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NeuroRehabilitation 24 (2009) 5–14 5
DOI 10.3233/NRE-2009-0449
IOS Press
Race/ethnicity differences in satisfaction with
life among persons with traumatic brain injury
Juan Carlos Arango-Lasprillaa,∗, Jessica M. Ketchumb, Kelli Garya, Tessa Hartc, John Corrigand,
Lauren Forsteraand Guido Mascialinoe
aDepartment of Physical Medicine and Rehabilitation, Virginia Commonwealth University, Richmond, VA, USA
bDepartment of Biostatistics, Virginia Commonwealth University. Richmond, VA, USA
cMoss Rehabilitation Research Institute, Elkins Park, PA, USA
dDepartment of Physical Medicine and Rehabilitation, The Ohio State University, Columbus, OH, USA
eMount Sinai Schoolof Medicine, Department of RehabilitationMedicine, New York, NY, USA
Abstract.Objective: To determine differences in life satisfaction at 1-year post-TBI among Caucasian, African American,
Hispanic, and Asian individuals with TBI, after adjusting for covariates that significantly differ between ethnic groups and/or
affect the Satisfaction with Life Scale (SWLS)at one year post-injury.
Design: Retrospective study. Setting: Longitudinal dataset of the TBI Model Systems National Database.
Participants: 3,368 individuals with moderate to severe TBI (2478 Caucasian, 629 African American, 180 Hispanic, and 81
Asian/Pacific Islander) hospitalized between 1989 and 2005.
Main Outcome Measures: Satisfaction with Life Total score at 1 year post injury.
Results: African Americans had 3.21 units lower SWLS scores one year post-injury than Asian/Pacific Islanders (95% CI
=0.61–5.81) and 1.99 units lower SWLS scores than Caucasians (95% CI =0.97–3.00) after controlling for marital status,
employment at admission, cause of injury, FIM at discharge, and LOS in acute care.
Conclusions: African Americans have poorer self-reported life satisfaction than Caucasians and Asians one year after TBI. This
effect is not due to pre-injury marital or employment status, cause of injury, nor injury severity or functional status. Further
research on the factors which might explain these differences is warranted, so that targeted rehabilitation programs can be designed
and implemented that enhance quality of life for all individuals who have suffered a TBI.
Keywords: Satisfaction with life, TBI, Race/ethnicity
1. Introduction
Traumatic brain injury (TBI) is an important public
health problem in the United States. Approximately
5.3 million Americans (over 2 % of the US population)
have long-term or permanent dysfunction as a result of
TBI [39]. TBI commonly results in multiple physical,
cognitive, and emotional changes that develop at the
∗Address for correspondence: Juan Carlos Arango-Lasprilla,
Ph.D., Assistant Professor, Department of Physical Medicine and
Rehabilitation, Virginia Commonwealth University, 730 East Broad
Street, 4th Floor, Room 4230a, Richmond, VA 23219, USA. Tel.:
+1 804 828 8797; E-mail: jcarangolasp@vcu.edu.
time of injury, or shortly thereafter, and can persist
over time [15,23,32]. Consequently, TBI negatively
affects areas of daily life as diverse as employment,
social integration, and family functioning [16,25,37].
Persons with TBI also tend to report less satisfaction
with life compared to non-disabled populations [1,33].
Life satisfaction, quality of life, and subjective well-
being have been used relatively interchangeablyin pre-
vious TBI research. Corrigan et al. [12] defined life
satisfaction as, “a cognitively oriented, subjectivejudg-
ment of one’s current life situation in relation to one’s
own expectation” (p. 544). The authors emphasized
that life satisfaction is an important aspect of a per-
son’s quality of life and noted a relationship with hav-
ISSN 1053-8135/09/$17.00 2009 – IOS Press and the authors. All rights reserved
6J.C. Arango-Lasprilla et al. / Race/ethnicity differences in satisfaction with TBI
ing a healthy and productive lifestyle. Thus it might
be expected that health, productivityand other lifestyle
changes imposed by TBI would be associated with re-
ducedlife satisfaction. Heinemann and Whiteneck[21]
were among the first to examinethe relationship among
life satisfaction and home, social, and productivity in-
tegration as measured by the Community Integration
Questionnaire (CIQ) for persons with TBI. Higher lev-
els of social integration (e.g., recreational pursuits and
interaction with family/ friends) and productivity (e.g.,
work or school activities) were both associated with
higher life satisfaction. Similarly, results from an ex-
amination of the World Health Organization’s Inter-
national Classification of Functioning, Disability, and
Health (ICF) components and life satisfaction indicat-
ed that greater social integration and productivity were
associated with increased life satisfaction [34]. Addi-
tional research supports the relationship between good
socialrelationsand/orintegration into productiveactiv-
itiesandhigherlevelsof life satisfaction amongpersons
who have experienced TBI [8,12,27,30]. In summary,
the literature suggests that life satisfaction after TBI is
directly related to the individual’s ability to participate
in meaningful activities and to interact with others in a
social environment.
The family plays an integral role in the recovery
of TBI and has also been found to be associated with
life satisfaction after injury. In a study of 247 persons
[190 with spinal cord injury (SCI) and 57 with TBI]
from two SCI and two TBI Model Systems sites, being
married was a significant predictor of life satisfaction
among persons with TBI, but not those with SCI [22].
Similarly, Warren et al. [40] studied factors affecting
life satisfaction in a longitudinal study for a group of
137 individuals with TBI and 38 with SCI. Multiple re-
gression analysis indicated that higher satisfactionwith
family relationships and being married were related to
greater life satisfaction in the TBI group.
The relationships between life satisfaction and nu-
merous other demographic and injury-relatedvariables
have been thoroughly examined in the TBI literature
with conflicting results. Some studies have found that
age, gender, and years post-TBI significantly predict
life satisfaction [8,11], while others have found no sig-
nificance for age, gender, education, or level of disabil-
ity [12,21,22,29,34,40].
Relatively few studies have examined the relation-
ship between race/ethnicity and life satisfaction among
persons with TBI, and most of these have not found
significant differences. Corrigan, Smith-Knapp, and
Granger [13] found that race/ethnicity affected life sat-
isfaction after TBI with a sample of 95 subjects (93%
Caucasians and 7% African Americans), but the direc-
tion of the relationship was not specified. Corrigan et
al. [12] conducted a prospective study with a longitudi-
nal sample of 218TBI patients that was 94% Caucasian
(n=204) and 6% minority (n=13) in which race
was not significantly associated with life satisfaction.
Hart et al. [20] investigatedthe impact of race and pre-
injury status on community outcomes following TBI
in a sample of 55 White and 39 African Americans.
Therewere no statistically significantdifferences in life
satisfaction between racial groups, although African
Americans reported slightly lower mean life satisfac-
tion scores than whites both prior to injury (using ret-
rospective self-report) and at 1-year follow-up. Hicken
andcolleagues(2002) found no differencesin life satis-
faction between 34 Caucasians and 23 minorities with
TBI. Pierce and Hanks (2006) studied the relationship
between demographic factors (gender, ethnicity, edu-
cation, marital status, and age), the WHO components
(body function and structure, activity, and participa-
tion), and life satisfaction in 180 individuals with TBI
(48 Caucasians, 126 African Americans, 4 Hispanics,
and 2 Asian, Pacific Islander). Although the stepwise
multiple regression did not find race/ethnicity to be a
predictor of life satisfaction, correlations revealed that
race/ethnicity was related to CIQ social and productiv-
ity subscales (the two strongest predictors of life sat-
isfaction), such that Caucasians had higher social and
productivity scores compared to minorities.
Althoughthe majority of studies seem to suggest that
race/ethnicity is not related to life satisfaction, current
researchin racial/ethnic disparities among persons with
TBI show that minorities are more likely than Cau-
casians to have lower levels of the correlates of life sat-
isfaction such as social integration, work productivity,
and being married. Several large sample studies have
shown that persons from minority backgrounds have
a less favorable outcome from TBI than their white
counterparts [35,38]. For example, compared to Cau-
casians, people from minority backgrounds with TBI
have lower levels of social functioning [24] and com-
munity integration [5]. Arango and colleagues [4] re-
ported that the odds of being unemployed versus com-
petitively employed at 1 year after TBI are 2.17 times
(95% CI =1.78, 2.66) greater for minorities than for
whites, after adjusting for employmentstatus at admis-
sion, gender, Disability Rating Scale at discharge,mar-
ital status, cause of injury,age, and education. Minori-
ties were less likely than Caucasians to have stable em-
ployment in the three years post-TBI [26]. Minorities
J.C. Arango-Lasprilla et al. / Race/ethnicity differences in satisfaction with TBI 7
with TBI reported less social support than Caucasian
TBI survivors [7], and were less likely to be stably
married at two years post-TBI [3].
In summary, the relationship between race/ethnicity
and life satisfaction has not been extensively studied
in TBI. Previous studies may have been underpow-
ered, and nearly all have combined people from mul-
tiple minority groups into one sample. Given that
race/ethnicity is clearly related to factors that are asso-
ciated with life satisfaction, further research is needed
to explore the impact of race/ethnicity on life satisfac-
tion in a larger, more ethnically diverse sample of per-
sonswithTBI. The present study aims to determine dif-
ferences in life satisfaction at 1-year post-TBI among
Caucasian, African American, Hispanic, and Asian in-
dividuals with TBI, after adjusting for covariates that
significantly differ between ethnic groups and/or affect
the Satisfaction with Life Scale (SWLS) at one year
post-injury.
2. Methods
2.1. Participants
Participants were enrolled in the national database
of the National Institute on Disability and Rehabili-
tation Research-funded TraumaticBrain Injury Model
System (TBIMS) program, a multi-center longitudinal
study of TBI outcomes [14]. Approval for informed
consent for each funded TBIMS center was given by
their individual institutional review board (IRB). Every
patient (or the patient’s legal guardian or family mem-
ber if appropriate) provided informedconsent to be en-
rolled in the study. According to the TBIMS, TBI is
defined as trauma to brain tissue caused by an external
mechanical force as evidenced by loss of conscious-
ness, posttraumatic amnesia (PTA), skull fracture, or
objective neurological findings that can be reasonably
attributed to TBI on physical or mental status examina-
tion [18].
For the present study, data from 5,181 patients with
primarily moderate to severe TBI occurring between
1998 and 2005 were extractedfrom the TBIMS nation-
al database. The 1998 start date was chosen because
SWLS was added to the database during this year and
the 2005 end date was chosen because all subjects’ one
year follow-upinformation was due by this date. There
were 3,408 subjects in this sample whose total SWLS
measure at one year post-injury was available. Missing
data for SWLS occurred for a variety of reasons such
as loss to follow-up, the follow-up interview was not
withthesurvivor,deathofsurvivor,ormissingitems on
the SWLS measure. Of the 3,408 subjects with avail-
able SWLS measures, there were 3,368 subjects whose
race/ethnicity was reported as Caucasian (n=2478),
African American (n=629), Hispanic (n=180), or
Asian/PacificIslander (n=81). The remaining40sub-
jects (19 Native Americans and 21 other/unclassified)
were not included in this analysis.
2.2. Measures
2.2.1. Dependent variable
The SWLS is a global measure of life satisfaction
(Diener et al., 1985). The measure consists of 5 ques-
tions (items) that are completed by the individualwith
responses corresponding to level of agreement with a
7–point scale: (1) strongly disagree, (2) disagree, (3)
slightly agree, (4) neither agree nor disagree, (5) slight-
ly agree, (6) agree, and (7) strongly agree. The 5 ques-
tions are as follows: (1) In most ways my life is close
to my ideal, (2) The conditions of my life are excellent,
(3) I am satisfied with my life, (4) So far I have gotten
the important things I want in life, and (5) If I could
live my life over, I would change almost nothing. The
SWLS Total score is a sum of the scores of the 5 items,
and can range from 7 to 35.
2.2.2. Independent variables
Race/ethnicity is a self-reported measure by TBIMS
participants. The variable was categorized as African
American, Hispanic, Asian, or Caucasian. Other de-
mographic variables available for analyses include age
at injury, gender, pre-injury education level, pre-injury
marital status, and pre-injury employment. Marital sta-
tuswasdichotomizedasmarriedornotmarried(single,
divorced, separated, and widowed). Level of education
was dichotomized into less than high school (grades 1–
11) and high school or more (highschool degree, GED,
trade school, some college, Associate’s degree, Bach-
elor’s degree, Master’s degree, and Doctoral degree).
Employment status was dichotomized as competitively
employed (paid employment) or unemployed (unem-
ployed, full time student, part time student, homemak-
er, volunteer work, and other).
Measures of injury characteristics available for anal-
ysis included cause of injury, Glasgow Coma Scale
(GCS) score at emergency admission, total Function-
al Independence Measure (FIM) at rehabilitation ad-
mission and discharge, total Disability Rating Scale
(DRS) score at rehabilitation admission and discharge,
8J.C. Arango-Lasprilla et al. / Race/ethnicity differences in satisfaction with TBI
length of post-traumatic amnesia (PTA), length of stay
in acute care and in rehabilitation. Cause of injury was
dichotomizedinto not violent (vehicular,sportsrelated,
falls, and pedestrian accidents) and violent (gun shots,
blunt assaults, and other violence). The GCS score is
a 15 point three component measure of injury severity.
The measure ranges from 3 to 15 with higher scores
indicative of less severe injuries. Patients with GCS
scores between 3 and 8 are typically considered to have
severe injuries, while scores of 9–12 and 13–15 are as-
sociated with moderate and mild injuries, respectively.
The FIM is an 18 item measure of disability rated at
rehabilitation admission and discharge with scores for
each item ranging from 1 (total assist) to 7 (complete
independence). The Disability Rating Scale (DRS) is
a measure of global outcome (from coma to full activ-
ities at home or in the community) and has been used
with adolescent and adult TBI populations. The eight
item scale is completed at rehabilitation admission and
discharge and ranges from 0 (no disability) to 29 (ex-
treme vegetative state). Inter-rater reliability has been
found to be high (kappa =0.97–0.98). Length of PTA
measures the time in days from TBI until the patient is
no longer disoriented. Length of stay (LOS) in acute
care and length of stay in rehabilitation were measured
in number of days.
2.3. Statistical analysis
There were a total of 1,752 subjects (Caucasian,
African American, Hispanic, or Asian/Pacific Islander)
who could have been included in the analysis if their
one year post-injury SWLS measure had been avail-
able. These subjects were compared to the 3,368 in-
cluded subjects with respect to demographic and injury
characteristics using chi-square analyses for categori-
cal variables and t-tests for continuous variables.
Preliminary analyses using ANOVA models for con-
tinuous variables and chi-square tests for categorical
variables were conducted to identify differences be-
tween the race/ethnicity groups with respect to age at
injury,gender,pre-injurymaritalstatus,pre-injury level
ofeducation, pre-injury employmentstatus,causeofin-
jury, GCS at admission, PTA, DRS at admissions, DRS
at discharge, FIM at admission, FIM at discharge, LOS
acute and LOS rehabilitation. Tukey’s HSD methods
were used to adjust for multiple comparisons among
the race/ethnicity groups.
Analyses using ANOVA (categorical predictors) and
simple linear regression (continuous predictors) mod-
elswereutilizedtoidentifysignificantunivariatedemo-
graphic and injury characteristics predictiveof SWLS.
For the primary aim, an ANCOVA model was fit with
an effect for race/ethnicity and adjusted for various de-
mographic and injury characteristics. The variables
included for adjustment in the ANCOVA model were
those identified as significant univariate predictors of
SWLS as well as those identified as being significantly
different between the race/ethnicities. Backwards se-
lection methods were used to reduce the model with
a criteria for removal of p0.05. The results from
the final model were summarized and interpreted us-
ing Tukey’s HSD to adjust for multiple comparisons
among groups.
3. Results
The demographic and injury characteristics of the
sample of 3,368 subjects are summarized in Table 1.
In this sample, 2,478 participants classified them-
selves as Caucasian (73.57%), 629 as African Amer-
ican (18.68%), 81 as Asian (2.40%), and 180 as His-
panic (5.34%). The mean SWLS Total score in this
sample at one year follow-upwas 20.74 with a standard
deviation of 8.22. At the time of injury, the mean age
of participants was 37.20 years (SD =17.12), 71.70%
were male, 66.25% were not married, 72.27% had at
least a high school level ofeducation, and 67.58% were
employed at admission. In this sample, 90.16% had
non-violent injuries, 49.45% had severe GCS scores,
15.40% had moderate GCS scores, and 35.14% had
mild GCS scores. On average, FIM admission scores
and discharge scores were 53.93 (SD =25.26) and
95.99 (SD =19.94), respectively, DRS admission and
discharge scores were 12.06 (SD =5.58) and 5.68
(SD =3.15),respectively,PTAwas 26.07days(SD =
27.60), LOS acute and rehabilitation were 19.80 days
(SD =15.02) and 25.37 days (SD =22.89), respec-
tively. There was some missing data for pre-injury
marital status (N=2), level of education (N=61),
and employment status (N=49), as well as for cause
of injury (N=25), GCS (N=810), FIM admission
(N=176) and discharge (N=213), DRS at admis-
sion (N=58) and discharge (N=48), PTA (N=
667), and LOS rehabilitation (N=147).
Withregard to the comparisonofincludedand not in-
cluded TBIMS database participants, the included sub-
jects were significantly younger at injury (37.2 years
versus 41.0 years, p<0.0001), had higher FIM scores
on admission (53.9 versus 51.2, p=0.0005) and dis-
charge (96.0 versus 87.6, p<0.0001) scores, had
J.C. Arango-Lasprilla et al. / Race/ethnicity differences in satisfaction with TBI 9
Table 1
Means and proportions of SWLS and predictors of SWLS
(Continuous) Variables N Mean SD
SWLS (1 year) 3368 20.74 8.22
Age 3368 37.20 17.12
PTA 2701 26.07 27.60
FIM admission 3192 53.93 25.26
FIM discharge 3155 95.99 19.94
DRS admissions 3310 12.06 5.58
DRS discharge 3320 5.68 3.15
LOS acute 3368 19.80 15.02
LOS rehabilitation 3221 25.37 22.89
(Categorical) Variables N %
Race/Ethnicity
Caucasian 2478 73.57
African American 629 18.68
Asian/Pacific Islander 81 2.40
Hispanic 180 5.34
Gender
Female 953 28.30
Male 2415 71.70
Marital Status
Married 1136 33.75
Not Married 22.30 66.25
Education Level
H.S. or More 2390 72.27
Less than H.S. 917 27.73
Employment Status
Employed 2243 67.58
Not Employed 1076 32.42
Cause of Injury
Non-violent 3014 90.16
Violent 329 9.84
GCS scores
Mild 899 35.14
Moderate 394 15.40
Severe 1265 49.45
SD =standard deviation.
lower DRS admission (12.1 versus 12.8, p<0.0001)
and discharge (5.7 versus 7.2, p<0.0001) scores,
longer lengths of PTA (26.1 versus 23.6, p=0.0069),
shorter LOS acute care stays (19.8 versus 21.3, p=
0.0016) and shorter LOS rehabilitation stays (25.4 ver-
sus 28.9, p<0.0001). Furthermore, as compared to
the participants who were not included, the subjects
included in the sample were more likely to be female
(28.3% versus 23.6%, p=0.0004), be married pre-
injury (33.8% versus 30.9%, p=0.0427), have at
least a high school education pre-injury (72.3% versus
63.8%, p<0.0001), be employed pre-injury (67.6%
versus 60.2%, p<0.0001), have non-violent injuries
(90.2%versus 84.6%, p<0.0001),andhavea different
distribution of GCS at admission (mild: 35.1% versus
38.2%; moderate: 15.4% versus 16.6%; severe: 49.5%
versus 45.20%, p=0.0414).
The SWLS Total scores at one year post injury are
summarized in Table 2 for the race/ethnicity groups
along with demographic and injury characteristics of
the sample. The race/ethnicity groups were not sig-
nificantly different with respect to PTA (p=0.5565),
admission DRS (p=0.1237), and rehabilitation LOS
(p=0.1852). There were differences among the
race/ethnicity groups noted for age at injury (p<
0.0001), admission (p=0.0097) and discharge FIM
(p<0.0001), discharge DRS (p<0.0001), and acute
LOS (p=0.0164). Using Tukey’s HSD to adjust for
multiple comparisons, Caucasians and African Amer-
icans were significantly older than Hispanics at the
time of injury; Asian/Pacific Islanders had significantly
higher admission FIM scores than African Americans;
African Americans had significantly lower discharge
FIM and significantly higher discharge DRS scores
than Caucasians, Asian/Pacific Islanders, and Hispan-
ics. No differences were found in acute LOS among
the race/ethnicity groups after adjusting for multiple
comparisons. In addition, there were significant dif-
ferences between the race/ethnicity groups noted for
pre-injury marital status (p<0.0001), pre-injury lev-
el of education (p<0.0001), pre-injury employment
status (p<0.0001), cause of injury (p<0.0001),
and admission GCS (p=0.0038), but not for gen-
der (p=0.6852). As indicated in Table 2, Cau-
casians and Asian/Pacific Islanders were more likely to
be married at admission as compared to Hispanics and
African Americans (36.4% and 33.3% versus 26.1%
and 25.6%); Caucasians were most likely to have at
least a high school education pre-injury (76.6%), fol-
lowed by Asian/Pacific Islanders (67.5%) and African
Americans (62.8%), while Hispanics were the least
likely (48.3%); Hispanics were the most likely to be
employed pre-injury (71.0%), followed by Caucasians
(69.4%), while Asian/Pacific Islanders and African
Americans were the least likely (61.3% and 60.1%);
African Americans were the most likely to suffer a vi-
olent injury (25.0%), followed by Hispanics (15.1%)
and Asian/Pacific Islanders (12.7%), while Caucasians
were the least likely (5.5%); Hispanics had the greatest
proportion of severe GCS (61.9%) and Caucasians and
Asian/Pacific Islanders had the greatest proportion of
mild GCS (36.9% and 35.7%).
Without adjusting for demographic and injury char-
acteristics, race/ethnicity was a significant predictor
of SWLS at one year post-injury (p<0.0001; see
Table 3). Using Tukey’s HSD to adjust for multi-
ple comparisons, African Americans had significantly
lower SWLS than Asian/Pacific Islanders, Caucasians,
and Hispanics. However SWLS was not different be-
tweenAsian/Pacific Islanders, Caucasians, and Hispan-
10 J.C. Arango-Lasprilla et al. / Race/ethnicity differences in satisfaction with TBI
Table 2
Means and proportions of SWLS and predictors of SWLS by Race/Ethnicity
Caucasian African American Asian/Pacific Islander Hispanic
(Continuous) Variables N Mean SD N Mean SD N Mean SD N Mean SD
SWLS (1 year) 2478 21.28 8.23 629 18.52 7.84 81 21.83 7.79 180 20.49 8.39
Age 2478 38.07 17.71 629 36.16 15.00 81 33.22 16.54 180 30.59 13.99
PTA 2022 25.98 28.37 458 27.03 27.72 75 22.16 19.12 146 26.23 18.72
FIM admission 2354 54.38 25.49 591 51.63 24.00 76 60.63 27.25 171 52.74 24.73
FIM discharge 2354 97.14 19.67 568 90.43 20.31 74 100.22 20.14 159 96.95 19.18
DRS admissions 2433 11.99 5.70 619 12.40 5.28 80 11.05 5.28 178 12.35 5.16
DRS discharge 2441 5.53 3.13 620 6.43 3.17 81 4.91 3.08 178 5.43 3.05
LOS acute 2478 19.35 14.90 629 21.02 15.69 81 19.04 12.71 180 21.96 14.91
LOS rehabilitation 2366 25.77 24.51 608 23.54 16.90 75 26.32 21.67 172 25.88 18.07
(Categorical) Variables N % N % N % N %
Gender
Female 715 28.85 169 26.87 22 27.16 47 26.11
Male 1763 71.15 460 73.13 59 72.84 133 73.89
Marital Status
Married 901 36.37 161 25.64 27 33.33 47 26.11
Not Married 1576 63.63 467 74.36 54 66.67 133 73.89
Education Level
H.S. or More 1861 76.58 390 62.80 54 67.50 85 48.30
Less than H.S. 569 23.42 231 37.20 26 32.50 91 51.70
Employment Status
Employed 1696 69.42 371 60.13 49 61.25 127 70.95
Not Employed 747 30.58 246 39.87 31 38.75 52 29.05
Cause of Injury
Non-violent 2322 94.51 471 75.00 69 87.34 152 84.92
Violent 135 5.49 157 25.00 10 12.66 27 15.08
GCS scores
Mild 667 36.89 183 32.68 20 35.71 29 21.64
Moderate 266 14.71 101 18.04 5 8.93 22 16.42
Severe 875 48.40 276 49.29 31 55.36 83 61.94
SD =standard deviation.
ics. Specifically, African Americans had 3.30 lower
SWLS than Asian/Pacific Islanders (95% CI =0.83,
5.78), 2.76 lower SWLS than Caucasians (95% CI =
1.82,3.70),and1.97lowerSWLS than Hispanics(95%
CI =0.20, 3.74).
Simple linear regression and ANOVA models (see
Table 3) indicated that age at injury (p=0.0001), PTA
(p=0.0002), FIM at admission (p<0.0001) and dis-
charge (p<0.0001), DRS at admission (p=0.0024)
and discharge (p<0.0001), LOS acute (p<0.0001)
and LOS rehabilitation (p=0.0040), pre-injury mari-
tal status (p<0.0001), cause of injury (p<0.0001),
and GCS (p<0.0001) were significant univariate pre-
dictors of SWLS one year post-injury. Gender (p=
0.3876), pre-injury level of education (p=0.0553),
and pre-injury employment status (p=0.1066) were
not significant predictors of SWLS at one year post-
injury. In general, increases in SWLS were associated
with increases in age at injury, admission and discharge
FIM, and decreases in PTA, admission and discharge
DRS, and acute and rehabilitation LOS (see Table 3 for
estimated slopes). Furthermore, significantly higher
SWLS was found with participants who were married
pre-injury, suffered non-violent injuries, or had less
severe GCS scores at admission (see Table 3 for the
estimated differences between the groups).
The primary aim was to determine effect of race/
ethnicity on SWLS one year post-injury. To correctly
understand the race/ethnicity effect on SWLS, the AN-
COVA model adjusted for differences between the eth-
nicgroups(age at injury,admission and dischargeFIM,
discharge DRS, acute LOS, pre-injury marital status,
pre-injury level of education, pre-injury employment
status, cause of injury, and GCS at admission) as well
as variables that significantly predicted SWLS (age at
injury, PTA, FIM at admission and discharge, DRS at
admission and discharge, LOS acute and LOS rehabil-
itation, pre-injury marital status, cause of injury, and
GCS at admission). Initially a model was fit with all of
the aforementioned covariates, however age at injury,
pre-injury level of education, GCS at admission, PTA,
FIMat admission, DRS atadmissionanddischarge,and
J.C. Arango-Lasprilla et al. / Race/ethnicity differences in satisfaction with TBI 11
Table 3
Univariate effects of predictors on SWLS
(Categorical) Variables F (NDF, DDF) p-value Difference (95% CI)
Ethnicity 19.67 (3, 3364) p<0.0001
(Asian/PI – Caucasian) 0.544 (−1.823, 2.911)
(Asian/PI – Hispanic) 1.333 (−1.472, 4.137)
(Asian/PI – African American)† 3.303 (0.828, 5.777)
(Caucasian – Hispanic) 0.789 (−0.829, 2.407)
(Caucasian – African American)† 2.759 (1.823, 3.695)
(Hispanic – African American) † 1.970 (0.198, 3.742)
Gender 0.75 (1, 3366) p=0.3876
(Females – Males) 0.272 (−0.345, 0.889)
Marital Status 58.86 (1, 3364) p<0.0001
(Married – Not Married)† 2.279 (1.697, 2.862)
Education Status 3.68 (1, 3305) p=0.0553
(HS or More – Less than HS) 0.612 (−0.014, 1.237)
Employment Status 2.61 (1, 3317) p=0.1066
(Not Employed – Employed) 0.492 (−0.106, 1.089)
Cause of Injury 40.29 (1, 3341) p<0.0001
(Non Violent – Violent)† 3.014 (2.083, 3.945)
GCS Score 9.39 (2, 2555) p<0.0001
(Mild – Moderate)† 1.324 (0.168, 2.480)
(Mild – Severe)† 1.501 (0.666, 2.335)
(Moderate – Severe) 0.177 (-0.927, 1.281)
(Continuous) Variables F (NDF, DDF) p-value Slope (95% CI)
Age† 14.67 (1, 3366) p=0.0001 0.032 (0.015, 0.048)
PTA† 13.88 (1, 2699) p=0.0002 −0.021 (−0.033, −0.010)
FIM admissions† 21.30 (1, 3190) p<0.0001 0.027 (0.015, 0.038)
FIM discharge† 34.91 (1, 3153) p<0.0001 0.043 (0.029, 0.057)
DRS admissions† 9.22 (1, 3308) p=0.0024 −0.078 (−0.128, −0.027)
DRS discharge† 27.96 (1, 3318) p<0.0001 −0.238 (−0.326, −0.150)
LOS acute† 44.86 (1, 3366) p<0.0001 −0.063 (−0.081, −0.044)
LOS rehabilitation† 8.28 (1, 3219) p=0.0040 −0.018 (−0.031, −0.006)
CI =confidence interval, NDF =numerator degrees of freedom, DDF =denominator degrees of freedom, † =
statistically significant, α=0.05.
LOSrehabilitationdid not remain significant predictors
in the adjusted model and were thus removedin a back-
wards selection manner. The final model (N=3087)
then included effects for race/ethnicity, pre-injury mar-
ital status, pre-injury employment status, cause of in-
jury, FIM at discharge, and LOS acute. This model
(see Table 4) indicated that there was a significant ef-
fect of race/ethnicity on SWLS scores one year post-
injury (p<0.0001), after adjusting for pre-injurymar-
ital status (p<0.0001), pre-injury employment status
(p=0.0009), cause of injury (p=0.0003), FIM at
discharge (p<0.0001), and LOS acute (p<0.0001).
Specifically, African Americans had 3.21 units lower
SWLS scores one year post injury than Asian/Pacific
Islanders (95% CI =0.61, 5.81) and 1.99 units lower
SWLS scores than Caucasians (95% CI =0.97, 3.00).
No other differences in SWLS were found between the
race/ethnicity groups after adjusting for multiple com-
parisons. A 10 unit increase in discharge FIM was
associated with a 0.32 unit increase in SWLS, and a
10 unit increase in acute LOS was associated with a
0.46 unit decrease in SWLS. In addition, subjects who
were married pre-injury had 2.07 units higher SWLS
scores than those who were not married (95% CI =
1.47, 2.68), subjects who were unemployed pre-injury
had 1.04 units higher SWLS scores than those who
were employed (95% CI =0.43, 1.65), and subjects
who suffered non-violent injuries had 1.87 units higher
SWLS scores than those who suffered violent injuries
(95% CI =0.85, 2.88).
4. Discussion
The purpose of the present study was to determine
differences in life satisfaction at one year post-injury
among Caucasian, African American, Hispanic, and
Asian individuals with TBI. The findings reportedhere
indicatethat there were significant differencesin SWLS
total scores among the race/ethnicity groups after ad-
justing for marital status, employment at admission,
cause of injury, and several indices of injury severity
12 J.C. Arango-Lasprilla et al. / Race/ethnicity differences in satisfaction with TBI
Table 4
Multivariate effects of predictors on SWLS for caucasians versus minorities (N=3564)
(Categorical) Variables F (NDF, DDF) p-value Difference (95% CI)
Ethnicity 9.47 (3, 3078) p<0.0001
(Asian/PI – Caucasian) 1.222 (−1.259, 3.703)
(Asian/PI – Hispanic) 2.007 (−0.933, 4.948)
(Asian/PI – African American)† 3.208 (0.606, 5.811)
(Caucasian – Hispanic) 0.785 (−0.912, 2.483)
(Caucasian – African American)† 1.987 (0.969, 3.004)
(Hispanic – African American) 1.201 (−0.665, 3.068)
Marital Status 45.27 (1, 3078) p<0.0001
(Married – Not Married)† 2.073 (1.469, 2.677)
Employment Status 11.08 (1, 3078) p=0.0009
(Not Employed – Employed)† 1.041 (0.428, 1.654)
Cause of Injury 13.00 (1, 3078) p=0.0003
(Non Violent – Violent)† 1.866 (0.851, 2.881)
(Continuous) Variables p-value Slope (95% CI)
FIM discharge† 15.85 (1, 3078) p<0.0001 0.032 (0.016, 0.047)
LOS acute† 19.21 (1, 3078) p<0.0001 −0.046 (−0.066, −0.025)
CI =confidence interval, SE =standard error, NDF =numerator degrees of freedom, DDF =denominator degrees
of freedom, † =statistically significant, α=0.05, PI =Pacific Islander.
(FIM at dischargeand acute care LOS). Amongthe eth-
nic groups, African Americans had lower satisfaction
with life than Asian/Pacific Islanders and Caucasians.
Thefindingsofthis study are in accordance with pre-
vious work suggesting that racial/ethnic background is
significantly associated with satisfaction with life after
TBI [13]. Studies that have failed to find racial differ-
ences in satisfaction with life may have done so due
to small samples overall [22] or small minority sam-
ples [12], or to the use of a local sample in which white
and African American samples had roughly equiva-
lent educational backgrounds and pre- and post-injury
employment rates [20]. An important difference be-
tween this study and some previous efforts is that we
had a large enough sample to compose separate groups
of African Americans, Asian Americans and individ-
uals of Hispanic background. These groups showed
substantial differences from one another in satisfaction
with life. Previous studies may have failed to uncover
racial differences in satisfaction with life if minority
groups were combined [34].
This study confirms the findings of previous work
showing higher life satisfaction for people with TBI
who are employed [21,34]. Also as in previous stud-
ies, satisfaction with life was significantly higher for
married individuals [22]. In the present study, vio-
lent (intentional) cause of TBI was also associated with
significantly lower satisfaction with life. Intentional
TBI has consistently shown to be related to poorer out-
comes of TBI and is a disproportionate mechanism of
injury for people in racial minority groups, especially
African-Americans [17,19,28].
In a large sample such as this, statistically signifi-
cant group differences may be expected with relative-
ly small numerical variations. Thus, it is important
also to interpret the clinical significance of observed
differences. Based on the normative data presented
by Pavot and Diener [33], both Caucasians and Asian
Americans reported a mean SWLS in the slightly sat-
isfied range (scores of 21–25) at one year post-TBI. In
contrast, African Americans fell into the slightly dis-
satisfied range (scores of 15–19), and Hispanics were
neutral (19–21).
It remains an open question why African Ameri-
cans reported lower levels of life satisfaction than Cau-
casians and Asians at one year post-injury. This study
does not examine the period of time between discharge
and one year follow-up, and it is possible that factors
occurring during that period contributed to these dif-
ferences. The amount of services received after in-
patient rehabilitation discharge could certainly be one
of these factors. In a study investigating the demo-
graphic characteristics of individuals that undergo dif-
ferent rehabilitation pathways after TBI, Mellick, Ger-
hart, and Whiteneck [31] found that 11.9% of Cau-
casians received inpatient rehabilitation plus outpatient
services or long-term care, while only 7.7% of minori-
ties received any service after inpatient rehabilitation
discharge. That study did not analyze differences be-
tween minority groups, so further research would be
needed to draw conclusions about African Americans;
receipt of service in particular.
To the best of the authors’ knowledge, there are no
studies that specifically address access, quality, and/or
J.C. Arango-Lasprilla et al. / Race/ethnicity differences in satisfaction with TBI 13
utilization of TBI services by African Americans af-
ter discharge from inpatient rehabilitation. There is,
however, some research that examines services during
inpatient rehabilitation for minorities in general. Bur-
nett and colleagues [9] found that, compared to Cau-
casians, minorities received fewer minutes of therapy
per day during inpatient rehabilitation. Shafi and col-
leagues [36] found that minority group members were
15% less likely than Caucasians to be placedin rehabil-
itation following a TBI, even after adjusting for the ef-
fectsofinjuryseverity, TBIseverity,age,andgender. It
is possible that disparities for African Americans exist
as well after discharge from inpatient rehabilitation.
Another factor worth considering is the role of per-
ceived discrimination in the African American com-
munity. For example, Casagrande and colleagues [10]
found that reported prior experiences of discrimination
were associated with delays in seeking medical care
and in adherence to treatment. As targets of discrim-
ination, African Americans would be at risk for lower
service utilization and adherence. Another aspect that
could hinder rehabilitation success for African Ameri-
cans is the presence of cultural mistrust [2]. Boulware
and colleagues [6] found that African Americans were
less likely to trust their physicians than Caucasians,
after adjusting for other variables. Higher levels of
mistrust could make it less likely that African Amer-
icans would seek the services they required after TBI
inpatient rehabilitation.
The results of this study should be interpreted with
caution due to the following limitations. 1) As not-
ed, the requirement that all patients enrolled in the
TBIMS database receive inpatient rehabilitation may
limit the generalizability of these results To those who
have milder TBI and/or lack coverage for inpatient re-
habilitation 2) Due to the small sample size of the Na-
tive American ethnic group, it was not possible to ana-
lyze this minority group separately in the present study.
The results of the present study cannot be generalized
to Native Americans with TBI or other ethnicities with
TBI not studied here. 3) In the current study it was not
possible to measure all factors that could be related to
satisfactionwith life in minority and non-minoritysam-
ples; these might include spirituality, religious beliefs,
immigration status, social support, level of accultura-
tion,concomitantmedicaldisorders, medicationusage,
language barriers, site-specific insurance limitations,
post-discharge therapy and medicalcare, and others.
Future studies are needed in a number of areas.
Futher research is needed to determine which factors
explain life satisfaction differences between African
Americans, Caucasians, and Asians at one year post-
TBI. Once these factors have been identified, rehabil-
itation programs will need to be designed to meet the
specific needs of minority groups with TBI to increase
their life satisfaction. Additional longitudinal follow-
up of this group is warranted to determine if racial
differences in life satisfaction also exist 5, 10, or 15
years post-injury. Changes in life satisfaction, or sta-
bility of satisfaction across years, between racial and
ethnic groups could also be examined in a study with
longer follow-up of participants. It would be impor-
tant to include as many diverse racial/ethnic groups as
possible in these types of studies, e.g. include more
Native Americans to compare their levels of life sat-
isfaction with the other groups. Finally, it would be
interesting to examine factors that might moderate the
relationshipbetween race/ethnicityand lifesatisfaction
and/or determine if moderating factors differ for spe-
cific racial/ethnic groups.
Acknowledgements
This research was supported by grants
H133A070036, and H133P040006 from the Nation-
al Institute on Disability and Rehabilitation Research,
United States Department of Education.
References
[1] D.B. Allison, V.C. Alfonso and G.M. Dunn, The Extended
Satisfaction With Life Scale, The Behavior Therapist 5(1991),
15–16.
[2] R.J. Alston and T.J. Bell, Cultural mistrust and the rehabilita-
tion enigma for african americans, Journal of Rehabilitation
62 (1996), 16.
[3] J.C. Arango Lasprilla, J.M. Ketchum, T. Dezfulian et al., Pre-
dictors of marital stability 2 years following traumatic brain
injury, Brain Inj (2008), 1–10.
[4] J.C. Arango-Lasprilla, J.M. Ketchum, K. Williams et al.,
Racial differences in employment outcomes after traumatic
brain injury, ArchPhys Med Rehabil 89 (2008), 988–995.
[5] J.C. Arango-Lasprilla, M. Rosenthal, J. Deluca et al., Trau-
matic brain injury and functional outcomes: Does minority
status matter? Brain Inj 21 (2007), 701–708.
[6] L.E. Boulware, L.A. ooper, L.E. Ratner, T.A. LaVeist and N.R.
Powe, Race and trust in the health care system, Public Health
Rep 118 (2003), 358–365.
[7] S.A. Brown, S.R. McCauley, H.S. Levin, C. Contant and C.
Boake, Perception of health and quality of life in minorities
after mild-to-moderate traumatic brain injury, Applied Neu-
ropsychology 11(1) (2004), 54.
[8] S.A. Burleigh, R.S. Farber and M. Gillard, Community inte-
gration and life satisfaction after traumatic brain injury: long-
term findings, Am J Occup Ther 52 (1998), 45–52.
14 J.C. Arango-Lasprilla et al. / Race/ethnicity differences in satisfaction with TBI
[9] D.M. Burnett, S.A. Kolakowsky-Hayner, D. Slater et al.,
Ethnographic analysis of traumatic brain injury patients in the
national Model Systems database, Arch Phys Med Rehabil
84(2) (Feb 2003), 263–267.
[10] S.S. Casagrande, T.L. Gary, T.A. LaVeist, D.J. Gaskin and
L.A. Cooper, Perceived discrimination and adherence to med-
ical care in a racially integrated community, J Gen Intern Med
22 (2007), 389–395.
[11] K.D. Cicerone and J. Azulay, Perceived self-efficacy and life
satisfaction after traumatic brain injury, J Head Trauma Re-
habil 22 (2007), 257–266.
[12] J.D. Corrigan, J.A. Bogner, W.J. Mysiw, D. Clinchot and L.
Fugate, Life satisfaction after traumatic brain injury, J Head
Trauma Rehabil 16 (2001), 543–555.
[13] J.D. Corrigan, K. Smith-Knapp and C.V. Granger, Outcomes
in the first 5 years after traumatic brain injury, Archives of
Physical Medicine and Rehabilitation 79 (1998), 298–305.
[14] E.R. Dahmer, M.A. Shilling, B.B. Hamilton et al., A model
systems database for traumatic brain injury, J Head Trauma
Rehabil 8(1993), 12–25.
[15] S.S. Dikmen, J.E. Machamer, J.M. Powell and N.R. Temkin,
Outcome 3 to 5 years after moderate to severe traumatic brain
injury, Arch Phys Med Rehabil 84 (2003), 1449–1457.
[16] E. Doig, J. Fleming and L. Tooth, Patterns of community in-
tegration 2-5 years post-discharge from brain injury rehabili-
tation, Brain Inj 15 (2001), 747–762.
[17] K. Gerhart, D. Mellick and A. Weintraub, Violence-related
traumatic brain injury: A population-based study, Journal of
Trauma 55(66), 1045–1053.
[18] C. Harrison-Felix, C.N. Newton, K.M. Hall andJ.S. Kreutzer,
Descriptive findings from the Traumatic Brain Injury Model
Systems National Database, J Head Trauma Rehabil 11(5)
(1996), 1–14.
[19] C. Harrison-Felix, R. Zafonte, N. Mann, M. Dijkers, J. Eng-
lander and J. Kreutzer, Brain injury as a result of violence:
preliminary findings from the traumatic brain injury model
systems, Arch Phys Med Rehabil 79(7) (Jul 1998), 730–737.
[20] T. Hart, J. Whyte, M. Polansky, G. Kersey-Matusiak and R.
Fidler-Sheppard, Community outcomes following traumatic
brain injury: impact of race and preinjury status, J Head
Trauma Rehabil 20 (2005), 158–172.
[21] A.W. Heinemann and G.G. Whiteneck, Relationships among
impairment, disability, handicap, and life satisfaction in per-
sons with traumatic brain injury, Journal of Head Trauma
Rehabilitation 10 (1995), 54–63.
[22] B.L. Hicken, J.D. Putzke, T. Novack, M. Sherer and J.S.
Richards, Life satisfaction following spinal cord and traumat-
ic brain injury: a comparative study, J Rehabil Res Dev 39
(2002), 359–365.
[23] D. Hoofien, A. Gilboa, E. Vakil and P.J. Donovick, Traumatic
braininjury (TBI) 10-20yearslater: a comprehensiveoutcome
study of psychiatric symptomatology, cognitive abilities and
psychosocial functioning, Brain Inj 15 (2001), 189–209.
[24] R.E. Jorge, R.G. Robinson, S.E. Starkstein and S.V. Arndt, In-
fluence of major depression on 1-year outcome in patients with
traumatic brain injury, Journal of Neurosurgery 81 (1994),
726–733.
[25] J.S. Kreutzer, A.H. Gervasio andP.S.Camplair, Primary care-
givers’ psychological status and family functioning after trau-
matic brain injury, Brain Inj 8(1994), 197–210.
[26] J.S. Kreutzer, J.H. Marwitz, W. Walker et al., Moderating
factors in return to work and job stability after traumatic brain
injury, J Head Trauma Rehabil 18(2) (Mar–Apr 2003), 128–
138.
[27] S.G. LoBello, A.T. Underhil, P.V.Valentine, T.P. Stroud, A.A.
Bartolucci and P.R. Fine, Social integration and life and fam-
ily satisfaction in survivors of injury at 5 years postinjury, J
Rehabil Res Dev 40 (2003), 293–299.
[28] J. Machamer, N. Temkin and S. Dikmen, Neurobehavioral
outcome in persons with violent or nonviolent traumatic brain
injury, Journal of Head Trauma Rehabilitation 18(5) (2003),
387–397.
[29] L. Mailhan, P. Azouviand A. Dazord, Life satisfaction and dis-
ability after severe traumatic brain injury, Brain Inj 19 (2005),
227–238.
[30] J.M. Mazaux, P. Croze, B. Quintard et al., Satisfaction of life
and late psycho-social outcome after severe brain injury: a
nine-year follow-up study in Aquitaine, Acta Neurochir Suppl
79 (2002), 49–51.
[31] D. Mellick, K.A. Gerhart and G.G. Whiteneck, Understanding
outcomes based on the post-acute hospitalization pathways
followed by persons with traumatic brain injury, Brain Inj
17(1) (Jan 2003), 55–71.
[32] S.R. Millis, M. Rosenthal, T.A. Novack et al., Long-term
neuropsychological outcome after traumatic brain injury, J
Head Trauma Rehabil 16 (2001), 343–355.
[33] W. Pavot and E. Diener, The affective and cognitive context
of self-reported measures of subjective well-being, Social In-
dicators Research 28 (1993), 1–20.
[34] C.A. Pierce and R.A. Hanks, Life satisfaction after traumat-
ic brain injury and the World Health Organization model of
disability, Am J Phys Med Rehabil 85 (2006), 889–898.
[35] M. Rosenthal, M. Dijkers, C. Harrison-Felix et al., Impact of
minority status on functional outcome and community inte-
gration after traumatic brain injury, Journal of Head Trauma
Rehabilitation 11 (1996), 69–79.
[36] S. Shafi, C. Marquez de la Plata, R. Diaz-Arrastia et al., Racial
disparities in long-term functional outcome after traumatic
brain injury, J Trauma 63(6) (Dec 2007), 1263–1268; discus-
sion 1268–1270.
[37] J. Shames, I. Treger, H. Ring and S. Giaquinto, Return to
work following traumatic brain injury: trends and challenges,
Disabil Rehabil 29 (2007), 1387–1395.
[38] M. Sherer, T.G. Nick, A.M. Sander et al., Race and produc-
tivity outcome after traumatic brain injury: influence of con-
founding factors, Journal of Head Trauma Rehabilitation 18
(2003), 408–424.
[39] D.J. Thurman, C. Alverson, K.A. Dunn, J. Guerrero and J.E.
Sniezek, Traumatic brain injury in the United States: A public
health perspective, J Head Trauma Rehabil 14 (1999), 602–
615.
[40] L. Warren, J.M. Wrigley, W.C. Yoels and P.F. Fine, Factors
associated with life satisfaction among a sample of persons
with neurotrauma, J Rehabil Res Dev 33 (1996), 404–408.
