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Detecting overlapping spatial clusters of high sugar-sweetened beverage intake and high body mass index in a general population: a cross-sectional study

By Stephane Joost, David De Ridder, Pedro Marques-Vidal, Beatrice Bacchilega, Jean-Marc Theler, Jean-Michel Gaspoz, Idris Guessous

Posted 29 Aug 2018
bioRxiv DOI: 10.1101/399584

Background: Evidence suggests that sugar-sweetened beverage (SSB) intake frequency is positively associated with the risk of obesity and diabetes. We aimed to identify populations and areas in high need for interventions to reduce SSB consumption using a fine scale geographical approach. Methods: Geo-referenced data from the population-based Bus Santé study (adults, n=15,767), state of Geneva, Switzerland) were used. SSB intake frequency was estimated using a validated food frequency questionnaire. We implemented spatial statistics to investigate the geographic dependence of SSB intake frequency and body mass index (BMI). Results: SSB intake frequency was not randomly distributed across the state. We identified clear clusters of high and low SSB intake frequency values. One eighth of the population was within clusters of high SSB intake frequency. We also identified clusters of BMI and found that clusters of SSB intake frequency and BMI overlapped in specific areas. One tenth of the population was within high SSB intake frequency and high BMI clusters. These clusters persisted after adjustment for neighborhood-level median income. Conclusion: A fine-scale spatial approach allows identifying specific areas presenting higher SSB consumption and, for some areas, higher SSB consumption with higher BMI. The use of this information to guide interventions such as prevention campaigns could pave the way for precision public health.

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