ARCHIVED – Health Status and Social Capital of Recent Immigrants in Canada: Evidence from the Longitudinal Survey of Immigrants to Canada

Regression Results and Discussion

Table 4 presents the survey means and standard errors of the variables used in our empirical models for all immigrants. Time variant variables and time invariant variables are differentiated in the table. The regression results from the GEE models are reported in Table 5.

Table 4:   Survey Means of Variables in the Final Specification Estimation, All Immigrants

N=7656; n=22320

  Weighted mean Standard error
Healthy 0.946 0.002

Time invariant variables

Immigration category Weighted mean Standard error
Family class 0.266 0.003
Skilled worker principal applicants 0.349 0.004
Skilled worker spouses and dependants 0.257 0.003
Refugees 0.063 0.001
Other immigrants 0.066 0.002

Sex Weighted mean Standard error
Male 0.497 0.004
Female 0.503 0.004

World region of birth Weighted mean Standard error
Asia and Pacific 0.598 0.004
North America, the United Kingdom and Western Europe 0.052 0.002
Caribbean and Guyana, South and Central America 0.059 0.002
Europe except UK and Western Europe 0.111 0.002
Africa and Middle-East 0.181 0.003

Education at landing Weighted mean Standard error
High school or less 0.250 0.003
Trade certificate or college, some university 0.199 0.003
University degree 0.361 0.004
Master's degree or above 0.190 0.003

Time variant variables

Age group Weighted mean Standard error
15-19 0.051 0.002
20-34 0.431 0.004
35-44 0.315 0.003
45-64 0.169 0.003
65+ 0.035 0.001

  Weighted mean Standard error
Having problems accessing health care services 0.178 0.003

CMA of residence Weighted mean Standard error
Toronto 0.439 0.004
Vancouver 0.147 0.002
Montreal 0.136 0.003
Calgary 0.052 0.001
Ottawa 0.033 0.001
Other cities 0.193 0.003

Self-assessed language ability Weighted mean Standard error
English 0.832 0.003
No English ability 0.168 0.003
French 0.158 0.003
No French ability 0.842 0.003

Family income Weighted mean Standard error
Income quartile 0-25% 0.251 0.003
Income quartile 25%-50% 0.252 0.003
Income quartile 50%-75% 0.248 0.003
Income quartile 75%-100% 0.250 0.003

Employment Weighted mean Standard error
Employed 0.580 0.004
Not employed 0.420 0.004
No spouse 0.390 0.004
Spouse employed 0.325 0.003
Spouse not employed 0.286 0.003

Social capital variables Weighted mean Standard error
Having relatives in Canada upon landing 0.547 0.004
Number of relatives in Canada 0.807 0.007
Frequency of contact with family sponsors 0.278 0.003
Having friends in Canada upon landing 0.574 0.004
Having made new friends 0.891 0.002
Number of sources meeting friends 2.629 0.012
Frequency of contact with friends 0.766 0.002
Ethnic diversity of friends 0.465 0.002
Number of organizations participated in 0.339 0.005
Ethnic diversity of organizational network 0.016 0.000
Frequency of activities with organizations 0.160 0.002
Numbers of organizations for which the respondent volunteered time 0.178 0.004

Time period Weighted mean Standard error
Wave 1 0.336 0.003
Wave 2 0.331 0.003
Wave 3 0.333 0.003

Source: LSIC (2005).

Let us first look at the regression results for all the LSIC immigrants (see Table 5). 

Column 1 reports the regression results of the specification without social capital variables. The estimated effects of the demographic variables (e.g., age and gender) are consistent with the theoretical explanations and the findings from the existing empirical studies. Males are more likely to report good health than females. Immigrants in the older age groups are more likely to rate their health status as fair or poor. The marginal effects related to the 15-19 age group (reference group) decline as age increases. Immigrants in the oldest age group of 65 and over are less likely to rate their health status as healthy compared to those aged 15-19. However, region of birth does not have a significant effect on the health status of recent immigrants. 

As discussed previously in the descriptive analysis, the health status varies across immigration categories. The regression results confirm that the health status is significantly different across immigration categories, controlled for other characteristics. Compared to family class immigrants, skilled worker principal applicants are more likely to report good health, while refugees are more likely to report poor health.

In terms of perceptions of official language ability variables, health status varies significantly across groups. Compared with no official language ability, being proficient in English is associated with a higher likelihood of reporting as healthy. However, the ability to speak French does not have a significant effect on health. The effect of level of education at landing is also not statistically significant during the initial four years after landing.

For the variables of accessibility to the Canadian health care system, immigrants who have had problems accessing health care services are more likely to rate their health as fair or poor. This may reflect the role of immigrants’ ability to effectively identify and access health care services (including preventive care) in positive perceptions of health status.

Looking at family income quartiles, there are quite large differences in health status across groups. Immigrants in the lowest family income quartile are more likely to report poor health. Furthermore, the employment status of both respondents and their spouses is positively associated with immigrants’ health. 

When including time indicators in the regressions, we confirm the “healthy immigrant effect” – when compared with the situation in wave 1, immigrants are less likely to report being in good health in wave 2 and wave 3 (the likelihoods are 3 percent points and 4.5 percent points, respectively, lower than that in wave 1). [ Note 9 ]

Columns 2 to 4 of Table 5 estimate models with social capital variables. As an initial step, column 2 only adds general indicators of the existing networks including relatives and friends in Canada upon landing, and development of new networks after landing captured by whether an immigrant made new friends in Canada. The addition of these indicators does not change other effects much. Also, making new friends in Canada shows a positive relationship with health status of immigrants. To further investigate which elements play a role among networks, column 3 includes all network content indicators in the model. The results confirm what column 2 indicates – friendship networks matter, particularly frequency of contact and ethnic diversity of the networks. Column 4 presents the final specification with social capital effects.

In terms of social capital variables, our results indicate that friendship networks have a significant effect on the respondents’ self-reported status of health. Both the frequency of contact with friends and the ethnic diversity of friends have significant and positive effects on immigrants’ health.

Immigrants who have more diverse friendship networks and who are in contact with their friends more frequently are more likely to report being in good health. However, it is important to note that we do not find significant effects of family and relative networks or group and organization networks on health for all immigrants.

Table 5:   GEE Population-Averaged Estimations of Probability of Being Healthy for All Immigrants in the First Four Years in Canada

Immigration category 1
No social capital indicators
Marginal effects (dy/dx)
2
Social capital (1)
Marginal effects (dy/dx)
3
Social capital (2)
Marginal effects (dy/dx)
4
Social capital (3)
Marginal effects (dy/dx)
[Family class]        
Skilled worker principal applicants 0.011** 0.008* 0.008 0.009**
Skilled worker spouses and dependants 0.003 0.000 0.000 0.002
Refugees -0.015** -0.018*** -0.018*** -0.016***
Other immigrants 0.013*** 0.011** 0.011** 0.012***

Gender 1
No social capital indicators
Marginal effects (dy/dx)
2
Social capital (1)
Marginal effects (dy/dx)
3
Social capital (2)
Marginal effects (dy/dx)
4
Social capital (3)
Marginal effects (dy/dx)
[Female]        
Male 0.016*** 0.016*** 0.015*** 0.015***

Age group 1
No social capital indicators
Marginal effects (dy/dx)
2
Social capital (1)
Marginal effects (dy/dx)
3
Social capital (2)
Marginal effects (dy/dx)
4
Social capital (3)
Marginal effects (dy/dx)
[15-19]        
20-34 -0.005 -0.004 -0.004 -0.003
35-44 -0.025** -0.024** -0.023** -0.021**
45-64 -0.058*** -0.053*** -0.053*** -0.05***
65+ -0.094*** -0.085*** -0.082*** -0.078***

Region of birth 1
No social capital indicators
Marginal effects (dy/dx)
2
Social capital (1)
Marginal effects (dy/dx)
3
Social capital (2)
Marginal effects (dy/dx)
4
Social capital (3)
Marginal effects (dy/dx)
[Asia and Pacific]        
North America, the United Kingdom and Western Europe 0.017*** 0.016*** 0.014** 0.014**
Caribbean and Guyana, South and Central America 0.008 0.008 0.007 0.006
Europe except UK and Western Europe 0.001 0.001 -0.001 0.000
Africa and Middle-East 0.003 0.004 0.003 0.002

Problems accessing health care services 1
No social capital indicators
Marginal effects (dy/dx)
2
Social capital (1)
Marginal effects (dy/dx)
3
Social capital (2)
Marginal effects (dy/dx)
4
Social capital (3)
Marginal effects (dy/dx)
[Not having problems accessing health care services]        
Having problems accessing health care services -0.039*** -0.039*** -0.038*** -0.039***

Census Metropolitan Area (CMA) of residence 1
No social capital indicators
Marginal effects (dy/dx)
2
Social capital (1)
Marginal effects (dy/dx)
3
Social capital (2)
Marginal effects (dy/dx)
4
Social capital (3)
Marginal effects (dy/dx)
[Other cities]        
Toronto -0.005 -0.005 -0.004 -0.004
Vancouver -0.019*** -0.019*** -0.017*** -0.017***
Montreal -0.002 -0.002 -0.002 -0.002
Calgary -0.012 -0.011 -0.011 -0.011
Ottawa 0.003 0.003 0.004 0.004

Official languages 1
No social capital indicators
Marginal effects (dy/dx)
2
Social capital (1)
Marginal effects (dy/dx)
3
Social capital (2)
Marginal effects (dy/dx)
4
Social capital (3)
Marginal effects (dy/dx)
[No English speaking ability]        
English 0.028*** 0.027*** 0.024*** 0.024***
[No French speaking ability]        
French 0.007 0.007 0.007 0.006

Economic status 1
No social capital indicators
Marginal effects (dy/dx)
2
Social capital (1)
Marginal effects (dy/dx)
3
Social capital (2)
Marginal effects (dy/dx)
4
Social capital (3)
Marginal effects (dy/dx)
[Income quartile 0%-25%]        
Income quartile 25%-50% 0.006** 0.006** 0.006** 0.006**
Income quartile 50%-75% 0.01*** 0.01*** 0.01*** 0.01***
Income quartile 75%-100% 0.011*** 0.011*** 0.011*** 0.012***

Employment status 1
No social capital indicators
Marginal effects (dy/dx)
2
Social capital (1)
Marginal effects (dy/dx)
3
Social capital (2)
Marginal effects (dy/dx)
4
Social capital (3)
Marginal effects (dy/dx)
[Not employed]        
Employed 0.012*** 0.012*** 0.012*** 0.011***

Employment status of spouse 1
No social capital indicators
Marginal effects (dy/dx)
2
Social capital (1)
Marginal effects (dy/dx)
3
Social capital (2)
Marginal effects (dy/dx)
4
Social capital (3)
Marginal effects (dy/dx)
[No spouse]        
Spouse employed 0.007** 0.007** 0.007** 0.007**
Spouse not employed 0.004 0.004 0.004 0.004

Education level at landing 1
No social capital indicators
Marginal effects (dy/dx)
2
Social capital (1)
Marginal effects (dy/dx)
3
Social capital (2)
Marginal effects (dy/dx)
4
Social capital (3)
Marginal effects (dy/dx)
[High school or less]        
Trade certificate or college, some university 0.000 0.000 0.000 0.000
University degree 0.004 0.004 0.004 0.004
Master's degree or above 0.003 0.002 0.003 0.002

Social capital
Family and relatives
1
No social capital indicators
Marginal effects (dy/dx)
2
Social capital (1)
Marginal effects (dy/dx)
3
Social capital (2)
Marginal effects (dy/dx)
4
Social capital (3)
Marginal effects (dy/dx)
Having relatives in Canada upon landing   -0.005*    
Number of relatives     -0.001  
Frequency of contact with family sponsors     -0.002  

Friends 1
No social capital indicators
Marginal effects (dy/dx)
2
Social capital (1)
Marginal effects (dy/dx)
3
Social capital (2)
Marginal effects (dy/dx)
4
Social capital (3)
Marginal effects (dy/dx)
Having friends in Canada upon landing   -0.003    
Having made new friends   0.014***    
Number of friends     0.000  
Frequency of contact with friends     0.015*** 0.015***
Ethnic diversity of friends     0.013** 0.013***

Groups and organizational network 1
No social capital indicators
Marginal effects (dy/dx)
2
Social capital (1)
Marginal effects (dy/dx)
3
Social capital (2)
Marginal effects (dy/dx)
4
Social capital (3)
Marginal effects (dy/dx)
Number of groups or organizations participated in     -0.003  
Frequency of activities with organizations     0.008  
Ethnic diversity of organizational networks     -0.001  
Number of organizations volunteered time for     0.002  

Time effect 1
No social capital indicators
Marginal effects (dy/dx)
2
Social capital (1)
Marginal effects (dy/dx)
3
Social capital (2)
Marginal effects (dy/dx)
4
Social capital (3)
Marginal effects (dy/dx)
[Wave 1]        
Wave 2 -0.028*** -0.03*** -0.03*** -0.03***
Wave 3 -0.042*** -0.042*** -0.046*** -0.045***

  1
No social capital indicators
Marginal effects (dy/dx)
2
Social capital (1)
Marginal effects (dy/dx)
3
Social capital (2)
Marginal effects (dy/dx)
4
Social capital (3)
Marginal effects (dy/dx)
No. of observations 22377 22375 22049 22320
No. of individuals 7656 7656 7652 7656

Notes: * p<0.1; ** p<0.05; *** p<0.01; marginal effects for dummy variables are for discrete change from 0 to 1; reference categories are in brackets.

Source: LSIC (2005).

Regression results for family class immigrants

In order to investigate the different ways in which social capital affects the health status of immigrant sub-groups, we also present the regression results of our GEE model for the reference group of family class immigrants (see Table 6). 

Noteworthy regression results indicate that family and relative networks, friendship networks, and group and organization networks all have significant effects on the health status of recent family class immigrants.

Unlike the results from the model for all immigrants, for each of the three networks the effects of frequency of contact with network members or units are all statistically significant. Compared to those who do not have contact with friends or take part in organizational activities regularly, family class immigrants who interact with friends or groups on a daily basis are more likely to report that they are healthy.

However, frequency of contact with family sponsors is associated with a lower likelihood of reporting a positive health status. This may be partly due to the fact that a large proportion of family class immigrants are sponsored parent and grandparent immigrants (PGPs), who tend to be much older than the average family class immigrant. [ Note 10 ] The LSIC shows that the majority of PGPs lived with their family sponsors during the initial years after landing, and elderly PGPs are more likely to live with their sponsors (Zhao 2007b). In addition, a significant number of PGPs (37 percent at six months after landing, and 34 percent at two years after landing) who live with their sponsors provide unpaid labour for their sponsors, such as maintaining a house and caring for family members, which might be a factor that negatively affects their health. Another possible explanation for this finding may rest in the negative potentiality of social capital. As indicated in the literature review, social capital is not inherently positive; it may be the case that the frequency of contact with family members is connected to increased demands for time, resources, and energy by these networks. These excessive demands may adversely affect the health of recent immigrants.

The regression results also indicate that social network size and social network diversity do not have any significant effect on family class immigrants’ health.

Table 6:   Social Capital Effects on Probability of Being Healthy in the Initial Four Years in Canada, Family Class Immigrants

Social capital Marginal effects (dy/dx) Standard error
Frequency of contact with family sponsors -0.018** 0.008
Frequency of contact with friends 0.027*** 0.009
Frequency of activities with organizations 0.031*** 0.010

Time effect Marginal effects (dy/dx) Standard error
[Wave 1]    
Wave 2 -0.044*** 0.009
Wave 3 -0.068*** 0.013

No. of observations 5621
No. of individuals 1985

Notes: * p<0.1; ** p<0.05; *** p<0.01. Reference categories are in brackets; marginal effects for dummy variables are for discrete change from 0 to 1; GEE population-averaged regression is used. The regression also includes controls for sex, age group, area of birth, incidence of problems accessing Canadian health care system, CMA of residence, ability of official languages, family income, employment status of the respondent and the spouse, and education. 

Source: LSIC (2005).


9 To investigate the time effects, we control for two types of time variables: (1) number of weeks in Canada since landing (continuous variable), and (2) wave variables (dummy variables). Both methods provide us with similar regression results: the respondents’ self-rated health status is significantly and negatively related to increased time in Canada. This is consistent with our findings in the descriptive analysis that the health of recent immigrants declines over time. In Table 5 we only report results from the models with wave indicators used.

10 In the LSIC, PGPs account for 34 percent of family class immigrants. In 2001, the average age at landing of family class immigrants was 34 years, while the average age at landing of PGPs was 52 years – calculations based on data extracts on 31 March 2009 from CIC’s Permanent Resident Data System (PRDS).

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