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A multi-stage approach to maximizing geocoding success in a large population-based cohort study through automated and interactive processes

机译:一种多阶段方法,可通过自动化和交互过程在基于人群的大型队列研究中最大程度地提高地理编码的成功率

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To enable spatial analyses within a large, prospective cohort study of nearly 86,000 adults enrolled in a 12-state area in the southeastern United States of America from 2002-2009, a multi-stage geocoding protocol was developed to efficiently maximize the proportion of participants assigned an address level geographic coordinate. Addresses were parsed, cleaned and standardized before applying a combination of automated and interactive geocoding tools. Our full protocol increased the non-Post Office (PO) Box match rate from 74.5% to 97.6%. Overall, we geocoded 99.96% of participant addresses, with only 5.2% at the ZIP code centroid level (2.8% PO Box and 2.3% non-PO Box addresses). One key to reducing the need for interactive geocoding was the use of multiple base maps. Still, addresses in areas with population density 920 persons/km2 (odds ratio (OR) = 5.24; 95% confidence interval (CI) = 4.23, 6.49), as were addresses collected from participants during in-person interviews compared with mailed questionnaires (OR = 1.83; 95% CI = 1.59, 2.11). This study demonstrates that population density and address ascertainment method can influence automated geocoding results and that high success in address level geocoding is achievable for large-scale studies covering wide geographical areas.
机译:为了在2002年至2009年对美国东南部12个州的近86,000名成年人进行的大规模前瞻性队列研究中进行空间分析,开发了多阶段地理编码协议,以有效地最大化分配给参与者的比例地址级别的地理坐标。在应用自动和交互式地理编码工具的组合之前,地址已被解析,清理和标准化。我们的完整协议将非邮政局(PO)邮箱的匹配率从74.5%提高到97.6%。总体而言,我们对99.96%的参与者地址进行了地理编码,而邮政编码重心级别仅为5.2%(2.8%的邮政信箱和2.3%的非邮政信箱地址)。减少交互式地理编码需求的一个关键是使用多个底图。尽管如此,人口密度为920人/ km2(比值比(OR)= 5.24; 95%置信区间(CI)= 4.23,6.49)的地区的地址,以及与邮寄调查表相比在面对面访谈中从参与者那里收集的地址( OR = 1.83; 95%CI = 1.59,2.11)。这项研究表明,人口密度和地址确定方法可以影响自动地理编码的结果,并且对于覆盖广泛地理区域的大规模研究,可以实现地址级别地理编码的高度成功。

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