Frailty Trajectories in an Elderly Population-Based Cohort.
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ABSTRACT:
SUBMITTER: Chamberlain AM
PROVIDER: S-EPMC4762174 | biostudies-literature | 2016 Feb
REPOSITORIES: biostudies-literature
Publications
Frailty Trajectories in an Elderly Population-Based Cohort.
Chamberlain Alanna M AM Finney Rutten Lila J LJ Manemann Sheila M SM Yawn Barbara P BP Jacobson Debra J DJ Fan Chun C Grossardt Brandon R BR Roger Véronique L VL St Sauver Jennifer L JL
Journal of the American Geriatrics Society 20160201 2
<h4>Objectives</h4>To identify distinct frailty trajectories (clusters of individuals following a similar progression of frailty over time) in an aging population and to estimate associations between frailty trajectories and emergency department visits, hospitalizations, and all-cause mortality.<h4>Design</h4>Population-based cohort study.<h4>Setting</h4>Olmsted County, Minnesota.<h4>Participants</h4>Olmsted County, Minnesota residents aged 60-89 in 2005.<h4>Measurements</h4>Longitudinal changes ...[more]
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Project description:BackgroundMaintaining physical function and delaying frailty are of significant importance in both quality of life and health longevity for successful aging. The objective of this study is to investigate whether different trajectories of long-term physical activity (PA) participation are associated with subsequent motor function declines and incident frailty in middle-aged and elderly adults.Materials and methodsData from 8,227 aged ≥ 50 years adults enrolled in the English Longitudinal Study of Aging were analyzed. Long-term PA participation trajectories were assessed using group-based trajectory modeling over the first 6-year period from wave 1 (2002-2003) to wave 4 (2008-2009). The longitudinal associations of PA trajectories with motor function declines and incident frailty were evaluated by a linear mixed model and Cox regression model, respectively, with follow-up of 10 years from wave 4 to wave 9 (2018-2019).ResultsFive distinct trajectories of long-term PA participation were identified in the aging cohort, including persistently low-active trajectory (N = 2,039), increasing active trajectory (N = 1,711), declining active trajectory (N = 216), persistently moderate-active trajectory (N = 2,254), and persistently high-active trajectory (N = 2,007). Compared with the persistently low-active group, the participants in persistently moderate- and high-active groups experienced significantly decelerated grip strength decline, decreased gait speed decline, and faster chair rises after multiple-adjustment. Similarly, participants maintaining moderate- and high-active PA were also associated with a lower risk of incident frailty (multiple-adjusted hazard ratio: 0.70, 95% confidence interval: 0.62-0.80, and 0.42, 95% CI: 0.36-0.49, respectively), compared with those with persistently low PA. Notably, the participants with the increasing active trajectory got similar health benefits as those with persistently moderate and high levels of PA.ConclusionIn addition to persistent PA, increasing PA was linked to a slower decline in motor function and lower risk of incident frailty in the cohort. Our findings suggest that regular PA is never too late.
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Project description:BackgroundTimely recognition of the end of life allows patients to discuss preferences and make advance plans, and clinicians to introduce appropriate care. We examined changes in frailty over 1 year, with the aim of identifying trajectories that could indicate where an individual is at increased risk of all-cause mortality and may require palliative care.MethodsElectronic health records from 13,149 adults (cases) age 75 and over who died during a 1-year period (1 January 2015 to 1 January 2016) were age, sex and general practice matched to 13,149 individuals with no record of death over the same period (controls). Monthly frailty scores were obtained for 1 year prior to death for cases, and from 1 January 2015 to 1 January 2016 for controls using the electronic frailty index (eFI; a cumulative deficit measure of frailty, available in most English primary care electronic health records, and ranging in value from 0 to 1). Latent growth mixture models were used to investigate longitudinal patterns of change and associated impact on mortality. Cases were reweighted to the population level for tests of diagnostic accuracy.ResultsThree distinct frailty trajectories were identified. Rapidly rising frailty (initial increase of 0.022 eFI per month before slowing from a baseline eFI of 0.21) was associated with a 180% increase in mortality (OR 2.84, 95% CI 2.34-3.45) for 2.2% of the sample. Moderately increasing frailty (eFI increase of 0.007 per month, with baseline of 0.26) was associated with a 65% increase in mortality (OR 1.65, 95% CI 1.54-1.76) for 21.2% of the sample. The largest (76.6%) class was stable frailty (eFI increase of 0.001 from a baseline of 0.26). When cases were reweighted to population level, rapidly rising frailty had 99.1% specificity and 3.2% sensitivity (positive predictive value 19.8%, negative predictive value 93.3%) for predicting individual risk of mortality.ConclusionsPeople aged over 75 with frailty who are at highest risk of death have a distinctive frailty trajectory in the last 12 months of life, with a rapid initial rise from a low baseline, followed by a plateau. Routine measurement of frailty can be useful to support clinicians to identify people with frailty who are potential candidates for palliative care, and allow time for intervention.
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Project description:IntroductionFrailty is an indicator of health status in old age and a common clinical syndrome in older adults that carries an increased risk of poor health outcomes, including falls, incidents of disability, hospitalization, and mortality. This study aimed to identify the different trajectories of frailty and the factors related to frailty among Mexican older adults over time.MethodsData are from a four-wave panel composed of older Mexican adults from 2001 to 2015 of the Mexican Health and Aging Study (MHAS). Frailty is the accumulation of deficits using a frailty index. A multilevel analysis, using hierarchical models, was applied to know the changes of frailty trajectories and what factors are related to it.ResultsBeing female, older, being widowhood, and having a lower level of education were risk factors for having a high frailty index and lower financial satisfaction doing activities at home have adverse effects.ConclusionThe findings of this work present information about the prevalence of frailty considering the proportion of deficits that individuals possess and their main associated components in older Mexican adults. It is necessary to improve socioeconomic health conditions in phases before old age to avoid developing frailty in the future.
| S-EPMC9286518 | biostudies-literature
Project description:BackgroundEmerging evidence suggests that there is significant variability in the progression of frailty in aging. We aimed to identify latent subpopulations of frailty trajectories, and examine their clinical and biological correlates.MethodsWe characterized frailty using a 41-item cumulative deficit score at baseline and annual visits up to 12 years in 681 older adults (55% women, mean age 74·6 years). Clinical risk profile and walking while talking performance as a clinical marker of trajectories were examined. Mortality risk associated with trajectories was evaluated using Cox regression adjusted for established survival predictors, and reported as hazard ratios (HR). Proteome-wide analysis was done.FindingsLatent class modeling identified 4 distinct frailty trajectories: relatively stable (34·4%) as well as mild (36·1%), moderate (24·1%) and severely frail (5·4%). Four distinct classes of frailty trajectories were also shown in an independent sample of 515 older adults (60% women, 68% White, 26% Black). The stable group took a median of 31 months to accumulate one additional deficit compared to 20 months in the severely frail group. The worst trajectories were associated with modifiable risk factors such as low education, living alone, obesity, and physical inactivity as well as slower walking while talking speed. In the pooled sample, mild (HR 2·33, 95% CI 1·30-4·18), moderate (HR 2·49, 95% CI 1·33-4·66), and severely frail trajectories (HR 5·28, 95% CI 2·68-10·41) had higher mortality compared to the stable group. Proteomic analysis showed 11 proteins in lipid metabolism and growth factor pathways associated with frailty trajectories.ConclusionFrailty shows both stable and accelerated patterns in aging, which can be distinguished clinically and biologically.
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Project description:ObjectiveTo assess the prospective associations of baseline and long term trajectories of physical activity on mortality from all causes, cardiovascular disease, and cancer.DesignPopulation based cohort study.SettingAdults from the general population in the UK.Participants14 599 men and women (aged 40 to 79) from the European Prospective Investigation into Cancer and Nutrition-Norfolk cohort, assessed at baseline (1993 to 1997) up to 2004 for lifestyle and other risk factors; then followed to 2016 for mortality (median of 12.5 years of follow-up, after the last exposure assessment).Main exposurePhysical activity energy expenditure (PAEE) derived from questionnaires, calibrated against combined movement and heart rate monitoring.Main outcome measuresMortality from all causes, cardiovascular disease, and cancer. Multivariable proportional hazards regression models were adjusted for age, sex, sociodemographics, and changes in medical history, overall diet quality, body mass index, blood pressure, triglycerides, and cholesterol levels.ResultsDuring 171 277 person years of follow-up, 3148 deaths occurred. Long term increases in PAEE were inversely associated with mortality, independent of baseline PAEE. For each 1 kJ/kg/day per year increase in PAEE (equivalent to a trajectory of being inactive at baseline and gradually, over five years, meeting the World Health Organization minimum physical activity guidelines of 150 minutes/week of moderate-intensity physical activity), hazard ratios were: 0.76 (95% confidence interval 0.71 to 0.82) for all cause mortality, 0.71 (0.62 to 0.82) for cardiovascular disease mortality, and 0.89 (0.79 to 0.99) for cancer mortality, adjusted for baseline PAEE, and established risk factors. Similar results were observed when analyses were stratified by medical history of cardiovascular disease and cancer. Joint analyses with baseline and trajectories of physical activity show that, compared with consistently inactive individuals, those with increasing physical activity trajectories over time experienced lower risks of mortality from all causes, with hazard ratios of 0.76 (0.65 to 0.88), 0.62 (0.53 to 0.72), and 0.58 (0.43 to 0.78) at low, medium, and high baseline physical activity, respectively. At the population level, meeting and maintaining at least the minimum physical activity recommendations would potentially prevent 46% of deaths associated with physical inactivity.ConclusionsMiddle aged and older adults, including those with cardiovascular disease and cancer, can gain substantial longevity benefits by becoming more physically active, irrespective of past physical activity levels and established risk factors. Considerable population health impacts can be attained with consistent engagement in physical activity during mid to late life.
| S-EPMC6592407 | biostudies-literature
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Project description:PurposeAcute illness severity predicts mortality in intensive care unit (ICU) patients, however, its predictive value decreases over time in ICU. Typically after 10 days, pre-ICU (antecedent) characteristics become more predictive of mortality, defining the onset of persistent critical illness (PerCI). How patient frailty affects development and death from PerCI is unknown.MethodsWe conducted a secondary analysis of data from a prospective binational cohort study including 269,785 critically ill adults from 168 ICUs in Australia and New Zealand, investigating whether frailty measured with the Clinical Frailty Scale (CFS) changes the timing of onset and risk of developing PerCI and of subsequent in-hospital mortality. We assessed associations between frailty (CFS ≥ 5) and mortality prediction using logistic regression and area under the receiver operating characteristics (AUROC) curves.Results2190 of 50,814 (4.3%) patients with frailty (CFS ≥ 5) versus 6624 of 218,971 (3%) patients without frailty (CFS ≤ 4) developed PerCI (P < 0.001). Among patients with PerCI, 669 of 2190 (30.5%) with frailty and 1194 of 6624 without frailty (18%) died in hospital (P < 0.001). The time point defining PerCI onset did not vary with frailty degree; however, with increasing length of ICU stay, inclusion of frailty progressively improved mortality discrimination (0.1% AUROC improvement on ICU day one versus 3.6% on ICU day 17).ConclusionCompared to patients without frailty, those with frailty have a higher chance of developing and dying from PerCI. Moreover the importance of frailty as a predictor of mortality increases with ICU length of stay. Future work should explore incorporation of frailty in prognostic models, particularly for long-staying patients.
| S-EPMC8866256 | biostudies-literature
Project description:BackgroundChina is among the largest and fastest aging countries. The elderly population is more vulnerable, with higher proportion of inappropriate sleep duration and risk of mortality, compared with young and middle-aged adults. Single-measured sleep duration has been associated with mortality, but the health effects of long-term sleep duration trajectories remain unknown. This study aimed to explore the prospective associations between sleep duration trajectories and all-cause mortality among Chinese elderly.MethodsParticipants (n = 3,895; median age: 82 years; females: 53.3%) who reported sleep duration in all three surveys (2005, 2008, and 2011) from the community-based Chinese Longitudinal Healthy Longevity Survey (CLHLS) were followed up until 2019 (about 8 years). We identified sleep duration trajectories by latent class mixed model and explored their association with all-cause mortality using Cox hazard proportional regression and Laplace regression models. Further, stratified analysis by demographic characteristics and lifestyles and sensitivity analysis by lag effect, health-related factors, and inverse probability weighting were used to verify the robustness of the association. In addition, we explored the threshold effect of baseline sleep duration on the risk of all-cause mortality.ResultsWe documented 1,881 all-cause deaths during 16,689 person-years of follow-up. Five sleep duration trajectories were identified: moderately increased trajectory (28.1%), rapidly increased trajectory (7.2%), persistent sleep trajectory of 7 h (33.7%), moderately decreased trajectory (21.3%), and rapidly decreased trajectory (9.7%). Compared with the persistent sleep trajectory of 7 h, the multivariable-adjusted HRs (95%CI) for moderately increased trajectory, rapidly increased trajectory, moderately decreased trajectory, and rapidly decreased trajectory were 1.21 (1.08, 1.36), 1.21 (1.01, 1.44), 0.95 (0.82, 1.10), and 0.93 (0.78, 1.11), respectively; and the corresponding difference in median survival time (95%CI) were -0.53 (-1.01, -0.05), -0.43 (0.16, -1.02), 0.26 (-0.34, 0.86), and 0.25 (-0.51, 1.02), respectively. Stratified and sensitivity analyses showed consistent results. Threshold analysis indicated a sharply increased risk of mortality in participants whose sleep exceeds 9 h (HR = 1.20, 95%CI: 1.11, 1.30).ConclusionCompared with the persistent sleep trajectory of 7 h, moderately and rapidly increased sleep duration trajectories were associated with higher subsequent mortality in Chinese elderly. Those who report sleep exceeding 9 h may be at high risk for all-cause mortality.
| S-EPMC10286431 | biostudies-literature
Project description:BackgroundA threshold Clinical Frailty Scale (CFS) of 5 (indicating mild frailty) has been proposed to guide ICU admission for UK patients with coronavirus disease 2019 (COVID-19) pneumonia. However, the impact of frailty on mortality with (non-COVID-19) pneumonia in critical illness is unknown. We examined the triage utility of the CFS in patients with pneumonia requiring ICU.MethodsWe conducted a retrospective cohort study of adult patients admitted with pneumonia to 170 ICUs in Australia and New Zealand from January 1, 2018 to September 31, 2019. We classified patients as: non-frail (CFS 1-4) frail (CFS 5-8), mild/moderately frail (CFS 5-6),and severe/very severely frail (CFS 7-8). We evaluated mortality (primary outcome) adjusting for site, age, sex, mechanical ventilation, pneumonia type and illness severity. We also compared the proportion of ICU bed-days occupied between frailty categories.Results1852/5607 (33%) patients were classified as frail, including1291/3056 (42%) of patients aged >65 yr, who would potentially be excluded from ICU admission under UK-based COVID-19 triage guidelines. Only severe/very severe frailty scores were associated with mortality (adjusted odds ratio [aOR] for CFS=7: 3.2; 95% confidence interval [CI]: 1.3-7.8; CFS=8 [aOR: 7.2; 95% CI: 2.6-20.0]). These patients accounted for 7% of ICU bed days. Vulnerability (CFS=4) and mild frailty (CFS=5) were associated with a similar mortality risk (CFS=4 [OR: 1.6; 95% CI: 0.7-3.8]; CFS=5 [OR: 1.6; 95% CI: 0.7-3.9]).ConclusionsPatients with severe and very severe frailty account for relatively few ICU bed days as a result of pneumonia, whilst adjusted mortality analysis indicated little difference in risk between patients in vulnerable, mild, and moderate frailty categories. These data do not support CFS ≥5 to guide ICU admission for pneumonia.
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