Transcript Slide 1

Black/White Racial Disparity in Child Welfare:
Findings from Linkages to Birth Record Data
Barbara Needell, PhD, MSW
Emily Putnam-Hornstein, PhD, MSW
Center for Social Services Research
University of California at Berkeley
We gratefully acknowledge the support of the
California Department of Social Services, the Stuart Foundation, and Casey Family
Programs
CENTER FOR SOCIAL SERVICES RESEARCH
School of Social Welfare, UC Berkeley
The problem with summary statistics:
The average human has one breast and one testicle. *
* ~Des McHale www.quotegarden.com/statistics.html
CENTER FOR SOCIAL SERVICES RESEARCH
School of Social Welfare, UC Berkeley
Data
• Unique dataset constructed by linking children reported for
maltreatment during the first five years of life to their birth
record
– state CWS/CMS records linked to vital birth records
– probabilistic methods (84% of child welfare records matched)
• 530,843 children born alive in CA in 2002
– 14% reported for maltreatment (N=74,182)
– 6% substantiated as a victims (N=27,805)
– 0.8% entered foster care (N=4,388)
• Racial disparities?
– examined aggregate Black vs. White disparity across decision points
– estimated child level risk at each decision point, after adjusting for
other risk factors
CENTER FOR SOCIAL SERVICES RESEARCH
School of Social Welfare, UC Berkeley
Racial Disparity…
CENTER FOR SOCIAL SERVICES RESEARCH
School of Social Welfare, UC Berkeley
Across several decision points.
Racial Disparities:
California's 2002 Birth Cohort, by Decision Point
2.55
2.46
Risk Ratios
2.25
Reported
Substantiated
Entered Care
(N=74,182)
(N=27,805)
(N=4,388)
Black vs. White RR
CENTER FOR SOCIAL SERVICES RESEARCH
School of Social Welfare, UC Berkeley
95% Confidence Interval
What is hidden beneath the summary statistics?
• Significant racial variations in the presence of risk factors that
are associated with disparities…
• In multivariate models, we adjusted for twelve
sociodemographic and biomedical risk factors for contact with
child protective services:
• child’s sex (n.s.), low birth weight, birth abnormality, prenatal care,
maternal birth place, maternal race/ethnicity, birth payment
method, maternal age, maternal education, abortion history,
paternity information, birth order
• Significant interactions between a number of covariates and
Medi-Cal coverage led us to stratify models
CENTER FOR SOCIAL SERVICES RESEARCH
School of Social Welfare, UC Berkeley
Reporting Disparities:
California's 2002 Birth Cohort, by Medi-Cal Coverage at Birth
* includes adjustments for other risk factors present at birth
2.62
2.25
1.54
1.19
crude
adjusted*
1.10
crude
adjusted*
0.93
Full Birth Cohort
Medi-Cal Coverage
(N=530,843)
(N=226,904)
Black vs. White RR
CENTER FOR SOCIAL SERVICES RESEARCH
School of Social Welfare, UC Berkeley
crude
adjusted*
Non Medi-Cal Coverage
(N=302,259)
95% Confidence Interval
Substantiation Disparities:
California's 2002 Birth Cohort, by Medi-Cal Coverage at Birth
* includes adjustments for other risk factors present at birth
3.03
2.46
1.50
1.06
crude
adjusted*
1.03
crude
crude
adjusted*
Full Birth Cohort
(N=530,843)
Black vs. White RR
CENTER FOR SOCIAL SERVICES RESEARCH
School of Social Welfare, UC Berkeley
0.82
Medi-Cal Coverage
(N=226,904)
adjusted*
Non Medi-Cal Coverage
(N=302,259)
95% Confidence Interval
Entry Disparities:
California's 2002 Birth Cohort, by Medi-Cal Coverage at Birth
* includes adjustments for other risk factors present at birth
3.64
2.55
1.46
1.07
1.03
crude
adjusted*
crude
crude
adjusted*
0.83
adjusted*
Full Birth Cohort
Medi-Cal Coverage
(N=530,843)
(N=226,904)
Black vs. White RR
CENTER FOR SOCIAL SERVICES RESEARCH
School of Social Welfare, UC Berkeley
Non Medi-Cal Coverage
(N=302,259)
95% Confidence Interval
• Summary statistics that indicate Black/White disparity
mask large covariate effects
Questions these data don’t answer:
• Why are people poor?*
• Are the service needs of Black and White children and families being
addressed?
• Are “thresholds” the same for Black and White children and
families?
• Why is there no disparity (or reverse disparity) in the Medi-Cal
group? Why are there relatively large disparities in the non Medi-cal
group?
• What are the appropriate rates for Black and White children?
* http://www.pisab.org/
CENTER FOR SOCIAL SERVICES RESEARCH
School of Social Welfare, UC Berkeley
More to come (e.g., Black vs. Hispanic analysis and full article with
detailed tables)
CENTER FOR SOCIAL SERVICES RESEARCH
School of Social Welfare, UC Berkeley