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A point system to predict the future risk of obesity in 10-year-old children
Risa Sonoda1, Mikiko Tokiya2, Kenichi Touri3
1Department of Public Health and Epidemiology, Faculty of Medicine, Oita University.
Insights
A new prediction model and point system can identify 10-year-old children at high risk for developing obesity within four years. This tool aids in early intervention and promotes better childhood health outcomes.
Area of Science:
- Pediatric Health
- Obesity Prediction
- Longitudinal Studies
Background:
- Childhood obesity is a significant public health concern requiring effective prediction tools.
- A 4-year longitudinal study was conducted to develop a predictive model for childhood obesity.
Purpose of the Study:
- To develop and validate a prediction model and point system for identifying children at risk of developing obesity.
- To provide a tool for early intervention and prevention of childhood obesity.
Main Methods:
- Included 1,504 Japanese 10-year-old children in a health check-up between 2011-2015.
- Utilized multivariable logistic regression analysis with variables including overweight and lifestyle factors.
- Defined obesity as percentage overweight (POW) ≥ 20% and validated the model using the Hosmer-Lemeshow test.
Main Results:
- A prediction model based on seven binary variables (sex, sleep, screen time, hypertension, dyslipidemia, hepatic dysfunction, overweight) was developed.
- The model demonstrated good predictive accuracy with an area under the curve of 0.803.
- Validation showed no significant difference between actual and predicted obesity cases in non-obese children.
Conclusions:
- The validated prediction model and point score are effective tools for assessing 4-year obesity risk in 10-year-olds.
- This point system can aid in reducing childhood obesity incidence and promoting long-term health.
- Early identification through this model supports targeted public health interventions.
Background:
A 4-year longitudinal study was conducted to develop a model and a point system for predicting childhood obesity.
Methods:
This study included 1,504 Japanese 10-year-old children who underwent health check-ups between 2011 and 2015. Multivariable logistic regression analysis was conducted using the explanatory variables overweight and lifestyle. Obesity was defined as percentage overweight (POW) ≥ 20% calculated by the following equation: (actual weight - standard weight by height and sex)/standard weight by height and sex × 100 (%). The model was validated using the Hosmer-Lemeshow test on 10-year-olds.
Results:
Our prediction model for development of childhood obesity was based on seven binary variables: sex, lack of sleep, ≥2-h use of television/ games/ smartphone, hypertension, dyslipidemia, hepatic dysfunction, and being overweight. The area under the curve of the receiver operating characteristic curve was 0.803 (95% confidence interval, 0.740 to 0.866). When validated in non-obese children (n = 415), there was no significant difference between actual and predicted numbers of children with obesity (Hosmer-Lemeshow chi-square = 7.90, p = 0.18).
Conclusions:
The validated prediction model and point score for obesity development were shown to be useful tools for predicting the future 4-year risk of developing obesity among 10 years-old children. The point system may be useful for reducing the occurrence of childhood obesity and promoting better health.
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