This proposal addresses multiple priorities of PAR-12-197 Improving Diet and Physical Activity (PA) Assessment by advancing assessment of population PA in common settings. Physical inactivity is responsible for ?200,000 deaths in the US and 5 million deaths worldwide annually. About 10% of breast and 10% of colon cancers are attributable to insufficient PA, and inactivity causes 9% of total premature mortality. Parks, schools and youth sports are important contributors of PA that are relevant to a majority of the population. Supporting PA in these settings would contribute to improvements in population levels of PA and disease prevention and control. We will develop a novel video analysis software system, named E-VIP (Ecological Video Identification of PA), which will estimate the number of people and aggregated volume of PA from video recordings of PA- relevant settings. E-VIP will provide automated and continuous (rather than momentary) assessment, which will allow ongoing feedback to inform adaptive interventions and decision making. E-VIP is based on computer science methods used to count crowds and identify behaviors. We will train the E-VIP machine learning algorithm on 32,400 seconds of video from 2 parks, 2 schools, and 2 youth sports settings. Participants will engage in a variety of activities while wearing accelerometers to capture PA intensity in Metabolic Equivalents (METs). The testing phase involves capturing 900, 5-minute videos of free-living behavior across 4 parks, 4 schools, and 4 youth sports settings, with half of the settings/zones being the same as from the training phase. A range of activities and density of people will be captured in both the training and testing phase to maximize coverage of more-difficult high-density situations. Systematic direct observation will be conducted on each time sample to provide the criterion measure for testing validity. The metrics that will be tested include the average number of people, average proportion of people in each activity category (sedentary, light, moderate, vigorous, very vigorous), and sum PA MET-minutes in the setting over the 5-minute (or any given) time period. A gender and age group classifier will be explored. PE classes taught by PE specialists vs classroom teachers will be compared to test construct validity of E-VIP. Bland Altman methods and intraclass correlation coefficients will be used to assess agreement. Potential sources of error such as occlusions (e.g., trees, shadows, other people) will be assessed using moderator analyses. By automating ecological PA assessment, E-VIP will be feasible for widespread use. E-VIP's capability of continuous assessment will improve precision by collecting higher resolution data than collected by existing direct observation tools. When embedded in specific settings through commonly-used security cameras or webcams, or by purposefully placing video recorders, E-VIP will be capable of ongoing assessment which will inform public health surveillance, intervention, and evidence-based decision making (e.g., optimizing intervention strategies, monitoring school Physical Education mandates, providing needs assessment prior to and evaluation after environmental modifications).

Public Health Relevance

This study will develop and test a software for automated ongoing measurement of use and physical activity intensity from video recordings in specific settings such as parks, schools (including Physical Education), and youth sports. This innovative software will support adaptive multilevel interventions and evidence-based decision making in physical activity-relevant settings to optimize strategies for improving population health.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21CA194492-01A1
Application #
9035822
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Troiano, Richard P
Project Start
2016-02-01
Project End
2018-01-31
Budget Start
2016-02-01
Budget End
2017-01-31
Support Year
1
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Children's Mercy Hosp (Kansas City, MO)
Department
Type
DUNS #
073067480
City
Kansas City
State
MO
Country
United States
Zip Code
64108
Carlson, Jordan A; Liu, Bo; Sallis, James F et al. (2017) Automated Ecological Assessment of Physical Activity: Advancing Direct Observation. Int J Environ Res Public Health 14: