Neighborhood archetypes for population health research: Is there no place like home?

University of California, Los Angeles, USA
Health & Place (Impact Factor: 2.81). 11/2010; 17(1):289-299. DOI: 10.1016/j.healthplace.2010.11.002


This study presents a new, latent archetype approach for studying place in population health. Latent class analysis is used to show how the number, defining attributes, and change/stability of neighborhood archetypes can be characterized and tested for statistical significance. The approach is demonstrated using data on contextual determinants of health for US neighborhoods defined by census tracts in 1990 and 2000. Six archetypes (prevalence 13–20%) characterize the statistically significant combinations of contextual determinants of health from the social environment, built environment, commuting and migration patterns, and demographics and household composition of US neighborhoods. Longitudinal analyses based on the findings demonstrate notable stability (76.4% of neighborhoods categorized as the same archetype ten years later), with exceptions reflecting trends in (ex)urbanization, gentrification/downgrading, and racial/ethnic reconfiguration. The findings and approach is applicable to both research and practice (e.g. surveillance) and can be scaled up or down to study health and place in other geographical contexts or historical periods.

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    • "classes on a continuum) (Hagenaars and Halman, 1989). Compared to cluster analysis LCA is also computationally superior and allows a test of model fit (Hagenaars and Halman, 1989; Rapkin and Luke, 1993; Weden et al., 2010). "
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    ABSTRACT: This study used latent class analysis to classify adolescent home neighborhoods (n=344) according to built environment characteristics, and tested how adolescent physical activity, sedentary behavior, and screen time differ by neighborhood type/class. Four distinct neighborhood classes emerged: (1) low-density retail/transit, low walkability index (WI), further from recreation; (2) high-density retail/transit, high WI, closer to recreation; (3) moderate-high-density retail/transit, moderate WI, further from recreation; and (4) moderate-low-density retail/transit, low WI, closer to recreation. We found no difference in adolescent activity by neighborhood class. These results highlight the difficulty of disentangling the potential effects of the built environment on adolescent physical activity.
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    • "Geographers have long been concerned with defining neighbourhoods and places, and examples of techniques to define neighbourhoods abound in the academic literature [see, for example: 2, 3, 5-10]. Weden et al. [10], for example discuss the evolution and theoretical foundations, including links to public health issues, associated with neighbourhood classification, starting with the Chicago School. However, there are many approaches to defining zones, ranging from simple cases that are based on existing or historical neighbourhoods, school catchments zones, and communities, to more complex approaches including hierarchical clustering and scale-space approaches [see, for example, 11-13]. "
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    ABSTRACT: The purpose of the project was to delineate a series of contiguous neighbourhood-based "Data Zones" within the Region of Peel (Ontario) for the purpose of health data analysis and dissemination. Zones were to be built on Census Tracts (N = 205) and obey a series of requirements defined by the Region of Peel. This paper explores a method that combines statistical analysis with ground-truthing, consultation, and the use of a decision tree. Census Tract data for Peel were derived from the 2006 Canadian Census Master file. Following correlation analysis to reduce the data set, Principal Component Analysis was applied to the data set to reduce the complexity and derive an index. The Getis-Ord Gi*statistic was then applied to look for statistically significant clusters of like Census Tracts. A detailed decision tree for the amalgamation of remaining zones and ground-truthing with Peel staff verified the resulting zones. A total of 15 Data Zones that are similar with respect to socioeconomic and sociodemographic attributes and that met criteria defined by Peel were derived for the region. The approach used in this analysis, which was bolstered by a series of checks and balances throughout the process, gives statistical validity to the defined zones and resulted in a robust series of Data Zones for use by Peel Public Health. We conclude by offering insight into alternative uses of the methodology, and limitations.
    Full-text · Article · May 2011 · International Journal of Health Geographics
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