Socioeconomic variables explain rural disparities in US mortality rates: Implications for rural health research and policy

Objectives: Rural disparities in age-adjusted mortality are growing in the United States. While socioeconomic variables have been found to explain significant variation in life expectancy across US counties, previous research has not examined the role of socioeconomic variables in explaining rural mortality disparities. The purpose of this study was to quantify the rural mortality disparity after controlling for socioeconomic variables.

Methods: Recursive partitioning, or tree regression, was used to fit models predicting premature mortality across counties in the United States, adjusted for age, median income, and percent in poverty in 4 time periods (from 2004 to 2012) with and without inclusion of an urban-rural variable.

Results: We found median income and percent in poverty explained about 50% of the variation in age-adjusted premature mortality rates across US counties in each of the four time periods. After controlling for these socioeconomic variables, rural mortality disparities largely disappeared, explaining less than 2% of the variance in premature mortality.

Conclusions: Addressing poverty and other socioeconomic issues should be a priority to improve health in rural communities. Interventions designed to target social determinants of health in rural areas are needed to address the growing rural mortality disparity that is largely explained by measures of poverty and income. Researchers examining rural health disparities should routinely include socioeconomic variables in their analyses.