Regular exercise participation is associated with lowered risk of premature mortality and chronic health conditions (1). Despite this knowledge, exercise participation remains low. Less than half of US adults meet the current guidelines for moderate-to-vigorous physical activity (≥150 min/wk of moderate, 75 min/wk of vigorous physical activity, or a combination) (2), and participation varies by region (3) with less physical activity in southern and western states.

Understanding why exercise participation varies by location must include an examination of the built environment (2,4). Most people exercise in their neighborhood, making accessibility to locations for exercise especially important (5). Those with gyms, neighborhood parks, or other recreational facilities in close proximity to their homes or work places are more likely to exercise (6–8). Although many different methods of systematically measuring the built environment exist, there is little consensus on which is the most appropriate.

The choice of a built environment measure for exercise is difficult because no standard measure exists. Giles-Corti et al (9) and Rutt (10) measured the distance from individual homes to the nearest recreational facility while others, such as Dill (11), focused on transit measures. Recreational facility density (12) or the ease of walking to specific locations such as parks (Walk Score) have also been used (13,14). Other methods, such as the ParkScore, which estimates the percentage of the population who are within a 10-minute walk of a well-maintained park, have been used as well, making a consensus for a comparable measure at different geographic levels difficult (15). Because of this lack of consensus, a new measure of access to exercise opportunities, measured at the county level, with national coverage, was created for the annual release of 2014 County Health Rankings & Roadmaps (www.countyhealthrankings.org) to address this research gap.

The County Health Rankings ranks counties within states on their current (Health Outcomes) and potential (Health Factors) health. One Health Factor area examined in the Rankings is Diet and Exercise. This Health Factor area includes measures of obesity, physical inactivity, and the food environment. We felt it was important to highlight the role that the built environment plays in providing opportunities for exercise. So, we developed a measure intended to provide communities a starting point for discussions on improving their county’s infrastructure to enhance exercise opportunities. In 2014, the County Health Rankings introduced the access to exercise opportunities measure, providing a nationally available county-level measure. The measure incorporates both park and recreational facility data to create a comparable county-to-county measure of access and the first to adjust for the differing needs and transportation patterns between urban and rural areas. We describe the development of the access to exercise opportunities measure, available at www.countyhealthrankings.org, and provide descriptive results.

Links between the built environment and exercise participation have led to the development of various built environment measures, comprehensively reviewed by Brownson et al (20). We were unable to find a national measure using publicly accessible data for all counties in the United States before the 2014 County Health Rankings. Therefore, we developed the access to exercise opportunities measure using ArcGIS and multiple data sources to describe the percentage of the population living in close proximity to parks and recreational facilities. The ultimate goals of the measure were to provide county-to-county comparisons of the built environment for exercise and assist in discussions on the alteration of the built environment to promote exercise.

Overall, we found evidence to suggest that the access to exercise opportunities measure has good construct validity. It was significantly associated with several theoretically similar Rankings’ Health Factor and Health Outcome measures in the expected directions. Negative correlations were found with premature mortality, poor quality of life, and obesity, and the strongest correlation was with a lack of self-reported leisure-time physical activity. This indicated the access to exercise opportunities measure was performing in the intended manner.

We discovered significant variation when we used the measure to examine state and regional differences in access to exercise opportunities. There was regional variation characterized by the Northeast having the largest percentage of their population with access to exercise opportunities while the Southeast had the smallest. In the southern regions, less than 50% of county populations had access to exercise opportunities. This lack of opportunity is ecologically consistent with the lack of self-reported physical activity in southern states (3) and may help partially explain this phenomenon. There was also large within-region variation evident by large standard deviations at the county level (Figure 2). Even within states, county variation and disparity in access exist. For example, in Wisconsin, only 1% of the population in Menominee County has access to an exercise opportunity compared with 98% of the population in Milwaukee County.

This measure is intended to initiate discussions on the relationship between the built environment, exercise, and health. Public health officials and community leaders can view the percentage of the population in their community with access to exercise opportunities and compare it to other counties at www.countyhealthrankings.org. This measure highlights public health disparities in terms of access to parks and recreational facilities. One obvious intervention to improve access to exercise opportunities is designating land for public parks. Parks can provide numerous physical, mental, and social health benefits for residents of a community (21). Additionally, they remove a significant exercise barrier if location efficiency is maximized so that a large percentage of the population lives close in urban areas (16) or if co-located near other amenities such as churches, town halls, or stores in rural areas. Accordingly, numerous studies have linked park use to increased likelihood of sufficient physical activity levels (22,23). Another public health intervention is to encourage the development of recreational facilities such as gyms, YMCAs, and community centers with exercise components. Several studies have found positive associations between use of these types of facilities and exercise. The likelihood of meeting physical activity recommendations was similarly increased by use of a private facility (22), access to an indoor facility (24), and use of an indoor gym (25).

The access to exercise opportunities measure serves as the first national measure, to our knowledge, of the built environment combining park and recreational facility information at the county level. It provides for all 50 states and 3,114 of 3,141 counties an objective assessment of their built environment for exercise. It also provides a method for comparison across counties or states, allowing communities to gauge their access relative to their peers. Further, this measure will change as parks and recreational facilities are added or removed or when population shifts occur, so longitudinal trends analysis and the evaluation of interventions to improve access are possible. The main source of strength for the access to exercise opportunities measure is the use of GIS tools. This allowed us to create a measure that incorporates multiple locations for exercise from several data sources on a large geographic scale. Researchers and public health practitioners can tailor the measure to their local geographic needs by adjusting buffer distances and adding data from other sources unavailable at the national level.

There are several limitations inherent in creating a measure on a national scale using archival data. First, no data set accurately captures data on all the possible locations for exercise within a county. One notable location not included in this measure is sidewalks, common locations for running or walking. Additionally, not all locations for exercise are identified by their primary or secondary business code. For example, malls frequently have walking clubs and schools may have open gyms for community members. Second, although a county may contain a park or recreational facility, there may still be barriers, such as cost and distance, to using the facility. Locations for exercise, as defined by using NAICS secondary codes, may slightly overestimate access to exercise opportunities. This measure also did not capture data on other barriers to the accessibility of parks or recreational facilities for exercise. The size or amenities of parks clearly differs across the data set, and we were unable to adjust for hours of operation, entrance locations, fees for entrance to parks, or membership fees for gyms and exercise classes. Finally, there are potential inaccuracies in the data sources because they are from previous years and may not capture data on all of the opportunities for exercise.

The 2014 County Health Rankings included a measure of opportunities for exercise that is comparable across counties. Although the access to exercise opportunities measure is not all-inclusive, it is the first to combine parks and recreational facilities to create a county-level measure. This measure should serve as a call for researchers and public health officials to engage in activities related to enhancing the built environment for exercise, such as improving and maintaining parkland, reducing gym membership fees, or providing organized community recreation programs. With such activities, our understanding of how the built environment influences health will advance and lead to public health interventions to improve health for all.