Abstract
Objective To identify populations and areas presenting higher consumption of sugar-sweetened beverages (SSB) and their overlap with populations and areas presenting higher body mass index (BMI).
Design Cross-sectional population-based study.
Setting State of Geneva, Switzerland.
Participants 15,767 non-institutionalized residents aged between 35 and 74 years (20 and 74 since 2011) of the state of Geneva, Switzerland.
Main outcome measures Spatial indices of sugar-sweetened beverage intake frequency and body mass index. Median regression analysis was used to control for characteristics of patients.
Results The SSB intake frequency and the BMI were not randomly distributed across the state. Among the 15,423 participants retained for the analyses, 2,034 (13.2%) were within clusters of high SSB intake frequency and 1,651 (10.7%) was within clusters of low SSB intake frequency, 11,738 (76.1%) showed no spatial dependence. We also identified clusters of BMI, 4,014 (26.0%) participants were within clusters of high BMI and 3,591 (23.3%) were within clusters of low BMI, 7,818 (50.7%) showed no spatial dependence. We found that clusters of SSB intake frequency and BMI overlap in specific areas. 1,719 (11.1%) participants were within high SSB intake frequency and high BMI clusters. After adjustment for covariates (education level, gender, age, nationality, and the median income of the area), the identified clusters persisted and were only slightly attenuated.
Conclusion A fine-scale spatial approach allows identifying specific populations and areas presenting higher SSB consumption and, for some areas, higher SSB consumption associated with higher BMI. These findings could guide legislators to develop targeted interventions such as prevention campaigns and pave the way for precision public health.
What is already known on this topic
The consumption of sugar-sweetened beverages (SSBs) is an important contributory factor of obesity and obesity-related diseases.
SSB consumption varies according to socioeconomic status, which could explain the higher prevalence of obesity in specific areas.
SSB taxation faces resistance in many countries due to its potential regressive nature.
What this study adds
The spatial analysis of individual-level SSB consumption in the state of Geneva provides a clear identification of populations and areas presenting higher SSB consumption and, for some areas, higher SSB consumption along with higher body mass index (BMI).
The results demonstrate the persistence of SSB clustering in the geographic space after adjusting for education level, gender, nationality, age, and neighborhood-level median income.
The findings provide guidance for future public health interventions to reduce SSB consumption by better targeting vulnerable populations.
Footnotes
↵Authors Stéphane Joost: Stephane.Joost{at}epfl.ch, Senior scientist David De Ridder: David.DeRidder{at}unige.ch, PhD student Pedro Marques-Vidal: Pedro-Manuel.Marques-Vidal{at}chuv.ch, Professor Beatrice Bacchilega: Beatrice.Bacchilega{at}alumni.epfl.ch, Gradu te student Jean-Marc Theler: Jean-Marc.Theler{at}hcuge.ch1, Database engineer Jean-Michel Gaspoz: Jean-Michel.Gaspoz{at}hcuge.ch, Professor Idris Guessous: Idris.Guessous{at}hcuge.ch, Professor