Introduction

Nutrition and health have closely relationship, and to make it true, an adequate food intake associated with a correct diet energy density allows that dogs and cats get the sufficient daily calories to correct the energy balance (Defretin 1994; Munday 1996). Nowadays, alimentation care and nutritional supplementation have vital importance to prevent and, in some cases, treat some pathologies, including the nutritional ones. Besides, animal ideal body weight determination is extremely hard, because there are a lot of differences including breeds and individual body mass (Markwel et al. 1991; Wolfsheimer 1994). Obesity is defined as an excessive accumulation of body fat, affecting not only humans but also their pets, especially dogs and cats (Jerico at al. 2006), causing numerous physiology shortcomings in different organ systems (cardiovascular, osteoarticular, immune, digestive and endocrine), and an obvious reduction in the animal life quality (Jerico & Scheffer 2002). Another point of importance is the protein-energy malnutrition, always associated with progressive weight loss, body weight and fat and muscle mass reserves decrease (McMahon & Bistrian 1990). There are little information about obesity, malnutrition, and techniques that enable not only visual confirmation of these changes in animals. This paper proposes a new formula to describe the Canine Body Mass Index (CBMI), called Koury (2008), expanding information on obesity and malnutrition, and making their clinical diagnosis easier.

Material and Methods

The study was conducted at Amazon Federal Rural University (UFRA), Belém Campus, Pará State, Brazil, at the Institute of Animal Health and Production (ISPA). Additional external data collections were obtained in the metropolitan area of Belém. 100 adult dogs were used of the most varied breeds and physical situations. A form that contained relevant information to the research was applied to animal's owners, and data as address, animal's age, owner's name, among others, were obtained. After general information collection, animals were restricted so that body measurements could be taken. A flexible tape measure and a caliper specially developed for this research, with a centimeters scale and total size corresponds to 1.5 meters, were used. The measures collected were: CC1 = distance from Atlanto-occipital joint to the tail basis; CC2 = from forelimb (scapula) to the tail basis; WS = width between scapulae; WI = width between ilium; AA = distance from scapula to the ground; D = Scapula depth until end of the chest from top to bottom; CC = chest circumference; and AC = abdominal circumference. The weighing scale was made by analog ground for small animals and mechanical pedestal balance for the large ones. Based on the classification of three evaluators were determined Laflamme's classes (Laflamme 1998; Muller & Schossler 2006) to guide the new equation of CBMI (Canine Body Mass Index), called Koury (2008). Thenceforward, nutritional status classes were identified as underfeed, ideal and overfeed. After total data collection, it was tabulated, edited and used to generate 5 expressions to indicate animal's nutritional status, using biometric measurements, correlated with body weight. A constant (1000) present in the expressions was used to facilitate index interpretation. For reach each equation, average and standard deviation was calculated within the classes underfeed, ideal and overfeed. Based on these parameters were calculated mean confidence intervals, for each index of Laflamme's class. Were also established correlations between index and in all tests was considered the significance level of 0.05.

Results

After the groups formation called underfeed, ideals and overfeed, Pearson's correlations were established between the morphometric measures and weight. The main measures and respective values were: AA (0.90, 0.86, 0.84); CC2 (0.83, 0.85, 0.91); CC1 (0.86, 0.85, 0.89). From these measurements were developed equations to describe the animal's nutritional status, based on morphometric studies. Later, were checked equations efficiencies using graphs generated from the confidence intervals. The CBMI 1 corresponds to equation CBMI1 = (WEIGHT/(AA x CC2)) x 1000; CBMI2 = WEIGHT/CC1x1000, had small area of thin and normal absolute and a wide range of intersection between the two classes, so it provides a worse differentiation and framework of the animals in thin or normal, despite having areas of obese absolute well bounded. The CBMI3 = WEIGHT/AA2x1000, presented great proportionality of 3 classes studied and overfeed and underfeed range better defined, so this limit is wider than in CBMI1 and CBMI 2. The CBMI4 = WEIGHT/cc1X1000, showed proportion qualities similar to the CBMI3. The CBMI5 = (WEIGHT/(AA X CT) X 1000, was the worse index exploitation because occurred almost complete intersection of underfeed and ideal classes, which almost deny to differentiate animals studied in this research. These results are shown in Figure 1. To better assess the behavior of the mean found for CBMI3 and CBMI4 were made comparisons with the CBMI proposed by Muller & Schossler (2007) (Table 1) by means of the Pearson's correlations (above the diagonal) and Spearman (below the diagonal). The higher indexes of correlation were 0.87 and 0.86 between the CBMI4 and CBMI of Muller & Schossler (2007).

Table 1. Pearson (above the diagonal) and Spearman's correlation (below the diagonal) between canine mass body indexes. Belém, 2009.

Figure 1. Mean results of each indexes reached for underfeed, ideal and overfeed groups.

Discussion and Conclusion

In this research both groups and indexes presented differences in the mean experimental studied behavior. Greater settings were viewed in CBMI 3 and 4, elected as the best indexes, because they reflected, in a better way, animal's type classification. Despite of the evidence described for the CBMI3 and CBMI4 as the best expression of the characteristics of body mass based on the groups, the Pearson and Spearman's correlations showed greater similarity in the behavior of the CBMI4 mean and CBMI of Muller & Schollers (2007), where it appears that the extreme upper classes of underfeed and higher ideals become very close. This showed the degree of behavior differentiation between CBMI4 and CBMI3 and CBMI. This research is unprecedented and concluded that the Canine Body Mass Index 3 becomes the most efficient for the diagnosis of nutritional changes in this species.

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