Ulirsch Gregory V, Ball Louise M, Kaye Wendy, Shy Carl M, Lee Carolyn V, Crawford-Brown Douglas, Symons Michael, Holloway Tracey
Division of Health Assessment and Consultation, Agency for Toxic Substances and Disease Registry, Public Health Service, Atlanta, GA 30345, USA.
J Expo Sci Environ Epidemiol. 2007 Aug;17(5):478-87. doi: 10.1038/sj.jes.7500542. Epub 2007 Feb 14.
Few, if any, published time series studies have evaluated the effects of particulate matter air exposures by combining hospital admissions with medical visit data for smaller populations. We investigated the relationship between daily particulate matter (<10 microm in aerometric diameter or PM10) exposures with admissions and medical visits (emergency room, urgent care, and family practice) for respiratory and cardiovascular disease in Pocatello and Chubbuck, Idaho (population about 60,000), from November 1994 through March 2000. Within generalized linear models, time, weather, influenza, and day-of-week effects were controlled. In single-pollutant models, respiratory disease admissions and visits increased (7.1-15.4% per 50 microg/m3 PM10) for each age group analyzed, with the highest increases in two groups, children and especially the elderly. Statistical analyses suggest that the results probably did not occur by chance. Sensitivity analyses did not provide strong evidence that the respiratory disease effect estimates were sensitive to reasonable changes in the final degrees of freedom choice for time and weather effects. No strong evidence of confounding by NO2 and SO2 was found from results of multi-pollutant models. Ozone and carbon monoxide data were not available to include multi-pollutant models, but evidence suggests that they were not a problem. Unexpectedly, evidence of an association between PM10 with cardiovascular disease was not found, possibly due to the lifestyles of the mostly Mormon study population. Successful time series analyses can be performed on smaller populations if diverse, centralized databases are available. Hospitals that offer urgent or other primary care services may be a rich source of data for researchers. Using data that potentially represented a wide-range of disease severity, the findings provide evidence that evaluating only hospital admissions or emergency room visit effects may underestimate the overall morbidity due to acute particulate matter exposures. Further work is planned to test this conclusion.
几乎没有已发表的时间序列研究通过将医院入院数据与较小人群的就诊数据相结合来评估颗粒物空气暴露的影响。我们调查了1994年11月至2000年3月期间，爱达荷州波卡特洛和丘巴克（人口约6万）每日颗粒物（空气动力学直径小于10微米或PM10）暴露与呼吸和心血管疾病的入院及就诊（急诊室、紧急护理和家庭医疗）之间的关系。在广义线性模型中，对时间、天气、流感和星期效应进行了控制。在单污染物模型中，每个分析的年龄组中，呼吸系统疾病的入院和就诊人数均有所增加（每50微克/立方米PM10增加7.1 - 15.4%），其中儿童组和尤其是老年组的增加幅度最大。统计分析表明，这些结果可能并非偶然发生。敏感性分析并未提供有力证据表明呼吸系统疾病效应估计值对时间和天气效应的最终自由度选择的合理变化敏感。多污染物模型的结果未发现二氧化氮和二氧化硫有强烈的混杂证据。由于没有臭氧和一氧化碳数据来纳入多污染物模型，但有证据表明它们不是问题所在。出乎意料的是，未发现PM10与心血管疾病之间存在关联的证据，这可能是由于研究人群主要是摩门教徒的生活方式所致。如果有多样化的集中数据库，就可以对较小人群进行成功的时间序列分析。提供紧急或其他初级护理服务的医院可能是研究人员丰富的数据来源。利用可能代表广泛疾病严重程度的数据，研究结果提供了证据，表明仅评估医院入院或急诊室就诊效应可能低估了急性颗粒物暴露导致的总体发病率。计划进一步开展工作来验证这一结论。
