BMC Medicine (Oct 2024)
Ultra-processed food consumption and renal cell carcinoma incidence and mortality: results from a large prospective cohort
Abstract
Abstract Background Growing evidence shows that ultra-processed food consumption is associated with the risk of cancer. However, prospective evidence is limited on renal cell carcinoma (RCC) incidence and mortality. In this study, we aimed to examine the association of ultra-processed food consumption and RCC incidence and mortality in a large cohort of US adults. Methods A population-based cohort of 101,688 participants were included from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Ultra-processed food items were confirmed by using the NOVA food classification system. The consumption of ultra-processed food was expressed as a percentage of total food intake (g/day). Prospective associations were calculated using Cox regression. Restricted cubic spline regression was used to assess nonlinearity. Subgroup analyses were performed to investigate the potential effect modifiers on the incidence and mortality of RCC. Results A total of 410 participants developed RCC during a total of 899,731 person-years of follow-up (median 9.41 years) and 230 RCC deaths during 1,533,930 person-years of follow-up (median 16.85 years). In the fully adjusted model, participants in the highest compared with the lowest quintiles of ultra-processed food consumption had a higher risk of RCC (HR quartile 4 vs 1:1.42; 95% CI: 1.06–1.91; P trend = 0.004) and mortality (HR quartile 4 vs. quartile 1: 1.64; 95% CI: 1.10–2.43; P trend = 0.027). Linear dose–response associations with RCC incidence and mortality were observed for ultra-processed food consumption (all P nonlinearity > 0.05). The reliability of these results was supported by sensitivity and subgroup analyses. Conclusion In conclusion, higher consumption of ultra-processed food is associated with an increased risk of RCC incidence and mortality. Limiting ultra-processed food consumption might be a primary prevention method of RCC.
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