Evidence map›Paper›PMID 32389121›Full record

ArticleBMC medicine2020

Predicting the risk of childhood overweight and obesity at 4-5 years using population-level pregnancy and early-life healthcare data.

Nida Ziauddeen, Sam Wilding, Paul J Roderick, Nicholas S Macklon, Dianna Smith, Debbie Chase, Nisreen A Alwan

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.1field-weighted citation impact, top 6% 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

19 citing papers in PubMed, 40 citations in OpenAlex.

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  10. A point system to predict the future risk of obesity in 10-year-old children.Environmental health and preventive medicine · 2023
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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

7 authors at 3 institutions in 2 countries.

Nida ZiauddeenSchool of Primary Care, Population Sciences and Medical Education, Faculty of Medicine, University of Southampton, Southampton, UK. Nida.Ziauddeen@soton.ac.uk.
Sam WildingSchool of Primary Care, Population Sciences and Medical Education, Faculty of Medicine, University of Southampton, Southampton, UK.
Paul J RoderickSchool of Primary Care, Population Sciences and Medical Education, Faculty of Medicine, University of Southampton, Southampton, UK.
Nicholas S MacklonDepartment of Obstetrics and Gynaecology, University of Copenhagen, Zealand University Hospital, Roskilde, Denmark.
Dianna SmithGeography and Environmental Science, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK.
Debbie ChasePublic Health, Southampton City Council, Southampton, UK.
Nisreen A AlwanSchool of Primary Care, Population Sciences and Medical Education, Faculty of Medicine, University of Southampton, Southampton, UK. N.A.Alwan@soton.ac.uk.
University of Southampton · GBSouthampton City Council · GBZealand University Hospital · DK

Funding

Wellcome Trust
6 · The paper itself

Abstract

backgroundNearly a third of children in the UK are overweight, with the prevalence in the most deprived areas more than twice that in the least deprived. The aim was to develop a risk identification model for childhood overweight/obesity applied during pregnancy and early life using routinely collected population-level healthcare data.

methodsA population-based anonymised linked cohort of maternal antenatal records (January 2003 to September 2013) and birth/early-life data for their children with linked body mass index (BMI) measurements at 4-5 years (n = 29,060 children) in Hampshire, UK was used. Childhood age- and sex-adjusted BMI at 4-5 years, measured between September 2007 and November 2018, using a clinical cut-off of ≥ 91st centile for overweight/obesity. Logistic regression models together with multivariable fractional polynomials were used to select model predictors and to identify transformations of continuous predictors that best predict the outcome.

resultsFifteen percent of children had a BMI ≥ 91st centile. Models were developed in stages, incorporating data collected at first antenatal booking appointment, later pregnancy/birth, and early-life predictors (1 and 2 years). The area under the curve (AUC) was lowest (0.64) for the model only incorporating maternal predictors from early pregnancy and highest for the model incorporating all factors up to weight at 2 years for predicting outcome at 4-5 years (0.83). The models were well calibrated. The prediction models identify 21% (at booking) to 24% (at ~ 2 years) of children as being at high risk of overweight or obese by the age of 4-5 years (as defined by a ≥ 20% risk score). Early pregnancy predictors included maternal BMI, smoking status, maternal age, and ethnicity. Early-life predictors included birthweight, baby's sex, and weight at 1 or 2 years of age.

conclusionsAlthough predictive ability was lower for the early pregnancy models, maternal predictors remained consistent across the models; thus, high-risk groups could be identified at an early stage with more precise estimation as the child grows. A tool based on these models can be used to quantify clustering of risk for childhood obesity as early as the first trimester of pregnancy, and can strengthen the long-term preventive element of antenatal and early years care.

Indexed as

Child, PreschoolCohort StudiesData AnalysisFemaleHumansMaleOverweightPediatric ObesityPregnancyRisk FactorsEarly lifeObesityOverweightPredictionPregnancy

Identifiers

PMID32389121
PMCPMC7212594
OpenAlexW3022781585

What OpenQuestion holds

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LicenceCC BY
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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.