The Scientific Basis of Guideline Recommendations on Sugar Intake
Bibliographic record
Abstract
Letters1 August 2017The Scientific Basis of Guideline Recommendations on Sugar IntakeBehnam Sadeghirad, PharmD, MPH and Bradley C. Johnston, PhDBehnam Sadeghirad, PharmD, MPHFrom McMaster University, Hamilton, Ontario, Canada. and Bradley C. Johnston, PhDFrom McMaster University, Hamilton, Ontario, Canada.Author, Article, and Disclosure Informationhttps://doi.org/10.7326/L17-0255 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail IN RESPONSE:Our systematic review of available public health guidelines on sugar intake aimed to assess the methodological quality of the guidelines and the quality (certainty) of the evidence provided for their recommendations. We agree that the overconsumption of calories, unhealthy eating habits, and the increase in sedentary lifestyles are the main drivers of the obesity epidemic in children and adults worldwide. However, this issue is separate from the quality and trustworthiness of public health guidelines on sugar intake. Our findings do not imply that increased sugar consumption is good. Instead, the message—which seemed to be largely dismissed—is that dietary ...References1. Moher D, Tricco AC. Issues related to the conduct of systematic reviews: a focus on the nutrition field. Am J Clin Nutr. 2008;88:1191-9. [PMID: 18996852] MedlineGoogle Scholar2. Salam RA, Welch V, Bhutta ZA. Systematic reviews on selected nutrition interventions: descriptive assessment of conduct and methodological challenges. BMC Nutrition. 2015;1:9. CrossrefGoogle Scholar3. Alexander PE, Brito JP, Neumann I, Gionfriddo MR, Bero L, Djulbegovic B, et al. World Health Organization strong recommendations based on low-quality evidence (study quality) are frequent and often inconsistent with GRADE guidance. J Clin Epidemiol. 2016;72:98-106. [PMID: 25618534] doi:10.1016/j.jclinepi.2014.10.011 CrossrefMedlineGoogle Scholar4. U.S. Department of Health and Human Services. Scientific Report of the 2015 Dietary Guidelines Advisory Committee: Advisory Report to the Secretary of Health and Human Services and the Secretary of Agriculture. Washington, DC: U.S. Department of Health and Human Services; February 2015. Google Scholar5. U.S. Department of Agriculture; U.S. Department of Health and Human Services.. Dietary Guidelines for Americans, 2015–2020. 8th ed. Washington, DC: US Gov Pr Off; 2015. Google Scholar Author, Article, and Disclosure InformationAffiliations: From McMaster University, Hamilton, Ontario, Canada.Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M16-2020. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoThe Scientific Basis of Guideline Recommendations on Sugar Intake Jennifer Erickson , Behnam Sadeghirad , Lyubov Lytvyn , Joanne Slavin , and Bradley C. Johnston The Scientific Basis of Guideline Recommendations on Sugar Intake C. Albert Yeung The Scientific Basis of Guideline Recommendations on Sugar Intake Stephen Strum Metrics Cited byFractional-Order Models for Biochemical ProcessesPossible Implication of Long Term Sucrose Diet on Integumentary Tissues' Minerals of Male Albino Rats 1 August 2017Volume 167, Issue 3Page: 219KeywordsDisclosureEatingEating habitsGrading of Recommendations Assessment Development and EvaluationNutritionObesityObservational studiesPrevention, policy, and public healthRandomized trialsSystematic reviews ePublished: 1 August 2017 Issue Published: 1 August 2017 Copyright & PermissionsCopyright © 2017 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
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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 | 0.273 | 0.736 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.014 | 0.011 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.010 | 0.006 |
| Research integrity | 0.014 | 0.018 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".