Socio-Demographic and Lifestyle Correlates of Obesity

Transcription

1 Socio-Demographic and Lifestyle Correlates of Obesity Technical Report on the Secondary Analyses Using the Canadian Community Health Survey C a n a d i a n P o p u l a t i o n H e a l t h I n i t i a t i v e

2

3 Socio-Demographic and Lifestyle Correlates of Obesity Technical Report on the Secondary Analyses Using the Canadian Community Health Survey Prepared by: Cora Lynn Craig (Canadian Fitness and Lifestyle Research Institute) Christine Cameron (Canadian Fitness Lifestyle Research Institute) Adrian Bauman (University of ew South Wales/ Canadian Fitness Lifestyle Research Institute)

4 The views expressed in this report do not necessarily represent the views of the Canadian Population Health Initiative or the Canadian Institute for Health Information. Contents of this publication may be reproduced in whole or in part provided the intended use is for non-commercial purposes and full acknowledgement is given to the authors and the Canadian Institute for Health Information. Canadian Institute for Health Information 495 Richmond Road Suite 600 Ottawa, Ontario K2A 4H6 Telephone: (613) Fax: (613) ISB (PDF) 2005 Canadian Institute for Health Information Cette publication est disponible en français sous le titre : Sommaire du rapport publié en anglais sous le titre «Socio-demographic and Lifestyle Correlates of Obesity Technical Report on the Secondary Analyses Using the Canadian Community Health Survey» ISB (PDF)

5 About the Canadian Population Health Initiative The Canadian Population Health Initiative (CPHI), a part of the Canadian Institute for Health Information (CIHI), was created in The mission of CPHI is twofold: to foster a better understanding of factors that affect the health of individuals and communities and to contribute to the development of policies that reduce inequities and improve the health and well-being of Canadians. As a key actor in population health, CPHI: provides analysis of Canadian and international population health evidence to inform policies that improve the health of Canadians; commissions research and builds research partnerships to enhance understanding of research findings and to promote analysis of strategies that improve population health; synthesizes evidence about policy experiences, analyzes evidence on the effectiveness of policy initiatives and develops policy options; and works to improve public knowledge and understanding of the determinants that affect individual and community health and well-being. i

6

7 Acknowledgements This report was written by Cora Lynn Craig, Canadian Fitness and Lifestyle Research Institute (CFLRI), Christine Cameron (CFLRI) and Adrian Bauman (University of ew South Wales/CFLRI). The report was commissioned by the Canadian Population Health Initiative (CPHI) of the Canadian Institute for Health Information (CIHI). The analysis for the report is based on Statistics Canada s Community Health Survey, Cycle 1.1, Public Use Microdata File, which contains anonymous data collected in the year The Canadian Fitness and Lifestyle Research Institute prepared all computations on these microdata, and the responsibility for the use and interpretation of these data is entirely that of the authors. It should be noted that the analyses and conclusions in the report do not necessarily reflect those of CPHI or CIHI. iii

8

9 Table of Contents About the Canadian Population Health Initiative... i Acknowledgements...iii Introduction...1 Research Questions...3 Methods...5 Study Design...5 Canadian Community Health Survey Measures Used in These Analyses...5 Analysis...10 Results...13 Section 1: Section 2: Section 3: Section 4: Body Mass and Lifestyle Patterns Among Canadians...13 Physical Activity, utrition and Smoking: Composite Lifestyle Profiles...17 Lifestyle and Socio-Demographic Correlates of Obesity...21 Potential Protective Factors in Following a Healthy Lifestyle...24 Summary of Key Results...32 Authors Discussion...33 Methodological Limitations...35 Authors Summary of Implications for Policy and Monitoring...39 Concluding Remarks of the Authors...40 Appendix 1 Detailed Tables...41 Appendix 2 Preliminary Investigation: Correlates of Diabetes Appendix 3 Prevalences of Lifestyle Factors for Youth (12 to 19 Years) References...121

10 List of Tables Table 1.1a Body Mass Index, Adults Aged 20 to Table 1.1b Body Mass Index, Men and Women Aged 20 to Table 1.2 Physical Activity Level of Adults Aged Table 1.3 Consumption of Fruits and Among Adults Aged Table 1.4 Smoking Patterns of Adults Aged Table 2.1a Lifestyle Correlates of Overweight and Obesity (BMI 25.0+), Adults Aged 20 to Table 2.1b Lifestyle Correlates of Obesity (BMI 30.0+), Adults Aged 20 to Table 2.1c Lifestyle Correlates of Obesity (BMI 30.0+), Men and Women Aged 20 to Table 2.2a Healthy Living Composite Score (on-smoking)...59 Table 2.2b Healthy Living Composite Score for Males (on-smoking)...62 Table 2.2c Healthy Living Composite Score for Females (on-smoking)...64 Table 2.2d Healthy Living Composite Score (Smoking)...66 Table 2.2e Healthy Living Composite Score for Males (Smoking)...68 Table 2.2f Healthy Living Composite Score for Females (Smoking)...70 Table 2.2g Physical Activity and utrition Profile by Body Mass Index...72 Table 3.1a Correlates of Overweight and Obesity (for on-smokers)...74 Table 3.1b Correlates of Obesity (for on-smokers)...76 Table 3.2 Correlates of Obesity for Men and Women (for on-smokers)...78 Table 3.3a Correlates of Overweight and Obesity (for Daily Smokers)...80 Table 3.3b Correlates of Obesity (for Daily Smokers)...82 Table 3.4 Correlates of Obesity for Men and Women (for Daily Smokers)...84 Table 4.1a Potential Protective Factors: Social Support and Stress...86 Table 4.1b Potential Protective Factors: Food Security, Self-Esteem, Mastery and Intention...88 Table 4.1c Table 4.2 Potential Protective Factors: Changes Made to Improve Health...91 Factors Distinguishing Between Those Following a Healthy Lifestyle and ot...94 Table 4.3a Factors Distinguishing Between Those Following a Healthy Lifestyle and ot...96 Table 4.3b Factors Distinguishing Between Those Following a Healthy Lifestyle and ot...98

11 List of Tables (cont'd) Table 4.3c Factors Distinguishing Between Those Following a Healthy Lifestyle and ot Table 4.3d Factors Distinguishing Between Those Following a Healthy Lifestyle and ot Table 4.3e Factors Distinguishing Between Those Following a Healthy Lifestyle and ot Table 4.3f Factors Distinguishing Between Those Following a Healthy Lifestyle and ot Appendix 2, Table 1 Correlates of Diabetes, Adults Aged 45 to Appendix 3, Table 1 Appendix 3, Table 2 Appendix 3, Table 3 Appendix 3, Table 4 Physical Activity of Youth Fruit and Vegetable Consumption of Youth Smoking Patterns of Youth Healthy Lifestyle Patterns of Youth (on-daily Smokers) List of Figures Figure 1 Overweight and Obesity by Age and Sex (%)...13 Figure 2 Overweight and Obesity by Education and Income (%)...14 Figure 3 Physical Activity by Age, Sex, Education and Income (%)...15 Figure 4 Fruit and Vegetable Consumption by Age, Sex, Education and Income (%)...16 Figure 5 Smoking Rates by Age, Sex, Education and Income (%)...17 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Relationship of Physical Activity, utrition and Smoking With Overweight and Obesity (Odds and 95% Confidence Intervals)...18 Healthy Lifestyles: Physical Activity and utrition Profile of Smokers and on-smokers...19 Lifestyle and Socio-Demographic Correlates of Obesity, on-smokers (Odds Ratios and 95% Confidence Limits)...21 Provincial Associations With Obesity, Controlling for Lifestyle and Other Demographic Factors, on-smokers (Odds and 95% Confidence Limits)...22 Lifestyle and Socio-Demographic Correlates of Obesity, Daily Smokers (Odds and 95% Confidence Limits)...23

12 List of Figures (cont'd) Figure 11 Figure 12 Figure 13 Environmental Correlates of Healthy Weight and Healthy Lifestyle (BMI ) (Odds Ratios and 95% Confidence Limits)...27 Association of Mastery and Self-Esteem With Healthy Weight and Healthy Lifestyle (BMI ) (Odds Ratios and 95% Confidence Limits)...28 Behavioural Correlates of Healthy Lifestyle and Healthy Weight (BMI ) (Odds Ratios and 95% Confidence Limits)...29

13 Introduction Introduction The prevalence of overweight and obesity has been increasing steadily among adult Canadians and children since the early 1970s to the late 1990s. 1, 2, 3, 4 The number of obese Canadian adults (aged 20 to 64) increased by more than 500,000, to almost 2.8 million, from to , 5 so that a full 15% of the adult population is currently classified as obese (vs. 13% in ). The burden on the health system attributable to overweight and obesity is substantial, due to associated increased risks of heart disease, high blood pressure, diabetes, some cancers and musculo-skeletal disorders, 6, 7, 8 as well as a host of psychological and social disorders. 9 For example, in the United States, researchers found that overweight and obesity were significantly associated with diabetes: compared with adults of normal weight, severely obese individuals were seven times more likely to have been diagnosed with diabetes (odds ratio of 7.37, CI of 6.39 to 8.50). 10 In the U.S., it is estimated that 300,000 deaths per year are related to physical inactivity and poor nutrition both of which are key factors related to obesity. 11 Moreover, recent estimates of the total direct cost of obesity in Canada amount to more than $1.8 billion (2.4% of total health care expenditures for all diseases). 12, 13 On the surface, it would appear that overweight and obesity are simply a result of a mismatch between energy consumed (through food intake) and energy expended (through physical activity). This perspective suggests individually targeted behaviour change strategies to increase individual self-efficacy, intention and perceived personal control over diet and physical activity choices would be an important approach to addressing overweight and obesity 14, 15, 16 However, Kumanyika 17 has illustrated the complex interaction of family and community (school, work and home) as well as regional, national and international-level factors that contribute to obesity by influencing physical activity and nutritional choices at the individual level. Furthermore, considerable research has demonstrated the association between socioeconomic factors and health, wherein people of lower income experience greater morbidity and premature mortality than do their higher-income counterparts, 18, 19, 20 and this same pattern is observed for lifestyle risk factors like smoking, dietary fat consumption and physical activity. 21, 22, 23 Persons of lower income and education are more likely to smoke, are more likely to consume higher levels of dietary fat and are less likely to be physically active. This suggests our understanding of conditions like obesity would be enhanced by simultaneously examining the social determinants of health and lifestyle practices. The Canadian Population Health Initiative (CPHI) of the Canadian Institute for Health Information (CIHI) fosters knowledge about the factors that affect population health. CPHI commissioned this paper to explore the associations of socioeconomic factors and healthy lifestyle characteristics with overweight and obesity among adult Canadians. In addition, this report identifies protective factors that enable individuals in disadvantaged groups (who are more likely to be overweight) to maintain a healthy weight and healthy lifestyle. In particular, it explores how social cohesion (being connected), social capital (sense of community and perceptions of mutual aid and support), civic engagement 1

14 Socio-Demographic and Lifestyle Correlates of Obesity Technical Report on the Secondary Analyses Using the Canadian Community Health Survey (involvement in social networks) and collective efficacy (sense of power) might be related to health outcomes in this case obesity and overweight. Additionally, the odds of being diagnosed with diabetes were examined. Results of this exploratory analysis are presented in the report. The Canadian Community Health Survey (CCHS) is a large survey conducted by Statistics Canada across Canada and examines health status and risk behaviours and their correlates. A broad range of information is gathered on physical activity, smoking, diet quality, height, weight, health and socio-demographic variables. The large representative sample makes it suitable for exploring the associations between lifestyle and socioeconomic variables and overweight and obesity, particularly among relatively small subgroups of the population. It asks for information about psychosocial health, as well as information on social support, self-esteem, mastery, stress, behavioural intentions, food insecurity and sedentary pursuits, which may be relevant to understanding why people have healthy lifestyles or not. The purpose of this paper is to examine the socio-economic and lifestyle factors associated with obesity among adults from the CCHS: Section 1 explores the prevalence of obesity and overweight (body mass index), and the relationship between obesity and overweight and age, sex, education, income, employment status, marital status, language, membership in a visible minority group and province; it also explores the prevalence of three major behavioural risk factors: smoking, low fruit and vegetable consumption and physical inactivity. The demographic correlates of these behavioural risk factors are also presented. Section 2 develops an overall lifestyle profile by examining the association between combinations of several lifestyle factors (behavioural risk factors) and levels of obesity and overweight. Section 3 further documents the associations between obesity and the derived lifestyle profile and socio-demographic factors. Section 4 explores protective factors, which may influence the relationships among the behavioural variables and obesity. Specifically, these analyses explore whether social support, 24, 25 self-esteem, 26, 27 mastery, stress, 28 intentions, 29, 30, 31, 32 food insecurity and sedentary pursuits are related to the likelihood that people follow the healthiest lifestyle pattern identified in Section 3 and maintain an optimal body mass. The influence of these factors has been documented in several prominent framework theories examining why individuals exhibit healthy lifestyle behaviours, including the Theory of Planned Behaviour. 14 The relative importance of protective factors is explored among persons in those socio-demographic groups who are most likely to be overweight or obese, but who do not engage in the unhealthy lifestyle behaviours expected. Finally, the policy and research implications of the findings are discussed for the general population and select groups. 2

15 Introduction Research Questions The primary research questions addressed in this report include: 1. What is the prevalence of overweight and obesity among adult Canadians? Is the prevalence of overweight and obesity higher in certain population groups than others? 2. Does the likelihood of being overweight or obese vary by physical activity and diet quality and, if so, do these differ between those who smoke daily and those who do not? 3. Does the strength of association between overweight or obesity and the sociodemographic factors and lifestyle factors differ for those who smoke daily and those who do not? 4. Are individual factors like perceived sense of control, intention and involvement in sedentary pursuits associated with following a healthy lifestyle pattern? Are psychosocial factors (for example, social support and social interaction) and environmental factors (for example, work stress and food insecurity) associated with following a healthy lifestyle pattern? Does the relative importance of individual, social and environmental factors differ between select disadvantaged groups (for example, lower income, lower education level and single women) and the population more generally? 3

16

17 Methods Methods Study Design This study analyzed data from Statistics Canada s Canadian Community Health Survey (CCHS). The sample design of the CCHS was a stratified multi-stage cluster design of the non-institutionalized household population. 33 Households were selected from the Labour Force Survey s area frame and supplemented by random digit dialing according to the methods of the General Social Survey. Eligible individuals were selected at random within households following a protocol based on the number of adults and youth living in the household. The CCHS was designed to produce estimates at the health region level within provinces and territories. The sample was allocated in proportion to the population and number of health regions within a province or territory and, within provinces, was selected in proportion to the square root of the population of the health regions. The 85% response rate yielded interviews from approximately 130,000 Canadians during the 14-month data collection period. Trained Statistics Canada interviewers conducted computer-assisted personal interviews with respondents selected from the area frame and computer-assisted telephone interviews with respondents from the telephone frame. Proxy data was collected if the selected respondent was unable to participate due to lack of availability throughout the data collection period due to physical or mental incapacity or to language barriers. This occurred in 6% of the cases nationally. In these cases, physical activity data were treated as missing and fruit and vegetable consumption was imputed. Canadian Community Health Survey Measures Used in These Analyses Body mass index. Self-reported height and weight were collected during the CCHS interviews, from which body mass index (BMI) was derived by Statistics Canada for individuals 20 to 64 years old, excluding pregnant women. BMI was calculated as the weight in kilograms divided by the squared height in metres (BMI=kg/m 2 ) and truncated to a minimum of 14 and a maximum of 58. These truncation rules were developed by Statistics Canada, and BMI data were not provided outside this range. Although there are certain limitations to using BMI (please see the Methodological Limitations section for further details), it is widely used in epidemiological studies as a measure of health risk. For the purpose of this analysis, we used the classifications of BMI from the Canadian guidelines. 34 These BMI guidelines are updated, based on the 1988 Canadian classifications. They were recently revised by Health Canada and a team of research experts as a result of the World Health Organization s recommendations for international standards for adults. The classifications are detailed in the table below. 5

18 Socio-Demographic and Lifestyle Correlates of Obesity Technical Report on the Secondary Analyses Using the Canadian Community Health Survey Body Mass Index Classifications for Adults Aged 18 to 65 Classification BMI category Underweight <18.5 Increased ormal weight Least Relative risk of developing health problems Overweight Increased Obese Class I High Class II Very high Class III >=40.0 Extremely high Source: Health Canada (2003). Adapted from: Health Canada s 2003 Canadian Guidelines for Body Weight Classification in Adults. Given the wide range of topics covered by the CCHS, not all questions were asked of all respondents, and some data were collapsed by Statistics Canada prior to release (for example, age groups for children were collapsed into two age groups: 12 to 14 and 15 to 19). This precluded the estimation of BMI cut-points for children, which requires calculation by single year of age. 35 Physical activity. Participation in leisure-time physical activity was evaluated using a modification of the Physical Activity Monitor, which was based on the Minnesota Leisure-Time Physical Activity Questionnaire (MLTPAQ). 36 Like the MLTPAQ, the physical activity question asked details about participation in each of a pre-determined list of physical activities and up to three additional activities that could be volunteered by the respondent. Detailed information included the number of occasions on which the respondent participated in the activity in the previous three months and the average time spent per occasion. However, there were two differences. The Statistics Canada question asked about a 3-month rather than a 12-month recall period, and the time spent in activity had the following four response categories: less than 15 minutes, 15 to 29 minutes, 30 to 59 minutes and more than 60 minutes. A physical activity index was derived by summing the number of occasions for each activity multiplied by the associated time per session and metabolic equivalents (MET) value for the intensity of the activity, where the MET value of metabolic energy cost represents a multiple of the resting metabolic rate. The MET values in kilocalories per kilogram body weight per day (KKD) were established by an expert panel in 1981 for the Canadian Fitness and Lifestyle Research Institute s surveys. 37 From this index, Statistics Canada derived a categorical variable: inactive (<1.5 KKD), moderately active (1.5 to 2.9 KKD) and active (3.0+ KKD). 6

19 Methods Although this investigation is restricted to adults, two additional cut-points were established to better understand the range of energy expenditure in the population for youth: a cut-point of 0.5 KKD in the lower end of the inactive category and 6.0 KKD in the most active category, the latter being an internationally recommended cut-point for adolescents. 38 The results appear in Appendix 3. Dietary practices. The nutrition question in the CCHS was the respondent s self-reported total daily consumption of fruit and vegetables. The respondent was asked to report on the number of times per day such items as fruit juice, fruits, salad, potatoes (not including french fries or potato chips), carrots and other vegetables were consumed. There are some methodological concerns regarding self-reported dietary indicators, but for the purpose of these analyses, responses were grouped into three broad categories. The number of times per day fruit and vegetables were consumed were summed and then categorized into: less than 5 times, 5 to 10 times and more than 10 times. The latter two categories were collapsed in the current analyses to maintain power, as relatively few people consumed fruit and vegetables more than 10 times daily. Smoking. Current (tobacco) smoking status was also assessed through self-report. Respondents were asked if they had ever smoked a total of 100 cigarettes in their lifetime, and then those who had done so were asked if they currently smoked daily, occasionally or not at all. The current status was then defined as daily, occasionally and not at all (including former smokers). Healthy living variable. A composite healthy living profile was derived for adults by examining combinations of physical activity, nutrition and smoking, and by assessing the relationship between these healthy living attributes and obese or overweight status, controlling for age, sex and demographic variables. The healthy living composite groupings were created separately for daily and for non-daily smokers, based on identified combinations of physical activity and nutrition. Then, the relationship between healthy living and the likelihood of being overweight or obese was examined. Based on the associations with obesity and overweight, a four-category healthy living grouping was developed for daily smokers, and a six-category grouping for those who did not smoke daily. For individuals who smoked daily, the four categories developed were: Smokers who were inactive, regardless of fruit and vegetable consumption; Smokers who were moderately active and consumed fruit and vegetables less than five times daily; Smokers who were moderately active and consumed fruit and vegetables more than five times daily; and Smokers who were active, regardless of fruit and vegetable consumption. 7

20 Socio-Demographic and Lifestyle Correlates of Obesity Technical Report on the Secondary Analyses Using the Canadian Community Health Survey For individuals who did not smoke daily, six categories developed were: on-smokers who were inactive and consumed fruit and vegetables less than five times daily; on-smokers who were inactive and consumed fruit and vegetables more than five times daily; on-smokers who were moderately active and consumed fruit and vegetables less than five times daily; on-smokers who were moderately active and consumed fruit and vegetables more than five times daily; on-smokers who were active and consumed fruit and vegetables less than five times daily; and on-smokers who were active and consumed fruit and vegetables more than five times daily. Sedentary pursuits, behaviour changes and intention. The total time spent in sedentary pursuits was a Statistics Canada derived variable totalling the amount of time spent in each of the following pursuits in a typical week other than at work or at school: using a computer, including playing computer games or using the internet or World Wide Web; playing video games, such as SEGA, intendo and Playstation; watching television or videos; and reading. Respondents were asked if they had made a change to improve their health in the previous 12 months, and those who did answered a subsequent question on the specific change made. Using a parallel approach, respondents were asked if they intended to make any change in the next year and what that change would be. Personal attributes. The self-esteem and mastery variables were derived by Statistics Canada based on standard scales. 39 The self-esteem variable used in this analysis is an index representing the extent of positive feelings held by the respondent. A higher score on the index variable represents greater self-esteem. The mastery variable is an index measuring degree to which respondents feel that their life chances are under their control. Higher scores on the index variable represent higher degrees of mastery. 8

21 Methods Social environmental level variables. Indicators for the respondent s social environment were based on Statistics Canada derived variables from the Medical Outcomes Study Social Support Survey scale. Four social support scales that were originally developed for the Medical Outcomes Study were used in the analysis: tangible support, affection, positive social interaction and emotional or informational support. Each item was scored on a five-point scale from 0 (representing none of the time ) to 4 (representing all of the time ). Tangible support was constructed from questions about whether or not people had someone to help them if they were either confined to bed, needed to go to a doctor or needed help preparing meals or doing other daily chores. Affection comprised items about receiving love, getting hugs or feeling wanted. Positive social interaction consisted of questions about whether the person had someone with whom they could get together for relaxation, have a good time, do something enjoyable or do something to get their mind off things. Respondents rated their perception of how much stress they faced in their life and at work generally as not at all, not very, a bit, quite a bit or extremely high. Perceived difficulty in accessing food was assessed by asking if someone in the household had been worried often, sometimes or never in the past 12 months that there would not be enough food to eat or that the quality or variety of food would be inadequate. These items were combined to form a food insecurity score, with some representing at least sometimes to at least one of the items. Socio-demographic variables. A number of socio-demographic variables were available on the microdata file. The highest level of education acquired by the respondent was classified as less than secondary school graduation, secondary school graduation with no post-secondary education, some post-secondary education or post-secondary degree/diploma. Household income was the reported total income before taxes, including income from all sources and across all household members. This was grouped into the following five categories: less than $15,000, $15,000 to $29,999, $30,000 to $49,999, $50,000 to $79,999 and $80,000 or more. In addition, a low-income variable was calculated based on household income and the number of individuals living in the household defined by: less than $15,000 if one or two people, less than $20,000 if three or four people or less than $30,000 if five or more people. In addition to education and household income, marital status, employment status, language and ethnicity variables were included in the analysis. Marital status was grouped into three categories: married or common-law; widowed, separated or divorced; and single (never married). Employment status was derived by combining the responses from three separate questions regarding whether or not a respondent was currently a student, whether he or she had a job in the week prior to being surveyed and, if he or she did not have a job and the reason (retired, illness, other responsibilities, no work available, etc.). The grouped responses were working students, working non-students, retired people and other nonworking people. 9

22 Socio-Demographic and Lifestyle Correlates of Obesity Technical Report on the Secondary Analyses Using the Canadian Community Health Survey Although language and ethnicity were asked with extensive response sets, they were highly aggregated. As a result, they do not provide a strong indication of cultural background. Language was a self-assessment of the official languages in which respondents could converse: English (with or without language other than French), French (with or without language other than English), English and French (with or without other language), and neither English nor French (other). Cultural origin was collapsed into whether or not the respondent s background included a visible minority (that is, yes to at least one of the following: Chinese, South Asian, Southeast Asian, Arab, West Asian, Japanese, Korean or Aboriginal Peoples or other). Finally, date of birth was asked, recoded into age and released in the age categories of 12 to 14, 15 to 19, 20 to 24, 25 to 29, 30 to 34 and so on to 75 to 79 and 80 years and older. We further grouped the age of adults to reflect major life stages (25 to 44, 45 to 64 and 65 and older). There were few indicators of the physical environment in which the respondent lived available through the CCHS. For purposes of this report, an indicator of location was the specific province in which the respondent lived and a grouped indicator for people living in any of the three territories. Analysis Statistics Canada s standard derived variables for daily consumption of fruit and vegetables, physical activity and smoking were used to investigate lifestyle practices among the adult population (20 to 64) for whom body mass index was available. Prevalence estimates were calculated for lifestyle variables for all Canadians 20 years old and older; the detailed tables are presented in Appendix 1. (Lifestyle prevalences for youth appear in Appendix 3.) This was then further examined controlling for socioeconomic variables. The relative strength of associations was estimated between overweight and obesity and both lifestyle and socio-demographic factors. The purpose of the final set of analyses was to understand which factors might act as potential protective factors in following a healthy lifestyle. The factors examined were social support, changes made to health, accessibility of food and sedentary activities. Their relative potential in this regard was examined by comparing the strength of their associations with following a healthy lifestyle among Canadians having an optimal body mass. This analysis was repeated among populations at increased risk of overweight and obesity to determine if these potential protective factors differ among higher-risk groups. Cut-points for the social support scales and the hours spent in sedentary pursuits in this analysis were created based on their frequency distributions. At risk groups were identified as those whose members had a higher likelihood of diabetes or overweight and obesity. 10

23 Methods A sample weight was provided to each individual on the microdata file reflecting the number of Canadians they effectively represented. The weight was calculated based on sample design, non-response and post-stratification by age and sex within health region. All estimates were calculated using a rescaled sample weight (average sample weight = 1). Students t-tests were used to compare prevalence rates using an appropriate design effect and Bonferroni adjustment for multiple comparisons. 40 Due to the large number of significant results, only comparisons with a specified category (usually the first) are presented in the tables. The relative associations between obesity and various sociodemographic and lifestyle factors were tested using fully adjusted odds ratios taking into account age, sex, income, education, marital status, language, ethnicity, smoking, physical activity and nutrition. All tests were performed at the p<0.05 level, using standard confidence intervals. 11

24

25 Results Results * Section 1: Body Mass and Lifestyle Patterns Among Canadians Body Mass Index Table 1.1a in Appendix 1 summarizes the distributions of individuals aged 20 to 64 according to internationally used categories of body mass index (BMI), a measure of weight relative to height. 41 Data were available for people aged 20 to 64. According to the Canadian Community Health Survey, 15% of adults aged 20 to 64 were obese and another 33% were overweight. As age increased, the prevalence of overweight and obese adults increased, with 21% and 8% of adults aged years classified as overweight and obese respectively, and 39% and 19% of adults years considered overweight and obese, respectively. Figure 1 Overweight and Obesity by Age and Sex (%) 100% 80% 60% % 20% % Women Men Age Sex < Source: Canadian Community Health Survey, Statistics Canada, Whereas there was a small significant difference in the prevalence of obesity between men and women (16% for men versus 14% for women), there was a marked difference in the prevalence of overweight (40% for men versus 26% for women) (Figure 1). The gender differences appear regardless of age group, with one exception. That exception is that there are no gender differences in obesity rates between those aged 20 to 24. * Findings from the analysis are provided in Appendix 1 (Tables 1 to 4.3f). The text discusses these findings along with figures where appropriate. 13

26 Socio-Demographic and Lifestyle Correlates of Obesity Technical Report on the Secondary Analyses Using the Canadian Community Health Survey Figure 2 shows the relationships between overweight/obesity and educational attainment and income. More individuals were obese in the lowest education group compared to other groups. The percentage of adults having a BMI in the optimal weight category was lower in the lower education groups (Figure 2). Other relationships detailed in Table 1.1b suggest that overweight was higher for middle- or high-income males compared to those with low income, while obesity was lower for middle- to high-income women. Obesity was highest among English speakers overall and among those from the Atlantic provinces and Saskatchewan (Table 1.1a). Figure 2 Overweight and Obesity by Education and Income (%) 100% 80% 60% % 20% % < secondary 2 Secondary 3 Some postsecondary 4 Post-secondary 2 < $15,000 4 $15,000 $29,999 4 $30,000 $49,999 3 $50,000 $79,999 2?80,000 2 Education Income < Source: Canadian Community Health Survey, Statistics Canada, Physical Activity Level Table 1.2 summarizes physical activity levels of Canadian adults. Just over half (56%) of Canadian adults were physically inactive, with more of the remaining adult population being moderately active (24%) than active (20%). There was an east-to-west decrease in inactivity levels across Canada: 61% of Canadians in the eastern provinces were inactive, compared with 50% in the western provinces. Although the actual percentages differed, these relationships held for males and females. 14

27 Results Figure 3 shows that older age groups had higher levels of physical inactivity, with 46% of adults aged 20 to 24, compared with 62% of older adults (aged 65 or older) considered to be inactive. More women than men were physically inactive, and this difference was apparent for all age groups. Adults with higher income and education levels had a lower prevalence of physical inactivity, and this was equally true for men and women. Physical inactivity was most prevalent among those not working (for a reason other than retirement), those widowed, divorced or separated, visible minorities and those who were underweight and obese compared to others (Table 1.2). Figure 3 Physical Activity by Age, Sex, Education and Income (%) 100% 80% 60% 40% 20% % Men Women < secondary Secondary Some postsecondary Post secondary < $15,000 $15,000 $29,999 $30,000 $49,999 $50,000 79,999?$80,000 Age Sex Education Income <1.5 KKD KKD 3+ KKD Source: Canadian Community Health Survey, Statistics Canada, Frequency of Fruit and Vegetable Consumption Almost two-thirds (63%) of adults reported consuming fewer than five fruits and vegetables daily, and this was more prevalent among men (69%) than women (57%) (Figure 4). Adults 65 years old and older were more likely to consume fruit and vegetables five or more times daily compared to younger adults. Differences between men and women appear at all ages, but are most apparent in the ages from 25 to 64 (Table 1.3). 15

28 Socio-Demographic and Lifestyle Correlates of Obesity Technical Report on the Secondary Analyses Using the Canadian Community Health Survey Figure 4 Fruit and Vegetable Consumption by Age, Sex, Education and Income (%) 100% 80% 60% 40% 20% % Men Women < secondary Secondary Some postsecondary Post secondary < $15,000 $15,000 $29,999 $30,000 $49,999 $50,000 79,999?$80,000 Age Sex Education Income <5 times 5 10 times >10 times Source: Canadian Community Health Survey, Statistics Canada, Low fruit and vegetable consumption was related to income, with those with the lowest income reporting worse nutritional intake, and with the gradients being stronger for women than men. Other prevalence rates in Table 1.3 suggest that low fruit and vegetable intake was most prevalent among adults living in ewfoundland and Labrador, ova Scotia, ew Brunswick, Manitoba, Saskatchewan, Alberta and the orth, among those who were obese and among women of visible minorities. Smoking Patterns In this survey, 23% of adult Canadians reported that they smoked daily, and 4% reported smoking occasionally. The majority reported being non-smokers (73%). More men (25%) than women (20%) reported smoking daily; also, the percentage of people smoking daily decreased as age increased (Figure 5). In general, relatively fewer people in higher education and income groups smoked daily compared with those with lower education and income levels. Smoking daily was more prevalent among those not working (for a reason other than retirement), those who had never been married, orthern residents, Caucasians and those speaking French, compared with other groups (Table 1.4). 16

29 Results Figure 5 100% Smoking Rates by Age, Sex, Education and Income (%) 80% 60% % 20% 0% Men Women < secondary Secondary Some postsecondary Post secondary < $15,000 $15,000 $29,999 $30,000 $49,999 $50,000 79,999?$80,000 Age Sex Education Income Daily Occasional ot at all Source: Canadian Community Health Survey, Statistics Canada, Section 2: Physical Activity, utrition and Smoking: Composite Lifestyle Profiles This section examines the interrelationships among physical activity, dietary pattern and smoking, and their relationship to overweight and obesity followed by a discussion on the proportion of the population with healthy and less healthy combinations of these lifestyle factors. Associations Between Physical Activity, utrition and Smoking With Overweight/Obesity Table 2.1a first shows the relationships between each of these lifestyle variables and the likelihood of being overweight or obese. Then, the associations between the derived lifestyle profiles with overweight or obesity are explored separately for daily smokers and occasional smokers/non-smokers. These analyses are carried out with adjustments made for age, sex and other demographic factors. Taking demographic factors into account, more active adults were less likely to be overweight or obese, with active adults being 22% less likely than inactive adults to be overweight or obese. Similarly, adults who consumed fruit and vegetables frequently were significantly (8%) less likely to be overweight or obese than those consuming them infrequently. By contrast, occasional and non-smokers were more likely to be overweight or obese than daily smokers (24% and 44% more likely, respectively). 17

30 Socio-Demographic and Lifestyle Correlates of Obesity Technical Report on the Secondary Analyses Using the Canadian Community Health Survey Figure 6 shows that similar associations were found between healthy lifestyle variables and overweight or obesity, and with obesity alone (right-hand side, Figure 6). Although the directions of the relationship persisted for all lifestyle factors, the association was stronger between being active and not being obese (Table 2.1b) than was found between being active and not being obese or overweight (Table 2.1a). Figure 6 Relationship of Physical Activity, utrition and Smoking With Overweight and Obesity (Odds and 95% Confidence Intervals) Odds of overweight/obesity Inactive Moderately active Active < 5 fruit/veg 5+ fruit/veg Smoking, daily Smoking, occasional Smoking, not at all Inactive Moderately active Active < 5 fruit/veg 5+ fruit/veg Smoking, daily Smoking, occasional Smoking, not at all Overweight or obese Obese Source: Canadian Community Health Survey, Statistics Canada, The relationships were then explored for the composite healthy lifestyle variables after stratification by smoking status. From a preliminary examination of relationships by type of smoker, it was determined that the pattern of odds for physical activity and nutrition combinations were fairly consistent for occasional and non-smokers. Therefore, occasional and non-smokers were combined. Among individuals who did not smoke daily, the chance of being overweight or obese decreased as physical activity level increased, controlling for fruit and vegetable consumption. Within each activity level, the frequent consumption of fruit and vegetables was associated with a further reduction in the chance of being overweight or obese. Finally, for the healthiest group (non-smokers, consuming five or more servings of fruit and vegetables and active) the likelihood of being overweight or obese was 37% lower than the least healthy group (non-smokers, consuming less than five servings of fruit and vegetables and inactive: Table 2.1a). Similarly, the healthiest group (non-smokers, consuming five or more servings of fruit and vegetables and active) had a 56% lower risk of being obese compared to the least healthy group (Table 2.1b). This relationship was also seen for both men and for women (Table 2.1c). The analyses also focused on daily smokers. Among this group, compared to those who were inactive (irrespective of nutrition), those who were active were less likely to be overweight or obese (14% to 15% less likely: Table 2.1a) or to be obese (32% to 37% less likely: Table 2.1b). 18

31 Results To summarize, among non-smokers, those who were active and had high fruit and vegetable consumption had reduced odds of being obese. In contrast, non-smokers who were inactive with low fruit and vegetable consumption had increased odds of being obese. Among smokers, being active was associated with lower odds of being obese compared to being inactive. Healthy Lifestyles: Physical Activity and utrition Profile of Smokers and on-smokers Figure 7 summarizes the proportions of daily smokers and non-smokers who face the highest and lowest odds of being overweight or obese. The healthy combinations were more prevalent among younger non-smokers and daily smokers. Further details on the prevalence of other lifestyle combinations are provided in Tables 2.2a through 2.2f. Figure 7 Healthy Lifestyles: Physical Activity and utrition Profile of Smokers and on-smokers (%) 100% 90% 80% 70% 60% 50% 40% % 20% 10% 0% Women Men years years years Women Men years years years on-smokers Daily smokers Less healthy combination Other combination Healthier combination Source: Canadian Community Health Survey, Statistics Canada,

32 Socio-Demographic and Lifestyle Correlates of Obesity Technical Report on the Secondary Analyses Using the Canadian Community Health Survey Over one-third of non-smokers (35%) were physically inactive and reported infrequent fruit and vegetable consumption, whereas only 11% followed the healthiest lifestyle pattern (physically active with frequent fruit and vegetable consumption) (Table 2.2a). Approximately two-thirds of smokers (63%) followed less healthy lifestyle practices, as they were inactive (Table 2.2d). Just under one-fifth of daily smokers (17%) followed a healthier lifestyle pattern in that they were considered active, regardless of their nutritional habits. There was a slightly higher proportion of non-smoking men and women in the 20- to 24-year-old age group who followed the healthiest lifestyle pattern, compared to those in other age groups (Table 2.2a). However, more young (20 to 24) and older (65 and older) non-smoking women than men followed the less healthy lifestyle pattern (inactive with infrequent fruit and vegetable consumption), whereas more non-smoking men than women followed this pattern in the other two age groups (Table 2.2a). Among smokers, the percentages following the healthiest pattern (that is, being physically active) decreased across age; the percentage of men who were active was as high or higher than women in every age group (Table 2.2d). Among non-smokers, following the least healthy lifestyle pattern was more prevalent among those having lower income and education levels (Table 2.2a). A similar pattern was seen among women (Table 2.2c). Similarly, for non-smokers, following the least healthy lifestyle pattern was more prevalent among those who spoke neither English nor French and those living in ewfoundland and Labrador, ew Brunswick, Manitoba and Saskatchewan (Table 2.2a). Among daily smokers, following the least healthy lifestyle pattern was more prevalent among those in the lowest education group, residents in the Atlantic provinces and Quebec, those not working (for a reason other than retirement) and those who spoke only French were more likely to have the least healthy lifestyle pattern. Those who were older tended to follow less healthy lifestyle patterns (Table 2.2d). A similar pattern was seen among men and women, where those who spoke only French tended to have the least healthy lifestyle patterns (Tables 2.2e and 2.2f). Also among women, those in the lowest education levels tended to follow less healthy lifestyle patterns (Table 2.2f). The relationship between physical activity, nutrition and body mass index is shown in further detail in Table 2.2g. Overall, among non-smokers and smokers combined, close to half of both women and men (46%) who were considered obese (BMI of 30 or more) followed the least healthy combination of physical activity and nutrition practices, and this was a significantly higher proportion than among adults with a healthy weight (BMI 18.5 to 24.9) (Table 2.2g). Very few obese women and men were active with high fruit and vegetable intake, compared to those in the optimal BMI range. The prevalence of unhealthy lifestyle characteristics (both inactive and consuming less than five servings of fruits and vegetables) was higher among daily smokers (over half of them) compared to non-smokers; this difference was present for both men and women (Table 2.2g). 20

33 Results Section 3: Lifestyle and Socio-Demographic Correlates of Obesity This section describes the correlates of overweight and obesity separately for smokers and non-smokers. on-smokers Table 3.1a summarizes the associations between socio-demographic factors and healthy lifestyle patterns (physical activity and nutrition) with overweight and obesity, stratified by smoking. Among non-smokers, women were 57% less likely to be overweight (or obese) compared with men, controlling for socio-demographic factors and lifestyle pattern. The odds of being overweight or obese also decreased among non-smokers as education increased and for middle- to high-income levels. Compared to their younger counterparts, the chance of being overweight or obese increased across successive age groups. For the healthy living characteristics, the healthier the lifestyle pattern, the lower the odds were of being overweight or obese. Figure 8 shows that among non-smokers, similar relationships for the various sociodemographic and lifestyle patterns were observed for obesity alone (Table 3.1b) as were observed for overweight and obesity (Table 3.1a). However, a few differences were found: the association between obesity and gender weakened and the relationship with less healthy patterns became stronger. Figure 8 Lifestyle and Socio-Demographic Correlates of Obesity, on- Smokers (Odds Ratios and 95% Confidence Limits) Odds of obesity by group Inactive, <5 fruit/veg Inactive, 5+ fruit/veg Moderately active, < 5 fruit/veg Moderately active, 5+ fruit/veg Active, <5 fruit/veg Active, 5+ fruit/veg years years years Men Women < secondary Secondary Some post-secondary Post-secondary Low income Middle/high income Source: Canadian Community Health Survey, Statistics Canada,