Dataset Information

Frailty Index Predicts All-Cause Mortality for Middle-Aged and Older Taiwanese: Implications for Active-Aging Programs.

ABSTRACT:

Background

Frailty Index, defined as an individual's accumulated proportion of listed health-related deficits, is a well-established metric used to assess the health status of old adults; however, it has not yet been developed in Taiwan, and its local related structure factors remain unclear. The objectives were to construct a Taiwan Frailty Index to predict mortality risk, and to explore the structure of its factors.

Methods

Analytic data on 1,284 participants aged 53 and older were excerpted from the Social Environment and Biomarkers of Aging Study (2006), in Taiwan. A consensus workgroup of geriatricians selected 159 items according to the standard procedure for creating a Frailty Index. Cox proportional hazard modeling was used to explore the association between the Taiwan Frailty Index and mortality. Exploratory factor analysis was used to identify structure factors and produce a shorter version-the Taiwan Frailty Index Short-Form.

Results

During an average follow-up of 4.3 ± 0.8 years, 140 (11%) subjects died. Compared to those in the lowest Taiwan Frailty Index tertile (< 0.18), those in the uppermost tertile (> 0.23) had significantly higher risk of death (Hazard ratio: 3.2; 95% CI 1.9-5.4). Thirty-five items of five structure factors identified by exploratory factor analysis, included: physical activities, life satisfaction and financial status, health status, cognitive function, and stresses. Area under the receiver operating characteristic curves (C-statistics) of the Taiwan Frailty Index and its Short-Form were 0.80 and 0.78, respectively, with no statistically significant difference between them.

Conclusion

Although both the Taiwan Frailty Index and Short-Form were associated with mortality, the Short-Form, which had similar accuracy in predicting mortality as the full Taiwan Frailty Index, would be more expedient in clinical practice and community settings to target frailty screening and intervention.

SUBMITTER: Lin SY

PROVIDER: S-EPMC4990295 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Frailty Index Predicts All-Cause Mortality for Middle-Aged and Older Taiwanese: Implications for Active-Aging Programs.

Lin Shu-Yu SY Lee Wei-Ju WJ Chou Ming-Yueh MY Peng Li-Ning LN Chiou Shu-Ti ST Chen Liang-Kung LK

PloS one 20160818 8

<h4>Background</h4>Frailty Index, defined as an individual's accumulated proportion of listed health-related deficits, is a well-established metric used to assess the health status of old adults; however, it has not yet been developed in Taiwan, and its local related structure factors remain unclear. The objectives were to construct a Taiwan Frailty Index to predict mortality risk, and to explore the structure of its factors.<h4>Methods</h4>Analytic data on 1,284 participants aged 53 and older w ...[more]

PMID: 27537684

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Project description:BackgroundParallel to growth of aging and obese populations, the prevalence of metabolic diseases is rising. How body mass index (BMI) relates to frailty and mortality across frailty levels is controversial. We examined the associations of high BMI with frailty and mortality and explored the effects of percent body fat on these associations.MethodsWe included 29,937 participants aged ≥50 years from the 2001-2006 National Health and Nutrition Examination Survey (NHANES) cohorts (N=6062; 53.7% females) and from wave 1 (2004) of Survey of Health, Ageing and Retirement in Europe (SHARE) (N=23,875; 54% females). BMI levels were categorized as: normal: 18.5-24.9 kg/m2, overweight: 25.0-29.9, obese grade 1: 30.0-34.9, and obese grade 2 or 3: >35.0. A frailty index (FI) was constructed excluding nutrition-related items: 36 items for NHANES and 57 items for SHARE. We categorized the FI using 0.1-point increments: FI ≤ 0.1 (non-frail), 0.1 < FI ≤ 0.2 (very mildly frail), 0.2 < FI ≤ 0.3 (mildly frail), and FI > 0.3 (moderately/severely frail). Percent body fat was measured using DXA for NHANES participants. All-cause mortality data were obtained until 2015 for NHANES and 2017 for SHARE to estimate 10-year mortality risk. All analyses were adjusted for age, sex, educational, marital, employment, and smoking statuses.ResultsMean age of participants was 63.3±10.2 years for NHANES and 65.0±10.0 years for SHARE. In both cohorts, BMI levels ≥25 kg/m2 were associated with higher frailty, compared to normal BMI. In SHARE, having a BMI level greater than 35 kg/m2 increased mortality risk in participants with FI≤0.1 (HR 1.31, 95%CI 1.02-1.69). Overweight participants with FI scores >0.3 were at lower risk for mortality compared to normal BMI [NHANES (0.79, 0.64-0.96); SHARE (0.71, 0.63-0.80)]. Higher percent body fat was associated with higher frailty. Percent body fat significantly mediated the relationship between BMI levels and frailty but did not mediate the relationship between BMI levels and mortality risk.ConclusionsBeing overweight or obese is associated with higher frailty levels. In this study, we found that being overweight is a protective factor of mortality in moderately/severely frail people and obesity grade 1 may be protective for mortality for people with at least a mild level of frailty. In contrast, obesity grades 2 and 3 may be associated with higher mortality risk in non-frail people. The relationship between BMI and frailty is partially explained by body fat.

Project description:BackgroundThe Institut Pasteur de Lille, in the north of France, has implemented a large, multidisciplinary health check, which aims to identify frailty in middle-aged caregivers. We aimed to construct an adapted frailty index of cumulative deficit (FI-CD) and study the associated factors, in particular socioeconomic factors.MethodsThe cross-sectional study included caregivers aged 45 to 65. A 34-item FI-CD including deficits adapted to a middle-aged population (related to cognition and autonomy, dietetics, physical activity, comorbidities, functional signs, lab values and paraclinical examinations) was constructed in accordance with standard procedures. It was calculated as a ratio of deficits present out of the total number of possible deficits, giving a continuous score between 0 and 1. Scores > 0.25 and > 0.4 were classified as frailty and severe frailty, respectively. Univariate and multivariate associations were studied using linear regressions.ResultsOne hundred and seventeen caregivers were included; among them, 111 were analyzed due to missing values. The mean FI-CD was 0.22 ± 0.08. Forty (36%) individuals were classified as frailty and three (2.7%) as severe frailty. In multivariate analysis, FI-CD was significantly associated with age (beta [95% confidence interval] = 0.005 [0.002; 0.009] per 1-year increase, p = 0.005) and social deprivation (beta = 0.054 [0.007; 0.102], p = 0.025). A significant interaction was observed between and age and social deprivation (p = 0.036). The adjusted relationship between FI-CD and age was beta = 0.010 [0.002; 0.019], p = 0.017 in precarious caregivers, and beta = 0.003 [- 0.001; 0.007], p = 0.19 in non-precarious caregivers.ConclusionsThe study suggested that the 34-item FI-CD could have clinical utility in the management of middle-aged caregivers. Social deprivation appeared as an important factor associated with frailty, highlighting the importance of early care and social support for precarious caregivers.

Project description:Evidence for the association between the frailty index and cardiovascular disease (CVD) is inconclusive, and this association has not been evaluated in Chinese adults. We aim to examine the association between the frailty index and CVD among middle-aged and older Chinese adults. We conducted cross-sectional and cohort analyses using nationally representative data from the China Health and Retirement Longitudinal Study (CHARLS). From 2011 to 2018, 17,708 participants aged 45 years and older were included in the CHARLS. The primary outcome was CVD events (composite of heart disease and stroke). Multivariable adjusted logistic regression and Cox proportional hazards models were used to estimate the association between the frailty index and CVD in cross-sectional and follow-up studies, respectively. A restricted cubic spline model was used to characterize dose-response relationships. A total of 16,293 and 13,580 participants aged 45 years and older were included in the cross-sectional and cohort analyses, respectively. In the cross-sectional study, the prevalence of CVD in robust, pre-frailty and frailty was 7.83%, 18.70% and 32.39%, respectively. After multivariable adjustment, pre-frailty and frailty were associated with CVD; ORs were 2.54 (95% confidence interval [CI], 2.28-2.84) and 4.76 (95% CI, 4.10-5.52), respectively. During the 7 years of follow-up, 2122 participants without previous CVD developed incident CVD; pre-frailty and frailty were associated with increased risk of CVD events; HRs were 1.53 (95% CI, 1.39-1.68) and 2.17 (95% CI, 1.88-2.50), respectively. Furthermore, a stronger association of the frailty index with CVD was observed in participants aged <55, men, rural community-dwellers, BMI ≥ 25, without hypertension, diabetes or dyslipidemia. A clear nonlinear dose-response pattern between the frailty index and CVD was widely observed (p < 0.001 for nonlinearity), the frailty index was above 0.08, and the hazard ratio per standard deviation was 1.18 (95% CI 1.13-1.25). We observed the association between the frailty index and CVD among middle-aged and elderly adults in China, independent of chronological age and other CVD risk factors. Our findings are important for prevention strategies aimed at reducing the growing burden of CVD in older adults.

Project description:IntroductionGovernments across Europe want to promote healthy and active aging, as a matter of both public health and economic sustainability. Designing policies focused on the most vulnerable groups requires information at the individual level. However, a measure of healthy and active aging at the individual level does not yet exist.ObjectivesThis paper develops the Selfie Aging Index (SAI), an individual-level index of healthy and active aging. The SAI is developed thinking about a tool that would allow each person to take a selfie of her aging status. Therefore, it is based entirely on self-assessed indicators. This paper also illustrates how the SAI may look like in practice.MethodsThe SAI is based on the Biopsychosocial Assessment Model (MAB), a tool for the multidimensional assessment of older adults along three domains: biological, psychological, and social. Indicators are selected and their weights determined based on an ordered probit model that relates the MAB indicators to self-assessed health, which proxies healthy and active aging. The ordered probit model predicts the SAI based on the estimated parameters. Finally, predictions are rescaled to the 0-1 interval. Data for the SAI development come from the Study of the Aging Profiles of the Portuguese Population and the Survey of Health, Aging, and Retirement in Europe.ResultsThe selected indicators are BMI, having difficulties moving around indoors and performing the activities of daily living, feeling depressed, feeling nervous, lacking energy, time awareness score, marital status, having someone to confide in, education, type of job, exercise, and smoking status. The model also determines their weights.ConclusionResults shed light on various factors that contribute significantly to healthy and active aging. Two examples are mental health and exercise, which deserve more attention from individuals themselves, health-care professionals, and public health policy. The SAI has the potential to put the individual at the center of the healthy and active aging discussion, contribute to patient empowerment, and promote patient-centered care. It can become a useful instrument to monitor healthy and active aging for different actors, including individuals themselves, health-care professionals, and policy makers.

Project description:This study was conducted to investigate the adherence of Daily Food Guides (DFGs) among older Taiwanese, and the relationship of dietary quality and frailty. 154 functional independent older adults who were retirement home residents or community dwellers involved in congregate meal services were recruited. DFGs adherence was measured using a novel Taiwanese Healthy Index (T-HEI). Dietary quality was further assessed using Dietary Approach to Stop Hypertension (DASH) and Mediterranean Diet Score (MDS). Frailty was defined using modified Fried's criteria. Of the total participants, 12.3% were considered non-frail individuals, while 77.3% were prefrail, and 10.4% were frail. Compared to non-frail participants, prefrail and frail individuals indicated significantly lower adherence to DFGs (ptrend = 0.025). Intake of dark or orange vegetables (ptrend = 0.010), whole grains (ptrend = 0.007), as well as nuts and seeds (ptrend = 0.029) by non-frail individuals were significantly higher than the levels by prefrail and frail individuals. Linear regression model adjusted for age, gender, and functional ability showed that T-HEI was inversely associated with frailty status (β = -0.16 ± 0, p = 0.047), but additional adjustment for nutritional status attenuated the association (β = -0.14 ± 0, p = 0.103). A similar relationship was observed for DASH but not MDS (DASH: β = -0.18 ± 0.01, p = 0.024; MDS: β = -0.06 ± 0.02, p = 0.465). After adjustment for confounders, the association was not observed. However, the distribution of whole grains component in both DASH and MDS was significantly higher in non-frail than prefrail and frail individuals, indicating the importance of whole grains intake in frailty prevention. In conclusion, higher adherence to DFGs and better dietary quality were associated with a lower prevalence of frailty. Higher nutrient-dense foods intake such as whole grains, dark or orange vegetables, nuts, and seeds mark a watershed in frailty prevention.

Dataset Information

Frailty Index Predicts All-Cause Mortality for Middle-Aged and Older Taiwanese: Implications for Active-Aging Programs.

Background

Methods

Results

Conclusion

Publications

Frailty Index Predicts All-Cause Mortality for Middle-Aged and Older Taiwanese: Implications for Active-Aging Programs.

Similar Datasets

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