Energy Quality of Dog Feeds and Owner Feeding Practices: Links to Body Condition Score

Authors

  • Ester Vargová Slovak University of Agriculture in Nitra, Faculty of Agrobiology and Food Resources,Institute of Nutrition and Genomics, Slovakia
  • Branislav Gálik Slovak University of Agriculture in Nitra, Faculty of Agrobiology and Food Resources,Institute of Nutrition and Genomics, Slovakia
  • Miroslav Juráček Slovak University of Agriculture in Nitra, Faculty of Agrobiology and Food Resources,Institute of Nutrition and Genomics, Slovakia
  • Milan Šimko Slovak University of Agriculture in Nitra, Faculty of Agrobiology and Food Resources,Institute of Nutrition and Genomics, Slovakia
  • Matúš Džima Slovak University of Agriculture in Nitra, Faculty of Agrobiology and Food Resources,Institute of Nutrition and Genomics, Slovakia
  • Kristína Kolbaská Slovak University of Agriculture in Nitra, Faculty of Agrobiology and Food Resources,Institute of Nutrition and Genomics, Slovakia
  • Ella Tarišková Slovak University of Agriculture in Nitra, Faculty of Agrobiology and Food Resources,Institute of Nutrition and Genomics, Slovakia
  • Michal Rolinec Slovak University of Agriculture in Nitra, Faculty of Agrobiology and Food Resources,Institute of Nutrition and Genomics, Slovakia

Keywords:

metabolisable energy, dog nutrition, direct calorimetry, feeding practices, body condition score

Abstract

The study aimed to evaluate the energy quality of complete commercial dog feeds by comparing declared metabolisable energy (ME) values with those determined by laboratory analysis. A total of 19 dry complete commercial dog feeds formulated for adult dogs in maintenance were analysed. Gross energy (GE) was measured by direct calorimetry and recalculated to ME using a conversion coefficient of 0.82. In addition, a questionnaire survey among 32 dog owners was conducted to assess feeding practices and their association with body condition score (BCS). The results showed that declared ME concentrations (15,870 ±720 kJ/kg) were on average higher than the recalculated values (14,800 ±1,030 kJ/kg), with a mean difference of 1,070 ±1,350 kJ/kg. For a 15 kg model dog, this discrepancy translated into daily intake variations of several hundred kilojoules, potentially leading to under- or overfeeding. The questionnaire confirmed that 75% of owners provided treats and 72% used dietary supplements, both of which significantly increased total energy intake. Pearson correlation analysis demonstrated strong positive associations between BCS and the use of treats (r = 0.71, P < 0.01) as well as supplements (r = 0.69, P < 0.01), whereas the amount of complete feed alone showed no significant effect (r = 0.31, P > 0.05). These findings underline the importance of precise feed labelling and highlight the role of owner behaviour as a determinant of canine body condition. Improvements in transparency of nutritional information and targeted owner education are essential to support optimal feeding strategies and prevent obesity in dog

References

AAFCO. (2015). Dog and Cat Food Nutrient Profiles. Association of American Feed Control Officials.

Case, L. P., Daristotle, L., Hayek, M. G., & Raasch, M. F. (2010). Canine and Feline Nutrition: A Resource for Companion Animal Professionals (3rd ed.). Mosby Elsevier.

Dodd, S. A. S., Cave, N. J., Adolphe, J. L., Shoveller, A. K., & Verbrugghe, A. (2021). A comparison of key essential nutrients in commercial plant-based pet foods sold in Canada to American and European canine and feline dietary recommendations. Animals, 11(8), 2348. https://doi.org/10.3390/ani11082348

German, A. J. (2006). The growing problem of obesity in dogs and cats. Journal of Nutrition, 136(7 Suppl), 1940S–1946S. https://doi.org/10.1093/jn/136.7.1940S

German, A. J. (2010). Obesity in companion animals. Veterinary Clinics of North America: Small Animal Practice, 40(2), 277–293. https://doi.org/10.1016/j.cvsm.2010.12.004

Hall, J. A., Melendez, L. D., & Jewell, D. E. (2013). Using gross energy improves metabolizable energy predictive equations for pet foods whereas undigested protein and fiber content predict stool quality. PLOS ONE, 8(1), e54405. https://doi.org/10.1371/journal.pone.0054405

Harčárová, M., Bujňák, L., Hreško Šamudovská, A., Hreško, S., & Tvrdá, A. (2025). The presence of deoxynivalenol and zearalenone in industrially produced dog feed. Folia Veterinaria, 69(2), 6–11. https://doi.org/10.2478/fv-2025-0012

Hervera, M., Daucells, M. D., Llanch, F., & Castrillo, C. (2007). Prediction of digestible energy content of extruded dog food by in vitro analyses. Animal Physiology and Animal Nutrition, 91(5–6), 205–209. https://doi.org/10.1111/j.1439-0396.2007.00705.x

Jewell, D. E., & Jackson, M. I. (2023). Predictive equations for dietary energy are improved when independently developed for dry and wet food which could benefit both the pet and the environment. Frontiers in Veterinary Science, 10, 1104695. https://doi.org/10.3389/fvets.2023.1104695

Laflamme, D. P. (2008). Companion animals symposium: Obesity in dogs and cats: What is wrong with being fat? Journal of Animal Science, 86(14 Suppl), 279–284. https://doi.org/10.2527/jas.2007-0460

Liyanage, A. T., Ramesh, N. B., & Ariyarathna, H. (2022). Owner-misperception of canine body condition reduces after using a five-point body condition score chart: A study of 95 large-sized purebred dogs. Topics in Companion Animal Medicine, 50, 100677. https://doi.org/10.1016/j.tcam.2022.100677

Marchi, P. H., Amaral, A. R., Príncipe, L. d. A., Risolia, L. W., Rentas, M. F., Fasolai, A. B., Zafalon, R. V. A., Finardi, G. L. F., Jeremias, J. T., Pedreira, R. S.,

Balieiro, J. C. d. C., & Vendramini, T. H. A. (2025). Accuracy of predictive equations for metabolizable energy compared to energy content of foods for dogs and cats estimated by in vivo methods in Brazil. Animals, 15(10), 1477. https://doi.org/10.3390/ani15101477

Mihok, T., Bujňák, L., Mihok, V., & Rovňanová, N. (2021). Effect of nutrition on the morphometric markers in spayed dogs. Folia Veterinaria, 65(4), 67–71. https://doi.org/10.2478/fv-2021-0039

Muñoz-Prieto, A., et al. (2018). European dog owner perceptions of obesity and factors associated with human and canine obesity. Scientific Reports, 8, 13353. https://doi.org/10.1038/s41598-018-31532-0

National Research Council (NRC). (2006). Nutrient Requirements of Dogs and Cats. The National Academies Press. https://doi.org/10.17226/10668

Rolinec, M., Bíro, D., Gálik, B., Šimko, M., Juráček, M., Tvarožková, K., & Ištoková, A. (2016). The nutritive value of selected commercial dry dog foods. Acta Fytotechnica et Zootechnica, 19(1), 25–28. https://doi.org/10.15414/afz.2016.19.01.25-28

Sallander, M., Hagberg, M., Hedhammar, Å., Rundgren, M., & Lindberg, J. E. (2010). Energy-intake and activity risk factors for owner-perceived obesity in a defined population of Swedish dogs. Preventive Veterinary Medicine, 96(1–2), 132–141. https://doi.org/10.1016/j.prevetmed.2010.05.004

Sanderson, L. (2023). Overview of nutrition: Small animals. In Merck Veterinary Manual. Retrieved February 2023 from https://www.merckvetmanual.com

World Small Animal Veterinary Association (WSAVA). (2021). Global Nutrition Toolkit: Selecting the best food for your pet. https://wsava.org/wp-content/uploads/2021/04/Selecting-a-pet-food-for-your-pet-updated-2021_WSAVA-Global-Nutrition-Toolkit.pdf

Downloads

Published

2026-07-01

Issue

Vol. 29 No. 2 (2026)

Section

Animal Science

License

Copyright (c) 2026 Ester Vargová

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.