Effects of Psychological Distress on
Employment among Mothers in
Low-Income Families
Leigh Ann White
June 7, 2004
AcademyHealth Annual Meetings
San Diego, CA
Support for this research
National Institute for Mental Health
Johns Hopkins Bloomberg School of Public Health,
Department of Health Policy & Management
University of Michigan, National Center on Poverty
I would like to acknowledge Eric Slade, Dan Ford, Darrell
Gaskin, Nan Astone, Harold Pollack, and others for their
input on my dissertation and working papers.
Thanks also go to Andy Cherlin, Robert Moffitt, Paula Fomby,
and Jen Roff for their work on the survey component of the
Welfare, Children, and Families Three-City Study.
Objective
• How does mental health of low-income
women affect their ability to find and
retain work?
• Main outcome: Labor force attachment
– proportion of time, in fractions of months,
that a woman spent in employment during
a specified period
Rationale
• Previous evidence
– documented relationship between mental
illness and labor market outcomes
• Policy concern: Welfare Reform
– Those left on the rolls experience more
obstacles to employment.
• Magnitude of problem
– relatively high prevalence of mental illness
among low-income women
Data
• WCF Three-City Study
– Longitudinal; 2 interview waves (1999 and 2000-01)
– Post-1996 Welfare Reform, pre-recession
experiences of 2,400 child/caregiver dyads in
Boston, Chicago, and San Antonio
• Study sample
– Female caregivers of sampled focal children,
interviewed in both waves, with complete data on
key variables
– In households <200% of FPL
– N=1,656 female caregivers aged 18-64
Conceptual Framework
Personal and Family
Characteristics
Human Capital
(education, job tenure,
employment history)
Employment Status
and Work Experience
@T1
Welfare Experience
Nonlabor Income
Social and Behavioral
Stressors
Survey-related variables
Mental Health
Status@T1
Labor Force
Attachment
T1 - T2
(Two-limit Tobit)
Measure of mental health status
• Brief Symptom Inventory (BSI-18)
– sensitive screening instrument (Derogatis)
– self-reported of level of distress, 0-4; 18 items
• Scoring
– Global Severity Index (GSI)
– Three subscores (DEP, ANX, SOM)
• Case criteria
– Standardized GSI or any of three subscores met
recommended clinical cutoff
– 19% in this sample met case criteria
Labor Force Attachment:
Descriptive Statistics
Sample
Mean
(95% C.I.)
Total sample (N=1,656)
Held a job between interviews
Proportion of time in employment, Wave 1-2
Conditional proportion of time employed (N=1,138)
.69
.50 (.48, .52)
.73 (.71, .74)
Limited to those with work experience (N=1,255)
Held a job between interviews
Proportion of time in employment, Wave 1-2
Conditional proportion of time employed (N=1,121)
.91
.65 (.63, .67)
.73 (.71, .75)
Results: Model Coefficients
Covariate
OLS
(N=1,656)
Tobit
(N=1,656)
Tobit
(N=1,255)
Met BSI-18 case criteria
-.071
-.129
-.086
Age
-.004
-.009
NS
.072
.109
.053
Married
-.088
-.152
NS
Pregnant
-.179
-.290
-.202
Log of nonlabor income
-.037
-.055
-.024
Other receiving SSDI
-.116
-.231
-.009
Months on welfare since 1/96
-.004
-.006
-.001
Dealt or used drugs in past year
-.097
-.162
-.151
Non-Hispanic Black
Results: Model Coefficients (con’d)
Covariate
Log of job tenure
OLS
(N=1,656)
Tobit
(N=1,656)
Tobit
(N=1,255)
-
-
.047
Education (HS omitted)
<HS
>HS
-.140
.044
-.216
.068
-.116
NS
Sample city (Chicago omitted)
Boston
San Antonio
-.049
-.056
-.087
-.078
NS
NS
.1975
.1178
518
1,017
121
.1195
134
1,002
119
Adjusted or Pseudo R-squared
N left-censored
N uncensored
N right-censored
Model Predictions from Two-Limit Tobit
Did not meet BSI18 Case Criteria
Met BSI-18
Case Criteria
Total sample (N=1,656)
N=1,347
N=309
Prob [Employed]
E [Prop time employed]
.57
.49 (.002)
.51
.43 (.004)
Limited sample (N=1,255)
N=1,047
N=208
Prob [Employed]
E [Prop time employed]
.71
.57 (.002)
.75
.51 (.005)
Implications
• Some evidence of a relationship between
mental health and job retention
– “job churning” a possibility
– Interventions improving mental health status are likely to
have a positive impact on productivity.
• Importance of addressing stressors
– Why does there exist a relationship between mental health
and employment?
– How do proximate and distal stressors induce symptoms
and affect employment?
Welfare, Children and Families ThreeCity Study: Principle Investigators
Ronald J. Angel, University of Texas at Austin
Linda M. Burton, Pennsylvania State University
P. Lindsay Chase-Lansdale, Northwestern
University
Andrew J. Cherlin, Johns Hopkins University
Robert A. Moffitt, Johns Hopkins University
William Julius Wilson, Harvard University
Website: http://www.jhu.edu/~welfare/
Welfare, Children and Families Study:
Federal Funding Agencies
National Institute of Child Health and Human Development
U.S. Department of Health and Human Services:
Office of Disability, Aging, and Long-Term Care Policy, Office
of the Assistant Secretary for Planning and Evaluation
Administration on Developmental Disabilities
Administration for Children and Families
Office of Research, Evaluation, and Statistics, Office of Policy,
Social Security Administration
National Institute of Mental Health
Welfare, Children, and Families Study:
Foundation Support
The Boston Foundation
The Annie E. Casey Foundation
The Edna McConnell Clark Foundation
The Lloyd A. Fry Foundation
Hogg Foundation for Mental Health
The Robert Wood Johnson Foundation
The Joyce Foundation
W.K. Kellogg Foundation
Kronkosky Charitable Foundation
The John D. and Catherine T. MacArthur Foundation
Charles Stewart Mott Foundation
Woods Fund of Chicago