The Impact of Marital Status on Health and Wellbeing: A Canadian Study
Keegan Lawrence
Thompson Rivers University

Supervised by Dr. Ehsan Latif
Undergraduate Research Experience Award Program

Abstract
Using survey data collected from the Canadian Community Health Survey (2016), this
study examined the impact of marital status on Canadians’ physical and mental health, and their
sense of wellbeing. The study found that for the overall sample, being married or being
divorced/separated/widowed has a significant positive impact on Canadians’ health, while living
in a cohabitating relationship has negative effects on health. The results also show that
quantitatively, being married has a larger positive impact on physical health compared to other
marital status categories. Further, being married, being in a cohabitating relationship, or being
divorced/separated/widowed each have positive effects on mental health. However,
quantitatively, being married has a larger positive effect on mental health compared to other
marital status categories. The study further examined whether there was a gender difference in
the impact of marital status and found slight differences between men and women. It found that
being married has a positive effect on men and women’s health, while cohabitating has a
negative effect on men and women’s health. Divorced/separated/widowed women are healthier
than single people, while there are no statistically significant results for
divorced/separated/widowed men. Onwards, women and men are both mentally healthiest
when married, and also mentally healthier when cohabitating as opposed to single people.
Divorced/separated/widowed women are mentally healthier than single women, and there is no
statistically significant result for separated/divorced/widowed men’s mental health effects.
Finally, being married has a positive effect on men and women’s wellbeing. Similarly,
cohabitating positively affects men and women’s wellbeing. There is no significant effect on
wellbeing for men who are divorced/separated/widowed whereas there is a positive effect on
divorced/separated/widowed women.
Keywords: Health outcomes; Gender; Marriage; Canada

2

1. Introduction
The objective of this study is to examine impacts of marital status on physical health,
mental health and wellbeing. Marital status for the purposes of this study includes being married,
single, common law or divorced/separated/widowed. Several socioeconomic studies have
concluded being married improves one’s wellbeing, their physical health and their mental health
in numerous ways.
Many existing studies examine the health benefits from marriage but fail to consider how
cohabitation affects health. Since the rate at which people are choosing to cohabitate rather than
marry is increasing in Canada, this study aims to compare the health benefits from being married
to the benefits of cohabitation or common law. Additionally, this study draws distinctions
between the health benefits from being married with health benefits from being
divorced/separated/widowed so health outcomes can be measured.
Both economic and psychological benefits can result from marriage. Economically,
marriage may result in two incomes and in economies of scale, ultimately improving the
economic wellbeing of people who marry (Lerman, 2002). More income leads to a higher
consumption level, better access to health care and lower levels of stress. Umberson (1987)
argues marriage positively impacts health through marriage protective effects since marriage can
protect people against poor health outcomes. The marriage protection effect hypothesis
suggests that married couples monitor each other’s health, they encourage healthy behaviours
in each other, such as regular exercise, and they discourage harmful health behaviours, such as
smoking. In addition to benefitting physical health outcomes, marriage may also lead to
improvements in mental health. Burgeoning literature suggests a wide array of benefits to
married adults such as emotional intimacy and support, fewer depressive symptoms and stress
reductions. Physical and mental health levels have major effects on one’s sense of wellbeing. The
research suggests, choosing to marry, to divorce or to cohabitate with someone may affect one’s
current and future health, as well as their wellbeing.
Umberson (1987) finds that married men experience higher health-compromising
behaviours than women, thus resulting in more harmful health outcomes. Regardless of these
health behaviours, the benefits of marriage far outweigh the costs in regard to personal health.
Additionally, the study found that divorced/separated/widowed women are healthier than single
women, yet the health of the men who are divorced/separated/widowed is virtually unaffected.
Wood, Goesling and Avellar (2007) finds that marital dissolution (divorce) typically lowers the
self-rated health of men over 50 years old, while finding no relationship between marital
dissolution and women’s self-rated health. Using data from the U.S. National Health Interview
Survey (2011-2012), Blumberg et al. (2014) found that cohabiting men were less likely to have
had a health care visit in the past 12 months compared with married and non-married men. The
study also found that cohabiting men were less likely to have had selected clinical preventive

3

services, including blood pressure checks and screenings for elevated cholesterol and diabetes.
Averett et al. (2013) found that cohabitation had a positive effect on some measures of health
for both men and women. However, the effects were smaller than for married couples.
This paper is structured as follows: Section 2 outlines the data and methodology
employed, Section 3 presents the results and Section 4 provides the conclusions.

2. Data and Methodology
The empirical analyses of this study are based on data collected from the Canadian
Community Health Survey 2016 (CCHS). This survey was created by joined forces of the Canadian
Institute for Health Information (CIHI), Statistics Canada, and Health Canada in an effort to
support health surveillance. The CCHS is a cross-sectional survey that collects information related
to health status, health care utilization and health determinants for the Canadian population. We
collected data from the respondents aged 18 and over from all Canadian regions.
There are three dependent variables in this study: Health, mental health and life
satisfaction. These followed an ordered probit regression in the analysis. Respondents recorded
the ‘health’ variable with categories: Poor health, fair health, good health, very good health and
excellent health. Likewise, mental health was recorded on a rating from 1-5 with the same
categories: Poor health, fair health, good health, very good health and excellent health. Life
satisfaction measures a person’s sense of wellbeing and was measured on a scale of 0-10, where
0 indicates “Very dissatisfied” and 10 indicates “Very satisfied”. Independent variables in these
models include: Marital status, gender, province of residence, education status, whether they
owned a home, whether they were an immigrant, race, income, age, and working status. The
independent variable ‘gender’ is a dummy variable that indicates whether a respondent is male
or female, with male being the base category. The ‘province’ independent variable has 13
categories: Newfoundland, Prince Edward Island, Nova Scotia, New Brunswick, Quebec,
Saskatchewan, Manitoba, Alberta, British Columbia, Yukon, Northwest Territory, Nunavut and
Ontario. Ontario is the base category. The independent variable ‘education’ has 3 categories: Less
than Secondary School graduation level, secondary school graduate, and university graduate;
with less than secondary school being the base category. The dummy variable ‘owned’ indicates
whether someone owns their house or rents their house, and owning their house is recognized
as the base category. The dummy variable ‘immigrant’ indicates whether someone is or is not an
immigrant, and ‘white’ is a dummy variable indicating if someone is or is not Caucasian.
Independent variable ‘income’ includes 5 categories: Less than $20,000, $20,000-$39,000,
$40,000-$59,999, $60,000-$79,000, and $80,000 or more with less than $20,000 being the base
category. The independent variable ‘age’ has 5 categories: 25-34 years old, 35-49 years old, 5064 years old, 65-79 years old and 80+ years old, with 25-34 years old being the base category.

4

Finally, ‘work’ serves as a dummy variable and the base category on whether the respondent is
currently working. There are 9 independent variables and 3 dependent variables in total.
Marital status includes the following categories in the study: Married, common-law,
divorced/separated/widowed with the base category being single. Below, Xi represents the listed
independent variables: Gender, province of residence, education status, whether they owned a
home, whether they’re an immigrant, race, income, age, and working status. The study will
estimate using the following empirical models:
Health = β0+ β1Married+ β2Common-Law+ β3 Divorced/Separated/Widowed +β4 Xi+ ɛ
Mental Health = β0+ β1Married+ β2Common-Law+ β3 Divorced/Separated/Widowed +β4 Xi+ ɛ
Life Satisfaction= β0+ β1Married+ β2Common-Law+ β3 Divorced/Separated/Widowed +β4 Xi+ ɛ
This study recognized health, mental health and wellbeing as the dependent ordered categorical
variables. To examine gender differences between health, mental health, and wellbeing, this
study re-estimated all of the models for males and females separately.

3. Results
The results shown in Table 1 indicate that married people are significantly healthier than
single people. According to the data, being in a common-law relationship has significant negative
health effects compared to single people and this is the case for both men and women. Being
divorced/separated/widowed has significant positive health effects for women, however being
divorced/separated/widowed has no significant impact on men’s health. Further results in the
table found Canadians living in Quebec self-rated their health higher than those in any other
province, meanwhile all three territories’ self-rated health scales were among the lowest in
Canada. Both education and level of income have significant effects on one’s health according to
our data in Table 1. For both men and women, secondary school graduates, and university
graduates are typically much healthier than individuals who did not graduate high school.
Similarly, for every increase in level of income, health levels improved.
Table 2 displays the marginal effects of an ordered probit regression for the overall
sample. Table 2 shows that being married reduces the probability of having poor health by .00272
units while it increases the probability of having excellent health by .014895 units. The table also
shows that being in a cohabitating relationship reduces the probability of having excellent health
by .00669829 units. Further, Table 2 shows that being divorced/separated/widowed reduces the
probability of having poor health by .0017 units while it increases the probability of having
excellent health by .0097 units. Thus, table 2 shows that being married has a quantitatively larger
impact on having excellent health compared to other marital status categories. Similarly, being

5

married has quantitatively larger effects on reducing the probability of being in poor health
compared to other marital status categories.
Table 3 shows the marginal effects for the male sample. It indicates that being married
reduces the probability of being in poor health by .002 units while it increases the probability of
being in excellent health by .009 units.
Table 4 shows the marginal effects for the female sample. Being married significantly
decreases the probability of having poor health by .004 units while being
divorced/separated/widowed significantly reduces the probability of having poor health by .009
units. Being married significantly increases the probability of having excellent health by .022 units
while being divorced/separated/widowed significantly increases the probability of having
excellent health by .015 units.
Table 5 shows the impact of marital status on mental health for men and women.
Common-law relationships positively affect mental health for both men and women. Being
divorced or separated or widowed has a positive effect on women’s health and no significant
effect on men’s health. The results also show that education, having owned a home, being an
immigrant, and higher incomes have significant positive impact on mental health for both males
and females. According to this analysis, mental health typically deteriorates as people get older
similar to the regular health variable outcomes. There is however one exception to this decline
in mental health reflected predominantly in female respondents. That is, women aged over 65
are significantly healthier than women aged between 25-34, and women aged between 65-79
have the greatest mental health compared to all other demographics. One of the largest ranges
analyzed in the study is the difference in mental health between men aged over 80 and women
aged over 80. There are statistically significant negative mental health effects for men aged 80
and above, whereas for women, there are statistically significant positive effects on mental
health.
Table 6 shows the marginal effects of the ordered probit regression model for the overall
sample. The results show that being married, being in a cohabitating relationship, and being
divorced/separated/widowed increase the probability of having excellent mental health by .050,
.0170, and .01774 units respectively. It means that being married has a quantitatively greater
positive impact on mental health compared to other marital status categories.
Table 7 shows the marginal mental health effects for the male sample. The results suggest
that being married and being in a cohabitating relationship increase the probability of being in
excellent health by .053 and .020 units respectively. Thus, for males, being married has more
positive impact on having excellent health compared to being in cohabitating relationship.
Table 8 shows the results of the marginal mental health effects for the female sample.
The results show that being married, being in a cohabitating relationship, and being
divorced/separated/widowed increase the probability of being in excellent health by .053, .017,

6

and .022 units respectively. Thus, for females, being married has quantitatively a greater positive
effect on having excellent health compared to other marital status categories.
Table 9 shows the ordered probit estimations of the impact of marital status on wellbeing.
It found that being married or in a common-law relationship has a significant positive impact on
one’s sense of wellbeing as compared to being single for both males and females. Being
divorced/separated/widowed has an insignificant impact on wellbeing in the male’s sample while
it has a significant positive impact on wellbeing in the male sample. Interestingly, this study found
that of all the provinces, those residing in the eastern provinces (Newfoundland, PEI, and Nova
Scotia) typically had the highest level of general wellbeing, and Alberta had the lowest. Level of
education doesn’t overwhelmingly affect someone’s sense of wellbeing, although university
graduates rank the highest. The data suggests owning a home has a significant positive effect on
someone’s wellbeing as opposed to renting. Additionally, income leads to significant positive
impacts while being unemployed has significant negative effects on wellbeing.

Conclusion
Using survey data collected from the Canadian Community Health Survey (2016), this
study examined the impact of marital status on Canadians’ physical and mental health, and their
sense of wellbeing. The study found that for the overall sample, being married or being
divorced/separated/widowed has a significant positive impact on Canadians’ health, while living
in a cohabitating relationship has negative effects on health. The results also show that
quantitatively, being married has a larger positive impact on physical health compared to other
marital status categories. Further, being married, being in a cohabitating relationship, or being
divorced/separated/widowed each have positive effects on mental health. However,
quantitatively, being married has a larger positive effect on mental health compared to other
marital status categories. The study further examined whether there was a gender difference in
the impact of marital status and found slight differences between men and women. It found that
being married has a positive effect on men and women’s health, while cohabitating has a
negative effect on men and women’s health. Divorced/separated/widowed women are healthier
than single people, while there are no statistically significant results for
divorced/separated/widowed men. The study found women and men are both mentally
healthiest when married, and also mentally healthier when cohabitating as opposed to being
single. Divorced/separated/widowed women are mentally healthier than single women, and
there is no statistically significant result for separated/divorced/widowed men’s mental health
effects. The data found that being married has a positive effect on men and women’s wellbeing,
and similarly, cohabitation positively affects someone’s sense of wellbeing. There is no
statistically significant effect on wellbeing for men who are divorced/separated/widowed
whereas there is a positive effect on divorced/separated/widowed women.

7

The data reveals that being married positively affects someone’s physical health as shown
in these results and argued by Umberson (1987) because married partners monitor each other’s
health. They promote healthy behaviours like medical check-ups and discourage harmful ones
like smoking. Averett et. al. (2013) examined the relationship between marital status and health
and found that both married men and married women had lower levels of negative health
behaviours than those who were not married. The overall conclusion as reflected in our results
indicate a strong relationship between marriage and physical health
The study found very similar results in self-rated mental health compared with physical
health with a few critical exceptions. The data suggests married people are typically mentally
healthier than single or common-law people and many studies discuss possible reasons behind
this phenomenon. It is important to note that many of the economic benefits from marriage up
until this point can occur from simply being in a common-law relationship. This data provides
evidence for the claim that marriage can create a greater sense of mental health than commonlaw relationships. For example, Brown (2000) found fewer cases of depression among married
people than among cohabitators. Measuring depressive symptoms is one common methods of
measuring mental health. Studies suggest that marriage reduces depressive symptoms and
divorce increases them (Kim and McKenry, 2002; Simon, 2002). Studies also found that adults in
stable marriages had fewer depressive symptoms than unmarried adults (Marks et al., 1998; Kim
and McKenry, 2002). Additionally, marriage provides emotionally fulfilling and intimate
relationships as described by Wood et. al (2007).
The data reflects the notion that marriage significantly enhances someone’s wellbeing.
Self-identity and self-worth can be enhanced through marriage according to Gove et al. (1990),
ultimately
contributing
to
one’s
overall
sense
of
personal
wellbeing.
Divorced/separated/widowed people tend to have similar sense of wellbeing scores as single
people across both genders. Divorce however, typically has negative effects on happiness levels,
and causes psychological distress following the dissolution of marriage (Johnson and Wu, 2002).
This would suggest that single people also experience lower levels of life satisfaction. Depaulo
and Morris (2005) speculate that one reasonable explanation behind this is society stigmatizes
single people. Rather than stigmatizing single people, wellbeing levels among adults could be
improved if health benefits of partnerships in marriage or common-law were encouraged. In any
case, the effects of marital status on wellbeing are significant, and there is a strong link between
one’s sense of wellbeing and health.
One limitation of this study is it fails to test whether healthy people tend to marry, or
happy people tend to marry. A correlation between being married and improved health doesn’t
necessarily indicate that marriage causes improvements in health. Rather, it’s possible that
healthier and happier people choose to marry in greater proportion than less healthy and happy
people. In order to account for this limitation, longitudinal data must be considered.

8

Future studies may address the relationship between marital status and health behaviour
impacts. If being married promotes certain health behaviours and discourages unhealthy
behaviours, the health benefits to marriage would be increased. Alternatively, if being married
discourages healthy behaviours such as exercising because monogamous partners are not in
need of a mate, health impacts could be negatively impacted.

9

References
Averett, S. L., Sikora, A., & Argys, L. M. (2008). For better or worse: relationship status and body
mass index. Economics & Human Biology, 6(3), 330-349.
Averett, S. L., Argys, L. M., & Sorkin, J. (2013). In sickness and in health: An examination of
relationship status and health using data from the Canadian National Public Health Survey.
Review of Economics of the Household, 11(4), 599-633.
Blumberg, S. J., Vahratian, A., & Blumberg, J. H. (2014). Marriage, cohabitation, and men's use of
preventive health care services, NCHS Data Brief, No. 154, June 2014.
Brown, S.L. (2000), “The Effect of Union Type on Psychological Wellbeing: Depression
Cohabitants Versus Marrieds”, Journal of Health and Social Behaviour, 41, 241-255.
DePaulo, B. M., & Morris, W. L. (2005). Singles in society and in science. Psychological
Inquiry, 16(2-3), 57-83.
Gove, W. R., Style, C. B., & Hughes, M. (1990). The effect of marriage on the wellbeing of adults:
A theoretical analysis. Journal of family issues, 11(1), 4-35.
House J.S., Umberson, D. and Landis, K.R. (1988) "Structures and Processes of Social Support."
Annual Review of Sociology, 14 (2), 293-318.
Johnson, D. R., & Wu, J. (2002). An empirical test of crisis, social selection, and role explanations
of the relationship between marital disruption and psychological distress: A pooled time‐series
analysis of four‐wave panel data. Journal of marriage and family, 64(1), 211-224.
Kim, H. K., & McKenry, P. C. (2002). The relationship between marriage and psychological
wellbeing: A longitudinal analysis. Journal of family Issues, 23(8), 885-911.
Lerman, R. (2002) "Marriage and the Economic Wellbeing of Families with Children: A Review of
the Literature." Washington, DC: The Urban Institute and American University.
Kaplan, R. M., & Kronick, R. G. (2006). Marital status and longevity in the United States
population. Journal of Epidemiology & Community Health, 60(9), 760-765.
Marks, N. F., & Lambert, J. D. (1998). Marital status continuity and change among young and
midlife adults: Longitudinal effects on psychological wellbeing. Journal of Family Issues, 19(6),
652-686.
Simon, R. W. (2002). Revisiting the relationships among gender, marital status, and mental
health. American journal of sociology, 107(4), 1065-1096.
Umberson, D. (1987). "Family Status and Health Behaviors: Social Control as a Dimension of
Social Integration." Journal of Health and Social Behavior, 28(3), 306-319.
Wood, R. G., Goesling, B., & Avellar, S. (2007). The effects of marriage on health: A synthesis of
recent research evidence. Princeton, NJ: Mathematica Policy Research, Inc.

10

Table 1: Impact of Marital Status on Health
Variables
Married
Common Law
Divorced/Separated/ Widow
Base Category: Single
Female
Base category: Male
Newfoundland
PEI
Nova Scotia
New Brunswick
Quebec
Saskatchewan
Manitoba
Alberta
British Columbia
Yukon
Northwest territory
Nunavut
Base Category: Ontario
Secondary School Graduate
University Graduate
Base Category: Less than Secondary
Owned Home
Immigrant

Overall
Sample
0.053***
(0.012)
-0.025*
(0.015)
0.034**
(0.014)

Male
Sample
0.032***
(0.017)
-0.030
(0.022)
0.008
(0.022)

Female
Sample
0.078***
(0.016)
-0.015
(0.021)
0.052***
(0.018)

0.058*
(0.024)
0.024
(0.029)
-0.026
(0.019)
-0.073***
(0.023)
0.166***
(0.011)
-0.063***
(0.019)
-0.021
(0.018)
-0.010
(0.013)
0.007
(0.013)
-0.090**
(0.045)
-0.146***
(0.054)
-0.170*
(0.087)

0.060*
(0.036)
-0.007
(0.047)
-0.047*
(0.029)
-0.086**
(0.036)
0.196***
(0.016)
-0.055*
(0.029)
-0.025
(0.027)
-0.008
(0.019)
0.007
(0.019)
-0.089
(0.062)
-0.129
(0.082)
-0.135
(0.124)

0.059*
(0.032)
0.040
(0.038)
-0.010
0.026
-0.062**
(0.030)
0.141***
(0.015)
-0.074***
(0.027)
-0.020
(0.025)
-0.013
(0.017)
0.007
(0.017)
-0.083
(0.064)
-0.164**
(0.072)
-0.214*
(0.121)

0.193***
(0.013)
0.293***
(0.012)

0.178***
(0.020)
0.280***
(0.018)

0.203***
(0.018)
0.305***
(0.017)

0.154***
(.010)
0.044***
(0.013)

0.142***
(0.015)
0.082***
(0.019)

0.165***
(0.013)
0.013
(0.018)

0.066***
(0.008)

11

White
Income: $20000-$39,999
Income: $40000-$59,999
Income: $60000-$79,999
Income: $80,000 or more
Base Category: Less than $20,000
Age3549
Age5064
Age6579
Age 80 or more
Base Category: Age 25-34
Working

Cut_1
Cut_2
Cut_3
Cut_4

-0.002
(0.016)
0.226***
(0.017)
0.345***
(0.017)
0.415***
(0.019)
0.543***
(0.018)

-0.035
(0.024)
0.205***
(0.028)
0.343***
(0.029)
0.395***
(0.030)
0.536***
(0.029)

0.026
(0.022)
0.235***
(0.021)
0.342***
(0.022)
0.426***
(0.024)
0.543***
(0.023)

-0.235***
(0.012)
-0.395***
(0.012)
-0.282***
(0.015)
-0.316***
(0.021)

-0.228***
(0.018)
-0.432***
(0.018)
-0.314***
(0.022)
-0.339***
(0.035)

-0.242***
(0.017)
-0.363***
(0.017)
-0.253***
(0.020)
-0.294***
(0.027)

0.275***
(0.010)

0.298***
(0.015)

0.254***
(0.013)

-1.311
(0.026)
-0.511
(0.025)
1.548
(0.026)
1.548
(0.026)

-1.400
(0.039)
-0.592
(0.038)
0.424
(0.038)
1.481
(0.039)

-1.303
(0.034)
-0.509
(0.033)
0.477
(0.033)
1.542
(0.034)

Note: Parentheses show standard errors; * significant at 10% level; ** significant at 5% level;
*** significant at 1% level.

12

Table 2: Marginal Effects After Ordered Probit (Health Model- overall sample)

Married
Common Law
Divorced/Separated/
Widow

Poor Health

Fair Health

-0.0027***
(0.0006)
0.0013
(0.0008)
-0.0017***
(0.0007)

-0.007
(0.002)
0.0034
(0.0021)
-0.0047
(0.0018)

Good
Health
-.010595
(.00236)
.0049741
(.00297)
-.0069377
(.00273 )

Very Good
Health
.0056734
(.00126)
-.0027731
(.00171)
.0035992
(.00137)

Excellent
Health
.0148945***
(.00332)
-.0069829*
(.00416)
.0097622***
(.00385)

Note: Parentheses show standard errors; * significant at 10% level; ** significant at 5% level; ***
significant at 1% level.

13

Table 3: Marginal Effects After Ordered Probit (Health Model- Male sample)

Married
Common Law
Divorced/Separated/ Widow

Poor Health

Fair Health

-0.002*
(0.001)
0.002
(0.001)
-0.000
(0.001)

-0.004*
(0.002)
0.004
(0.003)
-0.001
(0.003)

Good
Health
-0.006*
(0.003)
0.006
(0.004)
-0.002
(0.004)

Very Good
Health
0.003**
(0.002)
-0.003
(0.003)
0.001
(0.002)

Excellent
Health
0.009**
(0.005)
-0.008
(0.006)
0.002
(0.006)

Note: Parentheses show standard errors; * significant at 10% level; ** significant at 5% level; ***
significant at 1% level.

14

Table 4: Marginal Effects After Ordered Probit (Health Model- Female sample)

Married
Common Law
Divorced/Separated/ Widow

Poor Health

Fair Health

-0.004***
(0.001)
0.001
(0.001)
-0.003***
(0.001)

-0.011***
(0.002)
0.002
(0.003)
-0.007
(0.003)

Good
Health
-0.015***
(0.003)
0.003
(0.004)
-0.010***
(0.004)

Very Good
Health
0.008***
(0.002)
-0.002
(0.002)
0.005***
(0.002)

Excellent
Health
0.022***
(0.005)
-0.004
(0.006)
0.015***
(0.005)

Note: Parentheses show standard errors; * significant at 10% level; ** significant at 5% level; ***
significant at 1% level.

15

Table 5: Impact of Marital Status on Mental Health
Variables
Married
Common Law
Divorced/Separated/ Widow
Base Category: Single
Female
Base category: Male
Newfoundland
PEI
Nova Scotia
New Brunswick
Quebec
Saskatchewan
Manitoba
Alberta
British Columbia
Yukon
Northwest territory
Nunavut
Base Category: Ontario
Secondary School Graduate
University Graduate
Base Category: Less than Secondary
Owned Home
Immigrant

Overall
Sample
0.140***
(0.012)
0.047***
(0.015)
0.049***
(0.014)

Male
Sample
0.146***
(0.017)
0.056**
(0.022)
0.003
(0.021)

Female
Sample
0.151***
(0.017)
0.049**
(0.022)
0.062***
(0.018)

0.089***
(0.025)
0.022
(0.029)
-0.032*
(0.019)
-0.081***
(0.023)
0.197***
(0.011)
-0.074***
(0.020)
-0.060***
(0.019)
-0.025*
(0.013)
-0.035***
(0.013)
-0.101**
(0.045)
-0.072
(0.056)
-0.167*
(0.087)

0.053
(0.036)
0.018
(0.045)
-0.050*
(0.030)
-0.089**
(0.036)
0.216***
(0.017)
-0.082***
(0.030)
-0.067**
(0.028)
-0.022
(0.020)
-0.036*
(0.020)
-0.231***
(0.067)
-0.095
(0.077)
-0.199*
(0.118)

0.119***
(0.033)
0.021
(0.038)
-0.017
(0.026)
-0.075**
(0.030)
0.181***
(0.012)
-0.072***
(0.028)
-0.059**
(0.025)
-0.030*
(0.018)
-0.034*
(0.018)
0.019
(0.062)
-0.044
(0.081)
-0.131
(0.130)

0.161***
(0.014)
0.206***
(0.0122)

0.155***
(0.020)
0.202***
(0.018)

0.163***
(0.019)
0.213***
(0.017)

0.074***
(0.010)
0.060***
(0.013)

0.065***
(0.016)
0.071***
(0.020)

0.083***
(0.014)
0.051***
(0.018)

-0.046***
(0.008)

16

White
Income: $20000-$39,999
Income: $40000-$59,999
Income: $60000-$79,999
Income: $80,000 or more
Base Category: Less than $20,000
Age3549
Age5064
Age6579
Age 80 or more
Base Category: Age 25-34
Looking
Cut_1
Cut_2
Cut_3
Cut_4

-0.027***
(0.006)
0.234***
(0.017)
0.352***
(0.018)
0.397***
(0.019)
0.503***
(0.179)

-0.085***
(0.025)
0.229***
(0.028)
0.361***
(0.029)
0.415***
(0.030)
0.535***
(0.029)

-0.064***
(0.023)
0.241***
(0.021)
0.353***
(0.023)
0.389***
(0.024)
0.478***
(0.023)

-0.100***
(0.127)
-0.058***
(0.013)
0.112***
(0.014)
0.035*
(0.020)

-0.139***
(0.019)
-0.121***
(0.019)
0.006
(0.021)
-0.170***
(0.033)

-0.070***
(0.017)
-0.004***
(0.017)
0.197***
(0.019)
0.169***
(0.026)

-0.153***
(0.025)
-1.756
(0.028)
-0.967
(0.026)
0.039
(0.026)
1.046
(0.026)

-0.155***
(0.032)
-1.825
(0.042)
-1.034
(0.039)
-0.019
(0.039)
0.972
(0.039)

-0.158***
(0.039)
-1.646
(0.037)
-0.858
(0.035)
0.146
(0.034)
1.168
(0.034)

Note: Parentheses show standard errors; * significant at 10% level; ** significant at 5% level;
*** significant at 1% level.

17

Table 6: Marginal Effects After Ordered Probit (Mental Health Model- overall sample)

Married
Common Law
Divorced/Separated/
Widow

Poor Health

Fair Health

Good Health

-0.00343***
(0.00031)
-0.00110***
(0.00035)
-0.00116***
(0.00032)

-0.01274***
(0.00111)
-0.00416***
(0.00133)
-0.00437***
(0.00122)

-0.03135***
(0.00270)
-0.01047***
(0.00343)
-0.01091***
(0.00309)

Very Good
Health
-0.00324***
(0.00035)
-0.00134**
(0.00054)
-0.00131***
(0.00044)

Excellent
Health
0.05076***
(0.00436)
0.01707***
(0.00564)
0.01774***
(0.00506)

Note: Parentheses show standard errors; * significant at 10% level; ** significant at 5% level; ***
significant at 1% level.

18

Table 7: Marginal Effects After Ordered Probit (Mental Health Model- Male sample)

Married
Common Law
Divorced/Separated/
Widow

Poor Health

Fair Health

Good Health

-0.00325***
(0.00042)
-0.00117***
(0.00044)
-0.00006
(0.00047)

-0.01262***
(0.00154)
-0.00467***
(0.00179)
-0.00024
(0.00183)

-0.03273***
(0.00393)
-0.01251**
(0.00491)
-0.00063
(0.00477)

Very Good
Health
-0.00518***
(0.00067)
-0.00243**
(0.00112)
-0.00010
(0.00078)

Excellent
Health
0.05377***
(0.00642)
0.02079**
(0.00824)
0.00104
(0.00785)

Note: Parentheses show standard errors; * significant at 10% level; ** significant at 5% level; ***
significant at 1% level.

19

Table 8: Marginal Effects After Ordered Probit (Mental Health Model- Female sample)

Married
Common Law
Divorced/Separated/
Widow

Poor Health

Fair Health

-0.00393***
(0.00046)
-0.00124**
(0.00052
-0.00158***
(0.00046)

-0.01421***
(0.00159)
-0.00457**
(0.00194)
-0.00578***
(0.00169)

Good
Health
-0.03369***
(0.00375)
-0.01104**
(0.00481)
-0.01384***
(0.00413)

Very Good
Health
-0.00190***
(0.00039)
-0.00084
(0.00053)
-0.00093**
(0.00038)

Excellent
Health
0.05373***
(0.00600)
0.01769**
(0.00779)
0.02213***
(0.00664)

Note: Parentheses show standard errors; * significant at 10% level; ** significant at 5% level; ***
significant at 1% level.

20

Table 9: Impact of Marital Status on Wellbeing
Variables
Married
Common Law
Divorced/Separated/ Widow
Base Category: Single
Female
Base category: Male
Newfoundland
PEI
Nova Scotia
New Brunswick
Quebec
Saskatchewan
Manitoba
Alberta
British Columbia
Yukon
Northwest territory
Nunavut
Base Category: Ontario
Secondary School Graduate
University Graduate
Base Category: Less than Secondary
Owned Home
Immigrant

Overall
Sample
0.288***
(0.011)
0.177***
(0.014)
0.024*
(0.013)

Male
Sample
0.307***
(0.017)
0.191***
(0.021)
-0.008
(0.021)

Female
Sample
0.278***
(0.016)
0.168***
(0.020)
0.032*
(0.017)

0.202***
(0.027)
0.135***
(0.030)
0.052***
(0.020)
0.076***
(0.024)
0.097***
(0.011)
0.054***
(0.020)
-0.006
(0.019)
-0.049***
(0.013)
-0.028**
(0.123)
-0.025
(0.042)
-0.022
(0.055)
-0.057
(0.072)

0.189***
(0.039)
0.135***
(0.047)
0.067**
(0.031)
0.053
(0.037)
0.123***
(0.016)
0.067**
(0.028)
0.012
(0.028)
-0.035*
(0.019)
-0.016
(0.018)
-0.031
(0.065)
-0.016
(0.076)
0.028
(0.109)

0.211***
(0.037)
0.129***
(0.040)
0.040
(0.027)
0.092***
(0.032)
0.076***
(0.014)
0.042
(0.027)
-0.021
(0.025)
-0.062***
(0.017)
-0.037**
(0.017)
-0.015
(0.055)
-0.023
(0.081)
-0.161*
(0.086)

0.011
(0.014)
0.023**
(0.013)

-0.001
(0.021)
0.034*
(0.019)

0.019
(0.019)
0.012
(0.018)

0.153***
(0.010)
-0.021*
(0.013)

0.179***
(0.015)
-0.011
(0.019)

0.134***
(0.013)
-0.030*
(0.017)

0.098***
(0.008)

21

White
Income: $20000-$39,999
Income: $40000-$59,999
Income: $60000-$79,999
Income: $80,000 or more
Base Category: Less than $20,000
Age3549
Age5064
Age6579
Age 80 or more
Base Category: Age 25-34
Looking
Cut_1
Cut_2
Cut_3
Cut_4

0.044***
(0.015)
0.183***
(0.017)
0.308***
(0.018)
0.358***
(0.019)
0.485***
(0.018)

0.044**
(0.023)
0.148***
(0.029)
0.290***
(0.029)
0.345***
(0.030)
0.491***
(0.029)

0.043**
(0.021)
0.207***
(0.022)
0.325***
(0.023)
0.372***
(0.024)
0.478***
(0.023)

-0.198***
(0.012)
-0.194***
(0.012)
-0.027**
(0.013)
0.057***
(0.021)

-0.202***
(0.017)
-0.226***
(0.017)
-0.068***
(0.020)
-0.017
(0.035)

-0.196***
(0.016)
-0.169***
(0.016)
-0.000
(0.018)
0.095***
(0.027)

-0.289***
(0.023)
-2.357
(0.035)
-1.984
(0.029)
-1.682
(0.027)
-1.390
(0.026)

-0.283***
(0.030)
-2.423
(0.053)
-2.052
(0.044)
-1.725
(0.041)
-1.420
(0.039)

-0.302***
(0.035)
-2.406
(0.045)
-2.033
(0.038)
-1.749
(0.035)
-1.466
(0.034)

Note: Parentheses show standard errors; * significant at 10% level; ** significant at 5% level;
*** significant at 1% level.

22