Evidence map›Paper›PMID 37608084›Full record

ArticleScientific reports2023

Socioeconomic inequities of COVID-19 mortality in vulnerable Comunas of the City of Buenos Aires.

Agustina M Marconi, Carlos Castillo Salgado, Elena Beatriz Sarrouf, Rafael Jose Zamora, Alejandra Maria Irurzun, Nazrul Islam

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Agustina M MarconiUniversity Health Services, University of Wisconsin Madison, 333 East Campus Mall, Madison, WI, 53715, USA. agustina.marconi@wisc.edu.
Carlos Castillo SalgadoDepartment of Epidemiology at, Johns Hopkins University, 615 N Wolfe St, Baltimore, MD, 21205, USA.
Elena Beatriz SarroufDirection of Epidemiology, Province of Tucuman, Virgen de la Merced 196, San Miguel de Tucumán, Tucumán, Argentina.
Rafael Jose ZamoraMedicus, Larrea 877, Buenos Aires, Argentina.
Alejandra Maria IrurzunSub-Secretary of Primary, Ambulatory and Community Care of the CABA, Monasterio 480, 1283, Buenos Aires, Argentina.
Nazrul IslamFaculty of Medicine, University of Southampton, Southampton, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During the COVID-19 pandemic, the gap in health inequities was exposed and increased, showing how different vulnerable groups were affected. Our aim was to examine the correlation between an area-based health inequity index and mortality due to COVID-19 in people 60 years old or above in the City of Buenos Aires in 2020. We developed a Health Inequity Composite Index (HICI), including six core indicators. Each indicator value per Comuna was first standardized to a Z-score. All six Z-scores were summed into a final composite Z-score to rank the Comunas from lowest to highest social inequities. Comunas from the northern part of the city had lower inequities whereas those in the south had higher levels of inequities. COVID-19 age-standardized mortality rate in people 60 years or above was higher in the Comunas from the south and lower in those from the north. Finally, we found a strong positive correlation (Rho = 0.83, p < 0.0001 CI95% = 0.65-0.99) between HICI and age-standardized mortality rates from COVID-19 in people 60 years or above. Our finding of a strong correlation between the levels of health inequity and mortality calls for a concerted effort in narrowing or eliminating existing inequities.

Indexed as

COVID-19HumansMiddle AgedPandemicsSocioeconomic Factors

Identifiers

PMID37608084
PMCPMC10444792

What OpenQuestion holds

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.