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Ultra-Processed Food Intake, Circulating NMR Metabolomic Signatures and Risk of Osteoarthritis in Women

Li Y, Zhou X

International journal of women's health, 2026

13,122 participants

Abstract

Purpose: Prospective evidence reporting statistical associations between ultra-processed food (UPF) intake and osteoarthritis (OA) risk in women is sparse, women suffer a disproportionately heavy OA burden with distinct metabolic and inflammatory characteristics, and the circulating biological correlates of UPF intake have not been integrated with OA risk in a unified analytical framework.

Patients and methods: In a prospective multi-omics analysis, we studied women without baseline OA, with NOVA-based UPF intake reconstructed from repeated Oxford WebQ 24-hour dietary records. Cox proportional hazards models (age as time scale) estimated hazard ratios (HRs) per 1-SD UPF increase and across quartiles, adjusting for ethnicity, education, income, smoking, alcohol, physical activity and total energy intake (Model 2); stabilised inverse probability weighting (IPW) addressed UPF availability. Nightingale NMR metabolomic and Olink proteomic features were screened sequentially (UPF-to-omics, omics-to-OA; FDR<0.05); candidate correlates were summarised by principal component analysis into a UPF-related omics signature. We performed two-stage correlational screening for omics markers rather than formal causal mediation analysis. Notably, 61.8% of the female cohort lacked valid UPF dietary records; stabilised inverse probability weighting (IPW) with dual trimming thresholds was applied to mitigate potential selection bias from missing dietary data.

Results: Among 13,122 women with UPF…

How strong is the evidence?

Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence. Reported size: 13,122 participants or records.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

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