Community-Level Factors Associated with Health-Related Quality of Life Among Older Adults

Objective: Health-related quality of life (HRQOL) and well-being is a new topic area for Healthy People 2020 in the U.S. In a broad-based literature review, more research explored individual level factors of HRQOL, and few focused on older adults. Multilevel analysis was seldom adopted to investigate the relationship between area-level socioeconomic or social environment factors and HRQOL. In lieu of the traditional Chapter 4 (Results) and Chapter 5 (Conclusion), two manuscripts representing the two specific research aims are included. The main aim of first manuscript was to explore the association between area deprivation, area health resources and older adults’ HRQOL. The purpose of this study was to develop county-level estimates of poor HRQOL among older U.S. adults, and to identify spatial clusters of area deprivation and poor HRQOL using a multilevel, post-stratification (MPS) approach. Method: Cross-sectional study utilizing the 2011 and 2012 Behavioral Risk Factor Surveillance System (BRFSS), merged with data from the 2013-2014 the Area Health Resources File (AHRF), the 2014 Food Environment Atlas Data File, and 2014 County Health Rankings (CHRs) file. The dependent variables were three HRQOL dimensions (general health (GH), physical health (PH), and mental health (MH)). County level analysis utilized Ford and Dzealtowski’s area deprivation index, and other health resource factors. Multilevel reweighted modeling techniques examined the county effect on older adults’ HRQOL, after accounting for individual-level characteristics. Subsequently, post-stratification for small area estimation (SAE) was conducted to generate county-level probabilities of poor HRQOL in older adults in the U.S. Finally, we employed global and local Moran’s I (LISA) testing to evaluate the spatial autocorrelation of county-level probabilities of poor HRQOL in older adults and area deprivation. Results: Area variation was associated with HRQOL, although differences at the area level only contributed modestly to older adult’s HRQOL (6.58%, 2.08%, and 1.80% for GH, PH, and MH, respectively). Older adults living in higher area deprivation counties had a higher probability of having fair/poor GH and more physically unhealthy days compared to those living in lower area deprivation counties, but had a lower probability of having mentally unhealthy days, after adjusting for individual and other county characteristics. The range of county-level probabilities of poor HRQOL in older adults in each state is 0.18-0.35, 0.21-0.32, and 0.14-0.24 for general health, physical health, and mental health, respectively. The spatial autocorrelation tests found that county-level probabilities of poor HRQOL in older adults and area deprivation were spatially dependent. Conclusion: Despite adjusting for individual level factors, contextual factors continue to exert an important influence on health outcomes, although results were generally smaller than the effects from individual-level factors. Individual-level characteristics had a stronger affect than county-level factors. Furthermore, bivariate choropleth maps and spatial autocorrelations effectively identify vulnerable counties. These results may help to target interventions towards specific counties, based on the results from our SAEs and spatial clustering tests. There are potential implications for the provision of health and social services and more generally for policies affecting community cohesiveness