打印

作者

Chia-Yuan Yu;Ayoung Woo;Christopher T. Emrich;Biyuan Wang

来源

CITIES,Vol.97,Issue1,Article 102531

语言

英文

关键字

Built environment;Structural equation model;Multi-level;Health prevention;Social vulnerability

作者单位

School of Public Administration, College of Community Innovation and Education, University of Central Florida, Orlando, FL, USA;Graduate School of Urban Studies, Hanyang University, Seoul, Republic of Korea;H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, USA;School of Public Administration, College of Community Innovation and Education, University of Central Florida, Orlando, FL, USA;Graduate School of Urban Studies, Hanyang University, Seoul, Republic of Korea;H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, USA

摘要

The Social Vulnerability Index (SoVI) includes multiple socioeconomic and demographic indicators related to the risk of obesity. However, it is uncertain how the SoVI input variables empirically affect the individual-level risk of obesity or the mechanisms contributing to the condition via the contextual built environment. This study examines the influence of social vulnerability on individual obesity through county-level built environments, using both individual- and county-level data. The total sample size was 204,610 respondents from 205 counties in the US. We employed two-level structural equation modeling to test the hypothesized relationships. The results indicate that counties with high index of Hispanics, African Americans, females, single-parent families, and residents without health insurance were all linked to higher percentages of fast food restaurants and reduced access to exercise opportunities. Furthermore, counties with higher percentages of older adults and population with special needs were positively related to obesity, while wealthier counties and those with larger Asian populations were negatively related to obesity. Our results demonstrate that SoVI variables may be a quality substitute for typical needs assessments, not only for emergency preparedness but also for health prevention.