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Impact of Residential Mobility on Exposure Assessment in Longitudinal Air Pollution Studies: A Sensitivity Analysis within the ESCAPE Project

机译:纵向空气污染研究中居民流动性对暴露评估的影响:ESCAPE项目内的敏感性分析

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摘要

Exposure misclassification in longitudinal studies of air pollution exposure and health effects can occur due to residential mobility in a study population over followup. The aim of this study was to investigate to what extent residential mobility during followup can be expected to cause exposure misclassification in such studies, where exposure at the baseline address is used as the main exposure assessment. The addresses for each participant in a large population-based study (N > 25,000) were obtained via national registers. We used a Land Use Regression model to estimate the NOx concentration for each participant's all addresses during the entire follow-up period (in average 14.6 years) and calculated an average concentration during followup. The Land Use Regression model explained 83% of the variation in measured levels. In summary, the NOx concentration at the inclusion address was similar to the average concentration over followup with a correlation coefficient of 0.80, indicating that air pollution concentration at study inclusion address could be used as indicator of average air pollution concentrations over followup. The differences between an individual's inclusion and average follow-up mean concentration were small and seemed to be nondifferential with respect to a large range of factors and disease statuses, implying that bias due to residential mobility was small.
机译:在空气污染暴露和健康影响的纵向研究中,暴露的分类错误可能是由于研究人群在随访期间的居住流动性所致。这项研究的目的是调查在此类研究中预期在随访期间的居住者流动会导致暴露分类错误的程度,其中基线地址的暴露被用作主要暴露评估。一项大型人群研究(N> 25,000)中每个参与者的地址都是通过国家注册簿获得的。我们使用土地利用回归模型来估算整个随访期内(平均14.6年)每个参与者所有地址的NOx浓度,并计算出随访期间的平均浓度。土地利用回归模型解释了测量水平的83%的变化。总之,纳入地址处的NOx浓度与随访期间的平均浓度相似,相关系数为0.80,表明研究纳入地址处的空气污染浓度可以用作随访期间平均空气污染浓度的指标。个体的纳入与平均随访平均浓度之间的差异很小,并且在各种因素和疾病状态方面似乎没有差异,这表明因居住地流动性造成的偏见很小。

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