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Objectives To determine whether commonly used frailty scales exhibit shared characteristics when applied to a representative sample of middle-aged and older Europeans. Design Secondary analysis of the Survey of Health, Ageing, and Retirement in Europe ( SHARE). Setting Eleven European countries. Participants Community-dwelling adults (N = 27,527; mean age 65.3 ± 10.5, 55% female). Measurements Frailty was assessed using SHARE-operationalized versions of seven frailty scales: Edmonton Frail Scale, FRAIL scale, Groningen Frailty Indicator, frailty phenotype, Tilburg Frailty Indicator, a 70-item frailty index ( FI), and a 44-item frailty index based on Comprehensive Geriatric Assessment. Results All frailty scales demonstrated right-skewed density distributions. On all scales, frailty scores increased nonlinearly with age, between 1% ( FRAIL) and 3.6% ( FI) per year on a log scale. Frailty scores on all scales exhibited dose-response relationships with 5-year mortality. On all scales, women had higher frailty scores than men of the same age but demonstrated better survival than did men with the same frailty score. On all scales except the frailty phenotype, 99% of participants had scores below the scale's theoretical maximum. Conclusion On each frailty scale, frailty score increased nonlinearly with age, mortality risk increased with frailty score, and women had higher scores than men but demonstrated better survival. Each scale except the frailty phenotype demonstrated an upper limit to frailty below the scale's theoretical maximum. Across commonly used frailty scales, these characteristics are common in nature but differ in magnitude. [ABSTRACT FROM AUTHOR]

Objectives To operationalize frailty using eight scales and to compare their content validity, feasibility, prevalence estimates of frailty, and ability to predict all-cause mortality. Design Secondary analysis of the Survey of Health, Ageing and Retirement in Europe ( SHARE). Setting Eleven European countries. Participants Individuals aged 50 to 104 (mean age 65.3 ± 10.5, 54.8% female, N = 27,527). Measurements Frailty was operationalized using SHARE data based on the Groningen Frailty Indicator, the Tilburg Frailty Indicator, a 70-item Frailty Index ( FI), a 44-item FI based on a Comprehensive Geriatric Assessment ( FI- CGA), the Clinical Frailty Scale, frailty phenotype (weighted and unweighted versions), the Edmonton Frail Scale, and the FRAIL scale. Results All scales had fewer than 6% of cases with at least one missing item, except the SHARE-frailty phenotype (11.1%) and the SHARE-Tilburg (12.2%). In the SHARE-Groningen, SHARE-Tilburg, SHARE-frailty phenotype, and SHARE- FRAIL scales, death rates were 3 to 5 times as high in excluded cases as in included ones. Frailty prevalence estimates ranged from 6% ( SHARE- FRAIL) to 44% ( SHARE-Groningen). All scales categorized 2.4% of participants as frail. Of unweighted scales, the SHARE- FI and SHARE-Edmonton scales most accurately predicted mortality at 2 ( SHARE- FI area under the receiver operating characteristic curve ( AUC) = 0.77, 95% confidence interval ( CI) = 0.75-0.79); SHARE-Edmonton AUC = 0.76, 95% CI = 0.74-0.79) and 5 (both AUC = 0.75, 95% CI = 0.74-0.77) years. The continuous score of the weighted SHARE-frailty phenotype ( AUC = 0.77, 95% CI = 0.75-0.78) predicted 5-year mortality better than the unweighted SHARE-frailty phenotype ( AUC = 0.70, 95% CI = 0.68-0.71), but the categorical score of the weighted SHARE-frailty phenotype did not ( AUC = 0.70, 95% CI = 0.68-0.72). Conclusion Substantive differences exist between scales in their content validity, feasibility, and ability to predict all-cause mortality. These frailty scales capture related but distinct groups. Weighting items in frailty scales can improve their predictive ability, but the trade-off between specificity, predictive power, and generalizability requires additional evaluation. [ABSTRACT FROM AUTHOR]

Background: on an individual level, lower-income has been associated with disability, morbidity and death. On a population level, the relationship of economic indicators with health is unclear.Objective: the purpose of this study was to evaluate relative fitness and frailty in relation to national income and healthcare spending, and their relationship with mortality.Design and setting: secondary analysis of data from the Survey of Health, Ageing and Retirement in Europe (SHARE); a longitudinal population-based survey which began in 2004.Subjects: a total of 36,306 community-dwelling people aged 50 and older (16,467 men; 19,839 women) from the 15 countries which participated in the SHARE comprised the study sample. A frailty index was constructed as the proportion of deficits present in relation to the 70 deficits available in SHARE. The characteristics of the frailty index examined were mean, prevalence of frailty and proportion of the fittest group.Results: the mean value of the frailty index was lower in higher-income countries (0.16 ± 0.12) than in lower-income countries (0.20 ± 0.14); the overall mean frailty index was negatively correlated with both gross domestic product (r = −0.79; P < 0.01) and health expenditure (r = −0.63; P < 0.05). Survival in non-frail participants at 24 months was not associated with national income (P = 0.19), whereas survival in frail people was greater in higher-income countries (P < 0.05).Conclusions: a country's level of frailty and fitness in adults aged 50+ years is strongly correlated with national economic indicators. In higher-income countries, not only is the prevalence of frailty lower, but frail people also live longer. [ABSTRACT FROM AUTHOR]

Background Lacking long-term placebo-controlled trials of cholinesterase inhibitors (ChEIs) in Alzheimer's disease, how decline is modeled is crucial to interpreting the effects of long-term, open-label use. We aimed to: 1) understand changes in cognition and function in people taking galantamine; (2) identify treatment subgroups. Methods This is an open-label long-term extension (up to 48 months) of two placebo-controlled clinical trials from Europe and Canada. At baseline, 240 patients with mild-moderate Alzheimer's disease at baseline had received galantamine continuously for 36 months. The trajectory of scores on the Alzheimer's Disease Assessment Scale—Cognitive Subscale (ADAS-Cog) and the Disability Assessment for Dementia (DAD) was modeled over 48 months. Goodness of fit was compared using normalized residuals and by calculating correlation coefficients between observed and fitted data. Iterative K-means clustering identified subgroups. Results Of 240 patients, 51 (21%) withdrew between months 36–48 (nine died and 12 with adverse events). The mean ADAS-Cog worsened from 22.6 (mean) ± 8.6 (SD) at baseline to 31.3 ± 3.1, with similar changes in the DAD. The logistic function fit better (ADAS-Cog norm of residuals = 2.05, r = 0.993; DAD = 2.21, r = 0.998) than the commonly used Stern equation (ADAS-Cog = 4.22, r = 0.944; DAD = 7.51, r = 0.986). K-means clustering identified three stable groups; least decline (n = 82), persistent progression (n = 75), and an intermediate group (n = 82). Initial conditions were important: the mean ADAS-Cog score for those with least decline was 15 ± 8, better than both the intermediate group (20 ± 9) and persistent progressors (30 ± 10; p < 0.001). Conclusions Alzheimer's disease patients show variable long-term decline that is best modeled as a logistic function, not as linear decline. Over 48 months, about one-third of patients showed little decline, while one-third showed important decline. Copyright © 2007 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]