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i-PATHWAY: Development and validation of a prediction model for childhood obesity in an Australian prospective birth
Oliver J Canfell1,2,3, Robyn Littlewood4,5, Olivia R L Wright6
1Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia.
Insights
A new model, i-PATHWAY, predicts childhood overweight and obesity from infancy using factors like maternal BMI and infant weight change. This simple, valid tool can inform early screening and health policies.
Area of Science:
- Pediatric health
- Public health
- Biostatistics
Background:
- Childhood overweight and obesity are significant public health concerns.
- Early identification and intervention are crucial for managing this condition.
- Predictive models can aid in identifying at-risk children from an early age.
Purpose of the Study:
- To develop and validate the i-PATHWAY model for predicting childhood overweight/obesity.
- To utilize data from an Australian prospective birth cohort for model development.
- To establish a clinically relevant tool for early screening.
Main Methods:
- Followed the Transparent Reporting of a multivariable Prediction model for individual Prognosis or Diagnosis (TRIPOD) checklist.
- Utilized data from 1947 children in the Raine Study Gen2 cohort.
- Employed backward stepwise logistic regression and bootstrapping for model development and internal validation.
Main Results:
- 18.9% of children were overweight or obese at 8-9 years.
- Key predictors included infant weight change, parental BMI, maternal smoking, premature birth, infant sleep, and sex.
- The validated i-PATHWAY model demonstrated acceptable predictive accuracy (AUC=0.737).
Conclusions:
- The i-PATHWAY model is a simple, valid, and clinically relevant tool for predicting childhood overweight/obesity.
- The model can be used for early screening and informing health policy.
- Further validation is recommended before widespread implementation.
Aim:
To develop and validate a model (i-PATHWAY) to predict childhood (age 8-9 years) overweight/obesity from infancy (age 12 months) using an Australian prospective birth cohort.
Methods:
The Transparent Reporting of a multivariable Prediction model for individual Prognosis or Diagnosis (TRIPOD) checklist was followed. Participants were n = 1947 children (aged 8-9 years) from the Raine Study Gen2 - an Australian prospective birth cohort - who had complete anthropometric measurement data available at follow up. The primary outcome was childhood overweight or obesity (age 8-9 years), defined by age- and gender-specific cut-offs. Multiple imputation was performed to handle missing data. Predictors were selected using 2000 unique backward stepwise logistic regression models. Predictive performance was assessed via: calibration, discrimination and decision-threshold analysis. Internal validation of i-PATHWAY was conducted using bootstrapping (1000 repetitions) to adjust for optimism and improve reliability. A clinical model was developed to support relevance to practice.
Results:
At age 8-9 years, 18.9% (n = 367) of children were classified with overweight or obesity. i-PATHWAY predictors included: weight change (0-1 year); maternal pre-pregnancy body mass index (BMI); paternal BMI; maternal smoking during pregnancy; premature birth; infant sleep patterns; and sex. After validation, predictive accuracy was acceptable: calibration slope = 0.956 (0.952-0.960), intercept = -0.052 (-0.063, -0.048), area under the curve = 0.737 (0.736-0.738), optimised sensitivity = 0.703(0.568-0.790), optimised specificity = 0.646 (0.571-0.986). The clinical model retained acceptable predictive accuracy without paternal BMI.
Conclusions:
i-PATHWAY is a simple, valid and clinically relevant prediction model for childhood overweight/obesity. After further validation, this model can influence state and national health policy for overweight/obesity screening in the early years.
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