Universidad Politécnica de Francisco I. Madero, Dirección de Ingeniería Agroindustrial, Tepatepec, Hidalgo, Mexico.
CONACyT - Universidad Autónoma Metropolitana-Iztapalapa, Departamento de Química, Mexico City, Mexico.
J Infect Dev Ctries. 2022 Jun 30;16(6):969-980. doi: 10.3855/jidc.15618.
Mexico is one of the countries that is most affected by mortality due to COVID-19. Once infected, the indigenous population living in the lower-income states had worse outcomes. Our objectives were to analyze outcomes by ethnic group, and determine the association between state-level income and the incidence, hospitalizations, outpatients, and death rates per 100,000 population.
We analyzed 1,037,567 confirmed COVID-positive cases from February 29 to November 13, 2020 recorded in the Mexican COVID-19 cases database. Sociodemographic characteristics, comorbidities, and outcomes were analyzed. Data was allocated according to the state where the patients were treated. Statistical association between age-adjusted incidence and death rates with state-level GDP per capita (as a measure of income), were ascertained using Spearman correlations. Kruskal-Wallis tests examine the association of cumulative incidence, hospitalizations, outpatients, and death rates, with income quartiles. When significant, a follow-up analysis (Mann-Whitney) was conducted.
Respective cumulative incidence rates and death rates were: 900.3 (non-indigenous) and 94.4 (indigenous), and 87.1 (non-indigenous) and 13.9 (indigenous). Spearman correlation coefficients of income with age-standardized incidence and death rates were 0.657 and 0.607 (p < 0.001 for both). Kruskal-Wallis H-Values indicate significant median differences by income in total population rates: cumulative incidence 13.47 (p < 0.01), hospitalizations 11.67 (p < 0.01), outpatients 12.86 (p < 0.01), and deaths 8.92 (p < 0.05).
Cumulative incidence, hospitalizations, outpatients, and mortality rates presented a reversed socioeconomic status health gradient in Mexico. Less adverse outcomes were observed in the lowest-income states compared to higher-income states.
墨西哥是受 COVID-19 死亡率影响最大的国家之一。一旦感染,生活在低收入州的土著居民的预后更差。我们的目标是按族裔分析结果,并确定州级收入与发病率、住院率、门诊率和每 10 万人死亡率之间的关联。
我们分析了 2020 年 2 月 29 日至 11 月 13 日在墨西哥 COVID-19 病例数据库中记录的 1,037,567 例确诊 COVID-19 阳性病例。分析了社会人口统计学特征、合并症和结果。根据患者治疗的州分配数据。使用 Spearman 相关系数确定年龄调整后发病率和死亡率与州级人均 GDP(作为收入衡量标准)之间的统计关联。Kruskal-Wallis 检验用于检验累积发病率、住院率、门诊率和死亡率与收入四分位数的关联。当显著时,进行后续分析(Mann-Whitney)。
相应的累积发病率和死亡率分别为:900.3(非土著)和 94.4(土著),87.1(非土著)和 13.9(土著)。收入与年龄标准化发病率和死亡率的 Spearman 相关系数分别为 0.657 和 0.607(p < 0.001)。Kruskal-Wallis H 值表明,总收入人群的收入存在显著中位数差异:累积发病率为 13.47(p < 0.01),住院率为 11.67(p < 0.01),门诊率为 12.86(p < 0.01),死亡率为 8.92(p < 0.05)。
墨西哥的累积发病率、住院率、门诊率和死亡率呈现出与社会经济地位相反的健康梯度。与高收入州相比,低收入州的不良结局较少。