| Title: | Associations of diet with infectious diseases in UK Biobank |
| Journal: | Journal of Biomedical Research |
| Published: | 25 May 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38807412/ |
| DOI: | https://doi.org/10.7555/jbr.37.20230319 |
| URL: | http://www.jbr-pub.org.cn/en/article/pdf/preview/10.7555/JBR.37.20230319.pdf |
Publication 11982
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Abstract
This research aims to utilize multivariate logistic regression to explore associations between the frequency of 13 food groups intake (or four diet groups) and infectious diseases. 487849 participants from the UK Biobank were enrolled, and 75209 participants were diagnosed with infectious diseases. Participants reporting the highest intake frequency of processed meat [odds ratio ( OR) = 1.0964; 95% CI: 1.0622-1.1318] and red meat ( OR = 1.0895; 95% CI: 1.0563-1.1239) had a higher risk of infectious diseases compared to those with the lowest intake frequency. Consuming fish 2.0-2.9 times ( OR = 0.8221; 95% CI: 0.7955-0.8496), cheese ≥5.0 times ( OR = 0.8822; 95% CI: 0.8559-0.9092), fruit 3.0-3.9 servings ( OR = 0.8867; 95% CI: 0.8661-0.9078), and vegetables 2.0-2.9 servings ( OR = 0.9372; 95% CI: 0.9189-0.9559) per week were associated with a lower risk of infection. Low meat-eaters ( OR = 0.9404; 95% CI: 0.9243-0.9567), fish-eaters ( OR = 0.8391; 95% CI: 0.7887-0.8919), and vegetarians ( OR = 0.9154; 95% CI: 0.8561-0.9778) had a lower risk of infectious diseases compared to regular meat-eaters. Mediation analysis was performed, revealing glycosylated hemoglobin, white blood cell counts, and body mass index were mediators in the relationships between diet groups and infectious diseases. This study suggested that intake frequency of food groups is a factor in infectious diseases and fish-eaters have a lower risk of infection.</p>
8 Authors
- Junlan Tu
- Xuehong Cai
- Yifan Wang
- Xiangyu Ye
- Meijie Yu
- Sheng Yang
- Rongbin Yu
- Peng Huang
1 Application
| Application ID | Title |
|---|---|
| 67665 | Developing scalable computational tools for understanding polygenic trait architectures in large-scale genome-wide association studies |
Enabling scientific discoveries that improve human health