- Email: [email protected]
If I am biased, what am I supposed to do now?
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cANADIAN JoUrNAL oF DIAbEtEs
Patients were divided into four groups based on smoking status: Never Smokers, Former Smokers, Light Smokers, and Heavy Smokers. This was a prospective study, and weekly visit data were entered for each patient including: weight, weight management class attendance, quantity of meal replacement consumed, and mean number of cigarettes smoked. Using S.A.S. 9.2, statistical analysis was performed on the data, namely one-way ANOVA analysis, followed by Tukey’s HSD post-hoc analysis for the continuous data. Chi-square analysis was employed for the nominal data. results: There were 1,472 Never Smokers, 1,350 Former Smokers, 118 Light Smokers, and 241 Heavy Smokers. Never Smokers were more likely to attend weight-management classes than Heavy Smokers. Former Smokers followed the meal supplement plan more closely than Heavy Smokers. Never Smokers were the least likely of all groups to change their smoking status. Former Smokers were more likely than Never Smokers to smoke during the program. Light Smokers were more likely than Heavy Smokers to make a smoking cessation attempt. Significantly more per cent weight loss over the first eight weeks of the program was observed for Never Smokers, compared to Former Smokers. conclusons: By recognizing the significant differences between weighttreatment-seeking groups based on their smoking status, obesity and combined obesity-smoking cessation interventions could be developed to be more responsive to these different subgroups. 242 Use of Nutritional Information in canada: National trends between 2004 and 2008 S. Goodman1, D. Hammond1, F. Pillo-Blocka2, T. Glanville3, and R. Jenkins4 1 Department of Health Studies, University of Waterloo, Waterloo, Ontario, Canada; 2The Canadian Council of Food and Nutrition, Mississauga, Ontario, Canada; 3Faculty of Applied Human Nutrition, Mount Saint Vincent University, Halifax, Nova Scotia, Canada; 4Jenkins Research Inc., Ottawa, Ontario, Canada Introduction: Obesity is a primary risk factor for a range of chronic diseases, including cancer, type 2 diabetes, cardiovascular disease, and osteoarthritis. Diet is estimated to account for approximately 30% of cancers in industrialized countries. Recent estimates indicate that nearly one-quarter of adult Canadians are obese and 36% are overweight, while more than one-third of Canadian children and youth are either obese or overweight. Nutritional labelling on packaged food products is an important policy tool used to educate consumers and promote the selection of healthy foods. The present study sought to examine longitudinal trends in use of nutrition information among Canadian consumers over a five-year period. Methods: Representative samples of Canadian adults were recruited using Random Digit Dialling sampling in 2004 (n=2,405) and 2006 (n=2,014), and an online commercial panel in 2008 (n=2,001). Data was collected using population-based phone and Internet surveys. Main outcome measures included: socio-demographic predictors of product label use, use of nutrition information sources, and nutrient content information. Linear and logistic regression models were used to examine predictors and changes over time. results: Food product labels were the most common source of nutritional information in 2008, followed by the Internet and magazines/newspapers. The Internet was the only source to significantly increase over the study period; however, the frequency of reading food product labels increased since 2004. Food selection based on trans fat increased significantly in 2006, following mandatory labelling of trans fat on packaged foods. Taste and nutrition were consistently the primary factors guiding food choice. conclusions: Food product labels and the Internet emerged as nutrition information sources with broad reach. Longitudinal analyses revealed that more comprehensive labelling regulations were associated with increased label use and greater use of nutrient information over time.
243 consideration of measurement variability and its implication for feedback effects between body weight and physical activity behaviour P.B. Deck, S. White, C.L. Matteson, L.C. Masse, S.A. Lear, and D.T. Finegood Simon Fraser University, Department of Biomedical Physiology and Kinesiology, Burnaby, British Columbia, Canada background: Current knowledge of the complex interdependencies between physiological and behavioural mechanisms underlying weight regulation is incomplete. Understanding the variability and dynamics of measures used in feedback loops, such as body weight and physical activity levels, has implications for determining which measures are optimal for supporting behaviour change, and choosing the optimal frequency for measurement. approach: Nineteen healthy subjects ages 23-59 wore an Actigraph GTX3 accelerometer every day for 12 weeks. Weekly measurements included body weight, body composition, resting energy expenditure, and hip and waist circumference. Accelerometer data was processed using ActiLife v4.4.1 Software to generate steps, activity counts, and time spent at physical activity intensities. Body composition was measured using a Discovery X-Ray Bone Densitometer. results: Body weight (2.1%), waist circumference (2.9%), and per cent body fat (5.2%) varied by a small amount during the 12-week study. Physical activity measures, including mean daily steps (41.0%), activity counts (44.6%), and time spent in at least moderate intensity activity (62.8%), were highly variable. Despite a fourfold difference between the least active and the most active subject, there was no significant relationship between the level of physical activity (counts) and the weekly coefficient of variation (r=.350; P=0.155). conclusions: Highly variable measures, such as those that reflect activity levels, may demand more frequent measurement to enable integration and improved accuracy to enable use as feedback. Less variable measures such as body weight may help create more effective feedback loops when the time delay between behaviour change and the change in outcome is considered. 244 If I am biased, what am I supposed to do now? M. Vallis Capital Health/Dalhousie University, Halifax, Nova Scotia, Canada Introduction: The professional bias against obesity has become widely acknowledged. The extent of bias has been demonstrated in virtually all health care provider disciplines, including those professionals who provide service to the obese. In contrast to the literature demonstrating the existence of bias, there is very little in the way of effective strategies to reduce bias. This poster will provide a review of the literature on methods to reduce bias. Practical strategies to actively counter bias against obesity will be offered. A toolkit that can be used as an educational intervention will be outlined. The goal of this poster is to empower providers to take action to ensure that implicit bias does not inadvertently impair obesity management. 245 Multimodal measurement of body composition change with diet- and exercise-induced weight loss in obese women A.R. Josse1, S.A. Atkinson2, M.A. Tarnopolsky2, H. Azizian3, J.K.G. Kramer4 and S.M. Phillips1 1 Department of Kinesiology, McMaster University, Hamilton, Ontario, Canada; 2Pediatrics and Medicine, McMaster University Medical Centre, Hamilton, Ontario, Canada; 3NIR Technologies, Oakville, Ontario,
cANADIAN JoUrNAL oF DIAbEtEs
Patients were divided into four groups based on smoking status: Never Smokers, Former Smokers, Light Smokers, and Heavy Smokers. This was a prospective study, and weekly visit data were entered for each patient including: weight, weight management class attendance, quantity of meal replacement consumed, and mean number of cigarettes smoked. Using S.A.S. 9.2, statistical analysis was performed on the data, namely one-way ANOVA analysis, followed by Tukey’s HSD post-hoc analysis for the continuous data. Chi-square analysis was employed for the nominal data. results: There were 1,472 Never Smokers, 1,350 Former Smokers, 118 Light Smokers, and 241 Heavy Smokers. Never Smokers were more likely to attend weight-management classes than Heavy Smokers. Former Smokers followed the meal supplement plan more closely than Heavy Smokers. Never Smokers were the least likely of all groups to change their smoking status. Former Smokers were more likely than Never Smokers to smoke during the program. Light Smokers were more likely than Heavy Smokers to make a smoking cessation attempt. Significantly more per cent weight loss over the first eight weeks of the program was observed for Never Smokers, compared to Former Smokers. conclusons: By recognizing the significant differences between weighttreatment-seeking groups based on their smoking status, obesity and combined obesity-smoking cessation interventions could be developed to be more responsive to these different subgroups. 242 Use of Nutritional Information in canada: National trends between 2004 and 2008 S. Goodman1, D. Hammond1, F. Pillo-Blocka2, T. Glanville3, and R. Jenkins4 1 Department of Health Studies, University of Waterloo, Waterloo, Ontario, Canada; 2The Canadian Council of Food and Nutrition, Mississauga, Ontario, Canada; 3Faculty of Applied Human Nutrition, Mount Saint Vincent University, Halifax, Nova Scotia, Canada; 4Jenkins Research Inc., Ottawa, Ontario, Canada Introduction: Obesity is a primary risk factor for a range of chronic diseases, including cancer, type 2 diabetes, cardiovascular disease, and osteoarthritis. Diet is estimated to account for approximately 30% of cancers in industrialized countries. Recent estimates indicate that nearly one-quarter of adult Canadians are obese and 36% are overweight, while more than one-third of Canadian children and youth are either obese or overweight. Nutritional labelling on packaged food products is an important policy tool used to educate consumers and promote the selection of healthy foods. The present study sought to examine longitudinal trends in use of nutrition information among Canadian consumers over a five-year period. Methods: Representative samples of Canadian adults were recruited using Random Digit Dialling sampling in 2004 (n=2,405) and 2006 (n=2,014), and an online commercial panel in 2008 (n=2,001). Data was collected using population-based phone and Internet surveys. Main outcome measures included: socio-demographic predictors of product label use, use of nutrition information sources, and nutrient content information. Linear and logistic regression models were used to examine predictors and changes over time. results: Food product labels were the most common source of nutritional information in 2008, followed by the Internet and magazines/newspapers. The Internet was the only source to significantly increase over the study period; however, the frequency of reading food product labels increased since 2004. Food selection based on trans fat increased significantly in 2006, following mandatory labelling of trans fat on packaged foods. Taste and nutrition were consistently the primary factors guiding food choice. conclusions: Food product labels and the Internet emerged as nutrition information sources with broad reach. Longitudinal analyses revealed that more comprehensive labelling regulations were associated with increased label use and greater use of nutrient information over time.
243 consideration of measurement variability and its implication for feedback effects between body weight and physical activity behaviour P.B. Deck, S. White, C.L. Matteson, L.C. Masse, S.A. Lear, and D.T. Finegood Simon Fraser University, Department of Biomedical Physiology and Kinesiology, Burnaby, British Columbia, Canada background: Current knowledge of the complex interdependencies between physiological and behavioural mechanisms underlying weight regulation is incomplete. Understanding the variability and dynamics of measures used in feedback loops, such as body weight and physical activity levels, has implications for determining which measures are optimal for supporting behaviour change, and choosing the optimal frequency for measurement. approach: Nineteen healthy subjects ages 23-59 wore an Actigraph GTX3 accelerometer every day for 12 weeks. Weekly measurements included body weight, body composition, resting energy expenditure, and hip and waist circumference. Accelerometer data was processed using ActiLife v4.4.1 Software to generate steps, activity counts, and time spent at physical activity intensities. Body composition was measured using a Discovery X-Ray Bone Densitometer. results: Body weight (2.1%), waist circumference (2.9%), and per cent body fat (5.2%) varied by a small amount during the 12-week study. Physical activity measures, including mean daily steps (41.0%), activity counts (44.6%), and time spent in at least moderate intensity activity (62.8%), were highly variable. Despite a fourfold difference between the least active and the most active subject, there was no significant relationship between the level of physical activity (counts) and the weekly coefficient of variation (r=.350; P=0.155). conclusions: Highly variable measures, such as those that reflect activity levels, may demand more frequent measurement to enable integration and improved accuracy to enable use as feedback. Less variable measures such as body weight may help create more effective feedback loops when the time delay between behaviour change and the change in outcome is considered. 244 If I am biased, what am I supposed to do now? M. Vallis Capital Health/Dalhousie University, Halifax, Nova Scotia, Canada Introduction: The professional bias against obesity has become widely acknowledged. The extent of bias has been demonstrated in virtually all health care provider disciplines, including those professionals who provide service to the obese. In contrast to the literature demonstrating the existence of bias, there is very little in the way of effective strategies to reduce bias. This poster will provide a review of the literature on methods to reduce bias. Practical strategies to actively counter bias against obesity will be offered. A toolkit that can be used as an educational intervention will be outlined. The goal of this poster is to empower providers to take action to ensure that implicit bias does not inadvertently impair obesity management. 245 Multimodal measurement of body composition change with diet- and exercise-induced weight loss in obese women A.R. Josse1, S.A. Atkinson2, M.A. Tarnopolsky2, H. Azizian3, J.K.G. Kramer4 and S.M. Phillips1 1 Department of Kinesiology, McMaster University, Hamilton, Ontario, Canada; 2Pediatrics and Medicine, McMaster University Medical Centre, Hamilton, Ontario, Canada; 3NIR Technologies, Oakville, Ontario,