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.

Latent trajectories of frailty and risk prediction models among geriatric community dwellers: an interpretable machine learning perspective.

BACKGROUND: This study aimed to identify long-term frailty trajectories among older adults (≥65) and construct interpretable prediction models to assess the risk of developing abnormal frailty trajectory among older adults and examine significant factors related to the progression of frailty. METHODS: This study retrospectively collected data from the Chinese Longitudinal Healthy Longevity and Happy Family Study between 2002 and 2018 (N = 4083). Frailty was defined by the frailty index. The whole study consisted of two phases of tasks. First, group-based trajectory modeling was used to identify frailty trajectories. Second, easy-to-access epidemiological data was utilized to construct machine learning algorithms including naïve bayes, logistic regression, decision tree, support vector machine, random forest, artificial neural network, and extreme gradient boosting to predict the risk of long-term frailty trajectories. Further, Shapley additive explanations was employed to identify feature importance and open-up the black box model of machine learning to further strengthen decision makers' trust in the model. RESULTS: Two distinct frailty trajectories (stable-growth: 82.54%, rapid-growth: 17.46%) were identified. Compared with other algorithms, random forest performed relatively better in distinguishing the stable-growth and rapid-growth groups. Physical function including activities of daily living and instrumental activities of daily living, marital status, weight, and cognitive function were top five predictors. CONCLUSIONS: Interpretable machine learning can achieve the primary goal of risk stratification and make it more transparent in individual prediction beneficial to primary screening and tailored prevention.

Patterns of Social Isolation and Low Social Support and Frailty Trajectories Among Chinese Older Adults.

Objectives: This study aims to identify patterns of social isolation and low social support, and discover their associations with frailty trajectories among Chinese older adults. Methods: The paper used five waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS, 2005-2018). The latent class analysis, multi-trajectory modeling, and the multinomial logistic regression approaches were used to perform the analysis. Results: The paper identified five types of social isolation and low social support, and three typical frailty trajectories. Patterns of social isolation and low social support were associated with frailty trajectories among older adults. Conclusions: Distinct patterns of social isolation and low social support were significantly correlated with frailty trajectories. To improve frailty trajectories among older adults, interventions such as Healthy China 2030 should prioritize addressing the interplay between social isolation and low social support.

Utility of SCORE2 risk algorithm for predicting life course accelerated frailty and physical function decline.

BACKGROUND: Frailty is a dynamic process that increases with ageing, while it remains unclear whether cardiovascular disease (CVD) risk algorithm could predict life course dynamic frailty trajectories, for example, the longitudinal patterns of how frailty evolves with time. We intended to examine the predictive utility of the Systemic Coronary Risk Estimation 2 (SCORE2) algorithm for life course accelerated frailty and physical function decline, in comparison with the precedent SCORE algorithm. METHODS: Longitudinal data regarding accumulation of deficits frailty index (FI) and physical function (grip strength, gait speed, peak expiratory flow and timed chair rises) were drawn from the English Longitudinal Study of Ageing (ELSA) and Health and Retirement Study (HRS), two nationally representative cohorts with community-dwelling adults aged ≥50 years. SCORE and SCORE2 were calculated at baselines following European Society of Cardiology guidelines. A group-based trajectory modelling approach was used for identifying potential life course frailty trajectories, based on 14- and 12-year FI data in the ELSA and HRS. Modified Poisson regression and linear mixed model were applied for analysing associations between SCORE2 with accelerated frailty trajectory and physical function decline, respectively. Receiver operating characteristic curve (ROC) analysis was conducted to evaluate predictive utility for accelerated frailty increase trajectory of SCORE and SCORE2, with the area under the curve (AUC) compared using the paired DeLong's test. RESULTS: A total of 4834 participants from the ELSA and 7815 participants from the HRS were included (mean age: 64.0 ± 9.2 and 65.4 ± 9.9 years; men: 44.3% and 41.4%, respectively). Three frailty trajectories were consistently identified in both cohorts: (1) stable frailty increase (n = 3026 in ELSA and 4004 in HRS); (2) moderate frailty increase (n = 1325 in ELSA and 2955 in HRS); (3) accelerated frailty increase (n = 483 in ELSA and 856 in HRS). Each 10% increment in SCORE2 risk was associated with the higher risk of accelerated frailty increase (risk ratio [RR]: 3.58, 95% confidence interval [CI] [3.22, 3.98], P < 0.001 in ELSA; RR: 1.61, 95% CI [1.56, 1.67], P < 0.001 in HRS) and faster declines in all physical function measurements. SCORE2 algorithm showed good accuracy for predicting accelerated frailty increase (area under the curve [AUC] in ELSA: 0.759; HRS: 0.744), with better performance than the SCORE (AUC in ELSA: 0.729; HRS: 0.700) in both cohorts (P < 0.001 for comparison). CONCLUSIONS: SCORE2 algorithm could serve good utility for predicting life course accelerated frailty increase and physical function decline among community-dwelling non-frail adults aged ≥50 years.

Mediating Effect of Physical Activity in the Association between Low 25-Hydroxyvitamin D and Frailty Trajectories: The English Longitudinal Study of Ageing.

BACKGROUND: Frailty is associated with adverse health outcomes, and vitamin D (VD) deficiency may be a risk factor. We aimed to identify frailty trajectories and examine the mediating effect of physical activity (PA) on the association between VD deficiency and frailty trajectories. METHODS: We included 2997 participants aged 60 to 85 years from ELSA. VD was measured using serum 25-hydroxyvitamin D [25(OH)D] (sufficient: >50; insufficient: 30−50; deficient: <30 nmol/L). Frailty was assessed by a 60-item frailty index, and PA was measured on the basis of total energy expenditure. Frailty trajectories were identified using group-based trajectory modeling, and the mediation effect of PA was tested using causal mediation analysis. RESULTS: Three distinct frailty trajectories emerged: "Non-frail" (66.48%), "Pre-frail to frail" (25.67%) and "Frail to severely frail" (7.85%). VD deficiency was associated with the "Pre-frail to frail" (OR = 1.51, 95% CI: 1.14, 1.98) and "Frail to severely frail" trajectories (OR = 2.29, 95% CI: 1.45, 3.62). PA only mediated 48.4% (95% CI: 17.1%−270.8%) of the association between VD deficiency and the "Pre-frail to frail" trajectory. CONCLUSIONS: Vitamin D deficiency is associated with the onset and worsening of frailty in older adults, and reduced PA may mediate its impact on the transition from pre-frailty to frailty.

Transitions Between Frailty States and Its Predictors in a Cohort of Community-Dwelling Spaniards.

OBJECTIVES: Study the frequency and determinants of frailty transitions in a community-dwelling older population. DESIGN: Population-based prospective longitudinal study [The Toledo Study of Healthy Ageing (TSHA)]. SETTING AND PARTICIPANTS: 1748 community-dwelling individuals aged >65 years living in Toledo, a Spanish province. METHODS: Frailty was measured with the Fried phenotype. Logistic models were used to assess the associations of sociodemographic, clinical, life-habits, functional, physical performance, and analytical variables with frailty transitions (losing robustness, transitioning from prefrailty to robustness, and from prefrailty to frailty) over a median of 5.2 years. RESULTS: Mean age on enrolment was 75 years, and 55.8% were females. At baseline, 10.3% were frail and 43.1% prefrail. At follow-up, 35.8% of the frail individuals recovered to a prefrail and 15.1% to a robust state. In addition, 43.7% of the prefrail participants became robust, but 14.5% developed frailty. Of those robust at baseline, 32.9% became prefrail and 4.2% frail. In multivariate logistic models, chair-stands had a predictive role in all transitions studied: linearly in keeping robustness and with a floor effect (5 stands) in transitions from prefrailty to robustness and (inversely) from prefrailty to frailty. More depressive symptoms were associated with unfavorable transitions. Not declaring the amount of alcohol drunk and low grip strength were associated with loss of robustness. Hearing and cognitive impairment, low physical activity and smoking with transitioning from prefrailty to frailty. Autonomy for instrumental activities of daily living and uricemia were associated with transitions between robustness and prefrailty in both directions. Increasing body mass index in the range of moderate to severe obesity hampered regaining robustness. CONCLUSIONS AND IMPLICATIONS: Spontaneous improvement of frailty measured with the Fried phenotype is frequent, mainly to prefrailty. Most of the variables associated with transitions are modifiable and suggest research topics and interventions to reduce frailty in clinical and social care settings.

The Prevalence of Frailty Using Three Different Frailty Measurements in Two Finnish Cohorts Born Before and After the Second World War.

OBJECTIVES: To study the prevalence of frailty and its relationship to mortality in cohorts born before and after the Second World War using three different frailty measures. METHODS: Cross-sectional data from two cohorts born in 1935 (n=593) and 1945 (n=714) were studied for frailty at the mean age of 70.7 (SD 1.8) years. Frailty was measured using the Frailty Phenotype (FP), the Frail Scale (FS) and the 74-item Frailty Index (FI>0.21 denoted frailty). Information on socioeconomic factors was obtained via a study questionnaire and the data on mortality were obtained from the Population Information System. RESULTS: The prevalence of frailty by FI was more common in the older 1935 cohort than in the 1945 cohort (p<0.001). The percentage of robust subjects was higher in both sexes in the 1945 cohort using both FI and FS. After adjusting for sociodemographic factors, the difference in the prevalence of frailty between the cohorts remained significant in women only (OR 1.9 (95% CI 1.3-2.9), p=0.001). The FI classified people as frail more often (30.2% in the 1935 cohort and 17.5% in the 1945 cohort) than the FS (13.1% and 8.8%) or FP (1.8% and 1.6%). Low financial satisfaction was associated significantly with frailty in both sexes. Low level of education was associated with frailty in women and being unmarried or divorced in men. Frailty was associated to increased mortality using all frailty definitions in the 1935 cohort with a longer follow-up time. CONCLUSIONS: Improved living conditions and health care may have resulted in the lower prevalence of frailty in the 1945 cohort. The present study further strengthens the association between frailty and mortality and poor economic status and frailty. Frailty definitions are in need of further study.