Home and Workplace Built Environment Supports for Physical Activity

BACKGROUND: Physical inactivity has been associated with obesity and related chronic diseases. Understanding built environment (BE) influences on specific domains of physical activity (PA) around homes and workplaces is important for public health interventions to increase population PA.

PURPOSE: To examine the association of home and workplace BE features with PA occurring across specific life domains (work, leisure, and travel).

METHODS: Between 2012 and 2013, telephone interviews were conducted with participants in four Missouri metropolitan areas. Questions included sociodemographic characteristics, home and workplace supports for PA, and dietary behaviors. Data analysis was conducted in 2013; logistic regression was used to examine associations between BE features and domain-specific PA.

RESULTS: In home neighborhoods, seven of 12 BE features (availability of fruits and vegetables, presence of shops and stores, bike facilities, recreation facilities, crime rate, seeing others active, and interesting things) were associated with leisure PA. The global average score of home neighborhood BE features was associated with greater odds of travel PA (AOR=1.99, 95% CI=1.46, 2.72); leisure PA (AOR=1.84, 95% CI=1.44, 2.34); and total PA (AOR=1.41, 95% CI=1.04, 1.92). Associations between workplace neighborhoods' BE features and workplace PA were small but in the expected direction.

CONCLUSIONS: This study offers empirical evidence on BE supports for domain-specific PA. Findings suggest that diverse, attractive, and walkable neighborhoods around workplaces support walking, bicycling, and use of public transit. Public health practitioners, researchers, and worksite leaders could benefit by utilizing worksite domains and measures from this study for future BE assessments.

Choice of commuting mode among employees: Do home neighborhood environment, worksite neighborhood environment, and worksite policy and supports matter?

BACKGROUND: Promoting the use of public transit and active transport (walking and cycling) instead of car driving is an appealing strategy to increase overall physical activity.

PURPOSE: To quantify the combined associations between self-reported home and worksite neighborhood environments, worksite support and policies, and employees' commuting modes.

METHOD: Between 2012 and 2013, participants residing in four Missouri metropolitan areas were interviewed via telephone (n = 1,338) and provided information on socio-demographic characteristics, home and worksite neighborhoods, and worksite support and policies. Commuting mode was self-reported and categorized into car driving, public transit, and active commuting. Commuting distance was calculated using geographic information systems. Commuters providing completed data were included in the analysis. Multivariate logistic regression models were used to examine the correlates of using public transit and active commuting.

RESULT: The majority of participants reported commuting by driving (88.9%); only 4.9% used public transit and 6.2% used active modes. After multivariate adjustment, having transit stops within 10-15 minutes walking distance from home (p=0.05) and using worksite incentive for public transit (p<0.001) were associated with commuting by public transit. Commuting distance (p<0.001) was negatively associated with active commuting. Having free or low cost recreation facilities around the worksite (p=0.04) and using bike facilities to lock bikes at the worksite (p<0.001) were associated with active commuting.

CONCLUSION: Both environment features and worksite supports and policies are associated with the choice of commuting mode. Future studies should use longitudinal designs to investigate the potential of promoting alternative commuting modes through worksite efforts that support sustainable commuting behaviors as well as the potential of built environment improvements.

The first WASP public data release

The WASP (wide angle search for planets) project is an exoplanet transit survey that has been automatically taking wide field images since 2004. Two instruments, one in La Palma and the other in South Africa, continually monitor the night sky, building up light curves of millions of unique objects. These light curves are used to search for the characteristics of exoplanetary transits. This first public data release (DR1) of the WASP archive makes available all the light curve data and images from 2004 up to 2008 in both the Northern and Southern hemispheres. A web interface () to the data allows easy access over the Internet. The data set contains 3 631 972 raw images and 17 970 937 light curves. In total the light curves have 119 930 299 362 data points available between them.