Evidence map›Paper›PMID 33496075›Full record

ArticlePediatric obesity2021

Completeness and representativeness of body mass index in children's electronic general practice records: Linked cross-sectional study in an ethnically-diverse urban population in the United Kingdom.

Nicola Firman, John Robson, Zaheer Ahmed, Kambiz Boomla, Carol Dezateux

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Article in Pediatric obesity, 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. Review
  2. Article
  3. Supporting healthcare professionals to address child weight with parents: a qualitative study.The British journal of general practice : the journal of the Royal College of General Practitioners · 2024
    Article
  4. Article
  5. Article
  6. Article
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

5 authors.

Nicola FirmanCentre for Clinical Effectiveness and Health Data Science, Institute of Population Health Sciences, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, Abernethy Building, 4 Newark Street, London, UK.ORCID 0000-0001-5213-5044
John RobsonCentre for Clinical Effectiveness and Health Data Science, Institute of Population Health Sciences, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, Abernethy Building, 4 Newark Street, London, UK.
Zaheer AhmedCentre for Clinical Effectiveness and Health Data Science, Institute of Population Health Sciences, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, Abernethy Building, 4 Newark Street, London, UK.
Kambiz BoomlaCentre for Clinical Effectiveness and Health Data Science, Institute of Population Health Sciences, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, Abernethy Building, 4 Newark Street, London, UK.
Carol DezateuxCentre for Clinical Effectiveness and Health Data Science, Institute of Population Health Sciences, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, Abernethy Building, 4 Newark Street, London, UK.ORCID 0000-0001-9787-6276

Funding

Medical Research Council MR/S037527/1Wellcome Trust
6 · The paper itself

Abstract

objectiveTo assess completeness and accuracy of children's body mass index (BMI) recorded in general practice electronic health records (GP-EHRs).

methodsWe linked National Child Measurement Programme (NCMP) records from 29 839 5-year-olds and 26 660 11-year-olds attending state schools in inner London to GP-EHRs (95% linked; 49.1% girls). We estimated adjusted odds (aOR) of at least one GP-BMI record by sex, ethnic background, area-level deprivation, weight-status and long-term conditions. We examined within-child BMI differences and compared obesity prevalence from these sources.

results10.5% (2964/28330) and 26.0% (6598/25365) of 5- and 11-year-olds respectively had at least one GP-BMI record. Underweight (aOR;95% CI:1.71;1.34,2.19), obesity (1.45;1.27,1.65), South Asian background (1.55;1.38,1.74), presence of a long-term condition (8.15;7.31,9.10), and residence in deprived areas (Wald statistic 38.73; P-value<0.0001) were independently associated with at least one GP-BMI record. NCMP-BMI and GP-BMI differed by +0.45(95% Limits of Agreement -1.60,+2.51) and + 0.16(-2.86,+3.18) in 5- and 11-year-olds, respectively. The prevalence of obesity based on GP-BMI was 18.2%(16.1,20.5) and 35.9%(33.9,38.0) in 5- and 11-year-olds respectively, compared to 12.9%(12.5,13.3) and 26.9%(26.4,27.4) based on NCMP-BMI.

conclusionChild BMI is not comprehensively recorded in urban general practice. Linkage to school measurement records is feasible and enables assessment of health outcomes of obesity.

Indexed as

Body Mass IndexElectronic Health RecordsGeneral PracticeChildChild, PreschoolCross-Sectional StudiesCultural DiversityFemaleHumansMalePediatric ObesityUnited KingdomUrban PopulationBMIchildhoodelectronic health recordsgeneral practice

Identifiers

PMID33496075
PMCPMC11497231

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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.