Mortality Risk Along the Frailty Spectrum: Data from the National Health and Nutrition Examination Survey 1999 to 2004.
ABSTRACT: OBJECTIVES:To determine the relationship between frailty and overall and cardiovascular mortality. DESIGN:Longitudinal mortality analysis. SETTING:National Health and Nutrition Examination Survey (NHANES) 1999-2004. PARTICIPANTS:Community-dwelling older adults aged 60 and older (N = 4,984; mean age 71.1 ± 0.19, 56% female). MEASUREMENTS:We used data from 1999-2004 cross-sectional NHANES and mortality data from the National Death Index, updated through December 2011. An adapted version of Fried's frailty criteria was used (low body mass index, slow walking speed, weakness, exhaustion, low physical activity). Frailty was defined as persons meeting 3 or more criteria, prefrailty as meeting 1 or 2 criteria, and robust (reference) as not meeting any criteria. The primary outcome was to evaluate the association between frailty and overall and cardiovascular mortality. Cox proportional hazard models were used to evaluate the association between risk of death and frailty category adjusted for age, sex, race, smoking, education, coronary artery disease, heart failure, nonskin cancer, diabetes, and arthritis. RESULTS:Half (50.4%) of participants were classified as robust, 40.3% as prefrail, and 9.2% as frail. Fully adjusted models demonstrated that prefrail (hazard ratio (HR) = 1.64, 95% confidence interval (CI) = 1.45-1.85) and frail (HR = 2.79, 95% CI = 2.35-3.30) participants had a greater risk of death and of cardiovascular death (prefrail: HR = 1.84, 95% CI = 1.45-2.34; frail: HR = 3.39, 95% CI = 2.45-4.70). CONCLUSION:Frailty and prefrailty are associated with increased risk of death. Demonstrating the association between prefrail status and mortality is the first step to identifying potential targets of intervention in future studies.
Project description:To quantify the prognostic importance of prefrailty and frailty in a population-based sample of cancer survivors.The Third National Health and Nutrition Examination Survey mortality-linked prospective cohort study.Eighty-nine survey locations across the United States.Population-based sample of older adults (average age 72.2) with a self-reported diagnosis of non-skin-related cancer (N = 416).The primary outcome was all-cause mortality. Frailty components included low weight for height, slow walking, weakness, exhaustion, and low physical activity. Participants with none of the five criteria were classified as nonfrail, those with one or two as prefrail, and those with three or more as frail.The prevalence of prefrailty was 37.3% and of frailty was 9.1%. During a median follow-up of 11.2 years, 319 (76.7%) participants died. Median survival was 13.9 years for participants classified as nonfrail, 9.5 years for those classified as prefrail, and 2.5 years for those classified as frail. Cancer survivors classified as prefrail (hazard ratio (HR) = 1.84, 95% confidence interval (CI) = 1.28-2.65, P = .001) or frail (HR = 2.79, 95% CI = 1.34-5.81, P = .006) had a higher risk of premature mortality than those classified as nonfrail.Prefrailty and frailty are prevalent clinical syndromes that may confer greater risk of premature mortality in older adult cancer survivors. Identifying frail cancer survivors and targeting interventions for them may be a strategy to improve survival after cancer.
Project description:OBJECTIVES:To determine the prevalence of frailty and the association of sociodemographic characteristics, clinical aspects, and functional capacity with the frailty status of community-dwelling older adults from Curitiba, Southern Brazil. METHODS:This cross-sectional observational study included 1,716 participants aged ?60 years. Frailty was assessed using the Fried phenotype indicators of weakness, exhaustion, low activity, slowness, and weight loss. Sociodemographic characteristics, clinical aspects, and functional capacity and functionality were evaluated and compared between the sexes and the different frailty statuses (non-frail, prefrail, and frail). Multinomial logistic regression models were used to identify associations (p<0.05). RESULTS:A high prevalence of frailty (15.8%) and prefrailty (65.3%) were observed, and both were higher in female than in male individuals. The most predominant frailty criterion was weakness, followed by exhaustion. Compared with the non-frail elderly, the prefrail and frail elderly were older in age and presented more health problems, greater dependency for basic and instrumental activities of daily living, and reduced lower extremity strength performance and functional mobility. The highest proportion of illiterate individuals, individuals with 1-4 years of education, widowed individuals, polypharmacy, and possible cognition problems and diseases were seen in the frail elderly group. Moreover, the risk of being prefrail and frail was higher in those who were older and had more health problems, higher body mass index, and reduced lower extremity strength performance. Greater calf circumference and independence in activities of daily living were protective factors for prefrailty and frailty. Furthermore, lower functional mobility increased the chances of being frail. CONCLUSIONS:The prevalence of frailty was more pronounced in female than in male individuals, mainly because of a decline in force. Prefrailty was 4 times more prevalent than frailty, and the presence of health problems and reduced functional capacity increased the chances of being prefrail and frail.
Project description:Frailty is a geriatric syndrome characterized by anabolic-catabolic imbalance and multisystem dysregulation resulting in increased adverse health outcomes, and is closely related with dietary habits in the general population. Although chronic inflammatory diseases are thought to accelerate development of frailty, correlations between rheumatoid arthritis (RA), frailty and dietary habits have not been examined. We performed a cross-sectional study using our cohort database (KURAMA cohort), and classified 306 participants into three groups (robust, prefrail and frail) according to the Study of Osteoporotic Fracture (SOF) criteria. Multivariate logistic analysis revealed that the presence of frailty/prefrailty was significantly correlated with the disease activity score (DAS28-ESR) (OR 1.70 (1.30-2.22), p?<?0.0001). Additional analyses of frailty and food intake showed that 5 foods (fish, meat, milk, vegetables and fruits) of 20 groups on the questionnaire were inversely associated with the prevalence of frail/prefrail categories. In multivariate analysis with the five nutrients, fish intake (>?two times a week) was an independent covariate negatively correlated with frailty/prefrailty (OR 0.35 (0.19-0.63), p?=?0.00060). In conclusion, habitual fish intake may play a key role in nutritional intervention to prevent progression of frailty and RA.
Project description:<h4>Background</h4>Frailty is a common condition among older adults increasing risk of adverse outcomes including mortality; however, little is known about the incidence or risk of specific causes of death among frail individuals.<h4>Methods</h4>Data came from the Health and Retirement Study (HRS; 2004-2012), linked to underlying cause-of-death information from the National Death Index (NDI). Community-dwelling HRS participants aged 65 and older who completed a general health interview and physical measurements (n = 10,490) were included in analysis. Frailty was measured using phenotypic model criteria-exhaustion, low weight, low energy expenditure, slow gait, and weakness. Underlying causes of death were determined using International Classification of Diseases, Version 10 codes. We used Cox proportional hazards and competing risks regression models to calculate and compare incidence of cause-specific mortality by frailty status.<h4>Results</h4>During follow-up, prefrail and frail older adults had significantly greater hazard of all-cause mortality compared to individuals without symptoms (adjusted hazard ratio [HR] prefrail: 1.85, 95% CI: 1.51, 2.25; HR frail: 2.75, 95% CI: 2.14, 3.53). Frailty was associated with 2.96 (95% CI: 2.17, 4.03), 2.82 (95% CI: 2.02, 3.94), 3.48 (95% CI: 2.17, 5.59), and 2.87 (95% CI: 1.47, 5.59) times greater hazard of death from heart disease, cancer, respiratory illness, and dementia, respectively.<h4>Conclusions</h4>Significantly greater risk of mortality from several different causes should be considered alongside the potential costs of screening and intervention for frailty in subspecialty and general geriatric clinical practice. Findings may help investigators estimate the potential impact of frailty reduction approaches on mortality.
Project description:BACKGROUND:Frailty is the loss of ability to withstand a physiological stressor and is associated with multiple adverse outcomes in older people. Trials to prevent or ameliorate frailty are in their infancy. A range of different outcome measures have been proposed, but current measures require either large sample sizes, long follow-up, or do not directly measure the construct of frailty. METHODS:We propose a composite outcome for frailty prevention trials, comprising progression to the frail state, death, or being too unwell to continue in a trial. To determine likely event rates, we used data from the English Longitudinal Study for Ageing, collected 4?years apart. We calculated transition rates between non-frail, prefrail, frail or loss to follow up due to death or illness. We used Markov state transition models to interpolate one- and two-year transition rates and performed sample size calculations for a range of differences in transition rates using simple and composite outcomes. RESULTS:The frailty category was calculable for 4650 individuals at baseline (2226 non-frail, 1907 prefrail, 517 frail); at follow up, 1282 were non-frail, 1108 were prefrail, 318 were frail and 1936 had dropped out or were unable to complete all tests for frailty. Transition probabilities for those prefrail at baseline, measured at wave 4 were respectively 0.176, 0.286, 0.096 and 0.442 to non-frail, prefrail, frail and dead/dropped out. Interpolated transition probabilities were 0.159, 0.494, 0.113 and 0.234 at two years, and 0.108, 0.688, 0.087 and 0.117 at one year. Required sample sizes for a two-year outcome in a two-arm trial were between 1040 and 7242 for transition from prefrailty to frailty alone, 246 to 1630 for transition to the composite measure, and 76 to 354 using the composite measure with an ordinal logistic regression approach. CONCLUSION:Use of a composite outcome for frailty trials offers reduced sample sizes and could ameliorate the effect of high loss to follow up inherent in such trials due to death and illness.
Project description:BACKGROUND:Older adults with visual impairments are at increased risk of negative health outcomes. Here, we investigate the association between visual impairment and frailty. METHODS:Cross-sectional and longitudinal relationships between visual impairment (distance visual acuity) and frailty (frailty phenotype criteria) were examined using data from the National Health and Nutrition Examination Survey (NHANES, 1999-2002, ?60 years) and the Women's Health and Aging Studies (WHAS III). Imbalance of potential confounders, particularly age, was addressed using propensity score-based adjustment. Multinomial logistic regression determined the odds of prefrailty and frailty at baseline in NHANES and ordinal logistic regression examined the odds of baseline and incident frailty over 3 years in WHAS III after adjustment for confounders and probability weighting (survey weights × inverse propensity scores). RESULTS:In NHANES (n = 2,639, 9% vision impairment), participants with visual impairment were more likely to be prefrail (odds ratio [OR] = 3.2; 95% confidence interval [CI]: 1.9-5.3) and frail (OR = 3.7; 95% CI: 1.5-9.2) than those without visual impairment. In WHAS III (n = 796, 26% mild, 37% moderate/severe vision impairment), participants with mild and moderate/severe vision impairment were more likely to be frail (OR = 2.0; 95% CI: 1.5-2.5; OR = 5.5; 95% CI: 4.2-7.2, respectively). A one-line worse visual acuity (0.1 logMAR increase) was associated with greater odds of frailty (OR = 1.5; 95% CI: 1.4-1.7). Of those non-frail at baseline (n = 549), moderate/severe visual impairment and one-line worse visual acuity was associated with greater odds of incident frailty (OR = 3.5; 95% CI: 1.4-8.4; OR = 1.3; 95% CI: 1.1-1.5, respectively) over 3 years. CONCLUSIONS:Visual impairment may be an important, yet understudied risk factor for frailty.
Project description:Importance:Frailty is a common geriatric syndrome of significant public health importance, yet there is limited understanding of the risk of frailty development at a population level. Objective:To estimate the global incidence of frailty and prefrailty among community-dwelling adults 60 years or older. Data Sources:MEDLINE, Embase, PsycINFO, Web of Science, CINAHL Plus, and AMED (Allied and Complementary Medicine Database) were searched from inception to January 2019 without language restrictions using combinations of the keywords frailty, older adults, and incidence. The reference lists of eligible studies were hand searched. Study Selection:In the systematic review, 2 authors undertook the search, article screening, and study selection. Cohort studies that reported or had sufficient data to compute incidence of frailty or prefrailty among community-dwelling adults 60 years or older at baseline were eligible. Data Extraction and Synthesis:The methodological quality of included studies was assessed using The Joanna Briggs Institute's Critical Appraisal Checklist for Prevalence and Incidence Studies. Meta-analysis was conducted using a random-effects (DerSimonian and Laird) model. Main Outcomes and Measures:Incidence of frailty (defined as new cases of frailty among robust or prefrail individuals) and incidence of prefrailty (defined as new cases of prefrailty among robust individuals), both over a specified duration. Results:Of 15 176 retrieved references, 46 observational studies involving 120 805 nonfrail (robust or prefrail) participants from 28 countries were included in this systematic review. Among the nonfrail individuals who survived a median follow-up of 3.0 (range, 1.0-11.7) years, 13.6% (13 678 of 100 313) became frail, with the pooled incidence rate being 43.4 (95% CI, 37.3-50.4; I2 = 98.5%) cases per 1000 person-years. The incidence of frailty was significantly higher in prefrail individuals than robust individuals (pooled incidence rates, 62.7 [95% CI, 49.2-79.8; I2 = 97.8%] vs 12.0 [95% CI, 8.2-17.5; I2 = 94.9%] cases per 1000 person-years, respectively; P for difference < .001). Among robust individuals in 21 studies who survived a median follow-up of 2.5 (range, 1.0-10.0) years, 30.9% (9974 of 32 268) became prefrail, with the pooled incidence rate being 150.6 (95% CI, 123.3-184.1; I2 = 98.9%) cases per 1000 person-years. The frailty and prefrailty incidence rates were significantly higher in women than men (frailty: 44.8 [95% CI, 36.7-61.3; I2 = 97.9%] vs 24.3 [95% CI, 19.6-30.1; I2 = 8.94%] cases per 1000 person-years; prefrailty: 173.2 [95% CI, 87.9-341.2; I2 = 99.1%] vs 129.0 [95% CI, 73.8-225.0; I2 = 98.5%] cases per 1000 person-years). The incidence rates varied by diagnostic criteria and country income level. The frailty and prefrailty incidence rates were significantly reduced when accounting for the risk of death. Conclusions and Relevance:Results of this study suggest that community-dwelling older adults are prone to developing frailty. Increased awareness of the factors that confer high risk of frailty in this population subgroup is vital to inform the design of interventions to prevent frailty and to minimize its consequences.
Project description:OBJECTIVES:To compare the ability of frailty status to predict fall risk with that of community fall risk screening tools. DESIGN:Analysis of cross-sectional and longitudinal data from NHATS. SETTING:National Health and Aging Trend Study (NHATS) 2011-2015. PARTICIPANTS:Individuals aged 65 and older (N = 7,392). MEASUREMENTS:Fall risk was defined according to the Stopping Elderly Accidents, Deaths and Injuries (STEADI) initiative. Frailty was defined as exhaustion, weight loss, low activity, slow gait speed, and weak grip strength. Robust was defined as meeting 0 criteria, prefrailty as 1 or 2 criteria, and frailty as 3 or more criteria. Falls were self-reported and ascertained using NHATS subsequent rounds (2012-2015). We compared the ability of frailty to predict future falls with that of STEADI score, adjusting for age, race, sex, education, comorbidities, hearing and vision impairment, and disability. RESULTS:Of the 7,392 participants (58.5% female), there 3,545 (48.0%) were classified as being at low risk of falling, 2,966 (40.1%) as being at moderate risk, and 881 (11.9%) as being at high risk. The adjusted risk of falling over the 4 subsequent years was 2.5 times as great for the moderate-risk group (hazard ratio (HR) = 2.50, 95% confidence interval (CI) = 2.16-2.89) and almost 4 times as great (HR = 3.79, 95% CI = 2.76-5.21) for the high-risk group as for the low-risk group. Risk of falling was greater for those who were prefrail (HR = 1.34, 95% CI 1.16-1.55) and frail (HR = 1.20, 95% CI = 0.94-1.54) than for those who were robust. CONCLUSION:STEADI score is a strong predictor of future falls. Addition of frailty status does not improve the ability of the STEADI measure to predict future falls.
Project description:PURPOSE:To investigate the effect of early frailty transitions on 15-year mortality risk. METHODS:Longitudinal data analysis of the Hispanic Established Populations for the Epidemiological Study of the Elderly involving 1171 community-dwelling Mexican Americans aged ≥67 years and older. Frailty was determined using the modified frailty phenotype, including unintentional weight loss, weakness, self-reported exhaustion, and slow walking speed. Participants were defined at baseline as nonfrail, prefrail, or frail and divided into nine transition groups, during a 3-year observation period. RESULTS:Mean age was 77.0 years (standard deviation [SD] = 5.3) and 59.1% were female. Participants who transitioned from prefrail to frail (hazard ratio [HR] = 1.68, 95% confidence interval [CI] = 1.23-2.28), frail to prefrail (HR = 1.54, 95% CI = 1.05-2.28); or who remained frail (HR = 1.72, 95% CI = 1.21-2.44), had significant higher 15-year mortality risk than those who remained nonfrail. Participants transitioning from frail to nonfrail had a similar 15-year mortality risk as those who remained nonfrail (HR = 0.96, 95% CI = 0.53-1.72). Weight loss and slow walking speed were associated with transitions to frailty. CONCLUSIONS:An early transition from frail to nonfrail in older Mexican Americans was associated with a 4% decrease in mortality compared with those who remained nonfrail, although this difference was not statistically significant. Additional longitudinal research is needed to understand positive transitions in frailty.
Project description:BACKGROUND:Physical frailty, characterized by reduced physiologic complexity and ability to cope with stressors, is closely associated with cognitive impairment, which increases the risk of poor clinical outcomes. To better capture the association between frailty and cognitive impairment, a new construct, cognitive frailty, has been proposed. Cognitive frailty is a clinical condition characterized by the simultaneous presence of physical frailty and cognitive impairment. There is little evidence on the relationship between physical frailty and cognition, as well as cognitive frailty, in Chinese older adults. We aimed to elucidate whether physical frailty is associated with cognitive impairment in an older Chinese population. METHODS:Data were obtained from the China Comprehensive Geriatric Assessment Study. The sample comprised 3202 community-dwelling adults, aged 60 years and older, from seven Chinese cities. Physical frailty was assessed using a modified, four-item version of the Fried criteria, according to frailty phenotype. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). RESULTS:The prevalence of physical frailty, prefrailty, cognitive impairment, and cognitive frailty was 9.9, 33.9, 7.5, and 2.3%, respectively (weighted: 8.8, 33.8, 6.5, and 2.0%). The prevalence of the combination of prefrail/frail and cognitive impairment was 5.1% (weighted 4.5%). Frail participants performed worse on global cognition and all cognitive domains than robust and prefrail participants. The MMSE total score was positively correlated with walking speed and negatively correlated with age and frailty. A multivariate logistic regression revealed that after adjusting for age, gender, education level, living area, and chronic diseases, frailty, exhaustion, slowness, and inactivity were significantly associated with poor global cognition. CONCLUSIONS:The standard prevalence of physical frailty, prefrailty, cognitive impairment, and cognitive frailty in community-dwelling older adults in China was 8.8, 33.8, 6.5, and 2.0%, respectively. Frailty, exhaustion, slowness, and inactivity were significantly associated with poor global cognition.