Assessing the Impact of Individual Characteristics and Neighborhood Socioeconomic Status During the COVID-19 Pandemic in the Provinces of Milan and Lodi
Assessing the Impact of Individual Characteristics and Neighborhood Socioeconomic Status During the COVID-19 Pandemic in the Provinces of Milan and Lodi
复制标题
DOI：
10.1177/0020731421994842
复制
发表时间：
2021-03-02
影响因子：
3.4
通讯作者：
Russo, Antonio Giampiero
中科院分区：
文献类型：
--
作者：
Consolazio, David;Murtas, Rossella;Russo, Antonio Giampiero
众所周知，保健方面的社会不平等受到人们所居住领土的社会经济地位的影响。在2019冠状病毒病（COVID-19）持续大流行的背景下，本研究旨在评估意大利伦巴第米兰省和洛迪省5个区域级指标在影响传染风险方面的作用，即：教育劣势、失业、住房拥挤、流动性和人口密度。研究区域包括意大利第一次疫情爆发的城市。使用了来自米兰COVID-19分析综合数据库的COVID-19患者数据，并将其与意大利国家统计局（Istat）的汇总数据进行了匹配。使用多水平逻辑回归模型来估计人口普查块水平预测因子与COVID-19感染之间的关联，独立于年龄、性别、出生国家和先前存在的健康状况。所有变量都与结果显著相关，在封锁前后和居住省份的影响不同。这表明疫情中存在一种社会经济不平等的模式，在未来可能发生流行病时应考虑到这一点，以遏制其传播及其相关差异。
Social inequalities in health are known to be influenced by the socioeconomic status of the territory in which people live. In the context of the ongoing coronavirus disease 2019 (COVID-19) pandemic, this study is aimed at assessing the role of 5 area-level indicators in shaping the risk of contagion in the provinces of Milan and Lodi (Lombardy, Italy), namely: educational disadvantage, unemployment, housing crowding, mobility, and population density. The study area includes the municipalities at the origin of the first Italian epidemic outbreak. Data on COVID-19 patients from the Integrated Datawarehouse for COVID Analysis in Milan were used and matched with aggregate-level data from the National Institute of Statistics Italy (Istat). Multilevel logistic regression models were used to estimate the association between the census block-level predictors and COVID-19 infection, independently of age, sex, country of birth, and preexisting health conditions. All the variables were significantly associated with the outcome, with different effects before and after the lockdown and according to the province of residence. This suggests a pattern of socioeconomic inequalities in the outbreak, which should be taken into account in the eventuality of future epidemics to contain their spread and its related disparities.