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Introduction: There is evidence that 25-hydroxyvitamin D levels are lower in overweight and obese youth. This study examined the relationship between weight status and 25-hydroxyvitamin D, while controlling for confounders, in Canadian youth. Methods: Plasma 25-hydroxyvitamin D from subjects aged 6 to 17 years from the Canadian Health Measures Survey cycles 1 (2007 to 2009) and 2 (2009 to 2011) was used. Sex-specific multiple linear regression and logistic regressions examined the relationship of overweight and obesity (body mass index = 85th percentile) with 25-hydroxyvitamin D levels and the odds of 25-hydroxyvitamin D <40 nmol/L and <50 nmol/L. Results: The prevalence of risk of vitamin D deficiency (25-hydroxyvitamin D < 30 nmol/L) was 6% (95% confidence interval [CI] 3.26% to 10.12%). Vitamin D inadequacy, estimated by levels <40 nmol/L, was 15% (95% CI 10.34% to 20.39%; 19% [95% CI 13.1 to 25.6] for teenagers). Seventy per cent (95% CI 63.59 to 75.17) had levels >50 nmol/L, consistent with achieving the Recommended Dietary Allowance. In adjusted analyses, overweight/obesity (1/3 of subjects) was independently associated with lower 25-hydroxyvitamin D for both sexes after adjustment for age, race, income, season, vitamin D supplementation and daily milk consumption. For 25-hydroxyvitamin D <40 nmol/L, the overweight/obese odds ratio for males was 2.63 (95% CI 1.34 to 5.18). For 25-hydroxyvitamin D <50 nmol/L, overweight/obese odds ratios were 2.19 (95% CI 1.46 to 3.28) for males and 1.39 (95% CI 1.05 to 1.84) for females. Conclusions: This study confirms the inverse association between adiposity and serum concentrations of 25-hydroxyvitamin D in Canadian youth and the independent association of overweight/obesity to 25-hydroxyvitamin D level and vitamin D status after adjustment for other factors. [ABSTRACT FROM AUTHOR]

Background: Self-reported screen time is associated with elevated health risk in children and youth; however, research examining the relationship between accelerometer-measured sedentary time and health risk has reported mixed findings. The purpose of this study was to examine the association between accelerometer-measured patterns of sedentary time and health risk in children and youth. Methods: The results are based on 1,608 children and youth aged 6 to 19 years from the Canadian Health Measures Survey (2007-2009). Sedentary time was measured using the Actical accelerometer. Breaks in sedentary time and prolonged bouts of sedentary time lasting 20 to 120 minutes were derived for all days, weekend days and during the after-school period (i.e., after 3 pm on weekdays). Regression analyses were used to examine the association between patterns of sedentary time and body mass index (BMI), waist circumference, blood pressure and non-HDL cholesterol. Results: Boys accumulated more sedentary time on weekdays after 3 pm and had a higher number of breaks in sedentary time compared to girls. Overweight/obese boys (aged 6-19 years) accumulated more sedentary time after 3 pm on weekdays (282 vs. 259 min, p < .05) and as prolonged bouts lasting at least 80 minutes (171 vs. 133 min, p < .05) compared to boys who were neither overweight nor obese. Prolonged bouts of sedentary time lasting at least 80 minutes accumulated after 3 pm on weekdays were positively associated with BMI and waist circumference in boys aged 11-14 years (p < .006). Each additional 60 min of sedentary time after 3 pm on weekdays was associated with a 1.4 kgm-2 higher BMI and a 3.4 cm higher waist circumference in 11-14 year old boys. No sedentary pattern variables differed between girls who were not overweight or obese and those who were overweight/obese and none of the sedentary pattern variables were associated with any health markers in girls. Conclusions: The findings confirm results of other studies that reported accelerometer-measured sedentary time was not associated with health risk in children and youth. Even when the pattern and timing of sedentary time was examined relative to health markers, few associations emerged and were limited to boys aged 11-14 years. [ABSTRACT FROM AUTHOR]

Background: Physical activity and sedentary behavior habits are established during early childhood, yet only recently has objectively measured data been available on children aged 5 years and younger. This study presents data on the physical activity and sedentary behaviors of Canadian children aged 3-5 years. Methods: Data were collected as part of the Canadian Health Measures Survey between 2009 and 2011. A nationally-representative sample (n = 459) of children aged 3-5 years wore Actical accelerometers during their waking hours for 7 consecutive days. Data were collected in 60-sec epochs and respondents with ≤4 valid days were retained for analysis. Parents reported their child's physical activity and screen time habits in a questionnaire. Results: Eighty-four percent of 3-4 year old children met the physical activity guideline of 180 minutes of total physical activity every day while 18% met the screen time target of <1 hour per day. Fourteen percent of 5 year old children met the physical activity guideline of 60 minutes of daily moderate-to-vigorous physical activity (MVPA) while 81% met the screen time target of <2 hours per day. Children aged 3-4 years accumulated an average of 352 min/d of total physical activity and 66 minutes of MVPA while 5 year old children accumulated an average of 342 min/d of total physical activity and 68 minutes of MVPA. Children were sedentary for approximately half of their waking hours and spent an average of 2 hours per day in front of screens. Only 15% of 3-4 year olds and 5% of 5 year olds are meeting both the physical activity and sedentary behavior guidelines. Conclusions: Promoting physical activity while reducing sedentary behavior is important at all stages of life. The findings of the present study indicate that there remains significant room for improvement in these behaviors among young Canadian children. [ABSTRACT FROM AUTHOR]

The objective of this study was to evaluate the construct validity and reliability of the Healthy Eating Food Index-2019 (HEFI-2019), which was developed to measure adherence to Canada's Food Guide 2019 (CFG-2019) recommendations on healthy food choices. Dietary intake data from 24-hour dietary recalls in the 2015 Canadian Community Health Survey-Nutrition were used for that purpose. Multidimensionality was examined using principal component analysis. Mean scores were compared among subgroups of the population. The association between scores and energy intake was assessed using Pearson correlations. Cronbach's alpha was calculated to assess reliability. The estimated mean HEFI-2019 score (/80) was 43.1 (95% CI, 42.7 to 43.6) among Canadians aged 2 years and older. The first and 99th percentiles were 22.1 and 62.9 points. The mean HEFI-2019 score for smokers was 7.2 points lower than for non-smokers (95% CI, –8.5 to –5.9). The HEFI-2019 was weakly correlated with energy intake (r = –0.13; 95% CI, –0.20 to –0.06). The principal components analysis revealed at least 4 dimensions. Cronbach's alpha was 0.66 (95% CI, 0.63 to 0.69). Evidence of construct validity and internal consistency support the use of the HEFI-2019 to assess adherence to CFG-2019's recommendations on healthy food choices. Novelty: Examination of the HEFI-2019's psychometric properties is needed prior to implementation. Analyses support the construct validity and internal consistency of the HEFI-2019. Interpretation of the total HEFI-2019 score must be accompanied by its components' scores, considering it assesses multiple dimensions of food choices. [ABSTRACT FROM AUTHOR]

The release of Canada's Food Guide (CFG) in 2019 by Health Canada prompted the development of indices to measure adherence to these updated dietary recommendations for Canadians. This study describes the development and scoring standards of the Healthy Eating Food Index (HEFI-2019), which is intended to measure alignment of eating patterns with CFG-2019 recommendations on food choices among Canadians aged 2 years and older. Alignment with the intent of each key recommendation in the CFG-2019 was the primary principle guiding the development of the HEFI-2019. Additional considerations included previously published indices, data on Canadians' dietary intakes from the 2015 Canadian Community Health Survey-Nutrition, and expert judgement. The HEFI-2019 includes 10 components: Vegetables and fruits (20 points), Whole-grain foods (5 points), Grain foods ratio (5 points), Protein foods (5 points), Plant-based protein foods (5 points), Beverages (10 points), Fatty acids ratio (5 points), Saturated fats (5 points), Free sugars (10 points), and Sodium (10 points). All components are expressed as ratios (e.g., proportions of total foods, total beverages, or total energy). The HEFI-2019 score has a maximum of 80 points. Potential uses of the HEFI-2019 include research as well as monitoring and surveillance of food choices in population-based surveys. Novelty: The Healthy Eating Food Index-2019 was developed to measure adherence to the 2019 Canada's Food Guide recommendations on healthy food choices. The HEFI-2019 includes 10 components, of which 5 are based on foods, 1 on beverages and 4 on nutrients, for a total of 80 points. [ABSTRACT FROM AUTHOR]

ObjectiveTo evaluate the Canadian Diet History Questionnaire I (C-DHQ I) food list and to adapt the US DHQ II for Canada using Canadian dietary survey data.DesignTwenty-four-hour dietary recalls reported by adults in a national Canadian survey were analysed to create a food list corresponding to C-DHQ I food questions. The percentage contribution of the food list to the total survey intake of seventeen nutrients was used as the criterion to evaluate the suitability of the C-DHQ I to capture food intake in Canadian populations. The data were also analysed to identify foods and to modify portion sizes for the C-DHQ II.SettingThe Canadian Community Health Survey (CCHS) – Cycle 2.2 Nutrition (2004).SubjectsAdults (n 20 159) who completed 24 h dietary recalls during in-person interviews.ResultsFour thousand five hundred and thirty-three foods and recipes were grouped into 268 Food Groups, of which 212 corresponded to questions on the C-DHQ I. Nutrient intakes captured by the C-DHQ I ranged from 79 % for fat to 100 % for alcohol. For the new C-DHQ II, some food questions were retained from the original US DHQ II while others were added based on foods reported in CCHS and foods available on the Canadian market since 2004. Of 153 questions, 143 were associated with portion sizes of which fifty-three were modified from US values. Sex-specific nutrient profiles for the C-DHQ II nutrient database were derived using CCHS data.ConclusionsThe C-DHQ I and II are designed to optimize the capture of foods consumed by Canadian populations. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the Canadian Diet History Questionnaire I (C-DHQ I) food list and to adapt the US DHQ II for Canada using Canadian dietary survey data.Design: Twenty-four-hour dietary recalls reported by adults in a national Canadian survey were analysed to create a food list corresponding to C-DHQ I food questions. The percentage contribution of the food list to the total survey intake of seventeen nutrients was used as the criterion to evaluate the suitability of the C-DHQ I to capture food intake in Canadian populations. The data were also analysed to identify foods and to modify portion sizes for the C-DHQ II.Setting: The Canadian Community Health Survey (CCHS) - Cycle 2.2 Nutrition (2004).Subjects: Adults (n 20 159) who completed 24 h dietary recalls during in-person interviews.Results: Four thousand five hundred and thirty-three foods and recipes were grouped into 268 Food Groups, of which 212 corresponded to questions on the C-DHQ I. Nutrient intakes captured by the C-DHQ I ranged from 79 % for fat to 100 % for alcohol. For the new C-DHQ II, some food questions were retained from the original US DHQ II while others were added based on foods reported in CCHS and foods available on the Canadian market since 2004. Of 153 questions, 143 were associated with portion sizes of which fifty-three were modified from US values. Sex-specific nutrient profiles for the C-DHQ II nutrient database were derived using CCHS data.Conclusions: The C-DHQ I and II are designed to optimize the capture of foods consumed by Canadian populations. [ABSTRACT FROM AUTHOR]