Dataset Information

Predicting mortality and hospitalization of older adults by the multimorbidity frailty index.

ABSTRACT:

Background

Existing operational definitions of frailty are personnel-costly and time-consuming, resulting in estimates with a small sample size that cannot be generalized to the population level. The objectives were to develop a multimorbidity frailty index using Taiwan's claim database, and to understand its ability to predict adverse event.

Methods

This is a retrospective cohort study. Subjects aged 65 to 100 years who have full National Health Insurance coverage in 2005 were included. We constructed the multimorbidity frailty index using cumulative deficit approach and categorized study population according to the multimorbidity frailty index quartiles: fit, mild frailty, moderate frailty and severe frailty. The multimorbidity frailty index included deficits from outpatient and inpatient diagnosis. Associations with all-cause mortality, unplanned hospitalization and intensive care unit admission were assessed using Kaplan-Meier curves and Cox regression analyses.

Results

The multimorbidity frailty index incorporated 32 deficits, with mean multimorbidity frailty index score of 0.052 (standard deviation = 0.060) among 86,133 subjects included. Compared to subjects in fit category, subjects with severe frailty were associated with a 5.0-fold (adjusted hazard ratio, aHR 4.97; 95% confidence interval, 95% CI 4.49-5.50) increased risk of death at 1 year after adjusting for age and gender. Subjects with moderate frailty or mild frailty was associated with 3.1- (adjusted HR 3.08; 95% CI 2.80-3.39) or 1.9- (adjusted HR 1.86; 95% CI 1.71-2.01) folds increased risk, respectively.4.49-5.50). The risk trend of unplanned hospitalization and intensive care unit admission is similar among the study population. Besides, the association between the frailty categories and all three outcomes was slightly stronger among women.

Conclusion

The multimorbidity frailty index was highly associated with all-cause mortality, unplanned hospitalization and ICU admission. It could serve as an efficient tool for stratifying older adults into different risk groups for planning care management programs.

SUBMITTER: Wen YC

PROVIDER: S-EPMC5690585 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Predicting mortality and hospitalization of older adults by the multimorbidity frailty index.

Wen Yao-Chun YC Chen Liang-Kung LK Hsiao Fei-Yuan FY

PloS one 20171116 11

<h4>Background</h4>Existing operational definitions of frailty are personnel-costly and time-consuming, resulting in estimates with a small sample size that cannot be generalized to the population level. The objectives were to develop a multimorbidity frailty index using Taiwan's claim database, and to understand its ability to predict adverse event.<h4>Methods</h4>This is a retrospective cohort study. Subjects aged 65 to 100 years who have full National Health Insurance coverage in 2005 were in ...[more]

PMID: 29145407

Similar Datasets

Project description:BackgroundMultimorbidity and frailty are relevant conditions among older adult population. There is growing evidence about their association with poor health outcomes like disability, worst quality of life, and death. Nonetheless, the independent associations of both conditions have been studied, and few evidence exists about an interaction between them. Our aims were to assess the association of frailty and multimorbidity with the disability, quality of life and all-cause mortality as well as to analyze a potential interaction between these conditions.MethodsAnalytical samples included 1410 respondents for disability and quality of life, and 1792 for mortality. We performed a longitudinal analysis with older Mexican adults aged 50, using data collected from the WHO's Study on global AGEing and Adult Health Waves 1 and 2. Disability was measured using the World Health Organization Disability Assessment Schedule (WHODAS 2.0), and quality of life using the WHOQOL (WHO Quality of Life) instrument. All-cause mortality was determined by reviewing death certificates. Associations of frailty and multimorbidity with disability, quality of life and mortality were estimated using linear regression and Cox proportional hazards models.ResultsMultimorbidity assessed through three patterns (cardiopulmonary, vascular-metabolic, and mental-musculoskeletal) was associated with the three outcomes in this study. Cardiopulmonary and mental-musculoskeletal patterns increased the WHODAS mean score (β = 5.05; p < 0.01 and β = 5.10; p < 0.01, respectively) and decreased WHOQOL score (β = - 1.81; p < 0.01 and β = - 2.99; p < 0.01, respectively). Vascular-metabolic was associated with mortality (HR = 1.47; p = 0.04), disability (β = 3.27; p < 0.01) and quality of life (β = - 1.30; p = 0.02). Frailty was associated with mortality (pre-frail: HR = 1.48; p = 0.02 and frail: HR = 1.68; p = 0.03), disability (pre-frail: β = 5.02; p < 0.01; frail: β = 13.29; p < 0.01) and quality of life (pre-frail: β = - 2.23; p < 0.01; frail: β = - 4.38; p < 0.01). Interaction terms of frailty and multimorbidity were not statistically significant.ConclusionsMultimorbidity and frailty are important predictors of poor health outcomes. These results highlight the importance of carrying out health promotion and prevention actions as well as specific interventions aimed at older adults who suffer from multimorbidity and frailty, in such a way that deleterious effects on health can be avoided.

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:BACKGROUND:Frailty is associated with older age and multimorbidity (two or more long-term conditions); however, little is known about its prevalence or effects on mortality in younger populations. This paper aims to examine the association between frailty, multimorbidity, specific long-term conditions, and mortality in a middle-aged and older aged population. METHODS:Data were sourced from the UK Biobank. Frailty phenotype was based on five criteria (weight loss, exhaustion, grip strength, low physical activity, slow walking pace). Participants were deemed frail if they met at least three criteria, pre-frail if they fulfilled one or two criteria, and not frail if no criteria were met. Sociodemographic characteristics and long-term conditions were examined. The outcome was all-cause mortality, which was measured at a median of 7 years follow-up. Multinomial logistic regression compared sociodemographic characteristics and long-term conditions of frail or pre-frail participants with non-frail participants. Cox proportional hazards models examined associations between frailty or pre-frailty and mortality. Results were stratified by age group (37-45, 45-55, 55-65, 65-73 years) and sex, and were adjusted for multimorbidity count, socioeconomic status, body-mass index, smoking status, and alcohol use. FINDINGS:493 737 participants aged 37-73 years were included in the study, of whom 16 538 (3%) were considered frail, 185 360 (38%) pre-frail, and 291 839 (59%) not frail. Frailty was significantly associated with multimorbidity (prevalence 18% [4435/25 338] in those with four or more long-term conditions; odds ratio [OR] 27·1, 95% CI 25·3-29·1) socioeconomic deprivation, smoking, obesity, and infrequent alcohol consumption. The top five long-term conditions associated with frailty were multiple sclerosis (OR 15·3; 99·75% CI 12·8-18·2); chronic fatigue syndrome (12·9; 11·1-15·0); chronic obstructive pulmonary disease (5·6; 5·2-6·1); connective tissue disease (5·4; 5·0-5·8); and diabetes (5·0; 4·7-5·2). Pre-frailty and frailty were significantly associated with mortality for all age strata in men and women (except in women aged 37-45 years) after adjustment for confounders. INTERPRETATION:Efforts to identify, manage, and prevent frailty should include middle-aged individuals with multimorbidity, in whom frailty is significantly associated with mortality, even after adjustment for number of long-term conditions, sociodemographics, and lifestyle. Research, clinical guidelines, and health-care services must shift focus from single conditions to the requirements of increasingly complex patient populations. FUNDING:CSO Catalyst Grant and National Health Service Research for Scotland Career Research Fellowship.

Dataset Information

Predicting mortality and hospitalization of older adults by the multimorbidity frailty index.

Background

Methods

Results

Conclusion

Publications

Predicting mortality and hospitalization of older adults by the multimorbidity frailty index.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets