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Home / Equine Research Bank / Animals (Basel) / Recumbency as an Equine Welfare Indicator in Geriatric Horse...
Animals : an open access journal from MDPI2021; 11(11); 3189; doi: 10.3390/ani11113189

Recumbency as an Equine Welfare Indicator in Geriatric Horses and Horses with Chronic Orthopaedic Disease.

Abstract: Recumbency is a prerequisite for horses achieving rapid eye movement (REM) sleep and completing a full sleep cycle. An inability to lie down due to environmental insecurities or pain results in REM sleep deficiency, which can cause substantial impairment of welfare and health. Therefore, the present study used wearable automated sensor technology on 83 horses housed in an animal sanctuary to measure and compare the recumbency, locomotion, and standing time budgets of geriatric horses with and without chronic lameness to younger adult sound and lame horses. Recumbency times ranged from 0 to 319 min per day with an overall mean of 67.4 (±61.9) minutes; the time budget for locomotion was 19.1% (±11.2% s.d.) and for standing 75.6% (±13.1 s.d.). Interestingly, neither age nor lameness due to chronic orthopedic disease had a significant influence on recumbency times in this study. Eight horses showed symptoms of REM deficit. These horses had significantly shorter lying times (7.99 ± 11.4 min) and smaller locomotion time budgets than the other horses enrolled in this study (73.8 ± 61.8 min), indicating a general compromise of well-being. Thus, wearable sensor technology can be used to identify horses with low recumbency times at risk for REM sleep deficiency and to assess and monitor equine welfare objectively.
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Publication Date: 2021-11-08 PubMed ID: 34827921PubMed Central: PMC8614510DOI: 10.3390/ani11113189Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The research paper explores the use of wearable automated sensor technology to measure and compare the recumbency, locomotion, and standing time budgets of geriatric horses and adult horses with and without chronic lameness, and its relation to equine welfare.

Recumbency and Equine Welfare

  • The study begins by stating the importance of recumbency, which is the ability to lie down, for horses. It’s foundational for horses to complete their rapid eye movement (REM) sleep cycle.
  • A lack of REM sleep, caused by an inability to achieve recumbency due to pain or environmental insecurity, can substantially impair a horse’s health and welfare.

Experimental Set-up

  • The paper uses automated wearable sensor technology to monitor recumbency and locomotion in horses.
  • The researchers examined 83 horses housed in an animal sanctuary. The cohort comprised of geriatric horses as well as younger adults, both sound and those affected by chronic lameness.

Study Findings

  • The investigators found a range of recumbency times, between 0 to 319 minutes per day. The mean recumbency time was about 67.4 minutes.
  • The time spent on locomotion was around 19.1% and for standing was approximately 75.6%.
  • Surprisingly, age or chronic lameness did not significantly affect the recumbency times of the horses under study.

Special Case Findings

  • The researchers noted eight horses that showed symptoms of REM deficit. These horses registered significantly shorter lying times (about 8 minutes) and smaller locomotion time budgets compared to the others (approximately 74 minutes).
  • This significant decrease in recumbency time and locomotion budget indicates an overall compromise in the well-being of these horses.

Conclusions and Implications

  • The study concludes that wearable sensor technology can be used to identify horses with low recumbency times, who are at risk for REM sleep deficiency.
  • This detection aid can then be used to objectively assess and improve equine welfare, as it provides a practical indicator of health and well-being in horses.

Cite This Article

APA
Kelemen Z, Grimm H, Long M, Auer U, Jenner F. (2021). Recumbency as an Equine Welfare Indicator in Geriatric Horses and Horses with Chronic Orthopaedic Disease. Animals (Basel), 11(11), 3189. https://doi.org/10.3390/ani11113189

Publication

Animals : an open access journal from MDPI
ISSN: 2076-2615
NlmUniqueID: 101635614
Country: Switzerland
Language: English
Volume: 11
Issue: 11
PII: 3189

Researcher Affiliations

Kelemen, Zsofia
  • Equine Surgery Unit, University Equine Hospital, Department of Companion Animals and Horses, University of Veterinary Medicine Vienna, Veterinaerplatz 1, 1210 Vienna, Austria.
Grimm, Herwig
  • Unit of Ethics and Human-Animal-Studies, Messerli Research Institute, University of Veterinary Medicine Vienna, Medical University of Vienna, University of Vienna, Veterinaerplatz 1, 1210 Vienna, Austria.
Long, Mariessa
  • Unit of Ethics and Human-Animal-Studies, Messerli Research Institute, University of Veterinary Medicine Vienna, Medical University of Vienna, University of Vienna, Veterinaerplatz 1, 1210 Vienna, Austria.
Auer, Ulrike
  • Anaesthesiology and Perioperative Intensive Care Medicine Unit, Department of Companion Animals and Horses, University of Veterinary Medicine Vienna, Veterinaerplatz 1, 1210 Vienna, Austria.
Jenner, Florien
  • Equine Surgery Unit, University Equine Hospital, Department of Companion Animals and Horses, University of Veterinary Medicine Vienna, Veterinaerplatz 1, 1210 Vienna, Austria.

Conflict of Interest Statement

The authors declare no conflict of interest.

References

This article includes 94 references
  1. Littlejohn A, Munro R. Equine recumbency.. Vet Rec 1972 Jan 22;90(4):83-5.
    doi: 10.1136/vr.90.4.83pubmed: 5033197google scholar: lookup
  2. Houpt K. The Characteristics of Equine Sleep. Equine Pract 1980;2:8–17.
  3. Dallaire A. Rest behavior.. Vet Clin North Am Equine Pract 1986 Dec;2(3):591-607.
    doi: 10.1016/S0749-0739(17)30708-3pubmed: 3492247google scholar: lookup
  4. Aleman M, Willams C, Holliday T. Sleep and Sleep Disorders in Horses. AAEP Proc 2008;54:180–185.
  5. Belling T. Sleep Patterns in the Horse. Equine Pract 1990;12:22–27.
  6. Dallaire A, Rucklebusch Y. Sleep and wakefulness in the housed pony under different dietary conditions.. Can J Comp Med 1974 Jan;38(1):65-71.
    pmc: PMC1319968pubmed: 4272959
  7. Wöhr A, Kalus M, Reese S, Fuchs C, Erhard M. Equine Sleep Behaviour and Physiology Based on Polysomnographic Examinations. Equine Vet. J. 2016;48:9.
    doi: 10.1111/evj.08_12612pubmed: 0google scholar: lookup
  8. Williams DC, Aleman M, Holliday TA, Fletcher DJ, Tharp B, Kass PH, Steffey EP, LeCouteur RA. Qualitative and quantitative characteristics of the electroencephalogram in normal horses during spontaneous drowsiness and sleep.. J Vet Intern Med 2008 May-Jun;22(3):630-8.
    doi: 10.1111/j.1939-1676.2008.0096.xpubmed: 18466241google scholar: lookup
  9. Fuchs C, Kiefner C, Reese S, Erhard M, Wöhr A. Narcolepsy: Do Adult Horses Really Suffer from a Neurological Disorder or Rather from a Recumbent Sleep Deprivation/Rapid Eye Movement (REM)-Sleep Deficiency?. Equine Vet. J. 2016;48:9.
    doi: 10.1111/evj.09_12612pubmed: 0google scholar: lookup
  10. Zanker A, Wöhr AC, Reese S, Erhard M. Qualitative and quantitative analyses of polysomnographic measurements in foals.. Sci Rep 2021 Aug 11;11(1):16288.
    doi: 10.1038/s41598-021-95770-5pmc: PMC8357810pubmed: 34381127google scholar: lookup
  11. Burla JB, Rufener C, Bachmann I, Gygax L, Patt A, Hillmann E. Space Allowance of the Littered Area Affects Lying Behavior in Group-Housed Horses.. Front Vet Sci 2017;4:23.
    doi: 10.3389/fvets.2017.00023pmc: PMC5339441pubmed: 28326309google scholar: lookup
  12. Auer U, Kelemen Z, Engl V, Jenner F. Activity Time Budgets-A Potential Tool to Monitor Equine Welfare?. Animals (Basel) 2021 Mar 17;11(3).
    doi: 10.3390/ani11030850pmc: PMC8002676pubmed: 33802908google scholar: lookup
  13. Kelemen Z, Grimm H, Vogl C, Long M, Cavalleri JMV, Auer U, Jenner F. Equine Activity Time Budgets: The Effect of Housing and Management Conditions on Geriatric Horses and Horses with Chronic Orthopaedic Disease.. Animals (Basel) 2021 Jun 23;11(7).
    doi: 10.3390/ani11071867pmc: PMC8300227pubmed: 34201584google scholar: lookup
  14. Greening L, Downing J, Amiouny D, Lekang L, McBride S. The Effect of Altering Routine Husbandry Factors on Sleep Duration and Memory Consolidation in the Horse. Appl. Anim. Behav. Sci. 2021;236:105229.
    doi: 10.1016/j.applanim.2021.105229google scholar: lookup
  15. Fuchs C. Narkolepsie Oder REM-Schlafmangel?. Ph.D. Thesis. LMU; München, Germany: 2017.
  16. Kalus M. Schlafverhalten Und Physiologie Des Schlafes Beim Pferd Auf Der Basis Polysomnographischer Untersuchungen. Ph.D. Thesis. LMU; München, Germany: 2014.
  17. Bertone JJ. Excessive drowsiness secondary to recumbent sleep deprivation in two horses.. Vet Clin North Am Equine Pract 2006 Apr;22(1):157-62.
    doi: 10.1016/j.cveq.2005.12.020pubmed: 16627113google scholar: lookup
  18. Clothier J, Small A, Hinch G, Barwick J, Brown WY. Using Movement Sensors to Assess Lying Time in Horses With and Without Angular Limb Deformities.. J Equine Vet Sci 2019 Apr;75:55-59.
    doi: 10.1016/j.jevs.2019.01.011pubmed: 31002093google scholar: lookup
  19. Köster J, Hoffmann G, Bockisch F-J, Kreimeier P, Köster J.R, Feige K. Lying Behaviour of Horses Depending on the Bedding Material in Individual Housing in Boxes with or without Adjacent Pen. Pferdeheilkunde Equine Med. 2017;33:43–51.
    doi: 10.21836/PEM20170106google scholar: lookup
  20. Baumgartner M, Zeitler-Feicht M.H, Wöhr A-C, Wöhling H, Erhard M.H. Lying Behaviour of Group-Housed Horses in Different Designed Areas with Rubber Mats, Shavings and Sand Bedding. Pferdeheilkunde Equine Med. 2015;31:211–220.
    doi: 10.21836/PEM20150302google scholar: lookup
  21. Chaplin SJ, Gretgrix L. Effect of housing conditions on activity and lying behaviour of horses.. Animal 2010 May;4(5):792-5.
    doi: 10.1017/S1751731109991704pubmed: 22444135google scholar: lookup
  22. Werhahn H, Hessel E.F, Bachhausen I, Van den Weghe H.F.A. Effects of Different Bedding Materials on the Behavior of Horses Housed in Single Stalls. J. Equine Vet. Sci. 2010;30:425–431.
    doi: 10.1016/j.jevs.2010.07.005google scholar: lookup
  23. Raabymagle P, Ladewig J. Lying Behavior in Horses in Relation to Box Size. J. Equine Vet. Sci. 2006;26:11–17.
    doi: 10.1016/j.jevs.2005.11.015google scholar: lookup
  24. Price J, Catriona S, Welsh EM, Waran NK. Preliminary evaluation of a behaviour-based system for assessment of post-operative pain in horses following arthroscopic surgery.. Vet Anaesth Analg 2003 Jul;30(3):124-37.
    doi: 10.1046/j.1467-2995.2003.00139.xpubmed: 14498844google scholar: lookup
  25. Aristizabal F, Nieto J, Yamout S, Snyder J. The effect of a hay grid feeder on feed consumption and measurement of the gastric pH using an intragastric electrode device in horses: a preliminary report.. Equine Vet J 2014 Jul;46(4):484-7.
    doi: 10.1111/evj.12175pubmed: 23991941google scholar: lookup
  26. Correa M.G, e Silva C.F.R, Dias L.A, Junior S.D.S.R, Thomes F.R, do Lago L.A, de Mattos Carvalho A, Faleiros R.R. Welfare Benefits after the Implementation of Slow-Feeder Hay Bags for Stabled Horses. J. Vet. Behav. 2020;38:61–66.
    doi: 10.1016/j.jveb.2020.05.010google scholar: lookup
  27. Duncan P. Time-Budgets of Camargue Horses II. Time-Budgets of Adult Horses and Weaned Sub-Adults. Behaviour 1980;72:26–48.
    doi: 10.1163/156853980X00023google scholar: lookup
  28. Duncan P. Time-Budgets of Camargue Horses III. Environmental Influences. Behaviour 1985;92:188–208.
    doi: 10.1163/156853985X00442google scholar: lookup
  29. Boyd L.E. Time Budgets of Adult Przewalski Horses: Effects of Sex, Reproductive Status and Enclosure. Appl. Anim. Behav. Sci. 1988;21:19–39.
    doi: 10.1016/0168-1591(88)90099-8google scholar: lookup
  30. Kiley-Worthington M. The Behavior of Horses in Relation to Management and Training—Towards Ethologically Sound Environments. J. Equine Vet. Sci. 1990;10:62–75.
    doi: 10.1016/S0737-0806(06)80088-2google scholar: lookup
  31. Carson K, Wood-Gush D.G.M. Equine Behaviour: II. A Review of the Literature on Feeding, Eliminative and Resting Behaviour. Appl. Anim. Ethol. 1983;10:179–190.
    doi: 10.1016/0304-3762(83)90139-6google scholar: lookup
  32. Dallaire A, Ruckebusch Y. Sleep patterns in the pony with observations on partial perceptual deprivation.. Physiol Behav 1974 May;12(5):789-96.
    doi: 10.1016/0031-9384(74)90015-8pubmed: 4365612google scholar: lookup
  33. Ruckebusch Y. The relevance of drowsiness in the circadian cycle of farm animals.. Anim Behav 1972 Nov;20(4):637-43.
    doi: 10.1016/S0003-3472(72)80136-2pubmed: 4661312google scholar: lookup
  34. Boyd L.E, Carbonaro D.A, Houpt K.A. The 24-Hour Time Budget of Przewalski Horses. Appl. Anim. Behav. Sci. 1988;21:5–17.
    doi: 10.1016/0168-1591(88)90098-6google scholar: lookup
  35. Maisonpierre IN, Sutton MA, Harris P, Menzies-Gow N, Weller R, Pfau T. Accelerometer activity tracking in horses and the effect of pasture management on time budget.. Equine Vet J 2019 Nov;51(6):840-845.
    doi: 10.1111/evj.13130pubmed: 31009100google scholar: lookup
  36. Raspa F, Tarantola M, Bergero D, Bellino C, Mastrazzo CM, Visconti A, Valvassori E, Vervuert I, Valle E. Stocking Density Affects Welfare Indicators in Horses Reared for Meat Production.. Animals (Basel) 2020 Jun 26;10(6).
    doi: 10.3390/ani10061103pmc: PMC7341190pubmed: 32604808google scholar: lookup
  37. Ogilvie-Graham T. Time Budget Studies in Stalled Horses. Ph.D. Thesis. The University of Edinburgh; Edinburgh, UK: 1994.
  38. Hartman N, Greening LM. A Preliminary Study Investigating the Influence of Auditory Stimulation on the Occurrence of Nocturnal Equine Sleep-Related Behavior in Stabled Horses.. J Equine Vet Sci 2019 Nov;82:102782.
    doi: 10.1016/j.jevs.2019.07.003pubmed: 31732116google scholar: lookup
  39. Amiouny D. The Effects of Night Light and Bedding Depth on Equine Sleep Duration and Memory Consolidation. Master's Thesis. Aberystwyth University; Penglais, UK: 2020.
  40. Güntner K. Polysomnographische Untersuchung Zum Schlafverhalten des Pferdes. Ph.D. Thesis. LMU; München, Germany: 2010.
  41. Greening L, Shenton V, Wilcockson K, Swanson J. Investigating Duration of Nocturnal Ingestive and Sleep Behaviors of Horses Bedded on Straw versus Shavings. J. Vet. Behav. Clin. Appl. Res. 2013;8:82–86.
    doi: 10.1016/j.jveb.2012.05.003google scholar: lookup
  42. Ninomiya S, Aoyama M, Ujiie Y, Kusunose R, Kuwano A. Effects of bedding material on the lying behavior in stabled horses.. J Equine Sci 2008;19(3):53-6.
    doi: 10.1294/jes.19.53pmc: PMC4013947pubmed: 24833955google scholar: lookup
  43. Aoyama M, Yoshimura N, Sugita S, Kusunose R. Effects of Used Bedding Straw and Drying It in Sunshine on Lying Behavior in Stable Horses. J. Equine Sci. 2004;15:67–73.
    doi: 10.1294/jes.15.67google scholar: lookup
  44. Kwiatkowska-Stenzel A, Sowińska J, Witkowska D. The Effect of Different Bedding Materials Used in Stable on Horses Behavior. J. Equine Vet. Sci. 2016;42:57–66.
    doi: 10.1016/j.jevs.2016.03.007google scholar: lookup
  45. Pedersen G.R, Søndergaard E, Ladewig J. The Influence of Bedding on the Time Horses Spend Recumbent. J. Equine Vet. Sci. 2004;24:153–158.
    doi: 10.1016/j.jevs.2004.03.013google scholar: lookup
  46. Mills D.S, Eckley S, Cooper J.J. Thoroughbred Bedding Preferences, Associated Behaviour Differences and Their Implications for Equine Welfare. Anim. Sci. 2000;70:95–106.
    doi: 10.1017/S1357729800051638google scholar: lookup
  47. Daniel JA, Groux R, Wilson JA, Krawczel PD, Lee AR, Whitlock BK. Trimming and Re-shoeing Results in More Steps per Day and More Time Spent Lying per Day.. J Equine Vet Sci 2020 May;88:102947.
    doi: 10.1016/j.jevs.2020.102947pubmed: 32303318google scholar: lookup
  48. Boy V, Duncan P. Time-Budgets of Camargue Horses I. Developmental Changes in the Time-Budgets of Foals. Behaviour 1979;71:187–201.
    doi: 10.1163/156853979X00160google scholar: lookup
  49. Raspa F, Tarantola M, Bergero D, Nery J, Visconti A, Mastrazzo CM, Cavallini D, Valvassori E, Valle E. Time-Budget of Horses Reared for Meat Production: Influence of Stocking Density on Behavioural Activities and Subsequent Welfare.. Animals (Basel) 2020 Aug 1;10(8).
    doi: 10.3390/ani10081334pmc: PMC7460472pubmed: 32752257google scholar: lookup
  50. Sartori C, Guzzo N, Normando S, Bailoni L, Mantovani R. Evaluation of behaviour in stabled draught horse foals fed diets with two protein levels.. Animal 2017 Jan;11(1):147-155.
    doi: 10.1017/S1751731116001221pubmed: 27349277google scholar: lookup
  51. DuBois C, Zakrajsek E, Haley DB, Merkies K. Validation of triaxial accelerometers to measure the lying behaviour of adult domestic horses.. Animal 2015 Jan;9(1):110-4.
    doi: 10.1017/S175173111400247Xpubmed: 25273864google scholar: lookup
  52. Chung E.L.T, Khairuddin N.H, Azizan T.R.P.T, Adamu L. Sleeping Pattern of Horses in Selected Local Horse Stables in Malaysia. J. Vet. Behav. 2018;26:1–4.
    doi: 10.1016/j.jveb.2018.03.014google scholar: lookup
  53. Pritchett L.C, Ulibarri C, Roberts M.C, Schneider R.K, Sellon D.C. Identification of Potential Physiological and Behavioral Indicators of Postoperative Pain in Horses after Exploratory Celiotomy for Colic. Appl. Anim. Behav. Sci. 2003;80:31–43.
    doi: 10.1016/S0168-1591(02)00205-8google scholar: lookup
  54. Sutton GA, Dahan R, Turner D, Paltiel O. A behaviour-based pain scale for horses with acute colic: scale construction.. Vet J 2013 Jun;196(3):394-401.
    doi: 10.1016/j.tvjl.2012.10.008pubmed: 23141961google scholar: lookup
  55. Rietmann TR, Staﾬher M, Bernasconi P, Auer JA, Weishaupt MA. The association between heart rate, heart rate variability, endocrine and behavioural pain measures in horses suffering from laminitis.. J Vet Med A Physiol Pathol Clin Med 2004 Jun;51(5):218-25.
    doi: 10.1111/j.1439-0442.2004.00627.xpubmed: 15315700google scholar: lookup
  56. Lesimple C. Indicators of Horse Welfare: State-of-the-Art.. Animals (Basel) 2020 Feb 13;10(2).
    doi: 10.3390/ani10020294pmc: PMC7070675pubmed: 32069888google scholar: lookup
  57. Hausberger M, Fureix C, Lesimple C. Detecting Horses’ Sickness: In Search of Visible Signs. Appl. Anim. Behav. Sci. 2016;175:41–49.
    doi: 10.1016/j.applanim.2015.09.005google scholar: lookup
  58. Leruste H, Bokkers EA, Sergent O, Wolthuis-Fillerup M, van Reenen CG, Lensink BJ. Effects of the observation method (direct v. from video) and of the presence of an observer on behavioural results in veal calves.. Animal 2013 Nov;7(11):1858-64.
    doi: 10.1017/S1751731113001456pubmed: 23916373google scholar: lookup
  59. Rattenborg NC, de la Iglesia HO, Kempenaers B, Lesku JA, Meerlo P, Scriba MF. Sleep research goes wild: new methods and approaches to investigate the ecology, evolution and functions of sleep.. Philos Trans R Soc Lond B Biol Sci 2017 Nov 19;372(1734).
    doi: 10.1098/rstb.2016.0251pmc: PMC5647278pubmed: 28993495google scholar: lookup
  60. Wolfensohn S. Too Cute to Kill? The Need for Objective Measurements of Quality of Life.. Animals (Basel) 2020 Jun 18;10(6).
    doi: 10.3390/ani10061054pmc: PMC7341278pubmed: 32570914google scholar: lookup
  61. Murphy BA. Circadian and Circannual Regulation in the Horse: Internal Timing in an Elite Athlete.. J Equine Vet Sci 2019 May;76:14-24.
    doi: 10.1016/j.jevs.2019.02.026pubmed: 31084748google scholar: lookup
  62. Berger A, Scheibe K-M, Eichhorn K, Scheibe A, Streich J. Diurnal and Ultradian Rhythms of Behaviour in a Mare Group of Przewalski Horse (Equus Ferus Przewalskii), Measured through One Year under Semi-Reserve Conditions. Appl. Anim. Behav. Sci. 1999;64:1–17.
    doi: 10.1016/S0168-1591(99)00026-Xgoogle scholar: lookup
  63. Martin AM, Elliott JA, Duffy P, Blake CM, Ben Attia S, Katz LM, Browne JA, Gath V, McGivney BA, Hill EW, Murphy BA. Circadian regulation of locomotor activity and skeletal muscle gene expression in the horse.. J Appl Physiol (1985) 2010 Nov;109(5):1328-36.
    doi: 10.1152/japplphysiol.01327.2009pubmed: 20847133google scholar: lookup
  64. Smith JE, Pinter-Wollman N. Observing the unwatchable: Integrating automated sensing, naturalistic observations and animal social network analysis in the age of big data.. J Anim Ecol 2021 Jan;90(1):62-75.
    doi: 10.1111/1365-2656.13362pubmed: 33020914google scholar: lookup
  65. Ireland JL. Demographics, Management, Preventive Health Care and Disease in Aged Horses.. Vet Clin North Am Equine Pract 2016 Aug;32(2):195-214.
    doi: 10.1016/j.cveq.2016.04.001pubmed: 27449388google scholar: lookup
  66. Ireland JL, McGowan CM, Clegg PD, Chandler KJ, Pinchbeck GL. A survey of health care and disease in geriatric horses aged 30 years or older.. Vet J 2012 Apr;192(1):57-64.
    doi: 10.1016/j.tvjl.2011.03.021pubmed: 21550271google scholar: lookup
  67. Ireland JL, Clegg PD, McGowan CM, McKane SA, Chandler KJ, Pinchbeck GL. Disease prevalence in geriatric horses in the United Kingdom: veterinary clinical assessment of 200 cases.. Equine Vet J 2012 Jan;44(1):101-6.
    doi: 10.1111/j.2042-3306.2010.00361.xpubmed: 21668494google scholar: lookup
  68. Ireland JL, Clegg PD, McGowan CM, McKane SA, Chandler KJ, Pinchbeck GL. Comparison of owner-reported health problems with veterinary assessment of geriatric horses in the United Kingdom.. Equine Vet J 2012 Jan;44(1):94-100.
    doi: 10.1111/j.2042-3306.2011.00394.xpubmed: 21696434google scholar: lookup
  69. Ireland JL, Clegg PD, McGowan CM, McKane SA, Pinchbeck GL. A cross-sectional study of geriatric horses in the United Kingdom. Part 2: Health care and disease.. Equine Vet J 2011 Jan;43(1):37-44.
    doi: 10.1111/j.2042-3306.2010.00142.xpubmed: 21143632google scholar: lookup
  70. Ireland JL, Clegg PD, McGowan CM, McKane SA, Pinchbeck GL. A cross-sectional study of geriatric horses in the United Kingdom. Part 1: Demographics and management practices.. Equine Vet J 2011 Jan;43(1):30-6.
    doi: 10.1111/j.2042-3306.2010.00145.xpubmed: 21143631google scholar: lookup
  71. van Weeren PR, Back W. Musculoskeletal Disease in Aged Horses and Its Management.. Vet Clin North Am Equine Pract 2016 Aug;32(2):229-47.
    doi: 10.1016/j.cveq.2016.04.003pubmed: 27449390google scholar: lookup
  72. Clegg PD. Musculoskeletal disease and injury, now and in the future. Part 2: Tendon and ligament injuries.. Equine Vet J 2012 May;44(3):371-5.
    doi: 10.1111/j.2042-3306.2012.00563.xpubmed: 22486548google scholar: lookup
  73. United States Department of Agriculture. Animal and Plant Health Inspection Service. Veterinary Services. National Animal Health Monitoring System. Changes in the U.S. Equine Industry, 1998−2015. United States Department of Agriculture; Fort Collins, CO, USA: 2015.
  74. Jarvis N. Clinical Care of the Geriatric Horse. Practice 2021;43:35–44.
    doi: 10.1002/inpr.6google scholar: lookup
  75. Henneke DR, Potter GD, Kreider JL, Yeates BF. Relationship between condition score, physical measurements and body fat percentage in mares.. Equine Vet J 1983 Oct;15(4):371-2.
    doi: 10.1111/j.2042-3306.1983.tb01826.xpubmed: 6641685google scholar: lookup
  76. Sinovich M, Hewetson M, Lombardi M, Issard P, Archer D. Hospital-Based Validation of a Commercially Available Remote Activity Tracker for Determining Behaviour Changes, Including Colic, in Horses. Equine Vet. Educ. 2021;33:22.
    doi: 10.1111/eve.35_13534google scholar: lookup
  77. The R Development Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing; Vienna, Austria: 2017.
  78. Egan S, Kearney C.M, Brama P.A.J, Parnell A.C, McGrath D. Exploring Stable-Based Behaviour and Behaviour Switching for the Detection of Bilateral Pain in Equines. Appl. Anim. Behav. Sci. 2021;235:105214.
    doi: 10.1016/j.applanim.2021.105214google scholar: lookup
  79. Zeitler-Feicht M.H, Prantner V. Liegeverhalten von Pferden in Gruppenauslaufhaltung. Arch. Anim. Breed. 2000;43:327–336.
    doi: 10.5194/aab-43-327-2000google scholar: lookup
  80. Fader C, Sambraus H. The Resting Behaviour of Horses in Loose Housing Systems. Tierärztliche Umschau 2004;59:320–327.
  81. Kędzierski W, Janczarek I, Stachurska A, Wilk I. Comparison of Effects of Different Relaxing Massage Frequencies and Different Music Hours on Reducing Stress Level in Race Horses. J. Equine Vet. Sci. 2017;53:100–107.
    doi: 10.1016/j.jevs.2017.02.004google scholar: lookup
  82. Stachurska A, Janczarek I, Wilk I, Kędzierski W. Does Music Influence Emotional State in Race Horses?. J. Equine Vet. Sci. 2015;35:650–656.
    doi: 10.1016/j.jevs.2015.06.008google scholar: lookup
  83. Cooper CB, Neufeld EV, Dolezal BA, Martin JL. Sleep deprivation and obesity in adults: a brief narrative review.. BMJ Open Sport Exerc Med 2018;4(1):e000392.
    doi: 10.1136/bmjsem-2018-000392pmc: PMC6196958pubmed: 30364557google scholar: lookup
  84. Christie JL, Hewson CJ, Riley CB, McNiven MA, Dohoo IR, Bate LA. Management factors affecting stereotypies and body condition score in nonracing horses in Prince Edward Island.. Can Vet J 2006 Feb;47(2):136-43.
    pmc: PMC1345728pubmed: 16579039
  85. Jensen RB, Danielsen SH, Tauson AH. Body condition score, morphometric measurements and estimation of body weight in mature Icelandic horses in Denmark.. Acta Vet Scand 2016 Oct 20;58(Suppl 1):59.
    doi: 10.1186/s13028-016-0240-5pmc: PMC5073991pubmed: 27766968google scholar: lookup
  86. Owers R, Chubbock S. Fight the fat!. Equine Vet J 2013 Jan;45(1):5.
    doi: 10.1111/evj.12008pubmed: 23231382google scholar: lookup
  87. Schanz L, Krueger K, Hintze S. Sex and Age Don't Matter, but Breed Type Does-Factors Influencing Eye Wrinkle Expression in Horses.. Front Vet Sci 2019;6:154.
    doi: 10.3389/fvets.2019.00154pmc: PMC6549476pubmed: 31192235google scholar: lookup
  88. Schedlbauer M. Webbasierte Datenerhebung Und Elektroenzephalographische Messungen Bei Pferden Mit Verhaltensauffälligkeiten. Ph.D. Thesis. LMU; München, Germany: 2021.
  89. Marliani G, Sprocatti I, Schiavoni G, Bellodi A, Accorsi PA. Evaluation of Horses' Daytime Activity Budget in a Model of Ethological Stable: A Case Study in Italy.. J Appl Anim Welf Sci 2021 Apr-Jun;24(2):200-213.
    doi: 10.1080/10888705.2020.1857252pubmed: 33353417google scholar: lookup
  90. Roberts K, Hemmings A.J, McBride S.D, Parker M.O. Causal Factors of Oral versus Locomotor Stereotypy in the Horse. J. Vet. Behav. Clin. Appl. Res. 2017;20:37–43.
    doi: 10.1016/j.jveb.2017.05.003google scholar: lookup
  91. Sarrafchi A, Blokhuis H.J. Equine Stereotypic Behaviors: Causation, Occurrence, and Prevention. J. Vet. Behav. Clin. Appl. Res. 2013;8:386–394.
    doi: 10.1016/j.jveb.2013.04.068google scholar: lookup
  92. Hothersall B, Casey R. Undesired Behaviour in Horses: A Review of Their Development, Prevention, Management and Association with Welfare. Equine Vet. Educ. 2012;24:479–485.
    doi: 10.1111/j.2042-3292.2011.00296.xgoogle scholar: lookup
  93. Wei H, Zhao W, Wang YX, Pertovaara A. Pain-related behavior following REM sleep deprivation in the rat: influence of peripheral nerve injury, spinal glutamatergic receptors and nitric oxide.. Brain Res 2007 May 7;1148:105-12.
    doi: 10.1016/j.brainres.2007.02.040pubmed: 17368427google scholar: lookup
  94. May ME, Harvey MT, Valdovinos MG, Kline RH 4th, Wiley RG, Kennedy CH. Nociceptor and age specific effects of REM sleep deprivation induced hyperalgesia.. Behav Brain Res 2005 Apr 15;159(1):89-94.
    doi: 10.1016/j.bbr.2004.10.005pubmed: 15795001google scholar: lookup

Citations

This article has been cited 5 times.
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  2. Gobbo E, Maccario C, Zupan Šemrov M, Bovo M, Atallah E, Minero M, Dalla Costa E. Exploring the impact of housing routine on lying behavior in horses measured with triaxial accelerometer. Front Vet Sci 2025;12:1572051.
    doi: 10.3389/fvets.2025.1572051pubmed: 40420950google scholar: lookup
  3. Hall C, Kay R. Living the good life? A systematic review of behavioural signs of affective state in the domestic horse (Equus caballus) and factors relating to quality of life. Part 2: Horse-human interactions. Anim Welf 2024;33:e41.
    doi: 10.1017/awf.2024.41pubmed: 39469043google scholar: lookup
  4. Wilkins CL, McGreevy PD, Cosh SM, Henshall C, Jones B, Lykins AD, Billingsley W. Introducing the Mellorater-The Five Domains Model in a Welfare Monitoring App for Animal Guardians. Animals (Basel) 2024 Jul 25;14(15).
    doi: 10.3390/ani14152172pubmed: 39123698google scholar: lookup
  5. Chiavaccini L, Gupta A, Chiavaccini G. From facial expressions to algorithms: a narrative review of animal pain recognition technologies. Front Vet Sci 2024;11:1436795.
    doi: 10.3389/fvets.2024.1436795pubmed: 39086767google scholar: lookup
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