BigO

BigO measures obesogenic behaviors in children and adolescents by integrating objective behavioral and environmental data to quantify how local socioeconomic, cultural, and urban characteristics influence physical activity and related outcomes.

Key Features:

• Data Collection: Collects objective behavioral data from children and adolescents alongside detailed environmental information from local contexts.
• Context-Specific Analysis: Analyzes local socioeconomic, cultural, and urban characteristics to provide context-specific evidence on obesogenic drivers.
• Advanced Analytics and Modeling: Implements a novel analysis approach that models expected population behavior as a function of local environmental characteristics.
• Predictive Accuracy: Demonstrated capability to predict physical activity levels with 81% leave-one-out accuracy.
• Visualization Tools: Generates automatic heatmaps that visualize expected population behaviors across geographic areas.

Scientific Applications:

• Policy Support: Supplies context-specific evidence to inform public health policy decisions addressing childhood obesity.
• Intervention Design: Identifies environmental factors and spatial patterns to guide targeted public health interventions.
• Research and Development: Provides predictive models and spatial visualizations for studying interactions between children's behaviors and their environments.

Methodology:

Integrates data acquisition from schools and clinics, performs indicator extraction, exploration, and analysis, applies predictive modeling to estimate population behavior as a function of local environmental characteristics, evaluates models with leave-one-out cross-validation, and produces automatic heatmap visualizations.