Department of Epidemiology, The George Washington University Milken Institute School of Public Health, Washington, DC, USA.
Department of Epidemiology, The George Washington University Milken Institute School of Public Health, Washington, DC, USA.
Health Place. 2022 Mar;74:102771. doi: 10.1016/j.healthplace.2022.102771. Epub 2022 Mar 2.
Current efforts to characterize movers and identify predictors of moving have been limited. We used the ARIC cohort to characterize non-movers, short-distance movers, and long-distance movers, and employed best subset algorithms to identify important predictors of moving, including interactions between characteristics. Short- and long-distance movers were notably different from non-movers, and important predictors of moving differed based on the distance of the residential move. Importantly, systematic inclusion of interaction terms enhanced model fit and was substantively meaningful. This work has important implications for epidemiologic studies of contextual exposures and those treating residential mobility as an exposure.
目前，对迁居者进行特征描述和识别迁居预测因素的工作受到限制。我们使用 ARIC 队列对非迁居者、短距离迁居者和长距离迁居者进行了特征描述，并采用最佳子集算法确定了迁居的重要预测因素，包括特征之间的相互作用。短距离迁居者和长距离迁居者与非迁居者有显著差异，迁居距离不同，迁居的重要预测因素也不同。重要的是，系统地纳入交互项可以提高模型拟合度，并具有实质性意义。这项工作对环境暴露的流行病学研究以及将居住流动性作为暴露因素的研究具有重要意义。
