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Frailty Index in Europeans: association with determinants of health.

ABSTRACT: The Frailty Index (FI) summarizes differences in health status within individuals, and the determinants of health drive that variability. The aim of the present study was to investigate the influence of education, income, smoking, alcohol intake and parental longevity on the FI variability in subjects of the same chronological age group.Analyses were based on a 40-item FI based on the first wave of the Survey of Health, Aging and Retirement in Europe (SHARE, http://www.share-project.org/), including 29?905 participants aged ?50 years from 12 countries. For each sex, the sample was divided into age categories (50s, 60s, 70s, 80s and ?90), and FI quartiles within age categories were calculated. Multivariate ordinal regressions were computed to assess the relative contribution of the health determinants on the FI quartiles in each age group.In women, the most significant multivariate predictors were years of education (odds ratios [OR] around 0.9), and difficulties making ends meet (OR between 1.8 and 2.1). In men, the most significant multivariate predictors were years of education (OR around 0.9), difficulties making ends meet (OR between 1.6 and 2.1), mother's age at death (OR under 1), and father's age at death (OR under 1).Consistently with the literature, education and income explained, in both sexes, cross-sectional variability in FI in subjects of the same chronological age group. The influence of parental longevity seemed to be greater in men, which mirrors previous studies showing that genetic factors might have a higher impact on longevity in men.

SUBMITTER: Romero-Ortuno R

PROVIDER: S-EPMC3843989 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

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Frailty Index in Europeans: association with determinants of health.

Romero-Ortuno Roman R

Geriatrics & gerontology international 20130723 2

<h4>Aim</h4>The Frailty Index (FI) summarizes differences in health status within individuals, and the determinants of health drive that variability. The aim of the present study was to investigate the influence of education, income, smoking, alcohol intake and parental longevity on the FI variability in subjects of the same chronological age group.<h4>Methods</h4>Analyses were based on a 40-item FI based on the first wave of the Survey of Health, Aging and Retirement in Europe (SHARE, http://ww ...[more]

PMID: 23879634

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Project description:ObjectiveTo create an electronic frailty index (eFRAGICAP) using electronic health records (EHR) in Catalunya (Spain) and assess its predictive validity with a two-year follow-up of the outcomes: homecare need, institutionalization and mortality in the elderly. Additionally, to assess its concurrent validity compared to other standardized measures: the Clinical Frailty Scale (CFS) and the Risk Instrument for Screening in the Community (RISC).MethodsThe eFRAGICAP was based on the electronic frailty index (eFI) developed in United Kingdom, and includes 36 deficits identified through clinical diagnoses, prescriptions, physical examinations, and questionnaires registered in the EHR of primary health care centres (PHC). All subjects > 65 assigned to a PHC in Barcelona on 1st January, 2016 were included. Subjects were classified according to their eFRAGICAP index as: fit, mild, moderate or severe frailty. Predictive validity was assessed comparing results with the following outcomes: institutionalization, homecare need, and mortality at 24 months. Concurrent validation of the eFRAGICAP was performed with a sample of subjects (n = 333) drawn from the global cohort and the CFS and RISC. Discrimination and calibration measures for the outcomes of institutionalization, homecare need, and mortality and frailty scales were calculated.Results253,684 subjects had their eFRAGICAP index calculated. Mean age was 76.3 years (59.5% women). Of these, 41.1% were classified as fit, and 32.2% as presenting mild, 18.7% moderate, and 7.9% severe frailty. The mean age of the subjects included in the validation subsample (n = 333) was 79.9 years (57.7% women). Of these, 12.6% were classified as fit, and 31.5% presented mild, 39.6% moderate, and 16.2% severe frailty. Regarding the outcome analyses, the eFRAGICAP was good in the detection of subjects who were institutionalized, required homecare assistance, or died at 24 months (c-statistic of 0.841, 0.853, and 0.803, respectively). eFRAGICAP was also good in the detection of frail subjects compared to the CFS (AUC 0.821) and the RISC (AUC 0.848).ConclusionThe eFRAGICAP has a good discriminative capacity to identify frail subjects compared to other frailty scales and predictive outcomes.

Project description:ImportanceFrail patients are known to have poor perioperative outcomes. There is a paucity of literature investigating how the Modified Frailty Index (mFI), a validated measure of frailty, is associated with unplanned readmission among military veterans following surgery.ObjectiveTo understand the association between frailty and 30-day postoperative unplanned readmission.Design, setting, and participantsA retrospective cohort study was conducted among adult patients who underwent surgery and were discharged alive from Veterans Affairs hospitals for orthopedic, general, and vascular conditions between October 1, 2007, and September 30, 2014, with a postoperative length of stay between 2 and 30 days.ExposureFrailty, as calculated by the 11 variables on the mFI.Main outcomes and measuresThe primary outcome of interest is 30-day unplanned readmission. Secondary outcomes included any 30-day predischarge or postdischarge complication, 30-day postdischarge mortality, and 30-day emergency department visit.ResultsThe study sample included 236 957 surgical procedures (among 223 877 men and 13 080 women; mean [SD] age, 64.0 [11.3] years) from high-volume surgical specialties: 101 348 procedures (42.8%) in orthopedic surgery, 92 808 procedures (39.2%) in general surgery, and 42 801 procedures (18.1%) in vascular surgery. The mFI was associated with readmission (odds ratio [OR], 1.11; 95% CI, 1.10-1.12; R2 = 10.3%; C statistic, 0.71). Unadjusted rates of overall 30-day readmission (26 262 [11.1%]), postdischarge emergency department visit (34 204 [14.4%]), any predischarge (13 855 [5.9%]) or postdischarge (14 836 [6.3%]) complication, and postdischarge mortality (1985 [0.8%]) varied by frailty in a dose-dependent fashion. In analysis by individual mFI components using Harrell ranking, impaired functional status, identified as nonindependent functional status (OR, 1.16; 95% CI, 1.11-1.21; P < .01) or having a residual deficit from a prior cerebrovascular accident (OR, 1.17; 95% CI, 1.11-1.22; P < .01), contributed most to the ability of the mFI to anticipate readmission compared with the other components. Acutely impaired sensorium (OR, 1.12; 95% CI, 0.99-1.27; P = .08) and history of a myocardial infarction within 6 months (OR, 0.93; 95% CI, 0.81-1.06; P = .28) were not significantly associated with readmission.Conclusions and relevanceThe mFI is associated with poor surgical outcomes, including readmission, primarily due to impaired functional status. Targeting potentially modifiable aspects of frailty preoperatively, such as improving functional status, may improve perioperative outcomes and decrease readmissions.

Project description:BackgroundFrailty has been associated with a decline in sensory and motor function. However, given that different frailty measures were shown to overlap but also differ in their diagnostic properties, sensory and motor correlates of frailty might be different depending on the operationalization of frailty. Our objective was to identify sensory and motor determinants of frailty and compare the results between frailty phenotype (FP) and frailty index (FI).MethodsData from 44 pre-frail and frail subjects aged 65 and above were used. Frailty was measured using the FP and the FI. Sensory function in the visual, auditory, and tactile domain was assessed using visual acuity, absolute hearing threshold and mechanical detection threshold. Upper extremity motor performance was evaluated by the Purdue Pegboard Test and the Short Physical Performance Battery was used to assess lower extremity motor function. Multiple logistic regression models were employed to determine associations of sensory and motor function with frailty vs. pre-frailty for both frailty measures.ResultsThe frailty measures were moderately correlated (0.497, p ≤ 0.01) and had a Kappa agreement of 0.467 (p = 0.002). Using the FP, frailty was significantly associated with reduced upper extremity motor function only (OR = 0.50, 95% CI 0.29-0.87, p = 0.014). Frailty as assessed by the FI was significantly related to higher hearing thresholds (OR = 1.21, 95% CI 1.02-1.43, p = 0.027) and reduced lower extremity performance (OR = 0.32, 95% CI 0.13-0.77, p = 0.012).ConclusionFrailty is related to reduced performance in measures of sensory and motor function. However, traditional measures of frailty might be differentially sensitive to capture sensory and motor decline, possibly contributing to the much-observed discordance between the diagnostic instruments. This should be taken into account by researchers and clinicians when planning and evaluating therapeutic interventions for frailty.Trial registrationClinicalTrials.gov NCT03666039 . Registered 11 September 2018 - Retrospectively registered.

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Frailty Index in Europeans: association with determinants of health.

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Frailty Index in Europeans: association with determinants of health.

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