ArticleFrontiers in nutrition2026
Construction and empirical testing of a verifiable food safety complaint risk-triage model using human foods complaint system data from the United States Food and Drug Administration.
Article in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Food safety complaint systems contain large numbers of heterogeneous adverse-event reports, but surveillance use requires reproducible data sources and interpretable rules for ranking reports that may involve severe outcomes. Objective: To construct and test a transparent case-level logistic triage model that assigns FDA Human Foods Complaint System (HFCS) reports an urgent-priority score for earlier human review. Methods: The official HFCS quarterly workbook was downloaded from the FDA website on 2026-05-13, and case-based reports received from January 1, 2004 through December 31, 2025 were analyzed ( Results: Urgent-priority outcomes occurred in 47,093 reports (31.47%). Death appeared in 17,005 reports and hospitalization in 23,405. The hospitalization proportion was 24.9% (95% CI, 24.5-25.3%) among dietary-supplement reports and 18.2% (16.3-20.3%) among infant/baby-food reports; these unadjusted proportions were not interpreted as population risk differences. The model achieved an AUC of 0.723, PR-AUC of 0.526, Brier score of 0.214, Brier skill score of 0.008, a calibration intercept of -0.03, and a calibration slope of 0.91 on 37,411 test cases. Symptom count and the infant/baby-food indicator had the largest positive model weights. Conclusion: HFCS data can support reproducible complaint triage. The model is suitable for ordering reports for human review, whereas product-group contrasts and raw predicted probabilities require cautious interpretation and temporal or external validation.
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