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An evaluation of the American Community Survey indicators of disability.

ABSTRACT: BACKGROUND:Collection of data in the Census for implementing disability legislation has been continuous since 1970 although the questions used have changed several times. Concerns have been raised about the ability of the newest question set developed for the American Community Survey (ACS) to adequately represent the population with disabilities because it does not capture all those eligible for certain benefit programs. OBJECTIVE:Using national data, we examine how the addition of questions on the receipt of SSI/SSDI changes the composition of the population identified by the ACS measures. In ancillary materials we also examine the addition of a work limitation question to the population identified by ACS measures. METHODS:Using descriptive secondary analysis of 2011 NHIS data we compare the characteristics of those identified by the ACS questions to those identified by the ACS questions and receipt of SSI/SSDI and those only receiving SSI/SSDI. The comparison is based on conditions, specific functional limitations and severity of limitation. RESULTS:The results provide evidence ACS questions identify a population representing persons at risk for participation difficulties including those who receive SSI/SSDI. The ACS population has higher proportions with mental health and development disabilities than comparison population. The ancillary data demonstrates the work limitation question does not make a significant difference in identifying recipients of SSI/SSDI. CONCLUSION:The analysis demonstrates that the disability measures developed for the ACS produce an unbiased picture of the population with disabilities by including persons with all conditions, more severe disability or selected types of functional limitations.

SUBMITTER: Altman BM

PROVIDER: S-EPMC7532801 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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An evaluation of the American Community Survey indicators of disability.

Altman Barbara M BM Madans Jennifer J Weeks Julie D JD

Disability and health journal 20170315 4

<h4>Background</h4>Collection of data in the Census for implementing disability legislation has been continuous since 1970 although the questions used have changed several times. Concerns have been raised about the ability of the newest question set developed for the American Community Survey (ACS) to adequately represent the population with disabilities because it does not capture all those eligible for certain benefit programs.<h4>Objective</h4>Using national data, we examine how the addition ...[more]

PMID: 28385572

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Project description:BackgroundDisability in Activities of Daily Living (ADL) is an adverse outcome of frailty that places a burden on frail elderly people, care providers and the care system. Knowing which physical frailty indicators predict ADL disability is useful in identifying elderly people who might benefit from an intervention that prevents disability or increases functioning in daily life. The objective of this study was to systematically review the literature on the predictive value of physical frailty indicators on ADL disability in community-dwelling elderly people.MethodsA systematic search was performed in 3 databases (PubMed, CINAHL, EMBASE) from January 1975 until April 2010. Prospective, longitudinal studies that assessed the predictive value of individual physical frailty indicators on ADL disability in community-dwelling elderly people aged 65 years and older were eligible for inclusion. Articles were reviewed by two independent reviewers who also assessed the quality of the included studies.ResultsAfter initial screening of 3081 titles, 360 abstracts were scrutinized, leaving 64 full text articles for final review. Eventually, 28 studies were included in the review. The methodological quality of these studies was rated by both reviewers on a scale from 0 to 27. All included studies were of high quality with a mean quality score of 22.5 (SD 1.6). Findings indicated that individual physical frailty indicators, such as weight loss, gait speed, grip strength, physical activity, balance, and lower extremity function are predictors of future ADL disability in community-dwelling elderly people.ConclusionsThis review shows that physical frailty indicators can predict ADL disability in community-dwelling elderly people. Slow gait speed and low physical activity/exercise seem to be the most powerful predictors followed by weight loss, lower extremity function, balance, muscle strength, and other indicators. These findings should be interpreted with caution because the data of the different studies could not be pooled due to large variations in operationalization of the indicators and ADL disability across the included studies. Nevertheless, our study suggests that monitoring physical frailty indicators in community-dwelling elderly people might be useful to identify elderly people who could benefit from disability prevention programs.

Project description:BACKGROUND:In Australia, the proportion of medical students with disability remains low compared to students with disability in other university courses and to the prevalence of disability in society. Arguments for inclusion include medical school obligations to respond to community values in their programs, and that doctors with disabilities can offer valuable insights for patient care from their experiences. This study aimed to inform inclusive and socially accountable medical programs by investigating community views on doctors and medical students with disability. METHODS:A concurrent mixed methods study was conducted, simultaneously collecting quantitative fixed responses, and qualitative free text responses to provide in-depth and triangulated data on community views. Frequency and thematic analysis within and across response categories was used to identify patterns and relationships, providing context and meaning to the quantitative data for the integrated findings. RESULTS:Of 207 respondents aged 17 to 71 years, 71% were female, and 60.2% had university level education. Most (92.3%) knew someone with a long standing disability, illness, mental health condition or learning difficulty, 74.7% agreed that a person with a disability should be encouraged to study medicine, 79.7% agreed that a person with a disability should be accepted into medical school, and 81.4% that including people with disability would be an advantage in the medical profession. Five integrated themes explained these views: 1) Fair selection, support and monitoring is expected of medical schools, 2) Life experiences of disability promotes real empathy in doctors, 3) Career considerations for those with disability, 4) Medical role models to address disabling social barriers, and 5) Responsibility to monitor own health and ability to perform. CONCLUSIONS:This study indicates Australian community support for inclusion of people with disability as medical students and practitioners. Findings also suggest community expectations and trust in medical schools to effectively select and graduate only those who will be capable doctors, and to support health and development of all students towards being competent graduates. These findings provide support for medical schools to develop inclusive practices in medical education and training relevant to the health services and communities they serve.

Project description:Across the United States public health community in 2020, in the midst of a pandemic and increased concern regarding racial/ethnic health disparities, there is widespread concern about our ability to accurately estimate small-area disease incidence rates due to the absence of a recent census to obtain reliable population denominators. 2010 decennial census data are likely outdated, and intercensal population estimates from the Census Bureau, which are less temporally misaligned with real-time disease incidence data, are not recommended for use with small areas. Machine learning-based population estimates are an attractive option but have not been validated for use in epidemiologic studies. Treating 2010 decennial census counts as a "ground truth", we conduct a case study to compare the performance of alternative small-area population denominator estimates from surrounding years for modeling real-time disease incidence rates. Our case study focuses on modeling health disparities in census tract incidence rates in Massachusetts, using population size estimates from the American Community Survey (ACS), the most commonly-used intercensal small-area population data in epidemiology, and WorldPop, a machine learning model for high-resolution population size estimation. Through simulation studies and an analysis of real premature mortality data, we evaluate whether WorldPop denominators can provide improved performance relative to ACS for quantifying disparities using both census tract-aggregate and race-stratified modeling approaches. We find that biases induced in parameter estimates due to temporally incompatible incidence and denominator data tend to be larger for race-stratified models than for area-aggregate models. In most scenarios considered here, WorldPop denominators lead to greater bias in estimates of health disparities than ACS denominators. These insights will assist researchers in intercensal years to select appropriate population size estimates for modeling disparities in real-time disease incidence. We highlight implications for health disparity studies in the coming decade, as 2020 census counts may introduce new sources of error.

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An evaluation of the American Community Survey indicators of disability.

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An evaluation of the American Community Survey indicators of disability.

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