Abstract
Neighborhood context is recognized as an important predictor of individual-level behaviors and health outcomes (Pickett and Pearl 2001; Lee and Cubbin 2002; Sampson 2003). Neighborhoods, however, are difficult to define both in theory and in practice, and are often drawn to follow existing administrative boundaries or sampling schemes, or must be set arbitrarily due to a lack of sufficient data. Given the role of neighborhood context in influencing health outcomes, it is crucial that the area of influence surrounding the unit of analysis (be it a person, household, etc.) be properly defined. As already discussed in previous chapters, if we do not identify neighborhoods correctly, we cannot properly evaluate neighborhood effects. Defining neighborhoods is a challenge across the social sciences; investigations of the role of neighborhood context in decision making and shaping of individual-level outcomes are seen in public health, geography, demography, and sociology with no consistent approach to identifying and evaluating neighborhood effects. In this chapter, we outline several types of neighborhood definitions from the literature, and then, using data from the Women’s Health Study of Accra, implement a spatial model together with a simulation approach to examine how two alternative neighborhood definitions affect modeling of individual-level health outcomes.
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References
Aldstadt, J., & Getis, A. (2006). Using AMOEBA to create a spatial weights matrix and identify spatial clusters. Geographical Analysis, 38(4), 327–343. Last accessed 6 Mar 2012.
An, L., & Brown, D. G. (2008). Survival analysis in land change science: Integrating with GIScience to address temporal complexities. Annals of the Association of American Geographers, 98(2), 323–344.
An, L., Linderman, M., Qi, J., Shortridge, A., et al. (2005). Exploring complexity in a human environment system: An agent-based spatial model for multidisciplinary and multiscale integration. Annals of the Association of American Geographers, 95(1), 54–79.
An, L., He, G., Liang, Z., & Liu, J. (2006). Impacts of demographic and socioeconomic factors on spatio-temporal dynamics of panda habitat. Biodiversity and Conservation, 15(8), 2343–2363. Last accessed 15 May 2010.
Anselin, L., & Lozano-Garcia, N. (2009). Spatial hedonic models. In T. C. Mills & K. D. Patterson (Eds.), Palgrave handbook of econometrics. Basingstoke/New York: Palgrave Macmillan. Last accessed 20 Jan 2012.
Anselin, L., & Rey, S. (1991). Properties of tests for spatial dependence in linear regression models. Geographical Analysis, 23(2), 112–131. Last accessed 30 Mar 2012.
Axtell, R. L., et al. (2002). Population growth and collapse in a multiagent model of the Kayenta Anasazi in Long House Valley. Proceedings of the National Academy of Sciences, 99(90003), 7275–7279.
Bivand, R. (2012). spdep: Spatial dependence: Weighting schemes, statistics and models. http://CRAN.R-project.org/package=spdep
Brown, D. G., Pijanowski, B. C., & Duh, J. D. (2000). Modeling the relationships between land use and land cover on private lands in the Upper Midwest, USA. Journal of Environmental Management, 59, 247–263.
Corrado, L., & Fingleton, B. (2011). Multilevel modelling with spatial effects. University of Strathclyde Business School, Department of Economics. http://ideas.repec.org/p/str/wpaper/1105.html
Douptcheva, N., Hill, A. G., Adanu, R. M. K., Anarfi, J., Blanchard, K., Fink, G., et al. (2011). Final report on the women’s health study of Accra, Wave II. Accra: Institute for Statistical, Social and Economic Research, University of Ghana, Legon.
Engstrom, R., Ashcroft, E., Jewell, H., & Rain, D. (2011). Using remotely sensed data to map variability in health and wealth indicators in Accra, Ghana. In Urban Remote Sensing Event (JURSE), 2011 Joint (pp. 145–148), Munich.
Epstein, J. M. (1999). Agent-based computational models and generative social science. Complexity, 4(5), 41–60. Last accessed 16 Sept 2010.
Getis, A. (2009). Spatial autocorrelation. In M. M. Fischer & A. Getis (Eds.), Handbook of applied spatial analysis: Software tools, methods and applications (pp. 255–278). Berlin: Springer.
Grimm, V., et al. (2005). Pattern-oriented modeling of agent-based complex systems: Lessons from ecology. Science, 310(5750), 987–991.
Hays, R. D., et al. (1993). The RAND 36-item health survey 1.0. Health Economics, Health Economics. 2(3), 217–227. Last accessed 16 Apr 2012.
Hill, A. G., et al. (2007). Health of urban Ghanaian women as identified by the Women’s Health Study of Accra. International Journal of Gynecology & Obstetrics, 99(2), 150–156. Last accessed 3 Apr 2012.
Lambin, E. F., et al. (2001). The causes of land-use and land-cover change: Moving beyond the myths. Global Environmental Change, 11(4), 261–269. Last accessed 28 Jan 2010.
Lee, R. E., & Cubbin, C. (2002). Neighborhood context and youth cardiovascular health behaviors. American Journal of Public Health, 92(3), 428–436. Last accessed 3 May 2012.
Lee, B. A., et al. (2008). Beyond the census tract: Patterns and determinants of racial segregation at multiple geographic scales. American Sociological Review, 73(5), 766.
LeSage, J. P., & Pace, R. K. (2009). Spatial econometric models. In M. M. Fische & A. Getis (Eds.), Handbook of applied spatial analysis: Software tools, methods and applications (pp. 255–278). Berlin: Springer.
Millington, J., Perry, G., & Romero-Calcerrada, R. (2007). Regression techniques for examining land use/cover change: A case study of a Mediterranean landscape. Ecosystems, 10(4), 562–578.
Parker, D. C., Manson, S. M., Janssen, M. A., Hoffmann, M. J., et al. (2003). Multi-agent systems for the simulation of land-use and land-cover change: A review. Annals of the Association of American Geographers, 93(2), 314–337. Last accessed 27 Jan 2010.
Petit, C., Scudder, T., & Lambin, E. F. (2001). Quantifying processes of land-cover change by remote sensing: Resettlement and rapid-cover changes in south-eastern Zambia. International Journal of Remote Sensing, 22(17), 3435–3456.
Pickett, K. E., & Pearl, M. (2001). Multilevel analyses of neighbourhood socioeconomic context and health outcomes: A critical review. Journal of Epidemiology and Community Health, 55(2), 111–122.
R Development Core Team. (2012). R: A language and environment for statistical computing. Vienna, Austria. http://www.R-project.org/
Reardon, S. F., et al. (2008). The geographic scale of metropolitan racial segregation. Demography, 45(3), 489–514.
Sampson, R. J. (2003). The neighborhood context of well-being. Perspectives in Biology and Medicine, 46(3 Suppl), S53–S64. Last accessed 3 May 2012.
Stoler, J., et al. (2012). Assessing the utility of satellite imagery with differing spatial resolutions for deriving proxy measures of slum presence in Accra, Ghana. GIScience and Remote Sensing, 49(1), 31–52. Last accessed 3 May 2012.
Subramanian, S. V. (2010). Multilevel modeling. In M. M. Fischer & A. Getis (Eds.), Handbook of applied spatial analysis (pp. 507–525). Berlin/Heidelberg: Springer. http://dx.doi.org/10.1007/978-3-642-03647-7_24
Ware, J. E., Kosinski, M., & Keller, S. D. (1994). SF-36 physical and mental health summary scales: A users manual. Boston: The Health Institute, New England Medical Center.
Weeks, J. R., Hill, A. G., Stow, D., Getis, A., & Fugate, D. (2007). Can we spot a neighborhood from the air? Defining neighborhood structure in Accra, Ghana. GeoJournal, 69(1), 9–22.
Weeks, J. R., Getis, A., Hill, A. G., Agyei-Mensah, S., & Rain, D. (2010). Neighborhoods and fertility in Accra, Ghana: An AMOEBA-based approach. Annals of the Association of American Geographers, 100(3), 558–578.
Weeks, J. R., et al. (2012). Connecting the dots between health, poverty and place in Accra, Ghana. Annals of the Association of American Geographers. Last accessed 8 June 2012.
Yabiku, S. (2006). Land use and marriage timing in Nepal. Population and Environment, 27(5), 445–461.
Acknowledgements
This research was funded in part by grant number R01 HD054906 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (``Health, Poverty and Place in Accra, Ghana,'' John R. Weeks, Project Director/Principal Investigator). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Child Health and Human Development or the National Institutes of Health. Additional funding was provided by Hewlett/PRB (``Reproductive and Overall Health Outcomes and Their Economic Consequences for Households in Accra, Ghana,'' Allan G. Hill, Project Director/Principal Investigator). The 2003 Women's Health Study of Accra was funded by the World Health Organization, the US Agency for International Development, and the Fulbright New Century Scholars Award (Allan G. Hill, Principal Investigator).
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Zvoleff, A., An, L., Stoler, J., Weeks, J.R. (2013). What If Neighbors’ Neighborhoods Differ? The Influence of Neighborhood Definitions of Health Outcomes in Accra. In: Weeks, J., Hill, A., Stoler, J. (eds) Spatial Inequalities. GeoJournal Library, vol 110. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6732-4_8
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