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Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Dynamics of childhood growth and obesity: development and validation of a quantitative mathematical model
Insights
A new mathematical model quantifies childhood obesity drivers, predicting how interventions impact body weight. This tool aids clinicians and policymakers in addressing the childhood obesity epidemic with data-driven strategies.
Area of Science:
- Pediatric Endocrinology
- Obesity Research
- Mathematical Modeling
Background:
- Clinicians and policymakers require quantitative tools to predict childhood body weight responses to obesity interventions.
- Understanding the energy dynamics of childhood obesity is crucial for effective public health strategies.
Purpose of the Study:
- To develop and validate a mathematical model for predicting childhood body weight changes in response to obesity interventions.
- To quantitatively assess the energy excess contributing to childhood obesity and determine necessary intervention magnitudes.
Main Methods:
- Developed a mathematical model of childhood energy balance, incorporating healthy growth and obesity development.
- Calibrated the model using reference body composition data and validated it against independent datasets.
- The model accounts for energy expenditure and intake changes during growth and obesity development.
Main Results:
- The model accurately simulated healthy growth, predicting significant increases in energy intake from ages 5-18.
- Childhood obesity development requires substantially greater excess energy intake compared to adult obesity.
- Population-level analysis indicated a mean increase of ~200 kcal/day per child in US children from 1971-74 to 2003-06, contributing to excess weight.
- Identified potential therapeutic windows for children to outgrow obesity during high-growth periods, particularly in boys.
Conclusions:
- The developed model quantifies the energy excess underlying childhood obesity.
- It provides a quantitative method for calculating the intervention magnitude needed for body weight change in children.
- This offers policymakers and clinicians a valuable tool for understanding and intervening in the childhood obesity epidemic.
Background:
Clinicians and policy makers need the ability to predict quantitatively how childhood bodyweight will respond to obesity interventions.
Methods:
We developed and validated a mathematical model of childhood energy balance that accounts for healthy growth and development of obesity, and that makes quantitative predictions about weight-management interventions. The model was calibrated to reference body composition data in healthy children and validated by comparing model predictions with data other than those used to build the model.
Findings:
The model accurately simulated the changes in body composition and energy expenditure reported in reference data during healthy growth, and predicted increases in energy intake from ages 5-18 years of roughly 1200 kcal per day in boys and 900 kcal per day in girls. Development of childhood obesity necessitated a substantially greater excess energy intake than for development of adult obesity. Furthermore, excess energy intake in overweight and obese children calculated by the model greatly exceeded the typical energy balance calculated on the basis of growth charts. At the population level, the excess weight of US children in 2003-06 was associated with a mean increase in energy intake of roughly 200 kcal per day per child compared with similar children in 1971-74 [corrected]. The model also suggests that therapeutic windows when children can outgrow obesity without losing weight might exist, especially during periods of high growth potential in boys who are not severely obese.
Interpretation:
This model quantifies the energy excess underlying obesity and calculates the necessary intervention magnitude to achieve bodyweight change in children. Policy makers and clinicians now have a quantitative technique for understanding the childhood obesity epidemic and planning interventions to control it.
Funding:
Intramural Research Program of the National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases.
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