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Projection scenarios of body mass index (2013–2030) for Public Health Planning in Quebec

BACKGROUND: Projection analyses can provide estimates of the future health burden of increasing BMI and represent a relevant and useful tool for public health planning. Our study presents long-term (2013–2030) projections of the prevalence and numbers of individuals by BMI category for adult men and...

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Autores principales: Lo, Ernest, Hamel, Denis, Jen, Yun, Lamontagne, Patricia, Martel, Sylvie, Steensma, Colin, Blouin, Chantal, Steele, Russell
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4196088/
https://www.ncbi.nlm.nih.gov/pubmed/25253196
http://dx.doi.org/10.1186/1471-2458-14-996
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author Lo, Ernest
Hamel, Denis
Jen, Yun
Lamontagne, Patricia
Martel, Sylvie
Steensma, Colin
Blouin, Chantal
Steele, Russell
author_facet Lo, Ernest
Hamel, Denis
Jen, Yun
Lamontagne, Patricia
Martel, Sylvie
Steensma, Colin
Blouin, Chantal
Steele, Russell
author_sort Lo, Ernest
collection PubMed
description BACKGROUND: Projection analyses can provide estimates of the future health burden of increasing BMI and represent a relevant and useful tool for public health planning. Our study presents long-term (2013–2030) projections of the prevalence and numbers of individuals by BMI category for adult men and women in Quebec. Three applications of projections to estimate outcomes more directly pertinent to public health planning, as well as an in-depth discussion of limits, are provided with the aim of encouraging greater use of projection analyses by public health officers. METHODS: The weighted compositional regression method is applied to prevalence time series derived from sixteen cross-sectional survey cycles, for scenarios of linear change and deceleration. Estimation of the component of projected change potentially amenable to intervention, future health targets and the projected impact on type 2 diabetes, were done. RESULTS: Obesity prevalence in Quebec is projected to rise steadily from 2013 to 2030 in both men (from 18.0-19.4% to 22.2-30.4%) and women (from 15.5-16.3% to 18.2-22.4%). Corresponding projected numbers of obese individuals are (579,000-625,000 to 790,000-1,084,000) in men and (514,000-543,000 to 661,000-816,000) in women. These projected increases are found to be primarily an ‘epidemiologic’ rather than ‘demographic’ phenomenon and thus potentially amenable to public health intervention. Assessment of obesity targets for 2020 illustrates the necessity of using projected rather than current prevalence; for example a targeted 2% drop in obesity prevalence relative to 2013 translates into a 3.6-5.4% drop relative to 2020 projected levels. Type 2 diabetes is projected to increase from 6.9% to 9.2-10.1% in men and from 5.7% to 7.1-7.5% in women, from 2011–2012 to 2030. A substantial proportion of this change (25-44% for men, and 27-43% for women) is attributable to the changing BMI distribution. CONCLUSIONS: Obesity in Quebec is projected to increase and should therefore continue to be a public health priority. Application of projections to estimate the proportion of change potentially amenable to intervention, feasible health targets, and future chronic disease prevalence are demonstrated. Projection analyses have limitations, but represent a pertinent tool for public health planning. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2458-14-996) contains supplementary material, which is available to authorized users.
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spelling pubmed-41960882014-10-15 Projection scenarios of body mass index (2013–2030) for Public Health Planning in Quebec Lo, Ernest Hamel, Denis Jen, Yun Lamontagne, Patricia Martel, Sylvie Steensma, Colin Blouin, Chantal Steele, Russell BMC Public Health Research Article BACKGROUND: Projection analyses can provide estimates of the future health burden of increasing BMI and represent a relevant and useful tool for public health planning. Our study presents long-term (2013–2030) projections of the prevalence and numbers of individuals by BMI category for adult men and women in Quebec. Three applications of projections to estimate outcomes more directly pertinent to public health planning, as well as an in-depth discussion of limits, are provided with the aim of encouraging greater use of projection analyses by public health officers. METHODS: The weighted compositional regression method is applied to prevalence time series derived from sixteen cross-sectional survey cycles, for scenarios of linear change and deceleration. Estimation of the component of projected change potentially amenable to intervention, future health targets and the projected impact on type 2 diabetes, were done. RESULTS: Obesity prevalence in Quebec is projected to rise steadily from 2013 to 2030 in both men (from 18.0-19.4% to 22.2-30.4%) and women (from 15.5-16.3% to 18.2-22.4%). Corresponding projected numbers of obese individuals are (579,000-625,000 to 790,000-1,084,000) in men and (514,000-543,000 to 661,000-816,000) in women. These projected increases are found to be primarily an ‘epidemiologic’ rather than ‘demographic’ phenomenon and thus potentially amenable to public health intervention. Assessment of obesity targets for 2020 illustrates the necessity of using projected rather than current prevalence; for example a targeted 2% drop in obesity prevalence relative to 2013 translates into a 3.6-5.4% drop relative to 2020 projected levels. Type 2 diabetes is projected to increase from 6.9% to 9.2-10.1% in men and from 5.7% to 7.1-7.5% in women, from 2011–2012 to 2030. A substantial proportion of this change (25-44% for men, and 27-43% for women) is attributable to the changing BMI distribution. CONCLUSIONS: Obesity in Quebec is projected to increase and should therefore continue to be a public health priority. Application of projections to estimate the proportion of change potentially amenable to intervention, feasible health targets, and future chronic disease prevalence are demonstrated. Projection analyses have limitations, but represent a pertinent tool for public health planning. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2458-14-996) contains supplementary material, which is available to authorized users. BioMed Central 2014-09-25 /pmc/articles/PMC4196088/ /pubmed/25253196 http://dx.doi.org/10.1186/1471-2458-14-996 Text en © Lo et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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
Lo, Ernest
Hamel, Denis
Jen, Yun
Lamontagne, Patricia
Martel, Sylvie
Steensma, Colin
Blouin, Chantal
Steele, Russell
Projection scenarios of body mass index (2013–2030) for Public Health Planning in Quebec
title Projection scenarios of body mass index (2013–2030) for Public Health Planning in Quebec
title_full Projection scenarios of body mass index (2013–2030) for Public Health Planning in Quebec
title_fullStr Projection scenarios of body mass index (2013–2030) for Public Health Planning in Quebec
title_full_unstemmed Projection scenarios of body mass index (2013–2030) for Public Health Planning in Quebec
title_short Projection scenarios of body mass index (2013–2030) for Public Health Planning in Quebec
title_sort projection scenarios of body mass index (2013–2030) for public health planning in quebec
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4196088/
https://www.ncbi.nlm.nih.gov/pubmed/25253196
http://dx.doi.org/10.1186/1471-2458-14-996
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