Evidence map›Paper›PMID 40059170›Full record

ArticleBMC medicine2025

Smoking-related gut microbiota alteration is associated with obesity and obesity-related diseases: results from two cohorts with sibling comparison analyses.

Yiting Duan, Chengquan Xu, Wenjie Wang, Xiaoyan Wang, Nuo Xu, Jieming Zhong, Weiwei Gong, Weifang Zheng, Yi-Hsuan Wu, April Myers and 7 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. SupragingivalJournal of oral microbiology · 2026
    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

17 authors.

Yiting Duan *Department of Nutrition and Food Hygiene, Children'S Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China.
Chengquan Xu *Department of Nutrition and Food Hygiene, Children'S Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China.
Wenjie WangDepartment of Nutrition and Food Hygiene, Children'S Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China.
Xiaoyan WangDepartment of Nutrition and Food Hygiene, Children'S Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China.
Nuo XuDepartment of Nutrition and Food Hygiene, Children'S Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China.
Jieming ZhongDepartment of NCDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, 3399 Bin-Sheng Road, Hangzhou, Zhejiang, 310051, China.
Weiwei GongDepartment of NCDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, 3399 Bin-Sheng Road, Hangzhou, Zhejiang, 310051, China.
Weifang ZhengLanxi Red Cross Hospital, Lanxi, Zhejiang, 321102, China.
Yi-Hsuan WuDepartment of Medicine, Stanford Prevention Research Center, Stanford School of Medicine, Stanford University, Palo Alto, CA, 94304, USA.
April MyersDepartment of Medicine, Stanford Prevention Research Center, Stanford School of Medicine, Stanford University, Palo Alto, CA, 94304, USA.
Lisa ChuDepartment of Medicine, Stanford Prevention Research Center, Stanford School of Medicine, Stanford University, Palo Alto, CA, 94304, USA.
Ying LuDepartment of Biomedical Data Sciences, Stanford School of Medicine, Stanford University, Palo Alto, CA, 94305, USA.
Elizabeth DelzellDepartment of Medicine, Stanford Prevention Research Center, Stanford School of Medicine, Stanford University, Palo Alto, CA, 94304, USA.
Ann W HsingDepartment of Medicine, Stanford Prevention Research Center, Stanford School of Medicine, Stanford University, Palo Alto, CA, 94304, USA.
Min YuDepartment of NCDs Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, 3399 Bin-Sheng Road, Hangzhou, Zhejiang, 310051, China. myu@cdc.zj.cn.
Wei HeDepartment of Nutrition and Food Hygiene, Children'S Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China. zjuhewei@zju.edu.cn.
Shankuan ZhuDepartment of Nutrition and Food Hygiene, Children'S Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China. zsk@zju.edu.cn.

Funding

"Pioneer" and "Leading Goose" R&D Program of Zhejiang Grant No. 2024C03180the National Key R&D Program of China Grant No. 2022YFC2705300the National Key R&D Program of China Grant No. 2022YFC2705303
6 · The paper itself

Abstract

backgroundIndividuals who smoke tend to have a lower body mass index (BMI) but face an increased risk of obesity-related diseases. This study investigates this paradox from the perspective of gut microbiota.

methodsWe conducted microbiome analyses to identify smoking-related microbial genera and created a smoking-related microbiota index (SMI) using 16S rRNA sequencing data from 4000 male participants in WELL-China cohort and Lanxi cohort. We employed logistic regression to explore the association between SMI and obesity indices derived from dual-energy X-ray absorptiometry. Cox regression analyses were conducted to explore the association of SMI with incident of obesity-related diseases. To further control for unmeasured familial confounders, sibling comparison analyses were conducted using between-within (BW) model.

resultsThe smoking-related microbiota index (SMI) showed a positive association with BMI and other obesity indices. Further analyses revealed that SMI is linked to obesity-related diseases, with hazard ratios (95% confidence intervals) of 1.97 (1.41-2.75) for incident diabetes, 1.31 (1.01-1.71) for major adverse cardiovascular events, and 1.70 (1.05-2.75) for obesity-related cancers. Results from sibling comparison analyses reinforced these findings.

conclusionsWhile smoking may reduce weight through various mechanisms, alterations in gut microbiota related to smoking are associated with weight gain. Further research is required to determine if changes in the smoking-related microbiome contribute to weight gain following smoking cessation.

Indexed as

Gastrointestinal MicrobiomeObesitySmokingAdultBody Mass IndexCardiovascular DiseasesChinaCohort StudiesHumansMaleMiddle AgedRNA, Ribosomal, 16SSiblingsRNA, Ribosomal, 16SGut microbiotaObesityObesity-related diseaseSmoking

Identifiers

PMID40059170
PMCPMC11892230

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.