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Social inequalities and COVID-19 mortality between neighborhoods of Bariloche city, Argentina.
Perner, Mónica Serena; Trotta, Andrés; Bilal, Usama; Acharya, Binod; Quick, Harrison; Pacífico, Natalia; Berazategui, Romina; Alazraqui, Marcio; Diez Roux, Ana V.
Afiliação
  • Perner MS; Institute of Collective Health, National University of Lanus, Buenos Aires, Argentina. serenaperner@gmail.com.
  • Trotta A; CONICET (National Scientific and Technical Research Council), Buenos Aires, Argentina. serenaperner@gmail.com.
  • Bilal U; Institute of Collective Health, National University of Lanus, Buenos Aires, Argentina.
  • Acharya B; Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, USA.
  • Quick H; Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, USA.
  • Pacífico N; Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, USA.
  • Berazategui R; Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, USA.
  • Alazraqui M; Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, USA.
  • Diez Roux AV; Institute of Collective Health, National University of Lanus, Buenos Aires, Argentina.
Int J Equity Health ; 22(1): 198, 2023 Sep 28.
Article em En | MEDLINE | ID: mdl-37770868
ABSTRACT

BACKGROUND:

The COVID-19 pandemic has shown how intraurban inequalities are likely to reinforce health and social inequalities. Studies at small area level help to visualize social inequialities hidden in large areas as cities or regions.

AIM:

To describe the spatial patterning of COVID-19 death rates in neighborhoods of the medium-sized city of Bariloche, Argentina, and to explore its relationship with the socioeconomic characteristics of neighborhoods.

METHODS:

We conducted an ecological study in Bariloche, Argentina. The outcome was counts of COVID-19 deaths between June 2020 and May 2022 obtained from the surveillance system and georeferenced to neighborhoods. We estimated crude- and age-adjusted death rates by neighborhood using a Bayesian approach through a Poisson regression that accounts for spatial-autocorrelation via Conditional Autoregressive (CAR) structure. We also analyzed associations of age-adjusted death rates with area-level socioeconomic indicators.

RESULTS:

Median COVID-19 death rate across neighborhoods was 17.9 (10th/90th percentile of 6.3/35.2) per 10,000 inhabitants. We found lower age-adjusted rates in the city core and western part of the city. The age-adjusted death rate in the most deprived areas was almost double than in the least deprived areas, with an education-related relative index of inequality (RII) of 2.14 (95% CI 1.55 to 2.96).

CONCLUSION:

We found spatial heterogeneity and intraurban variability in age-adjusted COVID-19 death rates, with a clear social gradient, and a higher burden in already deprived areas. This highlights the importance of studying inequalities in health outcomes across small areas to inform placed-based interventions.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pandemias / COVID-19 Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pandemias / COVID-19 Idioma: En Ano de publicação: 2023 Tipo de documento: Article