Digitala Vetenskapliga Arkivet

Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Individual and neighborhood risk factors of hospital admission and death during the COVID-19 pandemic: a population-based cohort study
Stockholms universitet, Samhällsvetenskapliga fakulteten, Centrum för forskning om äldre och åldrande (ARC), (tills m KI). Center for Epidemiology and Community Medicine, Sweden.ORCID-id: 0000-0003-2656-8721
Vise andre og tillknytning
Rekke forfattare: 62023 (engelsk)Inngår i: BMC Medicine, E-ISSN 1741-7015, Vol. 21, nr 1, artikkel-id 1Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Background: The coronavirus disease 2019 (COVID-19) disproportionately affects minority populations in the USA. Sweden — like other Nordic countries — have less income and wealth inequality but lacks data on the socioeconomic impact on the risk of adverse outcomes due to COVID-19.

Methods: This population-wide study from March 2020 to March 2022 included all adults in Stockholm, except those in nursing homes or receiving in-home care. Data sources include hospitals, primary care (individual diagnoses), the Swedish National Tax Agency (death dates), the Total Population Register “RTB” (sex, age, birth country), the Household Register (size of household), the Integrated Database For Labor Market Research “LISA” (educational level, income, and occupation), and SmiNet (COVID data). Individual exposures include education, income, type of work and ability to work from home, living area and living conditions as well as the individual country of origin and co-morbidities. Additionally, we have data on the risks associated with living areas. We used a Cox proportional hazards model and logistic regression to estimate associations. Area-level covariates were used in a principal component analysis to generate a measurement of neighborhood deprivation. As outcomes, we used hospitalization and death due to COVID-19.

Results: Among the 1,782,125 persons, male sex, comorbidities, higher age, and not being born in Sweden increase the risk of hospitalization and death. So does lower education and lower income, the lowest incomes doubled the risk of death from COVID-19. Area estimates, where the model includes individual risks, show that high population density and a high percentage of foreign-born inhabitants increased the risk of hospitalization.

Conclusions: Segregation and deprivation are public health issues elucidated by COVID-19. Neighborhood deprivation, prevalent in Stockholm, adds to individual risks and is associated with hospitalization and death. This finding is paramount for governments, agencies, and healthcare institutions interested in targeted interventions.

sted, utgiver, år, opplag, sider
2023. Vol. 21, nr 1, artikkel-id 1
Emneord [en]
COVID-19, Socioeconomics, Population study, Cohort study, Stockholm, Epidemiology, Hospitalization, Mortality
HSV kategori
Identifikatorer
URN: urn:nbn:se:su:diva-223981DOI: 10.1186/s12916-022-02715-4ISI: 001092330800001PubMedID: 36600273Scopus ID: 2-s2.0-85145541779OAI: oai:DiVA.org:su-223981DiVA, id: diva2:1814366
Tilgjengelig fra: 2023-11-24 Laget: 2023-11-24 Sist oppdatert: 2023-11-24bibliografisk kontrollert

Open Access i DiVA

Fulltekst mangler i DiVA

Andre lenker

Forlagets fulltekstPubMedScopus

Søk i DiVA

Av forfatter/redaktør
Bell, MaxFors, Stefan
Av organisasjonen
I samme tidsskrift
BMC Medicine

Søk utenfor DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric

doi
pubmed
urn-nbn
Totalt: 20 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf