Identifying obesogenic environment through spatial clustering of body mass index among adults

Abstract

Abstract Background The environment plays a pivotal role in the increasing prevalence of obesity especially in developing countries due to globalization and nutrition transition. The tendency of body mass index (BMI) to cluster spatially indicates the presence of an obesogenic environment. However, spatial clustering analysis often requires lower regional data which are a challenge in developing countries. Therefore, this study aimed to determine the spatial clustering of BMI among adults in Malaysia through available point locations of national health survey respondents. Method This study utilized information of respondents aged 18 to59 years old from the National Health and Morbidity Survey (NHMS) 2014 and 2015 at Peninsular Malaysia and East Malaysia. Fast food restaurant proximity, district population density, and district median household income were determined from other sources. The analysis was conducted for total respondents and stratified by sex. Results Multilevel regression was used to produce the BMI estimates on a set of variables, adjusted for data clustering at enumeration blocks. Global Moran’s I and Local Indicator of Spatial Association statistics were applied to assess the general clustering and location of spatial clusters of BMI, respectively. Point locations of respondents and spatial weights of 8 km Euclidean radius or 5 nearest neighbours were applied. Spatial clustering of BMI independent of individual sociodemographic was significant (p < 0.001) in Peninsular and East Malaysia with Global Moran’s index of 0.12 and 0.15, respectively. High-BMI clusters (hotspots) were in suburban areas, whilst the main cities were low-BMI clusters (cold spots). Spatial clustering was greater among males with hotspots located closer to urban areas, whereas hotspots for females were in less urbanized areas. Conclusion Obesogenic environment was identified in suburban areas, where spatial clusters differ between males and females in some areas. Future studies and interventions on creating a healthier environment should be geographically targeted and consider gender differences.