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一种可推广的评估方法,应用先进的地理空间统计方法,在人口普查区尺度上识别高铅暴露地点:密歇根州案例研究。

A Generalizable Evaluated Approach, Applying Advanced Geospatial Statistical Methods, to Identify High Lead Exposure Locations at Census Tract Scale: Michigan Case Study.

机构信息

U.S. Environmental Protection Agency (EPA), Office of Research and Development, Research Triangle Park, North Carolina, USA.

LinTech Global, Inc., Boston, Massachusetts, USA.

出版信息

Environ Health Perspect. 2022 Jul;130(7):77004. doi: 10.1289/EHP9705. Epub 2022 Jul 27.

DOI:10.1289/EHP9705
PMID:35894594
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9327739/
Abstract

BACKGROUND

Despite great progress in reducing environmental lead (Pb) levels, many children in the United States are still being exposed.

OBJECTIVE

Our aim was to develop a generalizable approach for systematically identifying, verifying, and analyzing locations with high prevalence of children's elevated blood Pb levels (EBLLs) and to assess available Pb models/indices as surrogates, using a Michigan case study.

METHODS

We obtained BLL test results of children of age in Michigan from 2006-2016; we then evaluated them for data representativeness by comparing two percentage EBLL (%EBLL) rates (number of children tested with EBLL divided by both number of children tested and total population). We analyzed %EBLLs across census tracts over three time periods and between two EBLL reference values ( vs. ) to evaluate consistency. Locations with high %EBLLs were identified by a top 20 percentile method and a Getis-Ord Gi* geospatial cluster "hotspot" analysis. For the locations identified, we analyzed convergences with three available Pb exposure models/indices based on old housing and sociodemographics.

RESULTS

Analyses of 2014-2016 %EBLL data identified 11 Michigan locations via cluster analysis and 80 additional locations via the top 20 percentile method and their associated census tracts. Data representativeness and consistency were supported by a 0.93 correlation coefficient between the two EBLL rates over 11 y, and a Kappa score of of %EBLL hotspots across the time periods (2014-2016) and reference values. Many EBLL hotspot locations converge with current Pb exposure models/indices; others diverge, suggesting additional Pb sources for targeted interventions.

DISCUSSION

This analysis confirmed known Pb hotspot locations and revealed new ones at a finer geographic resolution than previously available, using advanced geospatial statistical methods and mapping/visualization. It also assessed the utility of surrogates in the absence of blood Pb data. This approach could be applied to other states to inform Pb mitigation and prevention efforts. https://doi.org/10.1289/EHP9705.

摘要

背景

尽管在降低环境铅 (Pb) 水平方面取得了巨大进展,但美国仍有许多儿童受到铅暴露。

目的

我们旨在开发一种可推广的方法,系统地识别、验证和分析儿童血铅水平升高 (EBLL) 高发地区,并评估可用的 Pb 模型/指标作为替代指标,使用密歇根州的案例研究。

方法

我们获取了 2006-2016 年密歇根州儿童的 BLL 检测结果;然后,通过比较两个百分比 EBLL (%EBLL) 率(用 EBLL 检测的儿童人数除以接受检测的儿童人数和总人口数)来评估数据代表性。我们在三个时间段内分析了普查区的 %EBLL,并在两个 EBLL 参考值( vs. )之间进行了分析,以评估一致性。通过 20%的最高百分比方法和 Getis-Ord Gi* 地理空间聚类“热点”分析确定高 %EBLL 地区。对于确定的位置,我们根据旧住房和社会人口统计学分析了三种可用的 Pb 暴露模型/指标的收敛性。

结果

通过聚类分析和 20%的最高百分比方法确定了 2014-2016 年的 11 个密歇根州地点,以及 80 个额外的地点及其相关的普查区。11 年来,两个 EBLL 率之间的相关系数为 0.93,以及在时间段(2014-2016 年)和参考值上的 %EBLL 热点的 Kappa 评分的一致性,证明了数据的代表性。许多 EBLL 热点地区与当前的 Pb 暴露模型/指标相吻合;其他地区则存在差异,这表明需要针对特定目标采取干预措施,以减少其他 Pb 来源。

讨论

本分析使用先进的地理空间统计方法和绘图/可视化技术,以比以前更高的地理分辨率确认了已知的 Pb 热点地区,并揭示了新的热点地区,同时还评估了替代指标在缺乏血 Pb 数据时的实用性。这种方法可以应用于其他州,以告知 Pb 缓解和预防工作。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ccb/9327739/1916077d68a7/ehp9705_f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ccb/9327739/4ba5fa58853a/ehp9705_f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ccb/9327739/7fb4dc911271/ehp9705_f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ccb/9327739/39f6f5673313/ehp9705_f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ccb/9327739/c3b159c9a925/ehp9705_f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ccb/9327739/1916077d68a7/ehp9705_f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ccb/9327739/4ba5fa58853a/ehp9705_f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ccb/9327739/7fb4dc911271/ehp9705_f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ccb/9327739/39f6f5673313/ehp9705_f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ccb/9327739/c3b159c9a925/ehp9705_f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ccb/9327739/1916077d68a7/ehp9705_f5.jpg

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