Scuola Normale Superiore, Pisa, Italy.
Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy.
Int J Health Geogr. 2024 Apr 4;23(1):8. doi: 10.1186/s12942-024-00367-6.
It has been shown that COVID-19 affects people at socioeconomic disadvantage more strongly. Previous studies investigating the association between geographical deprivation and COVID-19 outcomes in Italy reported no differences in case-hospitalisation and case-fatality. The objective of this research was to compare the usefulness of the geographic and individual deprivation index (DI) in assessing the associations between individuals' deprivation and risk of Sars-CoV-2 infection and disease severity in the Apulia region from February to December 2020.
This was a retrospective cohort study. Participants included individuals tested for SARS-CoV-2 infection during the study period. The individual DI was calculated employing polychoric principal component analysis on four census variables. Multilevel logistic models were used to test associations between COVID-19 outcomes and individual DI, geographical DI, and their interaction.
In the study period, 139,807 individuals were tested for COVID-19 and 56,475 (43.5%) tested positive. Among those positive, 7902 (14.0%) have been hospitalised and 2215 (4.2%) died. During the first epidemic wave, according the analysis done with the individual DI, there was a significant inversely proportional trend between the DI and the risk of testing positive. No associations were found between COVID-19 outcomes and geographic DI. During the second wave, associations were found between COVID-19 outcomes and individual DI. No associations were found between the geographic DI and the risk of hospitalisation and death. During both waves, there were no association between COVID-19 outcomes and the interaction between individual and geographical DI.
Evidence from this study shows that COVID-19 pandemic has been experienced unequally with a greater burden among the most disadvantaged communities. The results of this study remind us to be cautious about using geographical DI as a proxy of individual social disadvantage because may lead to inaccurate assessments. The geographical DI is often used due to a lack of individual data. However, on the determinants of health and health inequalities, monitoring has to have a central focus. Health inequalities monitoring provides evidence on who is being left behind and informs equity-oriented policies, programmes and practices. Future research and data collection should focus on improving surveillance systems by integrating individual measures of inequalities into national health information systems.
已表明 COVID-19 对社会经济地位较低的人群影响更大。此前研究意大利地理剥夺与 COVID-19 结局之间的关联，发现病例住院和病死之间无差异。本研究旨在比较地理剥夺指数（DI）和个体剥夺指数（DI）在评估 2020 年 2 月至 12 月普利亚地区个体剥夺与 SARS-CoV-2 感染和疾病严重程度风险之间关联的有用性。
本研究为回顾性队列研究。纳入研究期间接受 SARS-CoV-2 感染检测的个体。个体 DI 通过四项人口普查变量的多元主成分分析计算得出。采用多水平逻辑回归模型检验 COVID-19 结局与个体 DI、地理 DI 及其交互作用之间的关联。
在研究期间，共对 139807 例个体进行了 COVID-19 检测，其中 56475 例（43.5%）检测呈阳性。阳性个体中，7902 例（14.0%）住院，2215 例（4.2%）死亡。在第一波疫情中，根据个体 DI 分析，DI 与检测阳性风险呈显著负相关趋势。COVID-19 结局与地理 DI 无关联。在第二波疫情中，COVID-19 结局与个体 DI 相关联。地理 DI 与住院和死亡风险无关联。两波疫情中，COVID-19 结局与个体和地理 DI 之间的交互作用无关联。
本研究结果表明，COVID-19 大流行的经历不平等，最弱势社区的负担更大。本研究结果提醒我们要谨慎使用地理 DI 作为个体社会劣势的替代指标，因为可能导致不准确的评估。由于缺乏个体数据，地理 DI 通常被使用。然而，在健康和健康不平等的决定因素方面，监测必须是重点。健康不平等监测提供了谁被抛在后面的证据，并为面向公平的政策、方案和实践提供信息。未来的研究和数据收集应重点改进监测系统，将个体不平等衡量标准纳入国家卫生信息系统。
