Because of the growing problem of obesity in companion animals, this study aims to repeat a similar study conducted in 1993 in Palmerston North, by F. Allan, to determine if the proportion of obese cats has increased and to determine if the risk factors for the development of obesity in cats have changed.
The study is conducted in a non- hospitalised, randomly selected population of cats in the region
Palmerston North, New Zealand. A door-to-door survey obtained information about signalment, household variables, owner-cat affinity, cat feeding and cat characteristics of 200 cats. Also, cats were measured for weight, body length, leg length and body condition score. The interviewer’s assessment of the body condition of each cat was the dependant variable used in this study.
Variables were grouped into four different risk factor groupings; cat characteristics, owner’s perception, environmental and cat management variables and a combined model. A multivariable stepwise logistic regression analysis was run on each of the groupings. Variables from the first three risk factor groupings, that were identified as significant from each model (p ≤ 0,05), were included in a combined model.
The current study suggests that the incidence of feline obesity in Palmerston North, New Zealand has not increased over the last 15 years in comparison with the 1993 study of F. Allan, and only two risk factor agreed with both studies: the owner’s perception of the body condition of the cat and leg length.
Because of the association between obesity and the owner’s perception of the body condition of their cat, veterinarians need to correct the owners’ perception if their cats is overweight, for weight loss to be successful and for the prevention of obesity.

Obesity is a growing problem in companion animals. Twenty five years ago the prevalence of obese and overweight pet animals lay between 6 and 12 percent. Nowadays that percentage is at least twice as much in the developed countries. Studies in Australia, Brazil, France, Great Brittan, Spain,
USA and Sweden have shown that between 25 and 40 percent of all dogs and cats suffer from overweight or obesity. (B. de Leeuw, 2008)
The main medical concern of obesity relates to the associated clinical conditions. Numerous studies demonstrated that obesity can have detrimental effects on the health and longevity of dogs and cats.
The problems to which obese companion animals may be predisposed include orthopaedic disease, diabetes mellitus, cardiorespiratory diseases, urinary disorders, reproductive disorders, neoplasia, dermatological problems and anaesthetic complications. (A.J. German, 2006; S. Thissen, 2008; D. Robertson, 1999; Fettman et al., 1998; Scarlett and Donoghue, 1998; M. Lockhorst, 2008)
Multiple reports classify cats and dogs as overweight, when the bodyweight is between 5 and 20 percent above ideal weight. When the bodyweight exceeds more than 20 percent above ideal weight, we speak of obesity. (M. Lockhorst, 2008; A.J. German, 2006; L. Colliard et al., 2009)
The main reason for the development of obesity is a mismatch between energy intake and energy expenditure. Therefore, either excessive dietary intake or insufficient energy utilization can lead to a positive energy balance. However, numerous factors may predispose an individual to obesity including genetics and the amount of physical activity.
(A.J. German, 2006) Earlier studies suggested as risk factors for feline obesity: neutering, gender, middle age, a single or two cat household, inactivity and human-animal relationship (A.J. German, 2006; D. Robertson, 1999; L. Colliard et al., 2009) . Another problem is that owners often don’t recognise that their cat is obese or overweight. Many owners don’t know what the energy need of their animal is. Feeding the cat according to the feeding regulations on the packaging of the animal food can be a good help for not overfeeding the cat, but the problem is that owners use the current weight as a guideline instead of the ideal weight. (S. Thissen, 2008)
The objective of the current study is to asses the following risk factors for obesity, in a non- hospitalised, randomly selected population of cats in the region Palmerston North, New Zealand: neutering, age of the cat, activity of the cat, leg and body length of the cat, single or two cat household, presence of dogs in the household, human-animal relationship and owner’s underestimating the body condition of their cat. This study aims to repeat a similar study conducted in 1993 in Palmerston North (F.J. Allan et al., 2000) to determine if the proportion of obese cats has increased and to determine if the risk factors for the development of obesity in cats have changed.
Like 15 years ago, an a priori decision was made to obtain information on 200 cats. Between 10
October 2007 and 14 December 2007 the research was conducted by a door-to-door-survey in
Palmerston North. Palmerston North is a provincial city located on the northern island of New
Zealand with a population of 75.500
1 .
A stratified, random sampling approach was used to select the households and cats to be included in this study. The study used a proprietary database 2 to divide Palmerston North city into six geodemographic profile groups based on socio-economic status (SES) and family orientation. Socioeconomic status is a summary of educational, vocational and income measures. Family orientation is
1
Statistics New Zealand, 2006
2
Markerfind, Deltarg Distribution Systems Ltd, Auckland, New Zealand

based on household composition, mortgaged home acquisition and marital status. With these data, the percentage of households falling within each of the geo-demographic profile groups was calculated (table 1).
There is no profile group with High SES and Weak Family, these are the people living in apartment buildings, because Palmerston North does not have apartment buildings.
The number of cats sampled from each profile group was proportional to the number of households within each profile group in Palmerston North. For example, profile group 3 (mid SES – weak family) includes 19% of the households in Palmerston North, therefore, the number of cats required from this group was 19% of 200, so 38 cats.
Table 1 Proportion of households in Palmerston North falling within each geo-demographic profile
Profile Group
High SES – Strong Family
Mid SES – Strong Family
Mid SES – Weak Family
Low SES – Strong Family
Low SES – Weak Family
Disadvantaged
Households
(%)
5.5
32.0
18.9
26.6
4.7
12.3
‘SES’ stands for Socio economic status, ‘Family’ stands for family orientation of the profile groups.
An a priori decision was made to obtain four cats per street, so that the number of cats would be proportionally divided among the different streets per profile group. According to this, the number of streets necessary per profile group could be calculated.
The addresses (street name and number) in Palmerston North were randomly selected from the
Palmerston North phone book. The addresses were sorted according to profile group while still maintaining the order in which the addresses were drawn from the phone book. These addresses represented the starting addresses, that the interviewers would use during the study.
First, ten houses per street were flyered door-to-door with an information pamphlet about the research. When residents did not want to participate or did not have a cat, they could contact a contact number on the information pamphlet and they would not be bothered anymore. The rest of the houses were used in the survey. The interviewers proceeded door-to-door from the starting address, first up one side of the street and after the last house down the other side of the street, until they obtained data on 4 cats. If there weren’t enough participating households in the first ten houses, another ten houses in the same street would be flyered and later contacted door-to-door, until data of four cats was acquired from that street. If there weren’t enough houses in the street to obtain enough cats, another street, following the last street, was flyered and contacted. Once the data on 4 cats was obtained from one street, the interviewers would go to the second starting address on the list and so forth, until the required number of cats for that profile group was obtained.
If there was no reply at any particular house, the interviewers would revisit the house twice more on different times and/or different days. After the third attempt and still no reply, no further attempts were made to contact the households. The information about whether the owner was at home, whether the owner had a cat and whether the owner was willing to participate was written down on a household data sheet, which the interviewers completed for each household (enclosure 1).
Interviewing hours were between 0900 am and sundown (around 08:00 pm), 7 days per week. A survey form was completed on every participating household and the cat from that household was measured and weighed (enclosure 2).

When there were multiple cats in a household, only one cat was used for the survey. In this case, the cat whose name started closest to the beginning of the alphabet was used for the measurements, to keep the survey randomly.
Only cats that were over one year of age were used in the study, because kittens aren’t as easily influenced by the same risk factors as adult cats.
The potential for interviewer bias was limited by having a fixed questionnaire with ordered and specific procedures to be followed.
The questionnaire was divided in five sections: signalment, household variables, cat affinity variable, cat feeding variable and cat characteristic variables. Each of these sections consisted of several questions regarding that section. Both, open and closed questions were included in the questionnaire. The owners could answer the questions with simple answers, often just ‘yes’ or ‘no’, or with the help of a show card (enclosure 3), where the owner had to pick his or her response from a few options.
In the section ‘signalment’, a few questions like age, sex and whether or not the cat was neutered were asked , where the owner could respond by simple and short answers.
The second section ‘household variables’, was about the composition of the household the cat lived in. This included questions about the number of people in the household, the age of the residents and dog ownership.
Section three contained one question that attempted to establish the relationship of the members of the household with the cat. The owner could pick the best response out of five options from a show card, from ‘we dislike our cat and would rather not have it around’ to ‘our cat is very important to us, we treat it like our child’ (enclosure 3, show card 1).
In the ‘cat feeding variables’ section, the questions cover the feeding regimen in the household. This includes questions about frequency of feeding and types of food fed. The owner can again often respond with a simple ‘yes’ or ‘no’, or he or she can pick a response from a show card. (enclosure 3, show card 2)
The fifth section, ‘cat characteristics’, informed about the cats health status. Also, questions about the level of activity of the cat were asked and the owner’s perception of the cat’s body condition was determined, according to a show card (enclosure 3, show card 6). Owners were occasionally asked to give some additional information about their cats health.
Cats were excluded from the study if a cat was considered to be in poor health, if the cat suffered from a condition or was on medication which may had affected it’s body condition.
When the owners gave their opinion about the body condition of the cat, they were not provided with guidelines for assessing a body condition, so their opinion reflected their own perception of the body condition of their cat. The interviewers on the contrary, who determined the body condition of the cats in the sixth section, had a training in determining body condition of cats in a cattery at the
Massey University, Palmerston North, prior to the door-to-door survey.
This report is based on the non feeding risk factors for obesity in cats, so the feeding characteristics will be explained in another report.
Cats were weighed on a set of portable electronic scales (Nagata, model BW-2010, 20 kg max, 10g increments). The length of each cat was measured from a point where the spine intersects with an imaginary transverse line through the middle of both scapula to the base of the tail when it is held erect. The leg length was measured at a forelimb, on the palmer surface from the olecranon to the distal aspects of the digits, excluding the claws, with the limb and digits in full extension.
Each measurements was performed at least twice to ensure the results were repeatable.
To make an estimation of a possible overweight, the BCS (Body Condition Score) for companion animals can be used. (M. Lockhorst, 2008) The body condition was determined by visual assessment of the waist of the cat and by visual assessment and palpation of the subcutaneous fat covering on the ribs

and the inguinal and abdominal areas. After this an appropriate BCS was given, according to the validated 9-point body condition scoring system. (D. Laflamme, 1997) Point one being emaciated and point nine being grossly obese.
Both interviewers assessed each cat independently, when the body condition scores differed, they would reach agreement trough discussion. A different point system for the body condition scoring was used, compared to the 1993 study. The rest of the measurements were done the same way as in the study of 1993.
The interviewer’s assessment of the body condition of each cat was the dependant variable used in this study. The condition score data were converted to a dichotomous variable suitable for use as a dependent variable: ‘normal weight’ or ‘overweight’. Normal weight cats were given a BCS of 4 or 5 and overweight cats a BCS of 6, 7, 8 or 9. Cats that were considered underweight by the interviewers
(a BCS of 1, 2 or 3) were not included in this analysis, since the objective was to identify risk factors associated with cat obesity. So effectively, this compares BCS 4 and 5 with BCS 6, 7, 8 and 9. This study made no distinction between overweight cats and very overweight cats, like other studies have done. (Colliard et al., 2008; Lund et al., 2005; Russell et al., 2000) In this study the terms overweight and obese are used interchangeably.
Variables associated with multiple categories, like the showcards, were re-categorized to avoid category levels with very small numbers of observations. Continuous variables, like age, leg length and body length, were binned into categories, so all the data would be nominal.
The analysis was conducted in two steps. To obtain an understanding of the data and the population studied, first a descriptive analysis was conducted.
In the second step, a multivariable analysis was conducted to identify the most important risk factor variables. It included all variables, so that any mutual relationship could be explored. The variables were grouped into three biologically sensible risk factor grouping, namely; cat characteristics, owner’s perception of their cat and household characteristics. The multivariable analysis is conducted in two phases. The first phase performed multivariable analysis within the three risk factor groupings, this is called the component model. The other phase combined the factors which had been statistically significant in the multivariable analysis for each risk factor grouping, the overall model. These analysis were performed using stepwise logistic regression. Variables were selected using stepwise forward selection, based on the likelihood ratio statistic using a p-value for entry of
0,05 and for removal of 0,1. See table 2 for the variables assessed as potential risk factors for obesity, grouped according to the different biologically sensible risk factor groupings.
The regression coefficients were converted into odds ratios, to be able to describe the strength of association or dependence between the data values, with 95% confidence interval.
Receiver-operating-characteristic (ROC) analysis was conducted to describe the usefulness of the variables in the final model as quantitative indicators of obesity in cats. The area under the curve was estimated and its standard error was calculated using the non-parametric distribution assumption.
With the ROC and with the pseudo R 2 , the goodness of the model to fit the data was assessed. They measure the correlation between the observed and predicted values of the dependant variable, in this case, the BCS. (D.G. Altman, 1991) With a pseudo R 2 of approximately 0.43 and an area under the ROC curve of 80% the combined model is good at differentiating obese and normal weight cats.
Data analysis was conducted by statisticus D. Pfeiffer, using the statistical software packages SPSS for
Windows version 16 (SPSS Inc., Chicago, Illinois, USA) and SAS for Windows version 9 (SAS Institute,
Cary, North Carolina, USA).

Table 2. Variables assessed as potential risk factors for obesity grouped according to model of the
200 cats included in the study (New Zealand, 2007).
Model Variable Category levels Cats
(n)
Normal
(%)
O’weight
(%)
Cat characteristics
Age (years) a
Desexed?
a
≤ 2
3 – 7
8 – 12
≥ 13
Entire
29
87
58
24
9
59
40
31
13
89
41
60
69
88
11
Owner’s perception
Environmental and cat management variables
Gender
Level of activity a
Leg length (mm) a
Body length (mm)
Affinity to cat
Owner’s estimate of BCS a
Geo-demographic profile
Number of people in household?
Number of people over 60 years of age?
Desexed
Male
Female
Inactive
Normal
Overactive
≤ 180
181 – 186
187 – 197
≥ 198
≤ 341
342 – 362
363 – 381
≥ 382
Not important or some importance
Important or “like our child”
Underestimated
Correctly estimated
Overestimated
High SES – Strong Family
Mid SES – Strong Family
Mid SES – Weak Family
Low SES – Strong Family
Low SES – Weak Family
Disadvantaged
1
2
≥ 3
0
1
2
22
55
50
49
46
190
108
92
26
152
50
53
52
45
21
179
96
102
2
14
55
38
51
11
31
32
67
101
155
26
19
55
55
30
35
26
35
34
40
19
38
48
42
33
24
48
36
13
59
100
36
27
45
43
18
42
25
33
44
41
27
21
46
46
70
66
74
65
66
60
81
63
88
41
0
64
52
59
67
76
52
64
58
75
67
73
55
57
82
56
59
73
79

Have children less than 16 years of age?
a
Number of cats?
Have dogs?
No
Yes
Single
Multiple
No
Yes
118
82
138
62
156
44
35
42
35
31
45
46 a Indicates p < 0.1 for each variable
A total of 1045 households were visited by the interviewers and information of 215 cats was obtained. Table 3 shows the reasons for not participating of the remaining 830 households.
Table 3. Reasons for not participating
No of households
Reason
37
87
459
15
4
228
Not at home after 3 visits
Refused or unable to participate
Did not have a cat
Cat less than one year of age
Cat was absent on each of the three visits
Residents not contacted because the number of cats needed for that street had been reached prior to the third visit.
65
58
65
69
55
55
Of the participating households, 68% had only one cat, 21% had two cats and 8% had three or more cats. The median age of the cats was 72 months (25 th percentile was 33 months, 75 th percentile was
120 months). 54% Of the cats was male, 95% of the cats was desexed.
Of the 215 cats, 15 were excluded from analysis for reasons listed in table 4.
Table 4. Excluded cats
No of cats Reason of exclusion
9 BCS of 3 or lower
5
1
Medical grounds
Not able to determine BCS, too fractious
Of the cats that were excluded on medical grounds, one had hyperthyroidism, one had diabetes mellitus, one was being treated with fluoxetine, one was being treated with clomipramine and one was being treated with prednisolon. Clomipramine and fluoxetine are both human antidepressive medication (db.cbg-meb.nl) , also used in animals. Clomipramine is also known as Clomicalm as a veterinairy medicine. A side effect of this medication is a change in appetite (Fidin repertorium veterinairy

medicine) . Cats using these medication are excluded from the study, because these medication can affect the body condition of these cats.
In the reduced dataset of 200 cats, 126 (63%) cats were classed overweight by the interviewers and
74 (37%) normal weight. Figure 1 shows the BCS distribution of the population of study cats, less the cats that were excluded from the study on medical grounds.
Figure 1 Histogram showing the number of cats in each body condition score category. Note that cats which were excluded on medical grounds are not shown.
80
70
60
50
40
30
20
10
0
1 2 3 4 5 6 7 8 9
Body Condition Score
Most of the households had a strong affinity towards their cat. 54% picked number 4 out of 5 statements on the showcard (enclosure 3, showcard 1), claiming their cat was important and part of their family, and 36% picked number 5 on the showcard, claiming their cat was very important and they treated it like a child.
Table 5 shows the results of the stepwise multiple logistic regression, only the significant variables are shown. For each risk factor the odds ratio and the confidence limits were calculated, with a 95% confidence interval, describing the strength of association or dependence between the data values.
Table 5. Results of the stepwise forward multiple logistic regression
Neutered
Leg length
(mm) no yes
<=180
181-186
187-197
0.12
1 (ref)
1 (ref)
2.98
2.85
0.01 – 1.05
1.25-7.12
1.18-6.88

Age (years)
Less than 16 years old children?
Difference in
BCS
Leg length
(mm)
>= 198
<=2
3-7
8-12
>=13
Yes
No
Overestimate
4.08
1 (ref)
1.84
4.53
8.69
0.56
1.63-10.2
0.73-4.65
1.7-12.01
2.02-36.41
0.31-0.996
1 (ref)
Not estimated sample size too small
0.1 0.05-0.21 Correct
Underestimate 1 (ref)
<=180 2.39 0.88-6.45
Age (years)
181-186
187-197
>= 198
<=2
3-7
8-12
>=13
2.98
4.42
1 (ref)
2.30
5.45
13.80
1 (ref)
1.08-8.17
1.55-12.4
0.78-6.79
1.67-17.87
2.73-59.7
Difference in
BCS
Overestimate Not estimated Sample size too small
Correct
Underestimate
0.08
1 (ref)
0.03-0.17
In the 95% CL column, the confidence limits of the confidence interval for each risk factor are given.

After applying the stepwise multivariable logistic regression on the first three risk factor groupings, a few significant variables were found.
In the ‘characteristics model’ significant variables included: neutering (neutered cats, higher risk of obesity), the age of the cat (older cats, higher risk of obesity) and leg length (longer the leg length, greater risk for obesity).
‘The environmental and cat management variables’ only had one risk factor identified; whether there were children less than 16 years of age in the household. This was a negative risk.
In the ‘owner’s perception model’, cat’s whose owners underestimated their body condition were at greater risk for obesity.
The combined logistic regression model, derived from the variables which had been significant in the component models, yielded only three remaining significant variables. These included the cat’s leg length, it’s age and whether the owner underestimated the body condition of the cat. The other variables that were significant after applying the multivariable logistic regression analysis on the three component models and were not significant in the combined model, appeared to be able to be explained by the other variables in the combined model.
The goodness of fit of the different models to the data is expressed in the ROC curves presented in
Figure 2.
Figure 2. ROC curves for the four regression models
The model fit as reflected in the area under the curve is 0.85 (95% CL 0.79-0.91) for the overall model, 0.74 (95%CL 0.66-0.81) for the cat characteristics model, 0.76 (95% CL 0.69-0.83) for the owner perception model, 0.56 (95% CL 0.48-0.65) for the feeding model and 0.57 (95%CL 0.49-0.66) for the environment and management model. For both, the feeding model and the environment and management model the area under the curve is not significantly different from 0.5, indicating poor fit.

To be able to compare the 1993 study of Allan et al. (2000) with the current study, the same population base was used. In 1993 26% of the cats were categorised as overweight, compared to
63% in the current study. However, it is important to note that the studies used different body condition scoring systems. For the current study a 9-point body condition scoring system was used, because this is a globally accepted, validated scale (D. Laflamme, 1997) , in contrast to the 5-point scale that was used in 1993, which was specifically designed for the paper. Because of the difference in body condition scoring systems in the two studies, actual comparison between the prevalence of obesity in 1993 and in 2007 is not possible. That is why an estimation of the comparison between the two studies was made, by binning the 9-point scale into a 5-point scale: (BCS 1-2 = 1, extremely underweight; BCS 3-4 = 2, underweight; BCS 4-6 = 3, normal; BCS 7-8 = 4, overweight; BCS 9 = 5, extremely overweight; obese). In the current study, cat’s with a BCS of 4 or 5 were considered normal weight and those with a BSC of 6-9 were considered overweight. Cats with a BSC of 6 would have been considered normal weight if the 1993 criteria for body condition score would have been applied. After applying the 1993 study’s criteria to the current study, the estimation of the incidence of obesity in 2007 is 27%.
Therefore, this study suggests that the incidence of feline obesity in Palmerston North, New Zealand has not increased over the last 15 years. It is important to note that a good comparison between the two studies can only be made if the same scoring system is used. By changing the 9-point scale into a
5 point scale, a bias could arise and influence the results. A new study, with the same body condition scoring system as in 1993 would be necessary to see if the prevalence of obesity in the population of cats in Palmerston North, New Zealand has really changed over the last 15 years.
The owner underestimating the body condition of their cat was in this study, as well as the 1993 study (F. Allan et al., 2000) the best explanatory risk factor for obesity in cats. The study of L. Colliard et al.,
2009, supports the finding that underestimating the body condition of the cat is a significant risk factor. In the E. Kienzle and R. Bergler study of 2006, the majority of owners of overweight cats perceived the silhouette of their own cat as considerably thinner than the interviewer did. Some even likened their cats to underweight silhouettes. The finding that underestimating the body condition by the owner is a risk factor for obesity in cats is not surprising, because if an owner does not perceive that their cat is overweight, motivation to reduce the calorie intake of the cat will be low (E. Kienzle and R. Bergler, 2006) .
Owners underestimating the body condition of their cat is a risk factor that is readily amenable to practical intervention in weight loss programmes. For weight loss to be successful, veterinarians need to correct cat owners’ perception of the body condition if their cats is overweight. Prevention is a priority, as the management of a weight loss programme is relatively difficult in practice. BCS education prior to overweight may reduce the incidence of obesity in cats as they grow older. (L. Colliard et al., 2009) A body condition scoring card, such as the one developed by Laflamme (1997) might be a useful tool. However, in the study of E. Kienzle and R. Bergler (2006) owners were asked to compare the silhouette of their cat to 6 unlabeled body condition silhouettes that ranged from 1, emaciated, to 6, obese. The majority of owners of overweight cats perceived the silhouette of their own cat as considerably thinner than the interviewer did. Some even likened their cats to underweight silhouettes.
A new body condition scoring system, S.H.A.P.E (Size, Health And Physical Evaluation) was assessed by A.J. German et al (2006). This approach is designed to minimize interoperator variability and expertise required, allowing owners to evaluate their animals in the home and consult the veterinarian accordingly. This study concluded that this method of scoring woul d be suitable for inexperienced owners.
(A.J. German et al., 2006)

Like in the current study, leg length was a significant risk factor for obesity in cats in the 1993 study of F. Allan, (2000). In the cat characteristic model of the current study, cats with long legs had greater odds of obesity. However, in the overall model, it seems that the other variables had some influence on the leg length, because now it appears that cats with a leg length of 187-197mm had the greatest odds of obesity instead of a leg length of ≥ 198mm in the component model. Looking at the confidence limits, the owner’s perception of body condition is probably the most important variable in the overall model. This variable could have been of influence on the other two variables, age and leg length, what caused them to change in the overall model. More research and/or other statistical analysis would be necessary to research the significance of leg length as a risk factor for obesity in cats.
There is evidence to show that changes in the fetal environment in the period from conception to infancy can lead to permanent changes in physiology and/ or structure. This has been referred to as the ‘developmental origins of health and disease’ (DOHaD) phenomenon. It proposes that the greater the mismatch between the mature environment anticipated by the fetus and the actual mature environment of the mature animal, exposes the organism to greater risk of adverse consequences. It is hypothesized that the DOHaD paradigm accounts, in part, for the high incidence of human obesity and its consequential diseases such as non-insulin dependent diabetes mellitus.
The theory posits that in utero, the human fetus does not anticipate on the energy-dense, relatively inactive adult environment that has manifested in the Western world over recent decades ,what increases it’s risk for obesity (Gluckman et al., 2007) . This could be a cause for the connection between longer leg length and obesity.
As in the 1993 study of F. Allan, body length was not a significant risk factor for obesity in cats.
Multiple previous studies showed that age is a risk factor for obesity in cats. (E. Kienzle and R. Bergler 2006; S.
Donoghue, J. M. Scarlett., 1998; Scarlett et al., 1994; D. Robertson, 1999; D.S. Kronfeld, 1994 and L. Colliard et al., 2009)
Studies of E. Kienzle and R. Bergler (2006) and S. Donoghue and J. M. Scarlett. (1998) show that overweight cats are more likely to be middle aged.
In the study of D. Robertson (1999) and D.S. Kronfeld (1994) the prevalence of obesity and overweight was also highest in middle aged cats. However, D. Robertson categorized middle aged cats between the ages of 6 and 14 years old, while D.S. Kronfeld categorized middle aged as 4-6 years old. L. Colliard et al. (2009) found a higher risk of obesity in cats over 2 years of age.
Because of the difference in age used as middle aged, it is hard to compare these studies. In this study, the age of the cat was a risk factor in the cat characteristic model, with greater odds of obesity as cat’s grow older. In the combined model however, the odds of obesity increased up to an age of 8-
12 years old. In the age class ≥ 13 years the odds of obesity decreased. This would agree with earlier studies (E. Kienzle and R. Bergler (2006), S. Donoghue and J. M. Scarlett. (1998), D. Robertson (1999), D.S. Kronfeld (1994) that the risk of obesity is highest in middle aged cats. It should be noted that thin and sick cats were excluded from the analysis as this study was interested in risk factors for obesity, not leanness (BCS ≤ 3). The median age of the 9 cats excluded from this study because they were thin was 14.25 years and only one of these cats was less than 10 years of age (14 months). Although many middle-aged and older pets are overweight, a large percentage of geriatric cats and dogs have a low BCS. Approximately one third of cats older than 12 years of age may have a decreased ability to digest fat, whereas one in five may have a compromised ability to digest protein (Laflamme, D.P.,2005) This could suggest that geriatric ( ≥
13 years old) cats have really poor odds of obesity.
However, the fact that the results from the overall model differ with the component model, means that age as a risk factor for obesity is influenced by other variables in the overall model. Just as with the leg length, more research and/or statistical analysis is necessary to assess the significance of age as a risk factor.

Markwell et al. (1994) suggested that activity level had a significant impact on the obesity of an animal, with inactive cats having considerably lower maintenance requirements than active cats.
It is difficult to assess the activity level of a cat, mainly because the owner doesn’t know how active the cat is when it is outside or when the owner is not at home. In this study, the owner was asked how active he or she considered the cat to be. The owner could answer the question according to a showcard (enclosure 3, showcard 5), and pick a level of activity out of 5, from extremely overactive to extremely inactive.
People found it difficult to answer this question, because the cat had different levels of activity during the day and the owner couldn’t tell what the cat was doing outside. Many people didn’t have anything to compare the level of activity of their cat with, so they would just guess their cat was normally active.
In the similar study of F. Allan et al., (2000) activity level of the cat was assessed according to the question whether the cat was confined indoors or not. Restriction of cats to their houses reduces opportunity for exercise and increases attention to food because of loneliness or boredom (Scarlett et al.,
1994) . However, in the study of F. Allan et al., (2000) confined indoors did not appear to be a risk factor. That is why in this study a different approach was used to assess the activity level of the cats, but also in this study, the activity variable did not appear to be a significant risk factor for obesity.
Activity level is probably more likely to be an effect rather than a cause of obesity, but more research would be necessary to conclude this.
Increasing activity level of a cat is not that simple as for a dog. Interventions that are effective in dogs
(e.g. playing ‘catch’, swimming or going for a walk) do not generally apply to cats.
Nevertheless, in the study of E. Kienzle and R. Bergler (2006) playing with the cat appears to be an effective counterbalance against overweight. The study showed that owners of normal weight cats consider playing with their cats to be significantly more important than owners of overweight cats
Owners of normal cats more often used extra play time as a treat than owners of overweight cats, whereas extra food was more often used by the owners of overweight cats. (E. Kienzle and R. Bergler 2006)
However, it is unlikely that owners’ playing with their cats is likely to result in significant additional energy expenditure to account for the differences in body condition.
Unlike the current study, multiple previous studies have shown that desexing is a risk factor for obesity in cats (S. Donoghue and J. M. Scarlett. 1998, D. Robertson., 1999, F. Allan et al., 2000, L. Colliard et al., 2009) . Neutered cats are over three times more likely to be overweight compared to intact cats. Research has shown that neutering decreases the metabolic rate. (D. Laflamme, 1997) After desexing, the energy expenditure declines with 24-30% (S. Thissen, 2008) . However, in this study, 95% of the cats was neutered, so spayed versus intact cats couldn’t be modeled properly, because of insufficient numbers.
In ‘The environmental and cat management model’ the only risk factor identified was the presence of children less than 16 years of age in the household. This was a negative risk. Children might bother the cat more than an adult would do, thereby resulting in the cat being more active. However, this risk factor was explained by other factors in the combined model, like age of the cat. For example that mostly young cats lived in the households with children less than 16 years of age.
The presence of a child in the household was also associated with lower odds of obesity in the resent study of L. Colliard et al. (2009). However, in the study of E. Kienzle and R. Bergler (2006) the number of adult or juvenile persons in the household was not a significant risk for obesity in cats. Probably, more research is necessary on this subject to get a good association between children in the household and odds of obesity.
One of the objectives of this study was to see if a close owner-human relationship is a risk factor for obesity in cats. A study of E. Kienzle and R. Bergler (2006) assessed the human-animal relationship in a German population by a personal interview of cat owners, conducted according to a standardized questionnaire. The questionnaire contained 250 questions in 6 sections that included the following topics: psychological benefits and disadvantages of a cat ownership, activities involving playing with

the cat, feeding the cat, health care of the cat, and the health, eating behavior and demographics of the owner. 30% Of owners of overweight cats compared to 12% of owners of normal cats stated that they did not feel very happy prior to acquiring a cat, and the cat was intended to console and encourage them. These results are suggestive of a closer relationship between overweight cats and their owners than between normal cats and their owners, more over-humanization of overweight cats than normal cats and a potential role of overweight cats as a substitute for human companions.
A close relationship between cat and owner has been suggested in this study as a risk factor for the overweight cat. (E. Kienzle and R. Bergler, 2006)
In the present study, the human-animal relationship was assessed by only one question: ‘which of these statements best describes the relationship of your cat to the members of the household?’ The owner could answer this question according to a show card (enclosure 3, show card 1) with 5 options, from ‘We dislike our cat and would rather not have it around’ to ‘Our cat is very important to us. We treat it like our child’. We deliberately did not ask the question how much money an owner would spent on their cat, because the research includes different socio-economic profile groups and that could be of influence. In this study, the human-animal relationship did not appear to be a significant risk for obesity in cats, but it is probably necessary to ask more questions on this subject, to get a better idea of the human affection for their cat, like they did in the E. Kienzle and R. Bergler
(2006) study.
In an earlier study by D. Robertson (1999) cats originating from households with only one or two cats were more likely to be overweight than cats from households with more than two cats.
This might arise from closer attention and perhaps extra food given to individual cats or might arise from increased energy expenditure during playing and/ or fighting in multi-cat households. (D. Robertson,
1999) In the present study however, cats living in a multi-cat household or living with one or more dogs did not appear to be a risk factor for obesity in cats, in contrast with the 1993 study of F. Allan where living with a dog in the household was a negative risk factor for obesity. The study of L. Colliard et al.
(2009) confirmed the finding that cats living in a households with other pets did not appear to be a risk factor for obesity. The influence of other risk factors involved could be an explanation of the difference in the results of different studies.
Because of the use of different body condition scoring systems, it is difficult to say if the prevalence of obesity in Palmerston North, New Zealand has increased since the 1993 study of F. Allan.
However, after changing the 9-point scoring system used in the current study, to the 5-point system used in the 1993 study, the current study suggests that the incidence of feline obesity in Palmerston
North, New Zealand has not increased over the last 15 years
In comparison with the 1993 study of F. Allan only two risk factor agreed with both studies: the owner’s perception of the body condition of the cat and the leg length of the cat. In the current study, leg length and age of the cat appeared to be risk factors, although the odds of obesity for these variables in the component model differed from the overall model. This suggests that leg length and age are influenced by the other variables in the overall model. More research and/or statistical analysis are necessary to assess the significance of leg length and age of the cat as a risk factor for obesity.
The owner’s perception of the body condition of the cat is amenable to use in weight loss programmes and for prevention of obesity. It is important that veterinarians and their assistants correct the owners’ perception of the body condition if their cats, for weight loss and prevention of obesity to be successful.

1.
Allan, F.J., Pfeiffer, D.U., Stones, B.R., Esslemont, D.H.B., Wiseman, M.S. A cross-sectional
study of risk factors for obesity in cats in New Zealand. (2000) Preventive Veterinary
Medicine, Vol. 46, p. 183-196
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Altman, D.G. 1991. Practical statistics for medical research. Chapman & Hall/ CRC.
3.
Colliard, L., Paragon, B.-M., Lemuet, B., Benet, J.-J., Blanchard, G. (2009) Prevalence and riskfactors of obesity in an urban population of healthy cats. Journal of Feline Medicine and surgery. Vol. 11, p. 135-140
4.
Donoghue, S., Scarlett, J.M. Diet and Feline Obesity. (1998) The Journal of Nutrition, Vol. 128,
No 12, p. 2776S-2778S.
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German, A.J. The growing problem of obesity in dogs and cats. (2006) The American society for nutrition. J. Nutr., Vol. 136, p. 1940S-1946S
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German, A.J., Holden, S.L., Moxham, G.L., Holmes, K.L., Hackett, R.M., Rawlings, J.M. A
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for Later Disease: A Life History and Evolutionary Perspective. American journal of human biology. Vol. 19, p. 1-19
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clinical tool. Feline pract., Vol 25, p. 13-8
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Laflamme, D.P. (2005) Nutrition for aging cats and dogs and the importance of body
condition. Vet. Clin. North. Am. Anim. Pract. Vol. May 35(3), p. 713-42
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Leeuw, B. de. Overgewicht, wie doet er wat aan? (2008) In Praktijk, Nr. 2, april 2008, p. 1
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management of obesity in dogs and cats. Int. J. Obesity. Vol. 18, p. S39-S43
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owned cats from metropolitan Perth, Western Australia. (1999) Preventive Veterinary
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18.
http://db.cbg-meb.nl

Houshehold Identifier Code ...........................................................................................
How many cats live in the household? ..........................................................................
Cat Number ...................................................................................................................
SIGNALMENT
What is the name of your cat? .......................................................................................
How old is your cat? ......................................................................................................
What sex is your cat? M (1) F (2)
Has your cat been spayed or castrated?
HOUSEHOLD VARIABLES
Yes (1) No (2)
How many people usually live in the household? ..........................................................
And how many of those people in the household are: over 60 years of age? ......................................................................................... less than 16 years of age? ..................................................................................
How many dogs live in the household? .........................................................................
CAT AFFINITY VARIABLE
[Showcard 1] Which of these statements best describes the relationship of your cat to the members of the household? ...........................................................................................
CAT FEEDING VARIABLES
Do you usually ensure that your cat’s food bowl always contains food?
Yes (1) No (2)
[Showcard 2] How often do you put food down for your cat? ..................................
[Showcard 3] How often do you feed your cat:
Dry cat food? .............................................................................
Canned cat food? ......................................................................
Cat food in pouches? .................................................................
Rolls or chubs? ..........................................................................
5
10
15
20

Milk? ............................................................................................
Table scraps? ............................................................................
Fresh meat or fish? ....................................................................
Vitamins and supplements? .......................................................
[Showcard 4] Of the dry food that is fed, how much of it is:
Iams brand? ...............................................................................
Hills brand? ................................................................................
Purina brand? ............................................................................
Royal Canin brand? ...................................................................
Proplan brand? ..........................................................................
Other brands? ............................................................................
Of the dry food that is fed, how much of it is ‘lite’ or low-calorie? ........
............................................................................................................
Have you fed your cat a diet prescribed by your veterinarian in the last 6 months?
Yes (1) No (2)
If yes, probe: ..................................................................................................................
........................................................................................................................................
........................................................................................................................................
What was the diet called? ..............................................................................................
For what condition was the diet prescribed? .................................................................
........................................................................................................................................
CAT CHARACTERISTIC VARIABLES
[Showcard 5] How active do you consider your cat to be? ...........................................
[Showcard 6] Which description best describes your cat? ...........................................
Has your cat been on medication prescribed by your veterinarian in the last 6 months?
Yes (1) No (2)
If yes, probe: ..................................................................................................................
........................................................................................................................................
........................................................................................................................................
What was the drug(s) called? ........................................................................................
For what condition was the drug prescribed? ................................................................
........................................................................................................................................
25
30
35

........................................................................................................................................
Weight ...........................................................................................................................
BCS ...............................................................................................................................
Leg Length .....................................................................................................................
Body Length ..................................................................................................................
42

1.
We dislike our cat and would rather not have it around.
2.
Our cat is not important to us. We don’t give it a lot of attention.
3.
Our cat is of some importance to us. We like having it around.
4.
Our cat is important to us. It is a part of our family.
5.
Our cat is very important to us. We treat it like our child.
1.
More than three times per day
2.
Three times per day
3.
Twice per day
4.
Once daily
5.
Every second day
6.
Less frequently than every second day
1.
Daily
2.
Every second or third day
3.
Once weekly
4.
Once fortnightly
5.
Less often than once a fortnight
6.
Never

1.
Greater than 95% of it.
2.
Around three-quarters of it.
3.
Around half of it.
4.
Around one-quarter of it.
5.
Less than 5% of it.
6.
None of it.
1.
Extremely overactive
2.
Overactive
3.
Normally active
4.
Inactive
5.
Extremely inactive
1.
Extremely thin
2.
Thin
3.
Normal weight
4.
Overweight
5.
Extremely overweight