing, and Retirement in Europe, we derived a 56-item Frailty Index. In a coordinated analysis of repeated measures of the frailty index in 14 countries, we fitted growth curve models to estimate trajectories of frailty as a function of distance to death controlling both the level and rate of frailty progression for age, sex, years to death and dementia diagnosis.

RESULTS

Across all countries, frailty before death progressed linearly. In 12 of the 14 countries included in our analyses, women had higher levels of frailty close to the time of death, although they progressed at a slower rate than men (e.g. Switzerland (-0.008, SE = 0.003) and Spain (-0.004, SE = 0.002)). Older age at the time of death and incident dementia were associated with higher levels and increased rate of change in frailty, whilst higher education was associated with lower levels of frailty in the year preceding death (e.g. Denmark (0.000, SE = 0.001)).

CONCLUSION

The progression of frailty before death was linear. Our results suggest that interventions aimed at slowing frailty progression may need to be different for men and women. Further longitudinal research on individual patterns and changes of frailty is warranted to support the development of personalized care pathways at the end of life.

Prognostic significance of frailty status in patients with primary lung cancer

Lung cancer has one of the highest morbidity and mortality rates in the world. Frailty is common in many countries and is a major cause of premature functional decline and premature death in older adults, and may affect the treatment and prognosis of lung cancer patients. To investigate the predictive value of frailty at diagnosis on all-cause mortality in lung cancer patients, this study retrospectively collected and analysed clinical information on lung cancer patients from 2015-2018. A total of 1667 patients with primary lung cancer were finally included in this study. The median follow-up time of patients was 650 (493, 1001.5) days. A total of 297(17.8%) patients had FI-LAB(the frailty index based on laboratory test) status of frail at the moment of diagnosis and the all-cause mortality rate for all patients was 61.1% (1018/1667). In a univariate model, we found a higher total all-cause mortality risk in frail patients (frail vs. robust, HR(hazard ratio) = 1.616, 95% CI(confidence interval) = 1.349,1.936), after balancing other variables combined into model 1 to model 6. The results were analyzed visually using ROC(Receiver operating characteristic) curves with nomogram and the AUC values ranged from 0.866-0.874. The final inclusion of age, TNM stage, CCI(Charlson comorbidity index) score, surgery history and chemotherapy into a multifactorial model balanced the predictive power of frailty grading on all-cause mortality. The study showed that for lung cancer patients, the higher the level of frailty at diagnosis, the higher the risk of all-cause mortality. In the context of widespread electronic medical records in hospitals, it is convenient and feasible to use FI-LAB to assess the prognosis of lung cancer patients.

How Neighborhood Structural and Individual Characteristics Affect Frailty Progression: Evidence from the China Health and Retirement Longitudinal Study

OBJECTIVES

(1) To characterize the average trajectories of frailty over time in Chinese community-dwelling older adults; (2) To assess the effects of neighborhood structural and individual characteristics on frailty progression.

DESIGN

A nationally representative prospective cohort study.

SETTING

Communities in 28 provinces, China.

PARTICIPANTS

6238 respondents aged 60 and above in 447 communities from four waves of the China Health and Retirement Longitudinal Study.

MEASUREMENTS

Frailty was measured using the 61-item Frailty Index (FI).

RESULTS

The trajectory of FI was nonlinear, with an average growth rate of 0.025 that significantly slows down at the rate of 0.002 per year. Older, male, and uninsured respondents showed faster rates of growth in FI over time than younger, female, and insured counterparts. Respondents living in neighborhoods with a higher percentage of the older population and rural villages showed slower rates of growth in FI over time.

CONCLUSION

Expanding health insurance coverage and keeping a high clustering of the elderly in neighborhoods may be the potential strategies for population-level frailty prevention and interventions.

Trajectories, Transitions, and Trends in Frailty among Older Adults: A Review

Frailty is an age-related clinical state associated with deterioration across multiple physiological systems and a leading cause of morbidity and mortality later in life. To understand how frailty develops and what causes its progression, longitudinal data with repeated frailty measurements are required. This review summarizes evidence from longitudinal studies on frailty trajectories, transitions, and trends. We identified several consistent findings: frailty increases with aging and is a dynamic condition, and more recent generations of older adults have higher frailty levels. These findings have both clinical and public health relevance, including the provision of healthcare and aged care services in the coming years. Further studies are required, particularly those conducted in low- and middle-income countries and those investigating factors associated with changes in frailty. The latter may help develop better-targeted interventions to reverse or slow the progression of frailty.

Frailty and affective disorders throughout adult life: A 5-year follow-up of the Lifelines Cohort Study

BACKGROUND

Frailty is an important concept for risk stratification in clinical practice, but it is hardly acknowledged at all in mental healthcare settings. This paper aims to assess the impact of frailty on the course of depression and anxiety, and the impact of these affective disorders on the course of frailty.

METHODS

Lifelines, a prospective population-based cohort study, evaluated 167,729 people living in the northern Netherlands. Frailty was based on the deficit accumulation model, which resulted in a 60-item frailty index (FI) at baseline and a 35-item FI at baseline and 5-year follow-up. Current depressive and anxiety disorders were assessed with the Mini International Neuropsychiatric Interview according to DSM-IV criteria. Bidirectional associations between frailty and affective disorders were investigated using separate multivariable regression analyses in younger (<60 years) and older adults (≥60 years).

RESULTS

The FI was associated with the onset of a depressive disorder (younger adults: odds ratio [OR] = 1.12; 95% confidence interval [CI] 1.11-1.13; older adults: OR = 1.13; 95% CI 1.09-1.16) as well as any anxiety disorder (younger adults: OR = 1.10; 95% CI 1.09-1.10; older adults: OR = 1.07; 95% CI 1.04-1.09). The other way around, depressive disorder and anxiety disorders were associated with an accelerated increase of frailty over time (depressive disorder: younger adults: beta [β] = 0.03, p < 0.001; older adults: β = 0.04, p < 0.001; and any anxiety disorder: younger adults: β = 0.02, p < 0.001; older adults: β = 0.01, p < 0.142), although the effect of anxiety disorders was less equivocal among older adults.

CONCLUSIONS

Affective disorders are reciprocally related to frailty. Results with respect to the impact of anxiety disorders on frailty suggest most impact at lower levels of frailty. Our results might imply that interventions to slow biological aging should be broadened towards younger and middle-aged people as well as non-frail older patients. To develop targeted treatment, future clinical and epidemiologic studies on the underlying pathways of this bidirectional association are needed.

Frailty trajectory over one year among residential aged care (nursing home) residents

Objectives

Large population-based studies examining frailty trajectory found a linear increase in frailty over time. The pattern in which frailty changes over time for an individual person is less well-described. We examined the frailty trajectory of older adults living in aged-care in Australia.

Materials and methods

This secondary study used data from a randomised controlled trial involving 39 aged-care facilities in Australia. The trial intervention was an on-going pharmacist-led intervention occurring every 8 weeks over 12 months aimed at preventing medicine-induced deterioration and adverse reactions. Frailty was assessed using the Frailty Index. Participants were categorised as non-frail, pre-frail and frail. Individual frailty trajectory over 12 months was visualised using the alluvial plot. Case notes were examined to explore reasons for any rapid transitions in frailty status.

Results

A total of 248 participants was included. At baseline, 40.3% were non-frail and 59.7% were pre-frail. The proportion of participants who were non-frail and pre-frail decreased over time; 15.7% were frail at 6 months and 23.4% were frail at 12 months. Overall, twenty different combinations of frailty transitions were identified over 12 months. Retrospective analysis of case notes suggest that death or transition from non-frail to frail was often preceded by hospitalisation, falls, medication change or clinically significant deterioration in grip strength or cognition.

Conclusion

The degree of frailty increased over time, but there were variations in the individual trajectories. Regular monitoring of events that precede changes in frailty status is needed to identify strategies to prevent further deterioration in residents’ conditions.

Association of longitudinal repeated measurements of frailty index with mortality: Cohort study among community-dwelling older adults

BACKGROUND

Frailty indices (FIs), defined by accumulation of health deficits, have been shown to be strongly related to mortality in older adults. However, previous studies mostly relied on FI measurement at a single point of time. We aimed to investigate the association of frailty with mortality according to longitudinal repeated measurements of FI in a large population-based cohort study in Germany.

METHODS

Among 9912 men and women aged 50-75 years living in Saarland, Germany and recruited in the ESTHER study in 2000-2002, a FI based on 30 deficits was determined at baseline, 2-, 5-, 8-, and 11-year follow-up. Hazard ratios (HRs) were calculated to assess the associations of FI with all-cause mortality and cause-specific mortality during 14 years of follow-up using Cox proportional hazards models that included FI as a time-varying covariate.

FINDINGS

During the 14-year follow-up, a total of 2483 deaths were observed, of which 859 and 863 were due to cancer and cardiovascular diseases (CVD), respectively. The time-varying FI showed consistently strong associations with mortality throughout 14 years of follow-up, with HRs (95% confidence intervals) for frail (FI≥ 0·35) versus non-frail (FI≤ 0·11) participants of 4·72 (4.05-5.51), 2·55 (1·95-3·34) and 7·52 (5·69-9·94) for all-cause, cancer, and CVD mortality, respectively. Gradually decreasing associations with increasing length of follow-up would have been obtained by using baseline FI only.

INTERPRETATION

Longitudinal repeated measures of FI show strong, consistent associations with mortality, especially CVD mortality, throughout extended periods of follow-up among community-dwelling older adults.

FUNDING

The ESTHER study was funded by grants from the Baden-Württemberg state Ministry of Science, Research and Arts (Stuttgart, Germany), the Federal Ministry of Education and Research (Berlin, Germany), the Federal Ministry of Family Affairs, Senior Citizens, Women and Youth (Berlin, Germany), and the Saarland State Ministry of Health, Social Affairs, Women and the Family (Saarbrücken, Germany).

Frailty, lifestyle, genetics and dementia risk

OBJECTIVE

To optimise dementia prevention strategies, we must understand the complex relationships between lifestyle behaviours, frailty and genetics.

METHODS

We explored relationships between frailty index, healthy lifestyle and polygenic risk scores (all assessed at study entry) and incident all-cause dementia as recorded on hospital admission records and death register data.

RESULTS

The analytical sample had a mean age of 64.1 years at baseline (SD=2.9) and 53% were women. Incident dementia was detected in 1762 participants (median follow-up time=8.0 years). High frailty was associated with increased dementia risk independently of genetic risk (HR 3.68, 95% CI 3.11 to 4.35). Frailty mediated 44% of the relationship between healthy lifestyle behaviours and dementia risk (indirect effect HR 0.95, 95% CI 0.95 to 0.96). Participants at high genetic risk and with high frailty had 5.8 times greater risk of incident dementia compared with those at low genetic risk and with low frailty (HR 5.81, 95% CI 4.01 to 8.42). Higher genetic risk was most influential in those with low frailty (HR 1.31, 95% CI 1.22 to 1.40) but not influential in those with high frailty (HR 1.09, 95% CI 0.92 to 1.28).

CONCLUSION

Frailty is strongly associated with dementia risk and affects the risk attributable to genetic factors. Frailty should be considered an important modifiable risk factor for dementia and a target for dementia prevention strategies, even among people at high genetic risk.

Frailty in the oldest old: is the current level or the rate of change more predictive of mortality?

BACKGROUND

It is unclear whether frailty index (FI) change captures mortality risk better than and independently of the current FI level, i.e. whether a regular FI assessment among older adults provides additional insights for mortality risk stratification or not.

METHODS

We used data from the LASA 75-PLUS-study, which monitored health among 508 older adults (75+) between 2016 and 2019 every 9 months. Joint models for longitudinal and time-to-event data were used to assess the impact of both current FI and within-person FI change during the last year on mortality risk.

RESULTS

Twenty percent of the participants died during 4.5 years of follow-up. Adding within-person FI change to the current FI model improved model fit and it showed that FI increases during the last year were associated with an increase in mortality risk. Consequently, the effect of the current FI decreased considerably and became statistically non-significant.

CONCLUSIONS

The rate of FI change was more important than the current FI level for short-term mortality prediction among the oldest old, which highlights the benefits of regular frailty assessments.

Trajectories of Frailty With Aging: Coordinated Analysis of Five Longitudinal Studies

BACKGROUND AND OBJECTIVES

There is an urgent need to better understand frailty and its predisposing factors. Although numerous cross-sectional studies have identified various risk and protective factors of frailty, there is a limited understanding of longitudinal frailty progression. Furthermore, discrepancies in the methodologies of these studies hamper comparability of results. Here, we use a coordinated analytical approach in 5 independent cohorts to evaluate longitudinal trajectories of frailty and the effect of 3 previously identified critical risk factors: sex, age, and education.

RESEARCH DESIGN AND METHODS

We derived a frailty index (FI) for 5 cohorts based on the accumulation of deficits approach. Four linear and quadratic growth curve models were fit in each cohort independently. Models were adjusted for sex/gender, age, years of education, and a sex/gender-by-age interaction term.

RESULTS

Models describing linear progression of frailty best fit the data. Annual increases in FI ranged from 0.002 in the Invecchiare in Chianti cohort to 0.009 in the Longitudinal Aging Study Amsterdam (LASA). Women had consistently higher levels of frailty than men in all cohorts, ranging from an increase in the mean FI in women from 0.014 in the Health and Retirement Study cohort to 0.046 in the LASA cohort. However, the associations between sex/gender and rate of frailty progression were mixed. There was significant heterogeneity in within-person trajectories of frailty about the mean curves.

DISCUSSION AND IMPLICATIONS

Our findings of linear longitudinal increases in frailty highlight important avenues for future research. Specifically, we encourage further research to identify potential effect modifiers or groups that would benefit from targeted or personalized interventions.

The dynamics of frailty development and progression in older adults in primary care in England (2006-2017): a retrospective cohort profile

BACKGROUND

Frailty is a common condition in older adults and has a major impact on patient outcomes and service use. Information on the prevalence in middle-aged adults and the patterns of progression of frailty at an individual and population level is scarce. To address this, a cohort was defined from a large primary care database in England to describe the epidemiology of frailty and understand the dynamics of frailty within individuals and across the population. This article describes the structure of the dataset, cohort characteristics and planned analyses.

METHODS

Retrospective cohort study using electronic health records. Participants were aged ≥50 years registered in practices contributing to the Oxford Royal College of General Practitioners Research and Surveillance Centre between 2006 to 2017. Data include GP practice details, patient sociodemographic and clinical characteristics, twice-yearly electronic Frailty Index (eFI), deaths, medication use and primary and secondary care health service use. Participants in each cohort year by age group, GP and patient characteristics at cohort entry are described.

RESULTS

The cohort includes 2,177,656 patients, contributing 15,552,946 person-years, registered at 419 primary care practices in England. The mean age was 61 years, 52.1% of the cohort was female, and 77.6% lived in urban environments. Frailty increased with age, affecting 10% of adults aged 50-64 and 43.7% of adults aged ≥65. The prevalence of long-term conditions and specific frailty deficits increased with age, as did the eFI and the severity of frailty categories.

CONCLUSION

A comprehensive understanding of frailty dynamics will inform predictions of current and future care needs to facilitate timely planning of appropriate interventions, service configurations and workforce requirements. Analysis of this large, nationally representative cohort including participants aged ≥50 will capture earlier transitions to frailty and enable a detailed understanding of progression and impact. These results will inform novel simulation models which predict future health and service needs of older people living with frailty.

STUDY REGISTRATION

Registered on www.clinicaltrials.gov October 25th 2019, NCT04139278 .

Associations between lifestyle factors and multidimensional frailty: a cross-sectional study among community-dwelling older people

BACKGROUND

Multidimensional frailty, including physical, psychological, and social components, is associated to disability, lower quality of life, increased healthcare utilization, and mortality. In order to prevent or delay frailty, more knowledge of its determinants is necessary; one of these determinants is lifestyle. The aim of this study is to determine the association between lifestyle factors smoking, alcohol use, nutrition, physical activity, and multidimensional frailty.

METHODS

This cross-sectional study was conducted in two samples comprising in total 45,336 Dutch community-dwelling individuals aged 65 years or older. These samples completed a questionnaire including questions about smoking, alcohol use, physical activity, sociodemographic factors (both samples), and nutrition (one sample). Multidimensional frailty was assessed with the Tilburg Frailty Indicator (TFI).

RESULTS

Higher alcohol consumption, physical activity, healthy nutrition, and less smoking were associated with less total, physical, psychological and social frailty after controlling for effects of other lifestyle factors and sociodemographic characteristics of the participants (age, gender, marital status, education, income). Effects of physical activity on total and physical frailty were up to considerable, whereas the effects of other lifestyle factors on frailty were small.

CONCLUSIONS

The four lifestyle factors were not only associated with physical frailty but also with psychological and social frailty. The different associations of frailty domains with lifestyle factors emphasize the importance of assessing frailty broadly and thus to pay attention to the multidimensional nature of this concept. The findings offer healthcare professionals starting points for interventions with the purpose to prevent or delay the onset of frailty, so community-dwelling older people have the possibility to aging in place accompanied by a good quality of life.

Longitudinal changes of frailty in 8 years: comparisons between physical frailty and frailty index

Background

Few studies have made longitudinal comparisons between frailty phenotype (FP) and frailty index (FI) changes. We aimed to investigate frailty status changes defined by FP and FI concurrently, and to compare the associated factors and incident disability among different combination of FI and FP trajectory groups.

Methods

Data on respondents aged over 50 who completed the 1999, 2003 and 2007 Taiwan Longitudinal Study on Aging (TLSA) surveys (n = 2807) were excerpted. Changes of FI, FP and major time-dependent variables were constructed by group-based trajectory modeling. Logistic regression was used to investigate the associated factors and relationships with incident disability among different frailty trajectories.

Results

We identified four FP trajectories – stably robust, worsened frailty, improved frailty, and stably frail and three FI trajectories – stable FI, moderate increase FI and rapid increase FI. Lower self-rated health, mobility impairment, and depressed mood were associated with unfavorable FP and FI changes (all p < 0.001). Regardless of FP trajectory groups, the moderate and rapid increase FI group had significantly more comorbidities than the stable FI group, and more visual, hearing, oral intake impairment, more difficulty in meeting living expenses, and poorer cognitive function in ≥65-year-olds (all p < 0.05). In addition, the worsened frailty, improved frailty, and stably frail groups had ORs for incident disability of 10.5, 3.0, and 13.4, respectively, compared with the stably robust group (all p < 0.01); the moderate and rapid increase FI groups had 8.4-fold and 77.5-fold higher risk than the stable FI group (both p < 0.001). When combining FI and FP trajectories, risk increased with FI trajectory steepness, independent of FP change (all p < 0.01 in rapid increase FI vs stable FI).

Conclusions

Four FP trajectories (stably robust, worsened frailty, improved frailty, and stably frail) and three FI trajectories (stable FI, moderate increase FI and rapid increase FI) were identified. Lower self-rated health, mobility impairment, and depressed mood were associated with both unfavorable FP and FI trajectories. Nevertheless, even for individuals in stably robust or improved frailty FP groups, moderate or rapid increase in FI, either due to comorbidities, sensory impairment, cognitive deficits, or financial challenges, may still increase the risk of incident disability.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-021-02665-1.

Frailty and falls in people living with multiple sclerosis

OBJECTIVE

To explore the association between frailty and history of falls in people living with multiple sclerosis (MS).

DESIGN

Secondary analysis.

SETTING

University research laboratories in the United States and Israel.

PARTICIPANTS

118 people with relapsing-remitting MS [age=48.9 years (SD=10.0); 74.6% female; expanded disability status scale (EDSS) range=1.0-6.0] were studied in this cross-sectional analysis.

INTERVENTION

Not applicable.

MAIN OUTCOMES

A frailty index was calculated from 40 health deficits by following standard validated procedures. The number of falls (12-month history) was recorded.

RESULTS

Overall, 33.9%, 29.7%, and 36.4% of participants were classified as non-frail, moderately frail, and severely frail, respectively. The frailty index was significantly correlated (ρ=0.37, p<0.001) with higher scores on the EDSS. In univariable negative binomial regression analysis, the frailty index was associated with a higher number of falls (IRR=3.33, 95%CI[1.85-5.99], p<0.001). After adjustment for age, gender and EDSS, frailty remained strongly associated with history of falls (IRR=2.78, 95%CI[1.51-5.10], p=0.001).

CONCLUSION

The current study identifies a significant relationship between frailty and history of falls in MS, independent of age, gender, and disease severity. These findings support the notion that frailty is a syndrome related to, but independent of, disability in MS.

A 6-year prospective clinical cohort study on the bidirectional association between frailty and depressive disorder

INTRODUCTION

Depressive disorder has been conceptualised as a condition of accelerated biological ageing. We operationalised a frailty index (FI) as marker for biological ageing aimed to explore the bidirectional, longitudinal association between frailty and either depressive symptoms or depressive disorder.

METHODS

A cohort study with 6-year follow-up including 377 older (≥60 years) outpatients with a DSM-IV-defined depressive disorder and 132 never-depressed controls. Site visits at baseline, 2 and 6-year follow-up were conducted and included the CIDI 2.0 to assess depressive disorder and relevant covariates. Depressive symptom severity and mortality were assessed every 6 months by mail and telephone. A 41-item FI was operationalised and validated against the 6-year morality rate by Cox regression (HR_FI  = 1.04 [95% CI: 1.02-1.06]).

RESULTS

Cox regression showed that a higher FI was associated with a lower chance of remission among depressed patients (HR_FI  = 0.98 [95% CI: 0.97-0.99]). Nonetheless, this latter effect disappeared after adjustment for baseline depressive symptom severity. Linear mixed models showed that the FI increased over time in the whole sample (B[SE] = 0.94 (0.12), p < .001) with a differential impact of depressive symptom severity and depressive disorder. Higher baseline depressive symptom severity was associated with an attenuated and depressive disorder with an accelerated increase of the FI over time.

CONCLUSIONS

The sum score of depression rating scales is likely confounded by frailty. Depressive disorder, according to DSM-IV criteria, is associated with accelerated biological ageing. This argues for the development of multidisciplinary geriatric care models incorporating frailty to improve the overall outcome of late-life depression.

Trajectories of Frailty in the 5 Years Prior to Death Among U.S. Veterans Born 1927-1934

BACKGROUND

Electronic frailty indices (eFIs) are increasingly used to identify patients at risk for morbidity and mortality. Whether eFIs capture the spectrum of frailty change, including decline, stability, and improvement, is unknown.

METHODS

In a nationwide retrospective birth cohort of U.S. Veterans, a validated eFI, including 31 health deficits, was calculated annually using medical record and insurance claims data (2002-2012). K-means clustering was used to assign patients into frailty trajectories measured 5 years prior to death.

RESULTS

There were 214 250 veterans born between 1927 and 1934 (mean [SD] age at death = 79.4 [2.8] years, 99.2% male, 90.3% White) with an annual eFI in the 5 years before death. Nine frailty trajectories were identified. Those starting at nonfrail or prefrail had 2 stable trajectories (nonfrail to prefrail, n = 29 786 and stable prefrail, n = 28 499) and 2 rapidly increasing trajectories (prefrail to moderately frail, n = 28 244 and prefrail to severely frail, n = 22 596). Those who were mildly frail at baseline included 1 gradually increasing trajectory (mildly to moderately frail, n = 33 806) and 1 rapidly increasing trajectory (mildly to severely frail, n = 15 253). Trajectories that started at moderately or severely frail included 2 gradually increasing trajectories (moderately to severely frail, n = 27 662 and progressing severely frail, n = 14 478) and 1 recovering trajectory (moderately frail to mildly frail, n = 13 926).

CONCLUSIONS

Nine frailty trajectories, including 1 recovering trajectory, were identified in this cohort of older U.S. Veterans. Future work is needed to understand whether prevention and treatment strategies can improve frailty trajectories and contribute to compression of morbidity toward the end of life.

The degree of frailty as a translational measure of health in aging

Frailty is a multiply determined, age-related state of increased risk for adverse health outcomes. We review how the degree of frailty conditions the development of late-life diseases and modifies their expression. The risks for frailty range from subcellular damage to social determinants. These risks are often synergistic-circumstances that favor damage also make repair less likely. We explore how age-related damage and decline in repair result in cellular and molecular deficits that scale up to tissue, organ and system levels, where they are jointly expressed as frailty. The degree of frailty can help to explain the distinction between carrying damage and expressing its usual clinical manifestations. Studying people-and animals-who live with frailty, including them in clinical trials and measuring the impact of the degree of frailty are ways to better understand the diseases of old age and to establish best practices for the care of older adults.

Frailty Pathogenesis, Assessment, and Management in Older Adults With COVID-19

The 2019 coronavirus disease (COVID-19) is a highly contagious and deadly disease. The elderly people are often accompanied by chronic inflammation and immunodeficiency, showing a frail state. The strength, endurance, and physiological function of the elderly are significantly decreased, and the ability to deal with stress response is weakened. They are the high-risk group that suffering from COVID-19, and rapidly developing to critical illness. Several recent studies suggest that the incidence rate of COVID-19 in elderly patients with frailty is high. Early assessment, detection, and effective intervention of frailty in COVID-19 patients are conducive to significantly improve the quality of life and improve prognosis. However, there are insufficient understanding and standards for the current evaluation methods, pathogenesis and intervention measures for COVID-19 combined with frailty. This study reviews the progress of the research on the potential pathogenesis, evaluation methods and intervention measures of the elderly COVID-19 patients with frailty, which provides a reference for scientific and reasonable comprehensive diagnosis and treatment in clinical.

SARS CoV2 infection _The longevity study perspectives

Like other infectious diseases, COVID-19 shows a clinical outcome enormously variable, ranging from asymptomatic to lethal. In Italy, like in other countries, old male individuals, with one or more comorbidity, are the most susceptible group, and show, consequently, the highest mortality, and morbidity, including lethal respiratory distress syndrome, as the most common complication. In addition, another extraordinary peculiarity, that is a surprising resistance to COVID-19, characterizes some Italian nonagenarians/centenarians. Despite having the typical COVID-19 signs and/or symptoms, such exceptional individuals show a surprising tendency to recover from illness and complications. On the other hand, long-lived people have an optimal performance of immune system related to an overexpression of anti-inflammatory variants in immune/inflammatory genes, as demonstrated by our and other groups. Consequently, we suggest long-lived people as an optimal model for detecting genetic profiles associated with the susceptibility and/or protection to COVID-19, to utilize as potential pharmacological targets for preventing or reducing viral infection in more vulnerable individuals.

Effectiveness of Community-Delivered Functional Power Training Program for Frail and Pre-frail Community-Dwelling Older Adults: a Randomized Controlled Study

Translation of community-based functional training for older adults to reduce frailty is still lacking. We evaluated the effectiveness and implementation of a community-delivered group-based functional power training (FPT) program for frail older adults within their neighborhoods. A two-arm, multicenter assessor-blind stratified randomized controlled trial was conducted at four local senior activity centers in Singapore. Sixty-one community-dwelling older adults with low handgrip strength were randomized to intervention (IG) or control (CG) group. The IG underwent the FPT program (power and balance exercises using simple equipment) delivered by a community service provider. The 12-week program comprised 2 × 60 min sessions/week. CG continued usual activities at the centers. Functional performance, muscle strength, and frailty status were assessed at baseline and 3 months. Program implementation was evaluated using RE-AIM framework. The program was halted due to Coronavirus Disease 2019-related suspension of senior center activities. Results are reported from four centers, which completed the program. IG showed significantly greater improvement in the Short Physical Performance Battery test as compared to CG (p = 0.047). No effects were found for timed up and go test performance, muscle strength, and frailty status. The community program exhibited good reach, effectiveness, adoption, and implementation. Our study demonstrated that FPT was associated with greater improvement in physical function in pre-frail/frail participants as compared to exercise activities offered at local senior activity centers. It is a feasible intervention that can be successfully implemented for frail older adults in their neighborhoods. Trial registration ClinicalTrials.gov, NCT04438876. Registered 19 June 2020-retrospectively registered.

The Development of Multidimensional Frailty Over Seven Years A longitudinal study among Dutch community-dwelling older people using the Tilburg Frailty Indicator

PURPOSE

To examine the development of multidimensional frailty, including physical, psychological and social components, over a period of seven years. To determine the effects of sociodemographic factors (gender, age, marital status, education, income) on the development of frailty.

METHODS

This longitudinal study was conducted in sample of 479 community-dwelling people aged ≥ 75 years living in the municipality of Roosendaal, the Netherlands. The Tilburg Frailty Indicator (TFI), a self-report questionnaire, was used to collect data about frailty. Frailty was assessed annually.

RESULTS

Frailty increased significantly over seven years among the people who completed the entire TFI all years (n = 121), the average score was 3.75 (SD 2.80) at baseline and 5.05 (SD 3.18) after seven years. Regarding frailty transitions, most participants remained unchanged from their baseline status. The transition from non-frail to frail was present in 8.3% to 12.6% of the participants and 5.1% to 10.7% made a transition from frail to non-frail. Gender (woman), age (≥80 years), marital status (not married/cohabiting), high level of education, and incomes from €601-€1800 were significantly associated with a higher frailty score.

CONCLUSION

This study showed that multidimensional frailty, assessed with the TFI, increased among Dutch community-dwelling people aged ≥75 years using a follow-up of seven years. Gender, age, marital status, education, and income were associated with frailty transitions. These findings provide healthcare professionals clues to identify people at increased risk of frailty, and target interventions which aim to prevent or delay frailty and its adverse outcomes, such as disability and mortality.

Factors associated with frailty transition at different follow-up intervals: A scoping review

Frailty is a dynamic process. Identifying the factors associated with frailty transition may increase the opportunities for success in interventions for frailty. This scoping review, following Arksey and O'Malley's methodological framework, aimed to identify the factors associated with frailty transition and the rate of frailty transition among community-dwelling older people. A literature search was conducted. Among the included studies, 5, 13, and 3 involved follow-up intervals of 2-3 years (short term), 4-6 years (intermediate term), and >6 years (long term), respectively. Reportedly, life course characteristics, diseases, and psychological factors were related to frailty transitions at all follow-up intervals. Physical factors were related to frailty transition at both short and intermediate follow-up intervals, while social factors were related to frailty transition at intermediate follow-up intervals. The rate of improvement in frailty seemed to decrease, and that of worsening seemed to increase when the follow-up intervals lengthened.

Exploring Clinically Meaningful Changes for the Frailty Index in a Longitudinal Cohort of Hospitalized Older Patients

BACKGROUND

Clinically meaningful change (CMC) for frailty index (FI) scores is little studied. We estimated the CMC by associating changes in FI scores with changes in the Clinical Frailty Scale (CFS) in hospitalized patients.

METHODS

The Serious Outcomes Surveillance Network of the Canadian Immunization Research Network enrolled older adults (65+ years) admitted to hospital with acute respiratory illness (mean age = 79.6 ± 8.4 years; 52.7% female). Patients were assigned CFS and 39-item FI scores in-person at admission and via telephone at 1-month postdischarge. Baseline frailty state was assessed at admission using health status 2 weeks before admission. We classified those whose CFS scores remained unchanged (n = 1,534) or increased (n = 4,390) from baseline to hospital admission, and whose CFS scores remained unchanged (n = 1,565) or decreased (n = 2,546) from admission to postdischarge. For each group, the CMC was represented as the FI score change value that best predicted one level CFS change, having the largest Youden J value in comparison to no change.

RESULTS

From baseline to admission, 74.1% increased CFS by ≥1 level. From admission to postdischarge, 61.9% decreased CFS by ≥1 levels. A change in FI score of 0.03 best predicted both one-level CFS increase (sensitivity = 70%; specificity = 69%) and decrease (sensitivity = 66%; specificity = 61%) in comparison to no change. Of those who changed CFS by ≥1 levels, 70.9% (baseline to admission) and 72.4% (admission to postdischarge) changed their FI score by at least 0.03.

CONCLUSIONS

A clinically meaningful change of 0.03 in the frailty index score holds promise as a benchmark for assessing the meaningfulness of frailty interventions.

Impact of Multidomain Lifestyle Intervention on Frailty Through the Lens of Deficit Accumulation in Adults with Type 2 Diabetes Mellitus

BACKGROUND

Type 2 diabetes and obesity increase the accumulation of health deficits and may accelerate biological aging. Multidomain lifestyle interventions may mitigate against this.

METHODS

Within a large, randomized clinical trial of intensive lifestyle intervention including caloric restriction, increased physical activity, dietary counseling, and risk factor monitoring compared with diabetes support and education, we examined the accumulation of health deficits across 8 years. We used two complementary frailty indices (FIs) based on deficit accumulation, one modeled on work in the Systolic Blood Pressure Intervention Trial and the other including additional deficits related to obesity and type 2 diabetes mellitus. Differences between intervention groups and their consistency among subgroups were assessed with re-randomization tests.

RESULTS

Data from 4,859 adults (45-76 years at baseline, 59% female) were analyzed. Random assignment to intensive lifestyle intervention was associated with lower FI scores throughout follow-up as captured by areas under curves traced by longitudinal means (p ≤ .001), over which time mean (SE) differences between intervention groups averaged 5.8% (0.9%) and 5.4% (0.9%) for the two indices. At year 8, the percentage of participants classified as frail (FI > 0.21) was lower among intensive lifestyle intervention (39.8% and 54.5%) compared with diabetes support and education (42.7% and 60.9%) for both FIs (both p < .001). Intervention benefits were relatively greater for participants who were older, not obese, and without history of cardiovascular disease at baseline.

CONCLUSIONS

Eight years of multidomain lifestyle intervention create a buffer against the accumulation of age-related health deficits in overweight or obese adults with type 2 diabetes.ClinicalTrials.gov Identifier: NCT00017953.

Drivers of Frailty from Adulthood into Old Age: Results from a 27-Year Longitudinal Population-Based Study in Sweden

BACKGROUND

Frailty is a strong predictor of adverse outcomes. However, longitudinal drivers of frailty are not well understood. This study aimed at investigating the longitudinal trajectories of a frailty index (FI) from adulthood to late life and identifying the factors associated with the level and rate of change in FI.

METHODS

An age-based latent growth curve analysis was performed in the Swedish Adoption/Twin Study of Aging (N = 1,842; aged 29-102 years) using data from up to 15 measurement waves across 27 years. A 42-item FI was used to measure frailty at each wave.

RESULTS

A bilinear, two-slope model with a turning point at age 65 best described the age-related change in FI, showing that the increase in frailty was more than twice as fast after age 65. Underweight, obesity, female sex, overweight, being separated from one's co-twin during childhood, smoking, poor social support, and low physical activity were associated with a higher FI at age 65, with underweight having the largest effect size. When tested as time-varying covariates, underweight and higher social support were associated with a steeper increase in FI before age 65, whereas overweight and obesity were associated with less steep increase in FI after age 65.

CONCLUSIONS

Factors associated with the level and rate of change in frailty are largely actionable and could provide targets for intervention. As deviations from normal weight showed the strongest associations with frailty, future public health programs could benefit from monitoring of individuals with abnormal BMI, especially those who are underweight.

A Systematic Review of Clinical Practice Guidelines for Identification and Management of Frailty

OBJECTIVE

This study aims to appraise and summarize consistent recommendations from clinical practice guidelines (CPGs) for identification and management of frailty to maintain and improve functional independence of elderly population.

METHODS

A systematic search of Ovid MEDLINE, Embase, PubMed, PsycINFO, and CINAHL electronic databases using database-specific search terms in two broad areas "guidelines" and "frailty", and a manual search of websites with the key phrase "frailty guideline" was performed. The inclusion criteria included CPGs focusing on identifying and managing frailty in population >65 years old, published in English since January 2010. Three reviewers independently assessed guideline quality using the AGREE II instrument. Data extraction was performed, followed by compilation and comparison of all recommendations to identify the key consistent recommendations.

RESULTS

Six CPGs met the inclusion criteria; however, only three CPGs had high methodological quality in accordance with AGREE II appraisal. The average AGREE II scores of all six CPGs were: 84.5%, 68%, 46.5%, 81.5%, 56.3%, and 60.2% for domains 1-6 (scope and purpose, stakeholder involvement, rigour of development, clarity of presentation, applicability, and editorial independence) respectively. A total of 54 recommendations were identified, with 12 key recommendations suggested frequently by the CPGs.

CONCLUSION

The AGREE II instrument identified strengths and weaknesses of the CPGs, but failed to assess clinical implications and feasibility of the guidelines. Further research is needed to improve clinical relevance of CPGs in the identification and management of frailty. The feasibility in implementing these guidelines with regards to cost-effectiveness of frailty screening warrants further investigation.

Cluster of factors associated with physical frailty in community-dwelling elderly people

Abstract Frailty is characterized as a set of factors related to the body structure that lead the subject to a process of physical vulnerability, increasing their dependence. The study aims to investigate the aggregation of factors related to physical frailty (PF) in elderly residents of a city with a low Human Development Index (HDI). This is a cross-sectional study carried out in the city of Ibicuí, state of Bahia, Brazil, and including a random 270 elderly people aged ≥ 60 years. The physical frailty condition was identified according to the criteria proposed by Fried and collaborators. In the data analysis, descriptive statistics, cluster analysis, and multinominal logistic regression procedures were used. The highest prevalence of aggregation was identified when the four risk factors were combined: weight loss, strength, walking speed and physical activity levels (O/E = 4.36; CI = 4.04 - 4.68). It was identified that older people (80 years old or more) with a lower level of education (unlettered) were more likely to have three or more risk factors for physical frailty (p <0.05). As for sociodemographic variables, those who were older and had lower levels of education were more likely to have three or more risk factors. The development of actions that encourage a healthier lifestyle to favor the prevention and treatment of physical frailty, as well as to increase health literacy and knowledge, may reduce the problems related to this condition in older adults, mainly thinking about the next generations.

Frailty Combined with Loneliness or Social Isolation: An Elevated Risk for Mortality in Later Life

BACKGROUND/OBJECTIVES

Frailty, loneliness, and social isolation are all associated with adverse outcomes in older adults, but little is known about their combined impact on mortality.

DESIGN

Prospective cohort study.

SETTING

The Longitudinal Aging Study Amsterdam.

PARTICIPANTS

Community-dwelling older adults aged 65 and older (n = 1,427).

MEASUREMENTS

Frailty was measured with the frailty phenotype (Fried criteria). Loneliness was assessed with the De Jong Gierveld Loneliness Scale. Social isolation was operationalized using information on partner status, social support, and network size. Two categorical variables were created, for each possible combination regarding frailty and loneliness (FL) and frailty and social isolation (FS), respectively. Mortality was monitored over a period of 22 years (1995-2017). Survival curves and Cox proportional hazard models were used to study the effects of the FL and FS combinations on mortality. Analyses were adjusted for sociodemographic factors, depression, chronic diseases, and smoking.

RESULTS

Frailty prevalence was 13%, and 5.9% of the sample were frail and lonely, and 6.2% frail and socially isolated. In fully adjusted models, older adults who were only frail had a higher risk of mortality compared with people without any of the conditions (hazard ratio [HR] range = 1.40-1.48; P < .01). However, the highest risk of mortality was observed in people with a combined presence of frailty and loneliness or social isolation (HR_FL = 1.83; 95% confidence interval [CI] = 1.42-2.37; HR_FS = 1.77; 95% CI = 1.36-2.30). Sensitivity analyses using a frailty index based on the deficit accumulation approach instead of the frailty phenotype showed similar results, confirming the robustness of our findings.

CONCLUSION

Frail older adults are at increased risk of mortality, but this risk is even higher for those who are also lonely or socially isolated. To optimize well-being and health outcomes in physically frail older adults, targeted interventions focusing on both subjective and objective social vulnerability are needed.

Comparisons Between Hypothesis- and Data-Driven Approaches for Multimorbidity Frailty Index: A Machine Learning Approach

BACKGROUND

Using big data and the theory of cumulative deficits to develop the multimorbidity frailty index (mFI) has become a widely accepted approach in public health and health care services. However, constructing the mFI using the most critical determinants and stratifying different risk groups with dose-response relationships remain major challenges in clinical practice.

OBJECTIVE

This study aimed to develop the mFI by using machine learning methods that select variables based on the optimal fitness of the model. In addition, we aimed to further establish 4 entities of risk using a machine learning approach that would achieve the best distinction between groups and demonstrate the dose-response relationship.

METHODS

In this study, we used Taiwan's National Health Insurance Research Database to develop a machine learning multimorbidity frailty index (ML-mFI) using the theory of cumulative diseases/deficits of an individual older person. Compared to the conventional mFI, in which the selection of diseases/deficits is based on expert opinion, we adopted the random forest method to select the most influential diseases/deficits that predict adverse outcomes for older people. To ensure that the survival curves showed a dose-response relationship with overlap during the follow-up, we developed the distance index and coverage index, which can be used at any time point to classify the ML-mFI of all subjects into the categories of fit, mild frailty, moderate frailty, and severe frailty. Survival analysis was conducted to evaluate the ability of the ML-mFI to predict adverse outcomes, such as unplanned hospitalizations, intensive care unit (ICU) admissions, and mortality.

RESULTS

The final ML-mFI model contained 38 diseases/deficits. Compared with conventional mFI, both indices had similar distribution patterns by age and sex; however, among people aged 65 to 69 years, the mean mFI and ML-mFI were 0.037 (SD 0.048) and 0.0070 (SD 0.0254), respectively. The difference may result from discrepancies in the diseases/deficits selected in the mFI and the ML-mFI. A total of 86,133 subjects aged 65 to 100 years were included in this study and were categorized into 4 groups according to the ML-mFI. Both the Kaplan-Meier survival curves and Cox models showed that the ML-mFI significantly predicted all outcomes of interest, including all-cause mortality, unplanned hospitalizations, and all-cause ICU admissions at 1, 5, and 8 years of follow-up (P<.01). In particular, a dose-response relationship was revealed between the 4 ML-mFI groups and adverse outcomes.

CONCLUSIONS

The ML-mFI consists of 38 diseases/deficits that can successfully stratify risk groups associated with all-cause mortality, unplanned hospitalizations, and all-cause ICU admissions in older people, which indicates that precise, patient-centered medical care can be a reality in an aging society.

A Systematic Review of Frailty Trajectories: Their Shape And Influencing Factors

BACKGROUND AND OBJECTIVES

Frailty describes an increased vulnerability to adverse events such as disease or injury. Combatting this state remains a major challenge for geriatric research. By exploring how and why frailty changes throughout later life we will be better positioned to improve ways of identifying and treating those at high risk.

RESEARCH DESIGN AND METHODS

We systematically reviewed publications that captured rate of frailty progression over time and established any associated risk or protective factors that affected this progression. We included longitudinal observational studies which quantified frailty trajectories in adults aged 50+ using any validated continuous frailty measurement tool.

RESULTS

After screening 8,318 publications, 25 met our criteria. Findings show that despite a great degree of heterogeneity in the literature, progression of frailty is unquestionably affected by numerous risk and protective factors, with particular influence exhibited by social demographics, brain pathology, and physical co-morbidities.

DISCUSSION AND IMPLICATIONS

Findings that the gradient of frailty progression is affected by various influencing factors are valuable to clinicians and policymakers as will help identify those at highest frailty risk and inform prevention strategies. However, the heterogeneous methodological approaches of the publications included in this review highlights the need for consensus within the field to promote more coordinated research. Improved consistency of methods will enable further data synthesis and facilitate a greater understanding of the shape of frailty over time and the influencing factors contributing to change, the results of which could have crucial implications for frailty risk reduction.

The times we are born into and our lifestyle choices determine our health trajectories in older age - Results from the KORA-Age study

Health projections often extrapolate from observations in current ageing cohorts, but health in older age may depend not only on individual characteristics but also on a person's historical context. Our objective was to investigate how health deficit accumulation trajectories after age 65 differed in five adjacent birth cohorts and according to individual life course characteristics. Data originate from the 2008/09 KORA (Cooperative Health Research in the Region of Augsburg)-Age cohort study from Southern Germany and their 2012 and 2016 follow-ups. Deficit accumulation was assessed using a Frailty Index. The effects of birth cohort membership and individual life course characteristics on deficit accumulation trajectories were analyzed using generalized linear mixed models. Out of 2701 participants (49% male) from five birth cohorts (1919-23, 1924-28, 1929-33, 1934-38, 1939-43), we included 2512 individuals with 5560 observations. Frailty Index levels were higher for women, smokers, alcohol abstainers, obese participants and persons with a sedentary lifestyle or living below the poverty threshold. We found higher age-specific Frailty Index levels for the two most recent birth cohorts (e.g. 61%, CI: [13%; 130%] for the 1934-38 as compared to the 1919-23 cohort), but the rate of deficit accumulation with age (7% per life year, (CI: [5%, 9%]) was cohort-independent. Results indicate that the historical context (birth cohort membership) may influence the number of accumulated health deficits after age 65 in addition to poverty and other individual life course characteristics, but BMI, physical activity and smoking remain the modifiable risk factors offering the highest prevention potential.

Operationalization of a frailty index among older adults in the InCHIANTI study: predictive ability for all-cause and cardiovascular disease mortality

Background

The frailty index (FI) is a sensitive instrument to measure the degree of frailty in older adults, and is increasingly used in cohort studies on aging.

Aims

To operationalize an FI among older adults in the “Invecchiare in Chianti” (InCHIANTI) study, and to validate its predictive capacity for mortality.

Methods

Longitudinal data were used from 1129 InCHIANTI participants aged ≥ 65 years. A 42-item FI was operationalized following a standard procedure using baseline data (1998/2000). Associations of the FI with 3- and 6-year all-cause and cardiovascular disease (CVD) mortality were studied using Cox regression. Predictive accuracy was estimated by the area under the ROC curve (AUC), for a continuous FI score and for different cut-points.

Results

The median FI was 0.13 (IQR 0.08–0.21). Scores were higher in women, and at advanced age. The FI was associated with 3- and 6-year all-cause and CVD mortality (HR range per 0.01 FI increase = 1.03–1.07, all p < 0.001). The continuous FI score predicted the mortality outcomes with moderate-to-good accuracy (AUC range 0.72–0.83). When applying FI cut-offs between 0.15 and 0.35, the accuracy of this FI for predicting mortality was moderate (AUC range 0.61–0.76). Overall, the predictive accuracy of the FI was higher in women than in men.

Conclusions

The FI operationalized in the InCHIANTI study is a good instrument to grade the risk of all-cause mortality and CVD mortality. More measurement properties, such as the responsiveness of this FI when used as outcome measure, should be investigated in future research.

Electronic supplementary material

The online version of this article (10.1007/s40520-020-01478-3) contains supplementary material, which is available to authorized users.

Age-Related Frailty: A Clinical Model for Geroscience?

In their everyday practice, geriatricians are confronted with the fact that older age and multimorbidity are associated to frailty. Indeed, if we take the example of a very old person with no diseases that progressively becomes frail with no other explanation, there is a natural temptation to link frailty to aging. On the other hand, when an old person with a medical history of diabetes, arthritis and congestive heart failure becomes frail there appears an obvious relationship between frailty and comorbidity. The unsolved question is: Considering that frailty is multifactorial and in the majority of cases comorbidity and aging are acting synergistically, can we disentangle the main contributor to the origin of frailty: disease or aging? We believe that it is important to be able to differentiate age-related frailty from frailty related to comorbidity. In fact, with the emergence of geroscience, the physiopathology, diagnosis, prognosis and treatment will probably have to be different in the future.

Frailty: implications for clinical practice and public health

Frailty is an emerging global health burden, with major implications for clinical practice and public health. The prevalence of frailty is expected to rise alongside rapid growth in the ageing population. The course of frailty is characterised by a decline in functioning across multiple physiological systems, accompanied by an increased vulnerability to stressors. Having frailty places a person at increased risk of adverse outcomes, including falls, hospitalisation, and mortality. Studies have shown a clear pattern of increased health-care costs and use associated with frailty. All older adults are at risk of developing frailty, although risk levels are substantially higher among those with comorbidities, low socioeconomic position, poor diet, and sedentary lifestyles. Lifestyle and clinical risk factors are potentially modifiable by specific interventions and preventive actions. The concept of frailty is increasingly being used in primary, acute, and specialist care. However, despite efforts over the past three decades, agreement on a standard instrument to identify frailty has not yet been achieved. In this Series paper, we provide an overview of the global impact and burden of frailty, the usefulness of the frailty concept in clinical practice, potential targets for frailty prevention, and directions that need to be explored in the future.