The Foreclosure Crisis, Community Change, and the Cognitive Health of Older Adults

In the wake of a crisis: Caught between housing and healthcare

Objective

To measure the association between housing insecurity and foregone medication due to cost among Medicare beneficiaries aged 65+ during the Recession.

Methods

Data came from Medicare beneficiaries aged 65+ years from the 2006-2012 waves of the Health and Retirement Study (HRS). Two-wave housing insecurity changes are evaluated as follows: (i) No insecurity, (ii) Persistent insecurity, (iii) Onset insecurity, and (iv) Onset security. We implemented a series of four weighted longitudinal General Estimating Equation (GEE) models, two minimally adjusted and two fully adjusted models, to estimate the probability of foregone medications due to cost between 2008 and 2012.

Results

Our study sample was restricted to non-proxy interviews of non-institutionalized Medicare beneficiaries aged 65+ in the 2006 wave (n = 9936) and their follow up visits (n = 8753; in 2008; n = 7464 in 2010; and n = 6594 in 2012). Results from our fully adjusted model indicated that the odds of foregone medication was 64% higher among individuals experiencing Onset insecurity versus No insecurity in 2008, and also generally larger for individuals experiencing Onset Insecurity versus Persistent Insecurity. Odds of foregone medication was also larger among females, minority versus non-Hispanic white adults, those reporting a chronic condition, those with higher medical expenditures, and those living in the South versus Northeast.

Conclusion

This study drew from nationally representative data to elucidate the disparate health and financial impacts of a crisis on Medicare beneficiaries who, despite health insurance coverage, displayed variability in foregone medication patterns. Our findings suggest that the onset of housing insecurity is most closely linked with unexpected acute economic shocks leading households with little time to adapt and forcing trade-offs in their prescription and other needs purchases. Both housing and healthcare policy implications exist from these findings including expansion of low-income housing units and rent relief post-recession as well as wider prescription drug coverage for Medicare adults.

The Health and Retirement Study: Contextual Data Augmentation

The Health and Retirement Study is an amazing resource for those studying aging in the United States, and a fantastic model for other countries who have created similar longitudinal studies. The raw amount of information, from data on income, wealth, and use of health services to employment, retirement, and family connections on to the collection of clinical biomarkers can be both empowering and overwhelming to a researcher. Luckily through the process of engagement with the research community and constant improvement, these reams of data are not only consistently growing in a thoughtful and focused direction, they are also explained and summarized to increase the ease of use for all. One of the very useful areas of the HRS is the Contextual Data File (CDF), which is the focus of this review. The CDF provides access to easy-to-use helpful community-level data in a secure environment that has allowed researchers to answer questions that would have otherwise been difficult or impossible to tackle. The current CDF includes data in six categories (University of Michigan Institute for Social Research. 2017. HRS Data Book: The Health and Retirement Study: Aging in the 21st Century, Challenges and Opportunities for Americans. Ann Arbor: University of Michigan. Also available at https://hrs.isr.umich.edu/about/data-book, 17): 1. Socio-economic Status and Demographic Structure 2. Psychosocial Stressors 3. Health Care 4. Physical Hazards 5. Amenities 6. Land Use and the Built Environment. Each of these areas have allowed researchers to answer interesting questions such as what is the impact of air pollution on cognition in older adults (Ailshire, J., and K. M. Walsemann. 2021. "Education Differences in the Adverse Impact of PM 2.5 on Incident Cognitive Impairment Among U.S. Older Adults." Journal of Alzheimer's Disease 79 (2): 615-25), the impact of neighborhood characteristics on obesity in older adults (Grafova, I. B., V. A. Freedman, R. Kumar, and J. Rogowski. 2008. "Neighborhoods and Obesity in Later Life." American Journal of Public Health 98: 2065-71), or even what do we gain from introducing contextual data to a survey analysis (Wilkinson, L. R., K. F. Ferraro, and B. R. Kemp. 2017. "Contextualization of Survey Data: What Do We Gain and Does it Matter?" Research in Human Development 14 (3): 234-52)? My review focuses on the potential to expand contextual data in a few of these areas. From new data sets developed and released by the U.S. Census Bureau, to improved measurements of climate and environmental risk, there are numerous new data sources that would be a boon to the research community if they were joined together with the HRS. The following section begins by breaking down the opportunity provided by community or place-based data before moving on to specific recommendations for new data that could be included in the HRS contextual data file.