Overweight and obese body condition in ∼4.9 million dogs and ∼1.3 million cats seen at primary practices across the USA: Prevalences by life stage from early growth to senior
Bibliographic record
Abstract
Adult dogs and cats in overweight or obese condition are common, but prevalence data for different life stages, especially growth, are limited, and may help inform when preventative measures may be most effective. In this retrospective observational study, prevalences of overweight and obese condition were determined from the electronic medical records of dogs and cats of all life stages visiting Banfield Pet Hospital in the USA between 2020 and 2023. Animals were identified either by body condition score (BCS; overweight 6-7; obese 8-9) or from a clinical diagnosis of overweight condition or obesity when recorded. Life stages (early growth, late growth, young adult, adult, mature, and senior) were defined by age range, adjusted for species and breed size in dogs. Individuals could only be included once within each life stage, with the maximum BCS used. Prevalence was determined for the 4-year period and for each calendar year. The evolution of BCS was also assessed for animals with multiple records. In total, 4933,916 unique dogs and 1341,118 unique cats were included. In dogs, prevalences of overweight or obese condition were: 0.9 % and < 0.0 % (early growth), 9.5 % and 0.3 % (late growth), 24.4 % and 1.9 % (young adult); 44.5 % and 8.4 % (adult), 50.1 % and 12.6 % (mature); 46.4 % and 11.3 % (senior). In cats, prevalences of overweight or obese condition were: 0.8 % and < 0.0 % (early growth); 10.7 % and 0.4 % (late growth); 36.2 % and 3.6 % (young adult); 47.2 % and 13.9 % (adult); 44.8 % and 21.7 % (mature); and 32.0 % and 12.6 % (senior). From 2020-2021 and 2021-2022 prevalences of overweight and obese condition in dogs and overweight condition in cats increased in most life stages. The prevalence of overweight condition in dogs and obese condition in cats and dogs significantly decreased between 2022 and 2023 for some life stages. The odds ratio of an overweight or obese condition in adulthood was 1.85 (95 % confidence interval [CI]: 1.81, 1.86); P ≤ 0.001) for dogs and 1.52 (95 % CI: 1.48, 1.56; P ≤ 0.001) for cats where an overweight or obese condition was recorded during growth. In conclusion, both overweight and obese condition are prevalent throughout adult life, peaking during the mature life stage in dogs and cats, with overweight or obese condition during growth persisting into adulthood in most affected animals. Veterinarian-led prevention strategies are recommended from growth onwards, including the use of growth standard charts.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".