Evidence map›Paper›PMID 41720823›Full record

ArticleNPJ science of food2026

Mapping regional disparities in discounted grocery products.

Antonio Desiderio, Alessia Galdeman, Franziska Bäuerlein, Sune Lehmann

Abstract read
In one paragraph

Article in NPJ science of food, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

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

4 authors.

Antonio Desiderio *Department of Applied Mathematics and Computer Science, Technical University of Denmark, Copenhagen, Denmark. antde@dtu.dk.
Alessia Galdeman *Data Science Section, IT University of Copenhagen, Copenhagen, Denmark.
Franziska Bäuerlein *Department of Applied Mathematics and Computer Science, Technical University of Denmark, Copenhagen, Denmark.
Sune LehmannDepartment of Applied Mathematics and Computer Science, Technical University of Denmark, Copenhagen, Denmark. sljo@dtu.dk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Food waste represents a major challenge to global climate resilience, accounting for almost 10% of annual greenhouse gas emissions. The retail sector is a critical player, mediating product flows between producers and consumers, where supply chain inefficiencies can shape which items are put on sale. Yet how these dynamics vary across geographic contexts remains largely unexplored. Here, we analyze data from Denmark's largest retail group on near-expiry products put on sale. We uncover the geospatial variations using a dual-clustering approach. We characterize multi-scale spatial relationships in retail organization by correlating store clustering - measured using shortest-path distances along the street network-with product clustering based on promotion co-occurrence patterns. Using a bipartite network approach, we identify three regional store clusters, and use percolation thresholds to corroborate the scale of their spatial separation. We find that stores in rural communities put meat and dairy products on sale up to 2.2 times more frequently than metropolitan areas. In contrast, metropolitan and capital regions lean toward convenience products, which have more balanced nutritional profiles but less favorable environmental impacts. By linking geographic context to retail inventory, we provide evidence that reducing food waste requires interventions tailored to local retail dynamics, highlighting the importance of region-specific sustainability strategies.

Identifiers

PMID41720823
PMCPMC13036051

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.