Beverage consumption and energy intake among Canadians: analyses of 2004 and 2015 national dietary intake data
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.017 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".