Abstract: Disability is associated with lower quality of life and premature death in older people. Therefore, prevention and intervention targeting older people living with a disability is important. Frailty can be considered a major predictor of disability. In this study, we aimed to develop nomograms with items of the Tilburg Frailty Indicator (TFI) as predictors by using cross-sectional and longitudinal data (follow-up of five and nine years), focusing on the prediction of total disability, disability in activities of daily living (ADL), and disability in instrumental activities of daily living (IADL). At baseline, 479 Dutch community-dwelling people aged 75 years participated. They completed a questionnaire that included the TFI and the Groningen Activity Restriction Scale to assess the three disability variables. We showed that the TFI items scored different points, especially over time. Therefore, not every item was equally important in predicting disability. ‘Difficulty in walking’ and ‘unexplained weight loss’ appeared to be important predictors of disability. Healthcare professionals need to focus on these two items to prevent disability. We also conclude that the points given to frailty items differed between total, ADL, and IADL disability and also differed regarding years of follow-up. Creating one monogram that does justice to this seems impossible.
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BACKGROUND: Frailty is often associated with multimorbidity and disability. OBJECTIVES: We investigated heterogeneity in the frail older population by characterizing five subpopulations according to quantitative biological markers, multimorbidity and disability, and examined their association with mortality and nursing home admission. DESIGN: Observational study. PARTICIPANTS: Participants (n=4,414) were from the population-based Age Gene/Environment Susceptibility Reykjavik Study. MEASUREMENTS: Frailty was defined by ≥ 3 of five characteristics: weight loss, weakness, reduced energy levels, slowness and physical inactivity. Multimorbidity was assessed using a simple disease count, based on 13 prevalent conditions. Disability was assessed by five activities of daily living; participants who had difficulty with one or more tasks were considered disabled. Differences among frail subpopulations were based on the co-presence of multimorbidity and disability. Differences among the following subpopulations were examined: 1) Non-frail (reference group); 2) Frail only; 3) Frail with disability; 4) Frailty with multimorbidity; 5) Frail with disability and multimorbidity. RESULTS: Frailty was present in 10.7% (n=473). Frailty was associated with increased risk for mortality (OR 1.40; 95% CI 1.15-1.69) and nursing home admission (OR 1.50; 95% CI 1.16-1.93); risks differed by subpopulations. Compared to the non-frail, the frail only group had poorer cognition and increased inflammation levels but did not have increased risk for mortality (OR 1.40; 95% CI 0.84-2.33) or nursing home admission (OR 1.01; 95% CI 0.46-2.21). Compared to the non-frail, the other frail subpopulations had significantly poorer cognition, increased inflammation levels, more white matter lesions, higher levels of calcium, glucose and red cell distribution width and increased risk for mortality and nursing home admission. CONCLUSIONS: The adverse health risks associated with frailty in the general older adult population may primarily be driven by increased disease burden and disability.
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Objective: The Tilburg Frailty Indicator (TFI) is a self-report user-friendly questionnaire for assessing multidimensional frailty among community-dwelling older people. The main aim of this study is to re-evaluate the validity of the TFI, both cross-sectionally and longitudinally, focusing on the predictive value of the total TFI and its physical, psychological, and social domains for adverse outcomes disability, indicators of healthcare utilization, and falls. Methods: The validity of the TFI was determined in a sample of 180 Dutch communitydwelling older people aged 70 years and older. The participants completed questionnaires including the TFI, the Groningen Activity Restriction Scale (GARS) for assessing disability, and questions with regard to health care utilization and falls in 2016 and again one year later. Results: The physical and psychological domains of the TFI were significantly correlated as expected with adverse outcomes disability, many indicators of healthcare utilization, and falls. Regression analyses showed that physical frailty was mostly responsible for the effect of frailty on the adverse outcomes. The cross-sectional and longitudinal predictive validity of total frailty with respect to disability and receiving personal care was excellent, evidenced by Areas Under the Curves (AUCs) >0.8. In most cases, using the cut-off point 5 for total frailty ensured the best values for sensitivity and specificity. Conclusion: The present study provided new, additional evidence for the validity of the TFI for assessing frailty in Dutch community-dwelling older people aiming to prevent or delay adverse outcomes, including disability.
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ABSTRACT: Background Population aging is occurring worldwide. As a result, frailty and disability are in the full interest of practice, policy, and science. An increase in healthcare utilization is an adverse outcome of frailty and disability. Objective The aim of the present study was the prediction of six indicators of healthcare utilization by frailty and disability measures. The six indicators of healthcare utilization of interest were: use of informal care, number of visits to a general practitioner, hospital admission, receiving nursing care, receiving personal care, and contacts with (health)care professionals.
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Background: The population ageing in most Western countries leads to a larger number of frail older people. These frail people are at an increased risk of negative health outcomes, such as functional decline, falls, institutionalisation and mortality. Many approaches are available for identifying frailty among older people. Researchers most often use Fried and colleagues’ description of the frailty phenotype. The authors describe five physical criteria. Other researchers prefer a combination of measurements in the social, psychological and/or physical domains. The aim of this study is to describe the levels of social, psychological and physical functioning according to Fried’s frailty stages using a large cohort of Dutch community-dwelling older people. Methods: There were 8,684 community-dwelling older people (65+) who participated in this cross-sectional study. Based on the five Fried frailty criteria (weight loss, exhaustion, low physical activity, slowness, weakness), the participants were divided into three stages: non-frail (score 0), pre-frail (score 1–2) and frail (score 3–5). These stages were related to scores in the social (social network type, informal care use, loneliness), psychological (psychological distress, mastery, self-management) and physical (chronic diseases, GARS IADL-disability, OECD disability) domains. Results: 63.2 % of the participants was non-frail, 28.1 % pre-frail and 8.7 % frail. When comparing the three stages of frailty, frail people appeared to be older, were more likely to be female, were more often unmarried or living alone, and had a lower level of education compared to their pre-frail and non-frail counterparts. The difference between the scores in the social, psychological and physical domains were statistically significant between the three frailty stages. The most preferable scores came from the non-frail group, and least preferable scores were from the frail group. For example use of informal care: non-frail 3.9 %, pre-frail 23.8 %, frail 60.6 %, and GARS IADL-disability mean scores: non-frail 9.2, pre-frail 13.0, frail 19.7. Conclusion: When older people were categorised according to the three frailty stages, as described by Fried and colleagues, there were statistically significant differences in the level of social, psychological and physical functioning between the non-frail, pre-frail and frail persons. Non-frail participants had consistently more preferable scores compared to the frail participants. This indicated that the Fried frailty criteria could help healthcare professionals identify and treat frail older people in an efficient way, and provide indications for problems in other domains.
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Background: Over the years, a plethora of frailty assessment tools has been developed. These instruments can be basically grouped into two types of conceptualizations – unidimensional, based on the physical–biological dimension – and multidimensional, based on the connections among the physical, psychological, and social domains. At present, studies on the comparison between uni- and multidimensional frailty measures are limited. Objective: The aims of this paper were: 1) to compare the prevalence of frailty obtained using a uni- and a multidimensional measure; 2) to analyze differences in the functional status among individuals captured as frail or robust by the two measures; and 3) to investigate relations between the two frailty measures and disability.
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Objective: The Tilburg Frailty Instrument (TFI) is an instrument for assessing frailty in community-dwelling older people. Since its development, many studies have been carried out examining the psychometric properties. The aim of this study was to provide a review of the main findings with regard to the reliability and validity of the TFI. Methods: We conducted a literature search in the PubMed and CINAHL databases on May 30, 2020. An inclusion criterion was the use of the entire TFI, part B, referring to the 15 components. No restrictions were placed on language or year of publication. Results: In total, 27 studies reported about the psychometric properties of the TFI. By far, most of the studies (n = 25) were focused on community-dwelling older people. Many studies showed that the internal consistency and test–retest reliability are good, which also applies for the criterion and construct validity. In many studies, adverse outcomes of interest were disability, increased health-care utilization, lower quality of life, and mortality. Regarding disability, studies predominantly show results that are excellent, with an area under the curve (AUC) >0.80. In addition, the TFI showed good associations with lower quality of life and the findings concerning mortality were at least acceptable. However, the association of the TFI with some indicators of health-care utilization can be indicated as poor (eg, visits to a general practitioner, hospitalization). Conclusion: Since population aging is occurring all over the world, it is important that the TFI is available and well known that it is a user-friendly instrument for assessing frailty and its psychometric properties being qualified as good. The findings of this assessment can support health-care professionals in selecting interventions to reduce frailty and delay its adverse outcomes, such as disability and lower quality of life.
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A B S T R A C T Purpose: To determine cross-sectional and longitudinal associations of environmental factors with frailty and disability. Methods: This study was conducted in a sample of Dutch citizens. At baseline the sample consisted of 429 subjects (aged ≥ 65 years); a subset of this sample participated again two and half years later (N=355). The participants completed a web-based questionnaire, “the Senioren Barometer”, comprising seven scales for assessing environmental factors, and the Tilburg Frailty Indicator (TFI) and the Groningen Activity Restriction Scale (GARS), for assessing frailty and disability, respectively. Environmental factors of interest were: nuisance; housing; facilities; residents; neighborhood; stench/noise; and traffic. Results: Sequential regression analyses demonstrated that all environmental factors together explained a significant part of the variance of physical and social frailty and disability in performing activities of daily living (ADL) and instrumental activities of daily living (IADL), measured at Time 1 (T1) and Time 2 (T2). These analyses also showed that four of the environmental factors were associated with at least one of the outcome measures: housing, nuisance, residents, and neighborhood. Housing was the only environmental factor associated with three different outcome measures (social frailty, ADL disability, IADL disability), assessed at T1 and T2. Conclusion: The findings offer health-care and welfare professionals and also policymakers starting points for interventions. These interventions should focus, in particular, on housing, nuisance, residents, and neighborhood, because their impact on frailty and/or disability was the largest.
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Abstract Background: Multidimensional frailty, including physical, psychological, and social components, is associated to disability, lower quality of life, increased healthcare utilization, and mortality. In order to prevent or delay frailty, more knowledge of its determinants is necessary; one of these determinants is lifestyle. The aim of this study is to determine the association between lifestyle factors smoking, alcohol use, nutrition, physical activity, and multidimensional frailty. Methods: This cross-sectional study was conducted in two samples comprising in total 45,336 Dutch communitydwelling individuals aged 65 years or older. These samples completed a questionnaire including questions about smoking, alcohol use, physical activity, sociodemographic factors (both samples), and nutrition (one sample). Multidimensional frailty was assessed with the Tilburg Frailty Indicator (TFI). Results: Higher alcohol consumption, physical activity, healthy nutrition, and less smoking were associated with less total, physical, psychological and social frailty after controlling for effects of other lifestyle factors and sociodemographic characteristics of the participants (age, gender, marital status, education, income). Effects of physical activity on total and physical frailty were up to considerable, whereas the effects of other lifestyle factors on frailty were small. Conclusions: The four lifestyle factors were not only associated with physical frailty but also with psychological and social frailty. The different associations of frailty domains with lifestyle factors emphasize the importance of assessing frailty broadly and thus to pay attention to the multidimensional nature of this concept. The findings offer healthcare professionals starting points for interventions with the purpose to prevent or delay the onset of frailty, so communitydwelling older people have the possibility to aging in place accompanied by a good quality of life.
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Background & aims: Malnutrition, frailty, physical frailty, and disability are common conditions in patients with chronic obstructive pulmonary disease (COPD). Insight in the coexistence and relations between these conditions may provide information on the nature of the relationship between malnutrition and frailty. Such information may help to identify required interventions to improve the patient's health status. We therefore aimed to explore whether malnutrition, frailty, physical frailty, and disability coexist in patients with COPD at the start of pulmonary rehabilitation. Methods: For this cross-sectional study, from March 2015 to May 2017, patients with COPD were assessed at the start of a pulmonary rehabilitation program. Nutritional status was assessed with the Scored Patient-Generated Subjective Global Assessment (PG-SGA) based Pt-Global app. Frailty was assessed by the Evaluative Frailty Index for Physical activity (EFIP), physical frailty by Fried's criteria, and disability by the Dutch version of World Health Organization Disability Assessment Schedule 2.0 (WHODAS). These variables were dichotomized to determine coexistence of malnutrition, frailty, physical frailty, and disability. Associations between PG-SGA score and respectively EFIP score, Fried's criteria, and WHODAS score were analyzed by Pearson's correlation coefficient. Two tailed P-values were used, and significance was set at P < 0.05. Results: Of the 57 participants included (age 61.2 ± 8.7 years), malnutrition and frailty coexisted in 40%. Malnutrition and physical frailty coexisted in 18%, and malnutrition and disability in 21%. EFIP score and PG-SGA score were significantly correlated (r = 0.43, P = 0.001), as well as Fried's criteria and PG-SGA score (r = 0.37, P = 0.005). Conclusions: In this population, malnutrition substantially (40%) coexists with frailty. Although the prevalence of each of the four conditions is quite high, the coexistence of all four conditions is limited (11%). The results of our study indicate that nutritional interventions should be delivered by health care professionals across multiple disciplines.
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