Health and Social Care in the Community 13(6), 514–530
doi: 10.1111/j.1365-2524.2005.00584.x
Lay understandings of the effects of poverty: a Canadian perspective
Blackwell Publishing, Ltd.
Linda I. Reutter RN PhD1, Gerry Veenstra PhD2, Miriam J. Stewart PhD3, Dennis Raphael PhD4,
Rhonda Love PhD5, Edward Makwarimba PhD6 and Susan McMurray MA7
1
Faculty of Nursing, University of Alberta, Canada, 2Department of Anthropology and Sociology, University of British
Columbia, Canada, 3Faculty of Nursing and Faculty of Medicine (Public Health Sciences), University of Alberta, Canada,
4
School of Health Policy and Management, York University, Canada, 5Department of Public Health Sciences, University of
Toronto, Canada, 6Social Support Research Program, University of Alberta, Canada and 7Department of Public Health
Sciences, University of Toronto, Canada
Correspondence
Abstract
Dr Linda I. Reutter
Faculty of Nursing
3rd Floor Clinical Sciences Building
University of Alberta
Edmonton
Alberta
Canada
T6G 2G3
E-mail: [email protected]
Although there is a large body of research dedicated to exploring public
attributions for poverty, considerably less attention has been directed to
public understandings about the effects of poverty. In this paper, we
describe lay understandings of the effects of poverty and the factors that
potentially influence these perceptions, using data from a telephone survey
conducted in 2002 on a random sample (n = 1671) of adults from eight
neighbourhoods in two large Canadian cities (Edmonton and Toronto).
These data were supplemented with interview data obtained from 153
people living in these same neighbourhoods. Multivariate linear and logistic
regressions were used to determine the effects of basic demographic variables,
exposure to poverty and attribution for poverty on three dependent variables
relating to the effects of poverty: participation in community life, the relationship
between poverty and health and challenges facing low-income people. Ninety-one
per cent of survey respondents agreed that poverty is linked to health, while
68% agreed that low-income people are less likely to participate in
community life. Affordable housing was deemed especially difficult to
obtain by 96%, but other resources (obtaining healthy food, giving children
a good start in life, and engaging in healthy behaviours) were also viewed
as challenging by at least 70% of respondents. The regression models
revealed that when controlling for demographics, exposure to poverty
explained some of the variance in recognising the effects of poverty.
Media exposure positively influenced recognition of the poverty–health
link, and attending formal talks was strongly related to understanding
challenges of poverty. Attributions for poverty accounted for slightly
more of the variance in the dependent variables. Specifically, structural
and sociocultural attributions predicted greater recognition of the effects
of poverty, in particular the challenges of poverty, while individualistic
attributions predicted less recognition. Older and female respondents
were more likely to acknowledge the effects of poverty. Income was
positively associated with recognition of the poverty–health link, negatively
associated with understanding the challenges of low-income people, and
unrelated to perceptions of the negative effect of poverty on participation
in community life.
Keywords: attributions for poverty, effects of poverty, exposure to poverty,
public perceptions
Accepted for publication 6 April 2005
514
© 2005 Blackwell Publishing Ltd
Lay understanding of poverty
Introduction
Evidence for the negative effects of poverty on individual
and population health has continued to accumulate
(Dunn 2002, CIHI 2004). Indeed, poverty is now
thought to be among the greatest determinants of (ill)
health (Federal, Provincial, and Territorial Advisory
Committee on Population Health 1994, WHO 1997,
Raphael 2004). Despite Canada’s recent impressive
economic growth, the poverty rate has not decreased
proportionately; poverty rates have actually worsened
for some Canadians (National Council of Welfare 2002).
Moreover, income inequality is increasing in Canada
(Dunn 2002, Phipps 2003), with an accompanying
spatial concentration of poverty in certain neighbourhoods (Federation of Canadian Municipalities 2003).
Currently, 16% of Canadians live in poverty (National
Council of Welfare 2002).
Much of the recent discourse on poverty is framed
within a social exclusion/inclusion perspective, a
movement that began in Europe (e.g. Room 1995, PercySmith 2000) and, more recently, entered Canadian
discourse (e.g. Mitchell & Shillington 2002, Shookner
2002, Clutterbuck 2003, Galabuzi 2004). The inclusion/
exclusion discourse focuses on reducing inequities
and the conditions that marginalise, neglect, exclude, or
‘leave out’ certain people, and on providing access to
resources and participation for all people (Clutterbuck
& Novick 2003). Rather than focusing on the behaviours
of excluded individuals, social exclusion emphasises
the processes that lead to the marginalisation and
exclusion of individuals and social groups, including
the influence of public economic and social policies,
programmes, institutions and actors (Percy-Smith 2000,
Labonte 2004).
Understanding the lived experience of low-income
people is an obvious first step to creating inclusive
policies and programmes; however, given the relational
nature of social exclusion/inclusion, it is probably just
as important to ascertain the opinions of those not living
in poverty about the lived experience of poverty. Perceptions of poverty are an important element of societal
exclusion/inclusion because perceptions reflect the
attitudes and cognitive distancing that may precede,
accompany, and even justify exclusionary behaviours at
the interpersonal and institutional levels (Bullock 1999,
Lott 2002). More specifically, how people understand
poverty will likely influence interpersonal interactions
with people living in poverty, and even how low-income
people perceive themselves relative to others (Bullock
1999, Cozzarelli et al. 2001). Most significantly, perceptions about poverty may influence support for pertinent
public policy, considered to be the most effective strategy
for reducing poverty and its effects. For example,
perceptions of the causes of poverty have been found to
predict support for poverty-related policies: people who
explain poverty in societal (external) terms tend to be
more in favour of social spending and social protection
policies than are those who explain it in individualistic
(internal) terms (Iyengar 1989, Zucker & Weiner 1993,
Bullock 1999, Bullock et al. 2003, Alesina & Glaeser 2004).
Similarly, understanding the effects of poverty on health
and well-being may influence support for policies that
ameliorate poverty and its negative effects (Reutter
et al. 2002). To gain a better understanding of various
perceptions about poverty, this paper describes lay
understandings of the effects of poverty and the factors
that potentially influence these perceptions in a sample
of Canadian adults.
Most studies regarding lay understandings of
poverty have been conducted in the United States, and
much of this research focuses on public understandings
about attributions for poverty. This research continues
to confirm the existence of internal attributions that
individuals are responsible for their poverty as the
dominant explanation (Cozzarelli et al. 2002, Lott 2002),
although there is some indication that these views
may be changing (Hunt 1996, Shaw & Shapiro 2002).
Fewer studies exist regarding attributions for poverty
in countries with a more collectivistic culture and
traditionally higher levels of state intervention (van
Oorschot & Halman 1999), although some research
suggests that European countries are much less likely
than most others to feature a ‘dominant ideology’ of
individual blame (Kluegel et al. 1995, van Oorschot &
Halman 1999, Alesina & Glaeser 2004). These findings
underline the need for country-specific research that
acknowledges different historical, social and political
contexts.
In contrast with research exploring public attributions
for poverty, there are few studies that have focused
specifically on public understandings of the effects of
poverty. Some research has explored public perceptions
of the effect of poverty on health, primarily in the UK
(e.g. Blaxter 1997, Popay et al. 2003). A few Canadian
studies have investigated public understandings of the
relationship between poverty and health (Reutter et al.
1999) and their effects on support for poverty-related
policies (Reutter et al. 2002). This latter study suggests
that different understandings of how poverty influences
health predict different levels of support for government
funding in the policy areas of housing, nutrition, welfare
and child care.
The role of socio-demographic variables in predicting
attributions for poverty and support for poverty-related
policies has been well documented, particularly in the
US literature. These variables (income, education, age
and gender) are considered to be particularly important
© 2005 Blackwell Publishing Ltd, Health and Social Care in the Community 13(6), 514–530
515
L. I. Reutter et al.
as they reflect varying degrees of privilege and tend to
be correlated with media consumption and support for
the current system (Lee et al. 1992). Research regarding
antecedents of beliefs about poverty has generally
found that those of higher status (higher income, older,
male) favour individualistic explanations, while those
of lower status are more likely to favour structural
explanations ‘but not necessarily with greatly diminished support for individualistic explanations’ (Hunt
1996). Findings are conflicting, however, suggesting
that the relationship between such demographic
characteristics and perceptions of poverty is complex
(Wilson 1996).
Exposure to poverty as a factor influencing public
understandings about poverty has received less research
attention than has demographics, yet this factor also
has the potential to shift public attitudes and beliefs.
Exposure includes direct personal experiences with
poverty as well as indirect exposure through media
portrayals of poverty and educational efforts to increase
awareness of poverty issues. Greater personal experience with homelessness, for example, has been found to
be associated generally with greater compassion toward
homeless people (Cook & Barrett 1992, Link et al. 1995,
Lee & Farrell 2003). Different types of exposure to
poverty may have differential effects on attributions
for poverty (Wilson 1996) and on beliefs pertaining to
the effects of poverty on health (Reutter et al. 2004). For
example, Wilson (1996) found that prolonged contact
with low-income people (e.g. friendships) and hearing
about poverty from experts through formal learning
were more important in supporting a structural explanation of poverty than were brief encounters with lowincome people and informal discussions with others.
Reutter et al. (2004) found that nursing students’ personal
exposure with poverty was less important than formal
learning in understanding the structural relationship
between poverty and health.
There is substantial evidence documenting the extent
to which public perspectives influence governments
in the development of public policy, particularly in the
area of social welfare (Cook & Barrett 1992, Burstein
1998, Sharp 1999). The values, beliefs and interests of
the public are important factors in the development and
implementation of policies, as public policies operate
within a given culture or ideology (Lomas 1990, Golding
1995, Kushner & Rachlis 1998, Whitehead 1998). Yet,
there is surprisingly little Canadian research, other than
public opinion polling, that has explored public perceptions of poverty, and very little exploring Canadians’
perceptions of the effects of poverty. The purpose of this
paper is to describe lay understandings of the effects of
poverty and the factors that influence these perceptions
in the Canadian context.
516
Method
Sample sites
This study was conducted in two large Canadian cities:
Toronto, Ontario, and Edmonton, Alberta. Toronto is
Canada’s largest city, with a population of about 2.5
million, whereas Edmonton, Alberta’s capital city, has a
population of about 670 000 (Statistics Canada 2001a).
The poverty rate in both of these cities is 16%, based on
Statistics Canada low-income cut-offs (Statistics Canada
2001b), in spite of strong economic growth in these
provinces and in the country as a whole. In the early
1990s, Alberta and Ontario introduced particularly
severe cuts to their social programmes, including health,
education and social welfare, resulting from fiscal
policies aimed at deficit and debt reduction.
We chose four neighbourhoods in Toronto and in
Edmonton to situate our study. The eight neighbourhoods were selected on the basis of economic prosperity
and the degree of economic heterogeneity, in order
to include people from homogeneous places as well as
people from places possessing a multitude of income
groups. Information for both cities was drawn from the
most recent census of the population. The neighbourhoods chosen were Bonnie Doon, Highlands, Laurier
Heights and Montrose-Industrial Heights in Edmonton,
and New Toronto, The Beaches, North Riverdale and
Swansea-High Park in Toronto.
Ethical clearance for the study was obtained from
the appropriate university ethics review committees in
both provinces.
Data collection
Phase I consisted of individual interviews with lowincome and higher-income people and group interviews
with low-income people from the eight neighbourhoods,
conducted from October 2000 to March 2003. Higherincome and low-income were determined by Statistics
Canada low-income cut-offs (LICO). The LICOs,
commonly viewed as a measure of poverty, are income
levels at which Canadians, differentiated by family size
and the population of their community of residence,
spend 20% more of their income on basic needs than
the average proportion spent by Canadians. Currently,
families who spend more than 54.7% of their income
on basic needs are living below the LICO. Purposive
sampling was used to select participants with a variety
of low-income situations and demographic characteristics. Trained interviewers conducted interviews
using a semi-structured interview guide developed by
the researchers with input from a community advisory
committee. The interview guide covered the following
© 2005 Blackwell Publishing Ltd, Health and Social Care in the Community 13(6), 514–530
Lay understanding of poverty
Table 1 Characteristics of the survey sample
Survey item
Categories
Distribution
In what year were you born? mean (N, SD)
–
1958.5 (1639, 15.9)
What is your gender? N (%)
Female
Male
920 (55.0)
751 (45.0)
What is the highest level of education you
have completed? N (%)
Some elementary school
Completed elementary school
Some high school/junior high
Completed high school
Some community college, technical school or university
Completed community college or technical school
Completed bachelor’s degree
Post-graduate training: MA, MSc, MLS, MSW, MBA, etc.
Post-graduate training: professional degree or PhD
11 (0.7)
30 (1.8)
141 (8.5)
284 (17.1)
197 (11.9)
250 (15.1)
513 (30.9)
181 (10.9)
50 (3.0)
Could you please tell me how much income
you and other members of your household
received in the year ending 31 December
2001, before taxes? N (%)
Less than $20 000
Between $20 000 and $29 999
Between $30 000 and $39 999
Between $40 000 and $49 999
Between $50 000 and $59 999
Between $60 000 and $69 999
Between $70 000 and $79 999
Between $80 000 and $89 999
Between $90 000 and $99 999
Between $100 000 and $120 000
Between $120 000 and $150 000
More than $150 000
140 (9.7)
124 (8.6)
142 (9.8)
145 (10.1)
136 (9.4)
104 (7.2)
115 (8.0)
97 (6.8)
49 (3.4)
140 (9.7)
102 (7.1)
148 (10.3)
topics: sense of belonging, factors contributing to sense of
belonging, support received and provided, participation
in activities, effects of income on inclusion/exclusion
and belonging/isolation, strategies to enhance inclusion
and belonging for low-income people, and perceptions
of poverty and its effects. The interview guide was pilot
tested with low-income (n = 5) and higher-income (n =
5) people. Group interviews provided an opportunity
to expand the breadth of the data beyond the depth
of the individual interviews. These interviews elicited
information on factors that influence belonging/isolation
and inclusion/exclusion, and strategies for enhancing
inclusion/belonging.
Phase II consisted of a telephone survey of randomly
selected English-speaking adults living in these neighbourhoods conducted from July to November 2002. We
attempted to obtain approximately 200 completed
surveys per neighbourhood, enabling us to make relatively precise city- and neighbourhood-level inferences
for later use by our community partners. The Institute
for Social Research (ISR) at York University, Toronto,
devised the sampling framework. A two-stage probability selection process was used: (1) identification of
households by randomly selecting telephone numbers
within the selected neighbourhoods using postal code
data and (2) the random selection of respondents from
the household (person with the next birthday). The
110-item survey instrument was pilot tested with 20
respondents and then was administered by the ISR to
the sample using computer-assisted telephone interviewing and trained interviewers. Telephone calls were
made during days and evenings for both workdays and
weekends. To maximise response rate, up to 15 callbacks
were made, and those respondents who refused to be
interviewed were called a second time. The telephone
interviews took about 25 minutes to complete on average.
Survey items
The 110-item survey instrument was constructed by the
investigators specifically for this project, using relevant
subscales from validated measures as well as items
developed by the research team based on the findings
of Phase I. Information was obtained on various aspects
of exclusion/inclusion including perceptions about
poverty and its effects.
The survey items and response categories utilised
to measure socio-demographic characteristics of
respondents are presented in Table 1. Six items assessed
exposure to poverty through direct personal experiences and through indirect informational sources. Five
items assessed agreement with statements that address
individualistic, sociocultural and structural explanations of poverty, adapted from van Oorschot & Halman
© 2005 Blackwell Publishing Ltd, Health and Social Care in the Community 13(6), 514–530
517
L. I. Reutter et al.
Table 2 Survey items and distribution of responses
Survey item
Exposure to poverty
Have you ever received social assistance or welfare? N (%)
Have you ever had close friends or family who were living on low incomes? N (%)
Have you ever worked at a job where you helped people living on low incomes? N (%)
And have you ever done volunteer work to help people living on low incomes? N (%)
Have you read or obtained information or learned about poverty from reading
newspapers, listening to the radio, or watching television? N (%)
Have you got information or learned about poverty from courses, lectures,
conferences or workshops? N (%)
Attributions for poverty
Government policies have caused some people to become poor. N (%)
Most people are poor because they grew up in a poor family. N (%)
Most people are poor because of unequal opportunities in our society. N (%)
Most people are poor because they are lazy. N (%)
Poverty is just part of modern progress and globalisation. N (%)
Effects of poverty
Do you think people with low incomes participate more or less than other people in
community events and recreational activities? N (%)
Do you think there is a relationship or link between poverty and health? N (%)
(1999) and incorporating the qualitative findings from
Phase I. These items are presented in Table 2. Two items
assessing recognition of the effects of poverty – pertaining
to participation in community life and health effects
– are also presented in Table 2. A third variable also
assessing perceptions regarding the effects of poverty
was created by combining five additional survey items
into a single index assessing the nature of the ‘tough life’
of people living in poverty. The five items were: (1)
518
Categories
Distribution
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
252 (15.2)
1405 (84.8)
1066 (64.4)
588 (35.6)
669 (40.3)
992 (59.7)
747 (44.9)
917 (55.1)
1531 (92.2)
130 (7.8)
670 (40.3)
991 (59.7)
Strongly agree
Somewhat agree
‘Neutral’
Somewhat disagree
Strongly disagree
Strongly agree
Somewhat agree
‘Neutral’
Somewhat disagree
Strongly disagree
Strongly agree
Somewhat agree
‘Neutral’
Somewhat disagree
Strongly disagree
Strongly agree
Somewhat agree
‘Neutral’
Somewhat disagree
Strongly disagree
Strongly agree
Somewhat agree
‘Neutral’
Somewhat disagree
Strongly disagree
More
‘Neutral’
Less
Yes
No
476 (29.9)
691 (43.5)
5 (0.3)
301 (19.0)
115 (7.3)
157 (9.6)
766 (46.7)
3 (0.2)
436 (26.6)
276 (16.9)
312 (19.1)
651 (40.0)
9 (0.6)
413 (25.4)
244 (15.0)
133 (8.0)
282 (17.1)
8 (0.5)
484 (29.3)
744 (45.1)
139 (8.8)
460 (29.2)
16 (1.0)
429 (27.2)
533 (33.8)
307 (21.9)
145 (10.4)
946 (67.7)
1472 (90.6)
152 (9.4)
‘How easy or difficult is it for people living on low
incomes in [city name] to obtain each of the following.
First, what about affordable housing?’ (2) ‘Giving their
children a good start in life?’ (3) ‘What about affordable
healthy food?’ (4) ‘Affordable public transportation in
[city name]?’ (5) ‘And do you think it is very difficult,
somewhat difficult, or not difficult for people on low
incomes to adopt healthy behaviours like having a good
diet, not smoking and so on?’ Response categories for
© 2005 Blackwell Publishing Ltd, Health and Social Care in the Community 13(6), 514–530
Lay understanding of poverty
the five items were ‘very difficult’, ‘somewhat difficult’
and ‘not difficult’. Although respondents were much
more likely to feel that affordable housing was more
inaccessible than public transportation; for example, all
of the items in this index were strongly, significantly
and positively related to one another (with values for
Kendall’s tau_b ranging from a low of 0.25 to a high of
0.52, P < 0.001 in all cases). Cronbach’s alpha for the
‘tough life’ index was 0.73.
For those respondents who agreed that low-income
people participate less in community events than others,
we included six additional survey items pertaining to
possible explanations: (1) ‘People with low incomes do
not have enough time to participate in community events
and recreational activities.’ (2) ‘Other people do not make
people with low incomes feel welcome at community
events and recreational activities.’ (3) ‘People with low
incomes do not have enough money to participate in
community events and recreational activities.’ (4) ‘People
with low incomes choose not to participate in community events and recreational activities.’ (5) ‘People
with low incomes participate less in community events
and recreational activities because they are more likely
to have health problems.’ (6) ‘People with low incomes
participate less in community events and recreational
activities because they do not know what is available.’
The response categories for each of these items were
‘strongly agree’, ‘agree’, ‘disagree’ and ‘strongly disagree’.
Finally, for those respondents who recognise the
existence of a relationship between poverty and health,
we asked several additional items pertaining to possible
rationales, using survey items adapted from Reutter
et al. (1999): (1) ‘Not having adequate shelter, food, or
clothes is the main reason poor people have bad health.’
(2) ‘Lifestyle choices like smoking, poor diet, not getting
any exercise and so on are the main causes of bad health
for poor people.’ (3) ‘Poor people have more stress in
their lives than other people.’ The response categories
for these items were ‘strongly agree’, ‘agree’, ‘disagree’
and ‘strongly disagree’.
models were then used to determine the effects of basic
demographic and socioeconomic variables (age, gender,
education, household income), exposure to poverty and
attribution for poverty on the three dependent variables
that describe respondents’ perceptions of various effects
of poverty: participation in community life, the relationship
between health and poverty and challenges facing lowincome people. Logistic regression models were used to
predict the belief that low-income people participate
‘less’ in community events than other people (vs. ‘more’
or ‘neutral’ responses) and to predict the belief that a
relationship exists between poverty and health. Multiple linear regression models were used to predict the
degree to which respondents believe that low-income
people live a ‘tough life’.
This paper focuses primarily on the results of the
Phase II survey, with contributions from Phase I
qualitative data to provide context and interpretation
of the quantitative findings as appropriate.
Results
Demographic characteristics of survey participants
A total of 1671 people were surveyed (839 from Edmonton
and 832 from Toronto), with approximately equal
numbers of participants in each neighbourhood. The
conservatively estimated response rate (the number of
completed interviews divided by the estimated number
of eligible households) was 58%. Demographic characteristics of the survey sample are presented in Table 1.
The response rate is respectable but low enough to
caution against treating our numerical results as
representative of the neighbourhoods. Moreover, our
comparison of the demographic breakdown of our
survey sample in each neighbourhood to the 2001
Census along the lines of age, gender, educational
attainment and household income revealed that our
survey sample on the whole was better educated and a
little wealthier than the population from which the
sample was drawn.
Data analysis
Data from the Phase I taped and transcribed interviews
were transported into the NUD*IST qualitative software
program, and analysed using thematic content analysis.
A coding framework was developed from the initial
interviews and revised as analysis proceeded. The
coding categories were identified via inductive analysis
(moving from particular experiences of participants to
general themes or categories). Phase II survey data were
analysed using SPSS 11.0. First, descriptive statistics
were estimated for selected survey items and indices
created from survey items. Multivariate regression
Exposure to poverty
Table 2 reveals that while very few respondents had
personally experienced receiving welfare/social assistance, almost two-thirds had known family members or
close friends living on low incomes. About 4 in 10 had
personal experience working with low-income people
in their jobs or through volunteer work. Similar proportions had learned about poverty indirectly through
informational sources such as courses or workshops,
while almost all claimed to have learned about poverty
through the media.
© 2005 Blackwell Publishing Ltd, Health and Social Care in the Community 13(6), 514–530
519
L. I. Reutter et al.
Attributions for poverty
When asked to indicate their agreement with statements
addressing individualistic, sociocultural and structural
explanations of poverty, respondents were most likely
to give credence to structural explanations (Table 2).
Almost three-quarters of respondents agreed that
government policies may be responsible for poverty,
while the belief that there are unequal opportunities in
society was endorsed by 59% of respondents. Just over
half believed that there is constancy in poverty across
generations, while slightly over one-third agreed that
poverty is an inevitable part of progress and globalisation. Although the least popular explanation was an
individualistic one, a full quarter of respondents thought
that laziness was a viable reason for poverty.
Effects of poverty
Table 2 reveals that just over two-thirds of respondents
agreed that low-income people are less likely than others
to participate in community events and recreational
activities. When asked to indicate their agreement on
various reasons why low-income people may participate
less than others, 74.6% (n = 691) of these respondents
identified financial constraints, while 69.1% (n = 637)
thought that non-participation resulted from not
knowing what is available. However, 54.3% (n = 492)
believed that low-income people choose not to participate. About half (n = 468) thought that time was a
constraining factor, while fewer respondents identified
being made to feel unwelcome (43.1%, n = 397) or
health reasons (37.3%, n = 332) as factors influencing
non-participation.
When asked about the effect of poverty on health,
nearly everyone agreed that there is a relationship
between poverty and health (Table 2). When participants who answered affirmatively were then asked
to indicate their agreement on various explanations of
how poverty influences health, material deprivation of
basic necessities was given priority, with 82.9% (n =
1204) of people agreeing to some extent, and 46.3%
(n = 673) strongly agreeing. A behavioural explanation
of the relationship between poverty and health focusing
on lifestyle choices (e.g. smoking, poor diet, not getting
exercise) was endorsed by 75.1% (n = 1076) of respondents, with just over one-third (35.6%, n = 510) agreeing
strongly. In addition, 69.8% (n = 1011) agreed to some
extent (with 42.3%, n = 612 strongly agreeing) that poor
people have more stress in their lives.
To assess their understanding of the effects of
poverty on daily life, we asked respondents about their
perceptions of the difficulties that poverty may pose in
accessing basic resources. Obtaining affordable housing
520
was deemed especially challenging for low-income
people, with almost all (95.8%, n = 1524) indicating this
would be difficult, and 62.0% (n = 985) saying ‘very
difficult’. Other resources were considered to be
somewhat less difficult to access; however, all (except
affordable transportation) were viewed as difficult to at
least some degree by at least 70% of the respondents.
Giving children a good start in life was seen as difficult
by 86.5% (n = 1403) of respondents (and ‘very difficult’
by 37.2%, n = 604), obtaining affordable healthy food by
76.3% (n = 1238) of respondents (and ‘very difficult’ by
24.6%, n = 399), and adopting healthy lifestyle behaviours
by 72.3% (n = 1143) of respondents (and ‘very difficult’
by 23.8%, n = 376). Affordable public transportation
was thought to be difficult to obtain by 66.7% (n = 1065)
of respondents, with only 18.3% (n = 292) identifying
this as ‘very difficult’.
In the next section we explore demographic, exposure
to poverty and attributions for poverty predictors of
respondents’ perceptions regarding (i) participation
of low-income people in community events, (ii) the
existence of a poverty–health relationship and (iii) the
‘tough life’ of people living with low incomes. A series
of multivariate models describing predictors of these
three dependent variables are presented in Tables 3, 4
and 5. For each dependent variable we present a model
of demographic variables only, a second model with
demographics and the variables pertaining to exposure
to poverty, and a third model with demographic and
attributions for poverty variables. The latter two models
for each dependent variable allow us to determine the
degree to which the exposure to poverty and attributions
for poverty variables predict opinions on the effects
of poverty over and above personal demographic
circumstance.
Predictors of effects of poverty
Participation in community life
Model I in Table 3 shows that younger respondents
(OR 0.990, P = 0.025) and especially males (OR 0.616,
P < 0.001) were less likely than older respondents and
women, respectively, to think that low-income people
participate less in community events, after controlling for
the other demographic variables. Interestingly, neither
education nor household income had statistically significant relationships with this perception in the multivariate models of Table 3. Contrary to our expectations,
Model II shows that personally experiencing welfare
made respondents less likely to believe that low-income
people participate less in community events after
controlling for the other variables (OR 0.620, P = 0.008).
Model III suggests that only one of the variables relating
to attribution for poverty (i.e. intergenerational) was
© 2005 Blackwell Publishing Ltd, Health and Social Care in the Community 13(6), 514–530
© 2005 Blackwell Publishing Ltd, Health and Social Care in the Community 13(6), 514–530
Table 3 Logistic regression models, predicting belief that low-income people participate less in community events
Model I
Model II
Model III
95% CI for OR
Lower
Upper
Year of birth
Gender (male)
Education
Household income
Received welfare (yes)
Friend/family low income (yes)
Worked with poor (yes)
Volunteered with poor (yes)
Learned about poverty in media (yes)
Learned about poverty from talks (yes)
Poverty: government policies (yes)
Poverty: poor families (yes)
Poverty: unequal opportunities (yes)
Poverty: laziness (yes)
Poverty: modern progress (yes)
−0.010
−0.484
−0.035
−0.006
0.990
0.616
0.966
0.994
0.982
0.481
0.907
0.957
0.999
0.790
1.029
1.032
Constant
N
Percent correctly classified percentage
Model chi-squared (sig.)
Nagelkerke R squared
20.15
1207
68.3
23.53 (< 0.001)
0.027
95% CI for OR
B
Odds
ratio
Lower
Upper
−0.010
−0.515
−0.041
−0.020
−0.478
< 0.001
0.042
0.041
−0.005
−0.120
0.990
0.597
0.959
0.981
0.620
1.000
1.043
1.041
0.995
0.887
0.982
0.463
0.898
0.943
0.437
0.759
0.791
0.794
0.622
0.675
0.999
0.771
1.025
1.020
0.880
1.317
1.376
1.365
1.591
1.166
20.34
1183
68.7
32.91 (< 0.001)
0.039
95% CI for OR
B
Odds
ratio
Lower
Upper
−0.008
−0.608
−0.034
−0.011
0.992
0.545
0.967
0.989
0.983
0.419
0.903
0.950
1.001
0.708
1.036
1.030
0.016
0.279
0.183
0.295
0.173
1.017
1.322
1.201
1.343
1.188
0.742
1.007
0.903
0.971
0.904
1.393
1.734
1.597
1.858
1.562
16.57
1097
67.6
38.18 (< 0.001)
0.048
521
Lay understanding of poverty
B
Odds
ratio
L. I. Reutter et al.
522
Table 4 Logistic regression models, predicting belief that there is a relationship between poverty and health
Model I
Model II
Model III
95% CI for OR
© 2005 Blackwell Publishing Ltd, Health and Social Care in the Community 13(6), 514–530
B
Odds
ratio
lower
upper
Year of birth
Gender (male)
Education
Household income
Received welfare (yes)
Friend/family low income (yes)
Worked with poor (yes)
Volunteered with poor (yes)
Learned about poverty in media (yes)
Learned about poverty from talks (yes)
Poverty: government policies (yes)
Poverty: poor families (yes)
Poverty: unequal opportunities (yes)
Poverty: laziness (yes)
Poverty: modern progress (yes)
−0.017
−0.184
0.211
0.066
0.983
0.832
1.234
1.068
0.971
0.571
1.121
1.006
0.995
1.213
1.359
1.133
Constant
N
Percent correctly classified percentage
Model chi-squared (sig.)
Nagelkerke R squared
34.60
1399
90.8
43.66 (< 0.001)
0.067
95% CI for OR
B
Odds
ratio
lower
upper
−0.019
−0.130
0.185
0.069
0.335
0.251
0.040
0.481
0.713
0.312
0.981
0.878
1.204
1.071
1.399
1.286
1.041
1.617
2.040
1.367
0.969
0.598
1.089
1.007
0.806
0.860
0.673
1.043
1.163
0.875
0.994
1.290
1.331
1.139
2.428
1.922
1.610
2.508
3.576
2.134
36.52
1370
90.7
66.23 (< 0.001)
0.102
95% CI for OR
B
Odds
ratio
lower
upper
−0.019
−0.296
0.167
0.084
0.981
0.744
1.182
1.087
0.968
0.496
1.064
1.019
0.994
1.115
1.314
1.160
0.448
0.725
0.533
−0.579
0.302
1.566
2.064
1.703
0.560
1.353
1.009
1.356
1.114
0.367
0.884
2.431
3.142
2.604
0.856
2.071
37.95
1231
90.5
88.46 (< 0.001)
0.148
© 2005 Blackwell Publishing Ltd, Health and Social Care in the Community 13(6), 514–530
Table 5 Multiple linear regression models, predicting degree to which respondent believes that low-income people live a difficult life (‘tough life’ index)
Model I
Model II
Model III
95% CI for B
Beta
Lower
Upper
Year of birth
Gender (male)
Education
Household income
Received welfare (yes)
Friend/family low income (yes)
Worked with poor (yes)
Volunteered with poor (yes)
Learned about poverty in media (yes)
Learned about poverty from talks (yes)
Poverty: government policies (yes)
Poverty: poor families (yes)
Poverty: unequal opportunities (yes)
Poverty: laziness (yes)
Poverty: modern progress (yes)
−0.043
−1.448
0.136
−0.108
−0.139 −0.060 −0.026
−0.156 −1.958 −0.938
0.062
0.007
0.264
−0.083 −0.185 −0.030
Constant
N
F-statistic (sig.)
R squared
71.64
1249
20.03 (< 0.001)
0.060
B
Beta
Lower
−0.049
−1.311
0.078
−0.100
0.403
0.268
0.180
0.400
−0.728
1.240
−0.156
−0.141
0.035
−0.077
0.032
0.027
0.019
0.043
−0.041
0.132
−0.066 −0.032
−1.820 −0.801
−0.055
0.210
−0.179 −0.021
−0.314
1.119
−0.275
0.811
−0.378
0.738
−0.143
0.942
−1.699
0.242
0.690
1.790
82.573
1235
11.85 (< 0.001)
0.088
Upper
95% CI for B
B
Beta
Lower
−0.045
−1.057
0.034
−0.142
−0.143
−0.115
0.015
−0.110
−0.061 −0.028
−1.543 −0.572
−0.093
0.160
−0.216 −0.068
1.775
0.682
2.410
−1.360
−0.296
0.166
0.074
0.255
−0.127
−0.031
1.195
2.355
0.186
1.178
1.886
2.934
−1.947 −0.773
−0.797
0.206
72.837
1139
35.15 (< 0.001)
0.219
Upper
523
Lay understanding of poverty
B
95% CI for B
L. I. Reutter et al.
significant (and just barely, with OR 1.322, P = 0.044) when
controlling for demographics; only gender remained
a strong and significant predictor in this model. Values
of the Nagelkerke R squared suggested that very little
variability was explained by these models.
Relationship between poverty and health
Model I in Table 4 reveals that year of birth (OR 0.983,
P = 0.004), household income (OR 1.068, P = 0.030) and
especially education (OR 1.234, P < 0.001) were predictors
of a belief in a poverty–health relationship in a model of
demographic variables, wherein older, better-educated
and wealthier respondents were more likely than their
respective counterparts to hold this belief. In Model II,
knowledge about poverty gleaned from the media (OR
2.040, P = 0.013) and volunteering with low-income
people (OR 1.617, P = 0.032) had statistically significant
effects on this perception, after controlling for the other
variables. In total, the Nagelkerke R squared values in
Models I and II indicate that only a modest amount
of the variability in this perception was explained by
exposure to poverty and demographic variables. Model
III shows that three causal explanations for poverty
predicted a belief in the relationship between poverty
and health, over and above the influence of demographics:
those who blame low-income people for their poverty
(the laziness explanation) were less likely (OR 0.560, P =
0.007) and those who viewed poverty as intergenerational (OR 2.064, P = 0.001) or resulting from unequal
opportunities (OR 1.703, P = 0.014) were more likely than
their respective counterparts to support a link between
poverty and health. According to the Nagelkerke value
in Model III, demographics and attributions for poverty
together predicted a sizeable proportion of the total
variability.
Challenges facing low-income people
As shown in Model I of Table 5, younger and male
respondents were much less likely than older and female
respondents to believe that low-income people have a
tough life (P < 0.001 in both cases). Wealthier respondents were also less likely than poorer respondents to
believe this to be the case after controlling for the other
demographic variables (P = 0.007), whereas bettereducated respondents were slightly more likely than
less well-educated people to believe this (P = 0.039).
Learning about poverty from courses and workshops
made a statistically significant contribution to Model II,
wherein respondents who learned about poverty in this
way were more likely than others to believe that lowincome people live a tough life (P < 0.001). Education,
however, was no longer a significant predictor. Overall,
only a modest proportion of variability was explained
by these two models (between 6% and 9%). Model III
524
reveals that all but one of the explanations of poverty
were significant predictors of the perception that lowincome people have a difficult life, when controlling for
demographics. Those who believe that poverty results
from unequal opportunities (P < 0.001), from government policies (P < 0.001), or constancy in families (P =
0.007) were more likely than their respective counterparts
to indicate that low-income people have some difficult
struggles in life. On the other hand, the explanation that
poverty is due to laziness was negatively associated
with the belief that low-income people have difficulty
meeting basic needs (P < 0.001). The demographics and
explanations together explained a full 22% of the variability in this dependent variable.
Qualitative findings
We conducted individual interviews with 59 lowincome people and 60 higher-income people. In both
the low-income and higher-income samples, about twothirds of participants were women (67.8% and 66.7%,
respectively). The majority of low-income and higherincome participants were between 30–54 years of age
(62.1% and 69%, respectively). However, the low-income
participants were younger overall: 20.7% were under
30 years vs. 6.8% of the higher-income participants,
and 17.2% of the low-income participants were 55 years
and older, compared with 24.1% of the higher-income
participants. Low-income people were more likely to
live alone (50% vs. 13.8%), and to be in single-parent
households (22.4% vs. 6.9%). People living below the
poverty line were more likely than their higher-income
counterparts to have high school education or less (48.3%
vs. 8.6%) and less likely to have a university degree
(12.1% vs. 67.2%). About 12.1% of the low-income
participants had incomes below $5000; 27.6% between
$5000–9999, and 48.3% between $10 000–19 999. By
comparison, 36.8% of higher-income participants had
incomes between $20 000–59 999, 40.1% between
$60 000–99 999, and 22.8% had incomes of $100 000 or
more. Almost equal numbers of low-income participants
cited welfare (31%) and employment (29.3%) as their
main source of income, with 25.9% also citing disability
pensions. A total of 82.8% of higher-income participants
were employed. In terms of housing, 82.8% of higherincome people owned their home compared to only
10.3% of low-income people. Half of the low-income
sample paid market rent while a third (31%) lived in
subsidised housing.
We conducted six group interviews with low-income
people (n = 34). In this sample, 67.6% of participants
were female; 60.6% had a high school education or
less, and 3 (9.1%) had a university degree. Almost
half (44.1%) were 30 –44 years of age; there were no
© 2005 Blackwell Publishing Ltd, Health and Social Care in the Community 13(6), 514–530
Lay understanding of poverty
participants younger than 20 years or older than
64 years. The main source of income was welfare
(41.2%) and employment (38.2%). Only two participants owned their own home, 61.8% paid market
rent, and 32.4% lived in subsidised housing. About onethird (35.3%) were single parents, 29.4% were twoparent families with children at home, and 26.5% were
living alone.
The qualitative interviews provide further understanding and context regarding public perceptions of
the effects of poverty. People living in poverty as well as
wealthier respondents described how poverty negatively
influences the lives of low-income people, often using
descriptors such as ‘drastically’ and ‘profoundly’.
When asked how low income may affect people’s
health, the most commonly identified response by both
low-income and higher-income people was the inability
to obtain nutritious food. Although a few participants
(primarily higher-income people) attributed this to lack
of knowledge or skills, in that ‘[poor people] need to be
taught nutrition and how to make cheaper meals … in
other words, learn how to cook’, most participants
focused on inadequate purchasing power as the major
reason for inadequate nutrition and other healthenhancing activities:
Low income, especially government-supported income, is just
a guarantee for increased poor health, because you can’t afford
to buy the healthy foods or vitamins, and there’s not a lot of
access to things where you can pick yourself up and get some
exercise and feel like you’re part of stuff. (Higher-income
participant)
You’re trying to get them [children] to eat healthy, but you
can’t afford for them to eat healthy. So … you buy junk food
‘cause it’s cheaper … My kids love fresh broccoli, fresh
cauliflower – but we did without that for most of the time we
went through this retraining and finding a job process …
When fresh fruit … and even canned fruit … turns out just
to be a treat, there’s something wrong. (Low-income
participant)
Inaccessibility to healthcare services was also perceived
to influence health. In spite of Canada’s publicly funded
healthcare system wherein there are no direct costs for
medical and hospital services, there may be limited or
no coverage for other services. Both low- and higherincome participants commented that low-income
people may be unable to purchase prescription and
over-the-counter drugs and have decreased access to
non-insured services (e.g. dentists, optometrists, physiotherapists). As one higher-income participant stated,
‘They’ll tend not to go to the doctor because they know
there will be prescriptions to buy.’ The following
comment from a low-income participant exemplifies
the hardship in accessing proper dental care:
I have bad teeth … they’re getting worse. I have a dentist that’s
fixing my teeth … He’s taking all the little money that I have.
I owe him money … and I can’t go until I pay him at least that
much … We should be ashamed of our whole medical system
and our dental system in this country.
Congruent with the survey responses, many interview
participants concurred that poverty is stressful, largely
because of the constant struggle and uncertainty of
‘making ends meet’. Those living in poverty poignantly
recounted how depression and low self-esteem can
result from feelings of inadequacy as parents, not being
respected or cared about by others, and being ‘stuck’ in
a poverty situation with little hope:
When you’re having to pay the mortgage one month but
then the utilities don’t get paid … it’s nerve-wracking. It is so
stressful … my husband had a real hard time not biting at us
… it’s starting to put the family itself in danger.
I feel depressed about my situation … it makes me feel like I’m
not worth anything. I feel like I can’t provide for myself or my
daughter because I’m in subsidized housing because I’m on
social assistance right now. It almost feels impossible to get out
of … you feel stuck.
Those not living in poverty also acknowledged the
increased stress levels of low-income people and the
attendant feelings of low self-esteem, hopelessness and
depression:
Lack of support for working poor is abysmal in this society,
extremely stressful, and affects health of the whole family.
Poor people are attacked in a spiritual and a psychological
way – things that we take for granted they don’t have. You
know, they have to go and explain their story to how many
people to get assistance? I just think that’s just gross … there’s
a kind of mythology that if people wanted to work they could
find a job right now.
Higher-income people recognised that behaviours,
such as smoking, alcohol or drug consumption, are
often coping strategies to manage the stress of poverty:
I mean there’s more anxiety. You really notice how poor
people smoke more … And I think it’s linked to anxiety to a
great extent.
I guess poverty leads to excessive use of alcohol because of the
feeling of alienation and hopelessness, helplessness.
In their discussions about the effects of poverty,
higher-income people affirmed the views of those living
in poverty that basic resources, such as housing, are
often inaccessible for low-income people:
When you start to factor in housing and transportation and
heating, there can’t be much left for food or anything else.
It’s employment and housing and food and all your basics …
are all part of that health and a healthy lifestyle. And being
© 2005 Blackwell Publishing Ltd, Health and Social Care in the Community 13(6), 514–530
525
L. I. Reutter et al.
able to do the activities and being able to buy the medications
and having a job, having a place to sleep so that you can get to
that job. All of those things are part of health.
When asked to comment on whether they believe
that people living in poverty are ‘excluded’, the majority
of higher-income participants acknowledged that lowincome people, including children, are most likely
excluded from mainstream society. As with the findings
from the quantitative survey, the major reason cited
was financial constraints:
It’s the cost of transportation, the cost of babysitters … you
can’t really go any place without having it cost you something.
In a lot of the athletics, young kids need expensive equipment.
A lot of people can’t afford these things.
Several higher-income participants also acknowledged, however, that low-income people may decide not
to participate because of low self-esteem, or embarrassment and shame of their poverty status:
Oh definitely they’re excluded. There’s so many barriers when
you’re low income, be it the means to get there [transportation], the money to participate, the sense of self-worth that you
are as good as everyone else that’s accessing the service.
There’s a certain shame associated with poverty, so they might
not get involved with people that aren’t in the same circumstances… . Children may feel that they wouldn’t want to
participate because they don’t have the same things as others.
Higher-income participants suggested that low-income
people may feel uncomfortable participating because
they have different interests and experiences than those
who have more financial resources. An example was
given of how postnatal group discussions ‘exclude’ the
experiences of low-income women, which inhibits their
participation. These behaviours of the non-poor may be
perceived as ‘unwelcoming’. Only a few higher-income
people mentioned that non-participation of low-income
people may be due to lack of awareness, and none
mentioned health as a constraining factor. Overall,
comments about exclusion of low-income people were
not elaborated to the same degree as the effects of
poverty on health and access to basic resources.
Low-income participants identified many areas of
non-participation in community life (e.g. social, leisure,
cultural, family). Their reasons for non-participation
included health problems, inadequate financial resources
(user fees, high cost of basic necessities leaving little
disposable income for social activities), transportation
costs and exclusionary behaviours of others. Some
participants also indicated that they may isolate themselves (i.e. ‘choose’ not to participate) because of shame
and embarrassment of their poverty status, and to
protect themselves from the judgements of others. The
526
following comments speak to several of the factors that
constrained participation among low-income people:
A lot of [community programs] don’t accept the fee reduction
[program]… . They can only accept so many fee reduction
people, and they can only accept fee reduction people on
certain programs.
I feel as if I’m sort of really stuck as far as all those social events
go, because I don’t have the spare money, and they don’t
invite me … people just don’t include you if they figure you’re
going to be a financial burden on them.
I find it hard sometimes to go to the outside things because I
feel like people might be judging me because I’m on assistance
or low income. Sometimes I feel like they can tell just by
looking at me.
Discussion
This study found that, overall, a substantial majority of
study participants acknowledge the negative effects of
poverty on the lives of low-income people. Further, the
study suggests that a multitude of different factors –
demographics, exposure to poverty and attributions for
poverty – influence public understandings of these
effects.
Almost all survey respondents agreed that there is
a relationship between poverty and health, and while
most respondents favored a material deprivation explanation of that relationship, they also acknowledged the
presence of health-inhibiting behaviours and stress in
the lives of those living in poverty. That people have
multiple explanations for health inequalities has been
documented in other research (Blaxter 1997, Popay et al.
2003). As in this study, Popay et al. (2003) found that
structural factors were given more prominence in lay
theories of causation of health inequalities than were
individual behaviours. This finding also supports previous Canadian research, wherein a majority of Albertans
favoured a structural over a behavioural explanation of
the relationship between poverty and health (Reutter
et al. 1999, 2002).
A large majority of study respondents acknowledged the difficulties low-income people encounter in
accessing resources that influence family health and
well-being. It is not surprising that affordable housing
was thought to be particularly difficult to obtain, given
the acute housing shortage in these cities, especially
Toronto, due in part to reduced government provision
of social housing and lack of affordable rental accommodation (Bryant 2004). Interestingly, obtaining affordable food, adopting healthy lifestyle behaviours and
giving children a good start in life were not considered
to be as difficult, yet were clearly viewed as challenging.
Perhaps these resources are thought to be within the
© 2005 Blackwell Publishing Ltd, Health and Social Care in the Community 13(6), 514–530
Lay understanding of poverty
control of the individual (for example, through proper
money management) to a greater extent than is housing.
Respondents may also believe that there are adequate
resources available to meet these needs (e.g. food banks).
There is strong research evidence pertaining to the
effect of income on food security, child development
and health behaviours in Canada. Over one-quarter of
families receiving social assistance/welfare in Canada
report a compromised diet (Che & Chen 2001). Foodbank use in Canada has more than doubled since 1989
(Raphael et al. 2004), and in Alberta increased 30%
between 1997 and 2003, attributed in part to rising
housing and utility costs (Orchard et al. 2003). Similarly,
there is overwhelming evidence to show that children
living in poverty are disadvantaged. They are more
likely than their counterparts to experience chronic
medical problems (CCSD 1997) and are at greater risk
for poor school performance and a variety of other
negative developmental outcomes (Lipps & Frank 1997,
Ross & Roberts 1999). Finally, people living on low
incomes are also disadvantaged in terms of adopting
healthy behaviours such as physical activity (Ross &
Roberts 1999, CIHI 2004) and are more likely to smoke
(Health Canada 2003).
In contrast with study participants’ considerable
understanding of the consequences of poverty on health
and obtaining basic necessities in life, there is markedly
less recognition of the effects of poverty on exclusion
from community life. There is solid evidence showing
that social networks, social activities, and participation
in groups/associations are associated with enhanced
health and well-being (Wilkinson 1996, Cattell 2001,
Lindstrom et al. 2002, Reid et al. 2002). Low-income
people are less likely to participate in community life
(Baum et al. 2000, Lindstrom et al. 2002), which was also
borne out in this study (Stewart et al. 2004). Less attention
by the public to this aspect of poverty may indicate that
the public discourse on poverty has most commonly
reflected an ‘absolute’ definition of poverty emphasising
lack of basic necessities rather than a ‘relative’ definition
focusing on the inability to participate meaningfully in
society. Of particular interest is the finding that over
half of those who believed that low-income people tend
to participate less than others thought that they choose
not to participate.
One of the strengths of this study is the inclusion of
both exposure to poverty and attributions for poverty
(along with demographic characteristics) as factors
potentially influencing beliefs about the effects of
poverty on health and well-being. Overall, exposure to
poverty contributed very little to the variability in
perceptions of the effects of poverty when controlling
for demographics. Interestingly, having close friends or
family members who were living on low incomes or
working with low-income people did not influence
survey participants’ understanding of any of the three
variables representing the effects of poverty. Previous
or present experience with welfare influenced only the
belief that the poor participate less in community life
(and not in the expected direction). The media appeared
to be not only the most important source of information
about poverty but also positively influenced understanding of the link between poverty and health, which may
reflect increased media attention to this issue. Although
far fewer survey respondents had been exposed to
poverty through formal talks, this type of exposure was
strongly related to understanding the challenges faced
by low-income people. This supports other research
(Wilson 1996, Reutter et al. 2004) reporting that formal
exposure to poverty can positively influence structural
understandings of poverty.
Greater variability in perceptions of the effects of
poverty was accounted for by respondents’ causal explanations of poverty. As might be expected, structural and
sociocultural (intergenerational) explanations predicted
greater understanding of the effects of poverty, particularly for the challenges encountered in daily life, while
those who supported an individualistic explanation that
low-income people are to blame for their poverty were
less likely to acknowledge the negative effects of poverty.
Attributions for poverty together with demographics
contributed a full 22% of the variability in the ‘tough
life’ index and a sizeable proportion of the variance in
the belief that poverty is linked to health.
Several demographic characteristics exerted independent effects when considered in conjunction with
exposure and attributions for poverty. In particular,
age, education and income were positively associated
with a belief in the link between poverty and health,
suggesting that those in status positions appear to be
more ‘enlightened’ about the health consequences of
poverty. Being older, female and less wealthy were all
markers for acknowledging the challenges faced by
those living in poverty. Older, less wealthy respondents
may be more likely to have first-hand experience of
these difficulties, while female respondents as ‘primary
resource managers and caregivers’ may have a greater
understanding of the cost of resources. Interestingly,
respondents’ income did not influence their understanding about the effects of poverty on participation in
community life.
There are several limitations of this study that point
to the need for further research. First, our survey was
conducted in only eight neighbourhoods in two large
urban areas. By employing a representative sample of
economically diverse neighbourhoods in two cities, the
results of this study may have applicability in other
large urban centres in Canada. However, non-English-
© 2005 Blackwell Publishing Ltd, Health and Social Care in the Community 13(6), 514–530
527
L. I. Reutter et al.
speaking people and those who do not have landline
telephones were not included. In 2003, 3.7% of private
households in Canada did not have telephones (Statistics
Canada 2003). Low-income people may have been
under-represented in our sample as they may be less
likely to have telephones. Additionally, recent nonEnglish-speaking immigrants may be under-represented;
recent immigrants to Canada are more likely to live in
poverty (Lee 2000). It may also be the case that rural
populations hold different views about the effects of
poverty. A further limitation is that our survey questions
reflect the assumption that people have an undifferentiated view of poverty, when they may hold different
beliefs about the effects of poverty for different lowincome populations (Wilson 1996). Finally, while our
study provided data regarding perceptions of effects of
poverty, further research is needed to understand how
these perceptions influence respondents’ support for
poverty-related policies and programmes as well as
their relationships and interactions with people living
in poverty.
Overall, our findings suggest that the Canadian
public has considerable understanding of the challenges
faced by people living in poverty and the negative
effects of poverty on health. On the other hand, there is
also room for greater understanding in some areas,
particularly in relation to the exclusion of low-income
people from community life. The study points to the role
that indirect exposure to poverty through educational
presentations may have in enhancing public understanding. Public dialogue groups, such as those instituted
by the Canadian Policy Research Networks, have been
found to change beliefs and attitudes about povertyrelated issues (Peters 1995, Saxena 2003). Current initiatives such as the Inclusive Cities Project in five Canadian
cities, including Toronto and Edmonton, will hopefully
increase public dialogue and exposure to the concept of
inclusion. Given that the main information source for
the public is the media, it is important that media
presentations of poverty reflect the whole array of
effects of poverty on health, including the myriad
challenges in accessing basic resources and being able to
participate meaningfully in society. Public understanding of these effects may lead to greater support and
advocacy for policies and programmes that ultimately
will enhance health and well-being.
Acknowledgements
This study was funded by Social Sciences and Humanities Research Council of Canada. We gratefully
acknowledge the Institute for Social Research, York
University, for their administration of the survey, and
our community partners in Toronto and Edmonton.
528
References
Alesina A. & Glaeser E.L. (2004) Fighting Poverty in the US and
Europe: A World of Difference. Oxford University Press,
Toronto, ON.
Baum F., Bush R., Modra C., Muray C., Cox E., Alexander K.
& Potter R. (2000) Epidemiology of participation: an
Australian community study. Journal of Epidemiology and
Community Health 54, 414 – 423.
Blaxter M. (1997) Whose fault is it? People’s own conceptions
of the reasons for health inequalities. Social Science and
Medicine 44, 747–756.
Bryant T. (2004) Housing and health. In: D. Raphael (Ed.)
Social Determinants of Health: Canadian Perspectives, pp. 217–
232. Canadian Scholars Press, Toronto, ON.
Bullock H. (1999) Attributions for poverty: a comparison of
middle-class and welfare recipient attitudes. Journal of Applied
Social Psychology 29, 2059 –2082.
Bullock H., Williams W. & Limbert W. (2003) Predicting
support for welfare policies: the impact of attributions
and beliefs about inequality. Journal of Poverty 7 (3), 35–
56.
Burstein P. (1998) Bringing the public back in: should sociologists consider the impact of public opinion on public policy?
Social Forces 77 (1), 27– 63.
CCSD (1997) The Progress of Canada’s Children 1997. Canadian
Council on Social Development, Ottawa, ON.
CIHI. (2004) Improving the Health of Canadians. Canadian
Institute for Health Information, Ottawa, ON.
Cattell V. (2001) Poor people, poor places, and poor health: the
mediating role of social networks and social capital. Social
Science and Medicine 52, 1501–1516.
Che J. & Chen J. (2001) Food insecurity in Canadian households. [electronic version]. Health Reports 12 (4), 11–22.
Clutterbuck P. (2003) Building Inclusive Communities: A Social
Infrastructure Strategy for Canadian Municipalities. Final Report
on Cross-Canada Community Soundings for the Children’s
Agenda Program, The Laidlaw Foundation. The Laidlaw
Foundation, Toronto, ON.
Clutterbuck P. & Novick M. (2003) Building inclusive communities. Cross-Canada perspectives and strategies. Perception 26 (1 & 2), 19 –23.
Cook F. & Barrett E. (1992) Support for the American Welfare State:
The Views of Congress and the Public. Columbia University
Press, New York.
Cozzarelli C., Tagler M. & Wilkinson A. (2002) Do middle-class
students perceive poor women and poor men differently?
Sex Roles 47, 519 –529.
Cozzarelli C., Wilkinson A. & Tagler M. (2001) Attitudes
toward the poor and attributions for poverty. Journal of
Social Issues 57, 207–227.
Dunn J. (2002) Are Widening Income Inequalities Making Canada
Less Healthy? Ontario Public Health Association, Retrieved
20 May 2004 from http://www.opha.on.ca/resources/
incomeinequalities/incomeinequalities.pdf.
Federal, Provincial, and Territorial Advisory Committee on
Population Health. (1994) Strategies for Population Health:
Investing in the Health of Canadians. Minister of Supply and
Services Canada, Ottawa.
Federation of Canadian Municipalities. (2003) Falling Behind:
Our Growing Income Gap. Prepared by Caryl Arundel and
Associates in association with Henson Consulting Ltd,
Retrieved 13 May 2004 from http://www.fcm.ca/english/
communications/igover.pdf.
© 2005 Blackwell Publishing Ltd, Health and Social Care in the Community 13(6), 514–530
Lay understanding of poverty
Galabuzi G.E. (2004) Social exclusion. In: D. Raphael (Ed.)
Social Determinants of Health: Canadian Perspectives, pp. 235 –
251. Canadian Scholars Press, Toronto, ON.
Golding P. (1995) Public attitudes to social exclusion: some
problems of measurement and analysis. In: G. Room (Ed.)
Beyond the Threshold: The Measurement and Analysis of Social
Exclusion, pp. 212–232. Policy Press, Bristol, UK.
Health Canada. (2003) Smoking Behaviours of Canadians.
Retrieved 12 May 2004, from http://www.hc-sc.gc.ca/
pphb-dgspsp/ccdpc-cpcmc/cancer/publications/nphs-sboc/
nphs12_e.html.
Hunt M. (1996) The individual, society, or both? A comparison
of black, Latino, and white beliefs about the causes of
poverty. Social Forces 75, 293 –322.
Iyengar S. (1989) How citizens think about national issues: a
matter of responsibility. American Journal of Political Science
33, 878 – 900.
Kluegel L., Mason D. & Wegener B. (Eds) (1995) Social Justice
and Political Change: Public Opinion in Capitalist and Postcommunist States. de Gruyter, New York.
Kushner C. & Rachlis M. (1998) Civic lessons: strategies to
increased consumer involvement. In: Canada Health Action:
Building on the Legacy. Making Decisions: Evidence and
Information, vol. 5, pp. 303 –347. Commissioned Paper by
National Forum on Health. Editions MultiModes, SainteFoy, QC.
Labonte R. (2004) Social inclusion/exclusion and health:
dancing the dialectic. In: D. Raphael (Ed.) Social Determinants of Health: Canadian Perspectives, pp. 253 –266. Canadian
Scholars Press, Toronto, ON.
Lee K. (2000) Urban Poverty in Canada: A Statistical Profile.
Canadian Council on Social Development, Ottawa, ON.
Lee B. & Farrell C. (2003) Buddy, can you spare a dime?
Homelessness, panhandling, and the public. Urban Affairs
Review 38, 299 –324.
Lee B., Lewis D. & Jones S. (1992) Are the homeless to
blame? A test of two theories. Sociological Quarterly 33,
535 –552.
Lindstrom M., Merlo J. & Ostergren P. (2002) Individual and
neighbourhood determinants of social participation and
social capital: a multilevel analysis of the city of Malmo,
Sweden. Social Science and Medicine 54, 1779 –1791.
Link B., Schwartz S., Moore R., Phelan J., Streuening E.,
Stueve A. & Colten M. (1995) Public knowledge, attitudes,
and beliefs about homeless people: evidence for compassion
fatigue? American Journal of Community Psychology 23, 533 –
555.
Lipps G. & Frank J. (1997) The social context of school for
young children. Canadian Social Trends 47, 22.
Lomas J. (1990) Finding audiences, changing beliefs: the
structure of research use in Canadian health policy. Journal
of Health Politics, Policy, and Law 15, 525 –542.
Lott B. (2002) Cognitive and behavioural distancing from the
poor. American Psychologist 57, 100 –110.
Mitchell A. & Shillington R. (2002) Poverty, Inequality, and
Social Inclusion. Working Paper Series: Perspectives on Social
Inclusion. The Laidlaw Foundation, Toronto, ON.
National Council of Welfare. (2002) Poverty Profile 1999.
Minister of Public Works and Government Services Canada,
Ottawa.
van Oorschot W. & Halman L. (1999) To Blame or to Pity? An
International Comparison of Popular Explanations of Poverty.
Working Papers. Netherlands School for Social and Economic Policy Research, Utrecht, The Netherlands.
Orchard L., Penfold R. & Sage D. (2003) Hunger Count 2003.
Canadian Association of Food Banks, Toronto, ON.
Percy-Smith J. (Ed.) (2000) Policy Responses to Social Exclusion:
Towards Inclusion. Open University Press, Buckingham
UK.
Peters S. (1995) Exploring Canadian Values: Foundations for WellBeing. CPRN Study No. F/01. Revised version. Canadian
Policy Research Networks, Inc. Renouf Publishing, Ottawa.
Phipps S. (2003) The Impact of Poverty on Health: A Scan of the
Research Literature. Canadian Institute for Health Information and Canadian Population Health Initiative. Retrieved
13 October 2003 from http://secure.cihi.ca/cihiweb/
disPage.jsp?w_page=home_e.
Popay J., Bennett S., Thomas C., Williams G., Gatrell A. &
Bostock L. (2003) Beyond ‘beer, fags, egg and chips’? Sociology of Health and Illness 25 (1), 1–23.
Raphael D. (2004) Introduction to the social determinants of
health. In: D. Raphael (Ed.) Social Determinants of Health:
Canadian Perspectives, pp. 1–18. Canadian Scholars Press,
Toronto, ON.
Raphael D., Bryant T. & Curry-Stevens A. (2004) Toronto
charter outlines future health policy directions for Canada
and elsewhere. [electronic copy]. Health Promotion International 19, 269 –273.
Reid C., Frisby W. & Ponic P. (2002) Confronting two-tiered
community recreation and poor women’s exclusion:
promoting inclusion, health, and social justice. Canadian
Woman Studies 21 (3), 88 –94.
Reutter L., Harrison M.J. & Neufeld A. (2002) Public support
for poverty-related policies. Canadian Journal of Public Health
93, 97–302.
Reutter L., Neufeld A. & Harrison M.J. (1999) Public perceptions of the relationship between poverty and health.
Canadian Journal of Public Health 90, 13 –18.
Reutter L., Sword W., Meagher-Stewart D. & Rideout E. (2004)
Nursing students’ beliefs about the relationship between
poverty and health. Journal of Advanced Nursing 48, 299 –309.
Room G. (Ed.) (1995) Beyond the Threshold: The Measurement and
Analysis of Social Exclusion. Policy Press, Bristol.
Ross D. & Roberts P. (1999) Income and Child Well-Being: A New
Perspective on the Poverty Debate. Canadian Council of Social
Development, Ottawa.
Saxena N. (2003) Citizens’ Dialogue Experience: Follow-up
Survey Results. Canadian Policy Research Networks Public
Involvement Network, Ottawa.
Sharp E. (1999) The Sometime Connection: Public Opinion and
Social Policy. State University of New York Press, Albany,
NY.
Shaw G. & Shapiro R. (2002) The polls-trends: poverty and
public assistance. Public Opinion Quarterly 66, 105 –128.
Shookner M. (2002) An Inclusion Lens: Workbook for Looking at
Social and Economic Exclusion and Inclusion. Atlantic Regional
Office, Population and Public Health Branch, Health
Canada, Halifax, NS.
Statistics Canada. (2001a) Community Profile – Edmonton;
Community Profile – Toronto. Retrieved on 20 May 2003, from
http://www12.stat.ca/english/profil101/
PlaceseartchForm1.cfm.
Statistics Canada. (2001b) Incidence of low income among the
population living in private households, census metropolitan
areas. Retrieved on 3 November 2003, from http://statcan.ca/
English/Pgdb/famil60i.htm.
Statistics Canada. (2003) Survey of Household Spending 2003.
Author, Ottawa, ON.
© 2005 Blackwell Publishing Ltd, Health and Social Care in the Community 13(6), 514–530
529
L. I. Reutter et al.
Stewart M.J., Reutter L., Veenstra G., Raphael D. & Love R.
(2004) Left-out: Perspectives on Social Exclusion and Social Isolation in Low-Income Populations. Final Report. Social Support
Research Program, University of Alberta, Edmonton, AB.
Whitehead M. (1998) Diffusion of ideas on social inequalities
in health: a European perspective. Millbank Quarterly 76 (3),
469 – 492.
Wilkinson R. (1996) Unhealthy Societies. The Afflictions of Inequality. Routledge Press, London.
530
Wilson G. (1996) Toward a revised framework for examining
beliefs about the causes of poverty. Sociological Quarterly 37,
413 – 428.
World Health Organization. (1997) The Jakarta Declaration on
Health Promotion into the 21st Century. Available online:
http://www.ldb.org/vl/top/jakdec.htm.
Zucker G. & Weiner B. (1993) Conservatism and perceptions
of poverty: an analysis. Journal of Applied Social Psychology
23, 925 –943.
© 2005 Blackwell Publishing Ltd, Health and Social Care in the Community 13(6), 514–530