Exploring geographic variation in us mortality rates using a spatial durbin approach

Previous studies focused on identifying the determinants of mortality in US counties have examined the relationships between mortality and explanatory covariates within a county only and have ignored the well-documented spatial dependence of mortality. We challenge earlier literature by arguing that the mortality rate of a certain county may also be associated with the features of its neighbouring counties beyond its own features. Drawing from both the spillover (i.e. same-direction effect) and social relativity (i.e. opposite-direction effect) perspectives, our spatial Durbin modelling results indicate that both theoretical perspectives provide valuable frameworks to guide the modelling of mortality variation in US counties. Our empirical findings support that the mortality rate of a certain county is associated with the features of its neighbours. Specifically, we found support for the spillover perspective in which the percentage of the Hispanic population, concentrated disadvantage, and the social capital of a specific county are negatively associated with the mortality rate in the specific county and also in neighbouring counties. On the other hand, the following covariates fit the social relativity process: health insurance coverage, percentage of non-Hispanic other races, and income inequality. Their direction of the associations with mortality in the specific county is opposite to that of the relationships with mortality in neighbouring counties. Methodologically, spatial Durbin modelling addresses the shortcomings of traditional analytic approaches used in ecological mortality research such as ordinary least squares, spatial error, and spatial lag regression. Our results produce new insights drawn from unbiased estimates.