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      Cat caregivers’ perceptions, motivations, and behaviours for feeding treats: A cross sectional study

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          Abstract

          There is an abundance of research focusing on the nutritional needs of the cat, though aspects surrounding treat feeding have received far less attention. Feeding practices have the potential to cause nutrient imbalances and adverse health outcomes, including obesity. The objective of this study was to identify and describe the perceptions, motivations, and behaviours surrounding treats, and factors that influence treat feeding by cat caregivers. A 56-question online survey was disseminated to cat caregivers (n = 337) predominantly from Canada and the USA to collect data regarding caregiver and cat demographics, the pet-caregiver relationship, perceptions surrounding treats, and feeding practices and behaviours. Descriptive statistics, chi-square tests, Kruskal-Wallis one-way ANOVA, Wilcoxon signed-rank tests, and multivariable logistic regression models were used to analyze the survey data. Caregivers had varying interpretations of the term ‘treat’ and how treats relate to the primary diet, and these perceptions appeared to influence the quantity of treats provided. Aspects relating to the human-animal bond were highlighted as an important factor in decisions and behaviours surrounding treat feeding in our results. Though the majority (224/337, 66%) of respondents indicated they monitor their pet’s treat intake, using an eyeball estimate was the most frequent (139/337, 41%) method reported to measure treats. Multivariable logistic regression results revealed feeding jerky, bones, dental treats, and table scraps in select frequencies were predictive of caregivers perceiving their cat as overweight/obese. Results provide valuable new insights to cat caregiver feeding practices and perceptions of treats and can be used to inform veterinary nutrition support to caregivers. More research is warranted to further our understanding and ensure that cats receive optimal nutrition and care.

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          Logistic regression: a brief primer.

          Regression techniques are versatile in their application to medical research because they can measure associations, predict outcomes, and control for confounding variable effects. As one such technique, logistic regression is an efficient and powerful way to analyze the effect of a group of independent variables on a binary outcome by quantifying each independent variable's unique contribution. Using components of linear regression reflected in the logit scale, logistic regression iteratively identifies the strongest linear combination of variables with the greatest probability of detecting the observed outcome. Important considerations when conducting logistic regression include selecting independent variables, ensuring that relevant assumptions are met, and choosing an appropriate model building strategy. For independent variable selection, one should be guided by such factors as accepted theory, previous empirical investigations, clinical considerations, and univariate statistical analyses, with acknowledgement of potential confounding variables that should be accounted for. Basic assumptions that must be met for logistic regression include independence of errors, linearity in the logit for continuous variables, absence of multicollinearity, and lack of strongly influential outliers. Additionally, there should be an adequate number of events per independent variable to avoid an overfit model, with commonly recommended minimum "rules of thumb" ranging from 10 to 20 events per covariate. Regarding model building strategies, the three general types are direct/standard, sequential/hierarchical, and stepwise/statistical, with each having a different emphasis and purpose. Before reaching definitive conclusions from the results of any of these methods, one should formally quantify the model's internal validity (i.e., replicability within the same data set) and external validity (i.e., generalizability beyond the current sample). The resulting logistic regression model's overall fit to the sample data is assessed using various goodness-of-fit measures, with better fit characterized by a smaller difference between observed and model-predicted values. Use of diagnostic statistics is also recommended to further assess the adequacy of the model. Finally, results for independent variables are typically reported as odds ratios (ORs) with 95% confidence intervals (CIs). © 2011 by the Society for Academic Emergency Medicine.
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            Pet ownership and human health: a brief review of evidence and issues.

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              Health status and population characteristics of dogs and cats examined at private veterinary practices in the United States.

              To determine age, breed, sex, body condition score, and diet of dogs and cats examined at private veterinary practices in the United States during 1995, and estimate prevalences of the most common disorders for these animals. Cross-sectional study. 31,484 dogs and 15,226 cats examined by veterinary practitioners at 52 private veterinary practices. Information on age, breed, sex, body condition score, diet, and assigned diagnostic codes were collected electronically from participating practices and transferred to a relational database. Prevalence estimates and frequencies for population description were generated using statistical software. Dental calculus and gingivitis were the most commonly reported disorders. About 7% of dogs and 10% of cats examined by practitioners during the study were considered healthy. Many conditions were common to both species (e.g., flea infestation, conjunctivitis, diarrhea, vomiting). Dogs were likely to be examined because of lameness, disk disease, lipoma, and allergic dermatitis. Cats were likely to be examined because of renal disease, cystitis, feline urologic syndrome, and inappetence. Results can be used by veterinary practitioners to better understand and anticipate health problems of importance in cats and dogs they examine and to better communicate with clients regarding the most prevalent disorders in cats and dogs.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: Writing – original draft
                Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: SupervisionRole: Writing – review & editing
                Role: SupervisionRole: Writing – review & editing
                Role: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                10 January 2024
                2024
                : 19
                : 1
                : e0296011
                Affiliations
                [1 ] Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada
                [2 ] Department of Clinical Studies, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada
                Visayas State University, PHILIPPINES
                Author notes

                Competing Interests: A.V. is the Royal Canin Veterinary Diets Endowed Chair in Canine and Feline Clinical Nutrition and declares that they serve on industry advisory boards and received honoraria and research funding from various pet food manufacturers and ingredient suppliers.

                Author information
                https://orcid.org/0000-0003-2278-8057
                https://orcid.org/0000-0002-4555-7596
                Article
                PONE-D-23-20840
                10.1371/journal.pone.0296011
                10781132
                38198455
                e4ae2f6c-1da4-4670-b01e-e036b314cc58
                © 2024 Nielson et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 5 July 2023
                : 4 December 2023
                Page count
                Figures: 3, Tables: 8, Pages: 24
                Funding
                The author(s) received no specific funding for this work.
                Categories
                Research Article
                Medicine and Health Sciences
                Health Care
                Caregivers
                Biology and Life Sciences
                Veterinary Science
                Veterinary Medicine
                Small Animal Care
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Vertebrates
                Amniotes
                Mammals
                Cats
                Biology and Life Sciences
                Zoology
                Animals
                Vertebrates
                Amniotes
                Mammals
                Cats
                Biology and Life Sciences
                Nutrition
                Diet
                Medicine and Health Sciences
                Nutrition
                Diet
                Biology and Life Sciences
                Nutrition
                Diet
                Food
                Medicine and Health Sciences
                Nutrition
                Diet
                Food
                Biology and Life Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Obesity
                People and Places
                Population Groupings
                Age Groups
                Biology and Life Sciences
                Psychology
                Behavior
                Animal Behavior
                Social Sciences
                Psychology
                Behavior
                Animal Behavior
                Biology and Life Sciences
                Zoology
                Animal Behavior
                Custom metadata
                The data has been uploaded to a public repository. DOI: 10.5683/SP3/EEAXSO Reference: Nielson, Shelby, 2023, "Supplementary Data: Cat caregivers' perceptions, motivations, and behaviours for feeding treats: a cross sectional study", https://doi.org/10.5683/SP3/EEAXSO, Borealis, V1, UNF:6:bY9XKkmnQgG4QdLd5am8fg== [fileUNF]

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