Exploratory GIS Analysis of

Vulnerable Populations at Risk of Homelessness in Calgary

Report for Calgary Homeless Foundation

15th November 2009

Compiled by Chantal Hansen, MGIS Department of Community Health Sciences

Faculty of Medicine University of Calgary

Heritage Medical Research Building 3330 Hospital Drive NW

Calgary, Alberta CANADA T2N 4N1

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Table of Contents

1.0 Introduction……………………………………………………………………………...... 3

2.0 Geographic Information Systems…………………………………………...………….. 3

3.0 Vulnerable Populations At-risk of Homelessness………………………………….…. 4

4.0 Data………………………………………………………………………………………... 5

4.1 Data Sources…………………………………………………………………….. 5

4.2 Summary Statistics for Calgary…………………………………............…….. 5

5.0 Citywide Thematic Maps……………………………………………………….…….…..6

6.0 Homelessness Risk Modeling……………………………………………………...…… 19

6.1 Defining At-Risk Communities…………………………………………..……... 19

6.2 Modeling Homelessness Vulnerability by Community District……..…..…... 20

7.0 Limitations…………………………………………………………………..…………..… 26

8.0 Next Steps…………………………………………………………………..………..……26

9.0 References…………………………………………………………………………………27

10.0 Acknowledgements……………………………….………………………………….…27

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1.0 Introduction The Calgary Homeless Foundation (CHF) has initiated the use of Geographical Information Systems (GIS) to map the socio-economic characteristics of Calgary’s neighbourhoods and explore GIS functionality to generate community-level risk models for homelessness vulnerability. Data from a variety of sources (Statistics Canada, Alberta Government's Homeless and Eviction Prevention (HEP) Fund, Canada Mortgage and Housing Corporation) are thematically mapped for three primary purposes: to provide specific information about particular communities; to see geographical patterns of social phenomena; and to compare patterns on two or more maps.

A GIS is then used to objectively measure those characteristics of the social environment that may be associated with increased risk of homelessness. A Homelessness Risk Index is derived and used as a tool for identifying and prioritizing Calgary communities with vulnerable populations that would need special attention at the neighbourhood level. The intent of this project is to use GIS-based analysis and localized data to contribute to the discussion of risk factors, predictors and pathways in and out of homelessness. This knowledge is important to CHF policy and practice and may also contribute to homelessness prevention theory. 2.0 Geographic Information Systems GIS are computer-based decision support systems that link geographic information with descriptive information (Longley et al., 2005). GIS provide a technology and methodology to explore and analyze spatial data, or information about the earth, its people and the spaces within which they move. Recognising this ‘context’ (setting or environment) means people can be linked to place - and this means the ‘where’ that is critical to an event, behaviour or phenomena, may be identified. Often the ‘why’ depends on the ‘where’. Most social issues facing the world today exist in a geographic context and any analysis must consider that. In recent years, the use of GIS by social analysts has expanded rapidly, driven by the growing realization that: The majority of social data have a spatial component; Graphical representations, particularly maps, are extremely informative to various

aspects of social research; and There is value in associating social data with other data (e.g. health data,

environmental data, etc). Conducting research through a geographic lens provides a holistic view and a framework for a better understanding of people, events and processes being studied.

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3.0 Vulnerable Populations At-risk of Homelessness For a comprehensive literature review of homelessness, please refer to “Risks and Assets for Homelessness Prevention - A Literature Review for The Calgary Homeless Foundation”. Homelessness vulnerability at the community level is multifaceted and depends on many factors including demographic characteristics of the population, characteristics of the local economy, and characteristics of the local health care system. Identifying where vulnerable populations might be at-risk for homelessness shares with studies of neighbourhood poverty, deprivation sensitivity and housing affordability. “According to Bramley (1988: 24) ‘there is no single, simple definition of homelessness, but rather a range of definitions including partially overlapping approaches and categories…and we cannot assume that everyone agrees about the definition of homelessness’. Homelessness can be seen as ‘the end state of a long and complex social process and personal process…[t]he culmination of a long process of economic hardship, isolation, and social dislocation’ (Wolch et al. 1988: 443). Households with low incomes must spend excessive amounts of their income for housing making them less able to weather difficult financial circumstances caused by family break-up, injury, illness or loss of employment, leaving them at-risk for homelessness (Ringheim, 1990). Households that find themselves in this situation may also experience ‘shelter poverty’ where consumption of other non-shelter necessities is limited in order to pay the rent (Stone 1993). In this context, at-risk homelessness refers not to those already homeless, but to those who are precariously housed (i.e. living in substandard housing, doubled-up, or paying excessive rent-to-income ratios) (Bunting et al. 2004). At-risk areas are defined as locations where concentrated poverty, deprivation and housing need intersect.” (Fiedler, et al., 2006). For GIS purposes, the above dimensions (poverty, deprivation, and housing need) describing these vulnerable populations can be extracted from census data: specific variables or ‘indicators’ are collated to represent one of the above dimensions. Census data remains one of the few comprehensive sources of ‘mappable’ statistics. Here, we utilise Statistics Canada 2006 Census – Calgary Community Districts database to identify and examine the spatial dimensions of communities with vulnerable populations at risk of homelessness in Calgary.

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4.0 Data The analytical power of GIS comes from its ability to overlay and match different datasets for the same geographic area, which enables us to visualize the interactions among the different data. Here, we are able to relate social, economic and housing data.

4.1 Data Sources The information retrieved by querying the GIS database serves as inputs for the risk assessment models. The following datasets were used to generate a geo-database for Calgary. Source Dataset

Category Layer Description Date

University of Calgary

Boundary File Digital Data2006 Calgary Community Districts

2006

Statistics Canada Census File 2006 Census for Calgary Community Districts

2006

Canada Mortgage and Housing

Ratio Rent/Income File

Renters spending >30% income on shelter

2006

Homeless and Eviction Prevention Fund

Rental Assistance Cheque Counts

Total number of rent Assistance cheques by FSA

2008

4.2 Summary Statistics for Calgary - 2006

Total Population: 988,193 Private dwellings occupied by usual residents: 384,723 All renter households: 104, 040 Median age of the population: 35.7 Unemployment rate: 4.1 Median income in 2005 - All private households: $67,238 65% of median household income: $43, 705 Average monthly payments for rented dwellings: $825 Renter households that are overspending on shelter: 38,610 The goal of this project is to identify Calgary neighbourhoods with vulnerable populations at risk of homelessness. The desired final product is a neighbourhood-level map that identifies communities for homelessness prevention strategies and services.

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5.0 Citywide Thematic Maps In order to identify communities with vulnerable populations at risk for homelessness, we first mapped selected socio-economic variables citywide. Previous research has shown an association with certain demographic and housing characteristics and homelessness. Some of these characteristics include: income, unemployment rates, high housing cost burden, concentration of immigrants, and concentrations of lone parent households. There is no direct correlation between these variables and homelessness. However, it is understood that should some crisis occur that puts a strain on household income - such as family breakdown, illness, job loss, or a significant increase in rent - these households would be disproportionally affected. The following selected variables from the 2006 Census of Calgary are displayed as thematic maps:

Figure 1. City of Calgary Community Districts Reference Map Figure 2. Median Household Income Figure 3. Prevalence of Low Income Figure 4. 24 years+ Unemployment Rate Figure 5. Visible Minorities by Knowledge of Official Languages Figure 6. Lone Parent Families Figure 7. No High School Education Figure 8. % Government Transfer Payments Figure 9. Housing Tenure: Rented Figure 10. Rent to Income Ratio Figure 11. Tenant-occupied households spending 30% or more of household income on gross rent Figure 12. Number of Rent Assistance Cheques 2008

Here, GIS is primarily used as a visualization tool: it readily provides a holistic picture of selected population characteristics and provides a reference point for finer analyses.

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Figure 1. City of Calgary Community Districts Reference Map

This reference map contains the names of Calgary’s community districts. Some newer neighbourhoods will not have any data as there was very little population in these neighbourhoods at the time of the census (2006). Information on these areas will not be available until after the 2011 update.

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Figure 2. Median Household Income

Median income is a more accurate indicator than the average household income as it is not dramatically affected by unusually high or low values. Median income divides the income distribution range in half, one with households having incomes above the median, and the other with households having incomes below the median.

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Figure 3. Prevalence of Low Income

The prevalence of low income before tax is the proportion or percentage of persons not in economic families in a given classification below the before tax low income cut-offs. These prevalence rates are calculated from unrounded estimates of persons not in economic families 15 years of age and over.

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Figure 4. Total Population 24yrs+: Unemployment Rate

The unemployment rate for the total population 24 years and over is the unemployed in that group, expressed as a percentage of the labour force in that group, in the week prior to enumeration.

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Figure 5. Knowledge of Official Languages

Refers to the ability to conduct a conversation in English only, in French only, in both English and French, or in neither English nor French. This is an attempt to capture visible minority immigrants.

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Figure 6. Lone Parent Families

Refers to a lone parent of any marital status, with at least one child living in the same dwelling. Percentage calculated from total number of census families in private households.

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Figure 7. No Post Secondary Education

All certificates, diplomas and degrees are reported. There is an implied hierarchy in this variable (secondary school graduation, registered apprenticeship and trades, college, university) which is loosely tied to the 'in-class' duration of the various types of education.

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Figure 8. Percent Government Transfer Payments

Refers to total income from all transfer payments received from federal, provincial, territorial or municipal government: summed from the Old Age Security; Guaranteed Income Supplement; Survivor Allowance; Canada or Quebec Pension Plan; Employment Insurance; Child benefits; other income from government sources.

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Figure 9. Percent of occupied private dwellings by housing tenure: Rented

A dwelling is classified as 'rented' even if it is provided without cash rent or at a reduced rent, or if the dwelling is part of a cooperative. For census purposes, in a cooperative, all members jointly own the cooperative and occupy their dwelling units under a lease agreement.

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Figure 10. Rent to Income Ratio

A key measure of housing affordability is the rent-to-income ratio, defined as the ratio of the median annual rent of a dwelling unit and the median household income of renters. While these variables are not available to CHF, average gross rent and median income of private household ratio provide a picture of housing affordability here.

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Figure 11. Percent of tenant-occupied households spending 30% or more of

household income on gross rent The Canadian Housing and Mortgage Corporation states affordability as the cost of adequate shelter not exceed 30% of household income. Shelter related expenses include the monthly rent and the costs of electricity, heat, municipal services, etc.

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Figure 12. Number of Rent Assistance Cheques Provided during 2008

The Alberta Government’s Homeless & Eviction Prevention Fund provides transitional assistance to prevent homelessness and to help households obtain and maintain suitable accommodations. This data is aggregated by Forward Sortation Area (FSA) and the Calgary Community District file is overlaid for context.

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6.0 Homelessness Risk Modeling As discussed earlier, considerable research has identified risk factors associated with becoming homeless in Canada. The maps of these associated variables presented above have raised some interesting questions regarding factors associated with homelessness, and thus enabled the CHF to take a more focused approach with risk modeling. We present a method for identification of areas where vulnerable populations are at-risk for homelessness using census data that identifies where concentrated poverty, deprivation and housing need intersect. This methodology draws on the GIS techniques presented in the City of Calgary’s Indices of Community Well-Being for Calgary Community Districts and the Deprivation Index for Health and Welfare Planning in Quebec.

6.1 Defining At-Risk Communities: Poverty, Deprivation and Housing Issues

Poverty, deprivation and housing issues are identified at the community district level using approaches developed for existing studies conducted using aggregate data. These three dimensions, poverty, deprivation and housing issues and the indicators that comprise them are constructed for the following reasons: their relation to homelessness issues; their association with vulnerable populations; and their availability by community district level in the Canadian census data.

Poverty Index An important aspect of community well-being is the equitable distribution of resources and the ability of individuals and families to meet their basic needs. Communities with large numbers of individuals with low-incomes may exercise less economic influence and have a lower capacity to garner resources for collective goods or for local economic development. Further, individuals and families with low-incomes may experience greater risk to their physical and mental well-being. The census indicator for poverty utilised here is:

1. Prevalence of low-income households.

Deprivation Index Deprivation measures identify those who experience both material and social disadvantage compared to others in their community. Material disadvantage reflects income, education and employment, while social disadvantage mainly refers to marital status and whether the individual lives alone or in a single-parent family. The census indicators utilised here are:

Material disadvantage 1. 24yrs+ unemployment rate, 2. Percentage non-high school graduates, and 3. Percentage of income from government transfer payments.

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Social disadvantage 4. Percentage of lone-parent families, 5. Visible minorities by knowledge of official languages.

Housing Issues Index A useful measure of housing affordability is the percentage of an individual’s income that is devoted to paying for shelter. For housing to be affordable, the Canada Mortgage and Housing Corporation has defined that a household should not spend more than 30% of its gross income on rental shelter costs. In Calgary, 34% of renters are overspending on shelter. Highest priority for affordable housing are ‘core needs households’ that spend more than 50% of their income on shelter costs. These households are deemed to be living in unaffordable circumstances and therefore at risk. While this specific census variable is not available to CHF, average gross rent and median income of private household ratio provide a picture of housing affordability with a similar context. In addition, tenants may experience greater financial stress as rent affordability problems are less easily solved for renters than owners. Whereas owners may solve affordability problems by selling their home or otherwise utilizing their home equity, similar financial resources are not available to tenants. The selected census indicators of housing affordability utilised here:

1. Rent to Income Ratio 2. Tenure: Rented

Aside from the several variables that comprise the Deprivation Index and Housing Index, a number of potentially relevant variables were excluded from the Index constructions. For example, demographic variables, such as ethnicity (that is, recent immigrants or Aboriginal Peoples) age (older than 65) and social/cultural variables, (such as people living alone), were not considered here.

6.2 Modeling Homelessness Risk by Community District An overall Homelessness Risk Index consisting of three risk dimensions (poverty, deprivation and housing need) is used to identify the communities in Calgary with vulnerable populations at risk of homelessness at the community district level. Risk/Community is evaluated based on the following methodology: The additive approach, with equal weighting, is used to create an overall risk index to identify neighbourhoods with vulnerable populations at risk of homelessness. In general, to transform a raw variable, χ , into a unit-free index between 0 and 1 (which allows different indices to be added together), the following formula is used:

( )( ) ( )χ minχ max

χ min χ indexχ

−−

=−

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where ( )χ min and ( )χ max are the lowest and highest values the variable x can attain, respectively. The Homelessness Risk Index (HRI) then represents the average of the following three dimensions: Poverty, deprivation and housing affordability. Index of Poverty IP = Prevalence of Low Income/Maximum Prevalence Index of Deprivation IDU

= 24+ Unemployment Rate/Maximum Unemployment Rate IDLP = Percentage of Lone Parents/ Maximum percent of Lone Parents IDNHS = Percentage of People with No High School Certificate/Maximum percent with no High School Certificate IDGTP = Government Transfer Payments Percentage /Maximum percent of Government Transfer Payments IDVM = Percentage of Visible Minorities/ Maximum percent of Visible Minorities Index of Housing Issues IHRI

= Rent/Income Ratio IHR

= Percentage of Renters/Maximum percent of Renters Thus, the Homeless Risk Index for Calgary Community Districts is calculated:

HRI = (IP + ((IDU + IDLP + IDNHS + IDGTP + IDVM)/5) + ((IHRI + IHR)/2)) 3 Once the Homelessness Risk Index is calculated, communities are then ordered from lowest rank score to highest; the higher the score, the higher the need in the community. Each dimension is mapped and vulnerable areas are defined as locations where concentrated poverty, deprivation and housing need intersect. The following indices are displayed as thematic maps:

Figure 13. Index of Poverty Figure 14. Index of Deprivation Figure 15. Index of Housing Issues Figure 16. Index of Homelessness Risk

Here, GIS is primarily used as a modeling tool: new information is generated by combining disparate datasets and condensing a number of variables into a single variable for risk assessment purposes. These GIS derived measures can then be used to report need at the neighbourhood level.

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Figure 13. Index of Poverty

The above map is a spatial representation of poverty in Calgary. The top ten communities with the highest poverty indices are highlighted. As more specific data becomes available to the CHF, the construction of this poverty index can be refined.

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Figure 14. Index of Deprivation

The above map is a spatial representation of deprivation in Calgary. The top ten communities with the highest deprivation indices are highlighted. As more specific data becomes available to the CHF, the construction of this deprivation index can be refined.

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Figure 15. Index of Housing Issues

The above map is a spatial representation of housing need in Calgary. The top ten communities with the greatest housing needs are highlighted. As more specific data becomes available to the CHF, the construction of this housing index can be refined.

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Figure 16. Index of Homelessness Risk

This Homelessness Risk Index for Calgary is drawn from Poverty, Deprivation and Housing Issues Indices. This index can simplify the task of measuring population needs in order to allocate resources among local communities. When available to the CHF, other health/crime/social variables should be considered in the HRI construction.

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7.0 Limitations The methodology employed in this report is subject to several limitations: 1. Aside from the 5 variables that comprise the material and social components of the Deprivation Index, a number of potentially relevant variables were excluded from the Index. For example, demographic variables, such as ethnicity (recent immigrants, Aboriginal Peoples, etc). At this stage, health and crime variables are not available to the CHF. These would add to the construction of the Index. 2. Communities with missing census variables were not excluded from the final Homelessness Risk Index calculations. 3. These measures of risk tend to reveal similar results using more coarsely aggregated data, but produce quite different results using finer areal units. Social area analyses based on census tracts often provide too aggregate a picture of social difference to discern many of the social changes occurring in Canadian cities. 8.0 Next Steps The GIS derived Homelessness Risk Index can be used to analyse patterns of deprivation, identify areas that would benefit from special initiatives or programmes and as a tool to determine eligibility for specific funding streams. Future work could encompass: 1. Dissemination Area (DA) level census datasets. 2. To better represent the spatial variation of these socioeconomic phenomena cartographically, a dasymetric mapping approach could be used. 3. Finer/Specific variables: 65yo and still in labour market (unemployment rate) Racialised populations 50% income spent on shelter Health variables: mental health Crime variables: property and person crimes

We must emphasize the exploratory nature of this GIS report. Our results are based on a snapshot in time and the provision of free, community district census data for the city of Calgary.

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9.0 References

1. Bramley, G. 1988. The Definition and Measurement of Homelessness. In G. Bramley, K. Doogan, P. Leather, A. Murie and E. Watson (eds.), Homelessness and the London Housing Market. Bristol: SAUS, University of Bristol.

2. Bunting, T., A. Walks and P. Filion. 2004. The uneven geography of housing

affordability stress in Canadian metropolitan areas. Housing Studies 19(3): 361-93.

3. Cook, D. and Te Linde, J. 2009. The Indices of Community Well-Being for

Calgary Community Districts: A Neighborhood-Based Approach to Quality of Life Reporting. Community Quality-of-Life Indicators: Best Cases III, Volume 1

4. Longley, Paul A., Goodchild, Michael F., Maguire, David J., and David W. Rhind.

2005. Geographic Information Systems and Science, 2nd ed., John Wiley and Sons, Toronto.

5. Pampalon, R. and Raymond, G. “A Deprivation Index for Health and Welfare

Planning in Quebec,” Chronic Diseases in Canada 21, 3 (2000): pp. 104–113. 6. Ringheim, K. 1990. At Risk of Homelessness: the Roles of Income and Rent.

New York: Praeger Publishers. 7. Stone, M. 1993. Shelter Poverty: New Ideas on Housing Affordability.

Philadelphia: Temple University Press.

8. Wolch, J. R., M. J. Dear and A. Akita. 1988. Explaining Homelessness. Journal of American Planning Association 54: 443-53.

10.0 Acknowledgements This project has benefited from the generous contributions of time and advice from the following people: Professor J.C. Herbert Emery, Department of Economics, University of Calgary. Alina Tanasescu, Director, Research & Public Policy, Calgary Homeless Foundation. Derek Cook, Research Social Planner, City of Calgary.