Social Support,Depression and Self-Reported Physical Health in Persons Waiting for Access to Subsidized Housing

Abstract

Housing is a pervasive determinant of physical and mental health. Studies indicate the importance of social support to the mental and physical health of individuals who are unhoused; however, to date, little is known about this relationship in persons who are housed in unaffordable accommodations. As the demand for subsidized housing continues to increase far beyond sustainable levels in many countries, investigations of the implications of social support on the health and wellbeing of those waiting for access to subsidized accommodations becomes important to generate evidence-based policy responses. Using data from the NB Housing Study, this paper presents an analysis of the relationships between perceived social support, depression, and self-reported physical health in individuals who wait for access to subsidized housing in New Brunswick, Canada (n = 271). Hierarchical linear regression of Oslo Social Support Scale (OSSS-3) scores on Centre for Epidemiologic Studies Depression Scale 10 (CES-D-10) scores and of OSSS-3 scores on self-reported physical health scores finds increases in social support are associated with decreased depression (F [1, 260] = 26.34, p < .001, R² = .32) and greater physical health (F [1, 260] = 7.62, p = .006, R² = .15). The findings indicate a need to focus on health interventions that improve mental and physical health alongside social support. Implications for programming, policy, and future research are discussed.

Plain language summary

Subsidized Housing, Social Support and Health

Housing is a pervasive determinant of health. Studies find that social support impacts the mental and physical health of individuals who are unhoused; however, little is known about this relationship in persons who are housed in unaffordable accommodations. As housing crises persist in many countries, investigations of the implications of social support on the health of those waiting for access to government subsidized accommodations is important to generate evidence-based policy responses. Using data from the NB Housing Study, we analyze the relationships between perceived social support, depression, and self-reported physical health in individuals who wait for access to subsidized housing in New Brunswick, Canada. Our analyses indicate that individuals with higher social support report greater health and decreased depression. This indicates a need to focus on interventions that improve mental and physical health alongside social support, income support, and access to housing.

Keywords

subsidized housing housing affordability depression perceived social support housing inequity

Introduction

The World Bank forecasts that 1.6 billion people will experience challenges related to housing affordability and availability by 2025 (Triveno & Nielson, 2021). Housing is a highly influential determinant of self-reported physical (Balaj et al., 2017; Dunn, 2002; Dweik et al., 2022; Slopen et al., 2018; Stahre et al., 2015; L. A. Taylor, 2018) and mental health (Alegría et al., 2018; Allen et al., 2014; Baker et al., 2020; Dweik & Woodhall-Melnik, 2023). Although research affirms the downstream importance of housing to health outcomes, responses to the current housing crisis do not meet population needs in most countries (Aalbers, 2016; Fields & Hodkinson, 2018; Potts, 2020). Many wealthy nations offer subsidized housing as a mechanism to reduce affordability pressures; however, the demand for subsidized housing far exceeds availability in many jurisdictions (Carder et al., 2018; Suttor, 2016). Waitlists for access to publicly subsidized accommodations have grown beyond sustainable levels in many regions, which indicates heightened demand for the scarce resource of affordable housing. In 2018, 63% of individuals on waitlists for social housing in Canada had been waiting for subsidized housing for over 2 years (Statistics Canada, 2018). This is problematic, as underinvestment in affordable housing results in a chronic shortage of housing options for those in need, which leads to substantial growth in wait times and the heightened inability of the public sector to respond to housing need (Suttor, 2016).

Despite growth in waitlists and wait times for subsidized housing, we have little information about the health and social needs of individuals and households who are waiting for access to subsidized housing (Koppelman, 2018). Although individuals and households that experience homelessness comprise a segment of affordable housing waitlists in Canada, a substantial portion of households waiting for subsidized housing are living in unaffordable, inadequate, and/or unsuitable accommodations. Research on this population is limited and unhoused populations may experience significantly different social contexts with divergent exposures to trauma and structural barriers from those who are waiting for subsidized housing (Sippel et al., 2015).

This manuscript investigates the relationships between social support, depression, and self-reported physical health in subsidized housing applicants in New Brunswick, Canada. In doing so, the authors begin with a review of literature on social support and housing as social determinants of health and discuss the importance of both to health and mental health outcomes. This manuscript begins by defining social support and then discusses theories that exist to test the impacts of social support on health within populations that experience material disadvantage.

Background

Definitions and Measurements of Social Support

Social support is presented in the loosely defined field of poverty studies as an important, yet underexplored, non-material resource for individuals who experience economic disadvantage (Böhnke, 2008; Mood & Jonsson, 2016). The concept of social support generally refers to the psychosocial assistance (e.g., emotional, informational, instrumental) received from contacts and interpersonal networks (Gariepy et al., 2016; Kocalevent et al., 2018). It also refers to the perception and experience of being cared for and respected within an affirming social network (S. E. Taylor, 2011). Hence, social support can be operationalized to measure self-reports of received support or of the feeling that one is supported. This has resulted in diverse operationalizations of the concept itself (P. Williams et al., 2004).

The debate on the operationalization of the multifaceted concept of social support is not new (Hupcey, 1998a, 1998b; P. Williams et al., 2004). P. Williams et al.’s (2004) review of social support grapples with inconsistency in conceptualization and operationalization of the concept. They note:

Rather than clarifying the definition of social support, the academic literature revealed a fractured and confused concept. In particular, definitions of social support were many and varied. Their use seemed inconsistent, and definitional constructs bore little direct relevance to the contexts in which they were used for research and intervention studies (P. Williams et al., 2004: 493).

They ultimately argue for a context-dependent definition of social support that is useful for the development of the understanding of social support within a population of interest (P. Williams et al., 2004). To complicate this further, researchers often debate the utility of perceived versus received social support in research studies (Feeney & Collins, 2015; Haber et al., 2007; Uchino, 2009) . Perceived social support allows researchers to relate one’s view that they are supported or unsupported by interpersonal networks to outcomes, whereas assessments of received social support collect information on relationships and allow for an understanding of the mechanisms through which relationships contribute to wellbeing (Feeney & Collins, 2015). As social support has yet to be assessed in the present study’s population, the authors explore perceived social support to establish a baseline for future inquiry. Further, they heed P. Williams et al.’s (2004) advice and consider the context of the lives of those waiting for access to subsidized housing to determine a measure of social support. The following subsections provide background on theoretical approaches to assessing the impacts of social support on health and wellbeing.

Approaches to Understanding Social Support in Populations that Experience Poverty and Poor Health Outcomes

There is general consensus in the social sciences that social support serves a function and most recognize the importance of one’s social networks to wellbeing. However, the extent and ways in which social support contributes to improved life outcomes in individuals that experience poverty is of continued debate. Through an exploration of social support and poverty in European countries with different social welfare regimes, Böhnke (2008) questions whether social support—as a non-monetary resource—is bolstered or threatened by insufficient monetary resources. They ultimately find that social support is important to wellbeing, but that the extent to which this relationship exists is mediated by states’ welfare regimes and social norms surrounding relational support. The notion that social support may increase economic capital harkens to the work of famous Sociologist Pierre Bourdieu (1983) who argues that social support is a form of social capital which can be leveraged to generate economic capital. However, this is contextualized within social fields, wherein access to resources varies and dominant ideology, shaped by social, economic and political classes with power, often prevails (Bourdieu, 1979, 1987). Hence, individuals who live in societies that are more collective and view poverty as more systemic than individual are more likely to benefit from social support.

The utility of social support as a mechanism for promoting health and wellbeing in those who experience poverty is generally presented using two contradictory explanations (Böhnke, 2008). The thesis of compensation dictates that material disadvantage produces social solidarity, which in turn generates highly supportive social networks that are capable of sharing resources (e.g., housing, food, money, childcare, etc.) to those in need (Böhnke, 2008; Cobb, 1976; Feeney & Collins, 2015). The other approach to social support, which Böhnke (2008) deems the thesis of accumulation, postulates that social support largely functions through exchange, reciprocity and mutual aid (Böhnke, 2008; Bruhn & Philips, 1984; Pierce et al., 1996). In this view, those who experience poverty lack the resources necessary to fully participate in mutual exchange or may experience shame or stigma related to their economic circumstances (Lubbers et al., 2020), which produces social withdrawal and challenges with reciprocating support (Böhnke, 2008; Eckhard, 2018). In the second thesis, largely constructed using Bourdieu’s (1983) assertion that social networks demand care for preservation, social support becomes a function of familial networks (Böhnke, 2008; Mood & Jonsson, 2016), which is highly problematic for individuals with weak familial ties or who experience intergenerational poverty. Accumulation sits in direct opposition to the stipulation that social support serves a protective function against stress attributed to poverty.

The theses of accumulation and compensation both present social support as an indicator of advantage and disadvantage that independently impacts health and wellbeing. However, this relationship becomes more complex when other factors are taken into account. Social support operates in conjunction with a variety of social determinants of health to contribute to health outcomes. Disadvantage in several areas of economic and social life (e.g., work, education, housing, income, etc.) tends to result in poorer population health outcomes (Raphael, 2009; D. R. Williams et al., 2012). Dahlgren and Whitehead’s (2021) well-cited rainbow model of the social determinants of health presents five layers of factors that contribute to health outcomes. Herein, social and community networks are broadly presented underneath larger societal structures and socioeconomic conditions as contributors to health. This fits well with a Bourdieuian understanding that one’s ability to leverage social support to generate capital is highly dependent on social context. This rainbow model illustrates a practical depiction of social and community networks that allow researchers and practitioners to realize what “they can do in their own sector to influence the health of the population that they serve” (Dahlgren & Whitehead, 2021, p. 21). Within the context of the current iteration of housing crisis in Canada, establishing better understandings of factors that can protect or promote good health and operate under the context of larger social structures and socioeconomic conditions presents as a beneficial first step toward the generation of non-housing interventions that may improve health and wellbeing.

Social support is described as one of the most reliable predictors of disease (Uchino et al., 2018a) that operates within socioeconomic conditions as a contributor to health outcomes (Dahlgren & Whitehead, 2021). Research corroborates the relationships between social support and self-reported physical health and depression (Gadalla, 2009; Johnson & Winter, 2023; Marroquín, 2011; Uchino et al., 2018b). However, these relationships may vary by gender (Chambers et al., 2014; Gadalla, 2009; Lee & Dik, 2017; Szkody & McKinney, 2020) and marital status (Karimy et al., 2018; Mohebi et al., 2018; Nicolini et al., 2021). In their study of young adult college students, Lee and Dik (2017) conclude that gender moderates the effects between positive friendships and health, with stronger associations with self-reported physical health in women, and stronger associations with depression in men. This may be explained by differences in the utility of friendships, with women reporting greater social and emotional benefits and men reporting greater functional benefits associated with friendships (Morrison, 2009).

High levels of social support are beneficial to both physical and mental health (S. E. Taylor, 2011), yet the contribution of nuanced social positions (e.g., lengthy membership on a waitlist to access subsidized housing) to the relationship between social support and health outcomes are significantly understudied (Cohen & Janicki-Deverts, 2009; Dweik & Woodhall-Melnik, 2023; Gariepy et al., 2016; Thoits, 2011). This indicates a need to further understand social support as a contributor to health outcomes in varied contexts, wherein individuals experience different forms of disadvantage, such as housing unaffordability.

Housing Status and Social Support

Access to affordable housing is discussed as one form of socioeconomic advantage (Sánchez, 2017). However, the systematic understanding of the relationship between social support and health outcomes in individuals who lack affordable housing is limited. There is a paucity of research on those waiting for access to subsidized housing and social support. Singh et al.’s (2020) analysis of the Housing, Income and Labour Dynamics in Australia (HILDA) survey data finds a significant cumulative impact of financial hardship and social support on the mental health of persons who are housed in unaffordable accommodations. They note that financial hardship has a larger impact on mental health than social support; however, both contribute to mental health in persons whose housing is not affordable in Australia. However, to the present authors’ knowledge, no evidence exists that confirms or disputes this relationship in other countries, including Canada.

Rather, the use of social support is largely confined to the field of housing studies in works that focus on populations that experience homelessness (Chassman et al., 2023; Hwang et al., 2009; Irwin et al., 2008). Such studies find strong relationships between social support and health (Chambers et al., 2014; Durbin et al., 2019; Hwang et al., 2009; Johnstone et al., 2016) and often focus on specific populations, such as individuals who experience chronic homelessness and severe and persistent mental illness (Durbin et al., 2019; Hwang et al., 2009), youth (de la Haye et al., 2012; Tyler et al., 2018; Unger et al., 1998), and those who are discharged from institutions into homelessness (Chambers et al., 2013; Wang et al., 2021). In their longitudinal study of individuals who experience homelessness, Calsyn and Winter (2002) find that natural (informal) support, measured through the frequency of contact, perceptions of support, and satisfaction with the support received, is correlated with the number of days spent in stable housing. They argue that their findings provide modest support for a social causation model, wherein social support causes changes in housing. Further, they argue that there is likely a social selection model in operation, wherein those in stable housing have higher levels of social support.

Like the social causation and social selection models, the stress buffering effect (Cohen & Willis, 1985) is also offered as an explanation for the relationship between social support and health in individuals who experience homelessness (Aykanian, 2013; Jafry et al., 2021; Padgett et al., 2008; Toro et al., 2015). Proponents of the stress-buffering effect postulate that social support decreases stress which contributes to improvements in physical and mental health (Barton et al., 2018; Bøen et al., 2012; Zeng & Wu, 2022). The stress buffering effect is noted as a possible explanation for increased positive health and life outcomes for formerly homeless individuals who are housed through Housing First programs (Durbin et al., 2019), wherein rapid access to stable housing is a precursor to improved life outcomes. However, Golembiewski et al. (2017) find that program participants’ need to distance themselves from former street networks produces stress at first, and studies on the longer-term impacts of stress buffering in Housing First participants are needed. Individuals waiting for access to subsidized housing experience significant stress related to residence in unaffordable or unsuitable housing (Carder et al., 2018); therefore, one could hypothesize that the capacity of social support to decrease stress levels may result in better physical and mental health in those who are waiting for subsidized housing who simultaneously possess higher levels of social support. Significant positive relationships exist between social support and housing security (Calsyn & Winter, 2002; Logie et al., 2016; Moore, 2019); however, housing insecurity is higher in unaffordably housed populations (Schapiro et al., 2022), which suggests that those waiting for access to subsidized housing may be less likely to enjoy elevated levels of social support. Subsidized housing applicants may experience lower levels of social support which would reinforce the social selection model and diminish the impact of social support as a stress buffer in this population.

Unaffordable Housing as a Health Determinant

The recognition that Canada experiences a housing crisis marked by a shortage of affordable, adequate, accessible and suitable housing, which has negative consequences for health is not new. However, it leads to the understanding of the housing crisis as a public health crisis. Despite the importance of affordable, adequate, accessible and suitable housing to health (Braveman & Gottlieb, 2014; Forchuk et al., 2016; Raphael, 2009; Wilkinson & Marmot, 1998), it remains out of reach for many low-to-moderate income households in Canada. In their early-2000s piece on housing as a social determinant of health, Bryant (2004) discusses the emergence of a housing crisis in the 1980s, which remains unaddressed throughout the 1990s. They go as far as to deem housing in Canada a “national disaster” that has wide sweeping health implications (Bryant, 2004). Twenty years later, Canada’s affordable and suitable housing crisis has deepened, leading the present authors to deem it a disaster of epic proportions. Although housing is routinely and firmly established as a social determinant that impacts human health (Dahlgren & Whitehead, 2021; Forchuk et al., 2016), the key tenants and mechanisms by which housing impacts health are relatively understudied (Butler, 2022). Butler (2022) notes that to achieve optimal health outcomes from investments in housing, these tenants and mechanisms must be better understood by researchers.

Access to good quality, stable, affordable housing would undoubtedly improve long-term physical and mental health outcomes in those who currently lack this housing (Mueller et al., 2007; L. A. Taylor, 2018). However, it takes time and massive public investment to build new subsidized housing to accommodate growing waitlists. Futhermore, provincial, territorial and federal governments across Canada continually fail to invest in affordable housing at meaningful levels to provide decent, affordable accommodations to all those in need (Bryant, 2004; Suttor, 2016). This leads the current authors to investigate other potential health promoting mechanisms, such as social support, as potential resources that can be leveraged to improve health outcomes in those who lack access to affordable housing.

As noted above, there is a paucity of published research on social support and its relationship to health outcomes in those waiting for subsidized housing. This study fills this important gap in the literature on the relationship between housing unaffordability, waiting for access to subsidized housing, and health. The objective of this paper is to investigate the relationships between social support and depression, and social support and self-reported health in individuals as they wait for access to subsidized housing in New Brunswick, Canada. The authors present two hypotheses: (a) Social support is positively associated with self-reported physical health in subsidized housing applicants, and (b) Social support is negatively associated with depression scores in subsidized housing applicants.

Method

Study Population

The current study included participants from the baseline data collection phase of the New Brunswick Housing Study (see Woodhall-Melnik et al., 2022), which was designed to investigate the impact of subsidized housing on physical health, mental health, and healthcare use among people in New Brunswick who are waiting for access to and receive subsidized housing. To obtain the sample for the New Brunswick Housing Study, all households who were public housing applicants in the province (N = 4,750) in May 2021 received a letter from the New Brunswick Department of Social Development that provided information on the study, a link to the online version of the survey, and contact information for the study team (email and phone number). In order to avoid duplication of experiences on the waitlist, households that contained more than one person received letters addressed to the primary applicants on the waitlist and were asked to select only one individual from their household to participate in the study. Recipients of the letters who provided voluntary verbal, written, or electronic consent (n = 504) were provided with the option of completing the survey online, over the phone with a Research Assistant, via mail, or in person if they were living in an emergency shelter. Surveys were conducted in French and English. Participants received a $10 gift card and an entry into a draw for one of three $500 gift cards. The study received Research Ethics Board certification (REB 2020-032) from the University of New Brunswick.

To be included in the current study, participants from the New Brunswick Housing Study must have provided valid responses to all questions related to the variables of interest (i.e., covariates, social support, physical health, and depression). Further, participants who were unhoused and/or living in an emergency shelter were removed from the analyses as the present study is focused specifically on housed individuals who are waiting for access to subsidized housing.

Measures

Sociodemographic & Confounding Variables

Age (measured continuously), gender (Woman = reference, Man), marital status (Single/Separated/Widowed/Divorced = reference, Married/Common-law), education (Less than high school = reference, High school/GED or higher education), employment status (Unemployed = reference, Employed, Outside of labour force), ethnoracial group membership (North American = reference, non-White), residential/neighbourhood satisfaction (measured continuously using the RESS; Adriaanse, 2007), and self-stigma (measured continuously using the Self-Stigma Scale—Short Form; W. W. S. Mak & Cheung, 2010) were controlled for in all analyses. Notably, too few participants (n = 1) reported non-binary or transgender identity to be included in the analyses, which accounts for the gender binary adopted for analyses. Moreover, with respect to the scale variables that were controlled for in the present analyses, the RESS was found to have good internal consistency in the current study (α = .88), as was the Self-Stigma Scale (α = 0.89).

Social Support

The Oslo 3 Social Support Scale (OSSS-3; Kocalevent et al., 2018), a three-item measure, was used to assess participants’ perceived level of social support. The three items assess the number of close individuals in one’s life, the perception that one is cared about, and the perceived availability of practical help or support. All items were assessed using Likert-type scales. Lower numbers are indicative of low levels of perceived social support and higher numbers are indicative of higher levels of social support (Kocalevent et al., 2018). Participants’ responses to each of the three items were summed to compute a 12-point scale from 3 to 14, with greater scores indicating greater relative levels of social support. The internal consistency of the OSSS-3 was found to be acceptable in the current study (α = .65).

Physical Health

The EQ-5D-5L VAS, a standalone rating system, was used to measure participants’ perceptions of their physical health. Participants were asked to rate their physical health on a scale from 0 to 100 on the day they completed the baseline survey. A score of 0 indicated that they were experiencing the worst health they could imagine, and a score of 100 indicated they were experiencing the best health they could imagine. Participants who completed the survey online, by mail, or in person were provided with a visual scale to use to rate their health. Those who completed the survey over the phone were simply asked to rate their health on a scale of 0 to 100. Self-reported health rating scales from 0 to 100 are found to correlate with objective measures of physical health (see Hua et al., 2020, Meng et al., 2014).

Depression

The 10-item Centre for Epidemiological Studies Depression Scale (CES-D-10: Björgvinsson et al., 2013; Miller et al., 2008; Radloff, 1977) was employed to measure depressive symptoms in the week prior to the survey. Participants rated their responses to 10 statements (e.g., “I was bothered by things that usually don’t bother me in the past week”) on a 4-point Likert-type scale from 0 (Rarely or none of the time) to 3 (All of the time). Scoring was reversed for the two positive affect statements (i.e., items 5 and 8). Participants’ responses to all 10 items were then summed to create a scale ranging from 0 to 30, with greater scores indicating greater severity of depressive symptoms. The CES-D-10 was found to have a good internal consistency in the current study (α = .87).

Data Analysis

Data analysis was performed using Stata version 15 (StataCorp, 2017). Hierarchical linear regression analyses were employed to examine the unique associations that social support demonstrated with both outcomes (i.e., physical health and depression), while controlling for confounding and demographic variables. The statistical assumptions of linear regression were tested; no corrections were necessary. Both the physical health model and the depression model followed the same pattern: in Block 1, the outcome (i.e., physical health or depression) was regressed onto covariates; and in Block 2, social support was entered into the model.

Results

Descriptive statistics for the study sample (n = 271) are presented in Table 1. The majority of participants identified as women (66.79%) and as North American (90.77%). Most of the participants were either single, separated, widowed, or divorced (88.56%), and had completed high school/GED or a form of higher education (71.22%); however, only a small proportion of the sample was employed during the baseline data collection phase of the study (15.13%). The average age of participants was higher than the population mean at approximately 56 years. Participants’ mean residential/neighbourhood satisfaction score was 46.00 (SD = 12.87) on a scale with a minimum of 16 and a maximum of 76, and where greater scores indicate greater dissatisfaction; thus, this score indicates that they were relatively satisfied with their residential and neighbourhood environments. The average self-stigma score was 2.04 (SD = 0.61); possible scores range from 1 to 4, with greater scores indicating greater self-stigma. The sample’s mean social support score was 8.33 (SD = 2.61), which is considered poor (Kocalevent et al., 2018). The average physical health rating was 59.81 (SD = 24.30) on the EQ-5D-5L VAS scale, which ranges from 0 to 100, which is considerably lower than in studies of general national populations that produce VAS scores in the high 70s to mid-80s (Huber et al., 2017; Jensen et al., 2021; Sayah et al., 2016). The sample’s mean depression score was 13.34 (SD = 7.58); a score of 10 or greater on the CES-D-10 is considered a marker of significant depressive symptoms (Zhang et al., 2012).

Table 1.

Participant Characteristics (n = 271).

Variable	M/SD	%
Age	56.15/14.59
Gender
Women		66.79
Man		33.21
Marital status
Single/Separated/Widowed/Divorced		88.56
Married/Common-law		11.44
Education
Less than high school		28.78
High school/GED or higher education		71.22
Employment status
Employed		15.13
Unemployed		73.80
Outside of labour force		11.07
Ethnoracial group
North American		90.77
Non-White		9.23
Residential/neighbourhood satisfaction	46.00/12.87
Social stigma	2.04/0.61
Social support	8.33/2.61
Physical health	59.81/24.30
Depression	13.34/7.58

A correlation matrix was used to assess the associations between potential contributors to each model (see Table 2). Moderate relationships were observed between some of the potential model contributors. Residential and neighbourhood satisfaction was moderately associated with depression (.30). Self-stigma was moderately correlated with social support (−.24). Both dependent variables were moderately correlated with self-stigma (depression: .32; physical health: −.30). Depression was also moderately correlated with social support (−.40). The largest correlation observed was between the two dependent variables (−.55).

Table 2.

Summary of Correlations Between Select Study Variables.

Variable	1	2	3	4	5	6	7
1. Age	1.00
2. Gender	−.02	1.00
3. Residential/neighbourhood sat.	−.13*	.09	1.00
4. Self-stigma	.02	.10	.13*	1.00
5. Social support	.18**	−.13*	−.27***	−.24***	1.00
6. Physical health	.04	−.01	−.08	−.30***	.22***	1.00
7. Depression	−.22***	.03	.30***	.32***	−.40***	−.55***	1.00***

Note. Residential/neighbourhood sat. = Residential/neighbourhood satisfaction. Marital status, education, employment status, and ethnoracial identity were omitted due to brevity.

p < .05. **p < .01. ***p < .001.

Physical Health

In Block 1, physical health was regressed onto the sociodemographic and control variables, F (9, 261) = 4.11, p < .001, R² = 0.12 (see Table 3). Compared to being unemployed, being employed was associated with greater physical health, β = .14, SE = 4.18, p = .025, whereas greater levels of self-stigma was associated with poorer physical health, β = −.27, SE = 2.37, p < .001.

Table 3.

Hierarchical Linear Regression Analysis of Covariates (Block 1) and Social Support (Block 2) Predicting Physical Health.

	β/SE
n = 271	Block 1	Block 2
Age	.11/0.11	.09/0.10
Gender (Man)	.01/3.04	.02/3.01
Marital status (Married/Common-law)	.06/4.69	.07/4.64
Education (High school/GED or higher education)	.07/3.16	.06/3.12
Unemployed (reference)
Employed	.14/4.18*	.15/4.13*
Outside of labour force	.05/4.74	.03/4.72
Enthnoracial group (non-White)	.02/5.06	.05/5.07
Residential/neighbourhood satisfaction	−.04/0.11	.00/0.11
Self-stigma	−.27/2.37***	−.24/2.40***
Social support		.18/0.59**
R ²	.12***	.15**

Note.β = standardized regression coefficient; SE = standard error.

p < .05. **p < .01. ***p < .001.

In Block 2, social support was added to the model, and was found to be predictive of physical health, F (1, 260) = 7.62, p = .006, R² = .15. Greater social support was associated with greater self-reported physical health status, β = .18, SE = 0.59, p = .006, providing support for the hypothesis that social support was positively associated with physical health. In addition, as observed in Block 1, being employed (vs. unemployed) was associated with greater physical health, β = .15, SE = 4.13, p = .018, while greater self-stigma was predictive of poorer physical health, β = −.24, SE = 2.40, p < .001.

Depression

Depression was regressed onto covariates in Block 1, F (9, 261) = 9.84, p < .001, R² = 0.25 (see Table 4). Age was found to be negatively associated with depression, β = −.26, SE = 0.03, p < .001. Compared to being unemployed, being employed was associated with lesser severity of depressive symptoms, β = −0.15, SE = 1.20, p = .008, as was being outside the labour force, β = -0.14, SE = 1.36, p = .014. Residential/neighbourhood satisfaction was found to be positively associated with depression, β = .25, SE = 0.03, p < .001, suggesting that greater dissatisfaction was associated with greater severity of depressive symptoms. Self-stigma was also positively associated with depression, β = .29, SE = 0.68, p < .001.

Table 4.

Hierarchical Linear Regression Analysis of Covariates (Block 1) and Social Support (Block 2) Predicting Depression.

	β/SE
n = 271	Block 1	Block 2
Age	−.26/0.03***	−.23/0.03***
Gender (Man)	−.01/0.88	−.03/0.84
Marital status (Married/Common-law)	−.01/1.35	−.03/1.29
Education (High school/GED or higher education)	.02/0.91	.04/0.87
Unemployed (reference)
Employed	−.15/1.20**	−.16/1.15**
Outside of labour force	−.14/1.36*	−.10/1.32
Ethnoracial group (non-White)	−.07/1.46	−.12/1.41*
Residential/neighbourhood satisfaction	.25/0.03***	.18/0.03**
Self-stigma	.29/0.68***	.23/0.67***
Social support		−.29/0.16***
R ²	.25***	.32***

Social support was entered into the model in Block 2 and was found to be predictive of depression, beyond the predictive power of the covariates, F (1, 260) = 26.34, p < .001, R² = .32. Specifically, greater social support was predictive of lesser severity of depressive symptoms, β = −.29, SE = 0.16, p < .001, providing support for the hypothesis that social support was negatively associated with depression. As observed in Block 1, age was negatively associated with depression, β = −.23, SE = 0.03, p < .001, as was being employed (compared to being unemployed), β = −.16, SE = 1.15, p = .003. Also as observed in Block 1, residential/neighbourhood satisfaction was positively associated with depressive symptoms, β = .18, SE = 0.03, p = .001, as was self-stigma, β = .23, SE = 0.67, p < .001. In addition, in Block 2, membership in a non-White ethnoracial group was negatively associated with depressive symptoms, β = −.12, SE = 1.41, p = .026.

The following section situates the results within the literature on groups experiencing material deprivation and compares outcomes to those experienced in unhoused populations. Contributions to theories that explain social support in comparable populations are discussed. The subsequent section closes with a presentation of recommendations to leverage social support to improve the physical and mental health of subsidized housing waitlist applicants.

Discussion

The findings of this study indicate that those who wait for subsidized housing in New Brunswick, Canada typically experience low levels of social support and physical health, and a significant presence of depressive symptomatology. In the year since study recruitment, registration on New Brunswick’s subsidized housing waitlist has ballooned from the 4,750 households contacted for study participation by Social Development in May 2021 (Woodhall-Melnik et al., 2022) to an estimated 10,733 households in February of 2024 (Silberman, 2024). This indicates that demand is outpacing subsidized housing availability in the province and without significant increases in investment and development in the sector, households will experience longer wait times than previously anticipated. This is of particular interest, as Yap and Devilly (2004) find that perceived social support decreases with prolonged exposure to chronic stressors. Low levels of physical health, mental health, and social support indicate a need to intervene with physical and mental health and social support promotion mechanisms that are targeted to the needs of this population.

Previous research on social support finds that social support tends to be lower in populations that experience poverty or material deprivation (Israel, 2016). This is indeed the case in the present study, wherein low levels of support are observed. This lends support for Böhnke’s (2008) thesis of accumulation that stipulates that social support may be limited in populations that lack the economic resources and social capital to provide mutual aid or reciprocal support to others. Additionally, material deprivation may cause shame or perceived stigma leading to social withdrawal, which is displayed through low social support levels (Böhnke, 2008). Social isolation to avoid shame and stigma is common in unhoused populations and in those who experience poverty (Hodgkinson et al., 2017; Reutter et al., 2009). In the present study, self-stigma is a significant contributor to depression and self-rated physical health, which indicates support for the presence of this relationship in the individuals who wait for access to subsidized housing. This relationship is maintained when social support is added to the second block of regression for each dependent variable.

Further, in establishing correlations, the researchers observe a moderate negative contribution of stigma to social support which indicates that social support decreases with the increased presence of stigma. These findings reinforce a tenet of the accumulation thesis that notes the existence of stigma alongside low levels of social support, which contributes to physical and mental health concerns in other populations that experience other forms of housing instability, such as those who are unhoused (Chronister et al., 2013). In their rapid review of poverty stigma and wellbeing, Inglis et al. (2023)find that anticipated, received and self-stigma are associated with lower levels of social support. They argue that interventions to improve social support may actually lessen the adverse impacts of stigma.

Social Support and Depression

The addition of social support to the model that predicts depression indicates that social support is a significant contributor to depression, which supports the hypothesis that social support contributes to depression in individuals in New Brunswick who are on the waitlist for publicly subsidized housing. This corroborates findings in different unstably housed populations, such as those who experience homelessness (Irwin et al., 2008; Tyler et al., 2018; Unger et al., 1998), while contributing new knowledge of social support and depression in an understudied group of unstably housed individuals.

The contribution of social support to depression indicates that the perception of low social support is related to increased depressive symptomatology. The perception that one is not supported may be due to an actual lack of received social support, as indicated in other studies (Melrose et al., 2015; Walker, 2014). Melrose et al. (2015) find that low social support contributes to poor mental health; however, this relationship is strengthened when the need for social support is not fulfilled. This lack of social support may be due to the inadequate presence of systems-based and interpersonal support, such as a lack of access to affordable housing. Nevertheless, the relationship is quite likely more nuanced, as some studies suggest that those with high levels of depression may disengage with supportive people and networks because of their mental illness, which is explained by the social withdrawal and challenges that often operate alongside depressive symptomatology (Elmer & Stadtfeld, 2020; Katz et al., 2011).

Unemployment also contributes to higher depression scores in the present study. The significance of this relationship is maintained with the addition of social support. It is possible that this is related to stigma, as the relationship between stigma and unemployment is well established (Stuart, 2006), however, stigma and unemployment are not highly correlated in the present study. This may be due to the measure of stigma in the study, which asks specifically about the stigma attributed to one’s status as a subsidized housing waitlist applicant and not one’s employment status. W. W. Mak et al. (2007)find that the source of one’s stigma alters the relationship between self-stigma and mental health. Future studies may benefit from assessing the different sources of stigma experienced by applicants in order to gain a more nuanced understanding of how stigma impacts both social support and mental health.

As noted above, the findings generally refute the thesis of compensation as, in this case, material deprivation does not lead to higher levels of social support. However, membership in a non-White ethnic group was significantly negatively associated with depression scores when social support was added in block two of the analysis. Studies that focus on social support in non-White, low-income communities indicate that social ties and mutual aid may be higher in non-White than White communities that experience material deprivation (McDonald et al., 2020; Ochieng, 2011). This suggests that social support in non-White study participants may partially compensate for the negative impacts of material deprivation on mental health, offering some support for the thesis of compensation in non-White individuals.

The findings indicate the importance of social support as a mechanism for mental health promotion in individuals who are waiting for access to subsidized housing. Further, they indicate a need to provide mental health services to individuals who wait for subsidized housing. However, access to mental health services and social support is often difficult to obtain for individuals who experience poverty and housing instability (Frischmuth, 2014). Recommendations to address these concerns are presented below.

Social Support and Physical Health

In the present study, higher social support levels predict greater self-reported health. The model for physical health does not have as much explanatory power as the model predicting depression, although the results were significant nonetheless. These findings align with those in studies of social support and self-reported health in other unstably housed populations, such as those experiencing homelessness (Garibaldi et al., 2005; Umberson & Montez, 2010; Unger et al., 1998).

Self-stigma is a contributor to physical health in the present study. The significance of this contributor was maintained, yet decreased slightly, when social support was added into the second model, which indicates that the addition of social support slightly decreased the contribution of stigma to physical health. The Stigma Mechanisms in Health Disparities Framework indicates that stigma produces health behaviours, stress, and associated physiological changes that result in worsened health outcomes (Chaudoir et al., 2013). However, these factors that contribute to health outcomes are susceptible to larger social structures and policies, individual views on stigma, and interpersonal networks, wherein supportive networks can diminish some of the aforementioned factors that produce poor health. To achieve some health improvement in unaffordably housed persons, policymakers could seek to develop systems and structures that support individuals while simultaneously denouncing rhetoric that promotes stigma and provides opportunities to strengthen supportive social networks.

As in the model explaining depression, employment status is significantly associated with physical health, with those employed experiencing better physical health. This persists when social support is added to the model. Individuals who are already in poor health are less likely to work and may need to access public disability support benefits, which for a single individual in New Brunswick is $786 per month (Government of New Brunswick, 2023) and qualifies them for registration on the subsidized housing waitlist. In other words, employment may be linked to poor health, and although work can be an important source of social support (Hämmig, 2017), this relationship may be unrelated to social support. Further, the correlation between physical health and employment is quite small (−0.08). Future studies should be conducted to investigate contributors to health outcomes in a larger and specific sample of individuals who receive disability support benefits.

The results of the present study indicate that interventions to improve social support may be especially important for those who report lower levels of physical health, are unemployed, are retired or disabled, and/or are younger. Those who live with a marital or common law partner experience better physical health and less depressive symptomatology. However, unlike in other studies (Karimy et al., 2018; Koukouli et al., 2002; Mohebi et al., 2018; Nicolini et al., 2021) these findings are not significant. Further, identifying as a man is associated with more depressive symptomatology, yet better physical health. These findings, albeit interesting, are also not significant. The lack of explanatory power associated with marital status and gender in the present study may be due to the largely single and woman-dominated nature of the sample.

Recommendations

Despite the existence of a publicly funded healthcare system in Canada, waitlists for public psychiatric and psychological services are long and often limited (Moroz et al., 2020). Household registration on subsidized housing waitlists could be a critical and accessible intervention point where public social support and mental health promotion services may be offered. Goodcase et al. (2022) argue that poor coordination of mental health services and a lack of social support to assist with appointment attendance are barriers to treatment access. Providing community-based support and matching individuals with a primary care provider are cost effective solutions for increasing mental and physical health care accessibility for low-income households (Moroz et al., 2020). However, New Brunswick residents often experience problems with accessing primary care physicians (Duplessis & Hamilton, 2015). Concerted efforts to improve primary care access to date in New Brunswick often fall short, but recent attempts demonstrate reductions in the waitlist for physicians (Lothian, 2023), which may improve the health of all those in the province. Further, as the subsidized waitlist applicants experience lower levels of physical health and higher rates of depression, applicants could be provided with direct access to primary and mental healthcare to help meet unmet needs.

Participants in this study experience poor physical and mental health in addition to low levels of social support. Therefore, additional assistance to access and attend mental health treatment and to participate in health promoting activities is recommended. In other populations that experience material disadvantage, social support services and supports that are integrated into physical and mental healthcare produce positive health outcomes (Gale et al., 2018; Jego et al, 2018). Findings of the present study suggest a need for government intervention that alters typical approaches to healthcare to both increase social support and access to healthcare for households on the subsidized housing waitlist. Future work should focus on the efficacy of different approaches to social policy and their impacts on social support and physical and mental health in individuals who are waiting for access to publicly subsidized housing.

Social support can come from a variety of sources, and this provides an opportunity to promote diverse responses that improve multiple dimensions of support. In populations that experience poverty, da Silva et al. (2019)argue that four sources of social support (i.e., family, community, religious, and institutional) are particularly beneficial for health promotion and increased wellbeing. They argue that institutional support (e.g., formal health and social care) is important; nevertheless, interventions that focus on informal and community-based support may also be beneficial for health improvement (da Silva et al., 2019; Wahlbeck et al., 2017) in those waiting for subsidized housing. However, research on these interventions and other effective policy-based interventions is limited (Wahlbeck et al., 2017), which indicates a need to develop, assess and implement effective evidence-based models.

Limitations

This study was impacted by a few limitations. The length of the surveys was a concern to the research team. To avoid participant burden and to explore the general presence and absence of social support, the research team chose to measure perceived rather than received support. The same approach was taken with self-stigma and the SSS, wherein only questions about the primary condition of interest—registration on the subsidized housing waitlist—was assessed. Future studies may investigate how other potential stigmatizing conditions, such as poverty and unemployment, interact with both perceived and received social support to influence physical and mental health.

Legislation prohibits Social Development from using waitlist registration data for research purposes. Therefore, we were reliant on a group mailout by Social Development to recruit participants into the study. Consequently, we were not able to systematically oversample underrepresented groups within the study (e.g., men, single individuals, non-White individuals, etc.). Further, this legislation limits Social Development’s capacity to do research on their waitlist, which makes it impossible to know the true population characteristics of the waitlist. This is a threat to study validity, as we are unable to assess whether the study sample matches the characteristics of the population of the New Brunswick housing waitlist at the time of recruitment. Further, it is possible that some harder to reach individuals may have not been reached through study mailouts. The research team mitigated this to the best of their ability by physically recruiting and surveying at shelter and harm reduction services in the province’s main cities. There is a risk that unhoused individuals from rural areas were missed through mail recruitment. Reliability is also a challenge in the present study. As individuals self-selected into the research study, it may be possible that a different group of individuals could self-select in future replication studies. The waitlist has grown considerably since study recruitment and the findings of the present study may not be applicable to the current waitlist.

Despite these limitations, the present study provided one of the first explorations of the associations between social support, depression, and physical health in those waiting for subsidized housing and generated discussion on potentially valuable intervention points. The study included a sample size of approximately 10% of the waitlist in 2021 and provides a general understanding of social support and health in a previously unstudied population. The use of cross-sectional data provided indication that social support was an important determinant of health; however, additional data collected through the NB Housing Study in future survey waves may be useful for exploring the dynamic relationships between health status and social support over time.

Conclusion

This study concludes that social support is associated with lessened depressive symptomology and improved self-reported physical health in individuals on New Brunswick’s subsidized housing wait list. The study sample had low levels of social support and poor self-reported physical health. The prevalence of depressive symptomatology was high in this sample. These findings indicate a need to provide interventions that support the development of social support, mental health, and physical health in those who wait for access to subsidized accommodations. Future research from the NB Housing Study will focus on potential changes to these relationships over time as participants move into subsidized housing. This study provides valuable knowledge of a traditionally understudied, yet highly vulnerable, population; however, findings are specific to New Brunswick and research to understand the realities of those who wait for subsidized housing in other jurisdictions is critical to gaining a better understanding of needed supports and interventions to improve the wellbeing of subsidized housing applicants.

Footnotes

Acknowledgements

The authors acknowledge the tireless work and dedication of the Research Assistants with the Housing, Mobilization & Engagement Research Lab (HOME-RL) at the University of New Brunswick who conducted surveys with many study participants. Further, we provide our sincere gratitude to the research participants who took part in and continue to complete surveys with our team. Despite the personal nature of the surveys and the ongoing hardship they experience as they wait for access to subsidized housing, they took the time to engage with us and we are truly grateful. We also thank our community partners at local shelters, harm reduction sites, and at the Department of Social Development for the partnership and collaboration with this research.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The NB Housing Study is funded through a Project Grant with the Canadian Institutes of Health Research. Support for this work was also provided by the New Brunswick Health Research Foundation’s Establishment Award. Dr. Woodhall-Melnik is supported, in part, by the Canada Research Chairs Program. Some of the Graduate Research Assistants who worked on this project were supported, in part, by Community Housing Canada, led by Dr. Damian Collins at the University of Alberta and supported by the Social Sciences and Humanities Research Council of Canada.

Ethical Approval

This research was reviewed and received ethics certification from the University of New Brunswick’s Research Ethics Board (REB #2020-030).

ORCID iDs

Julia Woodhall-Melnik

Daniel D. J. Dutton

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

References

Aalbers

M. B.

(2016). The great moderation, the great excess and the global housing crisis. In The financialization of housing (pp. 64–80). Routledge. https://doi.org/10.1080/14616718.2014.997431

Adriaanse

C. C. M.

(2007). Measuring residential satisfaction: A residential environmental satisfaction scale (RESS). Journal of Housing and the Built Environment, 22(3), 287–304. https://doi.org/10.1007/s10901-007-9082-9

Aykanian

A. L.

(2013). Trauma history and social connection in a sample of chronically homeless adults: A test of the stress-buffering hypothesis (p. 158). Graduate Masters Theses. University of Massachusetts.

Alegría

NeMoyer

Falgàs Bagué

Wang

Alvarez

(2018). Social determinants of mental health: Where we are and where we need to go. Current Psychiatry Reports, 20(11), 95. https://doi.org/10.1007/s11920-018-0969-9

Allen

Balfour

Bell

Marmot

(2014). Social determinants of mental health. International Review of Psychiatry, 26(4), 392–407. https://doi.org/10.3109/09540261.2014.928270

Balaj

McNamara

C. L.

Eikemo

T. A.

Bambra

(2017). The social determinants of inequalities in self-reported health in Europe: Findings from the European social survey (2014) special module on the social determinants of health. European Journal of Public Health, 27(suppl_1), 107–114. https://doi.org/10.1093/eurpub/ckw217

Baker

Lester

Mason

Bentley

(2020). Mental health and prolonged exposure to unaffordable housing: A longitudinal analysis. Social Psychiatry and Psychiatric Epidemiology, 55(6), 715–721. https://doi.org/10.1007/s00127-020-01849-1

Barton

A. W.

Beach

S. R.

Bryant

C. M.

Lavner

J. A.

Brody

G. H.

(2018). Stress spillover, African Americans’ couple and health outcomes, and the stress-buffering effect of family-centered prevention. Journal of Family Psychology, 32(2), 186.

Björgvinsson

Kertz

S. J.

Bigda-Peyton

J. S.

McCoy

K. L.

Aderka

I. M.

(2013). Psychometric properties of the CES-D-10 in a psychiatric sample. Assessment, 20(4), 429–436. https://doi.org/10.1177/1073191113481998

10.

Bøen

Dalgard

O. S.

Bjertness

(2012). The importance of social support in the associations between psychological distress and somatic health problems and socio-economic factors among older adults living at home: A cross sectional study. BMC Geriatrics, 12(1), 1–12. https://doi.org/10.1186/1471-2318-12-27

11.

Böhnke

(2008). Are the poor socially integrated? The link between poverty and social support in different welfare regimes. Journal of European Social Policy, 18(2), 133–150.

12.

Bourdieu

(1979). Symbolic power. Critique of Anthropology, 4(13–14), 77–85.

13.

Bourdieu

(1983). The field of cultural production, or: The economic world reversed. Poetics, 12(4–5), 311–356.

14.

Bourdieu

(1987). Distinction: A social critique of the judgement of taste. Harvard University Press.

15.

Braveman

Gottlieb

(2014). The social determinants of health: It’s time to consider the causes of the causes. Public Health Reports, 129(Suppl 2), 19–31. https://doi.org/10.1177/00333549141291S206

16.

Bruhn

Philips

. (1984). Measuring social support: A synthesis of current approaches. Journal of Behavioral Medicine, 7(2):151–69. https://doi.org/10.1007/BF00845384

17.

Bryant

(2004). Housing and health. Social Determinants of Health: Canadian Perspectives, 32, 217–232.

18.

Butler

S. M.

(2022). Optimizing investment in housing as a social determinant of health. In JAMA health forum (Vol. 3, No. 9, pp. e223626-e223626). American Medical Association.

19.

Calsyn

R. J.

Winter

J. P.

(2002). Social support, psychiatric symptoms, and housing: A causal analysis. Journal of Community Psychology, 30(3), 247–259. https://doi.org/10.1002/jcop.10004

20.

Carder

P. C.

Kohon

Limburg

Becker

(2018). Waiting for housing assistance: Characteristics and narrative accounts of low-income older persons. Housing and Society, 45, 63–80. https://doi.org/10.1080/08882746.2018.1488212

21.

Chambers

Katic

Chiu

Redelmeier

D. A.

Levinson

Kiss

Hwang

S. W.

(2013). Predictors of medical or surgical and psychiatric hospitalizations among a population-based cohort of homeless adults. American Journal of Public Health, 103(Suppl 2), S380–S388. https://doi.org/10.2105/AJPH.2013.301646

22.

Chambers

Chiu

Scott

A. N.

Tolomiczenko

Redelmeier

D. A.

Levinson

Hwang

S. W.

(2014). Factors associated with poor mental health status among homeless women with and without dependent children. Community Mental Health Journal, 50(5), 553–559. https://doi.org/10.1007/s10597-013-9605-7

23.

Chassman

Sasser

Chaparro Rucobo

Calhoun

Barman-Adhikari

Bacon

Brisson

(2023). Substance use and housing stability among individuals experiencing homelessness and a traumatic brain injury: The role of social support. Psychoactives, 2(2), 144–161.

24.

Chaudoir

S. R.

Earnshaw

V. A.

Andel

(2013). “Discredited” versus “discreditable”: Understanding how shared and unique stigma mechanisms affect psychological and physical health disparities. Basic and Applied Social Psychology, 35(1), 75–87.

25.

Cobb

(1976). Social support as a moderator of life stress. Psychosomatic Medicine, 38(5), 300–314. https://doi.org/10.1097/00006842-197609000-00003

26.

Cohen

Janicki-Deverts

(2009). Can we improve our physical health by altering our social networks?. Perspectives on psychological science, 4(4), 375–378.

27.

Cohen

Wills

T. A.

(1985). Stress, social support, and the buffering hypothesis. Psychological Bulletin, 98(2), 310–357. https://doi.org/10.1037/0033-2909.98.2.310

28.

Chronister

Chou

C.-C.

Liao

H.-Y.

(2013). The role of stigma coping and social support in mediating the effect of societal stigma on internalized stigma, mental health recovery, and quality of life among people with serious mental illness. Journal of Community Psychology, 41(5), 582–600. https://doi.org/10.1002/jcop.21558

29.

Dahlgren

Whitehead

(2021). The Dahlgren-Whitehead model of health determinants: 30 years on and still chasing rainbows. Public Health, 199, 20–24.

30.

da Silva

L. B.

de Souza Feitosa

M. Z.

Nepomuceno

B. B.

Silva

A. M. S.

Ximenes

V. M.

Bomfimxys

Z. Á. C

. (2019). Social support as a way of coping with poverty. In Ximenes

Moura

Cidade

Nepomuceno

(Eds.), Psychosocial implications of poverty. Springer, Cham. https://doi.org/10.1007/978-3-030-24292-3_9

31.

de la Haye

Green

H. D.

Jr Kennedy

D. P.

Zhou

Golinelli

Wenzel

S. L.

Tucker

J. S.

(2012). Who is supporting homeless youth? Predictors of support in personal networks. Journal of Research on Adolescence, 22(4), 604–616. https://doi.org/10.1111/j.1532-7795.2012.00806.x

32.

Dunn

J. R.

(2002). Housing and inequalities in health: A study of socioeconomic dimensions of housing and self reported health from a survey of Vancouver residents. Journal of Epidemiology & Community Health, 56(9), 671–681. https://doi.org/10.1136/jech.56.9.671

33.

Duplessis

Hamilton

. (2015). Exploring the nurse practitioner role in palliative care in New Brunswick. Report: Fredericton, NB. https://unbscholar.dspace.lib.unb.ca/server/api/core/bitstreams/ac015592-5142-441c-b6eb-51fbfec5e97d/content

34.

Durbin

Nisenbaum

Kopp

O’Campo

Hwang

S. W.

Stergiopoulos

(2019). Are resilience and perceived stress related to social support and housing stability among homeless adults with mental illness?. Health & Social Care in the Community, 27(4), 1053–1062. https://doi.org/10.1111/hsc.12722

35.

Dweik

Watson

Woodhall-Melnik

(2022). Publicly subsidized housing and physical health: A literature review. Housing Studies, 39, 1–23.

36.

Dweik

Woodhall-Melnik

(2023). A systematic review of the relationship between publicly subsidised housing, depression, and anxiety among low-income households. International Journal of Housing Policy, 23, 1–31. https://doi.org/10.1080/19491247.2022.2037175

37.

Eckhard

(2018). Does poverty increase the risk of social isolation? Insights based on panel data from Germany. The Sociological Quarterly, 59(2), 338–359.

38.

Elmer

Stadtfeld

(2020). Depressive symptoms are associated with social isolation in face-to-face interaction networks. Scientific Reports, 10, 1. https://doi.org/10.1038/s41598-020-58297-9

39.

Feeney

B. C.

Collins

N. L.

(2015). A new look at social support: A theoretical perspective on thriving through relationships. Personality and Social Psychology Review, 19, 113–147.

40.

Fields

D. J.

Hodkinson

S. N.

(2018). Housing policy in crisis: An international perspective. Housing Policy Debate, 28(1), 1–5. https://doi.org/10.1080/10511482.2018.1395988

41.

Forchuk

Dickins

Corring

D. J.

(2016). Social determinants of health: Housing and income. Healthc Q, 18(Suppl), 27–31.

42.

Frischmuth

S. G.

(2014). Keep your sunny side: A street-level look at homelessness. Culture, Medicine & Psychiatry, 38(2), 312–323. https://doi.org/10.1007/s11013-014-9372-0

43.

Gadalla

T. M.

(2009). Determinants, correlates and mediators of psychological distress: A longitudinal study. Social Science & Medicine, 68(12), 2199–2205. https://doi.org/10.1016/j.socscimed.2009.03.040

44.

Gale

N. K.

Kenyon

MacArthur

Jolly

Hope

(2018). Synthetic social support: Theorizing lay health worker interventions. Social Science & Medicine, 196, 96–105. https://doi.org/10.1016/j.socscimed.2017.11.012

45.

Garibaldi

Conde-Martel

O’toole

T. P.

(2005). Self-reported comorbidities, perceived needs, and sources for usual care for older and younger homeless adults. Journal of General Internal Medicine, 20(8), 726–730. https://doi.org/10.1111/j.1525-1497.2005.0142.x

46.

Gariepy

Honkaniemi

Quesnel-Vallee

(2016). Social support and protection from depression: Systematic review of current findings in Western countries. The British Journal of Psychiatry, 209(4), 284–293. https://doi.org/10.1192/bjp.bp.115.169094

47.

Golembiewski

Watson

D. P.

Robison

Coberg

J. W.

(2017). Social network decay as potential recovery from homelessness: A mixed methods study in Housing First programming. Social Sciences, 6(3), 96.

48.

Goodcase

E. T.

Brewe

A. M.

White

S. W.

Jones

(2022). Providers as stakeholders in addressing implementation barriers to youth mental healthcare. Community Mental Health Journal, 58(5), 967–981. https://doi.org/10.1007/s10597-021-00905-7

49.

Government of New Brunswick (2023). Social assistance rate schedule A. Retrieved March 7, 2023, from https://www2.gnb.ca/content/gnb/en/departments/social_development/social_assistance/social_assistancerateschedules.html

50.

Haber

M. G.

Cohen

J. L.

Lucas

Baltes

B. B.

(2007). The relationship between self-reported received and perceived social support: A meta-analytic review. American journal of community psychology, 39, 133–144.

51.

Hämmig

(2017). Health and well-being at work: The key role of supervisor support. SSM-population Health, 3, 393–402.

52.

Hodgkinson

Godoy

Beers

L. S.

Lewin

(2017). Improving mental health access for low-income children and families in the primary care setting. Pediatrics, 139(1), e20151175. https://doi.org/10.1542/peds.2015-1175

53.

Hua

Lung

T. W. C.

Woodward

Salomon

J. A.

Hamet

Harrap

S. B.

Clarke

P. M. e.

(2020). Self-rated health scores predict mortality among people with type 2 diabetes differently across three different country groupings: Findings from the ADVANCE and ADVANCE-ON trials. Diabetic Medicine, 37, 1379–1385, https://doi.org/10.1111/dme.14237

54.

Huber

M. B.

Felix

Vogelmann

Leidl

(2017). Health-related quality of life of the general German population in 2015: Results from the EQ-5D-5L. International Journal of Environmental Research and Public Health, 14(4), 426.

55.

Hupcey

J. E.

(1998a). Clarifying the social support theory-research linkage. Journal of Advanced Nursing, 27(6), 1231–1241. https://doi.org/10.1046/j.1365-2648.1998.01231.x

56.

Hupcey

J. E.

(1998b). Social support: Assessing conceptual coherence. Qualitative Health Research, 8(3), 304–318. https://doi.org/10.1177/104973239800800302

57.

Hwang

S. W.

Kirst

M. J.

Chiu

Tolomiczenko

Kiss

Cowan

Levinson

(2009). Multidimensional social support and the health of homeless individuals. Journal of Urban Health, 86(5), 791–803. https://doi.org/10.1007/s11524-009-9388-x

58.

Katz

S. J.

Conway

C. C.

Hammen

C. L.

Brennan

P. A.

Najman

J. M.

(2011). Childhood social withdrawal, interpersonal impairment, and young adult depression: A mediational model. Journal of Abnormal Child Psychology, 39(8), 1227–1238. https://doi.org/10.1007/s10802-011-9537-z

59.

Inglis

Jenkins

McHardy

Sosu

Wilson

(2023). Poverty stigma, mental health, and well-being: A rapid review and synthesis of quantitative and qualitative research. Journal of Community & Applied Social Psychology, 33(4), 783–806.

60.

Irwin

LaGory

Ritchey

Fitzpatrick

(2008). Social assets and mental distress among the homeless: Exploring the roles of social support and other forms of social capital on depression. Social Science & Medicine, 67(12), 1935–1943. https://doi.org/10.1016/j.socscimed.2008.09.008

61.

Israel

(2016). More than cash: Societal influences on the risk of material deprivation. Social Indicators Research, 129(2), 619–637. https://doi.org/10.1007/s11205-015-1138-8

62.

Jafry

M. Z.

Martinez

Chen

T. A.

Businelle

M. S.

Kendzor

D. E.

Reitzel

L. R.

(2021). Perceived social support attenuates the association between stress and health-related quality of life among adults experiencing homelessness. International Journal of Environmental Research and Public Health, 18(20), 10713.

63.

Jego

Abcaya

Ştefan

D. E.

Calvet-Montredon

Gentile

(2018). Improving health care management in primary care for homeless people: A literature review. International Journal of Environmental Research and Public Health, 15(2), 309. https://doi.org/10.3390/ijerph15020309

64.

Jensen

M. B.

Jensen

C. E.

Gudex

Pedersen

K. M.

Sørensen

S. S.

Ehlers

L. H.

(2021). Danish population health measured by the EQ-5D-5L. Scandinavian Journal of Public Health, 51, 241–249. https://doi.org/14034948211058060

65.

Johnson

Winter

S. C.

(2023). Someone you can count on: Examining the mediating effect of social support on economic abuse and depression. American Journal of Community Psychology, 72(1–2), 3–14.

66.

Johnstone

Parsell

Jetten

Dingle

Walter

(2016). Breaking the cycle of homelessness: Housing stability and social support as predictors of long-term well-being. Housing Studies, 31(4), 410–426. https://doi.org/10.1080/02673037.2015.1092504

67.

Karimy

Koohestani

H. R.

Araban

(2018). The association between attitude, self-efficacy, and social support and adherence to diabetes self-care behavior. Diabetology & Metabolic Syndrome, 10(1), 1–6. https://doi.org/10.1186/s13098-018-0386-6

68.

Kocalevent

R.-D.

Berg

Beutel

M. E.

Hinz

Zenger

Härter

Nater

Brähler

(2018). Social support in the general population: Standardization of the Oslo Social Support Scale (OSSS-3). BMC Psychology, 6, 31. https://doi.org/10.1186/s40359-018-0249-9

69.

Koppelman

C. M.

(2018). “For now, we are in waiting”: Negotiating time in Chile’s social housing system. City & Community, 17(2), 504–524.

70.

Koukouli

Vlachonikolis

I. G.

Philalithis

(2002). Socio-demographic factors and self-reported functional status: the significance of social support. BMC Health Services Research, 2(1), 1–13. https://doi.org/10.1186/1472-6963-2-20

71.

Lee

C. Y. S.

Dik

B. J.

(2017). Associations among stress, gender, sources of social support, and health in emerging adults. Stress and Health, 33(4), 378–388. https://doi.org/10.1002/smi.2722

72.

Logie

C. H.

Jenkinson

J. I.

Earnshaw

Tharao

Loutfy

M. R.

(2016). A structural equation model of HIV-related stigma, racial discrimination, housing insecurity and wellbeing among African and Caribbean Black women living with HIV in Ontario, Canada. PLoS One, 11(9), e0162826. https://doi.org/10.1371/journal.pone.0162826

73.

Lothian

(2023). New Brunswick doctor waitlist falls to 59,000: ‘This will alleviate some of the stress.’ Global News. Retrieved June 17, 2023, from https://globalnews.ca/news/9425951/new-brunswick-doctor-waitlist-falls-to-59000-this-will-alleviate-some-of-the-stress/#:~:text=Want%20to%20discuss%3F-,New%20Brunswick%20doctor%20waitlist%20falls%20to%2059%2C000%3A%20’This%20will,alleviate%20some%20of%20the%20stress

74.

Lubbers

M. J.

Small

M. L.

García

H. V.

(2020). Do networks help people to manage poverty? Perspectives from the field. The Annals of the American Academy of Political and Social Science, 689(1), 7–25.

75.

Mak

W. W.

Poon

C. Y.

Pun

L. Y.

Cheung

S. F.

(2007). Meta-analysis of stigma and mental health. Social Science & Medicine, 65(2), 245–261.

76.

Mak

W. W. S.

Cheung

R. Y. M.

(2010). Self-stigma among concealable minorities in Hong Kong: Conceptualization and unified measurement. American Journal of Orthopsychiatry, 80(2), 267–281. https://doi.org/10.1111/j.1939-0025.2010.01030.x

77.

Marroquín

(2011). Interpersonal emotion regulation as a mechanism of social support in depression. Clinical Psychology Review, 31(8), 1276–1290. https://doi.org/10.1016/j.cpr.2011.09.005

78.

McDonald

Thompson

A. J.

Perzow

S. E. D.

Joos

Wadsworth

M. E.

(2020). The protective roles of ethnic identity, social support, and coping on depression in low-income parents: A test of the adaptation to poverty-related stress model. Journal of Consulting and Clinical Psychology, 88(6), 504–515. https://doi.org/10.1037/ccp0000477

79.

Melrose

K. L.

Brown

G. D.

Wood

A. M.

(2015). When is received social support related to perceived support and well-being? When it is needed. Personality and Individual Differences, 77, 97–105.

80.

Meng

Xie

Zhang

(2014). A single-item self-rated health measure correlates with objective health status in the elderly: a survey in suburban Beijing. Frontiers in public health, 2, 27.

81.

Miller

W. C.

Anton

H. A.

Townson

A. F.

(2008). Measurement properties of the CESD scale among individuals with spinal cord injury. Spinal Cord, 46(4), 287–292. https://doi.org/10.1038/sj.sc.3102127

82.

Mohebi

Parham

Sharifirad

Gharlipour

Mohammadbeigi

Rajati

(2018). Relationship between perceived social support and self-care behavior in type 2 diabetics: A cross-sectional study. Journal of Education and Health Promotion, 7, 17. https://doi.org/10.4103/jehp.jehp_73_17

83.

Mood

Jonsson

J. O.

(2016). The social consequences of poverty: An empirical test on longitudinal data. Social Indicators Research, 127, 633–652.

84.

Moore

(2019). Perceived functional social support and self-rated health: The health promoting effects of instrumental support for the Irish community in London. Journal of Immigrant and Minority Health, 21(5), 1004–1011. https://doi.org/10.1007/s10903-018-0831-5

85.

Moroz

D’Angelo

M. S.

(2020). Mental health services in Canada: Barriers and cost-effective solutions to increase access. In Healthcare management forum, 33(6), 282–287. https://doi.org/10.1177/0840470420933911

86.

Morrison

R. L.

(2009). The double edged sword: Organizational outcomes of workplace friendships. In Friends and enemies in organizations: A work psychology perspective (pp. 122–138). London: Palgrave Macmillan UK.

87.

Mueller

E. J.

Tighe

J. R.

(2007). Making the case for affordable housing: Connecting housing with health and education outcomes. Journal of Planning Literature, 21(4), 371–385. https://doi.org/10.1177/0885412207299653

88.

Nicolini

Abbate

Inglese

Rossi

P. D.

Mari

Cesari

(2021). Different dimensions of social support differentially predict psychological well-being in late life: Opposite effects of perceived emotional support and marital status on symptoms of anxiety and of depression in older outpatients in Italy. Psychogeriatrics, 21(1), 42–53, https://doi.org/10.1111/psyg.12633

89.

Ochieng

B. M. N.

(2011). The effect of kin, social network and neighbourhood support on individual well-being. Health & Social Care in the Community, 19(4), 429–437. https://doi.org/10.1111/j.1365-2524.2011.00992.x

90.

Padgett

D. K.

Henwood

Abrams

Drake

R. E.

(2008). Social relationships among persons who have experienced serious mental illness, substance abuse, and homelessness: Implications for recovery. American Journal of Orthopsychiatry, 78, 333–339.

91.

Pierce

G. R.

Sarason

B. R.

Sarason

I. G.

(Eds.). (1996). Handbook of social support and the family. Springer Science & Business Media.

92.

Potts

(2020). Broken cities: Inside the global housing crisis. Bloomsbury Publishing.

93.

Radloff

L. S.

(1977). A self report depression scale for research in the general populations. Applied Psychological Measurement, 1(3), 385–401. https://doi.org/10.1177/014662167700100306

94.

Raphael

(2009). Social structure, living conditions, and health. In Raphael

(ed.), Social determinants of health (pp. 20–36) Canadian Scholars’ Press.

95.

Reutter

L. I.

Stewart

M. J.

Veenstra

Love

Raphael

Makwarimba

(2009). “Who do they think we are, anyway?”: Perceptions of and responses to poverty stigma. Qualitative Health Research, 19(3), 297–311.

96.

Sánchez

J. C. B.

(2017, April 27–28). Mobilising anti-discrimination law to defend housing rights in Europe: Socioeconomic disadvantage and the right to housing. International conference on legal aspects of housing: “Ensuring the effective exercise of the right to housing in the EU”. Tarragona, Spain.

97.

Sayah

F. A.

Bansback

Bryan

Ohinmaa

Poissant

Pullenayegum

Johnson

J. A.

(2016). Determinants of time trade-off valuations for EQ-5D-5L health states: Data from the Canadian EQ-5D-5L valuation study. Quality of Life Research, 25(7), 1679–1685.

98.

Schapiro

Blankenship

Rosenberg

Keene

(2022). The effects of rental assistance on housing stability, quality, autonomy, and affordability. Housing Policy Debate, 32(3), 456–472. https://doi.org/10.1080/10511482.2020.1846067

99.

Silberman

(2024). Waitlist for subsidized housing doubles as N.B. vacancy rates fall. CBC News. Retrieved April 15, 2024, from https://www.cbc.ca/news/canada/new-brunswick/subsidized-housing-waitlist-grows-1.7110801

100.

Singh

Aitken

Baker

Bentley

(2020). Do financial hardship and social support mediate the effect of unaffordable housing on mental health? Social psychiatry and psychiatric epidemiology, 55, 705–713.

101.

Sippel

L. M.

Pietrzak

R. H.

Charney

D. S.

Mayes

L. C.

Southwick

S. M.

(2015). How does social support enhance resilience in the trauma-exposed individual? Ecology and Society, 20(4), 410. https://doi.org/10.5751/ES-07832-200410

102.

Slopen

Fenelon

Newman

Boudreau

(2018). Housing assistance and child health: A systematic review. Pediatrics, 141(6), 1–25.

103.

Stahre

VanEenwyk

Siegel

Njai

(2015). Peer reviewed: Housing insecurity and the association with health outcomes and unhealthy behaviors, Washington State, 2011. Preventing Chronic Disease, 12, 511. https://doi.org/10.5888/pcd12.140511

104.

StataCorp. (2017). Stata statistical software: Release 15. StataCorp LLC.

105.

Statistics Canada (2018). Waitlist status including length of time, by tenure including social and affordable housing, 2018, inactive. Social Science & Medicine, 68(12), 2199–2205. https://doi.org/10.1016/j.socscimed.2009.03.040

106.

Stuart

(2006). Mental illness and employment discrimination. Current Opinion in Psychiatry, 19(5), 522–526. https://doi.org/10.1097/01.yco.0000238482.27270.5d

107.

Suttor

(2016). Still renovating: A history of Canadian social housing policy (Vol. 6). McGill-Queen’s Press-MQUP.

108.

Szkody

McKinney

(2020). Appraisal and social support as moderators between stress and physical and psychological quality of life. Stress and Health, 36(5), 586–595. https://doi.org/10.1002/smi.2957

109.

Taylor

S. E.

(2011). Social support: A review. In Friedman

H. S.

(Ed.), The Oxford handbook of health psychology (pp. 189–214). Oxford University Press.

110.

Taylor

L. A.

(2018). Housing and health: An overview of the literature. Health Affairs Health Policy Brief.

111.

Thoits

P. A.

(2011). Mechanisms linking social ties and support to physical and mental health. Journal of health and social behavior, 52(2), 145–161.

112.

Toro

P. A.

Oko-Riebau

(2015). Social support and stress among homeless adults in southern Poland. Journal of Community Psychology, 43(4), 430–446.

113.

Triveno

Nielson

(2021). Can New Technology Solve the Global Housing Crisis? World Bank Blog. Retrieved August 12, 2022, from https://blogs.worldbank.org/sustainablecities/can-new-technology-solve-global-housing-crisis

114.

Tyler

K. A.

Schmitz

R. M.

Ray

C. M.

(2018). Role of social environmental protective factors on anxiety and depressive symptoms among Midwestern homeless youth. Journal of Research on Adolescence, 28(1), 199–210. https://doi.org/10.1111/jora.12326

115.

Uchino

B. N.

(2009). Understanding the links between social support and physical health: A life-span perspective with emphasis on the separability of perceived and received support. Perspectives on Psychological Science, 4(3), 236–255. https://doi.org/10.1111/j.1745-6924.2009.01122.x

116.

Uchino

B. N.

Bowen

Kent de Grey

Mikel

Fisher

E. B.

(2018a). Social support and physical health: models, mechanisms, and opportunities. In Principles and concepts of behavioral medicine. Springer, New York, NY. https://doi.org/10.1007/978-0-387-93826-4_12

117.

Uchino

B. N.

Trettevik

Kent de Grey

R. G.

Cronan

Hogan

Baucom

B. R.

(2018b). Social support, social integration, and inflammatory cytokines: A meta-analysis. Health Psychology, 37(5), 462. https://doi.org/10.1037/hea0000594

118.

Umberson

Karas Montez

(2010). Social relationships and health: A flashpoint for health policy. Journal of Health and Social Behavior, 51(1_suppl), S54–S66. https://doi.org/10.1177/0022146510383501

119.

Unger

J. B.

Kipke

M. D.

Simon

T. R.

Johnson

C. J.

Montgomery

S. B.

Iverson

(1998). Stress, coping, and social support among homeless youth. Journal of Adolescent Research, 13(2), 134–157. https://doi.org/10.1177/0743554898132003

120.

Wahlbeck

Cresswell-Smith

Haaramo

Parkkonen

(2017). Interventions to mitigate the effects of poverty and inequality on mental health. Social Psychiatry and Psychiatric Epidemiology, 52, 505–514. https://doi.org/10.1007/s00127-017-1370-4

121.

Walker

(2014). Poverty, shame, and stigma. In Walker

(Ed.), The shame of poverty. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199684823.003.0004

122.

Wang

Pridham

K. F.

Nisenbaum

Pedersen

Brown

Hwang

S. W.

(2021). Factors associated with readmission among general internal medicine patients experiencing homelessness. Journal of General Internal Medicine, 36, 1944–1950. https://doi.org/10.1007/s11606-020-06483-w

123.

Whitehead

Dahlgren

(1991). Policies and strategies to promote social equity in health. Institute for Future Studies.

124.

Wilkinson

R. G.

Marmot

(1998). Social determinants of health: The solid facts. World Health Organization.

125.

Williams

Barclay

Schmied

(2004). Defining social support in context: A necessary step in improving research, intervention, and practice. Qualitative Health Research, 14(7), 942–960.

126.

Williams

D. R.

Kontos

E. Z.

Viswanath

Haas

J. S.

Lathan

C. S.

MacConaill

L. E.

Chen

Ayanian

J. Z.

(2012). Integrating multiple social statuses in health disparities research: The case of lung cancer. Health Services Research, 47(3), 1255–1277. https://doi.org/10.1111/j.1475-6773.2012.01404.x

127.

Yap

M. B.

Devilly

G. J.

(2004). The role of perceived social support in crime victimization. Clinical Psychology Review, 24(1), 1–14.

128.

Zeng

(2022). Neighborhood collective efficacy in stressful events: The stress-buffering effect. Social Science & Medicine, 306, 115154. https://doi.org/10.1016/j.socscimed.2022.115154

129.

Zhang

O’Brien

Forrest

J. I.

Salters

K. A.

Patterson

T. L.

Montaner

J. S.

Hogg

R. S.

Lima

V. D.

(2012). Validating a shortened depression scale (10 item CES-D) among HIV positive people in British Columbia, Canada. PloS One, 7(7), e40793. https://doi.org/10.1371/journal.pone.0040793