Cerdá Magdalena, Tracy Melissa, Ahern Jennifer, Galea Sandro
Magdalena Cerdá, Melissa Tracy, and Sandro Galea are with the Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY. Jennifer Ahern is with the Department of Epidemiology, University of California, Berkeley.
Am J Public Health. 2014 Sep;104 Suppl 4(Suppl 4):S609-19. doi: 10.2105/AJPH.2014.302055.
As a case study of the impact of universal versus targeted interventions on population health and health inequalities, we used simulations to examine (1) whether universal or targeted manipulations of collective efficacy better reduced population-level rates and racial/ethnic inequalities in violent victimization; and (2) whether experiments reduced disparities without addressing fundamental causes.
We applied agent-based simulation techniques to the specific example of an intervention on neighborhood collective efficacy to reduce population-level rates and racial/ethnic inequalities in violent victimization. The agent population consisted of 4000 individuals aged 18 years and older with sociodemographic characteristics assigned to match distributions of the adult population in New York City according to the 2000 U.S. Census.
Universal experiments reduced rates of victimization more than targeted experiments. However, neither experiment reduced inequalities. To reduce inequalities, it was necessary to eliminate racial/ethnic residential segregation.
These simulations support the use of universal intervention but suggest that it is not possible to address inequalities in health without first addressing fundamental causes.
作为关于普遍干预与针对性干预对人群健康及健康不平等影响的案例研究,我们通过模拟来检验:(1)对集体效能进行普遍干预还是针对性干预能更好地降低人群层面暴力受害率及种族/民族不平等现象;(2)实验在未解决根本原因的情况下是否减少了差异。
我们将基于主体的模拟技术应用于邻里集体效能干预的具体实例,以降低人群层面暴力受害率及种族/民族不平等现象。主体人群由4000名18岁及以上个体组成,其社会人口学特征根据2000年美国人口普查分配,以匹配纽约市成年人口分布。
普遍干预实验比针对性干预实验更能降低受害率。然而,两种实验均未减少不平等现象。要减少不平等,必须消除种族/民族居住隔离。
这些模拟支持采用普遍干预,但表明若不首先解决根本原因,就不可能解决健康方面的不平等问题。