Künzli N, Tager I B
Institute of Social and Preventive Medicine University Basel, Switzerland.
Environ Health Perspect. 2000 Oct;108(10):915-8. doi: 10.1289/ehp.108-1240122.
There is need for the assessment of long-term effects of outdoor air pollution. In fact, a considerable part of the large amount of U.S. research money that has been dedicated to investigate effects of ambient particulate pollution should be invested to address long-term effects. Studies that follow the health status of large numbers of subjects across long periods of time (i.e., cohort studies) should be considered the key research approach to address these questions. However, these studies are time consuming and expensive. We propose efficient strategies to address these questions in less time. Apart from long-term continuation of the few ongoing air pollution cohort studies in the United States, data from large cohorts that were established decades ago may be efficiently used to assess cardiorespiratory effects and to target research on detection of the most susceptible subgroups in the population, which may be related to genetic, molecular, behavioral, societal, and/or environmental factors. This approach will be efficient only if the available air pollution monitoring data will be used to spatially model long-term outdoor pollution concentrations across a given country for each year with available pollution data. Such concentration maps will allow researchers to impute outdoor air pollution levels at any residential location, independent of the location of monitors. Exposure imputation may be based on residential location(s) of participants in long-standing cardiorespiratory cohort studies, which can be matched to pollutant levels using geographic information systems. As shown in European impact assessment studies, such maps may be derived relatively quickly.
有必要评估室外空气污染的长期影响。事实上,美国投入大量资金用于研究环境颗粒物污染影响的相当一部分资金,应转而用于研究长期影响。对大量受试者的健康状况进行长期跟踪的研究(即队列研究)应被视为解决这些问题的关键研究方法。然而,这些研究既耗时又昂贵。我们提出了在更短时间内解决这些问题的有效策略。除了长期延续美国正在进行的少数空气污染队列研究之外,几十年前建立的大型队列的数据可被有效用于评估心肺影响,并针对人群中最易受影响亚组的检测进行研究,这些亚组可能与遗传、分子、行为、社会和/或环境因素有关。只有当现有的空气污染监测数据用于对每年有可用污染数据的特定国家的长期室外污染浓度进行空间建模时,这种方法才会有效。这样的浓度图将使研究人员能够估算任何居住地点的室外空气污染水平,而不受监测器位置的限制。暴露估算可基于长期心肺队列研究参与者的居住地点,利用地理信息系统将其与污染物水平相匹配。如欧洲影响评估研究所表明的,这样的地图可以相对快速地得出。