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Association between leisure-time physical activity and the built environment in China: Empirical evidence from an accelerometer and GPS-based fitness app.

ABSTRACT: To reexamine the relationship between leisure-time physical activity (LTPA) and the built environment (BE), this paper takes advantage of the massive amount of data collected by an accelerometer and GPS-based fitness mobile app. Massive LTPA data from more than 3 million users were recorded by Codoon in 500m by 500m grid cells and aggregated to 742 natural cities in mainland China. Six BE indicators were quantified using GIS at the city scale. Robust regression analysis was used to estimate the correlation between LTPA and BE. Five of six BE indicators-connectivity, road density, land use mix, points of interest density, and density of parks and squares-were significantly, positively, independently, and linearly related to LTPA in the regression analysis. The study obtains findings that are consistent with the previous literature but also provides novel insights into the important role of POI density in encouraging LTPA, as well as how the relationship between LTPA and BE varies by time of day. The study also sheds light on the embrace of new technology and new data in public health and urban studies.

SUBMITTER: Chen L

PROVIDER: S-EPMC8719743 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Purpose: Most built environment studies have quantified characteristics of the areas around participants' homes. However, the environmental exposures for physical activity (PA) are spatially dynamic rather than static. Thus, merged accelerometer and global positioning system (GPS) data were utilized to estimate associations between the built environment and PA among adults. Methods: Participants (N = 142) were recruited on trails in Massachusetts and wore an accelerometer and GPS unit for 1-4 days. Two binary outcomes were created: moderate-to-vigorous PA (MVPA vs. light PA-to-sedentary); and light-to-vigorous PA (LVPA vs. sedentary). Five built environment variables were created within 50-meter buffers around GPS points: population density, street density, land use mix (LUM), greenness, and walkability index. Generalized linear mixed models were fit to examine associations between environmental variables and both outcomes, adjusting for demographic covariates. Results: Overall, in the fully adjusted models, greenness was positively associated with MVPA and LVPA (odds ratios [ORs] = 1.15, 95% confidence interval [CI] = 1.03, 1.30 and 1.25, 95% CI = 1.12, 1.41, respectively). In contrast, street density and LUM were negatively associated with MVPA (ORs = 0.69, 95% CI = 0.67, 0.71 and 0.87, 95% CI = 0.78, 0.97, respectively) and LVPA (ORs = 0.79, 95% CI = 0.77, 0.81 and 0.81, 95% CI = 0.74, 0.90, respectively). Negative associations of population density and walkability with both outcomes reached statistical significance, yet the effect sizes were small. Conclusions: Concurrent monitoring of activity with accelerometers and GPS units allowed us to investigate relationships between objectively measured built environment around GPS points and minute-by-minute PA. Negative relationships between street density and LUM and PA contrast evidence from most built environment studies in adults. However, direct comparisons should be made with caution since most previous studies have focused on spatially fixed buffers around home locations, rather than the precise locations where PA occurs.

Project description:BACKGROUND:Context-free outcome measures, such as overall leisure-time physical activity (LTPA), are habitually applied to study the neighborhood built environment correlates of physical activity. This cross sectional study identifies and empirically tests potential methodological limitations related to the use of context-free measures and discusses how these may help in the interpretation of inconsistent associations between participation in moderate-to-vigorous LTPA and objectively measured neighborhood-level built environment attributes. METHODS:We employ a public participation geographic information system (PPGIS), an advanced participatory mapping method, to study the spatial distribution of moderate-to-vigorous LTPA among adult urban Finnish residents (n 1322). Secondary sources of GIS land-use and sport facility data were used to disaggregate respondent-mapped LTPA by the behavioral context, such as indoor and outdoor sport facilities, green spaces, and other public open spaces. Associations between the use of the identified LTPA settings and a range of objectively measured neighborhood built environment attributes were studied with multilevel logistic regression models. RESULTS:Disaggregated by behavioral context, we observed varied and partly opposite built environment correlates for LTPA. The use of indoor and outdoor sport facilities showed no significant associations with their neighborhood availability, but were significantly associated with personal-level attributes. By contrast, participation in LTPA in green and built public open space shared significant associations with access to and availability of neighborhood green space that persisted after controlling for personal-level covariates. Moreover, neighborhood distances up to 1600 m poorly captured participation in moderate-to-vigorous LTPA, as, on average, 40% of visits were located further from home. However, we found the immediate home environment to be an important LTPA setting for the least active participants. CONCLUSIONS:This study demonstrates that LTPA can be a highly heterogeneous measure regarding both the spatial distribution and the environmental correlates of behavioral contexts. The results show that context-free LTPA outcome measures yield inconsistent associations with built environment exposure variables, challenging the applicability of such measures in designing neighborhood-level built environment interventions.

Project description:Leisure-time physical activity (LTPA) has been well documented as having substantial health benefits. The 2014 Chinese Fitness Survey Report stated that a lack of physical activity (PA) spaces is the most important non-human factor, leading to 10% of leisure-time physical inactivity in people aged 20 and above. We investigated the provision of sports venues in China and discussed the development of sports venues and national fitness policies in the context of promoting LTPA and public health. We analyzed information from China's most recent sport venue census, the Sixth National Sports Venues Census, conducted in 2013. The number of sports venues increased between 2000 and 2013, with an inflection point around the year 2008. At the end of 2013, there were 12.45 venues for every 10,000 residents, and the per capita area was 1.46 m2. However, numbers were still small compared with the United States and Japan. The percentages of full-time access, part-time access and membership venues were 51.5%, 14.3% and 34.2% respectively. Only half of sports venues were fully open to the public, meaning that the realized number and area per capita could be even lower. A lack of sports venues forces people who want to engage in PA to occupy other urban spaces that are not planned and designed for PA. Urban parks had 119,750 fitness station facilities (3.32% of the total), and 2366 urban fitness trails (19.24%), with a combined length of 6450 km (32.91%). On average, urban and rural areas had 13.17 and 10.80 venues per 10,000 persons, and 1.83 m2 and 0.97 m2 per capita. The urban-rural gap in sports venues exactly embodies some aspects of the "urban-rural dual structure" in China's society. Measures to promote PA should focus on new and existing sports venues. In the policy making process, Chinese governments need to pay attention to the potential impact of related, external factors such as the gap between the urban and the rural and the potential advantage of indoor venues against summer heat and air pollution.

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Association between leisure-time physical activity and the built environment in China: Empirical evidence from an accelerometer and GPS-based fitness app.

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