Predicting childhood overweight and obesity using maternal and early life risk factors: a systematic review
Predicting childhood overweight and obesity using maternal and early life risk factors: a systematic review
Background: Childhood obesity is a serious public health challenge, and identification of high-risk populations with early intervention to prevent its development is a priority. We aimed to systematically review prediction models for childhood overweight/obesity and critically assess the methodology of their development, validation and reporting.
Methods: Medline and Embase were searched systematically for studies describing the development and/or validation of a prediction model/score for overweight and obesity between 1 to 13 years of age. Data were extracted using the Cochrane CHARMS checklist for Prognosis Methods.
Results: Ten studies were identified that developed (one), developed and validated (seven) or externally validated an existing (two) prediction model. Six out of eight models were developed using automated variable selection methods. Two studies used multiple imputation to handle missing data. From all studies, 30,475 participants were included. Of 25 predictors, only seven were included in more than one model with maternal body mass index, birthweight and gender the most common.
Conclusion: Several prediction models exist, but most have not been externally validated or compared with existing models to improve predictive performance. Methodological limitations in model development and validation combined with non-standard reporting restrict the implementation of existing models for the prevention of childhood obesity.
302-312
Ziauddeen, Nida
3ad67dd8-26ba-498a-af0a-b1174298995b
Roderick, Paul J.
dbb3cd11-4c51-4844-982b-0eb30ad5085a
Macklon, Nicholas S.
7db1f4fc-a9f6-431f-a1f2-297bb8c9fb7e
Alwan, Nisreen A.
0d37b320-f325-4ed3-ba51-0fe2866d5382
1 March 2018
Ziauddeen, Nida
3ad67dd8-26ba-498a-af0a-b1174298995b
Roderick, Paul J.
dbb3cd11-4c51-4844-982b-0eb30ad5085a
Macklon, Nicholas S.
7db1f4fc-a9f6-431f-a1f2-297bb8c9fb7e
Alwan, Nisreen A.
0d37b320-f325-4ed3-ba51-0fe2866d5382
Ziauddeen, Nida, Roderick, Paul J., Macklon, Nicholas S. and Alwan, Nisreen A.
(2018)
Predicting childhood overweight and obesity using maternal and early life risk factors: a systematic review.
Obesity Reviews, 19 (3), .
(doi:10.1111/obr.12640).
Abstract
Background: Childhood obesity is a serious public health challenge, and identification of high-risk populations with early intervention to prevent its development is a priority. We aimed to systematically review prediction models for childhood overweight/obesity and critically assess the methodology of their development, validation and reporting.
Methods: Medline and Embase were searched systematically for studies describing the development and/or validation of a prediction model/score for overweight and obesity between 1 to 13 years of age. Data were extracted using the Cochrane CHARMS checklist for Prognosis Methods.
Results: Ten studies were identified that developed (one), developed and validated (seven) or externally validated an existing (two) prediction model. Six out of eight models were developed using automated variable selection methods. Two studies used multiple imputation to handle missing data. From all studies, 30,475 participants were included. Of 25 predictors, only seven were included in more than one model with maternal body mass index, birthweight and gender the most common.
Conclusion: Several prediction models exist, but most have not been externally validated or compared with existing models to improve predictive performance. Methodological limitations in model development and validation combined with non-standard reporting restrict the implementation of existing models for the prevention of childhood obesity.
Text
Prediction_review_resubmission_final_clean_obesity reviews_2 Oct 17
- Accepted Manuscript
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2017_Ziauddeen_Obesity_Reviews_SR_obesity prediction
More information
Accepted/In Press date: 30 September 2017
e-pub ahead of print date: 19 December 2017
Published date: 1 March 2018
Identifiers
Local EPrints ID: 415637
URI: http://eprints.soton.ac.uk/id/eprint/415637
ISSN: 1467-7881
PURE UUID: be63d4cc-80f1-40d2-8ada-68c3dc2f0fdd
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Date deposited: 16 Nov 2017 17:30
Last modified: 16 Mar 2024 05:50
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Author:
Nicholas S. Macklon
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