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首页> 外文期刊>International Journal of Environmental Research and Public Health >Spatial Clustering and Local Risk Factors of Chronic Obstructive Pulmonary Disease (COPD)
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Spatial Clustering and Local Risk Factors of Chronic Obstructive Pulmonary Disease (COPD)

机译：慢性阻塞性肺疾病（COPD）的空间聚集和局部危险因素

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Chronic obstructive pulmonary disease (COPD) mortality has been steadily increasing in Taiwan since 2009. In order to understand where the hotspot areas are and what the local risk factors are, we integrated an ecological and a case-control study. We used a two-stage approach to identify hotspots and explore the possible risk factors for developing COPD. The first stage used the annual township COPD mortality from 2000 to 2012 and applied the retrospective space-time scan statistic to calculate the local relative risks in each township. In the second stage, we conducted a case-control study, recruiting 200 patients from one local hospital within the one identified hotspot area located in southern Taiwan. Logistic regression was applied for analyzing the personal risk factors of COPD. The univariate analyses showed that higher percentages of aborigines, patients with tuberculosis (TB) history, and those with smoking history had COPD (p < 0.05). After controlling for demographic variables, aboriginal status (adjusted odds ratios (AORs): 3.01, 95% CI: 1.52–5.93) and smoking history (AORs: 2.64, 95% CI: 1.46–4.76) were still the two significant risk factors. This two-stage approach might be beneficial to examine and cross-validate the findings from an aggregate to an individual scale, and can be easily extended to other chronic diseases.
机译：自2009年以来，台湾的慢性阻塞性肺疾病（COPD）死亡率一直在稳步上升。为了了解热点地区在哪里以及当地的危险因素是什么，我们整合了生态学和病例对照研究。我们使用了两个阶段的方法来确定热点并探讨发展COPD的可能危险因素。第一阶段使用2000年至2012年的城镇年度COPD死亡率，并应用回顾性时空扫描统计数据来计算每个城镇的当地相对风险。在第二阶段，我们进行了病例对照研究，从位于台湾南部一个已确定的热点地区的一家当地医院招募了200名患者。应用逻辑回归分析COPD的个人危险因素。单因素分析显示，原住民，患有结核病（TB）病史和有吸烟史的人中有较高百分比的人患有COPD（p <0.05）。在控制了人口统计学变量后，原住民状态（调整后的优势比（AOR）：3.01，95％CI：1.52-5.93）和吸烟史（AOR：2.64、95％CI：1.46-4.76）仍然是两者重大危险因素。这种分为两个阶段的方法可能有益于从汇总到单个范围检查和交叉验证发现，并且可以轻松地扩展到其他慢性疾病。

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