Evidence map›Paper›PMID 41431227›Full record

ArticlePublic health nutrition2025

Using commercial dataset for extracting information on nutrition composition for policy evaluation purposes.

Beatriz Silva Nunes, Camila Aparecida Borges, Mariana Fagundes Grilo, Ana Clara Duran

Abstract read
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Article in Public health nutrition, 2025. 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

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Beatriz Silva NunesGraduate Program in Collective Health, School of Medical Sciences, https://ror.org/04wffgt70University of Campinas, Campinas, Brazil.ORCID 0000-0002-6431-8670
Camila Aparecida BorgesCenter for Epidemiological Studies in Nutrition and Health, University of São Paulo (USP), São Paulo, Brazil.
Mariana Fagundes GriloCenter for Food Studies and Research, https://ror.org/04wffgt70University of Campinas (UNICAMP), Campinas, Brazil.ORCID 0000-0002-0864-2169
Ana Clara DuranGraduate Program in Collective Health, School of Medical Sciences, https://ror.org/04wffgt70University of Campinas, Campinas, Brazil.ORCID 0000-0001-7317-5790

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study assessed the suitability of nutritional composition data from a commercial dataset for policy evaluation in Brazil.

designWe compared the proportions of packaged foods and beverages, classified according to the Nova food classification and the nutritional composition of matched products using data from a commercial database of food labels (Mintel-Global New Products Database (GNPD)) and the Brazilian Food Labels Database (BFLD), collected in 2017 as a 'gold standard.' We evaluated the agreement between the two datasets using paired

settingBrazil.

participantsTotally, 11 434 packaged foods and beverages collected in 2017 provided by BFLD and 67 042 packaged foods and beverages launched from 2001 to 2017 provided by Mintel-GNPD.

resultsThe proportions of ultra-processed foods (UPF) were similar in both datasets. Paired products exhibited an excellent correlation (ICC > 0·80), with no statistically significant difference in the mean values (

conclusionThe Mintel-GNPD dataset closely aligns with the BFLD in UPF distribution and shows a similar nutritional composition to a sample of matched foods available for purchase in stores, indicating its potential contribution to monitoring and evaluating food labelling policies in Brazil and in studies of food and beverages composition in food retail through the verification of policy compliance.

Indexed as

Databases, FactualFood LabelingNutrition PolicyNutritive ValueBeveragesBrazilFast FoodsFood AnalysisHumansComposition nutritionalEvaluatingFood labellingMonitoringNutrition policySecondary data analysis

Identifiers

PMID41431227
PMCPMC12780808

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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.