Gout is a common metabolic inflammatory arthropathy, and its growing burden parallels changes in dietary patterns. However, the independent effect of processed meat intake on gout risk and its underlying mechanisms remain unclear. This study aimed to examine the association between processed meat intake and incident gout and explore underlying mechanisms using epidemiology, machine learning, and plasma proteomics.

This prospective cohort study included 395,398 UK Biobank participants free of gout at baseline. Processed meat intake was categorized into low, middle, and high levels based on self-reported consumption frequency. Multivariable Cox proportional hazards models were used to evaluate associations between processed meat intake and incident gout, with further adjustment for socioeconomic status (SES), lifestyle patterns, and relevant covariates. To better account for longitudinal dietary changes, time-varying Cox models were additionally performed in participants with repeat assessments. SES and lifestyle factors were analyzed both independently and jointly with processed meat intake. To evaluate the relative importance of behavioral determinants in relation to gout occurrence, four supervised machine-learning models, including random forest, XGBoost, LASSO, and neural network, were further applied. In a proteomic subset, plasma proteomic analyses were conducted to identify proteins and biological pathways jointly associated with processed meat intake and gout.

During a mean follow-up of 15.7 years, 8,215 participants developed incident gout. Higher processed meat intake was independently associated with greater gout risk after adjustment for SES, lifestyle, and other covariates. Compared with low intake, middle and high intake were associated with 15% and 23% higher risks of gout, respectively. In time-varying Cox models incorporating repeated dietary assessments, the corresponding risk increases were more pronounced, reaching 62% and 101%, respectively. Lower SES and unfavorable lifestyle profiles were also independently associated with elevated gout risk, and joint analyses showed that individuals with both lower SES and higher processed meat intake or less healthy lifestyles experienced the greatest risk. Across four supervised machine-learning models, processed meat intake consistently ranked among the leading behavioral determinants of gout. Proteomic analyses identified 40 circulating plasma proteins jointly associated with processed meat intake and gout, with enrichment patterns suggesting metabolic dysregulation, heightened inflammatory activity, and neuroendocrine disturbance. Among these, PSPN, CALCA, and MMP3 were consistently highlighted across all four models as key candidate proteins linking processed meat intake to gout.

These findings establish processed meat as a distinct and potentially modifiable dietary risk factor for gout and emphasize the necessity of incorporating socioeconomic conditions and lifestyle behaviors into comprehensive gout prevention strategies.