What is the cross-sectional association of geospatially derived walkability with walking for leisure and transport? - Adalberto A. S. Lopes; Larissa L. Lima; Amanda S. Magalhães; Amanda C. S. Andrade; Tiago Canelas; Louise Foley; Tolu Oni; Waleska T. Caiaffa (PLoS ONE, 2025)
Background Built environments have been shown to shape active living behaviours, including walking. However, this literature is drawn predominantly from Europe and North America. This study aimed to create a geospatially derived city-wide walkability index and further investigate the association with walking in Belo Horizonte, Brazil. Methodology A cross-sectional analysis was conducted using data from participants in the 2014-15 MOVE-SE study in Belo Horizonte. A walkability index was created at the census tract level, which included net residential density, land use mix, and street connectivity, using ArcGIS software. Walking for leisure and transportation was self-reported via the International Physical Activity Questionnaire. Covariates such as sociodemographic characteristics, health indicators, and neighbourhood context were measured. A multilevel negative binomial regression was employed, incorporating confounders across five combined models with sequential addition of covariate groups. All statistical analyses were conducted in R software with a significance threshold of 5%. Results The study included 1,372 adults aged 18 years and older, with a female majority of 60.5%, a median age of 41, and 45.9% completed at most primary schooling. The family income for 63.7% ranged between one to three times the minimum wage. Self-rated health was considered good by 64.7% of participants, and the median Body Mass Index (BMI) was 26.2 kg/m2. Regarding neighbourhood context, the median length of residence was 15 years, per capita monthly income was US$175, and the average land slope was 8.2%. Participants reported a median of 180 minutes per week (interquartile range: 120 – 250) for walking for leisure and transportation. The median walkability index was -0.51 (interquartile range: -1.40 – 1.21). After adjusting for confounders, the final model indicated a positive association between the walkability index and walking for leisure (IRR: 1.33; CI95%:1.32-1.35; p < 0.001) and transportation (IRR: 1.22; CI95%:1.20-1.24; p < 0.001). Discussion The findings demonstrate a positive association between higher levels of walkability and increased walking behaviours in various contexts. It underscores the importance of urban planning, design, and policy interventions tailored to local environments to promote walkability, reduce car dependency, and facilitate healthier lifestyles as part of everyday living.