Evidence map›Paper›PMID 38062070›Full record

ArticleScientific reports2023

Assessing household lifestyle exposures from consumer purchases, the My Purchases cohort.

Frederik T Møller, Thor Grønborg Junker, Kathrine Kold Sørensen, Caroline Eves, Jan Wohlfahrt, Joakim Dillner, Christian Torp-Pedersen, Bartlomiej Wilkowski, Steven Chong, Tune H Pers and 4 more

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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

14 authors.

Frederik T MøllerDepartment of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Copenhagen, Denmark. FRTM@SSI.dk.
Thor Grønborg JunkerDepartment of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark.
Kathrine Kold SørensenDepartment of Cardiology, North Zealand Hospital, Hillerød, Denmark.
Caroline EvesDepartment of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Copenhagen, Denmark.
Jan WohlfahrtDepartment of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark.
Joakim DillnerDepartment of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden.
Christian Torp-PedersenDepartment of Cardiology, North Zealand Hospital, Hillerød, Denmark.
Bartlomiej WilkowskiDepartment for Digital Infrastructure, Statens Serum Institut, Copenhagen, Denmark.
Steven ChongDepartment for Digital Infrastructure, Statens Serum Institut, Copenhagen, Denmark.
Tune H PersThe Novo Nordisk Foundation, Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark.
Victor YakimovDepartment for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark.
Heimo MüllerDiagnostic and Research Center for Molecular BioMedicine, Medical University of Graz, Graz, Austria.
Steen EthelbergDepartment of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Copenhagen, Denmark.
Mads MelbyeDanish Cancer Society Research Center, Copenhagen, Denmark.

Funding

Horizon 2020 Framework Programme 874662Novo Nordisk Foundation Center for Basic Metabolic Research NNF18CC0034900
6 · The paper itself

Abstract

Consumer purchase data (CPD) is a promising instrument to assess the impact of purchases on health, but is limited by the need for manual scanning, a lack of access to data from multiple retailers, and limited information on product data and health outcomes. Here we describe the My Purchases cohort, a web-app enabled, prospective collection of CPD, covering several large retail chains in Denmark, that enables linkage to health outcomes. The cohort included 459 participants as of July 03, 2023. Up to eight years of CPD have been collected, with 2,225,010 products purchased, comprising 223,440 unique products. We matched 88.5% of all products by product name or item number to one generic food database and three product databases. Combined, the databases enable analysis of key exposures such as nutrients, ingredients, or additives. We found that increasing the number of retailers that provide CPD for each consumer improved the stability of individual CPD profiles and when we compared kilojoule information from generic and specific product matches, we found a median modified relative difference of 0.23. Combined with extensive product databases and health outcomes, CPD could provide the basis for extensive investigations of how what we buy affects our health.

Indexed as

Family CharacteristicsFoodConsumer BehaviorHumansLife StyleProspective Studies

Identifiers

PMID38062070
PMCPMC10703931

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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.