Evidence map›Paper›PMID 41882668›Full record

ArticleBMC medicine2026

Multimorbidity patterns and 15-year trajectories of physical performance: a population-based study.

Francesco Palmese, Davide Liborio Vetrano, Caterina Gregorio, Amaia Calderón-Larrañaga, Anna-Karin Welmer, Alessandra Marengoni, Giorgio Bedogni, Marco Domenicali, Federico Triolo

Abstract read
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

9 authors.

Francesco PalmeseAging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden. francesco.palmese@ki.se.
Davide Liborio VetranoAging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
Caterina GregorioAging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
Amaia Calderón-LarrañagaAging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
Anna-Karin WelmerAging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
Alessandra MarengoniAging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
Giorgio BedogniDepartment of Medical and Surgical Sciences, Alma Mater Studiorum University of Bologna, Ravenna Campus, Ravenna, Italy.
Marco DomenicaliDepartment of Medical and Surgical Sciences, Alma Mater Studiorum University of Bologna, Ravenna Campus, Ravenna, Italy.
Federico TrioloAging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChronic diseases can impact physical function, yet little is known about how specific disease combinations relate to long-term physical performance trajectories and whether these associations vary across different performance measures. This population-based study explored the association between multimorbidity patterns and 15-year changes in physical performance among older adults.

methodsWe analyzed 15-year longitudinal data on 3112 dementia-free individuals aged 60 and older participating in the Swedish National study on Aging and Care in Kungsholmen. Physical performance was assessed through walking speed and chair-stand tests, further combined into a z-standardized overall measure. Latent class analysis was used to identify groups of individuals with similar patterns of diseases. Linear mixed models were used to evaluate the association between multimorbidity patterns and changes in physical performance scores over time. Inverse probability weighting was used to account for attrition over the follow-up.

resultsFour multimorbidity patterns were identified: 1) psychiatric, respiratory, & musculoskeletal, 2) anemia & sensory impairment, 3) cardiometabolic & inflammatory, and 4) unspecific. Compared to individuals without multimorbidity (≤ 1 disease), all patterns were associated with faster annual declines in physical performance, with the steepest decline observed for the cardiometabolic & inflammatory pattern (β*time = -0.066, 95%CI: -0.111, -0.021), followed by the anemia & sensory impairment pattern (β*time = -0.043, 95%CI: -0.063, -0.023). Results remained consistent after adjustment for the number of chronic diseases.

conclusionsMultimorbidity patterns are differentially associated with the rate of decline in physical performance, with the cardiometabolic & inflammatory pattern being associated with the fastest decrease. Classifying individuals according to multimorbidity patterns may help guide targeted strategies to preserve physical function in later life.

Indexed as

MultimorbidityPhysical Functional PerformanceAgedAged, 80 and overAgingChronic DiseaseFemaleHumansLongitudinal StudiesMaleMiddle AgedSwedenAgingChair stand testFunctional declineMultimorbidity patternsPersonalized medicinePhysical performancePopulation-based studyWalking speed

Identifiers

PMID41882668
PMCPMC13063542

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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.