Evidence map›Paper›PMID 30562349›Full record

ArticlePLoS medicine2018

Supermarket policies on less-healthy food at checkouts: Natural experimental evaluation using interrupted time series analyses of purchases.

Katrine T Ejlerskov, Stephen J Sharp, Martine Stead, Ashley J Adamson, Martin White, Jean Adams

Abstract read
In one paragraph

Article in PLoS medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 8 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

44 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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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

6 authors.

Katrine T EjlerskovCentre for Diet and Activity Research, MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-5408-8402
Stephen J SharpCentre for Diet and Activity Research, MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0003-2375-1440
Martine SteadInstitute for Social Marketing, Faculty of Health Sciences and Sport, University of Stirling, Stirling, United Kingdom.ORCID 0000-0002-3066-4604
Ashley J AdamsonInstitute of Health & Society and the Human Nutrition Research Centre, Newcastle University, Newcastle upon Tyne, United Kingdom.
Martin WhiteCentre for Diet and Activity Research, MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-1861-6757
Jean AdamsCentre for Diet and Activity Research, MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-5733-7830

Funding

British Heart FoundationCancer Research UKDepartment of Health NIHR-RP-02-12-001Medical Research Council MR/K023187/1Wellcome Trust
6 · The paper itself

Abstract

backgroundIn response to public concerns and campaigns, some United Kingdom supermarkets have implemented policies to reduce less-healthy food at checkouts. We explored the effects of these policies on purchases of less-healthy foods commonly displayed at checkouts. METHODS AND

findingsWe used a natural experimental design and two data sources providing complementary and unique information. We analysed data on purchases of small packages of common, less-healthy, checkout foods (sugary confectionary, chocolate, and potato crisps) from 2013 to 2017 from nine UK supermarkets (Aldi, Asda, Co-op, Lidl, M&S, Morrisons, Sainsbury's, Tesco, and Waitrose). Six supermarkets implemented a checkout food policy between 2013 and 2017 and were considered intervention stores; the remainder were comparators. Firstly, we studied the longitudinal association between implementation of checkout policies and purchases taken home. We used data from a large (n ≈ 30,000) household purchase panel of food brought home to conduct controlled interrupted time series analyses of purchases of less-healthy common checkout foods from 12 months before to 12 months after implementation. We conducted separate analyses for each intervention supermarket, using others as comparators. We synthesised results across supermarkets using random effects meta-analyses. Implementation of a checkout food policy was associated with an immediate reduction in four-weekly purchases of common checkout foods of 157,000 (72,700-242,800) packages per percentage market share-equivalent to a 17.3% reduction. This decrease was sustained at 1 year with 185,100 (121,700-248,500) fewer packages purchased per 4 weeks per percentage market share-equivalent to a 15.5% reduction. The immediate, but not sustained, effect was robust to sensitivity analysis. Secondly, we studied the cross-sectional association between checkout food policies and purchases eaten without being taken home. We used data from a smaller (n ≈ 7,500) individual purchase panel of food bought and eaten 'on the go'. We conducted cross-sectional analyses comparing purchases of common checkout foods in 2016-2017 from supermarkets with and without checkout food policies. There were 76.4% (95% confidence interval 48.6%-89.1%) fewer annual purchases of less-healthy common checkout foods from supermarkets with versus without checkout food policies. The main limitations of the study are that we do not know where in the store purchases were selected and cannot determine the effect of changes in purchases on consumption. Other interventions may also have been responsible for the results seen.

conclusionsThere is a potential impact of checkout food polices on purchases. Voluntary supermarket-led activities may have public health benefits.

Indexed as

Consumer BehaviorFamily CharacteristicsAdolescentAdultAgedCross-Sectional StudiesFemaleHumansInterrupted Time Series AnalysisLongitudinal StudiesMaleMarketingMiddle AgedNutrition PolicySnacksUnited Kingdom

Identifiers

PMID30562349
PMCPMC6298641

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.