In this study, we present the results of longitudinal walking behaviors, before and after changes to the built environment occurring at a university campus in Hong Kong, and find that as exposure to the built environment changes, so do walking behaviors, including daily distances walked, the proportion of trips which are walked, and the altitude ranges walked by students.
Specifically, we found that an increase in pedestrian network connectivity, as measured by road intersections, was associated with a greater walking distance and walking ratio. Our findings are consistent with previous literatures showing that increased pedestrian network connectivity encourages walking for transportation [8, 23–25]. For example, Berrigan, D. and his colleagues found that street connectivity accounted for a small but significant influence on active transportation , while the Twin Cities walking study also reported positive associations between street connectivity and walking for transportation [24, 25]. Few studies, however, have been conducted in hilly topography environments, where pedestrian networks may not easily be established and added. In this longitudinal study we found that after the establishment of new pedestrian networks in a hilly environment, as measured by intersection density, people walked longer distance and their walking ratio also increased. These results provide evidence to suggest that even in hilly environments, walking can be promoted by increased pedestrian connectivity.
We found that changes to land use, including increasing the number work area buildings and life area buildings, influenced walking behaviors, but in different aspects. An increase in the number of work area buildings resulted in subjects having a decrease in the altitude ranges they walked, while the increased exposure to life area buildings encouraged subjects to take longer walking trips. For the destination-oriented walking findings in this study, newly established work area buildings mostly located in the lower height level of campus might serve as trip destinations thus decreasing walked altitude ranges. Increased life area buildings might provide more potential opportunities for walking trips. In addition, we noted that most of the newly constructed life area buildings were in locations closely connected to the newly established escalator. This may have a contributory effect on walking distance promotion. Our findings also highlight the need to parcel land use into distinct categories, as different land uses seem to influence different aspect of walking behaviors. However, very few studies have investigated the differential impact of different types of land uses [26–28]. Hirsch, J. A. and her colleagues used discrete land uses categorized by accessibility, intensity, and diversity to examine the influence on walking behaviors, and found small but non-significant associations in the expected direction between disaggregated land use measures and walking for transportation in New York. They postulate that individual components of land use patterns, which act as small components of the entire built environment, act in concert with other environmental features to encourage walking . Our longitudinal study likewise provides new evidence that discrete land use categories may help identify unique influences on walking behavior.
We found that changes to “soft” infrastructure such as to campus bus service, significantly influenced walking behavior on campus. Notably, after changes in the bus schedules were implemented, students altered the altitude ranges they were willing to walk. We considered walking and bus riding behaviors together. We did not find statistically significant evidence for partition of the trips by travel mode. The results were in the expected direction, with an increase in regular bus schedules negatively influencing walking ratio, and a decrease in middle-class bus schedules positively influencing walking ratio. These findings might imply a competitive relationship between different travel modes (walking versus bus riding). Our findings highlight the importance of including both non-motorized (walking of cycling) and motorized (car driving or bus riding) transportation when assessing travel patterns, otherwise a potential exists to fail to capture the complete picture of walking behaviors. Recently, other work has also begun using both Walking and Transit scores to assess the impact of the built environment on walking patterns . The categorization of bus services by intended function creates two different bus measures that avoid a zero-sum issue that could arise from a single bus measure which sums increases and decreases in services, potentially failing to capture changes to different types of services.
We found that an increase in population density was related to a significant increase in students’ walked altitude range, and overall walked distances. In the university’s hilly environment, it appears that population density played an important role on student’s walking choices. One possible explanation for our findings might be that as population density increases, crowding for bus transportation may intensify with a ceiling effect on ridership. In interviews we conducted with subject prior to this natural experiment, subjects reported a preference for walking if buses were crowded, even within the university’s hilly topography. Population density is a social aspect of the built environment, and decisions on whether to walk or ride a bus with friends may likewise be related to social environment influences .
The study has several limitations. Our study did not include a control group. Nevertheless, we found significant changes in walking behavior after changes to the built environment. We collected one follow-up survey in this study, and longer term effects on walking behavior are not clear . Our walking diary was not validated, though it was adapted from established travel diaries  and was assessed for face validity with experts in urban planning and pilot tested on volunteers. We postulated a simplified assumption on the population density distribution which is an even distribution throughout the campus. The population density would likely change throughout the day due to student movement around campus. This study did not measure the exact locations of the entire student body at different times throughout the day. The study included students at a single university in Hong Kong and findings may not be generalizable. Subjects in our study were 18 to 20 years old students; their age and student status may influence their walking choices. Finally, though our built environment variables included distinct measureable changes in the physical infrastructure, it is still difficult to rule out the possibility that other coinciding changes in the built environment may not also have played a role in the observed changes in walking behavior. This possibility of residual confounding makes it somewhat difficult to give clear guidance to urban planners or public health practitioners.
Despite these limitations, our study has important strengths. The longitudinal survey design provides insight into causal relationships. To our knowledge, there are few longitudinal studies that combine before-and after survey data with measured changes to the built environment, to study changes in walking behavior. Krizek K. J. used longitudinal household travel data in Seattle to examine the relationship between changes in neighborhood and household travel behavior. The results show that after controlling for changes in lifestyle, relocating households to neighborhoods with more accessibility could effectively reduce vehicle miles traveled, but found no significant effect on trip generation or travel mode . Cao and colleagues studied people who relocated in Northern California and identified promising neighborhood characteristic after controlling for “self-selection” (individuals who like to walk move to more walkable areas), however, recall bias after residential relocation remained possible . Natural experiments, especially those involving changes to the built environment are rare and difficult to anticipate, which can also make it difficult to follow a cohort of subjects over time. Our longitudinal study with a built environment natural experiment provides empirical evidence on how changes to the built environment are associated with changes in walking behavior.