Cargando…
Persistent spatial clusters of high body mass index in a Swiss urban population as revealed by the 5-year GeoCoLaus longitudinal study
OBJECTIVE: Body mass index (BMI) may cluster in space among adults and be spatially dependent. Whether and how BMI clusters evolve over time in a population is currently unknown. We aimed to determine the spatial dependence of BMI and its 5-year evolution in a Swiss general adult urban population, t...
Autores principales: | , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4716152/ https://www.ncbi.nlm.nih.gov/pubmed/26733572 http://dx.doi.org/10.1136/bmjopen-2015-010145 |
_version_ | 1782410510993457152 |
---|---|
author | Joost, Stéphane Duruz, Solange Marques-Vidal, Pedro Bochud, Murielle Stringhini, Silvia Paccaud, Fred Gaspoz, Jean-Michel Theler, Jean-Marc Chételat, Joël Waeber, Gérard Vollenweider, Peter Guessous, Idris |
author_facet | Joost, Stéphane Duruz, Solange Marques-Vidal, Pedro Bochud, Murielle Stringhini, Silvia Paccaud, Fred Gaspoz, Jean-Michel Theler, Jean-Marc Chételat, Joël Waeber, Gérard Vollenweider, Peter Guessous, Idris |
author_sort | Joost, Stéphane |
collection | PubMed |
description | OBJECTIVE: Body mass index (BMI) may cluster in space among adults and be spatially dependent. Whether and how BMI clusters evolve over time in a population is currently unknown. We aimed to determine the spatial dependence of BMI and its 5-year evolution in a Swiss general adult urban population, taking into account the neighbourhood-level and individual-level characteristics. DESIGN: Cohort study. SETTING: Swiss general urban population. PARTICIPANTS: 6481 georeferenced individuals from the CoLaus cohort at baseline (age range 35–74 years, period=2003–2006) and 4460 at follow-up (period=2009–2012). OUTCOME MEASURES: Body weight and height were measured by trained healthcare professionals with participants standing without shoes in light indoor clothing. BMI was calculated as weight (kg) divided by height squared (m(2)). Participants were geocoded using their postal address (geographic coordinates of the place of residence). Getis-Ord Gi statistic was used to measure the spatial dependence of BMI values at baseline and its evolution at follow-up. RESULTS: BMI was not randomly distributed across the city. At baseline and at follow-up, significant clusters of high versus low BMIs were identified and remained stable during the two periods. These clusters were meaningfully attenuated after adjustment for neighbourhood-level income but not individual-level characteristics. Similar results were observed among participants who showed a significant weight gain. CONCLUSIONS: To the best of our knowledge, this is the first study to report longitudinal changes in BMI clusters in adults from a general population. Spatial clusters of high BMI persisted over a 5-year period and were mainly influenced by neighbourhood-level income. |
format | Online Article Text |
id | pubmed-4716152 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-47161522016-01-31 Persistent spatial clusters of high body mass index in a Swiss urban population as revealed by the 5-year GeoCoLaus longitudinal study Joost, Stéphane Duruz, Solange Marques-Vidal, Pedro Bochud, Murielle Stringhini, Silvia Paccaud, Fred Gaspoz, Jean-Michel Theler, Jean-Marc Chételat, Joël Waeber, Gérard Vollenweider, Peter Guessous, Idris BMJ Open Nutrition and Metabolism OBJECTIVE: Body mass index (BMI) may cluster in space among adults and be spatially dependent. Whether and how BMI clusters evolve over time in a population is currently unknown. We aimed to determine the spatial dependence of BMI and its 5-year evolution in a Swiss general adult urban population, taking into account the neighbourhood-level and individual-level characteristics. DESIGN: Cohort study. SETTING: Swiss general urban population. PARTICIPANTS: 6481 georeferenced individuals from the CoLaus cohort at baseline (age range 35–74 years, period=2003–2006) and 4460 at follow-up (period=2009–2012). OUTCOME MEASURES: Body weight and height were measured by trained healthcare professionals with participants standing without shoes in light indoor clothing. BMI was calculated as weight (kg) divided by height squared (m(2)). Participants were geocoded using their postal address (geographic coordinates of the place of residence). Getis-Ord Gi statistic was used to measure the spatial dependence of BMI values at baseline and its evolution at follow-up. RESULTS: BMI was not randomly distributed across the city. At baseline and at follow-up, significant clusters of high versus low BMIs were identified and remained stable during the two periods. These clusters were meaningfully attenuated after adjustment for neighbourhood-level income but not individual-level characteristics. Similar results were observed among participants who showed a significant weight gain. CONCLUSIONS: To the best of our knowledge, this is the first study to report longitudinal changes in BMI clusters in adults from a general population. Spatial clusters of high BMI persisted over a 5-year period and were mainly influenced by neighbourhood-level income. BMJ Publishing Group 2016-01-05 /pmc/articles/PMC4716152/ /pubmed/26733572 http://dx.doi.org/10.1136/bmjopen-2015-010145 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/ This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
spellingShingle | Nutrition and Metabolism Joost, Stéphane Duruz, Solange Marques-Vidal, Pedro Bochud, Murielle Stringhini, Silvia Paccaud, Fred Gaspoz, Jean-Michel Theler, Jean-Marc Chételat, Joël Waeber, Gérard Vollenweider, Peter Guessous, Idris Persistent spatial clusters of high body mass index in a Swiss urban population as revealed by the 5-year GeoCoLaus longitudinal study |
title | Persistent spatial clusters of high body mass index in a Swiss urban population as revealed by the 5-year GeoCoLaus longitudinal study |
title_full | Persistent spatial clusters of high body mass index in a Swiss urban population as revealed by the 5-year GeoCoLaus longitudinal study |
title_fullStr | Persistent spatial clusters of high body mass index in a Swiss urban population as revealed by the 5-year GeoCoLaus longitudinal study |
title_full_unstemmed | Persistent spatial clusters of high body mass index in a Swiss urban population as revealed by the 5-year GeoCoLaus longitudinal study |
title_short | Persistent spatial clusters of high body mass index in a Swiss urban population as revealed by the 5-year GeoCoLaus longitudinal study |
title_sort | persistent spatial clusters of high body mass index in a swiss urban population as revealed by the 5-year geocolaus longitudinal study |
topic | Nutrition and Metabolism |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4716152/ https://www.ncbi.nlm.nih.gov/pubmed/26733572 http://dx.doi.org/10.1136/bmjopen-2015-010145 |
work_keys_str_mv | AT jooststephane persistentspatialclustersofhighbodymassindexinaswissurbanpopulationasrevealedbythe5yeargeocolauslongitudinalstudy AT duruzsolange persistentspatialclustersofhighbodymassindexinaswissurbanpopulationasrevealedbythe5yeargeocolauslongitudinalstudy AT marquesvidalpedro persistentspatialclustersofhighbodymassindexinaswissurbanpopulationasrevealedbythe5yeargeocolauslongitudinalstudy AT bochudmurielle persistentspatialclustersofhighbodymassindexinaswissurbanpopulationasrevealedbythe5yeargeocolauslongitudinalstudy AT stringhinisilvia persistentspatialclustersofhighbodymassindexinaswissurbanpopulationasrevealedbythe5yeargeocolauslongitudinalstudy AT paccaudfred persistentspatialclustersofhighbodymassindexinaswissurbanpopulationasrevealedbythe5yeargeocolauslongitudinalstudy AT gaspozjeanmichel persistentspatialclustersofhighbodymassindexinaswissurbanpopulationasrevealedbythe5yeargeocolauslongitudinalstudy AT thelerjeanmarc persistentspatialclustersofhighbodymassindexinaswissurbanpopulationasrevealedbythe5yeargeocolauslongitudinalstudy AT chetelatjoel persistentspatialclustersofhighbodymassindexinaswissurbanpopulationasrevealedbythe5yeargeocolauslongitudinalstudy AT waebergerard persistentspatialclustersofhighbodymassindexinaswissurbanpopulationasrevealedbythe5yeargeocolauslongitudinalstudy AT vollenweiderpeter persistentspatialclustersofhighbodymassindexinaswissurbanpopulationasrevealedbythe5yeargeocolauslongitudinalstudy AT guessousidris persistentspatialclustersofhighbodymassindexinaswissurbanpopulationasrevealedbythe5yeargeocolauslongitudinalstudy |