Evidence map›Paper›PMID 36735844›Full record

ArticleAge and ageing2023

Late-life depression and multimorbidity trajectories: the role of symptom complexity and severity.

Federico Triolo, Linnea Sjöberg, Amaia Calderón-Larrañaga, Martino Belvederi Murri, Davide Liborio Vetrano, Laura Fratiglioni, Serhiy Dekhtyar

Open access · hybridAbstract read
In one paragraph

Article in Age and ageing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
9.5field-weighted citation impact, top 1% of its field
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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.

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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 at 2 institutions in 3 countries.

Federico TrioloAging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.ORCID 0000-0002-8732-0036
Linnea SjöbergAging 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.
Martino Belvederi MurriInstitute of Psychiatry, Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara, Italy.
Davide Liborio VetranoAging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
Laura FratiglioniAging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
Serhiy DekhtyarAging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
Stockholm University · SEUniversity of Ferrara · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionas late-life depression is associated with poor somatic health, we aimed to investigate the role of depression severity and symptom phenotypes in the progression of somatic multimorbidity.

methodswe analysed data from 3,042 dementia-free individuals (60+) participating in the population-based Swedish National Study on Aging and Care in Kungsholmen. Using the baseline clinical assessment of 21 depressive symptoms from the Comprehensive Psychopathological Rating Scale, we: (i) diagnosed major, minor (in accordance with DSM-IV-TR) and subsyndromal depression; (ii) extracted symptom phenotypes by applying exploratory network graph analysis. Somatic multimorbidity was measured as the number of co-occurring chronic diseases over a 15-year follow-up. Linear mixed models were used to explore somatic multimorbidity trajectories in relation to baseline depression diagnoses and symptom phenotypes, while accounting for sociodemographic and behavioural factors.

resultsin multi-adjusted models, relative to individuals without depression, those with major (β per year: 0.33, 95% confidence interval [CI]: 0.06-0.61) and subsyndromal depression (β per year: 0.21, 95%CI: 0.12-0.30) experienced an accelerated rate of somatic multimorbidity accumulation, whereas those with minor depression did not. We identified affective, anxiety, cognitive, and psychomotor symptom phenotypes from the network analysis. When modelled separately, an increase in symptom score for each phenotype was associated with faster multimorbidity accumulation, although only the cognitive phenotype retained its association in a mutually adjusted model (β per year: 0.07, 95%CI: 0.03-0.10).

conclusionslate-life major and subsyndromal depression are associated with accelerated somatic multimorbidity. Depressive symptoms characterised by a cognitive phenotype are linked to somatic health change in old age.

Indexed as

DepressionMultimorbidityAnxietyAnxiety DisordersChronic DiseaseHumanscomorbiditydepressionepidemiologylongitudinalolder peoplepsychosomaticsymptom network

Identifiers

PMID36735844
PMCPMC9897302
OpenAlexW4319073320

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.