Abstract
The rural paradox refers to the phenomenon that the standardized mortality rates are lower in rural than in urban areas despite the relatively poor socioeconomic profiles among rural residents. Previous research on the geographic mortality differential has failed to recognize the complexity of the concept of rurality and the spatial structure underlying the ecological mortality data has not been fully utilized to advance our understanding of the rural paradox. Drawing from the drift and breeder hypotheses, this study first uses county-level data to measure “rural” with three distinct aspects, namely ecological dimension, economic integration, and natural resources dependency. Then, it employs the spatial Durbin approach to capture the exogenous relationships between the mortality of a county and the features of its neighbors. The key findings include that (1) the drift hypothesis (i.e., internal migration) did not appear to explain the rural paradox, but the breeder hypothesis (i.e., exposures to environments) partially accounts for the rural-urban mortality disparity, (2) the associations between the ecological dimension and economic integration with mortality were explained after accounting for the exogenous relationships, (3) the observed spatial feedback effects reflected the spatial dynamics across county boundaries, and (4) the spatial dynamic processes between mortality and its determinants were largely confined to the first- and second-order neighbors. The results of this study indicate that future ecological mortality research should further utilize the spatial structure to explain the variation of mortality across space.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Brown and Schafft (2011) discussed how rural residents are affected by the change in rural economies, institutions, and environment. The rurality measures of this study largely align with their perspective, but their organizational aspect of rurality is not considered in the analysis due to data limitations.
- 2.
Benzene-equivalents indicate the amounts of benzene that would have to be released into the air to pose the same level of health risk as the release of other chemicals. It is a useful measure to compare different carcinogenic toxic releases and their risks to benzene. The list of carcinogen chemicals could be found in the website below: http://www2.epa.gov/sites/production/files/documents/OSHA_carcinogen_table_2011.pdf
References
Abraido-Lanza, A. F., Dohrenwend, B. P., Ng-Mak, D. S., & Turner, J. B. (1999). The Latino mortality paradox: A test of the “salmon bias” and healthy migrant hypotheses. American Journal of Public Health, 89(10), 1543–1548.
Anselin, L. (1988). Spatial econometrics: Methods and models. Dordrecht: Kluwer Academic Publishers.
Autant-Bernard, C., & LeSage, J. P. (2011). Quantifying knowledge spillovers using spatial econometric models. Journal of Regional Science, 51(3), 471–496.
Bealer, R. C., Willits, F. K., & Kuvlesky, W. P. (1965). The meaning of rurality in American society: Some implications of alternative definitions. Rural Sociology, 30(3), 255–266.
Bouchard, C., Blair, S. N., & Haskell, W. L. (2012). Physical activity and health. Champaign: Human Kinetics Publishers.
Brown, D. L., & Schafft, K. A. (2011). Rural people and communities in the 21st century: Resilience and transformation. Malden: Polity Press.
Burnham, K. P., & Anderson, D. R. (2002). Model selection and multi-model inference: A practical information-theoretic approach. New York: Springer.
Cho, S., Kim, J., Roberts, R., & Kim, S. (2012). Neighborhood spillover effects between rezoning and housing price. The Annals of Regional Science, 48(1), 1–19.
Clifford, W. B., & Brannon, Y. S. (1985). Rural-urban differentials in mortality. Rural Sociology, 50(2), 210–224.
Clifford, W. B., Miller, M. K., & Stokes, C. S. (1986). Rural-urban differences in mortality in the United States, 1970–1980. In New dimensions in rural policy. Building upon Our heritage. Washington, DC: GPO.
Dietz Roux, D. (2002). The estimation of neighborhood effects in the social sciences: An interdisciplinary approach. Social Science Research, 31(4), 539–575.
Elhorst, J. P. (2010). Applied spatial econometrics: Raising the bar. Spatial Economic Analysis, 5(1), 9–28.
Firebaugh, G., & Schroeder, M. B. (2009). Does your neighbor’s income affect your happiness? American Journal of Sociology, 115(3), 805–831.
Fotheringham, A. S., & Wong, D. (1991). The modifiable areal unit problem in multivariate statistical analysis. Environment and Planning A, 23(7), 1025–1044.
Ginther, D., Haveman, R., & Wolfe, B. (2000). Neighborhood attributes as determinants of children’s outcomes: How robust are the relationships? Journal of Human Resources, 35(4), 603–642.
Haining, R. (2003). Spatial data analysis: Theory and practice. Cambridge: Cambridge University Press.
Hoyert, D. L. (2012). 75 years of mortality in the United States, 1935–2010. NCHS data brief (Vol. 88). Hyattsville: National Center for Health Statistics.
James, W. L., Cossman, R. E., Cossman, J. S., Campbell, C., & Blanchard, T. (2004). A brief visual primer for the mapping of mortality trend data. International Journal of Health Geographics, 3(7), 1–17.
Jensen, C. D., Lacombe, D. J., & McIntyre, S. G. (2012). A Bayesian spatial econometric analysis of the 2010 UK General Election. Papers in regional science, DOI: 10.1111/j.1435-5957.2012.00415.x.
Kawachi, I., & Kennedy, B. P. (1997). The relationship of income inequality to mortality: Does the choice of indicator matter? Social Science & Medicine, 45(7), 1121–1127.
Kawachi, I., & Kennedy, B. P. (1999). Income inequality and health: Pathways and mechanisms. Health Services Research, 34(1 Pt 2), 215–227.
Kawachi, I., Kennedy, B. P., & Wilkinson, R. G. (1999). Income inequality and health (Vol. 506). New York: The New Press.
Kawachi, I., Subramanian, S. V., & Kim, D. (2008). Social capital and health: A decade of progress and beyond. In I. Kawachi, S. V. Subramanian, & D. Kim (Eds.), Social capital and health (pp. 1–26). New York: Springer.
LeSage, J. P., & Pace, R. K. (2009). Introduction to spatial econometrics (Vol. 196). Boca Raton: Chapman & Hall/CRC.
Link, B. G., & Phelan, J. (1995). Social conditions as fundamental causes of disease. Journal of Health and Social Behavior, 35, 80–94.
Manski, C. F. (1993). Identification of endogenous social effects: The reflection problem. The Review of Economic Studies, 60(3), 531–542.
Matthews, S. A. (2011). Spatial polygamy and the heterogeneity of place: Studying people and place via egocentric methods. In L. M. Burton, S. P. Kemp, M. Leung, S. A. Matthews, & D. T. Takeuchi (Eds.), Communities, neighborhoods, and health: Expanding the boundaries of place (pp. 35–55). New York: Springer.
McLaughlin, D. K., & Stokes, C. S. (2002). Income inequality and mortality in US counties: Does minority racial concentration matter? American Journal of Public Health, 92(1), 99–104.
McLaughlin, D. K., Stokes, C. S., & Nonoyama, A. (2001). Residence and income inequality: Effects on mortality among US counties. Rural Sociology, 66(4), 579–598.
McLaughlin, D. K., Stokes, C. S., Smith, P. J., & Nonoyama, A. (2007). Differential mortality across the U.S.: The influence of place-based inequality. In L. M. Lobao, G. Hooks, & A. R. Tickamyer (Eds.), The sociology of spatial inequality (pp. 141–162). Albany: SUNY Press.
Miller, M. K., & Luloff, A. E. (1981). Who is rural? A typological approach to the examination of rurality. Rural Sociology, 46(4), 608–625.
Miller, M. K., Stokes, C. S., & Clifford, W. B. (1987). A comparison of the rural-urban mortality differentials for deaths from all causes, cardiovascular disease and cancer. Journal of Rural Health, 3(2), 23–34.
Morton, L. W. (2004). Spatial patterns of rural mortality. In N. Glasgow, L. W. Morton, & N. E. Johnson (Eds.), Critical issues in rural health (pp. 37–48). Ames: Blackwell Publishing Professional.
Mujahid, M. S., & Diez Roux, A. V. (2010). Neighborhood factors in health. In A. Steptoe (Ed.), Handbook of behavioral medicine (pp. 341–354). New York: Springer.
NCHS. (2011). Compressed mortality file, 1999–2008 (Machine readable data file and documentation, CD-ROM series 20, No.2N). Hyattsville: National Center for Health Statistics.
Openshaw, S. (1983). The modifiable areal unit problem (Vol. 38). Norwich: Geo books.
Porter, J. R., & Howell, F. M. (2012). Geographical sociology: Theoretical foundations and methodological applications in the sociology of location. New York: Springer.
Preston, S., Heuveline, P., & Guillot, M. (2001). Demography: Measuring and modeling population processes. Malden: Blackwell Publishers Inc.
Putnam, R. D. (2001). Bowling alone: The collapse and revival of American community. New York: Simon and Schuster.
Rupasingha, A., & Goetz, S. J. (2008). US county-level social capital data, 1990–2005. Accessed 17 Aug 2011.
Rupasingha, A., Goetz, S. J., & Freshwater, D. (2006). The production of social capital in US counties. Journal of Socio-Economics, 35(1), 83–101.
Sampson, R. J., Raudenbush, S. W., & Earls, F. (1997). Neighborhoods and violent crime: A multilevel study of collective efficacy. Science, 277(5328), 918–924.
Shoff, C., & Yang, T. C. (2013). Understanding maternal smoking during pregnancy: Does residential context matter? Social Science & Medicine, 78, 50–60.
Song, L., Son, J., & Lin, N. (2010). Social capital and health. In W. C. Cockerham (Ed.), The New Blackwell companion to medical sociology (pp. 184–210). Malden: Blackwell.
Sparks, P. J., & Sparks, C. S. (2010). An application of spatially autoregressive models to the study of US county mortality rates. Population, Space and Place, 16(6), 465–481.
Sparks, P. J., Sparks, C. S., & Campbell, J. J. A. (2013). An application of Bayesian spatial statistical methods to the study of racial and poverty segregation and infant mortality rates in the US. Geojournal, 78, 389–405.
Verheij, R. A. (1996). Explaining urban-rural variations in health: A review of interactions between individual and environment. Social Science & Medicine, 42(6), 923–935.
Voss, P. R. (2007). Demography as a spatial social science. Population Research and Policy Review, 26(5), 457.
Willits, F. K., Bealer, R. C., & Timbers, V. L. (1990). Popular images of ‘rurality’: Data from a Pennsylvania survey. Rural Sociology, 55(4), 559–578.
Wilmoth, J. M. (2010). Health trajectories among older movers. Journal of Aging and Health, 22(7), 862–881.
Yang, T. C., Chen, Y. J., Shoff, C., & Matthews, S. A. (2012). Using quantile regression to examine the effects of inequality across the mortality distribution in the US. Social Science & Medicine, 74(12), 1900–1910.
Yang, T. C., Jensen, L., & Haran, M. (2011). Social capital and human mortality: Explaining the rural paradox with county-level mortality data. Rural Sociology, 76(3), 347–374.
Yang, T. C., Noah, A. J., & Shoff, C. (2015). Exploring geographic variation in US mortality rates using a spatial Durbin approach. Population, Space and Place, 21(1), 18–37.
Acknowledgements
This study received support from the Geographic Information Analysis Core at Penn State’s Population Research Institute, which receives core funding from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD; R24-HD41025). We also acknowledge the help from Family Demography Training (T-32HD007514) from NICHD.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Yang, TC., Noah, A.J., Shoff, C. (2016). Revisiting the Rural Paradox in US Counties with Spatial Durbin Modeling. In: Howell, F., Porter, J., Matthews, S. (eds) Recapturing Space: New Middle-Range Theory in Spatial Demography. Spatial Demography Book Series, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-319-22810-5_13
Download citation
DOI: https://doi.org/10.1007/978-3-319-22810-5_13
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-22809-9
Online ISBN: 978-3-319-22810-5
eBook Packages: Social SciencesSocial Sciences (R0)