Development and validation of a hospital frailty risk measure using Canadian clinical administrative data.

BACKGROUND: Accessible measures specific to the Canadian context are needed to support health system planning for older adults living with frailty. We sought to develop and validate the Canadian Institute for Health Information (CIHI) Hospital Frailty Risk Measure (HFRM). METHODS: Using CIHI administrative data, we conducted a retrospective cohort study involving patients aged 65 years and older who were discharged from Canadian hospitals from Apr. 1, 2018, to Mar. 31, 2019. We used a 2-phase approach to develop and validate the CIHI HFRM. The first phase, construction of the measure, was based on the deficit accumulation approach (identification of age-related conditions using a 2-year look-back). The second phase involved refinement into 3 formats (continuous risk score, 8 risk groups and binary risk measure), with assessment of their predictive validity for several frailty-related adverse outcomes using data to 2019/20. We assessed convergent validity with the United Kingdom Hospital Frailty Risk Score. RESULTS: The cohort consisted of 788 701 patients. The CIHI HFRM included 36 deficit categories and 595 diagnosis codes that cover morbidity, function, sensory loss, cognition and mood. The median continuous risk score was 0.111 (interquartile range 0.056-0.194, equivalent to 2-7 deficits); 35.1% (n = 277 000) of the cohort were found at risk of frailty (≥ 6 deficits). The CIHI HFRM showed satisfactory predictive validity and reasonable goodness-of-fit. For the continuous risk score format (unit = 0.1), the hazard ratio (HR) for 1-year risk of death was 1.39 (95% confidence interval [CI] 1.38-1.41), with a C-statistic of 0.717 (95% CI 0.715-0.720); the odds ratio for high users of hospital beds was 1.85 (95% CI 1.82-1.88), with a C-statistic of 0.709 (95% CI 0.704-0.714), and the HR of 90-day admission to long-term care was 1.91 (95% CI 1.88-1.93), with a C-statistic of 0.810 (95% CI 0.808-0.813). Compared with the continuous risk score, using a format of 8 risk groups had similar discriminatory ability and the binary risk measure had slightly weaker performance. INTERPRETATION: The CIHI HFRM is a valid tool showing good discriminatory power for several adverse outcomes. The tool can be used by decision-makers and researchers by providing information on hospital-level prevalence of frailty to support system-level capacity planning for Canada's aging population.

Validation of the Pictorial Fit-Frail Scale in a Thoracic Surgery Clinic.

OBJECTIVE: Examine feasibility and construct validity of Pictorial Fit-Frail scale (PFFS) for the first time in older surgical patients. BACKGROUND: The PFFS uses visual images to measure health state in 14 domains and has been previously validated in outpatient geriatric clinics. METHODS: Patients ≥65 year-old who were evaluated in a multidisciplinary thoracic surgery clinic from November 2020 to May 2021 were prospectively included. Patients completed an in-person PFFS and Vulnerable Elders Survey (VES-13) during their visit, and a frailty index was calculated from the PFFS (PFFStrans). A geriatrician performed a comprehensive geriatric assessment (CGA) either in-person or virtually, from which a Frailty Index (FI-CGA) and Frailty Questionnaire (FRAIL) scale were obtained. To assess the validity of the PFFS in this population, the Spearman rank correlations (r spearman ) between PFFS trans and VES-13, FI-CGA, FRAIL were calculated. RESULTS: All 49 patients invited to participate agreed, of which 46/49 (94%) completed the PFFS so a score could be calculated. The majority of patients (59%) underwent an in-person CGA and the reminder (41%) a virtual CGA. The cohort was mainly female (59.0%), with a median age of 77 (range: 67-90). The median PFFS trans was 0.27 (interquartile range [IQR] 0.12-0.34), PFFS was 11 (IQR 5-14), and 0.24 (IQR 0.13-0.32) for FI-CGA. We observed a strong correlation between the PFFS trans and FI-CGA (r spearman = 0.81, P < 0.001) and a moderate correlation between PFFS trans and VES-13 and FRAIL score (r spearman = 0.68 and 0.64 respectively, P < 0.001). CONCLUSIONS: PFFS had good feasibility and construct validity among older surgical patients when compared to previously validated frailty measurements.

Relationship of body mass index with frailty and all-cause mortality among middle-aged and older adults.

BACKGROUND: Parallel to growth of aging and obese populations, the prevalence of metabolic diseases is rising. How body mass index (BMI) relates to frailty and mortality across frailty levels is controversial. We examined the associations of high BMI with frailty and mortality and explored the effects of percent body fat on these associations. METHODS: We included 29,937 participants aged ≥50 years from the 2001-2006 National Health and Nutrition Examination Survey (NHANES) cohorts (N=6062; 53.7% females) and from wave 1 (2004) of Survey of Health, Ageing and Retirement in Europe (SHARE) (N=23,875; 54% females). BMI levels were categorized as: normal: 18.5-24.9 kg/m2, overweight: 25.0-29.9, obese grade 1: 30.0-34.9, and obese grade 2 or 3: >35.0. A frailty index (FI) was constructed excluding nutrition-related items: 36 items for NHANES and 57 items for SHARE. We categorized the FI using 0.1-point increments: FI ≤ 0.1 (non-frail), 0.1 < FI ≤ 0.2 (very mildly frail), 0.2 < FI ≤ 0.3 (mildly frail), and FI > 0.3 (moderately/severely frail). Percent body fat was measured using DXA for NHANES participants. All-cause mortality data were obtained until 2015 for NHANES and 2017 for SHARE to estimate 10-year mortality risk. All analyses were adjusted for age, sex, educational, marital, employment, and smoking statuses. RESULTS: Mean age of participants was 63.3±10.2 years for NHANES and 65.0±10.0 years for SHARE. In both cohorts, BMI levels ≥25 kg/m2 were associated with higher frailty, compared to normal BMI. In SHARE, having a BMI level greater than 35 kg/m2 increased mortality risk in participants with FI≤0.1 (HR 1.31, 95%CI 1.02-1.69). Overweight participants with FI scores >0.3 were at lower risk for mortality compared to normal BMI [NHANES (0.79, 0.64-0.96); SHARE (0.71, 0.63-0.80)]. Higher percent body fat was associated with higher frailty. Percent body fat significantly mediated the relationship between BMI levels and frailty but did not mediate the relationship between BMI levels and mortality risk. CONCLUSIONS: Being overweight or obese is associated with higher frailty levels. In this study, we found that being overweight is a protective factor of mortality in moderately/severely frail people and obesity grade 1 may be protective for mortality for people with at least a mild level of frailty. In contrast, obesity grades 2 and 3 may be associated with higher mortality risk in non-frail people. The relationship between BMI and frailty is partially explained by body fat.

Frailty predicts outcomes in cystic fibrosis patients listed for lung transplantation.

BACKGROUND: Survival predictors are not established for cystic fibrosis (CF) patients listed for lung transplantation (LT). Using the deficit accumulation approach, we developed a CF-specific frailty index (FI) to allow risk stratification for adverse waitlist and post-LT outcomes. METHODS: We studied adult CF patients listed for LT in the Toronto LT Program (development cohort 2005-2015) and the Swiss LT centres (validation cohort 2008-2017). Comorbidities, treatment, laboratory results and social support at listing were utilized to develop a lung disease severity index (LI deficits, d = 18), a frailty index (FI, d = 66) and a lifestyle/social vulnerability index (LSVI, d = 10). We evaluated associations of the indices with worsening waitlist status, hospital and ICU length of stay, survival and graft failure. RESULTS: We studied 188 (Toronto cohort, 176 [94%] transplanted) and 94 (Swiss cohort, 89 [95%] transplanted) patients. The median waitlist times were 69 and 284 days, respectively. The median follow-up post-transplant was 5.3 and 4.7 years. At listing, 44.7% of patients were frail (FI ≥ 0.25) in the Toronto and 21.3% in the Swiss cohort. The FI was significantly associated with all studied outcomes in the Toronto cohort (FI and post-LT mortality, multivariable HR 1.74 [95%CI:1.24-2.45] per 0.1 point of the FI). In the Swiss cohort, the FI was associated with worsening waitlist status, post-LT mortality and graft failure. CONCLUSIONS: In CF patients listed for LT, FI risk stratification was significantly associated with waitlist and post-LT outcomes. Studying frailty in young populations with advanced disease can provide insights on how frailty and deficit accumulation impacts survival.

Eating Timing and Frequency as a Predictor of Hospitalization and/or Mortality From Coronary Artery Disease: The Linked CCHS-DAD-CMDB 2004-2013 Study.

Background: Coronary artery disease (CAD) is a major overlapping challenge in both clinical and public health realms due to high rates of hospitalization and mortality. Despite nutrition being a key risk factor for CAD, little is known about eating timing and frequency in Canadians or their relation to risk of hospitalization and/or mortality from CAD. Methods: Breakfast consumption, between-meal consumption, eating frequency, and established CAD risk factors were assessed at baseline in 13,328 adults free of cancer and CAD from the 2004 Canadian Community Health Survey, Cycle 2.2, Nutrition Focus and were linked to administrative health databases to determine incidence of hospitalization and/or mortality from CAD in the following 9 years. Multivariable-adjusted hazard ratios with 95% confidence intervals estimated from Cox proportional hazards models were computed to test for associations between eating timing/frequency and hospitalization and/or mortality from CAD (n = 746 cases). Results: Skipping breakfast (12.0% of participants) and engaging in between-meal consumption (90.2%) were common practices, as was eating 4-5 times per day (55.2%). Skipping breakfast, between-meal consumption, and eating more or less than 4-5 times/day were strongly and bi-directionally associated with many sociodemographic, lifestyle, and metabolic risk factors at baseline. No associations were observed between skipping breakfast, between-meal consumption, or eating frequency and risk of hospitalization and/or mortality from CAD. Conclusions: Skipping breakfast, between-meal consumption, and eating frequency were associated with numerous established risk and preventative factors for CAD at baseline but were not directly associated with the risk of hospitalization and/or mortality from CAD in this cohort of Canadian adults.

Introduction: La maladie coronarienne (MC) est un enjeu majeur chevauchant les domaines clinique et de santé publique en raison des taux élevés d'hospitalisation et de mortalité. Bien que la nutrition soit un facteur de risque fondamental de la MC, on en connaît peu sur le moment et la fréquence de la consommation d'aliments chez les Canadiens ou sur leur relation au risque d'hospitalisation et/ou de mortalité en raison de la MC. Méthodes: Nous avons initialement évalué la prise du déjeuner, la consommation entre les repas, la fréquence de la consommation d'aliments et les facteurs de risque établis de MC de 13 328 adultes indemnes de cancer et de MC de l'Enquête sur la santé dans les collectivités canadiennes de 2004, cycle 2.2, volet nutrition, et avons lié les bases de données administratives en santé pour déterminer la fréquence d'hospitalisation et/ou de mortalité en raison de la MC dans les neuf années subséquentes. Nous avons calculé les rapports de risque ajustés à plusieurs variables à intervalles de confiance à 95 % estimés à partir des modèles à risques proportionnels de Cox pour vérifier les associations entre le moment et la fréquence de la consommation d'aliments et l'hospitalisation et/ou la mortalité en raison de la MC (n = 746 cas). Résultats: L'absence du déjeuner (12,0 % des participants), la consommation d'aliments entre les repas (90,2 %) et la consommation d'aliments de 4 à 5 fois par jour (55,2 %) étaient des pratiques courantes. L'absence du déjeuner, la consommation d'aliments entre les repas et la consommation d'aliments plus ou moins 4-5 fois/jour étaient fortement et bidirectionnellement associées aux facteurs de risque sociodémographiques, liés au mode de vie et métaboliques initiaux. Nous n'avons observé aucune association entre l'absence du déjeuner, la consommation d'aliments entre les repas ou la fréquence de la consommation d'aliments, et le risque d'hospitalisation et/ou de mortalité en raison de la MC. Conclusions: L'absence du déjeuner, la consommation d'aliments entre les repas et la fréquence de la consommation d'aliments étaient associées à de nombreux risques établis et de facteurs préventifs initiaux de la MC, mais n'étaient pas directement associées au risque d'hospitalisation et/ou de mortalité en raison de la MC dans cette cohorte d'adultes canadiens.

Prospective study of breakfast frequency and timing and the risk of incident type 2 diabetes in community-dwelling older adults: the Cardiovascular Health Study.

BACKGROUND: No evidence-based recommendations regarding optimal breakfast frequency and timing and type 2 diabetes mellitus (T2DM) exist for older adults because of limited studies. OBJECTIVES: We sought to prospectively assess relations between breakfast frequency and timing and T2DM risk among older adults and determine whether these depended on sex or cardiometabolic risk factors. METHODS: Weekly breakfast frequency and usual daily breakfast time were assessed by questionnaire at baseline in 3747 older adults (aged ≥ 65 y) from the Cardiovascular Health Study (CHS) who were free of cancer and T2DM and followed for 17.6 y. Multivariable-adjusted hazard ratios (aHRs) with 95% CIs estimated from Cox proportional hazards models were used to quantify associations with T2DM. RESULTS: Most CHS participants (median age: 74 y; IQR: 71-78 y) consumed breakfast daily (85.5%), and 73% had their first daily eating occasion between 07:00 and 09:00, both of which were associated with higher socioeconomic status, factors that are indicative of a healthier lifestyle, and lower levels of cardiometabolic risk indicators at baseline. During follow-up, 547 T2DM cases were documented. No strong evidence was observed linking breakfast frequency and risk of T2DM. Compared with participants whose breakfast timing (first eating occasion of the day) was 07:00-09:00, those who broke fast after 09:00 had an aHR for T2DM of 0.71 (95% CI: 0.51, 0.99). This association was present in participants with impaired fasting glucose at baseline (aHR: 0.61; 95% CI: 0.39, 0.95) but not in those without (aHR: 0.83; 95% CI: 0.50, 1.38). No associations between eating frequency or timing and T2DM were observed within other prespecified subgroups. CONCLUSIONS: Eating breakfast daily was not associated with either higher or lower risk of T2DM in this cohort of older adults, whereas a later (after 09:00) daily first eating occasion time was associated with lower T2DM risk in participants with impaired fasting glucose at baseline.This trial was registered at clinicaltrials.gov as NCT00005133.

A simple test-based frailty index to predict survival among cancer patients with an unplanned hospitalization: An observational cohort study.

BACKGROUND: Frailty is a state of increased vulnerability to stressors, and predicts risk of adverse outcomes, such as mortality. Frailty can be defined by a frailty index (FI) using an accumulation of deficits approach. An FI comprised of 20 items derived from our previously studied test-based frailty index (TBFI) and an additional 33 survey-based elements sourced from the standard CGA was developed to evaluate if predictive validity of survival was improved. METHODS: One hundred eighty-nine cancer patients during acute hospitalization were consented between September 2018 and May 2019. Frailty scores were calculated, and patients were categorized into four groups: non-frail (0-0.2), mildly frail (0.2-0.3), moderately frail (0.3-0.4), and severely frail (>0.4). Patients were followed for 1-year to assess FI and TBFI prediction of survival. Area under the curve (AUC) statistics from ROC analyses were compared for the FI versus TBFI. RESULTS: Increasing frailty was similarly associated with increased risk of mortality (HR, 4.5 [95% CI, 2.519-8.075] and HR, 4.1 [95%CI, 1.692-9.942]) and the likelihood of death at 6 months was about 11-fold (odds ratio, 10.9 [95% CI, 3.97-33.24]) and 9.73-fold (95% CI, 2.85-38.50) higher for severely frail patients compared to non-frail patients for FI and TBFI, respectively. This association was independent of age and type of cancer. The FI and TBFI were predictive of survival for older and younger cancer patients with no significant differences between models in discriminating survival (FI AUC, 0.747 [95% CI, 0.6772-0.8157] and TBFI AUC, 0.724 [95% CI, 0.6513-0.7957]). CONCLUSIONS: The TBFI was predictive of survival, and the addition of an in-person assessment (FI) did not greatly improve predictive validity. Increasing frailty, as measured by a TBFI, resulted in a meaningfully increased risk of mortality and may be well-suited for screening of hospitalized cancer patients.

Relationship between diet quality scores and the risk of frailty and mortality in adults across a wide age spectrum.

BACKGROUND: Beyond intakes of total energy and individual nutrient, eating patterns may influence health, and thereby the risk of adverse outcomes. How different diet measures relate to frailty-a general measure of increased vulnerability to unfavorable health outcomes-and mortality risk, and how this might vary across the life course, is not known. We investigated the associations of five dietary indices (Nutrition Index (NI), the energy-density Dietary Inflammatory Index (E-DII™), Healthy Eating Index-2015 (HEI-2015), Mediterranean Diet Score (MDS), and Dietary Approaches to Stop Hypertension (DASH)) with frailty and mortality. METHODS: We included 15,249 participants aged ≥ 20 years from the 2007-2012 cohorts of the National Health and Nutrition Examination Survey (NHANES). The NI combined 31 nutrition-related deficits. The E-DII is a literature-derived dietary index associated with inflammation. The HEI-2015 assesses adherence to the Dietary Guidelines of Americans. The MDS represents adherence to the traditional Mediterranean diet. DASH combines macronutrients and micronutrients to prevent hypertension. Frailty was evaluated using a 36-item frailty index. Mortality status was ascertained up to December 31, 2015. RESULTS: Participants' mean age was 47.2 ± 16.7 years and 51.7% were women. After adjusting for age, sex, race, educational level, marital and employment status, smoking, BMI, and study cohort, higher NI and E-DII scores and lower HEI-2015, MDS, and DASH scores were individually significantly associated with frailty. All dietary scores were significantly associated with 8-year mortality risk after adjusting for basic covariates and frailty: NI (hazard ratio per 0.1 point, 1.15, 95%CI 1.10-1.21), E-DII (per 1 point, 1.05, 1.01-1.08), HEI-2015 (per 10 points, 0.93, 0.89-0.97), MDS (per 1 point, 0.94, 0.90-0.97), and DASH (per 1 point, 0.96, 0.93-0.99). The associations of E-DII, HEI-2015, and MDS scores with 8-year mortality risk persisted after additionally adjusting for NI. CONCLUSIONS: NI, E-DII, HEI-2015, MDS, and DASH scores are associated with frailty and 8-year mortality risk in adults across all ages. Nevertheless, their mechanisms and sensitivity to predict health outcomes may differ. Nutrition scores have the potential to include measures of both consumption and laboratory and physical measures of exposure.

Association between lifestyle behaviors and frailty in Atlantic Canadian males and females.

PURPOSE: The aim of this study was to identify lifestyle factors in males and females that are associated with a greater degree of frailty in a Canadian cohort. METHODS: Cross-sectional data analysis from participants aged 30-74 yrs of the Atlantic PATH cohort. Inclusion criteria included completion of mental health questionnaires and ≥1 vital measure (n = 9133, 70% female, mean age 55 yrs). A frailty index was created based on 38 items with higher values indicating increasing frailty. The association between lifestyle factors and frailty was assessed by logistic regression. RESULTS: 805 participants had a high level of frailty (frailty index ≥0.30). There was a significant interaction among sex, age, and lifestyle factors such as smoking status (P < 0.001), alcohol consumption (P < 0.001), physical activity level (P = 0.005), time spent sitting (P < 0.001) and sleeping (P < 0.001) on frailty. Smoking was harmful whereas sleep was protective for both males and females (<60 yrs). Females (<60yrs) that sat for ≥4 h/day were more likely to be highly frail whereas females (all ages) that consumed alcohol at least occasionally were less likely to be highly frail. Males, but not females, that engaged in a high level of physical activity were less likely to have a high level of frailty. CONCLUSIONS: Higher frailty is more prevalent among participants with unhealthy lifestyle behaviors related to smoking, alcohol consumption, sedentary and physical activity level, diet, and sleep. Differences in lifestyle behaviors of males and females of specific ages should be considered for managing frailty levels.

Medication-related criteria in frailty assessment tools: A narrative review.

OBJECTIVE: To review medication-related criteria within validated frailty tools. METHODS: Narrative review of validated frailty assessment tools. Frailty tools were identified from recently published reviews; each tool was reviewed to determine whether any medication-related criteria were included and how these criteria contributed to the scoring/assessment of frailty. RESULTS: Eight out of 16 validated frailty tools included medication-related criteria. The majority of criteria were a numerical cut-off of number of medications taken; however, the specific cut-off was not consistent. CONCLUSION: Inclusion of medication-related criteria in frailty tools is highly variable. Future research is required to determine whether incorporation of medication use into frailty assessment can impact outcomes in terms of frailty prevention and treatment.

Effects of Probiotics and Prebiotics on Frailty and Ageing: A Narrative Review.

Globally, the population over the age of 60 is growing fast, but people age in different ways. Frailty, shown by the accumulation of age-related deficits, is a state of increased vulnerability to adverse outcomes among people of the same chronological age. Ageing results in a decline in diversity and homeostasis of microbiomes, and gut flora changes are related to health deficit accumulation and adverse health outcomes. In older people, health deficits including inappropriate intake, sarcopenia, physical inactivity, polypharmacy, and social vulnerability are factors associated with gut dysbiosis. The use of probiotics and prebiotics is a cost-effective and widely available intervention. Intake of probiotics and prebiotics may improve the homeostasis of gut microflora and prevent frailty and unhealthy aging. However, health effects vary among probiotics and prebiotics and among individual populations. This narrative review summarizes recent evidence about the relationship between prebiotic and probiotic consumption with health outcomes in older people.

Replacing Sedentary Time with Light or Moderate-Vigorous Physical Activity Across Levels of Frailty.

We sought to examine how much sedentary times needs to be replaced by light or moderate-vigorous physical activity in order to reduce frailty and protect against mortality. We built isotemporal substitution models to assess the theoretical effect of replacing sedentary behavior with and equal amount of light or moderate-vigorous activity on frailty and mortality in community-based adults aged 50 years and older. Controlling for age, sex, body mass index, marital status, race, education, employment status, and National Health and Nutrition Examination Study cycle, replacing one hour of sedentary time with moderate-vigorous or light physical activity daily was associated with a lower Frailty Index. For mortality, results varied based on frailty level. Replacing sedentary behavior with moderate-vigorous exercise was associated with lower mortality risk in vulnerable individuals, however, replacing sedentary behavior with light activity was associated with lower mortality risk in frailer individuals.

Measuring Aging and Identifying Aging Phenotypes in Cancer Survivors.

Observational data have shown that some cancer survivors develop chronic conditions like frailty, sarcopenia, cardiac dysfunction, and mild cognitive impairment earlier and/or at a greater burden than similarly aged individuals never diagnosed with cancer or exposed to systemic or targeted cancer therapies. In aggregate, cancer- and treatment-related physical, cognitive, and psychosocial late- and long-term morbidities experienced by cancer survivors are hypothesized to represent accelerated or accentuated aging trajectories. However, conceptual, measurement, and methodological challenges have constrained efforts to identify, predict, and mitigate aging-related consequences of cancer and cancer treatment. In July 2018, the National Cancer Institute convened basic, clinical, and translational science experts for a think tank titled "Measuring Aging and Identifying Aging Phenotypes in Cancer Survivors." Through the resulting deliberations, several research and resource needs were identified, including longitudinal studies to examine aging trajectories that include detailed data from before, during, and after cancer treatment; mechanistic studies to elucidate the pathways that lead to the emergence of aging phenotypes in cancer survivors; long-term clinical surveillance to monitor survivors for late-emerging effects; and tools to integrate multiple data sources to inform understanding of how cancer and its therapies contribute to the aging process. Addressing these needs will help expand the evidence base and inform strategies to optimize healthy aging of cancer survivors.

The impact of physical activity and sedentary behaviors on frailty levels.

Heterogeneity in aging can be explained by frailty. Lifestyle behaviors such as physical activity can help manage frailty levels. Conversely, sedentary behaviours are associated with frailty independently of physical activity. Here, we summarize epidemiological and clinical trial evidence concerning the impact of physical activity and sedentary behaviors on frailty levels. We also analysed the National Health and Nutrition Examination Survey (NHANES) data to describe physical activity and sedentary behavior accumulation patterns across frailty levels and their impact on mortality risk. The few prospective and intervention studies demonstrate that higher physical activity levels are associated with a lower incidence of frailty. There are no interventions published which limit sedentary behaviors to manage frailty. Using the NHANES data we demonstrate that individuals are less likely to meet physical activity guidelines and are more likely to accumulate sedentary time in prolonged bouts. Prolonged sedentary bouts and total sedentary time were associated with a higher mortality risk in frail individuals but not in the fit group. Non-bouted sedentary time was not associated with mortality risk. Our review and novel data suggest that there is a need for more intervention studies which focus on increasing physical activity or minimizing sedentary time to manage frailty levels.

Frailty prevalence and factors associated with the Frailty Phenotype and Frailty Index: Findings from the North West Adelaide Health Study.

OBJECTIVE: To determine the prevalence of frailty and associated factors in the North West Adelaide Health Study (2004-2006) using the Frailty Phenotype (FP) and Frailty Index (FI). METHODS: Frailty was measured in 909 community-dwelling participants aged ≥65 years using the FP and FI. RESULTS: The FP classified 18% of participants as frail and the FI 48%. The measures were strongly correlated (r = 0.76, P < 0.001) and had a kappa agreement of 0.38 for frailty classification, with 37% of participants classified as non-frail by the FP being classified as frail by the FI. Being older, a current smoker, and having multimorbidity and polypharmacy were associated with higher frailty levels by both tools. Female, low income, obesity and living alone were associated with the FI. CONCLUSION: Frailty prevalence was higher when assessed using the FI. Socioeconomic factors and other health determinants contribute to higher frailty levels.

Predictors of transitions in frailty severity and mortality among people aging with HIV.

BACKGROUND: People aging with HIV show variable health trajectories. Our objective was to identify longitudinal predictors of frailty severity and mortality among a group aging with HIV. METHODS: Exploratory analyses employing a multistate transition model, with data from the prospective Modena HIV Metabolic Clinic Cohort Study, based in Northern Italy, begun in 2004. Participants were followed over four years from their first available visit. We included all 963 participants (mean age 46.8±7.1; 29% female; 89% undetectable HIV viral load; median current CD4 count 549, IQR 405-720; nadir CD4 count 180, 81-280) with four-year data. Frailty was quantified using a 31-item frailty index. Outcomes were frailty index score or mortality at four-year follow-up. Candidate predictor variables were baseline frailty index score, demographic (age, sex), HIV-disease related (undetectable HIV viral load, current CD4+ T-cell count, nadir CD4 count, duration of HIV infection, and duration of antiretroviral therapy [ARV] exposure), and behavioral factors (smoking, injection drug use (IDU), and hepatitis C virus co-infection). RESULTS: Four-year mortality was 3.0% (n = 29). In multivariable analyses, independent predictors of frailty index at follow-up were baseline frailty index (RR 1.06, 95% CI 1.05-1.07), female sex (RR 0.93, 95% CI 0.87-0.98), nadir CD4 cell count (RR 0.96, 95% CI 0.93-0.99), duration of HIV infection (RR 1.06, 95% CI 1.01-1.12), duration of ARV exposure (RR 1.08, 95% CI 1.02-1.14), and smoking pack-years (1.03, 1.01-1.05). Independent predictors of mortality were baseline frailty index (OR 1.19, 1.02-1.38), current CD4 count (0.34, 0.20-0.60), and IDU (2.89, 1.30-6.42). CONCLUSIONS: Demographic, HIV-disease related, and social and behavioral factors appear to confer risk for changes in frailty severity and mortality among people aging with HIV.

Comparison and Clinical Applications of the Frailty Phenotype and Frailty Index Approaches.

The previous chapter focused on the conceptualization and operationalization of the deficit accumulation and phenotypic approaches to the description of frailty. The purpose of this chapter is to summarize some studies that compared these most commonly used frailty definitions. We also discuss the strengths and limitations of using these two frailty assessments in clinical settings and how they might be usefully employed in future studies.

The association between sedentary behaviour, moderate-vigorous physical activity and frailty in NHANES cohorts.

OBJECTIVES: (1) To examine how sedentary behaviour and moderate-vigorous (MVPA) are each experienced during the day across different levels of frailty; (2) estimate and compare the extent to which high levels of sedentary behaviour and low levels of MVPA are associated with increased frailty and self-reported health, disability and healthcare utilization. METHODS: Community dwelling adults aged 50+ from the National Health and Nutrition Examination Survey (2003-2004; 2005-2006). Frailty was measured with the frailty index and physical activity was measured using ActiGraph accelerometers. RESULTS: On average, people engaged in about 8.5h of sedentary behaviour each day. The most frail individuals were more sedentary and less likely to meet weekly MVPA guidelines (9.57 h/day; 8.3%) than non-frail individuals (8.18 h/day; 1.1%; p<0.001). Frail individuals failed to demonstrate the patterns of the healthier individuals-higher levels of sedentary behaviour on Sundays and in the evenings and decreasing MVPA throughout the week. High sedentary behaviour and low MVPA were independently associated with higher levels of frailty, poor self-reported health, high ADL disability and higher healthcare usage. CONCLUSIONS: Many people over the age of 50, and most of those who are frail, were highly sedentary with very few meeting the recommended weekly levels of MVPA. Sedentary behaviour and MVPA were independently associated with frailty and adverse health outcomes in middle to older aged adults. Future research should focus on a longitudinal study to determine the temporal relationship between sedentary behaviour and frailty.