Features of the built environment (BE) are related to a wide range of health factors, including leisure-time physical activity (PA) and active forms of transportation. For working adults, worksite neighborhood is likely an important BE to better understand the impact of various factors on PA patterns. Compared to home neighborhood walkability research, worksite walkability has received relatively less attention. The objective of this project was to identify if worksite walkability was significantly associated with PA behavior.

Aims: to evaluate 1) the PA variation explained by work walkability, 2) the moderating effects of person-level characteristics to the relationship between PA and work walkability, and 3) the differences in the rate of change in PA over time by worksite walkability.

Methods: self-report and accelerometer measured PA at baseline (aim 1, 2); longitudinal accelerometer PA during the initial 56 days of a behavioral intervention (aim 3). Adults were generally healthy and reported part- or full-time employment with a geocodeable address outside the home. Geographic Information Systems (GIS) measured walkability followed established techniques (i.e., residential, intersection, and transit densities, and land-use-mix).

Results: On average, worksite walkability did not show direct relationships with PA (aim 1); yet certain person-level characteristics moderated the relationships: sex, race, and not having young children in the household (aim 2). During 56 days of intervention, the PA rate of change over time showed no evidence of a moderating effect by worksite walkability.

Discussion: Worksite walkability was generally not shown to relate to the overall PA. However, specific subgroups (women, those without young children) appeared more responsive to their worksite neighborhood walkability. Prior literature shows certain demographics respond differently with various BE exposures, and this study adds a potentially novel moderator of interest regarding young children at home. Understanding who benefits from access to walkable BE may inform targeted interventions and policy to improve PA levels and foster health equity.

Individuals in urban low-income areas often do not have easy access to large grocery stores and supermarkets, and regularly shop at nearby small/corner stores. These stores stock an abundance of processed, energy-dense, nutrient poor foods, combined with few nutrient-dense products. A high concentration of small/corner stores is associated with poor diets by nearby residents. Interventions that target small food stores for increasing the availability and sale of healthy foods have been launched in many communities, and validated survey instruments have been developed to evaluate the effectiveness of the interventions. However, in-store surveys can take up to thirty minutes to conduct and require individual visits from investigators. Many projects assess the food environment in a large number of stores spread across broad geographical areas, making in-person evaluations infeasible and resource-prohibitive. The purpose of this study was to develop a valid and feasible short survey that could be used in-store or over the phone to capture the healthfulness of corner stores. An adapted version of the Nutrition Environment Measures Survey for Corner Stores (NEMS-CS) was used to conduct store audits of 230 corner stores in four New Jersey cities. Audit results were used in exploratory factor analysis and item response theory to develop a seven-item survey. The short survey was highly correlated with the full survey (r=0.79), and the short survey's classification of stores as healthy (top 20% of scores) versus unhealthy (bottom 80% of stores) matched NEMS-CS categorizations in 88% of cases. A second round of audits was conducted in 100 corner stores to confirm the validity of the seven-item survey and to test its feasibility as a phone audit tool. Complete phone responses were obtained from 86% of stores. Response matches indicated that store owners did not distinguish between 2% and low-fat milk, and tended to round up the fruit and vegetable count to five if they had fewer varieties. The seven-item short survey discriminates between healthy and unhealthy stores and is feasible for use as a phone audit tool.