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Home / Equine Research Bank / Equine Vet J / Epidemiological investigation of insulin dysregulation in Sh...
Equine veterinary journal2024; 56(2); 281-290; doi: 10.1111/evj.14044

Epidemiological investigation of insulin dysregulation in Shetland and Welsh ponies in Australia.

Abstract: Insulin dysregulation (ID) is central to equine metabolic syndrome. There are limited epidemiological studies investigating dynamic testing of ID in ponies. Objective: To evaluate prevalence and risk factors for ID through dynamic testing of hyperinsulinaemia (DHI) and insulin resistance (IR). Methods: Cross-sectional. Methods: Sex, age, breed, height, cresty neck score (CNS), body condition score (BCS), laminitis, HMGA2:c.83G>A genotype and pituitary pars intermedia dysfunction (PPID) status were documented. Dynamic hyperinsulinaemia was diagnosed with an oral sugar test (OST) and IR with an insulin tolerance test (ITT). Owners completed surveys reporting activity, laminitis history and perception of body condition using a (1-9) visual analogue scale (VASo). Ordinal scores were converted to binary outcomes for CNS (≤2/5 or ≥3/5), BCS and VASo (≤6/9 or ≥7/9). Variables associated with insulin concentrations, glucose reduction after the ITT and laminitis were evaluated with mixed effects regression models accounting for random effects of farms. Results: Among 167 ponies tested, median (range) age was 9 (4-21) years and BCS was 6 (4-8). Prevalence (95% confidence interval [CI]) of ID was 61 (53-68)%. Factors associated with insulin concentrations (estimate [95% CI]; μIU/mL) 60 min post-OST were: age (1.07 [1.02-1.11]), CNS (≥3/5, 1.52 [1.04-2.23]) and VASo (≥7/9, 1.75 [1.09-2.79]); and 90 min post-OST were: age (1.08 [1.03-1.12]), CNS (≥3/5, 1.80 [1.22-2.64]), VASo (≥7/9, 2.49 [1.52-4.08]) and sex (male, 0.64 [0.45-0.91]). Factors associated with glucose reduction after the ITT (estimate [95% CI]; %) were: age (-1.34 [-2.01 to -0.67]), sex (female, -6.21 [-11.68 to -0.74]) and VASo (≥7/9, -1.74 [-18.89 to -4.78]). Factors associated with laminitis (odds ratio [95% CI]) were DHI (4.60 [1.68-12.58]), IR (3.66 [1.26-10.61]) and PPID (11.75 [1.54-89.40]). Conclusions: Single time-point sampling, laminitis definition and diet analysis. Conclusions: Ageing, being female and owner-perceived obesity were associated with ID.
© 2024 The Authors. Equine Veterinary Journal published by John Wiley & Sons Ltd on behalf of EVJ Ltd.
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Publication Date: 2024-01-03 PubMed ID: 38173146DOI: 10.1111/evj.14044Google Scholar: Lookup
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Summary

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The research article investigates the prevalence and risk factors associated with insulin dysregulation in Shetland and Welsh ponies in Australia, identified through hyperinsulinaemia and insulin resistance tests. This study reveals that key factors such as age, gender, and owner-perceived obesity are significantly associated with insulin dysregulation in ponies.

Methodology

  • The research opted for a cross-sectional study. Characteristics such as sex, age, breed, height, cresty neck score (an indicator for assessing regional fat deposits), body condition score, history of laminitis (a severe condition in the hooves of horses), genetic markers, and pituitary pars intermedia dysfunction status were examined.
  • Two dynamic tests were employed to diagnose insulin abnormalities: the oral sugar test to identify hyperinsulinaemia, and the insulin tolerance test for insulin resistance.
  • Pony owners also provided additional information via surveys. This included the ponies’ activity level, laminitis history, and their assessment of the pony’s body condition using a 1-9 visual scale.
  • The researchers used regression models to evaluate the variables affecting insulin levels, glucose reduction post-insulin tolerance test, and the occurrence of laminitis, adjusted for different farms.

Results

  • The study included 167 ponies with a median age of 9 years and a median body condition score of 6.
  • The prevalence of insulin dysregulation was found to be 61%.
  • The study found that factors affecting insulin concentrations 60 minutes after the oral sugar test included age, cresty neck score, and owner’s visual assessment.
  • Similarly, factors linked with insulin concentrations 90 minutes after the oral sugar test included age, cresty neck score, owner’s visual assessment, and the gender of the pony.
  • The study also identified age, sex, and owner’s visual assessment as factors affecting glucose reduction after the insulin tolerance test.
  • Finally, dynamic hyperinsulinaemia, insulin resistance, and pituitary pars intermedia dysfunction were associated with the likelihood of laminitis.

Conclusion

  • The study concluded that key factors influencing insulin dysregulation in ponies included age, sex (being female found to be at risk), and owner-perceived obesity.
  • Other notable findings of the study were the prevalence of single time-point sampling, laminitis definitions, and their implications for the diet of the ponies.
  • The data presents a detailed epidemiological view of insulin dysregulation issues in Shetland and Welsh ponies, shedding light on what owners and vets could do to manage these conditions better.

Cite This Article

APA
Clark BL, Norton EM, Bamford NJ, Randhawa IAS, Kemp KL, McCue ME, Bertin FR, Stewart AJ. (2024). Epidemiological investigation of insulin dysregulation in Shetland and Welsh ponies in Australia. Equine Vet J, 56(2), 281-290. https://doi.org/10.1111/evj.14044

Publication

Equine veterinary journal
ISSN: 2042-3306
NlmUniqueID: 0173320
Country: United States
Language: English
Volume: 56
Issue: 2
Pages: 281-290

Researcher Affiliations

Clark, Brianna L
  • School of Veterinary Science, The University of Queensland, Gatton, Queensland, Australia.
Norton, Elaine M
  • College of Agricultural and Life Sciences, The University of Arizona, Tucson, Arizona, USA.
Bamford, Nicholas J
  • Melbourne Veterinary School, The University of Melbourne, Parkville, Victoria, Australia.
Randhawa, Imtiaz A S
  • School of Veterinary Science, The University of Queensland, Gatton, Queensland, Australia.
Kemp, Kate L
  • School of Veterinary Science, The University of Queensland, Gatton, Queensland, Australia.
McCue, Molly E
  • College of Veterinary Medicine, The University of Minnesota, St Paul, Minnesota, USA.
Bertin, François-René
  • School of Veterinary Science, The University of Queensland, Gatton, Queensland, Australia.
Stewart, Allison J
  • School of Veterinary Science, The University of Queensland, Gatton, Queensland, Australia.

MeSH Terms

  • Horses
  • Animals
  • Female
  • Male
  • Insulin / metabolism
  • Cross-Sectional Studies
  • Hyperinsulinism / veterinary
  • Insulin Resistance
  • Pituitary Diseases / veterinary
  • Australia / epidemiology
  • Glucose
  • Horse Diseases / diagnosis

Grant Funding

  • The University of Queensland, School of Veterinary Science
  • American College of Veterinary Internal Medicine

References

This article includes 47 references
  1. Durham AE, Frank N, McGowan CM, Menzies-Gow NJ, Roelfsema E, Vervuert I. ECEIM consensus statement on equine metabolic syndrome.. J Vet Intern Med 2019;33(2):335-349.
  2. Norton EM, Schultz NE, Rendahl AK, Mcfarlane D, Geor RJ, Mickelson JR. Heritability of metabolic traits associated with equine metabolic syndrome in Welsh ponies and Morgan horses.. Equine Vet J 2018;51(4):475-480.
  3. Bailey SR, Habershon-Butcher JL, Ransom KJ, Elliott J, Menzies-Gow NJ. Hypertension and insulin resistance in a mixed-breed population of ponies predisposed to laminitis.. Am J Vet Res 2008;69(1):122-129.
  4. Karikoski NP, Box JR, Mykkanen AK, Kotiranta VV, Raekallio MR. Variation in insulin response to oral sugar test in a cohort of horses throughout the year and evaluation of risk factors for insulin dysregulation.. Equine Vet J 2022;54(5):905-913.
  5. Carslake HB, Argo CM, Pinchbeck GL, Dugdale AHA, McGowan CM. Insulinaemic and glycaemic responses to three forages in ponies.. Vet J 2018;235:83-89.
  6. Bamford NJ, Potter SJ, Harris PA, Bailey SR. Breed differences in insulin sensitivity and insulinemic responses to oral glucose in horses and ponies of moderate body condition score.. Domest Anim Endocrinol 2014;47:101-107.
  7. Box JR, McGowan CM, Raekallio MR, Mykkanen AK, Carslake H, Karikoski NP. Insulin dysregulation in a population of Finnhorses and associated phenotypic markers of obesity.. J Vet Intern Med 2020;34(4):1599-1605.
  8. Knowles EJ, Elliott J, Harris PA, Chang Y-M, Menzies-Gow NJ. Predictors of laminitis development in a cohort of nonlaminitic ponies.. Equine Vet J 2022;55(1):12-23.
  9. Morgan R, McGowan T, McGowan CM. Prevalence and risk factors for hyperinsulinaemia in ponies in Queensland, Australia.. Aust Vet J 2014;92(4):101-106.
  10. Norton EM, Avila F, Schultz NE, Mickelson JR, Geor RJ, McCue ME. Evaluation of an HMGA2 variant for pleiotropic effects on height and metabolic traits in ponies.. J Vet Intern Med 2019;33(2):942-952.
  11. Clark BL, Bamford NJ, Stewart AJ, McCue ME, Rendahl A, Bailey SR. Evaluation of an HMGA2 variant contribution to height and basal insulin concentrations in ponies.. J Vet Intern Med 2023;37:1186-1192.
    doi: 10.1111/jvim.16723google scholar: lookup
  12. Ellis JM, Hollands T. Use of height-specific weigh tapes to estimate the bodyweight of horses.. Vet Rec 2002;150(20):632-634.
  13. Carter RA, Geor RJ, Burton Staniar W, Cubitt TA, Harris PA. Apparent adiposity assessed by standardised scoring systems and morphometric measurements in horses and ponies.. Vet J 2009;179(2):204-210.
  14. Henneke DR, Potter GD, Kreider JL, Yeates BF. Relationship between condition score, physical measurements and body fat percentage in mares.. Equine Vet J 1983;15(4):371-372.
  15. Meier A, de Laat M, Pollitt C, Walsh D, McGree J, Reiche DB. A “modified Obel” method for the severity scoring of (endocrinopathic) equine laminitis.. PeerJ 2019;7:e7084.
  16. Bertin FR, Sojka-Kritchevsky JE. Comparison of a 2-step insulin-response test to conventional insulin-sensitivity testing in horses.. Domest Anim Endocrinol 2013;44(1):19-25.
  17. Cunneen A, Wood KA, Mathison K, Herndon AM, Bertin FR. Comparison of a continuous indwelling glucometer with a point-of-care device in healthy adult horses.. Vet Rec 2020;187(3):e21.
  18. Schuver A, Frank N, Chameroy KA, Elliott J. Assessment of insulin and glucose dynamics by using an oral sugar test in horses.. J Equine Vet 2014;34(4):465-470.
  19. Jocelyn NA, Harris PA, Menzies-Gow NJ. Effect of varying the dose of corn syrup on the insulin and glucose response to the oral sugar test.. Equine Vet J 2018;50(6):836-841.
  20. Frank N, Bailey S, Bertin F-R, de Laat M, Durham A, Kritchevsky J. Recommendations for the diagnosis and management of Equine Metabolic Syndrome (EMS).. 2022.
  21. Warnken T, Huber K, Feige K. Comparison of three different methods for the quantification of equine insulin.. BMC Vet Res 2016;12(1):196.
  22. McGilvray TA, Knowles EJ, Harris PA, Menzies-Gow NJ. Comparison of immunofluorescence and chemiluminescence assays for measuring ACTH in equine plasma.. Equine Vet J 2020;52(5):709-714.
  23. McFarlane D. Equine pituitary pars intermedia dysfunction.. Vet Clin North Am Equine Pract 2011;27(1):93-113.
  24. Hart KA, Durham A, Frank N, McGowan C, Schott H, Stewart A. Recommendations for the Diagnosis and Treatment of Pituitary Pars Intermedia Dysfunction (PPID).. 2019.
  25. . R: a language and environment for statistical computing.. Vienna: R Foundation for Statistical Computing; 2022.
  26. Bates D, Mächler M, Bolker B, Walker S. Fitting linear mixed-effects models using lme4.. J Stat Softw 2015;67(1):1-48.
  27. Gamer M, Lemon J. irr: Various Coefficients of Interrater Reliability and Agreement.. R package version 0.84.1.
  28. Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research.. J Chiropr Med 2016;15(2):155-163.
  29. Muno J, Gallatin L, Geor R. Prevalence and risk factors for hyperinsulinemia in clinically normal horses in central Ohio.. J Vet Intern Med 2009;23(3):721.
  30. de Laat MA, McGree JM, Sillence MN. Equine hyperinsulinemia: investigation of the enteroinsular axis during insulin dysregulation.. Am J Phys Endocrinol Metab 2016;310(1):E61-E72.
  31. Clark BL, Stewart AJ, Kemp KL, Bamford NJ, Bertin F-R. Evaluation of field-testing protocols to diagnose insulin dysregulation using a Bayesian approach.. Vet J 2023;298-299:106019.
  32. Potter SJ, Bamford N, Harris PA, Bailey SR. Prevalence of obesity and owners' perceptions of body condition in pleasure horses and ponies in south-eastern Australia.. Aust Vet J 2016;94(11):427-432.
  33. Furtado T, Perkins E, Pinchbeck G, McGowan C, Watkins F, Christley R. Exploring horse owners' understanding of obese body condition and weight management in UK leisure horses.. Equine Vet J 2021;53(4):752-762.
  34. Suagee JK, Corl BA, Crisman MV, Pleasant RS, Thatcher CD, Geor RJ. Relationships between body condition score and plasma inflammatory cytokines, insulin, and lipids in a mixed population of light-breed horses.. J Vet Intern Med 2013;27(1):157-163.
  35. Zak A, Siwinska N, Elzinga S, Barker VD, Stefaniak T, Schanbacher BJ. Effects of equine metabolic syndrome on inflammation and acute-phase markers in horses.. Domest Anim Endocrinol 2020;72:106448.
  36. Fitzgerald DM, Anderson ST, Sillence MN, de Laat MA. The cresty neck score is an independent predictor of insulin dysregulation in ponies.. PLoS One 2019;14(7):e0220203.
  37. Karikoski NP, Patterson-Kane JC, Singer ER, McFarlane D, McGowan CM. Lamellar pathology in horses with pituitary pars intermedia dysfunction.. Equine Vet J 2016;48(4):472-478.
  38. Horn R, Bamford NJ, Afonso T, Sutherland M, Buckerfield J, Tan RHH. Factors associated with survival, laminitis and insulin dysregulation in horses diagnosed with equine pituitary pars intermedia dysfunction.. Equine Vet J 2019;51(4):440-445.
  39. Tadros EM, Fowlie JG, Refsal KR, Marteniuk J, Schott HC II. Association between hyperinsulinaemia and laminitis severity at the time of pituitary pars intermedia dysfunction diagnosis.. Equine Vet J 2019;51(1):52-56.
  40. Mastro LM, Adams AA, Urschel KL. Pituitary pars intermedia dysfunction does not necessarily impair insulin sensitivity in old horses.. Domest Anim Endocrinol 2015;50:14-25.
  41. Billingham N, Beloff-Chain A, Cawthorne MA. Identification of β-cell-trophin, a peptide of the pituitary pars intermedia which stimulates insulin secretion in plasma from genetically obese (ob/ob) mice.. J Endocrinol 1982;94(1):125-130.
  42. Carslake HB, Pinchbeck GL, McGowan CM. Equine metabolic syndrome in UK native ponies and cobs is highly prevalent with modifiable risk factors.. Equine Vet J 2021;53(5):923-934.
  43. Jacob SI, Geor RJ, Weber PSD, Harris PA, McCue ME. Effect of age and dietary carbohydrate profiles on glucose on glucose and insulin dynamics in horses.. Equine Vet J 2018;50(2):249-254.
  44. Rapson JL, Schott HC, Nielsen BD, McCutcheon LJ, Harris PA, Geor RJ. Effect of age and diet on glucose and insulin dynamics in the horse.. Equine Vet J 2018;50(5):690-696.
  45. Adams AA, Breathnach CC, Katepalli MP, Kohler K, Horohov DW. Advanced age in horses affects divisional history of T cells and inflammatory cytokine production.. Mech Ageing Dev 2008;129(11):656-664.
  46. Wylie CE, Collins SN, Verheyen KLP, Newton JR. Frequency of equine laminitis: a systematic review with quality appraisal of published evidence.. Vet J 2011;189(3):248-256.
  47. Pollard D, Wylie CE, Verheyen KLP, Newton JR. Assessment of horse owners' ability to recognise equine laminitis: a cross-sectional study of 93 veterinary diagnosed cases in Great Britain.. Equine Vet J 2017;49(6):759-766.
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