Advertisement
BMC Nutrition volume 8, Article number: 116 (2022)
692
1
2
Metrics details
Good nutrition and access to healthy foods are essential for child growth and development. However, there are concerns that Canadian children do not have a healthy diet, which may be related to dietary choices as well as lack of access to healthy foods. The FANS (Food and Nutrition Security for Children and Youth) study examined the nutrition and food security status of youth in the province of Manitoba, Canada. This paper describes methods, dietary intakes, and body mass index for the FANS study.
This cross-sectional study included 1587 Manitoba grade nine students who completed a self-administered web-based survey. Data was collected on demographic characteristics, dietary intake (24-h recall), food behaviors, food security, and self-report health indicators. Dietary data was compared to national dietary guidelines (Dietary Reference Intakes and Canada’s Food Guide). Mean and median nutrient and food group intakes were calculated with corresponding measures of variability. Chi-square tests compared percentage of respondents not meeting key nutrients and food groups. Significant differences in percentage of total servings for each food group were determined by a Kruskal–Wallis test, and differences between different caloric groups were assessed using Dunn’s test for post-hoc comparisons.
Half of study respondents were female (50.5%). Median energy intake was higher in males (2281 kcal) compared with females (1662 kcal), with macronutrient distribution of 52%, 16%, and 32% for carbohydrates, protein, and fats respectively. Most participants consumed inadequate fibre (94%), vitamin D (90%), and calcium (73%), while median sodium intakes exceeded recommendations for males but not females. A majority of participants did not meet Health Canada’s recommendations for food group servings: Vegetables and Fruit (93%), Milk and Alternatives (74%), Meat and Alternatives (57%) and Grain Products (43%). Other Foods, including sugar sweetened beverages and juice, were consumed by most participants. Higher energy consumers had a greater proportion of food servings coming from Other Foods. 72.1% of students were classified as having a healthy weight and 25% were classified as overweight or obese.
Poor dietary intakes and body mass index values indicate an urgent need for policy and program strategies to support healthy eating habits and food awareness in Manitoba youth.
Peer Review reports
Diet is the largest contributor to mortality at a population level, ahead of other risk factors such as inactivity and smoking [1]. Food insecurity and nutrition insecurity are both strongly linked with poor diet (nutrition insufficiency) [2, 3]. Food security is the ability to access food without economic constraints [4]. Nutrition security includes addressing hunger, but also requires that foods contain sufficient nutrients, and people consume those foods rather than highly processed, low-nutrition foods [5]. Nutrition insecurity impacts populations who are food insecure and food secure; therefore, with continued growth in nutrition-sensitive conditions, both dimensions of food and nutrition security require addressing [6].
Poor diet is linked with a variety of poor health outcomes, including noncommunicable diseases (NCDs): type 2 diabetes, cardiovascular disease, cancer and respiratory disease account for over 80% of premature NCD deaths globally [7]. Type 2 diabetes is the most prominent NCD linked to diet [8, 9], and it is increasingly affecting young adults. One in ten Canadians over the age of one have been diagnosed with diabetes, and between 2000–2016 young adults aged 20–34 experienced a 41% increase [10]. Food insecure Canadians have more than double the risk of developing type 2 diabetes compared to food secure Canadians [11] and food insecure youth are at higher risk of developing mental health problems [12]. In 2021, 15.9% of Canadian households experienced food insecurity, including more than 1.3 million children [13].
The dietary risk factors for NCDs are well-established: calorie-dense diets high in sugar, salt, and fat primarily from ultra-processed foods, and low in fruits, vegetables, lean proteins and whole grains lead to increased body weight, high blood pressure, elevated blood lipids and glucose [14, 15]. There is increasing evidence that obesogenic diets are facilitated by food and social environments that support access to affordable highly processed food [16]; yet paradoxically promote the ‘thin ideal’ [17]. In Canada highly processed and fast food are consumed regularly, and are associated with higher body mass index [18,19,20].
Of particular concern are the dietary intakes of Canadian children and youth, many of whom appear to be on track for developing obesity and NCDs at earlier ages. Measured heights and weights from the 2019 Canadian Health Measures Survey indicate that 10.1% of children ages 5 to 17 are obese [21] and by 2030 it is predicted that 15% of children age 10–19 will be obese [22], with poor diet a significant risk factor. There are few studies of dietary intake in Canadian children and youth; however, evidence suggests that overall diet quality is poor [23, 24]. Further, 43% of adolescent Canadian girls report body weight dissatisfaction [25].
Canada has recently committed to a national food policy [26], including addressing food insecurity and a new food guide [27], setting the stage for population dietary health to become a key goal across diverse policy agendas. Adolescence is a critically important developmental stage for building awareness and behaviours that can promote nutritional health into adulthood. It is therefore critical that an empirical knowledge base of youth dietary habits be developed to inform programmatic and policy strategies aimed at improving diet quality. The purpose of this research, ‘Food and Nutrition Security for Manitoba Youth (FANS)’ is to create a knowledge base to support the development of adolescent nutrition policy and programming in the province of Manitoba, Canada. The FANS study collected information on the dietary intakes, food behaviors, food security status, self-reported health indicators and body mass index of a cohort of grade 9 students, as well as information on socio-demographic factors relevant to contextualizing observed dietary trends. This initial paper describes the methods for the FANS study, as well as dietary intakes and quality, and body mass index for all participants. Future papers will analyze remaining variables.
The study took place in the province of Manitoba, Canada which has a population of 1,278,365 [28]. The capital city of Winnipeg is the largest urban centre with 61% of the provincial population. The percentage of recent immigrants, or newcomers (5.1%), who arrived between 2011 and 2016 is almost 50% higher than the rest of Canada [29]. Manitoba has the highest provincial child poverty rate in Canada: 28.3% compared to 18.2% nationally [30].
Using a cross-sectional design, the study collected dietary intake, food behaviour and food security data using a web-based survey, from grade 9 students using a stratified two-stage sampling method as follows. First, the largest 18 of 37 provincial public school divisions were approached by email and follow-up phone calls to participate. Nineteen school divisions were excluded due to small numbers of grade 9 students and prohibitive data collection (travel) costs. Fourteen school divisions chose to participate, and all classes with ≥ 10 grade 9 students were approached. Participating class teachers distributed parent/guardian consent forms to all students. All students for whom consent was received had the opportunity to assent at the beginning of the online survey. The final study sample was 1587 participants, which represented 37% of eligible students in the 37 participating schools. Sampling details are outlined in Fig. 1. Data were collected between October 2018 and May 2019.
FANS sampling strategy
Demographic characteristic questions asked for participant age, sex/gender (male/female/other), self-reported Indigenous ancestry (First Nations, Métis, Inuit, don’t know) and age of arrival if not born in Canada. Indigeneity questions were developed with Indigenous academic and community partners. “Newcomer” was defined as being born outside Canada and moving to Canada within the past 7 years; this construct was developed with academic and settlement organization partners.
Participating school divisions, and respective schools, were classified into rural, urban and northern regions of the province, reflecting existing indicators of these classifications [31, 32].
Dietary intakes, food behaviours and health indicators were collected using the WEB-Q (Waterloo Eating Behaviour Questionnaire) [33]. WEB-Q is a valid, reliable tool for measuring the food and nutrient intake of adolescents using a 24-h dietary recall and food frequency questionnaire. The survey was administered on-site at schools and overseen by a research coordinator. Dietary intake was assessed through a 24-h recall module where students chose from a list of approximately 800 food items. Segmented into meals and snacks, students chose foods and beverages, and portion sizes, from pictures and associated text on the screen. A similar food was chosen if the original was not on the list. In addition to the recall, participants were asked about consumption frequency of sugar sweetened, caffeinated, and high protein beverages. Food behaviour assessment included questions about frequency of meal consumption, meals consumed with family members and food purchasing habits. Health indicators included questions about height and weight, attempts to lose or gain weight, and self-reported health and life satisfaction. Body mass index (BMI) was calculated using self-reported height and weight, and classified using World Health Organization z-scores [34]. Food security was assessed using the Child Food Security Survey Module validated for youth over 12 years of age [35]. The module consists of nine questions focused on access to food, concerns about food availability, modified eating behaviours, and hunger levels within the past twelve months [35].
A sub-set of students (n = 960) provided consent for FANS researchers to access de-identified provincial administrative health and socio-economic data using the student’s unique health number, through a Repository at the Manitoba Centre for Health Policy, University of Manitoba [36]. Dietary and survey data will be linked to income (neighbourhood level), mental health, housing and educational outcomes at the individual participant level and modelled for associations at the study population level in future papers [37].
Nutrient intakes were assessed using ESHA software (Salem, OR, 2002) [38] and the Canadian Nutrient File database [39]. Intakes were compared with Dietary Reference Intakes (DRI) [40]. Inadequacy estimates were calculated for nutrients using the Estimated Average Requirement approach (EAR) [41,42,43,44,45]. Adequate Intake (AI) was used for dietary fibre where EAR was not available [46]. Excess sodium intakes were assessed based on tolerable upper intake levels (UL) [44]. Macronutrients were compared with the Acceptable Macronutrient Distribution Ranges (AMDR) [46]. Food groups and servings were compared with Eating Well with Canada’s Food Guide (2007) (EWCFG) [47], which were based on portion sizes from Canadian Nutrient File definitions and databases [48].
Overall, 1571 students completed the diet recall. Records were manually checked for quality during the data collection period. Final line-level data were imported into SPSS software and verified for missing and biologically implausible values. Students’ dietary intake data were excluded from analyses if they consumed less than 200 kcal/day or exceeded 6000 kcal/day (n = 35) [49] which resulted in a final analytical sample of 1536. Records where a meal-specific food item was selected four times or more (due to slow internet connection in a few data collection sites) were visually inspected and deemed to represent an implausible selection of the item, as the ≥ 4 meal-specific food selections were inconsistent with other food selections for these records. This occurred in 28 instances and the intake was adjusted to 2 servings (the median number of servings chosen by the sample for the meal-specific food items in question).
Study data were analyzed using SAS version 9.4 (variable derivation) and SPSS version 27 (tables and statistical outputs) statistical software packages. Mean and median nutrient and food group intakes were calculated with corresponding measures of variability. Chi-square tests were performed to compare percentage of males and females not meeting key nutrient recommendations, and food group recommendations, and Cramer’s V was used as a measure of effect size. Data was checked for normality using the Shapiro–Wilk test. Significant differences in percentage total servings for each food group were determined by a Kruskal–Wallis non-parametric test and differences between the caloric intake groups were assessed using Dunn’s test for post-hoc comparisons. Statistical significance was accepted at p ≤ 0.05. All analyses were undertaken using unweighted sample data.
Half of study respondents (50.5%) were female and 44.7% were male, with 4.8% of study respondents self-identifying as “other” or not disclosing their sex (Table 1). These respondents were excluded from sex-dependent analyses. Participants ranged in age from 13–16 years with the majority (95.9%) in the 14- and 15-year-old categories. Over three-quarters (77.5%) were from urban areas of Manitoba.
Median energy intake for males was 2281 kcal and 1662 kcal for females (Table 2). One quarter of females consumed less than 1199 kcal while one quarter of males consumed less than 1736 kcal.
All study participants had adequate carbohydrate and protein intakes (Table 2). However, median fibre intake was inadequate for both sexes, with median intakes under half the recommended amount for males and just over half for females. Over 90% of respondents consumed inadequate fibre amounts (Fig. 2). Similarly, the majority of study participants consumed inadequate levels of vitamin D (90%) and calcium (70%) with a smaller proportion of males consuming inadequate levels of these nutrients compared to females. The majority of study participants consumed adequate levels of iron (75%). More than half of females did not meet recommendations for folate or zinc. Median sodium intakes exceeded recommendations for males but not for females, while median saturated fat intake as a percentage of total Energy exceeded recommendations for males and females. Average macronutrient distribution as proportion of total kilocalories for all participants was as follows: carbohydrates 52%; protein 16%; fats 32%.
Percentage of participants not meeting recommendations for select nutrients. EAR used for all micronutrients except for fiber (AI). For Total, participants not reporting sex (n = 72) were excluded for comparison with guidelines that vary by sex (fibre, iron, zinc). Bars represent the percentage of participants not meeting recommendations; whiskers represent 95% confidence intervals. p-values and Cramer’s V are for comparisons between sexes. Bars not sharing a similar letter (a,b) denote significant differences (p < 0.05)
The majority of respondents did not meet Health Canada’s recommendations for food group servings (Table 3). A statistically significant higher proportion of females compared to males were not consuming recommended servings of Grain Products (46.5% vs. 38.4%) and Milk and Alternatives (80.3% vs. 66.9%). Study participants averaged 4.5 servings (males) and 3.4 servings (females) of Other Foods (including beverages) outside the EWCFG four food groups.
Figure 3 and Table 4 show that respondents who consumed the most calories (above the 75th percentile in caloric intake distribution) obtained a significantly lower percentage of their total food group servings from Vegetables and Fruit (13.5%) and a higher percentage of servings from Other Foods (20.2%) and Sugar Sweetened Beverages and Juice (SSBs, 5.5%) than did respondents consuming the least calories (less than 25th percentile). The same trend was observed for both males and females (Table 4).
Mean percentage of food group servings contributing to total servings by energy intake group. Participant diet recalls were grouped according to whether their total caloric intake was below the 25th (1386 kcal), between 25 and 75th (1386–2608 kcal) or above 75th (2608 kcal) percentiles. Bars not sharing a similar letter (a,b) for specific food group denote significant differences (p < 0.05). SSBs: sugar sweetened beverages
Overall, 72.1% of students were classified as having a healthy BMI, with 25% classified as overweight or obese (Table 5). Significantly more males (9%) were classified as obese than females (5.9%). Four percent of males and 1.7% of females were classified as underweight.
This study is the most comprehensive review of dietary intake among Manitoba youth undertaken to date with significant implications for upstream adolescent nutrition programs and policies.
Results clearly demonstrate that Manitoba youth are consuming low intakes of key nutrients and food groups required for healthy growthy and development, with concomitant high intakes of nutrients and foods of public health concern. These findings are consistent with dietary patterns of youth observed in other jurisdictions [23], and indicate that Manitoba youth have dietary patterns that are putting them at serious risk for the development of chronic nutrition-related diseases in adulthood. The observation that over 25% of study participants are already overweight or obese reinforces that the negative trajectory toward future chronic illness is already in place in Manitoba youth. There is a sense of urgency here, as NCDs such as type 2 diabetes are no longer relegated to older adulthood, and are increasing dramatically in adolescents and young adults [50]. In Winnipeg, Manitoba’s largest city, it is projected that 5330 0–19 year olds will have diagnosed or undiagnosed diabetes by 2032, an expected increase of 29% since 2015 [51]. The data reported in this study also indicate that youth may be at risk for developing poor mental health related to body image, as body weight is a significant factor in youth mental well-being due to societal pressures for young women and men to have flawless bodies and be hyper-fit [52,53,54,55].
More than half of participants did not meet recommendations for food group intake the previous day for three out of four EWCFG food groups. Of particular concern, almost none of the participants consumed the recommended servings of Vegetables and Fruit, and three-quarters of females had inadequate Milk and Alternatives. Although mean intake of Vegetables and Fruit were below those reported from the 2015 Canadian Community Health Survey (CCHS; Nutrition, 13–17 years), servings for Grain Products, Milk and Alternatives, Meat and Alternatives were similar [56]. At the same time, participants consumed Other Foods and beverages outside the EWCFG four food groups [57], a similar pattern observed with adolescents elsewhere in Canada [24, 58, 59].
Students with higher energy intakes are obtaining additional kilocalories from less nutritious sources. This is not surprising, as foods such as salty snacks, candy and sweets, and sugar sweetened beverages are convenient, mostly ready-to-eat, and are among the foods most aggressively marketed to youth [60,61,62], due to their high differential profit margins [63]. In Canada, youth consume a significant number of calories from sugar sweetened beverages/juice [64].
Energy intakes observed for both males and females were similar to those reported in the 2015 CCHS (Nutrition) [65]. Both male and female respondents in the lowest quartile reported very low energy intakes. This could be a result of measurement error, a well-established observation in self-reported dietary studies, which tend to underestimate energy intake, often due to reporting bias. The same trend was been observed in the CCHS (Nutrition), where the 2015 data showed an almost 200 kcal decrease over the previous 2004 survey [66]. The low-calorie intakes observed may also be indicative of widespread diet culture, including body image dissatisfaction and attempts at weight loss/restriction [67, 68]. More research is required to understand the relationships between diet culture and diet quality.
Intake of a number of key nutrients were observed to be inadequate for boys and/or girls including fibre, vitamin D, calcium, zinc and folate. Adequate intake of fibre and micronutrients are essential for optimal growth and development, as well as for reduction of risk for nutrition-related chronic diseases such as type 2 diabetes, heart disease and cancer [69,70,71]. Of particular concern for young women is low folate intake, as this is associated with increased risk of low birthweight and birth defects [72]. Low vitamin D and calcium consumption in Manitoba are of particular concern, as the high latitude and cold climate preclude cholecalciferol skin synthesis for much of the year, and vitamin D-fortified milk is prohibitively expensive in many northern and remote communities. At the same time, sodium and saturated fat intakes were above recommended upper limits for the majority of participants, noted in other Canadian dietary intake data [73, 74]. Notably, significantly more males did not meet recommendations for vitamin D, iron, folate, calcium and zinc. This suggests that, although their caloric needs and intake are higher, the nutritional quality of the foods eaten by the group is sub-optimal.
The dietary patterns shown in this study may be associated with the high rates of overweight and obesity observed in this study, which are consistent with the most recent national statistics reporting 6.2% of 12–17 year-olds having obesity and 16.9% having overweight [75]. Further research, however, is warranted to identify specific dietary patterns and their association to body weight.
The sub-optimal consumption of Vegetables and Fruits, and Milk and Alternatives in particular, as well as other healthy foods observed in this study, may be indicative of food insecurity in segments of the adolescent population. Food security is inversely associated with income [76]. Manitoba has the highest child poverty rate in Canada, at 31.6% (12% above the national average) [30]. This may be higher now due to the negative economic impacts of COVID-19 [77].
There are several limitations to this research. First, the 24-h dietary recall and food frequency questions are self-reported and subject to recall error; inaccurate estimation of portion size; do not reflect day-to-day variability of individuals’ food intake; and may produce socially-desirable responses (e.g., reporting of less “junk” food and more “healthy” food) [78,79,80,81]. The web-based tool used for data collection, however, may have minimized the impact of some of these limitations through the use of graphic food images and prompts to enhance respondent memory [58]. Further, the 24-h recall method is an accepted and valid method for dietary assessment [82]. Second, some volunteer bias may be present, as not all schools participated, and parents needed to consent to having their child participate. Nonetheless, food patterns and nutrient intakes were similar to those observed in other Canadian regions, in similar populations. Finally, it is well-established that self-report measures yield bias, with height overestimated and weight underestimated [83]. Consequently, BMI results presented here may reflect underestimates of overweight and obesity. Despite these limitations, the FANS study presents an in-depth examination of adolescent nutrition, food behaviour and food security in a Canadian province, using a large sample. Further research is needed to examine food and eating behaviours, diet quality, and the role of food insecurity in dietary patterns, regional and other socio-demographic variations in dietary patterns. These will be examined in further research studies emerging from the FANS study. Additional studies will model linked administrative data to survey and dietary data.
The dietary patterns observed in this study signal cause for concern: too many adolescents are consuming a diet that puts them at risk for future health issues. Indeed, the emergence of NCDs, such as type 2 diabetes in younger age cohorts suggests a crisis is upon us. Further, the COVID pandemic has revealed the insidious linkages between chronic and infectious disease, where obesity and metabolic risk factors are contributing to significant predisposing conditions now understood to increase the risk of serious illness and death due to COVID-19 and variants [84].
Major policy and program strategies must be investigated, championed at the highest levels, and funded to reverse the alarming trend in dietary patterns and other risk factors for nutrition-related illness. This could be undertaken by a provincial task force with stakeholders representing diverse sectors including education, health, social welfare and business. For too long the mantra of individual/parental responsibility, along with concerns about financial implications of population preventive strategies, have been the fall-back discourse of politicians and other key decision-makers. Considering that in 2016 alone, diagnosed, undiagnosed and pre-diabetes in the 20–34 year old Winnipeg population was estimated to cost over $14 million, a re-examination of strategic prevention approaches is clearly warranted [85].
The datasets generated during and/or analysed during the current study are not publicly available due to the nature of the research and study participants not agreeing for their data to be shared with the public. Queries about data and materials should be directed to joyce.slater@umanitoba.ca.
Noncommunicable diseases
Food and Nutrition Security for Manitoba Youth
Waterloo Eating Behaviour Questionnaire
Body Mass Index
Dietary Reference Intakes
Estimated Average Requirement
Adequate Intake
Tolerable Upper Intake Levels
Acceptable Macronutrient Distribution Range
Eating Well with Canada’s Food Guide
Sugar Sweetened Beverages and Juice
Canadian Community Health Survey
Afshin A, Sur PJ, Fay KA, Cornaby L, Ferrara G, Salama JS, et al. Health effects of dietary risks in 195 countries, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2019;393(10184):1958–72.
Article Google Scholar
Kirkpatrick S, Dodd KW, Parsons R, Ng C, Garriguet D, Tarasuk V. Household food insecurity is a stronger marker of adequacy of nutrient intakes among Canadian compared to American youth and adults. J Nutr. 2015;145(7):1596–603. https://doi.org/10.3945/jn.114.208579.
Article CAS PubMed PubMed Central Google Scholar
Nardocci M, Polsky JY, Moubarac JC. Consumption of ultra-processed foods is associated with obesity, diabetes and hypertension in Canadian adults. Can J Public Health. 2021;112(3):421–9. https://doi.org/10.17269/s41997-020-00429-9.
Article PubMed Google Scholar
PROOF. Household Food Insecurity in Canada. https://proof.utoronto.ca/food-insecurity/. Accessed 17 Sept 2022.
Ingram J. Nutrition security is more than food security. Nat Food. 2020;1(2):2020. https://doi.org/10.1038/s43016-019-0002-4.
Article Google Scholar
Mozaffarian D, Fleischhacker S, Andrés JR. Prioritizing nutrition security in the US. JAMA. 2021;325(16):1605–6.
Article Google Scholar
Forouzanfar MH, Afshin A, Alexander LT, Biryukov S, Brauer M, Cercy K, et al. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388(10053):1659–724. https://doi.org/10.1016/S0140-6736(16)31679-8.
Article Google Scholar
Al-Goblan AS, Al-Alfi MA, Khan MZ. Mechanism linking diabetes mellitus and obesity. Diabetes Metab Syndr Obes. 2014;7:587–91. https://doi.org/10.2147/DMSO.S67400.
Article PubMed PubMed Central Google Scholar
Lin X, Xu Y, Pan X, Xu J, Ding Y, Sun X, et al. Global, regional, and national burden and trend of diabetes in 195 countries and territories: an analysis from 1990 to 2025. Sci Rep. 2020;10:14790. https://doi.org/10.1038/s41598-020-71908-9.
Article CAS PubMed PubMed Central Google Scholar
Public Health Agency of Canada. Canadian Chronic Disease Surveillance System (CCDSS), Data Tool 2000–2016, 2018 Edition. 2019. https://health-infobase.canada.ca/ccdss/data-tool/Index?G=00&V=1&M=5&Y=2016 Accessed 8 Feb 2022.
Tait CA, L’Abbé MR, Smith PM, Rosella LC. The association between food insecurity and incident type 2 diabetes in Canada: a population-based cohort study. PLoS One. 2018;13(5):1–14. https://doi.org/10.1371/journal.pone.0195962.
Article CAS Google Scholar
Men F, Elgar FJ, Tarasuk V. Food insecurity is associated with mental health problems among Canadian youth. J Epidemiol Community Health. 2021;75:741–8. https://doi.org/10.1136/jech-2021-216938.
Article PubMed Google Scholar
Tarasuk V, Li T, Fafard SAA. Household food insecurity in Canada, 2021. 2022. https://proof.utoronto.ca/resource/household-food-insecurity-in-canada-2021/ Accessed 17 Sep 2022.
Google Scholar
Peters R, Ee N, Peters J, Beckett N, Booth A, Rockwood K, et al. Common risk factors for major noncommunicable disease, a systematic overview of reviews and commentary: the implied potential for targeted risk reduction. Ther Adv Chronic Dis. 2019;10:1–14. https://doi.org/10.1177/2040622319880392.
Article CAS Google Scholar
Grosso G. Impact of nutritional risk factors on chronic non-communicable diseases. Eur J Public Health. 2019;29(Suppl 4):77. https://doi.org/10.1093/eurpub/ckz185.197.
Article Google Scholar
Branca F, Lartey A, Oenema S, Aguayo V, Stordalen GA, Richardson R, et al. Transforming the food system to fight non-communicable diseases. BMJ. 2019;28(364):l296. https://doi.org/10.1136/bmj.l296.
Article Google Scholar
Knobloch-Westerwick S, Crane J. A losing battle: effects of prolonged exposure to thin-ideal images on dieting and body satisfaction. Communic Res. 2012;39(1):79–102. https://doi.org/10.1177/0093650211400596.
Article Google Scholar
Vanderlee L, L’Abbé MR. Commentary – Food for thought on food environments in Canada. Heal Promot Chronic Dis Prev Canada. 2017;37(9):263–5. https://doi.org/10.24095/hpcdp.37.9.01.
Article Google Scholar
Moubarac JC. Ultra-processed foods in Canada: consumption, impact on diet quality and policy implications. 2017. https://www.heartandstroke.ca/-/media/pdf-files/canada/media-centre/hs-report-upp-moubarac-dec-5-2017.ashx Accessed 8 Feb 2022.
Google Scholar
Hack S, Jessri M, L’Abbé MR. Evaluating diet quality of Canadian adults using health Canada’s surveillance tool tier system: findings from the 2015 Canadian Community Health Survey-Nutrition. Nutrients. 2020;12(4):1113. https://doi.org/10.3390/nu12041113.
Article CAS PubMed Central Google Scholar
Statistics Canada. able 13–10–0373–01 Overweight and obesity based on measured body mass index, by age group and sex. 2021. https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1310037301&pickMembers%5B0%5D=3.1&cubeTimeFrame.startYear=2011&cubeTimeFrame.endYear=2019&referencePeriods=20110101%2C20190101 Accessed 8 Feb 2022.
Google Scholar
Lobstein T, Brinsden H. Global Atlas of Childhood Obesity. World Obesity. 2019. https://www.worldobesity.org/membersarea/global-atlas-on-childhood-obesity Accessed 8 Feb 2022.
Google Scholar
Tugault-Lafleur CN, Barr SI, Black JL. Examining differences in school hour and school day dietary quality among Canadian children between 2004 and 2015. Public Health Nutr. 2019;22(16):3051–62. https://doi.org/10.1017/S1368980019000788.
Article PubMed Google Scholar
Tugault-Lafleur CN, Black JL, Barr SI. Examining school-day dietary intakes among Canadian children. Appl Physiol Nutr Metab. 2017;42(10):1064–72. https://doi.org/10.1139/apnm-2017-0125.
Article CAS PubMed Google Scholar
Al Sabbah H, Vereecken CA, Elgar FJ, Nansel T, Aasvee K, Abdeen Z, et al. Body weight dissatisfaction and communication with parents among adolescents in 24 countries: international cross-sectional survey. BMC Public Health. 2009;9:52. https://doi.org/10.1186/1471-2458-9-52.
Article PubMed PubMed Central Google Scholar
Agriculture and Agri-Food Canada. The Food Policy for Canada. https://agriculture.canada.ca/en/about-our-department/key-departmental-initiatives/food-policy/food-policy-canada. Accessed 17 Sept 2022.
Health Canada. Canada’s Food Guide. 2019. https://food-guide.canada.ca/en/ Accessed 8 Feb 2022.
Google Scholar
Statistics Canada. Manitoba and Canada. Census Profile. 2016 Census; 2017. https://www12.statcan.gc.ca/census-recensement/2016/dp-pd/prof/index.cfm?Lang=E. Accessed 8 Feb 2022.
Statistics Canada. Focus on Geography Series, 2016 Census – Immigration and ethnocultural diversity. 2017. https://www12.statcan.gc.ca/census-recensement/2016/as-sa/fogs-spg/Facts-PR-Eng.cfm?TOPIC=7&LANG=Eng&GK=PR&GC=46 Accessed 8 Feb 2022.
Google Scholar
Frankel S, Brandon J, Vyrauen K, Assembly of Manitoba Chiefs First Nations Family Advocate Office, Erbus M, Champagne MR, et al. Manitoba: Poverty Central. 2020. https://campaign2000.ca/wp-content/uploads/2020/12/Manitoba-Poverty-Central-2020-Report-Update-1.pdf Accessed 8 Feb 2022.
Google Scholar
Fransoo R, Martens P, Prior H, Burchill CA, Koseva I, Bailly A, et al. The 2013 RHA Indicators Atlas. Manitoba Centre for Health Policy. 2013. http://mchp-appserv.cpe.umanitoba.ca/reference/RHA_2013_web_version.pdf Accessed 8 Feb 2022.
Google Scholar
Chartier M, Bolton J, Mota N, MacWilliam L, Ekuma O, Nie Y, et al. Mental Illness Among Adult Manitobans. Manitoba Centre for Health Policy. 2018. http://mchp-appserv.cpe.umanitoba.ca/reference/mh2015_Report_web.pdf Accessed 8 Feb 2022.
Google Scholar
Hanning RM, Royall D, Toews JE, Blashill L, Wegener J, Driezen P. Web-based Food Behavior Questionnaire: validation with grades six to eight students. Can J Diet Pract Res. 2009;70(4):172–8. https://doi.org/10.3148/70.4.2009.172.
Article PubMed Google Scholar
Rodd C, Metzger DL, Sharma A, Cummings E, Chanoine JP, Lawrence S, et al. Extending World Health Organization weight-for-age reference curves to older children. BMC Pediatr. 2014;14(32):1–7. https://doi.org/10.1186/1471-2431-14-32.
Article Google Scholar
Connell CL, Nord M, Lofton KL, Yadrick K. Food security of older children can be assessed using a standardized survey instrument. J Nutr. 2004;134(10):2566–72. https://doi.org/10.1093/jn/134.10.2566.
Article CAS PubMed Google Scholar
Roos NP, Roos LL. Administrative data and the Manitoba Centre for Health Policy: some reflections. Health Policy. 2011;6(Sp):16–28.
Google Scholar
Brownell M, Kozyrskyj A, Fuchs D, Santos R. Using administrative data to study child health. Heal Policy. 2011;6:91–3.
Google Scholar
ESHA Research. The Food Processor, Nutrition Analysis and Fitness Software (Version 8.0). Salem OR: ESHA Research. 2002.
Health Canada. Canadian Nutrient File. 2006. https://food-nutrition.canada.ca/cnf-fce/index-eng.jsp Accessed 8 Feb 2022.
Google Scholar
Government of Canada. Dietary Reference Intakes. https://www.canada.ca/en/health-canada/services/food-nutrition/healthy-eating/dietary-reference-intakes/tables.html Accessed 8 Feb 2022.
Institute of Medicine. Dietary Reference Intakes for Vitamin C, Vitamin E, Selenium, and Carotenoids (2000). Washington: The National Academies Press; 2000. https://doi.org/10.17226/13050.
Book Google Scholar
Institute of Medicine. Dietary Reference Intakes for Thiamin, Riboflavin, Niacin, Vitamin B6, Folate, Vitamin B12, Pantothenic Acid, Biotin, and Choline. Washington: The National Academies Press; 1998. https://doi.org/10.17226/6015.
Book Google Scholar
Institute of Medicine. Dietary Reference Intakes for Vitamin A, Vitamin K, Arsenic, Boron, Chromium, Copper, Iodine, Iron, Manganese, Molybdenum, Nickel, Silicon, Vanadium, and Zinc. Washington: The National Academies Press; 2001. https://doi.org/10.17226/10026.
Book Google Scholar
National Academies of Sciences, Engineering, and Medicine. Dietary Reference Intakes for Sodium and Potassium. Washington: The National Academies Pres; 2019. https://doi.org/10.17226/25353.
Institute of Medicine. Dietary Reference Intakes for Calcium and Vitamin D. Washington: The National Academies Press; 2011. https://doi.org/10.17226/13050.
Book Google Scholar
Institute of Medicine. Dieteary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids. Washington: he National Academies Press; 2005. https://doi.org/10.17226/10490.
Book Google Scholar
Health Canada. Eating Well with Canada’s Food Guide. 2007. https://www.canada.ca/en/health-canada/services/canada-food-guide/about/history-food-guide/eating-well-with-canada-food-guide-2007.html. Accessed 8 Feb 2022.
Hanning RM, Luan H, Orava TA, Valaitis RF, Jung JKHH, Ahmed R. Exploring student food behaviour in relation to food retail over the time of implementing Ontario’s school food and beverage policy. Int J Environ Res Public Health. 2019;16(14):2563. https://doi.org/10.3390/ijerph16142563.
Article PubMed Central Google Scholar
Woodruff SJ, Campbell K, Campbell T, Cole M. The associations of meals and snacks on family meals among a sample of grade 7 students from Southwestern Ontario. Appetite. 2014;82:61–6. https://doi.org/10.1016/j.appet.2014.07.017.
Article PubMed Google Scholar
Lascar N, Brown J, Pattison H, Barnett AH, Bailey CJ, Bellary S. Type 2 diabetes in adolescents and young adults. Lancet Diabetes Endocrinol. 2018;6(1):69–80. https://doi.org/10.1016/S2213-8587(17)30186-9.
Article PubMed Google Scholar
Manitoba Collaborative Data Portal. Projections of Diabetes, Undiagnosed Diabetes and Pre-Diabetes Cases and Costs, Winnipeg Health Region, 2016–203. 2019. https://public.tableau.com/profile/manitoba.collaborative.data.portal#!/vizhome/DiabProj1_15771373036700/Dashboard1 Accessed 8 Feb 2022.
Google Scholar
Murray K, Rieger E, Byrne D. Body image predictors of depressive symptoms in adolescence. J Adolesc. 2018;69:130–9. https://doi.org/10.1016/j.adolescence.2018.10.002.
Article PubMed Google Scholar
Kelly Y, Zilanawala A, Booker C, Sacker A. Social media use and adolescent mental health: findings from the UK Millennium Cohort Study. EClinicalMedicine. 2018;6:59–68. https://doi.org/10.1016/j.eclinm.2018.12.005.
Article PubMed Google Scholar
Marengo D, Longobardi C, Fabris MA, Settanni M. Highly-visual social media and internalizing symptoms in adolescence: the mediating role of body image concerns. Comput Human Behav. 2018;82:63–9. https://doi.org/10.1016/j.chb.2018.01.003.
Article Google Scholar
Shriver LH, Dollar JM, Calkins SD, Keane SP, Shanahan L, Wideman L. Emotional eating in adolescence: effects of emotion regulation, weight status and negative body image. Nutrients. 2021;13(1):1–12. https://doi.org/10.3390/nu13010079.
Article Google Scholar
Tugault-Lafleur CN, Black JL. Differences in the quantity and types of foods and beverages consumed by Canadians between 2004 and 2015. Nutrients. 2019;11(3):526. https://doi.org/10.3390/nu11030526.
Article CAS PubMed Central Google Scholar
Katamay SW, Esslinger KA, Vigneault M, Johnston JL, Junkins BA, Robbins LG, et al. Eating Well with Canada’s Food Guide (2007): development of the Food Intake Pattern. Nutr Rev. 2007;65(4):155–66. https://doi.org/10.1111/j.1753-4887.2007.tb00295.x.
Article PubMed Google Scholar
Hanning RM, Woodruff SJ, Lambraki I, Jessup L, Driezen P, Murphy CC. Nutrient intakes and food consumption patterns among Ontario students in grades six, seven and eight. Can J Public Heal. 2007;98(1):12–6. https://doi.org/10.1007/BF03405377.
Article Google Scholar
Wadsworth LA, McHugh TL, Thompson AM, Campagna PD, Durant MA, Murphy RJLL, et al. Dietary intake of Nova Scotia youth in grades 7 and 11. Can J Diet Pract Res. 2012;73(1):14–20. https://doi.org/10.3148/73.1.2012.14.
Article PubMed Google Scholar
Czoli CD, Pauzé E, Potvin KM. Exposure to food and beverage advertising on television among Canadian adolescents, 2011 to 2016. Nutrients. 2020;12(2):1–13. https://doi.org/10.3390/nu12020428.
Article Google Scholar
Potvin Kent M, Wanless A. The influence of the Children’s Food and Beverage Advertising Initiative: change in children’s exposure to food advertising on television in Canada between 2006–2009. Int J Obes. 2014;38(4):558–62. https://doi.org/10.1038/ijo.2014.4.
Article CAS Google Scholar
Pinto A, Pauzé E, Mutata R, Roy-Gagnon MH, Kent MP. Food and beverage advertising to children and adolescents on television: a baseline study. Int J Environ Res Public Health. 2020;17(6):1999. https://doi.org/10.3390/ijerph17061999.
Article PubMed Central Google Scholar
Winson A. Bringing political economy into the debate on the obesity epidemic. Agric Human Values. 2004;21(4):299–312. https://doi.org/10.1007/s10460-003-1206-6.
Article Google Scholar
Jones AC, Kirkpatrick SI, Hammond D. Beverage consumption and energy intake among Canadians: analyses of 2004 and 2015 national dietary intake data. Nutr J. 2019;18(1):1–14. https://doi.org/10.1186/s12937-019-0488-5.
Article CAS Google Scholar
Statistics Canada. Table 13–10–0772–01 Total energy intake from foods, by dietary reference intake age-sex group, household population aged 1 and over, Canadian Community Health Survey (CCHS) – Nutrition, Canada and provinces. 2021. https://doi.org/10.25318/1310077201-eng.
Book Google Scholar
Garriguet D. Accounting for misreporting when comparing energy intake across time in Canada. Health Reports. 2018;29(5):i–12.
Google Scholar
Rodgers RF, McLean SA, Marques M, Dunstan CJ, Paxton SJ. Trajectories of body dissatisfaction and dietary restriction in early adolescent girls: a latent class growth analysis. J Youth Adolesc. 2016;45(8):1664–77. https://doi.org/10.1007/s10964-015-0356-3.
Article PubMed Google Scholar
Findlay SM, Canadian Paediatric Society, Adolescent Health Committee. Dieting in adolescence. Paediatr Child Health. 2004;9(7):487–91. https://doi.org/10.1093/pch/9.7.487.
Article Google Scholar
Pereira MA, O’Reilly E, Augustsson K, Brown MM. Dietary fiber and risk of coronary heart disease. Evidence-Based Eye Care. 2004;5(4):226–7. https://doi.org/10.1001/archinte.164.4.370.
Article Google Scholar
Weickert MO, Pfeiffer AFH. Impact of dietary fiber consumption on insulin resistance and the prevention of type 2 diabetes. J Nutr. 2018;148(1):7–12. https://doi.org/10.1093/jn/nxx008.
Article PubMed Google Scholar
Zheng B, Shen H, Han H, Han T, Qin Y. Dietary fiber intake and reduced risk of ovarian cancer: a meta-analysis. Nutr J. 2018;17(1):17–22. https://doi.org/10.1186/s12937-018-0407-1.
Article CAS Google Scholar
Bailey LB, Stover PJ, McNulty H, Fenech MF, Gregory JF, Mills JL, et al. Biomarkers of nutrition for development-folate review. J Nutr. 2015;145(7):1636S–80S. https://doi.org/10.3945/jn.114.206599.
Article CAS PubMed PubMed Central Google Scholar
Health Canada. Sodium Intake of Canadians in 2017. 2018. https://www.canada.ca/en/health-canada/services/publications/food-nutrition/sodium-intake-canadians-2017.html Accessed 8 Feb 2022.
Google Scholar
Harrison S, Brassard D, Lemieux S, Lamarche B. Consumption and sources of saturated fatty acids according to the 2019 Canada food guide: data from the 2015 Canadian Community Health Survey. Nutrients. 2019;11(9):1964. https://doi.org/10.3390/nu11091964.
Article PubMed Central Google Scholar
Statistics Canada. Overweight and obese youth (self-reported), 2014. 2015. https://www150.statcan.gc.ca/n1/pub/82-625-x/2015001/article/14186-eng.htm Accessed 8 Feb 2022.
Google Scholar
PROOF. More Canadians are Food Insecure Than Ever Before – and the Problem is Only Getting Worse. 2020. https://proof.utoronto.ca/more-canadians-are-food-insecure-than-ever-before-and-the-problem-is-only-getting-worse/. Accessed 8 Feb 2022.
Gu W. Economic Impact of the COVID-19 Pandemic on Canadian Businesses across Firm Size Classes. 2020. https://www150.statcan.gc.ca/n1/pub/11-626-x/11-626-x2020017-eng.htm Accessed 8 Feb 2022.
Google Scholar
McPherson RS, Hoelscher DM, Alexander M, Scanlon KS, Serdula MK. Dietary assessment methods among school-aged children: validity and reliability. Prev Med. 2000;31:S11–33. https://doi.org/10.1006/pmed.2000.0631.
Article Google Scholar
Natarajan L, Pu M, Fan J, Levine RA, Patterson RE, Thomson CA, et al. Measurement error of dietary self-report in intervention trials. Am J Epidemiol. 2010;172(7):819–27. https://doi.org/10.1093/aje/kwq216.
Article PubMed PubMed Central Google Scholar
Freedman LS, Midthune D, Carroll RJ, Krebs-smith S, Subar AF, Troiano RP, et al. Adjustments to improve the estimation of usual dietary intake distributions in the population. Am Soc Nutr Sci. 2004;134(7):1836–43. https://doi.org/10.1093/jn/134.7.1836.
Article CAS Google Scholar
Hebert JR, Hurley TG, Peterson KE, Resnicow K, Thompson FE, Yaroch AL, et al. Social desirability trait influences on self-reported dietary measures among diverse participants in a multicenter multiple risk factor trial. J Nutr. 2008;138(1):226S-234S. https://doi.org/10.1093/jn/138.1.226S.
Article CAS PubMed Google Scholar
Subar AF, Freedman LS, Tooze JA, Kirkpatrick SI, Boushey C, Neuhouser ML, et al. Addressing current criticism regarding the value of self-report dietary data. J Nutr. 2015;145(12):2639–45. https://doi.org/10.3945/jn.115.219634.
Article CAS PubMed PubMed Central Google Scholar
Shields M, Gorber SC, Janssen I, Tremblay MS. Bias in self-reported estimates of obesity in Canadian health surveys: an update on correction equations for adults. Heal Reports. 2011;22(3):200. https://doi.org/10.1016/S1499-2671(11)52226-9.
Article Google Scholar
Mauvais-Jarvis F. Aging, male sex, obesity, and metabolic inflammation create the perfect storm for COVID-19. Diabetes. 2020;69(9):1857–63. https://doi.org/10.2337/dbi19-0023.
Article CAS PubMed PubMed Central Google Scholar
Manitoba Collaborative Data Portal. Estimated Diagnosed Diabetes, Undiagnosed Diabetes and PreDiabetes Cases, Winnipeg Health Region, 2016. 2020. https://public.tableau.com/profile/manitoba.collaborative.data.portal#!/vizhome/Diabetes_Jan3_20_ver6/Dashboard1 Accessed 8 Feb 2022.
Google Scholar
Download references
The authors would like to acknowledge Dr. Rhona Hanning, Dr. Natalie Riediger, Amy Henderson, the study partners including school divisions, and study participants.
This study was funded by Canadian Institutes of Health Research (CIHR), FRN-156400), which played no other role in this study.
Department of Food and Human Nutritional Sciences, University of Manitoba, Winnipeg, MB, R3T 2N2, Canada
Joyce Slater & Bhanu Pilli
Department of Community Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, MB, R3E 0W3, Canada
Aynslie Hinds, Alan Katz, Marcelo L. Urquia & Nathan Nickel
Department of Family Medicine, Max Rady College of Medicine, University of Manitoba, Winnipeg, MB, R3E 0W2, Canada
Alan Katz
Manitoba Metis Federation, Winnipeg, MB, R3B 0J7, Canada
Julianne Sanguins
Winnipeg Regional Health Authority, Winnipeg, MB, R3B 1E2, Canada
Chris Green
Department of Anthropology, University of Winnipeg, Winnipeg, MB, R3B 2E9, Canada
Jaime Cidro
Research School of Population Health, Australian National University, Canberra, ACT 0200, Australia
Dan Chateau
You can also search for this author in PubMed Google Scholar
You can also search for this author in PubMed Google Scholar
You can also search for this author in PubMed Google Scholar
You can also search for this author in PubMed Google Scholar
You can also search for this author in PubMed Google Scholar
You can also search for this author in PubMed Google Scholar
You can also search for this author in PubMed Google Scholar
You can also search for this author in PubMed Google Scholar
You can also search for this author in PubMed Google Scholar
You can also search for this author in PubMed Google Scholar
JS, AK, MLU, JS, CG, JC, DC, and NN contributed to conceptualization and design of the study. JS, BP, AH, AK, MLU, CG, JC, DC, and NN contributed to the methodology. JS, BP, and AH performed the formal analysis. JS and BP drafted the manuscript. JS supervised the study. JS, AK, MLU, CG, JC, DC, and NN contributed to funding acquisition. All authors critically reviewed and approved to the published version of the manuscript.
Correspondence to Joyce Slater.
Informed consent was obtained from all subjects and their legal guardian(s). Ethics approval for this study was obtained from the Joint Faculty Research Ethics Board at the University of Manitoba (protocol HS2166 J2018:040), and all experimental methods were performed in accordance with the relevant guidelines and regulations.
Not applicable.
The authors declare that they have no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Reprints and Permissions
Slater, J., Pilli, B., Hinds, A. et al. The Food and Nutrition Security for Manitoba Youth (FANS) study: rationale, methods, dietary intakes and body mass index. BMC Nutr 8, 116 (2022). https://doi.org/10.1186/s40795-022-00611-x
Download citation
Received: 23 February 2022
Accepted: 12 October 2022
Published: 20 October 2022
DOI: https://doi.org/10.1186/s40795-022-00611-x
Anyone you share the following link with will be able to read this content:
Sorry, a shareable link is not currently available for this article.
Provided by the Springer Nature SharedIt content-sharing initiative
Advertisement
ISSN: 2055-0928
By using this website, you agree to our Terms and Conditions, California Privacy Statement, Privacy statement and Cookies policy. Manage cookies/Do not sell my data we use in the preference centre.
© 2022 BioMed Central Ltd unless otherwise stated. Part of Springer Nature.