Frailty, multimorbidity patterns and mortality in institutionalized older adults in Italy.
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ABSTRACT: Background
Little is known on how frailty influences clinical outcomes in persons with specific multimorbidity patterns.Aims
To investigate the interplay between multimorbidity and frailty in the association with mortality in older individuals living in nursing homes (NH).Methods
We considered 4,131 NH residents aged 60 years and over, assessed through the interRAI LTCF instrument between 2014 and 2018. Follow-up was until 2019. Considering four multimorbidity patterns identified via principal component analysis, subjects were stratified in tertiles (T) with respect to their loading values. Frailty Index (FI) considered 23 variables and a cut-off of 0.24 distinguished between high and low frailty levels. For each pattern, all possible combinations of tertiles and FI were evaluated. Their association (Hazard Ratio [HR] and 95% confidence interval) with mortality was tested in Cox regression models.Results
In the heart diseases and dementia and sensory impairments patterns, the hazard of death increases progressively with patterns expression and frailty severity (being HR T3 vs. T1 = 2.36 [2.01-2.78]; HR T3 vs. T1 = 2.12 [1.83-2.47], respectively). In heart, respiratory and psychiatric diseases and diabetes, musculoskeletal and vascular diseases patterns, frailty seems to have a stronger impact on mortality than patterns' expression.Discussion
Frailty increases mortality risk in all the patterns and provides additional prognostic information in NH residents with different multimorbidity patterns.Conclusions
These findings support the need to routinely assess frailty. Older people affected by specific groups of chronic diseases need a specific care approach and have high risk of negative health outcomes.
SUBMITTER: Damiano C
PROVIDER: S-EPMC9562060 | biostudies-literature | 2022 Oct
REPOSITORIES: biostudies-literature
Publications
Frailty, multimorbidity patterns and mortality in institutionalized older adults in Italy.
Damiano Cecilia C Onder Graziano G Zazzara Maria Beatrice MB Carfì Angelo A Zucchelli Alberto A Marengoni Alessandra A Vetrano Davide L DL
Aging clinical and experimental research 20221014 12
<h4>Background</h4>Little is known on how frailty influences clinical outcomes in persons with specific multimorbidity patterns.<h4>Aims</h4>To investigate the interplay between multimorbidity and frailty in the association with mortality in older individuals living in nursing homes (NH).<h4>Methods</h4>We considered 4,131 NH residents aged 60 years and over, assessed through the interRAI LTCF instrument between 2014 and 2018. Follow-up was until 2019. Considering four multimorbidity patterns id ...[more]
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Project description:BackgroundFrailty and multimorbidity are independent prognostic factors for mortality, but their interaction has not been fully explored. We investigated the importance of multimorbidity patterns in older adults with the same level of frailty phenotype.MethodsIn a cohort of 7,197 community-dwelling adults aged 65 years and older, physical frailty status (robust, pre-frail, frail) was defined using shrinking, exhaustion, inactivity, slowness, and weakness. Latent class analysis was used to identify individuals with multimorbidity patterns based on 10 self-reported chronic conditions. We estimated hazard ratios (HR) and incidence rate differences (IRDs) for mortality comparing multimorbidity patterns within each frailty state.ResultsFive multimorbidity classes were identified: minimal disease (24.7%), cardiovascular disease (29.0%), osteoarticular disease (27.3%), neuropsychiatric disease (8.9%), and high multisystem morbidity (10.0%). Within each frailty state, the mortality rate per 1,000 person-years over 4 years was greatest in the neuropsychiatric class and lowest in the minimal disease class: robust (56.3 vs 15.7; HR, 2.11 [95% CI: 1.05, 4.21]; IRD, 24.1 [95% CI: -11.2, 59.3]), pre-frail (85.3 vs 40.4; HR, 1.74 [95% CI: 1.28, 2.37]; IRD, 27.1 [95% CI: 7.6, 46.7]), and frail (218.1 vs 96.4; HR, 2.05 [95% CI: 1.36, 3.10]; IRD, 108.4 [95% CI: 65.0, 151.9]). Although HRs did not vary widely by frailty, the excess number of deaths, as reflected by IRDs, increased with greater frailty level.ConclusionsConsidering both multimorbidity patterns and frailty is important for identifying older adults at greater risk of mortality. Of the five patterns identified, the neuropsychiatric class was associated with lower survival across all frailty levels.
| S-EPMC6625582 | biostudies-literature
Project description:BackgroundExisting 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.MethodsThis 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.ResultsThe 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.ConclusionThe 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.
| S-EPMC5690585 | biostudies-literature
Project description:IntroductionDementia is common in nursing homes (NH) residents. Defining dementia comorbidities is instrumental to identify groups of persons with dementia that differ in terms of health trajectories and resources consumption. We performed a cross-sectional study to identify comorbidity patterns and their associated clinical, behavioral, and functional phenotypes in institutionalized older adults with dementia.MethodsWe analyzed data on 2563 Italian NH residents with dementia, collected between January 2014 and December 2018 using the multidimensional assessment instrument interRAI Long-Term Care Facility (LTCF). A standard principal component procedure was used to identify comorbidity patterns. Linear regression analyses were used to ascertain correlates of expression of the different patterns.ResultsAmong NH residents with dementia, we identified three different comorbidity patterns: (1) heart diseases, (2) cardiovascular and respiratory diseases and sensory impairments, and (3) psychiatric diseases. Older age significantly related to increased expression of the first two patterns, while younger patients displayed increased expression of the third one. Recent hospital admissions were associated with increased expression of the heart diseases pattern (β = 0.028; 95% confidence interval [CI] 0.003 to 0.05). Depressive symptoms and delirium episodes increased the expression of the psychiatric diseases pattern (β = 0.130, 95% CI 0.10 to 0.17, and β 0.130, CI 0.10 to 0.17, respectively), while showed a lower expression of the heart diseases pattern.DiscussionWe identified different comorbidity patterns within NH residents with dementia that differ in term of clinical and functional profiles. The prompt recognition of health needs associated to a comorbidity pattern may help improve long-term prognosis and quality of life of these individuals.HighlightsDefining dementia comorbidities patterns in institutionalized older adults is key.Institutionalized older adults with dementia express different care needs.Comorbidity patterns are instrumental to identify different patients' phenotypes.Phenotypes vary in terms of health trajectories and demand different care plans.Prompt recognition of phenotypes in nursing homes can positively impact on outcomes.
| S-EPMC9197250 | biostudies-literature
Project description:Backgroundthe aim of this study was to examine the cross-sectional and longitudinal associations of different multimorbidity patterns with physical frailty in older adults.Methodswe used data from the Swedish National study on Aging and Care in Kungsholmen to generate a physical frailty measure, and clusters of participants with similar multimorbidity patterns were identified through fuzzy c-means cluster analyses. The cross-sectional association (n = 2,534) between multimorbidity clusters and physical frailty was measured through logistic regression analyses. Six- (n = 2,122) and 12-year (n = 2,140) longitudinal associations were determined through multinomial logistic regression analyses.Resultssix multimorbidity patterns were identified at baseline: psychiatric diseases; cardiovascular diseases, anaemia and dementia; sensory impairments and cancer; metabolic and sleep disorders; musculoskeletal, respiratory and gastrointestinal diseases; and an unspecific pattern lacking any overrepresented diseases. Cross-sectionally, each pattern was associated with physical frailty compared with the unspecific pattern. Over 6 years, the psychiatric diseases (relative risk ratio [RRR]: 3.04; 95% confidence intervals [CI]: 1.59-5.79); cardiovascular diseases, anaemia and dementia (RRR 2.25; 95% CI: 1.13-4.49) and metabolic and sleep disorders (RRR 1.99; 95% CI: 1.25-3.16) patterns were associated with incident physical frailty. The cardiovascular diseases, anaemia and dementia (RRR: 4.81; 95% CI: 1.59-14.60); psychiatric diseases (RRR 2.62; 95% CI: 1.45-4.72) and sensory impairments and cancer (RRR 1.87; 95% CI: 1.05-3.35) patterns were more associated with physical frailty, compared with the unspecific pattern, over 12 years.Conclusionswe found that older adults with multimorbidity characterised by cardiovascular and neuropsychiatric disease patterns are most susceptible to developing physical frailty.
| S-EPMC8581386 | biostudies-literature
Project description:BackgroundMultimorbidity is the most common chronic condition experienced among older adults. It is unknown which amount and source of protein influences the development of frailty and mortality in patients with multimorbidity. We aimed to examine the association of plant and animal sources of protein intake with frailty and mortality among this type of patients.MethodsThis longitudinal study included 1868 participants aged ≥ 60 years from the Seniors-ENRICA cohort in Spain with multimorbidity, defined as having 2 or more clinician-diagnosed chronic diseases. Habitual diet was assessed at baseline (2008-2010) with a validated computerized diet history. Participants underwent repeated physical examinations (in 2013, 2015 and 2017) for assessment of frailty (≥ 3 criteria from the frailty phenotype: low physical activity, slow walking speed, muscle weakness, weight loss and exhaustion). All-cause mortality was assessed up to January 2022. Analyses were conducted using Cox proportional hazard models and multistate models adjusted for sociodemographic, lifestyle and other dietary factors.ResultsMean consumption of protein was 90.2 (standard deviation [SD]: 26.8) g/day, which represents 18.7% of the total energy intake and 1.23 (0.39) g per kg of body weight per day. Plant protein represented 6.16% of the energy intake, while animal protein represented 12.5%. During a median follow-up of 12.9 (range: 11.7-13.9) years, we documented 196 incident cases of frailty and 490 deaths; of these mortality cases, 83 individuals died after a frailty diagnosis. Higher intake of total protein was associated with decreased risk of frailty (hazard ratio [HR] for tertile 3 vs. tertile 1: 0.66; 95% confidence interval [CI]: 0.45, 0.96; p trend: 0.03). In multistate models, higher fish protein intake decreased the risk in the progression from multimorbidity to frailty (HR per 1-SD increment: 0.81 [95% CI: 0.68, 0.97]), and higher plant protein decreased the risk of progressing from multimorbidity to mortality (0.86 [0.75, 0.98]). In the progression from frailty to mortality, estimates for total, plant and animal protein showed increased risk (HR for 1 SD increment in total protein: 1.38 [1.05, 1.81]; HR for plant protein: 1.29 [1.01, 1.67]; HR for animal protein: 1.41 [1.04, 1.92]). No significant associations were found between meat protein and dairy protein in any transition.ConclusionsIn individuals with multimorbidity, higher protein intake, especially fish protein, was associated with lower risk of subsequent frailty, whereas plant protein intake was associated with lower risk of mortality. Higher total protein intake, however, might be detrimental in patients with multimorbidity and frailty.Trial registrationClinicalTrials.gov identifier: NCT02804672.
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Project description:BackgroundPhysical frailty is defined as a syndrome of decreased physiologic reserve conferring vulnerability to functional decline, mortality, and other adverse outcomes upon experiencing stressors. Self-efficacy, which is confidence in one's ability to perform well in a domain of life, is modifiable. Self-efficacy is associated with improved health behavior and decreased chronic disease burden. Its relationship to frailty is unknown. The purpose of this study was to evaluate whether a general self-efficacy proxy predicts incident frailty.MethodsA nationally representative sample of 4825 U.S. older adults aged 65 and older living in the community or non-nursing home care setting enrolled in the National Health and Aging Trends Study from 2011 to 2018 was used. Self-efficacy was dichotomized into low and high groups using the one-item self-efficacy proxy measure. The Physical Frailty Phenotype was used to categorize participants as frail and non-frail. A discrete time hazard model using data from eight rounds was used to obtain incident hazard ratios of frailty in two models. Model 1 was adjusted for age, race, sex, education, and income. Model 2 contained Model 1 covariates and added disability and comorbidities.ResultsAmong people without frailty at baseline, risk of developing frailty over 7 years was increased by 41% among those with low versus high self-efficacy after adjustment for sociodemographics (P = 0.002), and by 27% after further adjustment for disability and comorbidities (P = 0.032).ConclusionThis study generates a rationale to further explore self-efficacy in frailty research. Self-efficacy may be a key modifiable element to incorporate into multimodal physical frailty interventions.
| S-EPMC8648965 | biostudies-literature
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.
| S-EPMC6172837 | biostudies-literature
Project description:Background: Limited research has examined how older adults' lifestyles intersect with multimorbidity to influence mortality risk. Methods: In this community-dwelling prospective cohort, the Sydney Memory and Ageing Study, principal component analysis was used to identify lifestyle patterns using baseline self-reported data on nutrition, lifestyle factors, and social engagement activities. Multimorbidity was defined by self-reported physician diagnoses. Multivariable logistic regression was used to estimate odds ratios (ORs) for multimorbidity cross-sectionally, and Cox proportional hazards models were used to assess hazard ratios (HRs) for mortality risk longitudinally. Results: Of 895 participants (mean age: 78.2 years; 56.3% female) with complete lifestyle data, 597 had multimorbidity. Two distinct lifestyle patterns emerged: (i) a nutrition pattern characterised by higher intakes of protein, fibre, iron, zinc, magnesium, potassium, and folate, and (ii) an exercise-sleep-social pattern marked by weekly physical activities like bowling, bicycling, sleep quality (low snoring/sleepiness), and high social engagement. Neither pattern was associated with multimorbidity cross-sectionally. Over a median 5.8-year follow-up (n = 869; 140 deaths), participants in the upper tertiles for combined lifestyle pattern scores had a 20% lower mortality risk than those in the lowest tertile [adjusted HR: 0.80 (95% CI: 0.65-0.97); p-trend = 0.02]. This association was stronger in participants with multimorbidity, with a 29% lower risk [0.71 (0.56-0.89); p-trend = 0.01], likely due to multimorbidity modifying the relationship between nutrition and mortality risk (p-interaction < 0.05). While multimorbidity did not modify the relationship between the exercise-sleep-social pattern and risk of mortality, it was consistently associated with a 19-20% lower risk (p-trend < 0.03), regardless of the multimorbidity status. Conclusions: Older adults with multimorbidity may particularly benefit from adopting healthy lifestyles focusing on nutrition, physical activity, sleep quality, and social engagement to reduce their mortality risk.
| S-EPMC11901584 | biostudies-literature
Project description:BackgroundFrailty 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.MethodsData 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.Findings493 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.InterpretationEfforts 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.FundingCSO Catalyst Grant and National Health Service Research for Scotland Career Research Fellowship.
| S-EPMC6028743 | biostudies-literature
Project description:ObjectiveThe aim of this study was to assess the impact of the burden and patterns of multimorbidity on disability domains.DesignIn a cross-sectional study of 425 older adults from the Boston Rehabilitative Impairment Study of the Elderly, participants self-reported 13 chronic conditions and underwent assessment of body function (leg strength, velocity, and power, trunk extensor endurance, leg range of motion, foot sensation), activities (400-m walk test, Short Physical Performance Battery, Late Life Function and Disability Instrument function scores) and participation (Late Life Function and Disability Instrument participation scores). The association between multimorbidity patterns (identified by latent class analysis) and disablement measures, as well as multimorbidity burden (captured by a multimorbidity score) and disablement measures, was tested.ResultsLatent class analysis identified three classes-low multimorbidity, high multimorbidity, and predominantly musculoskeletal conditions. Class membership (multimorbidity pattern) was not associated with disablement measures, but multimorbidity score was associated with poor performance in all domains. A 1-point higher multimorbidity score was associated with lower scores in body functions (by 0.06 SD unit), activities (0.07-0.10 SD units), as well as participation (0.07-0.09 units).ConclusionMultimorbidity counts may be an excellent tool for risk stratification and identification of persons in need of rehabilitation.To claim cme creditsComplete the self-assessment activity and evaluation online at http://www.physiatry.org/JournalCME CME OBJECTIVES: Upon completion of this article, the reader should be able to (1) describe and distinguish the effect of multimorbidity burden and multimorbidity patterns on three disability domains in older adults; (2) identify and discuss possible reasons why high multimorbidity burden may result in a restriction among social participation in older adults; and (3) detect disability risk among older patients during clinical assessment by using a simple count of common chronic conditions.LevelAdvanced ACCREDITATION: The Association of Academic Physiatrists is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.The Association of Academic Physiatrists designates this Journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 Credit(s)™. Physicians should only claim credit commensurate with the extent of their participation in the activity.
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