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The spatial dimensions of neighborhood effects
1Brown University, Spatial Structures in the Social Sciences, Maxcy Hall, 112 George Street, Box 1916, Providence, RI 02912, USA. Seth_Spielman@Brown.edu
Social Science & Medicine (1982)
|January 27, 2009
Summary
Understanding neighborhood health impacts requires better spatial modeling. This study shows that how we define "neighborhood" in statistical models significantly affects health outcome results, highlighting a gap in current methods.
Area of Science:
- Environmental health
- Spatial epidemiology
- Urban planning
Background:
- Growing interest in neighborhood contexts and public health.
- Applied research is limited by spatial concept operationalization.
- Existing methods for defining "neighborhood" and "built environment" in statistical models are inadequate.
Purpose of the Study:
- To argue for spatial concepts in statistical models to be based on individuals, place, and problem.
- To describe the sensitivity of neighborhood-health association estimates to spatial concept operationalization.
- To address the gap between understanding environment-health influences and spatial statistical modeling.
Main Methods:
- Simulation experiments to assess sensitivity of spatial concepts.
- Analysis of multiple scales to explore spatial dimensions.
- Evaluation of statistical model fit for discovering spatial relationships.
Main Results:
- Estimates of neighborhood-health associations are sensitive to spatial concept operationalization.
- Using model fit to "discover" spatial dimensions is problematic.
- A significant gap exists between environmental health understanding and spatial statistical modeling.
Conclusions:
- Spatial concepts in statistical models must be tailored to the specific study.
- Current spatial statistical modeling techniques need improvement for environmental health research.
- Closing the gap between spatial inquiry and modeling is crucial for effective neighborhood health research.
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