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Cutting edge methodology
P1-15 Obesity clustering in Cebu, Philippines: an application of satscan and the spatial scan statistic
  1. D Dahly
  1. University of Leeds, Leeds, UK


Introduction Obesity is an important, global, public health problem. To promote prevention, more research is needed to understand exactly how shared environments impact obesogenic behaviours. Identifying spatial clusters of obesity is the first step towards a better understanding of its environmental drivers, and can immediately inform public health practice. To date, research has overlooked lower-income contexts, where obesity is emergent and environments are changing at an unprecedented pace.

Methods Using data from a cohort of young adult Filipinos (21.5 y; n=1808), we used the Kulldorff spatial scan statistic to detect areas in Metropolitan Cebu with a high sample prevalence of obesity. Cluster locations were then compared to the urbanicity of constituent neighbourhoods. We also tested whether clusters were explained by the spatial distribution of household-assets scores in the study participants.

Results Significantly unusual clusters (rejection of H0: complete spatial randomness, at p<0.05) of overweight and obesity were detected for males and females. Clusters were primarily located in urban areas, but typically extended into peri-urban and even rural neighbourhoods. The exact location of clusters varied as a function of both sex and measure of obesity used. Clusters in males, but not females, were explained by the spatial distribution of socioeconomic status.

Conclusions Where a young adult lives is a strong predictor of obesity risk in Cebu. Environmental drivers of obesity among young adults in Cebu may vary by gender. Using simple urban-rural classifications to contextualise obesity in lower income countries may be overly simple, and misdirect public health efforts.

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