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新冠病毒疾病死亡率与城市社区的文盲率、年龄及空气污染相关:一项时空横断面分析

The COVID-19 Mortality Rate Is Associated with Illiteracy, Age, and Air Pollution in Urban Neighborhoods: A Spatiotemporal Cross-Sectional Analysis.

作者信息

Mohammadi Alireza, Pishgar Elahe, Fatima Munazza, Lotfata Aynaz, Fanni Zohreh, Bergquist Robert, Kiani Behzad

机构信息

Department of Geography and Urban Planning, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran.

Department of Human Geography, Faculty of Earth Sciences, Shahid Beheshti University, Tehran 19839-69411, Iran.

出版信息

Trop Med Infect Dis. 2023 Jan 26;8(2):85. doi: 10.3390/tropicalmed8020085.

Abstract

There are different area-based factors affecting the COVID-19 mortality rate in urban areas. This research aims to examine COVID-19 mortality rates and their geographical association with various socioeconomic and ecological determinants in 350 of Tehran's neighborhoods as a big city. All deaths related to COVID-19 are included from December 2019 to July 2021. Spatial techniques, such as Kulldorff's SatScan, geographically weighted regression (GWR), and multi-scale GWR (MGWR), were used to investigate the spatially varying correlations between COVID-19 mortality rates and predictors, including air pollutant factors, socioeconomic status, built environment factors, and public transportation infrastructure. The city's downtown and northern areas were found to be significantly clustered in terms of spatial and temporal high-risk areas for COVID-19 mortality. The MGWR regression model outperformed the OLS and GWR regression models with an adjusted R of 0.67. Furthermore, the mortality rate was found to be associated with air quality (e.g., NO, PM, and O); as air pollution increased, so did mortality. Additionally, the aging and illiteracy rates of urban neighborhoods were positively associated with COVID-19 mortality rates. Our approach in this study could be implemented to study potential associations of area-based factors with other emerging infectious diseases worldwide.

摘要

城市地区存在不同的基于区域的因素影响新冠死亡率。本研究旨在调查作为大城市的德黑兰350个社区的新冠死亡率及其与各种社会经济和生态决定因素的地理关联。纳入了2019年12月至2021年7月期间所有与新冠相关的死亡病例。运用了空间技术,如 Kulldorff 的时空扫描统计法、地理加权回归(GWR)和多尺度地理加权回归(MGWR),来研究新冠死亡率与预测因素之间的空间变化相关性,这些预测因素包括空气污染物因素、社会经济地位、建成环境因素和公共交通基础设施。研究发现,该市的市中心和北部地区在新冠死亡率的时空高风险区域方面存在显著聚集。MGWR 回归模型表现优于普通最小二乘法(OLS)和 GWR 回归模型,调整后的 R 值为0.67。此外,发现死亡率与空气质量(如一氧化氮、颗粒物和臭氧)有关;随着空气污染加剧,死亡率也随之上升。此外,城市社区的老龄化率和文盲率与新冠死亡率呈正相关。本研究中的方法可用于研究全球范围内基于区域的因素与其他新发传染病之间的潜在关联。

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