Access to affordable veterinary care and companion animal support services (such as grooming, behavior training, and companion animal supplies) has become increasingly acknowledged as an obstacle to the health and well-being of companion animals. This study explores whether demographic factors play a role in the lack of access to such companion animal resources. The authors used the city of Detroit as a case study due to its current economic distress and high risks of companion animal abandonment, bites, and rates of cruelty cases — all indicators which show a need for companion animal resources.

The locations of companion animal supply stores and veterinarians were gathered from two sources: ReferenceUSA Historic Business data and Google Maps. This study did not include the four Detroit animal shelters and various nonprofits that provide medical care to local animals. This decision was made because their locations do not reflect decisions made by the private market on where to locate services. This study also did not include grocery stores and chain pharmacies that sell companion animal supplies. 

This survey tested three hypotheses: 

1. Companion animal resources will be located in areas with better economic health.
2. Companion animal resources will be located in areas with more gentrification, as signaled by a higher population of “creative class” residents.
3. Companion animal resources will be located in areas with greater need for animal support services.

Three indexes for the three hypotheses were created by combining a number of variables, a strategy called exploratory factor analysis. EFA is a strategy that reduces complexity by grouping related variables together, making it easier to understand the data. 

The residential economic health index was created by tracking median household income and percentages of residents above the poverty line, employed, not using food stamps, and who are not under 18 years old. The index representing the need for animal support services was created by combining the number of police reports of dog bites and animal cruelty. The third index was created by compiling four variables representing the “creative class”: the population density of young adults aged 20 to 34, the number of college graduates, the proportion of residents who recently relocated from another U.S. county or from abroad, and the number of employees in creative or knowledge-based industries such as business, science, tech, or entertainment.

Correlation Analysis

Pearson correlation measures how strongly two variables are related and whether they increase or decrease together. It gives a value between -1 and 1, where 1 means a perfect positive relationship, -1 means a perfect negative relationship, and 0 means no relationship. The authors performed this analysis with both the independent variables and the indexes they created. 

They found that zip codes with more children, higher populations, percentage of residents on food stamps, and higher unemployment had fewer companion animal stores and vets per capita. Zip codes with a higher per capita income, higher median household income, a higher economic health index, and a higher creative class index had more. Areas with higher rates of dog bites and animal cruelty, which suggests a greater need for supportive services, tended to have fewer companion animal stores and veterinary services. However, this trend was not statistically significant.  Thus, both hypothesis 1 and 2 were supported by the analysis. 

Regression Analysis

Multiple regression is a statistical technique used to examine the relationship between one dependent variable and two or more independent variables. It helps determine how each independent variable influences the dependent variable while accounting for the effects of the others. Unlike the Pearson correlation, multiple regression considers multiple variables simultaneously, assessing the unique contribution of each variable to the outcome while controlling for others. If the effect of one variable overlaps with others (multicollinearity) or if other variables explain the outcome better, the unique contribution of that variable might not be statistically significant. 

The authors conducted a regression analysis with all the variables from the correlation analysis that reached statistical significance. Because of multicollinearity, the indexes for economic health and the creative class were used instead of the component parts. In the regression analysis, the economic health index did not remain significantly correlated — in a reduced model the creative class index and median rents were found to account for 40% of all variation in resources per capita. Through this, they concluded that suppliers of companion animal resources tend to favor more gentrified areas.

Conclusion

The availability of companion animal resources in a city is 40% explained by the creative class index and median rent, with these resources more concentrated in wealthier, gentrifying areas — potentially worsening inequalities. To address this, the authors suggest that governmental investments, such as business incubators that offer affordable rents and support services could be useful. These incubators could help new companion animal stores or veterinary practices establish themselves in underserved areas, with additional support from start-up capital and loan programs. 

In high poverty areas, often lacking animal welfare resources, it’s crucial to increase education and awareness about available support. Nonprofits and advocates play a key role in providing these services, particularly in cities like Detroit, where they offer essential companion animal care, food, rescue and adoption programs, and advocacy for better animal treatment. Food pantries can also carry human and nonhuman animal food together to allow easy access for poor or homeless families with companion animals.