Comparing objective measures of environmental supports for pedestrian travel in adults

Abstract

BackgroundEvidence is growing that the built environment has the potential to influence walking--both positively and negatively. However, uncertainty remains on the best approaches to representing the pedestrian environment in order to discern associations between walking and the environment. Research into the relationship between environment and walking is complex; challenges include choice of measures (objective and subjective), quality and availability of data, and methods for managing quantitative data through aggregation and weighting. In particular, little research has examined how to aggregate built environment data to best represent the neighborhood environments expected to influence residents' behavior. This study examined associations between walking and local pedestrian supports (as measured with an environmental audit), comparing the results of models using three different methods to aggregate and weight pedestrian features.MethodsUsing data collected in 2005-2006 for a sample of 251 adult residents of Montgomery County, MD, we examined associations between pedestrian facilities and walking behaviors (pedestrian trips and average daily steps). Adjusted negative binomial and ordinary least-squares regression models were used to compare three different data aggregation techniques (raw averages, length weighting, distance weighting) for measures of pedestrian facilities that included presence, condition, width and connectivity of sidewalks, and presence of crossing aids and crosswalks.ResultsParticipants averaged 8.9 walk trips during the week; daily step counts averaged 7042. The three aggregation techniques revealed different associations between walk trips and the various pedestrian facilities. Crossing aids and good sidewalk conditions were associated with walk trips more than were other pedestrian facilities, while sidewalk facilities and features showed associations with steps not observed for crossing aids and crosswalks.ConclusionAmong three methods of aggregation examined, the method that accounted for distance from participant's home to the pedestrian facility (distance weighting) is promising; at the same time, it requires the most time and effort to calculate. This finding is consistent with the behavioral assumption that travelers may respond to environmental features closer to their residence more strongly than to more distant environmental qualities.

Modeling public-transit connectivity with spatial quality-of-transfer measurements

“…The choice of walking of a transit passenger involves the uncertainty of missing a connection; fear of crime; weather; distance/time; social pressure; fatigue and fitness; parking charges (for park-and-ride); enjoyment of walking; inconvenience; and geography (Walton and Sunseri, 2010). Street-crossing aids and sidewalk conditions are also influencing the number of walk trips (Shay et al, 2009), and so are the street-crossing conditions (Hubbard et al, 2009).…”

Identifying GIS Measures of the Physical Activity Built Environment Through a Review of the Literature

“…Thirteen studies measured outcomes for total physical activity mediated by variables characterized along the 5 dimensions of access. 14,15,[19][20][21]25,30,32,35,37,39,41,42 In a similar fashion, leisure-time physical activity 14,16,[18][19][20][21][22]24,25,27,[29][30][31]34,[39][40][41] and transportation physical activity [17][18][19][20][21][22][23][25][26][27][28]30,32,34,36,38,39 were assessed in 17 of the studies in our review. With the exception of one study, 36 the geographic scale of analysis ranged from a one-quarter mile to a 3 mile radius about the study participant's geocoded home location.…”

“…The presence of sidewalks emerged as the only accessibility indicator of higher physical activity for this domain. 42 Measures of accessibility associated with leisure-time physical activity included sidewalk coverage and street connectivity. 27,30 Street pattern and access to public transit stops were the most common measures used in testing for associations with transportation physical activity.…”

Caminhabilidade e envelhecimento saudável: uma proposta de análise para cidades brasileiras de pequeno e médio porte

“…Espera-se que um maior número de interseções em cada área proporcione maior conectividade nas ruas e maior variedade de itinerários para caminhadas, o que, por sua vez, afeta positivamente a capacidade de locomoção a pé 15,44,45,46,47,48,49 Sim Crimes O número de ocorrências de delitos registrados indica o quanto os pedestres em circulação em determinado local estão expostos a riscos relativos à segurança pública. A maior ocorrência está associada com a menor chance de caminhada 44,50,51,52 Não Declividade A diferença de altura entre dois pontos ao longo de uma caminhada tem influência significativa na energia necessária para andar entre eles estando a maior inclinação do terreno associada a menores chances de caminhar 44,53,54,55 Não Densidade comercial Uma vez que sugere uma área onde muitos lugares estão a uma curta distância, um maior número de lojas e empresas pode influenciar positivamente a mobilidade 52,56 Sim Densidade residencial A alta densidade residencial implica áreas mais comerciais e recreativas na proximidade de áreas de habitação densas, influenciando positivamente a mobilidade 47,49,55,56,57,58 Sim Iluminação pública Calçadas e espaços públicos bem iluminados são essenciais para levar mais pessoas a aproveitarem os espaços. Espaços ativos e bem iluminados não são propícios ao crime e aumentam a sensação de segurança de seus usuários e a facilidade de caminhar à noite 52,59,60 Sim Paradas de transporte público Maior densidade de paradas e estações de ônibus e metrô afeta positivamente a capacidade de locomoção porque o transporte público mais elevado sugere uma infraestrutura urbana bem desenvolvida 9,52,61 Não Presença de calçadas A presença de calçadas pode influenciar a prática de atividade física, principalmente a caminhada, já que facilita os deslocamentos por oferecer segurança e atratividade 54,55,…”