, Volume 51, Issue 3, pp 811–834 | Cite as

Integrating Space With Place in Health Research: A Multilevel Spatial Investigation Using Child Mortality in 1880 Newark, New Jersey

  • Hongwei XuEmail author
  • John R. Logan
  • Susan E. Short


Research on neighborhoods and health increasingly acknowledges the need to conceptualize, measure, and model spatial features of social and physical environments. When ignoring underlying spatial dynamics, we run the risk of biased statistical inference and misleading results. In this article, we propose an integrated multilevel spatial approach for Poisson models of discrete responses. In an empirical example of child mortality in 1880 Newark, New Jersey, we compare this multilevel spatial approach with the more typical aspatial multilevel approach. Results indicate that spatially defined egocentric neighborhoods, or distance-based measures, outperform administrative areal units, such as census units. In addition, although results do not vary by specific definitions of egocentric neighborhoods, they are sensitive to geographic scale and modeling strategy. Overall, our findings confirm that adopting a spatial multilevel approach enhances our ability to disentangle the effect of space from that of place, pointing to the need for more careful spatial thinking in population research on neighborhoods and health.


Spatial Multilevel Egocentric neighborhood Child mortality Neighborhood effects 



The authors thank the research initiative on Spatial Structures in the Social Sciences at Brown University for providing the historical GIS data used in this study. The historical GIS data collection used in this work was supported by the National Science Foundation (Grant No. 0647584) and the National Institutes of Health (Grant No. 1R01HD049493–01A2). The authors gratefully acknowledge research support from the Population Studies and Training Center at Brown University, which receives core support from the NICHD (5R24HD041020, 5T32HD007338). The authors also thank Margot Jackson and participants at the 2011 annual meeting of the Population Association of America for helpful comments on an early draft of this article.


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Copyright information

© Population Association of America 2014

Authors and Affiliations

  1. 1.Institute for Social ResearchUniversity of MichiganAnn ArborUSA
  2. 2.Department of SociologyBrown UniversityProvidenceUSA

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