Abbreviations ANC average neck circumference BCS body condition score BMI body mass index DE digestible energy EBW estimated body weight EMS equine metabolic syndrome IR insulin resistance NCHR neck circumference to height ratio NSC nonstructural carbohydrate USDA United States Department of Agriculture VMRCVM Virginia‐Maryland Regional College of Veterinary Medicine Obesity, the accumulation of excess fat tissue, is a major health concern in humans and companion animals because of its high prevalence and associations with IR, diabetes mellitus, cardiovascular diseases, and other disorders. There is an increasing sentiment that the prevalence of obesity in horses has also become high, and that obesity either directly or indirectly negatively affects the health and performance of affected animals. Obesity is a primary component of EMS, a condition of horses and ponies that is also characterized by insulin resistance or hyperinsulinemia, and predisposition to laminitis. Alterations in adipose tissue function in obesity likely contribute to the pathophysiology of insulin resistance and hyperinsulinemia, and through this mechanism, increase the risk for development of laminitis. The recent American College of Veterinary Internal Medicine (ACVIM) consensus statement on EMS indicates that there is a scarcity of epidemiological data on the components of EMS, including obesity. A 1998 USDA National Animal Health Monitoring System (NAHMS) study estimated that approximately 1.5% of the US horse population was overconditioned or obese. In a later study, NAHMS reported that 3.4% of equine operations had horses that were overweight or obese, and that 0.9% of the horses were affected. However, these estimates were based on surveys of horse owners rather than a prospective study in which standardized methods were used to assess body condition and fatness. It was our belief that these studies markedly underestimated the current prevalence of overconditioned or obese horses in the general population of horses. The objective of the study was to determine the prevalence of overconditioned and obese horses and to evaluate risk factors for overconditioning of horses. An improved knowledge of factors contributing to obesity might enable development of management strategies that mitigate obesity and risk of associated conditions such as EMS. Materials and Methods Study Population A random sample of 300 adult horses (4–20 years old) from a study population of over 1,000 horses was selected from the equine field service practice at the VMRCVM in this cross‐sectional, prospective study. The practice population was from within a 35‐mile radius of the college and included a diversity of breeds and equine activities. The horses in the sample were from 114 farms and represented 138 horse owners. The unit of investigation was the horse, and the effect of nesting (300 horses, 114 farms, 138 owners) was ignored. Sample size was selected such that the precision of the prevalence estimate of overconditioned/obesity in the study population would be determined with 95% confidence to within less than ±5% for an expected prevalence of 25%. Ponies, miniature horses, donkeys, draft breeds, and their crosses were excluded from the study, as were pregnant and lactating mares and horses undergoing treatment for health problems. The Institutional Animal Care and Use Committee at Virginia Tech reviewed and approved the animal protocols (IACUC #06‐090‐CVM). Clients provided consent for the participation of their horse(s) in the study. The study was completed in 60 days (June 15 to August 15, 2006). A questionnaire was used to collect information from the owner or manager on the horses and feeding programs. The information collected was verified by the authors whenever possible. Horse information included age, breed, sex, exercise type, and medical history. Exercise was categorized as none, light, moderate, and intense using the guidelines of the National Research Council. Feeding information included pasture and hay type and amount; concentrate/grain amount; and whether supplements were fed. Body Condition Score, BMI, and Average NCHR Determinations Two independent scorers using a previously described method determined body condition and assigned a score to each horse. Both scores were averaged and averaged scores were rounded up to the next integer score. Horses with a BCS of <4 were classified as undercondition, BCS of 4–6 as optimal condition, BCS of 7 as overcondition, and BCS of 8–9 as obese condition. Morphometric measurements were taken on each horse to calculate EBW and BMI. Girth circumference, height at the withers, and length from the point of the shoulder to the ipsilateral tuber ischi were measured (cm). EBW was determined from the formula: EBW (kg) = [girth (cm) 2 × length (cm)]/11,877. The BMI was calculated as estimated weight (kg)/height (m) 2 . The horses neck circumference (cm) was measured in 3 locations: halfway between the poll and the point of the withers (center); halfway between the poll and the center of the neck; and, halfway between the center of the neck and the withers. These 3 measurements were averaged to determine ANC. Average NCHR [average neck circumference (cm)/wither height (m)] was used as an additional measurement of adiposity. The hoof walls of each horse were evaluated for evidence of a laminitic growth pattern. Data Analysis All statistical analyses were performed in SAS. Continuous variables were evaluated for normality using the UNIVARIATE procedure; linear, nonlinear relationships, or both among BCS and height, girth, ANC, length as well as EBW, BMI, and NCHR were determined using the CORRELATION AND REGRESSION procedures. Associations of categorical variables (breed, sex, age group, level of exercise, access to free choice feed, access to hay, access to pasture, feeding of concentrates, feeding of supplements, access to trace mineral salt) with BCS were determined first in univariable analyses. Variables that satisfied ( P < .10) in the univariable analyses were put into logistic regression analysis, using the LOGISTIC procedure. A P value <.05 was considered significant. Results Horse Sample Mixed breed was the most frequent breed designation (n = 71), followed by Quarter Horse (54), Warmblood (45), and Thoroughbred (42). There were 20 Tennessee Walking Horses, 16 Arabians, 12 Rocky Mountain Horses, and 11 Paint horses. There were 8 Appaloosas, 7 American Saddlebreds, 4 Racking Horses, and 3 Fjord horses. Other breed designations were Andalusian, Irish Sport Horse, Morgan Horse, Mustang, Palomino, Paso Fino, and Spanish Mustang (1 each). There were 140 mares (46.7%), 151 geldings (50.3%), and 9 stallions (3.0%). Mean (±SD) age of horses in the sample was 11.0 ± 4.7, with a median age of 10 years. Horses were classified into 4 age categories, with 106 horses (35.3%) in the 4–8 years, 76 horses (25.3%) in the 9–12 years, 68 horses (22.7%) in the 13–16 years, and 50 horses (16.7%) in the 17–20 years of age category. Exercise and Feeding Exercise regimen, concentrate feeding, and the type of hay for the 300 horses are presented in Table . One hundred sixty‐three horses (54.3%) had unlimited, continuous access to pasture (of which 77 horses had pasture only, 7 horses received supplemental hay, and 79 horses received supplemental concentrate/grain), whereas the other 137 horses had either restricted or no access to pasture. Among the horses that were fed more than 4 kg concentrate/grain per day (Table ), 3 horses were categorized as no exercise, 5 as light exercise, 1 as moderate exercise, and 2 as intense exercise. Two hundred seventy‐one horses (90.3%) were fed trace‐mineralized salt, and 29 horses were not fed trace‐mineralized salt or white salt. One hundred five horses (35.0%) were fed other mineral supplements, whereas the other 195 horses were not fed such supplements. Exercise regime, concentrate feeding, and type of hay for 300 horses Variable Categories Number (%) of Horses Exercise None Light Moderate Intense 175 (58.3) 90 (23.3) 46 (15.3) 9 (3) Concentrate/grain feeding (kg/day) None 0.1–1.4 1.5–2.5 2.6–4.0 >4 91 (30.3) 142 (47.3) 37 (12.3) 19 (6.3) 11 (3.7) Hay feeding None Grass hay Legume hay Mixed, primarily grass Mixed, primarily legume 159 (53) 21 (7) 1 (0.3) 108 (36) 11 (3.7) Body Condition Scores Agreement between the two body condition scorers was substantial (kappa = 0.65, 95% CI: [0.58; 0.72]; P < .001). Body condition scores are presented in Figure . Disagreements between scorers did not exceed 1 BCS unit, and all averaged half scores (n = 82; 36 of which were BCS = 6.5) were rounded up for further analyses and presentation. The BCS of 45 horses was 8 and of 11 horses was 9, for a prevalence of obesity, ie, proportion of horses with BCS ≥ 8, of 18.7% (95% CI: [14.4%; 23.5%]). In addition, 97 horses had a BCS of 7, for a prevalence of overconditioned/obese, (BCS ≥ 7) of 51.0% (95% CI: [45.2%; 56.8%]). One hundred forty‐two horses (47.3%) were in optimum body condition, and 5 horses (1.7%) were underconditioned. Body condition scores of 300 horses by conditioning status: underconditioned , optimal condition , overconditioned and obese . The BCS of 45 horses was 8, and of 11 horses was 9, for a prevalence of obesity, ie, proportion of horses with BCS ≥ 8, of 18.7% (95% CI: [14.4; 23.5]); an additional 97 horses had a BCS of 7, for a prevalence of overconditioned/obese, ie, proportion of horses with BCS ≥ 7 of 51.0% (95% CI: [45.2; 56.8]). One hundred forty‐two horses (47.3%) were in optimum body condition, and 5 horses (1.7%) were underconditioned. Associations of Body Condition Scores with Other Body Measurements Height ( P < .001), girth ( P < .001), and ANC ( P = .004), but not length ( P = .206) influenced BCS such that BCS = 5.266 − 0.136 height + 0.90 girth + 0.045 ANC ( R 2 = 0.396). Estimated body weight ( r Spearman = 0.14, P = .015), BMI ( r Spearman = 0.46, P < .001), and NCHR ( r Spearman = 0.50, P < .001) all increased with increasing BCS (Table ). Body weight ( BW ), body mass index ( BMI ), and neck circumference to height ratio ( NCHR ) (mean ± SD) for 300 horses within body condition score categories: underconditioned ( BCS < 4), optimal condition ( BCS 4–6), overconditioned ( BCS 7), and obese ( BCS 8 and 9) Body Condition Score Category BW (kg) Height (cm) BMI NCHR Underconditioned (n = 5) 492 ± 98.0 155.8 ± 11.73 201.2 ± 24.6 0.59 ± 0.017 Optimal condition (n = 142) 539 ± 77.9 157.7 ± 8.15 215.8 ± 17.4 0.61 ± 0.031 Overconditioned (n = 97) 552 ± 77.7 155.3 ± 7.52 227.8 ± 17.0 0.63 ± 0.026 Obese (n = 56) 567 ± 90.4 153.6 ± 7.77 239.2 ± 23.7 0.65 ± 0.031 In univariable analyses, sex, age group, access to hay, and feeding of concentrate affected the odds of being overconditioned/obese ( P < .05) (Table ). Exercise level tended to affect the odds of being overconditioned ( P = .081). Because of the lack of data for certain breeds, data were analyzed separately for 271 horses that belonged to 8 breed designations that had 11 or more representatives in the sample. Breed affected the odds of being overconditioned/obese ( P = .022), with Rocky Mountain Horse, Tennessee Walking Horse, Quarter Horse, Warm Blood, and Mixed Breed horses, but not Arabian and Paint horses, having higher odds to be overconditioned/obese than Thoroughbreds ( P < .05). Univariable analyses of effect of sex, age group, exercise, and access to pasture, hay, and concentrate on BCS Variable Category Number (%) of Horses OR [95% CI] P Value* Body Condition Score 2–6 7–9 Sex Female 140 60 (42.9) 80 (57.1) 1.59 [1.01;2.51] .047 Male 160 87 (54.4) 73 (45.6) 1.0 (reference) Age group 17 – 20 yr 50 21 (42.0) 29 (58.0) 2.19 [1.10; 4.34] .019 13 – 16 yr 68 30 (44.1) 38 (55.9) 2.01 [1.08; 3.73] 9 – 12 yr 76 31 (40.8) 45 (59.2) 2.30 [1.26; 4.20] 4 – 8yr 106 65 (61.3) 41 (38.7) 1.0 (reference) Exercise Intense 9 8 (88.9) 1 (11.1) 0.10 [0.01;0.86] .081 Moderate 46 27 (58.7) 19 (41.3) 0.59 [0.31; 1.14] Light 70 32 (45.7) 38 (54.3) 1.00 [0.57; 1.74] None 175 80 (45.7) 95 (54.3) 1.0 (reference) Free access to pasture Yes 163 69 (42.3) 94 (57.7) 1.80 [1.14; 2.85] .012 No 137 78 (56.9) 59 (43.1) 1.0 (reference) Access to hay Yes 141 83 (58.9) 58 (41.1) 0.47 [0.30; 0.75] .001 No 159 64 (40.25) 95 (59.75) 1.0 (reference) Concentrate >4.0 kg/d 11 10 (90.9) 1 (9.1) 0.09 [0.01; 0.73] <.001 2.6–4.0 kg/d 19 16 (84.2) 3 (15.8) 0.17 [0.05; 0.62] 1.5–2.5 kg/d 37 26 (70.3) 11 (29.7) 0.38 [0.17; 0.86] 0.1–1.4 kg/d 142 52 (36.6) 90 (63.4) 1.55 [0.91; 2.65] 0 kg/d 91 43 (47.25) 48 (52.75) 1.0 (reference) When introducing all variables, except breed, that satisfied P < .10 in a multivariable logistic regression model using a stepwise variable selection process, the odds of being overconditioned were influenced only by feeding of hay (OR = 0.499; 95% CI: [0.286; 0.869]; P = .014) and concentrate ( P < .001; with OR 0–1.4 kg/d vs. none = 2.199; 95% CI:[1.199; 4.033]). Age tended to influence odds of being overconditioned ( P = .078), with odds for 9–12‐year‐old horses being 2.230 (95% CI: [1.163; 4.273]) times the odds of 4–8‐year‐old horses to be overconditioned/obese. None of the horses in the study had laminitic hoof growth pattern. Discussion The result of the present study that 51% of the horses were overconditioned or obese differed markedly from previous studies conducted by the USDA, NAHMS, which reported in 2 separate studies that 1.5% and 0.9% of the US horse population were overweight/obese. The USDA NAHMS studies estimated overweight and obesity based on surveys of horse owners self‐reporting on the condition of their horses rather than using standardized assessment methods, such as an equine body condition scoring system, BMI, or NCHR. The large difference in the prevalence of overweight/obesity between our study and the USDA NAHMS studies is most likely because of owners underestimating the condition of their horses in the USDA NAHMS studies. In a study of 319 riding horses in Scotland performed in 2005, which used a different BCS scale, it was found that 45% of the horses were assigned a body condition score of fat or very fat. Results of this study are more similar to what was found in the current study. The authors also investigated the association between horses' body condition score and the owner's perception of the fat cover and found “only fair agreement” (kappa statistic 0.4) between the owner's perception of obesity and the actual body condition score. Misclassification by owners was most commonly due to them underestimating the horse's body condition. This finding, along with the disparity between the results of the USDA NAHMS studies and our study, indicates poor ability among horse owners to assess body condition accurately and the tendency for owners to underestimate the condition of their horses. A more recent study of 366 privately owned horses in North Carolina performed in 2010 also found a high prevalence of overweight/obesity, with 48% of horses being classified as overweight (BCS ≥ 6) and 20% of the horses classified as obese (BCS > 7). This study used the same standardized BCS system as the current study, and supports our conclusion that the prevalence of overcondition/obesity in US horses may be higher than previously recognized. Ponies, miniature horses, donkeys, draft breeds, and their crosses were excluded from the present study, as were pregnant and lactating mares, horses undergoing treatment for health problems, and horses less than 4 years of age and greater than 20 years of age. The purpose of excluding these groups was to reduce variability caused by the type of equine, pregnancy, lactation, health problems, and age (ie, growing horses and geriatric horses). A weakness of the present study is that the horses were from a small geographical region. However, we do believe that the horse population and management practices that were evaluated in the study are similar to that found in many other areas of the Mid‐Atlantic region. A recent Virginia National Agriculture Statistical Service study found that 65% of Virginia horses were used for trail riding/pleasure and breeding versus 35% for competition and work. These results are similar to an American Horse Council Study that showed that 42% are used recreationally rather than for competitive, work, or breeding purposes. Although not numerically defined, the study population in the present study is known to consist predominately of horses used for recreational purposes or kept essentially as simple pets. This population bias is likely responsible for the finding that greater than 50% of the horses were categorized as receiving no exercise (less than 1 hour of work per week). Another weakness of the present study is that the horses were only evaluated during 1 season. Given that the sampling period was in the summer, after many of the horses had access to high‐quality spring pasture, it is likely that prevalence of overweight/obesity was maximally represented. Additional research from other geographical locations and seasons is needed to determine if the findings from the present study are generalizable throughout the United States. Anecdotally, overcondition/obesity has been suggested to be more common in certain breeds such as Morgan Horses, Paso Finos, Arabians, American Saddlebreds, Spanish Mustangs, Warmbloods, Quarter Horses, and Tennessee Walking Horses, and less common in Thoroughbreds and Standardbreds. Breeds that had greater odds of being overcondition/obese in the present study included the Rocky Mountain Horse, Tennessee Walking Horse, Quarter Horse, Warm Blood, and Mixed Breed horse as compared to Thoroughbreds. Morgan Horses, Paso Finos, and Warmbloods were not included in our analysis because of lack of sufficient numbers of horses in each of these breed designations. Genetic predisposition to overweight/obesity in individual horses or certain breeds caused by enhanced metabolic efficiency has been suggested. Although there is minimal published data to support the concept of “easy keepers”, a recent study did demonstrate that Icelandic horses gained weight whereas Standardbred horses lost weight when they consumed the same diets and the same amount of digestible energy. It is noteworthy that in our final analysis, risk factors for developing overcondition/obesity included feeding 0–1.4 kg of grain or concentrate/day and being in the 9–12 year age group, whereas the feeding of hay was determined to be protective. Most of the horses in the study were fed primarily pasture and received little or no exercise. Horses receiving 0–1.4 kg of grain or concentrate/day might receive it as a “treat”, and that this practice of energy supplementation in combination with an already calorie rich pasture based diet and little or no exercise increased the risk for development condition/obesity, whereas horses that received more grain were not at greater odds of being overconditioned/obese. Feeding of hay to horses at the time of year our study was performed was an indication that horses did not have sufficient pasture access to meet their nutritional needs because of no pasture, insufficient pasture, or restricted access to pasture. Feeding of hay likely allowed owners/caretakers more control of energy intake than unrestricted pasture grazing, and thus was protective of development of overcondition/obesity. It has been suggested that horses develop overcondition and obesity after maturity. In the current study, the age group at highest risk for overcondition and obesity was horses in the 9–12 year age group. Thus, being overweight appears to be more problematic in middle‐aged horses, which is similar to what is found in other species such as the dog and cat; 42% of dogs and 44% of cats between 5 and 11 years are overweight in the United States. In conclusion, there has been limited information available on the prevalence of overcondition/obesity in horses in the United States. The results of this study and another recent study indicate that overcondition and obesity affects a much higher proportion of horses than previously reported. Because of the potential negative impacts of obesity on the health and performance of horses, veterinarians should implement measures to identify, treat, and prevent overcondition/obesity. Acknowledgments This study was completed using horses from the Equine Ambulatory Practice of the VMRCVM, Blacksburg, Virginia. Supported in part by the Virginia Horse Industry Board, Virginia Tech [Virginia‐Maryland Regional College of Veterinary Medicine and the College of Agriculture and Life Sciences], and the Macromolecular Interfaces with Life Sciences (MILES) Integrative Graduate Education and Research Traineeship (IGERT) of the National Science Foundation under Agreement No. DGE‐0333378. Presented and published in abstract form in the Proceedings of AAVN Symposium, June 5, 2007, Seattle, WA, page 6; and in the April (issue 2) 2008 Journal of Animal Physiology and Animal Nutrition (JAPAN) . The authors acknowledge and thank Kimberly A. Negrin, Julie Franklin, and Louisa Gay for data collection, Louisa Gay for technical laboratory expertise, and Stephen R. Were for statistical consultation and analyses. Conflict of Interest : Dr Ray Geor is an Associate Editor at the Journal of Veterinary Internal Medicine . Footnote SAS 9.1.3, SAS Institute, Carey, NC
Journal of Veterinary Internal Medicine – Wiley
Published: Nov 1, 2012
Keywords: ; ; ;
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera