Evidence map›Paper›PMID 41732684›Full record

ArticleJournal of public health research2026

Association between the number of comorbidities and all-cause mortality during the COVID-19 pandemic: A Danish nationwide, retrospective cohort study.

Virginia Zarulli, Cosmo Strozza, Silvia Rizzi

Abstract read
In one paragraph

Article in Journal of public health research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Virginia ZarulliCPop, Interdisciplinary Center for Population Dynamics, University of Southern Denmark, Odense, Denmark.ORCID https://orcid.org/0000-0003-3219-4658
Cosmo StrozzaCPop, Interdisciplinary Center for Population Dynamics, University of Southern Denmark, Odense, Denmark.ORCID https://orcid.org/0000-0001-8825-2971
Silvia RizziCPop, Interdisciplinary Center for Population Dynamics, University of Southern Denmark, Odense, Denmark.ORCID https://orcid.org/0000-0002-3512-2361

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Chronic illnesses have been linked to elevated risks of hospitalization and mortality during the COVID 19 pandemic. While many studies have examined how specific comorbidities influence outcomes among hospitalized COVID 19 patients, less is known about how the pandemic affected all cause mortality among comorbid individuals in the general population. Our objective is to assess how the number of pre pandemic comorbidities interacted with COVID 19 and whether all cause mortality risks for individuals with comorbidities changed during the pandemic. Methods: This is a population-based retrospective cohort study, where we analyzed the entire Danish population aged 45 years and older using nationwide registry data. We examined COVID 19 specific and non COVID 19 mortality in 2020-2021 to capture both direct and indirect pandemic effects. Survival analysis techniques were applied to estimate mortality patterns across comorbidity levels. Results: Kaplan-Meier curves indicated that traditional comorbidity gradients persisted for non COVID mortality, whereas COVID 19 mortality showed a relative equalization across comorbidity groups. Gender and educational disparities remained evident. Conclusion: The findings highlight the need for preparedness strategies that protect medically vulnerable groups while addressing persistent social inequalities. They also demonstrate the importance of population wide approaches for understanding the full mortality impact of pandemics.

Indexed as

agingcomorbiditiesCOVID-19Denmarkmortality

Identifiers

PMID41732684
PMCPMC12924997

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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 OpenQuestion graph.