COMPARATIVE PROGRAM ON HEALTH AND SOCIETY
( C P H S ) — W O R K I N G P A P E R S E R I E S , 2 0 1 4 ­– 2 0 1 5
A Longitudinal Examination of the
Canadian Workforce: The Effects of Job
Insecurity, Occupation, and Work Status
on Self-rated Health from 2004-2011
by
Emre Yurga and Amanda Veglia
Munk School of Global Affairs
University of Toronto
Editors’ Note
We are delighted to present this collection of research papers from the Comparative Program on Health and
Society based on work that our fellows undertook during 2014–2015. Founded in 2000, the Comparative
Program on Health and Society (CPHS) is a vital and growing research institute based at the Munk School of
Global Affairs at the University of Toronto. Generously funded by the Lupina Foundation, the CPHS supports
innovative, interdisciplinary, comparative research on health, broadly defined through our extensive range
of fellowships, which for 2014–2015 included CPHS MA Fellowships, Junior Doctoral Fellowships, CPHS
Senior Doctoral Fellowships, Lupina/OGS Doctoral Fellowships, Research Associate, and Senior Academic
Fellowships. Our program builds on the scholarly strengths of the University of Toronto in the social sciences,
humanities, and public health.
In 2011, CPHS adopted a renewed vision of the social determinants of health which recognizes the complexity
and interrelatedness of domestic, transnational, regional, and global factors that may have an impact on health
conditions and access to health-related services within any country, including Canada. We recognize similarly
that emerging and entrenched health inequalities may require policy-makers, communities, and researchers
to grapple with challenging ethical, human rights, and social justice questions. We accordingly expanded the
program’s thematic focus to accommodate research that specifically focuses on these definitional and operational
challenges. The research papers you will read in this year’s collection reflect these themes and demonstrate the
variety, complexity, and importance of comparative health research.
Comparative Program on Health and Society
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http://www.munkschool.utoronto.ca/
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© 2015 Emre Yurga and Amanda Veglia
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978-0-7727-0964-6
ISSN 1715-3484
A Longitudinal Examination of the Canadian
Workforce: The Effects of Job Insecurity,
Occupation, and Work Status on Self-rated Health
from 2004-2011
Emre Yurga and Amanda Veglia
Abstract
Background To examine the association between job insecurity, work status, and occupation on self-rated
health (SRH) using a nationally representative Canadian population sample.
Methods This study used longitudinal data from the National Population Health Survey (NPHS) from
2004 to 2011. Job insecurity was coded as a continuous variable, with lower scores indicating greater
job insecurity. Work status, denoting whether an individual worked full or part-time, was coded as a
binary variable for part-time. Three occupations were selected based on work status, two with the highest
probabilities of working part-time—sales/service and recreation/culture/sport, and one with the lowest
probability of working part-time—management. Self-rated health was coded as a continuous variable, with
higher scores indicating better self-rated health. Mixed-effects multilevel regression was used to estimate the
association between job insecurity, work status, occupation, and self-rated health. Analyses were controlled
for a number of covariates including health behaviours, demographic information, and work stress.
Results Job insecurity and management occupations were significantly associated with SRH at the 95%
confidence level, both at initial status and over time, even after adjusting for potential confounders.
Respondents with greater job security had a significant increase in SRH between 2004 and 2011 (0.01,
95% CI -.0001 to 0.021). Respondents with management occupations had a significant decrease in SRH
between 2004 and 2011 (-.04, 95% CI -.06 to -.012). Respondents employed in sales/service or recreation/
culture/sport occupations did not experience significant changes in SRH. Part-time work status also had no
significant effect on SRH.
Conclusions Occupation type and job insecurity are important determinants of health, more so than work
status. It is important for labour policies to address these trends in order to prevent declines in employee
health.
Biography
Emre Yurga is a Senior Advisor for the Government of Ontario Ministry of Tourism, Culture and Sport’s Culture Division.
Emre holds a Master of Architecture degree from the University of Waterloo and a Master of Public Policy from the University
of Toronto. He was a Canadian Institutes of Health Research (CIHR) Fellow in Public Health Policy at the Dalla Lana School
of Public Health and a Lupina Fellow in Health and Society with the Munk School of Global Affairs at the University of
Toronto. He has worked with many social and not-for-profit organizations as well as government agencies in Canada. His
research interests concern how spaces and built forms affect communities’ health and well-being. Emre is a member of the
Royal Architects Institute of Canada and of the Canadian Association of Heritage Professionals (CAHP, EA Specialty). He is
the past president of The Riverdale Immigrant Women Enterprise and currently serves on the Board of Artscape Foundation.
Amanda Veglia is a Policy Specialist at Cancer Care Ontario within Surgical Oncology. She is a recent Master of Public Health
graduate of the University of Toronto’s Dalla Lana School of Public Health, where she was also a Canadian Institutes of
Health Research Fellow in Public Health Policy. In addition, Amanda holds a Bachelor of Science degree from the University
of Waterloo and a Post-Graduate certificate in Clinical Research from the Michener Institute for Applied Health Sciences.
Amanda has gained extensive health policy and research experience through various work and volunteer initiatives in the
public and private sector.
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Emre Yurga and Amanda Veglia
INTRODUCTION
Occupational health is an important facet of public health, and is affected by a variety of factors including
occupation type, work status, and job insecurity. In Canada, occupational trends are shifting, with more
workers facing job insecurity than ever before (Grant 2015; McKenna 2010; Nazareth 2012). Job insecurity
and precarious employment are often considered synonymous and include work that is temporary, short
term, of low quality, or having unstable hours. Feelings of underemployment can also be included in this
definition (McKenna 2010). Numerous studies have demonstrated an association between high levels of
job insecurity and poor self-rated health (SRH) (Burgard et al 2009; Caroli and Godard 2014; Ferrie et al
2002; McDonough 2000; Rugulies et al 2008). Work status and its relationship with SRH has also been
studied (Pirani and Salvini 2015).
SRH is a commonly used predictor of health status and is useful given its composite nature of both
physical and non-physical health dimensions (Idler et al,1997; Vingilis et al 2002). Given the amount
of time individuals spend working relative to other daily activities, it is not surprising that the effects
of occupation on health have attracted international research interest. However, Canadian data on this
subject are limited. With the majority of coverage on occupation trends in Canada coming from mass
media, such as The Globe and Mail, there is a need for peer-reviewed literature on the intersection between
job insecurity, work status, and health (Grant 2013; Grant 2014; Grant 2015; McIsaac and Yates 2013;
Nazareth 2012).
To help fill this gap, this study examines the effects of job insecurity and work status on self-rated health
using data from the National Population Health Survey (NPHS). The longitudinal nature of the NPHS
offers an opportunity to explore the relationship between job insecurity, work status, and self-rated
health over time in a representative sample of Canadian labour force participants. Data from 2004 to 2011
are used to gain a more accurate picture of current trends and obtain findings relevant to the Canadian
workforce. (Statistics Canada 2014). Exploring the effect of occupation type on self-rated health is also
of interest, especially given the prevalence of part-time jobs in the education, culture, and hospitality
industries (Grant 2013). Accordingly, the objective of this study is to explore the effect of occupation,
work status, and job insecurity on self-rated health over an eight-year period.
In order to explore this effect, four primary research questions are explored in this study:
1. Has self-rated health changed in the Canadian working population from 2004 to 2011?
2. A
re job insecurity, work status, and occupation significantly associated with self-rated health
over this sampling period? What is the relationship?
3. D
o covariates affect self-rated health over time and do they alter the relationship between the
main predictor variables and self-rated health?
4. How can these results be used to evaluate and influence public health policy in Canada?
It is hypothesized that respondents employed in part-time occupations will experience greater
deterioration in self-rated health compared to those in full-time occupations, in the period from 2004 to
2011, while respondents with high levels of job insecurity will have similar negative health trajectories.
Findings will be used to evaluate and influence public health policy in this realm.
LITERATURE REVIEW
A review of the literature was conducted to include publications between 2004 and 2015 as well as
publications related to self-rated health in connection with job insecurity, occupation, or work status.
Excluded from the literature review were non-English language publications and publications from
outside of Europe or North America (for generalizability to the Canadian labour force).
PubMed database was searched for applicable literature. Titles, then abstracts, then full articles were
reviewed. A Google search was used to obtain relevant media pieces, such as Canadian newspaper articles.
Finally, the Canadian Research Data Centre (RDC) database was examined for relevant publications.
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A Longitudinal Examination of the Canadian Workforce: The Effects of Job Insecurity, Occupation,
and Work Status on Self-rated Health from 2004-2011
Results from PubMed, Google, and RDC Publications
1. Occupation and self-rated health
A total of two articles from PubMed were found to be relevant (Smith and Frank 2005; Smith et al 2008).
Smith et al (2008) found that individuals with positive change in job control over time reported better
health than those with negative change in job control. Smith and Frank’s article (2005) was also found
on the RDC database; the authors examined the relationship between occupation, educational attainment,
and self-rated health. They found that the effect of occupational attainment on health is important
for those individuals who have invested the most time in their education. Conversely, differential
occupational attainment is not associated with differences in the odds of decline in health for participants
with lower levels of education (Smith and Frank 2005). No articles were found that discussed specific
occupations with self-rated health.
2. Job insecurity and self-rated health
Numerous studies demonstrated an association between high levels of job insecurity and poor self-rated
health (Burgard et al 2009; Caroli and Godard 2014; Ferrie et al 2002; McDonough 2000; Rugulies
et al 2008). The most pertinent study was one recently published in the Journal of Occupational and
Environmental Medicine. Researchers found that perceived job insecurity was linked with significantly
higher odds of fair or poor self-reported health among subjects in Michigan, USA. The findings persisted
even after researchers adjusted for socio-demographic characteristics, previous health problems, whether
a person was a temporary worker, and recent job loss. They also found that workers who persistently
and chronically experience job insecurity are sometimes, in fact, in worse health than the unemployed
(Burgard et al 2012).
3. Work status and self-rated health
The majority of the literature covered was devoted to the relationship between work status and self-rated
health. Work status refers to whether an individual works part-time or full-time. Precarious employment,
which is another factor that can affect an individual’s self-rated health, is defined as temporary, part-time,
or fixed short-term work and is on the rise in Canada (Grant 2013; Grant 2014; Grant 2015; McIsaac and
Yates 2013; Nazareth 2012). In fact, the growth of precarious employment is a current concern in Canada
(multiple Globe and Mail articles cover this topic). Temporary work in Canada is growing at more than
triple the pace of permanent employment. Temporary positions are most prevalent in education, culture,
and the accommodation and food services sector. By province, most of the growth in temporary work
has been in British Columbia and Ontario (Grant 2013). A joint study by McMaster University and the
United Way in February 2013 found 4 in 10 people in the Greater Toronto and Hamilton region are in
some degree of precarious work and that this type of employment has risen by nearly 50 per cent in the
past two decades (Grant 2013). Without data on self-employment, it is difficult to determine how many
part-time workers may be self-employed or voluntary part-time workers. Women typically account for
about 70 per cent of part-time workers and the female labour participation rate among those aged 25 to
54 has been falling (Grant 2015). Toronto Dominion Bank, which has developed an index tool to measure
precarious employment in Canada, predicts that levels will remain high until at least 2017 (Grant 2015).
The health impacts of precarious work have also been studied extensively. A few studies were found
on PubMed, including one from Italy which found that temporary employment becomes particularly
negative for the individual’s health when it is prolonged over time, and that women’s health is more
negatively affected by temporary employment than men’s (Pirani and Salvini 2015).
METHODS
Study population and sample design
In order to analyze the relationship between job insecurity, work status, occupation, and self-rated health,
this study used longitudinal data from the NPHS. The NPHS began in 1994/95 and ended in 2010/11
with data collected biennially for a total of 9 collection Cycles. The NPHS employed a stratified two-stage
3
Emre Yurga and Amanda Veglia
sample design (clusters, dwellings) and responding to the survey was voluntary. Approximately 17,000
Canadians were sampled every two years for a total of 18 years (Statistics Canada 2012, 2014).
For this study, Cycles 6-9 were used, corresponding to years 2004/05, 2006/07, 2008/09, and 2010/11.
These Cycles most accurately reflect the current Canadian labour market. That is, within the past several
years, the proportion of temporary/contract positions has increased, there is Outcome variable
Self-rated health
SRH is considered a valid predictor of health and has been used throughout the published literature
(Idler and Benyamini 1997). SRH was measured in all four Cycles of the NPHS using a five point Likert
scale (4=excellent, 3=very good, 2=good, 1=fair, 0=poor). Originally, this scale was collapsed to form
a dichotomous variable (excellent, very good, good = good health; fair, poor = poor health). It is also
important to note that while non-physical health dimensions are captured elsewhere in the NPHS, SRH
is increasingly considered to be a composite measure of physical and non-physical health dimensions
(Herman et al 2015).
ANALYSIS
All analyses were completed in Stata 13 SE (Stata 2015). All analyses were assessed using mixed-effects
multilevel regression in the form of xtmixed, given the continuous nature of the outcome variable.
In order to examine whether self-rated health changed in the Canadian working population from 2004
to 2011, a null model was assessed of the form: outcome=a+B1*Time, where a represents SRH at the
beginning of the study (intercept) and B1*Time represents the change in outcome over time (slope).
Since time was significant in the null model at the 95% confidence level, another mixed-effects multilevel
model was created to assess the effect of the three main predictors, occupation, job insecurity, and work
status, on SRH. Given that the research questions addressed overall trends within individuals, we were
interested only in the level-1 sub model and examined the fixed effects in the xtmixed model. Exploring
the effect of job insecurity, work status, and occupation on self-rated health from 2004 to 2011 involved
a model of the form: outcome = a+B1*Time+ B2A+ B2A*Time+ B3B+ B3B*Time+….BnN+ BnN*Time, where
BnN*Time represents the interaction between the predictor and time and BnN represents the initial status.
The aim of this analysis was to determine if the main predictors were significantly associated with SRH at
the beginning of the study or over time, without controlling for other variables.
The final model included all control variables in addition to the main predictors. However, since
descriptive statistics illustrated that control variables did not vary significantly over time, interactions
with time were modelled only for the main predictors. The purpose of this analysis was to determine if the
main predictors were significantly associated with SRH at the beginning of the study or over time, when
controlling for other variables. Table 1 shows the analysis results for all three models.
RESULTS AND DISCUSSION
This study sought to examine how job insecurity, work status, and certain occupations affect self-rated
health in a representative sample of the Canadian labour force. This paper adds three main findings to
previous research on occupational health. First, respondents employed in management positions reported
better self-rated health at the beginning of the study, but over time their self-rated health decreased. Second,
respondents with greater job security reported poorer self-rated health at the beginning of the study, but
over time these individuals experienced an improvement in self-rated heath. Third, employment in sales/
service or recreation/culture/sport occupations or in part-time work did not appear to have a significant
effect on self-rated health at any point in the study.
As mentioned in the analysis section, three models were assessed using Akaike Information Criterion (AIC).
In general, AIC values are based on the log-likelihood function and are used to compare model fit. The
smaller the AIC, the better the models fits the data (Stata nd). Our null model established that the effect of
4
A Longitudinal Examination of the Canadian Workforce: The Effects of Job Insecurity, Occupation,
and Work Status on Self-rated Health from 2004-2011
Table 1. Effects of job insecurity, occupation type, and work status
on self-rated health, NPHS, 2004-2011
Statistical Results
Self-Rated Health (Outcome variable)
Model 1
Model 2
Model 3
AIC
103,391.150,384.3 31,440.76
Number of observations:
42,54522,796 14,699
Number of groups:
12,7698,369 5,530
Predictor Variables
Cycles
-.04***-.02*** -.03
(0.01)(0.01) (0.02)
Job Insecurity
-.06***
-.05***
(0.01)(0.02)
Management Jobs
0.07***
0.08***
(0.03)(0.04)
Jobs in Recreation, Culture and Sports
0.20***
0.10
(0.03)(0.07)
Jobs in Service and Sales
-.01
0.03
(0.07)(0.04)
Part-time -.020.01
(0.03)(0.04)
Rate of Change (∆)
Management Jobs (∆) -.02***-.03***
(0.01)(0.01)
Jobs in Recreation, Culture and Sports (∆) -.01 -.002
(0.02)(0.03)
Jobs in Service and Sales (∆) -.02***-.09
(0.01)(0.01)
Job Insecurity (∆)0.010.01***
(0.01)(0.005)
Part-time (∆) 0.01-.01
(0.01)(0.01)
Work Stress (∆)5.17e
(0.01)
_Cons
2.64***2.88*** 2.99***
(0.01)(0.02) (0.06)
Control Variables
Sex (Male)
-.05***
(0.02)
Work Stress
-.01***
(0.01)
Immigrant-.10***
(0.03)
Non-smoker0.16***
(0.02)
>= Bachelor Degree
0.10***
(0.02)
Age-.04***
(0.006)
Province -.01***
(0.006)
Has Children
-.08***
(0.02)
Household Income 0.03***
(0.003)
Non-drinker
Omitted due to collinearity
Note: Statistics are reported as coefficients and standard errors *** p<.05
5
Emre Yurga and Amanda Veglia
time was significant and led to further modeling of our predictor and control variables. In the null model,
the intercept was 2.64 log units (95% CI 2.62 to 2.66) and this effect was statistically significant, suggesting
that from one individual to the next, there is a statistically significant difference in initial self-rated health.
Also, in this model, self-rated health decreased by 0.04 log units (95% CI -.04 to -.03) per Cycle and this
effect was also statistically significant.
In Model 2, the main predictor variables were included: job insecurity, work status, sales/service jobs,
management jobs, and recreation/culture/sport jobs. We also used interaction terms with time to explore the
rates of change over Cycles. According to this model, the effect of time is smaller than Model 1 since selfrated health was associated with a 0.02 logarithmic unit (95% CI -.04 to -.01) decrease per Cycle compared
to a 0.04 log unit (95% CI -.04 to -.03) decrease in Model 1. The intercept of the function also increased
to 2.88 log units (95% CI 2.84 to 2.92) and is statistically significant. Without controlling for any other
factors, job insecurity is negatively correlated with self-rated health. That is, one log unit increase in job
insecurity is associated with a 0.06 log unit (95% CI -.09 to -.04) decrease in self-rated health and this effect
is statistically significant. On the other hand, having a job in management or recreation/culture/sport is
positively correlated with self-rated health, and their effects are statistically significant, whereas having a job
in service and sales is negatively correlated and its effect is not statistically significant. In addition, having
a part time job is negatively correlated with self-rated health, but its effect is not statistically significant.
The rate of change for jobs in management and service/sales had negative associations with self-rated
health. For both of these variables, the rate of change decreased over time. The rate of change for both
sectors was 0.02 log units (95% CI -.04 to -.004) and both figures were statistically significant. On the other
hand, jobs in recreation/culture/sports have a statistically insignificant rate of change with a magnitude of
0.01 log units (95% CI -.06 to -.03) and it is decreasing over time. In this model, the rate of change for
the part-time variable increased over time and its value is 0.01 log units (95% CI -.01 to 0.03) although its
effect was not statistically significant.
In comparison to the other models, Model 3 has the smallest AIC (31,440.76). We can therefore conclude
that it fits the data the best and will be the model discussed in most detail and used to make final conclusions.
In this model, we added all of the control variables. These included: sex, age, work stress, immigrant status,
smoking status, alcohol use, province of residence, household income, education, and numbers of children.
Trends for outcome variable
In all three models, self-rated health decreased over time. This supports the expected trend in the sample
as people are aging and are likely to experience a decline in health. However, in Model 3, the effect of time
became insignificant. This could be a result of omitted variable bias (Rossi 2013). That is, in Models 1 and 2,
it appeared that self-rated health significantly decreased over time and that changes over time could explain
our variables. However, Model 3 suggests that overall trends appear to be better explained by other factors,
rather than time. This is valid given the significance of all control variables at the 95% confidence level. The
intercept is still significant in Model 3, but does not have a meaningful interpretation.
Trends for main predictors at initial status
With regard to the main predictors, the significant variables in Model 3 were job insecurity and employment
in management. The negative coefficient -0.05 log units (95% CI -.08 to -.02) for job insecurity suggests
that, on average, individuals with greater job security have poorer self-rated health at initial status, which
was not expected. This may be explained by other factors which were not explored in this study, such as
a previous stressful job experience as in the case of middle-managers (Lam 2015; Thomas and Dunkerley
2002). In addition, at initial status, being employed in a management job has a positive effect on self-rated
health, on average based on the positive coefficient 0.08 log units (95% CI 0.01 to 0.15). Work status (parttime), jobs in sales/service, and jobs in recreation/culture/sport do not significantly affect self-rated health in
this model. These findings may reflect the literature in that individuals working part-time do so voluntarily
and thus do not experience significant changes in self-rated health (Grant 2014). This finding presents a
positive consequence for the high proportion of individuals in Canada working part-time or temporarily
6
A Longitudinal Examination of the Canadian Workforce: The Effects of Job Insecurity, Occupation,
and Work Status on Self-rated Health from 2004-2011
(Grant 2013). In future studies, it would be interesting to examine if differences in self-rated health exist
between women and men who work part-time, or if individuals employed in British Columbia and Ontario,
who reportedly have the highest proportion of part-time workers, do in fact experience poorer self-rated
health (Grant 2013).
Trends for main predictors over time
Over time, management jobs and job insecurity remained significant. The trend for job insecurity and selfrated health over time was as expected, namely, individuals with greater job security report better self-rated
health, on average. In particular, for every 1 unit increase in job security, self-rated health increased by
0.01 log units (95% CI 0.00 to 0.02) per Cycle. Numerous studies have demonstrated a similar association
between job security and self-rated health (Burgard et al 2009; Caroli and Godard 2014; Ferrie et al 2002;
McDonough 2000; Rugulies et al 2008). It also makes sense that job insecurity had more of an effect on SRH
than did work status, given the complex nature of job insecurity and that individuals may choose to work
part-time, but not to work precariously (Grant 2015; McKenn, 2010).
In order to mitigate the potential negative health effects for individuals in precarious employment situations,
several policy options can be considered. For example, legal frameworks might be considered, in which
employees are given advance knowledge of shift times and dates, a maximum number of hours per week,
and pension and medical/dental coverage even if they are temporary or part-time workers. Similar policies
have been implemented by companies such as Costco and Starbucks, which help to alleviate feelings of job
insecurity and balance the employer-employee work relationship (Grant 2014). The Danish government
has also created a set of polices to help tackle the challenges of globalization, while maintaining steady
economic growth and employment. This set of policies has three components: first, flexible rules for hiring
and firing make it easy for employers to lay off employees during financial crises and hire new ones or old
ones when the economy improves; second, unemployment security in the form of a guaranteed income for
a legally defined unemployment benefit is at a relatively high level—up to 90 per cent for the lowest paid
workers; and third, an active labour market policy is in effect. The labour market would offer guidance, jobs,
or education to all unemployed including previously part-time employees (Rugulies et al 2008).
For respondents in management positions, better self-rated health was reported at the outset, but over
time it appears that self-rated health decreased by 0.03 log units (95% CI -.06 to -.12) per Cycle. This
could be due to the fact that individuals with higher education obtain these management positions,
become dissatisfied with their jobs, or come to feel they are underemployed, which can have a
negative impact on SRH (Smith and Peter 2005). At the same time, management jobs require extensive
responsibility and time commitment, and the consequent high levels of work stress may cause self-rated
health to deteriorate. The impact of these factors would be worthwhile exploring in further studies. Since
there was no information on the specific types of management jobs, it is difficult to recommend specific
policy options. Nevertheless, if individuals in management jobs are experiencing lower self-rated health
over time, possibly due to stress, workplace policies could include stress-reducing activities such as social
gatherings, more communication with colleagues, and even separate spaces where employees can go to
relax (Ray 2011).
Trends for control variables
This study also found that all control variables were significant at initial status. These variables were not
modeled over time, as descriptive statistics suggested that there was no significant change in responses over
our sampling period. With the exception of education, smoking status, and household income, all other
control variables were negatively correlated with self-rated health. The positive correlation between education
(0.10, 95% CI 0.06 to 0.14) and self-rated health supports the published literature in that individuals with
higher educational attainment report better self-rated health on average. Similarly, non-smokers report
better self rated health on average (0.16, 95% CI 0.13 to 0.20). Finally, the positive coefficient (0.03, 95%
CI 0.02 to 0.04) between household income and self-rated health suggests that individuals with higher
household income report better self-rated health at initial status. These trends support our expectations.
7
Emre Yurga and Amanda Veglia
Males, immigrants, individuals with children, older individuals, those with higher work stress, and those
residing in western Canadian provinces demonstrated a negative relationship with self-rated health. For
example, at the beginning of the study, a 0.05 log unit (95% CI -.09 to -.02) decrease in self-rated health
was associated with being male and being older. A 0.08 log unit (95% CI -.11 to -.04) decrease in selfrated health was associated with having children. Although they are significant, these represent very small
magnitudes of effect. Work stress and province of residence also have a very small effect on self-rated
health, given that self-rated health decreases by only 0.01 log units (95% CI -.02 to -.01) for those with
higher work stress or those residing in western Canadian provinces. Conversely, immigrants appear to have
poorer self-rated health on average at the beginning of the study. The magnitude of this relationship is also
the largest—a 0.10 log unit (95% CI -.17 to -.04) decrease in self-rated health is associated with being an
immigrant. This finding challenges ‘the healthy immigrant effect’ as the research has repeatedly found that
immigrants’ health is generally better than that of the Canadian-born, although it tends to decline as their
years in Canada increase (Dyck, 2011; Statistics Canada, 2005).
Strengths and Limitations
Because this study included a large, representative sample followed longitudinally over eight years, it is
one of the few to examine this combination of predictors with self-rated health and for this period of time.
Furthermore, a balanced panel was also used, where individuals who provided a response to all questions
of interest, in all four Cycles, formed the final study population. We were also able to adjust for a large
number of possible confounders and all demonstrated a significant effect on the initial self-rated health
status. Finally, we avoided misclassification bias by leaving variables coded as they were in the NPHS or
creating dummy variables, rather than classifying variables subjectively.
At the same time, there are also limitations that may affect the interpretation of our findings. For instance,
while a balanced panel has been used extensively in the literature, by creating a balanced panel with only
complete cases, an unrepresentative sample of healthier individuals who are able and willing to respond to
all questions in all Cycles may form the final study population (Carter et al 2010). Even though excluded
non-responders and responders included in this study population showed less than 5% difference in their
responses for most variables, certain age categories and individuals within the highest and lowest household
income categories showed larger differences, which could affect the generalizability and representativeness
of our study population. In addition, by including only three occupations with the highest and lowest
probabilities of working part-time, associations between self-rated health and other occupation categories
may be missing. Even though two of the three occupations used were not significantly associated with the
outcome, it does not mean there is not a true effect; it may just be an artifact of our coding. Bootstrapping
methods and weighting were also not used, which could affect generalizability of our results. Finally,
despite the use of self-rated health as a meaningful measure used commonly throughout the literature, it is
subjective and could affect these findings.
CONCLUSIONS
This study suggests that work status and employment in sales/service or recreation/culture/sport occupations
do not significantly affect SRH, which runs counter to our initial hypotheses. Still, decreases in SRH from
2004 to 2011 were observed, although this effect was not statistically significant. The only occupation
that was significantly associated with changes in SRH was management. In particular, respondents in
management positions reported better SRH at the beginning of the study, but over time their SRH declined.
Labour policies for individuals in management positions could target stress reduction activities, if this is the
main source of decreases in SRH. In addition, respondents with greater job security reported poorer SRH at
initial status. However, over time, SRH improved for those with greater job security. Even though part-time
work status was not statistically associated with SRH in this study, the relatedness between job insecurity
and part-time work status should not be ignored. Adopting labour policies similar to the ones used by major
corporations in Canada or the ‘flexicurity’ ones used in Europe could help mitigate the negative health
effects often experienced for those with precarious or insecure jobs.
8
A Longitudinal Examination of the Canadian Workforce: The Effects of Job Insecurity, Occupation,
and Work Status on Self-rated Health from 2004-2011
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Emre Yurga and Amanda Veglia
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10
A Longitudinal Examination of the Canadian Workforce: The Effects of Job Insecurity, Occupation,
and Work Status on Self-rated Health from 2004-2011
APPENDIX: STATA OUTPUTS
Model 1: null model
xtmixed SELF_RATED_HEALTH cycle ||realukey: cycle, mle cov(un)
Performing EM optimization:
Performing gradient-based optimization:
Iteration
Iteration
Iteration
Iteration
0:
1:
2:
3:
log
log
log
log
likelihood
likelihood
likelihood
likelihood
=
=
=
=
-51711.063
-51689.637
-51689.556
-51689.556
Computing standard errors:
Mixed-effects ML regression
Group variable: realukey
Number of obs
Number of groups
Coef.
cycle
_cons
-.0389519
2.639538
42545
12769
Obs per group: min =
avg =
max =
1
3.3
4
Wald chi2(1)
Prob > chi2
Log likelihood = -51689.556
SELF_RATED_HEALTH
=
=
Std. Err.
Random-effects Parameters
z
P>|z|
.0030513
.010222
-12.77
258.22
Estimate
Std. Err.
=
=
162.97
0.0000
[95% Conf. Interval]
0.000
0.000
-.0449322
2.619503
-.0329715
2.659572
[95% Conf. Interval]
realukey: Unstructured
sd(cycle)
sd(_cons)
corr(cycle,_cons)
.1393153
.8221264
-.3776083
.005809
.0108175
.0249956
.1283827
.8011956
-.4255131
.1511788
.843604
-.3275931
sd(Residual)
.6069482
.003099
.6009046
.6130525
LR test vs. linear regression:
chi2(3) = 15193.36
Prob > chi2 = 0.0000
Note: LR test is conservative and provided only for reference.
. estat ic
Akaike's information criterion and Bayesian information criterion
Model
Obs
ll(null)
ll(model)
df
AIC
BIC
.
42545
.
-51689.56
6
103391.1
103443.1
Note:
N=Obs used in calculating BIC; see [R] BIC note
11
Emre Yurga and Amanda Veglia
Model 2: Outcome with main predictors
xtmixed SELF_RATED_HEALTH cycle INSECURITY_JOB bus_job rsc_job ss_job part_time cycle_busjob
cycle_rscjob cycle_ssjob cycle_insecjob cycle_parttime || realukey: cycle, mle cov (un)
Performing EM optimization:
Performing gradient-based optimization:
Iteration
Iteration
Iteration
Iteration
Iteration
0:
1:
2:
3:
4:
log
log
log
log
log
likelihood
likelihood
likelihood
likelihood
likelihood
=
=
=
=
=
-25207.436
-25176.792
-25176.15
-25176.147
-25176.147
Computing standard errors:
Mixed-effects ML regression
Group variable: realukey
Number of obs
Number of groups
Coef.
cycle
INSECURITY_JOB
bus_job
rsc_job
ss_job
part_time
cycle_busjob
cycle_rscjob
cycle_ssjob
cycle_insecjob
cycle_parttime
_cons
-.0224128
-.064044
.0648271
.1973096
-.0091837
-.0229247
-.0241944
-.0139572
-.0168113
.0051486
.0079459
2.883819
22796
8369
Obs per group: min =
avg =
max =
1
2.7
4
Wald chi2(11)
Prob > chi2
Log likelihood = -25176.147
SELF_RATED_HEALTH
=
=
Std. Err.
Random-effects Parameters
z
P>|z|
.0070382
.0117771
.0302963
.066808
.0288344
.0312144
.0103319
.0233154
.0100132
.0043305
.0112844
.0207004
-3.18
-5.44
2.14
2.95
-0.32
-0.73
-2.34
-0.60
-1.68
1.19
0.70
139.31
Estimate
Std. Err.
=
=
161.63
0.0000
[95% Conf. Interval]
0.001
0.000
0.032
0.003
0.750
0.463
0.019
0.549
0.093
0.234
0.481
0.000
-.0362075
-.0871267
.0054474
.0663684
-.0656981
-.0841039
-.0444445
-.0596545
-.0364368
-.003339
-.0141711
2.843247
-.0086181
-.0409614
.1242068
.3282508
.0473306
.0382544
-.0039443
.03174
.0028142
.0136363
.0300628
2.924391
[95% Conf. Interval]
realukey: Unstructured
sd(cycle)
sd(_cons)
corr(cycle,_cons)
.106602
.6635178
-.4081603
.0090756
.014348
.0412818
.0902191
.6359837
-.4857528
.12596
.6922439
-.3241855
sd(Residual)
.5563503
.0041057
.5483612
.5644557
LR test vs. linear regression:
chi2(3) =
5619.52
Prob > chi2 = 0.0000
Note: LR test is conservative and provided only for reference.
. estat ic
Akaike's information criterion and Bayesian information criterion
Model
Obs
ll(null)
ll(model)
df
AIC
BIC
.
22796
.
-25176.15
16
50384.29
50512.84
Note:
N=Obs used in calculating BIC; see [R] BIC note
12
A Longitudinal Examination of the Canadian Workforce: The Effects of Job Insecurity, Occupation,
and Work Status on Self-rated Health from 2004-2011
Model 3: Outcome with all predictors
xtmixed SELF_RATED_HEALTH cycle INSECURITY_JOB STRESS_WORK bus_job rsc_job ss_job part_
time cycle_busjob cycle_rscjob cycle_ssjob cycle_insecjob cycle_parttime cycle_workstress male immigrant
non_drinker non_smoker bac_plus age prov_res has_children INCOME_HOUSEHOLD || realukey: cycle,
mle cov (un)
*
Mixed-effects ML regression
Group variable: realukey
Number of obs
Number of groups
Coef.
cycle
INSECURITY_JOB
STRESS_WORK
bus_job
rsc_job
ss_job
part_time
cycle_busjob
cycle_rscjob
cycle_ssjob
cycle_insecjob
cycle_parttime
cycle_workstress
male
immigrant
non_drinker
non_smoker
bac_plus
age
prov_res
has_children
INCOME_HOUSEHOLD
_cons
-.0304782
-.0495504
-.0158726
.0817484
.1051122
.0297744
.0149497
-.0363046
-.0017382
-.0096434
.0107081
-.009053
-.0000394
-.0552012
-.1068135
0
.1652935
.0998163
-.0430414
-.0027057
-.0782006
.0315327
2.99534
14699
5530
Obs per group: min =
avg =
max =
1
2.7
4
Wald chi2(21)
Prob > chi2
Log likelihood = -15694.382
SELF_RATED_HEALTH
=
=
Std. Err.
z
.0187699
.0151778
.0030275
.035497
.0770358
.0383576
.0407706
.0121227
.0269645
.0132645
.0055388
.0145706
.0010718
.0188648
.0316008
(omitted)
.0182634
.018501
.0076226
.0005879
.01916
.00355
.0710093
Random-effects Parameters
Estimate
P>|z|
=
=
622.51
0.0000
[95% Conf. Interval]
-1.62
-3.26
-5.24
2.30
1.36
0.78
0.37
-2.99
-0.06
-0.73
1.93
-0.62
-0.04
-2.93
-3.38
0.104
0.001
0.000
0.021
0.172
0.438
0.714
0.003
0.949
0.467
0.053
0.534
0.971
0.003
0.001
-.0672665
-.0792983
-.0218063
.0121756
-.0458753
-.0454051
-.0649592
-.0600647
-.0545877
-.0356413
-.0001479
-.0376108
-.0021401
-.0921755
-.1687499
.00631
-.0198024
-.0099389
.1513211
.2560997
.1049539
.0948587
-.0125445
.0511113
.0163545
.021564
.0195049
.0020614
-.0182269
-.0448771
9.05
5.40
-5.65
-4.60
-4.08
8.88
42.18
0.000
0.000
0.000
0.000
0.000
0.000
0.000
.129498
.0635551
-.0579814
-.0038581
-.1157536
.0245749
2.856165
.201089
.1360775
-.0281013
-.0015534
-.0406476
.0384905
3.134516
Std. Err.
[95% Conf. Interval]
realukey: Unstructured
sd(cycle)
sd(_cons)
corr(cycle,_cons)
.1117516
.6194497
-.4073032
.0102998
.0177366
.0511145
.0932826
.5856441
-.5023779
.1338772
.6552067
-.3024971
sd(Residual)
.5385782
.0049774
.5289105
.5484226
LR test vs. linear regression:
chi2(3) =
3268.59
Prob > chi2 = 0.0000
Note: LR test is conservative and provided only for reference.
. estat ic
Akaike's information criterion and Bayesian information criterion
Model
Obs
ll(null)
ll(model)
df
AIC
BIC
.
14699
.
-15694.38
26
31440.76
31638.25
Note:
N=Obs used in calculating BIC; see [R] BIC note
.
13