Trajectories of frailty and related factors of elderly people in Mexico.
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ABSTRACT: Introduction
Frailty is an indicator of health status in old age and a common clinical syndrome in older adults that carries an increased risk of poor health outcomes, including falls, incidents of disability, hospitalization, and mortality. This study aimed to identify the different trajectories of frailty and the factors related to frailty among Mexican older adults over time.Methods
Data are from a four-wave panel composed of older Mexican adults from 2001 to 2015 of the Mexican Health and Aging Study (MHAS). Frailty is the accumulation of deficits using a frailty index. A multilevel analysis, using hierarchical models, was applied to know the changes of frailty trajectories and what factors are related to it.Results
Being female, older, being widowhood, and having a lower level of education were risk factors for having a high frailty index and lower financial satisfaction doing activities at home have adverse effects.Conclusion
The findings of this work present information about the prevalence of frailty considering the proportion of deficits that individuals possess and their main associated components in older Mexican adults. It is necessary to improve socioeconomic health conditions in phases before old age to avoid developing frailty in the future.
SUBMITTER: Rojas Huerta AV
PROVIDER: S-EPMC9286518 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:To identify distinct frailty trajectories (clusters of individuals following a similar progression of frailty over time) in an aging population and to estimate associations between frailty trajectories and emergency department visits, hospitalizations, and all-cause mortality.Population-based cohort study.Olmsted County, Minnesota.Olmsted County, Minnesota residents aged 60-89 in 2005.Longitudinal changes in frailty between 2005 and 2012 were measured by constructing a yearly Rockwood frailty index incorporating body mass index, 17 comorbidities, and 14 activities of daily living. The frailty index measures variation in health status as the proportion of deficits present of the 32 considered (range 0-1).Of the 16,443 Olmsted County residents aged 60-89 in 2005, 12,270 (74.6%) had at least 3 years of frailty index measures and were retained for analysis. The median baseline frailty index increased with age (0.11 for 60-69, 0.14 for 70-79, 0.19 for 80-89). Three distinct frailty trajectories were identified in individuals aged 60-69 at baseline and two trajectories in those aged 70-79 and 80-89. Within each decade of age, increasing frailty trajectories were associated with greater risks of emergency department visits, hospitalization, and all-cause mortality, even after adjustment for baseline frailty index.The number of frailty trajectories differed according to age. Within each age group, those in the highest frailty trajectory had greater healthcare use and worse survival. Frailty trajectories may offer a way to target aging individuals at high risk of hospitalization or death for therapeutic or preventive interventions.
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Project description:BackgroundSocial vulnerability is related to the health of elderly people, but its measurement and relationship to frailty are controversial. The aims of the present study were to operationalize social vulnerability according to a deficit accumulation approach, to compare social vulnerability and frailty, and to study social vulnerability in relation to mortality.Methods and findingsThis is a secondary analysis of community-dwelling elderly people in two cohort studies, the Canadian Study of Health and Aging (CSHA, 1996/7-2001/2; N = 3707) and the National Population Health Survey (NPHS, 1994-2002; N = 2648). Social vulnerability index measures that used self-reported items (23 in NPHS, 40 in CSHA) were constructed. Each measure ranges from 0 (no vulnerability) to 1 (maximum vulnerability). The primary outcome measure was mortality over five (CHSA) or eight (NPHS) years. Associations with age, sex, and frailty (as measured by an analogously constructed frailty index) were also studied. All individuals had some degree of social vulnerability. Women had higher social vulnerability than men, and vulnerability increased with age. Frailty and social vulnerability were moderately correlated. Adjusting for age, sex, and frailty, each additional social 'deficit' was associated with an increased odds of mortality (5 years in CSHA, odds ratio = 1.05, 95% confidence interval: 1.02-1.07; 8 years in the NPHS, odds ratio = 1.08, 95% confidence interval: 1.03-1.14). We identified a meaningful survival gradient across quartiles of social vulnerability, and although women had better survival than men, survival for women with high social vulnerability was equivalent to that of men with low vulnerability.ConclusionsSocial vulnerability is reproducibly related to individual frailty/fitness, but distinct from it. Greater social vulnerability is associated with mortality in older adults. Further study on the measurement and operationalization of social vulnerability, and of its relationships to other important health outcomes, is warranted.
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Project description:Frailty is considered to be a complex concept based mainly on physical vulnerability, but also vulnerabilities in mental/psychological and social aspects. Frailty can be reversible with appropriate intervention; however, factors that are important in recovering from frailty have not been clarified. The aim of the present study was to identify factors that help an individual reverse frailty progression and characteristics of individuals that have recovered from frailty. Community-dwelling people aged ≥75 years who responded to the Kihon Checklist (KCL) were enrolled in the study. The KCL consists of 25 yes/no questions in 7 areas: daily-life related activities, motor functions, nutritional status, oral functions, homebound, cognitive functions, and depressed mood. The number of social activities, degree of trust in the community, degree of interaction with neighbors, and subjective age were also evaluated. Frailty was assessed based on the number of checked items: 0-3 for robust, 4-7 for pre-frailty, and ≥8 for frailty. A total of 5050 participants were included for statistical analysis. At the time of the baseline survey in 2016, 18.7% (n = 942) of respondents had frailty, and the follow-up survey showed that the recovery rate from frailty within 2 years (median 24 months) was 31.8% (n = 300). Multiple logistic regression analysis showed that exercise-based social participation (odds ratio [OR] 2.0, 95% confidence interval [CI] 1.2-3.4; P<0.01) and self-rated health (OR 1.2, CI 1.0-1.5; P = 0.02) were related to reversing frailty progression. Principal component analysis indicated that the main factors constituting the first principal component (contribution rate, 18.3%) included items related to social capital, such as interaction with neighbors, trust in the community, and number of social participation activities. Our results demonstrate that exercise-based social participation and high self-rated health have associations with reversing frailty progression. Individuals that recovered from frailty are characterized by high individual-level social capital components (i.e., trust in community, interaction with neighbors, and social participation).
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Project description:Backgrounds and aimsHealth trajectories in aging, rather than single time-point assessments, could be early indicators of the onset of conditions such as dementia. The aim of this study was to identify different aging trajectories and to investigate their influence on the cumulative incidence of dementia.MethodsWe evaluated data referring to 993 elders from the InveCe.Ab study cohort. All subjects were free from dementia at baseline and re-assessed on at least one other occasion thereafter. Cognitive function was assessed using the Mini-Mental State Examination (MMSE), physical function using the Walking Speed Test (WST), and disability on the basis of the Activities of Daily Living (ADL) score. To describe the different courses of the three outcomes combined, the Group-Based Trajectory Model (GBTM) method was applied. We looked for differences in age, gender, education, ApoE-e4 carrier status and obesity, and then investigated the influence of the observed trajectories on the incidence of dementia.ResultsThree trajectories were identified: a "good" scenario was observed in 703 (70.2%) individuals, who showed substantially stable cognitive and physical function and no disability; an "intermediate" scenario in 248 subjects (25.5%), who recorded a longer walking time, lower MMSE score, and a one-point higher ADL score; and a "severe" scenario in 42 elders (4.3%), who recorded declines in all the outcomes. Female gender, obesity and low education were most represented in the "severe" group. ApoE-e4 carrier status showed no difference between groups. The estimated cumulative incidence of dementia was higher in the "severe" (37%) than in the "intermediate" (7%) and "good" (< 1%) scenarios.ConclusionsUsing simple measurements, we built different aging trajectories, and observed that the worst performers had the highest incidence of dementia. Better knowledge of trajectories of aging would be useful for preventive interventions aimed at promoting healthier aging.
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Project description:BackgroundInfluenza is an important cause of morbidity and mortality among older adults. Even so, effectiveness of influenza vaccine for older adults has been reported to be lower than for younger adults, and the impact of frailty on vaccine effectiveness (VE) and outcomes is uncertain. We aimed to study VE against influenza hospitalization in older adults, focusing on the impact of frailty.MethodsWe report VE of trivalent influenza vaccine (TIV) in people ≥65 years of age hospitalized during the 2011-2012 influenza season using a multicenter, prospective, test-negative case-control design. A validated frailty index (FI) was used to measure frailty.ResultsThree hundred twenty cases and 564 controls (mean age, 80.6 and 78.7 years, respectively) were enrolled. Cases had higher baseline frailty than controls (P = .006). In the fully adjusted model, VE against influenza hospitalization was 58.0% (95% confidence interval [CI], 34.2%-73.2%). The contribution of frailty was important; adjusting for frailty alone yielded a VE estimate of 58.7% (95% CI, 36.2%-73.2%). VE was 77.6% among nonfrail older adults and declined as frailty increased.ConclusionsDespite commonly held views that VE is poor in older adults, we found that TIV provided good protection against influenza hospitalization in older adults who were not frail, though VE diminished as frailty increased.Clinical trials registrationNCT01517191.
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Project description:BACKGROUND:Frailty is one of the most critical age-related conditions in older adults. It is often recognized as a syndrome of physiological decline in late life, characterized by a marked vulnerability to adverse health outcomes. A clear operational definition of frailty, however, has not been agreed so far. There is a wide range of studies on the detection of frailty and their association with mortality. Several of these studies have focused on the possible risk factors associated with frailty in the elderly population while predicting who will be at increased risk of frailty is still overlooked in clinical settings. OBJECTIVE:The objective of our study was to develop predictive models for frailty conditions in older people using different machine learning methods based on a database of clinical characteristics and socioeconomic factors. METHODS:An administrative health database containing 1,095,612 elderly people aged 65 or older with 58 input variables and 6 output variables was used. We first identify and define six problems/outputs as surrogates of frailty. We then resolve the imbalanced nature of the data through resampling process and a comparative study between the different machine learning (ML) algorithms - Artificial neural network (ANN), Genetic programming (GP), Support vector machines (SVM), Random Forest (RF), Logistic regression (LR) and Decision tree (DT) - was carried out. The performance of each model was evaluated using a separate unseen dataset. RESULTS:Predicting mortality outcome has shown higher performance with ANN (TPR 0.81, TNR 0.76, accuracy 0.78, F1-score 0.79) and SVM (TPR 0.77, TNR 0.80, accuracy 0.79, F1-score 0.78) than predicting the other outcomes. On average, over the six problems, the DT classifier has shown the lowest accuracy, while other models (GP, LR, RF, ANN, and SVM) performed better. All models have shown lower accuracy in predicting an event of an emergency admission with red code than predicting fracture and disability. In predicting urgent hospitalization, only SVM achieved better performance (TPR 0.75, TNR 0.77, accuracy 0.73, F1-score 0.76) with the 10-fold cross validation compared with other models in all evaluation metrics. CONCLUSIONS:We developed machine learning models for predicting frailty conditions (mortality, urgent hospitalization, disability, fracture, and emergency admission). The results show that the prediction performance of machine learning models significantly varies from problem to problem in terms of different evaluation metrics. Through further improvement, the model that performs better can be used as a base for developing decision-support tools to improve early identification and prediction of frail older adults.
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Project description:BACKGROUND AND OBJECTIVES:Frailty describes an increased vulnerability to adverse events such as disease or injury. Combatting this state remains a major challenge for geriatric research. By exploring how and why frailty changes throughout later life we will be better positioned to improve ways of identifying and treating those at high risk. RESEARCH DESIGN AND METHODS:We systematically reviewed publications that captured rate of frailty progression over time and established any associated risk or protective factors that affected this progression. We included longitudinal observational studies which quantified frailty trajectories in adults aged 50+ using any validated continuous frailty measurement tool. RESULTS:After screening 8,318 publications, 25 met our criteria. Findings show that despite a great degree of heterogeneity in the literature, progression of frailty is unquestionably affected by numerous risk and protective factors, with particular influence exhibited by social demographics, brain pathology, and physical co-morbidities. DISCUSSION AND IMPLICATIONS:Findings that the gradient of frailty progression is affected by various influencing factors are valuable to clinicians and policymakers as will help identify those at highest frailty risk and inform prevention strategies. However, the heterogeneous methodological approaches of the publications included in this review highlights the need for consensus within the field to promote more coordinated research. Improved consistency of methods will enable further data synthesis and facilitate a greater understanding of the shape of frailty over time and the influencing factors contributing to change, the results of which could have crucial implications for frailty risk reduction.
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Project description:BackgroundThe level of frailty in the older population across age cohorts and how this changes is a factor in determining future care costs and may also influence the extent of socioeconomic and gender inequalities in frailty.MethodsWe model cohort-specific trajectories in frailty among the community dwelling population older than 50 years, using five waves (2002-2010) of the English Longitudinal Study of Ageing. We stratify our analysis by wealth and gender and use a frailty index, based on accumulation of 'deficits'.ResultsFor males and females between the ages of 50 and 70 in 2002, frailty trajectories for adjacent age cohorts converge. However, levels of frailty are higher in recent compared with earlier cohorts at the older ages (for cohorts aged over 70 in 2002). These cohort differences are largest in the poorest wealth group, while for the most affluent, frailty trajectories overlap across all adjacent cohorts suggesting no change across cohorts.ConclusionsA key driver of the cohort differences in frailty that we observe is likely to be increased survival of frail individuals. Importantly, this paper illustrates that the social conditions experienced across the wealth distribution impacts on the rate of deficit accumulation in older populations. Our results on trajectories of frailty between 2002 and 2010 are pessimistic and, in the context of rising life expectancies, suggest that poorer older people in particular spend additional years of life in a frail state.
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Project description:Frailty is a geriatric syndrome, characterized by a loss in functional reserve with an increase in morbidity and mortality. There are no reports that link the genetic polymorphisms between interleukin 10 (IL10) and frailty; for this reason, our objective was used to analyze the role of the polymorphisms of IL10 (rs1800896, rs1800871) in the susceptibility to frailty in a Mexican population. Our study included 984 participants divided into 368 nonfrail, 309 prefrail, and 307 frail. The models for the polymorphisms rs1800896 and rs1800871 were recessive models in association with frailty (OR = 2.3, CI 95% = 1.6-3.2; OR = 1.53, CI 95% = 1.0-2.6), respectively. Two risk haplotypes were identified: ACG and CCG (p < .0001), and three protective haplotypes were identified: ACA, ATG, and ATA (p < .05). This study evaluated the relationship between IL10 and the three subtypes of this geriatric syndrome (frail, prefrail, and nonfrail). These results support a greater susceptibility to frailty for the minor alleles of rs1800871 and rs1800896. In addition, we found two risk haplotypes supporting the participation of the IL10 in the susceptibility for frailty in the Mexican population.
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Project description:To investigate associations between baseline frailty status and subsequent changes in QOL over time among community-dwelling older people.Among 363 community-dwelling older people ?65 years, frailty was measured using Frailty Index (FI) constructed from 40 deficits at baseline. QOL was measured using Older People's Quality of Life Questionnaire (OPQOL) six times over 2.5 years. Two-level hierarchical linear models were employed to predict QOL changes over time according to baseline frailty.At baseline, mean age was 73.1 (range 65-90) and 62.0 % were women. Mean FI was 0.17 (range 0.00-0.66), and mean OPQOL was 130.80 (range 93-163). The hierarchical linear model adjusted for age, gender, ethnicity, education, and enrollment site predicted that those with higher FI at baseline have lower QOL than those with lower FI (regression coefficient = -47.64, p < 0.0001) and that QOL changes linearly over time with slopes ranging from 0.80 (FI = 0.00) to -1.15 (FI = 0.66) as the FI increases. A FI of 0.27 is the cutoff point at which improvements in QOL over time change to declines in QOL.Frailty was associated with lower QOL among British community-dwelling older people. While less frail participants had higher QOL at baseline and QOL improved over time, QOL of frailer participants was lower at baseline and declined.
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