The development, validation, and application of the campus walk score measurement system.

Improving campus walkability can encourage students to walk and may inhibit the development of sedentary lifestyle habits, obesity, diabetes, and other health issues. This study aimed to formulate an optimized campus Walk Score (WS) measurement system that combines students' weekly demand for the use of facilities and unique campus environments. Bivariate correlation analysis and regression models were used to verify this system. The verified system was further applied to assess campus walkability and its influencing factors. The facility weight and walking time were established through questionnaires distributed on eight campuses in Tianjin, China. GIS and field audits were utilized to collect data on the objective built environment (BE), subjective environmental quality variables, and pedestrian volume (PV). Pearson's correlation analysis and Negative binomial regression models without spatial autocorrelation were used to verify the campus WS measurement system. The significant relationships between BE features and overall WS were found. PV was significantly correlated with overall WS and classified WSs. These findings were all found in the overall and three types of campuses. Therefore, our optimized system can be verified. Additionally, the WS was closely associated with facility distribution, planning mode, and other spatial attributes. Based on our results, how our findings can be utilized to promote campus walkability was proposed. • This study presented and verified a campus walkability measurement system based on the optimized Walk Score method. • Campus Walk Scores significantly correlated with built environment features and pedestrian volume. • The campus WS is closely associated with facility distribution, planning mode, and other spatial attributes. • Applications of the presented campus WS measurement system were proposed. [ABSTRACT FROM AUTHOR]