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Record W2948520893 · doi:10.2337/db19-152-or

152-OR: Changes in Consumption of Sugary Beverages and Artificially Sweetened Beverages and Risk of Type 2 Diabetes among U.S. Women and Men

2019· article· en· W2948520893 on OpenAlexaboutno aff
Jean‐Philippe Drouin‐Chartier, Yan Zheng, Yanping Li, Vasanti Malik, An Pan, JoAnn E. Manson, Walter C. Willett, Frank B. Hu

Bibliographic record

VenueDiabetes · 2019
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineType 2 diabetesHazard ratioConsumption (sociology)Environmental healthProportional hazards modelDiabetes mellitusLower riskDemographyConfidence intervalInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Background: Whether changes in consumption of sugary beverages or artificially sweetened beverages (ASBs) are associated with type 2 diabetes (T2D) risk has never been evaluated. Objective: We evaluated the association of changes in sugary beverage and ASB consumption over a 4-year period with subsequent 4-year risk of T2D among U.S. women and men. Methods: We followed-up 78,357 women in the Nurses’ Health Study (1986-2012), 82,937 women in the Nurses’ Health Study II (1991-2013) and 35,148 men in the Health Professionals Follow-up Study (1986-2012). Beverage intakes were assessed using validated food frequency questionnaires every 4 years. Cox proportional regression models were used to calculate hazard ratios (HRs) for T2D regarding 4-year changes in beverage consumption, adjusted for initial beverage intake and BMI. Results of the 3 cohorts were pooled using an inverse variance-weighted, fixed-effect meta-analysis. Results: During 2,849,389 person-years of follow-up, we documented 12,007 incident cases of T2D. Increasing sugary beverage intake by >0.5 serving/day over a 4-year period was associated with a 14% (95% CI: 7%, 21%) higher T2D risk compared with maintaining a stable consumption. Both beverages with added sugars (e.g., soft drinks) and 100% fruit juices were associated with higher T2D risk. Increasing ASB consumption by >0.5 serving/day was associated with a 19% (95% CI: 12%, 27%) higher T2D risk. Substituting ASB for sugary beverages was not associated with subsequent T2D risk (HR: 0.99, 95% CI: 0.96, 1.02). However, decreasing sugary beverage consumption and increasing water, coffee or tea intake by 1 serving/day was associated with a 3% to 11% lower risk of T2D. Conclusion: Increasing consumption of sugary beverages or ASBs was associated with a higher risk of T2D compared with maintaining a stable consumption of these beverages. Substituting water, coffee or tea but not ASB for sugary beverages was associated with lower T2D risk. Disclosure J. Drouin-Chartier: Other Relationship; Self; Dairy Farmers of Canada. Y. Zheng: None. Y. Li: None. V. Malik: None. A. Pan: None. J.E. Manson: None. W.C. Willett: None. F. Hu: None. Funding National Institutes of Health (UM1CA186107, UM1CA176726, UM1CA167552, DK112940, HL60712, HL118264); Canadian Institutes of Health Research (BPF-156628)

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.008
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.011
GPT teacher head0.232
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2019
Admission routes1
Has abstractyes

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