Designing an Agent-Based Model for Childhood Obesity Interventions: A Case Study of ChildObesity180.

Complex systems modeling can provide useful insights when designing and anticipating the impact of public health interventions. We developed an agent-based, or individual-based, computation model (ABM) to aid in evaluating and refining implementation of behavior change interventions designed to increase physical activity and healthy eating and reduce unnecessary weight gain among school-aged children. The potential benefits of applying an ABM approach include estimating outcomes despite data gaps, anticipating impact among different populations or scenarios, and exploring how to expand or modify an intervention.

Children's perceptions of weight, obesity, nutrition, physical activity and related health and socio-behavioural factors.

Objective: Approximately one-third of children in the USA are either overweight or obese. Understanding the perceptions of children is an important factor in reversing this trend.

Design: An online survey was conducted with children to capture their perceptions of weight, overweight, nutrition, physical activity and related socio-behavioural factors.

Whole grain consumption is inversely associated with BMI Z-score in rural school-aged children.

Objective: To examine the relationship between intake of whole grains and BMI Z-score in rural children.

Design: General linear models and logistic regression were used to examine the cross-sectional associations between whole grain intake and BMI Z-score, prevalence and odds ratios of overweight and obesity. Dietary intake was assessed using the Block Food Screener for ages 2-17 years.