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Minority stress, depression, and cigarette smoking among Chinese gay versus bisexual men: a two-group structural equation model analyses

Abstract

Background

Literature in the West suggested that bisexual men have a higher smoking rate compared to gay men. Data on patterns of smoking among gay and bisexual men are limited in Eastern Asian countries like China. This study examined the cigarette smoking prevalence for gay versus bisexual men in China and their unique minority stress - smoking pathways.

Methods

Between September 2017 and November 2018, we surveyed a convenience sample of 538 gay men and 138 bisexual men recruited from local sexual minority organizations in four metropolitan cities in China (i.e., Beijing, Wuhan, Nanchang, and Changsha). Measures included sexual orientation, sociodemographics, theory-based minority stressors, depressive symptoms, and past 30-day cigarette smoking. Two-group (gay men vs. bisexual men) structural equation modeling (SEM) was used to test possible distinct mechanisms between theory-based stressors, depressive symptoms, and cigarette smoking among gay men and bisexual men, respectively.

Results

The mean age of participants was 26.51 (SD = 8.41) years old and 76.3% of them had at least a college degree. Bisexual men reported a higher rate of cigarette smoking compared to gay men (39.9% vs. 27.3%). Two-group SEM indicated that the pathways for cigarette smoking were not different between gay and bisexual men. Higher rejection anticipation was associated with greater depressive symptoms (standardized β = 0.32, p < .001), and depressive symptoms were not associated with cigarette smoking.

Conclusions

Minority stress, specifically rejection anticipation, may be critical considerations in addressing depressive symptoms, but not smoking, among both gay and bisexual men in China.

Peer Review reports

Background

China has one of the highest burden of smoking in the world [1]. Each year, approximately 1,000,000 people in China die prematurely from smoking-related diseases [2, 3]. Men represent a disproportionate number of China’s smokers. According to the 2015 China Adult Tobacco Survey, on average, 51.4% Chinese adult (aged 15 and older) men were current cigarette smokers, while 2.7% of adult women smoke [4]. While several Chinese metropolitan cities have passed increasingly progressive municipal-level tobacco control regulations, the prevalence of males who currently smoke cigarettes in these localities is still high, ranging from 32.7 to 44.5% [5].

Data from Canada, the U.S. and Australia has extensively studied tobacco use among sexual minority populations – or lesbians, gays, and bisexuals (LGB). This literature has largely indicated high rates of cigarette use among sexual minorities compared to the general populations [6,7,8,9,10,11,12]. While the literature regarding smoking among sexual minorities in Eastern Asian countries like China is limited, some studies have similarly shown increased smoking prevalence in this population. A 2015 study conducted in Shanghai, China found that gay and bisexual boys were more likely to smoke cigarette compared to heterosexual boys (OR = 2.2), while lesbian and bisexual girls reported less any prior cigarette smoking compared to heterosexual girls (OR = 0.7) [13]. Another study focusing on Chinese adult gay and bisexual men indicated a cigarette smoking prevalence of 66%, [14] approximately 15% higher than the national average and 22–33% higher than the city-level prevalence [5]. Gay and bisexual men represent a large subgroup in China. It was estimated that the total population of Chinese gay and bisexual men is around 18 (10.2–25.4) million [15]. However, limited research has focused on the heightened smoking rates among this large population of gay and bisexual men in China.

Minority Stress Theory (Meyer, 1995; 2003) is a framework for examining and understanding mechanism of high-risk behaviors in sexual minorities. Specifically, Minority Stress Theory views hostile social conditions as causes of stress for sexual minority groups [16, 17]. Meyer (1995; 2003) suggested that minority stress can take the forms of distal minority stress, or external processes and experiences faced by sexual minorities, including discrimination experiences; and proximal stress, or internal processes and experiences such as outness, rejection anticipation, identity concealment, and internalized homophobia [16, 17]. These stressors can exacerbate mental health problems and consequently lead to increased health risk behaviors [18, 19]. Empirically, numerous studies have shown that these minority stressors are positively associated with psychological distress and health risk behaviors such as tobacco use [9, 20,21,22,23,24]. For example, Burgess et al. (2008) pointed out that distal stressors such as discrimination experience was associated with greater likelihood of depression, anxiety, greater perceived needs for mental healthcare, and more frequent use of mental health services [25]. Others focusing on proximal stressors like internalized homophobia or outness showed that these stressors were signification predictors of mental health problems [26,27,28,29]. However, few studies have focused on minor frustrations and annoyance such as everyday discrimination that could produce long-lasting feelings of rejection [30], and one main reason for sexual minorities to use substance including cigarettes was the feeling of rejection [31]. As multiple stressors increasingly challenge an individual’s coping capabilities, substance use such as smoking may serve as a coping strategy for sexual minorities who experience “minority stress” [10, 16]. Conversely, positive coping such as resilience and coping resources such as social support were found to buffer the negative effects of minority stress on adverse health outcomes [32,33,34,35,36].

Contextual factors such as culture can be specific manifestation of Minority Stress Theory. Researchers suggested that Chinese culture is more collectivism that weights interpersonal bonds over individual themselves and emphasized a greater responsibility to the collective goods [37]. Lai (2010) and others believe part of the Chinese culture is influenced by Confucianism, a Chinese ancient philosophy that strongly emphasizes duty, obedience, filial piety, and certain ethical and moral values [38, 39]. In research on Chinese contemporary sex norms, Li (2006) outlined that, cultivated in a collective culture, Chinese society sees the most commonly conducted behaviors as meeting the moral standards while less frequent behaviors would be viewed as ‘abnormal’ and ‘unethical’ [40]. Same-sex marriage is still illegal in China [41]. As a result, a sexual minority who does not act like his or her peers by not getting married at a certain age will become a concern and shame to the whole family for being deviant from the majority, and for failing to continue the family line [42]. Wang et al. (2015) found that gay/bisexual men in a qualitative study described constant pressure from family, social, and workplace to have a female partner, and they also stated the difficulties to establish stable same-sex relationships [43]. In 2020, researchers qualitatively examined minority stress among 24 Chinese sexual minority men and found that all participants suggested that Chinese culture (and cultural norm) functioned as source and context of minority stress [44]. Earlier study on Asian sexual minorities found same-sex behaviors would only be tolerant when they fulfill family duties including eventual heterosexual marriage [45]. In China, if men get older but are not married, family members, coworkers, peers and community acquaintances would start inquiring about their reasons for not getting married and even consider them as abnormal [46].

To date, the majority of research examining tobacco use through the lens of Minority Stress Theory has been done in North America [6, 47, 48]. In Southeast Asian countries, Minority Stress Theory was also used to inform study examining depression, suicide, and addictive behaviors among sexual minorities in Indonesia, Malaysia, Myanmar, Thailand, and Vietnam [49]. In Eastern Asian countries like China, the Minority Stress Theory has been almost exclusively applied to predicting physiological outcomes [50,51,52,53]. Although few Chinese studies have explicitly examined the mechanism between minority stress and cigarette use [13, 14, 54], qualitative research has suggested that Chinese sexual minority men may use substances to relieve the stress of hostile social stigma, as well as familial and cultural pressures [55]. Therefore, it is important to empirically examine specific pathways through which minority stressors might influence cigarette use among Chinese sexual minorities, particularly gay and bisexual men.

Particularly relevant to the current study, not all sexual minorities experience the same stressors or related health risks. In North America, evidence across studies indicates significant inter-group difference across sexual minority subgroups that bisexuals are at increased risk for mental health problems and substance use compared to monosexuals (i.e., gay/lesbians and heterosexuals) [47, 56]. Such intergroup differences between bisexuals and monosexuals can be explained by the unique minority stressors that bisexuals experience. For instance, bisexually-identified individuals might often be assumed to be gay/lesbian or heterosexual depending on the sex of their partners [56]. Thus, bisexual people might anticipate others to dismiss their bisexual identity; this anticipation may contribute to depressive symptoms and mental distress [56, 57]. Other research by Sweet and Welles (2012) indicates that bisexual men may experience significantly more adverse childhood experiences compared to gay men [58]. However, in contrast to the growing body of literature examining the heterogeneity of sexual minority stressors and subsequent psychological and health behavior risks across sexual minority subgroups in North America, very little is known about this topic in China. One 2015 paper by Lian et al. in China studied smoking among sexual minority youth and actually found the reverse pattern, that male bisexual and heterosexual youth shared similar smoking patterns while gay youth reported higher smoking rates compared to heterosexual counterparts [13]. Lian and colleagues believed that bisexual youth in China might be less involved with LGB activities with higher risk for smoking exposure (e.g., pride events), compared to gay youth; or, bisexual youth in China might be less likely to cope minority stress with smoking [13].

To date, it is unclear whether significant heterogeneity exist between Chinese gay and bisexual men regarding their minority stress experiences and related health risks. This study aimed to contribute to the literature by examining the prevalence of cigarette smoking in a sample of Chinese gay and bisexual men and their distinct minority stress - smoking pathways, using the two-group (gay vs. bisexual men) structural equation modeling (SEM). This research is critical, as the exploration of minority stressors and pathways among subgroups of sexual minority men may help advance our understanding of cigarette use behavior among high-risk populations in China and develop effective tobacco cessation interventions.

Methods

Study population and data collection

The authors obtained data from a survey study focusing on health risk behaviors of Chinese sexual minority men conducted by School of Health Sciences, Wuhan University, China. Details of the survey methodology have been published elsewhere [58]. Briefly, between September 2017 and January 2018, we collected baseline survey data of 755 self-identified gay and bisexual men using venue-based sampling from college campus-based sexual minority-serving organizations in four cities, namely Beijing, Wuhan, Nanchang, and Changsha, as these cities have high concentration of LGBT populations. We collected these data using a questionnaire developed by our research team for the purposes of this study (see Additional file 1). These data are among the most recent data available regarding tobacco use among sexual minority men in China. This convenient sample was mainly comprised of urban, well-educated, and high-income gay/bisexual men, and might not be representative to all sexual minority men. After screening for eligibility (self-identified as gay/bisexual men and aged 16 years or older), participants were given a brief explanation of the survey’s purpose. Informed consent was obtained from every participant. Each participant received a one-time compensation of 50 Chinese RMB (approximately $8 US dollars) for their time. For this study, we excluded 79 (10.5%) participants who reported “heterosexual/unsure/other” sexual orientation. Participants involved in tobacco cessation programs, including HIV-positive individuals who were linked to HIV care and provided with behavioral intervention (i.e., tobacco cessation services) [59], were excluded from this study. The analytical sample size for this study was 676. This study was approved by the Institutional Review Board (IRB) of Wuhan University Medical School, China.

Measures

Primary outcome: cigarette smoking

Participants were asked, “During the past 30 days, on how many days did you smoke cigarettes? Little cigars or cigarillos? Traditional pipe? Chewing tobacco? E-cigarettes? Hookah?” Given that fewer than 10 participants reported on alternative tobacco use (i.e., little cigars or cigarillos, traditional pipe, chewing tobacco, e-cigarette, and hookah), this study only focused on the past 30-day cigarette smoking outcome, dichotomized as “no” versus “any smoking.”

Primary grouping variable: sexual orientation

Sexual orientation was assessed by asking, “Is your sexual orientation: heterosexual; gay or homosexual; bisexual; or unsure?” All responses were coded dichotomously (0 = gay and 1 = bisexual).

Sociodemographic characteristics

Participants were asked to provide sociodemographic information, including age, education (high school/below vs. college/above), place of origin (urban vs. rural), employment (dummy coded into student, employed, and unemployed), marital status (unmarried/divorced vs. married), monthly income (≤ 3000 RMB [73 USD] vs. > 3000 RMB, note that the minimum monthly wage ranges between 1580 and 2000 RMB in 4 sampled cities [60]), and nature of their health insurance (yes vs. no/unsure).

Depressive symptoms

Depressive symptoms were hypothesized as the pathway between minority stressors and cigarette smoking (Fig. 1) and were assessed with the Center for Epidemiological Studies Depression (CES-D) scale [61]. The CES-D is a well-established and widely used [62] 20-item scale designed to measure depressive symptoms experienced by the individual within the past week, and its Chinese version has been validated [63, 64]. Items were answered on a 4-point scale ranging from 0 = less than a day or never to 3 = 5–7 days. The Cronbach’s alpha was 0.89.

Fig. 1
figure1

Hypothesized conceptual model of minority stressor to cigarette smoking among gay and bisexual men in China

Minority stressors

Informed by Minority Stress Theory [16, 17], we measured distal minority stressors (everyday discrimination), proximal minority stressors (outness, rejection anticipation, identity concealment, and internalized homophobia), general stressors (adverse childhood experiences), and stress-moderating factors (social support and resilience).

Everyday discrimination was assessed using the Everyday Discrimination Scale [65]. This scale asks about the frequency of 9 types of hassles and prejudice events that sexual minority people may encounter. This 9-item scale is rated on a 6-point Likert scale with response options of 1 = happens daily to 6 = never happened. All responses were reverse coded and averaged to create a mean score, with higher scores indicating severer everyday discrimination. The Cronbach’s alpha coefficient was 0.94 for this scale.

Outness was assessed by asking respondents “Have you ever ‘come out’ to anyone?” All responses were coded dichotomously (0 = no and 1 = yes).

Rejection anticipation was assessed with a scale which was originally used to assess stigma of mental illness [66]. Later, this scale was modified and adapted by Forst et al. (2015) for assessing sexual minority’s state of hypervigilance and worry about being rejected [21]. This 6-item scale is rated on a 5-point Likert scale, ranging from 1 = applies very strongly to 5 = does not apply at all. All responses were reverse coded and averaged to create a mean score, with higher scores indicating higher expectation of rejection. The Cronbach’s alpha of this scale in this study was 0.88.

Identity concealment was assessed using a subscale on nondisclosure developed and validated by Testa et al.(2015) [67]. This 6-item scale asks about the intentions and behaviors of sexual minority individuals to avoid disclose their sexual minority identities. This scale is rated on a 5-point Likert scale, ranging from 1 = applies very strongly to 5 = does not apply at all. All responses were reverse coded and averaged to create a mean score, with higher scores indicating greater identity concealment. The Cronbach’s alpha was 0.91.

Internalized homophobia was assessed using the Internalized Homophobia Scale which was originally developed by Martin and Dean (1987) [68] and further modified and validated by Forst et al. (2009; 2015) [21, 69]. This scale asks about the negative attitudes sexual minorities hold against their own sexual identities. This 8-item scale is rated on a 4-point Likert scale, ranging from 1 = never to 4 = always. Responses were averaged to create a mean score, with higher scores indicating greater internal homophobia. The Cronbach’s alpha was 0.89.

Adverse childhood experiences (ACEs) was assessed using a 10-item ACEs index developed by the U.S. Centers for Disease Control and Prevention [70, 71]. This index asks about the physical and mental abuse and traumatic experiences of participants prior to 18 years old. Participants answered 0 = no or 1 = yes to each item. Total score of all responses was summed; higher scores indicate more ACEs. The Cronbach’s alpha was 0.63.

Social support was assessed with the Multidimensional Scale of Perceived Social Support, [72] which measures perceived support from family, friends, and significant others. This 12-item scale is rated on a 7-point Likert scale, ranging from 1 = very strongly disagree to 7 = very strongly agree. The total score of this scale was calculated for each participant, with higher scores indicating more social support. The Cronbach’s alpha was 0.94.

Resilience was assessed with the 10-item Connor-Davidson Resilience scale [73, 74]. This scale is a measure of stress coping capabilities. It is rated on a 5-point Likert scale ranging from 1 = not true at all true to 5 = true nearly all of the time. The responses are summed to derive a total score, with higher scores indicating more resilience. The Cronbach’s alpha was 0.95.

Please see Additional file 1 for more details about the survey questionnaire used in this study.

Statistical analysis

Univariate analyses were conducted to examine the distribution of each variable. ANOVA and chi-square tests were conducted to assess the bivariate relationships of cigarette smoking outcome and sexual orientation to socio-demographic and psychosocial variables. We also examined the multi-collinearity between all variables. In consideration of study power, we excluded selected sociodemographic variables (i.e., education, marriage, monthly income, and health insurance) from the modeling analyses, as these variables either were not associated with the outcome or showed considerable collinearity (data not shown).

Next, we conducted sequential logistic regressions to identify significant associations between predictors and cigarette use to inform the approach to the structural equation models (SEMs). Specifically, we assessed the effects of sexual orientation on cigarette use in following models: (1) only included sexual orientation as predictor; (2) added other sociodemographic predictors (i.e., age, place of origin, and employment); (3) added psychosocial risk factors (i.e., everyday discrimination, outness, rejection anticipation, identity concealment, internalized homophobia, and ACEs), and (4) added psychosocial protective factors (i.e., social support and resilience). Collinearity between sexual orientation and all psychosocial factors was examined using Condition Index (CI) derived from the inverse of the Information Matrix [75] as well as the Variable Inflation Factors. No sign of collinearity was found (data not shown).

Two-group SEM is a way to compare the results from two groups simultaneously. The goal of two-group SEM is to examine whether the relationship of interest among predictor and response variables vary by group. The benefit of two-group SEM is that it could identify which paths change based on the group membership and which do not. Thus, we applied two-group SEM as our main analytical approach [76]. For constructing the two-group SEM, we specified the SEM model in Fig. 2 based on Minority Stress Theory, preliminary analyses, and correlation matrix results. SEM is a process that allows for testing one or more theories that are hypothesized a prior to explain the characteristics of measured variables [59]. SEM can be used for model confirmatory purpose, testing alternative models, or model generation [60]. Two-group SEM can be used to examine inter-group differences across sexual minority subgroups with increased rigor. The advantage of two-group SEM is that it allows the comparison of the extent of associations based on path coefficients [61] and uses model fit indices to determine which tested paths best fit the data. This method could help examine whether the underlying pathway are significantly different among sexual minority subgroups. Given the goals of this study, two-group SEM is a particularly useful tool for examining how different pathways might vary across sexual orientation. A two-phase modeling approach was used for the two-group SEM. First, we examined measurement invariance (i.e., item-scale relationships) between gay and bisexual participants using confirmatory factor analysis (CFA). Second, we examined structural invariance (i.e., hypothesized relationships among variables) between gay and bisexual participants. Chi-square differences between these two models were examined and indicated non-significant results and thus no group differences in the measurement models [77].

Fig. 2
figure2

Specified two-group structural equation model of rejection anticipation to cigarette smoking for both gay and bisexual men in China

Then, we examined the model fit and path-coefficients of the final two-group structural SEM. The model fit indices included: chi-square test, standardized root mean square residual (SRMR), comparative fit index (CFI), Tucker–Lewis fit index (TLI), the root mean-square error of approximation (RMSEA), and weighted root mean square residual (WRMR). The indicators of goodness of fit were: χ2 p < 0.05; SRMR > 0.08; CFI > 0.90; TLI > 0.90; RMSEA < 0.05; and WRMR < 1 [78]. The bootstrapping method was used to test 95% Confidence Interval (95% CI). Standardized regression (β) coefficients, the standard errors, and p-values for β were reported in the final model.

Data were double-entered and cleaned using EpiData 3.1 (The EpiData Association, Odense, Denmark) software. Descriptive analysis and sequential regressions were conducted using SAS 9.4 (SAS Institute Inc.: Cary, NC, USA). Two-group SEM was conducted using Mplus 8.0 (Muthén & Muthén: Los Angeles, CA, USA).

Results

Descriptive statistics

Table 1 shows that, among the full sample, the proportion of cigarette use was 29.9%. The mean age of the participants was 26.51 (SD = 8.41) years old, 76.3% reported holding college degree or above, 31.5% were current students, and 58.6% were employed. Bisexual men reported a higher rate of cigarette smoking compared to gay men (39.9% vs. 27.3%). Rejection anticipation was significantly associated with cigarette smoking. Because marriage and health insurance were not associated with cigarette smoking, these variables were excluded from subsequent modeling analyses. Because education and monthly income correlated with employment, we included employment but excluded education and monthly income in the subsequent modeling.

Table 1 Descriptive characteristics and bivariate analyses examining differences between past 30-day cigarette smoking (N = 202) vs. non-smoking (N = 474) and between gay vs. bisexual orientation in Chinese gay and bisexual men (N = 676)

Correlation statistics

The correlation matrix examining group differences between gays and bisexuals (Table 2) indicated that employment was the only significant correlate of cigarette smoking in both gay and bisexual subgroups. Among all psychosocial factors, group differences were only found regarding rejection anticipation and depressive symptoms. Thus, the two-group SEM included rejection anticipation, depressive symptoms, and cigarette smoking, predicted by employment (dummy coded as student or employed) (Fig. 2).

Table 2 Correlation matrix examining correlates of past 30-day cigarettes smoking among the full sample of Chinese sexual minority men, gays, and bisexuals, respectively (N = 676)

Sequential logistic regression models

Table 3 shows the results from four regression models. Model 1 result showed that compared to gay men, bisexual men were more likely to use cigarette (crude Odd Ratio [OR] = 1.76, 95% CI: 1.19–2.60). In model 2, bisexual men were still more likely to use cigarette compared to gay men (adjust OR = 1.79; 95% CI: 1.18–2.72). Compared to student, being unemployed was more likely to use cigarette (aOR = 3.96; 95% CI: 2.09–7.50). In model 3, only being unemployed (aOR: 3.69; 95% CI: 1.85–7.37) and rejection anticipation (aOR: 0.80; 95% CI: 0.65–1.00) were associated with cigarette use. In model 4, being unemployed was the only significant correlate of cigarette use (aOR: 3.78; 95% CI: 1.90–7.54). The majority of psychosocial factors were not associated with the outcome.

Table 3 Sequential logistic regressions identifying correlates of past 30-day cigarette use among gay and bisexual men in China (N = 676)

Two-group SEM

Measurement model

We constructed unconstrained and constrained measurement CFA models. According to the model fit indices for the unconstrained model (χ2 = 1326.7 (576), p < .001; RMSEA = .061; CFI = .908; TLI = .896; SRMR = .056) and factor-loading constrained model (χ2 = 1358.2 (600), p < .001; RMSEA = .061; CFI = .907; TLI = .900; SRMR = .061), the chi-square difference test (χ2 = 31.5 [24]) was non-significant, indicating factor loading invariance. Therefore, we moved on to the structural analysis using this invariant measurement model.

Structural model

According to the model fit indices for the unconstrained model (χ2 = 971.0 (761), p < .001; RMSEA = .029; CFI = .920; TLI = .916; WRMR = 1.312) and constrained model (χ2 = 981.3 (770), p < .001; RMSEA = .028; CFI = .920; TLI = .916; WRMR = 1.397), the chi-square difference test (χ2 = 10.3 [9]) was non-significant, indicating structural invariance for gay and bisexual samples. The final two-group SEM fits the data well.

Final modeling results

For both gay and bisexual men (Fig. 3), rejection anticipation was positively associated with greater depressive symptoms (standardized β = 0.30, p < .001) and negatively associated with being a current cigarette smoker (standardized β = − 0.15, p < .001). Being a student was positively associated with higher rejection anticipation (standardized β = 0.17, p < .05) and was negatively associated with cigarette smoking (standardized β = − 0.33, p < .05). Being a student was not associated with depressive symptoms. Depressive symptoms were not associated with cigarette smoking.

Fig. 3
figure3

Final structural equation model testing pathway between rejection anticipation, depressive symptoms, and cigarette smoking among Chinese gay men and bisexual men. Model fit: χ2 = 981.28, df = 770, p < 0.001 (recommended p > 0.05); RMSEA: 0.028 (recommended < 0.05); CFI: 0.920 (recommended > 0.90); TLI: 0.916 (recommended > 0.90); WRMR = 1.397 (recommended < 1). Coefficients: Rejection anticipation was positively associated with greater depressive symptoms (standardized β = 0.30, p < .001) and negatively associated with being a current cigarette smoker (standardized β = − 0.15, p < .001). Being a student was positively associated with higher rejection anticipation (standardized β = 0.17, p < .05) and was negatively associated with cigarette smoking (standardized β = − 0.33, p < .05). Being a student was not associated with depressive symptoms. Depressive symptoms not associated with cigarette smoking

Discussion

This study examined cigarette smoking among sexual minority men in China through the lens of the Minority Stress Theory. Our findings showed that bisexual men reported a higher rate of cigarette smoking compared to gay men (39.9% vs. 27.3%) in China. This is consistent with literature in other countries that bisexual men often report higher use of cigarette relative to gay men [79, 80].

Minority stress, particularly rejection anticipation, was positively associated with depressive symptoms in both gay and bisexual subgroups. This finding is consistent with studies suggesting that rejection anticipation is associated with the onset of depressive symptoms [81, 82]. In Chinese culture, being a majority represents righteousness and power, whereas minorities may be marginalized and/or ostracized [40]. Rejection anticipation was reversely associated with cigarette smoking. This unexpected result might be influenced by the launch of public smoke-free legislation in major cities like Beijing since 2014, that participants who anticipated rejections based on their sexual minority orientations might tend to minimize other types of rejections from the society including smoking. Taken together, rejection anticipation is a critical construct for sexual minority stress that is associated with important mental health outcomes, especially in a collective culture like China. We did not find associations between other minority stressors and depressive symptoms. However, a study in Thailand suggested that experiences of victimization, discrimination, and identify concealment also predicted depression among sexual minorities [83]. More research is needed to confirm the relationship between various minority stressors and depressive symptoms in different cultural contexts.

No direct relationship between depression and cigarette smoking among gay and bisexual men was indicated. However, other research has documented significant relationships between mental distress and smoking among sexual minority men globally [29, 84,85,86]. There might be some contextual factors – such as tobacco-free policy in our campus-based venues, peer influences, and social or cultural norms – confounding or buffering the effect of minority stressors on cigarette use in this study population. For example, structural discrimination was found to be a significant predictor of smoking among sexual minority subgroup [87]. Peer violence and pressure also could lead to tobacco use among sexual minority youth [88]. Future studies should consider the contextual influencing factors to better understand the effects of minority stressors on cigarette smoking.

We did not find distinctive inter-group differences between subgroups in the mechanism through which minority stress might affect cigarette smoking. According to a Chinese qualitative study on bisexuality, bisexual identity is a fairly new concept for many Chinese, especially among young adults and students, and bisexual individuals might undergo long time exploration of sexual identity and might experience enormous confusion and social pressure [89]. It may be that some young participants or student participants in our study might still be exploring their identities and assume themselves to be gay, bisexual, or heterosexual, depending on the sex of their current partners [56]. Thus, the distinction between gay men and bisexual men might be biased because of high proportion of students in our study. On the other hand, the staggering gender difference in smoking prevalence within the overall population in China (51.4% in men vs. 2.7% in women) may shed lights on the mechanism through which minority stress might affect smoking. In China, smoking behavior reflects the mainstream masculine norms and is more accepted and expected among men [90, 91]. Meanwhile, feminine devaluation is common across sexual minority communities [92]. Taken together, it is possible that Chinese bisexual men, who might have female sex partners, feel more pressured to adhere to masculine norms and are more likely to adopt masculine-associated behaviors such as smoking than gay men. Unfortunely, this study did not measure constructs related to gender norms or feminine/masculine identity. Thus, we could only speculate that gender norms or feminine/masculine identity may interact with internalized homophobia and contribute to the higher smoking rate in bisexual men. Further research is warranted to understand the extent to which the gender norms or feminine/masculine identity operates as an independent mediator or moderator on the pathway between internalized homophobia and smoking behaviors among Chinese sexual minority men.

Results indicated that being a student was positively associated with rejection anticipation among Chinese sexual minority men. Currently, no known study has evaluated the impact of school environments or policies on the health of sexual minority students in China, but empirical studies in the U.S. have found that sexual minority students experience higher rates of parental or peer rejections compared to heterosexual counterparts [93]. Moreover, 86.2% of U.S. sexual minority students experienced verbal harassment and 44.1% of these students experienced physical harassment [94]. In the U.S., sexual minority students felt less safe at school compared to heterosexual students [95]. Depending on the school climate, sexual minority students might be experiencing in a hostile or protective environment. Thus, more studies are needed to evaluate the impact of school setting toward their feeling of rejection, mental illness, and health risk behaviors among Chinese sexual minority students.

Limitations

We used data from a convenient sample that was mainly comprised of urban, well-educated, and high-income gay/bisexual men, which might not be representative to all sexual minority men. Thus, our study provided little evidence base regarding the mental health status and smoking behaviors among LGBs residing in rural areas of China or who are with lower socioeconomic statuses. Also, the data were collected in sexual minority-serving organizations located in or close to college campuses, thus our measurement of cigarette smoking might be influenced by the smoke-free campus policies enforced since 2014 and therefore might not reflect the actual cigarette smoking prevalence. The cross-sectional nature of the data limits the inference regarding our findings, as SEM analysis using cross-sectional data might potentially misrepresent the pathway processes. Thus, researchers should use caution when interpreting our results. Future research should use longitudinal data to obtain better representation of the causal pathway between rejection anticipation and smoking among LGBs. Due to the page limitation of the survey instrument, we did not assess important factors that might influence smoking behaviors such as cultural aspects or peers or family influences. Gender norms and feminine/masculine identity were not considered in the study design. Thus, we couldn’t explore the roles of these constructs in influencing smoking behaviors among sexual minority men in China. Last, data were collected based on self-report using pen-and-paper and thus might be prone to recall bias and social desirability.

Conclusions

Guided by Minority Stress Theory, this study is among the first to examine the minority stress – cigarette use pathway among a sample of Chinese gay and bisexual men. Our findings showed that bisexual men are more likely to smoke cigarette compared to gay men. Minority stress, particularly rejection anticipation, was associated with depressive symptoms in both gay and bisexual men, but depressive symptoms were not associated with cigarette smoking. Although we did not identify the pathway linking minority stress and cigarette smoking between gay and bisexual men, future studies can explore the role of minority stress and differences in cigarette smoking rates across sexual minority subgroups in urban and rural China and beyond in order to design tailored and targeted tobacco cessation interventions.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author (Dr. Hong Yan) on reasonable request.

Abbreviations

SEM:

Structural equation modeling

SD:

Standard deviation

OR:

Odd Ratio

CI:

Confidence Interval

CES-D:

Center for Epidemiological Studies Depression Scale

ACEs:

Adverse childhood experiences

ANOVA:

Analysis of variance

CFA:

Confirmatory factor analysis

SRMR:

Standardized root mean square residual

CFI:

Comparative fit index

TLI:

Tucker–Lewis fit index

RMSEA:

The root mean-square error of approximation

WRMR:

Weighted root mean square residual

References

  1. 1.

    WHO report on the global tobacco epidemic, 2017 [https://www.who.int/tobacco/surveillance/policy/country_profile/chn.pdf?ua=1].

  2. 2.

    Hu SS. Tobacco product use among adults—United States, 2013-2014. MMWR Morb Mortal Wkly Rep. 2016:65.

  3. 3.

    Chen ZM, Peto R, Iona A, Guo Y, Chen YP, Bian Z, et al. Emerging tobacco-related cancer risks in China: a nationwide, prospective study of 0.5 million adults. Cancer. 2015;121(S17):3097–106. https://0-doi-org.brum.beds.ac.uk/10.1002/cncr.29560.

  4. 4.

    China CDC. 2015 China adult tobacco survey [in Chinese]. Beijing: China CDC; 2015.

    Google Scholar 

  5. 5.

    China CDC. Report of China City adult tobacco survey 2013–14: a 14-city experience. UK: WHO; 2015.

    Google Scholar 

  6. 6.

    Wheldon CW, Kaufman AR, Kasza KA, Moser RP. Tobacco use among adults by sexual orientation: findings from the population assessment of tobacco and health study. Lgbt Health. 2018;5(1):33–44. https://0-doi-org.brum.beds.ac.uk/10.1089/lgbt.2017.0175.

    Article  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Baskerville NB, Dash D, Shuh A, Wong K, Abramowicz A, Yessis J, et al. Tobacco use cessation interventions for lesbian, gay, bisexual, transgender and queer youth and young adults: a scoping review. Prev Med Rep. 2017;6:53–62. https://0-doi-org.brum.beds.ac.uk/10.1016/j.pmedr.2017.02.004.

  8. 8.

    Berger I, Mooney-Somers J. Smoking cessation programs for lesbian, gay, bisexual, transgender, and intersex people: a content-based systematic review. Nicotine Tob Res. 2016;19(12):1408–17.

    Google Scholar 

  9. 9.

    Goldbach JT, Tanner-Smith EE, Bagwell M, Dunlap S. Minority stress and substance use in sexual minority adolescents: a meta-analysis. Prev Sci. 2014;15(3):350–63. https://0-doi-org.brum.beds.ac.uk/10.1007/s11121-013-0393-7.

    Article  PubMed  Google Scholar 

  10. 10.

    Blosnich J, Lee JG, Horn K. A systematic review of the aetiology of tobacco disparities for sexual minorities. Tob Control. 2013;22(2):66–73. https://0-doi-org.brum.beds.ac.uk/10.1136/tobaccocontrol-2011-050181.

    Article  PubMed  Google Scholar 

  11. 11.

    Lee JG, Griffin GK, Melvin CL. Tobacco use among sexual minorities in the USA, 1987 to may 2007: a systematic review. Tob Control. 2009;18(4):275–82. https://0-doi-org.brum.beds.ac.uk/10.1136/tc.2008.028241.

    CAS  Article  PubMed  Google Scholar 

  12. 12.

    Schauer GL, Berg CJ, Bryant LO. Sex differences in psychosocial correlates of concurrent substance use among heterosexual, homosexual and bisexual college students. Am J Drug Alcohol Abuse. 2013;39(4):252–8. https://0-doi-org.brum.beds.ac.uk/10.3109/00952990.2013.796962.

    Article  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Lian Q, Zuo X, Lou C, Gao E, Cheng Y. Sexual orientation and smoking history: results from a community-based sample of youth in Shanghai, China. Environ Health Prev Med. 2015;20(3):179–84. https://0-doi-org.brum.beds.ac.uk/10.1007/s12199-015-0444-8.

    Article  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Berg CJ, Nehl EJ, Wong FY, He N, Huang ZJ, Ahluwalia JS, et al. Prevalence and correlates of tobacco use among a sample of MSM in Shanghai, China. Nicotine Tob Res. 2011;13(1):29–35.

  15. 15.

    Zhang BC, Li XF, Shi TX, Yang LG, Zhang JD. A rough estimate of gay/lesbian population and their infect HIV prevalence. Chin J STD/AIDS Prev Cont. 2002;8:197–9.

    Google Scholar 

  16. 16.

    Meyer IH. Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: conceptual issues and research evidence. Psychol Bull. 2003;129(5):674–97. https://0-doi-org.brum.beds.ac.uk/10.1037/0033-2909.129.5.674.

    Article  PubMed  PubMed Central  Google Scholar 

  17. 17.

    Meyer IH. Minority stress and mental health in gay men. J Health Soc Behav. 1995;36(1):38–56. https://0-doi-org.brum.beds.ac.uk/10.2307/2137286.

    CAS  Article  PubMed  Google Scholar 

  18. 18.

    Fluharty M, Taylor AE, Grabski M, Munafò MR. The association of cigarette smoking with depression and anxiety: a systematic review. Nicotine Tob Res. 2016;19(1):3–13. https://0-doi-org.brum.beds.ac.uk/10.1093/ntr/ntw140.

    Article  PubMed  PubMed Central  Google Scholar 

  19. 19.

    Ziedonis D, Hitsman B, Beckham JC, Zvolensky M, Adler LE, Audrain-McGovern J, Breslau N, Brown RA, George TP, Williams J: Tobacco use and cessation in psychiatric disorders: National Institute of Mental Health report. In.: Society for Research on Nicotine and Tobacco; 2008.

  20. 20.

    Gamarel KE, Mereish EH, Manning D, Iwamoto M, Operario D, Nemoto T. Minority stress, smoking patterns, and cessation attempts: findings from a community-sample of transgender women in the San Francisco Bay Area. Nicotine Tob Res. 2016;18(3):306–13. https://0-doi-org.brum.beds.ac.uk/10.1093/ntr/ntv066.

    Article  PubMed  Google Scholar 

  21. 21.

    Frost DM, Lehavot K, Meyer IH. Minority stress and physical health among sexual minority individuals. J Behav Med. 2015;38(1):1–8. https://0-doi-org.brum.beds.ac.uk/10.1007/s10865-013-9523-8.

    Article  PubMed  Google Scholar 

  22. 22.

    Wong CF, Schrager SM, Holloway IW, Meyer IH, Kipke MD. Minority stress experiences and psychological well-being: the impact of support from and connection to social networks within the Los Angeles house and ball communities. Prev Sci. 2014;15(1):44–55. https://0-doi-org.brum.beds.ac.uk/10.1007/s11121-012-0348-4.

    Article  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Lehavot K. Minority stress, coping, and health among sexual minority women. US: ProQuest Information & Learning; 2012.

    Google Scholar 

  24. 24.

    Hamilton CJ, Mahalik JR. Minority stress, masculinity, and social norms predicting gay Men's health risk behaviors. J Couns Psychol. 2009;56(1):132–41. https://0-doi-org.brum.beds.ac.uk/10.1037/a0014440.

    Article  Google Scholar 

  25. 25.

    Burgess D, Lee R, Tran A, Van Ryn M. Effects of perceived discrimination on mental health and mental health services utilization among gay, lesbian, bisexual and transgender persons. J LGBT Health Res. 2008;3(4):1–14.

    Article  Google Scholar 

  26. 26.

    Newcomb ME, Mustanski B. Internalized homophobia and internalizing mental health problems: a meta-analytic review. Clin Psychol Rev. 2010;30(8):1019–29. https://0-doi-org.brum.beds.ac.uk/10.1016/j.cpr.2010.07.003.

    Article  PubMed  Google Scholar 

  27. 27.

    Villarreal C, Wiebe JS, Sauceda JA, Simoni JM. Internalized Hiv stigma, internalized homophobia, and depression among Latino Msm living with Hiv. Ann Behav Med. 2012;43:S277–7.

  28. 28.

    Poteat VP, Scheer JR, Digiovanni CD, Mereish EH: Short-Term Prospective Effects of Homophobic Victimization on the Mental Health of Heterosexual Adolescents. J Youth Adolesc 2013.

  29. 29.

    Xu W, Zheng L, Xu Y, Zheng Y. Internalized homophobia, mental health, sexual behaviors, and outness of gay/bisexual men from Southwest China. Int J Equity Health. 2017;16(1):36. https://0-doi-org.brum.beds.ac.uk/10.1186/s12939-017-0530-1.

    Article  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Meyer IH, Frost DM. Minority stress and the health of sexual minorities. Handbook Psychol Sex Orient. 2013:252–66.

  31. 31.

    Rosario M, Schrimshaw EW, Hunter J. Disclosure of sexual orientation and subsequent substance use and abuse among lesbian, gay, and bisexual youths: critical role of disclosure reactions. Psychol Addict Behav. 2009;23(1):175–84. https://0-doi-org.brum.beds.ac.uk/10.1037/a0014284.

    Article  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Pollitt AM, Muraco JA, Grossman AH, Russell ST. Disclosure stress, social support, and depressive symptoms among cisgender bisexual youth. J Marriage Fam. 2017;79(5):1278–94. https://0-doi-org.brum.beds.ac.uk/10.1111/jomf.12418.

    Article  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Sivadon AD. Social support and smoking among Midwest LGBT adults. US: ProQuest Information & Learning; 2015.

    Google Scholar 

  34. 34.

    Liu H, Feng T, Ha T, Liu H, Cai Y, Liu X, et al. Chinese culture, homosexuality stigma, social support and condom use: a path analytic model. Stig Res Action. 2011;1(1):27–35. https://0-doi-org.brum.beds.ac.uk/10.5463/sra.v1i1.16.

  35. 35.

    Cordero ED. Self-esteem, social support, collectivism, and the thin-ideal in Latina undergraduates. Body Image. 2011;8(1):82–5. https://0-doi-org.brum.beds.ac.uk/10.1016/j.bodyim.2010.11.006.

    Article  PubMed  Google Scholar 

  36. 36.

    Cohen S, Wills TA. Stress, social support, and the buffering hypothesis. Psychol Bull. 1985;98(2):310–57. https://0-doi-org.brum.beds.ac.uk/10.1037/0033-2909.98.2.310.

    CAS  Article  PubMed  Google Scholar 

  37. 37.

    Wong NY, Ahuvia AC. Personal taste and family face: luxury consumption in Confucian and Western societies. Psychol Mark. 1998;15(5):423–41.

  38. 38.

    Lai DW. Filial piety, caregiving appraisal, and caregiving burden. Res Aging. 2010;32(2):200–23. https://0-doi-org.brum.beds.ac.uk/10.1177/0164027509351475.

    Article  Google Scholar 

  39. 39.

    Koo F. The six categories of participation in physical activity among older Chinese Australians. Ageing Soc. 2012;1:67–84.

    Google Scholar 

  40. 40.

    Li Y. Li Yihen Self Selections: Sex, Love, Marriage and Other Issues. Hohhot: Inner Mongolia University Press; 2006.

    Google Scholar 

  41. 41.

    Kong TS. Chinese male homosexualities. Routledge: Memba, tongzhi and golden boy; 2010. https://0-doi-org.brum.beds.ac.uk/10.4324/9780203849200.

    Book  Google Scholar 

  42. 42.

    Wah-Shan C. Homosexuality and the cultural politics of Tongzhi in Chinese societies. J Homosex. 2001;40(3–4):27–46. https://0-doi-org.brum.beds.ac.uk/10.1300/J082v40n03_03.

    CAS  Article  PubMed  Google Scholar 

  43. 43.

    Wang S, Song D, Huang W, He H, Wang M, Manning D, et al. Heterosexual partnerships and the need for HIV prevention and testing for men who have sex with men and women in China: a qualitative study. AIDS Educ Prev. 2015;27(2):126–8. https://0-doi-org.brum.beds.ac.uk/10.1521/aeap.2015.27.2.126.

  44. 44.

    Sun S, Budge S, Shen W, Xu G, Liu M, Feng SJSS. Medicine: minority stress and health: a grounded theory exploration among men who have sex with men in China and implications for health research and interventions. Soc Sci Med. 2020;252:112917.

    Article  Google Scholar 

  45. 45.

    Liu P, Chan CS. Lesbian, gay and bisexual Asian American and their families. Asian Am. 2003:89–104.

  46. 46.

    Tao J, Ruan YH, Yin L, Vermund SH, Shepherd BE, Shao YM, et al. Sex with women among men who have sex with men in China: prevalence and sexual practices. Aids Pat Care St. 2013;27(9):524–8. https://0-doi-org.brum.beds.ac.uk/10.1089/apc.2013.0161.

  47. 47.

    la Roi C, Meyer IH, Frost DM. Differences in sexual identity dimensions between bisexual and other sexual minority individuals: implications for minority stress and mental health. Am J Orthopsychiatry. 2019;89(1):40–51. https://0-doi-org.brum.beds.ac.uk/10.1037/ort0000369.

    Article  PubMed  Google Scholar 

  48. 48.

    Fish JN, Watson RJ, Gahagan J, Porta CM, Beaulieu-Prévost D, Russell ST. Smoking behaviours among heterosexual and sexual minority youth? Findings from 15 years of provincially representative data. Drug Alcohol Rev. 2019;38(1):101–10. https://0-doi-org.brum.beds.ac.uk/10.1111/dar.12880.

    Article  PubMed  Google Scholar 

  49. 49.

    Peltzer K, Pengpid S. Minority stress among lesbian, gay, bisexual, and transgender (LGBT) university students in ASEAN countries: associations with poor mental health and addictive behavior. Gender Behav. 2016;14(3):7806–15.

    Google Scholar 

  50. 50.

    Zheng L, Hart TA, Noor SW, Wen G. Stressors based on sexual orientation and mental health among lesbian, gay, and bisexual individuals in China: minority stress and perceived pressure to get married. Arch Sex Behav. 2020;49(5):1769–82. https://0-doi-org.brum.beds.ac.uk/10.1007/s10508-020-01693-z.

    Article  PubMed  Google Scholar 

  51. 51.

    Sun S, Pachankis JE, Li X, Operario D. Addressing minority stress and mental health among men who have sex with men (MSM) in China. Curr Hiv-Aids Rep. 2020;17(1):35–62. https://0-doi-org.brum.beds.ac.uk/10.1007/s11904-019-00479-w.

    Article  Google Scholar 

  52. 52.

    Sun S, Budge S, Shen W, Xu G, Liu M, Feng S. Minority stress and health: a grounded theory exploration among men who have sex with men in China and implications for health research and interventions. Soc Sci Med. 2020;252:112917. https://0-doi-org.brum.beds.ac.uk/10.1016/j.socscimed.2020.112917.

    Article  PubMed  Google Scholar 

  53. 53.

    Shao J, Chang ES, Chen C. The relative importance of parent–child dynamics and minority stress on the psychological adjustment of LGBs in China. J Couns Psychol. 2018;65(5):598–604. https://0-doi-org.brum.beds.ac.uk/10.1037/cou0000281.

    Article  PubMed  Google Scholar 

  54. 54.

    Yu F, Nehl EJ, Zheng T, He N, Berg CJ, Lemieux AF, et al. A syndemic including cigarette smoking and sexual risk behaviors among a sample of MSM in Shanghai, China. Drug Alcohol Depen. 2013;132(1–2):265–70. https://0-doi-org.brum.beds.ac.uk/10.1016/j.drugalcdep.2013.02.016.

  55. 55.

    He N, Wong FY, Huang ZJ, Thompson EE, Fu C. Substance use and HIV risks among male heterosexual and 'money boy' migrants in Shanghai, China. Aids Care-Psychol Soc-Med Aspects Aids/Hiv. 2007;19(1):109–15.

    CAS  Article  Google Scholar 

  56. 56.

    Feinstein BA, Dyar C. Bisexuality, minority stress, and health. Curr Sex Health Rep. 2017;9(1):42–9. https://0-doi-org.brum.beds.ac.uk/10.1007/s11930-017-0096-3.

    Article  PubMed  PubMed Central  Google Scholar 

  57. 57.

    Brewster ME, Moradi B, DeBlaere C, Velez BL. Navigating the borderlands: the roles of minority stressors, bicultural self-efficacy, and cognitive flexibility in the mental health of bisexual individuals. J Couns Psychol. 2013;60(4):543–56. https://0-doi-org.brum.beds.ac.uk/10.1037/a0033224.

    Article  PubMed  Google Scholar 

  58. 58.

    Walters M, Chen JT, Breiding MJ. The National Intimate Partner and sexual violence survey (NISVS): 2010 findings on victimization by sexual orientation. Atlanta: National Center for Injury Prevention and Control, Centers for Disease Control and Prevention; 2013.

    Google Scholar 

  59. 59.

    Chinese Center for Disease Control and Prevention. Chinese guidelines for diagnosis and treatment of HIV/AIDS (2018). Chin J Clin Infect Dis. 2018;11(6):411–32.

    Google Scholar 

  60. 60.

    Koty AC, Qian Z. A Complete Guide to 2017 Minimum Wage Levels Across China. 2017. https://www.china-briefing.com/news/complete-guide-2017-minimum-wage-levels-across-china/?hilite=%27Guide%27%2C%27Minimum%27%2C%27Wages%27%2C%27China%27. Accessed 7 June 2021.

  61. 61.

    Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas. 1977;1(3):385–401. https://0-doi-org.brum.beds.ac.uk/10.1177/014662167700100306.

    Article  Google Scholar 

  62. 62.

    Chaiton MO, Cohen JE, O'Loughlin J, Rehm J. A systematic review of longitudinal studies on the association between depression and smoking in adolescents. BMC Public Health. 2009;9(1):356. https://0-doi-org.brum.beds.ac.uk/10.1186/1471-2458-9-356.

    Article  PubMed  PubMed Central  Google Scholar 

  63. 63.

    Song Y, Huang Y, Liu D, Kwan JSH, Zhang F, Sham PC, et al. Depression in college: depressive symptoms and personality factors in Beijing and Hong Kong college freshmen. Compr Psychiatry. 2008;49(5):496–502. https://0-doi-org.brum.beds.ac.uk/10.1016/j.comppsych.2008.02.005.

  64. 64.

    Cheung C-K, Bagley C. Validating an American scale in Hong Kong: the center for epidemiological studies depression scale (CES-D). J Psychol. 1998;132(2):169–86. https://0-doi-org.brum.beds.ac.uk/10.1080/00223989809599157.

    CAS  Article  PubMed  Google Scholar 

  65. 65.

    Gonzales KL, Noonan C, Goins RT, Henderson WG, Beals J, Manson SM, et al. Assessing the everyday discrimination scale among American Indians and Alaska natives. Psychol Assess. 2016;28(1):51–8. https://0-doi-org.brum.beds.ac.uk/10.1037/a0039337.

  66. 66.

    Link BG. Understanding labeling effects in the area of mental disorders: an assessment of the effects of expectations of rejection. Am Sociol Rev. 1987;52(1):96–112. https://0-doi-org.brum.beds.ac.uk/10.2307/2095395.

    Article  Google Scholar 

  67. 67.

    Testa RJ, Habarth J, Peta J, Balsam K, Bockting W. Development of the gender minority stress and resilience measure. Psychol Sex Orientat Gend Divers. 2015;2(1):65–77. https://0-doi-org.brum.beds.ac.uk/10.1037/sgd0000081.

    Article  Google Scholar 

  68. 68.

    Martin JL, Dean L: Summary of measures: mental health effects of AIDS on at-risk homosexual men. Unpublished manuscript 1987.

  69. 69.

    Frost DM, Meyer IH. Internalized homophobia and relationship quality among lesbians, gay men, and bisexuals. J Couns Psychol. 2009;56(1):97–109. https://0-doi-org.brum.beds.ac.uk/10.1037/a0012844.

    Article  PubMed  PubMed Central  Google Scholar 

  70. 70.

    Felitti VJ, Anda RF, Nordenberg D, Williamson DF, Spitz AM, Edwards V, et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: the adverse childhood experiences (ACE) study. Am J Prev Med. 1998;14(4):245–58. https://0-doi-org.brum.beds.ac.uk/10.1016/S0749-3797(98)00017-8.

  71. 71.

    Merrick MT, Ford DC, Ports KA, Guinn AS. Prevalence of Adverse Childhood Experiences From the 2011-2014 Behavioral Risk Factor Surveillance System in 23 States. JAMA Pediatrics. 2018;172(11):1038–44.

  72. 72.

    Tonsing K, Zimet GD, Tse S. Assessing social support among south Asians: the multidimensional scale of perceived social support. Asian J Psychiatr. 2012;5(2):164–8. https://0-doi-org.brum.beds.ac.uk/10.1016/j.ajp.2012.02.012.

    Article  PubMed  Google Scholar 

  73. 73.

    Campbell-Sills L, Stein MB. Psychometric analysis and refinement of the connor–Davidson resilience scale (CD-RISC): validation of a 10-item measure of resilience. J Trauma Stress. 2007;20(6):1019–28. https://0-doi-org.brum.beds.ac.uk/10.1002/jts.20271.

    Article  PubMed  Google Scholar 

  74. 74.

    Connor KM, Davidson JR. Development of a new resilience scale: the Connor-Davidson resilience scale (CD-RISC). Depress Anxiety. 2003;18(2):76–82. https://0-doi-org.brum.beds.ac.uk/10.1002/da.10113.

    Article  PubMed  Google Scholar 

  75. 75.

    Belsley DA. A guide to using the collinearity diagnostics. Comput Econ. 1991;4(1):33–50.

    Google Scholar 

  76. 76.

    Lefcheck JS. Structural equation modeling in R for ecology and evolution. Recuperado de: https://jslefche.github.io/sem_book/index.html [Consulta: 20 de junio de 2020]. 2019 Mar 19.

  77. 77.

    Thompson B. Exploratory and confirmatory factor analysis: understanding concepts and applications. Appl Psychol Meas. 2007;31(3):245–8.

    Article  Google Scholar 

  78. 78.

    Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model Multidiscip J. 1999;6(1):1–55. https://0-doi-org.brum.beds.ac.uk/10.1080/10705519909540118.

    Article  Google Scholar 

  79. 79.

    Tuthill Z, Denney JT, Gorman B. Racial disparities in health and health behaviors among gay, lesbian, bisexual and heterosexual men and women in the BRFSS-SOP. Ethnicity Health. 2020;25(2):177–88. https://0-doi-org.brum.beds.ac.uk/10.1080/13557858.2017.1414157.

    Article  PubMed  Google Scholar 

  80. 80.

    Clarke MP, Coughlin JR. Prevalence of smoking among the lesbian, gay, bisexual, transsexual, transgender and queer (LGBTTQ) subpopulations in Toronto — the Toronto rainbow tobacco survey (TRTS). Can J Public Health. 2012;103(2):132–6. https://0-doi-org.brum.beds.ac.uk/10.1007/BF03404218.

    Article  PubMed  PubMed Central  Google Scholar 

  81. 81.

    Normansell KM, Wisco BE. Negative interpretation bias as a mechanism of the relationship between rejection sensitivity and depressive symptoms. Cognit Emot. 2017;31(5):950–62. https://0-doi-org.brum.beds.ac.uk/10.1080/02699931.2016.1185395.

    Article  Google Scholar 

  82. 82.

    Slavich GM, Thornton T, Torres LD, Monroe SM, Gotlib IH. Targeted rejection predicts hastened onset of major depression. J Soc Clin Psychol. 2009;28(2):223–43. https://0-doi-org.brum.beds.ac.uk/10.1521/jscp.2009.28.2.223.

    Article  PubMed  PubMed Central  Google Scholar 

  83. 83.

    Kittiteerasack P, Steffen A, Matthews A. The influence of minority stress on level of depression among Thai LGBT adults. Jurnal Keperawatan Indonesia. 2020;23(1):74–84. https://0-doi-org.brum.beds.ac.uk/10.7454/jki.v23i1.1073.

    Article  Google Scholar 

  84. 84.

    Choi K-H, Steward WT, Miège P, Hudes E, Gregorich SE. Sexual stigma, coping styles, and psychological distress: a longitudinal study of men who have sex with men in Beijing, China. Arch Sex Behav. 2015:1–9.

  85. 85.

    Pachankis JE, Hatzenbuehler ML, Starks TJ. The influence of structural stigma and rejection sensitivity on young sexual minority men's daily tobacco and alcohol use. Soc Sci Med. 2014;103:67–75. https://0-doi-org.brum.beds.ac.uk/10.1016/j.socscimed.2013.10.005.

    Article  PubMed  PubMed Central  Google Scholar 

  86. 86.

    Blosnich JR, Horn K. Associations of discrimination and violence with smoking among emerging adults: differences by gender and sexual orientation. Nicotine Tob Res. 2011;13(12):1284–95. https://0-doi-org.brum.beds.ac.uk/10.1093/ntr/ntr183.

    Article  PubMed  PubMed Central  Google Scholar 

  87. 87.

    Shires DA, Jaffee KD. Structural discrimination is associated with smoking status among a National Sample of transgender individuals. Nicotine Tob Res. 2016;18(6):1502–8. https://0-doi-org.brum.beds.ac.uk/10.1093/ntr/ntv221.

    Article  PubMed  Google Scholar 

  88. 88.

    Rosario M, Corliss HL, Everett BG, Russell ST, Buchting FO, Birkett MA. Mediation by peer violence victimization of sexual orientation disparities in cancer-related tobacco, alcohol, and sexual risk behaviors: pooled youth risk behavior surveys. Am J Public Health. 2014;104(6):1113–23. https://0-doi-org.brum.beds.ac.uk/10.2105/AJPH.2013.301764.

    Article  PubMed  PubMed Central  Google Scholar 

  89. 89.

    Dong W. Bisexual identity: an in-depth interview [in Chinese]. Nanjing: Nanjing Normal University; 2013.

    Google Scholar 

  90. 90.

    Mao A, Bristow K, Robinson J. Caught in a dilemma: why do non-smoking women in China support the smoking behaviors of men in their families? Health Educ Res. 2013;28(1):153–64. https://0-doi-org.brum.beds.ac.uk/10.1093/her/cys078.

    Article  PubMed  Google Scholar 

  91. 91.

    Davey G. Zhao X: ‘a real man smells of tobacco smoke’—Chinese youth's interpretation of smoking imagery in film. Soc Sci Med. 2012;74(10):1552–9. https://0-doi-org.brum.beds.ac.uk/10.1016/j.socscimed.2012.01.024.

    Article  PubMed  Google Scholar 

  92. 92.

    Hoskin RA. Femmephobia: the role of anti-femininity and gender policing in LGBTQ+ people’s experiences of discrimination. Sex Roles. 2019;81(11):686–703. https://0-doi-org.brum.beds.ac.uk/10.1007/s11199-019-01021-3.

    Article  Google Scholar 

  93. 93.

    Ryan C, Huebner D, Diaz RM, Sanchez J. Family rejection as a predictor of negative health outcomes in white and Latino lesbian, gay, and bisexual young adults. Pediatrics. 2009;123(1):346–52. https://0-doi-org.brum.beds.ac.uk/10.1542/peds.2007-3524.

    Article  PubMed  Google Scholar 

  94. 94.

    Kosciw JG, Diaz EM: Involved, invisible, ignored: the experiences of lesbian, gay, bisexual and transgender parents and their children in our Nation's K-12 schools: ERIC; 2008.

  95. 95.

    Institute of Medicine. The Health of Lesbian, Gay, Bisexual, and Transgender People: Building a Foundation for Better Understanding. Washington: National Academies Press; 2011.

    Google Scholar 

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Acknowledgements

We thank all the LGBT organizations in Beijing, Wuhan, Nanchang, and Changsha, China for their supports in our research data collection.

Funding

This research is supported by the Emory University Professional Development Funds (PI: JL), China Humanities and Social Science Foundation, Ministry of Education (15YJAZH094, PI: HY), and National Natural Science Foundation of China (81673196, PI: HY). The funders had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication.

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Affiliations

Authors

Contributions

JL conceptualized the study, performed data analysis, and wrote the manuscript. DH contributed to the manuscript writing and manuscript review. CJB, MW, and RH contributed to the conceptualization of the study and oversaw data analytical methods. CE and CJB reviewed data analytical methods and contributed to manuscript writing. WW, XL, SL, and HY collected the data. KT, HY, and SL reviewed data analytical methods and contributed to manuscript writing. All authors have read and approved the manuscript.

Corresponding author

Correspondence to Hong Yan.

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Ethics approval and consent to participate

Our research project was approved by the Wuhan University Medical School Institutional Review Boards. All participants provide written informed consent prior to completing the survey.

Consent for publication

Not applicable.

Competing interests

All authors declare no competing interests.

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Supplementary Information

Additional file 1:.

China gay bisexual men study questionnaire__English. This file is the English version of the questionnaire used in this study (measurement only).

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Li, J., Huang, D., Windle, M. et al. Minority stress, depression, and cigarette smoking among Chinese gay versus bisexual men: a two-group structural equation model analyses. BMC Public Health 21, 1358 (2021). https://0-doi-org.brum.beds.ac.uk/10.1186/s12889-021-10888-5

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Keywords

  • Minority stress
  • Depression
  • Cigarette
  • Smoking
  • Gay men
  • Bisexual men
  • China