Evidence map›Paper›PMID 33292917›Full record

ArticlePublic health nutrition2021

Delivery of the National Child Measurement Programme in England.

Martin Čadek, Stuart W Flint, Ralph Tench

Abstract read
In one paragraph

Article in Public health nutrition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

3 authors.

Martin ČadekCarnegie School of Sport, Leeds Beckett University, LeedsLS6 3QS, UK.ORCID 0000-0003-4800-6543
Stuart W FlintSchool of Psychology, University of Leeds, Leeds, UK.ORCID 0000-0003-4878-3019
Ralph TenchLeeds Business School, Leeds Beckett University, Leeds, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe National Child Measurement Programme (NCMP) is a mandatory initiative delivered in England to children in Reception and Year 6. To date, no research has explored the methods used to deliver the NCMP by Local Government Authorities (LGA) across England.

designAn online survey was administered between February 2018 and May 2018 to explore the delivery of the NCMP across the 152 LGA in England and disseminated using non-probability convenience sampling.

settingLGA received an anonymous link to the survey.

participantsA total of 92 LGA participated in the survey.

resultsMost LGA who responded provide result feedback (86 %), a proactive follow-up (71 %) and referrals to services (80 %). Additionally, 65 % of the authorities tailor Public Health England specimen result letters to suit their needs, and 84 % provide attachments alongside. Out of 71 % of LGA who provide proactive follow-up, 19 (29 %) provide the proactive follow-up only to upper weight categories and only 4 (6 %) include Healthy Weight category with other categories in proactive follow-up. Regarding the service availability for children, out of 80 % of LGA who indicated that services are available, 32 (43 %) targeted solely upper weight categories, while the other 42 (57 %) offered services across all weight categories. Finally, most LGA (88 %) commission providers to manage various parts of the NCMP.

conclusionsThe results show that LGA in England localise the NCMP. Further guidance regarding standards of best practice would help LGA to find the most suitable localisation out of various options that exist across other LGA.

Indexed as

Pediatric ObesityChildEnglandFamilyHumansParentsSurveys and QuestionnairesChildhood ObesityLocal Government AuthorityNational Child Measurement ProgrammePolicy

Identifiers

PMID33292917
PMCPMC10195514

What OpenQuestion holds

Textmetadata
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.