Dataset Information

HUD Housing Assistance Associated With Lower Uninsurance Rates And Unmet Medical Need.

ABSTRACT: To investigate whether receiving US Department of Housing and Urban Development (HUD) housing assistance is associated with improved access to health care, we analyzed data on nondisabled adults ages 18-64 who responded to the 2004-12 National Health Interview Survey that were linked with administrative data from HUD for the period 2002-14. To account for potential selection bias, we compared access to care between respondents who were receiving HUD housing assistance at the time of the survey interview (current recipients) and those who received HUD assistance within twenty-four months of completing the survey interview (future recipients). Receiving assistance was associated with lower uninsurance rates: 31.8 percent of current recipients were uninsured, compared to 37.2 percent of future recipients. Rates of unmet need for health care due to cost were similarly lower for current recipients than for future recipients. No effect of receiving assistance was observed on having a usual source of care. These findings provide evidence that supports the effectiveness of housing assistance in improving health care access.

SUBMITTER: Simon AE

PROVIDER: S-EPMC5603165 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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HUD Housing Assistance Associated With Lower Uninsurance Rates And Unmet Medical Need.

Simon Alan E AE Fenelon Andrew A Helms Veronica V Lloyd Patricia C PC Rossen Lauren M LM

Health affairs (Project Hope) 20170601 6

To investigate whether receiving US Department of Housing and Urban Development (HUD) housing assistance is associated with improved access to health care, we analyzed data on nondisabled adults ages 18-64 who responded to the 2004-12 National Health Interview Survey that were linked with administrative data from HUD for the period 2002-14. To account for potential selection bias, we compared access to care between respondents who were receiving HUD housing assistance at the time of the survey i ...[more]

PMID: 28583959

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Project description:BackgroundIdentifying predictors of subjective unmet need for assistance with activities of daily living (ADL) is necessary to allocate resources in social care effectively to the most vulnerable populations. In this study, we aimed at identifying population groups at risk of subjective unmet need for assistance with ADL and instrumental ADL (IADL) taking complex interaction patterns between multiple predictors into account.MethodsWe included participants aged 55 or older from the cross-sectional German Health Update Study (GEDA 2019/2020-EHIS). Subjective unmet need for assistance was defined as needing any help or more help with ADL (analysis 1) and IADL (analysis 2). Analysis 1 was restricted to participants indicating at least one limitation in ADL (N = 1,957). Similarly, analysis 2 was restricted to participants indicating at least one limitation in IADL (N = 3,801). Conditional inference trees with a Bonferroni-corrected type 1 error rate were used to build classification models of subjective unmet need for assistance with ADL and IADL, respectively. A total of 36 variables representing sociodemographics and impairments of body function were used as covariates for both analyses. In addition, the area under the receiver operating characteristics curve (AUC) was calculated for each decision tree.ResultsDepressive symptoms according to the PHQ-8 was the most important predictor of subjective unmet need for assistance with ADL. Further classifiers that were selected from the 36 independent variables were gender identity, employment status, severity of pain, marital status, and educational level according to ISCED-11. The AUC of this decision tree was 0.66. Similarly, depressive symptoms was the most important predictor of subjective unmet need for assistance with IADL. In this analysis, further classifiers were severity of pain, social support according to the Oslo-3 scale, self-reported prevalent asthma, and gender identity (AUC = 0.63).ConclusionsReporting depressive symptoms was the most important predictor of subjective unmet need for assistance among participants with limitations in ADL or IADL. Our findings do not allow conclusions on causal relationships. Predictive performance of the decision trees should be further investigated before conclusions for practice can be drawn.

Dataset Information

HUD Housing Assistance Associated With Lower Uninsurance Rates And Unmet Medical Need.

Publications

HUD Housing Assistance Associated With Lower Uninsurance Rates And Unmet Medical Need.

Similar Datasets

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