Overlapping spatial clusters of sugar-sweetened beverage intake and body mass index in Geneva state, Switzerland.

Autor:	Joost S; Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.; Unit of Population Epidemiology, Division of Primary Care Medicine, Department of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland.; Group of Geographic Information Research and Analysis in Population Health (GIRAPH), Geneva, Switzerland.; La Source, School of Nursing, University of Applied Sciences and Arts Western Switzerland (HES-SO), Lausanne, Switzerland., De Ridder D; Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.; Unit of Population Epidemiology, Division of Primary Care Medicine, Department of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland.; Group of Geographic Information Research and Analysis in Population Health (GIRAPH), Geneva, Switzerland.; Faculty of Medicine, University of Geneva, Geneva, Switzerland., Marques-Vidal P; Group of Geographic Information Research and Analysis in Population Health (GIRAPH), Geneva, Switzerland.; Department of Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland., Bacchilega B; Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland., Theler JM; Unit of Population Epidemiology, Division of Primary Care Medicine, Department of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland., Gaspoz JM; Unit of Population Epidemiology, Division of Primary Care Medicine, Department of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland.; Faculty of Medicine, University of Geneva, Geneva, Switzerland., Guessous I; Unit of Population Epidemiology, Division of Primary Care Medicine, Department of Primary Care Medicine, Geneva University Hospitals, Geneva, Switzerland. Idris.Guessous@hcuge.ch.; Group of Geographic Information Research and Analysis in Population Health (GIRAPH), Geneva, Switzerland. Idris.Guessous@hcuge.ch.; Faculty of Medicine, University of Geneva, Geneva, Switzerland. Idris.Guessous@hcuge.ch.
Jazyk:	angličtina
Zdroj:	Nutrition & diabetes [Nutr Diabetes] 2019 Nov 14; Vol. 9 (1), pp. 35. Date of Electronic Publication: 2019 Nov 14.
DOI:	10.1038/s41387-019-0102-0
Abstrakt:	Background: Obesity and obesity-related diseases represent a major public health concern. Recently, studies have substantiated the role of sugar-sweetened beverages (SSBs) consumption in the development of these diseases. The fine identification of populations and areas in need for public health intervention remains challenging. This study investigates the existence of spatial clustering of SSB intake frequency (SSB-IF) and body mass index (BMI), and their potential spatial overlap in a population of adults of the state of Geneva using a fine-scale geospatial approach. Methods: We used data on self-reported SSB-IF and measured BMI from residents aged between 20 and 74 years of the state of Geneva (Switzerland) that participated in the Bus Santé cross-sectional population-based study (n = 15,423). Getis-Ord Gi spatial indices were used to identify spatial clusters of SSB-IF and BMI in unadjusted models and models adjusted for individual covariates (education level, gender, age, nationality, and neighborhood-level median income). Results: We identified a significant spatial clustering of BMI and SSB-IF. 13.2% (n = 2034) of the participants were within clusters of higher SSB-IF and 10.7% (n = 1651) were within clusters of lower SSB-IF. We identified overlapping clusters of SSB-IF and BMI in specific areas where 11.1% (n = 1719) of the participants resided. After adjustment, the identified clusters persisted and were only slightly attenuated indicating that additional neighborhood-level determinants influence the spatial distribution of SSB-IF and BMI. Conclusions: Our fine-scale spatial approach allowed to identify specific populations and areas presenting higher SSB-IF and highlighted the existence of an overlap between populations and areas of higher SSB-IF associated with higher BMI. These findings could guide policymakers to develop locally tailored interventions such as targeted prevention campaigns and pave the way for precision public health delivery.
Databáze:	MEDLINE
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