Total volume and composition of fluid intake and mortality in older women: a cohort study
Bibliographic record
Abstract
OBJECTIVES: The health benefits of 'drinking at least 8 glasses of water a day" in healthy individuals are largely unproven. We aimed to examine the relationship between total fluid and the sources of fluid consumption, risk of rapid renal decline, cardiovascular disease (CVD) mortality and all-cause mortality in elderly women. DESIGN, SETTING AND PARTICIPANTS: We conducted a longitudinal analysis of a population-based cohort study of 1055 women aged ≥70 years residing in Australia. MAIN OUTCOME MEASURES: The associations between total daily fluid intake (defined as total volume of beverage excluding alcohol and milk) and the types of fluid (water, black tea, coffee, milk and other fluids) measured as cups per day and rapid renal decline, CVD and all-cause mortality were assessed using adjusted logistic and Cox regression analyses. RESULTS: Over a follow-up period of 10 years, 70 (6.6%) experienced rapid renal decline and 362 (34.4%) died, of which 142 (13.5%) deaths were attributed to CVD. The median (IQR) intake of total fluid was 10.4 (8.5-12.5) cups per day, with water (median (IQR) 4 (2-6) cups per day) and black tea (median (IQR) 3 (1-4) cups per day) being the most frequent type of fluid consumed. Every cup per day higher intake of black tea was associated with adjusted HRs of 0.90 (95% CI 0.81 to 0.99) and 0.92 (95% CI 0.86 to 0.98) for CVD mortality and all-cause mortality, respectively. There were no associations between black tea intake and rapid renal decline, or between the quantity or type of other fluids, including water intake, and any clinical outcomes. CONCLUSIONS: Habitual higher intake of black tea may potentially improve long-term health outcomes, independent of treating traditional CVD risk factors, but validation of our study findings is essential.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".