Multiple Minority Stress and Behavioral Health Among Young Black and Latino Sexual Minority Men

Abstract

Purpose:

Young Black and Latino sexual minority men may experience multiple minority stressors, which may negatively impact behavioral health. To investigate this, longitudinal associations between multiple minority stressors and behavioral health outcomes were examined over a 2-year period.

Methods:

Data were from the Healthy Young Men's Cohort Study. The present study used five waves of data collected every 6 months from 2016 to 2019. Participants were young Black and/or Latino sexual minority men in Los Angeles, California (n = 448; aged 16–24). Participants self-reported their experiences of racial and homonegative discrimination, internalized homonegativity, alcohol use, and depressive symptoms. Latent growth curve models with time-varying covariates examined contemporaneous associations between minority stressors as well as general life stress and behavioral health measures.

Results:

After accounting for general life stress and demographic characteristics, racial discrimination was persistently associated with unhealthy alcohol use. Internalized homonegativity was associated with unhealthy alcohol use initially, but this association became non-significant over time. In models predicting depressive symptoms, racial discrimination was a significant predictor at early waves, and homonegative discrimination and internalized homonegativity emerged as significant predictors at later waves.

Conclusion:

These results help clarify which multiple minority stressors are more prominent in their relationship to young Black and Latino sexual minority men's unhealthy alcohol use and depressive symptoms. Interventions targeting multiple minority stressors may be needed at different times during young adulthood.

Introduction

Stigma and discrimination take many forms and have been linked to poor mental health and substance use among minority populations, including racial and ethnic minority^1,2 and sexual minority (i.e., lesbian, gay, bisexual, and queer [LGBQ]-identified) individuals.^3–5 Among young men, two of the most pressing public health problems are harmful alcohol use and mental health problems such as depression.⁶ Compared with young heterosexual men, a higher prevalence of both of these disorders exists among young sexual minority men.^3,7–11

Minority stress theory posits that distal minority stressors (e.g., overt discrimination experiences), proximal minority stressors (internalized homonegativity), and general life stress contribute to poor mental health and maladaptive coping behaviors such as substance use.³ However, research has only recently begun to examine how multiple minority stressors affect individuals who hold intersecting minority identities, such as young Black and Latino sexual minority men.

Minority stress research with sexual minority people of color has generally been framed in terms of risk and resilience.^12,13 According to the added risk perspective,^14,15 sexual minority people of color are at a greater risk of poor mental and physical health because they must contend not only with racial minority stressors (e.g., housing and job discrimination, racism within the LGBQ community), but with sexual minority stressors as well (e.g., machismo cultural values, homonegativity in religious communities).^16–18

As a member of a multiple minority group, these overt experiences of discrimination and stigma may lead to greater internalized stigma and homonegativity.¹⁹ However, some research provides greater support for the resilience perspective, which posits that due to previous exposure to racialized stigma, sexual minority people of color have developed greater resources for coping with sexual minority stigma than White sexual minority individuals.^13,15,20

Although previous research has tested competing hypotheses of risk and resilience among sexual minority people of color, this research has tended to examine stress processes between groups (by comparing White sexual minority people with sexual minority people of color). Less often have researchers compared multiple minority stress processes within racial/ethnic and sexual minority samples, which may provide additional insight into the lived experiences at the intersection of racism and homonegativism.

For example, research by Díaz et al. suggests that gay and bisexual Latino men may experience more homonegativity than racial discrimination, and that homonegativity alone may be positively associated with psychological distress.¹⁸ Other studies with sexual minority people of color report that homonegative discrimination, racial discrimination, and internalized homonegativity are independently associated with poor mental health in an additive manner.^21–23

Fewer studies have examined links between multiple minority stressors and alcohol use within samples of sexual minority people of color, particularly for men. One longitudinal study conducted with Black, Latino, and multiracial sexual minority men suggests that racial discrimination and its interaction with internalized homonegativity may result in greater heavy drinking.²⁴

Although research on multiple minority stress has grown in recent years, two important areas remain understudied. First, empirical research has rarely accounted for general life stress, or stressors unique to young Black and Latino sexual minority men,^25,26 despite the importance of general life stressors in minority stress theory.³ Second, aside from recent research examining sexual minority stress in isolation,^8,9 existing research has yet to examine how multiple minority stressors and their relations to behavioral health change over time.

The present study

The present study aimed at examining contemporaneous, time-varying associations that distal (experiences of racial and homonegative discrimination) and proximal (internalized homonegativity) minority stressors, as well as general life stress, have with unhealthy alcohol use and depressive symptoms over time. Our proposed model allowed us to determine not only which stressors influence these behavioral health outcomes, but also if and how the magnitude of these relationships changes over time. Given the lack of previous research in this area, we treat these analyses as exploratory and propose no a priori hypotheses.

Methods

Participants and procedures

Data were from the Healthy Young Men's Cohort Study (n = 448).²⁷ Recruitment included venue-based, social media, and participant and health clinic referrals. Eligible individuals were (1) between 16 and 24 years old at recruitment; (2) assigned male sex at birth; (3) identified as gay, bisexual, or uncertain about their sexual identity; (4) reported a sexual encounter with a man in the previous 12 months; (5) self-identified as African American/Black, Hispanic/Latino, or multi-racial/ethnic; and (6) lived in the Los Angeles area.

The present study used five waves of data collected every 6 months from 2016 to 2019. All participants provided written informed consent during face-to-face meetings; a waiver of parental consent/assent was obtained for participants younger than the age of 18. Participant retention was high, ranging from 87% to 90% at waves 2–5. This study was approved by the Children's Hospital Los Angeles Institutional Review Board.

Measures

General life stress

Participants indicated whether they experienced 32 stressful life events (yes = 1; no = 0) during the past 6 months. These included a subset of 27 items from Nott and Vedhara's scale for stressful events relevant to men who have sex with men living with HIV²⁸ (e.g., “You had problems or difficulties with a close friend”) and five additional stress events relevant to young men who have sex with men.²⁹ Item endorsements were summed to derive a total stress event score (range: 0–32). Scale reliability was high across waves (α = 0.72–0.81).

Racial discrimination

Participants completed 10 items assessing the frequency of racial discrimination experiences since childhood on a four-point scale ranging from never (0) to many times (3).¹⁸ Items included measures of both general racism and sexual racism (i.e., rejection of objectification based on race/ethnicity) (e.g., “How often did you hear sexual comments about your race or ethnicity?”). Items were summed at each wave (range: 0–30); scale reliability was high across waves (α = 0.85–0.90).

Homonegative discrimination

Participants completed six items measuring the frequency of homonegative discrimination experiences since childhood on a four-point scale, ranging from never (0) to many times (3).¹⁸ Items included measures of general homonegativity and strategies to manage anticipated homonegativity (e.g., “How often have you lost a job or career opportunity because of your sexuality?”). Subscales scores were calculated by averaging across all subscale items at each wave (range: 0–18). Although internal reliability was lower than recommended (α = 0.57–0.70), this scale is one of the very few developed among sexual minority men of color and thus carries strong construct validity not always found in other scales.¹⁸

Internalized homonegativity

The Revised Internalized Homophobia Scale³⁰ was used to measure internalized homonegativity. Participants rated their agreement with four items assessing affect toward sexual attraction and behavior (e.g., “Sometimes I feel guilty about having sex with men”), from strongly disagree (1) to strongly agree (4). Participant scale scores were averaged at each wave (range: 1–4), with higher scores indicating more internalized homonegativism. Scale reliability was high across waves (α = 0.87–0.93).

Unhealthy alcohol use

Participants completed the Alcohol Use Disorders Identification Test.³¹ Participants first reported how often they drank alcohol in the past 6 months. Participants endorsing any drinking reported how many drinks they have on a typical drinking day and how often they engage in six alcohol-related behaviors (binge drinking, trouble stopping drinking, failed responsibilities, needed drink in the morning, drinking-related guilt, and memory loss), with options never (0) to daily or almost daily (4) (α = 0.83–0.87). Items for this continuous measure were summed, with possible values ranging from 0 (never drank in the past 6 months) to 40.

Depressive symptoms

Depressive symptoms were measured by using the 6-item depression subscale from the 18-item Brief Symptom Inventory.³² Participants reported how often they experienced six depressive symptoms in the past 7 days on a scale ranging from never (0) to always (4). Scores were summed, with higher scores indicating more depressive symptoms (range: 0–24). Depressive symptoms were measured at every wave, and reliability was consistently high (α = 0.84–0.89).

Covariates

Participant race/ethnicity, age, sexual identity, and education level are reported in Table 1. Race/ethnicity included three categories of Latino (not Black), Black (not Latino), and multi-racial/ethnic. Participants reported their sexual identity as homosexual/gay, bisexual, other same-sex attracted, pansexual, heterosexual, unsure/questioning, other write-in, and don't know. Sexual identity was dichotomized (homosexual/gay coded as 1; heterosexual, bisexual, other same-sex, pansexual, unsure/questioning, other, and don't know coded as 0); participant education was also dichotomized (high school or less coded as 1).

Table 1.

Participant Characteristics at Baseline

Variable	M (SD) or N (%)
Age	22.3 (2.01)
Race/ethnicity
Black (not Latino)	94 (21.0%)
Latino (not Black)	264 (58.9%)
Multi-racial/ethnic	90 (20.1%)
Sexual identity
Homosexual/gay	334 (74.6%)
Heterosexual (straight)	1 (0.2%)
Bisexual	74 (16.5%)
Other same sex	20 (4.5%)
Pansexual	11 (2.4%)
Unsure/questioning	4 (0.9%)
Other	2 (0.4%)
Don't know	2 (0.4%)
Education
Less than high school	20 (4.5%)
High school graduate/GED	129 (29.0%)
Vocational school	16 (3.6%)
Some college	178 (40.1%)
Completed associate's degree	22 (5.0%)
Completed bachelor's degree	69 (15.5%)
Some graduate school	7 (1.6%)
Completed graduate school	3 (0.7%)
Positive HIV status	51 (11.4%)
Unhealthy alcohol use (AUDIT score)	6.58 (5.78)
Depressive symptoms	4.0 (4.09)
Stressors
General stress	7.48 (4.23)
Homonegative discrimination	2.71 (2.64)
Racial discrimination	6.76 (5.85)
Internalized homonegativity	1.65 (0.71)

The actual range of participant responses is as follows: unhealthy alcohol use (AUDIT scores) range = 0–31; Depression range = 0–24; general stress range = 0–22; homonegative discrimination range = 0–16; racial discrimination range = 0–29; internalized homonegativity range = 1–22. HIV status was obtained via a whole blood finger stick. n = 1 participant was missing all variables, n = 4 participants were missing internalized homonegativity values, and n = 4 participants were missing education data; these participants were excluded from further analyses.

AUDIT, Alcohol Use Disorders Identification Test; GED, general educational diploma; M, mean; SD, standard deviation.

Statistical analysis

A taxonomy of latent growth curve models with time-varying covariates was used to examine the associations between perceived stressors and behavioral health outcomes.³³ First, unconditional latent growth models for unhealthy alcohol use and depressive symptoms were fit to determine the functional form of the data. Models specifying random intercepts and random linear slopes (vs. fixed) were tested by using negative two log-likelihood ratio tests. Next, demographic control variables were added as predictors of the latent growth factors. Finally, in a series of models we introduced our time-varying covariates: general stress, racial discrimination, homonegative discrimination, and internalized homonegativity. At each time point, stressor variables were regressed onto the contemporaneously observed outcome variable.

We first introduced the time-varying covariates as constrained predictors (e.g., effects constrained to be equal over time); then, we tested this model against one where the time-varying covariates were unconstrained (e.g., freely estimated at each time point). Differences in negative two log-likelihood ratio tests were used to determine whether a constrained versus freely estimated model best fit the data. After testing each stressor, final models included each time-varying covariate as constrained or unconstrained effects.

Doing this allowed us to test which stressors have a consistent, stronger, or weaker influence on outcomes over time. All models utilized full information maximum likelihood estimation, which has been shown to be superior to listwise deletion when data are missing at random. None of the stressor variables were strongly correlated with one another at the bivariate level, suggesting that multi-collinearity was not a concern (Supplementary Table S1).

Results

In both the unhealthy alcohol use and depressive symptoms models, the better fitting model was one in which the slopes were allowed to be freely estimated (e.g., random slopes). Model fit was excellent for unhealthy alcohol use (Comparative Fit Index [CFI] = 0.99, Tucker-Lewis Index [TLI] = 0.99, Root Mean Square Error of Approximation [RMSEA] = 0.04, χ² = 20.05, p = 0.04; see Supplementary Table S2) and depressive symptoms (CFI = 0.97, TLI = 0.97, RMSEA = 0.06, χ² = 20.5, p = 0.003; see Supplementary Table S3). The final model of unhealthy alcohol use suggested a significant intercept and slope factor, with a slight decrease in unhealthy alcohol use over time (intercept = 6.54, standard error [SE] = 2.49, p < 0.01; slope = −0.26, SE = 0.07, p < 0.01).

A similar trend emerged for depressive symptoms, with a significant intercept and slope factor and a slight decrease in depressive symptoms over time (intercept = 3.99, SE = 0.18, p < 0.01; slope = −0.17, SE = 0.05, p < 0.01).

Effect of stressors on unhealthy alcohol use and depressive symptoms

Results of the final model of unhealthy alcohol use are displayed in Figure 1 and Supplementary Table S4. In terms of our covariates, the results indicated that Black participants, compared with Latino participants, had lower unhealthy alcohol use initially (intercept = −1.64, SE = 0.73, p = 0.027), but no effects for race/ethnicity emerged for the slope. For age, older participants reported a higher intercept (b = 0.34, SE = 0.16, p = 0.03), but a steeper decrease in unhealthy alcohol use over time (b = −0.10, SE = 0.04, p = 0.009).

FIG. 1.

Final time-varying covariate model for unhealthy alcohol use. Effects are presented as unstandardized beta regression coefficients and standard errors [B(SE)]; Boxes with “—” indicate nonsignificant effects; all other values indicate significant, contemporaneous, effects (p < 0.05). The effects of each time-varying covariate were tested to determine whether constrained (i.e., effects are stable over time) or freely estimated effects (i.e., effects allowed to vary over time) fit the data best. Alc_0-4: observed AUDIT scores at each timepoint; Alc_Int: latent intercept factor (representing the average AUDIT score at baseline); Alc_Slp: latent slope factor (representing an overall decrease in alcohol use over time). AUDIT, Alcohol Use Disorders Identification Test; SE, standard error.

For the time-varying covariates, the best fitting model was one in which general stress, homonegative discrimination, and racial discrimination were constrained to be equal over time, and internalized homonegativity was allowed to be freely estimated. Both general stress and racial discrimination had significant, consistent, relationships with unhealthy alcohol use over time. Although homonegative discrimination was also constrained to be equal over time, it did not emerge as a significant predictor of unhealthy alcohol use. For internalized homonegativity (freely estimated), we see strong effects on unhealthy alcohol use early on that become nonsignificant beginning at Time 3.

Figure 2 displays the final results of the depressive symptoms model (also see Supplementary Table S4). Race/ethnicity and age were not significantly associated with depressive symptoms growth factors. For our time-varying covariates, unlike unhealthy alcohol use, the best fitting model for depressive symptoms included each of the stressor variables being freely estimated. Similar to unhealthy alcohol use, general life stress had a relatively consistent effect on depressive symptoms over time, although actual estimates varied slightly.

FIG. 2.

Final time-varying covariate model for depressive symptoms. Effects are presented as unstandardized beta regression coefficients and standard errors [B(SE)]; Boxes with “—” indicate nonsignificant effects; all other values indicate significant, contemporaneous effects (p < 0.05). The effects of each time-varying covariate were tested to determine whether constrained (i.e., effects are stable over time) or freely estimated effects (i.e., effects allowed to vary over time) fit the data best. Dep_0-4: observed BSI-18 scores at each timepoint; Dep_Int: latent intercept factor (representing the average depressive symptom score at baseline); Dep_Slp: latent slope factor (representing an overall decrease in depressive symptoms over time). BSI-18, 18-item Brief Symptom Inventory.

Unlike the unhealthy alcohol use model, racial discrimination had a relatively robust effect on depressive symptoms over the first three time points, which eventually faded, not having an effect on depressive symptoms over the last two time points. Both homonegative discrimination and internalized homonegativity did not have an effect on depressive symptoms early on. However, over the last three time points, homonegative discrimination had a significant, positive effect, and internalized homonegativity had an increasing effect on depressive symptoms.

Discussion

Due to converging systems of racism and homonegativism, Black and Latino young sexual minority men may be exposed to multiple forms of oppression, manifested as greater discrimination and internalized stigma. Although previous literature has tended to frame multiple, intersecting identities among sexual minority people of color as harbingers of greater risk or resilience,^13,15 the present study used a within-group analysis to explore the relative effect of multiple minority stressors on two behavioral outcomes relevant for this population (unhealthy alcohol use and depressive symptoms). We further explored the extent to which these minority stressors vary over a 2-year period during young adulthood.

Except for internalized homonegativity, the influences of stressors on alcohol use appear to be quite stable over time. Among the minority stressors, racial discrimination, but not homonegative discrimination, was persistently associated with unhealthy alcohol use. This is consistent with research demonstrating positive associations between racial discrimination and harmful alcohol use among heterosexual African-American samples¹ and Black and Latino sexual minority men.²⁴

However, our results run counter to a recent study examining the role of multiple minority stressors on illicit drug use among lesbian, gay, bisexual, transgender, or queer people of color, which found that homonegative discrimination was related to illicit drug use, but racial discrimination was not.¹⁹ Our results are consistent with previous research showing that internalized homonegativity plays an important role in substance use behaviors, in addition to these distal minority stressors.^19,24

It is helpful to interpret these results with the perspective that unhealthy alcohol use is a means to cope with various kinds of stressors.^4,34–36 Thus, our results suggest that young Black and Latino sexual minority men may engage in unhealthy alcohol use more as a means to cope with racial discrimination and general life stress than with homonegative discrimination. Minority stress theory suggests that identity prominence may moderate associations between minority stressors and behavioral health outcomes.^3,37,38 Therefore, for some young Black and Latino sexual minority men, it may be the case that a greater prominence of one's racial/ethnic identity results in a stronger need to use alcohol to cope with racial discrimination than homonegative discrimination.

Our results also suggest that alcohol interventions may be more effective for this population if they encourage alternative ways of coping with the persistent impact of racial discrimination and general life stress, for example, by fostering social and community supports.^17,39 In addition, as internalized homonegativity had an initial association with unhealthy alcohol use, alcohol interventions that reduce internalized homonegativity may be needed for younger men, or those who have not yet developed a healthy sexual identity.^40,41

For depressive symptoms, contemporaneous associations with minority stressors appear to be more variable over time. As in the alcohol model, general life stress was persistently associated with depressive symptoms (except at Time 3). This is consistent with a large body of research showing that general life stressors are correlated with depressive symptoms^18,42,43 and further supports the recommendation that general stressors be accounted for in minority stress models.³

In addition, associations between racial discrimination and depressive symptoms were present, but in later waves these associations faded, and homonegativity (both enacted discrimination and internalized) emerged as a more salient predictors of depressive symptoms. Therefore, it appears that both racial and homonegative discrimination are associated with greater depressive symptoms for Black and Latino sexual minority men, but at different times.

It is possible that Black and Latino sexual minority men may habituate, or actively resist, racial discrimination during their young adulthood development, thereby attenuating the relationship between racism and depressive symptoms. This is partially consistent with the resilience perspective, which assumes that sexual minority people of color are better able to cope with sexual-minority related stress because of their prior exposure to racial discrimination.¹³

However, it may be that men who successfully mitigate the negative effects of racial discrimination on depression may be confronted with the task of mitigating the negative effects of homonegativity; a task that may require different coping strategies to resolve, given that one's sexual minority status may be a more concealable identity than one's racial/ethnic identity.⁴⁴ It follows that interventions to relieve depressive symptoms will likely be more effective if tailored to the unique needs of sexual minority men of color, namely, by minimizing the harmful effects of racial and sexual minority-based discrimination and their consequences (i.e., internalized homonegativity), in addition to other life stressors. Mental health practitioners and community advocates should also keep in mind that such interventions may be needed at different times during young adulthood.

Limitations

Our study has a number of limitations. Some of these relate to measurement. For example, our analysis did not include a proximal measure of internalized racism, as others have done,^19,24 and our measure of general life stress included many different types of stressors (relationship and employment problems, HIV-related stress) that may be examined as common factors in future research.

Further, the measure of homonegative discrimination had low internal consistency, which may have resulted in an underestimation of the effects between homonegative discrimination and behavioral health outcomes.⁴⁵ More broadly, we acknowledge that young Black and Latino sexual minority men in the United States are a heterogeneous population that differ in their nation of origin, immigration status, level of acculturation, and socioeconomic status.⁴⁶ Further, our analysis is limited by the use of an “additive” (rather than an “interactional”) approach to examine multiple minority stress.^47–49

Conclusion

Given that this is one of the first studies to examine the dynamic effects of multiple minority stressors during young adulthood, more research is needed. This may include more research from diverse geographic locations that explores the intersections of these identities, stigma, and behavioral health.⁵⁰ Qualitative research can shed light on the context in which multiple minority stress experiences occur,¹⁶ and quantitative research using moderation and mediation techniques can test complex hypotheses regarding the intersection of multiple minority stressors and identities.²⁴

Future research should also examine the factors that promote resilience against multiple minority stressors, such as coping and social support resources,¹³ and the potential role that brain maturation has in mitigating the effects of minority stress during emerging adulthood. Other research directions are to investigate the use of other commonly used substances among sexual minority men (i.e., cannabis and stimulants). Ultimately, research should inform broader societal interventions to reduce multiple forms of stigma and oppression, and tailored interventions for sexual minority people of color to mitigate their downstream effects.

Authors' Contributions

G.T.D. conducted the literature review, wrote the introduction and discussion sections, and edited the final draft of the article. J.P.D. performed data analysis, wrote the methods and results, and reviewed and edited the article. A.S. contributed to the conceptualization and early draft of the article, performed data analysis, and reviewed and edited final drafts. E.K.L. contributed to the literature review, the interpretation of results, and the reviewing and editing of the article. D.P. contributed to the literature review, edited and revised the article, and approved the final draft. M.D.K. was responsible for the design, data collection, and procuring funding for the larger study from which the data were used, and for revising and approving the final draft. All co-authors reviewed and approved the article before submission.

Disclaimer

The National Institutes of Health had no role in the study design, collection, analysis, or interpretation of data, writing the article, or the decision to submit the article for publication. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

M.D.K. is supported by the National Institute on Drug Abuse (U01 DA036926). E.K.L. is supported by the National Institute of Mental Health (T32 MH020031).

Supplementary Material

Supplementary Table S1

Supplementary Table S2

Supplementary Table S3

Supplementary Table S4