Keywords
Rheumatoid arthritis
NHANES
Categories
Data Availability Statement
The datasets utilized in the present study can be accessed from the NHANES database at https://wwwn.cdc.gov/nchs/nhanes/.
How to Cite
Abstract
Objective: To examine the association between blood and urine heavy metal concentrations and the risk of rheumatoid arthritis (RA) in U.S. adults using data from the National Health and Nutrition Examination Survey (NHANES) 2011-2020. Methods: We analyzed data from 5,530 participants aged ≥20 years. Heavy metal levels (blood cadmium, blood mercury, urine lead) were measured via mass spectrometry, and RA was diagnosed based on self-reported physician diagnosis. Multivariate logistic regression models were used to assess the relationship between heavy metals and RA risk, adjusting for potential confounders including age, gender, BMI (body mass index), race, education level, marital status, smoking history, diabetes history, hypertension history, coronary heart disease history, and serum albumin levels. Subgroup analyses, interaction tests, and mediation analysis were also conducted. Results: Elevated blood cadmium levels (OR = 1.23, 95% CI: 1.05-1.44) and urine lead levels (OR = 1.31, 95% CI: 1.09-1.57) were positively associated with RA risk, while higher blood mercury levels were negatively associated (OR = 0.78, 95% CI: 0.67-0.91). Dose-response relationships were observed for these metals. The negative correlation between blood mercury and RA was stronger among non-smokers and individuals with diabetes (P<.05 for interaction). Mediation analysis revealed that serum albumin did not mediate the associations between heavy metals and RA risk. Conclusion: Elevated blood cadmium and urine lead levels are associated with increased RA risk, whereas higher blood mercury levels are associated with reduced risk. These relationships are influenced by smoking and diabetes status and appear to be independent of serum albumin levels. Further prospective studies are needed to establish causality and explore the underlying mechanisms.
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