Cargando…
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
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...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9395267/ https://www.ncbi.nlm.nih.gov/pubmed/35662271 http://dx.doi.org/10.1038/s41366-022-01157-5 |
_version_ | 1784771653322932224 |
---|---|
author | Carrillo-Balam, Gabriela Doi, Lawrence Marryat, Louise Williams, Andrew James Bradshaw, Paul Frank, John |
author_facet | Carrillo-Balam, Gabriela Doi, Lawrence Marryat, Louise Williams, Andrew James Bradshaw, Paul Frank, John |
author_sort | Carrillo-Balam, Gabriela |
collection | PubMed |
description | 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 77.6% 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. |
format | Online Article Text |
id | pubmed-9395267 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-93952672022-08-24 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 Carrillo-Balam, Gabriela Doi, Lawrence Marryat, Louise Williams, Andrew James Bradshaw, Paul Frank, John Int J Obes (Lond) Article 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 77.6% 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. Nature Publishing Group UK 2022-06-03 2022 /pmc/articles/PMC9395267/ /pubmed/35662271 http://dx.doi.org/10.1038/s41366-022-01157-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Carrillo-Balam, Gabriela Doi, Lawrence Marryat, Louise Williams, Andrew James Bradshaw, Paul Frank, John 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 |
title | 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 |
title_full | 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 |
title_fullStr | 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 |
title_full_unstemmed | 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 |
title_short | 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 |
title_sort | 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 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9395267/ https://www.ncbi.nlm.nih.gov/pubmed/35662271 http://dx.doi.org/10.1038/s41366-022-01157-5 |
work_keys_str_mv | AT carrillobalamgabriela validityofscottishpredictorsofchildobesityage12forriskscreeninginmidchildhoodasecondaryanalysisofprospectivecohortstudydatawithsensitivityanalysesforsettingswithoutvariousroutinelycollectedpredictorvariables AT doilawrence validityofscottishpredictorsofchildobesityage12forriskscreeninginmidchildhoodasecondaryanalysisofprospectivecohortstudydatawithsensitivityanalysesforsettingswithoutvariousroutinelycollectedpredictorvariables AT marryatlouise validityofscottishpredictorsofchildobesityage12forriskscreeninginmidchildhoodasecondaryanalysisofprospectivecohortstudydatawithsensitivityanalysesforsettingswithoutvariousroutinelycollectedpredictorvariables AT williamsandrewjames validityofscottishpredictorsofchildobesityage12forriskscreeninginmidchildhoodasecondaryanalysisofprospectivecohortstudydatawithsensitivityanalysesforsettingswithoutvariousroutinelycollectedpredictorvariables AT bradshawpaul validityofscottishpredictorsofchildobesityage12forriskscreeninginmidchildhoodasecondaryanalysisofprospectivecohortstudydatawithsensitivityanalysesforsettingswithoutvariousroutinelycollectedpredictorvariables AT frankjohn validityofscottishpredictorsofchildobesityage12forriskscreeninginmidchildhoodasecondaryanalysisofprospectivecohortstudydatawithsensitivityanalysesforsettingswithoutvariousroutinelycollectedpredictorvariables |