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Investigation of Spatial Clusters of Chronic Cardiopulmonary Diseases in New York City

机译:纽约市慢性心肺疾病的空间簇调查

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We aim to identify localized spatial clusters for four common cardiopulmonary diseases: Asthma, chronic obstructive pulmonary disease (COPD), coronary heart disease (CHD), and stroke in New York City (NYC). We used the 500 Cities data from the Centers for Disease Control and Prevention, which provide prevalence estimates for chronic diseases, health behavioral and prevention measures at the census tract level for the 500 largest cities in the United States. Our analyses focused on NYC (n=2101 tracts) with additional sociodemographic data from the Census and pollution data from the Environmental Protection Agency. We first conducted a normal scan statistic (SatScan V9.5) using the crude prevalence with a weight adjustment based on the standard error of the prevalence. We also conducted a multivariate regression model using the four health outcomes as the dependent variables, with covariates being sociodemographic, unhealthy behavior and health care access, and pollution factors. Residuals from the model were used in SatScan for spatial cluster detection. Using the crude prevalence, we identified 3 and 2 high risk clusters for asthma and COPD, respectively. Using residuals, we found different cluster patterns. Comparisons of cluster locations and sizes showed a high residual risk cluster centered at 40.82N/73.96W with a 3.50-km radius (~ 100 tracts) in the west Harlem neighborhood for COPD, CHD, and stroke. The high residual cluster for asthma was centered at 40.64N/73.92W with an 11.54-km radius (n=1044 tracts), covering mostly Brooklyn and parts of Queens neighborhoods. The asthma cluster also overlapped with two small high risk clusters (<10 tracts) for COPD and stroke. Geographic variations of high and low risk clusters for chronic cardiopulmonary diseases exist in NYC even after adjusting for the usual suspected factors. The identified common clusters suggest intervention opportunities that may simultaneously benefit multiple chronic disease health outcomes.
机译:我们旨在确定四种常见的心肺疾病的局部空间簇:哮喘,慢性阻塞性肺疾病(COPD),冠心病(CHD)和纽约市(NYC)的中风。我们使用了疾病控制与预防中心的500个城市数据,该数据提供了美国500个最大城市在人口普查范围内对慢性病,健康行为和预防措施的普遍性估计。我们的分析重点是纽约市(n = 2101道),另外还有来自人口普查的社会人口统计学数据和来自环境保护局的污染数据。我们首先使用原始患病率进行了常规扫描统计(SatScan V9.5),并根据患病率的标准误差进行了权重调整。我们还使用四个健康结果作为因变量进行了多元回归模型,协变量是社会人口统计学,不良健康行为和卫生保健可及性以及污染因素。来自模型的残差在SatScan中用于空间聚类检测。使用粗略的患病率,我们分别确定了3个和2个哮喘和COPD高危人群。使用残差,我们发现了不同的聚类模式。比较星团的位置和大小,发现高残留风险星团的中心为40.82N / 73.96W,在哈林区西部的COPD,CHD和中风半径为3.50公里(约100道)。哮喘的高残留群集中在40.64N / 73.92W,半径为11.54公里(n = 1044道),主要覆盖布鲁克林和皇后区的部分地区。哮喘群也与COPD和中风的两个小型高风险群(<10道)重叠。即使在调整了通常的可疑因素之后,纽约市仍存在慢性心肺疾病高危和低危人群的地理变异。识别出的共同集群提示可能同时有益于多种慢性病健康结果的干预机会。

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