Research
Objectives
The Texas Physical Activity Research Collaborative (Texas PARC) was founded by Harold W. (Bill) Kohl, III. TPARC's faculty, students, and postdoctoral fellows seek to advance Physical Activity and Public Health research, practice, and graduate education throughout the state of Texas, the US, and the world. Whether physical activity is studied as an exposure, as an outcome, or as a policy, more people who are more active will make healthier populations.
Projects
Implementing Classroom-Based Physical Activity Approaches in Schools
Classroom-based physical activity approaches are an evidence-based way to support student’s physical activity, behavior, and learning. This study sets out to develop and test an implementation strategy to improve the use of classroom-based physical activity approaches among teachers in elementary schools.
Routes to Environmental Justice: Assessment of Ambient Environmental Exposures
Extreme heat may threaten the effectiveness of interventions for child physical activity including the national program Safe Routes to School. Using modeled estimates of heat stress and children’s geolocated physical activity on school routes, this three-year, NIH-funded study will determine the relations between built environment changes from Safe Routes to School, children’s exposure to ambient temperature, and their active school commuting behavior. Research findings can provide evidence for whether urban heat management strategies are needed to be incorporated as environmental interventions within Safe Routes to School and other programs designed to promote physical activity.
Pediatric Cardiovascular Health: Improving Prediction & Causal Inference Models
Using data from the ABCD study, which includes 11,800 children (9-10 years old), we’ll assess trajectories from pre-adolescence to adolescence for AHA's Life Essential 8® components, including healthy diet, physical activity, nicotine use, sleep, weight, blood lipids, blood glycated hemoglobin, and blood pressure. We'll also test if and how Social Determinants of Health (SDoH) impact these cardiovascular health trajectories, as well as develop an accurate, generalizable ABCD risk score using machine learning to predict cardiovascular outcomes based on SDoH.
