| Literature DB >> 33707573 |
Jiayang Jin1,2, Jing Li1,2, Yuzhou Gan1,2, Jiajia Liu1,2, Xiaozhen Zhao1,2, Jiali Chen1,2, Ruijun Zhang1,2, Yan Zhong1,2,3, Xiaomei Chen1,2,3, Lijun Wu3, Xiaohong Xiang1,2, Yunshan Zhou1,2, Jing He1,2, Jianping Guo1,2, Xu Liu1,2, Zhanguo Li4,5,6.
Abstract
Accumulating evidence has implicated dietary factors as important risks for rheumatoid arthritis (RA) development, but analyses of the effects of red meat consumption on RA have yielded diverging results. The aim of this study was to explore the association between red meat and RA in a large-scale, cross-sectional study. From June to December 2016, a total of 733 patients were investigated, from which 707 participants were included in the analysis. These patients were divided into two groups according to their consumption of red meat (< 100 g/day; ≥ 100 g/day). The intake of red meat was assessed via physician-administered questionnaire. Generalized linear models were used to analyze relationships between the red meat intake and RA, adjusting for potential confounders including demographic, clinical, laboratory, and other dietary factors. Compared with low-intake red meat RA patients, high-intake red meat patients had an earlier onset age (p = 0.02) and had higher BMI (p = 0.003). The age at disease onset for the high-intake patients was 6.46 years earlier than for low-intake patients, after adjustment for demographic and other possible confounders (β = - 6.46, 95% CI - 9.77, - 3.15; p = 0.0001). Further, stratified analyses showed that this inverse association of red meat intake with RA onset age was especially evident in smokers and overweight patients (BMI ≥ 24 kg/m2). In conclusion, high-intake red meat is associated with early onset of RA, especially in smokers or overweight patients. The findings indicate that eating less red meat could be a recommendation given to patients at risk for RA development.Entities:
Mesh:
Year: 2021 PMID: 33707573 PMCID: PMC7952581 DOI: 10.1038/s41598-021-85035-6
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379