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本文引用的文献

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Neighborhood-level measures of socioeconomic status are more correlated with individual-level measures in urban areas compared with less urban areas.与非城市地区相比,城市地区邻里层面的社会经济地位指标与个体层面的指标相关性更高。
Ann Epidemiol. 2020 Mar;43:37-43.e4. doi: 10.1016/j.annepidem.2020.01.012. Epub 2020 Feb 11.
2
Safety-Net Hospitals, Neighborhood Disadvantage, and Readmissions Under Maryland's All-Payer Program: An Observational Study.马里兰州全民医保计划下的安全网医院、社区劣势与再入院:一项观察性研究。
Ann Intern Med. 2019 Jul 16;171(2):91-98. doi: 10.7326/M16-2671. Epub 2019 Jul 2.
3
Approaches to Link Geospatially Varying Social, Economic, and Environmental Factors with Electronic Health Record Data to Better Understand Asthma Exacerbations.将地理空间上变化的社会、经济和环境因素与电子健康记录数据相联系以更好地理解哮喘急性加重的方法。
AMIA Annu Symp Proc. 2018 Dec 5;2018:1561-1570. eCollection 2018.
4
Value of Neighborhood Socioeconomic Status in Predicting Risk of Outcomes in Studies That Use Electronic Health Record Data.利用电子健康记录数据的研究中,邻里社会经济地位对预测结局风险的价值。
JAMA Netw Open. 2018 Sep 7;1(5):e182716. doi: 10.1001/jamanetworkopen.2018.2716.
5
The use of Electronic Health Records to Support Population Health: A Systematic Review of the Literature.利用电子健康记录支持人群健康:文献系统评价。
J Med Syst. 2018 Sep 29;42(11):214. doi: 10.1007/s10916-018-1075-6.
6
Making Neighborhood-Disadvantage Metrics Accessible - The Neighborhood Atlas.让邻里劣势指标易于获取——邻里地图集。
N Engl J Med. 2018 Jun 28;378(26):2456-2458. doi: 10.1056/NEJMp1802313.
7
Biases in electronic health record data due to processes within the healthcare system: retrospective observational study.由于医疗体系内的流程而导致电子健康记录数据出现偏差:回顾性观察性研究。
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8
Comparison of Methods for Estimating Prevalence of Chronic Diseases and Health Behaviors for Small Geographic Areas: Boston Validation Study, 2013.小地理区域慢性疾病和健康行为发生率的估计方法比较:2013 年波士顿验证研究。
Prev Chronic Dis. 2017 Oct 19;14:E99. doi: 10.5888/pcd14.170281.
9
Characteristics of COPD Patients Using United States Emergency Care or Hospitalization.使用美国急诊护理或住院治疗的慢性阻塞性肺疾病患者的特征
Chronic Obstr Pulm Dis. 2016 Mar 28;3(2):539-548. doi: 10.15326/jcopdf.3.2.2015.0155.
10
Enhancing Electronic Health Record Data with Geospatial Information.利用地理空间信息增强电子健康记录数据
AMIA Jt Summits Transl Sci Proc. 2017 Jul 26;2017:123-132. eCollection 2017.

个体与地理区域社会经济地位衡量指标对行为风险因素监测系统中观察到的健康关联的影响。

Impact of Individual versus Geographic-Area Measures of Socioeconomic Status on Health Associations Observed in the Behavioral Risk Factor Surveillance System.

机构信息

Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, United States.

出版信息

AMIA Annu Symp Proc. 2021 Jan 25;2020:707-716. eCollection 2020.

PMID:33936445
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8075432/
Abstract

Efforts to enhance Electronic Health Record (EHR) data for the study of conditions in which social and economic variables play a prominent role include linking clinical data to sources of external information via patient-specific geocodes. This approach is convenient, but whether geographic-area-level information from secondary sources is adequate as a surrogate of individual-level information is not fully understood. We used Behavioral Risk Factor Surveillance System (BRFSS) epidemiologic data to compare associations of individual income, median aggregate income, and Area Deprivation Index (ADI)-a validated score of U.S. socioeconomic deprivation-with various health outcomes. Median income and ADI assigned according to respondent area of residence were significantly associated with various health outcomes, but with substantially lower effect sizes than those of individual income. Our results show the limited ability of median income and ADI at the level of metropolitan/micropolitan statistical areas versus individual income for use as measures of socioeconomic status.

摘要

为了研究社会经济变量起突出作用的病症,我们致力于增强电子健康记录(EHR)数据,包括通过患者特定的地理位置编码将临床数据与外部信息源联系起来。这种方法很方便,但尚不完全清楚来自二级来源的地理区域信息是否可以作为个体水平信息的替代。我们使用行为风险因素监测系统(BRFSS)的流行病学数据,比较个人收入、中位数总收益和区域剥夺指数(ADI)——一个经验证的美国社会经济剥夺评分——与各种健康结果之间的关联。根据受访者居住区域分配的中位数收入和 ADI 与各种健康结果显著相关,但与个体收入相比,其效应大小要低得多。我们的研究结果表明,在大都市/大都市统计区层面上,中位数收入和 ADI 作为社会经济地位衡量标准的能力有限,而个体收入则不然。