Dataset Information

Population-Based Screening for Functional Disability in Older Adults.

ABSTRACT:

Background and objectives

Screening for functional disability is a promising strategy to identify high-need older adults. We compare 2 disability measures, activities of daily living (ADLs), and life space constriction (LSC), in predicting hospitalization and mortality in older adults.

Research design and methods

We used the nationally representative National Health and Aging Trends Study of 30,885 observations of adults aged 65 years and older. Outcomes were 1-year mortality and hospitalization. Predictors were ADLs (receiving help with bathing, eating, dressing, toileting, getting out of bed, walking inside) and LSC (frequency of leaving home).

Results

Of respondents, 12.4% reported 3 or more ADLs and 10.8% reported rarely/never leaving home. ADL disability and LSC predicted high rates of 1-year mortality and hospitalization: of those with 3 or more ADLs, 46.4% died and 41.0% were hospitalized; of those who never/rarely left home, 40.7% died and 37.0% were hospitalized. Of those with both 3 or more ADLs and who never/rarely left home, 58.4% died. ADL and LSC disability combined was more predictive of 1-year mortality and hospitalization than either measure alone. ADL disability and LSC screens identified overlapping but distinct populations. LSC identified more women (72.6% vs 63.8% with ADL disability), more people who live alone (40.7% vs 30.7%), fewer who were White (71.7% vs 76.2%) with cancer (27.6% vs 32.4), and reported pain (67.1% vs 70.0%).

Discussion and implications

LSC and ADLs both independently predicted mortality and hospitalization but using both screens was most predictive. Routine screening for ADLs and LSC could help health systems identify those at high risk for mortality and health care use.

SUBMITTER: Ankuda CK

PROVIDER: S-EPMC7817111 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

Population-Based Screening for Functional Disability in Older Adults.

Ankuda Claire K CK Freedman Vicki A VA Covinsky Kenneth E KE Kelley Amy S AS

Innovation in aging 20201222 1

<h4>Background and objectives</h4>Screening for functional disability is a promising strategy to identify high-need older adults. We compare 2 disability measures, activities of daily living (ADLs), and life space constriction (LSC), in predicting hospitalization and mortality in older adults.<h4>Research design and methods</h4>We used the nationally representative National Health and Aging Trends Study of 30,885 observations of adults aged 65 years and older. Outcomes were 1-year mortality and ...[more]

PMID: 33506111

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Project description:BackgroundIt is important to identify older adults at high risk of functional disability and to take preventive measures for them at an early stage. To our knowledge, there are no studies that predict functional disability among community-dwelling older adults using machine learning algorithms.ObjectiveTo construct a model that can predict functional disability over 5 years using basic machine learning algorithms.DesignA cohort study with a mean follow-up of 5.4 years.ParticipantsWe used data from the Japan Gerontological Evaluation Study, which involved 73,262 people aged ≥ 65 years who were not certified as requiring long-term care. The baseline survey was conducted in 2013 in 19 municipalities.Main measuresWe defined the onset of functional disability as the new certification of needing long-term care that was ascertained by linking participants to public registries of long-term care insurance. All 183 candidate predictors were measured by self-report questionnaires.Key resultsDuring the study period, 16,361 (22.3%) participants experienced the onset of functional disability. Among machine learning-based models, ridge regression (C statistic = 0.818) and gradient boosting (0.817) effectively predicted functional disability. In both models, we identified age, self-rated health, variables related to falls and posture stabilization, and diagnoses of Parkinson's disease and dementia as important features. Additionally, the ridge regression model identified the household characteristics such as the number of members, income, and receiving public assistance as important predictors, while the gradient boosting model selected moderate physical activity and driving. Based on the ridge regression model, we developed a simplified risk score for functional disability, and it also indicated good performance at the cut-off of 6/7 points.ConclusionsMachine learning-based models showed effective performance prediction over 5 years. Our findings suggest that measuring and adding the variables identified as important features can improve the prediction of functional disability.

Project description:AimsCognitive impairment and functional status are both important determinants of poor outcomes in heart failure (HF). However, little is known about how functional status impacts the changes in cognitive status during the disease course. This study aimed to describe the cognitive transitions in patients with HF and assess the relationship of these transitions to functional status, which was assessed by the dependency of activities of daily living (ADL).Methods and resultsThis retrospective cohort study included 1764 patients with an International Classification of Diseases-10 code of HF (≥65 years, mean age 82.3 ± 7.9 years, 39% male) from a long-term care and medical insurance database from Nobeoka city, a rural city of south-western Japan. Cognitive status at baseline and 6, 12, 18, and 24 month time points was collected, and participants were stratified based on ADL status at baseline. Generalized estimating equations and multi-state modelling were used to examine associations between ADL dependency and cognitive changes/mortality. Transition probabilities were estimated using multi-state modelling. At baseline, there were 1279 (73%) and 485 (27%) patients with independent and dependent ADL, respectively. In overall patients, 1656 (93.9%) patients had normal/mild cognitive status and 108 (6%) patients had a moderate/severe cognitive status at baseline. The majority [104 (96%) patients] of patients with moderate/severe cognitive status at baseline had dependent ADL. In patients with moderate/severe cognitive status, the number of patients with dependent ADL always outnumbered that of the independent ADL throughout the follow-up. Multi-state modelling estimated that patients with dependent ADL and normal/mild cognitive status at baseline had 47% probability of maintaining the same cognitive status at 24 months, while the probability of maintaining the same cognitive status was 86% for those with independent ADL. Patients with normal/mild cognitive status in the dependent ADL group at baseline had a higher risk of experiencing a transition to moderate/severe cognitive status at any time point during 24 months compared with those with independent ADL [hazard ratio 5.24 (95% confidence interval 3.47-7.90)].ConclusionsIn older patients with HF, the prevalence of cognitive impairment was always higher for those with reduced functional status. Despite having a normal/mild cognitive status at baseline, patients with dependent ADL are at high risk of experiencing cognitive decline over 24 months with substantially less chance of maintaining their cognitive status. ADL dependency was an important risk factor of cognitive decline in patients with HF.

Project description:ObjectivesTo examine associations between weight change, body composition, risk of mobility disability, and mortality in older adults.DesignProspective, longitudinal, population-based cohort.SettingThe Health, Aging, and Body Composition Study.ParticipantsWomen (n = 1,044) and men (n = 931) aged 70 to 79.MeasurementsWeight and lean and fat mass from dual-energy X-ray absorptiometry measured annually over 5 years. Weight was defined as stable (n = 664, reference), loss (n = 662), gain (n = 321), or cycling (gain and loss, n = 328) using change of 5% from year to year or from Year 1 to 6. Mobility disability (two consecutive reports of difficulty walking one-quarter mile or climbing 10 steps) and mortality were determined for 8 years after the weight change period. Associations were analyzed using Cox proportional hazards regression adjusted for covariates.ResultsDuring follow-up, 313 women and 375 men developed mobility disability, and 322 women and 378 men died. There was no risk of mobility disability or mortality with weight gain. Weight loss (hazard ratio (HR) = 1.88, 95% confidence interval (CI) = 1.40-2.53) and weight cycling (HR = 1.59, 95% CI = 1.11-2.29) were associated with mobility disability in women, and weight loss was associated with mobility disability in men (HR = 1.30, 95% CI = 1.01-1.69). Weight loss and weight cycling were associated with mortality risk in women (weight loss: HR = 1.47, 95% CI = 1.07-2.01; weight cycling: HR = 1.62, 95% CI = 1.15-2.30) and in men (weight loss: HR = 1.41, 95% CI = 1.09-1.83; weight cycling: HR = 1.50, 95% CI = 1.08-2.08). Adjustment for lean and fat mass and change in lean and fat mass from Year 1 to 6 attenuated the relationships between weight loss and mobility disability in men and between weight loss and mortality in men and women.ConclusionWeight cycling and weight loss predict impending mobility disability and mortality in old age, underscoring the prognostic importance of weight history.

Dataset Information

Population-Based Screening for Functional Disability in Older Adults.

Background and objectives

Research design and methods

Results

Discussion and implications

Publications

Population-Based Screening for Functional Disability in Older Adults.

Similar Datasets

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