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Prevalence and Risk Factors for
Obesity in Adult Dogs from Private
US Veterinary Practices
Elizabeth M. Lund, DVM, MPH, PhD1
P. Jane Armstrong, DVM, MS, MBA1Claudia A. Kirk, DVM, PhD2
Jeffrey S. Klausner, DVM, MS1
Veterinary Clinical Sciences Department
College of Veterinary Medicine
University of Minnesota
St. Paul, Minnesota
2Advanced Research Department
Hill's Pet Nutrition, Inc.
Science and Technology Center
Topeka, Kansas
1

KEY WORDS: epidemiology, population,
overweight, body condition, canine, obesity, risk factor
ABSTRACT
Using a cross-sectional study design, theprevalence of overweight and obesity indogs over 1 year of age seen by US veterinarians during 1995 was determined. Risk
factors for overweight and obesity were also
determined from the following variables:
age, breed, gender, body condition score,
food type, reported concurrent disease, andgeographic region. Thirty-four percent of
adult dogs (n = 21,754) were overweight orobese. From multivariate analyses, overweight dogs were more likely to be older, ofcertain breeds (Cocker Spaniel, Labrador
Retriever, Dalmatian, Dachshund,Rottweiler, Golden Retriever, Shetland
Sheepdog, Mixed-breed), neutered, and to
consume a semi-moist food as their major
diet source. In addition, overweight adultdogs were most likely to reside in the
Pacific, South Central, East North Central,or Northeast regions of the United States
and be diagnosed with hyperadrenocorticism, ruptured cruciate ligament, hypothyIntern J Appl Res Vet Med • Vol. 4, No. 2, 2006.

roidism, lower urinary tract disease, or oraldisease. Obese dogs were more likely to beolder, of certain breeds (Shetland Sheepdog,
Dachshund, and Golden Retriever),neutered, and to consume "other" foods(meat or other food products, commercial
treats, or table scraps), homemade, orcanned foods as their major diet source.
Also, obese adult dogs were more likely tolive in the Pacific or Northeast region of theUnited States and be diagnosed withhypothyroidism, diabetes mellitus, pancreatitis, ruptured cruciate ligament, or neoplasia. Practitioners can use these data tocounsel dog owners on obesity prevention,
especially owners of dogs with ≥1 risk factors for overweight/obesity, and to strongly
advocate for the maintenance of canine
patients at an ideal body condition.
INTRODUCTION
The prevalence of combined overweight andobesity in domestic canine populations has
been reported to range from 23%1 to 41%.2
Other studies in canine pet populations havefound relationships between canine obesity
and musculoskeletal disorders,3-5 cardiovascular problems,5 glucose intolerance and177

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diabetes mellitus,6,7 and bladder8 and mammary cancer.9 Experimentally, relationships
have also been shown between canine obesity and hypertension10 and immune dysfunction.11 Because of the known
relationship of human obesity to certain diseases (eg, hypertension, cardiovascular disease, diabetes mellitus, stroke, osteoarthritis,and some cancers) and premature mortality,
similar relationships may hold true fordogs.12,13 Knowledge of obesity/overweight
as a risk factor for disease can heighten
awareness and target health screening ofdogs. With evidence from canine researchstudies as a tool, practitioners may be able
to advocate more strongly for obesity prevention and weight reduction plans for theirclients' pets.
The major objectives of this study were
to determine the prevalence of overweight
and obesity in adult canine populations seen
by private veterinary practitioners in the
United States and to elucidate basic risk factors for overweight and obesity, that is, age,
breed, gender, and neuter status, food type,concurrent disease, and geographic regionof residence. Such associations or risk factors are very important for identifying dogs
at risk for obesity and for identifying which
diseases are more likely to afflict overweight and obese dogs.
MATERIALS AND METHODS
The general study methods and populationfrom the National Companion Animal Study(NCAS) have been previously described indetail.14 A proprietary practice management
system (Advanced Veterinary Systems[AVS], VetConnect Systems, Eau Claire,
WI) was used for data collection, including:date of birth, diagnoses (new and existing),
breed, gender, neuter status, body condition
score (BCS), major and minor food type andform, and geographic region.

was ideal, and 5 was obese. The amount of
fat cover over the dogs' ribs and tail baseand the abdominal contour were used inassessing body condition.
All participating clinics were provided
with a training videotape on the use of the
BCS scale. Multiple body condition scores
over the year of data collection were averaged to obtain a single BCS per animal.
Average BCS was used to place dogs ineither the overweight or obese category forthis analysis. Obese animals were defined ashaving an average BCS greater than 4.5.
Overweight animals were defined as having
an average BCS greater than 3.5 and lessthan or equal to 4.5.
Food Type and Form
Food categories were Popular Dry,
Premium Dry, Therapeutic Dry, Popular
Canned, Premium Canned, Therapeutic
Canned, Homemade, Semi-moist, andOther. "Popular" described brands typicallypurchased in a grocery store, farm store, orlarge-format pet retailer. "Premium" wasused to define brands typically purchased ina veterinary practice, pet store, or large-format pet retailer. "Therapeutic" referred tobrands prescribed and sold by veterinarians
for the treatment or prevention of disease.
"Homemade" referred to a complete dietprepared at home from individual foodingredients. "Other" included meat or otherfood products, commercial treats, or tablescraps.
The dog owner chose 1 major food component (≥60% of food by volume) and aminor food component (remainder of food,
if applicable). Additional food codes wereadded at subsequent patient visits only ifchanges in feeding had occurred. Only
major diet (≥60% of food fed by volume)
was included in this analysis.

Body Condition Score
Body condition scores were assigned as awhole number value from 1 to 5 by the veterinarian examining the dog. A BCS of 1
indicated the animal was excessively thin, 3

Geographic Region
West and East South Central were combined to form South Central; New Englandand Middle Atlantic were combined to
Northeast; Pacific included Alaska and
Hawaii.15

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Diagnoses
New and existing diagnoses for a specificdog at each clinic visit were recorded usinga system for standardized nomenclature.16
Subjects were counted only once in a category for ≥1 diagnoses reported during thestudy that fell into that category.
Statistical Methods
The adult dog population was defined asanimals over 1 year of age; analyses wereconducted on adult dogs that had ≥1 diagnosis (including "Healthy") of any kindrecorded over the study period and had ≥1
recorded BCS (ie, these dogs constituted the
population denominator for the study). The
SAS statistical program, 9th edition(Copyright© 2005 SAS Institute Inc., SAS
Campus Drive, Cary, NC, USA.), was used
to generate frequencies, prevalence estimates, univariate distributions, and multivariate analyses.
Disease and disease category prevalence
were estimated for obese and overweightdogs by BCS for all diseases included in themultivariate analysis. Overall adult population prevalence estimates for obesity andoverweight 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 generated
to describe the prevalence of overweight
and obesity by age, breed, gender, andneuter status of the population. To control
for confounding of the relationship between
risk factors and overweight or obesity, amultivariate analysis was conducted using
full logistic regression models.17
Confounders are factors—for example, age
or breed—that are related to both the exposure being examined and the outcome(overweight or obesity). Confounders candistort assessment of the relationshipbetween the exposure of interest and theoutcome. For example, when comparing
state-specific cancer rates between people
living in Colorado versus Florida, lower

cancer rates might be observed inColorado. Since age is a predictor of cancer risk, the differences in rates may reflect
the older state population of Florida compared to a younger Colorado population.
Age, therefore, is confounding the potential difference between rates. Because themultivariate model controls for confounding by age, breed, and so on, the risk factors generated are therefore independent
predictors of obesity.
Variables in the multivariate models forthis study included age in years; 25 mostprevalent breeds; gender; neuter status;
major food type consumed; concurrent disease; and geographic region of UnitedStates. The referent category for food type
was popular/dry; the West North Central
region was the referent category for geographic region.
Individual diseases and disease categories were included in the analysis basedon hypotheses informed by literature
review. Individual diseases included in thecanine model included arthritis/osteoarthritis, diabetes mellitus, dystocia, hypertension, hyperadrenocorticism,
hypothyroidism, intervertebral disc disease,lameness, neoplasia, oral disease, pancreatitis, paresis/ataxia, ruptured cruciate ligament, and tracheal collapse. Diseasecategories included in the model were dermatopathy, gastrointestinal disease, heartdisease, musculoskeletal disease, oral disease, renal disease, reproductive disease,respiratory disease, and lower urinary tract
disease (see Appendix). For all statisticaltests, α = 0.05. An interaction term for gender and neuter status was included in both
multivariate models.
In the multivariate analysis, the prevalence odds ratio (OR) was used as an
approximation of relative risk. Relative risk
is a measure of the strength of the association between a disease and potential risk
factors like age and breed. When the OR is>1, the factor is found to be associated withan increased risk of that disease. For example, the OR for obesity and a concurrent

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diagnosis of diabetes mellitus was found tobe 2.6; that is, an obese dog is 2.6 times
more likely to be diagnosed with diabetes
compared with an adult dog of
normal/underweight body condition (allother factors being equal) A relative risk
estimate does not necessarily reflect a
causal relationship (for example, that obesity causes diabetes mellitus), but rather anassociation between the disease and the predictive factor.
A Hosmer-Lemeshow goodness-of-fit
test17 was estimated for each disease model
to determine how well the model explained
the variability in the observed data. The
higher the P value, the better the "fit" of themodel to explain the relationship of the
independent variables (risk factors) to thedependent variable (overweight or obesity).
The null hypothesis for this statistic is thatthe model fits; a P value > 0.05 leads one to
fail to reject the null hypothesis.
RESULTSA total of 21,754 adult dogs with a reported
BCS were included in this analysis from a
National Companion Animal Study population of 24,975 adult dogs. Prevalence ofobesity in this private practice population
based on body condition assigned by veterinarians was 5.1% for adult dogs; prevalenceof overweight was 29.0%. A total of 34.1%
of dogs older than 1 year of age, therefore,
were either overweight or obese.
Prevalence of obesity for adult dogs
based on reported diagnoses (that is, when
obesity was entered as a diagnostic code)
was 2.5%; the prevalence of overweightbased on reported diagnosis was 1.4%. Only
3.8% of the adult dogs identified as overweight based on BCS were also coded by
the veterinarian as "overweight." Amongdogs identified as obese by BCS, 31.0%
also had a diagnostic code of "obesity"
entered by the veterinarian.
Prevalence of individual diseases anddisease categories included by hypothesis in
the analysis are detailed in Table 1. Oraldisease, dermatopathy, and neoplasia werethe most common diseases included in thisanalysis. Thirty-four percent of obese andoverweight adult dogs were diagnosed with
≥1 disease in the oral disease category.
The prevalence of obesity and overweight (Figure 1) is greatest for dogs intheir middle-aged years, roughly between 6
and 10 years. Neutered males and spayedfemales (Figure 2) had the highest prevalence of overweight (32.0% and 32.6%) andobesity (5.5% and 5.6%); intact males had
the lowest prevalence of overweight(20.0%) and obesity (3.6%). Overweight
prevalence of 30% or more (Figure 3) was
found for Cocker Spaniels, Beagles,
Labrador Retrievers, Golden Retrievers,
Shetland Sheepdogs, Rottweilers, andMixed-breed dogs. Among the 10 mostcommon breeds, obesity prevalence ranged
from 2.6% (Poodle [all sizes]) to 10.0%(Shetland Sheepdog).
In the multivariate analysis (Table 2),
overweight dogs were more likely to be to
be older (OR = 1.1), of certain breeds(Cocker Spaniel [OR = 1.9], Dachshund[OR = 1.6], Dalmatian [OR = 1.6], Labrador
Retriever [OR = 1.6], Rottweiler [OR =1.6], Golden Retriever [OR = 1.5], Shetland
Sheepdog [OR = 1.4], and Mixed-breed
dogs [OR = 1.1]) neutered (OR = 1.5), andto consume semi-moist foods as their major
diet (OR = 1.5). In addition, overweight
adult dogs were most likely to reside in the
Pacific (OR = 1.4), South Central (OR =1.3), East North Central or Northeast (both
OR = 1.2) regions and be diagnosed withhyperadrenocorticism (OR = 2.4), ruptured
cruciate ligament (OR = 1.7), hypothyroidism (OR = 1.4), lower urinary tract disease (OR = 1.3), or oral disease (OR = 1.1).
Obese dogs were more likely to be older(OR = 1.1), of certain breeds (Shetland
Sheepdog [OR = 1.9], Dachshund [OR =1.7], Golden Retriever [OR = 1.6], neutered[OR = 1.3] and to consume "other" (meat orother food products, commercial treats, ortable scraps) foods (OR = 2.3), homemade(OR = 1.9), or canned (OR = 1.4) foods as
their major diet source. Also, obese adult

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dogs were more likely to live in the Pacific(OR = 1.7) or Northeast (OR = 1.3) regionof the United States and be diagnosed withhypothyroidism (OR = 2.8), diabetes mellitus (OR = 2.6), pancreatitis (OR = 2.2), ruptured cruciate ligament (OR = 2.1), or
neoplasia (OR = 1.4).

more than 40% of all dogs were overweightor obese. Intact dogs were underrepresented
in the overweight and obese categories. The
overweight/obesity risk for neutered dogs
reported here is also consistent with otherstudy results.2,18 Multiple studies have documented a link between spaying or neuteringand decreased energy requirements.19-23

Table 1. Disease and Disease Category* Prevalence by Body Condition Category for Adult Dogs.

Disease/Disease Category

Obese(4.5 < BCS ≤ 5.0)
n = 1099

Overweight(3.5 < BCS ≤ 4.5)
n = 6302

Normal and Underweight(1.0 < BCS < 3.5)
n = 14,353

Arthritis/Osteoarthritis
Dermatopathy
Diabetes mellitus
Dystocia
Gastrointestinal disease
Heart disease
Hypertension
Hyperadrenocortism
Hypothyroidism
Intervertebral disc disease
Lameness
Lower urinary tract disease
Musculoskeletal disease
Neoplasia
Oral disease
Pancreatitis
Paresis/Ataxia
Renal disease
Reproductive disease
Respiratory disease
Ruptured cruciate ligament
Tracheal collapse

4.2%
18.9%
0.7%
0.0%
6.6%
3.8%
0.0%
0.6%
3.3%
1.7%
4.3%
3.6%
8.6%
10.3%
34.1%
0.9%
0.3%
1.1%
0.5%
3.5%
1.6%
0.4%

4.0%
18.6%
0.4%
0.1%
7.3%
3.4%
.08%
0.5%
1.5%
2.0%
3.7%
3.6%
8.3%
7.6%
30.5%
0.5%
0.2%
0.8%
1.0%
3.2%
1.1%
0.2%

2.4%
17.2%
0.3%
0.2%
7.3%
3.9%
.03%
0.2%
0.8%
1.8%
2.9%
3.0%
6.1%
5.3%
25.7%
0.4%
0.3%
0.9%
1.4%
3.6%
0.5%
0.1%

BCS = body condition score.
*Dog was reported to have at least 1 disease in category.

DISCUSSION
This study documents a combined overall
prevalence of overweight and obesity of
34.1% in the adult dog population seen in
private practices across the United States.
Obesity alone had a prevalence of 5.1%.
This is the first large-scale, nationally based
study to provide these important percentages. Of particular note is that roughly 38%
of all castrated male and spayed female
adult dogs in this study were overweight orobese. Between the ages of 6 and 10 years,

The data suggest that the primary targetof overweight and obesity prevention should
be young and middle-aged, spayed andneutered dogs. Since weight gain generally
occurs slowly and insidiously, targeting
obesity prevention counseling at the time ofthe spay or neuter surgery may be prudent,
especially for dogs of breeds prone to overweight or obesity. As reported in a recent
study, the ideal body condition range forhealth maintenance in dogs may be lower
than previously thought; euthanasia (end-of-Intern J Appl Res Vet Med • Vol. 4, No. 2, 2006.

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life decisions) due to incapacitating
osteoarthritis occurred earlier in dogs whenbody condition was not maintained within
an ideal range.24

evidence of the links between
overweight/obesity and specific diseases in
dogs. Overweight dogs are at greater risk oforal disease than the remainder of the adultdog population. Overweight
Figure 1. Prevalence of Obesity and Overweight by Year ofdogs are also at increased risk
Age for Adult Dogs.
for lower urinary tract disease; however, a relationshipbetween obesity and urinary
tract disease as a category
was not found, possibly due
to a lack of statistical power
because there were fewer%
obese dogs and/or the effects
of grouping many diseases
into one category. Obesedogs were found to be atincreased risk for hypothyroidism, diabetes mellitus,
pancreatitis, ruptured cruciate
Age in Years
ligament, and neoplasia, corFigure 2. Prevalence of Obesity and Overweight by Gender for roborating previous canine
Adult Dogs.
studies suggesting these associations.3-7 The relationship90
between overweight or obesi76.4
80
72.7
ty and skin disease suggested
70
62.5
61.8
by 1 earlier small study25 was60
not supported by our finding.
50
That study failed to separately consider endocrine dis40
32.6
32.0
Overweight (n=6290)
eases such as hypothyroidism30
23.1
Obese (n=1097)
20.0
and hyperadrenocorticism,
20
Normal/Under BCS
which are frequently associat(n=14326)
5.6
5.5
4.2
3.6
10
ed with skin disease. These 20endocrine disorders did show
Neutered Male
Intact Male
Spayed Female
Intact Female(n=3806)(n=9115)(n=2838)% (n=5954)
associations with overweight
and obesity in this study andGender Category
were not included in the dermatopathy category. An association of obesity with neoplasia is
Breed risk for overweight/obesity wasinteresting; however, risk for specific types
found in our study as has been reported inof cancer would require study designs moreother canine populations.2,5,25 Dog breeds insuited for the study of rare disease.
this study found to be more at risk for both
overweight and obesity were the Shetland
Feeding semi-moist foods was associatSheepdog, Dachshunds, and Golden
ed with increased risk of overweight in our
Retriever; these breeds may require extra
study. Feeding canned, homemade, or, parvigilance on the part of owners to keep pets
ticularly, "other" foods was associated withat normal body condition. The disease assoobesity. Possible explanations include theciations documented here provide additional
higher caloric density26 of these diets com90.0

Overweight (n=6302)

85.8

Obese (n=1099)

80.0

75.6

76.5

75.5

65.5

64.5

63.3

60.0

74.5

Normal or Underweight(n=14353)

68.8

70.0

60.9

61.9

57.5

58.1

57.2

57.1

56.3

50.0

36.4

40.0

32.4

35.8

36.3

34.8

31.5

30.0

33

35.6

28.9

29.8

26.9

21.5

20.0

22.5

22.2

19.4

13.1

10.0

1.1

7.1

5.7

5.2

4.3

2.9

6.1

8.0

6.5

7.3

6.0

5.8

5.7

2.0

4.1

3.3

0.0

1

182

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16+

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pared to other commercial formulations,feeding frequency,18 and different feedingpractices of owners who chose to feed thesetypes of food compared to the more common practice of feeding primarily dry food.

with which overweight or obesity wasrecorded as a diagnosis.
Results from the feline population of theNCAS27 revealed similar, although not identical, results for overweight/obesity preva-

Figure 3. Prevalence of Obesity and Overweight by Breed for Adult Dogs.
Obese (n=839)
Overweight (n=4920)

90

Normal/Under BCS (n=10472)

76.8

80

76.7
72.4

70

65.1

63.9
58.9

60

57.0

56.7

53.7

52.2

50

%

40.2

40

35.9

39.5
34.9
31.7

30.9

30

25.0
19.1

20
10

33.0

5.3

5.2

6.1

Mixed
(n=5719)

Labrador
Retriever(n=1738)

CockerSpaniel(n=1123)

20.1

10.0

8.4
4.2

3.2

2.6

3.2

GermanShepherd(n=651)

Shih Tzu(n=527)

Poodle,NOS(n=497)

Rottweiler(n=309)8.3

0GoldenRetriever(n=1075)

Shetland
Sheepdog(n=409)Beagle(n=385)

Region did emerge as a risk factor for
adult obesity/overweight and may reflect
differing lifestyles of dogs (and owners)
across the geographic areas of the United.
Some lifestyle factors not measured in ourstudy, such as exercise and urban/rural status,2,18 have been shown to increase risk forobesity.
We observed dramatic underreporting ofoverweight and obesity when comparing
prevalence from BCS results to reported
diagnoses, especially for overweight dogs.
For example, the prevalence of obesity
defined by BCS for dogs was 5.1% compared with 2.5% when defined by reported
diagnostic code. The difference between
overweight prevalence in dogs defined by
BCS (29.0%) and reported diagnosis (1.4%)
was even greater. Underreporting of thediagnosis of obesity and overweight may
reflect the perception of practitioners thatobesity/overweight does not constitute a disease state, especially for animals in the
overweight category. Alternatively, theknowledge that BCS was being collected forthis study may have reduced the frequency

lence and risk for disease. The overall
prevalence of overweight/obesity was 35%
for cats versus 34% for dogs; obesity wasslightly more prevalent in the feline as compared to the canine population (6.4% vs
5.1%, respectively). Neutering was a strongrisk factor for feline as well as canine obesity. Differential overweight/obesity risk wasalso observed by breed. Obese cats and dogs
are both at risk for diabetes mellitus andneoplasia. Overweight cats and dogs areboth at risk for oral and lower urinary tract
disease. However, obese dogs were notfound to be at risk for oral disease or dermatopathy as were obese cats. In contrast to
the canine population, no risk for feline
overweight/obesity was found by geographic region of residence, possibly reflecting
greater homogeneity of feline lifestyles
across the United States.
Probabilities calculated for the goodness-of-fit statistics were: P = 0.003 (overweight model) and P = 0.2 (obesity model).
Based on the Hosmer-Lemeshow goodnessof-fit statistic, the variables in the multivariate model for obesity were able toIntern J Appl Res Vet Med • Vol. 4, No. 2, 2006.

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Table 2. Multivariate Disease Models: Risk Factors for Overweight and Obese Adult Dogs
(N = 17,963).
Risk Factors (P value)

Odds Ratio (CI*)β†

Overweight Dogs
(n = 5188)

Age (<.0001)

1.1 (1.0,1.1)

0.05

Mixed Breed (.008)
Labrador Retriever (<.0001)
Cocker Spaniel (<.0001)
Golden Retriever (<.0001)
Rottweiler (.002)
Shetland Sheepdog (.01)
Dalmatian (.01)
Dachshund (.0005)
Neuter (<.0001)
Semi-moist foods (.02)
East North Central region (.01)
Northeast region (.003)
Pacific region (<.0001)
South Central region (.002)
Hyperadrenocorticism (.003)
Hypothyroidism (.03)
Lower urinary tract disease(.03)
Oral disease (.001)
Ruptured cruciate ligament (.01)

1.1 (1.0,1.2)
1.6 (1.4,1.8)
1.9 (1.6,2.2)
1.5 (1.3,1.7)
1.6 (1.2,2.0)
1.4 (1.1,1.8)
1.6 (1.1,2.2)
1.6 (1.2,2.2)
1.5 (1.3,1.7)
1.5 (1.1,2.0)
1.2 (1.0, 1.3)
1.2 (1.1,1.3)
1.4 (1.2,1.5)
1.3 (1.1,1.5)
2.4 (1.4,4.3)
1.4 (1.0,1.9)
1.3 (1.0, 1.6)
1.1 (1.1,1.2)
1.7 (1.1,2.6)

0.1
0.5
0.6
0.4
0.4
0.3
0.5
0.5
0.4
0.4
0.2
0.2
0.3
0.2
0.9
0.3
0.2
0.1
0.5

Obese Dogs
(n = 885)

Age (<.0001)

1.1 (1.0,1.1)

0.05

Golden Retriever (.0008)
Shetland Sheepdog (.003)
Dachshund (.03)
Neuter (.05)
Homemade foods (.007)
Other foods (.0003)
Canned Food (.005)
Northeast region (.03)
Pacific region (<.0001)
Neoplasm (.02)
Diabetes mellitus (.02)
Ruptured cruciate ligament (.04)
Hypothyroidism (<.0001)
Pancreatitis (.05)

1.6 (1.2,2.2)
1.9 (1.2,2.8)
1.7 (1.0,2.7)
1.3 (1.0,1.6)
1.9 (1.2,2.9)
2.3 (1.5,3.6)
1.4 (1.1,1.8)
1.3 (1.0,1.6)
1.7 (1.3,2.2)
1.4 (1.1,1.7)
2.6 (1.2,5.6)
2.1 (1.0,4.1)
2.8 (1.9,4.2)
2.2 (1.0,4.7)

0.5
0.6
0.5
0.2
0.6
0.5
0.3
0.3
0.5
0.3
1.0
0.7
1.0
0.8

*95% confidence interval (CI).
†
Parameter estimate/coefficient from logistic model.

adequately predict the outcome of obesity.
However, the P value for the overweightmodel statistic was <.05 (null hypothesis
rejected, ie, model does not fit) and so cannot completely explain the variability in thedata analyzed. There may be essential variables not collected in this study that would
help more fully predict the outcome, forexample, exercise patterns, single or multiple dog household status, urban/rural residence, and feeding frequency.
Major strengths of the study reported
here include the size and geographic distribution of the population studied as well as
the ability to generalize the results to private
practice populations in the United States.

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Although the data for this study were collected during 1995, the scope and the resultsof the study remain relevant to the contemporary description and assessment of theobesity problem of dogs seen in privatecompanion animal practice and provide abenchmark for subsequent measurements ofobesity and overweight prevalence in the
pet canine population. Surveillance andmonitoring of the health of US dogs is especially relevant in light of the current epidemic of human obesity.
Limitations of the study include the useof a cross-sectional study design, a lack ofstandardized case definitions, and the potential for underreporting of cases.14 A crosssectional study is of limited use fordiscerning disease causality.28 This is important to keep in mind when examining associations such as between obesity andhypothyroidism. Uncommon or rare diseases, even if of great interest, are not efficiently examined in this type of study.28 For
the results reported in this study, the lack ofcase definitions and the potential for disease
misclassification must be considered.
Grouping of individual diagnoses into system categories was necessary to increase theefficiency of the statistical analysis and tominimize error from disease misclassification. The failure of this study to document arisk relationship between overweight orobesity and an uncommon disease, such astransitional cell carcinoma of the urinary
bladder, does not prove or disprove such a
relationship. Misclassification of the outcome (overweight or obesity) by BCS mustalso be considered as a source of differences
between our study results and others as theassessment of body condition has not beenstandardized across research studies.
In addition to providing important
descriptive data on the problem of obesity
in dogs seen by practitioners in the UnitedStates, this study provides evidence that thepromotion of weight reduction approaches
for overweight/obese dogs may reduce morbidity. Feeding practices of neutered pets
may need to be more closely guided by vetIntern J Appl Res Vet Med • Vol. 4, No. 2, 2006.

erinarians, especially in regard to feeding
calorie-dense non-commercial foods. Futurestudies should ideally include additional
lifestyle factors such as exercise patterns,
single or multiple dog household status,
urban/rural residence, and feeding frequency
to help fully model and predict overweight/obesity. A cohort design would
allow dogs to be followed over their lifetime, enabling determination of the temporal
association of disease incidence to thedevelopment of overweight/obesity. Finally,
with these study results, the ability of practitioners to communicate the importance of
maintaining canine patients at ideal body
condition will be strengthened.
ACKNOWLEDGEMENTS
This research was supported by the MarkMorris Institute with a grant from Hill's Pet
Nutrition. Dr. Lund is now with Banfield,
The Pet Hospital, Portland, OR. Dr. Kirk is
now with the Department of Small Animal
Clinical Sciences, Veterinary Teaching
Hospital, College of Veterinary Medicine,
University of Tennessee, Knoxville, TN. Dr.
Klausner is now with the Dean's Office, atthe University of Minnesota, College of
Veterinary Medicine, St. Paul, MN.
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APPENDIX. DISEASES (WITHIN CATEGORY) IN STUDY DOGS DIAGNOSED BY VETERINARIANS
Dermatopathy (prevalent diagnoses > .05%): Acral lick granuloma, alopecia (endocrine and general), angioneurotic edema, dandruff, dermatitis (allergic contact, atopic, flea allergy, flea bite, fly bite, food allergy, foxtail, hormonal, intertrigenous/fold, moist, paronychial, perivulvar, prutitic, seborrheic), dermatophytosis, folliculitis,paronychia, pyoderma.
Gastrointestinal Disease (prevalent diagnoses > .05%): Ascites, anal sac disease, chronic diarrhea, colitis, constipation, enteritis, gastritis (acute, general), gastroenteritis, umbilical hernia.
Heart Disease (prevalent diagnoses > .05%): cardiac arrhythmia, congestive heart failure, cardiomegaly, heartdisease, heart murmur (acquired, general), mitral insufficiency.
Lower urinary Tract Disease (prevalent diagnoses > .05%): cystitis (acute, bacterial), bladder stone(s), urinary
tract infection, urolithiasis (calcium oxalate, cystine, silica, struvite, unspecified, urate, xanthine).
Musculoskeletal Disease (prevalent diagnoses > .05%): arthritis, cruciate ligament rupture, eosinophilic panosteitis, intervertebral disc disease, lameness, muscle atrophy, osteoarthritis, osteochondritis dessicans, patellar
luxation, soft tissue injury, spondylitis, spondylosis.
Neoplasia (prevalent diagnoses > .05%): adenocarcinoma, adenoma, eyelid margin tumor, hemangiosarcoma,
histiocytoma, lipoma, lymphosarcoma, mast cell tumor, mammary tumor, meibomian gland ademona,
melanocarcinoma, osteosarcoma, perianal gland tumor, sebaceous adenoma, tumor-unspecified.
Oral Disease (prevalent diagnoses > .05%): dental calculus, dental caries, fractured tooth, gingivitis, malocclusion, periodontal disease, retained deciduous teeth.
Renal Disease (prevalent diagnoses > .05%): azotemia, renal disease (acute and chronic), renal failure (acuteand chronic), uremia.
Reproductive Disease (prevalent diagnoses > .05%): balanoposthitis, dystocia, mastitis, metritis, prostatic disease, prostatic hypertrophy, prostatitis, pyometra, vaginitis.
Respiratory Disease (prevalent diagnoses > .05%): bronchial asthma, bronchitis, dyspnea, epistaxis, nasal discharge, pharyngitis, rhinitis, sinusitis, tracheal collapse, tracheitis, tracheobronchitis, pneumonia, pulmonary
edema, upper respiratory infection.

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