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Overlapping spatial clusters of sugar-sweetened beverage intake and body mass index in Geneva state, Switzerland
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 int...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6856345/ https://www.ncbi.nlm.nih.gov/pubmed/31727876 http://dx.doi.org/10.1038/s41387-019-0102-0 |
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author | Joost, Stéphane De Ridder, David Marques-Vidal, Pedro Bacchilega, Beatrice Theler, Jean-Marc Gaspoz, Jean-Michel Guessous, Idris |
author_facet | Joost, Stéphane De Ridder, David Marques-Vidal, Pedro Bacchilega, Beatrice Theler, Jean-Marc Gaspoz, Jean-Michel Guessous, Idris |
author_sort | Joost, Stéphane |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6856345 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-68563452019-11-21 Overlapping spatial clusters of sugar-sweetened beverage intake and body mass index in Geneva state, Switzerland Joost, Stéphane De Ridder, David Marques-Vidal, Pedro Bacchilega, Beatrice Theler, Jean-Marc Gaspoz, Jean-Michel Guessous, Idris Nutr Diabetes Article 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. Nature Publishing Group UK 2019-11-14 /pmc/articles/PMC6856345/ /pubmed/31727876 http://dx.doi.org/10.1038/s41387-019-0102-0 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Joost, Stéphane De Ridder, David Marques-Vidal, Pedro Bacchilega, Beatrice Theler, Jean-Marc Gaspoz, Jean-Michel Guessous, Idris Overlapping spatial clusters of sugar-sweetened beverage intake and body mass index in Geneva state, Switzerland |
title | Overlapping spatial clusters of sugar-sweetened beverage intake and body mass index in Geneva state, Switzerland |
title_full | Overlapping spatial clusters of sugar-sweetened beverage intake and body mass index in Geneva state, Switzerland |
title_fullStr | Overlapping spatial clusters of sugar-sweetened beverage intake and body mass index in Geneva state, Switzerland |
title_full_unstemmed | Overlapping spatial clusters of sugar-sweetened beverage intake and body mass index in Geneva state, Switzerland |
title_short | Overlapping spatial clusters of sugar-sweetened beverage intake and body mass index in Geneva state, Switzerland |
title_sort | overlapping spatial clusters of sugar-sweetened beverage intake and body mass index in geneva state, switzerland |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6856345/ https://www.ncbi.nlm.nih.gov/pubmed/31727876 http://dx.doi.org/10.1038/s41387-019-0102-0 |
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