Evidence map›Paper›PMID 39502295›Full record

ArticleFrontiers in psychiatry2024

The relationship between BMI and depression: a cross-sectional study.

Hongyu Cui, Ying Xiong, Chengmin Wang, Jiaming Ye, Weisen Zhao

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

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  6. [Correlational research on body fat rate and skeletal muscle rate with depression in the population of assisted reproduction].Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · 2026
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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

5 authors.

Hongyu Cui *Department of Psychiatry, the First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Ying Xiong *Department of Dermatology and Venereology, Shenzhen Longgang Center for Chronic Disease Control, Shenzhen, Guangdong, China.
Chengmin WangDepartment of Mental Health, Shenzhen Longgang Center for Chronic Disease Control, Shenzhen, Guangdong, China.
Jiaming YeDepartment of Biobank, Suzhou Center for Disease Control and Prevention, Suzhou, Jiangsuu, China.
Weisen ZhaoDepartment of Mental Health, Shenzhen Longgang Center for Chronic Disease Control, Shenzhen, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Mental health problems, especially depressive symptoms, are becoming increasingly prominent, posing a significant risk to public health. Changes in the body mass index (BMI) may impact an individual's mental health, however, the relationship between BMI and depressive symptoms is unclear. The purpose of this study was to investigate the association between BMI and depressive symptoms. Methods: Using a multi-stage sampling method, 10,686 adults in Longgang District, Shenzhen City, Guangdong Province, China, were selected for participation in this study. Surveys were distributed in 2020 and 2021 to measure participant demographic data and health. Binary logistic regression, restricted cubic spline regression, and subgroup analyses were performed to explore the relationship between BMI and depressive symptoms. Results: The results showed a U-shaped relationship between BMI and depression. Both obesity and underweight increased the risk of depression among the participants, especially in subgroups of participants who were young, highly educated, single and employed. Conclusion: These findings suggest that adults should try to maintain a normal body weight as a way to prevent depression and maintain their physical and mental health.

Indexed as

body mass indexdepressionrelationshiprestricted cubic splinerisk factorsubgroup analysis

Identifiers

PMID39502295
PMCPMC11534730

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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.