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Background: Among adults and children consuming Western diets, beverages are significant sources of free sugars, saturated fats, excess calories, and alcohol, with relevance to chronic disease risk. The impact of recent healthy eating policies and beverage market evolutions on population-level consumption patterns in Canada is unknown. The current study examined trends in intake of a range of beverage types among a nationally-representative sample of Canadians, with stratification by socio-demographic characteristics.Methods: The 2004 (n = 34,775) and 2015 (n = 20,176) nutrition-focused cycles of the Canadian Community Health Surveys are cross-sectional surveys representative of the population of the 10 Canadian provinces. Based on a single multiple-pass 24-h dietary recall for each participant, fluids consumed as beverages were grouped into seven categories. Using linear regression, reported intake (volume, ml and energy, kcal) of each category was characterized over time and in relation to sex, age, ethnicity, income, body mass index (BMI), and province of residence.Results: In 2015, Canadians reported consuming an average of 1806 ml (275 kcal) fluids as beverages per day, including: plain water 867 ml (0 kcal); other unsweetened beverages, e.g. coffee, 364 ml (6 kcal); sugar-sweetened beverages (SSBs) 204 ml (99 kcal); plain milk 132 ml (64 kcal); alcoholic drinks 120 ml (71 kcal); 100% juice 74 ml (34 kcal); and diet or low calorie beverages 44 ml (2 kcal). Differential consumption was observed across socio-demographic groups, with high consumption of sugary drinks (i.e., SSBs and 100% juice) and alcohol across groups. From 2004 to 2015, the reported volumes of beverages consumed decreased by 10% (energy: - 24%). With adjustment for socio-demographic characteristics, there were significant changes (p < 0.001) over time in intake of: 100% juice - 40% (- 38%); plain milk - 37% (- 35%); SSBs - 26% (- 20%); diet or low calorie beverages (- 46%); and other unsweetened beverages - 11% (- 42%). The volume of plain water consumed increased by 10% (p < 0.0001). Intake of alcoholic (volume and energy) and diet or light beverages did not change significantly.Conclusions: Lower intake of beverages was reported by Canadians in 2015 versus 2004, with a shift towards plain water. Consumption of sugary drinks decreased, but these beverages continue to contribute substantially to Canadians' overall energy intake. The findings underscore the need for policies to further reduce the consumption of sugary and alcoholic beverages, as well as calories from beverages. [ABSTRACT FROM AUTHOR]

Background: All self-reported dietary intake data are characterized by measurement error, and validation studies indicate that the estimation of energy intake (EI) is particularly affected.Methods: Using self-reported food frequency and physical activity data from Alberta's Tomorrow Project participants (n = 9847 men 16,241 women), we compared the revised-Goldberg and the predicted total energy expenditure methods in their ability to identify misreporters of EI. We also compared dietary patterns derived by k-means clustering under different scenarios where misreporters are included in the cluster analysis (Inclusion); excluded prior to completing the cluster analysis (ExBefore); excluded after completing the cluster analysis (ExAfter); and finally, excluded before the cluster analysis but added to the ExBefore cluster solution using the nearest neighbor method (InclusionNN).Results: The predicted total energy expenditure method identified a significantly higher proportion of participants as EI misreporters compared to the revised-Goldberg method (50% vs. 47%, p < 0.0001). k-means cluster analysis identified 3 dietary patterns: Healthy, Meats/Pizza and Sweets/Dairy. Among both men and women, participants assigned to dietary patterns changed substantially between ExBefore and ExAfter and also between the Inclusion and InclusionNN scenarios (Hubert and Arabie's adjusted Rand Index, Kappa and Cramer's V statistics < 0.8).Conclusions: Different scenarios used to account for EI misreporters influenced cluster analysis and hence the composition of the dietary patterns. Continued efforts are needed to explore and validate methods and their ability to identify and mitigate the impact of EI misestimation in nutritional epidemiology. [ABSTRACT FROM AUTHOR]