Do the Walkability and Urban Leisure Amenities of Neighborhoods Affect the Body Mass Index of Individuals? Based on a Case Study in Seoul, South Korea

Abstract

This study investigates the impact of neighborhood-built environments on obesity in interrelationship with socioeconomic status (SES)—controlling for dietary patterns and physical activities of residents—using structural equation modeling (SEM). A total of 577 samples who are between 19 and 64 years old and reside in Seoul are extracted from Korea National Health and Nutrition Examination Survey (KNHNES), 2015. Neighborhood environments are represented as the two latent constructs—walkability and leisure amenities—composited with indicators such as density of intersections, density of mixed-use area, and the area of open spaces and are aggregated by jurisdictional unit in Seoul. We found that greater walkability in a neighborhood explained a lower body mass index (BMI) among residents, whereas more urban leisure amenities in a neighborhood explained a higher BMI. The finding suggests that a walking-friendly environment is more effective than active recreational amenities in inducing people to engage in daily physical activities to the level that reduces obesity rate. SES exerted a negative impact on BMI of a greater magnitude than the impact of either of the environmental living conditions, reinforcing the importance of general wealth and education level in leading to a healthy lifestyle. Our research contributes to growing evidence of a relationship between obesity and the built environment in the context of Asian countries where the prevalence of obesity is becoming a serious issue and requires immediate attention.

Social Environment Related to Opportunities for Physical Activity within Different types of Built Environments: A Scoping Review

“…The presence and accessibility of walking facilities are generally identi ed as supporting walking [30,31]. In contrast to studies suggesting higher walkability in high-SES areas, an inverse relationship was found in studies by Choi and Yoon [32] and Conderino et al [2]. The last study reported that on average, low-income neighbourhoods had higher walking scores than high-income ones.…”

“…linked local economic resources with the number of sports facilities and PA, especially among older individuals and women.Hillsdon et al [78] and studies from Asia[32,34] observed a positive association between SES and leisure amenity availability.Ferguson et al [79] and Lamb et al [80] showed that public transport access in low-income areas provides closer proximity to sports facilities, a difference nulli ed by car ownership. Panter et al [81] and Hillsdon et al [53] discussed how poor facility coverage in deprived English areas affects PA levels, with individuals often travelling beyond local areas for activity.…”

Exploring the impact of pandemic fear on visitation to park attractions in urban city: A case study in Seoul, South Korea

“…This ensures that the parameter estimates remain unbiased. SEM provides a comprehensive, flexible approach for analyzing complex relationships between variables, making it valuable for validation or exploratory purposes [ 63 , 64 ].…”

Demographic data in the built environment and human health studies

“…Similar surveys exist in other countries. South Korea, for example, also conducts a national-level survey (i.e., Korea National Health and Nutrition Examination Survey [KNHNES]) [46]. (d) Mortality data: data on causes of death in the United States.…”