Predicting childhood overweight and obesity using maternal and early life risk factors: a systematic review

Summary 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 meth...

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Bibliographic Details
Published in:Obesity reviews 2018-03, Vol.19 (3), p.302-312
Main Authors: Ziauddeen, N., Roderick, P. J., Macklon, N. S., Alwan, N. A.
Format: Article
Language:English
Subjects:
Birth weight
Body mass
Body mass index
Body size
Body weight
Child
Childhood obesity
Children
Diet
Educational Status
Exercise
Female
Health Knowledge, Attitudes, Practice
Humans
Identification methods
Life Style
maternal factors
Mathematical models
Missing data
Mothers - education
Mothers - psychology
Obesity
Overweight
Overweight - epidemiology
Overweight - psychology
Pediatric Obesity
Pediatric Obesity - epidemiology
Pediatric Obesity - etiology
Pediatric Obesity - psychology
Performance prediction
Prediction models
Predictive Value of Tests
Pregnancy
Public health
Risk analysis
Risk Factors
Systematic review
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Summary:Summary 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.
ISSN:1467-7881
1467-789X
DOI:10.1111/obr.12640