ORIGINAL ARTICLE. Obesity in Canada: where and how many? A Vanasse 1,2, M Demers 3, A Hemiari 2 and J Courteau 2. Introduction

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1 (2006) 30, & 2006 Nature Publishing Group All rights reserved /06 $ ORIGINAL ARTICLE : where and how many? A Vanasse 1,2, M Demers 3, A Hemiari 2 and J Courteau 2 1 Family Medicine Department, Faculty of Medicine, Université de Sherbrooke, Sherbrooke, Quebec, Canada J1H 5N4; 2 PRIMUS Group, Clinical Research Center, Sherbrooke University Hospital, Sherbrooke, Quebec, Canada J1H 5N4 and 3 Conseil de la Science et de la Technologie, Gouvernement du Québec, Québec, Canada Context: Obesity rates are rising sharply among all industrialized countries; the situation seems to be worse in English speaking countries. Taking into account genetic predisposition, excess of caloric intake combined with low energy expenditure will usually result in obesity. Objectives: To describe and compare regional obesity rates across Canada and assess the ecological relationship between regional rates of obesity, low level of leisure-time physical activity, and low fruit and vegetable consumption. Design: Cross-sectional population-based analysis from the 2003 Canadian Community Health Survey. Measures and data analyses: Canadian population distributions of body mass index (BMI), leisure-time physical activity and daily fruit and vegetable consumption were obtained from Statistics Canada. All these measures were based on the respondent s selfreported answers to a computer-assisted personal or telephone interview. Obesity rates (BMIX30), rates of low level of leisure-time physical activity (less than 1.5 kcal of energy expenditure per day), and rates of low fruit and vegetable consumption (less than five times a day) for the 106 Canadian Health regions were mapped to illustrate their geographical distribution. Cartograms were used in addition to traditional mapping to take into account the differences in population density between these small areas. Results: In 2003, 15.2% of Canadian individuals aged 20 years and older were considered obese. The rates of obesity varied substantially between the 106 Canadian health regions: from 6.2% in Vancouver to 47.5% in aboriginal population area. At the health region level, low leisure-time physical activity and low fruit and vegetable consumption are both good predictors of obesity (odds ratio of 9.2 and positive predictive value of 93% when considered simultaneously). Conclusion: There is a strong gradient in obesity prevalence between Canadian health regions. At the regional level, high rates of low level of physical activity, and high rates of low fruit and vegetable consumption were both found good predictors of high rates of obesity. (2006) 30, doi: /sj.ijo ; published online 8 November 2005 Keywords: physical activity; dietary practices; lifestyle habits; regional variability; cartogram Introduction Overweight and obesity rates are rising sharply among all industrialized countries; according to the WHO, the situation has now reached epidemic proportions 1 and seems to be worse in English speaking countries such as the United States, the United Kingdom, Australia, and Canada. 2 Excess weight is not a matter of aesthetic or personal vanity: it contributes significantly to a large scope of chronic diseases and is also responsible for disability, work days lost, restricted activity days, and mobility limitations, 3 5 thus incurring Correspondence: Dr A Vanasse, Department of Family Medicine, Faculty of Medicine, Université de Sherbrooke, th Avenue North, Sherbrooke, Quebec, Canada J1H 5N4. Alain.Vanasse@USherbrooke.ca Received 25 May 2005; revised 8 September 2005; accepted 23 September 2005; published online 8 November 2005 huge costs for the health care system as well as for society as a whole. 6,7 For the year 2001, the economic burden of obesity in Canada has been estimated at $4.3 billion, representing 2.2% of the total health care costs. 8 The prevalence of obesity more than doubled in Canada between 1985 and In fact, there has been a progressive increase in overweight and obesity since , where the rates were, respectively, 40.0 and 9.7%, in comparison with 50.7 and 14.9% in The problem was even found more pronounced among children, 11 where the prevalence of overweight went from 11.4% in 1981 to 29.3% in 1996, nearly a threefold increase over the 15-year period. 12 According to this last research, the risk of being overweight was more related to geography than demographic variables, a much higher prevalence being found in the Atlantic Provinces. In 1985, all provinces reported adult obesity rates inferior to 10% while in 1998, only Quebec and British Columbia had a rate less than 15%. 9

2 678 Overweight can result from an imbalance between caloric intake and energy expenditure. In Canada, the only national nutrition survey took place between 1970 and 1972, which makes difficult to follow the evolution of energy intake. Nevertheless, a smaller survey found a reduction of fat intake among Canadians between 1970 and , but also a suboptimal fruit and vegetable consumption. 13 The frequency of fruit and vegetable intake has already been negatively associated with overweight. 14 On the other hand, the lack of physical activity has also been linked to overweight and obesity; 15 recent data from a representative sample of Canadian children support this evidence. 16 Although there was an increase in leisure-time physical activity levels among the Canadian adult population during the last two decades, 17 a majority of adults are still not sufficiently active for health benefits. 18 In Canada, most of the population is concentrated on a narrow strip along the American border, which makes it difficult to illustrate health determinants at the province level without bringing misleading representation. To overcome this problem, data from the 2003 Canadian Community Health Survey on obesity, leisure-time physical activity, and daily fruit and vegetable consumption were broken down into smaller units, and a spatial analytic tool, a cartogram, was used in addition to traditional mapping to take into account the differences in population density between these small areas. Geographic information systems (GIS) are providing new tools for studying geographical variations in disease and its determinants, but their full potential is still to be explored. 19,20 This study will also illustrate how spatial analysis methods are particularly useful when dealing with huge density differences between geographic areas. By using traditional geographical maps in the health field, we look for possible links between health parameters and geographic location. A traditional map illustrates the geographic variation (spatial dimension) of the study parameter. The use of a cartogram will add a population dimension to the study parameter by illustrating the population density variation. By adding this populationbased perspective to a study, the cartogram could be a helpful means for decision-makers in public health. Methods Design, study population, and study area We conducted a cross-sectional population-based analysis using data from the 2003 Canadian Community Health Survey. The study population consisted of all individuals aged 20 years or older living in Canada in The study area included the 106 health regions of Canada. The land area of the country reaches km 2 with a population of inhabitants in The population density varies widely across the 106 Canadian health regions, ranging from 0.01 to 4087 inhabitants per km 2, with an overall population density of 3.5 inhabitants per km 2. Data sources Data were obtained from the 2003 Canadian Community Health Survey (CCHS). 22 This survey was conducted on a sample of individuals across Canada using a computer-assisted interviewing questionnaire. The sample allocation strategy consisted of three steps. In the first two steps, the sample was allocated among the provinces according to their respective populations and the number of health regions they contain. In the third step, each province s sample was allocated among its health regions proportionally to the square root of the estimated population in each health region. The CCHS used three sampling frames to select the sample of households. The majority of the sample of household came from an area frame. In some health regions, a Random Digit Dialing sampling frame or a list frame of telephone numbers was also used. Sample units selected from the area frame were interviewed using the Computer-Assisted Personal Interviewing method while units selected from the Random Digit Dialing and telephone list frames were interviewed using the Computer-Assisted Telephone Interviewing method. The 106 health region data were obtained from Statistics Canada in an ArcGIS format to generate both the maps and cartograms. Variables Statistics Canada defined overweight and obesity according to the body mass index (BMI), which is a method of classifying body weight according to health risk. The BMI is calculated as follows: weight in kilograms divided by height in square meters. Information on height and weight were self-reported by the respondents to the survey. According to the World Health Organization and Health Canada guidelines, 23,24 health risk levels are associated with each of the following BMI categories: under 18.5 (underweight); (normal weight); (overweight); (obese-class I); (obese-class II); 40 or greater (obese - Class III). At the health region level, we considered the rate of individuals 20 years or older that were obese. Based on their self-reported answers to questions about the frequency, duration and intensity of their participation in leisure-time physical activity, population aged 20 years and over reported their level of physical activity. 25 For each leisure-time physical activity engaged in by the respondent over the past 3 months, average daily energy expenditure was calculated by multiplying the number of times the activity was performed by the average duration of the activity by the energy cost (kilocalories per kilogram of body weight per hour) of the activity. The index is calculated as the sum of the average daily energy expenditures of all activities. Respondents were then classified by Statistics Canada as follows: 3.0 kcal/kg/day or more ¼ high level of physical activity; kcal/kg/day ¼ moderate level of physical activity; less than 1.5 kcal per day ¼ low level of physical activity. At the health region level, we considered

3 the rate of individuals of 20 years or older with low level of leisure-time physical activity. For the population aged 20 years and over, fruit and vegetable consumption was measured by the average number of times per day they ate fruits and vegetables. 23 Their answers were classified into three categories: less than five times a day; between five and 10 times a day; and more than 10 times a day. At the health region level, we considered the rate of individuals of 20 years or older consuming fruits and vegetables less than five times a day. Analyses For each of the three variables under study (obesity, low level of leisure-time physical activity, and low fruit and vegetable consumption), a thematic traditional map at the Canadian health region level was drawn; in addition, a cartogram taking into account the differences in population density between these small areas was added. Predictive values and odds ratios were calculated at a health region level to assess the predictive power of leisure-time physical activity and fruit and vegetable consumption for obesity. Cartograms or density-equalizing maps. A cartogram is a purposely-distorted thematic map in which the map regions are resized in proportion to the geographic distribution of a variable by changing the area (or lengths) of regions on the map. 26,27 By spatially reflecting the data within the map base, the cartogram prominently emphasizes data distribution instead of territorial size, thereby providing a powerful tool for visualizing data distribution. 24 Cartograms are a well-known technique for showing geography-related statistical information, such as population demographic and epidemiological data. 28 A new diffusion-based method for producing the density-equalizing map (or cartogram) was applied here. 29 This method is relevant for public health application because the distribution of population by area of residence is perhaps the most frequently considered geographical distribution in public health and epidemiology. 30 Results In 2003, one third of Canadian individuals aged 20 years and older were overweight (BMI between 25 and 30), and 15. 2% were considered obese (BMIX30) (Table 1). The rates of obesity varied substantially between the 106 Canadian health regions: from 6.2% in Vancouver to 47.5% in aboriginal population area Terres-Cries-de-la-Baie-James. Overall, 41 of the 106 regions had an obesity rate of 20% and over. The three major metropolitan areas (Vancouver, Toronto, and to a lesser extent, Montreal) showed an obesity rate below the Canadian overall rate of 15.2%. Only 26 health regions stood below this national rate for obesity. Figure 1 shows the traditional map and the population cartogram of obesity rates by health regions. The cartogram Table 1 Body mass index, physical activity and daily fruit and vegetable consumption for the Canadian population aged 20 years and older in 2003 Canadian overall rate (%) Body mass index Underweight (BMIo18.5) 2.5 Normal weight (18.5pBMIo25.0) 45.9 Overweight (25.0pBMIo30.0) 33.9 Obesity (BMIX30.0) 15.2 Class I (30.0pBMIo35.0) 11.3 Class II (35.0pBMIo40.0) 2.8 Class III (BMIX40.0) 1.2 Not stated 2.5 Physical activity High level (X3.0 kcal/kg/day) 23.1 Moderate level (X1.5;o3.0 kcal/kg/day) 24.5 Low level (o1.5 kcal/kg/day) 49.7 Not stated 2.7 Daily fruit and vegetable consumption Less than five times 55.8 Between five and 10 times 35.1 More than 10 times 3.4 Not stated 5.7 shows clearly the purpose of this kind of map, since health areas are distorted to adjust for population density; larger areas with low populations, like Northern Canada, nearly disappeared, and small areas with high populations like Montreal, Toronto, and Vancouver, are overrepresented to better reflect their importance. Nearly half (49.7%) of Canadians aged 20 years and older had a low level of physical activity during their leisure time (daily energy expenditure less than 1.5 kcal per day) in 2003 (Table 1) with regional rates varying from 33.5% in British Columbia to 71.0% in Newfoundland, while 55.8% ate fruits and vegetables less than five times per day (Table 1). Once again, these rates varied substantially between health regions: from 46.3% in British Columbia to 79.8% in Newfoundland. It is interesting to note that two regions famous for their fruit production like Niagara in Ontario and Okanagan in British Columbia exhibit higher rates of low fruit and vegetable consumption than the national overall rate of 55.8%. Figures 2 and 3 show maps and population cartograms of the Canadian health regions according to their rate of low leisure-time physical activity and of their rate of low fruit and vegetable consumption, respectively. Most of the dark-colored regions, corresponding to health regions with high rates of each factor, appeared in the Maritimes and in the Prairies. On the opposite, the light-colored regions for both factors were concentrated in western Canada (British Columbia and Yukon). In order to assess the ecological predictive power of low leisure-time physical activity, and low fruit and vegetable consumption as determinants of obesity, predictive values and odds ratios were calculated (Table 2) at a health region level. The positive predictive value was always over 80%, meaning that the health regions showing higher rates of low 679

4 680 Figure 1 Rates of obesity for individuals aged 20 years and older in 2003 by health region in Canada: traditional map and population cartogram. physical activity or of low fruit and vegetable consumption also scored higher on obesity rates; the association was even stronger when both factors were present. However, the odds ratios were significant for low fruit and vegetable consumption rates, and for the presence of both factors simultaneously, but not for low physical activity rates. On the other hand, lower negative predictive values were observed. In fact, low rates of both factors were not found to be associated with low rates of obesity. Discussion Differences in obesity rates across Canada found in this study are similar to the results of other researches carried out at the province level 9,31 or according to the urban rural area of residence. 32 In a country like Canada where the population is unevenly distributed over a vast territory, GIS methods can be useful in studying geographical variations in health problems, and their ecological relationships. In our study, the health region distribution of two factors related to obesity was used to address this issue. As can be seen, cartograms adjust the distortion caused by huge differences in population density between geographic areas: when the traditional map is considered, obesity seems to be more widespread in Canada than it really is, because vast areas with a very low population level show the highest prevalence of obesity. One might argue that the resulting map is also distorted, since it is almost impossible to recognize the country under study. Dealing with public health issues, it could be relevant to illustrate complementary maps based on the population distribution and on surface areas to provide a better understanding on how and where health problems occur, and how they are related. This article is the first attempt to illustrate the distribution of obesity and some of its related factors in Canada on a small area basis with the help of cartograms. The approach goes beyond provincial representations, and can raise cultural as well as urban rural inequalities, since it is possible to distinguish between metropolitan areas and smaller communities. Although it relies on cross-sectional data, it could provide a better understanding of obesity underlying

5 681 Figure 2 Rates of low level of leisure-time physical activity for individuals aged 20 years and older in 2003 by health region in Canada: traditional map and population cartogram. processes regarding the distribution of its contributing factors. It reveals, for example, that all three major metropolitan areas of Canada Vancouver, Toronto and Montreal exhibit a lower prevalence of obesity than other parts of the country, despite differences in their rates of low leisure-time physical activity and low consumption of fruits and vegetables. Both factors rates reach high levels in Toronto, which should be under close scrutiny for the evolution of obesity among its population. These lower obesity rates in metropolitan areas are consistent with results from other studies showing a higher prevalence in rural areas compared to urban areas, in western Canada 29 and in the Province of Quebec. 33 The lower level of leisure-time physical activity found in southern Quebec, in the southern part of the Prairies, and in the Maritimes, and the higher rate observed along the Pacific Coast up to Yukon, suggest that the climate is not the main factor for inactivity: more emphasis put on outdoor life and facilities in some parts of the country might be responsible for the observed difference. Among the three major metropolitan areas, Vancouver is well known for its urban design focusing on outdoor life. It is also possible that people moving to the Pacific Coast be attracted by such a lifestyle. The maps also show that in areas like Yukon, the obesity rate is quite high despite low rates of both related factors, which may suggest the influence of other determinants such as a genetic disposition among its population. The similar higher rates of obesity in the Northwest Territories, the northern part of the Prairies, and Labrador are partly linked to the importance of their aboriginal populations, who seem to be more characterized by a low fruit and vegetable consumption than by physical inactivity. However, the data do not indicate if this behavior is more related to a low availability of fruits and vegetables or to cultural practices. However, this fact should help designing appropriate programs to fight obesity among such populations, more prone to obesity due to their genetic inheritance. 18 The Maritime Provinces should also be a big concern for public health authorities, considering their high rates of obesity, of low level of leisure-time physical activity and of low fruit and vegetable consumption.

6 682 Figure 3 Rates of low daily fruit and vegetable consumption for individuals aged 20 years and older in 2003 by health region in Canada: traditional map and population cartogram. Table 2 Association a between low physical activity, fruit and vegetable consumption, and obesity at the health region level in Canada in 2003 Above Canadian rate (415.2%) Obesity rate Under Canadian rate (p15.2%) PPV/NPV Rate of low level of physical activity Above Canadian rate (449.7%) PPV: 82% 2.23 b Under Canadian rate (p49.7%) NPV: 33% F Rate of low fruit and vegetable consumption Above Canadian rate (455.8%) 62 9 PPV: 87% 6.89 c Under Canadian rate (p55.8%) NPV: 50% F Number of factors above Canadian rate Both 43 3 PPV: 93% 9.2 d One or none NPV: 39% F a PPV ¼ positive predictive value; NPV ¼ negative predictive value; OR ¼ odds ratio. b The association is not statistically significant P ¼ c The association is statistically significant Po d The association is statistically significant Po OR The strong positive predictive values of high rates of the two obesity-related factors suggest their importance as determinants. The total caloric intake and the overall physical activity level (including active transportation as well as leisure and work activities) could possibly enhance the predictive power of energy intake and expenditure as determinants of obesity. However, data allowing a more exhaustive portrait are still scarce, probably due to the difficulty of obtaining valid measures. On the other hand, the low negative predictive values observed may suggest that we did not take into account other factors such as genetic inheritance and cultural behaviors in the population observed. The emphasis put on leisure-time physical activity and on fruit and vegetable consumption does not mean that other factors do not play a role in obesity development. Socioeconomic status (education and income) for example, was also found important, people from lower status usually being more at risk of obesity. 15,34 Rely on cross-sectional data might also be questioned, considering the usually long delay in the occurrence of obesity at a population level. Nevertheless, physical activity

7 and food consumption are behaviors relatively stable over time; their current level is probably a good reflection of habits carried on for decades. Unfortunately, the absence of more exhaustive valid and repeated measures over time limits the possibility of considering better alternatives at this moment. Another limitation regarding the data from the 2003 CCHS survey is that height and weight were selfreported data, which can result in a bias of the BMI measure. However, this bias seems to be systematic according to data of the 2004 CCHS survey involving direct weight and height measurements from a smaller national sample: although a higher prevalence of adult obesity was found, the provinces with lower rates are still the same as in the present study, suggesting that underestimations observed with self-report data are evenly distributed. 35 Acknowledgements We are indebted to Michael T Gastner and Mark Newman for their valuable help by generously sharing their algorithm for producing cartograms. This project was subsidized by the GEOIDE Network of Centers of Excellence and Merck Frosst Canada Ltd. The principal investigator was supported by the Department of Family Medicine, Université de Sherbrooke; the Clinical Research Center, Sherbrooke University Hospital; and the FRSQ. References 1 Chopra M, Galbraith S, Darnton-Hill I. A global response to a global problem: the epidemic of overnutrition. Bull World Health Organization 2002; 80: Cutler DM, Glaeser EL, Shapiro JM. Why have Americans become more obese? J Econ Perspect 2003; 17: Calle EE, Rodriguez C, Walker-Thurmond K, Thun MJ. Overweight, obesity, and mortality from cancer in a prospectively studied cohort of U.S. adults. N Engl J Med 2003; 348: Field AE, Coakley EH, Must A, Spadano JL, Laird N, Dietz WH et al. Impact of overweight on the risk of developing common chronic diseases during a 10-year period. Arch Int Med 2001; 161: Visscher TLS, Seidell J. The public health impact of obesity. Ann Rev Publ Health 2001; 22: Birmingham CL, Muller JL, Palepu A, Spinelli JJ, Anis AH. The cost of obesity in Canada. Can Med Assoc J 1999; 160: Sturm R. The effects of obesity, smoking, and drinking on medical problems and costs. Health Affairs 2002; 21: Katzmarzyk PT, Janssen I. The economic costs associated with physical inactivity and obesity in Canada: An update. Can J Appl Physiol 2004; 29: Katzmarzyk PT. The Canadian obesity epidemic, Can Med Assoc J 2002a; 166: Katzmarzyk PT. The Canadian obesity epidemic: An historical perspective. Obes Res 2002b; 10: Tremblay MS, Katzmarzyk PT, Willms JD. Temporal trends in overweight and obesity in Canada, Int J Obes 2002; 26: Willms JD, Tremblay MS, Katzmarzyk PT. Geographic and demographic variation in the prevalence of overweight Canadian children. Obes Res 2003; 11: Gray-Donald K, Jacob-Starkey L, Johnson-Down L. Food habits of Canadians: Reduction in fat intake over a generation. Can J Publ Health 2000; 91: Perez CE. Fruit and vegetable consumption. Health Rep 2002; 13: Bryan S, Walsh P. Physical activity and obesity in Canadian women. BMC Women s Health 2004; 4 (Suppl I): S6. 16 Tremblay MS, Willms JD. Is the Canadian childhood obesity epidemic related to physical inactivity? Int J Obes 2003; 27: Craig CL, Russell SJ, Cameron C, Bauman A. Twenty-year trends in physical activity among Canadian adults. Can J Publ Health 2004; 95: Raine K. Overweight and. A Population Health Perspective. Canadian Institute for Health Information: Ottawa, Cromley EK. GIS and disease. Ann Rev Publ Health 2003; 24: Rushton G. Public Health, GIS, and spatial analytic tools. Ann Rev Publ Health 2003; 24: Natural Resource Canada. Land and freshwater area. Government of Canada Available from learningresources/facts/surfareas.html. Accessed October Health Canada. Canadian Community Health Survey, Available from Accessed October Health Canada. Canadian Guidelines for Body Weight: Classification in Adults. Health Canada: Ottawa, World Health Organization. Obesity: preventing and managing the global epidemic WHO Technical Report Series No World Health Organization: Geneva, Statistics Canada. Canadian Community Health Survey Available from /defin2.htm. Accessed October Bao S, Chen CH, Di L, Ding Y, Li B, Liu L et al. (eds). International symposium on geoinformatics and socioinformatics and geoinformatics 99, Proceedings of geoinformatics and socioinformatics; June 1999; University of Michigan, Ann Arbor. 27 Kocmoud DJ. Constructing Continuous Cartograms: A Constraint- Based Approach MS Thesis, Texas A&M University, December Keim DA, North SC, Panse S. Cartodraw: a fast ALGORITHM for generating continuous cartograms. IEEE Trans Visual Comput Graph 2004; 10: Gastner MT, Newman ME. Diffusion-based method for producing density-equalizing maps. Proc Natl Acad Sci 2004; 101: Cromley EK, McLafferty SL. GIS and Public Health. The Guilford Press, New York, Katzmarzyk PT, Ardern CI. Overweight and obesity mortality trends in Canada, Can J Publ Health 2004; 95: Reeder BA, Chen Y, Macdonald SM, Angel A, Sweet L. Regional and rural-urban differences in obesity in Canada. Canadian Heart Health Surveys Research Group. CMAJ 1997; 157: S10 S Huot I, Paradis G, Ledoux M. Quebec Heart Health Demonstration Project research group. Factors associated with overweight and obesity in Quebec adults. Int J Obes Relat Metab Disord 2004; 28: Vandegrift D, Yoked T. Obesity rates, income, and suburban sprawl: an analysis of US states. Health Place 2004; 10: Tjepkema M. Adult obesity in Canada: measured height and weight. Nutrition Findings from the Canadian Community Health Survey 2004; Issue no. 1. Available from english/research/ mie/ /articles/adults/aobesity. htm. Accessed October Supplementary Information accompanies the paper on website (