work and mental health
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- An Analysis of Canadian Community Health Survey. Work and Mental Health. Miao Fang McMaster University May 13, 2005. Outline. Introduction Data, Sampling and Variables Analyses Results Discussion and Conclusion. Background. - PowerPoint PPT PresentationTRANSCRIPT
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Work and Mental Health - An Analysis of Canadian Community Health Survey
Miao Fang
McMaster University
May 13, 2005
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Outline
Introduction Data, Sampling and Variables Analyses Results Discussion and Conclusion
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Background Over 30% of Canadians reported that most days
at work were quite a bit or extremely stressful.
12% of Canadians aged from 15 to 64 suffer from a mental disorder or substance dependence.
The estimated cost of poor mental health in workplace is in billions of dollars.
Work Poor mental health disability and loss of productivity in workplace
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Objective
1. Describe the relationship between work and mental health.
2. Describe the relationship between work and mental health care use for people with mental disorders and substance dependences.
3. Further explore covariates and interactions of any relationships.
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Data Canadian Community Health Survey
CCHS1.1 Response rate: 84.7% Sample size: 131,535 (Ontario workers:23,110)
CCHS1.2 Response rate: 77.0% Sample size: 36,984 (Ontario workers: 8,008)
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Sampling
Complex survey – multistage stratified cluster design
All estimates were weighed to represent the target Ontario workers population
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Variables Dependent variables - Mental disorders and substance dependences (MDSD) CCHS1.1 – Depression (0,1) CCHS1.2 – Any mental disorder or substance dependence (AMDSD) (0,1)
Mental disorders Substance dependences Major depressive episode Alcohol dependence Manic episode Illicit drug dependence Panic disorder Social phobia Agoraphobia
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Variables- Mental health care utilization CCHS1.1 – Consultation with a m.h professional (0,1) CCHS1.2 – Utilization of any resource (for mental health)
(0,1)
Main predictors (exposures) Work stressors (0-48)
Covariates Age, sex, BMI, race, marital status, education, income,
type of smokers (all are categorical variables).
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Analyses
Descriptive Analysis
Bivariate analysis
Logistic regression analysis
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Descriptive Analysis
Two-sample t test
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group outcome theofeach within normal app.
)1,0(~
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Y
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Contingency Table Analysis
Pearson Chi-Squared test for independence
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2 Hunder ~
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Measuring Association The coefficient of contingency
Goodman and Kruskal’s Gamma - test for trend
)/( 22 NXXC
)/()( QPQPG
P - concordant pairs Q – discordant pairsP - concordant pairs Q – discordant pairs
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Multiple Logistic Regression Model
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Point Estimation of Coefficient
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:equations likelihood 1
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Variance Estimation
Maximum likelihood estimation
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Variance Estimation
Bootstrap method
2
1
ˆˆ1ˆˆ
B
bbBOOT B
V
BOOTVARE_V21.SPS
1) Calculate the point estimate using the final weight.
2) Calculate B estimates using the B bootstrap
weights.
3) Calculate the variance of the B estimates.
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Assessing the Fit of the Model- Hosmer-Lemeshow goodness of fit test
To calculate the test statistic Order the fitted values Group the fitted values into g classes of
roughly equal size Calculate the observed and expected number
in each group Perform a goodness of fit test
)exp(1
)exp()(:
)exp(1
)exp()(: 10
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Work Stressors (0 – 48)
Mean=19.4 (sd=5.0)
4239363330272421181512963
Perc
en
t
10
8
6
4
2
0
Mean=19.1 (sd=5.2)
39363330272421181512963
Perc
en
t
10
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6
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2
0
CCHS1.1CCHS1.1 CCHS1.2CCHS1.2
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Work stressors in different depression groups
Work stressors (Depression=1)
42.5
40.0
37.5
35.0
32.5
30.0
27.5
25.0
22.5
20.0
17.5
15.0
12.5
10.0
7.5
5.0
CCHS1.1
Frequency
400
300
200
100
0
Std. Dev = 5.58
Mean = 21.6
N = 1676.82
Work stressors (Depression=0)
50.045.040.035.030.025.020.015.010.05.00.0
CCHS1.1
Fre
quency
10000
8000
6000
4000
2000
0
Std. Dev = 4.92
Mean = 19.2
N = 21127.72
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Work Stressors by MDSD
depression mean mean diff. t Sig.
work stressors
Yes 21.58 2.35 16.74 <.01 No 19.23
AMDSD mean mean diff. t Sig.
work stressors
Yes 21.51 2.69 14.94 <.01 No 18.82
CCHS1.1
CCHS1.2
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Other variables by MDSD
Depression AMDSD C G C G
Age 0.07 -0.20 0.13 -0.32Sex 0.10 - 0.03 -Marital status 0.09 - 0.18 -Education 0.03 -0.08 0.11 -0.16Income 0.06 -0.16 0.02 -0.01Race 0.03 - 0.07 -BMI 0.03 (-0.00) 0.05 (0.04)Type of smoker 0.09 -
All values are significant at 0.05 level except those in parentheses.
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An Example: Logistic Regression Model for AMDSD
Variable Coeff. S.E. OR95% CI for OR
Sig. Lower Upper
Constant -4.70 0.23 0.01 <.01
Work Stressors 0.09 0.01 1.09 1.07 1.10
<.01
15-29 years old 0 1
<.0130-44 years old -0.02 0.11 0.98 0.79 1.22
45-64 years old -0.38 0.13 0.69 0.53 0.88
65 years old or more -0.68 0.38 0.51 0.24 1.06
Less than s.s. grad. 0 1
<.01S.s grad, no post-sec 0.02 0.12 1.02 0.81 1.28
Some post-sec edu 0.53 0.13 1.69 1.33 2.17
Post-sec deg/diploma
-0.04 0.10 0.97 0.79 1.18
Variable Coeff. S.E. OR95% CI for OR
Sig. Lower Upper
Constant -4.70 0.23 0.01 <.01
Work Stressors 0.09 0.01 1.09 1.07 1.10
<.01
15-29 years old 0 1
<.0130-44 years old -0.02 0.11 0.98 0.79 1.22
45-64 years old -0.38 0.13 0.69 0.53 0.88
65 years old or more -0.68 0.38 0.51 0.24 1.06
Less than s.s. grad. 0 1
<.01S.s grad, no post-sec 0.02 0.12 1.02 0.81 1.28
Some post-sec edu 0.53 0.13 1.69 1.33 2.17
Post-sec deg/diploma
-0.04 0.10 0.97 0.79 1.18
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Variable Coeff.
S.E. OR95% CI for OR
Sig. Lower Upper
White 0 1 <.01Non-white 0.64 0.11 1.89 1.54 2.32
Married 0 1
<.01Common-law 0.98 0.13 2.68 2.08 3.45
Wid./Sep./Div. 0.98 0.13 2.67 2.07 3.45
Single 0.85 0.11 1.89 1.54 2.32
An Example Model for AMDSD (Continued)
Goodness-of-fit: Hosmer and Lemeshow x2=3.79 on 8 d.f., P=0.88
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Comparison of Variance Estimations
Variable SE (1) (unadj.)
SE (2) (bootstrap)
Ratio of SE’s SE(2)/SE(1)
Work stressors
15-29 years old (baseline)
30-44 years old
45-64 years old
65 years old or more
Less than s.s grad.(baseline)
S.s.grad, no post-sec.edu.
Some post-sec.grad.
Post-sec. degree/diploma
0.007
0.11
0.13
0.38
0.12
0.13
0.10
0.009
0.12
0.18
0.71
0.14
0.16
0.15
1.29
1.09
1.38
1.87
1.17
1.23
1.50
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Comparison of Variance Estimations (Continued)
Variable SE (1) (unadj.)
SE (2) (bootstrap)
Ratio of SE’s SE(2)/SE(1)
White (baseline)
Non-white
Married (baseline)
Common-law
Wid./Sep./Div.
Single
0.11
0.13
0.13
0.11
0.20
0.23
0.15
0.14
1.82
1.77
1.15
1.27
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Summary of Findings
MDSD
Work stressors highly predicted MDSD
Sub-groups at higher risk of MDSD: non-white, women, younger workers,
smokers, higher BMI, not married
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Summary of Findings (Cont.)
Mental health care use CCHS1.1 - More likely to consult with a
mental health professional: older worker, women, whites, education
at least to high school graduation CCHS1.2 - More likely to use any
resource: older worker, women, non-whites, lower
work stressors
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Conclusion
Work stressors were confirmed as predictive of MDSD.
Identified sub-groups that do not use the health care service for their mental health problems.
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Thank you!