Health-related quality of life inequalities by sexual orientation: Results from the Barcelona Health Interview Survey
Health-related quality of life inequalities by sexual orientation: Results from the Barcelona Health Interview Survey
Marc Marti-Pastor 0 1 2
Gloria Perez 0 1
Danielle German 1
Angels Pont 0 1 2
Olatz Garin 0 1 2
Jordi Alonso 0 1 2
Mercè Gotsens 0 1
Montse Ferrer 0 1 2
0 CIBER en EpidemiologÂõa y Salud PuÂ blica (CIBERESP) , Madrid , Spain , 3 Universitat Autonoma de Barcelona (UAB) , Barcelona , Spain , 4 Public Health Agency of Barcelona , Barcelona , Spain , 5 Universitat Pompeu Fabra , Barcelona , Spain , 6 Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health , Baltimore , Maryland, United States of America, 7 Institute of Biomedical Research (IIB Sant Pau) , Barcelona , Spain
1 Editor: Brecht Devleesschauwer, Scientific Institute of Public Health (WIV-ISP) , BELGIUM
2 IMIM (Hospital del Mar Medical Research Institute), Health Services Research Group , Barcelona , Spain
Data Availability Statement: All relevant data are
within the paper and its Supporting Information
Funding: This study was supported by the
Departament d'InnovacioÂ, Universitats i Empresa,
Generalitat de Catalunya (2014 SGR 748) to Dr.
Jordi Alonso, and by the Contract of training in
research ISCIII FIS RÂõo Hortega CM15/00167 to
Competing interests: The authors have declared
that no competing interests exist.
After adjusting by socio-demographic variables, the LGB group presented a significantly
lower EQ-5D index than heterosexuals, and higher prevalence ratios of problems in physical
EQ-5D dimensions among both genders: adjusted prevalence ratio (aPR) = 1.70 for mobility
(p = 0.046) and 2.11 for usual activities (p = 0.019). Differences in mental dimensions were
only observed among men: aPR = 3.15 for pain/discomfort (p = 0.003) and 2.49 for anxiety/
depression (p = 0.030). All these differences by sexual orientation disappeared after adding
chronic conditions and health-related behaviors in the models.
The LGB population presented worse HRQoL than heterosexuals in the EQ-5D index and
most dimensions. Chronic conditions, health-related behaviors and gender play a major role
in explaining HRQoL differences by sexual orientation. These findings support the need of
including sexual orientation into the global agenda of health inequities.
Sexual orientation is a social determinant of health inequities which influences different
morbidity and mortality outcomes [
]. Even in western countries, where progress in social rights
has been large and rapidly implemented from the end of the 20th century, the lesbian, gay, and
bisexual (LGB) population presented worse health than the heterosexual one [3±6]. Health
inequalities among the LGB population have been reported for mental health [
conditions , and health-related behaviors [
]; but very few studies have assessed
healthrelated quality of life (HRQoL) [
HRQoL is a broad and multidimensional concept which describes the physical, social, and
psychological aspects of well-being and functioning [
]. It is considered an ultimate and
comprehensive outcome on the conceptual model of health . However, only two studies on
sexual orientation inequalities have considered HRQoL as a whole [
], while others [
included selected HRQoL dimensions. The California Quality of Life Survey [
] only reported
the physical component of the Short Form-12 Health Survey (SF-12), and the combined
metaanalysis of health surveys from United Kingdom (UK) only reported anxiety/depression from
the EuroQol-5 Dimensions (EQ-5D) [
]. The Dutch National Survey of General Practice
assessed both the physical and the mental health components covered by the Short Form-36
Health Survey (SF-36), [
] and the United States Growing Up Today Study [
] reported the
EQ-5D index. A major feature of the EQ-5D instrument lies on its single index (based on
societal preference utilities), which allows the calculation of quality-adjusted life years (QALYs)
It is important to distinguish between inequality and inequity in health among population
groups . Inequity refers to inequalities which are avoidable and unfair, since they are
consequence of the different opportunities and resources that people have due to their social
]. The aim of our study was to assess HRQoL inequalities between LGB and
heterosexuals in the 2011 Barcelona population, to describe the extent to which sociodemographic
characteristics, health-related behaviors, and chronic conditions could explain such
inequalities, and to understand if they are sexual orientation inequities.
Following the structural framework proposed by Mule et al. [
], we hypothesize worse
HRQoL in LGB than their heterosexual counterparts. Health determinants such as age,
education level, country of birth, partnership status, and social support can be potential
confounders when assessing health inequalities by sexual orientation [
]. Furthermore, age [
and gender [
] can modify the effect of sexual orientation in health. Despite the favorable
social climate of Barcelona toward sexual minorities in the world , our hypothesis is that
discrimination by sexual orientation may lead to increased vulnerabilities, such as distress and
2 / 15
worse health-related behaviors, which result in higher prevalence of chronic conditions and,
finally, worse HRQoL.
Material and methods
Data used in this study came from the Barcelona Health Interview Survey (BHIS) 2011 edition.
It is a cross-sectional study periodically performed in Barcelona [
], a city in the north-east of
Spain with about 1.5 million inhabitants. A representative sample of the non-institutionalized
population, older than 15 years, was surveyed through computer-assisted personal interviews
administered face to face by accredited interviewers in the respondent's home.
To ensure territorial representativeness, the sample was stratified by municipal districts. A
random sampling strategy was applied, using a simple extraction system from the municipal
census, between January 2011 and January 2012 taking into account gender and age
distribution. The sample size was estimated at 4,000 individuals (relative error margin of 1.55% with a
confidence level of 95.5%). The BHIS is an official statistical activity, and data confidentiality is
guaranteed by the Spanish Law Number 23/1998.
Variables and measurement instruments
The EQ-5D. The EQ-5D covers five dimensions of health (mobility, self-care, usual
activities, pain/discomfort, and anxiety/depression) with three levels of severity, from none to
extreme problems. Its validity and reliability have been demonstrated in general population
health surveys [
]. We used the conventional Time Trade Off preference values from the
Spanish general population  which produced a single preference-based index ranging
from 1 (best health state) to negative values, where 0 is equal to death.
Sexual orientation. Sexual orientation (1) was assessed from responses to the question of
the National Survey of Sexual Attitudes and Lifestyles of United Kingdom [
]: “Which of the
following statements do you feel more identified with?”, with six response options considering
attraction only to the opposite sex, usually to the opposite sex, equally to the same and opposite,
usually to the same, only to the same sex, or rather not answering. These were dichotomized into
heterosexual for those responding the first option, and LGB for the other four sexual attraction
Health-related behaviors. Information about lifetime use of the following psychoactive
drugs was gathered trough five groups of substances: tranquilizers, hashish or marihuana,
cocaine or by-products, amphetamines or similar, and heroine.
Alcohol consumption during the past year on working days and weekends separately was
collected, and weekly consumption was calculated with the formula: Standard drink units (1
unit = 10 g alcohol) Number of drinks frequency weekly [
]. Alcohol consumption was
categorized into non-drinker, moderate, or risk drinker (>17 or >28 alcohol units/week for
women and men, respectively).
Body mass index (BMI) was also considered, since the LGB population has consistently
been shown to have weight differences with respect to heterosexuals [
]. BMI was divided
into low/normal and overweight/obesity applying the cut-off point of 25.
Socio-demographic variables. Participants in 2011-BHIS were asked about their gender
(women or men), age, country of birth, education level, social class, social support, and
whether they were living with a partner. The maximum aggregation of categories for each
variable was used to avoid cells with zero individuals because the number of LGB participants was
small (n = 77).
3 / 15
Social class (manual and non-manual workers) was based on the Spanish National
Classification of Occupations 2011 using a neo-Weberian approach [
]. Country of birth was
categorized into low vs high income countries according to the GNI per capita (World Bank Atlas
Method for the 2011 fiscal year) [
]. Social support was assessed with the Duke-UNC
Functional Social Support Questionnaire composed of eight-items, using the recommended
percentile 15 [
] as the cut-off to define low social support.
Chronic conditions. Participants in the 2011-BHIS were asked about 15 chronic
conditions. A summary indicator based on the number of reported chronic conditions was
categorized according to sample distribution into 5 groups: none, 1, 2, 3±4, and 5 or more chronic
The 2011-BHIS sample size allows the detection of differences of 0.07 points on the EQ-5D
index mean (estimated as the minimal important difference [
]) between LGB (N = 77) and
heterosexual (N = 3,200) groups with alpha risk 0.05 and beta of 0.2. To restore the
representativeness of the Barcelona population, a weighting factor was applied for age, gender, and
municipal district. Unweighted frequencies and weighted percentages were calculated.
Differences between participants with and without information on sexual orientation, and
differences between LGB respondents and heterosexual counterparts were tested using χ2. Due to
the imbalance mainly in age between LGB and heterosexual groups, the percentages of chronic
conditions and health-related behaviors were adjusted by age and gender using logistic
To assess differences by sexual orientation on HRQoL, we built censored linear regression
models (Tobit) with EQ-5D index, and Poisson regression models with EQ-5D dimensions.
Censored linear regression models (Tobit) were used due to the right-skewed distribution of
EQ-5D index (dependent variable). Marginal effects were obtained from the Tobit model as
averaged individual marginal effects [
] to restore the original range of the EQ-5D index. The
original three-level response scale of EQ-5D dimensions was dichotomized into ªno problemsº
versus ªmoderate/extreme problemsº, and it was included as the dependent variable in Poisson
regression models with robust error variance. These models were used to estimate the
prevalence ratio [
], which is more interpretable and easier to communicate than an odds ratio
(obtained with logistic regression models) in cross-sectional studies.
In all cases, nested models were constructed to assess the mediator role of selected variables:
first including only sexual orientation, which is the principal explanatory variable (Model 1),
then adding sequentially gender and age (Model 2), socio-demographic variables (education
level, country of birth, and married or in sentimental partnership in Model 3), number of
chronic conditions (Model 4), and health-related behaviors (smoking status, alcohol
consumption, and psychoactive drug consumption in Model 5). These nested models were compared
with the immediately previous one using the log-likelihood ratio test. Interactions of sexual
orientation with gender and age were tested.
Finally, a sensitivity analysis was performed by excluding participants that reported being
attracted to the same sex only sometimes, to test validity of sexual orientation definition (S1
File). A sensitivity analysis was also carried out for comparison purposes by matching LGB
and heterosexual individuals with propensity score. The primary objective of this analysis
was to maximize the balance in the distribution of possible confounders between LGB and
heterosexual groups. A logistic regression model was constructed to estimate the conditional
probability of belonging to each group (propensity score) by including socio-demographic
characteristics as independent variables. Quartiles of this conditional probability were used to
4 / 15
define four propensity score categories. LGB individuals were matched with heterosexual
counterparts (ratio 1:5) according to propensity score quartile, age group, and gender. The five
heterosexual participants for each LGB individual were randomly selected, giving priority to
individuals with less potential pairs. In this sensitivity analysis, conditional logistic regression
was used to estimate odds ratio of reporting EQ-5D problems to take into account the
matching, instead of the Poisson regression with robust error variance used in the main analysis
strategy (S2 File).
Of the 3,524 participants, 247 (7%) did not state their sexual orientation. The non-respondents
were older (p<0.001), with a lower education level (p = 0.021), less frequently married or in a
sentimental partnership (p<0.001), and with lower social support (p = 0.011) than participants
who responded (Table 1).
Of 3,277 respondents, 3,200 only felt attracted to the opposite sex and 77 (2.3%) became
attracted to the same sex with varying frequency. This latter group was composed of: 34 who
only felt attracted to the same sex, 8 only sometimes to the opposite sex; 13 felt equally
attracted to both sexes; and 22 only sometimes to the same sex. Characteristics of the
heterosexual and LGB groups are shown in Table 2. Differences by sexual orientation were not
The first three columns show the unadjusted percentages, and the last three columns the adjusted percentages by gender and age. LGB: Lesbian, gay or bisexual. Bold:
significant p-value ( p-value<0.05; p-value<0.01).
6 / 15
significant regarding gender and social class, but they were significant for several other
variables. The LGB group was younger (56.6 vs 28.4% <35 years old; p<0.001), with higher
education level (44.7% vs 32.0% university; p = 0.013), was less frequently married or in a
sentimental partnership (25.0% vs 58.0%; p = 0.001), and came more frequently from low-income
countries (22.1% vs 12.7%; p = 0.031). Adjusted percentages of most health-related variables
presented statistically significant differences: the LGB group reported chronic conditions more
frequently (p = 0.018), higher consumption of tobacco (76.0% vs 48.2%; p<0.001), and
psychoactive substances (52.3% vs 18.8%; p<0.001).
Table 3 presents nested Tobit models with the EQ-5D index as the dependent variable.
Model 1 shows that there is no significant crude difference on EQ-5D index by sexual
orientation. After adjusting by gender and age (Model 2), the difference is statistically significant
(-0.052, p = 0.04). Model 3 with all the sociodemographic variables shows a very similar
difference (-0.055; p = 0.029). Once number of chronic conditions was considered (model 4),
the difference on EQ-5D index by sexual orientation is no longer significant (-0.031;
p = 0.145). After adding health-related behaviors (model 5), this difference was -0.003
(p = 0.899).
Nested models constructed with each of the three physical dimensions of the EQ-5D as
dependent variables are shown in Fig 1. The crude prevalence ratio (Model 1) was not
significant for any dimension. However, mobility and usual activities dimensions showed statistically
significant differences by sexual orientation after adjusting for age and gender (Model 2), for
all sociodemographic variables (Model 3), and for number of chronic conditions (Model 4).
These differences were no longer statistically significant after adding health-related behaviors
in model 5.
Since models of the EQ-5D's two mental dimensions presented statistically significant
interactions with gender, further models were constructed for men and women separately (Fig
2). Among men, nested models showed statistically significant adjusted prevalence ratios in
models 2 and 3: for pain/discomfort aPR was 2.88 and 3.15; and for anxiety/depression aPR
was 2.85 and 2.49. These differences ceased to be significant in model 5 for pain/discomfort,
and in model 4 for anxiety/depression. However, no differences by sexual orientation were
observed among women.
Sensitivity analysis performed after excluding the 22 participants who reported only
sometimes becoming attracted to the same sex is shown in S1 File. Results of nested models with the
EQ-5D index and its dimensions as dependent variables were consistent with the results
obtained from the 77 individuals primarily considered in the LGB group. Also, results of the
sensitivity analysis done with LGB individuals and matched heterosexual counterparts (ratio
1:5) were consistent with findings obtained through the main analysis strategy, showed in the
tables and figures within the article (S2 File).
In our study, the LGB group clearly showed worse HRQoL than the heterosexuals. This health
inequality was consistently observed in the EQ-5D index and most EQ-5D dimensions. Such
pattern is common among men and women for physical health dimensions (mobility and
usual activities), but differs by sex for mental health dimensions (pain/discomfort and anxiety/
depression). It is important to highlight that HRQoL differences by sexual orientation
disappeared when we considered chronic conditions and health-related behaviors, suggesting that
these played a major mediator role.
These results support our hypotheses of worse HRQoL in the LGB population, and that the
effect of sexual orientation on mental health is modified by gender. After adjusting by age,
7 / 15
gender, and socio-demographic variables, the magnitude of the EQ-5D index difference
(-0.055) is very close to the minimal important difference, estimated previously at ±0.07 for
this instrument [
]. Translating this adjusted mean difference to QALYs, -0.055 is
interpretable as 20 fewer days of full health per year experienced by each LGB individual. Considering
8 / 15
Fig 1. Prevalence ratios and 95% Confidence Intervals (65%CI) by sexual orientation for each physical EQ-5D dimension, considering
different adjustment variables. The EQ-5D dimension (dependent variable) was dichotomized into: no problems vs moderate/extreme problems.
Model 1: Crude prevalence ratio. Model 2: Adjusted by age and gender. Model 3: Adjusted by age and gender + sociodemographic variables
(education level, country of birth, and married or in sentimental partnership). Model 4: Adjusted by age and gender + sociodemographic
variables + number of chronic conditions. Model 5: Adjusted by age and gender + sociodemographic variables + number of chronic conditions +
health-related behaviors (smoking status, alcohol consumption, and psychoactive drug consumption).
9 / 15
Fig 2. Prevalence ratios and 95% Confidence Intervals (65%CI) by sexual orientation for each mental EQ-5D dimension stratified by gender, considering
different adjustment variables. The EQ-5D dimension (dependent variable) was dichotomized into: no problems vs moderate/extreme problems. Model 1: Crude
prevalence ratio. Model 2: Adjusted by age and gender. Model 3: Adjusted by age and gender + sociodemographic variables (education level, country of birth, and
married or in sentimental partnership). Model 4: Adjusted by age and gender + sociodemographic variables + number of chronic conditions. Model 5: Adjusted by
age and gender + sociodemographic variables + number of chronic conditions + health-related behaviors (smoking status, alcohol consumption, and psychoactive
the 2.3% proportion of LGB among the 1.6 million inhabitants, the total number of full health
days lost each year would be higher than 700,000 in Barcelona.
Results of the previous health surveys which have explored HRQoL inequalities by sexual
orientation consistently showed worse mental [
], but not physical  health for the LGB
group. The United States Growing Up Today Study showed sexual orientation differences in
the EQ-5D single index, without reporting mental and physical EQ-5D dimensions [
SF-36 physical component differences were reported in the Dutch survey [
]. The California
Quality of Life Survey [
] only showed a higher risk of poor SF-12 physical health for bisexual
women and homosexually-experienced heterosexuals. In our study, in contrast to these
previous findings, two of the main physical dimensions of EQ-5D, mobility and usual activities,
10 / 15
showed consistent health inequalities in both genders by sexual orientation. The prevalence
ratios indicate a 110% and 77% higher probability of having problems in usual activities and
mobility, respectively, for LGB people.
Regarding mental health, the prevalence ratio for anxiety/depression in our study indicates
a 185% higher probability of having problems among gay/bisexual men but not among
women. Similarly, pain/discomfort dimension also presented a 188% higher probability of
problems for gay/bisexual men compared to heterosexuals. Our results for men are consistent
with the SF-36 mental component in the Dutch survey [
], and also with the meta-analysis of
]. The latter additionally found that interaction with gender was statistically significant
indicating stronger effects for men.
In our study, the LGB group was considerably younger than its heterosexual counterpart
(mean 39.6 vs 48.6 years; p<0.001). Response and survival biases are two possible reasons for
this age difference. First, older LGB individuals may be less likely than the younger ones to
report their true sexual orientation, because during the Spanish dictatorship homosexuality
was punishable with prison under the ªLaw of Vagrants and Crooksº. This theory is consistent
with the results of our analysis comparing participants with and without information on sexual
orientation, as people who did not answer the question on sexual attraction were significantly
older than those who responded it. Second, there is considerable evidence of higher mortality
for the LGB population [
], leading possibly to a survival bias. The 2001±2010 National
Health and Nutrition Examination Surveys reported greater all-cause mortality for LGB than
for heterosexuals (adjusted hazard ratio = 2) . Another USA study [
] showing a 12-year
shorter life expectancy for LGB individuals from communities with high anti-gay prejudice
levels versus low ones [
] revealed suicide, homicide/violence, and cardiovascular diseases as
the underlying specific mortality causes.
Results from nested models support our hypothesis regarding the effect of sexual
orientation through the continuum from vulnerabilities to outcomes. Chronic conditions and risk
behaviors are the principal factors explaining the HRQoL differences by sexual orientation in
these models, suggesting their principal mediator role in LGB health inequalities. Statistical
significance of sexual orientation disappeared after including them in the models. The
Californian survey showed higher prevalence in LGB than in heterosexual participants for certain
chronic conditions, especially for those related with tobacco, alcohol and drug consumption,
such as asthma, heart disease, and cancer [
]. The prevalence of tobacco, alcohol and
psychoactive drug consumption in our LGB subsample is around 2-fold higher than that of their
heterosexual counterparts, even after adjusting by age and gender, which is consistent with
]. For example, in Massachusetts [
], the probability of current smoking
and any 30-day drug use was also at least 2 times greater among LGB than heterosexuals; and
in England [
], the LGB group reported almost 2 times higher significant alcohol and drug
dependence. This pattern of worse health-related behaviors has been related to discrimination
and stigma [
], which may lead to a reduction of self-control in those who feel threatened by
their social identity. Minority stress theory proposes that stressors induced by homophobic
culture require an individual to adapt and may affect physical and mental health [
should be considered an unfair and avoidable inequity. However, further than chronic
conditions related with discrimination and substance abuse, other risk behaviors, such as unsafe
sexual practices and their associated conditions should be considered as potential causes of the
worse HRQoL experienced by LGB individuals.
Since data of this study came from the health survey of a large European city, results are
representative of an urban setting. We have to highlight that the EQ-5D is a generic and
standardized instrument which provides a simple descriptive profile and a robust single
preference-based index [
]. In addition, the EQ-5D has proved its usefulness as a HRQoL
11 / 15
measure for the general population , and detecting socioeconomic health inequalities
]. This is the first study to have explored the mediator role of socio-demographic
characteristics, health-related behaviors, and chronic conditions in health inequalities by sexual
The main limitation is that the LGB group was constructed based only on sexual
attraction, without considering self-identification and sexual behavior [
]. However, sexual
attraction covers some of the gaps left out by behavior or identity measures, and it has been
argued that identity-based conceptualizations of sexual orientation may not adequately
account for the possible variations in the population's sexuality [
]. In addition, recent
studies have shown that sexual attraction measures are more predictive than sexual identity
ones to detect inequalities by sexual orientation [
]. Second, the proportion of individuals
not answering the question on sexual attraction was high (7%) and part of them could be
LGB. Taking into account the low number of LGB participants in the sample (2.3%), biases
of non-response and social desirability affecting the sexual orientation question may have
produced an infra-estimation of this group. However, the LGB percentage was similar to
other developed country population surveys [
]. As showed previously, a sizable
proportion of LGB people are unwilling to disclose their sexual orientation in surveys .
Consistently with our results, willingness is influenced by age, living environment (social support),
education and partnership status, suggesting that general population surveys may not be
fully representative of gay and bisexual populations. Third, the Barcelona Health Interview
Survey design is cross-sectional, which constrains causality assessment. However, it is
more plausible that sexual orientation has a negative effect on health than the inverse
relationship (poor health affecting sexual orientation). Finally, the small proportion of LGB
participants did not allow stratifying for age, but its interaction with sexual orientation was not
The LGB population presented worse HRQoL than the heterosexual one; and gender, chronic
conditions, and health-related behaviors play a major role in explaining such differences.
These findings support the need of including sexual orientation into the global agenda of
health inequities, and provide helpful information for developing new effective public health
strategies from promotion to tertiary prevention including: education based on sexual
diversity, evidence-based public health interventions on general population to reduce external/
social and internalized homophobia, and recommendations for health professionals to
improve the LGB population's health.
S1 File. Sensitivity analysis performed to test validity of sexual orientation definition by
excluding participants that reported being attracted to the same sex only sometimes.
S2 File. Sensitivity analysis with LGB individuals and matched heterosexual counterparts
We would like to acknowledge Aurea Martin for her help in the English editing process and
supervision of this manuscript.
12 / 15
Conceptualization: Marc Marti-Pastor, Gloria Perez, Danielle German, Jordi Alonso, Montse
Data curation: Marc Marti-Pastor, Angels Pont.
Formal analysis: Marc Marti-Pastor, Angels Pont, Jordi Alonso, Mercè Gotsens.
Investigation: Marc Marti-Pastor, Gloria Perez, Danielle German, Jordi Alonso, Mercè
Methodology: Marc Marti-Pastor, Angels Pont, Olatz Garin, Jordi Alonso, Mercè Gotsens,
Supervision: Gloria Perez, Danielle German, Jordi Alonso, Montse Ferrer.
Validation: Gloria Perez, Danielle German, Jordi Alonso, Montse Ferrer.
Visualization: Marc Marti-Pastor, Olatz Garin, Jordi Alonso, Montse Ferrer.
Writing ± original draft: Marc Marti-Pastor, Gloria Perez, Danielle German, Angels Pont,
Olatz Garin, Jordi Alonso, Mercè Gotsens, Montse Ferrer.
Writing ± review & editing: Marc Marti-Pastor, Danielle German, Jordi Alonso, Montse
13 / 15
14 / 15
1. Truman BI , Smith KC , Roy K , Chen Z , Moonesinghe R , Zhu J , et al. Rationale for regular reporting on health disparities and inequalitiesÐUnited States . MMWR Suppl 2011 ; 60 ( 1 ):3± 10 . PMID: 21430613
2. Hatzenbuehler ML , Bellatorre A , Lee Y , Finch BK , Muennig P , Fiscella K. Structural stigma and allcause mortality in sexual minority populations . Soc Sci Med 2014 ; 103 : 33 ± 41 . https://doi.org/10.1016/j. socscimed. 2013 . 06 .005 PMID: 23830012
3. Sandfort TG , Bakker F , Schellevis FG , Vanwesenbeeck I. Sexual orientation and mental and physical health status: findings from a Dutch population survey . Am J Public Health 2006 ; 96 ( 6 ): 1119 ± 1125 . https://doi.org/10.2105/AJPH. 2004 .058891 PMID: 16670235
4. Cochran SD , Mays VM . Physical health complaints among lesbians, gay men, and bisexual and homosexually experienced heterosexual individuals: results from the California Quality of Life Survey . Am J Public Health 2007 ; 97 ( 11 ): 2048 ± 2055 . https://doi.org/10.2105/AJPH. 2006 .087254 PMID: 17463371
Ward BW , Dahlhamer JM , Galinsky AM , Joestl SS . Sexual orientation and health among U.S. adults: national health interview survey , 2013. Natl Health Stat Report 2014 ;( 77): 1 ± 10 .
6. Semlyen J , King M , Varney J , Hagger-Johnson G . Sexual orientation and symptoms of common mental disorder or low wellbeing: combined meta-analysis of 12 UK population health surveys . BMC Psychiatry 2016 ; 16 ( 1 ): 67 .
7. Perez G , Marti-Pastor M , Gotsens M , Bartoll X , Diez E , Borrell C . Health and health-related behaviors according to sexual attraction and behavior . Gac Sanit 2015 ; 29 ( 2 ): 135 ± 138 .
8. Chakraborty A , McManus S , Brugha TS , Bebbington P , King M. Mental health of the non-heterosexual population of England . Br J Psychiatry 2011 ; 198 ( 2 ): 143 ± 148 . https://doi.org/10.1192/bjp.bp. 110 . 082271 PMID: 21282785
9. Austin SB , Gordon AR , Ziyadeh NJ , Charlton BM , Katz-Wise SL , Samnaliev M. Stigma and HealthRelated Quality of Life in Sexual Minorities . Am J Prev Med . 2017 Oct; 53 ( 4 ): 559 ± 566 . https://doi.org/ 10.1016/j.amepre. 2017 . 05 .007 PMID: 28756895
10. de Wit M , Hajos T . Encyclopedia of Behavioral Medicine. Gellman MD , Turner JR , editors. 929 ± 931 . 2013 . Springer Science+Business Media New York.
Wilson IB , Cleary PD . Linking clinical variables with health-related quality of life. A conceptual model of patient outcomes . JAMA 1995 ; 273 ( 1 ): 59 ± 65 . PMID: 7996652
12. Brooks R. EuroQol : the current state of play . Health Policy 1996 ; 37 ( 1 ): 53 ± 72 . PMID: 10158943
World Health Organization. Glossary of terms used. 10-3-2017.
14. Solar O , Irwin A . A conceptual framework for action on the social determinants of health . Discussion paper for the Commission on Social Determinants of Health . 2007 Apr.
15. Mule NJ , Ross LE , Deeprose B , Jackson BE , Daley A , Travers A , et al. Promoting LGBT health and wellbeing through inclusive policy development . Int J Equity Health 2009 ; 8 : 18 . https://doi.org/10.1186/ 1475 -9276-8-18 PMID: 19442315
16. Branstrom R , Hatzenbuehler ML , Pachankis JE . Sexual orientation disparities in physical health: age and gender effects in a population-based study . Soc Psychiatry Psychiatr Epidemiol 2016 ; 51 ( 2 ): 289 ± 301 . https://doi.org/10.1007/s00127-015 -1116-0 PMID: 26298574
17. Fredriksen-Goldsen KI , Kim HJ , Barkan SE , Muraco A , Hoy-Ellis CP . Health disparities among lesbian, gay, and bisexual older adults: results from a population-based study . Am J Public Health 2013 ; 103 ( 10 ): 1802 ± 1809 . https://doi.org/10.2105/AJPH. 2012 .301110 PMID: 23763391
18. Conron KJ , Mimiaga MJ , Landers SJ . A population-based study of sexual orientation identity and gender differences in adult health . Am J Public Health 2010 ; 100 ( 10 ): 1953 ± 1960 . https://doi.org/10.2105/ AJPH. 2009 .174169 PMID: 20516373
19. Pew Research Center. The Global Divide on Homosexuality. Greater acceptance in more acceptance and affluent countries . 2013 Jun 4 .
20. Bartoll X , Rodriguez-Sanz M , Borrell C. Manual de l'Enquesta de Salut de Barcelona 2011. Barcelona: Agència de Salut PuÂblica de Barcelona . 2012 . Departament de Salut, Generalitat de Catalunya; 2012 Jul 1 .
21. Johnson JA , Pickard AS . Comparison of the EQ-5D and SF-12 health surveys in a general population survey in Alberta, Canada . Med Care 2000 ; 38 ( 1 ): 115 ± 121 . PMID: 10630726
22. Cunillera O , Tresserras R , Rajmil L , Vilagut G , Brugulat P , Herdman M , et al. Discriminative capacity of the EQ-5D, SF-6D, and SF-12 as measures of health status in population health survey . Qual Life Res 2010 ; 19 ( 6 ): 853 ± 864 . https://doi.org/10.1007/s11136-010-9639-z PMID: 20354795
23. Badia X , Roset M , Herdman M , Kind P. A comparison of United Kingdom and Spanish general population time trade-off values for EQ-5D health states . Med Decis Making 2001 ; 21 ( 1 ):7± 16 . https://doi.org/ 10.1177/0272989X0102100102 PMID: 11206949
24. Erens B , McManus S , Prescott P et al. National Survey of Sexual Attitudes and Lifestyles II: Reference tables and summary report . National Centre for Social Research ; 2002 .
25. Rehm J , Klotsche J , Patra J . Comparative quantification of alcohol exposure as risk factor for global burden of disease . Int J Methods Psychiatr Res 2007 ; 16 ( 2 ): 66 ± 76 . https://doi.org/10.1002/mpr.204 PMID: 17623386
26. Katz-Wise SL , Blood EA , Milliren CE , Calzo JP , Richmond TK , Gooding HC , et al. Sexual Orientation Disparities in BMI among US Adolescents and Young Adults in Three Race/Ethnicity Groups . J Obes 2014 ; 2014 :537242. https://doi.org/10.1155/ 2014 /537242 PMID: 24872890
27. Domingo-Salvany A , Bacigalupe A , Carrasco JM , Espelt A , Ferrando J , Borrell C . Proposals for social class classification based on the Spanish National Classification of Occupations 2011 using neo-Weberian and neo-Marxist approaches . Gac Sanit 2013 ; 27 ( 3 ): 263 ± 272 .
28. The World Bank. World Bank Country and Lending Groups . 9 -3-2017.
29. Bellon Saameno JA , Delgado SA , Luna del Castillo JD , Lardelli CP . Validity and reliability of the DukeUNC-11 questionnaire of functional social support . Aten Primaria 1996 ; 18 ( 4 ): 153 ± 163 . PMID: 8962994
30. Walters SJ , Brazier JE . Comparison of the minimally important difference for two health state utility measures: EQ-5D and SF-6D . Qual Life Res 2005 ; 14 ( 6 ): 1523 ± 1532 . PMID: 16110932
31. Cunillera O. Tobit Models . Encyclopedia of quality of life and well-being research . In:Edited by Michalos AC , Springer, Netherlands, 2014 , pp 6671 ± 6676 .
32. Barros AJ , Hirakata VN . Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio . BMC Med Res Methodol . 2003 Oct 20 ; 3 : 21 . https://doi.org/10.1186/ 1471 -2288-3-21 PMID: 14567763
33. Cochran SD , Bjorkenstam C , Mays VM . Sexual Orientation and All-Cause Mortality Among US Adults Aged 18 to 59 Years, 2001 ± 2011 . Am J Public Health 2016 ; 106 ( 5 ): 918 ± 920 . https://doi.org/10.2105/ AJPH. 2016 .303052 PMID: 26985610
34. Pascoe EA , Smart RL . Perceived discrimination and health: a meta-analytic review . Psychol Bull 2009 ; 135 ( 4 ): 531 ± 554 . https://doi.org/10.1037/a0016059 PMID: 19586161
35. Meyer IH. Prejudice, social stress, and mental health in lesbian, gay and bisexual populations: conceptual issues and research evidence .
36. Maheswaran H , Kupek E , Petrou S . Self-reported health and socio-economic inequalities in England, 1996 ±2009: Repeated national cross-sectional study . Soc Sci Med 2015 ; 136 ± 137 : 135 ± 146 . https:// doi.org/10.1016/j.socscimed. 2015 . 05 .026 PMID: 26004207
37. Chandra A , Mosher WD , Copen C , Sionean C. Sexual behavior, sexual attraction, and sexual identity in the United States: data from the 2006±2008 National Survey of Family Growth . Natl Health Stat Report 2011 ;(36): 1 ± 36 . PMID: 21560887
38. Johns MM , Zimmerman M , Bauermeister JA . Sexual attraction, sexual identity, and psychosocial wellbeing in a national sample of young women during emerging adulthood . J Youth Adolesc 2013 ; 42 ( 1 ): 82 ± 95 . https://doi.org/10.1007/s10964-012 -9795-2 PMID: 22847750
39. Ferlatte O , Hottes TS , Trussler T , Marchand R . Disclosure of Sexual Orientation by Gay and Bisexual Men in Government-Administered Probability Surveys . LGBT Health . 2017 Feb; 4 ( 1 ): 68 ± 71 . https://doi. org/10.1089/lgbt. 2016 .0037 PMID: 27657734