Role of Air Pollution in Rheumatoid Arthritis Incidence and Exacerbation

描述（由申请人提供）：就空气污染而言，自身免疫性疾病几乎没有研究过。二氧化硅粉尘和吸烟作为RA事件的原因的证据表明，吸入颗粒或化学污染可能有助于RA的发病机制。这些危险因素引起RA的生物学机制-炎症，全身免疫效应和氧化应激-也与空气污染相关，为空气污染和RA之间的可能关联提供了生物学证据。风湿性症状的季节性波动进一步表明，空气污染可能有助于流行性RA的周期性恶化。我们建议调查环境空气污染作为RA发病率和恶化的贡献者，重点是颗粒物（PM2.5和PM10）的暴露。我们将在“边境空气质量战略”（BAQS）中追求我们的目标，在不列颠哥伦比亚省（BC）的格鲁吉亚空气盆地进行心血管疾病队列研究。这一队列是使用不列颠哥伦比亚省关联健康数据库中的登记记录进行枚举的，包括870 041名年龄在45-84岁之间的成年人，他们在1999年之前在该地区居住了五年。空气污染物暴露分配给每个主题的个人地理代码的居住地，使用空气污染监管监测网络和土地利用回归建模方法，其中包括城市内部的空间对比和时间变化。我们将在研究基线（1999年1月1日）随访高危受试者，通过检索住院和门诊数据中的ICD 9代码，确定随访期间（1999-2003）的RA结局。我们将使用巢式病例对照设计研究空气污染暴露对RA发病率的贡献-比较病例和匹配的风险对照之间RA发病前5年期间的平均暴露。我们将使用嵌套病例交叉设计研究空气污染暴露对RA加重事件的影响-将受试者在RA加重事件前一个月内的暴露与其在未发生RA加重的选定风险期内的暴露进行比较。病例交叉设计有效地调整了许多预计在研究期间不会改变的个人水平风险因素。RA发病率和恶化与污染物水平的关系将使用条件logistic回归进行估计，对于我们感兴趣的主要污染物- PM2.5和PM10。- 以及在队列中评估的其他空气污染物。 公共卫生相关性：使用已建立的BAQS队列，现有的健康记录和最先进的暴露模型将提供一种有效的方法来进行迄今为止关于空气污染对RA的潜在影响的第一项研究-这是一种新的假设，由于缺乏适合此目的的良好特征的大型研究人群，因此以前可能没有进行过研究。我们提出的RA研究将有助于更广泛地了解空气污染对潜在易感人群的影响。

DESCRIPTION (provided by applicant): Autoimmune diseases are virtually unstudied in terms of air pollution. Evidence for silica dust and smoking as causes of incident RA suggest that inhaled particulate or chemical pollution may contribute to RA pathogenesis. The purported biologic mechanisms by which these risk factors cause RA - inflammation, systemic immune effects, and oxidative stress - have also been correlated with air pollution, lending biologic plausibility to a possible association between air pollution and RA. Seasonal fluctuations in rheumatic symptoms further suggest that air pollution may contribute to periodic exacerbation of prevalent RA. We propose to investigate ambient air pollution as a contributor to RA incidence and exacerbation, with a focus on exposure to particulate matter (PM2.5 and PM10). We will pursue our aims within the "Border Air Quality Strategy" (BAQS) cohort study of cardiovascular diseases in the Georgia Air Basin of British Columbia (BC). This cohort was enumerated using registration records in the BC Linked Health Database, and includes 870,041 adults, ages 45-84, who had lived in the region for five years before 1999. Air pollutant exposures were assigned to each subject by their individual geographic code(s) of residence, using both air pollution regulatory monitoring networks and land-use regression modeling methods which incorporate both intraurban spatial contrasts and temporal variability. We will follow at-risk subjects at the study baseline (January 1, 1999) to identify RA outcomes during the follow-up period (1999-2003) through searches of ICD9 codes in inpatient and outpatient data. We will investigate the contribution of air pollution exposure on RA incidence using a nested case-control design - comparing average exposure during a 5-year period before RA incidence between cases and matched at-risk controls. We will investigate the contribution of air pollution exposure on RA exacerbation events using a nested case-crossover design - comparing a subject's exposure during a one- month period before the RA exacerbation event to their exposure during selected at-risk periods during which RA exacerbation did not occur. The case-crossover design effectively adjusts for many individual-level risk factors that are not expected to change during the study period. Associations of RA incidence and exacerbation with pollutant levels will be estimated using conditional logistic regression, for our primary pollutants of interest - PM2.5 and PM10. - as well as other air pollutants assessed within the cohort. PUBLIC HEALTH RELEVANCE: Use of the established BAQS cohort, existing health records, and state-of-the-art exposure modeling will provide an efficient means to conduct the first study to date on the potential effects of air pollution on RA - a novel hypothesis that presumably has not been studied previously due to lack of well-characterized, large study populations that are suitable for this purpose. Our proposed study of RA will contribute to a broader understanding of the effects of air pollution in a potentially susceptible population.