Evidence map›Paper›PMID 38052470›Full record

ArticleBMJ open2023

Changes in soft drinks purchased by British households associated with the UK soft drinks industry levy: a controlled interrupted time series analysis.

Nina T Rogers, David Pell, Oliver T Mytton, Tarra L Penney, Adam Briggs, Steven Cummins, Catrin Jones, Mike Rayner, Harry Rutter, Peter Scarborough and 4 more

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 2 pooled it
15.9field-weighted citation impact, top 1% of its field
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

33 citing papers in PubMed, 2 syntheses or guidelines pooled it, 68 citations in OpenAlex.

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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

14 authors at 9 institutions in 2 countries.

Nina T RogersMRC Epidemiology Unit, Cambridge, UK.
David PellMRC Epidemiology Unit, Cambridge, UK.ORCID 0000-0002-9357-6804
Oliver T MyttonMRC Epidemiology Unit, Cambridge, UK.ORCID 0000-0003-3218-9912
Tarra L PenneyYork University - Keele Campus, Toronto, Ontario, Canada.
Adam BriggsNuffield Department of Population Health, University of Oxford, Oxford, UK.
Steven CumminsDepartment of Social and Environmental Health Research, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0002-3957-4357
Catrin JonesMRC Epidemiology Unit, Cambridge, UK.
Mike RaynerNuffield Department of Population Health, University of Oxford, Oxford, UK.
Harry RutterUniversity of Bath Department of Social and Policy Sciences, Bath, UK.ORCID 0000-0002-9322-0656
Peter ScarboroughNIHR Oxford Biomedical Research Centre, Oxford, UK.ORCID 0000-0002-2378-2944
Stephen SharpMRC Epidemiology Unit, Cambridge, UK.
Richard SmithUniversity of Exeter, Exeter, UK.
Martin WhiteMRC Epidemiology Unit, Cambridge, UK.
Jean AdamsMRC Epidemiology Unit, Cambridge, UK jma79@medschl.cam.ac.uk.ORCID 0000-0002-5733-7830
MRC Epidemiology Unit · GBGreat Ormond Street Hospital · GBLondon School of Hygiene & Tropical Medicine · GBNuffield Health · GBUniversity of Bath · GBUniversity of Exeter · GBUniversity of Oxford · GBUniversity of Warwick · GBYork University · CA

Funding

Wellcome Trust
6 · The paper itself

Abstract

objectiveTo determine changes in household purchases of drinks 1 year after implementation of the UK soft drinks industry levy (SDIL).

designControlled interrupted time series.

participantsHouseholds reporting their purchasing to a market research company (average weekly n=22 091), March 2014 to March 2019.

interventionA two-tiered tax levied on soft drinks manufacturers, announced in March 2016 and implemented in April 2018. Drinks with ≥8 g sugar/100 mL (high tier) are taxed at £0.24/L, drinks with ≥5 to <8 g sugar/100 mL (low tier) are taxed at £0.18/L.

main outcome measuresAbsolute and relative differences in the volume of, and amount of sugar in, soft drinks categories, all soft drinks combined, alcohol and confectionery purchased per household per week 1 year after implementation.

resultsIn March 2019, compared with the counterfactual, purchased volume of high tier drinks decreased by 140.8 mL (95% CI 104.3 to 177.3 mL) per household per week, equivalent to 37.8% (28.0% to 47.6%), and sugar purchased in these drinks decreased by 16.2 g (13.5 to 18.8 g), or 42.6% (35.6% to 49.6%). Purchases of low tier drinks decreased by 170.5 mL (154.5 to 186.5 mL) or 85.8% (77.8% to 93.9%), with an 11.5 g (9.1 to 13.9 g) reduction in sugar in these drinks, equivalent to 87.8% (69.2% to 106.4%). When all soft drinks were combined irrespective of levy tier or eligibility, the volume of drinks purchased increased by 188.8 mL (30.7 to 346.9 mL) per household per week, or 2.6% (0.4% to 4.7%), but sugar decreased by 8.0 g (2.4 to 13.6 g), or 2.7% (0.8% to 4.5%). Purchases of confectionery and alcoholic drinks did not increase.

conclusionsCompared with trends before the SDIL was announced, 1 year after implementation, volume of all soft drinks purchased combined increased by 189 mL, or 2.6% per household per week. The amount of sugar in those drinks was 8 g, or 2.7%, lower per household per week. Further studies should determine whether and how apparently small effect sizes translate into health outcomes. TRIAL REGISTRATION NUMBER: ISRCTN18042742.

Indexed as

Carbonated BeveragesConsumer BehaviorBeveragesHumansInterrupted Time Series AnalysisSugarsTaxesUnited KingdomSugarsnutrition & dieteticsobesitypublic health

Identifiers

PMID38052470
PMCPMC10711915
OpenAlexW4389339454

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.