Department of Social and Behavioral Sciences, Yale School of Public Health, 60 College Street, LEPH 4th Floor, New Haven, CT, 06510, USA.
Division of Infectious Diseases, Brigham and Women's Hospital, Boston, MA, USA.
J Urban Health. 2021 Apr;98(2):222-232. doi: 10.1007/s11524-021-00532-3. Epub 2021 Mar 23.
Geographic inequalities in COVID-19 diagnosis are now well documented. However, we do not sufficiently know whether inequalities are related to social characteristics of communities, such as collective engagement. We tested whether neighborhood social cohesion is associated with inequalities in COVID-19 diagnosis rate and the extent the association varies across neighborhood racial composition. We calculated COVID-19 diagnosis rates in Philadelphia, PA, per 10,000 general population across 46 ZIP codes, as of April 2020. Social cohesion measures were from the Southeastern Pennsylvania Household Health Survey, 2018. We estimated Poisson regressions to quantify associations between social cohesion and COVID-19 diagnosis rate, testing a multiplicative interaction with Black racial composition in the neighborhood, which we operationalize via a binary indicator of ZIP codes above vs. below the city-wide average (41%) Black population. Two social cohesion indicators were significantly associated with COVID-19 diagnosis. Associations varied across Black neighborhood racial composition (p <0.05 for the interaction test). In ZIP codes with ≥41% of Black people, higher collective engagement was associated with an 18% higher COVID-19 diagnosis rate (IRR=1.18, 95%CI=1.11, 1.26). In contrast, areas with <41% of Black people, higher engagement was associated with a 26% lower diagnosis rate (IRR=0.74, 95%CI=0.67, 0.82). Neighborhood social cohesion is associated with both higher and lower COVID-19 diagnosis rates, and the extent of associations varies across Black neighborhood racial composition. We recommend some strategies for reducing inequalities based on the segmentation model within the social cohesion and public health intervention framework.
地理上的 COVID-19 诊断不平等现象现在已经得到充分证明。然而,我们并不清楚这些不平等是否与社区的社会特征有关,例如集体参与度。我们检验了邻里社会凝聚力是否与 COVID-19 诊断率的不平等有关,以及这种关联在邻里的种族构成方面的差异程度。我们计算了截至 2020 年 4 月,宾夕法尼亚州费城 46 个邮政编码内每 10000 名普通人群的 COVID-19 诊断率。社会凝聚力的衡量标准来自 2018 年宾夕法尼亚州东南部家庭健康调查。我们使用泊松回归来量化社会凝聚力与 COVID-19 诊断率之间的关联,检验邻里中黑人群体构成的乘积交互作用,我们通过邮政编码是否高于或低于全市平均黑人人口(41%)的二进制指标来操作化该交互作用。有两个社会凝聚力指标与 COVID-19 诊断显著相关。关联在黑人群体构成的邻里中存在差异(交互作用检验的 p 值<0.05)。在黑人人口比例≥41%的邮政编码中,较高的集体参与度与 COVID-19 诊断率升高 18%相关(IRR=1.18,95%CI=1.11,1.26)。相比之下,黑人人口比例<41%的地区,较高的参与度与诊断率降低 26%相关(IRR=0.74,95%CI=0.67,0.82)。邻里社会凝聚力与 COVID-19 诊断率的高低都有关联,关联的程度在黑人群体构成的邻里中存在差异。我们建议根据社会凝聚力和公共卫生干预框架内的细分模型,制定一些减少不平等的策略。