Reproducibility and responsiveness of the Frailty Index and Frailty Phenotype in older hospitalized patients

Frailty and loneliness among community-dwelling older adults: examining reciprocal associations within a measurement burst design

BACKGROUND

Previous research indicates that frailty and loneliness are interrelated. The aim of this study is to analyze their possible reciprocal relationship while disentangling between- and within-person effects. The separation of these sources of variance is vital for a better understanding of potential causal mechanisms.

METHODS

Within the FRequent health Assessment In Later life (FRAIL70+) project, participants aged 70 and over completed two measurement bursts spread one year apart with seven biweekly assessments each. The final sample consisted of 426 individuals at baseline (Mage=77.0; SD = 5.4; 64.6% female). A latent curve model with structured residuals was used to examine the potential reciprocal relationship between frailty (37-item deficit accumulation approach) and loneliness (3-item UCLA scale).

RESULTS

No relevant cross-lagged effects over repeated 2-week periods were found between frailty and loneliness at the within-person level, but increases in frailty co-occurred with increases in loneliness. At the between-person level, higher levels of frailty correlated with higher levels of loneliness in each burst.

CONCLUSION

The findings do not support the assumption that frailty and loneliness share a causal reciprocal relationship over weeks and months. Nonetheless, higher levels of frailty were weakly associated with higher levels of loneliness at the within- and considerably associated at the between-person level, which may indicate a common source of both domains.

Accelerometer-measured physical activity, frailty, and all-cause mortality and life expectancy among middle-aged and older adults: a UK Biobank longitudinal study

BACKGROUND

Physical activity (PA) is associated with reduced frailty and lower mortality rates among middle-aged and older adults. However, the extent to which total PA volume and specific PA intensities are associated with mortality risk across frailty status remains unclear. We aimed to investigate the interactive effects of accelerometer-measured PA with frailty on all-cause mortality and life expectancy.

METHODS

A total of 78,508 participants were sourced from the UK Biobank for analysis. Frailty index (FI) was used to assess frailty status. Physical activity and sedentary behavior were quantified through accelerometer measurements, capturing the total volume of physical activity (TVPA), moderate-to-vigorous-intensity physical activity (MVPA), light-intensity physical activity (LPA), and sedentary time (ST). Cox proportional hazard models were applied to calculate adjusted hazard ratios (HRs) and predict life expectancy.

RESULTS

During a median follow-up of 6.9 years, 2618 deaths (2.9%) were identified. Compared with robust and physically active counterparts, individuals characterized by frailty, combined with the lowest levels of TVPA (HR 3.05, 95% CI: 2.50-3.71), MVPA (HR 2.65, 95% CI: 2.19-3.21), LPA (HR 2.26; 95% CI: 1.81-2.83), or the highest level of ST (HR 2.08, 95% CI: 1.66-2.61), were found to have the greatest risk of all-cause mortality after comprehensive adjustment. The dose-response relationship, assessed using restricted cubic splines, consistently demonstrated that regardless of frailty categories, higher levels of TVPA, MVPA, and LPA were associated with lower mortality risks, while higher ST level was associated with increased risk. Notably, across the frailty spectrum, individuals in the low tertile of TVPA, MVPA, and LPA, or the top tertile of ST, were associated with reduced life expectancy, with this pattern being more pronounced among frail men compared to frail women.

CONCLUSIONS

Our findings highlighted the importance of increasing total PA volume, emphasizing MVPA and LPA, and reducing ST across the frailty spectrum to improve life expectancy.

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.

Prevalence, perceptions, and experiences of frailty among older migrants from Low- and Middle-Income Countries to High Income Countries: A mixed method systematic review

BACKGROUND

Frailty is increasingly becoming a public health concern, especially among vulnerable populations. Older migrants from Low- and Middle-Income Countries to High Income Countries present with poorer health and are at increased risk of becoming frail. This review aims to explore the prevalence, perceptions, and experiences of frailty among older migrants from Low- and Middle-Income Countries to High Income Countries.

METHODS

This review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. Five electronic databases were comprehensively searched for relevant literature published from January 1, 2000, to April 30, 2023. Quality appraisal for the quantitative studies was done with the Joanna Brigg's critical appraisal tool for analytic cross-sectional studies, and the qualitative studies were assessed with the Critical Appraisal Skill Program tool for qualitative studies.

RESULT

Seven studies met the inclusion criteria. Frailty was assessed using modified versions of the Frailty Phenotype and Frailty Index. The prevalence of frailty using the Frailty Phenotype was 16.6 %, and 17 % to 61.9 % according to the Frailty Index. The perceptions and experiences of frailty were characterised by chronic ill-health and a review of healthy pre-migration and early migration lives.

CONCLUSION

Despite the variation in frailty assessment methods, the high prevalence of frailty among older migrants was highlighted across the included studies. The perceptions and experiences of frailty reflect a state of resignation which can complicate the state of frailty. There is the need for ongoing research among migrant groups to identify their predisposition to frailty for early intervention.

Impact of Frailty on Heart Failure Prognosis: Is Sex Relevant?

PURPOSE OF REVIEW

Heart failure (HF) is one of the most frequent causes of hospital admission in elderly patients, especially in women, who present a high prevalence of geriatric syndromes like frailty. Studies have suggested that frailty and its impact may also differ between males and females. Understanding how frailty may differently affect HF patients depending on sex is therefore imperative for providing personalized care. The aim of this review is to summarize the role of sex in the prognostic impact of frailty in HF patients.

RECENT FINDINGS

Numerous studies have identified frailty as a significant predictor of all-cause mortality and hospital readmissions. A recent study of elderly HF out-patients demonstrated that while women had a higher prevalence of frailty, it was an independent predictor of mortality and readmission only in men. Moreover, another study revealed that physical frailty was associated with time to first clinical event among men but not among women. These results raise the question about why frailty affects differently HF prognosis in men and women. Women with HF present a higher prevalence of frailty, especially when it is considered as physical decline. Nevertheless, frailty affects differently HF prognosis in men and women. Women with HF present lower mortality than men and frailty is related with prognosis only in men. The different severity of HF between men and women and other hormonal, psychosocial, and clinical factors might be involved in this fact.

L-shaped association of serum α-Klotho and frailty among the middle-aged and older adults: results from NHANES 2007-2016

BACKGROUND

Frailty is common and not limited to older age group. Serum α-Klotho works as a biomarker of anti-aging effect. However, there is limited research about the relationship between them in middle-aged and older people and controversy still exists.

METHODS

Based on data from National Health and Nutrition Examination Survey (NHANES) 2007-2016, we constructed weighted logistic regression models and conducted sensitivity tests to investigate the correlation between frailty and α-Klotho among people aged 40 to 79. And then their relationship was visualized by Restricted Cubic Spline (RCS). Finally, the stratified analyses and interaction tests of covariables was presented in the forest plot.

RESULTS

A total of 7052 individuals were involved in this study, with mean age of 62.76 ± 0.18 years and females accounting for 51.05%. 2554 of them were in "frailty". After adjustment for relevant covariables, weighted logistic regression models showed that the odds ratio and 95% confidence interval [ORs (95%CI)] of correlation between frailty and Natural Logarithm(ln)-transformed α- Klotho[ln(α-Klotho)] was 0.63 (0.50, 0.79); we then performed a sensitivity analysis and found that the results remained stable. In model 3, individuals in quartiles 2, 3, and 4 showed statistical differences compared with the lowest ln(α-Klotho) quartiles, ORs (95% CI) were 0.74 (0.59, 0.93), 0.72 (0.57, 0.91), 0.71 (0.57, 0.87), respectively. Subsequently, non-linear associations were exhibited by RCS (p<0.001). The turning point for α-Klotho and ln(α-Klotho) were 785.7(pg/ml) and 6.67, respectively. Finally, analysis of the relationship between different levels of ln(α-Klotho) and frailty in different populations revealed differences between groups. The results of the interaction test showed that no other covariables had significant interaction with serum α-Klotho in our study.

CONCLUSION

The L-shaped and negative correlation was found between α-Klotho and frailty among people aged 40 to 79 in the NHANES from 2007 to 2016.

Translational research into frailty from bench to bedside: Salivary biomarkers for inflammaging

Frailty is a complex physiological syndrome associated with adverse ageing and decreased physiological reserves. Frailty leads to cognitive and physical disability and is a significant cause of morbidity, mortality and economic costs. The underlying cause of frailty is multifaceted, including immunosenescence and inflammaging, changes in microbiota and metabolic dysfunction. Currently, salivary biomarkers are used as early predictors for some clinical diseases, contributing to the effective prevention and treatment of diseases, including frailty. Sample collection for salivary analysis is non-invasive and simple, which are paramount factors for testing in the vulnerable frail population. The aim of this review is to describe the current knowledge on the association between frailty and the inflammatory process and discuss methods to identify putative biomarkers in salivary fluids to predict this syndrome. This study describes the relationship between i.-inflammatory process and frailty; ii.-infectious, chronic, skeletal, metabolic and cognitive diseases with inflammation and frailty; iii.-inflammatory biomarkers and salivary fluids. There is a limited number of previous studies focusing on the analysis of inflammatory salivary biomarkers and frailty syndrome; hence, the study of salivary fluids as a source for biomarkers is an open area of research with the potential to address the increasing demands for frailty-associated biomarkers.