Evidence map›Paper›PMID 39104756›Full record

ArticleFrontiers in nutrition2024

Association between body fat distribution and asthma in adults: results from the cross-sectional and bidirectional Mendelian randomization study.

Kang Wang, Zhujun Chen, Zhengxiao Wei, Lijun He, Liang Gong

Abstract read
In one paragraph

Article in Frontiers in nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

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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

15 citing papers in PubMed.

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  8. Exploring the Potential Roles ofInternational journal of molecular sciences · 2025
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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.

Kang Wang *Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Army Medical University, Chongqing, China.
Zhujun Chen *Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Army Medical University, Chongqing, China.
Zhengxiao WeiDepartment of Clinical Laboratory, Public Health Clinical Center of Chengdu, Chengdu, China.
Lijun HeDepartment of Ultrasound, The Second Affiliated Hospital of Army Medical University, Chongqing, China.
Liang GongDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Army Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Many studies define obesity based on body mass index (BMI) and explore its relationship with adult asthma. However, BMI only considers height and weight, ignoring other factors such as body fat, which may have a greater impact on health. We investigated the relationship between body fat distribution and adult asthma using both a cross-sectional study and bidirectional Mendelian randomization (MR) analysis. Methods: Weighted logistic regression models were used to examine the relationship between body fat distribution measurements and adult asthma in the cross-sectional study from National Health and Nutrition Examination Survey (NHANES) 2011-2018. Restricted cubic spline (RCS) curves were employed to explore the dose-response relationship between them. The inverse-variance weighted (IVW) method was used as the main method of MR analysis to explore the causal effect of exposure on outcome. Results: After adjusting for all covariates, weighted logistic regression analysis indicated that fat mass in the left arm, left leg, right arm, right leg, trunk, and total body is associated with an increased risk of developing adult asthma ( Conclusion: Our study supports a positive correlation and a unidirectional causality between body fat distribution measurements and the risk of adult asthma. Further studies are needed to validate our findings.

Indexed as

adult asthmabody fat distributioncross-sectional studyfat massMendelian randomization

Identifiers

PMID39104756
PMCPMC11299241

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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.