St Andrews Research Repository

St Andrews University Home
View Item 
  •   St Andrews Research Repository
  • University of St Andrews Research
  • University of St Andrews Research
  • University of St Andrews Research
  • View Item
  •   St Andrews Research Repository
  • University of St Andrews Research
  • University of St Andrews Research
  • University of St Andrews Research
  • View Item
  •   St Andrews Research Repository
  • University of St Andrews Research
  • University of St Andrews Research
  • University of St Andrews Research
  • View Item
  • Login
JavaScript is disabled for your browser. Some features of this site may not work without it.

Validity of Scottish predictors of child obesity (age 12) for risk screening in mid-childhood : a secondary analysis of prospective cohort study data—with sensitivity analyses for settings without various routinely collected predictor variables

Thumbnail
View/Open
Carrillo_Balam_2022_IJO_Scottishpredictors_CC.pdf (805.1Kb)
Date
01/09/2022
Author
Carrillo-Balam, Gabriela
Doi, Lawrence
Marryat, Louise
Williams, Andrew James
Bradshaw, Paul
Frank, John
Keywords
Child obesity
Screening
Epidemiology
Scotland
Overweight
Body Mass Index
Growing Up in Scotland study
RA0421 Public health. Hygiene. Preventive Medicine
RJ Pediatrics
E-DAS
MCC
Metadata
Show full item record
Altmetrics Handle Statistics
Altmetrics DOI Statistics
Abstract
Objective : To analyse the Growing Up in Scotland cohort for predictors of obesity at age 12, present at school entry (age 5-6). Methods : The initial model included literature-based risk factors likely to be routinely collected in high-income countries (HICs), as well as “Adverse/Protective Childhood Experiences (ACEs/PCEs)”. Missing data were handled by Multiple Chained Equations. Variable-reduction was performed using multivariable logistic regression with backwards and forwards stepwise elimination, followed by internal validation by bootstrapping. Optimal sensitivity/specificity cut-offs for the most parsimonious and accurate models in two situations (optimum available data, and routinely available data in Scotland) were examined for their referral burden, and Positive and Negative Predictive Values. Results : Data for 2787 children with full outcome data (obesity prevalence 18.3% at age 12) were used to develop the models. The final “Optimum Data” model included six predictors of obesity: maternal body mass index, indoor smoking, equivalized income quintile, child’s sex, child’s BMI at age 5-6, and ACEs. After internal validation, the area under the receiver operating characteristic curve was 0.855 (95% CI 0.852-0.859). A cut-off based on Youden’s J statistic for the Optimum Data model yielded a specificity of 77.8% and sensitivity of 76.3%. 37.0% of screened children were “Total Screen Positives” (and thus would constitute the “referral burden”.) A “Scottish Data” model, without equivalized income quintile and ACEs as a predictor, and instead using Scottish Index of Multiple Deprivation quintile and “age at introduction of solid-foods,” was slightly less sensitive (76.2%) but slightly more specific (79.2%), leading to a smaller referral burden (30.8%). Conclusion : Universally collected, machine-readable and linkable data at age 5-6 predict reasonably well children who will be obese by age 12. However, the Scottish treatment system is unable to cope with the resultant referral burden and other criteria for screening would have to be met.
Citation
Carrillo-Balam , G , Doi , L , Marryat , L , Williams , A J , Bradshaw , P & Frank , J 2022 , ' Validity of Scottish predictors of child obesity (age 12) for risk screening in mid-childhood : a secondary analysis of prospective cohort study data—with sensitivity analyses for settings without various routinely collected predictor variables ' , International Journal of Obesity , vol. 46 , no. 9 , pp. 1624–1632 . https://doi.org/10.1038/s41366-022-01157-5
Publication
International Journal of Obesity
Status
Peer reviewed
DOI
https://doi.org/10.1038/s41366-022-01157-5
ISSN
0307-0565
Type
Journal article
Rights
Copyright © 2022 The Authors. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Description
Funding: The authors acknowledge the generosity of the funders of this work, the Children’s Data Collaborative – a consortium of the Scottish Government, Data-Driven Initiative, UNICEF, and the University of Edinburgh. Additional salary support is gratefully acknowledged for LM’s/LD’S/AJW’s contributions to this work, from (respectively): LM -- School of Health Sciences, University of Dundee; LD -- School of Health in Social Science, University of Edinburgh; AJW -- School of Medicine, University of St Andrews.
Collections
  • University of St Andrews Research
URI
http://hdl.handle.net/10023/25492

Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

Advanced Search

Browse

All of RepositoryCommunities & CollectionsBy Issue DateNamesTitlesSubjectsClassificationTypeFunderThis CollectionBy Issue DateNamesTitlesSubjectsClassificationTypeFunder

My Account

Login

Open Access

To find out how you can benefit from open access to research, see our library web pages and Open Access blog. For open access help contact: openaccess@st-andrews.ac.uk.

Accessibility

Read our Accessibility statement.

How to submit research papers

The full text of research papers can be submitted to the repository via Pure, the University's research information system. For help see our guide: How to deposit in Pure.

Electronic thesis deposit

Help with deposit.

Repository help

For repository help contact: Digital-Repository@st-andrews.ac.uk.

Give Feedback

Cookie policy

This site may use cookies. Please see Terms and Conditions.

Usage statistics

COUNTER-compliant statistics on downloads from the repository are available from the IRUS-UK Service. Contact us for information.

© University of St Andrews Library

University of St Andrews is a charity registered in Scotland, No SC013532.

  • Facebook
  • Twitter