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Census and Geographic Differences between Respondents and Nonrespondents in a Case-Control Study of Non-Hodgkin Lymphoma

机译:非霍奇金淋巴瘤病例对照研究中受访者和非受访者的人口普查和地理差异

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摘要

To quantify nonresponse bias and estimate its potential impact, the authors compared census-based socioeconomic and demographic factors and geographic locations among respondents and nonrespondents in a multicenter case-control study of non-Hodgkin lymphoma (1998–2000). Using a geographic information system, the authors mapped current addresses and linked them to the 2000 US Census database to determine group-level demographic and socioeconomic information. They used logistic regression analysis to compute the risk of being a nonrespondent, separately for cases and controls. They used spatial scan methods to evaluate spatial clustering at each study center. Among cases at one or more centers, nonresponse was significantly associated with non-White race, lower household income, a greater proportion of multiple-unit housing, fewer years of education, and living in a more urbanized area. For most factors, the authors observed similar patterns among controls, although findings were mostly nonsignificant. They found two nonrandom elliptical clusters in Los Angeles, California, and Detroit, Michigan, that disappeared after adjustment for the demographic factors. The authors determined the bias in non-Hodgkin lymphoma risk associated with census-tract educational level by comparing risks among respondents and all subjects. The bias was 8%, indicating that the socioeconomic and demographic differences between respondents and nonrespondents did not result in a large bias in the risk estimate for education.
机译:为了量化无应答偏差并估计其潜在影响,作者在一项非霍奇金淋巴瘤多中心病例对照研究(1998-2000年)中比较了基于普查的社会经济和人口统计学因素以及应答者和无应答者的地理位置。作者使用地理信息系统映射了当前地址,并将其链接到2000年美国人口普查数据库,以确定群体级别的人口统计和社会经济信息。他们使用逻辑回归分析分别计算病例和对照者无应答者的风险。他们使用空间扫描方法来评估每个学习中心的空间聚类。在一个或多个中心的案例中,不响应与非白人种族,较低的家庭收入,多单元住房比例较高,受教育年限较短以及居住在城市化程度较高的地区显着相关。对于大多数因素,作者观察到对照组之间的模式相似,尽管发现大多无意义。他们在加利福尼亚的洛杉矶和密歇根州的底特律发现了两个非随机的椭圆簇,在调整了人口因素后消失了。作者通过比较受访者和所有受试者的风险,确定了与普查区教育水平相关的非霍奇金淋巴瘤风险的偏倚。偏差为8%,这表明受访者和未受访者之间的社会经济和人口差异不会导致教育风险估计值有较大偏差。

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