Palandri Lucia, Rizzi Cristiana, Vandelli Vittoria, Filippini Tommaso, Ghinoi Alessandro, Carrozzi Giuliano, Girolamo Gianfranco De, Morlini Isabella, Coratza Paola, Giovannetti Enrico, Russo Margherita, Soldati Mauro, Righi Elena
Department of Biomedical, Metabolic and Neural Sciences, Section of Public Health, University of Modena and Reggio Emilia, Modena, Italy; PhD Program in Clinical and Experimental Medicine, Department of Biomedical, Metabolic and Neural Sciences, Section of Public Health, University of Modena and Reggio Emilia, Modena, Italy.
Department of Biomedical, Metabolic and Neural Sciences, Section of Public Health, University of Modena and Reggio Emilia, Modena, Italy.
Int J Hyg Environ Health. 2025 Jan;263:114471. doi: 10.1016/j.ijheh.2024.114471. Epub 2024 Oct 3.
Up to now, studies on environmental, climatic, socio-economic factors, and non-pharmacological interventions (NPI) show diverse associations, often contrasting, with COVID-19 spread or severity. Most studies used large-scale, aggregated data, with limited adjustment for individual factors, most of them focused on viral spread than severe outcomes. Moreover, evidence simultaneously evaluating variables belonging to different exposure domains is scarce, and none analysing their collective impact on an individual level.
Our population-based retrospective cohort study aimed to assess the comprehensive role played by exposure variables belonging to four different domains, environmental, climatic, socio-economic, and non-pharmacological interventions (NPI), on individual COVID-19-related risk of hospitalization and death, analysing data from all patients (no. 68472) tested positive to a SARS-CoV-2 swab in Modena Province (Northern Italy) between February 2020 and August 2021. Using adjusted Cox proportional hazard models, we estimated the risk of severe COVID-19 outcomes, investigating dose-response relationships through restricted cubic spline modelling for hazard ratios.
Several significant associations emerged: long-term exposure to air pollutants (NO, PM, PM) was linked to hospitalization risk in a complex way and showed an increased risk for death; while humidity was inversely associated; temperature showed a U-shaped risk; wind speed showed a linear association with both outcomes. Precipitation increased hospitalization risk but decreased mortality. Socio-economic and NPI indices showed clear linear associations, respectively negative and positive, with both outcomes.
Our findings offer insights for evidence-based policy decisions, improving precision healthcare practices, and safeguarding public health in future pandemics. Refinement of pandemic response plans by healthcare authorities could benefit significantly.
到目前为止,关于环境、气候、社会经济因素以及非药物干预措施(NPI)的研究显示,它们与新冠病毒的传播或严重程度之间存在多样的关联,且往往相互矛盾。大多数研究使用的是大规模的汇总数据,对个体因素的调整有限,其中大多数研究关注的是病毒传播而非严重后果。此外,同时评估属于不同暴露领域变量的证据很少,也没有研究分析它们在个体层面的综合影响。
我们基于人群的回顾性队列研究旨在评估属于四个不同领域的暴露变量,即环境、气候、社会经济和非药物干预措施(NPI),对个体新冠病毒相关住院和死亡风险的综合作用,分析了2020年2月至2021年8月间意大利北部摩德纳省所有新冠病毒核酸检测呈阳性的患者(共68472例)的数据。我们使用调整后的Cox比例风险模型,估计了严重新冠病毒感染后果的风险,并通过受限立方样条模型对风险比进行建模来研究剂量反应关系。
出现了几个显著的关联:长期暴露于空气污染物(一氧化氮、细颗粒物、可吸入颗粒物)与住院风险存在复杂的关联,且死亡风险增加;而湿度与之呈负相关;温度呈现U型风险;风速与两种结果均呈线性关联。降水增加了住院风险但降低了死亡率。社会经济和非药物干预措施指数与两种结果均分别呈现明显的线性关联,分别为负相关和正相关。
我们的研究结果为基于证据的政策决策、改进精准医疗实践以及在未来大流行中保障公众健康提供了见解。医疗当局完善大流行应对计划可能会受益匪浅。