Seediscussions,stats,andauthorprofilesforthispublicationat:
https://www.researchgate.net/publication/263531121
DiagnosingDiscrimination:
StressfromPerceivedRacism
andtheMentalandPhysical
HealthEffects*
ArticleinSociologicalInquiry·February2013
ImpactFactor:0.79·DOI:10.1111/j.1475-682X.2012.00433.x
CITATIONS
READS
8
285
1author:
KathrynFreemanAnderson
TheUniversityofArizona
6PUBLICATIONS18CITATIONS
SEEPROFILE
Availablefrom:KathrynFreemanAnderson
Retrievedon:12May2016
Diagnosing Discrimination: Stress from Perceived Racism
and the Mental and Physical Health Effects*
Kathryn Freeman Anderson, University of Arizona
Differences in health between racial groups in the United States are significant
and persistent. Many studies have documented these differences as a result of a variety
of different social factors. An emerging emphasis is the impact of racism in its various
forms on physical and mental health. Social stress theory conceptualizes racism as a
social stresssor which can produce negative health consequences for racial minorities.
This study uses binary logit and negative binomial regression models of four items
from the 2004 Behavioral Risk Factor Surveillance System (BRFSS) to test social
stress theory and examine the relationship between stress symptoms from perceived
racism and overall health (N = 32,585). The effect of race on the experience of emotional and physical stress symptoms from racism is substantial. Furthermore, experiencing both emotional and physical stress from perceived racist treatment is an important
factor in predicting the number of poor mental and physical health days, indicating that
the experience of stress from perceived racism is related to overall poorer health.
Introduction
A well-established body of literature focuses on documenting the differences in health between racial groups in the United States (Williams 1999).
Several approaches for understanding why such disparities in health exist are
prevalent throughout this literature (Dressler, Oths, and Gravlee 2005; Hummer
1996). A more recent focus of this research emphasizes how the various
mechanisms of racism can impact health for certain racial minorities in the
United States (Dressler, Oths, and Gravlee 2005; Hummer 1996). Numerous
studies now demonstrate a relationship between racism and a variety of both
mental and physical health outcomes (Paradies 2006; Williams and Mohammed
2009). With this study, I provide further evidence of how the stress of
perceived discrimination can impact general mental and physical health.
The first portion of this study examines the determinants of emotional
and physical stress from perceived racism and addresses the question: How
does being a racial minority affect the experience of emotional or physical
stress from perceived racism? I hypothesize that being a racial minority will
be associated with a greater likelihood of experiencing stress from perceived
Sociological Inquiry, Vol. xx, No. x, 2012, 1–27
2012 Alpha Kappa Delta
DOI: 10.1111/j.1475-682X.2012.00433.x
2
KATHRYN FREEMAN ANDERSON
racism. The second portion of this study analyzes the relationship between
stress symptoms and health and seeks to answer the following question: Is the
experience of emotional or physical stress from racist treatment related to
overall poorer mental and physical health? I hypothesize that the stress symptoms produced from perceived racist treatment will be associated with overall
poorer health outcomes.
With this study, I contribute to this growing body of literature demonstrating a relationship between racism and a variety of negative health outcomes. I utilize social stress theory as a conceptual framework and contend
with prior critiques of the theory for studying the association between stress
and racial health disparities (Schwartz and Meyer 2010). To accomplish this,
I use the 2004 version of the Behavioral Risk Factor Surveillance System
(BRFSS), which provides a unique set of survey items on the emotional and
physical stress symptoms that one may experience in response to perceived
racism. Through these survey items, rather than studying the direct effects of
racism, this study analyzes the experience of stress in response to perceived
racism and relates the stress experience to overall poorer health outcomes.
I also use poor physical and mental days as the main health outcome, which is
an outcome seldom used in the current literature on the topic. From these theoretical and methodological advantages, I provide further evidence of the relationship between the stress that perceived racism may elicit and its overall
effect on general health.
Conceptual Framework
Racism and Health
Differences in health outcomes by race are well documented, and several
theoretical approaches have emerged for understanding why these differences
persist: genetics, cultural and behavioral practices, or socioeconomic status
(Dressler, Oths, and Gravlee 2005; Hummer 1996). While these theoretical
approaches are not mutually exclusive, the studies on the subject tend to
emphasize one primary approach. Racial health disparities need to be analyzed
and understood by taking into account the social conditions which created
them and the hostile racial climate of the United States which allows such
conditions to flourish. They need to be understood, ‘‘not only in terms of individual characteristics but also in light of patterned racial inequalities in exposure to societal risks and resources’’ (Williams and Braboy Jackson 2005:325).
A fourth theoretical approach emphasizes the impact of racism and racist
structures within society as a central explanatory factor for racial differences
in health. Only until fairly recently has racism in its numerous forms been
considered an important theoretical approach for our understanding of the
STRESS FROM RACISM AND THE HEALTH EFFECTS
3
sources of racial health disparities. This research examines the effect of perceived racism as one explanatory factor for the significant disparities in health
by race and contributes to this growing body of research which demonstrates
the connection between racism and a variety of health outcomes.
Racism is manifested in a number of different ways and across different
dimensions. It can be institutional, structural, individual, or internal. Racism is
the systematic disadvantage of certain groups, as well as the systematic privilege of the dominant group (Fujishiro 2009; Paradies 2006). Institutionally,
racism is pervasive throughout the systems of housing, education, the judicial
system, employment, and the healthcare system (Shavers and Shavers 2006).
Individual racism may take the more overt forms of social avoidance and
social exclusion, discrimination in the workplace, stigmatization, or harassment and threat (Brondolo et al. 2009; Shavers and Shavers 2006), or it may
take the less-perceptible forms such as attitudes and beliefs against minorities
in the form of ‘‘micro-aggressions’’ (Sue et al. 2007). Racism can also be
internalized, where racial minorities accept the racist attitudes and stereotypes
about themselves (Paradies 2006). Although this study does not focus on any
particular manifestation of racism, the focus is on the stress that may result
from perceived racism.
Much recent work has been conducted analyzing the various ways which
these sources of racism may impact health. Racism is negative event or
chronic experience which may produce a variety of reactions from those who
are subject to it. Williams and Mohammed (2009:21) write that, ‘‘targets of
discrimination are aware of some of the discriminatory behavior directed at
them and these perceptions of unfair treatment can generate stress.’’ A strong
emphasis in the empirical literature on the subject is the psychological impact
of individual-level perceived racism (Williams and Mohammed 2009). These
studies suggest that racism may be a mental stressor which acts to harm mental as well as physical health (Kwate et al. 2003; Okazaki 2009; Paradies
2006; Peters 2006; Williams and Williams-Morris 2000). Stress has been
shown to accelerate cellular aging, which can wear down the body’s systems
and produce a variety of illnesses and premature mortality (Williams and
Mohammed 2009). Additionally, racism as a stressor may also impact health
in that it may serve to prompt unhealthy coping behaviors such as eating, or
substance abuse in the form of smoking, drinking, and drug use (Brondolo,
Gallo, and Myers 2009; Brondolo et al. 2009; Kwate et al. 2003; Paradies
2006).
Numerous empirical studies document particular physical impacts on
health from racism (Williams and Mohammed 2009). To cite a few specific
examples, Kwate et al. (2003) found a relationship between short-term and
long-term racism and perceived health, lifetime disease, and the common cold
4
KATHRYN FREEMAN ANDERSON
in addition to psychological distress. Perceived racism is also linked to weight
gain for African American women, as demonstrated in Vines et al.’s study
(2007) on abdominal fat and Cozier et al.’s study (2009) on obesity. Gee and
Walsemann (2009) found a relationship between racial discrimination and
work-related health limitations, and Fujishiro (2009) found an association
between racial disadvantage in the workplace and generally poorer health.
Many of these studies, though, include an emphasis on emotional or mental
health as a pathway to physical symptoms (Cozier et al. 2009; Kwate et al.
2003; Vines et al. 2007). Similarly, this study contributes to this literature by
conceptualizing racism as a social stressor which can impact both mental and
physical health.
Social Stress
Social stress theory emphasizes the social sources of stress factors which
may impact mental and physical health outcomes (Aneshensel 1992; Pearlin
1989). The theory argues that certain groups within society are in a disadvantaged social position, which leads to an increased exposure to social sources
of stress and less resources with which to cope with stress (Aneshensel 1992;
Dressler, Oths, and Gravlee 2005). Aneshensel (1992:16) defines stress as
‘‘internal arousal’’ and stressors as ‘‘external circumstances that challenge or
obstruct.’’ Social stress theory highlights these ‘‘external circumstances’’ of
social life (Aneshensel 1992). These factors can then lead to higher prevalence
of health problems within those populations with social disadvantage (Aneshensel 1992; Pearlin 1989). This study examines race as one such source of
disadvantaged social position which can impact health. Of note, not all racial
and ethnic minority members experience this disadvantage or experience it
uniformly. However, minority status in U.S. society places one in a disadvantaged position at risk for discrimination and social stress.
Schwartz and Meyer (2010), in a recent article, are critical of the social
stress model for studying racial health disparities. Schwartz and Meyer (2010)
provide a conceptual model for social stress theory which involves two main
pathways, the second of which consists of two parts. The first pathway demonstrates a relationship between race and negative health outcomes (Schwartz
and Meyer 2010). The second pathway demonstrates a relationship between
race and stress, and then furthermore between stress and negative health outcomes (Schwartz and Meyer 2010). They argue that researchers must test all
three of these pathways to provide evidence for the social stress model
(Schwartz and Meyer 2010). They argue that most studies of social stress and
discrimination only examine either the first pathway between race and health
outcomes through between-group analyses, or the third part of the model
examining stress and mental disorder through within-group analyses (Schwartz
STRESS FROM RACISM AND THE HEALTH EFFECTS
5
and Meyer 2010). They argue that studies fall short by failing to consider the
complete pathway by demonstrating a relationship between race and stress,
and subsequently the impact of such stress on health outcomes (Schwartz and
Meyer 2010). This study fills this gap presented by the Schwartz and Meyer
criticism and examines both of these components of the social stress conceptual model by first examining whether or not being a racial minority leads to
higher incidence of reported stress symptoms and then whether or not the
experience of these symptoms leads to overall reduced health.1
Using the social stress model, I developed two hypotheses which I test in
this study. First, I test the first part of the second pathway, which examines
whether or not being a racial minority leads to greater stress. My hypothesis is
that racial minorities will be more likely to experience both emotional and
physical stress symptoms from differential treatment on the basis of race as
compared to whites. Next, I test the second part of the second pathway of the
model, which examines whether or not these stressors lead to higher rates of
mental and physical health problems. My hypothesis is that having experienced stress from perceived racism will be a predictor for overall poorer mental and physical health. The analysis of these items is meant to gain an
understanding of the significance of race in the experience of emotional and
physical stress symptoms, and whether or not experiencing this stress is a substantial indicator of generally poor mental and physical health.
Data and Methods
To examine the effect of symptoms from racism on health, I used the
2004 Behavioral Risk Factor Surveillance System (BRFSS) which is from the
National Center for Chronic Disease Prevention and Health Promotion (Centers for Disease Control and Prevention 2004). Each year the BRFSS includes
optional modules which are only conducted in select states. I used the ‘‘Reactions to Race’’ module of the 2004 version which was conducted in seven states
(Arkansas, Colorado, Delaware, Mississippi, Rhode Island, South Carolina,
and Wisconsin) and the District of Columbia. Although a more recent version
of the data set exists, I chose to the use the 2004 version as it includes more
states across various regions. One could argue that these eight areas are
diverse enough to be representative of the United States, but the module only
includes these eight locations and therefore any findings from this study can
only be generalized to these areas.2
I chose two items from the Reactions to Race module as the dependent
variables in the first set of statistical models which address the emotional and
physical stress symptoms produced by racism which could impact health.3 It
is important to note here that I only use two items to represent stress from
perceived racism. As the issue of perceived racism is complex and
6
KATHRYN FREEMAN ANDERSON
multi-faceted, previous research indicates that multi-item measures are more
reliable for understanding experiences with racism (Krieger et al. 2005). However, a series of questions of this sort in a large health data set is rare. Therefore, although the two items are limited in this manner, they are useful given
that they are present in such a large and comprehensive data set with a variety
of other health measures. The first item reads: ‘‘During the past 30 days, have
you felt emotionally upset, for example angry, sad, or frustrated, as a result of
how you were treated based on your race?’’ This item deals with the mental
or emotional stress of racist experiences. On the basis of the previous literature, which is more focused on mental health, I expect a greater effect from
this item. The second item reads: ‘‘Within the past 30 days, have you experienced any physical symptoms, for example headache, upset stomach, tensing
of your muscles, or a pounding heart, as a result of how you were treated
based on your race?’’ This item addresses the physical stress that one may
experience as a result of racism. The responses for these two items (yes and
no) were recoded into dummy variables (1 = yes, 0 = no). The response
options of ‘‘don’t know ⁄ not sure’’ and ‘‘refused’’ were included in the original
questionnaire, but these cases were dropped for this study. They only
accounted for .55 percent of the cases for physical symptoms and .69 percent
of the cases for emotional symptoms, and therefore their exclusion does not
meaningfully change the model. I subsequently included these two items as
the main independent variables for analysis in the second set of models.
The second set of statistical models uses two count variables as the dependent variables. These items ask the respondent about the number of poor mental
health days and poor physical health days they experienced within the past
30 days.4 These two items are included to examine the association between the
experience of emotional or physical symptoms from racism and one’s overall
health. The response options for these two items range from zero to thirty. Two
additional response categories of ‘‘don’t know ⁄ not sure’’ and ‘‘refused’’ were
included in the questionnaire. These response options constituted 1.89 percent of
the cases for physical health and 1.6 percent of the cases for mental health, and
these cases were dropped from the models as they are essentially missing values.
The substantive independent variable I examine for the first two models is
self-reported race. The questions about race in the BRFSS are based on the
United States Census categories, and a separate question is included for Hispanic
ethnic identity. I used a calculated variable from these items, which combines
the two race and ethnicity questions, and provides a six category item for
race ⁄ ethnicity with the options: non-Hispanic white, non-Hispanic black,
Hispanic, multiracial and other. A sixth category of ‘‘don’t know ⁄ refused’’ was
included in the original survey and accounted for 1.04 percent of respondents,
but was dropped from this study. I created four dummy variables from these
STRESS FROM RACISM AND THE HEALTH EFFECTS
7
categories which include: White, black, Hispanic, and other. The ‘‘other race’’
category includes Asians, Native Americans or Alaskan Natives, Pacific Islanders, multiracial respondents, and those who responded as ‘‘other.’’ As such, this
category will not be useful for analysis as it does not capture the important differences between these groups. These groups each made up too small of a percentage of the total to provide sufficient analysis individually. White was used as
the reference category in the four statistical models.
I also control for other social and demographic factors. While the BRFSS
contains a variety of health indicators, it only includes a limited number of social
and demographic variables. I included most that are available in the data set.
The control variables used in all four models include age, sex, education,
income, marital status, employment status, and healthcare coverage. Age (in
years) and education (in six categories) are treated as continuous variables. Sex
(1 = female, 0 = male), marital status (1 = married, 0 = else), employment
status (1 = employed, 0 = else) and healthcare coverage (1 = insured, 0 = else)
were recoded into dummy variables. Income was made into a group of six
dummy variables. I coded income as such to include a dummy variable for the
‘‘don’t know ⁄ refused’’ category as such a high number of respondents (12%)
had a missing value for this variable. The ‘‘<$15,000 a year’’ category was used
as the reference group. In the first set of statistical models, general health status
and a variable for how often one thinks about race were included. Health status
was included as a control as people of already reduced health status may be more
likely to report physical or emotional symptoms from a negative experience.
How often one thinks about race was included in the model to control for the
potential effect of the respondent being ‘‘overly sensitive’’ to race-related issues,
which has been a criticism of prior work (Sue et al. 2007; Okazaki 2009).
General health status, ranging from excellent to poor, was made into five dummy
variables, with the ‘‘excellent’’ category as the reference group. This variable for
how often one thinks about race provides eight response categories: never, once
a year, once a month, once a week, once a day, once an hour, constantly, and
don’t know ⁄ not sure. I created seven dummy variables from those categories
including one for ‘‘don’t know ⁄ not sure,’’ to keep as many respondents as possible in the sample. The categories for ‘‘once an hour’’ and ‘‘constantly’’ were
combined into one category because of the extremely small number of cases in
the ‘‘once an hour’’ category, and ‘‘once an hour’’ indicates a frequent consideration of race as does ‘‘constantly.’’ The dummy variable for ‘‘never’’ was used
as the reference category.
Results
The descriptive statistics for all variables used in all four models can be
found in Table 1. I also included a second table, Table 2, with a breakdown
8
KATHRYN FREEMAN ANDERSON
Table 1
Descriptive Statistics for Variables Used in Statistical Models
Variable name
Mean
SD
Range
Dependent variables
Emotional stress
from perceived racism
.06
.24
0–1
.03
.18
0–1
Poor mental health
3.56
7.73
0–30
Poor physical health
3.91
8.36
0–30
Physical stress
from perceived racism
Independent variables
Race
White (reference)
Black
Hispanic
Other race
Age
Gender
Education
Marital status
Employment status
Healthcare coverage
Income
<$15,000 (reference)
.77
.15
.04
.04
49.20
.62
4.83
.42 0–1
.35 0–1
.21 0–1
.19 0–1
16.71 18–99
.49 0–1
1.08 1–6
Description
1 = Experienced
emotional symptoms,
0 = Did not experience
emotional symptoms
1 = Experienced
physical symptoms,
0 = Did not experience
physical symptoms
Number of poor mental
health days in the
past 30 days
Number of poor
physical health days
in the past 30 days
.53
.61
.88
.50
.49
.33
0–1
0–1
0–1
1 = White, 0 = else
1 = Black, 0 = else
1 = Hispanic, 0 = else
1 = other race, 0 = else
Respondent age in years
1 = female, 0 = male
1 = no school,
2 = elementary,
3 = some high school,
4 = high school,
5 = some college,
6 = college graduate
1 = married, 0 = else
1 = employed, 0 = else
1 = insured, 0 = else
.10
.31
0–1
1 = <$15,000, 0 = else
STRESS FROM RACISM AND THE HEALTH EFFECTS
9
Table 1
(Continued)
Variable name
Mean
SD Range
$15,000 to $25,000
.15
.35
0–1
$25,000 to $35,000
.12
.33
0–1
$35,000 to $50,000
.16
.36
0–1
$50,000 or more
.35
.48
0–1
Don’t know ⁄ refused
.12
.33
0–1
.41
.47
.45
.32
.22
0–1
0–1
0–1
0–1
0–1
1
1
1
1
1
.50
.33
.30
.25
.22
.23
0–1
0–1
0–1
0–1
0–1
0–1
1
1
1
1
1
1
.18
0–1
General health status
Excellent (reference) .21
Very good
.33
Good
.29
Fair
.11
Poor
.05
How often think about race
Never (reference)
.56
Once a year
.13
Once a month
.10
Once a week
.07
Once a day
.05
Hourly ⁄ constantly
.05
Don’t know ⁄ not sure
.03
Description
1 = $15,000 to $25,000,
0 = else
1 = $25,000 to $35,000,
0 = else
1 = $35,000 to $50,000,
0 = else
1 = $50,000 or more,
0 = else
1 = don’t know ⁄ refused,
0 = else
=
=
=
=
=
excellent, 0 = else
very good, 0 = else
good, 0 = else
fair, 0 = else
poor, 0 = else
= never, 0 = else
= once a year, 0 = else
= once a month, 0 = else
= once a week, 0 = else
= once a day, 0 = else
= once an hour ⁄ constantly,
0 = else
1 = don’t know ⁄ not sure,
0 = else
Note: N = 32,585. Data come from the 2004 Behavioral Risk Factor
Surveillance System.
of the means for each dependent variable by race. Before examining the
regression results, some of the means by race provide some important comparisons. Compared to whites, all racial and ethnic minorities experience greater
incidence of both emotional and physical stress from perceived racism. Blacks
have the highest rates, with 18.2% experiencing emotional stress symptoms
10
KATHRYN FREEMAN ANDERSON
Table 2
Means for Dependent Variables by Race
Variable name
White
Black
Hispanic
Other race
Dependent variables
Emotional stress
Physical stress
Poor mental health
Poor physical health
.035
.016
3.375
3.798
.182*
.098*
4.079*
4.296*
.135*
.083*
3.992
3.931*
.124*
.070*
4.760*
4.690*
Note: N = 32,585. Data come from the 2004 Behavioral Risk Factor
Surveillance System.
*Indicates that the mean is significantly greater than the mean for white
respondents.
and 9.8% experiencing physical stress symptoms (compared to 3.5% and 1.6%
respectively for whites). Also, racial and ethnic minorities experience significantly more days of poor mental and physical health (except Hispanics for
physical health). Blacks and those in the ‘‘other race’’ category have a notably
high number of poor health days compared to whites.
To examine the relationship between stress from racism and its impacts
on health, I estimated four models using these variables. For the first two
models using the items on emotional or physical stress symptoms from treatment on the basis of race, I estimated two binary logit models. Those results,
including the coefficients and odds ratios, can be found in Table 3. The discrete change coefficients for those two models can be found in Table 4. For
the second two models, using the variables for number of days of poor physical and poor mental health, I estimated two negative binomial regression models. Those results, including the regression coefficients and factor change
coefficients, for both the number of poor mental health days and poor physical
health days can be found in Table 5. The discrete change coefficients of the
expected counts for those two models can be found in Table 6. For interpretation of the results, I focus on the discrete change coefficients found in Tables 4
and 6. I focus on these results as discrete change coefficients, compared to
other methods, provide a better indication of the relative impact of the
variables as the effects of the variables are all in the same metric. Also, with
such a large sample size (N = 32,585), the substantive impact of each variable
should be emphasized over significance.
STRESS FROM RACISM AND THE HEALTH EFFECTS
11
Table 3
Coefficients (Standard Errors) and Odds Ratios from Binary Logit Models
of Emotional and Physical Stress Symptoms from Perceived Racism
Variable Name
Model 1
Model 2
Emotional stress
from racism
Physical stress
from racism
b
Race
White (reference)
Black
1.144***
Hispanic
.579***
Other race
.715***
Age
).024***
Gender
.091
Education
.045
Marital status
).057
Employment status
.029
Healthcare coverage
).169**
Income
<$15,000 (reference)
$15,000 to $25,000 ).165*
$25,000 to $35,000 ).286**
$35,000 to $50,000 ).260**
$50,000 or more
).337***
Don’t know ⁄ refused ).405***
General health status
Excellent (reference)
Very good
.149*
Good
.397***
Fair
.771***
Poor
1.333***
How often think about race
Never (reference)
Once a year
.237*
SE
(.059)
(.095)
(.101)
(.002)
(.051)
(.026)
(.053)
(.058)
(.065)
OR
b
SE
OR
3.140 1.142*** (.080) 3.134
1.785
.757*** (.122) 2.131
2.044
.877*** (.131) 2.403
.668a ).019*** (.002) .729a
1.096
.199** (.070) 1.219
1.050a
.020
(.034) 1.022a
.945 ).052
(.072) .949
1.029
.091
(.078) 1.095
.855 ).205*
(.083) .815
(.083)
(.096)
(.097)
(.096)
(.101)
.848
.751
.771
.714
.667
).322**
).389**
).539***
).613***
).562***
(.100)
(.121)
(.128)
(.126)
(.127)
.725
.678
.583
.542
.570
(.075)
(.075)
(.091)
(.114)
1.160
1.488
2.162
3.793
.241*
.556***
1.175***
1.876***
(.114)
(.112)
(.124)
(.144)
1.273
1.744
3.237
6.525
(.096) 1.268
.245
(.129) 1.277
12
KATHRYN FREEMAN ANDERSON
Table 3
(Continued)
Variable Name
b
Model 1
Model 2
Emotional stress
from racism
Physical stress
from racism
SE
Once a month
.898*** (.083)
Once a Week
1.449*** (.081)
Once a Day
1.835*** (.078)
Once an hour ⁄
1.649*** (.078)
constantly
Don’t know ⁄
.467** (.150)
not sure
Constant
)2.867*** (.176)
Pseudo R2b
.174
Deviance ()2LL)
12818.230
OR
2.455
4.259
6.267
5.203
1.595
b
.675***
1.185***
1.542***
1.535***
.284
SE
OR
(.119)
(.114)
(.106)
(.099)
1.965
3.269
4.674
4.643
(.208)
1.328
)3.748*** (.237)
.168
7903.051
Notes: N = 32,585. Data come from the 2004 Behavioral Risk Factor
Surveillance System.
b = Logit coefficient. SE = Standard error. OR = Odds ratio (factor change).
a
The odds ratios for these continuous variables reflect an x-standardized factor
change.
b
The pseudo R2 represents the calculation for McFadden’s R2.
*p < .05, ** p < .01, *** p < .001 (two-tailed).
Examining the results from the first two binary logit models, we can see
that race is related to experiencing emotional and physical stress from racist
encounters. First, looking at emotional stress from racism, on which the current literature places more focus, all three race categories when compared to
whites have substantial results even when controlling for socioeconomic status,
general health status, and mental preoccupation with race. Furthermore, of
these three groups, blacks were most likely to experience mental or emotional
symptoms from experiences of perceived racism when compared to whites.
The predicted probability of experiencing emotional symptoms from racist
STRESS FROM RACISM AND THE HEALTH EFFECTS
13
Table 4
Discrete Change Coefficients from Binary Logit Models of Emotional
and Physical Stress Symptoms from Perceived Racism
Variable name
Race
White (reference)
Black
Hispanic
Other race
Age
Gender
Education
Marital status
Employment status
Healthcare coverage
Income
<$15,000 (reference)
$15,000 to $25,000
$25,000 to $35,000
$35,000 to $50,000
$50,000 or More
Don’t know ⁄ refused
General health status
Excellent (reference)
Very good
Good
Fair
Poor
How often think about race
Never (reference)
Once a year
Once a month
Once a week
Once a day
Emotional stress
Physical stress
.060
.023
.030
).015
.003
.002
).002
.001
).006
.029
.016
.019
).006
.003
).000
).001
.002
).004
).007
).012
).011
).014
).016
).008
).009
).011
).013
).012
.004
.013
.030
.070
.003
.008
.024
.058
.007
.035
.074
.114
.003
.012
.027
.044
14
KATHRYN FREEMAN ANDERSON
Table 4
(Continued)
Variable name
Once an hour ⁄ constantly
Don’t know ⁄ not sure
Emotional stress
.093
.014
Physical stress
.043
.004
Note: N = 32,585. Data come from the 2004 Behavioral Risk Factor
Surveillance System.
For the dummy variables (race, gender, marital status, employment status,
healthcare coverage, income, general health status, and how often think about
race), the discrete change coefficients reflect the change in the predicted
probability associated with a change from 0 to 1 in the variable. For the
continuous variables (age and education), the discrete change coefficients
reflect a change in the predicted probability associated with a standard
deviation increase, centered around its mean, in the variable. For each discrete
change coefficient, the remaining variables are held at their means.
treatment for blacks is .06 greater than the probability for whites.5 This figure
is .023 for Hispanics and .03 for the ‘‘other race’’ category, which are still
substantively important results, but are not quite as high as the coefficient for
blacks. The predicted probability for the ‘‘other race’’ category was greater
than the figure for Hispanics, but unfortunately, as previously mentioned, these
results are difficult to interpret as the category is made up of such a mixture
of groups.
Additionally, one’s physical health status was also associated with experiencing emotional stress symptoms because of racist experiences for all racial
categories. Those respondents with poorer health, compared to those with
excellent health, are more often estimated to experience emotional stress from
racism. The odds of experiencing emotional stress from racism increases as
the dummy categories for health status move from ‘‘very good’’ to ‘‘poor.’’
Being of poor health, compared to of excellent health, increases the predicted
probability of experiencing emotional stress as a result of racist treatment by
.07. This figure is even greater than the discrete change coefficient for blacks
(.06), showing that being of poor health is associated with having an
emotional reaction from racist experiences.
The largest coefficients in the model were for the set of variables for how
often one thinks about race. All six categories when compared to those who
Emotional stress
Physical stress
Race
White (reference)
Black
Hispanic
Other race
Age
Gender
Education
Marital status
Employment status
Healthcare coverage
Variable name
(.073)
(.098)
(.045)
(.074)
(.081)
(.001)
(.030)
(.016)
(.032)
(.037)
(.048)
).271***
).264***
.036
).018***
.370***
).116***
).272***
.278***
).142**
SE
.763
.768
1.037
.738a
1.449
.883a
.762
.757
.868
1.544
1.722
FC
).193***
).123
.101
.010***
.133***
).149***
).066*
).648***
).016
.264***
.435***
b
(.044)
(.072)
(.078)
(.001)
(.030)
(.015)
(.032)
(.035)
(.046)
(.071)
(.096)
SE
Physical health days
Mental health days
.434***
.543***
b
Model 2
Model 1
FC
.825
.885
1.107
1.179a
1.143
.851a
.936
.523
.985
1.303
1.545
Table 5
Coefficients (Standard Errors) and Factor Change Coefficients from Negative Binomial Regression Models
of Number of Poor Mental and Physical Health Days
STRESS FROM RACISM AND THE HEALTH EFFECTS
15
).244***
).429***
).522***
).655***
).593***
3.251***
b
(.061)
(.066)
(.065)
(.063)
(.065)
(.108)
6.912***
.011
11536.750
SE
FC
b
.784
.651
.593
.519
.552
).240***
).480***
).530***
).742***
).536***
2.244***
(.054)
(.063)
(.063)
(.061)
(.063)
(.107)
6.516***
.016
118656.648
SE
Physical health days
Mental health days
Note: N = 32,585. Data come from the 2004 Behavioral Risk Factor Surveillance System. b = Negative binomial
regression coefficient. SE = Standard error. FC = Factor change coefficient.
a
The factor change coefficients for these continuous variables reflect an x-standardized factor change.
b
The pseudo R2 represents the calculation for McFadden’s R2.
*p < .05, **p < .01, ***p < .001 (two-tailed).
Income
<$15,000 (reference)
$15,000 to $25,000
$25,000 to $35,000
$35,000 to $50,000
$50,000 or more
Don’t know ⁄ refused
Constant
Alpha
Pseudo R2b
Deviance ()2LL)
Variable name
Model 2
Model 1
Table 5
(Continued)
.786
.619
.588
.476
.585
FC
16
KATHRYN FREEMAN ANDERSON
STRESS FROM RACISM AND THE HEALTH EFFECTS
17
Table 6
Discrete Change Coefficients for the Expected Count from
Negative Binomial Regression Models of Number of Poor Mental
and Physical Health Days
Variable name
Emotional stress
Physical stress
Race
White (reference)
Black
Hispanic
Other race
Age
Gender
Education
Marital status
Employment status
Healthcare coverage
Income
<$15,000 (reference)
$15,000 to $25,000
$25,000 to $35,000
$35,000 to $50,000
$50,000 or more
Don’t know ⁄ refused
Mental health days
Physical health days
1.614
2.163
.938
1.693
).761
).746
).119
)1.931
1.090
).380
).839
).877
).457
).570
).375
).346
.519
.414
).508
).209
)2.226
).049
)1.056
)1.703
)1.985
)2.346
)2.185
)1.111
)1.982
)2.141
)2.725
)2.159
Note: N = 32,585. Data come from the 2004 Behavioral Risk Factor
Surveillance System.
For the dummy variables (race, gender, marital status, employment status,
healthcare coverage, income, and general health status), the discrete change
coefficients reflect the change in the expected count associated with a change
from 0 to 1 in the variable. For the continuous variables (age and education), the
discrete change coefficients reflect a change in the expected count associated
with a standard deviation increase, centered around its mean, in the variable. For
each discrete change coefficient, the remaining variables are held at their means.
18
KATHRYN FREEMAN ANDERSON
never think about race had highly significant results. The most notable of these
results was the variables for ‘‘once a day’’ and ‘‘once an hour ⁄ constantly,’’
which all indicate extremely frequent consideration of race. These two variables had the strongest discrete change coefficients out of all of the variables
in the model, even when accounting for race and socioeconomic status. These
show that thinking about race is highly associated with experiencing an emotional reaction to racism, regardless of the race of the respondent. Although
this group of variables produced a large effect in the model, the effects of race
are still substantial, indicating that the effect of race is not explained away by
racial consciousness, which is a critique of previous work (Sue et al. 2007).
When considering physical stress symptoms because of perceived racism,
the results are quite similar with a few notable exceptions. When examining
the discrete change coefficients, most of the values are slightly lower than they
were for the first model of emotional stress. This is possibly an indication that
in general, people are more likely to experience an emotional reaction to racism than a physical one, but these different results may just indicate that using
this set of variables, we are less able to predict the outcome for physical
stress. This result is expected from the previous literature, which places a
much stronger emphasis on emotional and mental effects than on physical
ones, or if it deals with physical symptoms, does so through the pathway of
mental health. Notably, all three variables for race, when compared to whites,
are significant predictors for experiencing physical stress symptoms from a
racist experience, with blacks being more likely than the other racial groups to
experience physical symptoms.
These two variables for emotional and physical stress were then included
in the two negative binomial regression models as the main substantive independent variables for analysis to examine whether experiencing these stress
symptoms is related to overall poorer health. The two negative binomial
regression models use variables for the number of poor physical and poor
mental health days as the dependent variables. While I reported the coefficients and factor change coefficients from both models in Table 5, I will focus
on the discrete change coefficients from Table 6 for interpretation. For interpretation purposes, the discrete change coefficients in these two models reflect
a change in the expected count of poor mental and physical health days.
Before analyzing the two substantive independent variables in the model,
a few of the control variables were notable. First, in both the model of number
of poor physical health days and the model of poor mental health days, the
variables for race alone did not produce substantial results. When controlling
for all the other factors in the model, the race dummy variables for blacks and
Hispanics were actually negatively related to having a higher number of poor
mental and poor physical health days compared to whites, with blacks being
STRESS FROM RACISM AND THE HEALTH EFFECTS
19
the least likely of the three groups to have a higher count. I also ran a set of
models (not shown here) using these outcomes with only the dummy variables
for race included to examine the gross effects of race on the outcome. All of
the race dummy variables (except for Hispanics for poor physical health days),
as compared to whites, were all significant and positively associated with a
higher count of both poor mental and physical health days. The gross effects
of race demonstrate racial health disparities, but this effect is removed when
controlling for all of these factors, including the stress symptom variables.
The stress symptom variables are highly associated with being a racial minority, as compared to whites (as shown in the first set of models). Thus, when
these variables are included in a model with the race variables, the effect of
being a racial minority is removed and whites actually have a higher predicted
count of poor mental and physical health days. Even with all of the variables
in the model, although they are significant because of the large N, they are not
substantively strong effects.6
When examining the main substantive variables for emotional and physical stress from the experience of perceived racism on overall mental health, it
is evident from the discrete change coefficients that they are associated. First
of all, experiencing both emotional and physical stress from the experience of
racism is significant and positively related to having more days of poor mental
health. For those who experienced emotional stress from perceived racism, the
expected number of poor mental health days is predicted to increase by 1.614,
or over 1 day and a half. For those who experienced physical symptoms from
perceived racism, the expected number of poor mental health days is predicted
to increase by 2.163, or a little over 2 days. While these numbers may appear
insignificant in the scope of thirty possible days of poor mental health, they
are among the highest positive values in the overall model. The only other
more substantially strong effects are for the set of dummy variables for
income. The effects of gender, education, marital status, employment status,
and even healthcare coverage are all substantively much weaker predictors
than the two stress variables.
The model for the number of days of poor physical health also produced
noteworthy results. The results for the two variables for physical and emotional reactions to racism are both significant and positively associated with
having a higher number of poor physical health days. For those who experienced emotional stress symptoms from perceived racism, the expected number
of days of poor physical health is predicted to increase by .938, or almost one
full day. For those who experienced physical stress from perceived racism, the
expected number of days of poor physical health is predicted to increase by
1.693, or a little more than one day and a half. Substantively, these effects
were not quite as strong as in the mental health model, as were all of the
20
KATHRYN FREEMAN ANDERSON
EmoƟonal Stress
No EmoƟonal Stress
Number of Days of Poor Health
6
5
4
3
2
1
0
White
Black
Hispanic
Mental Health
Other
Race
White
Black
Hispanic
Physical Health
Other
Race
Race
Physical Stress
No Physical Stress
Number
mber of Days of Poor Health
6
5
4
3
2
1
0
White
Black
Hispanic
Mental Health
Other
Race
White
Black
Hispanic
Physical Health
Other
Race
Race
Figure 1 Expected Count of Number of Poor Physical and Poor Mental
Health Days by Race and the Experience of Emotional and Physical Stress
from Perceived Racism.
Note: N = 32,585. Data come from the 2004 Behavioral Risk Factor Surveillance System. For each expected count, all of the remaining variables are held
at their means.
remaining variables (except the set of variables for income and employment
status). However, they were among the largest coefficients in the model.
To further develop this relationship, I calculated the expected count for
the number of poor physical and mental health days by race and the experience of emotional and physical stress from racist treatment. These results are
in Figure 1. The bars in Figure 1 demonstrate the difference in the expected
count between those who had and had not experienced stress symptoms
from perceived racist treatment. For all racial groups, I found a statistically
significant difference in the number of poor physical and poor mental health
STRESS FROM RACISM AND THE HEALTH EFFECTS
21
days between those who had and had not experienced stress from racism. For
those who experienced emotional stress from racism, the expected count of
poor mental health days increases by over a day for all racial groups, and
increases by over a day and a half for whites (1.697) and the ‘‘other race’’ category (1.76). For those who experienced physical stress from racism, this
count increases by over 1 day and a half for blacks (1.735), Hispanics (1.745),
and by over 2 days for whites (2.274) and for the ‘‘other race’’ category
(2.358). For those who experienced emotional stress from racist treatment, the
expected count of poor physical health days is predicted to increase by almost
1 day for blacks (.797), Hispanics (.856), and whites (.966), and by over 1 day
for the ‘‘other race’’ category (1.07). For those who experienced physical
stress from racism, this count increases by over a day and a half for all racial
groups, with the ‘‘other race’’ category having a count close to two full days
(1.93).
Whites who experienced stress symptoms have some of the highest
expected counts of both poor mental and physical health days, next to those in
the ‘‘other race’’ category. This seemingly odd result merely stems from the
fact that the effects of race and stress are additive, and the dummy variables
for blacks and Hispanics were significant and negative compared to whites
when including the symptom variables in the model (as discussed above).7 As
an additive effect, the effects of the stress symptom variables are uniform
across all racial groups, including whites. Furthermore, whites who reported
such symptoms make up such a small portion of the white sample (3.5%
for emotional stress and 1.6% for physical stress). These figures are much
higher for all other racial and ethnic categories. Therefore, the expected counts
for white respondents only reflect an extremely small portion of the sample,
and their expected counts also may not be particularly meaningful for that
reason.
Overall, the results in Figure 1 represent that having experienced such
stress leads to an increase in poor physical and mental health days for all
racial groups. This association is greater for mental health than for physical
health, especially for those who experienced physical stress from perceived
racism. The expected count for physical health was still substantial, with an
expected count of about 1 day greater for all cases for those who experienced
both physical and emotional stress from racist treatment. The results reveal a
statistically significant difference between those who had and had not experienced symptoms for all racial groups, for both emotional and physical stress
from racism and for both physical and mental health outcomes. Therefore,
having experienced symptoms from perceived racist treatment is related to
overall poorer mental and physical health.
22
KATHRYN FREEMAN ANDERSON
Discussion
Limitations of the Data
An obvious limitation of the study is that it is based on self-report of
both the experience of emotional and physical stress symptoms from racist
treatment and the number of poor mental and physical health days. The reports
are based on the perceptions of the respondent and may therefore be subject
to under or over-reporting of the incidence of these factors. Furthermore, selfreport makes it more difficult to conduct between-group analysis, as there may
be racial and ethnic differences in the way stress symptoms and health are
reported (Layes, Asada, and Kephart 2012). Several previous studies on the
health effects of racism use some measure of self-report or perceived experience
of racism (Paradies 2006; Vines et al. 2007; Brondolo et al. 2009; Fujishiro
2009; Gee and Walsemann 2009). However, some studies have used more
concrete measures of its effect on health outcomes (Kwate et al. 2003; Peters
2006; Vines et al. 2007). Krieger et al. (2005) found no problem with the use
of self-report in their work on the ‘‘Experiences of Discrimination’’ scale, but
did recommend that a multi-item measure would be more reliable. Selfreported health is also common in the work on racism and its health impacts
(Paradies 2006; Williams and Mohammed 2009). Using a secondary data
source makes it difficult to address these limitations. For example, it was not
possible using this data to use a multi-item scale for a measure of the stress
resulting from racism. Also, there are no general health questions in the
BRFSS data set which are not based on self-report. Whether or not the experience of symptoms or negative health effects is based on an absolute, concrete
measure, I argue, may be irrelevant, as the effects produced depend on the
individual’s experience. If the individual subjectively feels as though they
have experienced these outcomes, then that is where the effect is produced.
The other main limitation of the study is that the survey items only refer
to stress symptoms from racism experienced within the past 30 days, and the
number of poor mental and physical health days within the past 30 days.
Other studies indicate that time is an important component in the health
effects of racism and stress (Gee and Walsemann 2009; Geronimus et al.
2006; Kwate et al. 2003). They suggest a time lag in the effects of racism,
which may be compounded and become worse over time (Gee and Walsemann 2009). They also suggest that the effects of racist experiences over a
lifetime can lead to poor health outcomes (Kwate et al. 2003). Geronimus’
weathering hypothesis, for example, emphasizes the compounding of multiple
social factors and adverse circumstances for racial minorities in the United
States which may lead to substantial differences in health, particularly as it
STRESS FROM RACISM AND THE HEALTH EFFECTS
23
relates to aging (Geronimus et al. 2006). Findings from this study only address
experiences with racist treatment within the last thirty days using only a crosssectional study, which captures the respondent’s experience in a snapshot in
time. These results provide no indication of the frequency of stressful racist
events in the respondent’s life, how often they experience physical or emotional symptoms from the racist experience, for example, if this is a regular
occurrence or an isolated event, or if these experiences indicate some longterm impact on health. The results from the second two models indicate that
experiencing stress leads to having more days of poor mental and poor physical health within the parameter of the last thirty days, but does not indicate
whether frequent emotional or physical stress with these indicated symptoms
may lead to poor future health consequences. All of these considerations are
important for future research.
Conclusions
From the results from the first two models, it is evident that the association of race with the experience of physical or emotional stress from racism
is substantial. Additionally, African Americans are more likely than any other
racial group to experience such symptoms. I contend that this is the case
because the history of the racial discrimination of blacks in the United States
has been severe, and whose effects are only slightly mitigated in the postCivil Rights era (Byrd and Clayton 2001). Also, given the use of survey data,
it is difficult to tell whether or not blacks are more likely to experience such
stress because they are more likely to have racist experiences or because they
are more likely to be responsive to such experiences. But, it is clear, examining both Table 2 and the regression results, that blacks are more likely to
experience this effect. These results were still substantial even after controlling for socioeconomic status, health status, and how often one thinks about
race.
Socioeconomic status is still often suggested as a reason for the continued
racial differences in the United States, and in particular, health differences
(Dressler, Oths, and Gravlee 2005; Hummer 1996; Williams 1999). From the
results, education and employment status were not even significant factors in
experiencing symptoms. Income was a factor, with higher income leading to a
decreased probability of experiencing emotional or physical symptoms from
racism, but these effects were not as substantial as those from race, health
status, or how often one thinks about race. Studies also suggest that strong
reactions to racism are merely because of the individual’s sensitivity to racial
issues, rather than the actual experience of racism or its harmful effects (Sue
et al. 2007). The variable for how often one thinks about race was included to
capture the potential sensitivity on the part of the respondent that if one is
24
KATHRYN FREEMAN ANDERSON
mentally preoccupied with race, they are more likely to experience or even
notice any effect of a racist experience. These results were substantial in the
model, but if the effect was only produced by sensitivity, the other factors in
the model would be inconclusive. As such, the effects of race were still strong
for all racial categories in both models when compared to whites, and
especially for blacks.
Additionally, when the two stress variables were used in models on overall mental and physical health, the results were noteworthy. For both models,
having experienced physical or emotional stress were both substantial predictors for an increase in the number of poor mental health days and the number
of poor physical health days. This effect was somewhat stronger in the model
of number of poor mental health days. The expected count by racial group
also revealed that for all racial groups having experienced physical and emotional stress from racism leads to an increase in the count of both poor physical and poor mental health days. Therefore, having experienced emotional or
physical symptoms from a perceived racist experiences is related to an
increased number of poor mental or physical health days.
As an empirical test of social stress theory, these results affirm both of the
pathways outlined in the conceptual model discussed earlier, which has been a
point of criticism of previous studies on the subject (Schwartz and Meyer 2010).
The results from the first two models demonstrate that being a racial minority is
a substantial predictor for experiencing both emotional and physical stress symptoms from discriminatory experiences. Additionally, from the second set of models, the results demonstrate that having experienced stress symptoms was a
substantial predictor for all racial groups for having more days of poor mental
and physical health. These results provide empirical evidence for the second
pathway that social stress is related to health problems. Overall, from these
results, I conclude that there is a relationship between racism and poorer health,
both mental and physical. These findings demonstrate that experiencing both
emotional and physical stress symptoms from perceived racist treatment are
related to overall poorer mental and physical health.
ENDNOTES
*The author would like to thank Andrew Fullerton for helpful comments on earlier drafts of
this paper. Please direct all correspondence to Kathryn Freeman Anderson, Department of Sociology,
University of Arizona, Department of Sociology, P. O. Box 210027, Tucson, AZ 85721 (email:
[email protected]).
1
The results section of this article does not develop first pathway using a between-group
analysis to demonstrate that racial minorities have a higher incidence of health disorders. The
literature on the subject is highly developed; therefore, I felt it unnecessary to devote much of this
STRESS FROM RACISM AND THE HEALTH EFFECTS
25
article to this relationship. However, Schwartz and Meyer in the article question whether or not
such a pathway exists (2010). Although the full results are not provided here, I ran regression
analyses using the race variables and a variety of both mental and physical health outcomes. Those
results indicate that racial minorities when compared to whites (except for Hispanics for physical
health) are substantially more likely to experience both poorer mental and physical health
outcomes.
2
Each of the states in the BRFSS sample is distinct. They each have their own unique history of race relations, government and structural arrangements. Each of these features could affect
experiences of racism and any resulting symptoms. However, the focus of the study is on individual-level experiences and risk factors. The data cannot account for state-level or institutional forces
which may influence these outcomes.
3
The experience of stress may entail a variety of factors, including both life event and
chronic stressors. Although the data set includes a variety of demographic and health indicators, it
was not possible to control for all possible sources of stress. I included as many as possible that
were available in the data, such as employment status, income, health status, mental preoccupation
with race, etc. To examine the effect of stress from racism, I focus on the two items in the Reactions to Race module.
4
These two items are specifically worded as: ‘‘Now thinking about your mental health, which
includes stress, depression, and problems with emotions, for how many days during the past
30 days was your mental health not good?’’ for mental health, and ‘‘Now thinking about your
physical health, which includes physical illness and injury, for how many days during the past
30 days was your physical health not good?’’ for physical health.
5
For all interpretations of discrete change coefficients, the remaining variables are held at
their means.
6
I also ran the negative binomial regression models for poor mental and physical health days
with the race dummy variables and with and without the stress symptoms variables to demonstrate
that stress from perceived racism is an explanatory factor for racial health disparities. Because of
space constraints, I do not include the full results for these models. When only the group of race
dummy variables is included in the models, the results show that being a racial and ethnic minority, as compared to white, is associated with a higher count of poor mental and physical health
days (except Hispanics for poor physical health days). For all racial and ethnic groups, compared
to whites, the inclusion of the emotional and physical stress variables substantially reduced the
size of the race coefficients for the number of days of poor mental and physical health. With the
exception of the other race category for mental health days, the race dummy variables were no
longer significant with the inclusion of the stress variables. Thus, the inclusion of the stress symptom variables explains away the gross effects of being a racial minority on poor health days.
Furthermore, when the other social and demographic variables are included in the full model, the
coefficients for black and Hispanic actually become significant and negative compared to the white
reference group.
7
Stress because of racism increases the expected number of days of poor physical ⁄ mental
health for every racial and ethnic group (including whites) because there are no interaction terms
in the model. Without interaction terms, the effects of race and stress are additive. In other words,
the effect of stress will be the same for every racial group, and racial differences will be the same
for respondents with and without stress. To allow for different effects of stress by racial or ethnic
group, I would need to include interaction terms in the model between the race variables and the
stress variables. I estimated these models and found that none of the interaction terms were significant. Therefore, I present models without interaction terms in the study. Although the model
assumes that stress from racism leads to poorer health for whites, this is not a very important
finding because very few whites experience emotional or physical stress from racism (3.5% and
26
KATHRYN FREEMAN ANDERSON
1.6%, respectively). The effects are much more meaningful for blacks and Hispanics because they
are much more likely than whites to experience emotional or physical stress from racism (14–18%
and 8–10%, respectively). Also, as shown above, the net effects of race on poor health days are
mitigated by the inclusion of the stress symptom variables which are highly associated with being
a racial and ethnic minority as demonstrated in the first set of models predicting the experience of
stress symptoms caused by perceived racism.
REFERENCES
Aneshensel, Carol S. 1992. ‘‘Social Stress: Theory and Research.’’ Annual Review of Sociology
18:15–38.
Brondolo, Elizabeth, Linda C. Gallo, and Hector F. Myers. 2009. ‘‘Race, Racism, and Health:
Disparities, Mechanisms, and Interventions.’’ Journal of Behavioral Medicine 32:1–8.
Brondolo, Elizabeth, Nisha Brady ver Halen, Melissa Pencille, Danielle Beatty, and Richard J.
Contrada. 2009. ‘‘Coping with Racism: A Selective Review of the Literature and a
Theoretical and Methodological Critique.’’ Journal of Behavioral Medicine 32:64–88.
Byrd, W. Michael, and Linda A. Clayton. 2001. ‘‘Race, Medicine and Health Care in the United
States: A Historical Survey.’’ Journal of the National Medical Association 93(3):11S–34S.
Centers for Disease Control, Prevention (CDC). 2004. Behavioral Risk Factor Surveillance System
Survey Data, Atlanta, Georgia: U.S. Department of Health and Human Services, Centers for
Disease Control and Prevention.
Cozier, Yvette C., Lauren A. Wise, Julie R. Palmer, and Lynn Rosenberg. 2009. ‘‘Perceived
Racism in Relation to Weight Change in the Black Women’s Health Study.’’ Annals of
Epidemiology 19(6):379–87.
Dressler, William W., Kathryn S. Oths, and Clarence C. Gravlee. 2005. ‘‘Race and Ethnicity in
Public Health Research: Models to Explain Health Disparities.’’ Annual Review of
Anthropology 34:231–52.
Fujishiro, Kaori. 2009. ‘‘Is Perceived Racial Privilege Associated with Health? Findings from the
Behavioral Risk Factor Surveillance System.’’ Social Science and Medicine 68:840–4.
Gee, Gilbert, and Katrina Walsemann. 2009. ‘‘Does Health Predict the Reporting of Racial
Discrimination or Do Reports of Discrimination Predict Health? Findings from the National
Longitudinal Study of Youth.’’ Social Science and Medicine 68:1676–84.
Geronimus, Arline T., Margaret Hicken, Dayna Keene, and John Bound. 2006. ‘‘‘Weathering’ and
Age Patterns of Allostatic Load Scores Among Blacks and Whites in the United States.’’
American Journal of Public Health 96(5):826–33.
Hummer, Robert A. 1996. ‘‘Black-Whites Differences in Health and Mortality: A Review and
Conceptual Model.’’ The Sociological Quarterly 37(1):105–25.
Krieger, Nancy, Kevin Smith, Deepa Naishadham, Cathy Hartman, and Elizabeth M. Barbeau. 2005.
‘‘Experiences of Discrimination: Validity and Reliability of a Self-report Measure for
Population Health Research on Racism and Health.’’ Social Science and Medicine 61:1576–96.
Kwate, Naa Oyo A, Heiddis B. Valdimarsdottir, Josephine S. Guevarra, and Dana H. Bovbjerg.
2003. ‘‘Experiences of Racist Events are Associated with Negative Health Consequences for
African American Women.’’ Journal of the National Medical Association 95(6):450–60.
Layes, Audrey, Yukiko Asada, and George Kephart. 2012. ‘‘Whiners and Deniers—What Does
Self-Rated Health Measure?’’ Social Science and Medicine 75:1–9.
Okazaki, Sumie. 2009. ‘‘Impact of Racism on Ethnic Minority Mental Health.’’ Perspectives on
Psychological Science 4(1):103–7.
STRESS FROM RACISM AND THE HEALTH EFFECTS
27
Paradies, Yin. 2006. ‘‘A Systematic Review of Empirical Research on Self-Reported Racism and
Health.’’ International Journal of Epidemiology 35:888–901.
Pearlin, Leonard I. 1989. ‘‘The Sociological Study of Stress.’’ Journal of Health and Social
Behavior 30(3):241–56.
Peters, Rosalind M. 2006. ‘‘The Relationship of Racism, Chronic Stress Emotions, and Blood
Pressure.’’ Journal of Nursing Scholarship 38(3):234–40.
Schwartz, Sharon, and Ilan H. Meyer. 2010. ‘‘Mental Health Disparities Research: The Impact of
Within and Between Group Analyses on Tests of Social Stress Hypotheses.’’ Social Science
and Medicine 70:1111–8.
Shavers, Vickie L., and Brenda S. Shavers. 2006. ‘‘Racism and Health Inequity among
Americans.’’ Journal of the National Medical Association 98(3):386–96.
Sue, Derald Wing, Christina M. Capodilupo, Gina C. Torino, Jennifer M. Bucceri, Aisha M. B.
Holder, Kevin L. Nadal, and Marta Esquilin. 2007. ‘‘Racial Microagressions in Everyday
Life: Implications for Clinical Practice.’’ American Psychologist 62(4):271–86.
Vines, Anissa I., Donna Day Baird, June Stevens, Irva Hertz-Picciotto, Kathleen C. Light, and
Maya McNeilly. 2007. ‘‘Associations of Adominal Fat with Perceived Racism and Passive
Emotional Responses to Racism in African American Women.’’ American Journal of Public
Health 97(3):526–30.
Williams, David R. 1999. ‘‘Race, Socioeconomic Status, and Health: The Added Effects of
Racism and Discrimination.’’ Annals New York Academy of Sciences 896:173–88.
Williams, David R., and Pamela Braboy Jackson. 2005. ‘‘Social Sources of Racial Disparities in
Health.’’ Health Affairs 24(2):325–34.
Williams, David R., and Selina A. Mohammed. 2009. ‘‘Discrimination and Racial Disparities in
Health: Evidence and Needed Research.’’ Journal of Behavioral Medicine 32:20–47.
Williams, David R., and Ruth Williams-Morris. 2000. ‘‘Racism and Mental Health: The African
American Experience.’’ Ethnicity and Health 5(3 ⁄ 4):243–68.