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Once-daily feeding is associated with better health in companion dogs: results from the Dog Aging Project

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Abstract

A variety of diets have been studied for possible anti-aging effects. In particular, studies of intermittent fasting and time-restricted feeding in laboratory rodents have found evidence of beneficial health outcomes. Companion dogs represent a unique opportunity to study diet in a large mammal that shares human environments. The Dog Aging Project has been collecting data on thousands of companion dogs of all different ages, sizes, and breeds since 2019. We leveraged this diverse cross-sectional dataset to investigate associations between feeding frequency and cognitive function (n = 10,474) as well as nine broad categories of health conditions (n = 24,238). Controlling for sex, age, breed, and other potential confounders, we found that dogs fed once daily rather than more frequently had lower mean scores on a cognitive dysfunction scale, and lower odds of having gastrointestinal, dental, orthopedic, kidney/urinary, and liver/pancreas disorders. Therefore, we find that once-daily feeding is associated with better health in multiple domains. Future research with longitudinal data can provide stronger evidence for a possible causal effect of feeding frequency on health in companion dogs.

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Data availability

These data are housed on the Terra platform at the Broad Institute of MIT and Harvard.

Code availability

This study did not use custom code or mathematical algorithms.

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Acknowledgements

The Dog Aging Project thanks study participants, their dogs, and community veterinarians for their important contributions.

Dog Aging Project Consortium Authors

Joshua M. Akey1, Brooke Benton2, Elhanan Borenstein3,4,5, Marta G. Castelhano6, Amanda E. Coleman7, Kate E. Creevy8, Kyle Crowder9,10, Matthew D. Dunbar10, Virginia R. Fajt11, Annette L. Fitzpatrick12,13,14, Unity Jeffrey15, Erica C. Jonlin2,16, Elinor K. Karlsson17,18, Jonathan M. Levine8, Jing Ma19, Robyn L. McClelland20, Daniel E.L. Promislow2,21, Audrey Ruple22, Stephen M. Schwartz13,23, Sandi Shrager24, Noah Snyder-Mackler25,26,27, Silvan R. Urfer2, Benjamin S. Wilfond28,29

1Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA

2Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, USA

3Department of Clinical Microbiology and Immunology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel

4Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel

5Santa Fe Institute, Santa Fe, NM, USA

6Cornell Veterinary Biobank, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA

7Department of Small Animal Medicine and Surgery, College of Veterinary Medicine, University of Georgia, Athens, GA, USA

8Department of Small Animal Clinical Sciences, Texas A&M University College of Veterinary Medicine & Biomedical Sciences, College Station, TX, USA

9Department of Sociology, University of Washington, Seattle, WA, USA

10Center for Studies in Demography and Ecology, University of Washington, Seattle, WA, USA

11Department of Veterinary Physiology and Pharmacology, Texas A&M University College of Veterinary Medicine & Biomedical Sciences, College Station, TX, USA

12Department of Family Medicine, University of Washington, Seattle, WA, USA

13Department of Epidemiology, University of Washington, Seattle, WA, USA

14Department of Global Health, University of Washington, Seattle, WA, USA

15Department of Veterinary Pathobiology, Texas A&M University College of Veterinary Medicine & Biomedical Sciences, College Station, TX, USA

16Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA

17Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA

18Broad Institute of MIT and Harvard, Cambridge, MA, USA

19Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA

20Department of Biostatistics, University of Washington, Seattle, WA, USA

21Department of Biology, University of Washington, Seattle, WA, USA

22Department of Population Health Sciences, Virginia-Maryland College of Veterinary Medicine, Virginia Tech, Blacksburg, VA, USA

23Epidemiology Program, Fred Hutchinson Cancer Research Center, Seattle, WA, USA

24Department of Biostatistics, Collaborative Health Studies Coordinating Center, University of Washington, Seattle, WA, USA

25School of Life Sciences, Arizona State University, Tempe, AZ, USA

26Center for Evolution and Medicine, Arizona State University, Tempe, AZ, USA

27School for Human Evolution and Social Change, Arizona State University, Tempe, AZ, USA

28Treuman Katz Center for Pediatric Bioethics, Seattle Children's Research Institute, Seattle, WA, USA

29Department of Pediatrics, Division of Bioethics and Palliative Care, University of Washington School of Medicine, Seattle, WA, USA

Funding

The Dog Aging Project is supported by U19AG057377 and R24AG073137 from the National Institute on Aging, a part of the National Institutes of Health, and by additional grants and private donations. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Author information

Authors and Affiliations

  1. Arizona Canine Cognition Center, School of Anthropology, University of Arizona, Tucson, AZ, USA

    Emily E. Bray

  2. Canine Companions for Independence, National Headquarters, Santa Rosa, CA, USA

    Emily E. Bray

  3. Department of Biostatistics, University of Washington, Seattle, WA, USA

    Zihan Zheng & Kathleen F. Kerr

  4. Gastrointestinal Laboratory, Department of Small Animal Clinical Sciences, College of Veterinary Medicine, Texas A&M University, College Station, TX, USA

    M. Katherine Tolbert

  5. School of Life Sciences, Arizona State University, Tempe, AZ, USA

    Brianah M. McCoy

  6. Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA

    Matt Kaeberlein

Authors
  1. Emily E. Bray
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  2. Zihan Zheng
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  3. M. Katherine Tolbert
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  4. Brianah M. McCoy
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  5. Matt Kaeberlein
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  6. Kathleen F. Kerr
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Consortia

Dog Aging Project Consortium

  • Joshua M. Akey
  • , Brooke Benton
  • , Elhanan Borenstein
  • , Marta G. Castelhano
  • , Amanda E. Coleman
  • , Kate E. Creevy
  • , Kyle Crowder
  • , Matthew D. Dunbar
  • , Virginia R. Fajt
  • , Annette L. Fitzpatrick
  • , Unity Jeffrey
  • , Erica C. Jonlin
  • , Elinor K. Karlsson
  • , Jonathan M. Levine
  • , Jing Ma
  • , Robyn L. McClelland
  • , Daniel E. L. Promislow
  • , Audrey Ruple
  • , Stephen M. Schwartz
  • , Sandi Shrager
  • , Noah Snyder-Mackler
  • , Silvan R. Urfer
  •  & Benjamin S. Wilfond

Contributions

All authors contributed to writing — review and editing. E.B.: conceptualization, methodology, data curation, writing — original draft, and project administration. Z.Z.: conceptualization, methodology, formal analysis, and visualization. K.T.: conceptualization and data curation. B.M.: data curation. DAP consortium: resources. M.K.: conceptualization, writing — original draft, and funding acquisition. K.K.: conceptualization, methodology, formal analysis, data curation, writing — original draft, visualization, project administration, and supervision.

Corresponding author

Correspondence to Emily E. Bray.

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Competing interests

The authors declare no competing interests.

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Supplementary Information

Below is the link to the electronic supplementary material.

11357_2022_575_MOESM1_ESM.pdf

Supplementary file1 Supplementary Information 1: Summary of the inclusion and exclusion criteria for subjects across all analyses, including guidelines for how all relevant variables were coded. (PDF 241 KB)

11357_2022_575_MOESM2_ESM.pdf

Supplementary file2 Supplementary Information 2: Criteria for determining whether or not a dog had a history of training (coded as a binary variable). (PDF 159 KB)

11357_2022_575_MOESM3_ESM.pdf

Supplementary file3 Supplementary Information 3: Regression outputs from the CSLB analysis, as well as the regression outputs from the health outcome analyses (both primary and secondary). (PDF 304 KB)

11357_2022_575_MOESM4_ESM.pdf

Supplementary file4 Supplementary Information 4: Complete list of purebred dogs (n = 76) included in the CSLB analysis, with sample sizes. (PDF 144 KB)

11357_2022_575_MOESM5_ESM.pdf

Supplementary file5 Supplementary Information 5: Complete list of purebred dogs (n = 100) included in analysis of health conditions, with sample sizes. (PDF 147 KB)

11357_2022_575_MOESM6_ESM.pdf

Supplementary file6 Supplementary Information 6: Secondary Analyses of four-level unordered categorical feeding frequency. (PDF 303 KB)

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Bray, E.E., Zheng, Z., Tolbert, M.K. et al. Once-daily feeding is associated with better health in companion dogs: results from the Dog Aging Project. GeroScience 44, 1779–1790 (2022). https://doi.org/10.1007/s11357-022-00575-7

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  • DOI: https://doi.org/10.1007/s11357-022-00575-7

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