Department of Social and Political Sciences, Universidad Iberoamericana, Ciudad de México, Mexico.
Colegio de Postgraduados, Montecillo, Mexico.
Front Public Health. 2024 Oct 9;12:1463979. doi: 10.3389/fpubh.2024.1463979. eCollection 2024.
Poverty is one of the macro factors that has been little studied in terms of its effect on death from COVID-19 since most studies have focused only on investigating whether the pandemic increased poverty or not. With that on mind, the present study aims to analyze how the social deprivations that comprise the measurement of municipal poverty in interaction with health comorbidities and sociodemographic characteristics, increased the probability of death from COVID-19.
The study is cross-sectional and covers daily reports on the conditions of COVID-19 in the Mexican population for almost 2 years. Using data from the National Epidemiological Surveillance System and the National Council for Evaluation of the Social Development Policy ( = 5,387,981), we employ a Generalized Linear Mixed Model (GLMM), specifically a binomial generalized linear mixed model.
The findings indicate that, besides comorbidities, sociodemographic traits, and clinical aspects, living in a municipality where one or more of the social deprivations exist increases the probability of death. Specifically, in those municipalities where there is deprivation in education, social security, and food, as well as deprivation due to access to health services and deprivation in household services, the probability of death was greater.
Living in a municipality with one or more of the social deprivations that compose poverty generated a greater probability of death. Each one of them or together, shows that poverty is a substantial factor for a pandemic like COVID-19 to worsen contagion and death, becoming a circle from which it is difficult to escape.
贫困是影响 COVID-19 死亡的宏观因素之一，但大多数研究仅关注于调查大流行是否导致了贫困加剧，因此对于贫困对 COVID-19 死亡的影响，相关研究相对较少。有鉴于此，本研究旨在分析构成城市贫困衡量标准的社会剥夺因素与健康合并症和社会人口特征之间的相互作用，如何增加 COVID-19 死亡的概率。
本研究为横断面研究，涵盖了近 2 年来墨西哥人口 COVID-19 状况的每日报告。利用国家流行病学监测系统和国家社会发展政策评估委员会的数据（ = 5387981），我们采用了广义线性混合模型（GLMM），具体来说是二项广义线性混合模型。
研究结果表明，除了合并症、社会人口特征和临床特征外，生活在一个存在一种或多种社会剥夺的城市也会增加死亡的概率。具体来说，在那些在教育、社会保障和食品方面存在剥夺、由于获得医疗服务和家庭服务而受到剥夺以及存在剥夺的城市，死亡的概率更高。
生活在一个存在一种或多种构成贫困的社会剥夺的城市会增加死亡的概率。它们中的每一个或共同表明，贫困是 COVID-19 等大流行导致传染和死亡恶化的一个重要因素，成为一个难以摆脱的恶性循环。
