Evidence map›Paper›PMID 36427648›Full record

SynthesisJournal of affective disorders2023

Association of metabolic syndrome and its components with the risk of depressive symptoms: A systematic review and meta-analysis of cohort studies.

Hong-Bae Kim, Bethany J Wolf, Jung-Ha Kim

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Journal of affective disorders, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

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  14. The association of the comorbidity status of metabolic syndrome and cognitive dysfunction with health-related quality of life.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024
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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

3 authors.

Hong-Bae KimDepartment of Family Medicine, Myongji Hospital, Hanyang University, College of Medicine, Goyang, Republic of Korea.
Bethany J WolfDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, United States.
Jung-Ha KimDepartment of Family Medicine, Chung-ang University Medical Center, Chung-ang University, College of Medicine, Seoul, Republic of Korea. Electronic address: girlpower219@cau.ac.kr.

Funding

South Carolina Clinical & Translational Research Institute (SCTR)UL1TR001450 · NCATS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI BRADY, KATHLEEN T., FLUME, PATRICK A · 2015 to 2024
$41.1M
NCATS NIH HHS UL1 TR001450
6 · The paper itself

Abstract

backgroundThe purpose of this meta-analysis was to quantitatively analyze the association between metabolic syndrome (MetS) and the risk of depressive symptoms.

methodsThree electronic databases (PubMed, Embase, and PsycINFO) were searched for articles published through February 15, 2022. Cohort studies evaluating the association between MetS and depressive symptoms were selected for inclusion in this study. A random-effects model was used to evaluate the pooled estimates of MetS, including each of its components, associated with depressive symptoms.

resultsA total of 11 cohort studies were selected including >2.65 million participants. There was a significant association between MetS and depressive symptoms risk, albeit with a high degree of heterogeneity (relative risk = 1.29, 95 % confidence interval: 1.12-1.48; I

conclusionsMetS is a risk factor for depressive symptoms. Further large-scale prospective cohort studies are required to confirm our findings.

Indexed as

Metabolic SyndromeAsiaDepressionHumansProspective StudiesRisk FactorsDepressive symptomsmeta-analysisMetabolic syndromeObservational cohort study

Identifiers

PMID36427648
PMCPMC10252993

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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.