Global Variations in the Mineral Content of Bottled Still and Sparkling Water and a Description of the Possible Impact on Nephrological and Urological Diseases
Bibliographic record
Abstract
Kidney stone disease (KSD) is a complex disease. Besides the high risk of recurrence, its association with systemic disorders contributes to the burden of disease. Sufficient water intake is crucial for prevention of KSD, however, the mineral content of water might influence stone formation, bone health and cardiovascular (CVD) risk. This study aims to analyse the variations in mineral content of bottled drinking water worldwide to evaluate the differences and describes the possible impact on nephrological and urological diseases. The information regarding mineral composition (mg/L) on calcium, bicarbonate, magnesium, sodium and sulphates was read from the ingredients label on water bottles by visiting the supermarket or consulting the online shop. The bottled waters in two main supermarkets in 21 countries were included. The evaluation shows that on a global level the mineral composition of bottled drinkable water varies enormously. Median bicarbonate levels varied by factors of 12.6 and 57.3 for still and sparkling water, respectively. Median calcium levels varied by factors of 18.7 and 7.4 for still and sparkling water, respectively. As the mineral content of bottled drinking water varies enormously worldwide and mineral intake through water might influence stone formation, bone health and CVD risk, urologists and nephrologists should counsel their patients on an individual level regarding water intake.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.001 | 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".