Dataset Information

Factors Contributing to Unexpected Retirement and Unemployment in Adults Over 50 Years Old in Ireland.

ABSTRACT: Older adults are increasingly important to maintaining stable workforces. As such, factors contributing to early workforce exit must be identified. This study aimed to identify predictors of unexpected retirement and unemployment at older age, with respect to psychological constructs, resulting adverse behaviors, and health-related factors reflecting functional status. Data were extracted from The Irish Longitudinal Study on Ageing (TILDA) to predict unexpected retirement and unemployment in older adults in Ireland. Increasing age, increasing number of impairments in activities of daily living, and frailty status of "pre-frail/frail" (relative to non-frail) increased the likelihood of unexpected retirement; while greater numbers of physical limitations and "pre-frail/frail" status significantly predicted unemployment at older age. Pre-frail/frail status or reduced physical capability for everyday tasks may adversely affect older individuals' ability to obtain and/or maintain employment. These findings advance the current understanding of factors associated with unexpected retirement and unemployment at older ages. Findings may aid in identifying strategies to extend working life and to aid at-risk older adults, and may inform components of care on which to focus to minimize loss of function and mobility, and maintain independence, with aging.

SUBMITTER: Schinkel-Ivy A

PROVIDER: S-EPMC5536377 | biostudies-other | 2017 Jan-Dec

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:BackgroundIt is well reported that malnutrition in acute care is associated with poorer health outcomes including increased mortality. However, the consequences of malnutrition on survival in community settings is uncertain. Malnutrition in people 65 years or over is often cited. Nevertheless, this study includes both middle-aged and older adults as current public health policy is highlighting the need to increase disease-free life years and is moving away from just extending life to increase overall longevity. The aim of this study is to describe the association of the risk of malnutrition using the Malnutrition Universal Screening Tool (MUST) with mortality in community-dwelling middle-aged and older adults.MethodsWe used the UK Biobank to investigate the association between those at risk of malnutrition and mortality in participants aged ≥50 years. MUST identified risk of malnutrition and linked data to national death registries confirmed mortality. Years of life lost (YLL) and Cox proportional hazard models with hazard ratios (HR) and confidence intervals (CI) described risk associated with all-cause mortality.ResultsThere were 502 408 participants recruited, 117 830 were ≤50 years leaving 384 578 eligible participants. Based on MUST scores 63 495 (16.5%) were at risk of malnutrition with 401 missing some data and excluded. Incidence of mortality for at risk participants was 755 per 100 000 person-years, corresponding to 153 476 YLL. Of those at risk of malnutrition, 9.5% died versus 7.8% at low risk. Initial survival analysis reported an increased risk of mortality (HR 1.29, 95% CI: 1.25 to 1.33) that decreased after adjusting for confounders (HR 1.14, 95% CI: 1.11 to 1.18) in those at risk of malnutrition versus those at low risk.ConclusionsRisk of malnutrition was associated with increased overall mortality. Modest effect sizes are demonstrated but are supportive of public health policies, which advocate wide-scale community, based nutritional screening for middle-aged and older adults.

Project description:BackgroundFunctional limitations may be more common in middle-aged adults than previously recognized. However, there are few published data on the prevalence of activity limitations, and their association with multimorbidity, among adults 50 to 64 years old.ObjectiveTo describe the prevalence of activity limitations and the association with multimorbidity in middle-aged adults.DesignCross-sectional analysis of US population-based National Health and Nutrition Examination Survey (NHANES) 2011-2016.ParticipantsThe total number of community-dwelling NHANES participants aged 50-64 years old is 4217.Main measuresChronic conditions included hypertension, high cholesterol, diabetes mellitus, obesity, chronic kidney disease, cancer, stroke, coronary heart disease, heart failure, chronic obstructive pulmonary disease/asthma, arthritis, and depression. Activity limitations were defined as any difficulty within each of four International Classification of Functioning (ICF) domains: functional limitations (kneeling, carrying, standing, sitting, reaching, grasping, pulling), mobility (walking ¼ mile, climbing 10 steps), basic activities of daily living (BADLs; walking, transferring, eating, dressing), and instrumental activities of daily living (IADLs; finances, chores, cooking). We calculated prevalence ratios for activity limitations using generalized estimating equations.Key resultsThe prevalence of functional limitations, mobility limitations, BADL difficulty, and IADL difficulty was 34%, 11%, 15%, and 17%, respectively. Seventy-two percent of participants had two or more chronic conditions; 23% had two, 18% had three, 15% had four, and 16% had five or more. Multivariable adjusted prevalence ratios (95% CI) for functional limitations among those with 2, 3, 4, and 5 or more chronic conditions, compared with 0-1 conditions, were 1.94 (1.43-2.63), 2.50 (1.93-3.23), 3.26 (2.48-4.27), and 4.54 (3.48-5.93), respectively (p trend < 0.001). Larger prevalence ratios at a higher number of chronic conditions were present for mobility limitations, BADL difficulty, and IADL difficulty.ConclusionsProblems with function are not limited to older adults and multimorbidity may be helpful for identifying middle-aged adults with a high prevalence of activity limitations.

Dataset Information

Factors Contributing to Unexpected Retirement and Unemployment in Adults Over 50 Years Old in Ireland.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets