Feline diabetes mellitus in the UK: the prevalence within an insured cat population and a questionnaire-based putative risk factor analysis

Theresa M McCann, Kerry E Simpson, Darren J Shaw, Jennifer A Butt, Danielle A Gunn-Moore

Research output: Contribution to journalArticlepeer-review

Abstract

Prevalence and risk factors for the development of diabetes mellitus (DM) in cats in the United Kingdom have not previously been reported. The prevalence of DM was evaluated in a large insured population and was found to be 1 in 230 cats. In this insured cat population Burmese cats were 3.7 times more likely to develop DM than non-pedigree cats. A convenience-sampling questionnaire-based study was used in order to identify putative risk factors for the development of DM. The univariate risk factor analysis identified being male, neutered, inactive, weighing >or=5 kg and having a history of corticosteroid treatment as significant risk factors for the development of DM in these cats. In addition, male cats treated with megestrol acetate had a significantly increased risk of developing DM compared to females. In contrast, there was no difference in DM occurrence between male and female Burmese cats. A multivariate classification tree-based model on the questionnaire data looking for interactions between risk factors, identified gender as the most important overall risk factor for the development of DM with low physical activity being the next most important risk factor for female cats and breed the next most important for male cats.
Original languageEnglish
Pages (from-to)289-99
Number of pages11
JournalJournal of Feline Medicine and Surgery
Volume9
Issue number4
DOIs
Publication statusPublished - 2007

Keywords

  • Animals
  • Cat Diseases
  • Cats
  • Databases, Factual
  • DIABETES MELLITUS
  • Female
  • Great Britain
  • Male
  • OWNERSHIP
  • Pedigree
  • Prevalence
  • QUESTIONNAIRES
  • Risk Factors
  • Sex Factors

Fingerprint Dive into the research topics of 'Feline diabetes mellitus in the UK: the prevalence within an insured cat population and a questionnaire-based putative risk factor analysis'. Together they form a unique fingerprint.

Cite this