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Bikesharing programs in their current form have been in place for several years in many cities across the United States. Encouraging people to use bikesharing for their daily routine travels has numerous social, economic, environmental, and health benefits. Therefore, it is important to understand factors influencing bikesharing usage in different urban areas in order to improve the system and encourage more use. This paper investigates how built environment at both local and regional scales influences bikesharing usage in five large metropolitan US areas in the US The study areas include Boston, Chicago, Philadelphia, Minneapolis, and Washington, DC and the data consists of around 9 million bike trips in over 1,500 stations over a one-year period. Multi-level mixed effect regression model is built to predict the number of trips originated from each station with respect to the station’s built environment pattern, as well as the overall urban form in the entire city. The results are consistent with previous research on the effect of land use at the local level on bikesharing demand. At the regional level, results suggest that the overall walkability and job accessibility via bikesharing networks are significant factors influencing bikesharing activities and demand. Models developed in this study could be applied to other communities that are seeking to improve and/or expand their bikesharing systems, as well as cities planning to launch new bikesharing programs.