Evidence map›Paper›PMID 41788343›Full record

ArticleJournal of multimorbidity and comorbidity

Multimorbidity patterns and their associations with patient-perceived treatment burden: A latent class analysis of 14,344 Danish adults.

Marie Hauge Pedersen, Mathias Lasgaard, Camilla Palmhøj Nielsen, Anders Prior, Polly Duncan, Stine Schramm, Finn Breinholt Larsen

Abstract read
In one paragraph

Article in Journal of multimorbidity and comorbidity. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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

7 authors.

Marie Hauge PedersenDEFACTUM - Public Health Research, Central Denmark Region, Aarhus, Denmark.ORCID https://orcid.org/0000-0001-8472-0555
Mathias LasgaardDEFACTUM - Public Health Research, Central Denmark Region, Aarhus, Denmark.ORCID https://orcid.org/0000-0001-5808-8883
Camilla Palmhøj NielsenDEFACTUM - Public Health Research, Central Denmark Region, Aarhus, Denmark.ORCID https://orcid.org/0000-0001-9199-3463
Anders PriorDepartment of Public Health, Aarhus University, Aarhus, Denmark.ORCID https://orcid.org/0000-0003-4053-3701
Polly DuncanCentre for Academic Primary Care, University of Bristol, Bristol, UK.
Stine SchrammNational Institute of Public Health, University of Southern Denmark, Odense, Denmark.ORCID https://orcid.org/0000-0001-8039-8095
Finn Breinholt LarsenDEFACTUM - Public Health Research, Central Denmark Region, Aarhus, Denmark.ORCID https://orcid.org/0000-0002-6848-123X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To identify population groups with distinct multimorbidity patterns and to examine their associations with high treatment burden. Methods: Latent class analysis was conducted using cross-sectional, self-reported data on 16 long-term conditions from Danish adults aged 25 years and older in treatment (N = 14,344), drawn from the Danish National Health Survey. Treatment burden was assessed using the Multimorbidity Treatment Burden Questionnaire, and associations between identified multimorbidity patterns and high treatment burden (score ≥22) were examined using a bias-adjusted three-step approach. Results: Eight latent classes were identified: 1 Conclusion: Specific multimorbidity patterns were strongly associated with high treatment burden. These findings may inform healthcare planning, resource allocation, and tailored interventions to reduce treatment burden.

Indexed as

comorbiditycross-sectional surveylatent class analysismultimorbiditypublic health

Identifiers

PMID41788343
PMCPMC12957603

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.