A Meta-analysis of the Literature on the Association of the Social and Built Environment With Obesity: Identifying Factors in Need of More In-Depth Research. Issue 5 (June 2019) - Zhang, Hao; Yin, Li
Objective: This study aims to identify groups of the social and built environment factors that have been studied substantially along with factors that need further attention, to guide the research, designing, and planning of the social and built environment for reducing obesity prevalence. Data Source: A systematic search of literature was undertaken from PubMed, Google Scholar, and Web of Knowledge. Study Inclusion and Exclusion Criteria: Keyword combination of "built environment, " "social environment, " and "obesity" were used to expand the search scope. Exclusion criteria included (1) any article with less than 50 citations from 2005 to 2010, and those with less than 25 citations from 2011 to 2015. In this way we included the most prominent peer-reviewed studies published in recent years while excluding less influential publications; (2) any article published in a language other than English; (3) literature review articles; (4) any article studying health outcomes not obesity related. We included research on eating behaviors since the studies contributed profoundly to food environment research. Data Synthesis: A meta-analysis of 153 empirical studies, selected from 2005 to 2015 based on a series of criteria, was conducted using factor analysis. The exploratory factor analysis was undertaken to group the prevalence and use of the social and built environment factors associated with obesity. Results: The findings suggested that the research community has gained a substantial understanding of the D variables of the built environment, including density, diversity, design, distance to transit, and destination access. Factors concerning different age groups, minority populations, groups with low socioeconomic status, food environment, and street-level urban design features have been less examined. Conclusions: The findings are important to guide future research directions, giving more attention to the factors in need of more in-depth research.