Explaining the spatial variation in American life expectancy. (February 2020)

• Record Type: Journal Article
• Authors: Dobis, Elizabeth A.; Stephens, Heather M.; Skidmore, Mark; Goetz, Stephan J.
• Is Part Of: Social science & medicine. Volume 246(2020)
• Publication Date: 2020-02
• Subjects: United States -- Life expectancy -- Community -- Spatial variation -- Spatial analysis; I12 -- R12; Social medicine -- Periodicals; Medical anthropology -- Periodicals; Public health -- Periodicals; Psychology -- Periodicals; Medicine -- Periodicals; Medicine -- Periodicals; Médecine sociale -- Périodiques; Anthropologie médicale -- Périodiques; Santé publique -- Périodiques; Psychologie -- Périodiques; Médecine -- Périodiques; Electronic journals; 362.105
• DOI: 10.1016/j.socscimed.2019.112759
• Languages: English
• ISSNs: 0277-9536

Abstract

Abstract: Since 1980, average life expectancy in the United States has increased by roughly five years; however, in recent years it has been declining. At the same time, spatial variation in life expectancy has been growing. To explore reasons for this trend, some researchers have focused on morbidity factors, while others have focused on how mortality trends differ by personal characteristics. However, the effect community characteristics may play in expanding the spatial heterogeneity has not yet been fully explored. Using a spatial Durbin error model, we explore how community and demographic factors influence county-level life expectancy in 2014, controlling for life expectancy in 1980 and migration over time, and analyzing men and women separately. We find that community characteristics are important in determining life expectancy and that there may be a role for policy makers in addressing factors that are associated with lower life expectancy in some regions. Highlights: There is statistically significant spatial clustering in county life expectancy. Community characteristics are associated with spatial variation in life expectancy. Community factors may influence life expectancy in surrounding locations. Individual characteristics continue to be strongly correlated with life expectancy.