Geographic Variation in the Health-Related Quality of Life (HRQOL) of US Counties

Background:  HRQOL research determines the burden of preventable disease, injuries, and disabilities known to impact physical or mental health.  Healthy People goals have identified improvement in quality of life as a central goal since 2000.  However, geographic variations in HRQOL at the US county level is a relatively unexplored area.  This study’s objective was to fill that gap. 

Methods:  Using the CDC Healthy Days measures from the US County Health Rankings data, 1) maps were created showing the geospatial distribution of mean physical and mental unhealthy days (in the past 30 days), 2) a bivariate map was developed to visually represent HRQOL clusters in the US.   Residuals from non-spatial multiple regression models (controlling for demographic and behavioral risks) were analyzed to find counties where expected physical and mental unhealthy days deviate from observed; maps were created that showed the geographic distributions of areas that are outperforming or underperforming expectations.  Spatial multiple regressions were conducted to examine geographic variability in the impacts of demographic and behavioral risks.

Results:  Areas with more unhealthy days clustered in central Appalachia and extending to the lower Midwest while areas with fewer unhealthy days clustered in the upper Midwest and the Northeast corridor.  Traditional risks accounted for approximately 49% and 36% of the variance in mean unhealthy physical and mental health days, respectively.  Results of the residual analysis identified areas that performed better or worse than expected after accounting for traditional risks. 

Conclusions:  Results suggest clusters of mean unhealthy and healthy HRQOL days in the US.  Furthermore, some US counties experience relatively more mean unhealthy mental health days than unhealthy physical health days, and vice versa.  Implications for interventions and health service needs are discussed.