Evidence map›Paper›PMID 33737627›Full record

ArticleScientific reports2021

A prediction model for childhood obesity in New Zealand.

Éadaoin M Butler, Avinesh Pillai, Susan M B Morton, Blake M Seers, Caroline G Walker, Kien Ly, El-Shadan Tautolo, Marewa Glover, Rachael W Taylor, Wayne S Cutfield and 2 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 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
2.0field-weighted citation impact, top 14% 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

6 citing papers in PubMed, 17 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

12 authors at 5 institutions in 3 countries.

Éadaoin M ButlerA Better Start-National Science Challenge, Auckland, New Zealand.ORCID 0000-0001-5078-1851
Avinesh PillaiGrowing Up in New Zealand, Centre for Longitudinal Research, University of Auckland, Auckland, New Zealand.ORCID 0000-0001-9928-5090
Susan M B MortonA Better Start-National Science Challenge, Auckland, New Zealand.ORCID 0000-0002-2231-7020
Blake M SeersDepartment of Statistics, University of Auckland, Auckland, New Zealand.ORCID 0000-0001-6841-4312
Caroline G WalkerGrowing Up in New Zealand, Centre for Longitudinal Research, University of Auckland, Auckland, New Zealand.ORCID 0000-0002-9210-7651
Kien LyGrowing Up in New Zealand, Centre for Longitudinal Research, University of Auckland, Auckland, New Zealand.
El-Shadan TautoloA Better Start-National Science Challenge, Auckland, New Zealand.ORCID 0000-0001-8444-6410
Marewa GloverA Better Start-National Science Challenge, Auckland, New Zealand.ORCID 0000-0002-1572-3784
Rachael W TaylorA Better Start-National Science Challenge, Auckland, New Zealand.ORCID 0000-0001-9516-2253
Wayne S CutfieldA Better Start-National Science Challenge, Auckland, New Zealand. w.cutfield@auckland.ac.nz.ORCID 0000-0001-6107-3682
José G B DerraikA Better Start-National Science Challenge, Auckland, New Zealand. j.derraik@auckland.ac.nz.ORCID 0000-0003-1226-1956
COPABS Collaborators
University of Auckland · NZUniversity of Otago · NZAuckland University of Technology · NZMassey University · NZUppsala University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several early childhood obesity prediction models have been developed, but none for New Zealand's diverse population. We aimed to develop and validate a model for predicting obesity in 4-5-year-old New Zealand children, using parental and infant data from the Growing Up in New Zealand (GUiNZ) cohort. Obesity was defined as body mass index (BMI) for age and sex ≥ 95th percentile. Data on GUiNZ children were used for derivation (n = 1731) and internal validation (n = 713). External validation was performed using data from the Prevention of Overweight in Infancy Study (POI, n = 383) and Pacific Islands Families Study (PIF, n = 135) cohorts. The final model included: birth weight, maternal smoking during pregnancy, maternal pre-pregnancy BMI, paternal BMI, and infant weight gain. Discrimination accuracy was adequate [AUROC = 0.74 (0.71-0.77)], remained so when validated internally [AUROC = 0.73 (0.68-0.78)] and externally on PIF [AUROC = 0.74 [0.66-0.82)] and POI [AUROC = 0.80 (0.71-0.90)]. Positive predictive values were variable but low across the risk threshold range (GUiNZ derivation 19-54%; GUiNZ validation 19-48%; and POI 8-24%), although more consistent in the PIF cohort (52-61%), all indicating high rates of false positives. Although this early childhood obesity prediction model could inform early obesity prevention, high rates of false positives might create unwarranted anxiety for families.

Indexed as

Birth WeightBody Mass IndexChildChild, PreschoolCohort StudiesFathersFemaleHumansInfantInfant, NewbornMaleNew ZealandOverweightPacific IslandsPediatric ObesityPregnancy

Identifiers

PMID33737627
PMCPMC7973754
OpenAlexW3136925576

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.