Measuring Physical Activity and Its Contexts in Parks

Wednesday, March 17, 2010: 3:50 PM
110 (Convention Center)
Phillip Ward1, Thom McKenzie2, Deborah Cohen3, Terry Marsh3, Kelly Evenson4, Amy Hillier5, Sandra Lapham6 and Claude M. Setodji3, (1)The Ohio State University, Columbus, OH, (2)San Diego State University, San Diego, CA, (3)RAND Corporation, Santa Monica, CA, (4)University North Carolina–Chapel Hill, Chapel Hill, NC, (5)University of Pennsylvania, Philadelphia, PA, (6)Behavioral Health Research Center of the Southwest, Albuquerque, NM
Background/Purpose

Neighborhood parks are important locations for physical activity (PA), particularly for minority populations who are at increased risk from sedentary lifestyles. Recreation professionals and governments are becoming increasingly aware of the importance of both accessibility to PA venues and policies that support these venues. Yet, we know little about who uses parks, what activities parks users engage in, and their level of physical activity in the parks. We validated a method for systematic observation of physical activity, testing its ability to estimate the total number of people using a neighborhood park.

Method

We conducted observations every hour for 14 hours per day for two weeks in 10 urban/suburban parks: 2 each in Los Angeles, CA, Albuquerque, NM, Columbus, OH, Durham, NC, and Philadelphia, PA in the spring, summer and fall. In nine of the parks two independent observers conducted 15% of all observations simultaneously. We counted users by gender, age group, race/ethnicity, and activity level. We then used a standardized Cronbach's alpha to determine the minimum number of observations that would be necessary to estimate total park use, including providing a robust estimate of the characteristics of park users and level of physical activity.

Analysis/Results

Over 10 parks observed in 2 seasons, 14 hours a day, 7 days of the week in clement weather, we counted 76,632 individuals. The least busy park was in North Carolina counting only 1,091 individuals in a one week period; the most busy park was in Ohio in the summer and had 7,858 individuals. On average, each park was visited by 547 persons per day (range 155- 786). There was an average of 94.7 % agreement between observers (standard deviation = 3.2%.). Three randomly chosen days of data collection 4 times a day is sufficient for just the counting of the number of people using the different target areas (average alpha=0.88 and ICC=0.76) but a 4 days a week, 4 times a day schedule, was needed to robustly measure walking and sedentary behavior.

Conclusions

An abbreviated schedule of observations limited to three days per week, four observations per day is sufficient for estimating park use. SOPARC can be easily learned and staff exhibit high reliability after 1 week of training. Applying these observation methods can help us advance the goal of increasing physical activity when interventions are implemented in park settings.