Evidence map›Paper›PMID 42006759›Full record

ArticleBMJ public health2026

Intersectional inequalities in COVID-19 morbidity and mortality in Sweden: a retrospective population-based cohort study.

Helena Honkaniemi, Sol P Juárez

Abstract read
In one paragraph

Article in BMJ public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Helena HonkaniemiDepartment of Public Health Sciences, Stockholm University, Stockholm, Sweden.ORCID https://orcid.org/0000-0003-0800-0892
Sol P JuárezDepartment of Public Health Sciences, Stockholm University, Stockholm, Sweden.ORCID https://orcid.org/0000-0001-9086-7588

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: During the global pandemic, the elderly, foreign-born and socioeconomically deprived experienced disproportionately higher rates of COVID-19 morbidity and mortality than general populations. However, these groups have typically been analysed in isolation, without considering how social factors jointly influenced COVID-19-related health. Thus, the aim of this study is to quantify intersectional inequalities in COVID-19 morbidity and mortality in Sweden. Methods: In this retrospective cohort study, national registers were used to identify 35-to-100-year-old residents of Sweden in January 2020 (n=6 014 164), tracking COVID-19 hospitalisations and deaths (International Classification of Diseases-10 Codes U07.1/U07.2, plus B34.2 for deaths) until December 2022. Intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy was applied with logistic regression, nesting individuals within intersectional strata based on age, gender, migrant status and region of origin, and income. Measures of discriminatory accuracy (area under the receiver operating characteristic curve or AUC), predicted probabilities and random effects were calculated. Results: During follow-up, 77 844 (1.29%) individuals were hospitalised and 18 126 (0.30%) died due to COVID-19. Intersectional models explained 2.22% of the variation in mortality (AUC=0.835) vs 0.60% in hospitalisations (AUC=0.728). Predicted probabilities were lowest in 35-44-year-old Swedish-born women with high income at 0.19% (95% CI 0.16% to 0.21%) for hospitalisations, and 0.01% (95% CI 0.01% to 0.02%) for mortality; and highest among 85-100-year-old foreign-born men from the Global South with low income at 14.85% (95% CI 12.84% to 17.10%) for hospitalisations, and 8.25% (95% CI 6.32% to 10.70%) for mortality. Random effects indicated wider income inequalities in both outcomes in the youngest and narrower in the oldest, native-born and foreign-born groups from the Global North. Conclusions: Intersectional inequalities in COVID-19 outcomes consistently increased with age, decreased with income and were higher for men and foreign-born individuals. The results emphasise the need to consider universal public health strategies to reach vulnerable populations during a pandemic.

Indexed as

COVID-19EpidemiologyPublic HealthSocial Medicine

Identifiers

PMID42006759
PMCPMC13084887

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Registered trials

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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 Socratic graph.