Prediction of childhood overweight and obesity at age 10-11: Findings from the Studying Lifecourse Obesity PrEdictors and the Born in Bradford cohorts
Prediction of childhood overweight and obesity at age 10-11: Findings from the Studying Lifecourse Obesity PrEdictors and the Born in Bradford cohorts
Background: in England, 41% of children aged 10–11 years live with overweight or obesity. Identifying children at risk of developing overweight or obesity may help target early prevention interventions. We aimed to develop and externally validate prediction models of childhood overweight and obesity at age 10–11 years using routinely collected weight and height measurements at age 4–5 years and maternal and early-life health data.
Methods: we used an anonymised linked cohort of maternal pregnancy and birth health records in Hampshire, UK between 2003 and 2008 and child health records. Childhood body mass index (BMI), adjusted for age and sex, at 10–11 years was used to define the outcome of overweight and obesity (BMI ≥ 91st centile) in the models. Logistic regression models and multivariable fractional polynomials were used to select model predictors and to identify transformations of continuous predictors that best predict the outcome. Models were externally validated using data from the Born in Bradford birth cohort. Model performance was assessed using discrimination and calibration.
Results: childhood BMI was available for 6566 children at 4–5 (14.6% overweight) and 10–11 years (26.1% overweight) with 10.8% overweight at both timepoints. The area under the curve (AUC) was 0.82 at development and 0.83 on external validation for the model only incorporating two predictors: BMI at 4–5 years and child sex. AUC increased to 0.84 on development and 0.85 on external validation on additionally incorporating maternal predictors in early pregnancy (BMI, smoking, age, educational attainment, ethnicity, parity, employment status). Models were well calibrated.
Conclusions: this prediction modelling can be applied at 4–5 years to identify the risk for childhood overweight at 10–11 years, with slightly improved prediction with the inclusion of maternal data. These prediction models demonstrate that routinely collected data can be used to target early preventive interventions to reduce the prevalence of childhood obesity.
1065-1073
Ziauddeen, Nida
8b233a4a-9763-410b-90c7-df5c7d1a26e4
Roderick, Paul J.
dbb3cd11-4c51-4844-982b-0eb30ad5085a
Santorelli, Gillian
c2c548fe-a51c-4aae-a054-5357d5242987
Alwan, Nisreen A.
0d37b320-f325-4ed3-ba51-0fe2866d5382
November 2023
Ziauddeen, Nida
8b233a4a-9763-410b-90c7-df5c7d1a26e4
Roderick, Paul J.
dbb3cd11-4c51-4844-982b-0eb30ad5085a
Santorelli, Gillian
c2c548fe-a51c-4aae-a054-5357d5242987
Alwan, Nisreen A.
0d37b320-f325-4ed3-ba51-0fe2866d5382
Ziauddeen, Nida, Roderick, Paul J., Santorelli, Gillian and Alwan, Nisreen A.
(2023)
Prediction of childhood overweight and obesity at age 10-11: Findings from the Studying Lifecourse Obesity PrEdictors and the Born in Bradford cohorts.
International Journal of Obesity, 47 (11), .
(doi:10.1038/s41366-023-01356-8).
Abstract
Background: in England, 41% of children aged 10–11 years live with overweight or obesity. Identifying children at risk of developing overweight or obesity may help target early prevention interventions. We aimed to develop and externally validate prediction models of childhood overweight and obesity at age 10–11 years using routinely collected weight and height measurements at age 4–5 years and maternal and early-life health data.
Methods: we used an anonymised linked cohort of maternal pregnancy and birth health records in Hampshire, UK between 2003 and 2008 and child health records. Childhood body mass index (BMI), adjusted for age and sex, at 10–11 years was used to define the outcome of overweight and obesity (BMI ≥ 91st centile) in the models. Logistic regression models and multivariable fractional polynomials were used to select model predictors and to identify transformations of continuous predictors that best predict the outcome. Models were externally validated using data from the Born in Bradford birth cohort. Model performance was assessed using discrimination and calibration.
Results: childhood BMI was available for 6566 children at 4–5 (14.6% overweight) and 10–11 years (26.1% overweight) with 10.8% overweight at both timepoints. The area under the curve (AUC) was 0.82 at development and 0.83 on external validation for the model only incorporating two predictors: BMI at 4–5 years and child sex. AUC increased to 0.84 on development and 0.85 on external validation on additionally incorporating maternal predictors in early pregnancy (BMI, smoking, age, educational attainment, ethnicity, parity, employment status). Models were well calibrated.
Conclusions: this prediction modelling can be applied at 4–5 years to identify the risk for childhood overweight at 10–11 years, with slightly improved prediction with the inclusion of maternal data. These prediction models demonstrate that routinely collected data can be used to target early preventive interventions to reduce the prevalence of childhood obesity.
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Prediction_Yr6_final
- Accepted Manuscript
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s41366-023-01356-8
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Accepted/In Press date: 19 July 2023
e-pub ahead of print date: 4 August 2023
Published date: November 2023
Additional Information:
Funding Information:
We would like to thank David Cable (Electronic Patient Records Implementation and Service Manager) and Florina Borca (Senior Information Analyst R&D) at University Hospital Southampton for support in accessing the SLOPE data. We thank Gareth Edwards (Business Intelligence Developer at Solent NHS Trust) and as well as the Research and Development and data team at Southern Health NHS Foundation Trust for their help in access the early life data used in SLOPE.
Funding Information:
The SLOPE study was supported by an Academy of Medical Sciences and Wellcome Trust grant to NAA [grant no AMS_HOP001\1060]. The funders had no role in designing the research or writing the manuscript. Born in Bradford (BiB) receives core infrastructure funding from the Wellcome Trust (WT101597MA), and a joint grant from the UK Medical Research Council (MRC) and UK Economic and Social Science Research Council (ESRC) (MR/N024397/1) and one from the British Heart Foundation (BHF) (CS/16/4/32482). The National Institute for Health Research Yorkshire and Humber ARC, and Clinical Research Network both provide support for BiB research. NZ is supported by NIHR Applied Research Collaboration Wessex. The views and opinions expressed in this paper are those of the authors and do not necessarily reflect those of the NIHR or the Department of Health and Social Care. For the purpose of open access, the author has applied a CC-BY public copyright licence to any Author Accepted Manuscript version arising from this submission
Publisher Copyright:
© 2023, The Author(s).
Identifiers
Local EPrints ID: 483666
URI: http://eprints.soton.ac.uk/id/eprint/483666
ISSN: 0307-0565
PURE UUID: bdd8b901-a968-44ca-9022-82a93321f271
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Date deposited: 03 Nov 2023 17:44
Last modified: 18 Mar 2024 02:40
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Author:
Nida Ziauddeen
Author:
Gillian Santorelli
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