Impact of Perceived
Discrimination on Use of
Preventive Health Services
Amal Trivedi, M.D., M.P.H.
John Z. Ayanian,
Ayanian, M.D., M.P.P.
Background
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Harvard Medical School/Brigham and Women’s Hospital
AcademyHealth Annual Research Meeting
June 8, 2004
Inequalities in health care based on race,
gender, socioeconomic status, and
geography
Mechanisms for disparities not known
Institutional or individual biases in delivery
of care
Discrimination and Health
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Growing body of research focusing on
experiences of discrimination and their
impact on health
Several forms of discrimination including
institutional and interpersonal
Evidence of association between perceived
discrimination and correlates of health
Research Questions
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What proportion of the population has had
recent experience with discrimination in the
health care setting?
What is the impact of perceived
discrimination on receipt of appropriate
preventive care?
What proportion of observed health care
disparities can be explained by perceived
discrimination?
Methods – Source of Data
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CrossCross-sectional study of the 2001 California
Health Interview Survey (CHIS)
54,968 adult respondents representative of
nonnon-institutionalized population
Oversampling of Asian, Latino, and rural
populations
Unweighted response rate of 43% and
participation rate of 76%
Methods – Study Variables
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Independent variable:
Subjects asked “Thinking of your experiences
receiving health care over the past twelve
months, have you ever felt discriminated
against?”
„ If respondents answered yes, they were asked
for specific reason for discrimination
„
1
Methods – Outcome Variables
Preventive Service
Time Period Population
1. Aspirin Use
Current
Persons with Heart
Disease, HTN>50
2. Cholesterol Test
12 months
Persons with Heart
Disease, HTN>50
3. HbA1C Testing
12 months
Persons with Diabetes
4. Foot Exam
12 months
Persons with Diabetes
5. Flu Vaccination
12 months
Adults > 65
6. Sigmoidoscopy
5 years
Adults > 50
7. PSA Testing
12 months
Men > 50
8. Pap Testing
3 years
Women 1818-65 with no
previous hysterectomy
9. Mammography
2 years
Women 5050-79
Results
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Methods - Analyses
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Bivariate analysis/chianalysis/chi-square tests:
perceived discrimination across subgroups
Multivariable logistic regression using
propensity scores predicting likelihood of
discrimination
Stratified by race, gender, and insurance
status and determined odds ratios for receipt
of services before and after adjusting for
discrimination
Results – Rates of Discrimination
4.7% of population reported recent discrimination
in receiving health care
Population estimate of nearly 1.1 million
Californian adults
Most common reasons for discrimination were
insurance type (28%), race (14%) and income(7%)
Insurance type most common reported reason for
men, women, uninsured, insured, Whites, Latinos,
American
- Indians
Discrimination due to race most commonly
reported by African
- Americans and Asians
Unadjusted Estimates of
Preventive Service Use
Characteristic
Race*
AfricanAfrican-American
White
Latino
Asian
AmericanAmerican-Indian
6.1%
4.2%
5.8%
2.9%
8.8%
Gender*
Male
Female
4.0%
5.3%
Income (% of FPL)*
<100
100100-199
200200-299
300 or more
7.6%
6.2%
4.4%
3.4%
Characteristic
%Reporting
Discrimination
Insurance Status*
Uninsured
Medicaid
Medicare/Private
7.7%
9.2%
3.4%
Perceived Health
Status*
Excellent
Very Good
Good
Fair
Poor
2.7%
3.0%
4.5%
9.0%
15.4%
* P<0.01 (Chi-Square Test)
Unadjusted Estimates of Cancer
Preventive Service Use
90
90
80
80
70
70
60
% Reporting
Discrimination
60
50
Discrimination
No Discrimination
40
30
50
Discrimination
No Discrimination
40
30
20
10
* P<0.05
20
* P <0.05
10
0
ASA
Use
Chol
Test*
Foot HbA1C Flu Shot
Exam Test*
0
Sigmoidoscopy
PSA Test*
Pap Test
Mammogram*
2
Adjusted Odds Ratios for Receipt of AgeAgeand DiseaseDisease-Appropriate Preventive Care
ASA Use
Adjusted Odds Ratios for Receipt of
Cancer Preventive Services
Sigmoidoscopy
Cholesterol
Test*
Discrimination
No Discrimination
Foot Exam*
PSA Test
Pap Test
* P<0.05
HbA1C Test*
Discrimination
No Discrimination
Flu Vaccine*
Mammogram
0
0.2
0.4
0.6
0.8
1
1.2
0
Observed Disparities in Receipt
of Preventive Services
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Women less likely to receive 5 of 6 services
AfricanAfrican-Americans less likely to receive 2,
American Indians 3, Asians 6 and Latinos all
9 preventive services relative to Whites
Uninsured less likely to receive all 9 services
Adjusting for perceived discrimination had a
negligible impact on disparities by race,
gender, and insurance status
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Nearly 5% of a statewide sample report recent
experience with health care discrimination
Persons who report discrimination are less likely to
receive some age- and disease appropriate
preventive services
Perceived discrimination is unlikely to account for
a large portion of observed disparities by race,
gender, and insurance status
0.4
0.6
0.8
1
1.2
1.4
Limitations
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Conclusions
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0.2
Lack of information about specialized
medical services; intensity and frequency of
experienced discrimination; and other
domains of discrimination
CrossCross-sectional study design precluded
assessment of causal mechanisms between
discrimination and use of health care
Implications
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Need to more clearly elucidate reasons for
perceived discrimination in obtaining health
care
Examine other forms of discrimination and
their impact on health and other health care
outcomes including use of tertiary/specialty
services
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