Where Are We on the Animal Welfare Map? Using GIS to Assess Stakeholder Diversity and Inclusion

Inequities exist in all facets of society, and animal welfare organizations (AWOs) and their communities are no exception. These organizations interface with multiple stakeholder groups. An active analysis of stakeholder groups to identify under-served areas and communities has not been performed. Using stakeholder data from Toronto Humane Society (THS) from 2015–2019, this study performed a retrospective spatial analysis to identify well served and under-served geographic areas for adopters, surrenders, public veterinary service (PVS) clients, volunteers and foster parents, using Hot Spot analysis. Correlation analysis was performed to determine whether the spatial distribution of the groups correlated with the four socioeconomic metrics of the 2016 Ontario Marginalization Index (residential instability, material deprivation, dependency, and ethnic concentration), and a metric representing the distribution of Indigenous residents. For each stakeholder group, there were well served areas, typically in central Toronto where THS is located, and under-served areas, typically in the north-west and north-east corners of Toronto and in the surrounding cities of the Greater Toronto Area. The area served by THS PVS extended further north than the other hot spot areas. The number of adopters increased as the residential instability metric increased, whereas the number of adopters decreased as the ethnic concentration metric increased. The rate of surrenders increased as the Indigenous metric increased. Public Veterinary Service clients increased as the residential instability, material deprivation, and Indigenous metrics increased. One of the primary limitations of this study was the confounding factor of distance from THS. Individuals living further from THS are less likely to utilize its services, particularly if there is another accessible AWO nearby, and therefore may appear to reflect an under-served population that may not truly be under-served. A regional approach would help to overcome this limitation. The results provide useful insights into stakeholder engagement and provide a foundation for analysis of more targeted areas, as well as for strategies to reach under-served demographics. Similar analyses by other AWOs would be helpful to address inequities in a larger geographic area. Animal welfare organizations can improve program effectiveness by adding data analytics skills to the more traditional skills associated with this sector.

The Impact of Marginalization on Diffuse Large B-Cell Lymphoma Overall Survival: A Retrospective Cohort Study

Introduction: While health disparities in diffuse large B-cell lymphoma (DLBCL) have been previously noted, literature systematically describing the impact of social determinants of health (SDOH) on DLBCL overall survival (OS) is sparse. Furthermore, existing data largely examine SDOH of health in isolation, not accounting for key covariates or disease-related variables. Marginalization, which accounts for various SDOH, is a process of systemic discrimination and exclusion. Given the paucity of literature to date, we examined how marginalization influences DLBCL OS in the Canadian setting. The objectives of this study were: 1) To describe the impact of marginalization on DLBCL OS and 2) To identify which dimensions of marginalization, if any, impacted OS. Methods: We conducted a population-based retrospective cohort study of adult patients with newly diagnosed DLBCL in Ontario between January 1, 2005 to December 31, 2017 receiving a rituximab-containing chemotherapy regimen for curative intent, followed until March 1, 2020. Our primary exposure of interest was the Ontario Marginalization Index (ON-Marg), an administrative database tool which combines demographic indicators into four distinct marginalization dimensions: residential instability (% renters and % living alone), material deprivation (% low income and % lone parent families), dependency (% seniors and % employment), and ethnic concentration (% recent immigrants and % visible minority). Our primary outcome was 2-year OS, defined as time from the date of first rituximab-based treatment to date of death or completion of follow-up. Survival curves were generated using Kaplan-Meier methods, and Cox regression analyses were used to identify covariates that were independently associated with OS. Our final model adjusted for age (as increments of 10 years), sex, and comorbidity burden as measured by aggregate diagnostic groups (ADGs). Results: A total of 10,344 patients were diagnosed with DLBCL and treated with a rituximab-containing regimen in Ontario between January 1, 2005 and December 31, 2017. The median age was 67 (IQR, 55-75) and 46% were female. Of patients who had staging data (49%), 54% were advanced stage at diagnosis, and the median number of cycles of chemoimmunotherapy received was 6 (4-6). Median number of ADGs was 10 (8-12), indicating a moderate-to-high burden of comorbidities within this cohort, and 13% of patients resided in a rural area. Cohort characteristics and mortality rates per ON-Marg quintile (Q5 = most marginalized) are provided in Table 1. Overall, group characteristics were evenly distributed, except that the most marginalized group had a higher proportion of patients residing in urban settings and nearer to treatment hospitals. Two-year overall survival was 73.2%. After controlling for relevant confounders, material deprivation (hazard ratio [HR] 1.06, 95% confidence interval [CI] 1.02 - 1.10, p=0.003) and ethnic concentration (HR 1.05, 95% CI 1.01 - 1.09, p=0.013) contributed to increased risk of all-cause mortality. Residential instability and dependency had no significant effect. Increasing age (HR 1.29, 95% CI 1.25 - 1.33, p<0.0001) and increasing number of ADGs (HR 1.028, 95% CI 1.025 - 1.031, p<0.0001) were also associated with increased risk of all-cause mortality, while female sex was found to be protective (HR 0.89, 95% CI 0.83 - 0.97, p=0.005). Discussion: To our knowledge, no study has examined the impact of marginalization and collective SDOH on DLBCL outcomes. We found that increased material deprivation and ethnic concentration conferred increased mortality. While Canada's largely single-payer system and previously documented healthy immigrant effect may have been expected to attenuate effects of income and immigration, our study suggests otherwise. Possible explanations may include barriers to healthcare access for patient subsets, who may have less support for treatment. Structural factors such as systemic racism, health literacy, and caregiver burden must also be taken into account. These factors require further evaluation to inform targeted interventions and establish support for increased access to timely care amongst this patient population. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

(Re)conceptualizing Neighborhood Ecology in Social Disorganization Theory: From a Variable-Centered Approach to a Neighborhood-Centered Approach

Shaw and McKay advanced social disorganization theory in the 1930s, kick-starting a large body of research on communities and crime. Studies emphasize individual impacts of poverty, residential instability, and racial/ethnic heterogeneity by examining their independent effects on crime, adopting a variable-centered approach. We use a “neighborhood-centered” approach that considers how structural forces combine into unique constellations that vary across communities, with consequences for crime. Examining neighborhoods in Southern California we: (1) identify neighborhood typologies based on levels of poverty, instability, and heterogeneity; (2) explore how these typologies fit within a disorganization framework and are spatially distributed across the region; and (3) examine how these typologies are differentially associated with crime. Results reveal nine neighborhood types with varying relationships to crime.

1313Is private rental instability bad for mental health?

Background People in the private rental sector move more than people in other tenures. Yet we know little about the consequences for health of this instability. We are the first to use a nationally representative longitudinal survey of Australians (2000-2018) to causally examine mental health effects of residential instability for a low-income working-aged cohort of private renters. Methods Mental health was measured using the SF-36 (MH) and Kessler Psychological Distress scale (K10). We examined effects of 1) cumulative time spent in private rental compared with other sectors (homeowner or social housing), 2) total numbers of transitions, and 3) average numbers of transitions within 5 years, using marginal structural models to account for complex confounding of tenure, socio-economic position, and mental health over time. Results The mental health of private renters was similar to homeowners at initial occupancy but became worse after one to five years. The more moves private renters made, the worse their mental health, with people who had >five moves in total reporting a -3.77-point (95%CI -6.79; -0.75) difference on MH and -3.84-point difference (95%CI -7.61; -0.07) on K10 (rescaled). If numbers of moves were small, the mental health of private tenants was better than social tenants. When moves were frequent, however, their mental health scores became similar. Conclusions Residential instability negatively affects mental health. Frequent moves in private rental worsen tenants’ mental health compared to owners. Key messages Reducing housing instability in lower-income households in private rental with greater protection from forced moves will increase resident’s wellbeing.

Neighborhood Change and Residential Instability in Oakland

Affordable housing is critical to ensuring healthy and resilient communities and broad access to economic opportunity. In this report, we examine neighborhood change and residential instability in the City of Oakland over the past two decades. We employ multiple data sources, including individual-level data from the Federal Reserve Bank of New York Consumer Credit Panel/Equifax data. We analyze historical and contemporary data to understand patterns of residential instability, and we identify which residents and areas are most likely to experience heightened challenges in the context of the COVID-19 pandemic. Our results show that lower-SES residents experience residential instability in different ways in different parts of Oakland, suggesting the need for more geographically targeted strategies that focus on stabilizing lower-SES residents and address the multiple ways in which lower-SES residents navigate limited affordable housing.

Exploring the Relationship Between Human Social Deprivation and Animal Surrender to Shelters in British Columbia, Canada

Previous studies identify owner-related issues, such as cost and housing, as common reasons for relinquishment of companion animals to animal shelters. It is likely that the burden of surrendering for owner-related reasons falls on those who are socially vulnerable (e.g., low income, unemployed); however, very few studies have assessed social determinants as a predictor of animal relinquishment. The present study used the Canadian Index of Multiple Deprivation (CIMD), which uses four factors of social vulnerability (Ethnocultural Composition, Economic Dependency, Residential Instability, and Situational Vulnerability) to predict risk of surrender for various reasons, of various species and breeds, and of various health statuses across British Columbia, Canada (n = 29,236). We found that CIMD factors predicted increased risk of surrender across many shelter variables. For further understanding of differences between areas in the province, the present study also analyzed the relationship between CIMD factors and animal surrender variables in two areas of interest: Metro Vancouver (n = 3,445) and Kamloops (n = 2,665), and plotted these relationships on a geospatial scale. We found that there were some similarities across areas, such as Situational Vulnerability predicting increased odds of surrendering pit bull-labeled dogs vs. all other dog breeds. There were also differences in predictors of animal surrender variables, suggesting that provision of animal services, such as veterinary care, for vulnerable groups may be specific to location. For example, whereas Ethnocultural Composition predicted increased risk of owner surrender for multiple owner-related reasons in Metro Vancouver, these same reasons for surrender were predicted by Residential Instability in Kamloops, indicating demographic differences that affect animal shelter service use. The results of this research validate the use of geospatial analysis to understand relationships between human vulnerability and animal welfare, but also highlight the need for further interventions in marginalized populations to increase retention of animals.

Examining how changes in provincial policy on vape marketing impacted the distribution of vaping advertisements near secondary schools in London, Ontario

Objectives On January 1, 2020, the Government of Ontario passed a regulation banning vaping advertisements by retailers, apart from specialty shops. A motivation for this ban was to limit youth exposure to vaping advertisements. The primary goal of this research was to evaluate the impact of this ban on the number and density of vaping advertisements surrounding secondary schools. Additionally, we examined whether the number of vaping advertisements varied by school socio-demographic characteristics. Methods This study used a pre-post design. Audits were conducted December 2019 (pre-ban) and again January to February 2020 (post-ban), to identify vaping advertisements within 800 m surrounding secondary schools (n = 18) in London, Ontario. Results Prior to the ban, there were 266 vaping advertisements within 800 m of secondary schools. After the ban, this was reduced to 58, a 78.2% reduction. The mean number of vaping advertisements surrounding schools significantly decreased from 18.1 before the ban to 3.6 after the ban (p < 0.001). A significant positive correlation was found, prior to the ban, between the number of vaping advertisements surrounding schools and school-level residential instability (r = 0.42, p = 0.02). After the ban, no significant correlations were found between the number of vaping advertisements and school socio-demographic characteristics. Conclusion The provincial ban of vaping advertisements in select retail settings significantly reduced the number of vaping advertisements in the areas surrounding secondary schools in London, Ontario. The ban also reduced socio-demographic inequities in youths’ potential exposure to marketing of vaping products. Continued monitoring of the geographic accessibility and promotion of vaping products is warranted.