Evidence map›Paper›PMID 38297466›Full record

ArticlePublic health nutrition2024

Complementarity between the updated version of the front-of-pack nutrition label Nutri-Score and the food-processing NOVA classification.

Barthélemy Sarda, Emmanuelle Kesse-Guyot, Valérie Deschamps, Pauline Ducrot, Pilar Galan, Serge Hercberg, Melanie Deschasaux-Tanguy, Bernard Srour, Leopold K Fezeu, Mathilde Touvier and 1 more

Abstract read
In one paragraph

Article in Public health nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
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  6. Review
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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

11 authors.

Barthélemy SardaUniversité Sorbonne Paris Nord and Université Paris Cité, INSERM, INRAE, CNAM, Nutritional Epidemiology Research Team (EREN), Center of Research in Epidemiology and StatisticS (CRESS), 74 rue Marcel Cachin, F-93017Bobigny, France.
Emmanuelle Kesse-GuyotUniversité Sorbonne Paris Nord and Université Paris Cité, INSERM, INRAE, CNAM, Nutritional Epidemiology Research Team (EREN), Center of Research in Epidemiology and StatisticS (CRESS), 74 rue Marcel Cachin, F-93017Bobigny, France.
Valérie DeschampsNutritional Epidemiology Surveillance Team (ESEN), Santé publique France, The French Public Health Agency, Bobigny, France.
Pauline DucrotSanté publique France, French National Public Health Agency, Saint- Maurice, France.
Pilar GalanUniversité Sorbonne Paris Nord and Université Paris Cité, INSERM, INRAE, CNAM, Nutritional Epidemiology Research Team (EREN), Center of Research in Epidemiology and StatisticS (CRESS), 74 rue Marcel Cachin, F-93017Bobigny, France.
Serge HercbergUniversité Sorbonne Paris Nord and Université Paris Cité, INSERM, INRAE, CNAM, Nutritional Epidemiology Research Team (EREN), Center of Research in Epidemiology and StatisticS (CRESS), 74 rue Marcel Cachin, F-93017Bobigny, France.
Melanie Deschasaux-TanguyUniversité Sorbonne Paris Nord and Université Paris Cité, INSERM, INRAE, CNAM, Nutritional Epidemiology Research Team (EREN), Center of Research in Epidemiology and StatisticS (CRESS), 74 rue Marcel Cachin, F-93017Bobigny, France.ORCID 0000-0002-3359-420X
Bernard SrourUniversité Sorbonne Paris Nord and Université Paris Cité, INSERM, INRAE, CNAM, Nutritional Epidemiology Research Team (EREN), Center of Research in Epidemiology and StatisticS (CRESS), 74 rue Marcel Cachin, F-93017Bobigny, France.ORCID 0000-0002-1277-3380
Leopold K FezeuUniversité Sorbonne Paris Nord and Université Paris Cité, INSERM, INRAE, CNAM, Nutritional Epidemiology Research Team (EREN), Center of Research in Epidemiology and StatisticS (CRESS), 74 rue Marcel Cachin, F-93017Bobigny, France.
Mathilde TouvierUniversité Sorbonne Paris Nord and Université Paris Cité, INSERM, INRAE, CNAM, Nutritional Epidemiology Research Team (EREN), Center of Research in Epidemiology and StatisticS (CRESS), 74 rue Marcel Cachin, F-93017Bobigny, France.
Chantal JuliaUniversité Sorbonne Paris Nord and Université Paris Cité, INSERM, INRAE, CNAM, Nutritional Epidemiology Research Team (EREN), Center of Research in Epidemiology and StatisticS (CRESS), 74 rue Marcel Cachin, F-93017Bobigny, France.ORCID 0000-0003-2006-5269

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo compare the initial and the updated versions of the front-of-pack label Nutri-Score (related to the nutritional content) with the NOVA classification (related to the degree of food processing) at the food level.

designUsing the OpenFoodFacts database - 129,950 food products - we assessed the complementarity between the Nutri-Score (initial and updated) with the NOVA classification through a correspondence analysis. Contingency tables between the two classification systems were used. SETTINGS: The food offer in France.

participantsNot applicable.

resultsWith both versions (i.e. initial and updated) of the Nutri-Score, the majority of ultra-processed products received medium to poor Nutri-Score ratings (between 77·9 % and 87·5 % of ultra-processed products depending on the version of the algorithm). Overall, the update of the Nutri-Score algorithm led to a reduction in the number of products rated A and B and an increase in the number of products rated D or E for all NOVA categories, with unprocessed foods being the least impacted (-3·8 percentage points (-5·2 %) rated A or B and +1·3 percentage points (+12·9 %) rated D or E) and ultra-processed foods the most impacted (-9·8 percentage points (-43·4 %) rated A or B and +7·8 percentage points (+14·1 %) rated D or E). Among ultra-processed foods rated favourably with the initial Nutri-Score, artificially sweetened beverages, sweetened plant-based drinks and bread products were the most penalised categories by the revision of Nutri-Score while low-sugar flavoured waters, fruit and legume preparations were the least affected.

conclusionThese results indicate that the update of the Nutri-Score reinforces its coherence with the NOVA classification, even though both systems measure two distinct health dimensions at the food level.

Indexed as

Food LabelingSweetening AgentsFood HandlingFood QualityHumansNutritive ValueSweetening AgentsFood processingNOVANutrient profiling systemNutri-ScorePublic health

Identifiers

PMID38297466
PMCPMC10897572

What Socratic holds

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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 Socratic graph.