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Examining the associations between socioeconomic status and school-day dietary intake among Vancouver… Ahmadi, Naseam 2013

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EXAMINING THE ASSOCIATIONS BETWEEN SOCIOECONOMIC STATUS AND SCHOOL-DAY DIETARY INTAKE AMONG VANCOUVER CHILDREN AND ADOLESCENTS  by Naseam Ahmadi B.Sc., The University of British Columbia, 2010  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES (Human Nutrition)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  May 2013 © Naseam Ahmadi, 2013  Abstract Background: The majority of Canadian children and adolescents (9 to 18 years old) are not meeting Canada’s Food Guide recommendations for healthy eating. Moreover, evidence suggests that SES and dietary quality are positively associated. Yet little is known about the influence of parents, peers, and food purchasing practices on the associations between SES and dietary intake or about whether these associations are pertinent in the school context. The primary objective of this study is therefore to explore associations between SES and school-day dietary intake among Vancouver youth, before and after controlling for psychosocial factors and food purchasing practices.  Methods: In 2012, grade 5-8 students (n=950 from 26 schools) completed a school-based survey and reported school-day intake of vegetables, whole grains, low fat milk, packaged snack foods, and sugar-sweetened beverages (SSB). Multivariate logistic regression examined associations between parent education and food security status with dietary intake, before and after controlling for peer modeling and parental normative beliefs of dietary intake, and frequency of purchasing food on school days.  Results: Compared to students whose parents completed high school or less, students whose parents completed some college were significantly more likely to consume vegetables daily on school days (unadjusted OR=1.85, 95% CI=1.06, 3.22). Compared to food insecure students,  ii  food secure students were significantly less likely to consume SSB daily on school days (unadjusted OR=0.51, 95% CI=0.28, 0.93). Both vegetable and SSB intake were not significantly associated with SES measures in final adjusted models. In adjusted models, compared to students whose parents completed high school or less, students whose parents completed college or university were significantly less likely to consume packaged snacks daily on school days (adjusted OR=0.61, 95% CI=0.42, 0.90). Parent education and food security status were not significantly associated with the remaining dietary intake outcomes.  Conclusions: SES was significantly associated with three of five dietary outcomes; however, we did not find that either SES measure was consistently a significant determinant of dietary intake across foods categories. Overall, there is room for improvement in dietary intake of Vancouver children and adolescents on school days and school nutrition interventions would benefit all students.  iii  Preface This thesis is original work by the author, Naseam Ahmadi, under the supervision of Dr. Jennifer Black, and committee members Dr. Gwen Chapman and Dr. Gerry Veenstra. The thesis is part of a larger study designed by Dr. Jennifer Black and Dr. Gwen Chapman to investigate the dietary behaviours, knowledge, and attitudes of Vancouver grade 7-8 students. I collaborated with Dr. Jennifer Black, Dr. Gwen Chapman, and other graduate students to develop the survey tool, to recruit participants, and to collect data for the study and two pilot studies. Data analysis and thesis writing were independently conducted with supervision from Dr. Jennifer Black, Dr. Cayley Velazquez, and the supervisory committee. The Behavioural Research Ethics Board of the University of British Columbia approved procedures for the pilot studies and the Food Practices on School Days Study, ethics certificate number (H11-01369). The Vancouver School Board (VSB) provided permission for UBC researchers to contact VSB administrators, teachers and students to participate in this study.  iv  Table of Contents  Abstract .................................................................................................................................... ii Preface ..................................................................................................................................... iv Table of Contents .................................................................................................................... v List of Tables ........................................................................................................................ viii List of Figures ......................................................................................................................... xi List of Abbreviations ............................................................................................................ xii Acknowledgements .............................................................................................................. xiii Chapter 1: Introduction ........................................................................................................ 1 1.1  Background and study rationale................................................................................... 1  1.2  Study purpose............................................................................................................... 5  1.3  Literature review .......................................................................................................... 5  1.3.1 1.4  Dietary practices of Canadian children and adolescents....................................... 6  SES definitions and measurement ............................................................................... 7  1.4.1  SES and dietary quality......................................................................................... 9  1.4.2  Psychosocial factors and dietary quality ............................................................. 14  1.4.3  School-day food purchasing practices ................................................................ 18  1.5  Summary .................................................................................................................... 20  Chapter 2: Methods ............................................................................................................. 22 2.1  Food Practices on School Days study design ............................................................ 22  2.1.1  Questionnaire development ................................................................................ 23  2.1.2  Pilot Study A recruitment and data collection procedures.................................. 23  v  2.1.3 2.2  Food Practices on School Days Study sampling........................................................ 25  2.2.1 2.3  Pilot Study B recruitment and data collection procedures .................................. 25  Sampling strategy................................................................................................ 26  Measures .................................................................................................................... 27  2.3.1  Outcome variables .............................................................................................. 27  2.3.2  Explanatory variables.......................................................................................... 29  2.3.3  Sample characteristics ......................................................................................... 36  2.4  Data analysis .............................................................................................................. 38  2.4.1  Descriptive statistics ........................................................................................... 38  2.4.2  Logistic regression models ................................................................................. 39  2.4.3  Analytic sample .................................................................................................. 41  Chapter 3: Results................................................................................................................ 43 3.1  Sample characteristics ................................................................................................ 43  3.2  Parent education and food security status .................................................................. 44  3.3  School-day dietary intake .......................................................................................... 45  3.4  Peer modeling and parental normative beliefs about dietary intake .......................... 46  3.5  Food purchasing practices.......................................................................................... 52  3.6  Associations between dietary outcomes and SES measures, controlling for parental  normative beliefs, peer modeling, and food purchasing practices ...................................... 52 3.6.1  Daily vegetable intake......................................................................................... 53  3.6.2  Daily whole grain intake ..................................................................................... 55  3.6.3  Daily low fat milk intake .................................................................................... 56  3.6.4  Daily intake of packaged snack foods ................................................................ 56  vi  3.6.5 3.7  Daily SSB intake ................................................................................................. 57  Summary of regression models .................................................................................. 59  Chapter 4: Discussion .......................................................................................................... 67 4.1  Study strengths and limitations .................................................................................. 76  4.2  Future directions for research .................................................................................... 79  4.3  Implications for practice ............................................................................................ 80  Chapter 5: Conclusion .......................................................................................................... 84 References .............................................................................................................................. 87 Appendices ............................................................................................................................. 97 Appendix A IEAT Questionnaire ....................................................................................... 97 Appendix B Sensitivity Analyses of Different Coding Options for Key Explanatory Variables ........................................................................................................................... 136 Appendix C Examining Other Measures of SES (Mother’s and Father’s Education, and Single Parent vs. 2 or More Parent Families) ................................................................... 142 Appendix D Bivariate Analyses........................................................................................ 144 Appendix E Considering Other Explanatory Variables for Regression Model ................ 145  vii  List of Tables Table 2-1 Food consumption items grouped by food categories ............................................ 29 Table 2-2 Household food security status questions............................................................... 33 Table 2-3 Questionnaire items addressing peer modeling and parent normative beliefs. ...... 35 Table 3-1 Sample characteristics ............................................................................................ 44 Table 3-2 Parent education and household food security status ............................................. 45 Table 3-3 Sample distribution on daily intake of food categories. ......................................... 46 Table 3-4 Peer modeling items ............................................................................................... 48 Table 3-5 Parental normative beliefs items ............................................................................ 50 Table 3-6 Distribution of weekly food purchasing at food retailers on campus, off campus, or both on and off campus ........................................................................................................... 52 Table 3-7 Logistic regression analysis of daily vegetable intake by parent education, food security status, parental normative beliefs, peer modeling, and food purchasing. ................. 61 Table 3-8 Logistic regression analysis of daily whole grain intake by parent education, food security status, parental normative beliefs, peer modeling, and food purchasing. ................. 62 Table 3-9 Logistic regression analysis of daily low fat milk intake by parent education, food security status, parental normative beliefs, peer modeling, and food purchasing. ................. 63 Table 3-10 Logistic regression analysis of daily packaged snack intake by parent education, food security status, parental normative beliefs, peer modeling, and food purchasing. ......... 64 Table 3-11 Logistic regression analysis of daily SSB intake by parent education, food security status, parental normative beliefs, peer modeling, and food purchasing. ................. 65 Table 3-12 Summary for unadjusted and final adjusted associations of SES measures and all daily dietary intake outcomes. ................................................................................................ 66  viii  Table 4-1 Unadjusted logistic regression of the association between parent education (4 groups) and dietary outcomes. .............................................................................................. 136 Table 4-2 Unadjusted logistic regression of the association between parent education (3 groups) and dietary outcomes. .............................................................................................. 137 Table 4-3 Unadjusted logistic regression of the association between food security status (total score from 0-5) and dietary outcomes. ................................................................................. 138 Table 4-4 Unadjusted logistic regression of the association between food security status (dichotomous coding) and dietary outcomes. ....................................................................... 138 Table 4-5 Unadjusted logistic regression of the association between food security status (3 categories) and dietary outcomes. ......................................................................................... 138 Table 4-6 Distribution of food security status (total score from 0-5) ................................... 139 Table 4-7 Distribution of food security status (3 categories) ............................................... 139 Table 4-8 Unadjusted logistic regression of the association between peer modeling items (numeric coding 0-4) and related dietary outcomes. ............................................................ 140 Table 4-9 Unadjusted logistic regression of the association between peer modeling items (categorical coding 0/1) and related dietary outcomes. ........................................................ 140 Table 4-10 Unadjusted logistic regression of association between parental normative belief items (numeric coding 0-4) and dietary outcomes. ............................................................... 141 Table 4-11 Unadjusted logistic regression of association between parental normative belief items (categorical coding 0/1) and dietary outcomes. .......................................................... 141 Table 4-12 Bivariate associations between mother’s highest education and dietary intake . 142 Table 4-13 Bivariate associations between father’s highest education and dietary intake ... 142  ix  Table 4-14 Bivariate associations between number of parents (single vs. 2 or more) and dietary intake ......................................................................................................................... 143 Table 4-15 Bivariate associations between parent education and dietary intake .................. 144 Table 4-16 Bivariate associations between food security status and dietary intake ............. 144 Table 4-17 Bivariate associations between parent education and ‘other explanatory variables’ for the regression model........................................................................................................ 145 Table 4-18 Bivariate associations between food security status and ‘other explanatory variables’ for the regression model ....................................................................................... 145  x  List of Figures  Figure 2-1 Phases of the study and pilots in terms of study design and objective ................. 23  xi  List of Abbreviations  BC  British Columbia  CCHS  Canadian Community Health Survey  EFM  Enterprise Feedback Management Survey Tool  IEAT  Individual Eating Assessment Tool  NSLP  National School Lunch Program  PMK  The Person Most Knowledgeable  SCT  Social Cognitive Theory  SES  Socioeconomic status  SNDAIII  The Third School Nutrition Dietary Assessment Study  SSB  Sugar-sweetened beverages  TPB  Theory of Planned Behaviour  VSB  Vancouver School Board  xii  Acknowledgements This thesis would not be possible without the contributions of many people. I feel sincerely fortunate to have had Dr. Jennifer Black as my thesis supervisor and mentor; her commitment to supporting my work went above and beyond expectations. She pushed me to think critically and I was consistently encouraged by her confidence in me. The invaluable guidance from my committee members shaped my thesis and kept my work on track. I owe particular thanks to Dr. Gwen Chapman for contributing to the development of my proposal and strengthening its rationale. I am very grateful for Dr. Gerry Veenstra’s positive feedback and clear suggestions for next steps throughout this process. I am thankful for the funding support provided by Dr. Jennifer Black, Dr. Gwen Chapman, the UBC Food Nutrition and Health Vitamin Research Fund, and the Canadian Institutes of Health Research. I would also like to thank the Vancouver School Board as well as the teachers and students who participated in this study. I sincerely appreciate Dr. Jean-Michel Billette’s generous contribution of his time to provide thorough answers to my statistical questions. A special thank you goes to Dr. Cayley Velazquez for constantly sharing her expertise and moral support. I would like to thank my incredible lab-mate Teya Stephens, who was a dependable partner in conducting this study. I send gratitude to Joshua Edward, Stephanie Shulhan, and Sarah Carten for their contributions to this study. Dr. Alejandro Rojas and the entire team of Think & Eat Green @ School are also thanked for their contributions and for the opportunity to be a part of this study. Lastly, I must thank Mom and Dad for their unwavering support of my many and varied educational pursuits.  xiii  Chapter 1: Introduction 1.1  Background and study rationale In 2004, the Canadian Community and Health Survey (CCHS) revealed that 29% of  12 to 17 year-old Canadians were classified as overweight or obese (1), double the prevalence of 14% observed in 1978/1979 (1). The upward trend in the Canadian adolescent obesity rate raises concerns about the dietary practices of the population. For instance, a risk factor for overweight or obesity is consuming less than the recommended intake of fruits and vegetables (1). The increasing rate of overweight and obesity in children and adolescents elicits a need to examine the dietary health of the population. Data from the 2004 CCHS also show that diets of children and adolescents deviate from recommendations for fruits, vegetables, milk, grains, snacks, and sugar-sweetened beverages. The majority of Canadians 9 to 13 years and 14 to 18 years do not meet Health Canada’s recommendations for fruit and vegetable intake (2). Fruit and vegetable intake has been documented to have protective effects against chronic illnesses such as cardiovascular disease and some cancers (3,4). In addition, Canadians aged 10 to 16 consumed milk products below recommended levels and over a quarter of females both 9 to 13 years and 14 to 18 years did not meet grain requirements (2). Whole grain intake recommendations are supported by evidence of positive associations with decreased chronic disease risk factors, such as type II diabetes and cardiovascular disease (5), and milk consumption reduces the risk of osteoporosis (6). Packaged snacks and sugar-sweetened beverages are also cause for concern in this population. Snack foods predominantly fall into the formerly referred to “other foods” category in Canada’s Food Guide, defined as foods not in the other food groups (6). In 14 to  1  18 year olds, “other foods” accounted for 25% of energy intake (2). Although “other foods” include a variety of items, two-thirds of the calories from this category comprised of only ten food items including high sugar, high fat, and high salt foods such as potato and corn chips (2). The most predominantly consumed “other foods” items were sugar-sweetened beverages (SSB) (2). Consumption of SSB has been found to displace consumption of nutrient-rich beverages such as milk and contribute to an increased risk of obesity (7). As a result of the incongruence between early adolescent dietary intake and public health nutrition recommendations, there is interest in studying this population. Adolescents are an ideal population for health behaviour interventions as they are developing their values and beliefs during this developmental period (8) and evidence demonstrates that adolescent dietary behaviours persist into adulthood (9). For example, reports of high fruit and vegetable intake during childhood has been shown to predict fruit and vegetable intake in adulthood (10). This age group is at a pivotal mental, physical, and social growth phase, with long-term physiological health impacts, particularly in the development of dietary behaviours. Nationally representative data of US children and adolescents indicate that this population consumes 35% of daily energy at school, reflecting a meaningful contribution to overall dietary intake during this time-period (11). Therefore, schools can be a valuable setting for dietary interventions aimed at moving child and adolescent dietary intake towards recommendations. Currently limited research exists pertaining to school-day dietary intake among Canadian children and adolescents. In addition to below recommended dietary intake among the majority of Canadian children and adolescents, a previously documented barrier to dietary health is low socioeconomic status (SES). Previous research consistently indicates healthier food  2  consumption patterns among high SES individuals; however, previous research has predominantly focused on adults (12,13). Low socioeconomic status among children and adolescents is of particular concern in British Columbia (BC). In 2009, BC had the highest child poverty rate in Canada, rising to 16.4% from the 2008 BC child poverty rate of 14.5%. Child poverty refers to family income below the low-income after tax cut off and is the most commonly used definition of poverty in Canada (14–16). BC surpassed the national child poverty rate in 2009 of 9.5% (15). Currently, the BC Provincial Government does not have a poverty reduction strategy, the deficit of which has been criticized as a factor influencing the persistent child poverty observed in BC (17). The impact of regional child and adolescent poverty on dietary intake is indicated by data showing that almost one-third of BC Food Bank users in 2011 were children and youth (18). In the same year, Dietitians of Canada calculated that a family of 4 on income assistance in BC would require over 100% of their income for shelter and food (17). Socioeconomic inequity is certainly an important factor to consider in evaluating barriers to nutritional health among children and adolescents in BC. Socioeconomic differences in health outcomes have previously been explained by a differential distribution of factors that influence health outcomes, including psychosocial factors (19,20), which are social and psychological factors that influence an individual’s behaviour (21). Evidence suggests that income-related food insufficiency may be associated with low social support (22). Youth are particularly influenced by psychosocial factors during this period of life with, family, friends, and school as the main realms of socialization  3  for early adolescents (20). Few studies have investigated the role of psychosocial factors in possible explanatory pathways of socioeconomic differences in health outcomes (20). Evaluating the psychosocial factors that influence health behaviours can inform public health strategies or nutrition interventions with the goal to encourage healthier choices and ultimately improve population health status. Social Cognitive Theory (SCT) and Theory of Planned Behaviour (TPB) provide a theoretical framework for conceptualizing the personal and situational factors that influence human behaviour and are established theories in health research (23,24). SCT suggests that other behaviours may vary with the target behaviour of interest, such as food consumption. For example, a behaviour that may vary with dietary intake is purchasing food from limited food service retailers, which previous research suggests is significantly more common among low SES groups (25). Research shows that lower dietary quality is associated with consuming foods purchased from limited service retailers (26,27). Food purchasing practices may be another key factor shaping the associations between socioeconomic status and school-day dietary intake among children and adolescents. Previous research analyzing variation in dietary intake explained by socioeconomic status among children and adolescents has mainly examined dietary intake of fruits and vegetables as indicators of nutritional health. This indicates a need to investigate dietary intake of other foods recommended for public health, such as increasing consumption of whole grains and low fat dairy, as well as decreasing consumption of SSB and energy-dense, low nutrient snack foods (2,28). Also, few studies have investigated the influence of psychosocial factors and food purchasing practices on the associations between measures of SES and dietary intake and the relevance of these associations in the context of Vancouver  4  school days. Understanding the factors underlying food consumption in terms of student SES can inform nutrition interventions customized for a population particularly vulnerable to low quality dietary intake.  1.2  Study purpose For this study a quantitative cross-sectional survey was conducted to describe school-  day dietary intake of a sample of grade 5-8 students attending Vancouver public schools. The primary objective of this study was to explore the associations between SES and school-day dietary intake among Vancouver children and adolescents before and after controlling for psychosocial factors and food purchasing practices.  1.3  Literature review The purpose of this literature review is to summarize existing research that examines  the relationship between SES and dietary intake of children and adolescents in urban settings within developed countries, namely, but not limited to, the US and Canada. The literature review will begin by discussing dietary intake of Canadian children and adolescents. SES measurement methods with children and adolescents are then considered and research examining the associations between SES and dietary outcomes is summarized. Health behaviour theories are discussed to frame the role of parents, peers, and food purchasing practices in potentially explaining the associations between socioeconomic status and dietary outcomes.  5  1.3.1  Dietary practices of Canadian children and adolescents As previously described, nationally representative data on Canadian dietary intake  suggests that children and adolescents are not meeting Canada’s Food Guide recommendations for consumption of fruits, vegetables, whole grains, dairy, and are consuming items from the “other foods” categories above recommendations (2). The following studies completed after the CCHS cycle in 2004 corroborate national findings on child and adolescent food consumption. Hanning et al (29) implemented a cross-sectional survey of the dietary intakes of grade 6 through 8 students in the Peel district of Waterloo, Ontario (n=662). Median daily intakes of males and females were as follows: 4.6 and 3.8 grain servings, 3.8 and 4.1 fruit and vegetable servings, 2.0 and 1.8 milk products servings, and 3.0 and 2.6 “other foods” servings (29). These findings show that the daily consumption of grains, fruits and vegetables, and milk and alternative food groups in the Hanning et al (29) study fell below Canada’s Food Guide recommendations, as Canada’s Food Guide recommendation for grade 6-8 students are 6 daily servings of grain products, 6-7 servings of fruits and vegetables, and 3-4 of milk and alternatives (30). Also, the study reports consumption of foods from the “other foods” category above Canada’s Food Guide recommendations, resembling levels reported in nationally representative data of Canada (1,29). This research implies that youth from Waterloo, Ontario, much like Canadian youth overall, are not meeting Canada’s Food Guide recommendations for food groups. Limited data exist on the dietary intake of children and adolescents in BC; however, the following two studies provide some insight into the topic. A survey was conducted with Grade 4 and 5 students in Victoria, BC (n=444) to examine fruit and vegetable intake at baseline of an intervention study (31). Fruit and vegetable consumption was measured by a  6  validated 24-hour recall. Baseline fruit and vegetable intake was 4.24 servings in the treatment group and 5.44 in the control group (31). Consistent with the previous study, the baseline assessment of fruit and vegetable intake in Victoria grade 4 and 5 students was below Canada Food Guide recommendations. The 5-Today study also conducted a nutrition assessment of grade 5 and 6 students in Vancouver, BC (n=133) (32). Researchers similarly used a 24-hour recall to measure fruit and vegetable consumption (32). Mean 24-hour recall fruit and vegetable intake among males and females was 3.25 servings and 3.66 servings, respectively (32). Studies of children and youth in Canada repeatedly demonstrate inadequate intake of fruits and vegetables and can serve as interesting comparisons to results from the study of Vancouver grade 5-8 student dietary intakes.  1.4  SES definitions and measurement By 2009, BC had maintained the highest child poverty rates in the country for 8  consecutive years, indicated by family income below the low-income after tax cut off (14). Possible socioeconomic inequity in dietary quality among BC children and adolescents is an important issue to examine. However, valid individual-level measures of SES among children and adolescents can be difficult to attain in applied research for a number of reasons. Children and adolescent populations are limited in their ability to accurately report incomerelated SES because these variables may be unknown to children and adolescents or difficult to describe (33). Therefore, missing data on SES measures commonly exist in this field of research as children and early adolescents have difficulty reporting parent occupation, education, income (20,33). 7  Previous research on socioeconomic determinants of healthy eating among children and adolescents support the use of parent education as the primary indicator of SES with the population. Parent education was most frequently included as a proxy indicator of SES among the studies in a 2007 review of adolescent SES and dietary health outcomes (13). A number of studies not included in the Hanson and Chen (13) review also included parent education as the measure of SES in the examination of child and adolescent food behaviour in North America (34–38). US studies frequently use eligibility for free or reduced-cost National School Lunch Programs (NSLP) as a measure of low income, as eligibility for these programs is determined by family income. Free NSLP meals are provided for parent-reported incomes below 130% of the poverty line and reduced-price NSLP for incomes 131 - 185% of the poverty line (42). Although a useful measure, school lunch and breakfast program participation in Canada is neither specified by distinct family income levels nor nationally regulated. A measure of food sufficiency strongly tied to income is household food security status, which is commonly used by Canadian researchers and in national censes, such as the US Census Bureau and Statistics Canada (30,39,40). Household food security status is characterized by factors such as skipping meals, reducing the size of meals, or running out of food by the end of the week due to exhausted finances (40). Compared to parent education, household food security status can be considered a more extreme measure of low socioeconomic status, given the items that comprise the measure, which will be discussed in more detail in Chapter 2: Methods. Characterizing low SES among children is also difficult because household income is not constant (14). The following factors predict persistent childhood low-income: main  8  income earner does not have higher than a high-school education, is not in the labour force, or is under 30 years old (14). Given limitations of SES measurements with Vancouver children and adolescents, parent education appears to be an appropriate choice of primary SES indicator in the population.  1.4.1  SES and dietary quality Socioeconomic inequity in health outcomes has been observed among adult  populations but relatively less research of children and adolescents has been conducted (33,41–43). A 2007 systematic review of SES and dietary health in adolescents found that despite a considerable degree of heterogeneity between studies in measurement methods of explanatory and outcome variables, 25 of 31 studies found a positive relationship between the SES and nutritional health of adolescents (13). Fruit and vegetable intake was significantly lower among low SES adolescents (13). High fat and refined sugar intakes, which are nutrients of concern in packaged snack foods, were also more common among the low SES groups (13). The findings of this review indicate that similar to observations of adults, poor quality dietary intake persists among low SES adolescents. Notwithstanding the consistency of these findings, a number of studies not included in the Hanson and Chen (13) review indicate that the relationship between SES and nutritional quality is unclear among children and adolescents. For example, a study of US low-income students in the Third School Nutrition Dietary Assessment Study (SNDAIII) found a negative association between SES and nutritional quality (44). It is important to note that the negative association between SES and dietary intake in the SNDAIII may be attributed to low-income student participation in free or reduced price meals offered in the  9  US NSLP (45), the equivalent of which does not exist in Canada on a federally regulated level. The SNDAIII included a nationally representative sample of US public schools participating in the NSLP and the students in grades 1 through 12 that attend these schools (45). Receipt of free or reduced cost school lunch program meals indicated low SES (45). In addition to nutrient-specific intake, when dietary outcomes were measured as discrete food items, NSLP participation increased odds of healthy food consumption. NSLP participants were significantly more likely to consume milk, fruit, and vegetables than non participants (45). NSLP students were less likely to drink a sugar sweetened beverage, eat dessert, chips and other snack foods (45). Overall, participation in the NSLP increased the likelihood of healthy eating, considering many food items; however, there were mixed findings within this study, given that NSLP students had significantly higher sodium and saturated fat intakes (45,46). This study indicates that low SES, among those participating in NSLP, may not increase the risk of poor dietary intake; however, the provision of school lunches may be a mediating factor. In contrast to the mixed findings reported by SNDAIII, the following studies report significant positive associations between SES and dietary quality. Richter et al (20) conducted a cross-sectional survey of SES and multiple health outcomes among grade 5, 7, and 9 students (n=6997) in Germany. The dietary measures included daily or less than daily consumption of fruits, vegetables, sugary food items, and soft drinks (20). Fruit and vegetable consumption significantly increased with SES among girls and SSB intake significantly decreased with SES among boys (20). These findings support the hypothesis that dietary quality is positively associated with SES  10  Xie et al (47) used a validated FFQ to evaluate sociodemographic predictors of dietary intake among children and adolescents aged 11-20 years old in Southern California (n=3201). Average daily intake of all food groups fell below recommendations from the Food Guide Pyramid, the US Food Guide at the study time (47). Parent education was included among the sociodemographic characteristics evaluated, and mean daily intake of fruits, vegetables, and dairy significantly increased with parent education level (47). Fahlman et al (48) conducted a cross-sectional survey to measure dietary intake of middle school students in Detroit, Michigan (n=2186). The low SES students compared to the high SES students had a significantly lower mean intakes of recommended food groups: grains (3.0 compared to 3.8 servings), vegetables (1.0 compared to 2.2 servings), fruit (2.4 compared to 3.5 servings) and dairy (2.6 compared to 4.1 servings) (p<0.001 for all comparisons) (48). Also, the low SES group had a higher mean intake of non-nutritious foods: packaged snack foods, such as potato chips, cookies, and donuts, (5.6 compared to 3.4 servings) and fried foods (2.6 compared to 1.2 servings) (p<0.001 for all comparisons) (48). For various healthy and unhealthy food items, SES consistently held a positive association with dietary quality. In the Canadian context, a cross-sectional study assessed the influence of socioeconomic status on the diets of grade 9 and 10 students from Ontario and Alberta (n=2615) (49). Two measures indicating socioeconomic status were separately analyzed for their associations with diet quality: median family income of the school neighbourhood (as reported by Statistics Canada in 2001) and the distinction between private and public schools (49). Mean fruit and vegetable intake had a significantly positive association with school neighbourhood SES (p<0.001), with a 0.33 serving increase for every $10,000 increase in the  11  SES of the school region (49). High calorie beverages were consumed significantly more often in public compared to private schools (1.0 vs. 0.7 servings, p=0.007) (49). These findings suggest that some healthy dietary practices are positively associated with neighbourhood SES among Canadian early adolescents. Johnson-Down et al (35) conducted a cross-sectional survey of 9-12 year olds in a low-income Montreal neighbourhood (n=498). Researchers administered a single 24-hour recall to estimate daily dietary intake and defined dietary quality as percentage of fat consumed and micronutrient profile (35). SES was measured by parent reported education, single-parent families, and income sufficiency (35). Income sufficiency was measured on a 3-point scale with cut points above $40,000 per year for a family of 4, between the poverty line to $40,000, and below the poverty line (35). There was no significant difference in energy intake by income sufficiency (35). Intake of vitamin A, vitamin C, iron and folate significantly decreased with income level, but the estimated intake did not fall below the Dietary Reference Intakes (DRI) (35,50–52). Low income was significantly associated with low dietary quality, in terms of some micronutrients; however the intake of these nutrients was within the DRIs (35,53) implying the nutritional adequacy of child dietary intake, irrespective of significant socioeconomic differences. The influence of household food security status on dietary quality has also been evaluated. A cross-sectional study in Toronto, Ontario aimed to evaluate food purchasing among food insecure families (54). A significantly greater proportion of food insecure families, compared to food secure, reported that they were unable to purchase sufficient amounts of the following recommended food items: fruit, vegetables, and milk for the family  12  (54). Food insecurity may increase the risk of low dietary quality through limited food purchasing power by the household shopper. Kirkpatrick and Tarasuk (39) investigated the nutritional implications of household food security status using CCHS cycle 2.2 data. Nutritional quality was significantly compromised among food insecure adults; however, fewer differences in nutritional intake were observed between food secure and food insecure children and adolescents (39). However, this study did find significant differences in dietary intake among food insecure children and adolescents of some age/sex groups (39). Energy intake was significantly higher among food insecure children in the 9-18 age group (39). Food insecure males aged 14-18 and children aged 1-3 consumed fewer servings of fruits and vegetables (39). Significantly fewer servings of milk were reported by food insecure children aged 1-8 (39). Nutritional inadequacy was significantly higher among food insecure children aged 9-18 (39). This study indicated that compared to adults, differences in nutritional quality by food security status was less consistent among children and adolescents; however the findings qualified food security status as a risk factor for suboptimal nutritional quality among Canadians. Although many studies suggest SES-linked dietary health inequalities among children and adolescents, some recent research presents conflicting findings between food items or in terms of nutritional adequacy. Also, the pertinence SES as a determining factor for healthy eating in the context of school days among Vancouver children and adolescents remains unclear. A number of factors have been considered in the explanation for socioeconomic variation in dietary intake. Low education has been associated with low income and household food insecurity (39,54,55). Low income restricts purchasing power, with price  13  being a factor of greater influence on food purchasing decisions, over quality and health considerations (54). A common concern cited from interviews with a convenience sample of low-income Vancouver families was dependence on low-priced foods for feeding children (56). Limited food budgets decrease household availability of fresh produce and increase the use of filling foods such as starches, and the purchase of canned or convenience foods (54,57), which are typically low nutrient, energy-dense foods (2). With limited income, financial priorities have been previously reported as primarily rent, with food costs considered a more flexible expenditure (54). Psychosocial factors can also vary by education level, influencing differences in dietary intake (19). Education and income level may influence social networks, with the norms and modeling of parents or peers possibly varying by educational and income-related strata, resulting in divergence in quality of dietary intake. Increased education level may also lead to healthier eating through increased nutritional knowledge (58). High parent education has been associated with awareness of feeding children according to dietary recommendations (59). Considering the influence of psychosocial factors on the associations between SES and dietary intake may reveal an effective avenue for nutrition interventions. This line of inquiry can address whether interventions aimed at psychosocial interventions have the potential to overcome socioeconomic barriers to healthy eating among children and adolescents.  1.4.2  Psychosocial factors and dietary quality Health behaviour theories identify determinants of health or factors that facilitate  effective health interventions (60,61). As socioeconomic status is a difficult factor to change  14  through health interventions, modifiable factors identified to be positively associated with dietary quality nutrition interventions may have the potential to overcome socioeconomic barriers to nutritional health. Nutrition interventions are more likely to succeed when designed to target influential factors ascertained through baseline assessments framed by health behaviour theories (60,61). TPB and SCT are health behaviour theories used to identify potential determining factors of nutrition behaviour. Constructs from both theories will be examined in this study. TPB identifies ‘attitudes’, ‘subjective norms’ and ‘perceived behavioural ability’ as influential actors on behaviour (24). An indirect measurement of subjective norms includes ‘normative beliefs’. Normative beliefs assess the individual’s perception of the degree to which referents (people important to the subject) think the individual should perform the behaviour (24). SCT explains that the behaviour, situation and person domains are reciprocally influential. The social situation includes the modeling construct, which is operationalized as the degree to which the individual observes referents performing the behaviour (62). Similar to the approach by Birnbaum et al (63), TPB will be used in this thesis to supplement and operationalize constructs of SCT. The psychosocial constructs considered in this study are normative beliefs and modeling. The following studies demonstrate current knowledge on the associations between these psychosocial constructs and dietary intake among in children and youth. A 2009 systematic review explored the body of literature examining psychosocial determinants of healthy eating in children and adolescents (64). The objective of the review was to investigate the psychosocial variables most consistently associated with eating  15  behaviours in children and adolescents. Among the 77 studies included in the review, the most frequent predictors of dietary measurements were psychosocial variables related to fruit and vegetable intake (64). Other measurements included psychosocial determinants of fat, energy, sugary snack, milk, fast food and SSB consumption (64). Among the psychosocial factors observed by previous studies, modeling was most frequently reported to have significant positive associations with eating behaviour (64). For example, a study of Flemish children and adolescents found that peer modeling, the extent to which participants perceived their peers to eat fruit daily, was significantly and positively associated with dietary intake of fruits (p<0.01) (64,65). The norms construct demonstrated moderate consistency across studies in reporting positive correlations with food consumption outcomes (64). Yet these findings are limited by variability between studies in the food outcomes measured and in parallel, the items that compose the psychosocial scales (64). Although many other psychosocial factors have been considered in the previous literature, to narrow the scope of the psychosocial dimension of the thesis, modeling and norms were selected as key psychosocial factors due to the consistent findings of significant positive associations by the McClain et al (64) systematic review of the associations of psychosocial factors with eating behaviour among children and adolescents. Research shows that parents may have the strongest influence on child health behaviours (66). Feunekes et al (67) examined the influence of social networks on dietary intake of 15 year olds. Dietary intake was measured of participants (n=347), their mothers (n=296), fathers (n=257) and the ‘best friend’ identified by the participant by FFQ (n=240) (67). Correlations were calculated between intake of the participants, parents, and peers (67). Most dietary items consumed by participants were significantly associated with intake of  16  mothers (87% of food items) and with intake of fathers (76% of food items) (67). This contrasts with a significant association between participant and peers on intake of only 19% of dietary items (67). In terms of parental normative beliefs, Granner and Evans (68) reported significant, yet weak associations with child dietary intake. The authors evaluated the influences of family normative belief on dietary intake among 11-15 year olds in Minnesota (n=674) (68). An FFQ was used to estimate mean daily servings of fruits and vegetables consumed. Family normative beliefs was measured as a numeric variable and was significantly positively associated with fruit intake (r=0.19), vegetable intake (r=0.19) (68). Research with families demonstrates their significant associations with the dietary intake of children and adolescents. Peers are another key social influence of child and adolescent dietary intake. Childhood and adolescence are life stages significantly spent in the company of peers and individual behaviour is assumed to be strongly influenced by peer acceptance (69). A systematic review of studies investigating associations between adolescent social networks and dietary behaviours found that there is consistent evidence of similarities in eating behaviours between school friends, such as consumption of fast food (70). Feunekes et al (67) demonstrated that foods consumed by participants and friends were significantly associated (r=0.19), although weaker than the associations between dietary intake of participants and parents (67). In the Granner and Evans (68) study, peer modeling had significant positive correlations with fruit intake (r=0.14), vegetable intake (r=0.16), and combined fruit and vegetable intake (r=0.18), respectively, similar to the correlations observed between family normative beliefs and participant dietary intake. These observations  17  of peer dietary intake suggest a significant yet weak association with individual dietary intake. Nutrition interventions have the capacity to address psychosocial factors that are discerned to influence dietary behaviour. This thesis aims to examine the associations between SES and dietary intake before and after controlling for psychosocial factors, to consider whether the influence of parents and peers may mitigate socioeconomic health disparities in student dietary behaviour.  1.4.3  School-day food purchasing practices Another factor potentially influencing the associations between SES and dietary  intake is the frequency of food purchase from limited service retailers. Evidence suggests that low SES individuals are more likely to purchase foods at limited service food retailers due to relatively low costs (25) and that consumption of food outside the home is associated with consumption of foods recommended to be limited in intake, such as fast food and SSB (69,71). Several studies support the hypothesis that food purchases outside the home are more frequent among low SES groups. Thornton et al (25) studied fast food purchasing among adults from Melbourne, Australia (n=2564). Fast food purchases were significantly higher among low SES groups, characterized by low education (p<0.0001) and low household income (p<0.0001) (25). In another study, take-out food was more frequently purchased by participants with high school education, compared to a university degree (p=0.017) (72). Current knowledge of the socioeconomic differences in food purchasing practices of Canadian children and adolescents is limited. A study of grade 7 and 8 children from  18  London, Ontario found that father’s education was not a significant individual-level predictor of weekly purchases at fast food or convenience stores in statistical models examining associations between the neighbourhood-level food environment and food purchasing practices (73). Research suggests that low SES groups are more likely to purchase fast food compared to high SES groups, yet food purchasing practices among Canadian children and adolescents are not well understood. A review of literature on determinants of adolescent dietary intake found that poor dietary quality was correlated with eating food outside the home (69). Surkan et al (74) conducted a cross-sectional survey of 10 to 14 year old African American children in lowincome Baltimore neighbourhoods (n=206) to evaluate the association between food purchasing and SES. SES indicators included a material style of life scale and parent education, which was measured by number of years in formal education (74). To measure foods purchased for personal consumption, a healthy food purchasing scale was constructed from 27 food items, with healthy food defined as food items that provide <10% daily fat value or <10g sugar/per serving (74). Stratified by gender, girls only had significantly higher odds of weekly healthy food purchases with a high material style of life (OR=1.2) (74). This study suggests that purchase of healthy foods may be more likely among high SES girls. Research has also indicated that school vending machine purchases may be significantly associated with intake of foods recommended to be limited in intake (26,27). A nationally representative sample of 9-18 year olds reported intake frequency of a number of discrete food items consumed the previous day (26). Compared to students that purchase from vending machines less than weekly, students that purchased from vending machines weekly were significantly more likely to report daily intake of regular soda, chocolate candy,  19  and pizza or fried food (26). A study of grade 6 and 7 students from Massachusetts similarly found that mean SSB servings consumed per day significantly increased with greater than 1 purchase per week from vending machine or fast food restaurant (27). Vending machine purchases may be a correlate of consuming food recommended to be limited in intake. Research indicates that low SES populations may be more likely to purchase food from limited service retailers—a food purchasing practice documented to have significant negative associations with dietary quality. Therefore, food purchasing practices are another factor potentially explaining socioeconomic differences in dietary intake. Current food purchase literature is limited to specific types of food vending, such as vending machine and fast food restaurant purchases, and few have considered the combined influence of purchasing from any on or off campus food retailer. Further, more research is needed regarding the food purchasing practices of Canadian children and adolescents.  1.5  Summary Evidence suggests a positive association between socioeconomic status and  nutritional quality of dietary intake among children and adolescents. The further influence of psychosocial constructs and food purchasing practices on the associations between socioeconomic status and dietary intake has been minimally explored. Also, little is known about the relationship between SES, psychosocial constructs, and food purchasing with dietary intake within the context of school days in Vancouver. Identifying factors that alternate the association between SES and dietary intake can inform nutrition interventions targeted to improve factors with the potential overcome socioeconomic barriers to healthy  20  eating. This study aims to address these gaps in the literature on Canadian child and adolescent dietary intake.  21  Chapter 2: Methods 2.1  Food Practices on School Days study design Data for this thesis are from the Food Practices on School Days Study, a cross-  sectional survey study that was conducted between March and June 2012, which sampled students attending elementary and secondary schools within the Vancouver School Board. Surveys are commonly used to evaluate the personal, situational, and behavioural domains of nutritional health in a population to evaluate behaviours, such as dietary intake (75), and key characteristics of populations to inform and justify nutrition interventions or policy changes (24,62). A web-based self-report questionnaire, entitled the Individual Eating Assessment Tool (IEAT), was developed to assess usual frequency of dietary intake, demographic characteristics, psychosocial factors related to dietary intake, and other food practices of youth. The final questionnaire consisted of 123 questions and drew upon the theoretical frameworks of SCT and TPB. Questionnaire development was characterized by three phases: questionnaire drafting, Pilot Study A and Pilot Study B. The final IEAT questionnaire can be found in Appendix A. Figure 2-1 summarizes the objectives and chronology of the pilot studies and Food Practices on School Days Study. The objectives of the pilot studies were to guide questionnaire development and data collection procedures by 1) evaluating content validity of the survey tool with nutrition and food studies faculty members and graduate students, 2) gathering feedback from participants regarding readability and relevance of items in the survey tool, and 3) testing protocol for data collection procedures with children and adolescents and in the school classroom setting.  22  Pilot A Fall 2011  ->  Final Sample: Grade 7-12 students (n=30); nutrition and food studies faculty and graduate students (n=10)  Pilot B February 2012 Final Sample: Grade 7 students (n=25) Objectives: - Readability and relevance of revised questionnaire items - Pilot data collection protocol in a VSB classroom  ->  Food Practices on School Days Study Spring 2012 Final Sample: Grade 5-8 students (n=950) Objectives: - See Study Purpose  Objectives: - To establish readability and relevance of questionnaire items - Content validity - Pilot data collection protocol with children and adolescents Figure 2-1 Phases of the study and pilots in terms of study design and objective  2.1.1  Questionnaire development A literature review was conducted to identify previous survey tools that assessed  dietary intake, socioeconomic status, and psychosocial constructs related to nutritional behaviour among children and adolescents. Wherever possible, questionnaire items were selected from tools previously validated with children and adolescents (63,76–82). When no previous tool or items were available or applicable, the research team devised new questions to address the constructs missing from the existing literature.  2.1.2  Pilot Study A recruitment and data collection procedures In order to evaluate content validity of the survey items, the first draft of the IEAT  questionnaire was circulated among graduate students and faculty members in the Faculty of Land and Food Systems at the University of British Columbia (n=10). Content validity evaluation examined whether the questionnaire captured the universe of items pertaining to the concepts measured on the questionnaire (83). After revisions, Pilot Study A was 23  conducted to gain feedback and perspective from individuals in the target population. A convenience sample of grade 7 through 12 students (n=30) was recruited in Metro Vancouver to complete Pilot Study A. Participants were recruited through poster advertisements and invitations sent to community centres, youth workers, and personal contacts. Prospective participants contacted the researchers via email and were sent active parental consent forms, which were required to be signed and brought to the survey sessions in order for individuals to participate. Research assistants met participants at public libraries or UBC computer facilities. The Pilot Study A questionnaire was accessed on computers from a website hosted on an internet server based in the University of Waterloo, adapted from a survey tool developed by Hanning et al (84). Following completion of the questionnaire, small-group discussions were conducted with participants to identify any issues related to the clarity of survey items. Additionally, participants were asked to provide feedback about content relevant to student food behaviours and identify any topics that may have been missing from the questionnaire. Participants in Pilot Study A received remuneration of a $10 gift card to a movie theatre, music store, or other retailer. The small group discussions resulted in several changes suggested by participants. Most notably, participants suggested making changes to the wording of questions in order to meet the reading abilities of the sample. As such, revisions to the language of the questionnaire were made. To reduce costs associated with the University of Waterloo survey tool and to provide more flexibility in editing the web-based survey tool, the IEAT tool was  24  transferred to Enterprise Feedback Management Survey Tool (EFM)—a questionnaire development website hosted in Canada, subscribed to by UBC.  2.1.3  Pilot Study B recruitment and data collection procedures The aims of Pilot Study B were to 1) pilot test classroom data collection protocol and  2) conduct a final assessment of readability and relevance of the revised questionnaire. Pilot Study B recruited one grade 7 class from an elementary school in the VSB to complete the revised questionnaire. The protocol was similar to Pilot Study A, with the exception that the active parental consent was changed to obtaining passive parental consent and the web-based questionnaire was hosted by EFM. We implemented the questionnaire during a class period in a computer lab at the participating school. As incentive, the class instructor received a $20 gift card to a retailer of classroom teaching resources.  2.2  Food Practices on School Days Study sampling A sample of grade 5-8 students (n=1182) was recruited from 26 schools in the VSB  for the Food Practices on School Days Study. Study researchers were granted permission from the VSB Research Committee to contact school administrators and teachers to invite their classes to participate in the study. Participants were recruited through invitations sent directly to VSB teachers, and teachers provided permission for researchers to visit their classes for the survey sessions. Parents provided passive consent; parents who did not want their children to participate signed and returned dissent forms that were distributed to students prior to data collection. Participants provided assent before beginning the questionnaire by selecting “YES” to participate, the first item on the IEAT questionnaire  25  before participants proceeded to answer the subsequent questionnaire items. If participants selected “NO” to the first questionnaire item, the questionnaire would end and the only variable recorded for the participant was the consent variable = No. Participants completed the IEAT questionnaire during class time in their school classrooms, computer labs, or libraries. The questionnaire was accessed on computers from a website hosted on EFM. Research assistants conformed to a standardized protocol for data collection. At the outset of questionnaire sessions, researchers stated 1) the purposes of the study, 2) that participant responses are confidential, 3) that participants are free to decide whether or not to participate, 4) and that they can stop the questionnaire at any time. Researchers collected any signed forms that indicated parental dissent and provided these students with alternate web-based activities with permission from the teacher. In some cases, the teacher instructed non-participating students to do school work. Researchers made note of students who decided to stop the questionnaire due to difficulties with English or accessibility issues. As incentive for participating, each teacher received a $20 gift card to a retailer of classroom teaching resources and reduced price admission for a teacher professional development session associated with this study.  2.2.1  Sampling strategy Grade 5 through 8 students in the Vancouver School Board (n=950) participated in  the study, from 20 elementary schools (of 75) and 6 secondary schools (of 18), with grade 8 being the lowest grade in secondary schools in the City of Vancouver. Power calculations for sample size were not feasible given the exploratory nature of this research. The participating VSB schools were selected from Vancouver neighbourhoods that  26  varied in terms of neighbourhood-level SES, food environment, and commercial density to recruit a sample of participants reflective of the demographic and food retail variability between Vancouver neighbourhoods. The VSB has defined 6 sectors, and at least 1 school from every VSB sector participated (85).  2.3 2.3.1  Measures Outcome variables Dietary intake Dietary intake was measured using an FFQ that consisted of 64 items. An FFQ was  selected as the method for measuring dietary intake because they are frequently used in nutritional epidemiology to estimate usual intake of food categories over a period of time and impose relatively less burden on the participant (compared to dietary records) (86). The FFQ items were adapted from a dietary survey tool developed by the Propel Centre for Population Health Impact because the survey tool was piloted for use with Canadian grade 5 through 12 students (87). The Food Practices on School Days Study researchers further supplemented the FFQ with items recommended by Canada’s Food Guide, such as distinguishing whole milk from 2%, 1%, or skim milk (30). For this study, serving sizes were not included in the FFQ measures for a number of reasons, most of which relate to reducing participant fatigue. Previous research indicates that reliable and accurate estimates of previous dietary intake are challenging for children to provide (88). Both respondent memory lapses and inattention among this population contribute to the difficulties with dietary measures, especially in respect to estimating serving sizes (88). The IEAT questionnaire was also quite extensive, requiring over 60 minutes to complete. The dietary outcomes were intended to measure  27  relative intake frequency of broad food categories, not to estimate usual intake of specific nutrients. Therefore, the researchers simplified the FFQ by excluding the detail of estimating portion sizes to reduce respondent burden and potential fatigue. The FFQ measured frequency of consumption over the past 30 days, on schools days. The term “on school days” was defined as either during school hours or on the way to and/or from school. The questions asked students to report how often, on average, over the past 30 days, they consumed certain items. The FFQ items were measured on an ordinal scale, with response options of: Never, 1 time per month, 2-3 times per month, 1 time per week, 2-4 times per week, 1 time per day, and equal to or greater than 2 times per day. For this study, items were grouped into the following categories: fruits, vegetables, whole grains, low fat milk and milk alternatives, energy-dense processed foods, packaged snack foods, and sugarsweetened beverages. Table 2-1 outlines the items comprising the dietary outcomes. These groupings were based on recommendations from 3 Registered Dietitians and similarities to Canada’s Food Guide, where possible, to characterize consumption of foods recommended to increase or decrease. For each grouping, dietary intake was coded as a dichotomous measure composed of all possible combinations of the items within a food category that equalled at least once per school day (e.g., 2-4 times/week fresh fruit, 2-4 times/week frozen, and 1 time/week canned fruit would be considered daily consumption of fruit). Thus, consumption of each category was coded as 1 to indicate daily consumption (i.e. intake of foods in the category 5 times per week or more) and 0 (i.e., intake of the food category less than 5 times per week). Measures of daily dietary intake are commonly coded as either numeric variables, such as reporting mean servings per day (29,35,63,89), or dichotomous measures comparing high to low  28  consumption frequency or meeting versus not meeting recommended daily intake of food groups (37,90,91). As the IEAT FFQ was measured on an ordinal scale and did not include serving sizes, dietary intake was coded as a dichotomous variable, following the example of previous studies that used similar measures.  Table 2-1 Food consumption items grouped by food categories Food category Food items within each category Fruits - Fresh fruit, not including juice - Dried fruit - Fruit (frozen or canned) Vegetables - Fresh vegetables (raw or cooked, not including French fries) - Vegetables (frozen or canned) Whole grains - Whole grains (e.g. whole grain bread, whole grain bagel, pita or tortilla, cup brown rice or whole grain pasta, oatmeal or shredded wheat) Low fat fluid milk and alternatives - 2% milk - 1% or skim milk - Soy milk (plain) Energy-dense processed foods - Pizza - Hot dog - Hamburger/ cheeseburger - Breaded/ fried chicken or fish - French fries or other fried potatoes - Taco or nachos - Frozen packaged dinner Packaged snack foods - Salty packaged snacks - Candy or chocolate bars - Baked sweets - Frozen desserts Sugar sweetened beverages - Fruit-flavoured drinks - Regular (non-diet) pop or soft drinks - Iced tea (sugar sweetened) - Sports drinks - Energy drinks - Slurpees®, slushies, or snow cones  2.3.2  Explanatory variables Socioeconomic status Socioeconomic status was indicated by two self-reported measures, parent education  level and household food security status. Parent education is often used as an indicator of  29  SES and is the most frequently used measure in previous nutrition research evaluating child and adolescent SES (13,35–38,118). Participants could report the highest education level completed of up to four parents and/or guardians. The question asked, “What is the highest level of education completed by this parent or primary caregiver? ” with response options of: “did not finish high school”, “finished high school”, “did some college/university training after high school”, and “ finished a college or university degree or higher”. From this series of questions a final “Parent education” variable was created to identify the highest education level completed by any of the parents reported by each participant coded as “Less than high school” = 0, “High school” = 1, “Some college” = 2 and “Finished a university or college degree” = 3. A number of steps were taken to derive the final “Parent education” variable from the original series of questions pertaining to parent and/or guardian education levels. 1. Step 1. Separate variables were created for each education level: College = 1 if the education level of any of the parents equalled “finished a college or university degree”. Some college = 1 if the education level of any of the parents equalled “did some college/university training after high school”. High school = 1 if the education level of any of the parents equalled “finished high school”. Less than high school = 1 if the education level of any of the parents equalled “did not finish high school”. 2. Step 2. From the variables generated in Step 1, a series of variables were generated to identify the highest education level among the parents reported by each student. Highest college = 1 if College = 1.  30  Highest some college = 1 if Some college =1 and College did not =1. Highest high school = 1 if High school = 1 and College did not = 1 and Some college did not = 1. Highest less than high school = 1 if Less than high school = 1 and College did not = 1 and Some college did not = 1 and High school did not = 1. 3. Step 3 A single variable was generated from the variables created in Step 2 for the highest education among the parents reported by each participant. Parent education = 3 if Highest college = 1. Parent education = 2 if Highest some college = 1. Parent education = 1 if Highest high school = 1. Parent education = 0 if Highest less than high school = 1. All remaining observations were coded Parent education = missing.  However, there were very few responses in the Less than high school category (Chapter 3: Results, Table 3-2). Thus, for regression analyses, the Parent education = 0 and Parent education = 1 groups were combined to recode the Parent education variable as: “High school or less” = 0, “Some college” = 1, and “Finished a university or college degree” = 2. Sensitivity analyses confirmed that the associations between parent education and key outcomes were similar between the original and recoded parent education variables (Appendix B, Tables 4-1 and 4-2). These tables in Appendix B display the unadjusted associations between parent education and the dietary outcomes, comparing the original and recoded parent education variables. The significance and direction of associations were similar between the original and recoded parent education variables.  31  The following alternate SES measures were also considered: mother’s highest education level, father’s highest education level, and single parent vs. 2 or more parents, as previous literature has suggested that these measures may be indicators of child or adolescent SES (14,15). Appendix C summarizes bivariate analyses of the associations between dietary outcomes and the alternate SES measures and also displays theχ2 statistics calculated. The analyses conducted informed the decision to drop these measures of SES from further analysis because they were not significantly associated with a consistent set of dietary outcomes. Household food security status is a measure of food insufficiency related to annual income (92), and may represent a more extreme case of low SES compared to parent education level. Household food security status was measured by 5 questions (Table 2-2) that were modified from a household food security module used in the Canadian Community Health Survey and originally developed by the United States Department of Agriculture (USDA) (40,93). Response options for each of these questions followed the adapted example of CCHS items to be: “A lot”, “Sometimes”, “Never”. To follow the coding guide suggested by the USDA, responses were coded as “Never” = 0, whereas the “Sometimes” and “A lot” categories were collapsed to equal 1. The USDA Guide to Measuring Household Food Security recommends summing the number of items responded to affirmatively to determine food security status (40). To compare food secure to food insecure populations, a participant whose total score summed to either 0 or 1 was considered “food secure”, whereas a total score of 2, 3, 4, or 5 was considered “food insecure with or without hunger”. The dichotomous coding of food security status was selected based on the example of coding used in previous literature that also examines food security status among Canadians  32  (39,54,94), sensitivity analyses, and small sample sizes in categories of contending coding options (Appendix B, Tables 4-3 to 4-7). Sensitivity analyses confirmed that the direction and significance of associations between food security status and dietary outcomes were similar between the dichotomous and a 0-5 scale coding of food security status variables (Appendix B, Tables 4-3 and 4-4). These tables in Appendix B display the unadjusted associations between food security status and the dietary outcomes, comparing the dichotomous and 0-5 scale coding of food security status variables. A 3-category coding for food security status was considered using cut-offs defined by the USDA (40); the total score summed to either 0 or 1 was considered “food secure”, a total score of 2, 3, of 4 was considered “food insecure without hunger and a total score of 5 was considered “food insecure with hunger”. The unadjusted associations between this coding option and dietary outcomes revealed non-significant associations (Appendix B Table 4-5). However, the dichotomous coding of food security status was chosen due to small sample sizes in both the 0-5 scale and 3 category coding structures. Appendix B Table 4-6 and 4-7 display the low proportion of the sample with a cumulative food insecurity scores from 2 to 6, and in the food secure without or with hunger groups, respectively.  Table 2-2 Household food security status questions “In the past 12 months…”1: - Did the food that your family bought run out, and you didn't have money to get more? - Were you not able to eat a balanced meal because your family didn't have enough money? - Have you skipped a meal or has the size of your meals been cut because your family didn't have enough money for food? - Did you have to eat less because your family didn't have enough money to buy food? - Were you hungry but didn't eat because your family didn't have enough food? 1. Response options: “A lot”, “Sometimes”, “Never”  33  Psychosocial constructs The psychosocial constructs used in this study were parental normative beliefs and peer modeling related to dietary intake. The focus on the psychosocial constructs of peer modeling and parental normative beliefs stemmed from a review by McClain et al (64) of studies with children and adolescents that examined the psychosocial correlates of nutrition behaviour. McClain et al (64) reported consistency in associations between modeling and dietary health and the construct of norms was found to have moderate consistency in associations with dietary health. Consistency was defined as over 60% agreement in the associations between the psychosocial factor and dietary intake reported by at least two studies (64). Table 2-3 lists the questionnaire items addressing peer modeling and parental normative beliefs. An example item was “How much do you agree with the following statements? My parent(s) or primary caregiver(s) think I should… Eat vegetables at least once a day”. The response options for each of the psychosocial items were on a 5-point Likert-type scale that included: “Disagree a lot” = 0, “Disagree a little” = 1, “Neither agree nor disagree” = 2, “Agree a little” = 3, and “Agree a lot” = 4. In addition, each question included an “I’m not sure” option – an uncommon response option in previous research on psychosocial constructs of dietary intake, but requested by participants in the pilot studies. One study that included a similar measure to the “I’m not sure” option coded the constructs as categorical variables, collapsing the disagree, neutral, and undecided option into one category (32). Therefore, the responses were further collapsed into categories of 0 equaling “Disagree a lot”, “Disagree a little”, “Neither agree nor disagree”, or “I’m not sure” and 1 equaling “Agree a little” or “Agree a lot”. Sensitivity analyses confirmed that the  34  associations between psychosocial items and related dietary outcomes were similar between both numeric (0-4) and categorical coding of psychosocial variables (Appendix B, Tables 4-8 to 4-11). Tables 4-8 to 4-11 in Appendix B compare the unadjusted associations between psychosocial variables coded as numeric variables and related dietary outcomes to unadjusted associations between psychosocial variables coded as categorical variables and related dietary outcomes.  Table 2-3 Questionnaire items addressing peer modeling and parent normative beliefs. Psychosocial construct Peer modeling  Questionnaire items Most of my close friends...1 - Eat vegetables at least once a day - Eat whole grains at least once a day - Drink low-fat milk (e.g. 1 cup or small carton of 2%, 1% or skim milk) - Avoid soft drinks and other sugar-sweetened beverages - Eat packaged snack foods Parental normative beliefs My parent(s) or primary caregiver(s) think I should... 1 - Eat vegetables at least once a day - Eat whole grains at least once a day - Drink low-fat milk (e.g. 1 cup or small carton of 2%, 1% or skim milk) - Avoid soft drinks and other sugar-sweetened beverages - Eat packaged snack foods 1. Five-point Likert-type scale from “Agree a lot” to “Disagree a lot”, with an additional option: “I’m not sure”  Food purchasing practices Food purchasing practices were assessed with one question that asked students, “In a typical month, how often do you drink or eat food that you purchased at the following places on school days (either during school hours or on your way to or from school)?”. Students reported the frequency of food purchases from any of the following limited service food retail locations: school cafeteria, school store, school vending machine, fast food restaurant, coffee shop, and convenience store. Food retailer types were similar to categories used in  35  previous research (73,78,95,96). Response options were: Never, 1 time per month, 2-3 times per month, 1 time per week, 2-4 times per week, 1 time per day, and equal to or greater than 2 times per day. Any possible combination of weekly food purchasing was coded as a categorical variable, to identify students who purchased food less than weekly, only on school campus weekly, only off school campus weekly, or both off and on campus weekly. Weekly was considered to represent a habitual food practice and was similar to coding of food purchasing practices used in previous research (25,73). Off campus food retailer options were fast food restaurant, coffee shop, and convenience store, and on campus food retailer options were school cafeteria, school store, and school vending machine.  2.3.3  Sample characteristics Gender Gender was self-reported from a question asking participants “How would you  describe your gender?” with response options of “Male” or “Female”. Spending money Participants reported spending money, (in dollars) to the following question: “On average, how many dollars do you have at your disposal to spend as you wish (eg. on food, entertainment, etc.)? Please enter numbers only”. Participants wrote the dollars per week and the IEAT questionnaire was set to accept only numeric values for this item. Spending money was coded as “$0” = 0, “$>0 -10” = 1, “$>10 - 20” = 2, and “$>20” = 3. Acculturation A crude measure of acculturation was composed of three questions: “In which country were you born?”, “Were your parent(s) or primary caregiver(s) born in Canada?”,  36  and “What language(s) do you usually speak at home? Choose all that apply”. Participants were assigned a 0 (least acculturated) if the participant and parents were not born in Canada, and if English was not selected. Participants were assigned a 1 if the participant or parents were born in Canada, or if English was selected as being spoken at home (but not both). Participants were assigned a 2 (most acculturated) if both the participant and parents were born in Canada and if English was selected as being spoken at home. Physical activity Students reported physical activity in 3 questions asking about the amount of time spent on strenuous, moderate, or mild exercise from a previous youth health behaviour survey (76,97,98). The strenuous exercise question asked “In a usual week, how many hours do you spend doing the following activities: Strenuous exercise (heart beats rapidly) Examples: biking fast, aerobic dancing, running, jogging, swimming laps, rollerblading, skating, lacrosse, tennis, cross-country skiing, soccer, basketball, football” (76,97,98). The moderate exercise option was “Moderate exercise (not exhausting) Examples: walking quickly, baseball, gymnastics, easy bicycling, volleyball, skiing, dancing, skateboarding, snowboarding” (76,97,98). The mild exercise options as “Mild exercise (little effort) Examples: walking slowly (to school, to a friend’s house, etc.), bowling, golf, fishing, snowmobiling, yoga” (76,97,98). The response options were None, Less than ½ hour per week, ½ - 2 hours per week, 2 ½ - 4 hours per week, 4 ½ - 6 hours per week, More than 6 hours per week. The physical activity variable was coded as “> 60 minutes of moderate or vigorous physical activity” = 1, and “< 60 minutes of moderate or vigorous physical activity” = 0. Dichotomizing the physical activity was selected based on physical activity guidelines for children and adolescents aged 5-17 years (99), based on the examples of previous  37  literature that compares students that meet to those who do not meet the physical activity recommendations (20,100). BMI Students self-reported height and weight from the following questions, "What is your height?” and “What is your weight?”. Students selected from drop-down menus that provided imperial and metric units that ranged from “3”0” or 91 cm or less” to “6’8” or 203 cm or more” and “68 lbs or 31 kgs or less” to “280 lbs or 127 kgs or more”. The height and weight questions both included the option “I don’t know”. BMI was coded based on International Obesity Task Force guidelines for BMI cut-offs for specific age and gender groups (101). BMI was coded as “Underweight” = 0, “Normal” = 1, “Overweight” = 1, and “Obese” = 2.  2.4 2.4.1  Data analysis Descriptive statistics All data were managed in and analyzed using STATA 12 (102). Descriptive statistics  explored the distribution of key variables in the sample, such as daily dietary intake of food categories, parent education, food insecurity status, other demographic characteristics, peer modeling, parental normative beliefs, and food purchasing practices. For example, the proportion of students in each category of the parent education variable was examined. The distribution of variables was visually examined with histograms for numeric variables and bar charts for categorical variables.  38  2.4.2  Logistic regression models The main objective of this thesis was to evaluate the variation in dietary intake  explained by SES, before and after controlling for peer modeling, parental normative beliefs, and food purchasing. Therefore, associations between measures of SES (parent education and food security status) were each evaluated with the dietary outcomes for which corresponding psychosocial construct items were available (i.e., daily intake of vegetables, whole grains, low fat milk, packaged snack foods, and SSB). Bivariate associations were analyzed using χ2 tests, to examine associations between dietary outcomes and SES measures (Appendix D). Appendix D summarizes and presents the χ2 statistics of bivariate associations between dietary outcomes and each of parent education and food security status. The following factors were considered as variables to potentially further control for in regression analyses: spending money, acculturation, physical activity, and BMI. To decide whether to adjust for these variables in the regression models, we tested whether they were significantly associated with the key explanatory variables – measures of SES. Spending money, acculturation, and physical activity were not controlled for in regression analysis because they were significantly associated with neither parent education nor food security status (Appendix E). BMI was significantly associated with food security status, but not parent education, the primary explanatory variable of interest. Therefore, BMI was also not included in the final regression models. Appendix E presents χ2 statistics of associations between each of the SES variables (parent education and food security status) with spending money, acculturation, physical activity, and BMI. The outcome, daily dietary intake, was coded as a binary outcome; therefore, logistic regression was used to evaluate the variation in the binary outcome, before and after  39  controlling for multiple potentially explanatory variables. As the recruiting procedures involved a non-probability sample of students within classrooms at schools, the nesting of individuals within schools in the IEAT sample does not meet the assumption of regression that the outcome is independent between individuals in a sample (103), often resulting in an underestimated standard error and p-value (103), which increases the likelihood of a type I error. Calculating robust standard errors was an acceptable approach given the scope of this thesis (104). The following seven logistic regression models were fit to evaluate the variation in each of the five dietary outcomes explained by parent education, food security status, parental normative beliefs, peer modeling, and food purchasing. Model 1 examines the unadjusted associations between parent education and the dietary outcome. Model 2 examines the unadjusted associations between food security status and the dietary outcome. Models 3 through 7 adjust for parent education and food security status. Model 4 adjusts for parent education, food security status, and parental normative beliefs of the related dietary outcome (for example, adjusting for parental normative beliefs of vegetable intake when examining the outcome of daily vegetable intake). Model 5 adjusts for parent education, food security status, and the peer modeling of the related dietary outcome (for example, adjusting for peer modeling of vegetable intake when examining the outcome of daily vegetable intake). Model 6 adjusts for parent education, food security status, parental normative beliefs, and peer modeling.  40  Model 7 adjusts for parent education, food security status, parental normative beliefs, peer modeling, and food purchasing practices.  2.4.3  Analytic sample Of the 80 classes that were invited to participate in the Food Practices on School  Days Study, 48 classes (from a total of 26 schools) agreed to participate. Among the nonparticipating classes, 8 teachers expressed that they were not interested in participating, 12 did not respond to the invitation or to book the data collection appointment, and 12 were unable to participate due to scheduling problems or because school computers were not available. A total of 1182 grade 5-12 students were recorded to be present at data collection visits. Parents did not provide informed passive consent for 143 students; these students were excluded from participation. At the outset of the questionnaire, 18 students did not provide assent and 3 declined to participate after beginning the questionnaire. As identified by teachers, 8 students did not assent due to language difficulties and 3 did not assent due to learning disabilities. As a result of a lack of working computers, 43 students were unable to participate and 3 did not participate for other reasons (e.g., students closed the questionnaire without informing research assistants). Researchers reviewed the dataset and noted that 11 participants wrote inappropriate responses in the open-ended questions. These 11 individuals were excluded from the dataset by virtue of the possibility that the inappropriate responses indicated that the participants were not giving due diligence to the questionnaire. The final sample size was 950.  41  Logistic regression models used listwise deletion to exclude observations with any missing values for the variables included in the models. Therefore, the unadjusted and adjusted models, of each dietary outcome, were fitted on the same analytic sample. The resulting sample sizes were 588 for vegetable intake, 585 for whole grain intake, 561 for low fat milk intake, 574 for packaged snack food intake, and 585 for SSB intake.  42  Chapter 3: Results 3.1  Sample characteristics Table 3-1 presents sample characteristics. Gender was approximately evenly  distributed, with 48.6% female. Most of the sample was in elementary school (74.7%). Compared to the ‘least acculturated’ group (11.3%), there were slightly more students in the ‘most acculturated’ group (18.1%). Normal and underweight BMI were reported by 69.4% and 14.6% of the sample, respectively and the majority of the sample (68.6%) reported less than 60 minutes of moderate or vigorous physical activity per day.  43  Table 3-1 Sample characteristics Sample characteristic n (%) Gender (n=948) Female 461 (48.6) Male 487 (51.4) Grade (n=936) Grade 5 13 (1.4) Grade 6 139 (14.9) Grade 7 546 (58.3) Grade 8 238 (25.4) School type (n=950) Secondary school 240 (25.3) Elementary school 719 (74.7) Spending money1 (n=630) $0 89 (14.1) $ > 0 - 10 234 (37.1) $ > 10 - 20 146 (23.2) $ > 20 161 (25.6) Acculturation2 (n=877) 0 (Least acculturated) 99 (11.3) 1 619 (70.6) 2 (Most acculturated) 159 (18.1) Physical activity3 (n=863) < 60 minutes of moderate or vigorous physical activity 592 (68.6) > 60 minutes of moderate or vigorous physical activity 271 (31.4) BMI (n=601) Underweight 88 (14.6) Normal 417 (69.4) Overweight 73 (12.2) Obese 23 (3.8) Note. Total n=950. Sample size varies between variables due to missing values. 1. Weekly availability of money students reported having at their disposal to spend as they wish (e.g. on food, entertainment, etc.) 2. 0 (Least acculturated) = participant and parents were not born in Canada and English was not spoken at home 1 = participant or parents were born in Canada or English was selected as being spoken at home (but not both) 2 (Most acculturated) = participant and parents were born in Canada and English was spoken at home 3. Daily physical activity  3.2  Parent education and food security status Table 3-2 shows the distribution of parent education and food security status  variables. Most students reported that their parents had “Finished a university or college degree” (63.7%), whereas 15.7% reported “Some college”, 15.9% reported “High school”, and 4.7% reported “Less than high school”. A high proportion of the sample was missing on  44  the parent education variable (28.32%). Food insecurity (with or without hunger) was reported by 15.8% of the sample.  Table 3-2 Parent education and household food security status Sample characteristic n (%) Parent education1 (n=681) Less than high school 32 (4.7) High school 108 (15.9) Some college 107 (15.7) Finished a university or college degree 434 (63.7) Household food security status (n=831) Food secure 700 (84.2) Food insecure with or without hunger 131 (15.8) Note. Total n=950. Sample size varies between variables due to missing values. 1. Highest education level of among parent(s) reported by each participant  3.3  School-day dietary intake The descriptive statistics for dietary intake can be seen in Table 3-3. Findings from  this study indicate that less than half of participants reported daily school-day consumption of fruits (49.6%), vegetables (42.3%), whole grains (34.7%), and low fat fluid milk (46.3%). Additionally, energy-dense processed foods, packaged snack foods, and SSBs were consumed on a daily basis by 15.4%, 20.1, and 30.0% of the sample, respectively. Given that the dietary intake questions asked students to report on their school-day intake (i.e., either during school hours or on the way to and/or from school), it is thought that participant responses represent approximately 6 hours per day, which reflects a meaningful proportion of participants’ daily intake of these food and beverage items.  45  Table 3-3 Sample distribution on daily intake of food categories. Food category n (%) Fruits (n=942) < 1 time per day 475 (50.4) > 1 time per day 467 (49.6) Vegetables (n=930) < 1 time per day 537 (57.7) > 1 time per day 393 (42.3) Whole grains (n=938) < 1 time per day 613 (65.3) > 1 time per day 325 (34.7) Low fat fluid milk and alternatives (n=922) < 1 time per day 495 (53.7) > 1 time per day 427 (46.3) Energy-dense processed foods (n=942) < 1 time per day 797 (84.6) > 1 time per day 145 (15.4) Packaged snack foods (n=948) < 1 time per day 757 (79.9) > 1 time per day 191 (20.1) Sugar sweetened beverages (n=936) < 1 time per day 655 (69.9) > 1 time per day 281 (30.0) Note. Total n=950. Sample size varies between variables due to missing values.  3.4  Peer modeling and parental normative beliefs about dietary intake Tables 3-4 and 3-5 show that most peer modeling and parental normative beliefs  items were skewed left. This was indicated by medians greater than means of most items and the skewed distribution presented by the histograms. However, the distribution of peer modeling regarding avoiding SSB was different than the distributions of peer modeling of vegetable, whole grain, low fat milk, and packaged snack food intake. The mean peer modeling of avoiding SSB was 2.09 (sd=1.22), which was lower than the mean peer modeling of vegetable, whole grain, low fat milk, and packaged snack food intake. The distribution of parental normative beliefs of packaged snack food intake was also different than the distributions of parental normative beliefs of vegetable, whole grain, and low fat milk intake, as well as SSB avoidance. The mean parental normative beliefs of packaged snack food intake appeared was 2.42 (sd=1.56), which was lower than the mean parental 46  normative beliefs of vegetable, whole grain, and low fat milk intake, and SSB avoidance. The histogram presents the distribution of parental normative beliefs of packaged snack food intake, which appeared more normally distributed than the other parental normative beliefs items. The mean agreement with most parental normative beliefs items was higher than mean agreement with peer modeling items. For example, the mean agreement regarding peer modeling of eating vegetables at least once a day was 2.82 (median = 3 “Agree a little”), with a standard deviation of 1.07. The mean agreement regarding parental normative beliefs of eating vegetables at least once a day was 3.70 (median = 4 “Agree a lot”) with a standard deviation of 0.92. Overall, among the psychosocial construct items, students most frequently agreed with the item regarding daily vegetable intake. Students most frequently agreed that their peers ate vegetables daily (58.2%) and that their parents think they should eat vegetables daily (83.3%).  47  Table 3-4 Peer modeling items Item Mean1 (SD) 2.82 (1.07) Eat vegetables at least once median=3 a day (n=849)  Histogram1 Disagree or Neutral Agree  n (%) 355 (41.8) 494 (58.2)  Eat whole grains at least once a day (n=842)  2.64 (1.05) median=3  Disagree or Neutral Agree  417 (49.5) 425 (50.5)  Drink low-fat milk (e.g. 1 cup or small carton of 2%, 1% or skim milk) (n=831)  2.31 (1.06) median=2  Disagree or Neutral Agree  542 (65.2) 289 (34.8)  48  Item  Mean (SD)1  Histogram1  Eat packaged snack foods (n=831)  2.50 (1.07) median=2  Disagree or Neutral Agree  460 (55.4) 371 (44.7)  Avoid soft drinks and other sugar-sweetened beverages (n=841)  2.09 (1.22) median=2  Disagree or Neutral Agree  568 (67.5) 273 (32.5)  n (%)  Note. The peer modeling questions asked, “How much do you agree with the following statements? Most of my close friends…”. This statement was followed by the items listed above. 1. 0= “Disagree a lot” 1= “Disagree a little” 2= “Neither agree nor disagree” or “I’m not sure” 3= “Agree a little” 4= “Agree a lot”  49  Table 3-5 Parental normative beliefs items Item Mean (SD)1 3.70 (0.92) Eat vegetables at least once median=4 a day (n=888)  Histogram1 Disagree or Neutral Agree  n (%) 148 (16.7) 740 (83.3)  Eat whole grains at least once a day (n=882)  3.51 (1.05) median=4  Disagree or Neutral Agree  229 (26.0) 653 (74.0)  Drink low-fat milk (e.g. 1 cup or small carton of 2%, 1% or skim milk) (n=865)  3.10 (1.40) median=3  Disagree or Neutral Agree  413 (47.8) 452 (52.3)  50  Item  Mean (SD)1  Histogram1  Eat packaged snack foods (n=862)  2.42 (1.56) median=2  Disagree or Neutral Agree  613 (71.1) 249 (28.9)  Avoid soft drinks and other sugar-sweetened beverages (n=875)  3.03 (1.34) median=3  Disagree or Neutral Agree  289 (33.0) 586 (67.0)  n (%)  Note. The parental normative beliefs questions asked, “How much do you agree with the following statements? My parent(s) or primary caregiver(s) think I should…”. This statement was followed by the items listed above. 1. 0= “Disagree a lot” 1= “Disagree a little” 2= “Neither agree nor disagree” or “I’m not sure” 3= “Agree a little” 4= “Agree a lot”  51  3.5  Food purchasing practices Table 3-6 shows that nearly one-fifth of participants (18.7%) reported purchasing  food on campus (from the school cafeteria, school store, and/or vending machines) once per week or more, whereas 13.3% of participants reported purchasing food off campus (from any fast food restaurant, coffee shop, and/or convenience store) once per week or more. Moreover, 22.0% of participants reported purchasing food from both an on-campus and an off-campus location at least once per week.  Table 3-6 Distribution of weekly food purchasing at food retailers on campus, off campus, or both on and off campus Food purchase (n=939) n (%) Purchase food < 1 time per week 431 (45.9) Purchase food only on campus > 1 time per week 176 (18.7) Purchase food only off campus > 1 time per week 125 (13.3) Purchase food both on and off campus > 1 time per week 207 (22.0)  3.6  Associations between dietary outcomes and SES measures, controlling for  parental normative beliefs, peer modeling, and food purchasing practices I will present the findings for each dietary outcome in Tables 3-7 to 3-11. For each dietary outcome, I will first present unadjusted associations between parent education and the dietary outcome (model 1), then unadjusted associations between food security status and the dietary outcome (model 2). Next, I will discuss models that adjust for parent education and food security status (models 3-7), parental normative beliefs of food items related to each dietary outcome (for example, adjusting for parental normative beliefs of vegetable intake when examining the outcome of daily vegetable intake) (models 4, 6, and 7), peer modeling of food items related to each dietary outcome (for  52  example, adjusting for peer modeling of vegetable intake when examining the outcome of daily vegetable intake) (models 5, 6, and 7), and food purchasing practices (model 7).  3.6.1  Daily vegetable intake Model 1 Findings for the outcome of daily vegetable intake are presented in Table 3-7. The  unadjusted logistic regression analyses suggest that parent education was significantly associated with daily vegetable intake. Specifically, students with parents who completed some college were significantly more likely than those with parents who completed high school or less to report daily vegetable consumption (OR=1.85, 95% CI=1.06, 3.22). However, students who reported that their parents completed university or college were not significantly more likely than those with parents who completed high school or less to report daily vegetable intake (OR=1.30, 95% CI=0.80, 2.12). Model 2 The unadjusted logistic regression analyses suggest that food security status was not significantly associated with daily vegetable intake (OR=1.40, 95% CI=0.89, 2.21). Model 3 After controlling for food security status, the parent education some college group and daily vegetable intake remained significantly associated, which is consistent with the unadjusted findings (model 1). Model 4 After controlling for food security status and parental normative beliefs, the parent education some college group was no longer significantly more likely to report  53  daily vegetable intake and the magnitude of the association decreased, compared to models 1 and 2 (OR=1.54, 95% CI=0.85, 2.80). Students in agreement with parental normative beliefs about vegetable consumption were significantly more likely to report daily vegetable consumption compared to students responding neutral or disagree (OR=3.38, 95% CI=1.61, 7.09). Model 5 After controlling for food security status and peer modeling, the association between the parent education some college group and vegetable intake remained significant (OR=1.78, 95% CI=1.01, 3.16), consistent with models 1 and 3. Students reporting agreement with peer modeling about vegetable intake were significantly more likely to report daily vegetable intake compared to students responding neutral or disagree (OR=1.71, 95% CI=1.25, 2.32). Model 6 After controlling for food security status, parental normative beliefs, and peer modeling, the parent education some college group was no longer significantly associated with vegetable intake (OR=1.57, 95% CI=0.86, 2.87), similar to the model controlling for parental normative beliefs but not peer modeling (model 4). Parental normative beliefs (OR=2.91, 95% CI=1.38, 6.15) and peer modeling (OR=1.42, 95% CI=1.04, 1.94) both remained positively significantly associated with daily vegetable intake. Model 7 After controlling for food security status, parental normative beliefs, peer modeling, and food purchasing, the parent education some college group was not significantly associated with daily vegetable intake (OR=1.57, 95% CI=0.86, 2.86),  54  similar to models 4 and 6, which also controlled for parental normative beliefs. Parental normative beliefs (OR=3.05, 95% CI=1.42, 6.54) and peer modeling (OR=1.42, 95% CI=1.05, 1.92) both remained positively significantly associated with daily vegetable intake. Food purchasing was not significantly associated with daily vegetable intake.  3.6.2  Daily whole grain intake The dietary outcome of daily whole grain intake is described by Table 3-8. Daily  whole grain intake did not significantly vary by parent education or food security status in unadjusted (models 1 and 2, respectively) or adjusted models (models 3 through 7). Parental normative beliefs of whole grain intake was positively associated with daily whole grain intake in all adjusted models (models 4, 6, and 7). Peer modeling was significantly positively associated with daily whole grain intake when controlling for parent education and food security status (model 5); however, the significance of this association was lost when controlling for parental normative beliefs (models 6 and 7) and food purchasing (model 7). In model 7, when controlling for parent education, food security status, parental normative beliefs, and peer modeling, students who purchase food both on and off campus weekly were significantly more likely than students that purchase food less than weekly (reference group) to report daily whole grain intake (OR=1.71, 95% CI=1.06, 2.77).  55  3.6.3  Daily low fat milk intake The dietary outcome of daily low fat milk intake is described by Table 3-9. Daily  low fat milk intake did not significantly vary by parent education or food security status in unadjusted (models 1 and 2, respectively) or adjusted models (models 3 through 7). Parental normative beliefs (models 4, 6 and 7) and peer modeling were also not significantly associated with daily low fat milk intake (models 5 through 7). In model 7, after accounting for parent education, food security status, parental normative beliefs, and peer modeling, students purchasing food weekly both on and off campus were significantly more likely to report daily low fat milk consumption, compared to students purchasing food less than weekly (reference group) (OR=1.66, 95% CI=1.01, 2.74); however, the confidence interval was close to non-significance.  3.6.4  Daily intake of packaged snack foods The dietary outcome of daily packaged snack food intake is described by Table 3-  10. In the unadjusted model 1, parent education was not significantly associated with daily packaged snack food intake. Controlling for food security status in model 3, parent education was not significantly associated with the outcome; however, it is interesting to note that the upper value for the confidence interval of the college or university group, compared to high school or less (reference group) was 1.00 (OR=0.66, 95% CI=0.44, 1.00). In models 4 through 7, parent education was significantly negatively associated with daily packaged snack food intake and the magnitude of the association was similar across models. The upper level of the confidence intervals for the college or university  56  group in adjusted models 4 through 6 were close to 1.00, indicating that the OR estimated for the college or university group was close to non-significance. However, in the final adjusted model 7, the upper level of the confidence interval for the college or university group shifts to 0.90, confirming that the college or university group was significantly less likely to report daily packaged snack food intake (OR=0.61, 95% CI=0.42, 0.90), almost half as likely compared to the high school or less group. Daily packaged snack intake did not significantly vary by food security status in unadjusted (models 1 and 2, respectively) and adjusted models (models 3 through 7). Parental normative beliefs (models 4, 6, and 7) and peer modeling (models 5 through 7) of packaged snack food consumption were not significantly associated with packaged snack intake. In model 7, food purchasing was significantly associated with daily packaged snack food intake. Students reporting weekly off campus food purchases (OR=2.25, 95% CI=1.13, 4.51) and students reporting weekly food purchases both on and off campus (OR=7.14, 95% CI=4.47, 11.39) were significantly 7.14 times more likely to report daily packaged snack food intake, compared to students reporting less than weekly food purchase (reference group).  3.6.5  Daily SSB intake Model 1 The dietary outcome of daily SSB intake is described by Table 3-11. Parent  education was not significantly associated with daily SSB intake (unadjusted).  57  Model 2 There was a significant unadjusted association between food security status and daily SSB intake. Food secure students were significantly less likely than food insecure students to report daily SSB consumption (OR=0.51, 95% CI= 0.28, 0.93), which is almost half as likely as the food insecure students. Model 3 Controlling for parent education, the magnitude and significance of association between food security status and daily SSB intake remained consistent with the unadjusted association (model 2); however, the confidence interval was close to 1.00 (OR=0.52, 95% CI=0.28, 0.99), indicating that the association was close to nonsignificance. Model 4 Controlling for parent education and parental normative beliefs, the magnitude of association between food security status and daily SSB intake was consistent with previous models, but was no longer significant, with the upper level of the confidence interval at 1.00 (OR=0.52, 95% CI=0.28, 1.00). Parental normative beliefs were not significantly associated with SSB intake, but the direction of association was as expected, with students in agreement with parental normative beliefs regarding SSB avoidance less likely to report daily SSB intake (OR=0.71, 95% CI=0.50, 1.01). Model 5 After controlling for parent education and peer modeling, the magnitude and significance of the association between food security status and SSB intake was consistent with the unadjusted association (model 2). Yet again, the upper limit of the  58  confidence interval was at 1.00, indicating that the association was close to nonsignificance (OR=0.53, 95% CI=0.28, 1.00). Peer modeling was not significantly associated with daily SSB intake (OR=1.17, 95%, CI=0.77, 1.77). Model 6 After controlling for parent education, parental normative beliefs, and peer modeling, food security status was no longer significantly associated with SSB intake (OR=0.54, 95% CI=0.29, 1.01), similar to model 4, which also included parental normative beliefs. Parental normative beliefs changed to significantly associated with daily SSB intake (OR=0.68, 95% CI=0.48, 0.98). Peer modeling remained nonsignificantly associated with daily SSB intake (OR=1.17, 95% CI=0.77, 1.77). Model 7 After controlling for parent education, parental normative beliefs, peer modeling, and food purchasing, food security status remained non-significantly associated with daily SSB intake (OR=0.59, 95% CI=0.31, 1.12), similar to models 4 and 6, which also included parental normative beliefs. Parental normative beliefs (OR=0.75, 95% CI=0.53, 1.06) and peer modeling (OR=1.19, 95% CI=0.78, 1.81) were both not significantly associated with daily SSB intake. Students that reported purchasing foods both on and off campus weekly were significantly 4 times more likely to report daily SSB intake (OR=4.00, 95% CI=2.80, 5.71) compared to students reporting less than weekly food purchase (reference group).  3.7  Summary of regression models  In summary (Table 3-12), the unadjusted logistic regression analyses found that daily vegetable intake was significantly associated with parent education. Specifically, 59  students who reported that their parents completed some college were significantly more likely to report daily school-day vegetable consumption compared to students who reported that their parents completed high school or less (OR=1.85, 95% CI=1.06, 3.22). After controlling for food security status, parental normative beliefs, peer modeling, and food purchasing, the association between parent education and daily vegetable intake decreased in magnitude and was no longer significant. The final adjusted logistic regression model found that daily packaged snack food intake was significantly associated with parent education. Students who reported that their parents completed a college or university degree were significantly less likely to report daily packaged snack food intake compared to students who reported that their parents completed high school or less (OR = 0.61, 95% CI = 0.42, 0.90), after controlling for food security status, parental normative beliefs, peer modeling, and food purchasing. The unadjusted logistic regression analyses found that daily SSB intake was significantly associated with food security status. Specifically, food secure students were significantly less likely than food insecure students to report daily SSB intake (OR=0.51, 95% CI=0.28, 0.93). After controlling for parent education, parental normative beliefs, peer modeling, and food purchasing, the magnitude of the association between food security status and daily SSB intake was consistent with the unadjusted model but the association was no longer significant. For the remaining dietary outcomes, both parent education and food insecurity were not significantly associated with daily whole grain or low fat milk intake in the unadjusted or adjusted logistic regression models.  60  Table 3-7 Logistic regression analysis of daily vegetable intake by parent education, food security status, parental normative beliefs, peer modeling, and food purchasing. Daily vegetable intake Model 11 Model 22 Model 33 Model 44 Model 55 Model 66 Model 77 Parent education High school or less (Reference) 1.00 1.00 1.00 1.00 1.00 1.00 Some college 1.85* 1.80* 1.54 1.78* 1.57 1.57 [1.06,3.22] [1.04,3.11] [0.85,2.80] [1.01,3.16] [0.86,2.87] [0.86,2.86] College or university 1.30 1.25 1.10 1.24 1.12 1.08 [0.80,2.12] [0.76,2.07] [0.67,1.81] [0.75,2.04] [0.69,1.83] [0.67,1.75] Food security status Food insecure (Reference) 1.00 1.00 1.00 1.00 1.00 1.00 Food secure 1.40 1.35 1.27 1.35 1.29 1.32 [0.89,2.21] [0.85,2.15] [0.81,2.00] [0.85,2.15] [0.81,2.04] [0.81,2.17] Parental normative beliefs vegetable consumption Disagree or neutral (Reference) 1.00 1.00 1.00 Agree 3.38** 2.91** 3.05** [1.61,7.09] [1.38,6.15] [1.42,6.54] Peer modeling vegetable consumption Disagree or neutral (Reference) 1.00 1.00 1.00 Agree 1.71*** 1.42* 1.42* [1.25,2.32] [1.04,1.94] [1.05,1.92] Food purchase < Weekly food purchase (Reference) 1.00 Weekly on campus food purchase 0.73 [0.44,1.21] Weekly off campus food purchase 0.98 [0.60,1.58] Weekly food purchase on and off campus 1.23 [0.74,2.05] N 588 588 588 588 588 588 588 Odds ratios; 95% confidence intervals in brackets; * p < 0.05, ** p < 0.01, *** p < 0.001 1. Model 1 includes parent education (unadjusted). 2. Model 2 includes food security status (unadjusted). 3. Model 3 includes parent education and food security status. 4. Model 4 includes parent education, food security status, and parental normative beliefs. 5. Model 5 includes parent education, food security status, and peer modeling. 6. Model 6 includes parent education, food security status, parental normative beliefs, and peer modeling. 7. Model 7 includes parent education, food security status, parental normative beliefs, peer modeling and food purchasing.  61  Table 3-8 Logistic regression analysis of daily whole grain intake by parent education, food security status, parental normative beliefs, peer modeling, and food purchasing. Daily whole grain intake Model 11 Model 22 Model 33 Model 44 Model 55 Model 66 Parent education High school or less (Reference) 1.00 1.00 1.00 1.00 1.00 Some college 1.08 1.10 0.96 1.12 0.98 [0.58,2.01] [0.58,2.09] [0.49,1.86] [0.57,2.19] [0.49,1.96] College or university 1.12 1.14 1.05 1.12 1.05 [0.74,1.70] [0.74,1.77] [0.67,1.66] [0.72,1.76] [0.66,1.67] Food security status Food insecure (Reference) 1.00 1.00 1.00 1.00 1.00 Food secure 0.88 0.85 0.76 0.86 0.78 [0.54,1.41] [0.52,1.41] [0.46,1.26] [0.51,1.45] [0.47,1.30] Parental normative beliefs whole grain consumption Disagree or neutral (Reference) 1.00 1.00 Agree 3.03*** 2.69*** [1.76,5.19] [1.54,4.69] Peer modeling whole grain consumption Disagree or neutral (Reference) Agree 1.73** 1.41 [1.22,2.46] [0.98,2.01] Food purchase < Weekly food purchase (Reference) Weekly on campus food purchase Weekly off campus food purchase Weekly food purchase on and off campus N  585  585  585  585  585  585  Model 77 1.00 0.97 [0.49,1.94] 1.08 [0.68,1.71] 1.00 0.81 [0.47,1.38] 1.00 2.78*** [1.63,4.76] 1.42 [0.99,2.04] 1.00 1.21 [0.73,2.02] 0.95 [0.53,1.69] 1.71* [1.06,2.77] 585  Odds Ratios; 95% confidence intervals in brackets; * p < 0.05, ** p < 0.01, *** p < 0.001 1. Model 1 includes parent education (unadjusted). 2. Model 2 includes food security status (unadjusted). 3. Model 3 includes parent education and food security status. 4. Model 4 includes parent education, food security status, and parental normative beliefs. 5. Model 5 includes parent education, food security status, and peer modeling. 6. Model 6 includes parent education, food security status, parental normative beliefs, and peer modeling. 7. Model 7 includes parent education, food security status, parental normative beliefs, peer modeling and food purchasing.  62  Table 3-9 Logistic regression analysis of daily low fat milk intake by parent education, food security status, parental normative beliefs, peer modeling, and food purchasing. Daily low fat milk intake Model 11 Model 22 Model 33 Model 44 Model 55 Model 66 Model 77 Parent education High school or less (Reference) 1.00 1.00 1.00 1.00 1.00 1.00 Some college 0.70 0.72 0.71 0.71 0.72 0.70 [0.36,1.35] [0.38,1.36] [0.38,1.35] [0.37,1.37] [0.38,1.37] [0.36,1.37] College or university  0.77 [0.54,1.11]  Food security status Food insecure (Reference) Food secure  1.00 0.75 [0.47,1.19]  0.80 [0.56,1.13]  0.79 [0.57,1.11]  0.79 [0.55,1.13]  0.79 [0.56,1.12]  0.81 [0.57,1.16]  1.00 0.78 [0.50,1.21]  1.00 0.78 [0.50,1.22]  1.00 0.81 [0.51,1.29]  1.00 0.81 [0.51,1.29]  1.00 0.83 [0.52,1.33]  1.00 0.95 [0.66,1.38]  1.00 0.98 [0.67,1.43]  1.00 1.37 [0.84,2.23]  1.00 1.34 [0.84,2.16]  561  1.00 1.44 [0.82,2.53] 1.33 [0.80,2.21] 1.66* [1.01,2.74] 561  Parental normative beliefs low fat milk consumption Disagree or neutral (Reference) Agree  1.00 1.05 [0.76,1.45]  Peer modeling low fat milk consumption Disagree or neutral (Reference) Agree  1.00 1.35 [0.87,2.09]  Food purchase < Weekly food purchase (Reference) Weekly on campus food purchase Weekly off campus food purchase Weekly food purchase on and off campus N  561  561  561  561  561  Odds ratios; 95% confidence intervals in brackets; * p < 0.05, ** p < 0.01, *** p < 0.001 1. Model 1 includes parent education (unadjusted). 2. Model 2 includes food security status (unadjusted). 3. Model 3 includes parent education and food security status. 4. Model 4 includes parent education, food security status, and parental normative beliefs. 5. Model 5 includes parent education, food security status, and peer modeling. 6. Model 6 includes parent education, food security status, parental normative beliefs, and peer modeling. 7. Model 7 includes parent education, food security status, parental normative beliefs, peer modeling and food purchasing.  63  Table 3-10 Logistic regression analysis of daily packaged snack intake by parent education, food security status, parental normative beliefs, peer modeling, and food purchasing. Daily packaged snack food intake 1 2 Model 1 Model 2 Model 33 Model 44 Model 55 Model 66 Model 77 Parent education High school or less (Reference) 1.00 1.00 1.00 1.00 1.00 1.00 Some college 0.69 0.67 0.66 0.66 0.66 0.60 [0.37,1.28] [0.35,1.27] [0.35,1.25] [0.35,1.25] [0.35,1.24] [0.34,1.06] College or university 0.69 0.66 0.65* 0.66* 0.65* 0.61* [0.45,1.04] [0.44,1.00] [0.42,0.98] [0.44,0.99] [0.43,0.98] [0.42,0.90] Food security status Food insecure (Reference) 1.00 1.00 1.00 1.00 1.00 1.00 Food secure 1.17 1.26 1.31 1.26 1.31 1.67 [0.70,1.94] [0.77,2.08] [0.79,2.16] [0.77,2.07] [0.80,2.14] [0.92,3.02] Parental normative beliefs packaged snack Disagree or neutral (Reference) 1.00 1.00 1.00 consumption Agree 1.49 1.48 1.11 [0.96,2.29] [0.94,2.35] [0.70,1.73] Peer modeling packaged snack consumption Disagree or neutral (Reference) 1.00 1.00 1.00 Agree 1.08 1.00 1.05 [0.68,1.73] [0.61,1.64] [0.62,1.79] Food purchase < Weekly food purchase (Reference) 1.00 Weekly on campus food purchase 1.05 [0.48,2.30] Weekly off campus food purchase 2.25* [1.13,4.51] Weekly food purchase on and off campus 7.14*** [4.47,11.39 ] N 574 574 574 574 574 574 574 Odds ratios; 95% confidence intervals in brackets; * p < 0.05, ** p < 0.01, *** p < 0.001 1. Model 1 includes parent education (unadjusted). 2. Model 2 includes food security status (unadjusted). 3. Model 3 includes parent education and food security status. 4. Model 4 includes parent education, food security status, and parental normative beliefs. 5. Model 5 includes parent education, food security status, and peer modeling. 6. Model 6 includes parent education, food security status, parental normative beliefs, and peer modeling. 7. Model 7 includes parent education, food security status, parental normative beliefs, peer modeling and food purchasing.  64  Table 3-11 Logistic regression analysis of daily SSB intake by parent education, food security status, parental normative beliefs, peer modeling, and food purchasing. Daily SSB intake Model 11 Model 22 Model 33 Model 44 Model 55 Model 66 Model 77 Parent education High school or less (Reference) 1.00 1.00 1.00 1.00 1.00 1.00 Some college 0.81 0.86 0.90 0.86 0.89 0.87 [0.46,1.42] [0.48,1.55] [0.49,1.62] [0.47,1.57] [0.49,1.64] [0.48,1.61] College or university 0.81 0.89 0.93 0.88 0.92 0.86 [0.55,1.20] [0.57,1.37] [0.59,1.45] [0.57,1.37] [0.59,1.45] [0.51,1.43] Food security status Food insecure (Reference) 1.00 1.00 1.00 1.00 1.00 1.00 Food secure 0.51* 0.52* 0.53 0.53* 0.54 0.59 [0.28,0.93] [0.28,0.99] [0.28,1.00] [0.28,1.00] [0.29,1.01] [0.31,1.12] Parental normative beliefs SSB consumption Disagree or neutral (Reference) 1.00 1.00 1.00 Agree 0.71 0.68* 0.75 [0.50,1.01] [0.48,0.98] [0.53,1.06] Peer modeling SSB consumption Disagree or neutral (Reference) 1.00 1.00 1.00 Agree 1.17 1.25 1.19 [0.77,1.77] [0.82,1.92] [0.78,1.81] Food Purchases < Weekly food purchase (Reference) 1.00 Weekly on campus food purchase 0.51 [0.26,1.01] Weekly off campus food purchase 1.46 [0.94,2.26] Weekly food purchase on and off campus 4.00*** [2.80,5.71] N 585 585 585 585 585 585 585 Odds ratios; 95% confidence intervals in brackets; * p < 0.05, ** p < 0.01, *** p < 0.001 1. Model 1 includes parent education (unadjusted). 2. Model 2 includes food security status (unadjusted). 3. Model 3 includes parent education and food security status. 4. Model 4 includes parent education, food security status, and parental normative beliefs. 5. Model 5 includes parent education, food security status, and peer modeling. 6. Model 6 includes parent education, food security status, parental normative beliefs, and peer modeling. 7. Model 7 includes parent education, food security status, parental normative beliefs, peer modeling and food purchasing.  65  Table 3-12 Summary for unadjusted and final adjusted associations of SES measures and all daily dietary intake outcomes. Packaged snack Vegetable SSB Whole grain Low fat milk foods 2 2 *(Parent education) NS *(Food security) NS NS2 Unadjusted models of outcomes NS2 * (Parent education) NS2 NS2 NS2 Adjusted models 1 Magnitude of the Magnitude of the Magnitude of the of outcomes association association did not association did not decreased change change * Significantly associated with outcome 1. Adjusted models include parent education, food security status, parental normative beliefs and peer modeling of related food categories, and food purchasing 2. NS = Not significantly associated with SES measures  66  Chapter 4: Discussion This thesis provides novel understanding of school-day dietary intake among grade 58 Vancouver public school students, indicating that there is room for improvement in dietary intake. Less than half of the grade 5-8 Vancouver public school students sampled reported daily school-day consumption of fruits, vegetables, whole grains, and low fat milk. Further, daily school-day consumption of SSB, packaged snack foods, and energy-dense processed foods was reported by 30%, 20%, and 15%, respectively, of the sample. School-day dietary intake has previously been reported to comprise 35% of dietary intake among K-12 students (105), reflecting a meaningful contribution to overall dietary intake of students. For example, the majority of our study sample reported less than daily intake of fruits and vegetables on school days, characterized by approximately one-third of daily energy intake. Whereas, Canada’s Food Guide recommends 6 daily servings of fruits and vegetables for girls and boys aged 9-13 (30). This gap in fruit and vegetable intake exemplifies that overall dietary intake of the population may benefit from increasing school-day intake frequency of foods recommended for daily intake (e.g. fruits, vegetables, whole grains, and low fat milk) and by decreasing intake frequency of foods recommended to by limited in daily intake (e.g. packaged snack foods and SSB) (30,106). These results are similar to national estimates of child and adolescent dietary intake, where the majority of school-aged children were found not to be meeting daily serving recommendations for fruits, vegetables, whole grains, and dairy, as well as consuming servings above recommendations from the “other foods” group (2). Previous research with children and adolescents in various Canadian cities has similarly found dietary intake out of line with recommendations. Hanning et al (29) reported that daily servings consumed of fruit,  67  vegetable, dairy, and grain food groups fell below Canada’s Food Guide recommendations, among grade 6-8 students in the Peer district of Waterloo, Ontario. The study also found intake of foods from the “other foods” category above Canada’s Food Guide recommendations (29). Research with school-aged children in BC reports similar results. Grade 4 and 5 students in Victoria, BC and grade 5 and 6 students in Vancouver, BC were also found to consume daily servings of fruits and vegetables below Canada Food Guide recommendations (31,32). This study identified potential for improvement in school-day dietary intake. This study further revealed that daily school-day intake of vegetables, SSB, and packaged snack foods significantly varied by SES. However, whole grains and low fat milk were not significantly associated with either SES measure. In terms of the significant findings, the unadjusted model for vegetable intake showed that daily vegetable intake was significantly more likely among students from households where the highest parent education level was some college, compared to students whose parent/guardian had a high school education or less. While this finding is in line with the study hypothesis that higher education would be associated with greater vegetable intake, it was surprising that the highest educational attainment level (college or university education) did not significantly differ from the high school or less reference group. Adjusted models showed a significant and negative association between parent education and packaged snack food intake and unadjusted models revealed that food security status was significantly and negatively associated with SSB intake. Given these significant associations, it is possible that SES may have a role in shaping the dietary intake of Vancouver children and adolescents; however, findings from this study were inconsistent. Specifically, SES was significantly associated  68  with three out of the five dietary outcomes examined; yet, different measures of SES were noted for each of the associations. As a result, more research in this area is warranted. The significant findings are consistent with previous research that has found significant positive associations between SES and vegetable intake (47,91,107), as well as negative associations between SES and SSB (94,108), and packaged snack foods (48). Xie et al (47) measured usual dietary intake using an FFQ with adolescents in Southern California. The study found that that mean daily servings of vegetables significantly increased with the student-reported measure of parent education level. Researchers conducting a study of Australian children and adolescents aged 2-16 administered two 24 hour recalls to compare students reporting no SSB to any SSB intake (108). Low parent education was significantly associated with a greater likelihood of SSB intake (p<0.001) (108). Research with CCHS Cycle 2.2 also revealed that among low income girls aged 9-18, food insecurity was significantly associated with higher SSB intake (94). A nationally representative study of US adolescents measured daily intake of foods similar to the ‘packaged snack food’ category measured by our study, which both included chips and baked sweets (48). Low SES students consumed significantly more daily servings of packaged snacks compared to high SES students (p<0.001) (48). Previous research supports the significant differences in dietary intake by SES observed in this thesis. However, it is important to note that significant associations between SES measures and dietary outcomes were not consistently observed. This is congruent with a study of Canadian children and adolescents. Kirkpatrick and Tarasuk (39) noted that compared to adults, fewer significant differences in dietary intake by food security status were observed among Canadian children and adolescents (39). Similarly, a study examining the  69  consumption of added sugars, to examine socioeconomic differences in unhealthy eating behaviour, found non-significant associations between SES and added sugar intake among Norwegian grade 8 students (109). The mixed findings in this thesis indicate a need for further research on the role of socioeconomic status in dietary intake among Vancouver children and adolescents. Multiple considerations may explain the null findings of the associations between SES and dietary intake among Vancouver public school students. Compared to cities where previous research found significant positive associations between SES and dietary quality, this study found a different distribution of education among adults, with a lower proportion of parents with high school education or less reported by grade 5-9 students. A study in Baltimore, Maryland had a higher prevalence, with 69% of parents completing less than 12 years of education (74). The sample in a study in Montreal, Quebec reported that high school education or less than 12 years of education ranged from 55 to 75% among mother’s and father’s highest education level (35). A study in Toronto, Ontario found that 56% of parents completed high school or less (54). Previous studies reporting significant positive associations between SES and dietary quality may have educational environments that are different than Vancouver. High neighbourhood-level socioeconomic status in Vancouver may positively influence the dietary quality of individuals, notwithstanding individual-level SES and the high area-level prevalence of high education may contribute to the observed similarities in dietary intake between SES groups. The high SES environment may influence dietary intake through psychosocial factors (19) such as family and community norms and knowledge about dietary health (58,59). Further research is required to evaluate associations  70  of neighbourhood-level SES with school-day dietary intake of Vancouver school-aged children and to understand the factors explaining the associations. Dietary quality may significantly vary by SES among Vancouver children and adolescents, yet at a more sensitive scale of dietary intake than measured by this study. The binary measure of daily versus less than daily intake of food categories was the most appropriate measure for the purposes of this study, given the limitations of conducting a comprehensive survey with this specific population, as discussed in Chapter 2: Methods. Perhaps the use of a numeric measure of dietary intake, such as serving sizes, may reveal socioeconomic differences in nutritional quality of dietary intake. A numeric measure of dietary intake would require additional information from respondents regarding portion size estimation. A number of previous studies found significant differences in mean servings sizes by SES among children and adolescents (12,35,48). Yet, due to potential participant fatigue and low attention, identified particularly with this age group, the age-appropriate FFQ measure selected did not include serving size estimation (88). To accurately measure serving sizes among this population, the survey tool would have to be dramatically reduced in length, and thus would reduce the detail of other constructs measured. Among dietary outcomes observed to significantly vary with SES measures, controlling for parental normative beliefs decreased the magnitude of the association with daily vegetable intake, removed the significance of the association with vegetable and SSB intake, but did not change the association with packaged snack food intake. The OR for the estimate of the parent education some college group decreased from 1.85 (unadjusted) to 1.54 (when controlling for food security status and parental normative beliefs), suggesting that parental normative beliefs may have a small role in explaining the association between  71  parent education and daily vegetable intake. In other words, high parental normative beliefs, (for example, students that strongly agree that their parents think they should eat vegetables every day) may abate socioeconomic differences in daily vegetable intake. In the case of the SSB outcome, although controlling for parental normative beliefs removed the significance with food security status, the magnitude of the association between food security status and SSB intake was similar before and after controlling for parental normative beliefs and the 95% confidence interval for the estimate of food security status was close to 1.00. The change in association between parent education and daily vegetable intake, after controlling for parental normative beliefs, suggests that school nutrition interventions aimed at shifting parental normative beliefs towards dietary recommendations may be effective at overcoming socioeconomic barriers to healthy eating among children and adolescents. Yet the change in association with daily vegetable intake was minimal and was not observed with the SSB and packaged snack food outcomes, which warrants further research regarding the influence of parental normative beliefs on the associations between SES and dietary intake. On the other hand, the SES associations with vegetable, SSB, and packaged snack food intake remained consistent after controlling for peer modeling. This finding indicated that after adjusting for peer modeling, SES still explained significant differences in dietary intake. Higher peer modeling of healthy eating, such as observing friends eating vegetables daily, may not overcome the socioeconomic barriers to dietary intake. This finding may be explained by previous research that suggests a stronger role of parents, compared to peers, in shaping child and adolescent dietary intake (66,110). After controlling for SES, parental normative beliefs was significantly associated with daily vegetable and whole grain intake and peer modeling was significantly associated  72  with daily vegetable intake. Our findings are supported by previous research with 11-15 year olds in Minnesota, US (68). Researchers found that parental normative beliefs and peer modeling had significant yet weak associations with fruit and vegetable intake (68). Fruit (r=0.19) and vegetable intake (0.21) were significantly associated with family normative beliefs (68). Peer modeling was significantly associated with fruit (r=0.14) and vegetable intake (r=0.16) (68). However, this thesis found that the psychosocial variables did not consistently vary across dietary outcomes. In final adjusted models, parental normative beliefs were significantly associated with only two dietary outcomes (daily vegetable and whole grain intake) and peer modeling was significantly associated with one (daily vegetable intake). This contrasts with a previous study that reported a significant influence of parents with student dietary intake of many foods. van der Horst et al (111) found that among 12-15 year old students in Rotterdam, the Netherlands, parental norms and peer modeling were significantly and positively associated with daily soft drink and packaged snack food intake, after adjusting for demographic characteristics, including parent education. However, few studies have examined parental normative beliefs of food consumption beyond fruit and vegetable intake; therefore, more research on this topic is needed. The non-significant associations between peer modeling and dietary intake may be supported by previous research (66,110). A study of psychosocial correlates of dietary intake among 12-15 year old Australians found that dietary intake of parents was significantly associated with the child’s intake among all 22 food items, while peer intake was significantly associated with the child’s intake among only half of the food items. The psychosocial variables served as control variables in the objectives of the regression analyses  73  for this thesis; therefore, to better understand role of peers and parents in shaping dietary intake, future research should examine both adjusted and unadjusted associations. After adjusting for food purchasing practices, the significant associations between SES and dietary outcomes did not substantially change in magnitude or significance. This finding indicates that food purchasing practices may not explain the significant variation in dietary intake accounted for by SES. However we did observe that, after controlling for SES and psychosocial variables, food purchases on and around school campus were significantly associated with dietary intake on school days. Students who purchased food both on and off campus weekly rather than purchased food less than weekly were significantly more likely to report four of five dietary outcomes, after accounting for parental education, food security status, parental normative beliefs, and peer modeling. For example, students purchasing food both on and off campus weekly were more likely to report daily SSB and packaged snack food intake. Evidence suggests that limited service retail may provide foods recommended to be limited in intake (27,69,74,112). Research by Thompson et al (112) found that students purchasing vending machine food weekly, compared to purchasing less than weekly, were significantly more likely to report daily intake of regular soda and chocolate candy. Also, Wiecha et al (27) found that SSB intake significantly increased with weekly vending machine or fast food restaurant purchases. Our measure of food purchasing practices moved beyond specific retailers and combined many possible on campus and off campus food purchasing locations. Yet we observed findings similar to previous research of significantly greater likelihood of consuming SSB and packaged snack foods among Vancouver students reporting weekly food purchases both on and off campus, compared to less than weekly food purchases.  74  Increased frequency of intake of nutritious foods such as school-day intake of whole grains and low fat milk was also significantly associated with weekly food purchases both on and off campus. A higher likelihood of daily whole grain and low fat milk intake was observed when students purchased food weekly both on and off campus compared to students that report less than weekly food purchasing. These findings were unexpected as previous research indicates that dietary intake “away from home” has been as associated with lower likelihood of consuming recommended items such as whole grains among adults (113). As fluid milk is not commonly brought from home to school due to food safety concerns regarding refrigeration, it is possible that students are more likely to consume fluid milk when available for purchase at or around schools. These findings indicate that food retailing has the potential to positively influence student dietary intake. A further possible explanation for the increased likelihood of most dietary outcomes with purchasing food both on and off campus is that students purchasing foods frequently may be more frequent consumers of all foods, compared to students that purchase food less than weekly. The regression models did not control for energy intake; therefore, it is possible that students who purchase food frequently are purchasing food in addition to foods brought from home, and consequently are more frequent consumers of most dietary categories, compared to students that purchase food less than weekly. Another interesting finding was that the estimated proportion of students reporting food insecurity was approximately 10 percentage points higher among the study sample (15.8%) compared to CCHS 2010 estimates of household food security in the Vancouver Health Region (6.8%) (114), which was comprised of the City of Vancouver, Electoral Area A, and Musqueam 2 (115). The geographical regions sampled are quite similar between the  75  CCHS data and the Food Practices on School Days Study; however, the age group is slightly different, as the CCHS data refers to anyone aged 12 or older (115), and this study includes 10-14 year olds. Also, unlike the self-reported household food security measure in this study, the Statistics Canada estimate (114) was reported by “The Person Most Knowledgeable” (PMK) in the household when respondents were under 15 years of age (115). Perhaps schoolaged children perceived the questionnaire items indicating food insecurity differently than the PMK, resulting in a higher prevalence of self-reported food insecurity among 10-14 year olds.  4.1  Study strengths and limitations There are a number of notable strength to this study. Although nonprobability-  sampling methods were employed, multiple factors demonstrate the external validity of the findings. This study sampled 950 students from mandatory classes of grade 5-8 students in Vancouver public schools. The VSB defined 6 sectors of the City of Vancouver and this study sampled classes from each VSB sector (85). The VSB (85) reported that demographic characteristics, such as income and language spoken at home, vary between sectors; therefore this sampling strategy captured the spectrum of demographic variation of Vancouver neighbourhoods by ensuring that at least one class from each school sector was sampled. Also, the distribution of parent education, the primary explanatory variable of interest, was similar to the Statistics Canada estimate (116). The highest education level was high school or less for 30.4% and college or university for 62.9% of adults 25-64 years old in the City of Vancouver (116) (compared to 20.6% and 63.7% in our study sample, respectively). The sampling strategy and similarity of the key explanatory variable with the Statistics Canada  76  estimate of the region suggest that the sample decently represents Vancouver public school students in grade 5-8 in terms of geography and parent education. The measures examined in this study were carefully selected and are well suited for answering the primary research question. For example, the dietary outcomes were measured by a FFQ adapted from previous research used with Canadian students in grades 5-12 (87). Three Registered Dietitians contributed to decisions on the categorization of items into broader food categories and the coding of these categories as daily versus less than daily intake, coding which has also been used by previous child and adolescent dietary intake studies (37,90,91,117). Parent education was chosen as the primary measure of SES, as this was the SES measure most commonly employed by previous studies of child and adolescent nutritional quality (13,35–38,118). Also, the coding of many variables was decided after conducting sensitivity analyses for the parent education, food security status, and psychosocial variables described in Chapter 2: Methods and Appendix B. Whenever possible, coding decisions followed examples of variables used in previous research, such as parent education (39), food security status (39) the psychosocial variables (32), and food purchasing (25). Many thoughtful decisions were made regarding study measures, contributing to the strength of this study. Of course there are some limitations to this study that deserve consideration. Causal relationships of dietary intake with psychosocial factors and food purchased practices cannot be inferred from results, as this was a cross-sectional study. The self-reported data in this study is subject to potential response error due to respondent memory lapses with the FFQ (86) or the lack of knowledge of SES measures commonly documented among children and  77  adolescents (33). The direction of error due to self-reported data is not known as students may have either over-reported or under-reported dietary intake. However, self-reported data is a more common approach, considering the logistical difficulties with collecting data from a large sample of both parents and children, or with direct observation of usual dietary intake (86). Our study did not include measures of subsidized school meal programs as indicators of SES. US studies of socioeconomic differences in dietary intake among school-aged children have examined eligibility for reduced-price or free school meal programs as a measure of SES (37,44,118). Although a similar federally regulated program does not exist in Canada, the Vancouver School Board does operate a subsidized school meal program for elementary school students, where parents provide a confidential payment to offset the cost of the program; however, no student would be refused due to finances (119). Such a measure may have leant further insight into the socioeconomic differences in dietary intake with Vancouver children and adolescents. The survey tool had two questions addressing participation in Vancouver school meal programs. However, the questions were added to the final questionnaire and were piloted with only the second administration of the questionnaire in Pilot Study B, thus most small-group discussions with participants during the pilot studies did not include the school meal program measures. Therefore, the school meal program measures were not piloted as rigorously for readability and clarity with the target population, compared to the rest of the questionnaire items. Field notes from the Food Practices on School Days Study data collection visits indicated that students were unfamiliar with the terms “School Lunch Program” and “School Breakfast Program”, with many misinterpreting this to refer to other unrelated school events where students can purchase meals delivered to  78  the schools. Therefore, the measures of subsidized school meal programs were considered invalid and not further examined with regard to student SES. The subsidized school meal program measures would require further piloting with the study population to ensure specification in terms of VSB subsidized meal programs, worded in a way familiar to the target population. Yet, student-reported measures of subsidized school meal program participation in the Vancouver School Board would generally be difficult to measure due to the confidentiality of the amount paid by parents.  4.2  Future directions for research Measuring school-day dietary intake was an innovative undertaking, with few  validated examples to draw upon. It is recommended to conduct a future study of the validity and reliability of this survey tool in terms of measuring school-day dietary intake of schoolaged Canadian children. Although content validity was examined and input was provided on the survey tool from grade 7 through 12 students, a study of the validity and reliability of the tool would provide even greater confidence in the accuracy and precision of measures. Such a study could involve evaluating test-retest reliability and relative validity of the survey tool with a sizable subset of the future study sample. To assess test-retest reliability, kappa statistics can be calculated to test agreement between two administrations of the questionnaire, separated by a 1 or 2 week period of time to reduce participant memory of responses, similar to previous research (63). Relative validity of the test dietary method, in this case, the FFQ, can be examined by administrating a reference method, such as 24-hour dietary recalls or diet records (86). The FFQ should precede the reference method so that the pilot study mimics the experience of participants in the final study. Evidence suggests that  79  the act of completing the reference methods prior may improve the participants’ abilities to accurately report their dietary intake on the FFQ (86). The reference and test methods should be spaced with a lapse in time, similarly to reduce participant memory of responses (86). Multiple administrations of the reference methods would be required to calculate dietary intake that represents the same period of time measured by the FFQ (86), in the case of this survey tool, 30 days. Analysis of percent agreement between dietary assessment methods on food categories can indicate validity of the FFQ (120,121). Future research can address these study design and methodological limitations to further knowledge on the topic of school-day dietary intake of children and adolescents.  4.3  Implications for practice Overall, this study indicates that among grade 5-8 students in Vancouver public  schools, the majority of students did not report daily school-day intake of fruits, vegetables, whole grains, or low fat milk and a sizable proportion of students reported daily school-day intake of SSB, packaged snack foods, and energy-dense processed foods. Moreover, SES was significantly associated with daily vegetable, packaged snack food, and SSB intake. While the significant associations that were observed between either parent education or food security status and some of the dietary outcomes are notable, we did not find that either measure of SES was consistently a significant determinant of dietary intake across all food categories. Therefore, the suboptimal prevalence of daily dietary intake among youth, in combination with the inconsistent associations between SES and dietary outcomes, suggest that all students would benefit from school nutrition interventions aimed at moving the population towards dietary recommendations.  80  Evidence signaling the need for improvements in school-day dietary intake among all students demonstrates the multifaceted nature of predictors of health outcomes, and avoids possible overgeneralization of poor nutrition as solely a problem among low SES groups. McPhail et al (122) discuss the potential othering of low SES groups through the common linking of obesity and public health burden to low SES groups. Qualitative research has revealed judgment regarding dietary intake among adolescents, as some youth qualified rejecting unhealthy foods, such as chips and burgers, by describing them as “‘greasy’, ‘fattening’ or ‘disgusting’” (123). Wills et al (124) reported that middle class youth perceived foods to be healthier when higher in price, for example, some considered eating at Starbucks a healthier choice over cheaper limited service food retailers, such as McDonalds. This revealed middle class youth distinguishing themselves from others by avoiding foods thought of as inexpensive and consequently unhealthy (124). Moral judgment surrounding dietary intake may also extend to perceived divisions between middle and working classes. Identifying needs among all students for improved dietary intake mitigates potential stigmatization of school nutrition interventions that target only socioeconomically disadvantaged children. Future research of the role of psychosocial factors in shaping dietary intake is also recommended for the design of school nutrition interventions with the population. The influence of parents and peers may reveal encouraging avenues for shaping dietary intake; however, evidence from this study is somewhat weak. Parental normative beliefs and peer modeling were significantly associated with few dietary outcomes in models examining socioeconomic differences of dietary intake. Future research should also examine unadjusted associations of dietary intake with parental normative beliefs and peer modeling. Other  81  psychosocial factors, measured by the IEAT questionnaire, which may be interesting to further explore include attitudes, perceived environment, self-efficacy, and nutrition knowledge. A comprehensive evaluation of these constructs, similar to previous research (123,125), may lend insight into valuable approaches for designing school nutrition interventions with this population. Further examination of the unadjusted and adjusted associations between food purchasing location and dietary intake would be valuable, in light of our findings that students who purchased food weekly both on and off campus were significantly more likely to consume whole grains, low fat milk, packaged snack foods, and SSB, compared to students who purchased less than weekly, after controlling for measures of SES, parental normative beliefs, and peer modeling. These findings can support policies or education programs for food retail on and around schools. Food retail may be modifiable by regional policies, with the intent to encourage the availability of foods in line with public health nutrition recommendations on and around school campuses. Policy changes may also benefit from supplemental education programs for food retailers on and around schools on the topic of profitable approaches for incorporating more fresh produce and other foods recommended by dietary guidelines, the availability of which is relatively low in limited service food retailers, compared to grocery stores or supermarkets (68). Education programs for children and adolescents regarding healthy food purchasing decisions should also be further investigated. This stage of life is characterized by increased autonomy over food purchase decisions (125) and dietary behaviours developed during this age carry into adulthood (124). Therefore, this may be a critical population for research into effective strategies for healthy food purchasing education. Future research regarding the  82  influence of food purchasing location would be a meaningful approach for improving schoolday dietary intake.  83  Chapter 5: Conclusion At the time of this study, to my knowledge, no other research examined socioeconomic differences of school-day dietary intake among grade 5-8 Vancouver students, controlling for parental normative beliefs, peer modeling, and food purchasing practices. This study therefore provided novel insight showing that most students reported less than daily school-day consumption of fruits, vegetables, whole grains, and low fat milk. A sizable proportion reported daily intake of energy-dense processed foods, packaged snack foods, and SSB. As school-day food consumption accounts for approximately one-third of daily energy intake (9), school-day dietary intake contributes to a meaningful proportion of the dietary intake of the entire day. Further, daily vegetable, packaged snack food, and SSB intake significantly varied by SES; however, we did not find that either measure of SES was consistently a significant determinant of dietary intake across all food categories. Therefore, the suboptimal prevalence of daily dietary intake among youth, in combination with the inconsistent associations between SES and dietary outcomes, suggest that all students would benefit from school nutrition interventions aimed at moving the population towards dietary recommendations. Possible avenues for school nutrition intervention design may consider targeting psychosocial factors or healthy food retail on and around school campuses. In contexts where low socioeconomic status groups are vulnerable to low nutritional quality, school nutrition interventions aimed at parental normative beliefs may improve the dietary intake of low SES students. Parental normative beliefs may explain the association between SES and dietary intake, as this study found that controlling for parental normative beliefs decreased the magnitude and removed the significance of the association between parent education and  84  daily vegetable intake. However, controlling for parental normative beliefs did not change the associations of SES with daily packaged snack food and SSB intake. Therefore, it is difficult to firmly conclude this finding, thus further research is required. The SES measures remained significantly associated with packaged snack food, vegetable, and SSB intake after controlling for peer modeling and food purchasing practices. This finding indicated that in addition to the influences of peer modeling and food purchasing practices, SES still explained differences in dietary intake. Students purchasing food frequently both on and off campus were significantly more likely to report daily intake of whole grains, low fat milk, packaged snack foods, and SSB, compared to students who purchased food less than weekly, after controlling for parent education, food security status, parental normative beliefs and peer modeling. These findings can support policies or education regarding food retail on and off campus, but future research should examine the unadjusted and adjusted associations between food purchasing location and dietary intake. Further evidence pertaining to the role of student food purchasing practices in shaping dietary intake can inform policy changes or school nutrition interventions aimed at increasing the availability and purchase of foods recommended by public health nutritionists on and around school campuses. This study reinforces current evidence indicating the need for improvements in dietary intake among Canadian children and adolescents. 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Grimes C, Riddell L, Campbell K, Nowson C. Dietary salt intake, sugar-sweetened beverage consumption, and obesity risk. Pediatrics. 2013 Jan;131(1):14–21. 109. Overby NC, Lillegaard ITL, Johansson L, Andersen LF. High intake of added sugar among Norwegian children and adolescents. Public Health Nutr. 2004;7(2):285–94. 110. Woodward D, Boon J, Cumming F, Ball P, Williams H, Hornsby H. Adolescents’ reported usage of selected foods in relation to their perceptions and social norms for those foods. Appetite. 1996 Oct;27(2):109–17. 111. van der Horst K, Timperio A, Crawford D, Roberts R, Brug J, Oenema A. The school food environment: associations with adolescent soft drink and snack consumption. Am J Prev Med. 2008 Sep;35(3):217–23. 112. Thompson OM, Yaroch AL, Moser RP, Rutten LJF, Agurs-Collins T. School vending machine purchasing behavior: results from the 2005 YouthStyles survey. J Sch Health. 2010 May;80(5):225–32. 113. McGuire S. Todd J.E., Mancino L., Lin B-H. 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Available from: http://abacus.library.ubc.ca.ezproxy.library.ubc.ca/handle/10573/41852 117. Robinson-O’Brien R, Larson N, Neumark-Sztainer D, Hannan P, Story M. Characteristics and dietary patterns of adolescents who value eating locally grown, organic, nongenetically engineered, and nonprocessed food. J Nutr Educ Behav. 2009 Feb;41(1):11–8. 118. French S, Story M, Fulkerson J, Gerlach A. Food environment in secondary schools: a la carte, vending machines, and food policies and practices. Am J Public Health. 2003 Jul;93(7):1161–7. 119. Vancouver School Board. Vancouver Board of Education inner city schools project review report and recommendation [Internet]. 2009 [cited 2013 Mar 15]. Available from: http://www.vsb.bc.ca/sites/default/files/schoolfiles/Resources/ICP_Recommendations_Report_May_2009.pdf 120. Speck B, Bradley C, Harrell J, Belyea M. A food frequency questionnaire for youth: psychometric analysis and summary of eating habits in adolescents. J Adolesc Health. 2001 Jan;28(1):16–25. 121. Hoelscher D, Day R, Kelder S, Ward J. Reproducibility and validity of the secondary level school-based nutrition monitoring student questionnaire. J Am Diet Assoc. 2003 Feb;103(2):186–94. 122. McPhail D, Chapman GE, Beagan BL. “Too much of that stuff can’t be good”: Canadian teens, morality, and fast food consumption. Soc Sci Med. 2011 Jul;73(2):301– 7. 123. Wills W, Backett-Milburn K, Gregory S, Lawton J. The influence of the secondary school setting on the food practices of young teenagers from disadvantaged backgrounds in Scotland. Health Educ Res. 2005 Aug;20(4):458–65. 124. Wills W, Backett-Milburn K, Lawton J, Roberts M-L. Consuming fast food: the perceptions and practices of middle class young teenagers. In: James A, Tingstad V, Kjorholt A, editors. Children, food and identity in every day life. Palgrave Macmillan; 2010. p. 52–69. 125. Bustillos B, Sharkey J, Anding J, McIntosh A. Availability of more healthful food alternatives in traditional, convenience, and nontraditional types of food stores in two rural Texas counties. J Am Diet Assoc. 2009 May;109(5):883–9.  96  Appendices Appendix A IEAT Questionnaire  IEAT VSB Students Dr. Jennifer Black, Dr. Gwen Chapman, Dr. Alejandro Rojas, nutritionist Sarah Carten and researchers from the Faculty of Land and Food Systems at the University of British Columbia would like to learn what Vancouver students think about food, nutrition and the food environment at school. We have designed a survey so that students can tell us about the things they eat and what they think about eating at school and in the nearby neighbourhood. We are asking other students in Vancouver the same questions and we know that everyone eats different things and has unique opinions about food. Before we use this survey in schools, we want to know if our questions make sense to students your age and if there are any ways can make this survey more fun and user friendly. The choice to participate in the study is completely yours and you can choose to stop the survey at any time by closing the internet window. The survey will take about 60 minutes and is strictly confidential. No one except the researchers will see your responses. For any question, if you don’t know how to respond or if you don’t want to respond, that’s okay, just move on to the next question. At the end, we will ask you if there were any questions that didn’t make sense to you, or if you can think of ways we can improve this survey.  THIS IS NOT A TEST. Your responses will not influence your grades in any class or your chance of being a student at the University of British Columbia. So feel free to answer the questions as honestly as you can. Thank you for your valuable input.  1) Please enter your user ID. (Note: User ID should be 4 letters followed by 2 numbers) ____________________________________________________________ 2)  Do you agree to participate in this survey? Please note: if you click NO, you will not be able to continue to the next screen.  Yes  No  3) How old are you?  7 years old 97              8 years old 9 years old 10 years old 11 years old 12 years old 13 years old 14 years old 15 years old 16 years old 17 years old 18 years old  4) What grade are you in?           4 5 6 7 8 9 10 11 12  5) How would you describe your gender?  Male  Female 6) What school do you go to?                        Acadia Road Elementary Admiral Seymour Bayview Britannia Elementary Captain James Cook Carnarvon Champlain Heights Champlain Heights Annex Charles Dickens Charles Dickens Annex Chief Maquinna Collingwood Neighbourhood (Bruce Annex) David Livingstone David Lloyd George David Oppenheimer Dr. A.R. Lord Dr. Annie B. Jamieson Dr. George M. Weir Dr. H.N. MacCorkindale Dr. R.E. McKechnie Edith Cavell Elsie Roy 98                                                        Emily Carr False Creek Florence Nightingale Garibaldi Annex General Brock General Gordon General Wolfe George T. Cunningham Graham D Bruce Grandview Hastings Henderson Annex Henry Hudson Kerrisdale Annex J.W. Sexsmith John Henderson John Norquay Jules Quesnel Kerrisdale L'Ecole Bilingue Laura Secord Lord Beaconsfield Lord Kitchener Lord Nelson Lord Roberts Lord Selkirk Lord Strathcona Lord Tennyson Maple Grove Maquinna Annex McBride Annex Mount Pleasant Nootka Pierre Elliott Trudeau Queen Alexandra Queen Elizabeth Queen Elizabeth Annex Queen Mary Queen Victoria (Grandview Annex) Quilchena Renfrew Roberts Annex Selkirk Annex Shaughnessy Simon Fraser Sir Alexander Mackenzie Sir Charles Kingsford-Smith Sir Guy Carleton Sir James Douglas Sir James Douglas Annex Sir John Franklin Sir Matthew Begbie Sir Richard McBride 99                                        Sir Sandford Fleming Sir Wilfred Grenfell Sir Wilfrid Laurier Sir Wilfrid Laurier Annex Sir William MacDonald Sir William Osler Sir William Van Horne Southlands Tecumseh Tecumseh Annex Thunderbird Tillicum Annex Trafalgar Tyee University Hill Elementary Vancouver Learning Network Elementary Walter Moberly Waverley Britannia Secondary David Thompson Eric Hamber Gladstone John Oliver Killarney King George Kitsilano Lord Byng Magee Point Grey Prince of Wales Sir Charles Tupper Sir Winston Churchill Templeton University Hill Vancouver Learning Network - Secondary Vancouver Technical Windermere  7) How many years have you attended this school?  this is my first year at this school  this is my second year at this school  I have been at this school for three years or more 8) If you attended a different school(s) before, what school(s) did you go to? Choose all that apply.        Acadia Road Elementary Admiral Seymour Bayview Britannia Elementary Captain James Cook Carnarvon 100                                                        Champlain Heights Champlain Heights Annex Charles Dickens Charles Dickens Annex Chief Maquinna Collingwood Neighbourhood (Bruce Annex) David Livingstone David Lloyd George David Oppenheimer Dr. A.R. Lord Dr. Annie B. Jamieson Dr. George M. Weir Dr. H.N. MacCorkindale Dr. R.E. McKechnie Edith Cavell Elsie Roy Emily Carr False Creek Florence Nightingale Garibaldi Annex General Brock General Gordon General Wolfe George T. Cunningham Graham D Bruce Grandview Hastings Henderson Annex Henry Hudson Kerrisdale Annex J.W. Sexsmith John Henderson John Norquay Jules Quesnel Kerrisdale L'Ecole Bilingue Laura Secord Lord Beaconsfield Lord Kitchener Lord Nelson Lord Roberts Lord Selkirk Lord Strathcona Lord Tennyson Maple Grove Maquinna Annex McBride Annex Mount Pleasant Nootka Pierre Elliott Trudeau Queen Alexandra Queen Elizabeth Queen Elizabeth Annex 101                                                        Queen Mary Queen Victoria (Grandview Annex) Quilchena Renfrew Roberts Annex Selkirk Annex Shaughnessy Simon Fraser Sir Alexander Mackenzie Sir Charles Kingsford-Smith Sir Guy Carleton Sir James Douglas Sir James Douglas Annex Sir John Franklin Sir Matthew Begbie Sir Richard McBride Sir Sandford Fleming Sir Wilfred Grenfell Sir Wilfrid Laurier Sir Wilfrid Laurier Annex Sir William MacDonald Sir William Osler Sir William Van Horne Southlands Tecumseh Tecumseh Annex Thunderbird Tillicum Annex Trafalgar Tyee University Hill Elementary Vancouver Learning Network Elementary Walter Moberly Waverley Britannia Secondary David Thompson Eric Hamber Gladstone John Oliver Killarney King George Kitsilano Lord Byng Magee Point Grey Prince of Wales Sir Charles Tupper Sir Winston Churchill Templeton University Hill Vancouver Learning Network - Secondary Vancouver Technical Windermere 102   Other 9) If you chose other, please provide the name of the school you went to, and the city or town where your school was located. __________________________________________________________________________________ __________________________________________________________________________________ ________________________________________________________ 10) The next set of questions asks about the types of foods and beverages you typically eat or drink on school days (either during school hours or on your way to or from school)? Beverages: Looking back on the past 30 days, on average, how often did you drink the following on school days (either during school hours or on your way to or from school)? A serving size is one cup or small carton. Hold the arrow over the beverage to learn more about the beverage or serving sizes.  Whole milk 2% milk 1% or skim milk Chocolate milk Soy milk (plain) Chocolate soy milk Rice or almond milk 100% fruit juice or vegetable juice  Never Once a month 2-3 times a Once a 2-4 times a Once a or less month week week day                                                       2 or more times a day          11) Beverages: Looking back on the past 30 days, on average, how often did you drink the following on school days (either during school hours or on your way to or from school)? A serving size is about one cup, can, or drinking box. Hold the arrow over the beverage to learn more about the beverage or serving sizes.  Never  Fruit-flavoured drinks Regular (non-diet) pop or soft drinks Diet pop or soft drinks Iced tea (sugar sweetened) Sports drinks Energy drinks Hot chocolate or specialty coffee Regular coffee or tea    Once a month or less     2-3 times a Once a 2-4 times Once a 2 or more month week a week day times a day                                                                                      103  Bottled water Water, not bottled Slurpees®, slushies, or snow cones Fruit smoothie, Booster Juice®, or Jugo Juice®) Milkshake or ice cream smoothie                                                                 12) Vegetables and Fruit: Looking back on the past 30 days, on average, how often did you eat the following on school days (either during school hours or on your way to or from school)? Hold the arrow over the food to learn more about the food or serving sizes.  Never  Fresh fruit, not including juice Dried fruit Fruit (frozen or canned) Fresh vegetables (raw or cooked, not including French fries) Vegetables (frozen or canned) Dark green vegetables Orange vegetables      Once a 2-3 times a Once a 2-4 times Once a 2 or more month or month week a week day times a day less                                                              13) Dairy Products and Dairy Alternatives: Looking back on the past 30 days, on average, how often did you eat the following on school days (either during school hours or on your way to or from school)? Hold the arrow over the food to learn more about the food or serving sizes.  Never  Once a 2-3 times a Once a 2-4 times a Once a 2 or more month or less month week week day times a day         Cheese Plain yogurt, plain yogurt  drink, or kefir) Flavoured yogurt, yogurt  drink, or kefir)                          14) When you choose dairy products and dairy alternatives do you usually choose low fat?       Never Rarely Sometimes Often Always 104   I don't know 15) Meat and Meat Alternatives: Looking back on the past 30 days, on average, how often did you eat the following on school days (either during school hours or on your way to or from school)? Hold the arrow over the food to learn more about the food or serving sizes.  Never Once a month or less Meat or poultry Fish or shellfish Eggs Meat alternatives  2-3 times a month  Once a week  2-4 times a Once a 2 or more times week day a day                                                          16) Grain Products: Looking back on the past 30 days, on average, how often did you eat the following on school days (either during school hours or on your way to or from school)? Hold the arrow over the food to learn more about the food or serving sizes.  Whole grains Grains (not whole grains)  Never Once a month 2-3 times a or less month          Once a week    2-4 times a Once a week day       2 or more times a day    17) Fast Foods: Looking back on the past 30 days, on average, how often did you eat the following on school days (either during school hours or on your way to or from school)? Hold the arrow over the food to learn more about the food or serving sizes.  Never  Pizza or pizza snack  Hot dog Hamburger or  cheeseburger Breaded/fried chicken or  fish  Other burger French fries or other  fried potatoes Sub, deli sandwich,  wrap or pita  Taco or nachos  Once a 2-3 times a Once a 2-4 times a Once a 2 or more month or less month week week day times a day                                                                                     105  Pasta or noodle/rice bowl Sushi Frozen packaged dinner                                     18) Snack Foods and Desserts: Looking back on the past 30 days, on average, how often did you eat the following on school days (either during school hours or on your way to or from school)? Hold the arrow over the food to learn more about the food or serving sizes.  Never Once a month 2-3 times a or less month Salty packaged snacks Candy or chocolate bars Baked sweets Frozen desserts  Once a week  2-4 times a Once a week day  2 or more times a day                                                   19) Other Food Products: Looking back on the past 30 days, on average, how often did you eat the following on school days (either during school hours or on your way to or from school)? Hold the arrow over the food to learn more about the food or serving sizes.  Never  Meal replacement bars or meal replacement shakes, protein bars, or energy bars    Once a 2-3 times Once a 2-4 times Once a 2 or more month or a month week a week day times a less day             20) Are there any other foods or beverages, including snack foods, fast foods, and desserts, that you frequently eat, that we did not ask you about? Please list. For each item, indicate what serving size you eat or drink, and how often you eat or drink this item? Example: pudding, 1 pudding cup, 1 time per day __________________________________________________________________________________ __________________________________________________________________________________ ________________________________________________________ 21) If you take any dietary supplements (such as multivitamins, minerals, meal replacement bars or shakes, protein powder, herbal supplements or weight loss supplements) please specify the type/brand and amount you usually take: Example: multivitamin/mineral, Flinstones® chewable, 1 tablet per day  106  __________________________________________________________________________________ __________________________________________________________________________________ ________________________________________________________ 22) The following question asks you about eating specific categories of foods. Looking back on the past YEAR, on average, how often did you eat the following on school days (either during school hours or on your way to or from school)?  Never  Organic food Local food (food that is grown or produced locally e.g. from a community garden, farm, or farmers market ) Food that was purchased at a local farmers market Food bought directly from a farm Food grown at a school (e.g. in a garden, in balcony planters, or in an orchard or greenhouse) Food grown by someone you know (e.g. at home, in the community, etc.)    Once a 2-3 times 1 time a 2 or more I don’t month or a month week times a know less week                                                                   23) Looking back on the past YEAR, on average, how often did you eat the following on school days (either during school hours or on your way to or from school)?  Food that you helped grow Food or beverages in recyclable packaging (instead of packaging that goes in the garbage) Food or beverages in compostable packaging that can be composted (instead of packaging that goes in the garbage) Food from a Community Supported Agriculture (CSA) program  Never Once a 2-3 1 time 2 or 1 2 or I don't month or times a a week more time more know less month times a a day times a week day                                                         24) In a typical month, how often do you drink or eat food that you purchased at the following places on school days (either during school hours or on your way to or from school)?  107  Never  School cafeteria (including pizza days or other special meals) School store, snack shop or canteen Fast food or take out restaurant or food court Restaurant (not fast food) Vending machines at your school Grocery store Convenience store (such as 7Eleven) Coffee shop  Once a 2-3 times a Once a 2-4 times Once a 2 or more month or month week a week day times a day less                                                                                                                  25) Looking back on the past YEAR, did you have lunch from the School Lunch Program ?       No Yes I don't know My school does not offer a School Lunch Program  26) Looking back on the past YEAR, did you have breakfast from the School Breakfast Program?      No Yes I don't know My school does not offer a School Breakfast Program  27) The following questions are about school vending food and beverage machines. Does your school have a snack or beverage vending machine that you can buy snacks or beverages from?  Yes  No  I don't know 28) In the vending machines at your school, are the foods in them labelled “Choose Most”, “Choose Sometimes”, “Choose Least” “Not Recommended” or with happy faces or checkmarks? (e.g. Choose Most = √√)  Yes  No  I don't know 29) Do you choose foods or beverages depending on these labels?  108        Never Rarely Sometimes Often Always  30) In a typical month, how often do you do each of the following on school days (either during school hours or on your way to or from school)?  Eat nothing for lunch Bring a lunch that you helped to prepare or pack from home Bring a lunch that someone (other than you) prepared or packed from home Get lunch from a friend (e.g. sharing or trading food) Put leftover food that you didn’t finish eating into a compost bin at school Eat lunch in a school cafeteria Eat food grown at school, at home or in your community (for example in a garden, in balcony planters, or in an orchard or greenhouse)?  Never Once a 2-3 times Once a 2-4 month or a month week times a less week       Every school day                                                                           31) Are there any other places that were not mentioned above where you get food for lunch from on school days (either during school hours or on your way to or from school)? __________________________________________________________________________________ __________________________________________________________________________________ ________________________________________________________ 32) In a typical month, on school days (either during school hours or on your way to or from school), how often do you…  Never Once a month or less Eat lunch friends Eat lunch family Eat lunch Eat lunch teachers  with your with your alone with your  2-3 times a month  Once a week  2-4 times a week  Every school day                                                  109  33) In a typical month, on Monday through Friday (anytime of the day), how often do you...  Never Once a month or less Eat dinner at home with your family Eat breakfast  2-3 times a month  Once a week  2-4 times a week  Once a day                          34) The last time you purchased LUNCH on a school day, about how much money did you spend on your LUNCH? If you never buy lunch, Select $0.00              $0.00 less that $1.00 $1.00 $2.00 $3.00 $4.00 $5.00 $6.00 $7.00 $8.00 $9.00 $10.00 or more  35) If you wanted to, how sure are you that you could (or are able to) do the following?  Use a recipe (including measuring and combining ingredients) to cook a simple dish Prepare and chop vegetables (for example, wash and chop carrots) Eat vegetables at least once a day Eat healthy food Eat food that was grown or produced in an environmentally friendly way Eat local food (food that is grown or produced locally e.g. from a community garden, farm, or farmers market ) Eat food that is safe to eat Drink tap water  Very sure I could not  Somewhat sure I could not  Not sure Somewhat whether I sure I could could or could not  Very sure I could                                                                        36) How often are these foods or drinks sold at your school? 110  Any food or drink Food that was grown or produced in an environmentally friendly way Local food (food that is grown or produced locally e.g. from a community garden, farm, or farmers market ) Food that is safe to eat Healthy food  Never Less than Once a week to once a a few times a week week     Every school day   I don't know                                      37) Approximately how long would it take a student from your school to walk to a location where the following foods or beverages are sold?  Any food or beverage Fresh Fruit Vegetables, not including French fries French fries or other fried potatoes Sugar sweetened beverages (e.g. pop) Low-fat milk or milk alternative (e.g. soy, rice, or almond beverage) Salty packaged snacks Candy or chocolate bars Fast food Organic food Local food (food that is grown or produced locally e.g. from a community garden, farm, or farmers market )  Less than 5 5-10 minutes minutes            10-15 minutes       More than I don't 15 minutes know                                                         38) Are there any foods or beverages you wish were more easily available at school or near your school? __________________________________________________________________________________ __________________________________________________________________________________ ________________________________________________________ 39) If you were to buy food or beverages on school days (either during school hours or on your way to or from school), how important would it be to you that…  Not at all  Not very  Somewhat  Very  111  The food includes fresh vegetables The food includes whole-grain items (for example, whole grain bread or pasta, brown rice, whole grain cereal, like oatmeal or shredded wheat) The food includes low-fat milk or a milk alternative (e.g. 1 cup or small carton of 2%, 1%, skim milk, or a soy, rice, or almond beverage ) The food includes a milk alternative (e.g. 1 cup or small carton of soy, rice, or almond beverage) The food is healthy The food is tasty The food is similar to food that your friends eat The food is similar to food you eat with your family The food is convenient (easy to get, make, and/or eat)  important   important   important   important                                                           40) If you were to buy food or beverages on school days (either during school hours or on your way to or from school), how important would it be to you that…  Not at all important  Not very important  Somewhat important  Very important                                          The food is something that won't make you gain weight The food is fresh rather than packaged The food is inexpensive The food makes you feel full The food is local (food that is grown or produced locally e.g. from a community garden, farm, or farmers market ) The food is organic  41) If you were to buy food or beverages on school days (either during school hours or on your way to or from school), how important would it be to you that…  The food is environmentally friendly (e.g. grown, processed and/or packaged in ways that have the smallest negative impact on the environment) The food is minimally processed (foods without chemicals, preservatives, and processing e.g. brown rice, fresh fruit or nuts, roasted vegetables, baked beans) The food is safe to eat  Not at all important  Not very important  Somewhat important  Very important                          112  42) If you buy food at the cafeteria, what is(are) the reason(s)? Choose all that apply.                         My school doesn't have a cafeteria I don't buy food at the cafeteria The food is tasty The food looks tasty I like the food The food is nutritious The food is fresh The food is safe to eat The food looks healthy The food is familiar to me The food portions are consistent The food is an affordable price The servings are an adequate size There is a lot of variety in the food served The food I like is available at the cafeteria every day I don't have to wait long to order my food I don't bring food from home My parents don't have food at home for me to bring I don't like the packed-lunch options from home There is always enough space to sit in the cafeteria The staff chat with me The staff is friendly Other  43) If you chose "other", please describe. __________________________________________________________________________________ __________________________________________________________________________________ ________________________________________________________ 44) Are there any other factors that are important to you when deciding WHERE you eat your lunch on school days ? Please describe: __________________________________________________________________________________ __________________________________________________________________________________ ________________________________________________________ 45) Are there any other factors that are important to you when deciding WHAT to eat for lunch on school days? Please describe: __________________________________________________________________________________ __________________________________________________________________________________ ________________________________________________________  113  46) Have you learned about food or healthy eating in any of these classes or subjects at school?  Culinary Arts Home Economics/ Foods Environment Ecology Health or Physical Education  I have not taken this subject   I took this subject but I did not learn about food or healthy eating   Yes - During this school Yes - In a year (anytime since previous school September) year                                47) Are there any other classes or subjects at school where you have learned about food or healthy eating?  Yes  No 48) Please name/describe the class and explain whether you took this course this school year or in a previous school year. __________________________________________________________________________________ __________________________________________________________________________________ ________________________________________________________ 49) Have you participated in any of the following this school year (anytime since September)? Choose all that apply.  No Yes - At school (or as part of a school activity)  Learning how to cook  Cooking on my own  (e.g. making dinner at  a friend's house) Learning how to   grocery shop Grocery shopping on   my own Choosing healthy   foods   Preparing healthy  Yes At home   Yes - At someone else's home   Yes - In my community  Yes Other    Yes - In a summer program                                                       114  foods Tasting healthy foods  Learning about  Canada’s Food Guide Learning about what  foods are grown in British Columbia                                      50) If you selected "other" for any of the activities above, please name the activity, where you participate(d) in the activity, and how often you participate(d) (e.g. 3 days a week for 1 hour). __________________________________________________________________________________ __________________________________________________________________________________ ________________________________________________________ 51) Have you participated in any of the following this school year (anytime since September)? Choose all that apply.  No Yes - At school Yes Yes - At (or as part of a At someone school activity) home else's home Learning how to grow food in a garden Growing food in a garden on my own (e.g. gardening at home) Learning how to make compost Composting on my own (e.g. putting my leftovers from lunch in a compost bin) Learning how to recycle Recycling on my own (e.g putting my recyclables in a recycle bin)  Yes - In my community  Yes - In a summer program  Yes Other                                                                                      52) If you selected "other" for any of the activities above, please name the activity, where you participate(d) in the activity, and how often you participate(d) (e.g. 3 days a week for 1 hour). __________________________________________________________________________________ __________________________________________________________________________________ ________________________________________________________  115  53) Have you participated in any of the following in a previous school year (before this September)? Choose all that apply.  No Yes - At school (or as part of a school activity)   Learning how to cook Cooking on my own  (e.g. making dinner at  a friend's house) Learning how to   grocery shop Grocery shopping on   my own Choosing healthy   foods Preparing healthy   foods  Tasting healthy foods  Learning about   Canada’s Food Guide Learning about what   foods are grown in British Columbia  Yes At home   Yes - At someone else's home   Yes - In my community  Yes Other    Yes - In a summer program                                                                                     54) If you selected "other" for any of the activities above, please name the activity, where you participate(d) in the activity, and how often you participate(d) (e.g. 3 days a week for 1 hour). __________________________________________________________________________________ __________________________________________________________________________________ ________________________________________________________ 55) Have you participated in any of the following in a previous school year (before this September)? Choose all that apply.  No Yes - At school Yes Yes - At (or as part of a At someone school activity) home else's home Learning how to grow  food in a garden Growing food in a garden  on my own (e.g. gardening at home) Learning how to make  compost  Yes - In my community  Yes - In a summer program  Yes Other                                      116  Composting on my own (e.g. putting my leftovers  from lunch in a compost bin)  Learning how to recycle Recycling on my own (e.g putting my recyclables in  a recycle bin)                                      56) If you selected "other" for any of the activities above, please name the activity, where you participate(d) in the activity, and how often you participate(d) (e.g. 3 days a week for 1 hour). __________________________________________________________________________________ __________________________________________________________________________________ ________________________________________________________ 57) Have you ever been a member of any of the following clubs?: Environmental Club, Ecology Club, Cooking Club, Recycling Club, Composting Club, Gardening Club (growing food…)  Yes - I have been a member of one of more of these clubs  No - I have never been a member of any of these clubs 58) Were you a member of any of the clubs this school year (anytime since September)? Environmental Club, Ecology Club, Cooking Club, Recycling Club, Composting Club, Gardening Club (growing food…)  Yes - I have been a member of a club this school year  No - I have not been a member of a club this school year 59) In which club(s) did you participate this school year, and where did you participate? Choose all that apply.  Environmental Club Ecology Club Cooking club Recycling Club Composting Club Gardening Club (growing food…)  At school (or as part of a school activity) Outside of school              60) How often do you currently participate in this(these) club(s)?  Once a month or less  2-3 times a month  Once a week  2-4 times a Every school week day 117  Club(s) at school (or as part of a school activity) Club(s) outside of school                      61) Have you worked with food or learned about food and healthy eating in any of the clubs in which you participated? Choose all the clubs that apply.        Environmental Club Ecology Club Cooking club Recycling Club Composting Club Gardening Club (growing food…)  62) Were you a member of any of the clubs in a previous school year (before this September)? Environmental Club, Ecology Club, Cooking club, Recycling Club, Composting Club, Gardening Club (growing food…)  Yes - I have been a member of a club in a previous school year  No - I have not been a member of a club in a previous school year 63) In which club(s) did you participate in a previous school year, and where did you participate? Choose all that apply.  Environmental Club Ecology Club Cooking club Recycling Club Composting Club Gardening Club (growing food…)  At school (or as part of a school activity) Outside of school              64) How often did you previously participate in this(these) club(s)?  Club(s) at school (or as part of a school activity) Club(s) outside of school  Once a month or less  2-3 times a month  Once a week  2-4 times a Every school week day                      65) Have you worked with food or learned about food and healthy eating in any of the clubs you selected in the previous question? Choose all the clubs that apply.      Environmental Club Ecology Club Cooking club Recycling Club 118   Composting Club  Gardening Club (growing food…) 66) Does your school have a teaching cafeteria?  No  Yes  I don't know 67) This year, have you ever worked in the teaching cafeteria?  No  Yes 68) Which of the following have you done this year in the teaching cafeteria? Please choose all that apply.      I I I I  have have have have  helped helped helped helped  prepare food clean up during or after a meal serve food collect money from customers  69) Have you participated in any other clubs or activities where you learn about food and healthy eating or where you work with food?  Yes  No 70) Please name and describe the activity(ies) or club(s), where you participate(d), and how often you participate(d)? Please also explain if you participated this school year (anytime since September) or in a previous school year? __________________________________________________________________________________ __________________________________________________________________________________ ________________________________________________________ 71) The following questions are about school salad bars. Do you have a salad bar at your school?  Yes  No  I don't know 72) How many of the days that it is open do you buy or eat from the salad bar?      Always Most of the time Sometimes Never  73) How much do you agree with the following statements? My parent(s) or primary 119  caregiver(s) think I should...  Eat vegetables at least once a day Eat whole grains at least once a day Avoid soft drinks and other sugarsweetened beverages Drink tap water (filtered, unfiltered or boiled) Drink bottled water Drink low-fat milk or a milk alternative (e.g. soy, rice, or almond beverage) Eat packaged snack foods Local food (food that is grown or produced locally e.g. from a community garden, farm, or farmers market )  Disagree Disagree a They don’t Agree a Agree I’m not a lot little have an little a lot sure what opinion they think                                                                                     74) How much do you agree with the following statements? My parent(s) or primary caregiver(s) think I should...  Eat organic food Eat food that is grown or produced in an environmentally friendly way Stay fit and exercise Eat healthy food Compost Recycle Grow food plants grown at school, at home or in your community (for example in a garden, in balcony planters, or in an orchard or greenhouse) Eat food that is minimally processed (food without chemicals, preservatives, and processing e.g. brown rice, fresh fruit or nuts, roasted vegetables, baked beans) Bring my lunch from home whenever possible Eat in the cafeteria  Disagree Disagree They don’t Agree Agree I’m not a lot a little have an a little a lot sure opinion what they think                                                                                                 120  75) Are there any other issues about what you eat that are important to your parent(s) or primary caregiver(s)? __________________________________________________________________________________ __________________________________________________________________________________ ________________________________________________________ 76) The next set of questions asks about what your parent(s) or primary caregiver(s) do for work. Many students have a different number of people that they consider parents or primary caregivers. How many parents or primary caregivers do you live with?      1 2 3 4  77) Please tell us more about each parent or primary caregiver. Who are you going to tell us about?  My mother  My father  Other (e.g. my step-parent, grandparent, older sibling, etc.) 78) What is the highest level of education completed by this parent or primary caregiver?       Did not finish high school Finished high school Did some college/university or training after high school Finished a university or college degree or higher I don't know  79) What is their working status?      Not currently working for pay Works part-time for pay Works full-time for pay I don't know  80) What is their job? ____________________________________________________________ 81) Please tell us more about each parent or primary caregiver. Who are you going to tell us about?  My mother  My father  Other (e.g. my step-parent, grandparent, older sibling, etc.) 121  82) What is the highest level of education completed by this parent or primary caregiver?       Did not finish high school Finished high school Did some college/university or training after high school Finished a university or college degree or higher I don't know  83) What is their working status?      Not currently working for pay Works part-time for pay Works full-time for pay I don't know  84) What is their job? ____________________________________________________________ 85) Please tell us more about each parent or primary caregiver. Who are you going to tell us about?  My mother  My father  Other (e.g. my step-parent, grandparent, older sibling, etc.) 86) What is the highest level of education completed by this parent or primary caregiver?       Did not finish high school Finished high school Did some college/university or training after high school Finished a university or college degree or higher I don't know  87) What is their working status?      Not currently working for pay Works part-time for pay Works full-time for pay I don't know  88) What is their job? ____________________________________________________________ 89) Please tell us more about each parent or primary caregiver. Who are you going to tell us about?  My mother  My father 122   Other (e.g. my step-parent, grandparent, older sibling, etc.) 90) What is the highest level of education completed by this parent or primary caregiver?       Did not finish high school Finished high school Did some college/university or training after high school Finished a university or college degree or higher I don't know  91) What is their working status?      Not currently working for pay Works part-time for pay Works full-time for pay I don't know  92) What is their job? ____________________________________________________________ 93) How much do you agree with the following statements? Most of my close friends...  Disagree Disagree a Neither agree Agree a Agree a lot little nor disagree little a lot Eat vegetables at least once a day Eat whole grains at least once a day Avoid soft drinks and other sugarsweetened beverages Drink tap water (filtered, unfiltered or boiled) Drink bottled water Drink low-fat milk or a milk alternative (e.g. soy, rice, or almond beverage) Eat packaged snack foods Eat local food (food that is grown or produced locally e.g. from a community garden, farm, or farmers market )                 I'm not sure                                                                            94) How much do you agree with the following statements? Most of my close friends...  Disagree Disagree a lot a little Eat organic food Eat food that is grown or produced in an environmentally friendly way          Neither Agree Agree I'm agree nor a little a lot not disagree sure             123  Stay fit and exercise Eat healthy food Compost Recycle Grow food plants grown at school, at home or in your community (for example, in a garden, in balcony planters, or in an orchard or greenhouse) Eat food that is minimally processed (food without chemicals, preservatives, and processing e.g. brown rice, fresh fruit or nuts, roasted vegetables, baked beans) Bring their lunch from home whenever possible Eat in the cafeteria                                                                          95) Are there any other issues about what your friends eat that are important to your friends? __________________________________________________________________________________ __________________________________________________________________________________ ________________________________________________________ 96) At your school, when students dispose of the following items, what is the most environmentally friendly place to dispose each item available at your school?  Single-use plates from the cafeteria Napkins from the cafeteria Meat scraps Uneaten salad Plastic soft drink bottle Tetrapak (juice container) Milk container Orange peel Wooden chopsticks Polystyrene (eg. Styrofoam) container  Garbage Compost Recycling                                97) Please tell us if you think farmers grow the following foods in British Columbia.  Yes No I don't know where the food is grown I’m not familiar with this food     Bananas     Beans     Corn   Cranberries       Kale 124    Peppers Pineapples   Pumpkins            98) Does your school have any policies about the kinds of foods or drinks that are sold at your school? Please describe (e.g. what’s sold in vending machines, or in the cafeteria or what’s offered in meal programs) __________________________________________________________________________________ __________________________________________________________________________________ ________________________________________________________ 99) Do you think that you can influence your school’s policies and/or programs about food?       Very sure I cannot Somewhat sure I cannot Not sure whether I can or cannot Somewhat sure I can Very sure I can  100) How do you usually get to school? (Choose all that apply)       By foot (walking) By bicycle By public transit (e.g. bus or skytrain) By car Other (please specify)  If you selected other, please specify ______________________________________________________________________ 101) In a usual week, how many hours do you spend doing the following activities: Strenuous exercise (heart beats rapidly) Examples: biking fast, aerobic dancing, running, jogging, swimming laps, rollerblading, skating, lacrosse, tennis, cross-country skiing, soccer, basketball, football.        None Less than ½ hour a week ½-2 hours a week 2 ½ - 4 hours a week 4 ½ - 6 hours a week More than 6 hours per week  102) Moderate exercise (not exhausting) Examples: walking quickly, baseball, gymnastics, easy bicycling, volleyball, skiing, dancing, skateboarding, snowboarding  None  Less than ½ hour a week 125       ½-2 hours a week 2 ½ - 4 hours a week 4 ½ - 6 hours a week More than 6 hours per week  103) Mild exercise (little effort) Examples: walking slowly (to school, to a friend’s house, etc.), bowling, golf, fishing, snowmobiling, yoga        None Less than ½ hour a week ½-2 hours a week 2 ½ - 4 hours a week 4 ½ - 6 hours a week More than 6 hours per week  104) In the past 12 months:  Never Sometimes A lot Did the food that your family bought run out, and you didn't have money to get more? Were you not able to eat a balanced meal because your family didn't have enough money? Have you skipped a meal or has the size of your meals been cut because your family didn't have enough money for food? Did you have to eat less because your family didn't have enough money to buy food? Were you hungry but didn't eat because your family didn't have enough food?                                105) In general, would you say your health is:       Poor Fair Good Very Good Excellent  106) What is your height? '=feet "=inches              I don't know 3' 0'' or 91 cm or less 3' 1'' or 93 cm 3' 2'' or 96 cm 3' 3'' or 99 cm 3' 4'' or 101 cm 3' 5'' or 104 cm 3' 6'' or 106 cm 3' 7'' or 109 cm 3' 8'' or 111 cm 3' 9'' or 114 cm 3' 10'' or 116 cm 126                                     3' 4' 4' 4' 4' 4' 4' 4' 4' 4' 4' 4' 4' 5' 5' 5' 5' 5' 5' 5' 5' 5' 5' 5' 5' 6' 6' 6' 6' 6' 6' 6' 6' 6'  11'' or 119 cm 0'' or 121 cm 1'' or 124 cm 2'' or 127 cm 3'' or 129 cm 4'' or 132 cm 5'' or 134 cm 6'' or 137 cm 7'' or 139 cm 8'' or 142 cm 9'' or 144 cm 10'' or 147 cm 11'' or 149 cm 0'' or 152 cm 1'' or 154 cm 2'' or 157 cm 3'' or 160 cm 4'' or 162 cm 5'' or 165 cm 6'' or 167 cm 7'' or 170 cm 8'' or 172 cm 9'' or 175 cm 10'' or 177 cm 11'' or 180 cm 0'' or 182 cm 1'' or 185 cm 2'' or 187 cm 3'' or 190 cm 4'' or 193 cm 5'' or 195 cm 6'' or 198 cm 7'' or 200 cm 8'' or 203 cm or more  107) What is your weight? lbs=pounds kgs=kilograms                  I don't know 68 lbs or 31 kgs or less 69 lbs or 31 kgs 70 lbs or 32 kgs 71 lbs or 32 kgs 72 lbs or 33 kgs 73 lbs or 33 kgs 74 lbs or 34 kgs 75 lbs or 34 kgs 76 lbs or 34 kgs 77 lbs or 35 kgs 78 lbs or 35 kgs 79 lbs or 36 kgs 80 lbs or 36 kgs 81 lbs or 37 kgs 82 lbs or 37 kgs 127                                                        83 lbs or 38 kgs 84 lbs or 38 kgs 85 lbs or 39 kgs 86 lbs or 39 kgs 87 lbs or 39 kgs 88 lbs or 40 kgs 89 lbs or 40 kgs 90 lbs or 41 kgs 91 lbs or 41 kgs 92 lbs or 42 kgs 93 lbs or 42 kgs 94 lbs or 43 kgs 95 lbs or 43 kgs 96 lbs or 44 kgs 97 lbs or 44 kgs 98 lbs or 44 kgs 99 lbs or 45 kgs 100 lbs or 45 kgs 101 lbs or 46 kgs 102 lbs or 46 kgs 103 lbs or 47 kgs 104 lbs or 47 kgs 105 lbs or 48 kgs 106 lbs or 48 kgs 107 lbs or 49 kgs 108 lbs or 49 kgs 109 lbs or 49 kgs 110 lbs or 50 kgs 111 lbs or 50 kgs 112 lbs or 51 kgs 113 lbs or 51 kgs 114 lbs or 52 kgs 115 lbs or 52 kgs 116 lbs or 53 kgs 117 lbs or 53 kgs 118 lbs or 54 kgs 119 lbs or 54 kgs 120 lbs or 54 kgs 121 lbs or 55 kgs 122 lbs or 55 kgs 123 lbs or 56 kgs 124 lbs or 56 kgs 125 lbs or 57 kgs 126 lbs or 57 kgs 127 lbs or 58 kgs 128 lbs or 58 kgs 129 lbs or 59 kgs 130 lbs or 59 kgs 131 lbs or 59 kgs 132 lbs or 60 kgs 133 lbs or 60 kgs 134 lbs or 61 kgs 135 lbs or 61 kgs 128                                                        136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188  lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs  or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or  62 62 63 63 64 64 64 65 65 66 66 67 67 68 68 68 69 69 70 70 71 71 72 72 73 73 73 74 74 75 75 76 76 77 77 78 78 78 79 79 80 80 81 81 82 82 83 83 83 84 84 85 85  kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs 129                                                        189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241  lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs  or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or  86 kgs 86 kgs 87 kgs 87 kgs 88 kgs 88 kgs 88 kgs 89 kgs 89 kgs 90 kgs 90 kgs 91 kgs 91 kgs 92 kgs 92 kgs 93 kgs 93 kgs 93 kgs 94 kgs 94 kgs 95 kgs 95 kgs 96 kgs 96 kgs 97 kgs 97 kgs 98 kgs 98 kgs 98 kgs 99 kgs 99 kgs 100 kgs 100 kgs 101 kgs 101 kgs 102 kgs 102 kgs 103 kgs 103 kgs 103 kgs 104 kgs 104 kgs 105 kgs 105 kgs 106 kgs 106 kgs 107 kgs 107 kgs 108 kgs 108 kgs 108 kgs 109 kgs 109 kgs 130                                          242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280  lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs lbs  or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or or  110 110 111 111 112 112 112 113 113 114 114 115 115 116 116 117 117 117 118 118 119 119 120 120 121 121 122 122 122 123 123 124 124 125 125 126 126 127 127  kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs kgs or more  108) How satisfied are you with your current body shape and size?       Very dissatisfied Dissatisfied Neutral Satisfied Very satisfied  109) With which ethnic or cultural group(s) do you identify?  131  __________________________________________________________________________________ __________________________________________________________________________________ ________________________________________________________ 110) What language(s) do you usually speak at home? Choose all that apply                                      Amharic Arabic Cantonese Dutch English Fijian French German Greek Gujarati Hindi Italian Japanese Kirundi/Rundi Korean Mandarin Persian/Farsi Polish Portuguese Punjabi Romanian Russian Samoan Spanish Sundanese Swahili Swedish Tagalog Taiwanese Thai Tigrinya Ukrainian Urdu Vietnamese Other Other (please specify)  If you selected other, please specify ______________________________________________________________________ 111) In which country were you born?  Canada  Other (please specify)  132  If you selected other, please specify ______________________________________________________________________ 112) Were your parent(s) or primary caregiver(s) born in Canada?  Yes  No, one or more were born outside of Canada. Please list the country(ies) where they were born in "Additional comments": Additional comments ______________________________________________________________________ 113) What is the name of the street you currently live on? ____________________________________________________________ 114) What is the postal code where you live? ____________________________________________________________ 115) Are you currently doing any paid or unpaid work (other than school work)? For example, babysitting, work in your family's business or farm, a co-op program or work placement organized by your school, odd jobs, or at a job or business for pay such as working at a store or restaurant, or running your own business).  No  Yes 116) If yes, please describe the type of work you do: __________________________________________________________________________________ __________________________________________________________________________________ ________________________________________________________ 117) On average, how many dollars do you have at your disposal to spend as you wish (eg. on food, entertainment, etc.)? Please enter numbers only $____________________________________________________________per week 118) Are their any other reasons that you choose the foods you eat? Please check any of the following that apply:        Vegetarian or vegan Lactose intolerance Food intolerance (other than lactose) Health issues (e.g. diabetes, celiac disease) Religious reasons Other (please specify) 133  If you selected other, please specify ______________________________________________________________________ 119) If you consider yourself a vegetarian, what are your main reason(s) for eating a vegetarian diet? Choose all that apply           I don't consider myself a vegetarian Want a healthier diet To help the environment Religious reasons Do not want to kill animals A family member is vegetarian I don’t like the taste of meat To lose weight or keep from gaining weight Other (please specify)  If you selected other, please specify ______________________________________________________________________ 120) How do you feel about going to school?  I don't like school  I like school sometimes  I like school very much 121) Do you think health experts would say that most Canadian teens should be eating/drinking MORE of the following foods/beverages in order to be healthy?  No Yes I don't know    Vegetables    Red Meat    Whole fruit    High fibre foods    Low-fat milk    100% fruit juice    Water    Fried foods  Sugar-sweetened beverages (like soft drinks)    122) How strongly do you agree with the following statements? The types of food I eat affects:  My health The environment  Strongly disagree    Disagree    Neither agree nor disagree    Agree    Strongly agree   134  My weight How well I do in school Relationships with my friends                           123) How much do you care about….  Doing well in school Volunteering in your community How animals are treated before they are eaten How food choices impact the environment Making sure other families in your community have enough food to eat Where the food you eat comes from Being involved in extra-curricular activities at your school  Not at all      A little Somewhat bit          Very much                          135  Appendix B Sensitivity Analyses of Different Coding Options for Key Explanatory Variables  Comparing two coding options for highest parent education level Option 1: (0) less than high school (1) high school (2) some college (3) finished a college or university degree Option 2: (0) less than high school or high school (1) some college (2) finished a college or university degree  Summary In most comparisons, the two different coding options of parent education were consistent in their significance and direction of association with the outcomes (Tables 4-1 and 4-2). The 0-2 scale coding, which groups less than high school with high school educated parents (option 2), has been selected for further analysis as the primary explanatory variable due to the low sample size in the less than high school group.  Table 4-1 Unadjusted logistic regression of the association between parent education (4 groups) and dietary outcomes. Dietary outcomes (Daily intake =1) Packaged Whole grain Vegetable Low fat milk SSB Parent education snack foods <High school 1.13 0.64 0.61 1.81 2.00* [0.63,2.02] [0.29,1.43] [0.33,1.14] [0.60,5.51] [1.06,3.78] High school  0.80 [0.52,1.25]  0.72 [0.43,1.20]  1.31 [0.90,1.92]  1.55 [1.00,2.39]  1.42 [0.90,2.24]  Some college  1.00 [0.62,1.63]  1.29 [0.91,1.82]  1.00 [0.55,1.83]  1.07 [0.65,1.75]  0.90 [0.66,1.23]  1.00  1.00  1.00  1.00  1.00  675  670  663  681  672  College or university (Reference) N  136  Odds ratios; 95% confidence intervals in brackets * p < 0.05, ** p < 0.01, *** p < 0.001  Table 4-2 Unadjusted logistic regression of the association between parent education (3 groups) and dietary outcomes. Dietary outcomes (Daily intake = 1) Packaged Whole grain Vegetable Low fat milk SSB Parent education snack foods * High school or less 0.87 0.70 1.10 1.60 1.54* [0.59,1.28] [0.44,1.10] [0.78,1.56] [1.06,2.42] [1.09,2.18] Some college  1.00 [0.62,1.63]  1.29 [0.91,1.82]  1.00 [0.55,1.83]  1.07 [0.65,1.75]  0.90 [0.66,1.23]  1.00  1.00  1.00  1.00  1.00  675  670  681  672  College or university (Reference) N  *  Odds ratios; 95% confidence intervals in brackets p < 0.05,  663 **  p < 0.01,  ***  p < 0.001  Comparing coding options for food security status Option 1: A numeric variable - Total score from (0 – 5) Option 2: A dichotomous variable - Total score = (0 or 1) Food secure; (2-5) Food insecure with or without hunger Option 3: A 3-category variable - Total score = (0 or 1) Food secure; (2-4) Food insecure without hunger; (5) Food insecure with hunger  Summary In most comparisons, the 0-5 scale and dichotomous coding options of food security status were consistent in their significance and direction of association with the outcomes (Tables 4-3 and 4-4). The unadjusted associations between the 3 category coding option revealed non-significant associations between food security status and the dietary outcomes (Table 4-5). The small sample sizes in both the numeric and 3 category coding structures, the dichotomous coding of food security status was chosen. Table 4-6 and 4-7 demonstrate 137  the low proportion of the sample with a cumulative food insecurity score from 2 to 6, and in the food secure without and with hunger groups, respectively  Table 4-3 Unadjusted logistic regression of the association between food security status (total score from 0-5) and dietary outcomes. Dietary outcomes (Daily =1) Packaged Whole grain Vegetable Low fat milk SSB snack foods Food security index (0 – 5)  0.90*  1.03  1.15**  1.07  [0.81,0.99] [0.94,1.13] [1.04,1.28] [0.95,1.20] N 818 824 819 805 Odds Ratios; 95% confidence intervals in brackets * p < 0.05, ** p < 0.01, *** p < 0.001  1.01 [0.92,1.10] 830  Table 4-4 Unadjusted logistic regression of the association between food security status (dichotomous coding) and dietary outcomes. Dietary outcomes (Daily =1) Packaged Whole grain Vegetable Low fat milk SSB snack foods Food secure 1.00 1.00 1.00 1.00 1.00 (Reference) Food insecure (with or without 0.66* 1.12 1.70* 1.18 0.97 hunger) [0.44,0.98] [0.77,1.63] [1.08,2.68] [0.75,1.86] [0.70,1.34] N 818 824 819 805 830 * ** *** Odds Ratios; 95% confidence intervals in brackets p < 0.05, p < 0.01, p < 0.001  Table 4-5 Unadjusted logistic regression of the association between food security status (3 categories) and dietary outcomes. Dietary outcomes (Daily =1) Packaged Whole grain Vegetable Low fat milk SSB snack foods Food secure 1.00 1.00 1.00 1.00 1.00 (Reference) Food insecure 0.61 1.02 1.54 0.94 0.91 (without hunger) [0.35,1.05] [0.63,1.67] [0.87,2.72] [0.56,1.60] [0.55,1.51] Food insecure 0.73 1.28 1.97 1.64 1.05 (with hunger) [0.44,1.20] [0.73,2.22] [0.98,3.98] [0.87,3.07] [0.63,1.76] N 818 824 819 805 830 * ** *** Odds Ratios; 95% confidence intervals in brackets p < 0.05, p < 0.01, p < 0.001  138  Table 4-6 Distribution of food security status (total score from 0-5) Total score n (%) 0 618 (74.4) 1 82 (9.9) 2 29 (3.5) 3 34 (4.1) 4 14 (1.7) 5 54 (6.5) Note. Total n=950. Sample size varies between variables due to missing values.  Table 4-7 Distribution of food security status (3 categories) Food security status n (%) Food secure 700 (84.2) Food insecure without hunger 77 (9.3) Food insecure with hunger 54 (6.5) Note. Total n=950. Sample size varies between variables due to missing values.  Comparing two coding options for the psychosocial constructs (peer modeling and parental normative beliefs). Option 1: a numeric variable (0-4) “disagree a lot” – “agree a lot” Option 2: a categorical variable (0) “disagree a lot”, “disagree a little”, or “neutral” (1) “agree a little” or “agree a lot”  Summary In most comparisons, the two different coding options of peer modeling (Tables 4-8 and 4-9) and parental normative beliefs (Tables 4-10 and 4-11) were consistent in their significance and direction of association with most outcomes. Due to skewness of the numeric variable, it is difficult to interpret the association between the psychosocial variable and the outcome. For example, an increase from 0 to 1 on the psychosocial construct will have a different relationship with the outcome compared to an increase from 3 to 4 with the  139  outcome. The categorical coding of peer modeling and parental normative beliefs will be used in multiple regression models.  Table 4-8 Unadjusted logistic regression of the association between peer modeling items (numeric coding 0-4) and related dietary outcomes. Dietary intake outcomes Peer modeling items Vegetable intake  Vegetable  Whole grain  SSB  Low fat milk  Packaged snack foods  1.31*** [1.15,1.49]  Whole grain intake  1.43*** [1.22,1.67]  SSB avoidance  0.99 [0.86,1.14]  Low fat milk intake  1.15 [0.98,1.33]  Packaged snack food intake  0.99  N 834 833 830 804 Odds Ratios; 95% confidence intervals in brackets * p < 0.05, ** p < 0.01, *** p < 0.001  [0.81,1.22] 831  Table 4-9 Unadjusted logistic regression of the association between peer modeling items (categorical coding 0/1) and related dietary outcomes. Dietary intake outcomes Peer modeling items Vegetable intake  Vegetable  Whole grain  SSB  Low fat milk  Packaged snack foods  1.58*** [1.21,2.07]  Whole grain intake  1.81*** [1.34,2.45]  SSB avoidance Low fat milk intake  1.17 [0.86,1.60] 1.43* [1.02,2.00]  Packaged snack food intake N 834 833 830 804 Odds Ratios; 95% confidence intervals in brackets * p < 0.05, ** p < 0.01, *** p < 0.001  0.95 [0.62,1.44] 831  140  Table 4-10 Unadjusted logistic regression of association between parental normative belief items (numeric coding 0-4) and dietary outcomes. Dietary outcomes (Daily intake = 1) Parental Packaged Vegetable Whole grain SSB Low fat milk normative beliefs snack foods items Vegetable intake 1.65*** [1.38,1.98] Whole grain intake 1.79*** [1.49,2.15] SSB avoidance 0.85** [0.76,0.94] Low fat milk intake 1.11 [0.98,1.27] Packaged snack 1.26** food intake [1.08,1.47] N 871 873 862 839 861 * ** *** Odds Ratios; 95% confidence intervals in brackets p < 0.05, p < 0.01, p < 0.001  Table 4-11 Unadjusted logistic regression of association between parental normative belief items (categorical coding 0/1) and dietary outcomes. Dietary outcomes (Daily intake = 1) Parental Packaged Vegetable Whole grain SSB Low fat milk normative beliefs snack foods items Vegetable intake 2.41*** [1.51,3.86] Whole grain intake 2.48*** [1.72,3.58] SSB avoidance 0.66** [0.52,0.85] Low fat milk intake 1.22 [0.95,1.58] Packaged snack 1.68* food intake [1.11,2.53] N 871 873 862 839 861 * ** *** Odds Ratios; 95% confidence intervals in brackets p < 0.05, p < 0.01, p < 0.001  141  Appendix C Examining Other Measures of SES (Mother’s and Father’s Education, and Single Parent vs. 2 or More Parent Families)  Summary Mother’s highest education (Table 4-12) was significantly associated with student reported daily vegetable and fruit intake. Mother’s highest education was not significantly associated with the remaining dietary outcomes. Father’s highest education (Table 4-13) was not significantly associated with daily consumption of any of the food categories. Single parent vs. 2 or more parent families (Table 4-14) was not significantly associated with daily consumption of any of the food categories.  Table 4-12 Bivariate associations between mother’s highest education and dietary intake Dietary outcomes (Daily intake = 1) χ2 ; p-value Fruit intake χ2 =11.63; p=0.009 Vegetable intake χ2 =13.71; p=0.003 Whole grain intake χ2 =0.59; p=0.90 Low fat milk intake χ2 =0.95; p=0.81 Energy-dense processed food intake χ2 =6.02; p=0.11 Packaged snack food intake χ2 =4.02; p=0.26 SSB intake χ2 =4.97; p=0.17  Table 4-13 Bivariate associations between father’s highest education and dietary intake Dietary outcomes (Daily intake = 1) χ2 ; p-value Fruit intake χ2 =3.55; p=0.31 Vegetable intake χ2 =1.56; p=0.67 Whole grain intake χ2 =0.55; p=0.91 Low fat milk intake χ2 =4.16; p=0.25 Energy-dense processed food intake χ2 =4.04; p=0.26 Packaged snack food intake χ2 =2.77; p=0.43 SSB intake χ2 =1.14; p=0.77  142  Table 4-14 Bivariate associations between number of parents (single vs. 2 or more) and dietary intake Dietary outcomes (Daily intake = 1) χ2 ; p-value Fruit intake χ2 =0.28; p=0.60 Vegetable intake χ2 =0.70; p=0.40 Whole grain intake χ2 =0.01; p=0.92 Low fat milk intake χ2 =0.26; p=0.61 Energy-dense processed food intake χ2 =0.05; p=0.82 Packaged snack food intake χ2 =0.03; p=0.87 SSB intake χ2 =4.97; p=0.17  143  Appendix D Bivariate Analyses Summary Dietary outcomes examined to answer the main research objective were only those with a corresponding psychosocial factors (daily intake of vegetables, whole grains, low fat milk, packaged snack foods, and SSB). In bivariate analyses, parent’s highest education (coded from 0-2 “High school or less”, “Some college”, or “Finished a college or university degree”) was significantly associated with no dietary outcomes (Table 4-15). Food security status was significantly associated with daily vegetable and SSB intake (Table 4-16).  Table 4-15 Bivariate associations between parent education and dietary intake Dietary outcomes (Daily intake = 1) χ2 ; p-value Vegetable intake χ2 =5.65; p=0.06 Whole grain intake χ2 =0.47; p=0.79 Low fat milk intake χ2 =0.25; p=0.88 Packaged snack food intake χ2 =4.33; p=0.11 SSB intake χ2 =5.27; p=0.07  Table 4-16 Bivariate associations between food security status and dietary intake Dietary outcomes (Daily intake = 1) χ2 ; p-value Vegetable intake χ2 =4.31; p=0.04 Whole grain intake χ2 =0.34; p=0.56 Low fat milk intake χ2 =0.75; p=0.39 Packaged snack food intake χ2 =0.02; p=0.89 SSB intake χ2 =7.18; p=0.007  144  Appendix E Considering Other Explanatory Variables for Regression Model Summary Spending money, acculturation, and physical activity were significantly associated with neither parent education (Table 4-17) nor food security status (Table 4-18). BMI was significantly associated with food security status, but not parent education, the primary explanatory variable of interest. Therefore, BMI was also not included in the final regression models.  Table 4-17 Bivariate associations between parent education and ‘other explanatory variables’ for the regression model ‘Other explanatory variables’ χ2 ; p-value Spending money χ2 =3.01; p=0.800 Acculturation χ2 =8.85; p=0.07 Physical activity χ2 =3.77; p=0.15 BMI χ2 =6.34; p=0.39  Table 4-18 Bivariate associations between food security status and ‘other explanatory variables’ for the regression model ‘Other explanatory variables’ χ2 ; p-value Spending money χ2 =0.99; p=0.80 Acculturation χ2 =0.58; p=0.75 Physical activity χ2 =0.58; p=0.45 BMI χ2 =10.49; p=0.015  145  

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