Evidence map›Paper›PMID 38912261›Full record

ArticleFrontiers in public health2024

The exposure to volatile organic compounds associate positively with overactive bladder risk in U.S. adults: a cross-sectional study of 2007-2020 NHANES.

Dawen Zhang, Ziyi Yan, Junhao He, Yunmin Yao, Kai Liu

Abstract read
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Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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.

Dawen Zhang *Department of Urology, The Fifth People's Hospital of Wujiang District, Suzhou, China.
Ziyi Yan *Department of Urology, The Fifth People's Hospital of Wujiang District, Suzhou, China.
Junhao HeDepartment of Urology, The Fifth People's Hospital of Wujiang District, Suzhou, China.
Yunmin YaoDepartment of Urology, The Fifth People's Hospital of Wujiang District, Suzhou, China.
Kai LiuDepartment of Urology, The Fifth People's Hospital of Wujiang District, Suzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The aim of this study was to comprehensively investigate the potential relationship between blood volatile organic compounds (VOCs) and overactive bladder (OAB) risk. Methods: A total of 11,183 participants from the 2007-2020 National Health and Nutrition Examination Survey (NHANES) were included in this cross-sectional study. We used multivariate logistic regression models to investigate the relationship between nine blood VOCs and OAB risk. Restricted cubic spline (RCS) analysis was used to investigate the dose-response relationship between blood VOCs and OAB. In addition, the overall association of blood VOCs with OAB risk was assessed by weighted quantile sum (WQS) regression model. Finally, we conducted subgroup analyses to explore the findings in different high-risk populations. Results: After adjusting for potential confounders, logistic regression analysis revealed that blood 2,5-dimethylfuran (aOR = 2.940, 95% CI: 1.096-7.890, Conclusions: The results of this study indicate that high exposure to VOCs is independently and positively associated with OAB risk in U.S. adults, particularly 2,5-dimethylfuran, benzene, and furan. In addition, age, gender, hypertension and alcohol consumption may influence the association. Our study provided novel epidemiologic evidence to explore the potential role of environmental pollutants in OAB.

Indexed as

Nutrition SurveysUrinary Bladder, OveractiveVolatile Organic CompoundsAdultAgedCross-Sectional StudiesEnvironmental ExposureFemaleHumansLogistic ModelsMaleMiddle AgedRisk FactorsUnited StatesVolatile Organic Compoundscross-sectional studiesenvironmental pollutionNational Health and Nutrition Examination Surveyoveractive bladdervolatile organic compounds (VOCs)

Identifiers

PMID38912261
PMCPMC11190323

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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.