Cozier Yvette C
Am J Epidemiol. 2017 Jun 1;185(11):1203-1205. doi: 10.1093/aje/kwx085.
In public health, it has long been observed that "place"-specifically, where one lives-affects individual health, with the main research question distinguishing between the effects of "context" (defined as area characteristics) and "composition" (the characteristics of inhabitants) on health outcomes. There have been many studies in which the spatial patterning of disease has been explored, but they were often ecological in design, used broad census geographic levels, lacked individual-level data, or when available, did not simultaneously analyze community- and individual-level risk factors using appropriate modeling techniques. The paper by Diez-Roux et al. (Am J Epidemiol. 1997;146(1):48-63) represents an important expansion of the literature in terms of analytic methods used and level of geography studied. The authors demonstrated that both neighborhood- and individual-level measures of socioeconomic status work together to play an important role in shaping disease risk. Analyses incorporating both levels of data have the potential to provide epidemiologists with a deeper understanding of the divergent pathways via which neighborhood affects health.
在公共卫生领域,长期以来人们观察到,“地点”——具体而言,一个人的居住地点——会影响个人健康,主要研究问题在于区分“环境”(定义为区域特征)和“构成”(居民特征)对健康结果的影响。已有许多研究探讨了疾病的空间模式,但这些研究在设计上往往属于生态学研究,采用宽泛的人口普查地理层面,缺乏个体层面的数据,或者即便有个体层面的数据,也未使用适当的建模技术同时分析社区层面和个体层面的风险因素。迪埃斯 - 鲁克斯等人发表于《美国流行病学杂志》1997年第146卷第1期第48 - 63页的论文,在所用分析方法和研究的地理层面方面,是该领域文献的一项重要拓展。作者证明,邻里层面和个体层面的社会经济地位衡量指标共同作用,在塑造疾病风险方面发挥着重要作用。纳入这两个层面数据的分析,有可能让流行病学家更深入地理解邻里影响健康的不同途径。