Evidence map›Paper›PMID 36494386›Full record

ArticleScientific reports2022

Estimation and feasibility of correction modelling for mother-reported child height and weight at 2 years using data from the Australian CHAT trial.

Yan Cheng, Huilan Xu, Chris Rissel, Philayrath Phongsavan, Limin Buchanan, Sarah Taki, Alison Hayes, Louise A Baur, Li Ming Wen

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 2 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

3 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Interventions to prevent obesity in children aged 2 to 4 years old.The Cochrane database of systematic reviews · 2025
    Pooled it
  3. 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

9 authors.

Yan ChengFamily Planning NSW, Sydney, Australia.
Huilan XuHealth Promotion Unit, Population Health Research and Evaluation Hub, Sydney Local Health District, Sydney, Australia.
Chris RisselSydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Philayrath PhongsavanSydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Limin BuchananHealth Promotion Unit, Population Health Research and Evaluation Hub, Sydney Local Health District, Sydney, Australia.
Sarah TakiHealth Promotion Unit, Population Health Research and Evaluation Hub, Sydney Local Health District, Sydney, Australia.
Alison HayesSydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Louise A BaurSydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Li Ming WenHealth Promotion Unit, Population Health Research and Evaluation Hub, Sydney Local Health District, Sydney, Australia. Liming.Wen@health.nsw.gov.au.ORCID http://orcid.org/0000-0003-1381-4022

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Correction modelling using reported BMI values has been employed in adolescent and adult populations to improve the accuracy of self-reporting. This study aimed to evaluate the feasibility of establishing correction modelling for mother-reported child height and weight at 2 years using data from an Australian trial in 2019. Correction modelling for BMI was conducted using mother-reported and objectively measured height and weight of 2-year-olds. Mother-reported height, weight and BMI values of 2-year-old children were adjusted based on objectively measured anthropometric data using linear regression models. 'Direct' and 'indirect' corrections were applied to the correction of BMI values. We defined the direct collection as using corrected BMI values that were predicted directly by the model and indirect correction as using corrected weight and height values to calculate corrected BMI values. Corrected BMI values via the indirect correction showed higher sensitivity or similar specificity in predicting overweight status, compared to the direct correction, and also showed higher agreement with measured values compared to the mother-reported measures. Corrected self-reported measures via an indirect correction had a better accuracy and agreement with the objectively measured data in the BMI values and classification of overweight, compared to the mother-reported values.

Indexed as

Body HeightMothersAdolescentAdultAustraliaBody Mass IndexBody WeightChild, PreschoolFemaleHumansOverweightReproducibility of Results

Identifiers

PMID36494386
PMCPMC9734091

What OpenQuestion holds

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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.