Use of a morphometric method and body fat index system for estimation of body composition in overweight and obese cats

Angela L. Witzel Small Animal Clinical Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, TN 37996

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Claudia A. Kirk Small Animal Clinical Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, TN 37996

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George A. Henry Small Animal Clinical Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, TN 37996

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Philip W. Toll Hill's Pet Nutrition Inc, 400 SW 8th St, Topeka, KS 66601

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John J. Brejda Alpha Statistical Consulting, 4501 S 54th, Lincoln, NE 68516

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Inke Paetau-Robinson Hill's Pet Nutrition Inc, 400 SW 8th St, Topeka, KS 66601

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 PhD

Abstract

Objective—To develop morphometric equations for prediction of body composition and create a body fat index (BFI) system to estimate body fat percentage in overweight and obese cats.

Design—Prospective evaluation study.

Animals—76 overweight or obese cats ≥ 1 year of age.

Procedures—Body condition score (BCS) was determined with a 5-point scale, morphometric measurements were made, and dual-energy x-ray absorptiometry (DEXA) was performed. Visual and palpation-based evaluation of various body regions was conducted, and results were used for development of the BFI system. Best-fit multiple regression models were used to develop equations for predicting lean body mass and fat mass from morphometric measurements. Predicted values for body composition components were compared with DEXA results.

Results—For the study population, prediction equations accounted for 85% of the variation in lean body mass and 98% of the variation in fat mass. Values derived from morphometric equations for fat mass and lean mass were within 10% of DEXA values for 55 of 76 (72%) and 66 of 76 (87%) cats, respectively. Body fat as a percentage of total body weight (ie, body fat percentage) predicted with the BCS and BFI was within 10% of the DEXA value for 5 of 39 (13%) and 22 of 39 (56%) cats, respectively.

Conclusions and Clinical Relevance—The BFI system and morphometric equations were considered accurate for estimation of body composition components in overweight and obese cats of the study population and appeared to be more useful than BCS for evaluation of these patients. Further research is needed to validate the use of these methods in other feline populations. (J Am Vet Med Assoc 2014;244:1285–1290)

Abstract

Objective—To develop morphometric equations for prediction of body composition and create a body fat index (BFI) system to estimate body fat percentage in overweight and obese cats.

Design—Prospective evaluation study.

Animals—76 overweight or obese cats ≥ 1 year of age.

Procedures—Body condition score (BCS) was determined with a 5-point scale, morphometric measurements were made, and dual-energy x-ray absorptiometry (DEXA) was performed. Visual and palpation-based evaluation of various body regions was conducted, and results were used for development of the BFI system. Best-fit multiple regression models were used to develop equations for predicting lean body mass and fat mass from morphometric measurements. Predicted values for body composition components were compared with DEXA results.

Results—For the study population, prediction equations accounted for 85% of the variation in lean body mass and 98% of the variation in fat mass. Values derived from morphometric equations for fat mass and lean mass were within 10% of DEXA values for 55 of 76 (72%) and 66 of 76 (87%) cats, respectively. Body fat as a percentage of total body weight (ie, body fat percentage) predicted with the BCS and BFI was within 10% of the DEXA value for 5 of 39 (13%) and 22 of 39 (56%) cats, respectively.

Conclusions and Clinical Relevance—The BFI system and morphometric equations were considered accurate for estimation of body composition components in overweight and obese cats of the study population and appeared to be more useful than BCS for evaluation of these patients. Further research is needed to validate the use of these methods in other feline populations. (J Am Vet Med Assoc 2014;244:1285–1290)

Reports in recent years indicate that obesity in pet cats is a growing problem,1 with approximately 25% to 40% of pet cats considered overweight or obese.2–5 Obesity is associated with a wide range of diseases in cats, including diabetes and other metabolic and endocrine disorders, oral disease, and lower urinary tract diseases as well as decreased longevity.6,7

Although DEXA is considered the reference method for assessment of body condition in cats,8 it is expensive and impractical for routine use. Several numeric BCS systems have been developed for body condition assessment on the basis of palpation and visual assessment of the animal's silhouette.6,9,10 Body condition scores correspond reasonably well with body fat as a percentage of total body weight (ie, body fat percentage) for normal to slightly overweight animals but can underestimate adiposity for the most obese cats. To design effective weight loss plans, veterinarians must estimate energy requirements on the basis of ideal weight. Without broader tools to assess the body composition, weight loss plans can fail in morbidly obese cats.

Equations based on morphometric measurements have been developed as a simple, noninvasive, and accurate way to predict body fat percentage in dogs,11,12 and this approach has also been used for lean, anesthetized cats.13 The purpose of the study reported here was to develop equations for accurate prediction of lean body mass and fat mass on the basis of morphometric measurements and to create a visual assessment– and palpation-based BFI system to accurately predict body fat percentage in overweight or obese cats with DEXA used as a reference standard. We further intended to assess the accuracy of a 5-point BCS for estimation of body fat percentage in this population. Our group has recently tested similar tools for assessment of body composition in overweight and obese dogs.14

Materials and Methods

Animals—Pet cats ≥ 1 year of age and considered overweight or obese in the opinion of the investigator were recruited during regular visits to the Veterinary Clinic at the University of Tennessee College of Veterinary Medicine, Knoxville, Tenn, between August 10, 2009, and January 5, 2011. Cats were excluded if they were known to have severe concurrent systemic or organ disease that might have interfered with accurate assessment of body composition or increased the health risks of general anesthesia; had an injury or condition resulting in clinically relevant swelling or edema; or were pregnant, fractious, or deemed poor candidates for anesthesia by the investigator. Informed written consent from owners was obtained prior to enrollment of cats in the study. The study was approved by the institutional animal care and use committees at the University of Tennessee and Hill's Pet Nutrition Inc and performed in compliance with the Hill's Pet Nutrition Inc Global Animal Welfare Policy.

Study design—The study was conducted prospectively and in 2 phases. In phase 1, feasibility of morphometric measurements for use in predicting lean body mass and fat mass was assessed in a clinical setting, and a new BFI system was developed as a tool for estimation of body fat percentage. In phase 2, an additional group of cats was enrolled in the study and used to assess accuracy of the BFI in a new population. Morphometric measurements from cats in both phases were used to create a data set for the development of equations to predict body composition. Accuracy of BCS for estimation of body fat percentage was assessed and subjectively compared with that of the BFI system by use of data from phase 2 of the study.

During a single visit, 1 of the 2 lead investigators (ALW and CAK) recorded the cat's medical and dietary history, age, sex, and reproductive status and determined body weight and BCS. These investigators also performed a physical examination. A blood sample was collected for a CBC and serum biochemical analysis. From a pool of 6 licensed veterinary technicians and veterinary nutritionists, 4 individuals performed morphometric measurements as well as a visual and palpation-based assessment of each cat for use in development of validation of the BFI. All measurements and assessments were performed in duplicate with ≥ 1 hour between repetitions. Although formal steps were not taken to ensure blinding to other investigators' subjective evaluations during this stage, all assessments were performed independently. Because of temperament issues, some cats had measurements performed while sedated for DEXA. Radiographs of the chest and abdomen were obtained immediately prior to DEXA measurements. Dual-energy x-ray absorptiometry was then used to determine lean body mass, fat mass, and body fat percentage in all cats.

Determination of BCS and BFI—In both phases of the study, BCS was assessed by investigators on a 5-point scale (where 1 = emaciated and 5 = obese).6 A BFI chart for overweight and obese cats was developed in phase 1 as described elsewhere for dogs.14 Briefly, each investigator was asked to assess and describe various regions or aspects of each cat's body by use of a prepared list.a Variables for the head and neck included the amount of fat cover and prominence of bony structures of the face, shape and distinction of the neck, tightness of the scruff, and thickness of fat at the scruff. In the thoracic area, the amount of fat covering in the pectoral region and prominence and ease of palpation of the sternum, scapulae, and ribs (examined at approx one-third of the distance between the dorsum and ventrum) were assessed. For the abdomen and caudal body region, prominence, ease of palpation, and amount of fat cover at the tail base as well as the presence and amount of fat present in the inguinal fat pad were evaluated. Ease of palpation of the abdominal contents and body shape as viewed from the side (lateral aspect), from above (dorsal aspect), and from behind (caudal aspect) were also assessed. Investigators selected the best description for each variable and provided additional comments if needed. At the time of measurement, investigators were blinded to the body fat percentage determined by DEXA. Cats were subsequently categorized on the basis of DEXA-measured body fat percentage (26% to 35% [BFI, 30], 36% to 45% [BFI, 40], 46% to 55% [BFI, 50], or 56% to 65% [BFI, 60]). The description most commonly selected for each variable for cats with a given body fat percentage was identified. This description was entered into the BFI chart for that variable and category combination. For example, all descriptions of body shape as viewed from above for cats with a body fat percentage of 36% to 45% were noted, and the description that was used most often was incorporated into the chart for that variable in the BFI 40 category.

The new BFI chart was used to assign a BFI score to cats enrolled in phase 2, with an overall BFI score chosen for each cat on the basis of the most frequently selected descriptions for that animal (Appendix 1). Results of BCS and BFI determination for cats in phase 2 were then used to estimate body fat percentages, and these were evaluated by comparison with the DEXA-measured values.

Morphometric measurements—Four investigators each made duplicate morphometric measurements of the body, hind limb, forelimb, and head (Appendix 2) of each animal with a standard tailor's measuring tape or digital calipers.b The mean of the duplicate measurements was used in the development of prediction equations.

DEXA—General anesthesia was induced and maintained with propofol (2 to 4 mg/kg [0.91 to 1.8 mg/lb]) delivered through a cephalic catheter, and DEXA was performed with a bone densitometerc set up for an adult whole-body scan. Cats were placed in sternal recumbency on the DEXA table with the head positioned at the end of the table where the scan was initiated and the nose behind the line at that end of the table. The head and spine were aligned on the center line, and the carpal joints were flexed to position the forefeet at approximately 90° from the long axis of the limb and, when possible, below the caudal aspect of the skull. The hind limbs and tail were extended but included in the whole-body scan. Calculations for lean body mass, fat mass, and body fat percentage were made with commercially available software.d

Data analysis—Statistical analysis was performed with statistical software.e Values of P < 0.05 were considered significant.

Multiple regression analysis was used to determine which morphometric variables provided the best estimates of lean body mass and fat mass as previously described.14 All morphometric measurements were initially screened for collinearity.f,g Sets of variables with small eigenvalues and a condition index > 30 were considered to be highly correlated, and only 1 variable from each highly correlated set was included in the model selection procedure. The best model was selected from among the stepwise selection procedure, Akaike information criterion, Schwarz Bayesian criterion statistics, and the maximum adjusted R2 statistic. This selection was based on meeting most of the following criteria: all predictor variables significant at α = 0.05; residuals normally distributed, as assessed with the Shapiro-Wilk test; low or trivial collinearity among predictor variables as indicated by a variance inflation factor < 10 for all predictor variables; no pattern in the studentized residuals; and absolute values < 2.5 for the studentized residuals. In addition to these criteria, the prediction equation for the selected model had the smallest SE from among all candidate models. Only the best candidate model was evaluated further. If different procedures selected the same model, that model was only evaluated once.

Inter-rater variability was estimated with a random-effects ANOVA model that included technicians, animals, the duplicate observations made by each technician, and all interactions as sources of variation in the analysis. The variance associated with the technician divided by total variation for each measurement was used as the estimate of intrarater variability.

In addition to measured variables, calculated variables were created by addition, subtraction, multiplication or division of measured morphometric variables to account for differences in body size and conformation among cats. These included variables of limb length raised to the power of 0.8 and 1.2, selected according to known scaling factors for metabolic body size and skeletal mass in mammals.15 Diameter and area variables were calculated from circumference measurements for the head, thorax, and pelvis as previously described14; additional variables used to account for differences in limb length and body shape included head diameter multiplied by hind leg length and thoracic diameter multiplied by front leg length.

Accuracy of the BCS and BFI systems for determination of body fat percentage in cats was evaluated by assigning a body fat percentage estimate to each score6 and then dividing that value for each animal by the body fat percentage as measured by DEXA. For the BCS scale, scores of 3, 4, and 5 were assigned body fat estimates of 20%, 30%, and 40%, respectively.6 For the BFI, a score of 30, 40, 50, or 60 was assigned a body fat estimate of 30%, 40%, 50%, or 60%, respectively.14 Accuracy of morphometric equations was assessed by dividing the predicted value for a given variable by the actual DEXA-measured value.

For these calculations, body weight was measured in pounds, and all other measurements were in centimeters. Diameters were calculated as circumference/3.

Results

Cats—Seventy-six cats were included in the study (37 in phase 1 and 39 in phase 2). There were 38 females (all spayed) and 38 males (1 sexually intact and 37 neutered). Breeds included domestic shorthair (n = 54), domestic longhair (14), and Burmese (2) as well as Abyssinian or Somali, Singapura, Snowshoe, American Shorthair, and Devon Rex (1 each); breed for 1 cat was not recorded. Mean ± SD age of cats was 5.9 ± 3.7 years (range, 1 to 15 years), and weight was 6.2 ± 1.9 kg (13.64 ± 4.18 lb; range, 2.8 to 11.5 kg [6.16 to 25.3 lb]). Body fat percentage measured with DEXA ranged from 25.2% to 62.1% and was ≥ 50% in 33 cats, 40% to < 50% in 21 cats, 30% to < 40% in 16 cats, and < 30% in 6 cats. Ideal body fat percentage for cats is approximately 15% to 25% body fat.6,7 The BCS was 3 for 1 cat, 4 for 17 cats, and 5 for 58 cats.

Scores for the BFI developed in phase 1 ranged from 30 to 60. These values represented estimates of 26% to 65% body fat (Appendix 2).

Estimation of body composition through morphometric measurements—Inter-rater variability was low for most measured variables (< 2% for pelvic circumference, thoracic circumference, and hind limb length; 2.1% for forelimb length; 2.3% for circumference of the head; 2.8% for hind limb circumference; and 5% for body length), with slightly higher values for metacarpal (16.4%) and metatarsal (16.4%) pad width, forelimb circumference (17.8%), and metacarpal (18.1%) and metatarsal (19.5%) pad length. Intrarater variability was < 2% for all measurements.

The best-fit equations for estimating lean body mass and fat mass on the basis of morphometric data from cats in both study phases were determined by multiple regression analysis (Table 1); the adjusted R2 value of the models was 0.85 for estimation of mean lean body mass and 0.98 for estimation of fat mass. When the best-fit equations were applied to all cats in the study, there appeared to be a linear relationship between the predicted value and the DEXA-measured value over the entire range of values (Figure 1). Deviations between estimated and DEXA values did not correlate with body weight or with the lean body mass, fat mass, or body fat percentage determined by DEXA (data not shown). The predicted lean mass was within 10% of the DEXA value for 66 of 76 (87%) of the cats, and the predicted fat mass was within 10% of the DEXA value for 55 (72%) cats (Table 2).

Table 1—

Best-fit equations for estimation of body composition with morphometric measurements in 76 overweight or obese cats.

VariableEquationAdjusted R2
Lean body mass (g)30.3 × (head diameter × hind limb length) + 316.9 × forelimb circumference + 2.55 × (thoracic diameter × forelimb length) + 14.4 × body length – 3,058.70.85
Fat mass (g)436.9 × body weight – 24.0 × (head diameter × forelimb length) – 309.2 × forelimb circumference + 2,522.70.98

For these calculations, body weight was measured in pounds, and all other measurements were in centimeters. Diameters were calculated as circumference/3.

Table 2—

Accuracy of the prediction equations in Table 1 for body composition components when applied to the study population (n = 76 cats).

Variable predicted
Result (comparison with DEXA value)Lean massFat mass
Underestimated by > 20%0 (0)1 (1)
Underestimated by > 10%–20%4 (5)6 (8)
Within 10%66 (87)55 (72)
Overestimated by > 10%–20%6 (8)8 (11)
Overestimated by > 20%0 (0)6 (8)

Data are number (%) of cats.

Estimation of body fat percentage with BCS and BFI—When the 5-point BCS system was used for evaluation of cats in phase 2, body fat percentage estimated on the basis of BCS was within 10% of that determined with DEXA in 5 of 39 (13%) cats, whereas the body fat percentage estimated with the BFI system in phase 2 was within 10% of the DEXA value in 22 of 39 (56%) cats. With the BCS system, body fat percentage was within 20% of that determined by DEXA in 15 of 39 (38%) cats, and when the BFI system was used, the result was within 20% of the DEXA value in 35 of 39 (90%) cats. The BCS underestimated body fat percentage by > 10% to 20% in 9 of 39 (23%) cats and > 20% in 24 (62%) cats.

Figure 1—
Figure 1—

Observed body composition values determined by DEXA and predicted with best-fit equations on the basis of morphometric measurements in 76 pet cats ≥ 1 year of age that were considered overweight or obese by their veterinarians. A—Lean body mass. B—Fat mass.

Citation: Journal of the American Veterinary Medical Association 244, 11; 10.2460/javma.244.11.1285

Discussion

Recent studies9,16 have found that a number of cats visiting veterinary clinics have > 50% body fat. Those reports and the results of our study indicate that gross obesity in cats is not uncommon. Accurate assessment of body composition, especially lean body mass, is important for the development of appropriate feeding plans for pet cats. In the present study, we developed equations for predicting body composition on the basis of morphometric measurements in overweight and obese cats with up to 62.1% body fat as measured by DEXA. The equations for estimation of lean body mass were accurate across a wide range of body conditions in the specific population of cats used in development of these equations, with predicted values within 10% of the DEXA value for 66 of 76 (87%) cats. When traditional BCS scores of 3, 4, and 5 on a 5-point scale were assigned body fat estimates of 20%, 30%, and 40%, respectively,6 the BCS underestimated body fat percentage by > 10% to 20% in 9 of 39 (23%) cats and > 20% in 24 (62%) cats. This may be attributable to the fact that the highest BCS score (5/5) equates to only approximately 40% body fat.6 In veterinary practice, an overestimation of lean body mass can lead to overestimation of energy needs and result in failure of a weight loss regimen.

In the present study, we measured more variables than were needed for the final morphometric equations, and the cats underwent 8 rounds of measurement (4 investigators in duplicate). Several cats became intolerant of these repeated measurements and had to have some measurements performed while sedated. This did not appear to affect the results of the study because interrater and intrarater variability were low. In a veterinary practice setting, a single round of measurements should be well tolerated and require only about 5 min/cat to complete. Although the best-fit morphometric equations appeared to provide accurate estimates of lean body mass and fat mass in most study cats, further validation in a separate study population is needed. Importantly, morphometric equations were not evaluated in cats of many breeds, cats that were not considered overweight, or patients with medical conditions that often alter body composition (eg, chronic kidney disease).

The BFI system developed and tested in this study was intended as an adjunctive method to the BCS system, which also relies on palpation and visual assessment; however, the BFI system was designed for use with measurements from overweight and obese cats with a wide range of body conditions and compositions. Whereas the 5-point BCS predicted body fat percentage within 10% of DEXA values for only 5 of 39 (13%) cats, BFI results were within this range for 22 (56%) cats, suggesting that it may be a more useful tool for assessment of these patients. As pet cats are kept indoors with greater frequency than in the past, with a more sedentary lifestyle and an often unlimited food supply, obesity will continue to be a problem. Although further research is needed, the tools described in this paper provide an important step in the development of simple and reliable methods for veterinarians to use in estimation of body fat and ideal body weight to design effective weight loss plans.

ABBREVIATION

BCS

Body condition score

BFI

Body fat index

DEXA

Dual-energy x-ray absorptiometry

a.

A copy of the original chart is available from the corresponding author upon request.

b.

Ultratech, General, New York, NY.

c.

QDR4500 Acclaim Series Elite, Hologic Inc, Danbury, Conn.

d.

Apex, version 2.3, Hologic Inc, Danbury, Conn.

e.

SAS, version 9.13, SAS Institute Inc, Cary, NC.

f.

COLLIN, SAS, version 9.13, SAS Institute Inc, Cary, NC.

g.

PROC REG, SAS, version 9.13, SAS Institute Inc, Cary, NC.

References

  • 1. German AJ. The growing problem of obesity in dogs and cats. J Nutr 2006;136:1940S1946S.

  • 2. Cave N, Allan F, Schokkenbroek S. A cross-sectional study to compare changes in the prevalence and risk factors for feline obesity between 1993–2007 in New Zealand. Prev Vet Med 2012;107:121133.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 3. Colliard L, Paragon B & Lemuet B, et al. Prevalence and risk factors for obesity in an urban population of healthy cats. J Feline Med Surg 2009;11:135140.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 4. Courcier EA, O'Higgins R & Mellor DJ, et al. Prevalence and risk factors for feline obesity in a first opinion practice in Glasgow, Scotland. J Feline Med Surg 2010;12:746753.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 5. Lund E, Armstrong P & Kirk C, et al. Prevalence and risk factors for obesity in adult cats from private US veterinary practices. Int J Appl Res Vet Med 2005;3:8896.

    • Search Google Scholar
    • Export Citation
  • 6. Toll PW, Yamka RM & Schoenherr WD, et al. Obesity. In: Hand MS, Thatcher CD, Remillard RL, et al., eds.Small animal clinical nutrition. Topeka, Kan: Mark Morris Institute, 2010;501542.

    • Search Google Scholar
    • Export Citation
  • 7. Laflamme DP. Understanding and managing obesity in dogs and cats. Vet Clin North Am Small Anim Pract 2006;36:12831295.

  • 8. Buelund LE, Nielsen DH & McEvoy FJ, et al. Measurement of body composition in cats using computed tomography and dual energy x-ray absorptiometry. Vet Radiol Ultrasound 2011;52:179184.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 9. German AJ, Holden SL & Moxham GL, et al. A simple, reliable tool for owners to assess the body condition of their dog or cat. J Nutr 2006;136:2031S2033S.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 10. Laflamme D. Development and validation of a body condition score system for cats: a clinical tool. Feline Pract 1997;25 (2):1318.

    • Search Google Scholar
    • Export Citation
  • 11. Jeusette I, Greco D & Aquino F, et al. Effect of breed on body composition and comparison between various methods to estimate body composition in dogs. Res Vet Sci 2010;88:227232.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12. Mawby DI, Bartges JW & d'Avignon A, et al. Comparison of various methods for estimating body fat in dogs. J Am Anim Hosp Assoc 2004;40:109114.

  • 13. Stanton CA, Hamar DW & Johnson DE, et al. Bioelectrical impedance and zoometry for body composition analysis in domestic cats. Am J Vet Res 1992;53:251257.

    • Search Google Scholar
    • Export Citation
  • 14. Witzel AL, Kirk CA & Toll PW, et al. Use of a novel morphometric method and body fat index system for estimation of body composition in overweight and obese dogs. J Am Vet Med Assoc 2014;244:12791284.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15. National Research Council. Energy. In: Nutrient requirements of dogs and cats. Washington, DC: The National Academies Press, 2006;2839.

    • Search Google Scholar
    • Export Citation
  • 16. Bjornvad CR, Nielsen DH & Armstrong PJ, et al. Evaluation of a nine-point body condition scoring system in physically inactive pet cats. Am J Vet Res 2011;72:433437.

    • Crossref
    • Search Google Scholar
    • Export Citation

Appendix 1

Body fat index chart with descriptors for visual and palpation-based assessment of overweight and obese cats.

BFI
Variable30405060
Body fat (%)26–3536–4546–5556–65
Face structuresSlight fat cover; defined bony structuresSlight to moderate fat cover; defined to slight bony structuresModerate fat cover; slight to minimal bony structuresThick fat cover; minimal to no bony structures
Head and neckClear distinction between head and shoulder; loose scruff; slight scruff fatClear to slight distinction between head and shoulder; loose to snug scruff; slight to moderate scruff fatMinimal distinction between head and shoulder; loose to snug scruff; slight to moderate scruff fatPoor to no distinction between head and shoulder; snug to tight scruff; moderate to very thick scruff fat
SternumDefined, slightly prominent; easy to palpate; slight to moderate pectoral fatMinimally prominent; palpable; moderate pectoral fatPoorly defined to not prominent; difficult to palpate; moderate to thick pectoral fatNot prominent; very or extremely difficult to palpate; very or extremely thick pectoral fat
ScapulaeDefined, slightly prominent; easy or very easy to palpateSlightly prominent; easy to palpateMinimally to not prominent; palpableNot prominent; difficult to palpate
RibsNot prominent; easy to palpateNot prominent; palpableNot prominent; difficult to palpateNot prominent; extremely difficult or impossible to palpate
AbdomenLoose abdominal skin with minimal fat; easy to palpate abdominal contentsObvious skin fold with moderate fat; easy to palpate abdominal contentsHeavy fat pad; difficult to palpate abdominal contentsVery heavy fat pad; indistinct from abdominal fat; impossible to palpate abdominal contents
Tail baseSlightly to minimally prominent bony structure; palpable; slight fat coverSlightly to minimally prominent bony structure; palpable; slight to moderate fat coverPoorly defined bony structure; difficult to palpate; moderate to thick fat coverBony structure not prominent; very or extremely difficult to palpate; very thick to extremely thick fat cover
Body shape
  From behindClear to poor muscle definition under a thin to moderate layer of fatPoor muscle definition under a moderate layer of fatRounded appearance; thick layer of fatRounded to square appearance; thick layer of fat
  From the sideNo abdominal tuckSlight abdominal bulgeModerate abdominal bulgeSevere abdominal bulge
  From aboveSlight hourglass or lumbar waistLumbar waistBroadened backSeverely broadened back

The BFI was developed in phase 1 of the study on the basis of data obtained for 37 cats. In phase 2, the BFI was used to estimate body fat percentage in a new group of 39 cats. Investigators chose the best description for each variable for each cat; the score most frequently assigned for a given cat (ie, the score for the column with the highest number of descriptions chosen) was used as its overall BFI score. Results were evaluated by comparison with the body fat percentage determined by means of DEXA.

Appendix 2

List of morphometric measurements used in the regression analysis to determine equations that best predicted body composition components of interest (lean body mass and fat mass).

MeasurementDevice used (units)Description
Body
  Length*Tailor's tape (cm)From the nasal planum to the tail base (approx level of S2–S3); tape was placed along the dorsum, following natural curvatures of the body
  Thoracic circumference*Tailor's tape (cm)Around the thorax at the level of fourth through sixth ribs
  Pelvic circumferenceTailor's tape (cm)Around the caudal aspect of the abdomen in the region of the fifth lumbar vertebra
Hind limb
  Length*Tailor's tape (cm)From the proximal aspect of the metatarsal pad to the proximal tip of the calcaneal tuber
  CircumferenceTailor's tape (cm)Midshaft around the tibia
  Metatarsal pad widthDigital caliper (mm)Micrometer laid flat onto the foot at the base of the pad
  Metatarsal pad lengthDigital caliper (mm)Micrometer laid flat onto the foot at the base of the pad
Forelimb
  Length*Tailor's tape (cm)From the proximal aspect of metacarpal pad to the proximal tip of the olecranon
  Circumference*Tailor's tape (cm)Midshaft around the radius
  Metacarpal pad widthDigital caliper (mm)Micrometer laid flat onto the foot at the base of the pad
  Metacarpal pad lengthDigital caliper (mm)Micrometer laid flat onto the foot at the base of the pad
Head
  Circumference*Tailor's tape (cm)Widest point of the head between the eyes and ears

Measurements used in the best-fit morphometric equations.

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