ArticleReviews in cardiovascular medicine2024
The Cumulative and Single Effect of 12 Aldehydes Concentrations on Cardiovascular Diseases: An Analysis Based on Bayesian Kernel Machine Regression and Weighted Logistic Regression.
Article in Reviews in cardiovascular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
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Who cites it
1 citing paper in PubMed.
- An Exploration of Machine Learning Methods in Human Biomonitoring.International journal of environmental research and public health · 2026Review
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: This study investigates the individual and cumulative effects of 12 aldehydes concentrations on cardiovascular disease (CVD). Methods: A total of 1529 individuals from the 2013-2014 National Health and Nutrition Examination Survey were enrolled. We assessed serum concentrations of 12 aldehydes, including benzaldehyde, butyraldehyde, crotonaldehyde, decanaldehyde, heptanaldehyde, hexanaldehyde, isopentanaldehyde, nonanaldehyde, octanaldehyde, o-tolualdehyde, pentanaldehyde, and propanaldehyde. CVD patients were identified based on self-reported disease history from questionnaires. The Bayesian kernel machine regression was used to evaluate the cumulative effect of 12 aldehyde concentrations on CVD. Both weighted and unweighted logistic regression were used to assess the association of serum aldehyde concentrations with CVD, presenting effect sizes as odds ratio (OR) with 95% confidence interval (CI). Additionally, a restricted cubic spline analysis was also conducted to explore the relationship between benzaldehyde and CVD. Results: Among the participants, 111 (7.3%) were identified as having CVD. Isopentanaldehyde concentrations were notably higher in CVD patients compared to those without CVD. Bayesian kernel machine regression indicated no cumulative effect of aldehydes on CVD. Unweighted logistic regression revealed a positive association between benzaldehyde and CVD when adjusting for age and sex (OR = 1.12, 95% CI = 1.03-1.21). This association persisted after adjusting for age, sex, race, education, hypertension, diabetes, alcohol consumption, and smoking, with an OR of 1.12 (95% CI = 1.02-1.22). The restricted cubic spline showed a linear association between benzaldehyde and CVD. In the weighted logistic model, the association between benzaldehyde and CVD remains significant (OR = 1.17, 95% CI = 1.06-1.29). However, no significant association was found between other aldehydes and CVD. Conclusions: Our study reveals the potential contributing role of benzaldehyde to CVD. Future studies should further validate these findings in diverse populations and elucidate the underlying biological mechanisms.
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