Relation between sugar‐sweetened beverage consumption and incident hypertension: a systematic review and meta‐analysis of prospective cohorts (267.4)
Bibliographic record
Abstract
Background: The role of fructose‐containing sugar‐sweetened beverages (SSBs) in incident hypertension is unclear. Aims: To quantify the relation between fructose‐containing SSBs and incident hypertension, we conducted a systematic review and meta‐analysis of prospective cohorts. Methods: MEDLINE, EMBASE, CINAHL, and the Cochrane registry were searched (through August 4, 2013) for relevant prospective cohorts. We pooled risk ratios (RR) of extreme (lowest vs. highest) quantiles of intake using generic inverse variance random effects models. Heterogeneity and cohort quality were assessed. Results: Five prospective cohorts (n=240,508) with 79,584 cases of hypertension observed over 蠅3‐million person‐years were included. SSB intake ranged from none to 蠅1‐serving (200mL, 8 or 12 oz)/day. Comparing extreme quantiles, SSBs significantly increased the risk of developing hypertension by 11% (RR:1.11 [95%CI: 1.06 to 1.17]), and a positive linear dose‐response was established (β=0.0027, p<0.001). However, significant heterogeneity was observed (I²=64%, p=0.02). Limitations: Significant unexplained heterogeneity and residual confounding due to important collinearity with a Western dietary pattern. Conclusions: SSBs are associated with a small risk of developing hypertension in five cohorts. Its contribution to hypertension risk appears to be small relative to other established risk factors. Grant Funding Source : Supported by Calorie Control Council
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 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 | 0.015 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.037 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".