Current perspectives on global sugar consumption: definitions, recommendations, population intakes, challenges and future direction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Currently, there is considerable emphasis on the relationship between dietary sugar consumption and various health outcomes, with some countries and regions implementing national sugar reduction campaigns. This has resulted in significant efforts to quantify dietary sugar intakes, to agree on terms to describe dietary sugars and to establish associated recommendations. However, this information is infrequently collated on a global basis and in a regularised manner. The present review provides context regarding sugar definitions and recommendations. It provides a global review of the available data regarding dietary sugar intake, considering forms such as total, free and added sugars. A comprehensive breakdown of intakes is provided by age group, country and sugar form. This analysis shows that free sugar intakes as a percentage of total energy (%E) are the highest for children and adolescents (12-14%E) and the lowest for older adults (8%E). This trend across lifecycle stages has also been observed for added sugars. The available data also suggest that, while some reductions in sugar intake are observed in a few individual studies, overall intakes of free/added sugars remain above recommendations. However, any wider conclusions are hampered by a lack of detailed high-quality data on sugar intake, especially in developing countries. Furthermore, there is a need for harmonisation of terms describing sugars (ideally driven by public health objectives) and for collaborative efforts to ensure that the most up-to-date food composition data are used to underpin recommendations and any estimates of intake or modelling scenarios.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it