Alcohol and hypertension: An analysis using The Health Survey for England 2014
Bibliographic record
Abstract
Aims: This study aims to model the risk relationships between alcohol consumption and hypertension, as alcohol is likely an important modifiable risk factor in treating hypertension and an important lifestyle variable to be taken into consideration by policy makers and physicians. Design/Participants/Measures: This cross-sectional study uses data from the The Health Survey for England to perform a correlational analysis, as well as multinomial and binomial modeling to evaluate alcohol’s impact on hypertension outcomes, all while controlling for relevant covariates (age, sex, smoking, exercise, body mass index, and education). Findings: Findings indicate that alcohol consumption correlates with blood pressure and hypertension, yet the significance of these findings is weakened by large between-person variability and by confounding factors. Conclusions: Based on these results, for the best cardiovascular health outcomes, we suggest that it is best to err on the side of caution and recommend, regarding alcohol intake, very limited (in the case of healthy patients) to no (for those with hypertension) alcohol consumption.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".