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Mixed, or Manx breeds, being fed a premi-um or therapeutic food, and concurrentlydiagnosed with diabetes mellitus, neoplasia,oral disease, or dermatopathy. Practitionerscan use these data to strongly advocate forthe maintenance of feline patients at idealbody condition.

INTRODUCTIONThe prevalence of obesity in domestic felinepopulations has been estimated from a limit-ed number of studies. Results from thesestudies range from a combined overweightand obesity prevalence of 40% in a popula-tion of cats from a Danish veterinaryh o s p i t a l1 to 25% in a population of adult catsfrom a northeastern United States veterinaryhospitals population.2 The relationship of obe-sity to the development of disease in cats isof much clinical interest, but has been thesubject of limited research. A cohort study ofdisease risk in obese and overweight catsrevealed associations with diabetes mellitus,lameness, and skin disease.3 More numerousstudies in canine populations have foundrelationships between canine obesity andmusculoskeletal disorders,4-6 c a r d i o v a s c u l a rp r o b l e m s ,6 glucose intolerance and diabetesm e l l i t u s ,7 , 8 h y p e r t e n s i o n ,9 immune dysfunc-

Prevalence and Risk Factors forObesity in Adult Cats from PrivateUS Veterinary PracticesElizabeth M. Lund, DVM, MPH, PhD*

P. Jane Armstrong, DVM, MBA*

Claudia A. Kirk, DVM, PhD†

Jeffrey S. Klausner, DVM

*Veterinary Clinical Sciences Department College of Veterinary MedicineUniversity of MinnesotaSt. Paul, MN

†Advanced Research DepartmentHill’s Pet Nutrition, Inc.Science and Technology CenterTopeka, KS

This research was supported by the Mark MorrisInstitute with a grant from Hill’s Pet Nutrition.*Dr. Lund is now with DataDogs, Lake Elmo, MN. *Dr. Klausner is now with the Dean’s Office at theUniversity of Minnesota College of VeterinaryMedicine, St. Paul, MN.†Dr. Kirk is now with the Department of Small AnimalClinical Sciences, Veterinary Teaching Hospital,College of Veterinary Medicine, University ofTennessee, Knoxville, TN.

KEY WORDS: Epidemiology, population,overweight body condition, feline

ABSTRACTUsing a cross-sectional study design, theprevalence of overweight and obesity inadult cats seen by US veterinarians during1995 was determined. Risk factors for over-weight and obesity were also determinedfrom the following variables: age, breed,gender, body condition score, food type,reported concurrent disease, and geographicregion. Thirty-five percent of adult cats (n =8,159) were overweight or obese. Frommultivariate analyses, overweight cats weremore likely to be neutered, male, eating apremium or therapeutic food, and to be con-currently diagnosed with disease of the oralcavity or urinary tract. Obese cats weremore likely to be of the Domestic Shorthair,Domestic Longhair, Domestic Mediumhair,

Intern J Appl Res Vet Med • Vol. 3, No. 2, 200588

t i o n ,1 0 and bladder1 1 and mammary cancer.1 2

Because of the known relationship of humanobesity to certain diseases, such as hyperten-sion, cardiovascular disease, diabetes melli-tus, stroke, osteoarthritis, some cancers, andpremature mortality, it is speculated that sim-ilar relationships may hold true for cats.1 3 , 1 4

Knowledge of obesity/overweight as a riskfactor for disease can heighten awareness andtarget health screening of cats. With evidencefrom feline research studies as a tool, practi-tioners may be able to advocate more strong-ly for obesity prevention and weightreduction plans for their clients’ pets.

The major objectives of this study wereto determine the prevalence of overweightand obesity in adult feline populations seenby private veterinary practitioners in theUnited States and to elucidate basic risk fac-tors for overweight and obesity, that is, age,breed, gender and neuter status, food type,concurrent disease, and geographic regionof residence. Such associations or risk fac-tors are very important for identifying catsat risk for obesity and for identifying whichdiseases are more likely to afflict over-weight and obese cats.

MATERIALS AND METHODSThe general study methods and populationfrom the National Companion Animal Study(NCAS) have been previously described ind e t a i l .1 5 Using a proprietarypractice man-agement system (Advanced VeterinarySystems [AVS], VetConnect Systems, EauClaire, WI, USA), data collected included:date of birth, diagnoses (new and existing),breed, gender, neuter status, body conditionscore (BCS),1 6 major and minor food typeand form, and geographic region.

Body condition score. Body conditionscores were assigned as a whole numbervalue from 1 to 5 by the veterinarian exam-ining the cat. A BCS of 1 indicated the ani-mal was excessively thin, 3 was ideal, and 5was obese. The amount of fat cover over thecats’ ribs and the abdominal contour wereused in assessing body condition. (Criteriafor assessing the abdomen were not consid-

ered in assigning a BCS in cats less than 6months of age because kittens often havependulous abdomens.)

All participating clinics were providedwith a training videotape on the use of theBCS scale. Multiple body condition scoresover the year of data collection were aver-aged to obtain a single BCS per animal.Average BCS was used to place cats in eitherthe overweight or obese category for thisanalysis. Obese animals were defined as hav-ing an average BCS greater than 4.5 and lessthan or equal to 5.0. Overweight animalswere defined as having an average BCSgreater than 3.5 and less than or equal to 4.5.

Food type and form. Food categorieswere Popular Dry, Premium Dry,Therapeutic Dry, Popular Canned, PremiumCanned, Therapeutic Canned, Homemade,Semi-moist, and Other. “Popular” describedbrands typically purchased in a grocerystore, farm store, or large-format pet retail-er. “Premium” was used to define brandstypically purchased in a veterinary practice,pet store, or large-format pet retailer.“Therapeutic” referred to brands prescribedand sold by veterinarians for the treatmentor prevention of disease. “Homemade”referred to a complete diet prepared at homefrom individual food ingredients. “Other”included meat or other food products, com-mercial treats, or table scraps.

The cat owner chose one major foodcomponent (greater or equal to 60% of foodby volume) and a minor food component(remainder of food, if applicable).Additional food codes were added at subse-quent patient visits only if changes in feed-ing had occurred. Only major diet (greaterthan or equal to 60% of food fed by vol-ume) was included in this analysis; semi-moist food was combined with food in the“Other” category due to the low frequencyof feeding semi-moist as a major food.

Geographic region. West and EastSouth Central were combined to form SouthCentral; New England and Middle Atlanticwere combined to Northeast; Pacific includ-ed Alaska and Hawaii.

89Intern J Appl Res Vet Med • Vol. 3, No. 2, 2005

D i a g n o s e s . New and existing diagnosesfor a specific cat at each clinic visit wererecorded using a system for standardizedn o m e n c l a t u r e .1 7 Individual diseases and dis-ease categories were included in the analy-sis based on hypotheses informed byliterature review. Subjects were countedonce in a category for one or more diag-noses reported during the study that fell intothat category.

Statistical Methods The adult cat population was defined as ani-mals over 1 year of age; analyses were con-ducted on cats that had at least one diagnosis(including “Healthy”) of any kind recordedover the study period (i.e., these cats consti-tuted the population denominator for thestudy) and had at least one recorded BCS.The SAS statistical program, 6t h e d i t i o n18 ( S A SInstitute, Cary, NC, USA), was used to gener-ate frequencies, prevalence estimates, univari-ate distributions, and multivariate analyses.

Disease and disease category prevalencewas estimated for obese and overweight catsby BCS for all diseases included in the mul-tivariate analysis. Overall adult populationprevalence estimates for obesity and over-weight were generated using 2 methods:average BCS and reported diagnoses forobesity and overweight (that is, when either“obesity” or “overweight” was entered as adiagnosis for that visit by the veterinarian).

Univariate distributions were generatedto describe the prevalence of overweight andobesity by age, breed, gender, and neuterstatus of the population. To control for con-founding of the relationship between riskfactors and overweight or obesity, a multi-variate analysis was conducted using fulllogistic regression models.1 9 Confounders arefactors—for example, age or breed—that arerelated to both the exposure being examinedand the outcome (overweight or obesity).Confounders can distort assessment of therelationship between the exposure of interestand the outcome. For example, when com-paring state-specific cancer rates betweenpeople living in Colorado versus Florida,

lower cancer rates might be observed inColorado. Since age is a predictor of cancerrisk, the rates may reflect the older popula-tion in Florida compared with a youngerpopulation in Colorado. Age, therefore, isconfounding the potential differencebetween rates. Because the multivariatemodel controls for confounding by age,breed, and so on, the risk factors generatedare therefore independent predictors of obe-sity. Variables in the multivariate models forthis study included age in years; 10 mostprevalent breeds; gender; neuter status;major food type consumed (greater than orequal to 60% of food volume fed); concur-rent disease; and geographic region o fUnited States.

Concurrent diseases and disease cate-gories included in the feline model included:arthritis, dermatopathy, diabetes mellitus,gastrointestinal disease, heart disease, hepat-ic lipidosis, lameness, musculoskeletal dis-ease, neoplasia, oral disease, and urinarydisease (see Appendix). An interaction termfor gender and neuter status was also includ-ed in all logistic models to account for thepotential of differential risk for obesity formales versus females by neuter status. Thereferent category for food type was popu-lar/dry; the West North Central region wasthe referent category for geographic region.For all statistical tests, α = .05.

In the multivariate analysis, the preva-lence odds ratio (OR) was used as anapproximation of relative risk. Relative riskis a measure of the strength of the associa-tion between a disease and potential risk fac-tors like age and breed. When the OR isgreater than one, the factor is found to beassociated with an increased risk of that dis-ease. For example, the OR for obesity and aconcurrent diagnosis of diabetes mellitus is2.2; an obese cat is more than twice as likelyto be diagnosed with diabetes compared withan adult cat of normal/underweight bodycondition (all other factors being equal)(Table 1). A relative risk estimate does notnecessarily reflect a causal relationship (forexample, that obesity causes diabetes melli-


tus), but rather an association between thedisease and the predictive factor.

A Hosmer-Lemeshow goodness-of-fitt e s t19 was estimated for each disease model todetermine how well the model explained thevariability in the observed data. The higherthe P value, the better the “fit” of the modelto explain the relationship of the independ-ent variables (risk factors) to the dependentvariable (overweight or obesity). The nullhypothesis for this statistic is that the modelfits; a P value greater than .05 leads one tofail to reject the null hypothesis.

RESULTSA total of 8,159 adult cats with a reportedBCS were included in this analysis of aNational Companion Animal Study popula-tion of 11,102 adult cats. Prevalence of obe-sity in this adult private practice populationbased on body condition assigned by veteri-narians was 6.4% for adult cats; 28.7% wereoverweight. A total of 35.1% of cats olderthan 1 year of age, therefore, were eitheroverweight or obese.

Prevalence of obesity for adult catsbased on reported diagnoses (that is, whenobesity was entered as a diagnostic code)was 2.2%; the prevalence of overweightbased on reported diagnosis was 1.4%. Only3.2% of the adult cats identified as over-weight based on BCS were also coded bythe veterinarian as “overweight.” Amongcats identified as obese by BCS, 21.5% hada diagnostic code of “obesity” entered bythe veterinarian.

Prevalence of individual disease and dis-ease categories included by hypothesis inthe analysis are detailed in Table 2. Oraldisease, dermatopathy, and urinary diseasewere the most common diseases included inthis analysis. Over 40% of obese and over-weight adult cats were diagnosed with atleast 1 disease in the oral disease category.

The prevalence of obesity and over-weight (Figure 1) is greatest for cats in theirmiddle-aged years (between 5 and 11 years).Neutered males (Figure 2) had the highestprevalence of overweight (33.3%) and obesi-ty (7.7%); intact females had the lowest

Table 1. Multivariate Disease Models: Risk Factors for Overweight and Obese Adult Cats (N = 8,159)

Risk Factors(P-value) Odds Ratio (CI*) β†

Overweight Cats Male (.05) 1.4 (1.0,1.8) .31(n = 2,342) Neuter (.006) 1.4 (1.1,1.7) .30

Premium foods (< .0001) 1.4 (1.2,1.5) .31Therapeutic foods (.002) 1.3 (1.1,1.6) .24Oral disease (< .0001) 1.8 (1.6,2.0) .57Urinary disease (.0002) 1.6 (1.3,1.9) .46

Obese Cats Domestic Shorthair (.02) 10.5 (1.5,76.1) 2.4(n = 522) Domestic Mediumhair (.03) 10.3 (1.3,78.7) 2.3

Domestic Longhair (.04) 8.0 (1.1,58.5) 2.1Manx (.04) 13.0 (1.1,151.1) 2.6

Mixed breed (.05) 8.1 (1.0,63.3) 2.1Premium foods (<. 0001) 1.8 (1.5,2.2) .60

Therapeutic foods (< .0001) 2.4 (1.8,3.3) .86Dermatopathy (.006) 1.5 (1.1,2.0) .39

Diabetes mellitus (.01) 2.2 (1.1, 4.4) .88Neoplasm (.04) 2.0 (1.0, 3.8) .67

Oral disease (.002) 1.4 (1.1,1.7) .31*95% confidence interval (CI).†Parameter estimate/coefficient from logistic model.


prevalence of overweight (20.4%) and obesi-ty (4.8%). Overweight prevalence of 30% ormore (Figure 3) was found in the DomesticShorthair (DSH), Domestic Mediumhair(DMH), unknown, and Manx breeds. Breedprevalence for obesity ranged from 1.8%(Persian, Himalayan) to 9.4% (Manx).

In the multivariate analysis (Table 1),overweight cats were more likely to beneutered, male, eating a premium or therapeu-tic food, and were more likely to be concur-rently diagnosed with oral or urinary tract

disease. Obese catswere likely to be ofthe DomesticShorthair (DSH),D o m e s t i cMediumhair (DMH),Domestic Longhair(DLH), Mixed orManx breeds; fed apremium or therapeu-tic food, and morelikely to be concur-rently diagnosed withdiabetes mellitus, oraldisease, dermatopa-thy, or neoplasia.

No associationwas found betweenoverweight or obesityand geographic region

of residence or age. Interaction between genderand neuter status did not emerge as a signifi-cant predictor in the multivariate models.Probabilities calculated for the Goodness of Fitstatistics were: P = 0.3 (overweight model) andP = 0.9 (obesity model).

DISCUSSIONThis study documents a combined overallprevalence of overweight and obesity of 35%in the adult cat population in the UnitedStates. Obesity alone had a prevalence of

Table 2. Disease and Disease Category* Prevalence by Body Condition Category for Adult Cats

Obese Overweight Normal and(4.5 <BCS† ≤ 5.0) (3.5 < BCS ≤ 4.5) Underweight

n = 639 n = 2,792 (1.0 < BCS < 3.5)Disease/Disease Category n = 6,434Arthritis 0.3% 0.4% 0.3%Dermatopathy 12.8% 9.3% 9.3%Diabetes mellitus 1.9% 0.6% 0.8%Gastrointestinal disease 4.2% 2.7% 2.8%Heart disease 1.7% 2.1% 3.1%Hepatic lipidosis 0.2% .04% .09%Lameness 0.9% 1.1% 1.2%Musculoskeletal disease 0.8% 0.7% 0.7%Neoplasia 1.7% 1.0% 1.4%Oral disease 42.3% 44.3% 31.5%Urinary disease 7.4% 7.1% 4.8%*Cat was reported to have at least 1 disease in category.†BCS indicates body condition score.

Figure 1. Prevalence of obesity and overweight by year of age for adult cats.


6.4%. The NCAS isthe first nationwidestudy to providethese important per-centages. Of particu-lar note is that morethan a third (41.0%)of all castrated malecats in this studywere overweight orobese. Between theages of 5 and 11years, over 40% ofall cats were over-weight or obese. Asexpected, based onprevious research onthe effects of neuter-ing on energyrequirements, intactcats were underrepre-sented in the over-weight and obesec a t e g o r i e s .2 0 , 2 1 T h edata suggest that theprimary target ofoverweight and obe-sity preventionshould be young andm i d d l e - a g e d ,neutered cats, espe-cially males. Recentcanine data suggestthat the ideal body condition range for healthmaintenance for dogs is lower than previouslyt h o u g h t .2 2 In this study, euthanasia (end-of-lifedecisions) due to incapacitating osteoarthritisoccurred earlier in dogs when body conditionwas not maintained within an ideal range.Although cats are not prone to developingclinically apparent osteoarthritis as they age,arthritis is evident radiographically.2 3 B e c a u s eof this and other disease risks, similar recom-mendations may need to be extended to cats.

Data from this study also demonstratethat the prevalence of overweight or obesitydiminishes in very old cats. A cross-section-al study cannot determine whether this wasdue to weight loss in cats as they age or the

death of overweight and obese cats at anearlier age than their lighter-weight counter-parts. A recent report on weight distributionin a large colony of cats suggests that thisobservation is likely due to weight loss witha g e .24 Our results suggest that it may be pru-dent to take steps to encourage maintenanceof adequate body weight in geriatric catsbefore significant weight loss is noted. Thismay require a change to a higher-caloric-density food in aging cats even while theirBCS is still optimal.

Breed documentation is less certain incats than in dogs, with the majority of catsbeing designated DSH, DMH, DLH orMixed types without pedigree information

Figure 2. Prevalence of obesity and overweight by gender for adult cats.

Figure 3. Prevalence of obesity and overweight by breed* for adult cats.*In order of decreasing overall breed frequency. DSH indicates domestic shorthair;DLH, domestic longhair; DMH, domestic mediumhair.


to make such categorization. Regardless,some useful breed-specific data emergedfrom this study. Based on the multivariateanalysis, Manx cats were at risk for obesity.Conversely, Siamese cats, often anecdotallysaid to be prone to obesity, were not foundto be at risk for overweight or obesity.

The disease associations documentedhere are of particular interest as they pro-vide additional evidence of the linksbetween overweight or obesity and specificdiseases in cats. Both overweight and obesecats are at greater risk of oral disease thanthe rest of the adult cat population.Overweight cats are at increased risk forurinary tract disease; however, a relation-ship between obesity and urinary tract dis-ease as a category was not found, possiblydue to a lack of statistical power becausethere were fewer obese cats and/or effectsof grouping many diseases into one catego-ry. Obese cats are at increased risk for dia-betes mellitus, corroborating previous felinestudies suggesting this association.3,25

Obesity therefore joins gender (male-neutered) as a risk factor for diabetes melli-tus.25 Obesity also increased risk fordermatopathy and neoplasia in our study.The relationship between obesity and skindisease supports the finding in an earliercohort study of cats.3 An association ofobesity with neoplasia is interesting; how-ever, risk for specific types of cancer wouldrequire study designs more suited for thestudy of rare disease. Despite the greaterprevalence of gastrointestinal disease inobese cats (Table 2), the multivariate analy-sis did not reveal a significant associationof obesity or overweight with this group ofdiseases.

Feeding premium and therapeutic foodswas associated with increased risk of over-weight and obesity in this study. Premiumfoods, defined for this study as nontherapeuticbrands typically purchased from a veterinaryclinic, pet store, or large-format pet productr e t a i l e r , are typically higher in caloric densitythan “popular” dry foods. Our results may

indicate that the caloric density of premiumfoods as they are fed (in quantity or frequen-cy), may exceed the needs of many cats.Therapeutic foods were defined as brandsprescribed and sold by a veterinarian for thetreatment or prevention of disease. This studydid not collect data on the indication for beingfed a therapeutic food (for example, weightmanagement). Presumably, some percentageof overweight or obese cats was being fedtherapeutic foods for this reason.

Region did not emerge as a risk factorfor adult cat obesity or overweight andcould reflect the fact that the lifestyle ofcats across the geographic regions of theUnited States is fairly uniform and does notinfluence the risk for obesity/overweight.However, it is also possible that we wereunable to discern any differences based onlifestyle since data on whether cats livedpredominately indoors or outdoors were notcollected. Previous studies have identifiedinactivity,3,26 indoor living,27 and apartmentdwelling3 as risk factors for feline obesity.

We observed dramatic underreporting ofoverweight and obesity when comparingprevalence from BCS results to reporteddiagnoses, especially for overweight cats.For example, the prevalence of obesitydefined by BCS for cats was 6.4% com-pared with 2.2% when defined by reporteddiagnostic code. The difference betweenoverweight prevalence in cats defined byBCS (28.7%) and reported diagnosis (1.4%)was even greater. Underreporting of thediagnosis of obesity and overweight mayreflect the perception of practitioners thatobesity/overweight does not constitute a dis-ease state, especially for animals in theoverweight category. Alternatively, theknowledge that BCS was being collected forthis study may have reduced the frequencywith which overweight or obesity wasrecorded as a diagnosis.

Major strengths of the study reportedhere include the size and geographic distribu-tion of the population studied as well as theability to generalize the results to privatepractice populations in the United States.


Although the data for this study were collect-ed during 1995, the scope and the results ofthe study remain relevant to the contempo-rary description and assessment of the obesi-ty problem of cats seen in private companionanimal practice. Surveillance and monitoringof the health of US cats is especially relevantin light of the current epidemic of humanobesity. Despite the “age” of the data, theNCAS provides knowledge that will enhancethe health care of feline populations today.

Limitations of the study include the useof a cross-sectional study design, a lack ofstandardized case definitions, and thepotential for underreporting of cases.15 Across-sectional study is of limited use fordiscerning disease causality as well as riskfor rare diseases.28 For the results reportedin this study, the lack of case definitionsand the potential for disease misclassifica-tion must be considered. Grouping of indi-vidual diagnoses into system categories wasnecessary to increase the efficiency of thestatistical analysis and to minimize errorfrom disease misclassification. The failureof this study to document a risk relationshipbetween overweight or obesity and anuncommon disease, such as hepatic lipido-sis, does not prove or disprove such a rela-

tionship. Misclassification of the outcome(overweight or obesity) by BCS must alsobe considered as a source of differencesbetween our study results and others as theassessment of body condition has not beenstandardized across research studies.

In addition to providing importantdescriptive data on the problem of obesityin cats seen by practitioners in the UnitedStates, the factors reported in this study canhelp practitioners anticipate predispositionto obesity/overweight. Feeding practices ofneutered pets may need to be more closelyguided by veterinarians, especially inregard to feeding calorie-dense premiumfoods. Future studies should ideally includeadditional lifestyle factors such asindoor/outdoor status as variables to helpfully model and predict obesity. A cohortdesign would allow cats to be followedover their lifetime, enabling determinationof which cats transition from overweight toobesity as well as to elucidate whetherobese cats are dying at younger ages thantheir normal-weight cohorts. Finally, withthese study results, the ability of practition-ers to communicate the importance ofmaintaining feline patients at ideal bodycondition will be strengthened.

APPENDIX. Diseases Diagnosed by Veterinarians in Study CatsDermatopathy (prevalent diagnoses > .05%): acne, alopecia (general, psychogenic, pustular), dandruff,dermatitis (allergic, flea bite, food allergy, foxtail, fly bite, general, miliary, moist, paronychial, pruritic,seborrheic), dermatophytosis, folliculitis, ingrown toenail, pyoderma (deep, general).Gastrointestinal Disease (prevalent diagnoses > .05%): anal sac disease, chronic diarrhea, colitis (acute,general), constipation, enteritis, gastritis, gastritis (acute, general), gastroenteritis (bacterial, eosinophilic,general), inflammatory bowel disease (eosinophilic, lymphoplasmacytic, mixed), megacolon. Heart Disease (prevalent diagnoses > .05%): congestive heart failure, cardiomyopathy (congestive, dilat-ed, general, hypertrophic, taurine deficiency), heart disease, heart murmur (acquired, general), hyperten-sion.Musculoskeletal Disease (prevalent diagnoses > .05%): arthritis, cruciate ligament rupture, patellar luxa-tion, soft tissue injury, osteomyelitis.Neoplasia (prevalent diagnoses > .05%): adenocarcinoma, basal cell carcinoma, fibrosarcoma, lipoma,lymphosarcoma, mammary tumor, mast cell tumor, squamous cell carcinoma, tumor-unspecified.Oral Disease (prevalent diagnoses > .05%): cervical lesion, dental caries, dental calculus, dental calcu-lus/gingivitis, fractured tooth, gingivitis, periodontal disease, ptyalism, stomatitis.Urinary Tract Disease (prevalent diagnoses > .05%): acute cystitis (acute, bacterial, chronic, general),bladder stone(s), feline urologic syndrome, obstruction, urinary tract infection, urolithiasis (calciumoxalate, struvite, unspecified).


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