The association of unhealthy and healthy food store accessibility with obesity prevalence among adults in the Netherlands: A spatial analysis

Abstract

Introduction: Obesity prevalence has almost tripled in Europe since 1980, and the obesogenic (food) environment is hypothesised to be one of the main drivers. Still, empirical evidence is rare for Europe. Objective: This ecological study explores spatial patterns of obesity prevalence of adults (aged 19+) in the Netherlands in 2016. It studies, in particular, its global associations with (un)healthy food store accessibility while assessing local differences and evaluating the importance of the immediate versus the wider food surroundings. Methods: In our ecological study, we used small-area estimated obesity prevalence (adults, aged 19+) from 2836 neighbourhoods (six-digit postal codes, wijken) and combined this with measures from Statistics Netherlands on accessibility to (unhealthy) fast food and (healthy) fresh food. Spatial lag of X (SLX) models were estimated for the entire Netherlands to explore global associations. Separate models for urban, suburban, and rural neighbourhoods and a geographically weighted regression (GWR) were estimated to explore and visualise local variations in the associations. Total associations from the SLX models were then decomposed to yield contributions of the immediate and wider food surroundings. Results: Regional clusters of high obesity were observed in selected areas in the north-east, the south-west, and south-east. Limited accessibility to unhealthy food was globally associated with lower obesity prevalence, whereas better accessibility to fresh food stores and supermarkets was not. The association regarding worse accessibility to unhealthy food was strongest for urban neighbourhoods, especially for the Randstad region. In urban settings, also better accessibility to fresh food stores proved relevant. The wider food surrounding proved more important than the immediate food surrounding, throughout. Discussion: Public policies addressing obesity might be more effective when reducing the presence of unhealthy food rather than expanding healthy food supply. Moreover, they should focus on urban regions and high obesity clusters, thereby considering wider food surroundings.

Keywords

• Local food environment
• Obesity
• Spatial analysis
• Spatial lag of X model
• Geographically weighted regression