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基于人群的研究:加拿大安大略省邻里级社会人口统计学特征与 COVID-19 发病率和死亡率的关系。

Neighbourhood-level socio-demographic characteristics and risk of COVID-19 incidence and mortality in Ontario, Canada: A population-based study.

机构信息

Public Health Ontario, Toronto, Ontario, Canada.

ICES, Toronto, Ontario, Canada.

出版信息

PLoS One. 2022 Oct 20;17(10):e0276507. doi: 10.1371/journal.pone.0276507. eCollection 2022.

Abstract

OBJECTIVES

We aimed to estimate associations between COVID-19 incidence and mortality with neighbourhood-level immigration, race, housing, and socio-economic characteristics.

METHODS

We conducted a population-based study of 28,808 COVID-19 cases in the provincial reportable infectious disease surveillance systems (Public Health Case and Contact Management System) which includes all known COVID-19 infections and deaths from Ontario, Canada reported between January 23, 2020 and July 28, 2020. Residents of congregate settings, Indigenous communities living on reserves or small neighbourhoods with populations <1,000 were excluded. Comparing neighbourhoods in the 90th to the 10th percentiles of socio-demographic characteristics, we estimated the associations between 18 neighbourhood-level measures of immigration, race, housing and socio-economic characteristics and COVID-19 incidence and mortality using Poisson generalized linear mixed models.

RESULTS

Neighbourhoods with the highest proportion of immigrants (relative risk (RR): 4.0, 95%CI:3.5-4.5) and visible minority residents (RR: 3.3, 95%CI:2.9-3.7) showed the strongest association with COVID-19 incidence in adjusted models. Among individual race groups, COVID-19 incidence was highest among neighbourhoods with the high proportions of Black (RR: 2.4, 95%CI:2.2-2.6), South Asian (RR: 1.9, 95%CI:1.8-2.1), Latin American (RR: 1.8, 95%CI:1.6-2.0) and Middle Eastern (RR: 1.2, 95%CI:1.1-1.3) residents. Neighbourhoods with the highest average household size (RR: 1.9, 95%CI:1.7-2.1), proportion of multigenerational families (RR: 1.8, 95%CI:1.7-2.0) and unsuitably crowded housing (RR: 2.1, 95%CI:2.0-2.3) were associated with COVID-19 incidence. Neighbourhoods with the highest proportion of residents with less than high school education (RR: 1.6, 95%CI:1.4-1.8), low income (RR: 1.4, 95%CI:1.2-1.5) and unaffordable housing (RR: 1.6, 95%CI:1.4-1.8) were associated with COVID-19 incidence. Similar inequities were observed across neighbourhood-level sociodemographic characteristics and COVID-19 mortality.

CONCLUSIONS

Neighbourhood-level inequities in COVID-19 incidence and mortality were observed in Ontario, with excess burden experienced in neighbourhoods with a higher proportion of immigrants, racialized populations, large households and low socio-economic status.

摘要

目的

我们旨在评估社区层面的移民、种族、住房和社会经济特征与 COVID-19 发病率和死亡率之间的关联。

方法

我们对安大略省的 28808 例 COVID-19 病例进行了基于人群的研究,这些病例来自于加拿大安大略省的省级传染病报告监测系统(公共卫生病例和接触管理系统),其中包括 2020 年 1 月 23 日至 2020 年 7 月 28 日报告的所有已知 COVID-19 感染和死亡病例。我们排除了集体居住环境、保留地的原住民社区以及人口少于 1000 人的小社区的居民。在比较社会人口统计学特征的第 90 百分位和第 10 百分位的社区时,我们使用泊松广义线性混合模型估计了 18 个社区层面的移民、种族、住房和社会经济特征与 COVID-19 发病率和死亡率之间的关联。

结果

在调整后的模型中,移民比例最高(相对风险 (RR):4.0,95%置信区间:3.5-4.5)和可见少数民族居民比例最高(RR:3.3,95%置信区间:2.9-3.7)的社区与 COVID-19 发病率的关联最强。在各个种族群体中,黑人(RR:2.4,95%置信区间:2.2-2.6)、南亚人(RR:1.9,95%置信区间:1.8-2.1)、拉丁美洲人(RR:1.8,95%置信区间:1.6-2.0)和中东人(RR:1.2,95%置信区间:1.1-1.3)居民比例最高的社区 COVID-19 发病率最高。平均家庭规模最大(RR:1.9,95%置信区间:1.7-2.1)、多代家庭比例最高(RR:1.8,95%置信区间:1.7-2.0)和住房过度拥挤(RR:2.1,95%置信区间:2.0-2.3)的社区与 COVID-19 发病率相关。受教育程度较低(RR:1.6,95%置信区间:1.4-1.8)、收入较低(RR:1.4,95%置信区间:1.2-1.5)和住房负担过重(RR:1.6,95%置信区间:1.4-1.8)的社区与 COVID-19 发病率相关。在 COVID-19 死亡率方面也观察到了类似的社区层面社会人口统计学特征的不平等现象。

结论

在安大略省,COVID-19 的发病率和死亡率存在社区层面的不平等现象,在移民比例较高、种族化人口较多、家庭规模较大和社会经济地位较低的社区,负担过重。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf44/9584389/eb6752568c8f/pone.0276507.g001.jpg

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