| Literature DB >> 33187259 |
Laura A Reese1, Joshua J Vertalka2, Cassie Richard3.
Abstract
BACKGROUND: Animal cruelty appears to be widespread. Competing theories have been posed regarding the causes of animal cruelty leading to conflicting findings and little direction for public policies to combat it.Entities:
Keywords: animal cruelty; neighborhood disorganization; theories of animal cruelty
Year: 2020 PMID: 33187259 PMCID: PMC7696964 DOI: 10.3390/ani10112095
Source DB: PubMed Journal: Animals (Basel) ISSN: 2076-2615 Impact factor: 2.752
Regression of traits of perpetrator (Female serves as the referent category for gender. Age of perpetrator was collapsed into ordinal categories; there were insufficient incidents for child and adult suspects to calculate regression data) and animal cruelty.
| Variables | Estimate | Std.Error | Probability | Variance Inflation Factor | |
|---|---|---|---|---|---|
| Perp. White | −8.40 | 1.53 | 7.34 | 0.29 | 1.05 |
| Perp. of color | 0.87 | 1.64 | 0.53 | 0.60 | 4.46 |
| Male | −1.85 | 1.91 | −0.97 | 0.34 | 4.46 |
| Teen | −9.26 | 7.65 | −1.21 | 0.24 | 1.00 |
| Constant | 11.25 | 1.53 | 7.34 | 1.39 | |
| Adjusted R2 = 0.02 |
Regression of human relationships/circumstances surrounding cruelty. (A number of variables were removed from the equation due to high VIFs including: location of cruelty; breed of dog other than pit bull designation; abuse caused by police, unknown persons, in the course of a break-in, and neighbors; whether there was a history of abuse or bites for the animal involved; type of animal involved; specific nature of the cruelty; and number of animals involved. Reference categories thus include cruelty not part of domestic violence, cruelty by neighbor, and other dog breeds).
| Variables | Estimate | Std.Error | Probability | VIF | |
|---|---|---|---|---|---|
| With domestic violence | −0.45 | 2.19 | −0.21 | 0.84 | 3.73 |
| Owner is suspect | 2.33 | 1.23 | 1.89 | 0.07 | 2.19 |
| Pit bull | −0.66 | 0.94 | −0.70 | 0.49 | 1.10 |
| Family member is suspect | 1.64 | 0.94 | 0.70 | 0.49 | 2.58 |
| Constant | 7.18 | 1.70 | 4.24 | 0 | |
| Adjusted R2 = 0.17 |
Regression of relationship between socioeconomics of the neighborhood and cruelty (Several demographic variables were removed from the equation due to high VIFs including: median household income, % with a bachelor’s degree, and % with a high school degree.).
| Variables | Estimate | Std.Error | Probability | VIF | |
|---|---|---|---|---|---|
| Rent/income | 0.335 | 0.133 | 2.51 | 0.02 | 2.67 |
| Unemployment | 0.00172 | 0.000828 | 2.08 | 0.05 | 5.39 |
| % in poverty | 2.85 | 7.05 | 0.41 | 0.69 | 1.37 |
| % kids under 5 | 0.00180 | 0.000914 | 1.97 | 0.06 | 3.39 |
| Constant | −13.6 | 4.03 | −3.38 | 0 | |
| Adjusted R2 = 0.81 |
Regression of relationship between physical characteristics of the neighborhood and cruelty (Variables removed from the equation due to high VIF include: bus stops; robbery; assault; land bank properties; liquor stores; parks; childcares; and middle and elementary school buildings).
| Variables | Estimate | Std.Error | Probability | VIF | |
|---|---|---|---|---|---|
| Vacancy | 0.0132 | 0.00532 | 2.48 | 0.02 | 2.95 |
| Blight | 0.206 | 0.101 | 2.05 | 0.05 | 1.24 |
| Murder | 0.00266 | 0.000980 | 2.71 | 0.01 | 3.12 |
| Building Permits | −0.0254 | 0.0109 | −2.33 | 0.03 | 1.31 |
| Green spaces | −0.231 | 9.59 | −2.41 | 0.02 | 1.21 |
| Constant | −0.0725 | 2.11 | −0.34 | 0.73 | |
| Adjusted R2 = 0.72 |
Regression of best fitting model across categories of variables.
| Variables | Estimate | Std.Error | Probability | VIF | |
|---|---|---|---|---|---|
| Vacancy | 9.01 | 6.12 | 1.47 | 0.15 | 4.03 |
| Blight | 2.03 | 9.92 | 2.05 | 0.05 | 1.24 |
| Murder | 2.97 | 9.94 | 2.99 | 0.01 | 3.31 |
| Building Permits | −2.54 | 1.07 | −2.27 | 0.03 | 1.31 |
| Green spaces | −2.02 | 9.70 | −2.08 | 0.05 | 1.28 |
| Owner is suspect | 8.00 | 6.05 | 1.32 | 0.20 | 1.60 |
| Constant | −4.77 | 2.09 | −0.23 | 0.82 | |
| Adjusted R2 = 0.73 |