Dataset Information

Neighborhood Walkability and Active Transportation: A Correlation Study in Leisure and Shopping Purposes.

ABSTRACT: A walkable environment is a crucial factor for promoting active transportation. The purpose of this study is to examine the association between neighborhood walkability and active transportation for noncommuting purposes (leisure and shopping) in Seoul, Korea. The Walkability Score is used as a measure of walkability, and a multilevel logistic regression model is employed to measure the odds of active transportation (i.e., walking and cycling; nonmotorized trips) at two levels: individual (level 1) and neighborhood (level 2). The results of the study showed that the Walkability Score was significantly correlated with higher odds of active transportation in shopping models. Specifically, every one-point increase in the Walkability Score was associated with 1.5%-1.8% higher odds of active transportation in shopping models. However, there was no significant correlation between the two in leisure models. Meanwhile, individual characteristics associated with the odds of active transportation differed in the leisure and shopping models. Older age was positively correlated with the odds of active transportation in the leisure model, while females showed a positive correlation in the shopping model. Based on the study, urban and transportation planners can recommend urban policies to promote active transportation in an urban setting.

SUBMITTER: Kim EJ

PROVIDER: S-EPMC7177876 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Neighborhood Walkability and Active Transportation: A Correlation Study in Leisure and Shopping Purposes.

Kim Eun Jung EJ Kim Jiyeong J Kim Hyunjung H

International journal of environmental research and public health 20200325 7

A walkable environment is a crucial factor for promoting active transportation. The purpose of this study is to examine the association between neighborhood walkability and active transportation for noncommuting purposes (leisure and shopping) in Seoul, Korea. The Walkability Score is used as a measure of walkability, and a multilevel logistic regression model is employed to measure the odds of active transportation (i.e., walking and cycling; nonmotorized trips) at two levels: individual (level ...[more]

PMID: 32218233

Similar Datasets

Project description:Walking, and in particular, outdoor walking, is the most common form of physical activity for older adults. To date, no study investigated the association between the neighborhood built environment and physical activity habits of older adults of low SES. Thus, our overarching aim was to examine the association between the neighborhood built environment and the spectrum of physical activity and walking for transportation in older adults of low socioeconomic status.Cross-sectional data were from the Walk the Talk Study, collected in 2012. Participants (n?=?161, mean age?=?74 years) were in receipt of a rental subsidy for low income individuals and resided in neighbourhoods across Metro Vancouver, Canada. We used the Street Smart Walk Score to objectively characterize the built environment main effect (walkability), accelerometry for objective physical activity, and the Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire to measure walking for transportation. We used regression analyses to examine associations of objectively measured physical activity [total volume, light intensity and moderate intensity physical activity (MVPA)] and self-reported walking for transportation (any, frequency, duration) with walkability. We adjusted analyses for person- and environment-level factors associated with older adult physical activity.Neighbourhood walkability was not associated with physical activity volume or intensity and self-reported walking for transportation, with one exception. Each 10-point increase in Street Smart Walk Score was associated with a 45% greater odds of any walking for transportation (compared with none; OR?=?1.45, 95% confidence interval?=?1.18, 1.78). Sociodemographic, physical function and attitudinal factors were significant predictors of physical activity across our models.The lack of associations between most of the explored outcomes may be due to the complexity of the relation between the person and environment. Given that this is the first study to explore these associations specifically in older adults living on low income, this study should be replicated in other settings.

Project description:Background Literature focusing on youth has reported limited evidence and non-conclusive associations between neighborhood walkability measures and active commuting to and from school (ACS). Moreover, there is a lack of studies evaluating both macro- and micro-scale environmental factors of the neighborhood when ACS is analyzed. Likewise, most studies on built environment attributes and ACS focus on urban areas, whereas there is a lack of studies analyzing rural residential locations. Moreover, the relationship between built environment attributes and ACS may differ in children and adolescents. Hence, this study aimed to develop walkability indexes in relation to ACS for urban and rural children and adolescents, including both macro- and micro-scale school-neighborhood factors. Methods A cross-sectional study of 4593 participants from Spain with a mean age of 12.2 (SD 3.6) years was carried out. Macro-scale environmental factors were evaluated using geographic information system data, and micro-scale factors were measured using observational procedures. Socio-demographic characteristics and ACS were assessed with a questionnaire. Several linear regression models were conducted, including all the possible combinations of six or less built environment factors in order to find the best walkability index. Results Analyses showed that intersection density, number of four-way intersections, and residential density were positively related to ACS in urban participants, but negatively in rural participants. In rural children, positive streetscape characteristics, number of regulated crossings, traffic calming features, traffic lanes, and parking street buffers were also negatively related to ACS. In urban participants, other different factors were positively related to ACS: number of regulated crossings, positive streetscape characteristics, or crossing quality. Land use mix acted as a positive predictor only in urban adolescents. Distance to the school was a negative predictor on all the walkability indexes. However, aesthetic and social characteristics were not included in any of the indexes. Conclusions Interventions focusing on improving built environments to increase ACS behavior need to have a better understanding of the walkability components that are specifically relevant to urban or rural samples.

Dataset Information

Neighborhood Walkability and Active Transportation: A Correlation Study in Leisure and Shopping Purposes.

Publications

Neighborhood Walkability and Active Transportation: A Correlation Study in Leisure and Shopping Purposes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets