Department of Mechanical Engineering, University of Colorado Boulder, 427 UCB, Boulder, CO 80309 USA.
Department of Geography and Division of Epidemiology, The Ohio State University, 1036 Derby Hall, 154 North Oval Mall, Columbus, OH 43210, USA.
Int J Environ Res Public Health. 2019 Mar 29;16(7):1133. doi: 10.3390/ijerph16071133.
Consensus is growing on the need to investigate the joint impact of neighborhood-level social factors and environmental hazards on respiratory health. This study used latent profile analysis (LPA) to empirically identify distinct neighborhood subtypes according to a clustering of social factors and environmental hazards, and to examine whether those subtypes are associated with lung function. The study included 182 low-income participants who were enrolled in the Colorado Home Energy Efficiency and Respiratory Health (CHEER) study during the years 2015⁻2017. Distinct neighborhood typologies were identified based on analyses of 632 census tracts in the Denver-Metro and Front Range area of Colorado; neighborhood characteristics used to identify typologies included green space, traffic-related air pollution, violent and property crime, racial/ethnic composition, and socioeconomic status (SES). Generalized estimating equations were used to examine the association between neighborhood typology and lung function. We found four distinct neighborhood typologies and provide evidence that these social and environmental aspects of neighborhoods cluster along lines of advantage/disadvantage. We provide suggestive evidence of a double jeopardy situation where low-income populations living in disadvantaged neighborhoods may have decreased lung function. Using LPA with social and environmental characteristics may help to identify meaningful neighborhood subtypes and inform research on the mechanisms by which neighborhoods influence health.
人们越来越认识到,有必要调查社区层面的社会因素和环境危害对呼吸系统健康的共同影响。本研究使用潜在剖面分析(LPA)根据社会因素和环境危害的聚类,实证地识别不同的社区亚型,并研究这些亚型是否与肺功能有关。该研究包括 2015 年至 2017 年期间参加科罗拉多州家庭能源效率和呼吸系统健康(CHEER)研究的 182 名低收入参与者。根据对科罗拉多州丹佛都会区和前岭地区的 632 个普查区的分析,确定了不同的社区类型;用于确定类型的社区特征包括绿地、与交通相关的空气污染、暴力和财产犯罪、种族/族裔构成和社会经济地位(SES)。使用广义估计方程来检验社区类型与肺功能之间的关系。我们发现了四种不同的社区类型,并提供了证据表明,这些社区的社会和环境方面沿着优势/劣势的路线聚集。我们提供了一些暗示性的证据,表明生活在弱势社区的低收入人群可能会出现肺功能下降的双重风险情况。使用具有社会和环境特征的 LPA 可能有助于识别有意义的社区亚型,并为研究社区影响健康的机制提供信息。