Dataset Information

Age, Race, and Gender Factors in Incident Disability.

ABSTRACT:

Background

Incident disability rates enable the comparison of risk across populations. Understanding these by age, sex, and race is important for planning for the care of older adults and targeting prevention.

Methods

We calculated incident disability rates among older adults in the Cardiovascular Health Study, a study of 5,888 older adults aged ≥ 65 years over 6 years of follow-up. Disability was defined in the following two ways: (i) self-report of disability (severe difficulty or inability) in any of six Activities of Daily Living (ADL), and (ii) mobility difficulty (any difficulty walking half a mile or climbing 10 steps). Incident disability rates were calculated as events per 100 person years for age, gender, and race groups.

Results

The incidence of ADL disability, and mobility difficulty were 2.7 (2.5-2.8), and 9.8 (9.4-10.3) events per 100 person years. Women, older participants, and blacks had higher rates in both domains.

Conclusion

Incidence rates are considerably different based on the domain examined as well as age, race, and gender composition of the population. Prevention efforts should focus on high risk populations and attempt to ameliorate factors that increase risk in these groups.

SUBMITTER: Jacob ME

PROVIDER: S-EPMC5861898 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Age, Race, and Gender Factors in Incident Disability.

Jacob Mini E ME Marron Megan M MM Boudreau Robert M RM Odden Michelle C MC Arnold Alice M AM Newman Anne B AB

The journals of gerontology. Series A, Biological sciences and medical sciences 20180101 2

<h4>Background</h4>Incident disability rates enable the comparison of risk across populations. Understanding these by age, sex, and race is important for planning for the care of older adults and targeting prevention.<h4>Methods</h4>We calculated incident disability rates among older adults in the Cardiovascular Health Study, a study of 5,888 older adults aged ≥ 65 years over 6 years of follow-up. Disability was defined in the following two ways: (i) self-report of disability (severe difficulty ...[more]

PMID: 29045556

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Project description:BackgroundIn 2012, over half of US medical students experienced burnout and depression. Since that time, there have been many changes to student demographics, school resources and awareness of burnout in the medical field altogether. New tools are also available to screen for student distress, a condition that correlates with low mental quality-of-life, suicidal ideation and serious thoughts of dropping out. Despite increased attention on wellbeing and improved screening methods, no large-scale studies have evaluated student distress in the modern era of medical education. The objective of this study was to determine the current prevalence of medical student distress and contributing risk factors.MethodsStudent wellbeing from a national cohort of US medical students was measured with an electronic survey in a prospective, observational survey study from 2019-2020. Medical student distress was defined as a Medical Student Wellbeing Index (MS-WBI) of ≥4. Demographic details including age, race, gender, marital status, disability, desired specialty, and debt burden were evaluated in a multivariate logistic regression model to determine possible risk factors for the development of distress.ResultsA total of 3,162 students responded to the survey, representing 110 unique medical schools. Of these respondents, 52.9% met criteria for distress and 22% had either taken or considered taking a leave of absence for personal wellbeing. Independent risk factors for distress included involvement in the clinical phase of medical school (OR 1.37); non-male gender (OR 1.6); debt burden >$20,000 (OR 1.37), >$100,000 (OR 1.81), and >$300,000 (OR 1.96); and disability status (OR 1.84).ConclusionsMedical student wellbeing remains poor in the modern era of medical education despite increased attention to wellbeing and increased availability of wellbeing resources. Disability status is a novel risk factor for distress identified in this study. The persistence of previously identified risk factors such as non-male gender, debt burden and clinical phase of school suggest that efforts to curb medical student distress have been inadequate to date.

Project description:Background and Purpose- Cross sectional analyses have found large race differences in poststroke disability, yet these analyses do not account for prestroke disability, hospitalization factors, postacute care, transitions, or mortality. In this context, we explore mortality, nursing home placement, and disability in a longitudinal analysis of older stroke survivors who survived at least 90 days poststroke. Methods- A prospective cohort of black or white stroke survivors from the National Health and Aging Trends Study (2009-2016) linked to Medicare were used. Disability was assessed during in-person interviews with validated scales (0-7). We used cox proportional hazards models to separately assess mortality and nursing home admission adjusting for age, sex, sociodemographics (marital status, education, income, insurance status, social network size), comorbidities, hospitalization factors, postacute care, and 90-day readmissions. To estimate racial differences in disability, we used a multilevel linear regression model initially adjusting for age and sex and then compared with a model adjusted for sociodemographics, comorbidities, hospitalization factors, postacute care, and 90-day readmissions. Results- There were 282 stroke survivors, of which 76 (12.6%) were black. There were no race differences in long-term mortality (hazard ratio for black, 1.2 [95% CI, 0.7-2.2]; P=0.5) or nursing home placement (hazard ratio for black, 0.7 [95% CI, 0.2-2.4]; P=0.5). The largest race differences in disability were observed immediately prestroke, estimated age- and sex-adjusted activity limitations were (2.6 [2.0-3.2] in blacks versus 1.4 [1.0-1.8] in whites, mean difference, 1.2 [0.5-1.9], P<0.001) and immediately poststroke (2.6 [2.0-3.3] in blacks versus 1.7 [1.2-2.1] in whites, mean difference, 1.0 [0.2-1.7], P<0.01). Full adjustment did not substantially change the associations between race and disability. Conclusions- Race differences in nursing home placement, long-term mortality, sociodemographics, comorbidities, hospitalization factors, postacute care, and readmissions are unlikely to be large contributors to race differences in poststroke disability. Further research is needed to understand the drivers of race differences in poststroke disability.

Dataset Information

Age, Race, and Gender Factors in Incident Disability.

Background

Methods

Results

Conclusion

Publications

Age, Race, and Gender Factors in Incident Disability.

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