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• Chronic diseases had the strongest associations with total and physical frailty. • The effects of chronic diseases on frailty differed strongly across diseases. • Urinary incontinence and severe back disorder impaired frailty most. • Cancer and hypertension had the weakest associations with frailty. • Different weight should be given to individual chronic diseases in a measure of multimorbidity. To examine the associations between individual chronic diseases and multidimensional frailty comprising physical, psychological, and social frailty. Dutch individuals (N = 47,768) age ≥ 65 years completed a general health questionnaire sent by the Public Health Services (response rate of 58.5 %), including data concerning self-reported chronic diseases, multidimensional frailty, and sociodemographic characteristics. Multidimensional frailty was assessed with the Tilburg Frailty Indicator (TFI). Total frailty and each frailty domain were regressed onto background characteristics and the six most prevalent chronic diseases: diabetes mellitus, cancer, hypertension, arthrosis, urinary incontinence, and severe back disorder. Multimorbidity was defined as the presence of combinations of these six diseases. The six chronic diseases had medium and strong associations with total ((f2 = 0.122) and physical frailty (f2 = 0.170), respectively, and weak associations with psychological (f2 = 0.023) and social frailty (f2 = 0.008). The effects of the six diseases on the frailty variables differed strongly across diseases, with urinary incontinence and severe back disorder impairing frailty most. No synergetic effects were found; the effects of a disease on frailty did not get noteworthy stronger in the presence of another disease. Chronic diseases, in particular urinary incontinence and severe back disorder, were associated with frailty. We thus recommend assigning different weights to individual chronic diseases in a measure of multimorbidity that aims to examine effects of multimorbidity on multidimensional frailty. Because there were no synergetic effects of chronic diseases, the measure does not need to include interactions between diseases. [ABSTRACT FROM AUTHOR]

• Of the participants, 65% were younger than 80 years, 50% were married or cohabiting, 87% reported a healthy lifestyle, and 63% had no diseases or chronic disorders. • Each year, more participants changed from status not disabled to disabled than vice versa. • The transition of the disability score is strongly influenced by lifestyle and diseases or disorders. • For health care professionals, our study provides starting points for interventions focused on the prevention of worsening disability and for community-dwelling older people 75 year or older. • The most important recommendation is: live healthy! Recent world population predictions show that the world population aged >=65 years will increase from 10% in 2022 to 16% in 2050. Population aging is accompanied by an increase in people with disability. It is important to pay special attention to people with disability, as these people are at high risk of adverse outcomes. Our study aimed to investigate the transitions of disability among Dutch community-dwelling older people aged 75 years or older, using a follow-up of nine years. We used socio-demographic factors gender, age, marital status, education, and income, but also lifestyle, diseases, and life events to predict the disability transitions over time. We used a sample of 484 people that was randomly drawn from the municipality of Roosendaal (the Netherlands), a municipality with 78,000 inhabitants. A subset of people who completed part A of the Tilburg Frailty Indicator (TFI) at baseline and the Groningen Activity Restriction Scale (GARS) questionnaires was used with a nine-year follow-up. Paired Wilcoxon tests were used to compare the consecutive measurements. Socio-demographic factors gender, age, marital status, education, and income, but also lifestyle, diseases, and life events were included to predict the disability transitions over time. For the univariable and multivariable analysis of the measurements over time with the predictor variables, we used generalized estimation equations (GEE). A p-value <0.05 was considered significant. R version 3.4.4 was used for all analyses. Of the participants, 65% were younger than 80 years, 50% were married or cohabiting, 87% reported a healthy lifestyle, and 63% had no diseases or chronic disorders. Each year, more participants changed from status not disabled to disabled than vice versa. The GEE analyses showed that lifestyle ('not healthy') and diseases or chronic disorders ('two or more') were significant in the multivariable analysis for the disability score and only diseases or chronic disorders ('two or more') was significant in the multivariable analysis for the dichotomous disability score. The transition of the disability score is strongly influenced by lifestyle and diseases or disorders. This applies to a lesser extent to the dichotomous disability score. There, only diseases or disorders are an important predictor. For health care professionals our study provides starting points for interventions focused on the prevention of worsening disability and for community-dwelling older people >= 75, the most important recommendation is: live healthy! [ABSTRACT FROM AUTHOR]

Abstract: Aims: To establish whether the prediction of the adverse outcomes disability and six indicators of health care utilization one and two years later by the three frailty domains (physical, psychological, social) of the Tilburg Frailty Indicator (TFI) is improved by adding interview and physical measures of frailty. Materials and methods: A representative sample of 245 Dutch community-dwelling persons aged 75 years and older (response rate 53%) participated in 2008, one year later in 2009 (n =179, 73%) and again two years later in 2010 (n =141, 58%). Frailty was assessed with the TFI, an easy to administer self-report measure. Disability was measured using the Groningen Activity Restriction Scale (GARS). Indicators of health care utilization were: visit to a general practitioner (gp), contacts with health care professionals (hcps), hospital admission, receiving personal care, receiving nursing care, and receiving informal care. Results: After controlling for background characteristics, the TFI predicted disability and the indicators of health care utilization. Interviews and physical measures of frailty improved the prediction of disability. The Hospital Anxiety and Depression Scale (HADS-A) improved the prediction of contacts with hcps, but the interview and physical measures of frailty did not improve the predictions of the other indicators of health care utilization. Conclusions: Assessment by the self-report TFI is sufficient for predicting six indicators of health care utilization, but for predicting disability the use of both the TFI and the Timed Up & Go (TUG) test is recommended. It is advisable assessing all three frailty domains when examining frailty and its prediction of adverse outcomes. [Copyright &y& Elsevier]

• We examined the development of multidimensional frailty over seven years • We determined the effects of sociodemographic factors on multidimensional frailty • Multidimensional frailty increased among community-dwelling people aged ≥75 years • Healthcare professionals are offered clues to identify people at risk of frailty : To examine the development of multidimensional frailty, including physical, psychological and social components, over a period of seven years. To determine the effects of sociodemographic factors (gender, age, marital status, education, income) on the development of frailty. : This longitudinal study was conducted in sample of 479 community-dwelling people aged ≥ 75 years living in the municipality of Roosendaal, the Netherlands. The Tilburg Frailty Indicator (TFI), a self-report questionnaire, was used to collect data about frailty. Frailty was assessed annually. : Frailty increased significantly over seven years among the people who completed the entire TFI all years (n = 121), the average score was 3.75 (SD 2.80) at baseline and 5.05 (SD 3.18) after seven years. Regarding frailty transitions, most participants remained unchanged from their baseline status. The transition from non-frail to frail was present in 8.3% to 12.6% of the participants and 5.1% to 10.7% made a transition from frail to non-frail. Gender (woman), age (≥80 years), marital status (not married/cohabiting), high level of education, and incomes from €601-€1800 were significantly associated with a higher frailty score. : This study showed that multidimensional frailty, assessed with the TFI, increased among Dutch community-dwelling people aged ≥75 years using a follow-up of seven years. Gender, age, marital status, education, and income were associated with frailty transitions. These findings provide healthcare professionals clues to identify people at increased risk of frailty, and target interventions which aim to prevent or delay frailty and its adverse outcomes, such as disability and mortality. [ABSTRACT FROM AUTHOR]

To predict mortality with the Tilburg Frailty Indicator (TFI) in a sample of community-dwelling older people, using a follow-up of 7 years. Longitudinal. 479 Dutch community-dwelling people aged 75 years or older. The TFI, a self-report questionnaire, was used to collect data about total, physical, psychological, and social frailty. The municipality of Roosendaal (a town in the Netherlands) provided the mortality dates. Total, physical, and psychological frailty predicted mortality, with unadjusted hazard ratios of 1.295, 1.168, and 1.194, and areas under the receiver operating characteristic curves of 0.664, 0.671, and 0.567, respectively. After adjustment for age and gender, the areas under the curves for total, physical, and psychological frailty were 0.704, 0.702, and 0.652, respectively. Analyses using individual components of the TFI show that difficulty in walking and unexplained weight loss predict mortality. This study has shown the predictive validity of the TFI for mortality in community-dwelling older people. Our study demonstrated that physical and psychological frailty predicted mortality. Of the individual TFI components, difficulty in walking consistently predicted mortality. For identifying frailty, using the integral instrument is recommended because total, physical, psychological, and social frailty and its components have proven their value in predicting adverse outcomes of frailty, for example, increase in health care use and a lower quality of life. [ABSTRACT FROM AUTHOR]

• Frailty is a common clinical syndrome in the elderly. • Screening allows early intervention in frailty. • Early detection and intervention in frailty help improve the quality of life of the elderly. • The TFI is a highly sensitive tool for detecting frailty. Screening is one of the most important ways for early frailty detection that contributes to its prevention and timely treatment. The aim of this study was to determine the diagnostic value of the Persian version of the Tilburg Frailty Indicator (P-TFI) in the frailty screening. This is a diagnostic test accuracy study that uses known group method. It was designed based on a STARD statement and performed on 175 elderly people in the City of Kashan, Iran. The subjects were selected among older people available in health centers affiliated to Kashan University of Medical Sciences using purposive sampling. Data analysis was carried out using SPSS v16. Descriptive statistics were used to describe the characteristics of the research subjects. Independent t -test was used to determine the ability of the P-TFI to discriminate frail and non-frail individuals, and to evaluate the cut-off point and instrument accuracy, the receiver operating characteristic (ROC) curve was used. The best cut-off point was determined among the proposed points using Youden index. At the determined cut-off point, the diagnostic value parameters of the P-TFI (sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, accuracy, and diagnostic odds ratio) were calculated and their range was estimated with 95 % confidence interval. A total of 74.3 % of the sample was male and their mean age was 68.6 ± 54.44 years. The area under the ROC curve was calculated 0.922, indicating high accuracy of the instrument. The sensitivity and specificity of this instrument at the cut-off point of 4.5 were 0.95 and 0.86, respectively. Positive and negative predictive values were calculated 0.68 and 0.98, respectively, and the accuracy of the instrument was reported to be 0.88. The P-TFI can be used as a sensitive and accurate instrument, which is highly applicable to screen frailty in older people. [ABSTRACT FROM AUTHOR]

• This study establishes a consensus on an operational definition of oral frailty. • An international expert panel assessed 55 potential components of oral frailty. • Oral frailty constitutes mastication, swallowing, oral motor skill, and salivation. • Based on these findings a revised method for assessing oral frailty is recommended. Building upon our recently developed conceptual definition of oral frailty (the age-related functional decline of orofacial structures), this e-Delphi study aims to develop an operational definition of oral frailty by identifying its components. We used a modified e-Delphi study to reach a consensus among international experts on the components of oral frailty. Twelve out of fifteen invited experts in the field of gerodontology participated. Experts responded to three rounds of an online 5-point scale questionnaire of components to be included or excluded from the operational definition of oral frailty. After each round, scores and rationales were shared with all experts, after which they could revise their position. A consensus was reached when at least 70% of the experts agreed on whether or not a component should be included in the operational definition of oral frailty. The experts achieved a high level of agreement (80 – 100%) on including eight components of oral frailty and excluding nineteen. The operational definition of oral frailty should include the following components: 1) difficulty eating hard or tough foods , 2) inability to chew all types of foods , 3) decreased ability to swallow solid foods , 4) decreased ability to swallow liquids , 5) overall poor swallowing function , 6) impaired tongue movement , 7) speech or phonatory disorders, and 8) hyposalivation or xerostomia. This e-Delphi study provided eight components that make up the operational definition of oral frailty. These components are the foundation for the next stage, which involves developing an oral frailty assessment tool. [ABSTRACT FROM AUTHOR]

Objectives The objectives of this study were to provide reference values of the Tilburg Frailty Indicator (TFI) for community-dwelling older people by age, sex, marital status, ethnicity, education, income, and residence, and examine the effects of these seven socio-demographic variables on frailty. Methods 47,768 individuals aged 65 years and older living in the Netherlands completed a health questionnaire (58.5% response rate), including the TFI. The TFI is a self-report questionnaire for measuring frailty, developed from an integral approach of frailty, including physical, psychological, and social domains. Results Reference values were provided for men and women separately, as a function of age. We found associations of all socio-demographic variables with frailty, also after controlling for the effects of age. These associations held for both sexes and for big cities as wells as more rural areas. For instance, the effect of age was large for total and physical frailty, women were more frail than men, and some very large average frailty differences between the ethnic groups were found, with autochthon people having the lowest frailty score. Conclusions In conclusion, this study offers reference values of the TFI by socio-demographic characteristics and explains frailty using these characteristics. This information will support researchers, policymakers and health care professionals in interpreting scores of the TFI, which may guide their efforts to reduce frailty and its adverse outcomes. [ABSTRACT FROM AUTHOR]