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

Lo E, Hamel D, Jen Y, Lamontagne P, Martel S, Steensma C, Blouin C, Steele R - BMC Public Health (2014)

Bottom Line: 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.A substantial proportion of this change (25-44% for men, and 27-43% for women) is attributable to the changing BMI distribution.Application of projections to estimate the proportion of change potentially amenable to intervention, feasible health targets, and future chronic disease prevalence are demonstrated.

View Article: PubMed Central - PubMed

Affiliation: Institut National de Santé Publique du Québec, 190 blvd Crémazie Est, Montréal, Québec H2P 1E2, Canada. ernest.lo@mail.mcgill.ca.

ABSTRACT

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.

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Related in: MedlinePlus

Projections (2013 to 2030) of age-aggregated prevalence by BMI category, for men and women. The linear scenario is indicated by the black line, the deceleration scenario is indicated by the gray line, and the historical BMI time series data are indicated by the open circles.
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Fig1: Projections (2013 to 2030) of age-aggregated prevalence by BMI category, for men and women. The linear scenario is indicated by the black line, the deceleration scenario is indicated by the gray line, and the historical BMI time series data are indicated by the open circles.

Mentions: Projection results showing fitted and projected age aggregated prevalence are shown in Figure 1a to h for men and women. The ‘pessimistic’ linear scenario is represented by the black line and the ‘optimistic’ deceleration scenario is represented by the gray line; the range of possible future outcomes can be interpreted as falling between the span of the two scenarios [30, 31]. Values representing age aggregated survey time series data are indicated by the circles. Projected prevalence values are listed in Table 2a and b for the years 2013, 2020 and 2030.


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

Lo E, Hamel D, Jen Y, Lamontagne P, Martel S, Steensma C, Blouin C, Steele R - BMC Public Health (2014)

Projections (2013 to 2030) of age-aggregated prevalence by BMI category, for men and women. The linear scenario is indicated by the black line, the deceleration scenario is indicated by the gray line, and the historical BMI time series data are indicated by the open circles.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4196088&req=5

Fig1: Projections (2013 to 2030) of age-aggregated prevalence by BMI category, for men and women. The linear scenario is indicated by the black line, the deceleration scenario is indicated by the gray line, and the historical BMI time series data are indicated by the open circles.
Mentions: Projection results showing fitted and projected age aggregated prevalence are shown in Figure 1a to h for men and women. The ‘pessimistic’ linear scenario is represented by the black line and the ‘optimistic’ deceleration scenario is represented by the gray line; the range of possible future outcomes can be interpreted as falling between the span of the two scenarios [30, 31]. Values representing age aggregated survey time series data are indicated by the circles. Projected prevalence values are listed in Table 2a and b for the years 2013, 2020 and 2030.

Bottom Line: 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.A substantial proportion of this change (25-44% for men, and 27-43% for women) is attributable to the changing BMI distribution.Application of projections to estimate the proportion of change potentially amenable to intervention, feasible health targets, and future chronic disease prevalence are demonstrated.

View Article: PubMed Central - PubMed

Affiliation: Institut National de Santé Publique du Québec, 190 blvd Crémazie Est, Montréal, Québec H2P 1E2, Canada. ernest.lo@mail.mcgill.ca.

ABSTRACT

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.

Show MeSH
Related in: MedlinePlus