ArticlePopulation, space and place2015
Exploring geographic variation in US mortality rates using a spatial Durbin approach.
Article in Population, space and place, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
20 citing papers in PubMed.
- Spatial Analysis of Lung Cancer Mortality and Its Potential Risk Factors: A Regional Study in Kansas.Preventive oncology & epidemiology · 2026Article
- Spatial spillover effects of area-level socioeconomic factors on life expectancy in Japan: an ecological study.International journal of health geographics · 2025Article
- Spatial characteristics of health outcomes and geographical detection of its influencing factors in Beijing.Frontiers in public health · 2024Article
- System Failure: The Geographic Distribution of Sepsis-Associated Death in the USA and Factors Contributing to the Mortality Burden of Black Communities.Journal of racial and ethnic health disparities · 2023Article
- Article
- Spatial analysis of cardiovascular mortality and associated factors around the world.BMC public health · 2022Article
- Spatial variations and social determinants of life expectancy in China, 2005-2020: A population-based spatial panel modelling study.The Lancet regional health. Western Pacific · 2022Article
- Neighbourhood Social Determinants of Health and Geographical Inequalities in Premature Mortality in Taiwan: A Spatiotemporal Approach.International journal of environmental research and public health · 2021Article
- The sociospatial factors of death: Analyzing effects of geospatially-distributed variables in a Bayesian mortality model for Hong Kong.PloS one · 2021Article
- Looking Back, Looking Forward: Progress and Prospect for Spatial Demography.Spatial demography · 2021Article
- Florida neighborhood analysis of social determinants and their relationship to life expectancy.BMC public health · 2020Article
- Modeling the Importance of Within- and Between-County Effects in an Ecological Study of the Association Between Social Capital and Mental Distress.Preventing chronic disease · 2019Article
- Looking through a different lens: Examining the inequality-mortality association in U.S. counties using spatial panel models.Applied geography (Sevenoaks, England) · 2017Article
- Spatial spillover and the socio-ecological determinants of diabetes-related mortality across US counties.Applied geography (Sevenoaks, England) · 2017Article
- Population Well-Being Measures Help Explain Geographic Disparities In Life Expectancy At The County Level.Health affairs (Project Hope) · 2016Article
- Putting Families Into Place: Using Neighborhood-Effects Research and Activity Spaces to Understand Families.Journal of family theory & review · 2015Article
- How Does the Context of Reception Matter? The Role of Residential Enclaves in Maternal Smoking During Pregnancy Among Mexican-Origin Mothers.Maternal and child health journal · 2015Article
- Ten-Year Outcomes of First-Episode Psychoses in the MRC ÆSOP-10 Study.The Journal of nervous and mental disease · 2015Article
- Mortality in schizophrenia and other psychoses: a 10-year follow-up of the ӔSOP first-episode cohort.Schizophrenia bulletin · 2015Article
- Article
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Authors and funding
3 authors.
Funding
Abstract
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 neighboring 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 modeling results indicate that both theoretical perspectives provide valuable frameworks to guide the modeling of mortality variation in US counties. Our empirical findings support that mortality rate of a certain county is associated with the features of its neighbors beyond its own features. 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 neighboring 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 neighboring counties. Methodologically, spatial Durbin modeling 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.
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