A Frailty Index for UK Biobank Participants

Proteomic aging clock (PAC) predicts age-related outcomes in middle-aged and older adults

Beyond mere prognostication, optimal biomarkers of aging provide insights into qualitative and quantitative features of biological aging and might, therefore, offer useful information for the testing and, ultimately, clinical use of gerotherapeutics. We aimed to develop a proteomic aging clock (PAC) for all-cause mortality risk as a proxy of biological age. Data were from the UK Biobank Pharma Proteomics Project, including 53,021 participants aged between 39 and 70 years and 2,923 plasma proteins assessed using the Olink Explore 3072 assay®. The Spearman correlation between PAC proteomic age and chronological age was 0.77. A total of 10.9% of the participants died during a mean follow-up of 13.3 years, with the mean age at death 70.1 years. We developed a proteomic aging clock (PAC) for all-cause mortality risk as a surrogate of BA using a combination of least absolute shrinkage and selection operator (LASSO) penalized Cox regression and Gompertz proportional hazards models. PAC showed robust age-adjusted associations and predictions for all-cause mortality and the onset of various diseases in general and disease-free participants. The proteins associated with PAC were enriched in several processes related to the hallmarks of biological aging. Our results expand previous findings by showing that age acceleration, based on PAC, strongly predicts all-cause mortality and several incident disease outcomes. Particularly, it facilitates the evaluation of risk for multiple conditions in a disease-free population, thereby, contributing to the prevention of initial diseases, which vary among individuals and may subsequently lead to additional comorbidities.

Dietary patterns, metabolomics and frailty in a large cohort of 120 000 participants

Objective: To examine the associations of dietary patterns with frailty and whether metabolic signatures (MSs) mediate these associations. Methods: We used UK Biobank data to examine (1) the associations of four dietary patterns (i.e., alternate Mediterranean diet [aMED], Recommended Food Score [RFS], Dietary Approaches to Stop Hypertension [DASH] and Mediterranean-DASH Intervention for Neurodegenerative Delay [MIND] diet) with frailty (measured by the frailty phenotype and the frailty index) using multivariable logistic regression (analytic sample 1: N = 124 261; mean age = 57.7 years), and (2) the mediating role of MSs (weighted sums of the metabolites selected from 168 plasma metabolites using the LASSO algorithm) in the above associations via mediation analysis (analytic sample 2: N = 26 270; mean age = 57.7 years). Results: Four dietary patterns were independently associated with frailty (all P < 0.001). For instance, compared to participants in the lowest tertile for RFS, those in the intermediate (odds ratio [OR]: 0.81; 95% confidence interval [CI]: 0.74, 0.89) and highest (OR: 0.62; 95% CI: 0.56, 0.68) tertiles had a lower risk of frailty. We found that 98, 68, 123 and 75 metabolites were associated with aMED, RFS, DASH and MIND, respectively, including 16 common metabolites (e.g., fatty acids, lipoproteins, acetate and glycoprotein acetyls). The MSs based on these metabolites partially mediated the association of the four dietary patterns with frailty, with the mediation proportion ranging from 26.52% to 45.83%. The results were robust when using another frailty measure, the frailty index. Conclusions: The four dietary patterns were associated with frailty, and these associations were partially mediated by MSs. Adherence to healthy dietary patterns may potentially reduce frailty development by modulating metabolites.

Association of altitude and frailty in Chinese older adults: using a cumulative frailty index model

Objective

The population is aging exponentially and the resulting frailty is becoming increasingly evident. We aimed to explore the association between altitude and frailty, and to identify associated factors for frailty.

Methods

This is a community-based cross-sectional survey. 1,298 participants aged ≥60 years from three different altitudes were included in the study. To quantify frailty, we constructed a frailty index (FI) and a frailty score (FS). The FI was divided into non-frailty, prefrailty, and frailty. The Odds Ratios and confidence intervals (ORs, 95%CIs) were used to evaluate the association between altitude and FI and FS in multivariate ordinal logistic regression and linear regression.

Results

There were 560 (53.1%) participants in the prefrailty and 488 (37.6%) in the frailty group. The FS increased with higher altitude (P for trend <0.001). Multivariate ordinal logistic regression analysis revealed an association between altitude and frailty, OR = 1.91 (95% CI: 1.38-2.64) in mid-high altitude and 2.49 (95% CI:1.40-4.45) in high altitude. The same trend of association was found in the univariate analysis. The FS increased by 1.69 (95% CI: 0.78-2.60) at mid-high altitude and 3.24 (95%CI:1.66-4.81) at high altitude compared to medium altitude.

Conclusion

The study indicates that high altitude exposure is an associated factor for frailty in older adults. This association become stronger with higher altitudes. As a result, it is essential to conduct early frailty screening for residents living at high altitudes.

Differential effects of size-specific particulate matter on frailty transitions among middle-aged and older adults in China: findings from the China Health and Retirement Longitudinal Study (CHARLS), 2015-2018

BACKGROUND

This study aimed to assess the long-term effects of size-specific particulate matter (PM) on frailty transitions in middle-aged and older Chinese adults.

METHODS

We included 13 910 participants ≥45 y of age from the China Health and Retirement Longitudinal Study (CHARLS) for 2015 and 2018 who were classified into three categories in 2015 according to their frailty states: robust, prefrail and frail. Air quality data were obtained from the National Urban Air Quality Real-time Publishing Platform. A two-level logistic regression model was used to examine the association between concentrations of PM and frailty transitions.

RESULTS

At baseline, the total number of robust, prefrail and frail participants were 7516 (54.0%), 4324 (31.1%) and 2070 (14.9%), respectively. Significant associations were found between PM concentrations and frailty transitions. For each 10 μg/m3 increase in the 3-y averaged 2.5-μm PM (PM2.5) concentrations, the risk of worsening in frailty increased in robust (odds ratio [OR] 1.06 [95% confidence interval {CI} 1.01 to 1.12]) and prefrail (OR 1.07 [95% CI 1.01 to 1.13]) participants, while the probability of improvement in frailty in prefrail (OR 0.91 [95% CI 0.84 to 0.98]) participants decreased. In addition, the associations of PM10 and coarse fraction of PM with frailty transitions showed similar patterns.

CONCLUSIONS

Long-term exposure to PM was associated with higher risks of worsening and lower risks of improvement in frailty among middle-aged and older adults in China.

Midlife cumulative deficit frailty predicts Alzheimer's disease-related plasma biomarkers in older adults

BACKGROUND

The study explores whether frailty at midlife predicts mortality and levels of biomarkers associated with Alzheimer's disease and related dementias (ADRD) and neurodegeneration by early old age. We also examine the heritability of frailty across this age period.

METHODS

Participants were 1,286 community-dwelling men from the Vietnam Era Twin Study of Aging at average ages 56, 62 and 68, all without ADRD at baseline. The cumulative deficit frailty index (FI) comprised 37 items assessing multiple physiological systems. Plasma biomarkers at age 68 included beta-amyloid (Aβ40, Aβ42), total tau (t-tau) and neurofilament light chain (NfL).

RESULTS

Being frail doubled the risk of all-cause mortality by age 68 (OR = 2.44). Age 56 FI significantly predicted age 68 NfL (P = 0.014), Aβ40 (P = 0.001) and Aβ42 (P = 0.023), but not t-tau. Age 62 FI predicted all biomarkers at age 68: NfL (P = 0.023), Aβ40 (P = 0.002), Aβ42 (P = 0.001) and t-tau (P = 0.001). Age 68 FI scores were associated with age 68 levels of NfL (P = 0.027), Aβ40 (P < 0.001), Aβ42 (P = 0.001) and t-tau (P = 0.003). Genetic influences accounted for 45-48% of the variance in frailty and significantly contributed to its stability across 11 years.

CONCLUSIONS

Frailty during one's 50s doubled the risk of mortality by age 68. A mechanism linking frailty and ADRD may be through its associations with biomarkers related to neurodegeneration. Cumulative deficit frailty increases with age but remains moderately heritable across the age range studied. With environmental factors accounting for about half of its variance, early interventions aimed at reducing frailty may help to reduce risk for ADRD.

Frailty mediating the causality between leucocyte telomere length and mortality: a cohort study of 440,551 UK Biobank participants

Introduction

Previous studies reported leucocyte telomere length (LTL) and frailty were associated with mortality, but it remains unclear whether frailty serves as a mediator in the relationship between leucocyte telomere length and mortality risk. This study aimed to evaluate how measuring LTL and frailty can support early monitoring and prevention of risk of mortality from the prospective of predictive, preventive, and personalized medicine (PPPM/3PM).

Methods

We included 440,551 participants from the UK Biobank between the baseline visit (2006-2010) and November 30, 2022. The time-dependent Cox proportional hazards model was conducted to assess the association between LTL and frailty index with the risk of mortality. Furthermore, we conducted causal mediation analyses to examine the extent to which frailty mediated the association between LTL and mortality.

Results

During a median follow-up of 13.74 years, each SD increase in LTL significantly decreased the risk of all-cause [hazard ratio (HR): 0.94, 95% confidence interval (CI): 0.93-0.95] and CVD-specific mortality (HR: 0.92, 95% CI: 0.90-0.95). The SD increase in FI elevated the risk of all-cause (HR: 1.35, 95% CI: 1.34-1.36), CVD-specific (HR: 1.47, 95% CI: 1.44-1.50), and cancer-specific mortality (HR: 1.22, 95% CI: 1.20-1.24). Frailty mediated approximately 10% of the association between LTL and all-cause and CVD-specific mortality.

Conclusions

Our results indicate that frailty mediates the effect of LTL on all-cause and CVD-specific mortality. There findings might be valuable to predict, prevent, and reduce mortality through primary prevention and healthcare in context of PPPM.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00355-7.

Inflammatory markers and frailty in home-dwelling elderly, a cross-sectional study

BACKGROUND

Low-grade, chronic inflammation during ageing, ("inflammageing"), is suggested to be involved in the development of frailty in older age. However, studies on the association between frailty, using the frailty index definition, and inflammatory markers are limited. The aim of this study was to investigate the relationship between inflammatory markers and frailty index (FI) in older, home-dwelling adults.

METHOD

Home-dwelling men and women aged ≥ 70 years old, living in South-East Norway were recruited and included in a cross-sectional study. The FI used in the current study was developed according to Rockwood's frailty index and included 38 variables, resulting in an FI score between 0 and 1 for each participant. Circulating inflammatory markers (IL-6, CRP, IGF-1, cystatin C, cathepsin S, and glycoprotein Acetyls) were analyzed from non-fasting blood samples using ELISA. Whole-genome PBMC transcriptomics was used to study the association between FI score and inflammation.

RESULTS

The study population comprised 403 elderly (52% women), with a median age of 74 years and a mean BMI of 26.2 kg/m2. The mean FI score for the total group was 0.15 (range 0.005-0.56). The group was divided into a frail group (FI score ≥ 0.25) and non-frail group. After adjusting for BMI, age, sex, and smoking in the whole group, IL-6, cathepsin S, cystatin C, and Gp-acetyls remained significant associated to FI score (IL-6: 0.002, 95% CI: 0.001, 0.002, cathepsin S: 6.7e-06, 95% CI 2.44e-06, 0.00001, cystatin C: 0.004, 95% CI: 0.002, 0.006, Gp- Acetyls: 0.09, 95% CI: 0.05, 0.13, p < 0.01 for all), while CRP and IGF-1 were not (0.0003, 95% CI: -00001, 0.0007, p = 0.13, (-1.27e-06), 95% CI: (-0.0003), 0.0003, p = 0.99). There was a significant association between FI score and inflammatory markers, and FI score and monocyte-specific gene expression.

CONCLUSIONS

We found an association between FI score and inflammatory markers, and between FI score and monocyte-specific gene expression among elderly subjects above 70 years of age. Whether inflammation is a cause or consequence of frailty and whether the progression of frailty can be attenuated by reducing inflammation remains to be clarified.

Associations of healthy aging index and all-cause and cause-specific mortality: a prospective cohort study of UK Biobank participants

The healthy aging index (HAI) has been recently developed as a surrogate measure of biological age. However, to what extent the HAI is associated with all-cause and cause-specific mortality and whether this association differs in younger and older adults remains unknown. We aimed to quantify the association between the HAI and mortality in a population of UK adults. In the prospective cohort study, data are obtained from the UK Biobank. Five HAI components (systolic blood pressure, reaction time, cystatin C, serum glucose, forced vital capacity) were scored 0 (healthiest), 1, and 2 (unhealthiest) according to sex-specific tertiles or clinically relevant cut-points and summed to construct the HAI (range 0-10). Cox proportional hazard regression models were used to estimate the associations of the HAI with the risk of all-cause and cause-specific mortality. 387,794 middle-aged and older participants were followed up for a median of 8.9 years (IQR 8.3-9.5). A total of 14,112 all-cause deaths were documented. After adjustments, each 1-point increase in the HAI was related to a higher risk of all-cause mortality (hazards ratio [HR], 1.17; 95%CI, 1.15-1.18). Such association was stronger among adults younger than 60 years (1.19, 1.17-1.21) than that among those 60 years and older (1.15, 1.14-1.17) (P interaction < 0.001). For each unit increment of the HAI, the multivariate-adjusted HRs for risk of death were 1.28 (1.25-1.31) for cardiovascular diseases, 1.09 (1.07-1.10) for cancer, 1.36 (1.29-1.44) for digestive disease, 1.42 (1.35-1.48) for respiratory disease, 1.42 (1.33-1.51) for infectious diseases, and 1.15 (1.09-1.21) for neurodegenerative disease, respectively. Our findings indicate that the HAI is positively associated with all-cause and cause-specific mortality independent of chronological age. Our results further underscore the importance of effective early-life interventions to slow aging and prevent premature death.

Assessment of relationships between frailty and chronic pain: a bidirectional two-sample Mendelian randomisation study

BACKGROUND

Previous observational studies have indicated a complex association between chronic pain and frailty. This study aimed to examine the bidirectional causal relationship between frailty and chronic pain and to quantify mediating effects of known modifiable risk factors.

METHODS

A bidirectional two-sample Mendelian randomisation (MR) analysis was applied in this study. Summary genome-wide association statistics for frailty, as defined by both frailty index (FI) and Fried Frailty Score (FFS), pain at seven site-specific chronic pain (SSCP) (headache, facial, neck/shoulder, stomach/abdominal, back, hip and knee) and multisite chronic pain (MCP) were extracted from populations of European ancestry. Genetic instrumental variables strongly correlated with each exposure were selected. The inverse-variance-weighted method was the primary method used in the MR, supplemented by a range of sensitivity and validation analyses. Two-step MR analysis was undertaken to evaluate the mediating effects of several proposed confounders.

RESULTS

Genetically predicted higher FI and FFS were associated with an increased risk of MCP and specific types of SSCP, including neck/shoulder pain, stomach/abdominal pain, back pain, hip pain and knee pain. In the reverse direction analysis, genetic liability to MCP was found to be associated with increased FI and FFS. These results remained consistent across sensitivity and validation assessments. Two-step MR suggested a mediating role for body mass index, smoking initiation, physical inactivity, educational attainment and depression.

CONCLUSIONS

Our research provided genetic evidence that the association between frailty and chronic pain was bidirectional where the coexistence of both conditions will exacerbate each other.

Association of Childhood Adversity With Frailty and the Mediating Role of Unhealthy Lifestyle: A Lifespan Analysis

OBJECTIVES

Childhood adversity and lifestyle have been associated with frailty in later life, but not much is known about factors that may explain these associations. Therefore, this study aims to investigate the association of childhood adversity with frailty, and the mediating role of unhealthy lifestyle in the association.

METHODS

This lifespan analysis included 152,914 adults aged 40-69 years old from the UK Biobank. We measured childhood adversity with five items: physical neglect, emotional neglect, sexual abuse, physical abuse, and emotional abuse through online mental health survey. Frailty was measured by the frailty index; an unhealthy lifestyle score (range: 0-5) was calculated based on unhealthy body mass index, smoking, alcohol consumption, physical inactivity, and unhealthy diet at the baseline survey. Multiple logistic regression and mediation analysis were performed.

RESULTS

A total of 10,078 participants (6.6%) were defined as having frailty. Participants with any childhood adversity had higher odds of frailty. For example, in the fully adjusted model, with a one-point increase in cumulative score of childhood adversity, the odds of frailty increased by 38% (odds ratio: 1.38; 95% Confidence Interval: 1.36, 1.40). Unhealthy lifestyle partially mediated the associations of childhood adversity with frailty (mediation proportion: 4.4%-7.0%). The mediation proportions were largest for physical (8.2%) and sexual (8.1%) abuse.

CONCLUSIONS

Childhood adversity was positively associated with frailty, and unhealthy lifestyle partially mediated the association. This newly identified pathway highlights the potential of lifestyle intervention strategies among those who experienced childhood adversity (in particular, physical, and sexual abuse) to promote healthy aging.

Genetic liability to frailty in relation to functional outcome after ischemic stroke

BACKGROUND

Frailty appears to be associated with unfavorable prognosis after stroke in observational studies, but the causality remains largely unknown.

AIMS

The aim of this study is to investigate the potential causal effect of frailty on functional outcome at 3 months after ischemic stroke using the Mendelian randomization (MR) framework.

METHODS

Genetic instruments for frailty index were identified in a genome-wide association study meta-analysis including 175,226 individuals of European descent. Corresponding genetic association estimates for functional outcome after ischemic stroke at 90 days were taken from the Genetic of Ischemic Stroke Functional Outcome (GISCOME) network of 6021 patients. We performed inverse-variance weighted MR as the main analyses, followed by several alternate methods and sensitivity analyses.

RESULTS

In univariable MR, we found evidence that genetically predicted higher frailty index (odds ratio (OR) = 5.12; 95% confidence interval (CI) = 1.31-20.09; p = 0.019) was associated with worse functional outcome (modified Rankin Scale score ⩾3) after ischemic stroke. In further multivariable MR adjusting for potential confounding traits including body mass index, C-reactive protein, inflammatory bowel disease, and smoking initiation, the overall patterns between genetic liability to frailty and poor functional outcome status remained. Sensitivity analyses with complementary methods and with model unadjusted for baseline stroke severity (OR = 4.19; 95% CI = 1.26-13.90; p = 0.019) yielded broadly concordant results.

CONCLUSIONS

The present MR study suggested a possible causal effect of frailty on poor functional outcome after ischemic stroke. Frailty might represent a potential target for intervention to improve recovery after ischemic stroke.

Obesity, birth weight, and lifestyle factors for frailty: a Mendelian randomization study

Obesity, birth weight and lifestyle factors have been found associated with the risk of frailty in observational studies, but whether these associations are causal is uncertain. We conducted a two-sample Mendelian randomization study to investigate the associations. Genetic instruments associated with the exposures at the genome-wide significance level (p < 5 × 10-8) were selected from corresponding genome-wide association studies (n = 143,677 to 703,901 individuals). Summary-level data for the frailty index were obtained from the UK Biobank (n = 164,610) and Swedish TwinGene (n = 10,616). The β of the frailty index was 0.15 (p = 3.88 × 10-9) for 1 standard deviation increase in the prevalence of smoking initiation, 0.19 (p = 3.54 × 10-15) for leisure screen time, 0.13 (p = 5.26 × 10-7) for body mass index and 0.13 (p = 1.80 × 10-4) for waist circumference. There was a suggestive association between genetically predicted higher birth weight and moderate-to-vigorous intensity physical activity with the decreased risk of the frailty index. We observed no causal association between genetically predicted age of smoking initiation and alcoholic drinks per week with the frailty index. This study supports the causal roles of smoking initiation, leisure screen time, overall obesity, and abdominal obesity in frailty. The possible association between higher birth weight, proper physical activity and a decreased risk of frailty needs further confirmation.

Associations of physical frailty with incidence and mortality of overall and site-specific cancers: A prospective cohort study from UK biobank

OBJECTIVE

Evidence regarding the role of physical frailty in cancer-related outcomes is limited. We aimed to examine the association of frailty with cancer incidence and mortality risk.

METHODS

This prospective study included 348,144 participants free of cancer at baseline from the UK Biobank. Frailty phenotypes (non-frail, pre-frail, and frail) were constructed from 5 components: weight loss, exhaustion, low physical activity, slow gait speed, and low grip strength. The outcome was incidence and mortality of overall and cite-specific cancers. Cox proportional hazard regression was used to estimate the association of frailty phenotypes with cancer incidence and mortality risk.

RESULTS

A total of 43,304 incident cancer cases and 10,152 cancer deaths were documented during a median of 12.0 years of follow-up. For overall cancer, compared with non-frailty, the incidence risk increased by 4% for pre-frailty and 11% for frailty, and the mortality risk increased by 11% for pre-frailty and 39% for frailty. Frailty phenotypes were also dose-dependently associated with a higher risk of incidence and mortality of some site-specific cancers (including liver and lung), with significant sex differences. We observed a synergetic association of frailty phenotypes and smoking with overall cancer incidence and mortality risk.

CONCLUSIONS

Frailty phenotypes contributed significantly to a higher risk of overall and some site-specific cancers incidence and mortality in a stepwise manner or within individual categories. Future studies are warranted to emphasize the identification, management and prevention of frailty in the whole population and complements of lifestyle-targeted interventions such as quitting smoking.

Frailty and Processing Speed Performance at the Cusp of Midlife in CATSLife

OBJECTIVES

Frailty is not an end state of aging, but rather represents physiological vulnerability across multiple systems that unfolds across adulthood. However, examinations of frailty at the midlife transition, and how frailty may impact other age-sensitive traits, such as processing speed (PS), remain scarce. Our research aims were to examine frailty and frailty-speed associations before midlife, a ripe developmental period for healthy aging interventions.

METHODS

Using data from the Colorado Adoption/Twin Study of Lifespan behavioral development and cognitive aging (N = 1,215; Mage = 33.23 years; standard deviation = 4.98), we constructed 25-item (FI25) and 30-item (FI30) frailty indices. PS was measured using the Colorado Perceptual Speed task and WAIS-III Digit Symbol (DS) subtest. Multilevel models accounted for clustering among siblings and adjusted for sex, race, ethnicity, adoption status, educational attainment, and age.

RESULTS

Reliability of FI measures was apparent from strong intraclass correlations (ICCs) among identical twin siblings, although ICC patterns across all siblings suggested that FI variability may include nonadditive genetic contributions. Higher FI was associated with poorer PS performance but was significant for DS only (BFI25 = -1.17, p = .001, d = -0.12; BFI30 = -1.21, p = .001, d = -0.12). Furthermore, the negative frailty-DS association was moderated by age (BFI25×age = -0.14, p = .042; BFI30×age=-0.19, p = .008) where increasingly worse performance with higher frailty emerged at older ages.

DISCUSSION

Frailty is evident before midlife and associated with poorer PS, an association that magnifies with age. These findings help elucidate the interrelationship between indicators of frailty and cognitive performance for adults approaching midlife, an understudied period within life-span development.

Frailty, an Independent Risk Factor in Progression Trajectory of Cardiometabolic Multimorbidity: A Prospective Study of UK Biobank

BACKGROUND

Although frailty was associated with cardiometabolic diseases (CMDs, including coronary heart disease, stroke, and diabetes here), there was no systematic analyses estimating its role in incidence, progression, and prognosis of cardiometabolic multimorbidity (CMM).

METHODS

We included 351 205 participants without CMDs at baseline in UK Biobank. Occurrences of first CMD, CMM, and death were recorded. We used multistate models to assess transition-specific role of baseline frailty measured by frailty phenotype and frailty index in CMM progression trajectory from no disease to single CMD, CMM, and death. Association between changes in frailty and outcomes was investigated among 17 264 participants.

RESULTS

Among 351 205 participants (44.0% male, mean age 56.55 years), 8 190 (2.3%) had frail phenotype, and 13 615 (3.9%) were moderate/severe frail according to the frailty index. During median follow-up of 13.11 years, 41 558 participants experienced ≥1 CMD, 4 952 had CMM, and 20 670 died. In multistate models, frail phenotype-related hazard ratios were 1.94 and 2.69 for transitions from no CMD to single disease and death, 1.63 and 1.67 for transitions from single CMD to CMM and death, and 1.57 for transitions from CMM to death (all p < .001). Consistent results were observed for frailty index. Improvement of frailty reduced the risk of CMD progression and death.

CONCLUSIONS

Frailty is an independent risk factor for all transitions of CMM progression trajectory. Frailty-targeted management is a potential strategy for primary and secondary prevention of CMM beyond chronological age.

Frailty Among Sexual and Gender Minority Older Adults: The All of Us Database

BACKGROUND

Despite known disparities in health status among older sexual and gender minority adults (OSGM), the prevalence of frailty is unknown. The aim of this study was to develop and validate a deficit-accumulation frailty index (AoU-FI) for the All of Us database to describe and compare frailty between OSGM and non-OSGM participants.

METHODS

Developed using a standardized approach, the AoU-FI consists of 33 deficits from baseline survey responses of adults aged 50+. OSGM were self-reported as "not straight" or as having discordant gender and sex assigned at birth. Descriptive statistics characterized the AoU-FI. Regression was used to assess the association between frailty, age, and gender. Validation of the AoU-FI used Cox proportional hazard models to test the association between frailty categories (robust <0.15, 0.15 ≤ pre-frail ≤ 0.25, frail >0.25) and mortality.

RESULTS

There were 9 110 OSGM and 67 420 non-OSGM with sufficient data to calculate AoU-FI; 41% OSGM versus 50% non-OSGM were robust, whereas 34% versus 32% were pre-frail, and 26% versus 19% were frail. Mean AoU-FI was 0.19 (95% confidence interval [CI]: 0.187, 0.191) for OSGM and 0.168 (95% CI: 0.167, 0.169) for non-OSGM. Compared to robust, odds of mortality were higher among frail OSGM (odds ratio [OR] 6.40; 95% CI: 1.84, 22.23) and non-OSGM (OR 3.96; 95% CI: 2.96, 5.29).

CONCLUSIONS

The AoU-FI identified a higher burden of frailty, increased risk of mortality, and an attenuated impact of age on frailty among OSGM compared to non-OSGM. Future work is needed to understand how frailty affects the OSGM population.

Prevalence of frailty in severe mental illness: findings from the UK Biobank

BACKGROUND

Severe mental illness (SMI) is associated with significant morbidity. Frailty combines biological ageing, comorbidity and psychosocial factors and can predict adverse health outcomes. Emerging evidence indicates that frailty is higher in individuals with SMI than in the general population, although studies have been limited by sample size.

AIMS

To describe the prevalence of frailty in people with SMI in a large cohort using three different frailty measures and examine the impact of demographic and sociodemographic variables.

METHOD

The UK Biobank survey data, which included individuals aged 37-73 years from England, Scotland and Wales from 2006 to 2010, with linked in-patient hospital episodes, were utilised. The prevalence of frailty in individuals with and without SMI was assessed through three frailty measures: frailty index, physical frailty phenotype (PFP) and Hospital Frailty Risk Score (HFRS). Stratified analysis and dichotomous logistic regression were conducted.

RESULTS

A frailty index could be calculated for 99.5% of the 502 412 UK Biobank participants and demonstrated greater prevalence of frailty in women and an increase with age. The prevalence of frailty for those with SMI was 3.19% (95% CI 3.0-3.4), 4.2% (95% CI 3.8-4.7) and 18% (95% CI 15-23) using the frailty index, PFP and HFRS respectively. The prevalence ratio was between 3 and 18 times higher than in those without SMI.

CONCLUSIONS

As a measure, frailty captures the known increase in morbidity associated with SMI and may potentially allow for earlier identification of those who will benefit from targeted interventions.

Is Frailty Different in Younger Adults Compared to Old? Prevalence, Characteristics, and Risk Factors of Early-Life and Late-Life Frailty in Samples from Sweden and UK

INTRODUCTION

Although frailty is commonly considered as a syndrome of old individuals, recent studies show that it can affect younger adults, too. Whether and how frailty differs in younger adults compared to old is however unknown. To this end, we analyzed the prevalence, characteristics, and risk factors of early-life (aged <65) and late-life (aged ≥65) frailty.

METHODS

We analyzed individuals in the UK Biobank (N = 405,123) and Swedish Screening Across the Lifespan Twin (SALT; N = 43,641) study. Frailty index (FI) scores ≥0.21 were used to demarcate frailty. Characteristics of early-life versus late-life frailty were analyzed by collating the FI items (deficits) into domains and comparing the domain scores between younger and older frail individuals. Logistic regression was used to assess the risk factors of frailty.

RESULTS

The pooled prevalence rates of frailty were 10.3% (95% confidence interval [CI]: 2.7-32.7), 14.4% (95% CI: 4.5-37.2), 19.2% (95% CI: 2.5-68.5) in individuals aged ≤55, 55-64, 65-74, respectively. Younger frail adults (aged <65) had higher scores in immunological, mental wellbeing, and pain-related domains, whereas older frail adults (aged ≥65) had higher scores in cardiometabolic, cancer, musculoskeletal, and sensory-related domains. Higher age, female sex, smoking, lower alcohol consumption, lower education, obesity, overweight, low income, and maternal smoking were similarly associated with the risk of early-life and late-life frailty.

CONCLUSION

Frailty is prevalent also in younger age groups (aged <65) but differs in some of its characteristics from the old. The risk factors of frailty are nevertheless largely similar for early-life and late-life frailty.

Unraveling the metabolic underpinnings of frailty using multicohort observational and Mendelian randomization analyses

Identifying metabolic biomarkers of frailty, an age-related state of physiological decline, is important for understanding its metabolic underpinnings and developing preventive strategies. Here, we systematically examined 168 nuclear magnetic resonance-based metabolomic biomarkers and 32 clinical biomarkers for their associations with frailty. In up to 90,573 UK Biobank participants, we identified 59 biomarkers robustly and independently associated with the frailty index (FI). Of these, 34 associations were replicated in the Swedish TwinGene study (n = 11,025) and the Finnish Health 2000 Survey (n = 6073). Using two-sample Mendelian randomization, we showed that the genetically predicted level of glycoprotein acetyls, an inflammatory marker, was statistically significantly associated with an increased FI (β per SD increase = 0.37%, 95% confidence interval: 0.12-0.61). Creatinine and several lipoprotein lipids were also associated with increased FI, yet their effects were mostly driven by kidney and cardiometabolic diseases, respectively. Our findings provide new insights into the causal effects of metabolites on frailty and highlight the role of chronic inflammation underlying frailty development.

The role of lifestyle in the association between frailty and all-cause mortality amongst older adults: a mediation analysis in the UK Biobank

OBJECTIVE

frailty is a syndrome characterised by increased vulnerability to stressors, which manifests as higher death risk. Whilst guidelines for frailty management usually entails lifestyle modifications (e.g. physical exercise, diet), the mediating role of lifestyle on the excess mortality associated with frailty is unclear. This study estimates the death risk due to frailty that could be avoided with a healthy lifestyle in older adults.

SUBJECTS AND METHODS

we analysed data from 91,906 British individuals aged ≥60 years recruited between 2006 and 2010. At baseline, frailty was identified according to Fried's phenotype, and a four-item Healthy Lifestyle Index (HLS) was calculated based on physical activity, diet, smoking and alcohol consumption. Mortality was ascertained from baseline through 2021. A mediation analysis under the counterfactual framework was performed adjusting for the main confounders.

RESULTS

during a median follow-up of 12.5 years, 9,383 deaths occurred. Frailty was directly associated with all-cause mortality (hazard ratio: 2.30 [95% confidence interval {CI} 2.07, 2.54]), and inversely associated with the HLS (ß: -0.45 points [-0.49, -0.40]). The hazard ratio [95%CI] for the direct effect of frailty on mortality was 2.12 [1.91, 2.34], whilst for the indirect effect (mediated by HLS) was 1.08 [1.07, 1.10]. The mediated proportion of HLS on mortality was 13.55% [11.26, 16.20], with physical activity having the highest proportion amongst the four HLS items (7.69% [5.00, 10.40]).

CONCLUSIONS

a healthy lifestyle partly mediates the association between frailty and mortality in British older adults. Since this was an exploratory mediation analysis, these results should be specifically tested in future research.

Midlife Life's Simple 7, Psychosocial Health, and Physical Frailty, Hospital Frailty, and Comprehensive Frailty 10 Years Later

This study aims to examine the associations between midlife Life's Simple 7 (LS7) status, psychosocial health (social isolation and loneliness), and late-life multidimensional frailty indicators, and to investigate their synergistic effect on frailty. We used cohort data from the UK Biobank. Frailty was assessed using physical frailty phenotype, hospital frailty risk score, and frailty index. Cox proportional-hazards models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) on the association between the LS7 score, psychosocial health, and frailty. For the association of LS7 with physical and comprehensive frailty, 39,047 individuals were included. After a median follow-up of 9.0 years, 1329 (3.4%) people were identified with physical frailty, and 5699 (14.6%) with comprehensive frailty. For the association of LS7 with hospital frailty, 366,570 people were included. After a median follow-up of 12.0 years, 18,737 (5.1%) people were identified with hospital frailty. Compared to people with a poor LS7 score, those with an intermediate (physical frailty: 0.64, 0.54-0.77; hospital frailty: 0.60, 0.58-0.62; and comprehensive frailty: 0.77, 0.69-0.86) and optimal LS7 score (physical frailty: 0.31, 0.25-0.39; hospital frailty: 0.39, 0.37-0.41; and comprehensive frailty: 0.62, 0.55-0.69) were associated with a lower risk of frailty. Poor psychosocial health was associated with an increased risk of frailty. People who had a poor psychosocial status and poor LS7 score had the highest risk of frailty. A better LS7 score in midlife was associated with a reduced risk of physical, hospital, and comprehensive frailty. There was a synergistic effect of psychosocial status and LS7 on frailty.

Frailty and all-cause and cause-specific mortality in Japan

BACKGROUND

In aging societies, there is an increasing focus on the concept of frailty. However, there is no consistent means to assess this concept. We assessed frailty using the Kihon Checklist (KCL), which is widely used in Japan, and examined the association between frailty and all-cause and cause-specific mortality in Japan, the most aged society in the world.

METHODS

This was a retrospective cohort study, and we analyzed 43,312 participants aged ≥ 65 years who were enrolled in basic health checkups in Okayama City, Japan. We defined the frailty status of the participants using the KCL. To assess the association of frailty status with all-cause and cause-specific mortality, we used cause-specific Cox proportional hazard models to estimate hazard ratios (HRs), adjusting for individual potential confounders. Mean follow-up time was 9.3 years.

RESULTS

The fully adjusted HR for all-cause mortality was 1.34 (95% confidence interval [CI]: 1.27-1.41) for the prefrail group and 2.22 (95% CI: 2.11-2.33) for the frail group. A similar pattern was observed for cardiovascular disease, respiratory disease, and cancer mortality. Younger people (65-74 years) and women tended to have higher effect estimates than older people (≥ 75 years) and men.

CONCLUSION

Prefrailty and frailty can increase the risk of both all-cause and cause-specific mortality. Our study suggests that to support frail patients, it could be effective to focus on the prevention and management of cardiovascular and respiratory disease, and that the KCL may be useful as a method of screening for frailty.

Can frailty scores predict the incidence of cancer? Results from two large population-based studies

While chronological age is the single biggest risk factor for cancer, it is less clear whether frailty, an age-related state of physiological decline, may also predict cancer incidence. We assessed the associations of frailty index (FI) and frailty phenotype (FP) scores with the incidence of any cancer and five common cancers (breast, prostate, lung, colorectal, melanoma) in 453,144 UK Biobank (UKB) and 36,888 Screening Across the Lifespan Twin study (SALT) participants, who aged 38-73 years and had no cancer diagnosis at baseline. During a median follow-up of 10.9 and 10.7 years, 53,049 (11.7%) and 4,362 (11.8%) incident cancers were documented in UKB and SALT, respectively. Using multivariable-adjusted Cox models, we found a higher risk of any cancer in frail vs. non-frail UKB participants, when defined by both FI (hazard ratio [HR] = 1.22; 95% confidence interval [CI] = 1.17-1.28) and FP (HR = 1.16; 95% CI = 1.11-1.21). The FI in SALT similarly predicted risk of any cancer (HR = 1.31; 95% CI = 1.15-1.49). Moreover, frailty was predictive of lung cancer in UKB, although this association was not observed in SALT. Adding frailty scores to models including age, sex, and traditional cancer risk factors resulted in little improvement in C-statistics for most cancers. In a within-twin-pair analysis in SALT, the association between FI and any cancer was attenuated within monozygotic but not dizygotic twins, indicating that it may partly be explained by genetic factors. Our findings suggest that frailty scores are associated with the incidence of any cancer and lung cancer, although their clinical utility for predicting cancers may be limited.

Education mediating the associations between early life factors and frailty: a cross-sectional study of the UK Biobank

OBJECTIVES

Exposures in utero and during infancy may impact the development of diseases later in life. They may be linked with development of frailty, although the mechanism is unclear. This study aims to determine the associations between early life risk factors and development of frailty among middle-aged and older adults as well as potential pathways via education, for any observed association.

DESIGN

A cross-sectional study.

SETTINGS

This study used data from UK Biobank, a large population-based cohort.

PARTICIPANTS

502 489 individuals aged 37-73 years were included in the analysis.

PRIMARY AND SECONDARY OUTCOME MEASURES

Early life factors in this study included being breast fed as a baby, maternal smoking, birth weight, the presence of perinatal diseases, birth month and birth place (in or outside the UK). We developed a frailty index comprising 49 deficits. We used generalised structural equation modelling to examine the associations between early life factors and development of frailty and whether any observed association was mediated via educational attainment.

RESULTS

A history of breast feeding and normal birth weight were associated with a lower frailty index while maternal smoking, the occurrence of perinatal diseases and birth month with a longer day length were associated with a higher frailty index. Educational level mediated the relationship between these early life factors and frailty index.

CONCLUSIONS

This study highlights that biological and social risk occurring at different stages of life are related to the variations in frailty index in later life and suggests opportunities for prevention across the life course.

Association of frailty with the incidence risk of cardiovascular disease and type 2 diabetes mellitus in long-term cancer survivors: a prospective cohort study

BACKGROUND

Comorbidities among cancer survivors remain a serious healthcare burden and require appropriate management. Using two widely used frailty indicators, this study aimed to evaluate whether frailty was associated with the incidence risk of cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM) among long-term cancer survivors.

METHODS

We included 13,388 long-term cancer survivors (diagnosed with cancer over 5 years before enrolment) free of CVD and 6101 long-term cancer survivors free of T2DM, at the time of recruitment (aged 40-69 years), from the UK Biobank. Frailty was assessed by the frailty phenotype (FP_Frailty, range: 0-5) and the frailty index (FI_Frailty, range: 0-1) at baseline. The incident CVD and T2DM were ascertained through linked hospital data and primary care data, respectively. The associations were examined using Cox proportional hazards regression models.

RESULTS

Compared with non-frail participants, those with pre-frailty (FP_Frailty [met 1-2 of the components]: hazard ratio [HR]=1.18, 95% confidence interval [CI]: 1.05, 1.32; FI_Frailty [0.10< FI ≤0.21]: HR=1.51, 95% CI: 1.32, 1.74) and frailty (FP_Frailty [met ≥3 of the components]: HR=2.12, 95% CI: 1.73, 2.60; FI_Frailty [FI >0.21]: HR=2.19, 95% CI: 1.85, 2.59) had a significantly higher risk of CVD in the multivariable-adjusted model. A similar association of FI_Frailty with the risk of incident T2DM was observed. We failed to find such an association for FP_Frailty. Notably, the very early stage of frailty (1 for FP_Frailty and 0.1-0.2 for FI_Frailty) was also positively associated with the risk of CVD and T2DM (FI_Frailty only). A series of sensitivity analyses confirmed the robustness of the findings.

CONCLUSIONS

Frailty, even in the very early stage, was positively associated with the incidence risk of CVD and T2DM among long-term cancer survivors, although discrepancies existed between frailty indicators. While the validation of these findings is required, they suggest that routine monitoring, prevention, and interventive programs of frailty among cancer survivors may help to prevent late comorbidities and, eventually, improve their quality of life. Especially, interventions are recommended to target those at an early stage of frailty when healthcare resources are limited.

Association of childhood adversity with frailty and the mediating role of unhealthy lifestyle: Findings from the UK biobank

Background

Childhood adversity and lifestyle have been associated with frailty in later life, but not much is known about factors that may explain these associations. An unhealthy lifestyle may play an important role in the pathway from childhood adversity to frailty. Therefore, this study aims to investigate the association of childhood adversity with frailty, and the mediating role of unhealthy lifestyle in the association.

Methods

This lifespan analysis included 152914 adults aged 40-69 years old from the UK Biobank. We measured childhood adversity with five items: physical neglect, emotional neglect, sexual abuse, physical abuse, and emotional abuse through online mental health survey. Frailty was measured by the frailty index; an unhealthy lifestyle score (range: 0-5) was calculated based on unhealthy body mass index, smoking, drinking, physical inactivity, and unhealthy diet at the baseline survey. Multiple logistic regression and mediation analysis were performed.

Results

A total of 10078 participants (6.6%) were defined as having frailty. Participants with any childhood adversity had higher odds of frailty. For example, in the fully adjusted model, with a one-point increase in cumulative score of childhood adversity, the odds of frailty increased by 41% (Odds Ratio: 1.41; 95% Confidence Interval: 1.39, 1.44). Unhealthy lifestyle partially mediated the associations of childhood adversity with frailty (mediation proportion: 4.4%-7.0%). The mediation proportions were largest for physical (8.2%) and sexual (8.1%) abuse.

Conclusions

Among this large sample, childhood adversity was positively associated with frailty, and unhealthy lifestyle partially mediated the association. This newly identified pathway highlights the potential of lifestyle intervention strategies among those who experienced childhood adversity (in particular, physical and sexual abuse) to promote healthy aging.

Smoking, alcohol consumption, and frailty: A Mendelian randomization study

Background: Tobacco smoking and alcohol consumption have been associated with frailty in observational studies. We sought to examine whether these associations reflect causality using the two-sample Mendelian randomization (MR) design. Methods: We used summary genome-wide association statistics for smoking initiation (N = 2,669,029), alcohol consumption (N = 2,428,851), and the frailty index (FI, N = 175,226) in participants of European ancestry. Both univariable and multivariable MR were performed to comprehensively evaluate the independent effects of smoking and alcohol consumption on the FI, accompanied by multiple sensitivity analyses. Results were verified using lifetime smoking and alcohol use disorder. Reverse direction MR was undertaken to assess the potential for reverse causation. Results: Genetic predisposition to smoking initiation was significantly associated with increased FI (univariable MR: β = 0.345; 95% confidence interval [CI] = 0.316 to 0.374; p = 1.36E-113; multivariable MR: β = 0.219; 95% CI = 0.197 to 0.241; p = 2.44E-83). Genetically predicted alcohol consumption showed a suggestive association with the FI (univariable MR: β = -0.090; 95% CI = -0.151 to -0.029; p = 0.003; multivariable MR β = -0.153; 95% CI = -0.212 to -0.094; p = 2.03E-07), with inconsistent results in sensitivity analyses. In complementary analysis, genetic predicted lifetime smoking, but not alcohol use disorder was associated with the FI. There is no convincing evidence for reverse causation. Conclusion: The present MR study supported smoking as a causal risk factor of frailty. Further research is warranted to investigate whether alcohol consumption has a causal role in frailty.

The increased medical burden associated with frailty is partly attributable to household solid fuel: A nationwide prospective study of middle-aged and older people in China

BACKGROUND

Frail individuals often face a high medical burden, and household solid fuel use is associated with a range of functional declines or diseases, but evidence on the relationship between household solid fuel and frailty and the resulting medical burden is limited. We aim to investigate the effect of household solid fuel on frailty and further quantify how much of the increased medical burden associated with frailty is attributable to household solid fuel.

METHODS

The prospective data were from the China Health and Retirement Longitudinal Study, 4685 non-frail participants at baseline were included. Inverse probability weighting was used to balance the covariates between groups. The modified Poisson regression was used to analyze the association of household solid fuel (including baseline and switching across three-wave survey) with frailty, and the generalized linear model was used to analyze the association of frailty with the change in medical burden. Further, the increased medical burden associated with frailty attributable to household solid fuel was quantified.

RESULTS

Using solid fuel for cooking (RR = 1.29, 95%CI, 1.07-1.57), heating (RR = 1.38, 95%CI, 1.09-1.73), or both (RR = 1.40, 95%CI, 1.05-1.86) had a higher risk of frailty than using clean fuel. In addition, the risk of frailty generally increases with the times of solid fuel use across the three-wave survey. Then, frailty participants had a greater increase in the annual number of hospitalizations (β = 0.11, 95%CI, 0.02-0.19) and annual costs of hospitalizations (β = 2953.35, 95%CI, 1149.87-4756.83) than those non-frailty. Heating coal caused the largest frailty-related increase in the annual number of hospitalizations and annual costs of hospitalizations, with 0.04 and 1195.40, respectively.

CONCLUSION

The increased medical burden associated with frailty was partly attributable to household solid fuel, which suggested that intervention targeting household solid fuels can delay frailty and thus reduce individual medical burden.

Prevalence and association of frailty with SARS-CoV-2 infection in older adults in Southern Switzerland-Findings from the Corona Immunitas Ticino Study

BACKGROUND

Frailty is an age-associated state of increased vulnerability to stressors that strongly predicts poor health outcomes. Epidemiological evidence on frailty is limited during the COVID-19 pandemic, and whether frailty is associated with the risk of infection is unknown.

OBJECTIVES

We derived a robust Frailty Index (FI) to measure the prevalence of frailty and its risk factors in community-dwelling older adults in Southern Switzerland (Ticino), and we explored the association between frailty and serologically confirmed SARS-CoV-2 infection.

METHODS

In September 2020, we recruited a random sample of community-dwelling older adults (65 +) in the Corona Immunitas Ticino prospective cohort study (CIT) and assessed a variety of lifestyle and health characteristics. We selected 30 health-related variables, computed the Rockwood FI, and applied standard thresholds for robust (FI < 0.1), pre-frail (0.1 ≤ FI < 0.21), and frail (FI ≥ 0.21).

RESULTS

Complete data for the FI was available for 660 older adults. The FI score ranged between zero (no frailty) and 0.59. The prevalence of frailty and pre-frailty were 10.3% and 48.2% respectively. The log-transformed FI score increased by age similarly in males and females, on average by 2.8% (p < 0.001) per one-year increase in age. Out of 481 participants with a valid serological test, 11.2% were seropositive to either anti-SARS-CoV-2 IgA or IgG. The frailty status and seropositivity were not statistically associated (p = 0.236).

CONCLUSION

Advanced age increases the risk of frailty. The risk of COVID-19 infection in older adults may not differ by frailty status.

Lithium treatment extends human lifespan: findings from the UK Biobank

Lithium is a nutritional trace element that is also used pharmacologically for the management of bipolar and related psychiatric disorders. Recent studies have shown that lithium supplementation can extend health and lifespan in different animal models. Moreover, nutritional lithium uptake from drinking water was repeatedly found to be positively correlated with human longevity. By analyzing a large observational aging cohort (UK Biobank, n = 501,461 individuals) along with prescription data derived from the National Health Services (NHS), we here find therapeutic supplementation of lithium linked to decreased mortality (p = 0.0017) of individuals diagnosed with affective disorders. Subsequent multivariate survival analyses reveal lithium to be the strongest factor in regards to increased survival effects (hazard ratio = 0.274 [0.119-0.634 CI 95%, p = 0.0023]), corresponding to 3.641 times lower (95% CI 1.577-8.407) chances of dying at a given age for lithium users compared to users of other anti-psychotic drugs. While these results may further support the use of lithium as a geroprotective supplement, it should be noted that doses applied within the UK Biobank/NHS setting require close supervision by qualified medical professionals.

Frailty Index as a Predictor of Mortality in Middle-Aged and Older People: A Prospective Analysis of Chilean Adults

We aimed to investigate the association between frailty status and all-cause mortality in middle-aged and older people. We included 2661 individuals aged ≥ 35 from the Chilean National Health Survey 2009−2010. Mortality was determined through linkage with the Chilean Civil Registry and Identification. A 36-item frailty index (FI) was used to assess the frailty status. Associations between frailty status and all-cause mortality were assessed using Kaplan−Meier and Cox proportional hazard models adjusted for sociodemographic and lifestyle factors. A non-linear association was investigated using penalized cubic splines fitted in the Cox models. During an 8.9 median follow-up (interquartile range of 8.6−9.0), 308 individuals died (11.5%). Lower survival rates were observed in frail individuals compared to pre-frail and robust people (log-rank < 0.001). Compared with robust individuals, frail people had a higher mortality risk (HR: 2.35 [95% CI: 1.57 to 3.51]). Frail middle-aged individuals had a higher risk of dying independently of major risk factors.

Increased Frailty in Individuals With Osteoarthritis and Rheumatoid Arthritis and the Influence of Comorbidity: An Analysis of the UK Biobank Cohort

OBJECTIVE

To determine the association between osteoarthritis (OA), rheumatoid arthritis (RA), and frailty and to determine whether comorbidities interact with OA and RA to further increase the likelihood of frailty.

METHODS

Participants of the UK Biobank age 40-69 years at baseline were included. Demographic, lifestyle, and clinical data were collected at baseline and follow-up in a subset. Frailty was assessed using a frailty index (FI) (continuous) and a modified frailty phenotype (robust, pre-frail, frail). The association between RA and OA and frailty at baseline and follow-up was assessed using multiple regression models. We looked at whether comorbidities, including cardiovascular disease, diabetes mellitus, chronic obstructive pulmonary disease, and depression interacted additively with OA and RA to increase the likelihood of frailty.

RESULTS

In total, 457,561 participants contributed data. Those with (versus without) RA (n = 4,894) and OA (n = 35,884), respectively, were more likely to be frail (adjusted relative risk ratio 10.7 [95% confidence interval (95% CI) 9.7, 11.7] and 3.4 [95% CI 3.3, 3.6]) and were more likely to have a higher FI at baseline. There was evidence of additive interaction between RA, OA, and common comorbidities increasing the occurrence of prevalent frailty. Among 25,163 participants included in longitudinal analysis, patients with RA (n = 202) and OA (n = 1,811) at baseline had an increased adjusted frailty incidence rate ratio (2.8 [95% CI 1.7, 4.6] and 1.7 [95% CI 1.3, 2.1], respectively) and also a higher FI during follow-up.

CONCLUSION

Individuals with RA and OA are more likely to have, or develop, frailty. Common comorbidities interact with OA and RA to further increase the likelihood of frailty.

Efficacy and Safety of Dapagliflozin According to Frailty in Patients With Heart Failure: A Prespecified Analysis of the DELIVER Trial

BACKGROUND

Frailty is increasing in prevalence. Because patients with frailty are often perceived to have a less favorable risk/benefit profile, they may be less likely to receive new pharmacologic treatments. We investigated the efficacy and tolerability of dapagliflozin according to frailty status in patients with heart failure with mildly reduced or preserved ejection fraction randomized in DELIVER (Dapagliflozin Evaluation to Improve the Lives of Patients With Preserved Ejection Fraction Heart Failure).

METHODS

Frailty was measured using the Rockwood cumulative deficit approach. The primary end point was time to a first worsening heart failure event or cardiovascular death.

RESULTS

Of the 6263 patients randomized, a frailty index (FI) was calculable in 6258. In total, 2354 (37.6%) patients had class 1 frailty (FI ≤0.210; ie, not frail), 2413 (38.6%) had class 2 frailty (FI 0.211-0.310; ie, more frail), and 1491 (23.8%) had class 3 frailty (FI ≥0.311; ie, most frail). Greater frailty was associated with a higher rate of the primary end point (per 100 person-years): FI class 1, 6.3 (95% CI 5.7-7.1); class 2, 8.3 (7.5-9.1); and class 3, 13.4 (12.1-14.7; P<0.001). The effect of dapagliflozin (as a hazard ratio) on the primary end point from FI class 1 to 3 was 0.85 (95% CI, 0.68-1.06), 0.89 (0.74-1.08), and 0.74 (0.61-0.91), respectively (Pinteraction=0.40). Although patients with a greater degree of frailty had worse Kansas City Cardiomyopathy Questionnaire scores at baseline, their improvement with dapagliflozin was greater than it was in patients with less frailty: placebo-corrected improvement in Kansas City Cardiomyopathy Questionnaire Overall Summary Score at 4 months in FI class 1 was 0.3 (95% CI, -0.9 to 1.4); in class 2, 1.5 (0.3-2.7); and in class 3, 3.4 (1.7-5.1; Pinteraction=0.021). Adverse reactions and treatment discontinuation, although more frequent in patients with a greater degree of frailty, were not more common with dapagliflozin than with placebo irrespective of frailty class.

CONCLUSIONS

In DELIVER, frailty was common and associated with worse outcomes. The benefit of dapagliflozin was consistent across the range of frailty studied. The improvement in health-related quality of life with dapagliflozin occurred early and was greater in patients with a higher level of frailty.

REGISTRATION

URL: https://www.

CLINICALTRIALS

gov; Unique identifier: NCT03619213.

Molecular and histological correlates of cognitive decline across age in male C57BL/6J mice

INTRODUCTION

Increasing age is the number one risk factor for developing cognitive decline and neurodegenerative disease. Aged humans and mice exhibit numerous molecular changes that contribute to a decline in cognitive function and increased risk of developing age-associated diseases. Here, we characterize multiple age-associated changes in male C57BL/6J mice to understand the translational utility of mouse aging.

METHODS

Male C57BL/6J mice from various ages between 2 and 24 months of age were used to assess behavioral, as well as, histological and molecular changes across three modalities: neuronal, microgliosis/neuroinflammation, and the neurovascular unit (NVU). Additionally, a cohort of 4- and 22-month-old mice was used to assess blood-brain barrier (BBB) breakdown. Mice in this cohort were treated with a high, acute dose of lipopolysaccharide (LPS, 10 mg/kg) or saline control 6 h prior to sacrifice followed by tail vein injection of 0.4 kDa sodium fluorescein (100 mg/kg) 2 h later.

RESULTS

Aged mice showed a decline in cognitive and motor abilities alongside decreased neurogenesis, proliferation, and synapse density. Further, neuroinflammation and circulating proinflammatory cytokines were increased in aged mice. Additionally, we found changes at the BBB, including increased T cell infiltration in multiple brain regions and an exacerbation in BBB leakiness following chemical insult with age. There were also a number of readouts that were unchanged with age and have limited utility as markers of aging in male C57BL/6J mice.

CONCLUSIONS

Here we propose that these changes may be used as molecular and histological readouts that correspond to aging-related behavioral decline. These comprehensive findings, in the context of the published literature, are an important resource toward deepening our understanding of normal aging and provide an important tool for studying aging in mice.

Frailty in individuals with depression, bipolar disorder and anxiety disorders: longitudinal analyses of all-cause mortality

BACKGROUND

Frailty is a medical syndrome that is strongly associated with mortality risk and an emerging global health burden. Mental disorders are associated with reduced life expectancy and elevated levels of frailty. In this study, we examined the mortality risk associated with frailty in individuals with a lifetime history of mental disorders compared to individuals without a history of mental disorders.

METHODS

The UK Biobank study recruited > 500,000 adults, aged 37-73, between 2006 and 2010. We derived the two most common albeit distinctive measures of frailty, the frailty phenotype and the frailty index. Individuals with lifetime depression, bipolar disorder or anxiety disorders were identified from multiple data sources. The primary outcome was all-cause mortality. We have also examined differences in frailty, separately by sex and age.

RESULTS

Analyses included up to 297,380 middle-aged and older adults with a median follow-up of 12.19 (interquartile range = 1.31) years, yielding 3,516,706 person-years of follow-up. We observed higher levels of frailty in individuals with mental disorders for both frailty measures. Standardised mean differences in the frailty index ranged from 0.66 (95% confidence interval [CI] 0.65-0.67) in individuals with anxiety disorders to 0.94 (95% CI 0.90-0.97) in individuals with bipolar disorder, compared to people without mental disorders. For key comparisons, individuals with a mental disorder had greater all-cause mortality hazards than the comparison group without mental disorders. The highest hazard ratio (3.65, 95% CI 2.40-5.54) was observed among individuals with bipolar disorder and frailty, relative to non-frail individuals without mental disorders.

CONCLUSIONS

Our findings highlight elevated levels of frailty across three common mental disorders. Frailty and mental disorders represent potentially modifiable targets for prevention and treatment to improve population health and life expectancy, especially where both conditions coexist.

Sacubitril/Valsartan and Frailty in Patients With Heart Failure and Preserved Ejection Fraction

BACKGROUND

Frailty is an increasingly common problem, and frail patients are less likely to receive new pharmacologic therapies because the risk-benefit profile is perceived to be less favorable than in nonfrail patients.

OBJECTIVES

This study investigated the efficacy of sacubitril/valsartan according to frailty status in 4,796 patients with heart failure with preserved ejection fraction randomized in the PARAGON-HF (Prospective Comparison of ARNI With ARB Global Outcomes in Heart Failure With Preserved Ejection Fraction) trial.

METHODS

Frailty was measured by using the Rockwood cumulative deficit approach. The primary endpoint was total heart failure hospitalizations or cardiovascular death.

RESULTS

A frailty index (FI) was calculable in 4,795 patients. In total, 45.2% had class 1 frailty (FI ≤0.210, not frail), 43.5% had class 2 frailty (FI 0.211-0.310, more frail), and 11.4% had class 3 frailty (FI ≥0.311, most frail). There was a graded relationship between FI class and the primary endpoint, with a significantly higher risk associated with greater frailty (class 1: reference; class 2 rate ratio: 2.19 [95% CI: 1.85-2.60]; class 3 rate ratio: 3.29 [95% CI: 2.65-4.09]). The effect of sacubitril/valsartan vs valsartan on the primary endpoint from lowest to highest FI class (as a rate ratio) was: 0.98 [95% CI: 0.76-1.27], 0.92 [95% CI: 0.76-1.12], and 0.69 [95% CI: 0.51-0.95]), respectively (P_interaction = 0.23). When FI was examined as a continuous variable, the interaction with treatment was significant for the primary outcome (P_interaction = 0.002) and total heart failure hospitalizations (P_interaction < 0.001), with those most frail deriving greater benefit.

CONCLUSIONS

Frailty was common in heart failure with preserved ejection fraction and associated with worse outcomes. Compared with valsartan, sacubitril/valsartan seemed to show a greater reduction in the primary endpoint with increasing frailty, although this was not significant when FI was examined as a categorical variable. (Prospective Comparison of ARNI With ARB Global Outcomes in Heart Failure With Preserved Ejection Fraction [PARAGON-HF]; NCT01920711).

Frailty in COPD: an analysis of prevalence and clinical impact using UK Biobank

BACKGROUND

Frailty, a state of reduced physiological reserve, is common in people with chronic obstructive pulmonary disease (COPD). Frailty can occur at any age; however, the implications in younger people (eg, aged <65 years) with COPD are unclear. We assessed the prevalence of frailty in UK Biobank participants with COPD; explored relationships between frailty and forced expiratory volume in 1 second (FEV1) and quantified the association between frailty and adverse outcomes.

METHODS

UK Biobank participants (n=3132, recruited 2006-2010) with COPD aged 40-70 years were analysed comparing two frailty measures (frailty phenotype and frailty index) at baseline. Relationship with FEV1 was assessed for each measure. Outcomes were mortality, major adverse cardiovascular event (MACE), all-cause hospitalisation, hospitalisation with COPD exacerbation and community COPD exacerbation over 8 years of follow-up.

RESULTS

Frailty was common by both definitions (17% frail using frailty phenotype, 28% moderate and 4% severely frail using frailty index). The frailty phenotype, but not the frailty index, was associated with lower FEV1. Frailty phenotype (frail vs robust) was associated with mortality (HR 2.33; 95% CI 1.84 to 2.96), MACE (2.73; 1.66 to 4.49), hospitalisation (incidence rate ratio 3.39; 2.77 to 4.14) hospitalised exacerbation (5.19; 3.80 to 7.09) and community exacerbation (2.15; 1.81 to 2.54), as was frailty index (severe vs robust) (mortality (2.65; 95% CI 1.75 to 4.02), MACE (6.76; 2.68 to 17.04), hospitalisation (3.69; 2.52 to 5.42), hospitalised exacerbation (4.26; 2.37 to 7.68) and community exacerbation (2.39; 1.74 to 3.28)). These relationships were similar before and after adjustment for FEV1.

CONCLUSION

Frailty, regardless of age or measure, identifies people with COPD at risk of adverse clinical outcomes. Frailty assessment may aid risk stratification and guide-targeted intervention in COPD and should not be limited to people aged >65 years.

All-Subset Analysis Improves the Predictive Accuracy of Biological Age for All-Cause Mortality in Chinese and U.S. Populations

BACKGROUND

Klemera-Doubal's method (KDM) is an advanced and widely applied algorithm for estimating biological age (BA), but it has no uniform paradigm for biomarker processing. This article proposed all subsets of biomarkers for estimating BAs and assessed their association with mortality to determine the most predictive subset and BA.

METHODS

Clinical biomarkers, including those from physical examinations and blood assays, were assessed in the China Health and Nutrition Survey (CHNS) 2009 wave. Those correlated with chronological age (CA) were combined to produce complete subsets, and BA was estimated by KDM from each subset of biomarkers. A Cox proportional hazards regression model was used to examine and compare each BA's effect size and predictive capacity for all-cause mortality. Validation analysis was performed in the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and National Health and Nutrition Examination Survey (NHANES). KD-BA and Levine's BA were compared in all cohorts.

RESULTS

A total of 130 918 panels of BAs were estimated from complete subsets comprising 3-17 biomarkers, whose Pearson coefficients with CA varied from 0.39 to 1. The most predictive subset consisted of 5 biomarkers, whose estimated KD-BA had the most predictive accuracy for all-cause mortality. Compared with Levine's BA, the accuracy of the best-fitting KD-BA in predicting death varied among specific populations.

CONCLUSION

All-subset analysis could effectively reduce the number of redundant biomarkers and significantly improve the accuracy of KD-BA in predicting all-cause mortality.

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 rheumatoidrmdopen-2021-002111 arthritis and its relationship with disease activity, hospitalisation and mortality: a longitudinal analysis of the Scottish Early Rheumatoid Arthritis cohort and UK Biobank

OBJECTIVE

To assess the prevalence of frailty in rheumatoid arthritis (RA) and its association with baseline and longitudinal disease activity, all-cause mortality and hospitalisation.

PARTICIPANTS

People with RA identified from the Scottish Early Rheumatoid Arthritis (SERA) inception cohort (newly diagnosed, mean age 58.2 years) and UK Biobank (established disease identified using diagnostic codes, mean age 59 years). Frailty was quantified using the frailty index (both datasets) and frailty phenotype (UK Biobank only). Disease activity was assessed using Disease Activity Score in 28 joints (DAS28) in SERA. Associations between baseline frailty and all-cause mortality and hospitalisation was estimated after adjusting for age, sex, socioeconomic status, smoking and alcohol, plus DAS28 in SERA.

RESULTS

Based on the frailty index, frailty was common in SERA (12% moderate, 0.2% severe) and UK Biobank (20% moderate, 3% severe). In UK Biobank, 23% were frail using frailty phenotype. Frailty index was associated with DAS28 in SERA, as well as age and female sex in both cohorts. In SERA, as DAS28 lessened over time with treatment, mean frailty index also decreased. The frailty index was associated with all-cause mortality (HR moderate/severe frailty vs robust 4.14 (95% CI 1.49 to 11.51) SERA, 1.68 (95% CI 1.26 to 2.13) UK Biobank) and unscheduled hospitalisation (incidence rate ratio 2.27 (95% CI 1.45 to 3.57) SERA 2.74 (95% CI 2.29 to 3.29) UK Biobank). In UK Biobank, frailty phenotype also associated with mortality and hospitalisation.

CONCLUSION

Frailty is common in early and established RA and associated with hospitalisation and mortality. Frailty in RA is dynamic and, for some, may be ameliorated through controlling disease activity in early disease.

Frailty index and gender-specific mortality in Korean adults: Findings from the Korean Longitudinal Study of Aging (2006-2018)

AIMS

To examine the predictive ability of the frailty index in estimating gender-specific mortality in a population of Korean adults.

DESIGN

A descriptive and prospective longitudinal design.

METHODS

Data were used from the Korean Longitudinal Study of Aging conducted from 2006 through 2018. A total of 10,254 adults aged 45-98 years at baseline were included. A 41-item deficit accumulation frailty index was measured, based on multi-domain assessment such as self-rating of health, physical condition, mental status, cognitive function, activities of daily living, instrumental activities of daily living and chronic conditions. We categorized the frailty index into robust (≤0.10), prefrail (0.10-0.25) and frail (≥0.25). Cox's proportional hazards regression analysis was employed to determine the association between the frailty index and all-cause mortality.

RESULTS

A total of 4705 individuals (45.9%) were categorized as robust, 4178 (40.7%) as prefrail and 1371 (13.4%) as frail. The frailty index increased with age, and females were found to have a higher frailty index than males. The survival probabilities were significantly lower in older adults (aged ≥65) compared with adults and significantly lower in males compared with females. Compared with the robust group, the risk of mortality in the prefrail and frail groups was 1.37 and 2.57 times higher, respectively. The association between frailty status and all-cause mortality was similar in adults and older adults, while the hazard ratios were higher in frail group of males than that of females.

CONCLUSION

The frailty index had a predictive ability for all-cause mortality with respect to age and sex.

IMPACT

Using a frailty index among community-dwelling adults could be beneficial to support healthcare providers in early detection of individuals with frailty and facilitate the development of more effective interventions for reducing mortality.

Comparison of Machine Learning Techniques for Mortality Prediction in a Prospective Cohort of Older Adults

As global demographics change, ageing is a global phenomenon which is increasingly of interest in our modern and rapidly changing society. Thus, the application of proper prognostic indices in clinical decisions regarding mortality prediction has assumed a significant importance for personalized risk management (i.e., identifying patients who are at high or low risk of death) and to help ensure effective healthcare services to patients. Consequently, prognostic modelling expressed as all-cause mortality prediction is an important step for effective patient management. Machine learning has the potential to transform prognostic modelling. In this paper, results on the development of machine learning models for all-cause mortality prediction in a cohort of healthy older adults are reported. The models are based on features covering anthropometric variables, physical and lab examinations, questionnaires, and lifestyles, as well as wearable data collected in free-living settings, obtained for the "Healthy Ageing Initiative" study conducted on 2291 recruited participants. Several machine learning techniques including feature engineering, feature selection, data augmentation and resampling were investigated for this purpose. A detailed empirical comparison of the impact of the different techniques is presented and discussed. The achieved performances were also compared with a standard epidemiological model. This investigation showed that, for the dataset under consideration, the best results were achieved with Random UnderSampling in conjunction with Random Forest (either with or without probability calibration). However, while including probability calibration slightly reduced the average performance, it increased the model robustness, as indicated by the lower 95% confidence intervals. The analysis showed that machine learning models could provide comparable results to standard epidemiological models while being completely data-driven and disease-agnostic, thus demonstrating the opportunity for building machine learning models on health records data for research and clinical practice. However, further testing is required to significantly improve the model performance and its robustness.

Protein Nutritional Status and Frailty: A Mendelian Randomization Study

BACKGROUND

Observational studies have suggested that better protein nutritional status may contribute to prevention of frailty.

OBJECTIVE

We sought to examine this hypothesis using a Mendelian randomization (MR) analysis.

METHODS

We conducted a two-sample MR study using GWAS summary statistics data of the UK Biobank. We applied genetically predicted serum albumin as a primary exposure measure and serum total protein as a secondary exposure measure. The outcome measure was the Rockwood frailty index (FI) based on 49 deficits from 356,432 individuals (53.3% of them were women, with a mean ± SD age of 56.7 ± 8.0 y. The association between serum protein measures and FI was mainly analyzed by use of the inverse variance weighted method.

RESULTS

A genetically predicted serum albumin concentration was not statistically significantly associated with FI in the full sample. However, in women, we observed a preventive association between genetically predicted serum albumin and FI (β = -0.172 per g/L; 95% CI: -0.336, -0.007; P = 0.041). In the full sample, genetically predicted serum total protein was inversely associated with FI (β: -0.153 per g/L; 95% CI: -0.251, -0.056; P = 0.002). In both women and men, higher serum total protein was significantly inversely associated with FI; regression coefficients were -0.148 per g/L (95% CI: -0.287, -0.009; P = 0.037) for women, -0.154 per g/L (95% CI: -0.290, -0.018; P = 0.027) for men.

CONCLUSIONS

The present MR study implies that better protein nutritional status modestly contributes to reducing the risk of frailty.

Adherence to Healthy Lifestyle and Attenuation of Biological Aging in Middle-Aged and Older Chinese Adults

BACKGROUND

Little is known about the effects of lifestyle modification on biological aging in population-based studies of middle-aged and older adults.

METHOD

We examined the individual and joint associations of multiple lifestyle factors with accelerated biological aging measured by change in frailty index (FI) over 8 years in a prospective study of Chinese adults. Data were obtained on 24 813 participants in the China Kadoorie Biobank on lifestyle factors and frailty status at baseline and at 8 years after baseline. Adherence to healthy lifestyle factors included nonsmoking or quitting smoking for reasons other than illness, avoidance of heavy alcohol consumption, daily intake of fruit and vegetables, being physically active, body mass index of 18.5-23.9 kg/m2, and waist-to-hip ratio of <0.90 (men)/0.85 (women). FI was constructed separately at baseline and resurvey using 25 age- and health-related items.

RESULTS

Overall, 8 760 (35.3%) individuals had a worsening frailty status. In multivariable-adjusted logistic regression analyses, adherence to healthy lifestyle was associated with a lower risk of worsening frailty status. Compared with robust participants maintaining 0-1 healthy lifestyle factors, the corresponding odds ratios (95% CIs) were 0.93 (0.83-1.03), 0.75 (0.67-0.84), 0.68 (0.60-0.77), and 0.55 (0.46-0.65) for robust participants with 2, 3, 4, and 5-6 healthy lifestyle factors. The decreased risk of frailty status worsening by adherence to healthy lifestyle factors was similar in both middle-aged and older adults, and in both robust and prefrail participants at baseline.

CONCLUSIONS

Adherence to a healthy lifestyle may attenuate the rate of change in biological aging in middle-aged and older Chinese adults.

Frailty trajectories in three longitudinal studies of aging: Is the level or the rate of change more predictive of mortality?

BACKGROUND

frailty shows an upward trajectory with age, and higher levels increase the risk of mortality. However, it is less known whether the shape of frailty trajectories differs by age at death or whether the rate of change in frailty is associated with mortality.

OBJECTIVES

to assess population frailty trajectories by age at death and to analyse whether the current level of the frailty index (FI) i.e. the most recent measurement or the person-specific rate of change is more predictive of mortality.

METHODS

3,689 individuals from three population-based cohorts with up to 15 repeated measurements of the Rockwood frailty index were analysed. The FI trajectories were assessed by stratifying the sample into four age-at-death groups: <70, 70-80, 80-90 and >90 years. Generalised survival models were used in the survival analysis.

RESULTS

the FI trajectories by age at death showed that those who died at <70 years had a steadily increasing trajectory throughout the 40 years before death, whereas those who died at the oldest ages only accrued deficits from age ~75 onwards. Higher level of FI was independently associated with increased risk of mortality (hazard ratio 1.68, 95% confidence interval 1.47-1.91), whereas the rate of change was no longer significant after accounting for the current FI level. The effect of the FI level did not weaken with time elapsed since the last measurement.

CONCLUSIONS

Frailty trajectories differ as a function of age-at-death category. The current level of FI is a stronger marker for risk stratification than the rate of change.

Smoking Status and Factors associated with COVID-19 In-hospital Mortality among U.S. Veterans

Introduction

The role of smoking in risk of death among patients with COVID-19 remains unclear. We examined the association between in-hospital mortality from COVID-19 and smoking status and other factors in the United States Veterans Health Administration (VHA).

Methods

This is an observational, retrospective cohort study using the VHA COVID-19 shared data resources for February 1 to September 11, 2020. Veterans admitted to the hospital who tested positive for SARS-CoV-2 and hospitalized by VHA were grouped into Never (as reference, NS), Former (FS), and Current smokers (CS). The main outcome was in-hospital mortality. Control factors were the most important variables (among all available) determined through a cascade of machine learning. We reported adjusted odds ratios (aOR) and 95% confidence intervals (95%CI) from logistic regression models, imputing missing smoking status in our primary analysis.

Results

Out of 8 667 996 VHA enrollees, 505 143 were tested for SARS-CoV-2 (NS = 191 143; FS = 240 336; CS = 117 706; Unknown = 45 533). The aOR of in-hospital mortality was 1.16 (95%CI 1.01, 1.32) for FS vs. NS and 0.97 (95%CI 0.78, 1.22; p > .05) for CS vs. NS with imputed smoking status. Among other factors, famotidine and nonsteroidal anti-inflammatory drugs (NSAID) use before hospitalization were associated with lower risk while diabetes with complications, kidney disease, obesity, and advanced age were associated with higher risk of in-hospital mortality.

Conclusions

In patients admitted to the hospital with SARS-CoV-2 infection, our data demonstrate that FS are at higher risk of in-hospital mortality than NS. However, this pattern was not seen among CS highlighting the need for more granular analysis with high-quality smoking status data to further clarify our understanding of smoking risk and COVID-19-related mortality. Presence of comorbidities and advanced age were also associated with increased risk of in-hospital mortality.

Implications

Veterans who were former smokers were at higher risk of in-hospital mortality compared to never smokers. Current smokers and never smokers were at similar risk of in-hospital mortality. The use of famotidine and nonsteroidal anti-inflammatory drugs (NSAIDs) before hospitalization were associated with lower risk while uncontrolled diabetes mellitus, advanced age, kidney disease, and obesity were associated with higher risk of in-hospital mortality.

Fatty Acids and Frailty: A Mendelian Randomization Study

BACKGROUND

Observational studies have suggested that fatty acids such as higher levels of n-3 polyunsaturated fatty acids (PUFAs) may prevent frailty. By using Mendelian randomization analysis, we examined the relationship between fatty acids and frailty.

METHODS

We used summary statistics data for single-nucleotide polymorphisms associated with plasma levels of saturated fatty acids (palmitic acid, stearic acid), mono-unsaturated fatty acids (MUFAs) (palmitoleic acid, oleic acid), n-6 PUFAs (linoleic acid, arachidonic acid), and n-3 PUFAs (alpha-linolenic acid, eicosapentaenoic acid, docosapentaenoic acid, docosahexaenoic acid), and the corresponding data for frailty index (FI) in 356,432 individuals in the UK Biobank.

RESULTS

Although there were no robust associations on the MUFAs or the PUFAs, genetically predicted higher plasma stearic acid level (one of saturated fatty acids) was statistically significantly associated with higher FI (β = 0.178; 95% confidence interval = -0.050 to 0.307; p = 0.007). Such a relationship was also observed in a multivariate MR (β = 0.361; 95% confidence interval = 0.155 to 0.567; p = 0.001). Genetically predicted higher palmitic acid was also significantly associated with higher FI (β = 0.288; 95% confidence interval = 0.128 to 0.447; p < 0.001) in the multivariate MR analysis.

CONCLUSIONS

The present MR study implies that saturated fatty acids, especially stearic acid, is a risk factor of frailty.

A genome-wide association study of the frailty index highlights brain pathways in ageing

Frailty is a common geriatric syndrome and strongly associated with disability, mortality and hospitalization. Frailty is commonly measured using the frailty index (FI), based on the accumulation of a number of health deficits during the life course. The mechanisms underlying FI are multifactorial and not well understood, but a genetic basis has been suggested with heritability estimates between 30 and 45%. Understanding the genetic determinants and biological mechanisms underpinning FI may help to delay or even prevent frailty. We performed a genome-wide association study (GWAS) meta-analysis of a frailty index in European descent UK Biobank participants (n = 164,610, 60-70 years) and Swedish TwinGene participants (n = 10,616, 41-87 years). FI calculation was based on 49 or 44 self-reported items on symptoms, disabilities and diagnosed diseases for UK Biobank and TwinGene, respectively. 14 loci were associated with the FI (p < 5*10-8 ). Many FI-associated loci have established associations with traits such as body mass index, cardiovascular disease, smoking, HLA proteins, depression and neuroticism; however, one appears to be novel. The estimated single nucleotide polymorphism (SNP) heritability of the FI was 11% (0.11, SE 0.005). In enrichment analysis, genes expressed in the frontal cortex and hippocampus were significantly downregulated (adjusted p < 0.05). We also used Mendelian randomization to identify modifiable traits and exposures that may affect frailty risk, with a higher educational attainment genetic risk score being associated with a lower degree of frailty. Risk of frailty is influenced by many genetic factors, including well-known disease risk factors and mental health, with particular emphasis on pathways in the brain.

An analysis of frailty and multimorbidity in 20,566 UK Biobank participants with type 2 diabetes

Background

Frailty and multimorbidity are common in type 2 diabetes (T2D), including people <65 years. Guidelines recommend adjustment of treatment targets in people with frailty or multimorbidity. It is unclear how recommendations to adjust treatment targets in people with frailty or multimorbidity should be applied to different ages. We assess implications of frailty/multimorbidity in middle/older-aged people with T2D.

Methods

We analysed UK Biobank participants (n = 20,566) with T2D aged 40–72 years comparing two frailty measures (Fried frailty phenotype and Rockwood frailty index) and two multimorbidity measures (Charlson Comorbidity index and count of long-term conditions (LTCs)). Outcomes were mortality, Major Adverse Cardiovascular Event (MACE), hospitalization with hypoglycaemia or fall/fracture.

Results

Here we show  that choice of measure influences the population identified: 42% of participants are frail or multimorbid by at least one measure; 2.2% by all four measures. Each measure is associated with mortality, MACE, hypoglycaemia, and fall or fracture. The absolute 5-year mortality risk is higher in older versus younger participants with a given level of frailty (e.g. 1.9%, and 9.9% in men aged 45 and 65, respectively, using frailty phenotype) or multimorbidity (e.g. 1.3%, and 7.8% in men with 4 LTCs aged 45 and 65, respectively). Using frailty phenotype, the relationship between higher HbA1c and mortality is stronger in frail compared with pre-frail or robust participants.

Conclusions

Assessment of frailty/multimorbidity should be embedded within routine management of middle-aged and older people with T2D. Method of identification as well as features such as age impact baseline risk and should influence clinical decisions (e.g. glycaemic control).