RAND Corporation, CA, USA.
Health Place. 2011 Jan;17(1):289-99. doi: 10.1016/j.healthplace.2010.11.002. Epub 2010 Nov 12.
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.
本研究提出了一种新的、潜在的原型方法来研究人口健康中的位置。潜在类别分析用于展示如何描述和检验邻里原型的数量、定义属性以及变化/稳定性,并具有统计学意义。该方法使用了 1990 年和 2000 年美国按人口普查区定义的邻里的健康决定因素的上下文数据进行演示。六个原型(流行率为 13-20%)描述了来自社会环境、建筑环境、通勤和迁移模式以及人口统计和家庭构成的美国邻里健康决定因素的统计学显著组合。基于研究结果的纵向分析表明存在显著的稳定性(十年后仍属于同一原型的邻里比例为 76.4%),但也存在例外情况,反映了(前)城市化、高档化/降级以及种族/族裔重新配置的趋势。该发现和方法适用于研究和实践(例如监测),可以扩展或缩小规模以研究其他地理背景或历史时期的健康和位置。