Shelley L. Holden

Improvement in insulin resistance and reduction in plasma inflammatory adipokines after weight loss in obese dogs

Obesity is now a major disease of dogs, predisposing to numerous disorders including diabetes mellitus. Adipocytes are active endocrine cells, and human obesity is characterized by derangements in inflammatory adipokine production. However, it is unclear as to whether similar changes occur in dogs. The purpose of the current study was to assess insulin sensitivity and inflammatory adipokine profiles in dogs with naturally occurring obesity and to investigate the effect of subsequent weight loss. Twenty-six overweight dogs were studied, representing a range of breeds and both sexes. All dogs underwent a weight loss program involving diet and exercise. Body fat mass was measured by dual-energy x-ray absorptiometry; plasma concentrations of insulin, glucose, and a panel of inflammatory adipokines (including acute-phase proteins, cytokines, and chemokines) were also analyzed. Body fat mass before weight loss was positively correlated with both plasma insulin concentrations (Kendall tau=0.30, P=0.044) and insulin:glucose ratio (Kendall tau=0.36, P=0.022), and both decreased after weight loss (P=0.0037 and 0.0063, respectively). Weight loss also led to notable decreases in plasma tumor necrosis factor-alpha (TNF-alpha), haptoglobin, and C-reactive protein concentrations (P<0.05 for all), suggesting improvement of a subclinical inflammatory state associated with obesity. This study has demonstrated that in obese dogs, insulin resistance correlates with degree of adiposity, and weight loss improves insulin sensitivity. Concurrent decreases in TNF-alpha and adipose tissue mass suggest that in dogs, as in humans, this adipokine may be implicated in the insulin resistance of obesity.

A Simple, Reliable Tool for Owners to Assess the Body Condition of Their Dog or Cat

Numerous methods exist for quantifying body composition and body fat mass in companion animals. In a clinical setting, the most widely accepted and practical method of body condition evaluation is condition scoring using visual assessment and palpation (1). All such systems attempt to partition a body composition continuum into a finite number of categories. Currently, 3 main systems exist, all of which use similar visual and palpable characteristics, but which differ by the number of integer categories within the scoring system (e.g., 5 points, 6 points, and 9 points) (2–8). The most widely accepted system is the 9-integer scale system, which has previously been shown to correlate well with body fat mass determined by dual-energy X-ray absorptiometry (DXA) (2–4). To aid decision making, a series of animal silhouettes are also provided that illustrate the visual characteristics for a typical (e.g., Labrador morphology) dog and cat. Scores determined by different operators have also been shown to correlate well (2–4), although a degree of expertise is required, rendering this system less accessible to untrained pet owners. S.H.A.P.E (Size, Health And Physical Evaluation) is a new algorithm-based system that uses similar visual and palpable characteristics as existing scoring systems (see http://www.petslimmers.com/shape.htm). A series of questions are followed that direct the operator to examine the animal in a sequential fashion. The questions instruct the operator to perform examinations that will determine the presence and amount of subcutaneous fat (over the ribcage and spine, etc.), and the amount of abdominal fat (by determining the presence and degree of abdominal tuck). Ultimately, 1 of 7 categories of body condition is chosen, each of which is assigned an alphabetical character from A (underweight) to G (obese). Letters were chosen for this new system to avoid confusion with current body condition score systems. 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. The aim of the current study was to assess the performance of the algorithm system in predicting body composition in dogs and cats, and to acquire preliminary data on how the system performed in the hands of both experienced and inexperienced operators.

Obesity-related metabolic dysfunction in dogs: a comparison with human metabolic syndrome

BackgroundRecently, metabolic syndrome (MS) has gained attention in human metabolic medicine given its associations with development of type 2 diabetes mellitus and cardiovascular disease. Canine obesity is associated with the development of insulin resistance, dyslipidaemia, and mild hypertension, but the authors are not aware of any existing studies examining the existence or prevalence of MS in obese dogs.Thirty-five obese dogs were assessed before and after weight loss (median percentage loss 29%, range 10-44%). The diagnostic criteria of the International Diabetes Federation were modified in order to define canine obesity-related metabolic dysfunction (ORMD), which included a measure of adiposity (using a 9-point body condition score [BCS]), systolic blood pressure, fasting plasma cholesterol, plasma triglyceride, and fasting plasma glucose. By way of comparison, total body fat mass was measured by dual-energy X-ray absorptiometry, whilst total adiponectin, fasting insulin, and high-sensitivity C-reactive protein (hsCRP) were measured using validated assays.ResultsSystolic blood pressure (P = 0.008), cholesterol (P = 0.003), triglyceride (P = 0.018), and fasting insulin (P < 0.001) all decreased after weight loss, whilst plasma total adiponectin increased (P = 0.001). However, hsCRP did not change with weight loss. Prior to weight loss, 7 dogs were defined as having ORMD, and there was no difference in total fat mass between these dogs and those who did not meet the criteria for ORMD. However, plasma adiponectin concentration was less (P = 0.031), and plasma insulin concentration was greater (P = 0.030) in ORMD dogs.ConclusionsIn this study, approximately 20% of obese dogs suffer from ORMD, and this is characterized by hypoadiponectinaemia and hyperinsulinaemia. These studies can form the basis of further investigations to determine path genetic mechanisms and the health significance for dogs, in terms of disease associations and outcomes of weight loss.

Quality of life is reduced in obese dogs but improves after successful weight loss

Obesity is thought to affect quality of life, but limited objective data exist to support this supposition. The current study aim was to use a questionnaire to determine health-related quality of life (HRQOL) both before and after weight loss, in obese client-owned dogs. Fifty obese dogs were included, and represented a variety of breeds and genders. Prior to weight loss, owners were asked to complete a validated standardised questionnaire to determine HRQOL. Thirty of the dogs successfully completed their weight loss programme and reached target, and owners then completed a follow-up questionnaire. The completed questionnaire responses were transformed to scores corresponding to each of four factors (vitality, emotional disturbance, anxiety and pain), and scored on a scale of 0-6. Changes in the scores were used to explore the sensitivity of the questionnaire, and scores were correlated with responses to direct questions about quality of life and pain, as well as weight loss. Dogs that failed to complete their weight loss programme had lower vitality and higher emotional disturbance scores than those successfully losing weight (P=0.03 for both). In the 30 dogs that completed, weight loss led to an increased vitality score (P<0.001), and decreased scores for both emotional disturbance (P<0.001) and pain (P<0.001). However, there was no change in anxiety (P=0.09). The change in vitality score was positively associated with percentage weight loss (r(P)=0.43, P=0.02) and percentage body fat loss (r(P)=0.39, P=0.03). These results indicate demonstrable improvement in HRQOL for obese dogs that successfully lose weight.

Faecal microbiota in lean and obese dogs

Previous work has shown obesity to be associated with changes in intestinal microbiota. While obesity is common in dogs, limited information is available about the role of the intestinal microbiota. The aim of this study was to investigate whether alterations in the intestinal microbiota may be associated with canine obesity. Using 16S rRNA gene pyrosequencing and quantitative real-time PCR, we evaluated the composition of the faecal microbiota in 22 lean and 21 obese pet dogs, as well as in five research dogs fed ad libitum and four research dogs serving as lean controls. Firmicutes, Fusobacteria and Actinobacteria were the predominant bacterial phyla. The phylum Actinobacteria and the genus Roseburia were significantly more abundant in the obese pet dogs. The order Clostridiales significantly increased under ad libitum feeding in the research dogs. Canine intestinal microbiota is highly diverse and shows considerable interindividual variation. In the pet dogs, influence on the intestinal microbiota besides body condition, like age, breed, diet or lifestyle, might have masked the effect of obesity. The study population of research dogs was small, and further work is required before the role of the intestinal microbiota in canine obesity is clarified.

Effects of weight loss in obese cats on biochemical analytes related to inflammation and glucose homeostasis.

The aim of the current study was to measure circulating metabolic and inflammation-related biochemical analytes in obese cats before and after weight loss. Thirty-seven overweight neutered cats were studied, median body weight 6.85 kg (range, 4.70 to 10.30 kg), representing a range of ages and both sexes. An individualized weight-loss program was devised for each cat and monitored until completion. Body fat mass was determined by dual-energy x-ray absorptiometry, whereas plasma concentrations of acute-phase proteins (APPs; eg, haptoglobin and serum amyloid A), hormones (eg, insulin, IGF-1, and adiponectin), and enzymes (eg, butyrylcholinesterase and paraoxonase type 1 [PON-1]) associated with inflammation and metabolic compounds (eg, glucose) were also measured. No significant changes were found in APPs after weight loss (P > 0.3), but significant increases in plasma adiponectin (P = 0.021) and IGF-1 (P = 0.036) were seen, whereas insulin (P < 0.001) and homeostasis model assessment (P = 0.005) decreased significantly. Plasma concentrations before weight loss of PON-1 (P = 0.004), adiponectin (P = 0.02), and IGF-1 (P = 0.048) were less in cats that failed to complete weight loss than cats that were successful, whereas glucose concentration was greater. Finally, multivariable linear regression analysis showed that lean tissue loss during weight management was associated with percentage weight loss (greater weight loss, greater lean tissue loss; R = 0.71, P < 0.001) and plasma adiponectin concentration before weight loss (lesser adiponectin, more lean tissue loss; R = -0.52, P = 0.023). In conclusion, various metabolic abnormalities occur in feline obesity, and these can be linked to outcomes of weight-loss programs. The changes that occur with weight loss suggest an improved metabolic status.

Imprecision when using measuring cups to weigh out extruded dry kibbled food

Many pet cats and dogs are fed dry extruded kibbled food by measuring cup, yet the precision and accuracy of this feeding strategy is not known. Over 12 studies, we assessed precision and accuracy of weighing out food portions, of various dry kibbled foods, by measuring cup. Poor precision was noted in all studies, with intra- and inter-subject coefficients of variation ranging from 2 to 13% and 2 to 28% respectively. Variable accuracy was also noted, which ranged from an 18% under-estimate to an 80% over-estimate in portion size. No specific factors were associated with imprecision, but the degree of inaccuracy was negatively associated with portion size (R = -0.67, p = 0.022), and positively associated with the number of subjects participating in the study (R = 0.60, p = 0.048). This is the first study to document imprecision and inaccuracy of using measuring cups to estimate portions of extruded dry kibbled food. Over time, such errors could contribute to insidious weight gain in companion animals, potentially contributing to the development of obesity. Imprecision in measuring food portions could also contribute to failure of weight management programmes for obese animals.

Long-term follow-up after weight management in obese dogs: The role of diet in preventing regain

Regain after weight loss is widely reported in humans, but there is little information on this phenomenon in dogs. The current study aim was to determine long-term success of a weight loss regime and those factors linked with regain. Thirty-three obese dogs, that had successfully lost weight, were included, all enrolled between December 2004 and May 2009. After weight loss, dogs were switched to a maintenance regime and follow-up weight checks were performed periodically. A review of cases that had completed their weight programme was held during the summer of 2010 and a follow-up check was subsequently conducted, where dogs were reweighed and information was collected on current feeding practices. Median duration of follow-up was 640 days (119-1828 days). Fourteen dogs (42%) maintained weight, 3 (9%) lost >5% additional weight, and 16 (48%) gained >5% weight. Dogs fed a purpose-formulated weight loss diet regained less weight than those switched onto a standard maintenance diet (P=0.0016). Energy intake at the time of follow-up was significantly higher in those dogs fed a standard maintenance diet, compared with those that had remained on a purpose-formulated weight loss diet (P=0.017). These results suggest that weight regain occurs in about half of dogs after successful weight loss. Long-term use of a purpose-formulated weight management diet can significantly limit regain in the follow-up period, likely by limiting food intake.

Effect of Weight Loss in Obese Dogs on Indicators of Renal Function or Disease

BACKGROUND Obesity is a common medical disorder in dogs, and can predispose to a number of diseases. Human obesity is a risk factor for the development and progression of chronic kidney disease. OBJECTIVES To investigate the possible association of weight loss on plasma and renal biomarkers of kidney health. ANIMALS Thirty-seven obese dogs that lost weight were included in the study. METHODS Prospective observational study. Three novel biomarkers of renal functional impairment, disease, or both (homocysteine, cystatin C, and clusterin), in addition to traditional markers of chronic renal failure (serum urea and creatinine, urine specific gravity [USG], urine protein-creatinine ratio [UPCR], and urine albumin corrected by creatinine [UAC]) before and after weight loss in dogs with naturally occurring obesity were investigated. RESULTS Urea (P = .043) and USG (P = .012) were both greater after weight loss than before loss, whilst UPCR, UAC, and creatinine were less after weight loss (P = .032, P = .006, and P = .026, respectively). Homocysteine (P < .001), cystatin C (P < .001) and clusterin (P < .001) all decreased upon weight loss. Multiple linear regression analysis revealed associations between percentage weight loss (greater weight loss, more lean tissue loss; r = -0.67, r(2) = 0.45, P < .001) and before-loss plasma clusterin concentration (greater clusterin, more lean tissue loss; r = 0.48, r(2) = 0.23, P = .003). CONCLUSION AND CLINICAL IMPORTANCE These results suggest possible subclinical alterations in renal function in canine obesity, which improve with weight loss. Further work is required to determine the nature of these alterations and, most notably, the reason for the association between before loss plasma clusterin and subsequent lean tissue loss during weight management.

Use of starting condition score to estimate changes in body weight and composition during weight loss in obese dogs.

Prior to starting a weight loss programme, target weight (TW) is often estimated, using starting body condition score (BCS). The current study assessed how well such estimates perform in clinical practice. Information on body weight, BCS and body composition was assessed before and after weight loss in 28 obese, client-owned dogs. Median decrease in starting weight per BCS unit was 10% (5-15%), with no significant difference between dogs losing moderate (1-2 BCS points) or marked (3-4 BCS points) amounts of weight (P=0.627). Mean decrease in body fat per BCS unit change was 5% (3-9%). A model based on a change of 10% of starting weight per unit of BCS above ideal (5/9) most closely estimated actual TW, but marked variability was seen. Therefore, although such calculations may provide a guide to final TW in obese dogs, they can either over- or under-estimate the appropriate end point of weight loss.