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Predicting childhood overweight and obesity at school entrance using healthcare, demographic, and socioeconomic data in Wales, UK

Nida Ziauddeen Orcid Logo, Simon D S Fraser Orcid Logo, Sebastian Stannard Orcid Logo, Ann Berrington, Roberta Chiovoloni, Ashley Akbari Orcid Logo, Rhiannon Owen Orcid Logo, Nisreen A Alwan Orcid Logo

European Journal of Public Health, Volume: 36, Issue: 3, Start page: ckag051

Swansea University Authors: Roberta Chiovoloni, Ashley Akbari Orcid Logo, Rhiannon Owen Orcid Logo

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DOI (Published version): 10.1093/eurpub/ckag051

Abstract

In Wales, 24.8% of children aged 4–5 years live with overweight/obesity. Obesity is linked to developing multiple long-term conditions. We aimed to predict childhood obesity using healthcare and wider demographic, socioeconomic, and area-level data. The Secure Anonymized Information Linkage (SAIL) D...

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Published in: European Journal of Public Health
ISSN: 1101-1262 1464-360X
Published: Oxford University Press (OUP) 2026
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URI: https://cronfa.swan.ac.uk/Record/cronfa71802
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spelling 2026-05-13T14:05:59.7019730 v2 71802 2026-04-26 Predicting childhood overweight and obesity at school entrance using healthcare, demographic, and socioeconomic data in Wales, UK 08502855f683911aeb83edd02904be23 Roberta Chiovoloni Roberta Chiovoloni true false aa1b025ec0243f708bb5eb0a93d6fb52 0000-0003-0814-0801 Ashley Akbari Ashley Akbari true false 0d30aa00eef6528f763a1e1589f703ec 0000-0001-5977-376X Rhiannon Owen Rhiannon Owen true false 2026-04-26 MEDS In Wales, 24.8% of children aged 4–5 years live with overweight/obesity. Obesity is linked to developing multiple long-term conditions. We aimed to predict childhood obesity using healthcare and wider demographic, socioeconomic, and area-level data. The Secure Anonymized Information Linkage (SAIL) Databank in Wales contains routinely collected individual-level anonymized data from health records and administrative data. Two subsamples were created. The first restricted to singleton births between 15 March 2010 and 28 March 2012 to include Census 2011 data. The second included births after 1 January 2014 to include early-life measurements. Age- and sex-adjusted body mass index (BMI) at 4–5 years was used to define outcome of overweight/obesity (≥91st centile). Backward stepwise logistic regression models with multivariable fractional polynomials were used to develop models in stages. Data were available on 53 815 children at 4–5 years in census and 60 990 children in early-life subsample. Maternal BMI, smoking, marital status, birthweight, ethnic group, gender, and breastfeeding at birth were retained in all models. Additional variables were retained on adding census and area-level factors but increase in discrimination (Area Under the Curve, AUC) was marginal (0.66–0.67). In the second subsample, AUC improved from 0.67 to 0.79 as factors up to weight at 27 months were incorporated. Factors from healthcare records were largely consistent with existing literature. Additional insights were provided by including census data, though increase in model discrimination was marginal. Childhood obesity can act as a mediator on the pathway to multiple long-term conditions, and risk identification tools may target early prevention. Journal Article European Journal of Public Health 36 3 ckag051 Oxford University Press (OUP) 1101-1262 1464-360X 1 6 2026 2026-06-01 10.1093/eurpub/ckag051 COLLEGE NANME Medical School COLLEGE CODE MEDS Swansea University Another institution paid the OA fee This work was supported by the National Institute for Health Research (NIHR) under its Programme Artificial Intelligence for Multiple and Long-Term Conditions (NIHR203988) and NIHR Applied Research Collaboration Wessex. 2026-05-13T14:05:59.7019730 2026-04-26T17:31:57.1067460 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Health Data Science Nida Ziauddeen 0000-0002-8964-5029 1 Simon D S Fraser 0000-0002-4172-4406 2 Sebastian Stannard 0000-0002-6139-1020 3 Ann Berrington 4 Roberta Chiovoloni 5 Ashley Akbari 0000-0003-0814-0801 6 Rhiannon Owen 0000-0001-5977-376X 7 Nisreen A Alwan 0000-0002-4134-8463 8 71802__36717__141c7bb7135141aab26f5d0a9d00d694.pdf 71802.VOR.pdf 2026-05-13T14:02:09.8179501 Output 1095363 application/pdf Version of Record true © The Author(s) 2026. Published by Oxford University Press on behalf of the European Public Health Association. This is an Open Access article distributed under the terms of the Creative Commons Attribution License. true eng https://creativecommons.org/licenses/by/4.0/
title Predicting childhood overweight and obesity at school entrance using healthcare, demographic, and socioeconomic data in Wales, UK
spellingShingle Predicting childhood overweight and obesity at school entrance using healthcare, demographic, and socioeconomic data in Wales, UK
Roberta Chiovoloni
Ashley Akbari
Rhiannon Owen
title_short Predicting childhood overweight and obesity at school entrance using healthcare, demographic, and socioeconomic data in Wales, UK
title_full Predicting childhood overweight and obesity at school entrance using healthcare, demographic, and socioeconomic data in Wales, UK
title_fullStr Predicting childhood overweight and obesity at school entrance using healthcare, demographic, and socioeconomic data in Wales, UK
title_full_unstemmed Predicting childhood overweight and obesity at school entrance using healthcare, demographic, and socioeconomic data in Wales, UK
title_sort Predicting childhood overweight and obesity at school entrance using healthcare, demographic, and socioeconomic data in Wales, UK
author_id_str_mv 08502855f683911aeb83edd02904be23
aa1b025ec0243f708bb5eb0a93d6fb52
0d30aa00eef6528f763a1e1589f703ec
author_id_fullname_str_mv 08502855f683911aeb83edd02904be23_***_Roberta Chiovoloni
aa1b025ec0243f708bb5eb0a93d6fb52_***_Ashley Akbari
0d30aa00eef6528f763a1e1589f703ec_***_Rhiannon Owen
author Roberta Chiovoloni
Ashley Akbari
Rhiannon Owen
author2 Nida Ziauddeen
Simon D S Fraser
Sebastian Stannard
Ann Berrington
Roberta Chiovoloni
Ashley Akbari
Rhiannon Owen
Nisreen A Alwan
format Journal article
container_title European Journal of Public Health
container_volume 36
container_issue 3
container_start_page ckag051
publishDate 2026
institution Swansea University
issn 1101-1262
1464-360X
doi_str_mv 10.1093/eurpub/ckag051
publisher Oxford University Press (OUP)
college_str Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Health Data Science{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Health Data Science
document_store_str 1
active_str 0
description In Wales, 24.8% of children aged 4–5 years live with overweight/obesity. Obesity is linked to developing multiple long-term conditions. We aimed to predict childhood obesity using healthcare and wider demographic, socioeconomic, and area-level data. The Secure Anonymized Information Linkage (SAIL) Databank in Wales contains routinely collected individual-level anonymized data from health records and administrative data. Two subsamples were created. The first restricted to singleton births between 15 March 2010 and 28 March 2012 to include Census 2011 data. The second included births after 1 January 2014 to include early-life measurements. Age- and sex-adjusted body mass index (BMI) at 4–5 years was used to define outcome of overweight/obesity (≥91st centile). Backward stepwise logistic regression models with multivariable fractional polynomials were used to develop models in stages. Data were available on 53 815 children at 4–5 years in census and 60 990 children in early-life subsample. Maternal BMI, smoking, marital status, birthweight, ethnic group, gender, and breastfeeding at birth were retained in all models. Additional variables were retained on adding census and area-level factors but increase in discrimination (Area Under the Curve, AUC) was marginal (0.66–0.67). In the second subsample, AUC improved from 0.67 to 0.79 as factors up to weight at 27 months were incorporated. Factors from healthcare records were largely consistent with existing literature. Additional insights were provided by including census data, though increase in model discrimination was marginal. Childhood obesity can act as a mediator on the pathway to multiple long-term conditions, and risk identification tools may target early prevention.
published_date 2026-06-01T06:30:12Z
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