Nicotine & Tobacco Research, Volume 13, Number 12 (December 2011) 1284–1295
Advance Access published on October 12, 2011
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Decades of research demonstrate staggering human and mone-
tary costs caused by cigarette smoking, which is currently hailed
as the most preventable source of morbidity and mortality
(Dube, Asman, Malarcher, & Carabollo, 2009). Literature also
clearly documents disparities in smoking among lesbian, gay,
and bisexual populations (i.e., sexual minorities) in the United
States, suggesting 50%–70% higher prevalence than the general
population (Austin et al., 2004; Garofalo, Wolf, Kessel, Palfrey, &
DuRant, 1998; Gruskin, Greenwood, Matevia, Pollack, & Bye,
2007; Lee, Griffin, & Melvin, 2009; McCabe, Boyd, Hughes, &
d’Arcy, 2003; Skinner, 1994; Stall, Greenwood, Acree, Paul, &
Coates, 1999; Tang et al., 2004). Moreover, the American Lung
Association (2010) published a special report of tobacco dis-
parities among sexual minorities, harkening a call for more
Despite overall concordance of higher smoking prevalence,
knowledge remains relatively underdeveloped about factors
driving this disparity. A few risk factors have been empirically
tested and significantly associated with smoking outcomes, such
as internalized homophobia (Amadio & Chung, 2004), alcohol
abuse and depression (McKirnan, Tolou-Shams, Turner, Dyslin, &
Hope, 2006), issues involving disclosure of sexual minority status
(Rosario, Schrimshaw, & Hunter, 2009), and early sexual expe-
rience (Lombardi, Silvestre, Janosky, Fisher, & Rinaldo, 2008).
Socially based stressors, such as discrimination and violence vic-
timization, are also identified risk factors salient to negative
health outcomes among sexual minority men and women
(Herek, Gillis, & Cogan, 1999; Mays & Cochran, 2001; Meyer,
The diversity among sexual minority people notwithstanding,
they report notably similar experiences related to discrimination,
stigma, rejection, and violence (Herek, 2009). Research consis-
tently demonstrates that fear of victimization, including dis-
crimination and violence, affects overall health and well-being
Introduction: Lesbian, gay, and bisexual (i.e., sexual minority)
populations have higher smoking prevalence than their het-
erosexual peers, but there is a lack of empirical study into
why such disparities exist. This secondary analysis of data
sought to examine associations of discrimination and violence
victimization with cigarette smoking within sexual orientation
Methods: Data from the Fall 2008 and Spring 2009 National
College Health Assessments were truncated to respondents of
18–24 years of age (n = 92,470). Since heterosexuals comprised
over 90% of respondents, a random 5% subsample of hetero-
sexuals was drawn, creating a total analytic sample of 11,046.
Smoking status (i.e., never-, ever-, and current smoker) was
regressed on general (e.g., not sexual orientation–specific) mea-
sures of past-year victimization and discrimination. To examine
within-group differences, two sets of multivariate ordered
logistic regression analyses were conducted: one set of models
stratified by sexual orientation and another set stratified by
Results: Sexual minorities indicated more experiences of
violence victimization and discrimination when compared with
their heterosexual counterparts and had nearly twice the cur-
rent smoking prevalence of heterosexuals. After adjusting for
age and race, lesbians/gays who were in physical fights or were
physically assaulted had higher proportional odds of being
current smokers when compared with their lesbian/gay coun-
terparts who did not experience those stressors.
Conclusions: When possible, lesbian/gay and bisexual groups
should be analyzed separately, as analyses revealed that bisexuals
had a higher risk profile than lesbians/gays. Further research is
needed with more nuanced measures of smoking (e.g., intensity),
as well as examining if victimization may interact with smoking
Associations of Discrimination and
Violence With Smoking Among Emerging
Adults: Differences by Gender and Sexual
John R. Blosnich, M.P.H. & Kimberly Horn, Ed.D.
Translational Tobacco Reduction Research Program, Mary Babb Randolph Cancer Center, Prevention Research Center, West Virginia
University, Morgantown, WV
Corresponding Author: John R. Blosnich, M.P.H., Translational Tobacco Reduction Research Program, Mary Babb Randolph
Cancer Center and Prevention Research Center, Department of Community Medicine, West Virginia University, PO Box 9190,
Morgantown, WV 26506, USA. Telephone: 724-344-8504; Fax: 304-293-8624; E-mail: email@example.com
Received November 30, 2010; accepted July 18, 2011
Nicotine & Tobacco Research, Volume 13, Number 12 (December 2011)
across many types of minority populations (Mays, Cochran, &
Barnes, 2007; Meyer, 2003b; Williams, Neighbors, & Jackson,
2003). In fact, certain types of victimization, such as intimate
partner violence, sexual assault, and traumatic events, can be
independent risk factors for continued smoking (Amstadter
et al., 2009; Roberts, Fuemmeler, McClernon, & Beckham,
2008; Stueve & O’Donnell, 2007). Prior work with adolescent
and young adult racial minorities demonstrates associations
between racial- and ethnic-based discrimination and smoking
(Guthrie, Young, Williams, Boyd, & Kintner, 2002; Landrine &
Klonoff, 2000; Wiehe, Aalsma, Liu, & Fortenberry, 2010).
Although smoking was not assessed, Mays and Cochran (2001)
found support that discrimination moderated the relationship
between sexual orientation differences in psychiatric problems,
including alcohol and illicit drug use.
A unifying theme through minority health disparities
research suggests that elevated risk results from socially based
stressors (e.g., discrimination and victimization). From an eco-
social perspective, Krieger (1994, 2001) maintains that socially
derived factors bear critical importance for examining health
outcomes, that social context matters to circumspectly under-
stand individual health behaviors, and that health inequities are
largely socially produced. The ecosocial framework has been
used widely in conceptualizing how social factors—from
victimization, to targeted advertising, to racism—associate with
health and health risk behaviors—such as risk of sexually trans-
mitted infections (Buffardi, Thomas, Holmes, & Manhart, 2008),
alcohol use (Kwate & Meyer, 2009), poor mental and physical
health (Sanders-Phillips, Settles-Reaves, Walker, & Brownlow,
2009), and smoking (Barbeau, Wolin, Naumova, & Balbach,
Harkening elements of an ecosocial perspective, a growing
body of research, has demonstrated associations between dis-
crimination and poor mental and physical health outcomes
among racial/ethnic minority populations (Williams, Neighbors, &
Jackson, 2003). However, stress is also associated with health
risk behaviors, such as smoking. Generally, research with smokers
consistently shows that individuals who smoke cite stress as a
reason for both why they smoke (i.e., trigger for smoking) and
the amount of cigarettes they smoke (Kassel, Stroud, & Paronis,
2003; McClernon & Gilbert, 2010; Pomerleau & Pomerleau,
1991). Literature has documented positive associations between
racial- and ethnic-based discrimination and smoking behaviors
among Black (Bennett, Wolin, Robinson, Fowler, & Edwards,
2005), Hispanic (Wiehe et al., 2010), and Asian American
(Chae, Takeuchi, Barbeau, Bennett, Lindsey, & Krieger, 2008)
populations. However, research examining discrimination
(either general discrimination or sexual orientation–specific
discrimination) and smoking among sexual minority popula-
tions is relatively limited. In a probability-based sample of adults
in Minnesota, Burgess, Lee, Tran, and van Ryn (2007) found that
sexual minority respondents reported more instances of discrim-
inatory events in the past year, regardless of whether the discrim-
ination was perceived to be based on sexual orientation or some
other characteristic (e.g., gender, race, or religion). Moreover,
although discrimination was associated with smoking among the
sample in general, discrimination did not mediate the relation-
ship between sexual orientation and smoking.
Most investigations examining stress and health among
sexual minorities focus on explaining mental health disparities,
such as depression and anxiety (Burgess et al., 2007; Hatzenbuehler,
McLaughlin, Keyes, & Hasin, 2010; Meyer, 1995, 2003). Few
investigations examine how socially based stressors may also as-
sociate with health risk behaviors, such as smoking (Hamilton &
Mahalik, 2009). Among a probability-based sample of adoles-
cent school students, Bontempo and D’Augelli (2002) found
that lesbian, gay, and bisexual students’ elevated risk behaviors,
which included smoking, were attributable to at-school victim-
ization, which was defined as having their property vandalized or
being threatened or injured with a weapon in the past 12 months;
discrimination was not assessed. Furthermore, at least two qual-
itative studies with sexual minorities reported emergent themes
of stress management cited by participants as reasons for their
smoking (Gruskin, Byrne, Altschuler, & Dibble, 2008; Remafedi,
2007), but quantitative investigations are needed to empirically
investigate these associated risk factors.
Recent work by Ortiz-Hernandez, Gomez Tello, and Valdes
(2009) tested whether family violence, sexual orientation–based
discrimination, and being a victim of crime mediated the rela-
tionship between smoking and three different measures of
sexual orientation (i.e., same-sex attraction, sexual minority
identity, and same-sex sexual behavior) among a probability-
based sample of Mexican adolescents and young adults. It is
important to note that the family violence and crime victimiza-
tion items in the survey were assessed with single items and
asked in general (i.e., not specific to sexual orientation), where-
as the discrimination question was a single item that was sexual
orientation–specific. The authors found that the three stressor
variables, together, mediated the relationship between same-sex
attraction and current smoking and the relationship between
self-identified sexual minority status and lifetime smoking.
Importantly, however, the stressors did not mediate the rela-
tionships between sexual orientation and smoking intensity
(smoking ≥6 cigarettes/day). These results also suggest that the
associations between victimization/discrimination and health
risk behaviors, such as smoking, are likely complex and may not
follow linear paths for all outcomes.
This study aimed to test independent associations of past-
year experiences of socially based stressors (i.e., general measures of
discrimination and victimization) with smoking status among
sexual minority young adults. We use the term socially based
stressor to indicate that the stressor was interpersonal and origi-
nated from the social environment, rather than a biologically
based stressor (e.g., genetic or hormonal factors). There is
substantial evidence demonstrating higher smoking prevalence
among sexual minority men and women when compared with
heterosexual men and women (Lee et al., 2009), and our initial
hypotheses test whether these differences in smoking prevalence
endure with our sample (i.e., compared with their heterosexual
peers, significantly more sexual minority individuals will report
While testing differences between sexual orientation groups
presents an aggregate perspective of disparity, between-group
analyses do not reveal potential within-group differences that
could contribute to differential risk among subsets within a
population (e.g., bisexual women, gay men). Consequently, our
second set of hypotheses focus on questions of heterogeneity
within each sexual orientation category. To those ends, we strat-
ified analyses by gender and sexual orientation group, which
allowed us to test research questions such as “Do gay men who
Discrimination and violence with smoking
experience discrimination have increased odds of smoking when
compared with their gay male counterparts who do not experi-
This project used the National College Health Assessment (NCHA)
data, collected by the American College Health Association.
Each fall and spring semester, post-secondary educational insti-
tutions choose to purchase and administer the NCHA with their
students. To form national datasets, the American College Health
Association (2009c) combines data from institutions that used
either a random or a census sample design and gained institu-
tional review board approval to implement the survey. As a
secondary analysis of de-identified data, the authors’ institu-
tional review board considered this project nonhuman subjects
From the total combined sample of 113,790 participants, we
first selected only those respondents of 18–24 years old (n =
92,470) in order to comprise a young adult-only sample (Park,
Mulye, Adams, Brindis, & Irwin, 2006). Sexual orientation was
measured with an item asking respondents to self-identify as
heterosexual (n = 85,710), gay/lesbian (n = 1,825), bisexual (n =
2,545), or unsure (n = 1,545). For the purposes of this project,
we defined sexual minority as persons who identified as lesbian,
gay, or bisexual. Persons who were unsure of their sexual orien-
tation were analyzed as a separate group. Since analyses were
stratified by sexual orientation and heterosexuals comprised
over 90% of the sample, to keep the heterosexual analyses from
being statistically overpowered, a random 5% subsample was
drawn from the original heterosexual young adult sample (n =
4,286). Using chi-square tests of independence, comparisons
were made between the random 5% heterosexual subsample
and the original heterosexual sample on demographics (i.e., sex,
race, and age) and found no statistically significant differences
(data not shown). Consequently, the final analytic sample for all
analyses was 11,046.
Participating institutions administered the survey via either
the Internet or paper-and-pencil. Overall, paper-and-pencil
surveys generated higher mean response rates than Web-based
formats (Paper2008 = 63%; Web2008 = 22%; Paper2009 = 82%;
Web2009 = 20%). Globally, the mean response rates among par-
ticipating institutions in the Fall 2008 and Spring 2009 semes-
ters were 27% and 30%, respectively (American College Health
Association, 2009a, 2009b). Detailed analyses of the NCHA II
survey reliability and validity are available from the American
College Health Association (n.d.).
The NCHA assessed race/ethnicity in one item, in which
participants could indicate more than one racial/ethnic category
(i.e., “How do you usually describe yourself? White, non-Hispanic
[includes Middle Eastern]; Black, non-Hispanic; Hispanic or
Latino/a; Asian or Pacific Islander; American Indian, Alaska
Native, or Native Hawaiian; Biracial or Multiracial; Other”).
Hispanic ethnicity was recoded separately from race, in that
anyone who indicated Hispanic ethnicity—regardless of race—
was coded as Hispanic. The racial categories were recoded
into White (non-Hispanic), Black (non-Hispanic), Asian (non-
Hispanic), and “Other” (non-Hispanic) race. The “Other” race
category included those respondents who indicated being
biracial or multiracial or marked more than one racial category.
Due to small sample size, American Indian, Alaska Native, or
Native Hawaiian (0.35%) was also recoded into the “Other”
Past-year, general measures of violence victimization and
discrimination were considered two separate indicators of
socially based stressors. Participants completed questions with
dichotomous responses (yes/no) about general experiences of
the following in the past 12 months: verbally threatened with
harm, physical fight, physical assault, sexually touched without
consent, attempted sexual penetration without consent, and
sexually penetrated without consent; the latter three items were
combined to form one variable of any sexual assault.
Participants were asked about various experiences in the
context of their academics (i.e., “Within the last 12 months,
have any of the following affected your academic performance?”),
with one of those experiences being “discrimination (e.g.,
homophobia, racism, sexism).” Participants indicated one re-
sponse from the following options: this did not happen to me/
not applicable; I have experienced this issue buy my academics
have not been affected; received a lower grade on an examination
or important project; received lower grade in the course;
received an incomplete or dropped the course; significant dis-
ruption in thesis, dissertation, research, or practicum work. To
operationalize discrimination, the response categories were
dichotomized into those who reported no discrimination and
those who reported some experience of discrimination. Interac-
tions for race/ethnicity and discrimination and gender and
discrimination were tested in multivariate models but were not
statistically significant (p = .07–.84).
A key covariate of smoking behaviors among young adults
is binge drinking (Weitzman & Chen, 2005). Thus, a variable
was included for binge drinking in the previous two weeks (0 = no
binge drinking in past two weeks/1 = at least one episode of binge
drinking in past two weeks). Analyses were also adjusted for
region of the country (Northeast, Midwest, South, West, Out-
side United States; West as reference), given regional differences
in smoking prevalence across the United States and the West
having the lowest smoking prevalence (Dube et al., 2010). All
models were adjusted for race (White as reference), and aggre-
gate models were adjusted for sex (female as reference).
Finally, the outcome of interest was gleaned from a question
asking about cigarette use in the past 30 days, to which respon-
dents could answer: never use, have used but not in the last 30
days; 1–2 days; 3–5 days; 6–9 days; 10–19 days; 20–29 days; used
daily. These responses were combined into smoking statuses of
never-smokers (i.e., never used cigarettes), ever-smokers (have
used but not in the last 30 days), and current smokers (those
who reported any smoking in the past 30 days); this definition
of current smoking has been used with other national studies of
youth and young adult smoking (Ling, Neilands, & Glantz,
2009; Wechsler, Rigotti, Gledhill-Hoyt, & Lee, 1998). The smoking
status recoding process was based on an iterative category
reduction process through assessment of the parallel regression
assumption for ordered logistic regression analyses (see below).
Bivariate differences were assessed using chi-square tests of
independence by sexual orientation (e.g., bisexual vs. heterosexual)
and by gender and sexual orientation (lesbians vs. heterosexual
Nicotine & Tobacco Research, Volume 13, Number 12 (December 2011)
women). Based both on significant bivariate differences within
the sample and a robust literature that documents gender
and sexual orientation differences in violence victimization
(Faulkner & Cranston, 1998; FBI, n.d.; Herek, 2009; Russell,
Franz, & Driscoll, 2001) and discrimination (Hatzenbuehler
et al., 2010; Mays & Cochran, 2001), a series of stratified multi-
variate models were conducted based on sexual orientation and
gender by sexual orientation. Moreover, stratified models
allowed to better answer the driving research question of exam-
ining the heterogeneity within sexual orientation groups.
Multivariate ordered logistic regression models were used
to test the association between key independent variables and
the proportional odds of smoking status (never-smoker, ever-
smoker, and current smoker). Ordered logistic regression
procedures assert that an outcome with more than two cate-
gories has a hypothesized, but unquantifiable, hierarchical
order among categories (Long & Freese, 2006). The outcome of
smoking status in this analysis maintains that never-smokers
would represent an absolute zero use, that ever-smokers repre-
sent at least some use that is greater than never-smokers but less
than current smokers, and that current smokers represent the
most use. The proportional odds ratios are interpreted as the
likelihood of being in one of the three smoking status categories
that indicates more smoking according to the aforementioned
three-category ordinal structure (e.g., whether respondents who
indicate victimization have increased odds of being in a category
representative of more smoking when compared with a refer-
ence group of respondents who do not indicate victimization).
All multivariate ordered logistic models used the Brant test
as a diagnostic of the parallel regression assumption, which stip-
ulates that the specified model holds for all equations for k−1
ordered categories of the dependent variable, that is, requiring
the same slope for k−1 ordered categories but allowing for inter-
cepts to vary. Thus, a nonsignificant Brant test indicates that the
model exhibits the same slope but allows the intercepts to vary
across k−1 equations of the dependent variable categories (Long &
Freese, 2006). If violation of the Brant test occurred or small cell
sizes precluded calculation of Brant diagnostics, the categories
of the dependent variable were collapsed to better fit the data,
which ultimately resulted in a three-category dependent vari-
able that fit nearly all the stratified models.
Proportional odds ratios are reported with 95% CIs. Miss-
ing data analysis showed that, on all variables germane to the
models, none were missing more than 5%, thus listwise deletion
was used (Tabachnick & Fidell, 2007). All analyses were con-
ducted using Stata/SE version 11.1 (Stata Corp, 2009).
The analytic sample tended to be female (62.1%) and non-
Hispanic White (66.0%). The mean age was 20.1 years (SD =
1.6), recalling that the sample was truncated to only include
those in the age range of young adulthood (i.e., 18–24 years).
Since a random 5% subsample of heterosexual individuals was
used for this analysis, the percentages of sexual orientation
groups were made more equivalent than the original dataset
that included all heterosexual persons; however, they still com-
prised the largest percent (42%) within the analytic sample (see
Table 1). Significantly more men than women identified as gay,
while significantly more women than men identified as bisexual,
a finding that is typical among studies using sexual identity
measures of sexual orientation (Chandra, Mosher, Copen, &
Sionean, 2011; Laumann, Gagnon, Michael, & Michaels, 1994).
Bivariate analyses revealed that, globally, among sexual ori-
entation categories, significantly greater proportions of sexual
minority individuals indicated experiences of victimization and
discrimination when compared with their heterosexual coun-
terparts (see Table 1). Of particular note is that more than 37%
of gay/lesbian respondents indicated experiencing some form of
discrimination in the past 12 months compared with approxi-
mately 4% of heterosexual respondents. Furthermore, gay/
lesbian and bisexual respondents differed on some stressors. For
instance, gay/lesbian individuals reported significantly more
discrimination than their bisexual peers (p < .01), and bisexual
respondents reported significantly more fights and physical
assault (p < .01, respectively) than gay/lesbian respondents.
Table 1 also illustrates numerous differences in smoking.
Significantly fewer sexual minority individuals were never-
smokers when compared with their heterosexual peers, and,
conversely, more sexual minority individuals than heterosexual
individuals reported being ever-smokers and current smokers.
Gay and bisexual men did not differ in their smoking status
categories, but significantly less bisexual women than lesbians
reported never smoking (p < .05; see Table 2). From the high
prevalence of both smoking and victimization among sexual
minorities shown in Table 1, we constructed Figure 1 to depict
differences in experiences of victimization and discrimination
across smoking status among sexual minority individuals only.
Sexual minority current smokers experienced significantly more
fights, physical assault, verbal threats of harm, and sexual
assault than sexual minority never-smokers.
Adjusted ordered logistic models, stratified by sexual
orientation, showed that many stressors were associated with
increased proportional odds of smoking status (see Table 3).
However, despite having a much higher prevalence of experiencing
discrimination, gay/lesbian respondents who experienced dis-
crimination, when compared with lesbian/gay respondents who
did not experience discrimination, did not have significantly
increased odds of being in the current smoker category versus
being either in the never-smoker or ever-smoker categories.
Being involved in a physical fight had the strongest association
with smoking status across all groups except for the bisexual
group, and being physically assaulted was significant across all
groups, though the finding was not as robust among heterosexual
individuals. Additionally, model fit for heterosexual individuals
violated the parallel regression assumption, thus estimates for
that group should be viewed with caution.
Additionally, models stratified by sexual orientation gender
groups revealed distinct associations. Interestingly, for gay men,
no stressors were significantly associated with increased propor-
tional odds of being in the current smoker versus ever- or
never-smoker categories. After adjusting for race and binge
drinking, lesbians who were involved in a fight had twice the
proportional odds of being a current smoker compared with
lesbians who were not involved in a physical fight. Moreover,
bisexual women who were verbally threatened with harm or
who were sexually assaulted had a 57% and 37% increase in
proportional odds, respectively, of being a current smoker
Discrimination and violence with smoking
when compared with bisexual women who did not experience
verbal threats of harm or sexual assault.
First, consistent with prior research, we found that sexual
minorities in our sample had significantly higher (nearly two-fold)
current smoking status than heterosexuals (Lee et al., 2009). For
the year the NCHA sample data were collected, the national
current smoking (i.e., smoked ≥100 cigarettes in lifetime and
smoked every day or some days), prevalence was 21.8% for
people aged 18–24 years, with approximately 28.0% of men and
15.6% of women being current smokers within the age range of
18–24 years (Dube et al., 2010). In our original full sample, the
global current smoking prevalence (i.e., smoked in the last
30 days) was 16.3%, with 19.7% of men and 14.7% of women
being current smokers. Although direct comparison is not
possible due to differences in definition of current smoking, we
Table 1. Demographic Characteristics, Smoking Status, and Victimization by Sexual
Gay/lesbian (n = 1,825), n (%) Bisexual (n = 2,545), n (%) Unsure (n = 1,545), n (%)
(n = 4,286), n (%)
Verbal threat of harm
Note. aRacial categories are non-Hispanic.
bHeterosexual is reference category for pair-wise comparisons (e.g., gay/lesbian vs. heterosexual).
*p < .05.
Table 2. Smoking Status and Victimization by Sexual Orientation and Gender
Smoking status Victimization
smoke, n (%) Fight
of harmSexual assault Discrimination
Sexual orientation and gender
Heterosexual womena1,955 (69.8)
202 (10.5)* 154 (8.0)* 595 (30.9)*
75 (7.3)*60 (5.8)* 232 (22.5)*
119 (4.2)117 (4.2)
61 (5.5)* 51 (4.6)* 328 (29.5)
82 (14.2) 65 (11.3)* 215 (37.2)
52 (10.9)* 33 (6.9)
233 (16.0)110 (7.6)
50 (7.4)* 216 (31.8)* 65 (9.6)
Note. aReference category for pair-wise comparisons (e.g., gay men vs. heterosexual men, lesbians vs. heterosexual women, etc.).
*p < .05.
Nicotine & Tobacco Research, Volume 13, Number 12 (December 2011)
expected smoking prevalence to be lower than the general
population since respondents were enrolled in higher educa-
tion, which is known to protect against smoking (Escobedo,
Anda, Smith, Remington, & Mast, 1990).
By separating out gay/lesbian and bisexual groups, analyses
revealed a significantly higher risk profile among bisexuals, sug-
gesting variability between lesbian/gay and bisexual groups. Not
only did bisexual individuals report the highest prevalence of
all forms of violence victimization, they also had the highest
prevalence of being ever- and current smokers and the lowest
prevalence of being never-smokers. By analyzing data from the
California Health Interview Survey, Tang et al. (2004) found
that bisexual women had the highest prevalence of current
smoking among females, but bisexual men’s current smoking
prevalence was slightly less than gay men. Our results indicate
a similar pattern of smoking behaviors among this sample of
young adult bisexuals. Furthermore, literature suggests that
bisexual people may experience increased stress from being stig-
matized by both their heterosexual and gay/lesbian peers (Ross,
Dobinson, & Eady, 2010; Zinik, 2000). Consequently, salient
group differences between gay/lesbian and bisexual groups may
be overlooked as a consequence of combining them.
Interestingly, despite previous research with racial and
ethnic minority youth that demonstrates an association between
discrimination and smoking (Bennett et al., 2005; Wiehe et al.,
2010), discrimination was not significantly associated with
smoking among sexual minority groups in multivariate models,
even among the gay/lesbian group in which nearly 40% reported
past-year experiences of discrimination.
We hypothesize three potential reasons for this. First, as a
secondary analysis of data, measurement of discrimination was
limited to a single item and may have introduced measurement
error on at least two key areas of discrimination research: severity
and specificity. In terms of severity, Meyer (2003) outlines that
measuring discriminatory and prejudicial events is a difficult
task for multiple reasons, including recall bias, reference
period for the participant, framing the questions to adequately
assess research needs, and the subjective interpretation of dis-
criminatory events. That is, assessing the characteristics of a dis-
criminatory event may be more salient than simply whether or
not an event occurred, as well as assessing the perceived impact
or distress the incident caused a person. Thus, the unknown
nuances of a discriminatory event (e.g., severity, frequency,
personal distress) may better quantify the association of said
discrimination with health risk behaviors, such as smoking.
In terms of specificity, various operational definitions of
discrimination have been used among research with sexual
minority populations. For instance, some studies have used mea-
sures of personal experiences of specific sexual orientation–based
discrimination, ranging from multiple-item inventories (Mays &
Cochran, 2001; Meyer, Schwartz, & Frost, 2008) to single ques-
tions (Huebner, Rebshook, & Kegeles, 2004; Meyer, 1995; Ortiz-
Hernandez et al., 2009). Yet another way of defining discrimination
was developed in recent work by Hatzenbuehler et al. (2010),
who used presence of state-level constitutional bans on gay
marriage as a measure of discrimination. The present analysis
used a single item that asked about discrimination in general,
without the ability to assess either the specific sexual orientation–
based discrimination (e.g., gender-based, sexual orientation-
based, race-based, etc.) or the potential additive effects of multiple
forms of discrimination (e.g., someone who has both racial and
sexual minority statuses). For example, Mays and Cochran
(2001) found that, among sexual minority persons in their sam-
ple who reported discrimination, only 25% reported that they
perceived the discrimination was solely due to their sexual ori-
entation, whereas nearly 60% reported that the discrimination
was due to reasons other than their sexual orientation. The lack
Figure 1. Victimization and discrimination by smoking status, sexual minority, and heterosexual. 1 = Sexual minority includes lesbian, gay,
bisexual, and unsure. a = sexual minority, b = heterosexual.
Discrimination and violence with smoking
of specificity notwithstanding, the fact that nearly 40% of gay/
lesbian respondents—versus 4% of heterosexual respondents—
reported discrimination, is a notable difference despite the fact that
we could not assess the perceived cause of the discrimination.
Second, the mechanisms through which discrimination impact
health and health behaviors are likely very complex and may
vary depending on the outcome. For example, Hatzenbuehler
et al. (2010), who used presence of state-level constitutional
bans on gay marriage to operationalize discrimination, found
significant associations with some, but not all, mental health
disorders. The authors found that discrimination was signifi-
cantly associated with having any mood disorder but not with
having any anxiety disorder. Discrimination did not relate to
smoking status in the present study; however, discrimination
may relate with other facets of smoking behaviors, such as
intensity and smoking uptake, neither of which were assessed in
the present dataset. Thus, in addition to collecting more nuanced
measures of discrimination, collecting multiple measures of
smoking behaviors may also help to more clearly understand
how discrimination may associate with cigarette use.
Third, this sample of sexual minority young adults may be a
particularly resilient sample, even in the face of high prevalence
of discrimination. Sexual minority youth bear a disproportionate
burden of bullying, harassment, and victimization during pri-
mary, middle, and high school and the negative consequences
thereof, including depression, truancy, and dropout (Birkett,
Espelage, & Koenig, 2009; Bontempo & D’Augelli, 2002). Sexual
minority young people who make it to college may have shown
resilience in the face of such adversity, similar to Kimmel’s
notion of crisis competence, in which enduring injustices at
Table 3. Aggregate and Gender-Stratified Adjusted Proportional Odds of Smoking Status
by Sexual Orientation
AOR (95% CI)
AOR (95% CI)
AOR (95% CI)
AOR (95% CI)
n = 1,578
n = 3,846
Brant test, c2 (df), p
17.4 (15), .30 11.7 (15), .708.7 (15), .8930.5 (15), .01
n = 1,084
n = 509
n = 421
n = 1,308
Brant test, c2 (df), p
17.3 (14), .2424.0 (14), .05–c
11.4 (14), .65
n = 600
n = 1,738
n = 910
n = 2,538
Brant test, c2 (df), p
12.6 (14), .56 9.8 (14), .775.6 (14), .98 42.7 (14), <.00
Note. AOR = adjusted proportional odds ratio.
aModels adjusted for sex, race, binge drinking, and region of the United States.
bModels adjusted for race, binge drinking, and region of the United States.
cBrant test diagnostic could not be calculated due to small sample size.
*p < .05
Nicotine & Tobacco Research, Volume 13, Number 12 (December 2011)
younger ages may equip a person to handle subsequent incivil-
ities (Kimmel & Garnets, 1993). Thus, even though there was
high prevalence of discrimination reported in this sexual
minority sample, it is possible that the experiences of discrimi-
nation may not have been salient enough stressors to evidence
specifically in smoking behaviors.
The victimization measures used to operationalize socially
based stressors in this analysis revealed interesting associations
with smoking and raise several questions. First, in aggregate
models stratified by sexual orientation group, several forms
of victimization were associated with increased proportional
odds of being a current smoker over being an ever- or never-
smoker. These findings lend some support that, from the ecosocial
perspective of social production of health disparities (Krieger,
2001), sexual minority persons experiencing some forms of
victimization may have increased odds of smoking, and their
increased burden of victimization may help to explain disparately
higher smoking prevalence. More specifically, these findings can
be interpreted under the idea of negative affect regulation
among smokers, which posits that people smoke because they
believe that it mitigates stressed or distressed emotional states
(Carmody, Vieten, & Astin, 2007), and previous research with
college smokers has found support for such a theory of smoking
(Schleicher, Harris, Catley, & Nazir, 2009). In the present re-
sults, victimization may relate with smoking in that these events
may increase negative affect. However, interpersonal violence
and discrimination are only parts of the larger ecosocial frame-
work, in which there are multiple components creating chal-
lenging—if not hostile—environments for sexual minorities
(e.g., marriage equality issues, conflict with some religious insti-
tutions). Detailed investigation of these multilevel factors,
though a complex endeavor, may present more revealing path-
ways and interactions of how social inequality relates with
health risk behaviors, such as smoking.
In gender-stratified models, female sexual minority respon-
dents seemed to be the drivers behind the significant associa-
tions found in the aggregate models. Given the general nature of
the measures of victimization, it is possible that sexism could
have a role in the victimization experienced by sexual minority
females; however, we could not specifically assess the perceived
causes of discrimination. None of the victimization or discrimi-
nation measures were significantly associated with gay/unsure
males, and only verbally threatened with harm was significantly
associated with smoking among bisexual males. The reason for
these null findings could be attributable to multiple reasons,
including measurement issues, model specification, sampling
bias, or sample size. Lack of direction association between the
victimization and discrimination measures in the present study
do not necessarily stand as evidence that these factors are irrele-
vant. As mentioned before with the findings from Hatzenbuehler
et al. (2010), the relationship between discrimination and health is
complex. It is possible that socially based stressors impact smoking
through mediating pathways of depression and anxiety.
Interestingly, sexual assault was not associated with smoking
status among the gay/lesbian and unsure groups as it was in the
heterosexual group, in spite of significantly more gay/lesbian
and unsure individuals experiencing sexual assault than their
heterosexual peers. The lack of significant association between
sexual assault and smoking could be related to sample size. For
instance, gender-stratified models revealed that past-year sexual
assault was associated with smoking status among heterosexual
and bisexual women but not lesbians, even though lesbians and
heterosexual women had similar prevalence of sexual assault.
Given research demonstrating that female survivors of sexual as-
sault have increased risk of smoking (Acierno et al., 2000; Cloutier,
Martin, & Poole, 2002; Roberts et al., 2008), this lack of association
for lesbians may be an artifact of relatively smaller sample size, as
there were over four times as many heterosexual women.
An alternative reason for the lack of significance of sexual
assault and other victimization measures may be issues with
measurement of exposure to trauma versus measurement of
post-traumatic stress disorder (PTSD). Sexual assault is a trau-
matizing experience, but two reviews of the literature (Feldner,
Babson, & Zvolensky, 2007; Fu et al., 2007) noted that the
negative sequelae of traumas (i.e., PTSD) is more predictive of
smoking than the actual traumatic experience itself. The inabil-
ity to assess PTSD in our dataset may help explain the differen-
tial associations in sexual assault and smoking across the groups.
Further research is needed to examine the mechanisms underly-
ing why some forms of victimization may be associated with
increased smoking while others may not. Could more severe
forms of victimization (e.g., sexual assault) result in use of
stronger substances, such as alcohol or illicit drugs rather than
The drastically higher prevalence of smoking and victimiza-
tion among sexual minority young adults in this large national
sample clearly identify a population in need of targeted services,
yet there remains a paucity of research on the topic of preven-
tion and cessation efforts among sexual minority individuals
(Scout, Miele, Bradford, & Perry, 2006). Moreover, persons suf-
fering from PTSD fare worse at quitting smoking (Feldner et al.,
2007), and given the disproportionate burden of victimization
borne by sexual minority populations, more investigation is
needed to adequately assess whether victimization and resultant
PTSD may singularly or synergistically impact cessation.
The findings presented here must be qualified in light of
several limitations. First, causation between victimization and
smoking cannot be established, given the cross-sectional nature
of the data. Second, selection bias could be an issue given both
the self-selection of institutions to participate in the NCHA and
the self-identity measure of sexual orientation, which is more
likely to identify respondents who are comfortable to disclose
their sexual minority status. Third, the measures of victimiza-
tion and discrimination were general and did not assess whether
respondents associated their victimization as being due to their
minority status or other potentially salient factors of victimiza-
tion, such as gender, personality characteristics, and social
environmental context. Moreover, the time limitation of the
victimization measures (within the past 12 months), pre-
sumably excludes victimization or discriminatory events that
occurred earlier (e.g., a physical assault in high school) yet still
could have had long-lasting effects on risk behaviors, such as
smoking. Lastly, self-reported data—especially about sexual
assault—are more likely to be underreported.
It is important to emphasize that the present findings should
not be misinterpreted to suggest that sexual orientation is a risk
factor for smoking. Rather, our findings support that risks for
elevated smoking may stem from stressful events like discrimi-
nation and victimization, which sexual minority populations
Discrimination and violence with smoking
experience at disparately higher rates than their heterosexual
peers (Balsam, Rothblum, & Beauchaine, 2005; Mays & Cochran,
2001). As found in other studies, it is not simply being gay, but
the stressful events (e.g., homophobia and heterosexism) and
resulting emotional or psychological distress that can be predic-
tive of cigarette smoking (see Kassel et al., 2003).
In order to more confidently qualify and estimate sexual
minority tobacco health disparities, measures of sexual ori-
entation must be added to large, national probability-based
surveillance projects. Perhaps more importantly, critical
questions remain about the health consequences of higher
cigarette smoking. Previous research has found that sexual
minority young adults may experience increased odds of
acute respiratory infections (Blosnich, Jarrett, & Horn, 2010),
but little is known if sexual minorities experience increased
burdens of smoking-related chronic disease and premature
As research continues to address smoking disparities in this
minority population, the heterogeneity within sexual minority
categories is underexplored, and recent studies demonstrate
that nuances among sexual minority communities may help to
understand disparate health risk behaviors, such as smoking.
For instance, Willoughby, Lai, Doty, Mackey, and Malik (2008)
found that, in a sample of gay men, self-identified subgrouping
categories (e.g., Goths, Twinks, Bears) differentiated preva-
lence of current (i.e., once in past 30 days) smoking. Rosario,
Schrimshaw, and Hunter (2008) noted that among lesbians,
women who identified as butch (i.e., more masculine) tended to
smoke more than women who identified as femme (i.e., more
feminine). Clearly, there are details in the divisions, and future
studies should strive to innovatively seine and disentangle critical
information from the oft-combined lesbian, gay, and bisexual
identities in sexual minority research.
This work was supported partially by a 2010 Will Rogers
Institute doctoral fellowship through the Will Rogers Institute
to JRB. The project was also partially supported by a training
fellowship in the Summer Institute in LGBT Population Health,
under award number R25HD064426 from the Eunice Kennedy
Shriver National Institute of Child Health and Human Devel-
opment (NICHD) to JRB.
Declaration of Interests
The authors thank the American College Health Association
for use of the NCHA dataset. For their feedback on the ideation
of this project, the first author (JRB) also thanks dissertation
committee members Robert Anderson, Steven Branstetter,
Geri Dino, and Cindy Tworek. The content is solely the
responsibility of the authors and does not necessarily represent
the official views of the NICHD or the National Institutes of
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