Evidence map›Paper›PMID 42861017›Full record

ArticleLancet regional health. Americas2026

Novel approaches for identifying unhealthy food and beverages for policy: a cross-sectional study of purchases of packaged products in Latin America.

Lilia S Pedraza, Elizabeth K Dunford, Lindsey Smith Taillie, Shu Wen Ng, Donna R Miles, Camila Zancheta, Francisco Diez-Canseco, Barry Popkin

Abstract read
In one paragraph

Article in Lancet regional health. Americas, 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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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Lilia S PedrazaCenter for Research in Nutrition and Health, National Institute of Public Health of Mexico, Av. Universidad 655, Santa María Ahuacatitlán, Cuernavaca 62100, Morelos, Mexico.
Elizabeth K DunfordDepartment of Nutrition and Carolina Population Center, The University of North Carolina at Chapel Hill, 123 W Franklin St, Chapel Hill, NC 27516, USA.
Lindsey Smith TaillieDepartment of Nutrition and Carolina Population Center, The University of North Carolina at Chapel Hill, 123 W Franklin St, Chapel Hill, NC 27516, USA.
Shu Wen NgDepartment of Nutrition and Carolina Population Center, The University of North Carolina at Chapel Hill, 123 W Franklin St, Chapel Hill, NC 27516, USA.
Donna R MilesDepartment of Nutrition and Carolina Population Center, The University of North Carolina at Chapel Hill, 123 W Franklin St, Chapel Hill, NC 27516, USA.
Camila ZanchetaInstitute of Nutrition and Food Technology, University of Chile, El Líbano 5524, Macul, Región Metropolitana, Chile.
Francisco Diez-CansecoUniversidad Científica del Sur, Antigua Panamericana Sur 19, Villa El Salvador, Lima 15067, Peru.
Barry PopkinDepartment of Nutrition and Carolina Population Center, The University of North Carolina at Chapel Hill, 123 W Franklin St, Chapel Hill, NC 27516, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This research aims to facilitate the identification of unhealthy food and beverages by examining approaches that progressively integrate nutrient criteria and specific markers of ultra-processing to strengthen and support the development and implementation of regulations targeting unhealthy foods within Latin America. Methods: This cross-sectional study examined urban representative household purchase data for packaged foods and beverages from Kantar Chile, Mexico, and Peru in 2018-2019. Five approaches identifying products as unhealthy were compared: the Nova classification system to identify ultra-processed foods (UPFs); products high in saturated fat, sodium, and sugar (HFSS) based on the Pan American Health Organization (PAHO) criteria; and three approaches combining HFSS criteria with the presence of cosmetic additives (e.g., non-nutritive sweeteners, colors, flavors, other additives). Proportions of products targeted for regulation under each approach were compared within and between countries. Findings: The proportion of unhealthy products identified across the different approaches ranged from 57 to 81% for beverages and 50-77% for foods. The most comprehensive identification of unhealthy products for policy targeting was found when products met either HFSS criteria or contained any cosmetic additive. Interpretation: A combined approach that identifies products meeting either PAHO's nutrient thresholds or containing UPF additive markers can substantially increase the proportion of foods and beverages identified as potentially unhealthy for policy targeting, compared with using either approach alone. Policymakers should select an identification approach that is practical to implement within their country's existing technical capacities and policy frameworks, while prioritizing broad coverage of all potentially unhealthy products. Funding: Bloomberg Philanthropies.

Indexed as

Food policyFood purchasesLatin AmericaNutrient profile modelsUltra-processed foods

Identifiers

PMID42861017
PMCPMC13654040

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.