Identifying clusters of active transportation using spatial scan statistics.

ABSTRACT:

Background

There is an intense interest in the possibility that neighborhood characteristics influence active transportation such as walking or biking. The purpose of this paper is to illustrate how a spatial cluster identification method can evaluate the geographic variation of active transportation and identify neighborhoods with unusually high/low levels of active transportation.

Methods

Self-reported walking/biking prevalence, demographic characteristics, street connectivity variables, and neighborhood socioeconomic data were collected from respondents to the 2001 California Health Interview Survey (CHIS; N=10,688) in Los Angeles County (LAC) and San Diego County (SDC). Spatial scan statistics were used to identify clusters of high or low prevalence (with and without age

SUBMITTER: Huang L 

PROVIDER: S-EPMC2739375 | biostudies-literature | 2009 Aug

REPOSITORIES: biostudies-literature