Evidence map›Paper›PMID 35011033›Full record

ArticleNutrients2021

Estimating Dietary Intake from Grocery Shopping Data-A Comparative Validation of Relevant Indicators in Switzerland.

Jing Wu, Klaus Fuchs, Jie Lian, Mirella Lindsay Haldimann, Tanja Schneider, Simon Mayer, Jaewook Byun, Roland Gassmann, Christine Brombach, Elgar Fleisch

Abstract read
In one paragraph

Article in Nutrients, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
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

10 authors.

Jing WuInteraction- and Communication-based Systems, Institute of Computer Science, University of St. Gallen, 9000 St. Gallen, Switzerland.
Klaus FuchsETH AI Center, ETH Zurich, Swiss Federal Institute of Technology in Zurich, 8092 Zurich, Switzerland.ORCID 0000-0003-3226-920X
Jie LianInteraction- and Communication-based Systems, Institute of Computer Science, University of St. Gallen, 9000 St. Gallen, Switzerland.
Mirella Lindsay HaldimannD-One Solutions AG, 8003 Zurich, Switzerland.
Tanja SchneiderTechnology Studies, School of Humanities and Social Sciences, University of St. Gallen, 9000 St. Gallen, Switzerland.ORCID 0000-0002-5988-0001
Simon MayerInteraction- and Communication-based Systems, Institute of Computer Science, University of St. Gallen, 9000 St. Gallen, Switzerland.
Jaewook ByunDepartment of Software, Sejong University, Seoul 05006, Korea.ORCID 0000-0001-9854-5647
Roland GassmannInstitute of Food and Beverage Innovation, Zurich University of Applied Sciences, 8820 Waedenswil, Switzerland.
Christine BrombachInstitute of Food and Beverage Innovation, Zurich University of Applied Sciences, 8820 Waedenswil, Switzerland.
Elgar FleischInformation Management, Department of Management, Technology, and Economics, Swiss Federal Institute of Technology in Zurich, 8092 Zurich, Switzerland.

Funding

Swiss National Science Foundation 188402
6 · The paper itself

Abstract

In light of the globally increasing prevalence of diet-related chronic diseases, new scalable and non-invasive dietary monitoring techniques are urgently needed. Automatically collected digital receipts from loyalty cards hereby promise to serve as an objective and automatically traceable digital marker for individual food choice behavior and do not require users to manually log individual meal items. With the introduction of the General Data Privacy Regulation in the European Union, millions of consumers gained the right to access their shopping data in a machine-readable form, representing a historic chance to leverage shopping data for scalable monitoring of food choices. Multiple quantitative indicators for evaluating the nutritional quality of food shopping have been suggested, but so far, no comparison has validated the potential of these alternative indicators within a comparative setting. This manuscript thus represents the first study to compare the calibration capacity and to validate the discrimination potential of previously suggested food shopping quality indicators for the nutritional quality of shopped groceries, including the Food Standards Agency Nutrient Profiling System Dietary Index (FSA-NPS DI), Grocery Purchase Quality Index-2016 (GPQI), Healthy Eating Index-2015 (HEI-2015), Healthy Trolley Index (HETI) and Healthy Purchase Index (HPI), checking if any of them performs differently from the others. The hypothesis is that some food shopping quality indicators outperform the others in calibrating and discriminating individual actual dietary intake. To assess the indicators' potentials, 89 eligible participants completed a validated food frequency questionnaire (FFQ) and donated their digital receipts from the loyalty card programs of the two leading Swiss grocery retailers, which represent 70% of the national grocery market. Compared to

Indexed as

Consumer BehaviorDiet, HealthyFood MarketsNutritive ValueEatingFeeding BehaviorFood PreferencesHumansSurveys and QuestionnairesSwitzerlanddietary intakediet monitoringdigital receiptsfood shopping quality indicatorsFSA-NPS DI

Identifiers

PMID35011033
PMCPMC8747076

What OpenQuestion holds

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LicenceCC BY
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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.