The Association of Mixed Mineral Intake Exposure With Gout: A National Cross‐Sectional National Health and Nutrition Examination Survey ( NHANES ) Study

Minerals influence urate production, renal clearance, oxidative stress, and systemic inflammation, yet epidemiologic evidence linking mineral intake to gout is limited and rarely considers co‐exposures. We analyzed six NHANES cycles (2007–2018) comprising 22,661 adults ≥ 20 years. After 1:1 propensity‐score matching, usual intakes of nine dietary minerals were divided into quartiles. Survey‐weighted multivariable logistic regression quantified single‐mineral associations with gout. Weighted quantile sum (WQS) regression, quantile g‐computation (qgcomp), and Bayesian kernel machine regression (BKMR) evaluated combined effects and potential interactions. In logistic regression analysis, only calcium showed a consistent inverse, dose‐dependent relation with gout. For the highest versus lowest calcium quartile, the ORs were 0.55 (95% CI 0.37–0.81, p = 0.003) in Model 1, 0.52 (95% CI 0.36–0.77, p = 0.001) in Model 2, and 0.51 (95% CI 0.36–0.74, p < 0.001) in Model 3. No significant associations were observed for phosphorus, magnesium, zinc, iron, copper, potassium, selenium, or sodium (all p > 0.05). In mixture analyses, the mineral index was inversely associated with gout: WQS‐OR = 0.88 (95% CI 0.78–0.99) and qgcomp‐OR = 0.87 (95% CI 0.79–0.97). BKMR confirmed an overall inverse exposure‐response function for the combined minerals and identified calcium as the dominant contributor (posterior inclusion probability 0.72). Pair‐wise response surfaces showed no consistent synergistic or antagonistic interactions. Greater calcium intake was associated with reduced gout prevalence in US adults. These findings highlight calcium‐rich foods, particularly low‐fat dairy products, as potential components of gout‐preventive dietary strategies and underscore the utility of mixture modeling for clarifying complex nutritional exposures. Prospective studies are warranted to confirm causality and elucidate underlying mechanisms.