Public health policy should be grounded in established evidence that acknowledges uncertainty: a response to The Lancet series on ultra-processed foods.

Authors

Daniel B Ibsen, Michael Fridén, Georgia D Tomova, Natalia Ortega, Peter W G Tennant

Published in

BMC medicine. Volume 24. Issue 1. Sep 28, 2026. Epub Sep 28, 2026.

Abstract

The recent three-part Lancet series on ultra-processed foods (UPFs) argued that the displacement of traditional diets by UPFs is a major driver of poor diet quality and diet-related chronic diseases, which is becoming a major public health challenge worldwide. This Debate article aims to highlight key uncertainties surrounding that evidence base and the causal interpretation of the reported associations.
We discuss uncertainties related to three core questions central for making causal claims: what are UPFs, what are the mechanisms and what is the right comparison group? We argue that the breadth of the Nova classification system as an exposure framework encompasses nutritionally and functionally diverse foods that are unlikely to share common biological effects. This heterogeneity complicates causal inferences and risks conflating well-established dietary risk factors with more speculative attributes related to processing, additives, and food structure. Many of the proposed mechanisms linking UPFs to adverse health outcomes are not unique to ultra-processing and may operate similarly across foods regardless of processing level. While much emphasis has been given to the comparison between minimally processed and UPF, the comparison between processed food and UPF may better isolate the effects of ultra-processing. By embracing these uncertainties, we outline a way forward focusing on disaggregation of UPFs into specific components and characteristics.
Advancing the evidence base in this way will support clearer attribution of risk and more targeted interventions. Public health policy should remain grounded in well-characterised dietary exposures while transparently acknowledging uncertainty around ultra-processing as an independent causal factor.

PMID:
42802224
Bibliographic data and abstract were imported from PubMed on 28 Sep 2026.

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