Evidence map›Paper›PMID 39482639›Full record

ArticleThe international journal of behavioral nutrition and physical activity2024

Evaluating the impact of the universal infant free school meal policy on the ultra-processed food content of children's lunches in England and Scotland: a natural experiment.

Jennie C Parnham, Kiara Chang, Fernanda Rauber, Renata B Levy, Anthony A Laverty, Jonathan Pearson-Stuttard, Martin White, Stephanie von Hinke, Christopher Millett, Eszter P Vamos

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Article in The international journal of behavioral nutrition and physical activity, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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0cells of the map it votes in
6citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Inequities in Children's Food Environment: A Comparison between Slum and Non-slum Settings in Urban Bangladesh.Journal of urban health : bulletin of the New York Academy of Medicine · 2026
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

10 authors.

Jennie C ParnhamDepartment of Primary Care & Public Health, Public Health Policy Evaluation Unit, School of Public Health, Imperial College London, 90 Wood Lane, London, W12 0BZ, UK. j.parnham18@imperial.ac.uk.ORCID 0000-0002-4385-2153
Kiara ChangDepartment of Primary Care & Public Health, Public Health Policy Evaluation Unit, School of Public Health, Imperial College London, 90 Wood Lane, London, W12 0BZ, UK.
Fernanda RauberCenter for Epidemiological Research in Nutrition and Health, University of São Paulo, São Paulo, 01246-904, Brazil.
Renata B LevyCenter for Epidemiological Research in Nutrition and Health, University of São Paulo, São Paulo, 01246-904, Brazil.
Anthony A LavertyDepartment of Primary Care & Public Health, Public Health Policy Evaluation Unit, School of Public Health, Imperial College London, 90 Wood Lane, London, W12 0BZ, UK.
Jonathan Pearson-StuttardDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, SW7 2AZ, UK.
Martin WhiteMRC Epidemiology Unit, University of Cambridge, Cambridge, CB2 0QQ, UK.
Stephanie von HinkeSchool of Economics, University of Bristol, Priory Road Complex, Bristol, BS8 1TU, UK.
Christopher MillettDepartment of Primary Care & Public Health, Public Health Policy Evaluation Unit, School of Public Health, Imperial College London, 90 Wood Lane, London, W12 0BZ, UK.
Eszter P VamosDepartment of Primary Care & Public Health, Public Health Policy Evaluation Unit, School of Public Health, Imperial College London, 90 Wood Lane, London, W12 0BZ, UK.

Funding

Department of Health PD-SPH-2015Medical Research Council G1002345Medical Research Council MC/UU/00006/7School for Public Health Research Grant Reference Number PD-SPH-2015
6 · The paper itself

Abstract

backgroundThe Universal Infant Free School Meal (UIFSM) policy was introduced in 2014/15 in England and Scotland for schoolchildren aged 4-7 years, leading to an increase in school meal uptake. UK school meals are known to be healthier and less industrially processed than food brought from home (packed lunches). However, the impact of the UIFSM policy on the quantity of ultra-processed food (UPF) consumed at school during lunchtime is unknown. This study aimed to evaluate the impact of the UIFSM policy on lunchtime intakes of UPF in English and Scottish schoolchildren.

methodsData from the UK National Diet and Nutrition Survey (2008-2019) were used to conduct a difference-in-difference (DID) natural experiment. Outcomes included school meal uptake and the average intake of UPF (% of total lunch in grams (%g) and % total lunch in Kcal (%Kcal)) during school lunchtime. The change in the outcomes before and after the introduction of UIFSM (September 2014 in England, January 2015 in Scotland) in the intervention group (4-7 years, n = 835) was compared to the change in an unexposed control group (8-11 years, n = 783), using linear regression. Inverse probability weights were used to balance characteristics between intervention and control groups.

resultsBefore UIFSM, school meal uptake and consumption of UPFs were similar in the intervention and control groups. The DID model showed that after UIFSM, school meal uptake rose by 25%-points (pp) (95% CI 14.2, 35.9) and consumption of UPFs (%g) decreased by 6.8pp (95% CI -12.5,-1.0). Analyses indicated this was driven by increases in minimally processed dairy and eggs, and starchy foods, and decreases in ultra-processed salty snacks, bread and drinks. The differences were larger in the lowest-income children (-19.3 UPF(%g); 95% CI -30.4,-8.2) compared to middle- and high-income children. Analyses using UPF %Kcal had similar conclusions.

conclusionsThis study builds on previous evidence suggesting that UIFSM had a positive impact on dietary patterns, showing that it reduced consumption of UPFs at school lunchtime, with the greatest impact for children from the lowest-income households. Universal free school meals could be an important policy for long term equitable improvements in children's diet.

Indexed as

Fast FoodsFood ServicesLunchNutrition PolicySchoolsChildChild, PreschoolDietEnergy IntakeEnglandFemaleFood, ProcessedHumansMaleNutrition SurveysScotlandChildrenPolicy evaluationSchool foodUltra-processed foodUniversal free school meals

Identifiers

PMID39482639
PMCPMC11528988

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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.