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

Ernest Lo 0 1 3 4 Denis Hamel 1 4 Yun Jen 1 4 Patricia Lamontagne 1 4 Sylvie Martel 1 4 Colin Steensma 2 Chantal Blouin 1 4 Russell Steele 5 0 Department of Epidemiology , Biostatistics and Occupational Health , McGill University , Purvis Hall, 1020 Pine Avenue West, Montreal, Quebec H3A 1A2 , Canada 1 Institut National de Sante Publique du Quebec , 190 blvd Cremazie Est, Montreal, Quebec H2P 1E2 , Canada 2 Public Health Agency of Canada , 200, boulevard Rene-Levesque Ouest, Montreal, Quebec H2Z 1X4 , Canada 3 Department of Epidemiology , Biostatistics and Occupational Health , McGill University , Purvis Hall, 1020 Pine Avenue West, Montreal, Quebec H3A 1A2 , Canada 4 Institut National de Sante Publique du Quebec , 190 blvd Cremazie Est, Montreal, Quebec H2P 1E2 , Canada 5 Department of Mathematics and Statistics, McGill University , 805 Sherbrooke Ouest, Montreal, Quebec H3A 2K6 , Canada 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. - Background The prevalence of obesity in Quebec (the second most populous province of Canada, with an estimated population of 8,067,319 in 2013) has seen a continuous increase over at least the past 2.5 decades [1,2], mirroring trends in developed countries around the world [3]. From 1987 to 2012 for example, the prevalence of (self-report) obesity in Quebec adults more than doubled in value from 8% to 17%. These trends indicate a growing health and economic burden, as elevated BMI is associated with a range of co-morbidities and increased mortality [4-7]. Projection analyses of obesity have been done with increasing frequency in recognition of the need to estimate the future magnitude of this public health issue, and thus to plan health services, programs and interventions [8-13]. Projection studies however are not standard surveillance tools used by public health officers, and are largely the purview of university research scientists who may have different aims and perspectives. The objective of the current study is thus to provide projection analyses of BMI prevalence for the Quebec adult population, with the aim of informing and supporting public health planning. Shortterm (20122019) projections using simple linear regression [12] represent the only other known projection study of Quebec obesity trends. Our study provides long-term (20132030) projections using a weighted compositional approach that overcomes methodological shortcomings of simple linear regression that may lead to bias and inaccuracy [10]. One issue that may limit the adoption of projection analyses for public health planning is that public health professionals may not be aware of the ways in which projections can be applied to estimate outcomes more directly related to policy and programs. To address this issue, three methodological techniques by which BMI prevalence projections can be translated into more concrete measures for health planning are demonstrated: (1) the separation of the projected time trends into demographic and epidemiologic components and thus estimation of the component potentially amenable to intervention, (2) use of projections in the planning of health targets including metrics that measure the difficulty of achieving targets as well as the consequences of not achieving them, and (3) the estimation of the projected impact on chronic disease using type 2 diabetes as an example, including estimation of the proportion of diabetes prevalence change potentially amenable to intervention. Finally, projections may be perceived as technical and abstract mathematical constructs that are far removed from the multi-faceted (e.g. social, cultural, and technological) and complex nature of real-world public health issues. Thus we also provide a detailed discussion of the major limits and assumptions of the scenarios that underlie the BMI projections and suggest ways in which the results can be interpreted. Methods Data sources and variables BMI prevalence time series were constructed from available cross-sectional surveys that measured self-report height and weight, and were representative of the Quebec population of adults 18 years of age and over. All surveys excluded the northern health regions of Nunavik and Terre-Cries-de-laBaie-James. Sixteen independent survey cycles spanning the years from 1987 to 2012 were identified. These included four survey types: the Quebec Health Survey or ESQ (1987) [14] and the Quebec Health and Social Survey or ESS (19921993, 1998) [15] which were conducted by the Quebec Statistics Institute, and the National Population Health Survey or NPHS (19941995, 19961997, 19981999) [16] and the Canadian Community Health Survey or CCHS (20002001, 2002, 2003, 2005, 2007, 2008, 2009 (...truncated)