Frequency, breed predisposition and demographic risk factors for overweight status in dogs in the UK

Autor: Pegram, C., Raffan, E., White, E., Ashworth, A. H., Brodbelt, D. C., Church, D. B., O'Neill, D. G.
Přispěvatelé: O'Neill, DG [0000-0003-1115-2723], Apollo - University of Cambridge Repository, O'Neill, D. G. [0000-0003-1115-2723]
Rok vydání: 2021
Předmět:
Popis: Funder: Kennel Club Charitable Trust
Objectives: To evaluate the prevalence and risk factors for overweight status in dogs under primary veterinary care in the UK. Materials and Methods: A retrospective study design was used to estimate the 1‐year (2016) period prevalence of overweight status. The clinical records were randomly ordered and manually validated for dogs with overweight status during 2016. Univariable and multivariable logistic regression modelling were used to evaluate associations between risk factors (breed, brachycephalic status, adult bodyweight, bodyweight relative to breed‐sex mean, age, sex‐neuter and insurance) and overweight status. Results: There were 1580 of 22,333 dogs identified as overweight during 2016. The estimated 1‐year period prevalence for overweight status recorded in dogs under veterinary care was 7.1% (95% confidence interval 6.7–7.4). After accounting for confounding factors, eight breeds showed increased odds of overweight status compared with crossbred dogs. The breeds with the highest odds included the Pug (OR 3.12, 95% confidence interval 2.31 to 4.20), Beagle (OR 2.67, 1.75 to 4.08), Golden Retriever (OR 2.58, 1.79 to 3.74) and English Springer Spaniel (OR 1.98, 1.31 to 2.98). Being neutered, middle‐aged and insured were additionally associated with overweight status. Clinical Significance: Targeted overweight prevention strategies should be prioritised for predisposed breeds, such as Pugs and Beagles. The findings additionally raise questions about further preventative efforts following neutering. The prevalence estimate suggests veterinary professionals are underreporting overweight status and therefore could be missing key welfare opportunities.
Databáze: OpenAIRE