Do D Phuong, Finch Brian Karl
Institute for Social Research, School of Public Health, University of Michigan, Ann Arbor, MI 48109-2029, USA.
Am J Epidemiol. 2008 Sep 15;168(6):611-9. doi: 10.1093/aje/kwn182. Epub 2008 Aug 6.
Cross-sectional studies of neighborhood context and health are subject to upward bias due to unobserved heterogeneity and to downward bias due to overadjustment for potential mediators in the pathway between neighborhood context and health. In this study, the authors employed two strategies that addressed these two sources of bias. First, to mitigate overadjustment of mediators, they adjusted for baseline characteristics observed just prior to the measurement of neighborhood context, using a combined propensity score and regression strategy. Second, to mitigate underadjustment of unmeasured confounders, they employed a fixed-effects modeling strategy to account for unobserved non-time-varying heterogeneity. Analyses were based on a nationally representative sample of the nonimmigrant US population from the Panel Study of Income Dynamics (1980-1997) in which respondent-rated health was regressed on neighborhood poverty. The samples consisted of approximately 6,000 respondents for the propensity score/regression models and 45,000 person-years for the fixed-effects models. Both modeling strategies yielded significant estimates of neighborhood poverty and supported a causal link between neighborhood context and health.
邻里环境与健康的横断面研究由于未观察到的异质性而存在向上偏差,并且由于对邻里环境与健康之间路径中的潜在中介因素过度调整而存在向下偏差。在本研究中,作者采用了两种策略来解决这两种偏差来源。首先,为了减轻中介因素的过度调整,他们使用倾向得分和回归相结合的策略,对在测量邻里环境之前观察到的基线特征进行调整。其次,为了减轻未测量混杂因素的调整不足,他们采用固定效应建模策略来考虑未观察到的非时变异质性。分析基于收入动态面板研究(1980 - 1997年)中具有全国代表性的美国非移民人口样本,其中将受访者自评健康状况对邻里贫困程度进行回归分析。倾向得分/回归模型的样本约有6000名受访者,固定效应模型的样本有45000人年。两种建模策略都得出了邻里贫困的显著估计值,并支持了邻里环境与健康之间的因果关系。