Scientific Results: Big data from small animals: integrating multi-level environmental data into the Dog Aging Project

August 14, 2023 - 6 minutes read

Posts in our Scientific Results series introduce recent papers published in the scientific literature by members of the Dog Aging Project research team. Follow this series to learn more about the scientific questions we’re asking, the kinds of results we’re getting, and what it all means for you and your dog.

Who worked on this research?

Diane Xue
Devin Collins
Mandy Kauffman
Matt Dunbar
Kyle Crowder
Steve Schwartz
Audrey Ruple

Where was it published?

World Organization for Animal Health- Scientific and Technical Review

What is this paper about?

This paper describes the infrastructure developed by the Dog Aging Project to integrate and analyze environmental data with the goal of understanding how these factors can affect the health of dogs. Within the Dog Aging Project, data has been collected from dogs’ homes, yards, and neighborhoods. These data can be combined with health information, including medical records, behavioral surveys, genetics, and other biological data, to investigate contextual determinants of health and interactions between contextual and individual-level factors.

Variables have been collected across four environmental domains: Physical and Built Environment, Chemical Environment and Exposures, Diet and Exercise, and Social Environment. These data are collected through a combination of owner-reported surveys and census-based secondary data connected to individual households using geocoding tools.

While there has been extensive research on how the environment influences human health, this is one of the first major efforts to capture the impact of the built, natural, and social environment on companion dogs. The infrastructure developed by the Dog Aging Project is flexible and designed to grow and improve as more dogs are added to the Dog Aging Project Pack each year and as new investigators contribute additional environmental variables. This type of ‘big data’ approach to analyzing environmental data alongside other data types is critical to discovering key factors that contribute to healthy lifespans and setting up potential precision health approaches in the future.

What do these results mean for me and my dog?

By completing the Dog Aging Project Health and Life Experience Study, not only are you able to learn more about your dog, but you are contributing to our understanding of environmental factors, helping to identify potential health risks, and promoting potential population-level interventions to improve dog health.

The environmental data infrastructure allows us to provide a deeper understanding of how the surrounding environment can influence health and aging in companion dogs. As more studies are done, this knowledge may help you become more aware of the environmental influences on your dog’s health and take appropriate measures to create a healthy environment.

Of course, environmental- or neighborhood-level trends will not apply to every dog but often present an overall average effect, so keep in mind that there are factors that make your dog unique. Before making any changes in your home, yard, or neighborhood environment, keep in mind that conclusions based on the Dog Aging Project studies cannot sufficiently prove a causal relationship and further studies are needed to understand the mechanisms underlying environmental factors and health outcomes.

Where can I learn more?

XUE D.;COLLINS D.;KAUFFMAN M.;DUNBAR M.;CROWDER K.;SCHWARTZ M.;Dog Aging Project Consortium;RUPLE A.. Big data from small animals: integrating multi-level environmental data into the Dog Aging Project. Scientific & Technical Review. 2023 01 1; 42: pp. 65-74. doi:


Environmental exposures can have large impacts on health outcomes. While many resources have been dedicated to understanding how humans are influenced by the environment, few efforts have been made to study the role of built and natural environmental features on animal health. The Dog Aging Project (DAP) is a longitudinal community science study of aging in companion dogs. Using a combination of owner-reported surveys and secondary sources linked through geocoded coordinates, DAP has captured home, yard, and neighborhood variables for over 40,000 dogs. The DAP environmental data set spans four domains: the physical and built environment; chemical environment and exposures; diet and exercise; and social environment and interactions. By combining biometric data, measures of cognitive function and behavior, and medical records, DAP is attempting to use a big-data approach to transform the understanding of how the surrounding world affects the health of companion dogs. In this paper, the authors describe the data infrastructure developed to integrate and analyze multi-level environmental data that can be used to improve the understanding of canine co-morbidity and aging.