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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