Associations of cereal grains intake with cardiovascular disease and mortality across 21 countries in Prospective Urban and Rural Epidemiology study: prospective cohort study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the association between intakes of refined grains, whole grains, and white rice with cardiovascular disease, total mortality, blood lipids, and blood pressure in the Prospective Urban and Rural Epidemiology (PURE) study. DESIGN: Prospective cohort study. SETTING: PURE study in 21 countries. PARTICIPANTS: 148 858 participants with median follow-up of 9.5 years. EXPOSURES: Country specific validated food frequency questionnaires were used to assess intakes of refined grains, whole grains, and white rice. MAIN OUTCOME MEASURE: Composite of mortality or major cardiovascular events (defined as death from cardiovascular causes, non-fatal myocardial infarction, stroke, or heart failure). Hazard ratios were estimated for associations of grain intakes with mortality, major cardiovascular events, and their composite by using multivariable Cox frailty models with random intercepts to account for clustering by centre. RESULTS: Analyses were based on 137 130 participants after exclusion of those with baseline cardiovascular disease. During follow-up, 9.2% (n=12 668) of these participants had a composite outcome event. The highest category of intake of refined grains (≥350 g/day or about 7 servings/day) was associated with higher risk of total mortality (hazard ratio 1.27, 95% confidence interval 1.11 to 1.46; P for trend=0.004), major cardiovascular disease events (1.33, 1.16 to 1.52; P for trend<0.001), and their composite (1.28, 1.15 to 1.42; P for trend<0.001) compared with the lowest category of intake (<50 g/day). Higher intakes of refined grains were associated with higher systolic blood pressure. No significant associations were found between intakes of whole grains or white rice and health outcomes. CONCLUSION: High intake of refined grains was associated with higher risk of mortality and major cardiovascular disease events. Globally, lower consumption of refined grains should be considered.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".