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Public Health ; 193: 69-75, 2021 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-33743216

RESUMO

OBJECTIVE: The aim of the study was to explore the factors that could explain the differences in fatality rates among indigenous groups with COVID-19 diagnosis compared with the rest of the population in Mexico. STUDY DESIGN: We analyzed the public data of COVID-19 surveillance, of the Mexican Ministry of Health, to estimate COVID-19 fatality rates by ethnicity. METHODS: We explored associated factors using Cox proportional hazards models stratified by outpatient and hospital management at diagnosis; analysis was conducted in three scenarios: national level, states with 89% of the indigenous population, and South Pacific region. RESULTS: A total of 412,017 COVID-19 cases were included, with 1.1% of the indigenous population. The crude fatality rate per 1000 person-weeks was 64.8% higher among indigenous than among non-indigenous people (29.97 vs. 18.18, respectively), and it increased more than twice within outpatients (5.99 vs. 2.64, respectively). Cox analysis revealed that indigenous people who received outpatient management had higher fatality rate than non-indigenous outpatients, at the national level (hazard ratio [HR] = 1.63; 95% confidence interval [CI] = 1.34-1.98), within the subgroup of 13 states (HR = 1.66; 95% CI = 1.33-2.07), and in the South Pacific region (HR = 2.35; 95% CI = 1.49-3.69). Factors associated with higher fatality rates among non-indigenous and indigenous outpatients were age, sex, and comorbidities. CONCLUSIONS: COVID-19 fatality is higher among indigenous populations, particularly within cases managed as outpatients.


Assuntos
COVID-19/etnologia , COVID-19/mortalidade , Disparidades nos Níveis de Saúde , Povos Indígenas/estatística & dados numéricos , Adulto , Distribuição por Idade , Idoso , COVID-19/terapia , Comorbidade , Feminino , Hospitalização/estatística & dados numéricos , Humanos , Estudos Longitudinais , Masculino , México/epidemiologia , Pessoa de Meia-Idade , Pacientes Ambulatoriais/estatística & dados numéricos , Fatores de Risco , Distribuição por Sexo
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