Use of emerging technologies to assess differences in outdoor physical activity in St. Louis, Missouri

• Main Authors: Deepti eAdlakha (Author), Elizabeth L. Budd (Author), Rebecca eGernes (Author), Sonia eSequeira (Author), James Aaron Hipp (Author)
• Format: Book
• Published: Frontiers Media S.A., 2014-05-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 2296-2565; 10.3389/fpubh.2014.00041
• Keywords: physical activity; Parks; MapMyRun.com; web data feeds; socioeconomic status (SES); Public aspects of medicine; RA1-1270
• Source: Frontiers in Public Health, Vol 2 (2014)

Introduction<br/>Abundant evidence shows that regular physical activity (PA) is an effective strategy for preventing obesity in people of diverse socioeconomic status (SES) and race groups. The proportion of PA performed in parks and how this differs by proximate neighborhood SES has not been thoroughly investigated. The present project analyzes online public web data feeds to assess differences in outdoor PA by neighborhood SES in St. Louis, Missouri, US.<br/><br/>Methods<br/>First, running and walking routes submitted by users of the website MapMyRun.com were downloaded. The website enables participants to plan, map, record, and share their exercise routes and outdoor activities like runs, walks, and hikes in an online database. Next, the routes were visually illustrated using Geographic Information Systems (GIS). Thereafter, using park data and 2010 Missouri census poverty data, the odds of running and walking routes traversing a low-SES neighborhood, and traversing a park in a low-SES neighborhood were examined in comparison to routes in high-SES neighborhoods and high-SES parks.<br/><br/>Results <br/>Results show that a majority of running and walking routes occur in, or at least traverse through a park. However, this finding does not hold when comparing low-SES neighborhoods to higher-SES neighborhoods in St. Louis. The odds of running in a park in a low-SES neighborhood were 54 percent lower than running in a park in a higher-SES neighborhood (OR=0.46, CI=0.17-1.23). The odds of walking in a park in a low-SES neighborhood were 17 percent lower than walking in a park in a higher-SES neighborhood (OR = 0.83, CI = 0.26-2.61).<br/><br/>Conclusions<br/>The novel methods of this study include the use of inexpensive, unobtrusive, and publicly available web data feeds to evaluate PA in parks and differences by neighborhood SES. Emerging technologies like MapMyRun.com present significant advantages to enhance tracking of user-defined PA across large geographic and temporal settings.