Overlay of geographical clusters of sweetened beverage consumption and body mass index in the canton of Geneva, Switzerland

Stéphane Joost, David De Ridder, Pedro Marques-Vidal, Beatrice Bacchilega, Jean-Marc Theler,Jean-Michel Gaspoz and Idris Guessous.
Overlapping spatial clusters of sugar-sweetened beverage intake and body mass index in Geneva state, Switzerland.Nutrition & Diabetes volume 9, Article number: 35 (2019)

Abstract

Background Obesity and related diseases represent a major public health issue. Recent studies have confirmed the role of sugar-sweetened beverage (SSB) consumption in the development of these diseases. The precise identification of populations and areas requiring public health action remains a challenge. Using a precision geospatial approach, this study examines the existence of geographical groupings(clusters) of SSB consumption frequency (SSB-IF) and body mass index (BMI), as well as their possible geographical superposition within the adult population of the canton of Geneva.

Methods We used data corresponding to self-reported SSB-IF and measured BMI among residents aged 20 to 74 in the canton of Geneva (Switzerland) who took part in the Bus Santé cross-sectional population study (n = 15,423). Getis-Ord Gi spatial indices were used to identify spatial clustering of SSB-IF and BMI within the unadjusted data and after adjustment for individual characteristics such as education level, sex, age, nationality and median neighbourhood income.

Results We identified significant spatial clustering of BMI and SSB-IF. 13.2% (n = 2034) of participants lived in clusters with higher SSB-IF and 10.7% (n = 1651) lived in clusters with lower SSB-IF. We identified overlaps of SSB-IF and BMI clusters in specific areas where 11.1% (n = 1719) of the participants lived. Even after adjusting for individual characteristics, the identified clusters persisted and were only slightly attenuated, indicating that other determinants at the neighbourhood level influence the geographical distribution of SBF-IF and BMI.

Conclusion: Our precision spatial approach identified specific populations and areas with a higher frequency of consumption of sugar-sweetened beverages. It also revealed a spatial association between higher frequency of consumption of sugar-sweetened beverages and higher BMI. These results could guide political authorities in developing locally adapted interventions such as targeted prevention campaigns, while paving the way for precision public health.

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