2446 - Monitoring Daily Activities and Linking Physical Activity Levels Attributed to Transportation Mobility Choices

Abstract

Background Transportation decisions impact human health at least in three ways, such as traffic crashes, environmental impact, and physical fitness. While there have been ample efforts in reducing traffic crashes and environmental impacts, less attention has been paid to their impacts on physical fitness. Recent efforts on the relationship between transportation and physical fitness were mostly from the context of active transportation. Potential benefits of active transportation include saving in mobility costs, benefits from related businesses, community savings in costs associated with health and environmental benefits. Although it is difficult to predict how a particular transportation planning decision affects physical fitness, total impacts are likely to be large. Diseases associated with inadequate physical fitness cause an order of magnitude of more deaths, and more than road crashes. Even modest reductions in these illnesses could provide significant health benefits. Therefore, there is a strong need for investigating how transportation options affect the physical activities and public health. Methods The research team developed a mobile application that collects individuals’ daily travel activities physical fitness activities. While the travel activity data are collected from the GPS information from individuals’ mobile phone, the fitness activity data are collected from Fitbit. Data collected from 200 subjects chosen in Michigan and Texas are transmitted to a server for further analysis. The data allows comparison of physical activity associated with transportation choices in different geographical areas and its seasonal variations. Results The data logged each minute were processed to determine daily activity (type, location, and duration), travel activity (transportation mode, travel time), and physical activity (heart rates and duration). The heart rates collected from Fitbit were useful in determining activity types and the transportation mode. The integrated approach allowed classification of various activity types and transportation modes. The amount of physical activity by activity type and travel mode was quantified by using the heart rate and the activity duration. The initial survey showed that those who were active in physical activity tend to choose active transportation options. Conclusion This study developed a mobile system that is able to collect daily activity, transportation choices, and the amount of physical activity. The data collected were analyzed to quantify the amount of physical activity by different transportation choice. This research is expected to help incorporate public health in evaluating transportation policies and alternatives by providing a method quantifying the amount of physical activities and associated health benefits.