Dataset Information

Morphometric Measurements and Muscle Atrophy Scoring as a Tool to Predict Body Weight and Condition of Horses.

ABSTRACT: Accurate estimation of body weight (BW) and condition (BCS) is important in the equine practice. The main goal of this research was to develop models for the prediction of BW and BCS of horses in the practice using both common morphometric measurements and measurements of Cresty Neck Score (CNS) and Muscle Atrophy Scoring System (MASS) as a measure of muscularity. Our model showed that the BW of horses could be predicted with high reproducibility (concordance correlation coefficient = 0.97), accuracy (0.99), and precision (0.97) using the morphometric measurements of the height at withers, circumference of the chest, cane circumference, body length, and body circumference as well as the BCS, CNS, and muscle atrophy score of the hindlimbs. The stepwise multiple regression analysis revealed that the BCS of horses can be predicted with the data of parameters such as age, body length and an index consisting of measurements of the body circumference to height of withers, and the atrophy of the neck. Future research should use larger cohorts of animals to validate the findings of this study.

SUBMITTER: Urbanek N

PROVIDER: S-EPMC10458044 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature

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Morphometric Measurements and Muscle Atrophy Scoring as a Tool to Predict Body Weight and Condition of Horses.

Urbanek Nadine N Zebeli Qendrim Q

Veterinary sciences 20230809 8

Accurate estimation of body weight (BW) and condition (BCS) is important in the equine practice. The main goal of this research was to develop models for the prediction of BW and BCS of horses in the practice using both common morphometric measurements and measurements of Cresty Neck Score (CNS) and Muscle Atrophy Scoring System (MASS) as a measure of muscularity. Our model showed that the BW of horses could be predicted with high reproducibility (concordance correlation coefficient = 0.97), acc ...[more]

PMID: 37624301

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Project description:BackgroundEquine obesity is a significant health and welfare concern. The proportion of domestic horse populations that are overweight are as high as 45%. As the primary decision-makers for their horses' care, owners are theoretically ideally placed to identify whether their horses are appropriately conditioned, however, research in other countries has shown that many owners are unable to accurately judge their horse's body condition. In this study, through the comparison of body condition scoring (BCS) performed by an expert and the horse owners and interviews with owners, we aimed to identify the proportion of horses that were overweight or obese, to assess the accuracy of horse owners' BCS assessment both prior to and after receiving information and instructions on body condition scoring, and to identify common themes amongst owners' views regarding BCS assessment and the Henneke BCS system.ResultsForty-five percent of the horses in this study were overweight or obese. The agreement between the owners and an equine veterinarian regarding the horses' BCS was fair to good both prior to (κ = .311, P < 0.001; ICC = .502, P < 0.001) and after (κ = .381, P < 0.001; ICC = .561, P < 0.001) receiving information and instructions on scoring. Three quarters of the owners who took part in the study did not use any method of monitoring their horse's body condition. Thematic analysis of owner responses was varied, with the most common theme being an awareness of the need to monitor or make changes to their horse's condition with responses in this theme split between owners who felt in control and those who did not. Owner feedback on the utility and useability of the scorning system was that it was useful however parts are too technical or need improvement.ConclusionsEquine obesity is a significant problem in this population in Ireland. Horse owners' ability to accurately judge their horse's condition does not improve with provision of instructions on body condition scoring. These results combined with owners' feedback on the Henneke BCS system indicate that it is not a tool that can be reliably used by owners.

Project description:The relationship between ewe body condition score (BCS) and liveweight (LW) has been exploited previously to predict the former from LW, LW-change, and previous BCS records. It was hypothesized that if fleece weight and conceptus-free liveweight and LW-change, and in addition, height at withers were used, the accuracy of current approaches to predicting BCS would be enhanced. Ewes born in 2017 (n = 429) were followed from 8 mo to approximately 42 mo of age in New Zealand. Individual ewe data were collected on LW and BCS at different stages of the annual production cycle (i.e., prebreeding, at pregnancy diagnosis, prelambing, and weaning). Additionally, individual lambing dates, ewe fleece weight, and height at withers data were collected. Linear regression models were fitted to predict current BCS at each ewe age and stage of the annual production cycle using two LW-based models, namely, unadjusted for conceptus weight and fleece weight (LW alone1) and adjusted (LW alone2) models. Furthermore, another two models based on a combination of LW, LW-change, previous BCS, and height at withers (combined models), namely, unadjusted (combined1) and adjusted for conceptus and fleece weight (combined2), were fitted. Combined models gave more accurate (with lower root mean square error: RMSE) BCS predictions than models based on LW records alone. However, applying adjusted models did not improve BCS prediction accuracy (or reduce RMSE) or improve model goodness of fit (R 2) (P > 0.05). Furthermore, in all models, both LW-alone and combined models, a great proportion of variability in BCS, could not be accounted for (0.25 ≥ R 2 ≥ 0.83) and there was substantial prediction error (0.33 BCS ≥ RMSE ≥ 0.49 BCS) across age groups and stages of the annual production cycle and over time (years). Therefore, using additional ewe data which allowed for the correction of LW for fleece and conceptus weight and using height at withers as an additional predictor did not improve model accuracy. In fact, the findings suggest that adjusting LW data for conceptus and fleece weight offer no additional value to the BCS prediction models based on LW. Therefore, additional research to identify alternative methodologies to account for individual animal variability is still needed.

Dataset Information

Morphometric Measurements and Muscle Atrophy Scoring as a Tool to Predict Body Weight and Condition of Horses.

Publications

Morphometric Measurements and Muscle Atrophy Scoring as a Tool to Predict Body Weight and Condition of Horses.

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