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Finding big shots: small-area mapping and spatial modelling of obesity among Swiss male conscripts

BACKGROUND: In Switzerland, as in other developed countries, the prevalence of overweight and obesity has increased substantially since the early 1990s. Most of the analyses so far have been based on sporadic surveys or self-reported data and did not offer potential for small-area analyses. The goal...

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Autores principales: Panczak, Radoslaw, Held, Leonhard, Moser, André, Jones, Philip A., Rühli, Frank J., Staub, Kaspar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4758017/
https://www.ncbi.nlm.nih.gov/pubmed/26918194
http://dx.doi.org/10.1186/s40608-016-0092-6
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author Panczak, Radoslaw
Held, Leonhard
Moser, André
Jones, Philip A.
Rühli, Frank J.
Staub, Kaspar
author_facet Panczak, Radoslaw
Held, Leonhard
Moser, André
Jones, Philip A.
Rühli, Frank J.
Staub, Kaspar
author_sort Panczak, Radoslaw
collection PubMed
description BACKGROUND: In Switzerland, as in other developed countries, the prevalence of overweight and obesity has increased substantially since the early 1990s. Most of the analyses so far have been based on sporadic surveys or self-reported data and did not offer potential for small-area analyses. The goal of this study was to investigate spatial variation and determinants of obesity among young Swiss men using recent conscription data. METHODS: A complete, anonymized dataset of conscription records for the 2010–2012 period were provided by Swiss Armed Forces. We used a series of Bayesian hierarchical logistic regression models to investigate the spatial pattern of obesity across 3,187 postcodes, varying them by type of random effects (spatially unstructured and structured), level of adjustment by individual (age and professional status) and area-based [urbanicity and index of socio-economic position (SEP)] characteristics. RESULTS: The analysed dataset consisted of 100,919 conscripts, out of which 5,892 (5.8 %) were obese. Crude obesity prevalence increased with age among conscripts of lower individual and area-based SEP and varied greatly over postcodes. Best model’s estimates of adjusted odds ratios of obesity on postcode level ranged from 0.61 to 1.93 and showed a strong spatial pattern of obesity risk across the country. Odds ratios above 1 concentrated in central and north Switzerland. Smaller pockets of elevated obesity risk also emerged around cities of Geneva, Fribourg and Lausanne. Lower estimates were observed in North-East and East as well as south of the Alps. Importantly, small regional outliers were observed and patterning did not follow administrative boundaries. Similarly as with crude obesity prevalence, the best fitting model confirmed increasing risk of obesity with age and among conscripts of lower professional status. The risk decreased with higher area-based SEP and, to a lesser degree – in rural areas. CONCLUSION: In Switzerland, there is a substantial spatial variation in obesity risk among young Swiss men. Small-area estimates of obesity risk derived from conscripts records contribute to its understanding and could be used to design further studies and interventions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40608-016-0092-6) contains supplementary material, which is available to authorized users.
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spelling pubmed-47580172016-02-25 Finding big shots: small-area mapping and spatial modelling of obesity among Swiss male conscripts Panczak, Radoslaw Held, Leonhard Moser, André Jones, Philip A. Rühli, Frank J. Staub, Kaspar BMC Obes Research Article BACKGROUND: In Switzerland, as in other developed countries, the prevalence of overweight and obesity has increased substantially since the early 1990s. Most of the analyses so far have been based on sporadic surveys or self-reported data and did not offer potential for small-area analyses. The goal of this study was to investigate spatial variation and determinants of obesity among young Swiss men using recent conscription data. METHODS: A complete, anonymized dataset of conscription records for the 2010–2012 period were provided by Swiss Armed Forces. We used a series of Bayesian hierarchical logistic regression models to investigate the spatial pattern of obesity across 3,187 postcodes, varying them by type of random effects (spatially unstructured and structured), level of adjustment by individual (age and professional status) and area-based [urbanicity and index of socio-economic position (SEP)] characteristics. RESULTS: The analysed dataset consisted of 100,919 conscripts, out of which 5,892 (5.8 %) were obese. Crude obesity prevalence increased with age among conscripts of lower individual and area-based SEP and varied greatly over postcodes. Best model’s estimates of adjusted odds ratios of obesity on postcode level ranged from 0.61 to 1.93 and showed a strong spatial pattern of obesity risk across the country. Odds ratios above 1 concentrated in central and north Switzerland. Smaller pockets of elevated obesity risk also emerged around cities of Geneva, Fribourg and Lausanne. Lower estimates were observed in North-East and East as well as south of the Alps. Importantly, small regional outliers were observed and patterning did not follow administrative boundaries. Similarly as with crude obesity prevalence, the best fitting model confirmed increasing risk of obesity with age and among conscripts of lower professional status. The risk decreased with higher area-based SEP and, to a lesser degree – in rural areas. CONCLUSION: In Switzerland, there is a substantial spatial variation in obesity risk among young Swiss men. Small-area estimates of obesity risk derived from conscripts records contribute to its understanding and could be used to design further studies and interventions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40608-016-0092-6) contains supplementary material, which is available to authorized users. BioMed Central 2016-02-18 /pmc/articles/PMC4758017/ /pubmed/26918194 http://dx.doi.org/10.1186/s40608-016-0092-6 Text en © Panczak et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Panczak, Radoslaw
Held, Leonhard
Moser, André
Jones, Philip A.
Rühli, Frank J.
Staub, Kaspar
Finding big shots: small-area mapping and spatial modelling of obesity among Swiss male conscripts
title Finding big shots: small-area mapping and spatial modelling of obesity among Swiss male conscripts
title_full Finding big shots: small-area mapping and spatial modelling of obesity among Swiss male conscripts
title_fullStr Finding big shots: small-area mapping and spatial modelling of obesity among Swiss male conscripts
title_full_unstemmed Finding big shots: small-area mapping and spatial modelling of obesity among Swiss male conscripts
title_short Finding big shots: small-area mapping and spatial modelling of obesity among Swiss male conscripts
title_sort finding big shots: small-area mapping and spatial modelling of obesity among swiss male conscripts
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4758017/
https://www.ncbi.nlm.nih.gov/pubmed/26918194
http://dx.doi.org/10.1186/s40608-016-0092-6
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