Diet format, protein, amino acids, salt, and osmolytes, as well as water viscosity, affect water consumption in domestic cats: a scoping review of 32 publications (published from 1975 to 2025) on water intake, hydration status, and related health outcomes
Bibliographic record
Abstract
Ensuring cats consume sufficient water to maintain their health is a common concern for cat owners. Despite the connection between water intake and animal health, the optimal water intake levels for cats are poorly understood. The present scoping review aimed to determine the extent to which cat hydration research has been conducted, the reported average daily water intake of cats, and whether their water intake requirements have been identified. Online databases were used to identify papers published between 1975 and 2025, from which we selected 32 publications written in English that provided the water intake of cats as an outcome variable. Across an assessment of five groups of healthy domestic cats, 23 to 51 mL/kg BW of total water was consumed daily. A further eight papers reported that cats consumed 70 to 293 mL of water daily. Urine specific gravity (USG) was the most reported physiological biomarker used to assess a cat's hydration status and is used to assist in the diagnosis of diabetes insipidus, glomerulonephritis, pyelonephritis, adrenal insufficiency, hepatic disease, and congestive heart failure. USG was frequently measured in conjunction with urine pH, volume (or output), calcium oxalate, struvite, and/or serum biochemistry and a complete blood count to evaluate gross kidney function. The water intake of cats was highly variable within and across studies. Still, it was influenced by factors such as diet format (wet or dry), dietary protein or amino acid content, salt, osmolytes, and water viscosity. The water intake of cats was not affected by fat content or water source type (static or flowing). Healthy cats that consumed 42 to 51 mL/kg BW of total water daily often had a USG <1.035, and this was achieved only when consuming a wet diet or a dry diet with supplemented nutrient-enriched water. Except for those supplemented with nutrient-enriched water, cats on a dry diet had lower TWI and higher USG, suggesting they may be at greater risk of developing feline lower urinary disease, including crystalluria and urolithiasis. Although the minimum water requirement before cats become at a greater risk of developing urinary or renal disease remains unknown, these results provide some evidence of the minimum water intake required for optimal hydration. If not consumed, these cats would likely benefit from a wet, semi-moist, or fresh (high-moisture) diet.
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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".