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医疗保健利用的差异:超级基金场址与邻近对照场址比较。

Disparities in Healthcare Utilization: Superfund Site vs. Neighboring Comparison Site.

机构信息

Division of Pulmonary, Allergy and Critical Care Medicine, School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA.

Division of Preventive Medicine, School of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA.

出版信息

Int J Environ Res Public Health. 2022 Jul 28;19(15):9271. doi: 10.3390/ijerph19159271.

Abstract

Inequities in pollution-attributable health disparities are similar in most urban areas throughout the United States, and appear to encompass racial and socio-demographic differences, thereby suggesting increased health risks for those living in these areas. Individuals residing in close proximity to Superfund sites, predominantly people of color, are increasingly stricken with lung diseases. The prevalence of chronic lung diseases, such as chronic obstructive pulmonary disease (COPD), asthma in children, and lower respiratory tract infections (LRTI), is significantly higher in the affected area compared to the neighboring control area, irrespective of smoking, socio-economic status, or demographics. We conducted a retrospective analysis using data collected from patients who obtained healthcare from the University of Alabama at Birmingham (UAB) Health System. The data were procured from the Enterprise Data Warehouse (UAB Informatics for Integrating Biology and the Bedside (i2b2)). We evaluated healthcare utilization and classification of disease (defined by ICD-10 codes) of patients residing in zip codes: affected (35207, 35217) and neighboring comparison (35214). The results of the analysis may provide evidence that can be used for risk mitigation strategies or outreach education campaign(s) for those who live in the affected area.

摘要

在美国的大多数城市地区,污染导致的健康差异不平等现象都很相似,而且似乎包含了种族和社会人口差异,这表明生活在这些地区的人面临着更高的健康风险。居住在超级基金场地附近的人,主要是有色人种,越来越多地患有肺部疾病。受影响地区的慢性肺部疾病(如慢性阻塞性肺疾病、儿童哮喘和下呼吸道感染)的患病率明显高于邻近的对照地区,无论吸烟、社会经济地位或人口统计学如何。我们使用从阿拉巴马大学伯明翰分校(UAB)医疗系统获得医疗服务的患者收集的数据进行了回顾性分析。这些数据来自企业数据仓库(UAB 用于整合生物学和床边信息学(i2b2))。我们评估了居住在邮政编码为:受影响(35207、35217)和邻近比较(35214)地区的患者的医疗保健利用率和疾病分类(由 ICD-10 代码定义)。分析结果可能为生活在受影响地区的人们提供可用于风险缓解策略或外展教育活动的证据。

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