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生活方式对美国 COVID-19 传播风险的影响:市场细分系统评估。

Lifestyle Effects on the Risk of Transmission of COVID-19 in the United States: Evaluation of Market Segmentation Systems.

机构信息

Spatial Analysis and Geographic Education Laboratory, Department of Earth Sciences, University of Memphis, Memphis, TN 38152, USA.

Department of Geosciences, Mississippi State University, Starkville, MS 39762, USA.

出版信息

Int J Environ Res Public Health. 2021 Apr 30;18(9):4826. doi: 10.3390/ijerph18094826.

Abstract

The aim of this study was to associate lifestyle characteristics with COVID-19 infection and mortality rates at the U.S. county level and sequentially map the impact of COVID-19 on different lifestyle segments. We used analysis of variance (ANOVA) statistical testing to determine whether there is any correlation between COVID-19 infection and mortality rates and lifestyles. We used ESRI Tapestry LifeModes data that are collected at the U.S. household level through geodemographic segmentation typically used for marketing purposes to identify consumers' lifestyles and preferences. According to the ANOVA analysis, a significant association between COVID-19 deaths and LifeModes emerged on 1 April 2020 and was sustained until 30 June 2020. Analysis of means (ANOM) was also performed to determine which LifeModes have incidence rates that are significantly above/below the overall mean incidence rate. We sequentially mapped and graphically illustrated when and where each LifeMode had above/below average risk for COVID-19 infection/death on specific dates. A strong northwest-to-south and northeast-to-south gradient of COVID-19 incidence was identified, facilitating an empirical classification of the United States into several epidemic subregions based on household lifestyle characteristics. Our approach correlating lifestyle characteristics to COVID-19 infection and mortality rate at the U.S. county level provided unique insights into where and when COVID-19 impacted different households. The results suggest that prevention and control policies can be implemented to those specific households exhibiting spatial and temporal pattern of high risk.

摘要

本研究旨在探讨美国县一级的生活方式特征与 COVID-19 感染和死亡率之间的关联,并依次绘制 COVID-19 对不同生活方式群体的影响图谱。我们采用方差分析(ANOVA)统计检验来确定 COVID-19 感染和死亡率与生活方式之间是否存在任何相关性。我们使用 ESRI Tapestry LifeModes 数据,这些数据是通过地理人口统计学细分在美国家庭层面收集的,通常用于营销目的,以识别消费者的生活方式和偏好。根据 ANOVA 分析,2020 年 4 月 1 日至 2020 年 6 月 30 日期间,COVID-19 死亡与 LifeModes 之间存在显著关联。我们还进行了均值分析(ANOM),以确定哪些 LifeModes 的发病率明显高于/低于总体平均发病率。我们依次绘制并图形化地说明了每个 LifeMode 在特定日期的 COVID-19 感染/死亡风险高于/低于平均水平的时间和地点。我们确定了 COVID-19 发病率从西北到东南和从东北到西南的强烈梯度,这使得我们能够根据家庭生活方式特征将美国分为几个疫情亚区。我们将生活方式特征与美国县一级的 COVID-19 感染和死亡率相关联的方法,为了解 COVID-19 在不同家庭中的影响地点和时间提供了独特的见解。研究结果表明,可以针对那些表现出高风险时空模式的特定家庭实施预防和控制政策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cfd/8125751/a13f672d40b9/ijerph-18-04826-g001.jpg

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