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Health Policy 91 (2009) 24–32

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Health Policy

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Unmet healthcare need, gender, and health inequalities in Canada

Toba Bryanta,∗, Chad Leaverb, James Dunnc

a Department of Sociology, York University, 4700 Keele Street, Toronto, Ontario Canada M3J 1P3 b Institute for Clinical and Evaluative Studies, Toronto, Ontario, Canada c Centre for Research on Inner City Health, St. Michael’s Hospital, Toronto, Ontario, Canada

a r t i c l e i n f o

Keywords: Unmet healthcare need Healthcare policy Women Health inequalities

a b s t r a c t

Unmet healthcare need should be rare in nations with a universally accessible publicly funded healthcare system such as Canada. This however is not the case. This study exam- ines the extent to which predictors of such need are consistent with various paradigmatic approaches (e.g., structural–critical, social capital, social support, and lifestyle) that con- sider such issues. Analyses of data from a probability sample of 2536 urban residents in British Columbia specified the relationship of unmet need with socioeconomic issues such as income, gender, and housing tenure, community issues such as social networks and social support, and traditional lifestyle or behavioural risk factors. The structural–critical model

concerned with socio-demographics provided the most parsimonious explanation for hav- ing an unmet healthcare need. Consistent with a structural–critical approach, gender was found to be a reliable predictor of having an unmet health need in each of the models tested. Increasing federal transfers to healthcare and providing childcare and other com- munity supports that are of special value for women may help to reduce unmet healthcare

need.

1. Introduction

Like legislation in most developed nations, the Canada Health Act ensures reasonable access to medically neces- sary health services for Canadians [1]. Unmet healthcare need therefore should be relatively rare but this appears not to be the case. While there has been little empirical work that has identified under what situations Canadians come to have an unmet need, there is a plethora of paradigmatic approaches (e.g., structural–critical, social capital, social support, and lifestyle) that offer a number of hypotheses to explain unmet need. The present study was able to draw

upon an existing data set that allowed an evaluation of the empirical validity of these approaches. The specific fac- tors examined included socio-demographic measures of income, employment status and gender, community issues

∗ Corresponding author. Tel.: +1 416 465 7455; fax: +1 416 465 7455. E-mail address: [email protected] (T. Bryant).

0168-8510/$ – see front matter © 2008 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.healthpol.2008.11.002

© 2008 Elsevier Ireland Ltd. All rights reserved.

such as the connections one has with the community, indi- vidual issues of social support, and so-called lifestyle or individual behavioural risks factors such as tobacco use and exercise. Lifestyle approaches also include issues such as coping with stress and having a social life, situations seen as being under some personal control.

Briefly, the structural–critical approach – also known as a political economy approach – is concerned with the distribution of economic and social resources – including power and political influence – among the population and the forces that shape such distribution [2]. Its variables of interest are those of income, employment status, and gen- der, among others. There is frequent focus on what might be called the opportunity structure provided by a society for those of differing socioeconomic position [3].

The social capital and social support approaches are con- cerned with community and individual factors that are seen as shaping coping and opportunities to access resources and information [4]. While social capital has been defined by some as providing structural analysis as defined by

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ourdieu, the conceptualization of social capital that has ome to dominate the political science literature in North merica is focused more on building trust and social net- orks [5,6]. Rather less concerned with the distribution

f economic and social resources or political influence, his conceptualization tends to have a rather de-politicized pproach to health and healthcare issues [4].

Finally, the lifestyle or behavioural risk factor approach s also common. In this approach, health and healthcare ssues are frequently reduced to a very narrow focus on ndividuals and the things they do or do not do in support f health. Analyses of context and the broader forces that hape such behaviours is very uncommon [7,8].

.1. Unmet healthcare need and accessibility of ealthcare

The literature on unmet health need in Canada has ocused on access to primary and specialist care with

more recent emphasis on length of waiting times for pecialists [9–12]. A perceived inadequacy of access to spe- ialist care has led to calls to increase human resources n the healthcare sector. It has also fuelled calls for the evelopment of a parallel private system to ease waiting imes in the public system. The decision of the Supreme ourt in June 2005 that struck down a Quebec ban on rivate insurance for services covered by Medicare has rein- orced this trend [13]. Few studies of unmet healthcare need ave moved beyond descriptive studies of the perceived

nadequacies of the healthcare system to consider how ocioeconomic issues related to the distribution of material esources and community organization shape the access of ndividuals to healthcare services. This study attempted to xamine some of these issues.

Unmet need refers to a perceived healthcare need for hich care is not provided. Statistics Canada annually doc- ments the extent of unmet healthcare need [1,12,14,15]. An

mportant aspect of unmet need is waiting for care. Aver- ge waiting times for all specialised care remained stable etween 2003 and 2005 at 3–4 weeks depending on the ype of care required [16].

In 2006, 80% of Canadian considered their waiting time cceptable, yet about 20% thought they waited too long. tudies on unmet need usually outline strategies to bet- er provide care for patients who have been on waiting ists for a particular length of time or provide care to those

hose conditions present greater urgency [17,18]. They ecommend management techniques that entail periodic eviews of files to remove patients who no longer require are and prioritize patients who are still waiting for care. he net effect of these actions would be to reduce waiting imes.

Moreover, there is little consensus among researchers, oliticians, or the public on how long is too long to wait for are or for specific procedures. The data suggest that the xtent of unmet need may in reality be less than presented

y the media and politicians. Indeed, Statistics Canada sug- ests that public perceptions regarding waiting times for are may be influenced by the “intense focus and atten- ion paid to this issue by both policymakers and the media” 16]. Most studies consider the solution to lie in improving

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waiting list management or by allowing private services to develop [12,19]. Clearly, there is a relationship between unmet healthcare needs and access issues. While it is cer- tainly important to tease these issues out, it is clear that a focus on waiting times, however, may detract from other policy issues that contribute to perceptions of unmet need.

1.2. Social and health inequalities and health service utilization

Lower income Canadians report a greater incidence of unmet healthcare needs. The joint Canada/United States Health Survey found that 17% of lowest income quintile Canadians experienced an unmet healthcare need in the previous 12 months as compared to only 9% of wealthi- est income quintile Canadians [14]. This appears to be the case since at a minimum, lower income is associated with poor health status with its implications of greater health- care need. And indeed, Canadians in the lowest income quintile were the most likely to report fair or poor – rather than good, very good, or excellent – health and having a motor mobility problem [20]. Having more health prob- lems should increase the likelihood of having an unmet healthcare need.

Lower income could also be related to unmet need as it may reflect living conditions that make accessing health- care services more difficult. Income is but one indicator of socioeconomic status and is strongly correlated with education, employment status, and other socio-economic indicators. Individuals at the bottom of this hierarchy – due to their more vulnerable employment conditions – may also have more issues with attending appointments, advancing their health agenda with health profession- als, and accessing services that may require additional resources such as prescription medicine care [21].

Roos and Mustard examined these hypotheses in an extensive study of healthcare use among 600,000 resi- dents in Winnipeg, Manitoba [22]. Enumeration areas of approximately 700 people were classified into one of five income quintiles based on median income. Income quin- tile was related to the number of female-led households, unemployment rate, and educational level. Residents in middle and poor neighbourhoods experienced greater age- standardized death rates, shortened life expectancies, and greater death rates from a range of diseases. The lowest quintile population had higher incidences of most chronic diseases as compared to the highest quintile. Hospitaliza- tion rates were highest in the poorest quintile, lowest in the richest quintile. Average number of days spent in hospital paralleled these findings.

Roos and Mustard also found that lower income resi- dents were more likely than higher income residents to see general physicians. But they were no more likely – despite their poor health status – to be referred to or see specialists than those living in the wealthiest quintile of neighbour- hoods. The National Population Health Survey found that

healthcare need – itself related to income – was related to greater use of physician services [23]. It also found that those in the lowest income quintile were more likely to access general practitioners, but were less likely to have visited a specialist than wealthier Canadians. These and

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other findings highlight problems with universal access to specialist care among lower income Canadians. There it is expected that lower income – and the associated health indicators of fair or poor health – will be significant predic- tors of unmet healthcare need.

1.3. Gender as a determinant of unmet healthcare need

A missing dimension from unmet healthcare need work is that of gender [24,25]. Extensive research has doc- umented the association between gender, income, and health [26,27]. Women of low income (either employed or not) show poorer health status as compared to women with higher incomes [28]. Women in general report lower incomes than men. In 2003, women employed full-time full-year received average earnings of $36,500, or 71% of those of similarly employed men [29].

In addition, since responsibility for primary care of fam- ily members frequently falls to women, women who work full-time outside the home may have increased responsi- bilities that may threaten their health [30]. These added responsibilities may threaten health directly through the stress of having greater responsibilities that threaten health or indirectly by making the scheduling and meet- ing of medical appointments more difficult. Gender may therefore be an additional source of unmet healthcare need.

These difficulties women encounter would be accen- tuated by public policies that have reduced federal government transfers to provincial healthcare programs, thereby increasing the burden on women who usually are primary caregivers within their immediate and extended families [31]. Because of their role as family caregivers, women are particularly vulnerable to such policy changes. It is predicted therefore that female gender will predict unmet healthcare need.

1.4. Housing tenure

Housing tenure is emerging as a unique contributor to quality of living conditions. Hulchanski has demonstrated that Canadians renting rather than owning their homes have experienced profoundly deteriorating incomes [32]. Much of this has to do with the inability of low- and middle- end incomes to keep up with rising accommodation costs. Renters may therefore be at greater risk of poorer health and have greater likelihood of having unmet healthcare needs. It may also be the case that renters may be at a disadvantage in accessing needed healthcare due to poten- tial income loss as a result of taking time from work to follow up on appointments and care. It is predicted that renter status—as opposed to homeowner status – will pre- dict unmet healthcare need.

1.5. Social integration and support

The social capital literature suggests that community engagement – and associated social support – can assist in coping with life situations [5]. Though there is a somewhat acrimonious debate about the value of social capital as an explanatory device for health status [4,33], evidence sug-

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gests that community connections may be a determinant of health status [34,35]. Such connections may facilitate inter- actions with the healthcare system allowing for greater information sharing and providing supports for community members to schedule and attend medical appointment. In addition, when people have the support of family, friends, and other community supports such as social services, they may be better able to cope with healthcare issues. It is pre- dicted then that lack of social connections and lack of social supports will predict the presence of unmet healthcare need.

1.6. Traditional lifestyle or individual risk factors

The traditional epidemiological and biomedical approach is to emphasize lifestyle risk factors of diet, exercise, and minimal alcohol and tobacco consumption as determinants of health. A nutritious diet, physical activity and moderate alcohol consumption – it is argued – can reduce the incidence of chronic diseases such as diabetes, hypertension, and cardiovascular disease [36,37]. Again, this paradigmatic view is strongly contested [38–40]. Also associated with so-called lifestyle approaches is an emphasis on stress and developing a social life. Again, the assumption is that coping with stress and having friends are under voluntary control. The key question is whether the presence of these issues provides additional explanatory power to explain unmet healthcare need that the socio-demographic and community indicators already specified. It is predicted therefore that greater presence of behavioural risk factors will be a predictor of unmet healthcare need.

In summary, this study tested five hypotheses that grow out of different paradigmatic views of the nature of health and how these should be related to unmet healthcare need. These hypotheses involve issues of: (a) income and related socio-demographics; (b) gender; (c) housing tenure; (d) community engagement and social support; and (e) the presence of behavioural risk factors.

2. Methods

2.1. Sample

These hypotheses were tested on a probability sample of urban residents in British Columbia from the Tri-City Sur- vey. The Tri-City Survey was a neighbourhood telephone survey that randomly sampled residents in 12 Census Sub-Divisions (CSD) in British Columbia. The eligible CSDs consisted of geographic communities of Vancouver, Surrey and Kamloops as defined by postal code Forward Sorting Address.

2.1.1. Response rates Of the total sampling frame of 24,075 households within

the selected CSDs interviewer contact was made with 61%

(14,708) of identified households. For reasons that are unclear 65% (9661) of these households refused to partici- pate. A further 16.5% (2423) were excluded due to English language proficiency; and 0.6% (88) were excluded due to age <18 years, the respondent not being knowledge-

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ble about household expenses; or the respondent was emporarily residing or had recently moved into the area. espite these exclusions, a rather large sample of 2536

espondents agreed to complete the survey.

.2. Analysis

Since the dependent variable, unmet healthcare need as dichotomous, logistic regression was applied. Seven

onstructs – consisting of 27 variables – served as predic- ors of unmet healthcare need and included demographics ndicators, housing tenure, measures of community ngagement and social support and the presence of ifestyle-related health risk factors.

Demographic variables included age, gender, annual ncome (> $40,000CDN versus <$40,000CDN), educational evel, marital status, housing tenure, and self-reported ealth status. Seven indicators of community engagement, ve of social support, four of housing and four of lifestyle ere examined as predictors of unmet healthcare need. ivariate analyses provided uncorrected correlations of hese indicators with unmet need. Multivariate models ere then applied to test the validity of the various paradig- atic assumptions outlined earlier.

. Results

Table 1 presents the observed sample frequencies for ach variable and the results of the bivariate regression redicting the presence of an unmet health need in the ast 12 months. Odds ratios for variables that were sta- istically significant at the p < .05 level are bolded. Of the 536 respondents, 335 (13.2%) reported an unmet health- are need over the past 12 months.

.1. Description of sample

The mean age of respondents was 46 years and 61% ere women. More than two-thirds of respondents had ost-secondary education. Just over half of respondents eported annual incomes >$40,000CDN. Most respondents eported having community acquaintances, such as know- ng a lawyer, doctor, or other professional.

Regarding social support, about 13% indicated they do ot feel part of one or more group(s) that share similar

nterests, attitudes, and/or beliefs. Regarding community ngagement, few respondents reported belonging to orga- izations active on political issues or organizations related o their nationality or ethnic group. Almost half belonged to recreational club/group; and slightly more than half had olunteered in the past year.

About half reported being physically active on a regular asis. One quarter of respondents reported being limited in mount and kind of activity because of a long-term physical

llness or disability. About three in five found most days ery or extremely stressful, and three in five experienced a tressful life event in the previous year, such as a change of ob, birth or adoption of a child, financial or legal worries, mong others.

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3.2. The socio-demographics of unmet healthcare need

Examining Table 1 from top to bottom, the following associations were observed. Age was unrelated to unmet need as was educational level. However female gender, having been married but now single, reporting less than $40,000 annual income, and being unemployed were all reliably related to having an unmet need. And not sur- prisingly, the best predictor of unmet need was report of poor or bad health. All of these findings are consistent with a critical–structural approach that concentrates on the role played by income, gender, and employment situation in determining life opportunities. In the present situation these factors play a significant role in shaping health status and access to healthcare.

3.3. Housing tenure

As expected, renters had almost twice the risk of report- ing an unmet healthcare need as compared to home owners. This provides support for the view that tenants experience greater threats to life opportunities.

3.4. Community engagement and social support

Three of seven community engagement indicators pre- dicted unmet need in the expected direction. Unmet healthcare need was less likely for those belonging to a job- related association as well as for those in an organization concerned with politics or an organization related to one’s nationality or ethnic group.

Findings were stronger for the social support cluster. Unmet health need was more likely for those with no one to call on for help, without a group association, with no close relationships, and without one to turn to for advice, offering some support for a social capital, social support perspective.

3.5. Lifestyle or behavioural risks

Not participating regularly in physical activity increased the likelihood of reporting an unmet healthcare need as was being a smoker and experiencing a limiting physical or health problem. Finding life to be stressful – an indicator of coping – and being dissatisfied with one’s social life were also predictors of greater unmet need.

3.6. Additional associations

While as a group, women were more than 50% more likely than men to report an unmet need (see Table 1), un- tabled analysis indicates that women of working age were 60% more likely than men of working age to report unmet health need: OR: 1.60 (95 CI: 1.18, 2.13). Similarly, women were also more than twice as likely to have poorer self- rated health status than men: OR: 2.20 (95 CI: 1.48, 3.30)

and women were more likely than men to report having a disability (�2 = 61.40, p < .001). Interestingly, women were more likely than men to belong to political organizations: OR: 0.50 (95 CI: 0.34, 0.71) or organizations related to their ethnicity: OR: 0.53 (95 CI: 0.35, 0.78).

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Table 1 Predicting the presence of unmet health need—bivariate logistic regression.

Predictors N % OR 95%CI

Social demographics (2536)

Age (5+ years) (711) 28.0 18–34 years (680) 26.8 0.95 (0.72, 1.25) 35–54 years (1096) 43.2 0.76 (0.55, 1.04) Missing (49) 1.9

Sex (male) (981) 38.7 Female (1555) 61.3 1.52 (1.19, 1.95)

Education (Post-Secondary, Professional/Trade/Technical School) (1741) 68.7 1.21 (0.95, 1.54) High school diploma or less (790) 31.2

Marital status (married/common law) (1473) 58.1 Separated/divorced/widowed (455) 17.9 1.53 (1.14, 2.05) Single—never married (594) 23.4 1.29 (0.98, 1.71) Missing (5) 2

Per annum income ≥ $40,000CDN (1378) 54.3 <$40,000CDN (821) 32.4 1.71 (1.34, 2.20)

Employed in previous year (1859) 73.3 Not employed in previous year (674) 26.6 1.52 (1.19, 1.94) Missing (3) 1

Self-rated health status (excellent/very good) (1484) 58.5 Good (692) 27.3 2.03 (1.54, 2.69) Fair/poor (356) 14.0 5.14 (3.84, 6.88) Missing (4) 2

Housing indicators Owns home (1435) 56.6 Rents home (1101) 43.4 1.86 (1.47, 2.34)

City of residence: (Vancouver) (1262) 49.8 Surrey (907) 35.8 1.10 (0.86, 1.41) Kamloops (367) 14.5 1.09 (0.77, 1.53)

Community engagement Has both instrumental and status acquaintances in community (2219) 87.5 Has status acquaintances only in community (105) 4.1 1.44 (0.83, 2.35) Has no instrumental or status acquaintances in community (185) 7.3 1.04 (0.71, 1.62) Does not belongs to a job-related association, e.g., labour union (954) 37.6 1.31 (1.01, 1.65) Does not belongs to a recreational group (1106) 43.6 1.20 (0.95, 1.52) Belongs to an organization active on political issues (333) 13.1 0.63 (0.46, 0.86) Belongs to organization related to respondent’s nationality or ethnic group (247) 9.7 0.65 (0.46, 0.92) Follows news regularly via radio, television, newspaper or other media (2317) 91.4 1.43 (0.94, 2.00) Volunteered in the past 12 months (1412) 55.7 0.87 (0.69, 1.10)

Social support No one to depend on for help (93) 6.7 3.04 (1.92, 4.82) No one depends on me for help (164) 6.5 1.03 (0.65, 1.64) Does not feel part of any group(s) that shares interests/beliefs (333) 13.1 2.29 (1.72, 3.05) No close relationships that provide emotional security (175) 6.9 2.81 (1.97, 4.00) No trustworthy person to turn to for advice if having problems (100) 3.9 2.02 (1.25, 3.26)

Lifestyle Participates regularly in physical activity (1361) 53.7 Participates periodically in physical activity (841) 33.2 1.36 (1.05, 1.77) Does not participate in physical activity (323) 12.7 2.44 (1.78, 3.34) Smoker (428) 16.9 1.70 (1.30, 2.24)

h binary

Daily life is a bit/quite a bit/extremely stressful Dissatisfied with social life

Notes: Odds ratios (ORs) for individual characteristics were calculated wit Bolded entries indicate statistical significance at p < .05.

In summary, these findings offer support for each of the paradigmatic views concerning the sources of health

and – in the case of this study – the sources of unmet healthcare need. Since adherents to each paradigm usually neglect to include indicators from other schools of thought in their analyses, it is not surprising that each paradigmatic school continues to report findings such as these, thereby

(1574) 62.1 2.09 (1.60, 2.72) (331) 13.1 3.58 (2.73, 4.70)

logistic regression. The dependent variable was “Unmet Health Need”.

continuing to assert the validity of their paradigmatic views.

3.7. Multivariate models

Multivariate models were applied to further test the validity of each of the paradigmatic views presented.

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Table 2 Predicting unmet health need (adjusted models).

Model 1 Model 2 Model 3 Model 4 Model 5 Final model

OR 95%CI OR 95%CI OR 95%CI OR 95%CI OR 95%CI OR 95%CI

Social demographics (reference group) Age: (55+) 18–34 0.95 (0.70, 1.32) 0.90 (0.65, 1.24) 0.87 (0.63, 1.20) 0.79 (0.57, 1.09) 0.82 (0.60, 1.13) 0.85 (0.61, 1.19) 35–54 0.56 (0.37, 0.85) 0.70 (0.45, 1.08) 0.64 (0.42, 0.98) 0.63 (0.41, 0.96) 0.74 (0.48, 1.13) 0.73 (0.49, 1.21)

Sex (male) female 1.45 (1.10, 1.90) 1.48 (1.12, 1.96) 1.55 (1.16, 2.07) 1.56 (1.17, 2.09) 1.57 (1.18, 2.09) 1.61 (1.20, 2.16)

High educational attainment (post-secondary) others 1.05 (0.80, 1.38) 0.96 (0.72, 1.28) 1.08 (0.80, 1.45) 0.96 (0.72, 1.29) 0.92 (0.68, 1.23) 1.01 (0.75, 1.36)

Marital status (married) divorced, widowed 1.50 (1.06, 2.13) 1.37 (0.96, 1.96) 1.50 (1.05, 2.15) 1.35 (0.93, 1.96) 1.22 (0.84, 1.76) 1.15 (0.79, 1.68) Single, never married 1.13 (0.81, 1.57) 1.09 (0.77, 1.53) 1.13 (0.80, 1.59) 1.15 (0.81, 1.61) 1.03 (0.73, 1.45) 0.95 (0.66, 1.35) Per annum income 1.40 (1.05, 1.87) 1.07 (0.79, 1.47) 1.14 (0.84, 1.55) 1.10 (0.81, 1.50) 1.05 (0.77, 1.43) 0.98 (0.70, 1.30)

Earned income (YES) No earned income from employment 1.52 (1.10, 2.12) 1.20 (0.85, 1.69) 1.11 (0.78, 1.59) 1.15 (0.80. 1.64) 1.27 (0.89, 1.80) 1.29 (0.90, 1.84)

Self-rated health status (excellent or very good) good 2.08 (1.54, 2.80) 2.13 (1.58, 2.87) 2.13 (1.57, 2.88) 2.13 (1.57, 2.90) 1.81 (1.32, 2.52) 1.86 (1.36, 2.54) Fair, poor 3.95 (2.80, 5.56) 4.39 (3.13, 6.16) 4.43 (3.12, 6.29) 4.37 (3.06, 6.23) 2.84 (1.92, 4.08) 2.09 (1.48, 4.37)

Housing rents home 1.39 (1.01, 1.98) 1.24 (0.91,1.71) Lives in Vancouver 1.09 (0.80, 1.46) Surrey 1.17 (0.80, 1.73)

Community engagement (reference group—none) instrumental and status acquaintances 1.50 (0.84, 2.68) Status acquaintances only 0.94 (0.58, 1.54) Membership in job organization 1.13 (0.84, 1.51) Membership in recreational group 1.06 (0.80, 1.40) Membership in political organization 0.50 (0.34, 0.72) 0.48 (0.33, 0.68) Membership in organization related to nationality 0.57 (0.39, 0.84) 0.54 (0.36, 0.79) Listen to news 1.23 (0.80, 1.89) Volunteer 0.94 (0.71, 1.25)

Social support I do not have people I can depend on for help 1.98 (1.06, 3.68) 0.87 (0.50, 1.50) I do not have people who depend on me for help 0.78 (0.44, 1.38) Does not feel part of groups who share their beliefs 1.49 (1.03, 2.17) 1.36 (0.94, 1.96) No close relationships that provide emotional support 1.60 (0.97, 2.64) Does not have people they trust 1.02 (0.51, 2.04) Has no one who admires me 0.85 (0.45, 1.62)

Lifestyle Participation (regular) participates periodically in physical activity 0.93 (0.69, 1.26) Does not participate in physical activity 1.19 (0.80, 1.75) Smoker 1.28 (0.92, 1.76) Stressful life event in previous 12 months 1.86 (1.35, 2.55) 1.83 (1.33, 2.52) Have extremely stressful life 1.44 (1.05, 1.97) 1.38 (1.01, 1.97) Dissatisfied with social life 2.29 (1.66, 3.16) 2.30 (1.63, 3.25)

Notes: Bolded entries indicate statistical significance at p < .05.

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Multivariate models allow for the testing of unique con- tributions of factors to the presence of unmet healthcare need taking into account the interrelationships among the predictors. Table 2 shows the results of the tests of these multivariate models.

3.7.1. Model 1: socio-demographics and gender as predictors of unmet healthcare need

In Model 1 analysis is limited to the socio-demographic measures. Middle aged – as compared to older – Canadi- ans were less likely to report an unmet need. However, being a woman, divorced or widowed, having less than $40,000CDN annual income, or having no earned income were independent contributors to having an unmet health- care need. Not surprisingly, reporting less than excellent or very good health were strong independent contributors to having an unmet healthcare need. Those reporting fair or poor health were especially likely to report an unmet healthcare need.

3.7.2. Model 2: adding dwelling status and location to the socio-demographic indictors

Being a renter served as an additional predictor of unmet healthcare need in addition to the socio-demographic mea- sures contained in Model 1. Being a renter increased the likelihood of having an unmet need by 40%. City of resi- dence did not contribute to having an unmet need.

3.7.3. Model 3: adding community engagement to the socio-demographic indictors

In Model 3 the community engagement variables were added to the socio-demographic indicators. Of these, only two of eight provided additional predictive power: belonging to a political organization or belonging to an organization related to a respondent’s nationality reduced the risk of having an unmet healthcare need. Adding these variables led to attenuation of the previously observed income and earned income associations observed in Model 1.

3.7.4. Model 4: adding social support to the socio-demographic indictors

In Model 4, social support variables were added to the socio-demographic indicators. Of these only two of six pro- vided additional predictive power: Not having someone to depend on for help and not belonging to groups that share one’s beliefs increased the risk of having an unmet health- care need. Adding these variables also led to attenuation of the previously observed income and earned income asso- ciations observed in Model 1.

3.7.5. Model 5: adding lifestyle measures to the socio-demographic indictors

In Model 5, the lifestyle variables were added to the socio-demographic indicators. Interestingly, physical activ- ity and smoking did not add any predictive power to

explaining unmet healthcare need. Instead, two of the stress-related variables did so as did the social life measure. Adding these variables also led to attenuation of the pre- viously observed income and earned income associations observed in Model 1.

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3.7.6. Model 6: retaining socio-demographic indicators and all previously obtained significant predictors

In the final model, the significant predictors of unmet healthcare need were being female, reporting less than excellent or very good health status, the two community engagement indicators from Model 2, but none of the social support measures. The two stress measures and the dissat- isfaction with social life were related. Clearly, adding the hodge-podge of community engagement and social sup- port measures to the model serves to spread the variance associated with the socio-demographic measures such as income and not having earned income such that their asso- ciation with unmet health need becomes attenuated to non-significant levels.

Yet, this dissipation of variance did not accrue specif- ically to one cluster of measures to provide sufficient support for any of the specific community engagement, social support, or lifestyle paradigmatic views. Indeed, such clustering within one paradigmatic view was only apparent in Model 1. And of note was the presence of female gender and less than excellent or very good health status as reli- able predictors of unmet healthcare in each and every one of the tested models.

4. Discussion

The perusal of the various models suggest that the most consistent and reasonable explanation for the pres- ence of an unmet healthcare need is provided by the indicators contained in Model 1, the one focused on socio- demographics and self-reported health status. The other models – while providing some insights into the correlates of unmet healthcare need – did not do so in a manner consistent enough to suggest these models add greater explanatory power than that seen in Model 1. Even so, gen- der emerged as a reliable predictor of unmet healthcare need in each and every model.

In Model 1, the model limited to socio-demographic measures, incomes greater than $40,000CDN were indica- tive of not having an unmet healthcare need. It has been suggested elsewhere that people with incomes of $40,000 or more are more likely to seek care than those with lower incomes, and may be more likely to request and secure request specialist care than lower income groups [22,23,41]. These analyses however do not consider the generally better economic and living circumstances these individuals experience and how these may contribute to having their health needs met.

Indeed, the clustering of variables seen in Model 1 is consistent with the clustering of disadvantage viewpoint. Shaw et al. show that health inequalities develop from the clustering of disadvantage in education and employment opportunities, material conditions, and health behaviours [42]. It follows from these findings that the material and social deprivation associated with falling on the bottom end of the socioeconomic distribution may explain the presence

of unmet healthcare need.

Those at the lower end of the socioeconomic distribu- tion will have higher incidences of a wide range of health and health-related problems, and by virtue of their greater incidence of health problems, have greater healthcare need.

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heir lower socioeconomic standing will not only con- ribute to their greater healthcare need but also contribute o their not having these needs met. This would be the ase since they might have more precarious employment hich would make asking for, scheduling and attend-

ng to healthcare appointments more difficult. Precarious mployment refers to jobs that are low-paying with few r no benefits and high job insecurity. Indeed, about 25% f jobs in the Canadian labour market are low-paying [43]. s noted earlier, despite their poorer health status, lower

ncome individuals are either no more likely or even less ikely to see healthcare specialists than their more well-off eers.

The findings of this study also highlight the importance f female gender – particularly among women of work- ng age – as a unique predictor of unmet healthcare need.

omen were more likely than men to report an unmet ealth need in each and every multivariate model. While

t was beyond the scope of the study to specify the direct athways by which this occurs, it may be that working full- ime outside the home and providing unpaid care to their amilies may impede the ability of women to seek care for hemselves, thereby explaining both their poorer self-rated ealth status than men as well as their greater report of nmet healthcare need.

These findings offer support for Armstrong’s view that ender has implications for opportunities for health and tructures opportunities for receiving care. The implica- ions of these findings are that women experience unique arriers to accessing healthcare [44]. These barriers stem

argely from the structure of the lives since the majority of omen assume primary caregiving roles within their fam-

lies. Because of their caregiving responsibilities, women ay take time from employment or choose to work part-

ime to accommodate family caregiving responsibilities. aring for others may impede women’s ability to attend to heir own healthcare needs. In addition, women are more ikely than men to have precarious employment which ncreases their risk of having an unmet health need. Women n precarious employment may risk losing income if they ake time from their jobs to attend medical appointments. hus, women’s caregiving responsibilities and the struc- ure of their employment can increase their risk of having n unmet healthcare need.

Adding renter status to the socio-demographic variables dded predictive power. The value of renter status was owever dissipated once stress measures were included. evertheless, the finding lends support to the view that

enter status is associated with having greater likelihood f having an unmet healthcare need. The mechanisms by hich this comes about remain to be explored.

Hulchanski and others have examined the net worth of omeowners compared to renters [32]. This work found hat between 1984 and 1999 the income and wealth of anadian homeowners had risen significantly while that f renters had declined. During that period, the median

ncome of homeowners grew by $2100 (5%) while renters’ ncome had fallen by $600 (−3%). These findings suggest hat one pathway to poor health status and unmet health- are needs may be income insecurity and related to this ousing insecurity. Changing rental laws such as remov-

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ing rent control in Ontario and other Canadian provinces has increased the housing insecurity of renters [45]. Recent work by Hulchanski shows growing income inequality in Toronto neighbourhoods between 1970 and 2000 [46]. This reflects growing inequality between high and low income groups in Canada as a whole [47]. Indeed, Canada has expe- rienced one of the highest increases in income inequality among developed economies [48].

In the final model, experiencing a stressful life event was also a significant predictor of unmet healthcare need. It may be that stress such as bereavement, job loss, or divorce, may cause people to be less attentive to their phys- ical health, and not to seek needed healthcare. It may also be that those whose coping mechanisms are less developed will experience even greater unmet healthcare need when faced with the difficulties associated with the circum- stances associated with a poor socio-demographic profile. Note that social support networks added nothing to these measures.

From a public policy perspective, these findings direct attention to the importance of social stratification and the differences in resources – economic and social – available to individuals of varying status. Federal cuts to healthcare and social services – in addition to those seen in many Cana- dian provinces including British Columbia in which this study took place – may contribute to reported unmet health needs especially among women [24].

It may be that the primary means of reducing unmet healthcare need are outside the healthcare system. As examples, providing public day care for pre-school and school-aged children and responsive health and social ser- vices for seniors may provide opportunities for women to devote greater attention to their own health and seek care for themselves in a timely manner, thereby reducing their unmet healthcare needs.

These findings affirm that gender structures opportu- nities for health and for accessing care. Women’s primary care responsibilities have implications for their ability to address their own healthcare needs. In addition to investing more resources in the healthcare system to ensure suffi- cient resources are available to provide needed healthcare, public policy solutions such as providing child care and other social supports will help reduce unmet healthcare need.

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