A socioecological measurement of homophobia for all countries and its public health impact

A socioecological measurement of homophobia for all countries and its public health impact Abstract Background Measuring homophobia at country level is important to guide public health policy as reductions in stigma are associated with improved health outcomes among gay men and other men who have sex with men. Methods: We developed a Homophobic Climate Index incorporating institutional and social components of homophobia. Institutional homophobia was based on the level of enforcement of laws that criminalise, protect or recognise same-sex relations. Social homophobia was based on the level of acceptance and justifiability of homosexuality. We estimated the Index for 158 countries and assessed its robustness and validity. Results Western Europe is the most inclusive region, followed by Latin America. Africa and the Middle East are home to the most homophobic countries with two exceptions: South Africa and Cabo Verde. We found that a 1% decrease in the level of homophobia is associated with a 10% increase in the gross domestic product per capita. Countries whose citizens face gender inequality, human rights abuses, low health expenditures and low life satisfaction are the ones with a higher homophobic climate. Moreover, a 10% increase in the level of homophobia at country level is associated with a 1.7-year loss in life expectancy for males. A higher level of homophobia is associated with increased AIDS-related death among HIV-positive men. Conclusion The socioecological approach of this index demonstrates the negative social, economic and health consequences of homophobia in low- and middle-income countries. It provides sound evidence for public health policy in favour of the inclusion of sexual minorities. Introduction Despite noticeable progress in terms of inclusion of sexual minorities in the vast majority of countries over the last 40 years, the stigma associated with gay men and other men who have sex with men (MSM) is still prevalent in most societies. Stigma applies when elements of labelling, stereotyping, separation, status loss and discrimination co-occur in a power situation that allows the components of stigma to unfold.1 Stigma can occur at individual, interpersonal and structural levels.2,3 Homophobia, a particular case of stigma based on sexual orientation and gender identity, affects primarily lesbian, gay, bisexual, transgender and intersex people (LGBTI). Several definitions focus on the clinical aspect of a phobia, describing homophobia as ‘an irrational, persistent fear or dread of homosexuals’.4 Here, we use the term homophobia to refer to any negative attitude, belief, or action toward persons of differing sexual orientation or gender identity. It includes laws and structural manifestations of that prejudice in institutional settings, such as the workplace.5 This working definition encompasses the three levels of stigma described earlier. The level of infringement of human rights, verbal and physical violence and denial of health services associated with homophobia is a public health issue. Stigma is a central driver of morbidity and mortality at a population level.6 Gay men facing enacted sexual stigma are more likely to engage in sexual risk behaviours.7,8 They are less likely to adhere to their antiretroviral treatment9 and have lower HIV testing rates.9–15 Finally, internalized homonegativity is associated with lower levels of HIV testing and lower levels of condom use in gay and bisexual men.16 A socio-ecological approach to health-related behaviour17 allows for studies of stigma related to sexual orientation and gender identity in their broader structural and social dimensions.1,6,18 Most studies of homophobia focused at the individual level. Being able to identify the level of homophobia at country level is important to guide public health policies as recent evidence shows that reductions in the homophobic climate are associated with improved health outcomes among gay men and other MSM.19 This study aims to propose and validate a robust index to measure homophobia at country level, including in low- and middle-income countries (LMIC). Methods Data sources The availability and reliability of data on stigma and discrimination related to gender identity and sexual orientation and gender identity is uneven from country to country. Data on HIV and on gay men and other MSM were obtained from AIDSinfo20 an online repository of global AIDS data compiled and maintained by UNAIDS, as well as from scientific articles and grey literature. Economic and development indicators such as gross domestic product, health expenditures, proportion of seats held by women in parliaments, gender inequality, mean years of schooling and life expectancy were drawn from the IMF World Economic Outlook, the 2015 Human Development Report and the World Population Prospects published by the Department of Economic and Social Affairs of the United Nations Population Division. We used the individual data from the World Values Survey which we aggregated at country level. The information on laws and legislation comes from the International Lesbian, Gay, Bisexual, Trans and Intersex Association (ILGA). The rule of law index comes from the World Justice Project and the Cantril index from the Gallup World Poll. We used the data on homophobia made available by the Pew Research Center. We used STATA 14 for statistical analysis. Model and analytic strategy We propose a socio-ecological construct for measuring homophobia that translates the important role played by institutional but also interpersonal factors. Let the level of homophobia for a country (i) be the combination of institutional (IsH) and social (SoH) homophobia for each country (i). HCIi=β1IsHi+β2SoHi (1) Institutional homophobia Institutional homophobia, IsHi, relates to the formal codes, such as laws and legislations that societies adhere to. Some of these codes may establish an institutional construct for inclusion or discrimination against people based on their sexual orientation or gender identity. These laws in their turn influence people’s behaviour and thoughts towards persons of differing sexual orientations and gender identities.21–24 First, we considered a set of 11 laws that characterise the level of institutionalized of homophobia of a country. For each country, those 11 laws are individually valued from 1 to 3 whether it is inexistent, existent and in force, or in force only in parts of its territory. The level of implementation is the one reported by the International Lesbian, Gay, Bisexual, Trans and Intersex Association.25 Second, we estimated the coefficients for these 11 laws globally. To ensure a transparent and objective weighting system, we considered the way all countries are combining (or not) a said law with the ten other laws considered here. By doing so, we reflect the choice of countries to enforce laws favouring inclusion and protection or, a contrario, laws criminalizing same-sex relationships. To do so, we built polychoric correlation matrices as these variables are categorical and ordinal. Our methods demonstrated high internal consistency with an ordinal alpha of 0.92 and 0.83 for the inclusion and the criminalizing laws, respectively. The weight of each law was then estimated by a factor analysis. Laws and their coefficients are presented in Supplementary annex S1. Institutional homophobia is expressed as IsHi=∑n=111γnLn,i+ɛi (2) where γn are the factor loadings for the each law n and Ln,i is the level of enforcement of law n in country i, with Ln=1, 3 and i=1, 158. Social homophobia Social homophobia, SHi, relates to interactions between communities or groups and individuals. A key characteristic is the direct reaction of individuals towards gay men and other MSM. Social homophobia reflects societal norms and behaviours based on moral, religious and cultural beliefs. It encompasses interpersonal processes as well as physical reactions such as avoidance or aggression, whether sexual, verbal or physical. These reactions take form in social networks such as family, workplace or friends. It can also be found within communities, whether ethnic, cultural, moral or religious ones. Markers of social homophobia are difficult to measure, particularly at country level. We focus on the interpersonal reactions, assuming it reflects the ultimate degree of societal penetration. We considered two representative questions asked to >460 000 individuals in 91 countries within the three most recent waves of World Values Survey,26 the 2008 European Values Survey27 and the Afrobarometer.28 The first question is ‘On this list are various groups of people. Could you please mention any that you would not like as neighbours?’ This is a dichotomized answer whether respondents selected ‘homosexuals’ or not. The second question was, ‘Do you think [homosexuality] can always be justified, never be justified, or something in between?’ Answers were given on a scale from 1 to 10, with 1 meaning never justifiable and 10 meaning always justifiable. For each question, we considered the answers from all respondents for each country and calculated a country-specific value. Following a factor analysis, we weighted these two variables equally. We performed multiple imputations and predicted values for the remaining 45 countries with missing values for social homophobia, representing slightly more than a quarter (28%) of the total number of countries studied (158). The social homophobia component can be expressed as: SoHi=1n∑nacceptance n,i+justifiabilityn,i (3) Where n = number of respondents for country i and i=1, 158. We also considered homophobic violence. Unfortunately, only a minority of countries, essentially the least homophobic ones, systematically record homophobic violence and hate crimes. Reporting homophobic violence requires that the victims reveal their sexual orientation which, in too many countries still, may expose him/her to additional risks of violence and retaliation. It is worth noting that there has been remarkable progress by non-State actors in reporting hate crimes in several countries. Despite these advancements, data are still scarce, often limited to capital cities or large urban areas. If more data become available in the future, homophobic violence can be integrated in equation (3). We developed the homophobic climate index by compiling institutional and social homophobia data. Both components are weighted equally as confirmed with a factor analysis, i.e. β1=β2 in equation (1). Reliability and validity of the homophobic climate index We measured the internal consistency of the index with a reliability coefficient, measured by the Cronbach’s alpha. We also performed a confirmatory factor analysis to confirm that the scale in question is unidimensional. In order to assess the validity of the HCI, we first controlled the results from regressions of the HCI for two subsamples of countries randomly selected, with independent social and economic variables such as income, gender equality, human rights, satisfaction in life, health expenditures and compared with the results obtained with the whole set of countries. Finally, we examined the stability of the correlation between the HCI and a control index to assess whether our instrument measures what we want to measure. We used the Gallup29 question on homophobia ‘is the city or area where you live a good place or not a good place for gay or lesbian people’ as control index and performed iterated regressions. Results The model and data available enabled the estimation of the homophobic climate index (HCI) for 158 countries. The index shows good internal consistency, with a Cronbach’s alpha of 0.82, and the control regressions with subsamples countries as well as with the control index enable us to consider the HCI a statistically reliable and valid index to measure homophobia. Regression and statistical tests are presented in Supplementary annex S2. The index ranges from 0 to 1, with higher values for more homophobic countries. Figure 1 presents the map of the homophobic climate (See Supplementary annex S3 for the ranking of 158 countries). Table 1 presents the 10 most inclusive countries, globally (1a) and among low- and middle-income countries (1b). The 10 most homophobic countries are also listed (1c). Table 1 Homophobic Climate Index 2017: Top 10 most inclusive and most homophobic countries 1a: Top 10 most inclusive countries 1b: Top 10 most inclusive low-and middle-income countries (LMIC) 1c: Top 10 most homophobic countries Rank Country HCI Rank Country HCI Rank Country HCI 1 Sweden 0.112 18 Colombia 0.321 149 Tunisia 0.870 2 Netherlands 0.131 20 Brazil 0.338 150 Burundi 0.873 3 Denmark 0.137 22 South Africa 0.352 151 Iraq 0.878 4 Norway 0.140 25 Mexico 0.369 152 Guinea 0.880 5 Spain 0.163 28 Ecuador 0.400 153 Nigeria 0.884 6 Finland 0.168 35 Romania 0.443 154 Qatar 0.897 7 Belgium 0.177 36 Costa Rica 0.444 155 South Sudan 0.905 8 France 0.180 41 Cabo Verde 0.474 156 Saudi Arabia 0.926 9 Uruguay 0.189 42 Serbia 0.482 157 Afghanistan 0.935 10 United Kingdom 0.206 43 Bolivia 0.489 158 Sudan 0.957 1a: Top 10 most inclusive countries 1b: Top 10 most inclusive low-and middle-income countries (LMIC) 1c: Top 10 most homophobic countries Rank Country HCI Rank Country HCI Rank Country HCI 1 Sweden 0.112 18 Colombia 0.321 149 Tunisia 0.870 2 Netherlands 0.131 20 Brazil 0.338 150 Burundi 0.873 3 Denmark 0.137 22 South Africa 0.352 151 Iraq 0.878 4 Norway 0.140 25 Mexico 0.369 152 Guinea 0.880 5 Spain 0.163 28 Ecuador 0.400 153 Nigeria 0.884 6 Finland 0.168 35 Romania 0.443 154 Qatar 0.897 7 Belgium 0.177 36 Costa Rica 0.444 155 South Sudan 0.905 8 France 0.180 41 Cabo Verde 0.474 156 Saudi Arabia 0.926 9 Uruguay 0.189 42 Serbia 0.482 157 Afghanistan 0.935 10 United Kingdom 0.206 43 Bolivia 0.489 158 Sudan 0.957 Table 1 Homophobic Climate Index 2017: Top 10 most inclusive and most homophobic countries 1a: Top 10 most inclusive countries 1b: Top 10 most inclusive low-and middle-income countries (LMIC) 1c: Top 10 most homophobic countries Rank Country HCI Rank Country HCI Rank Country HCI 1 Sweden 0.112 18 Colombia 0.321 149 Tunisia 0.870 2 Netherlands 0.131 20 Brazil 0.338 150 Burundi 0.873 3 Denmark 0.137 22 South Africa 0.352 151 Iraq 0.878 4 Norway 0.140 25 Mexico 0.369 152 Guinea 0.880 5 Spain 0.163 28 Ecuador 0.400 153 Nigeria 0.884 6 Finland 0.168 35 Romania 0.443 154 Qatar 0.897 7 Belgium 0.177 36 Costa Rica 0.444 155 South Sudan 0.905 8 France 0.180 41 Cabo Verde 0.474 156 Saudi Arabia 0.926 9 Uruguay 0.189 42 Serbia 0.482 157 Afghanistan 0.935 10 United Kingdom 0.206 43 Bolivia 0.489 158 Sudan 0.957 1a: Top 10 most inclusive countries 1b: Top 10 most inclusive low-and middle-income countries (LMIC) 1c: Top 10 most homophobic countries Rank Country HCI Rank Country HCI Rank Country HCI 1 Sweden 0.112 18 Colombia 0.321 149 Tunisia 0.870 2 Netherlands 0.131 20 Brazil 0.338 150 Burundi 0.873 3 Denmark 0.137 22 South Africa 0.352 151 Iraq 0.878 4 Norway 0.140 25 Mexico 0.369 152 Guinea 0.880 5 Spain 0.163 28 Ecuador 0.400 153 Nigeria 0.884 6 Finland 0.168 35 Romania 0.443 154 Qatar 0.897 7 Belgium 0.177 36 Costa Rica 0.444 155 South Sudan 0.905 8 France 0.180 41 Cabo Verde 0.474 156 Saudi Arabia 0.926 9 Uruguay 0.189 42 Serbia 0.482 157 Afghanistan 0.935 10 United Kingdom 0.206 43 Bolivia 0.489 158 Sudan 0.957 Figure 1 View largeDownload slide Homophobic climate index Figure 1 View largeDownload slide Homophobic climate index The most inclusive countries are essentially in Western Europe and Uruguay. Among the LMIC, Latin America appears as a leading region in promoting inclusion and fighting homophobia. It is worth noting that two African countries, South Africa and Cabo Verde are among the top 10 most inclusive LMIC. The case of South Africa is particularly interesting as it paves the way to a more comprehensive and successful response to the HIV epidemic that could serve as an example in other countries of the region. Homophobia and socioeconomic determinants We performed multivariate regressions, using the country level of homophobia as explanatory variable to predict the value of key socioeconomic and public health outcome variables. It should be reminded that results of these regressions represent correlation and do not necessarily imply causal relationships. Descriptive statistics of the variables are presented in Supplementary annex S4. We found a clear negative relationship between the level of homophobia and income. A 10% change in GDP per capita is associated with a 1% point reduction in the mean homophobic climate index (table 2, model 1). In addition, gender inequality, measured by the share of parliamentary seats held by women, is strongly correlated with higher homophobic climate. One can also note the statistically robust association between the level of homophobia and abuses of human rights. There is a strong negative relationship between the level of homophobia of a country and the level of satisfaction in life of its citizens, measured by the Cantril ladder (figure 2). Table 2 Associations between homophobia and key socioeconomic and public health outcome variables Model 1 Model 2 Model 3 (95% CI) (95% CI) (95% CI) Revenue per capita (ln GDP pc) −0.101  *** −0.033  ** −0.031  ** (−0.119  −0.083) (−0.057  −0.010) (−0.060  −0.003) Share of parliament seats by women (√x) −0.26  ** −0.018  ** (−0.043  −0.008) (−0.035  −0.001) Human rights abuse (√x) 0.054  *** 0.047  *** (0.036  0.072) (0.029  0.064) Satisfaction in life −0.041  ** −0.050  *** (−0.069  −0.013) (−0.079  −0.020) Health expenditures −0.009  ** (−0.016  −0.003) Proportion of MSM among total pop −6.501  *** −5.644  ** (−8.669  −4.342) (−7.918 −3.371) Share of male AIDS death among male HIV+ (√x) 0.507  ** (0.031  0.982) Constant 1.481  *** 1.246  *** 1.086  *** (1.341  1.620) (1.098  1.394) (0.828  1.345) Model fit indices R2 0.49 0.79 0.81 R2 adjusted 0.49 0.78 0.80 F 125.09 100.65 110.27 Prob>f 0.0000 0.0000 0.0000 N 158 147 137 Model 1 Model 2 Model 3 (95% CI) (95% CI) (95% CI) Revenue per capita (ln GDP pc) −0.101  *** −0.033  ** −0.031  ** (−0.119  −0.083) (−0.057  −0.010) (−0.060  −0.003) Share of parliament seats by women (√x) −0.26  ** −0.018  ** (−0.043  −0.008) (−0.035  −0.001) Human rights abuse (√x) 0.054  *** 0.047  *** (0.036  0.072) (0.029  0.064) Satisfaction in life −0.041  ** −0.050  *** (−0.069  −0.013) (−0.079  −0.020) Health expenditures −0.009  ** (−0.016  −0.003) Proportion of MSM among total pop −6.501  *** −5.644  ** (−8.669  −4.342) (−7.918 −3.371) Share of male AIDS death among male HIV+ (√x) 0.507  ** (0.031  0.982) Constant 1.481  *** 1.246  *** 1.086  *** (1.341  1.620) (1.098  1.394) (0.828  1.345) Model fit indices R2 0.49 0.79 0.81 R2 adjusted 0.49 0.78 0.80 F 125.09 100.65 110.27 Prob>f 0.0000 0.0000 0.0000 N 158 147 137 Notes: Bootstrap jackknife regressions, CI confidence intervals. *P < 0.05, **P < 0.01 and ***P < 0.001. Table 2 Associations between homophobia and key socioeconomic and public health outcome variables Model 1 Model 2 Model 3 (95% CI) (95% CI) (95% CI) Revenue per capita (ln GDP pc) −0.101  *** −0.033  ** −0.031  ** (−0.119  −0.083) (−0.057  −0.010) (−0.060  −0.003) Share of parliament seats by women (√x) −0.26  ** −0.018  ** (−0.043  −0.008) (−0.035  −0.001) Human rights abuse (√x) 0.054  *** 0.047  *** (0.036  0.072) (0.029  0.064) Satisfaction in life −0.041  ** −0.050  *** (−0.069  −0.013) (−0.079  −0.020) Health expenditures −0.009  ** (−0.016  −0.003) Proportion of MSM among total pop −6.501  *** −5.644  ** (−8.669  −4.342) (−7.918 −3.371) Share of male AIDS death among male HIV+ (√x) 0.507  ** (0.031  0.982) Constant 1.481  *** 1.246  *** 1.086  *** (1.341  1.620) (1.098  1.394) (0.828  1.345) Model fit indices R2 0.49 0.79 0.81 R2 adjusted 0.49 0.78 0.80 F 125.09 100.65 110.27 Prob>f 0.0000 0.0000 0.0000 N 158 147 137 Model 1 Model 2 Model 3 (95% CI) (95% CI) (95% CI) Revenue per capita (ln GDP pc) −0.101  *** −0.033  ** −0.031  ** (−0.119  −0.083) (−0.057  −0.010) (−0.060  −0.003) Share of parliament seats by women (√x) −0.26  ** −0.018  ** (−0.043  −0.008) (−0.035  −0.001) Human rights abuse (√x) 0.054  *** 0.047  *** (0.036  0.072) (0.029  0.064) Satisfaction in life −0.041  ** −0.050  *** (−0.069  −0.013) (−0.079  −0.020) Health expenditures −0.009  ** (−0.016  −0.003) Proportion of MSM among total pop −6.501  *** −5.644  ** (−8.669  −4.342) (−7.918 −3.371) Share of male AIDS death among male HIV+ (√x) 0.507  ** (0.031  0.982) Constant 1.481  *** 1.246  *** 1.086  *** (1.341  1.620) (1.098  1.394) (0.828  1.345) Model fit indices R2 0.49 0.79 0.81 R2 adjusted 0.49 0.78 0.80 F 125.09 100.65 110.27 Prob>f 0.0000 0.0000 0.0000 N 158 147 137 Notes: Bootstrap jackknife regressions, CI confidence intervals. *P < 0.05, **P < 0.01 and ***P < 0.001. Figure 2 View largeDownload slide Relationship between homophobia and income, human rights abuses, satisfaction in life and gender inequality Figure 2 View largeDownload slide Relationship between homophobia and income, human rights abuses, satisfaction in life and gender inequality It appears from table 2 that homophobia is also negatively associated with the share of MSM among total population; meaning that a larger share of gay men and other MSM among the population is associated with lower degree of homophobia. We found that a 10% point reduction in public health spending as a share of GDP is associated with an increase in the homophobic climate of 9% points (table 2, model 2). Moreover, AIDS-related deaths among men living with HIV are associated homophobia (table 2, model 3). Finally, even after controlling for markers of economic and social inequalities, the level of homophobia at country level is strongly associated with premature death among men. This translates into a 1.7-year reduction in life expectancy among its male population for a 10% point increase of the level of homophobia. See Supplementary annex S5. It should be reminded here that the correlations we identified between the level of homophobia at country-level and different markers of health, social and economic development do not necessarily imply a causal relationship. Discussion In this study, we developed a statistically robust and valid index that translates institutional and social homophobia in most low- and middle-income countries across the globe. This socioecological approach provides a holistic picture of sexual orientation related stigma. We showed that homophobia is associated with lower economic output at country level. Furthermore, the level of homophobia appears to be closely related to lower investment in health and to social inequalities, such as lack of recognition of human rights and gender inequality. We found a negative relationship between the level of homophobia and life expectancy among males and showed that AIDS-related deaths among HIV-positive men are associated with higher level of homophobia. We also found that homophobia is negatively associated with the share of MSM among the total population. This finding raises two caveats: first, a correlation does not imply causality. This point is important to prevent misinterpretation to justify or promote homophobia in order ‘to contain’ the number of men having sex with men. Second and paradoxically, it does not imply that homophobic countries have fewer gay men and other MSM. Instead, it may mean that in these settings, this population group is underreported and underestimated.30–32 Cultural, moral, religious beliefs may prevent men in some countries from coming out of the closet.33 In addition, individuals expecting negative reactions from others due to their differing sexual orientation or gender identity are less likely to report their sexual activity. In highly homophobic countries, gay men and other MSM cannot disclose their sexual orientation without exposing themselves to severe prejudices. Gay men and other MSM may conceal their sexual orientation, or have heterosexual behaviour,34 leading to additional under-reporting. Finally, the definition of homosexuality varies among different settings. In many countries the insertive male partner is not labelled or considered homosexual, only the receptive partner is.35 Two limitations should be noted. First, modelling homophobia at country level implied trade-offs in the identification of variables and proxies that adequately translate the different dimensions of homophobia, in addition to being available for all countries. Country-level analysis also means that variations within countries cannot be captured. The level of homophobia may vary from one city to another and from urban to rural areas. State and non-State actors at country level play a key role in filling these gaps and ensuring that no sexual minority is denied its rights and its access to care. Second, even though we controlled for collinearity, one should keep in mind that the institutional and social homophobia are interrelated to some extent: individuals may live in an environment where social, religious and cultural norms deeply interact with legislation. In other settings, laws and policies may implicitly favour stigma and discrimination against some minorities. Finally, the social homophobia experienced by individuals in some closed societies may provide ground for internalized homonegativity. This favours arguments for a holistic approach when identifying interventions aiming to reduce sexual-orientation related stigma and discrimination. Recent epidemiological evidence shows the increasing incidence of HIV among gay men and other MSM in most countries; new HIV infections rose by almost 12% between 2011 and 2015.36 There is growing evidence that homophobia impedes access to prevention, care and treatment by gay men and other MSM.16,37–40 The availability of this index of homophobia at country level enables the better understanding of the determinants of vulnerability to HIV infection among gay men and other MSM in low- and middle-income countries. The socioecological model developed here provides a robust and valid measure of homophobia that can inform public health decision-making. Increased availability of data in low- and middle-income countries could enable future development of the socioecological approach to measuring homophobia. For example, internalized homonegativity and homophobic violence are important variables that could be considered if more data are made available at country level. Too many people are victims of stigma and discrimination related to sexual orientation and gender identity. Countering homophobia is part of public health policy and all actors with influence, including civil society and policy-makers should promote more inclusive societies. Supplementary data Supplementary data are available at EURPUB online. Acknowledgements We thank Michel Sidibé and Peter Ghys for making this study possible and for supporting it. We also thank Carole Siani and Bruno Ventelou for their invaluable technical inputs. The views expressed in this article are those of the authors and do not necessarily reflect those of their respective institutions. Disclaimers All co-authors contributed to this article in their personal capacity. The views expressed are their own and do not necessarily represent the views of their respective organization. Conflicts of interest: None declared. Key points There is a significant negative correlation between economic development and homophobia. Homophobia is associated with lower life expectancy for males at country level. Males living with HIV are more likely to die from AIDS in homophobic countries. Countering homophobia and other stigma related to sexual orientation and gender identity should be part of public health policy. References 1 Link BG , Phelan JC . Conceptualizing stigma . Annu Rev Sociol 2001 ; 27 : 363 – 85 . Google Scholar CrossRef Search ADS 2 Hatzenbuehler ML . Structural stigma and health. In: Major B , Dovidio JF , Link BG , editors. The Oxford Handbook of Stigma, Discrimination, and Health . Oxford : Oxford University Press ; 2017 : 105 – 21 . 3 Hatzenbuehler ML , Link BG . 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State-Sponsored Homophobia: A World Survey of Laws: Criminalisation, Protection and Recognition of Same-Sex Love, 11th edn. Geneva: ILGA, 2016. 26 World Values Survey Association . World Values Survey, Wave 6 2010–2014. official aggregate v.20150418, Madrid: Aggregate File Producer Asep/JDS, 2015. 27 Leibniz Institute for the Social Sciences . European values study 2008: Integrated dataset. GESIS Data Archive, Cologne, ZA4800, Data file version 3.0.0. Available at: https://dbk.gesis.org/ (6 January 2018, date last accessed). 28 Dulani B , Gift S , Dionne KY . Afrobarometer Round 6. Updated 15 Sept. 2016 . Available at: http://www.afrobarometer.org/online-data-analysis (6 January 2018, date last accessed). 29 Gallup MCarthy. J . Nearly 3 in 10 worldwide see their areas as good for gays. 2014 . Available at: Gallup http://news.gallup.com/poll/175520/nearly-worldwide-areas-good-gays.aspx (17 December 2018, date last accessed). 30 Wu E , Terlikbayeva A , Hunt T , et al. Preliminary population size estimation of men who have sex with men in Kazakhstan: implications for HIV testing and surveillance . LGBT Health 2017 ; 4 : 164 – 7 . Google Scholar CrossRef Search ADS PubMed 31 Quaye S , Fisher Raymond H , Atuahene K , et al. Critique and lessons learned from using multiple methods to estimate population size of men who have sex with men in Ghana . AIDS Behav 2015 ; 19 : 16 – 23 . Google Scholar CrossRef Search ADS 32 Coffman KB , Coffman LC , Ericson KMM . The size of the LGBT population and the magnitude of anti-gay sentiment are substantially underestimated. NBER Work Pap Ser. 2013 ; No. 19508. 33 Ross MW . Married homosexual men: prevalence and background . Marriage Fam Rev 1989 ; 14 : 35 – 57 . Google Scholar CrossRef Search ADS 34 Pachankis JE , Hatzenbuehler ML , Mirandola M , et al. The geography of sexual orientation: structural stigma and sexual attraction, behavior, and identity among men who have sex with men across 38 European countries . Arch Sex Behav 2017 ; 46 : 1491 – 502 . Google Scholar CrossRef Search ADS PubMed 35 Mitchell G . Tourist Attractions: Performing Race and Masculinity in Brazil's Sexual Economy . Chicago : University of Chicago Press , 2015 : 264 . Google Scholar CrossRef Search ADS 36 UNAIDS . Get on the Fast-Track: The Life-Cycle Approach to HIV. Geneva: UNAIDS, 2016. 37 Pachankis JE , Hatzenbuehler ML , Hickson F , et al. Hidden from health: structural stigma, sexual orientation concealment, and HIV across 38 countries in the European MSM Internet Survey . AIDS 2015 ; 29 : 1239 – 46 . Google Scholar CrossRef Search ADS PubMed 38 Anderson AM , Ross MW , Nyoni JE , McCurdy SA . High prevalence of stigma-related abuse among a sample of men who have sex with men in Tanzania: implications for HIV prevention . AIDS Care 2015 ; 27 : 63 – 70 . Google Scholar CrossRef Search ADS PubMed 39 Ross MW , Nyoni J , Ahaneku HO , et al. High HIV seroprevalence, rectal STIs and risky sexual behaviour in men who have sex with men in Dar es Salaam and Tanga, Tanzania . BMJ Open 2014 ; 4 : e006175 . Google Scholar CrossRef Search ADS PubMed 40 Ross MW , Kajubi P , Mandel JS , et al. Internalized homonegativity/homophobia is associated with HIV-risk behaviours among Ugandan gay and bisexual men . Int J STD AIDS 2013 ; 24 : 409 – 13 . Google Scholar CrossRef Search ADS PubMed © The Author(s) 2018. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The European Journal of Public Health Oxford University Press

A socioecological measurement of homophobia for all countries and its public health impact

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Oxford University Press
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© The Author(s) 2018. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.
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1101-1262
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1464-360X
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10.1093/eurpub/cky023
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Abstract

Abstract Background Measuring homophobia at country level is important to guide public health policy as reductions in stigma are associated with improved health outcomes among gay men and other men who have sex with men. Methods: We developed a Homophobic Climate Index incorporating institutional and social components of homophobia. Institutional homophobia was based on the level of enforcement of laws that criminalise, protect or recognise same-sex relations. Social homophobia was based on the level of acceptance and justifiability of homosexuality. We estimated the Index for 158 countries and assessed its robustness and validity. Results Western Europe is the most inclusive region, followed by Latin America. Africa and the Middle East are home to the most homophobic countries with two exceptions: South Africa and Cabo Verde. We found that a 1% decrease in the level of homophobia is associated with a 10% increase in the gross domestic product per capita. Countries whose citizens face gender inequality, human rights abuses, low health expenditures and low life satisfaction are the ones with a higher homophobic climate. Moreover, a 10% increase in the level of homophobia at country level is associated with a 1.7-year loss in life expectancy for males. A higher level of homophobia is associated with increased AIDS-related death among HIV-positive men. Conclusion The socioecological approach of this index demonstrates the negative social, economic and health consequences of homophobia in low- and middle-income countries. It provides sound evidence for public health policy in favour of the inclusion of sexual minorities. Introduction Despite noticeable progress in terms of inclusion of sexual minorities in the vast majority of countries over the last 40 years, the stigma associated with gay men and other men who have sex with men (MSM) is still prevalent in most societies. Stigma applies when elements of labelling, stereotyping, separation, status loss and discrimination co-occur in a power situation that allows the components of stigma to unfold.1 Stigma can occur at individual, interpersonal and structural levels.2,3 Homophobia, a particular case of stigma based on sexual orientation and gender identity, affects primarily lesbian, gay, bisexual, transgender and intersex people (LGBTI). Several definitions focus on the clinical aspect of a phobia, describing homophobia as ‘an irrational, persistent fear or dread of homosexuals’.4 Here, we use the term homophobia to refer to any negative attitude, belief, or action toward persons of differing sexual orientation or gender identity. It includes laws and structural manifestations of that prejudice in institutional settings, such as the workplace.5 This working definition encompasses the three levels of stigma described earlier. The level of infringement of human rights, verbal and physical violence and denial of health services associated with homophobia is a public health issue. Stigma is a central driver of morbidity and mortality at a population level.6 Gay men facing enacted sexual stigma are more likely to engage in sexual risk behaviours.7,8 They are less likely to adhere to their antiretroviral treatment9 and have lower HIV testing rates.9–15 Finally, internalized homonegativity is associated with lower levels of HIV testing and lower levels of condom use in gay and bisexual men.16 A socio-ecological approach to health-related behaviour17 allows for studies of stigma related to sexual orientation and gender identity in their broader structural and social dimensions.1,6,18 Most studies of homophobia focused at the individual level. Being able to identify the level of homophobia at country level is important to guide public health policies as recent evidence shows that reductions in the homophobic climate are associated with improved health outcomes among gay men and other MSM.19 This study aims to propose and validate a robust index to measure homophobia at country level, including in low- and middle-income countries (LMIC). Methods Data sources The availability and reliability of data on stigma and discrimination related to gender identity and sexual orientation and gender identity is uneven from country to country. Data on HIV and on gay men and other MSM were obtained from AIDSinfo20 an online repository of global AIDS data compiled and maintained by UNAIDS, as well as from scientific articles and grey literature. Economic and development indicators such as gross domestic product, health expenditures, proportion of seats held by women in parliaments, gender inequality, mean years of schooling and life expectancy were drawn from the IMF World Economic Outlook, the 2015 Human Development Report and the World Population Prospects published by the Department of Economic and Social Affairs of the United Nations Population Division. We used the individual data from the World Values Survey which we aggregated at country level. The information on laws and legislation comes from the International Lesbian, Gay, Bisexual, Trans and Intersex Association (ILGA). The rule of law index comes from the World Justice Project and the Cantril index from the Gallup World Poll. We used the data on homophobia made available by the Pew Research Center. We used STATA 14 for statistical analysis. Model and analytic strategy We propose a socio-ecological construct for measuring homophobia that translates the important role played by institutional but also interpersonal factors. Let the level of homophobia for a country (i) be the combination of institutional (IsH) and social (SoH) homophobia for each country (i). HCIi=β1IsHi+β2SoHi (1) Institutional homophobia Institutional homophobia, IsHi, relates to the formal codes, such as laws and legislations that societies adhere to. Some of these codes may establish an institutional construct for inclusion or discrimination against people based on their sexual orientation or gender identity. These laws in their turn influence people’s behaviour and thoughts towards persons of differing sexual orientations and gender identities.21–24 First, we considered a set of 11 laws that characterise the level of institutionalized of homophobia of a country. For each country, those 11 laws are individually valued from 1 to 3 whether it is inexistent, existent and in force, or in force only in parts of its territory. The level of implementation is the one reported by the International Lesbian, Gay, Bisexual, Trans and Intersex Association.25 Second, we estimated the coefficients for these 11 laws globally. To ensure a transparent and objective weighting system, we considered the way all countries are combining (or not) a said law with the ten other laws considered here. By doing so, we reflect the choice of countries to enforce laws favouring inclusion and protection or, a contrario, laws criminalizing same-sex relationships. To do so, we built polychoric correlation matrices as these variables are categorical and ordinal. Our methods demonstrated high internal consistency with an ordinal alpha of 0.92 and 0.83 for the inclusion and the criminalizing laws, respectively. The weight of each law was then estimated by a factor analysis. Laws and their coefficients are presented in Supplementary annex S1. Institutional homophobia is expressed as IsHi=∑n=111γnLn,i+ɛi (2) where γn are the factor loadings for the each law n and Ln,i is the level of enforcement of law n in country i, with Ln=1, 3 and i=1, 158. Social homophobia Social homophobia, SHi, relates to interactions between communities or groups and individuals. A key characteristic is the direct reaction of individuals towards gay men and other MSM. Social homophobia reflects societal norms and behaviours based on moral, religious and cultural beliefs. It encompasses interpersonal processes as well as physical reactions such as avoidance or aggression, whether sexual, verbal or physical. These reactions take form in social networks such as family, workplace or friends. It can also be found within communities, whether ethnic, cultural, moral or religious ones. Markers of social homophobia are difficult to measure, particularly at country level. We focus on the interpersonal reactions, assuming it reflects the ultimate degree of societal penetration. We considered two representative questions asked to >460 000 individuals in 91 countries within the three most recent waves of World Values Survey,26 the 2008 European Values Survey27 and the Afrobarometer.28 The first question is ‘On this list are various groups of people. Could you please mention any that you would not like as neighbours?’ This is a dichotomized answer whether respondents selected ‘homosexuals’ or not. The second question was, ‘Do you think [homosexuality] can always be justified, never be justified, or something in between?’ Answers were given on a scale from 1 to 10, with 1 meaning never justifiable and 10 meaning always justifiable. For each question, we considered the answers from all respondents for each country and calculated a country-specific value. Following a factor analysis, we weighted these two variables equally. We performed multiple imputations and predicted values for the remaining 45 countries with missing values for social homophobia, representing slightly more than a quarter (28%) of the total number of countries studied (158). The social homophobia component can be expressed as: SoHi=1n∑nacceptance n,i+justifiabilityn,i (3) Where n = number of respondents for country i and i=1, 158. We also considered homophobic violence. Unfortunately, only a minority of countries, essentially the least homophobic ones, systematically record homophobic violence and hate crimes. Reporting homophobic violence requires that the victims reveal their sexual orientation which, in too many countries still, may expose him/her to additional risks of violence and retaliation. It is worth noting that there has been remarkable progress by non-State actors in reporting hate crimes in several countries. Despite these advancements, data are still scarce, often limited to capital cities or large urban areas. If more data become available in the future, homophobic violence can be integrated in equation (3). We developed the homophobic climate index by compiling institutional and social homophobia data. Both components are weighted equally as confirmed with a factor analysis, i.e. β1=β2 in equation (1). Reliability and validity of the homophobic climate index We measured the internal consistency of the index with a reliability coefficient, measured by the Cronbach’s alpha. We also performed a confirmatory factor analysis to confirm that the scale in question is unidimensional. In order to assess the validity of the HCI, we first controlled the results from regressions of the HCI for two subsamples of countries randomly selected, with independent social and economic variables such as income, gender equality, human rights, satisfaction in life, health expenditures and compared with the results obtained with the whole set of countries. Finally, we examined the stability of the correlation between the HCI and a control index to assess whether our instrument measures what we want to measure. We used the Gallup29 question on homophobia ‘is the city or area where you live a good place or not a good place for gay or lesbian people’ as control index and performed iterated regressions. Results The model and data available enabled the estimation of the homophobic climate index (HCI) for 158 countries. The index shows good internal consistency, with a Cronbach’s alpha of 0.82, and the control regressions with subsamples countries as well as with the control index enable us to consider the HCI a statistically reliable and valid index to measure homophobia. Regression and statistical tests are presented in Supplementary annex S2. The index ranges from 0 to 1, with higher values for more homophobic countries. Figure 1 presents the map of the homophobic climate (See Supplementary annex S3 for the ranking of 158 countries). Table 1 presents the 10 most inclusive countries, globally (1a) and among low- and middle-income countries (1b). The 10 most homophobic countries are also listed (1c). Table 1 Homophobic Climate Index 2017: Top 10 most inclusive and most homophobic countries 1a: Top 10 most inclusive countries 1b: Top 10 most inclusive low-and middle-income countries (LMIC) 1c: Top 10 most homophobic countries Rank Country HCI Rank Country HCI Rank Country HCI 1 Sweden 0.112 18 Colombia 0.321 149 Tunisia 0.870 2 Netherlands 0.131 20 Brazil 0.338 150 Burundi 0.873 3 Denmark 0.137 22 South Africa 0.352 151 Iraq 0.878 4 Norway 0.140 25 Mexico 0.369 152 Guinea 0.880 5 Spain 0.163 28 Ecuador 0.400 153 Nigeria 0.884 6 Finland 0.168 35 Romania 0.443 154 Qatar 0.897 7 Belgium 0.177 36 Costa Rica 0.444 155 South Sudan 0.905 8 France 0.180 41 Cabo Verde 0.474 156 Saudi Arabia 0.926 9 Uruguay 0.189 42 Serbia 0.482 157 Afghanistan 0.935 10 United Kingdom 0.206 43 Bolivia 0.489 158 Sudan 0.957 1a: Top 10 most inclusive countries 1b: Top 10 most inclusive low-and middle-income countries (LMIC) 1c: Top 10 most homophobic countries Rank Country HCI Rank Country HCI Rank Country HCI 1 Sweden 0.112 18 Colombia 0.321 149 Tunisia 0.870 2 Netherlands 0.131 20 Brazil 0.338 150 Burundi 0.873 3 Denmark 0.137 22 South Africa 0.352 151 Iraq 0.878 4 Norway 0.140 25 Mexico 0.369 152 Guinea 0.880 5 Spain 0.163 28 Ecuador 0.400 153 Nigeria 0.884 6 Finland 0.168 35 Romania 0.443 154 Qatar 0.897 7 Belgium 0.177 36 Costa Rica 0.444 155 South Sudan 0.905 8 France 0.180 41 Cabo Verde 0.474 156 Saudi Arabia 0.926 9 Uruguay 0.189 42 Serbia 0.482 157 Afghanistan 0.935 10 United Kingdom 0.206 43 Bolivia 0.489 158 Sudan 0.957 Table 1 Homophobic Climate Index 2017: Top 10 most inclusive and most homophobic countries 1a: Top 10 most inclusive countries 1b: Top 10 most inclusive low-and middle-income countries (LMIC) 1c: Top 10 most homophobic countries Rank Country HCI Rank Country HCI Rank Country HCI 1 Sweden 0.112 18 Colombia 0.321 149 Tunisia 0.870 2 Netherlands 0.131 20 Brazil 0.338 150 Burundi 0.873 3 Denmark 0.137 22 South Africa 0.352 151 Iraq 0.878 4 Norway 0.140 25 Mexico 0.369 152 Guinea 0.880 5 Spain 0.163 28 Ecuador 0.400 153 Nigeria 0.884 6 Finland 0.168 35 Romania 0.443 154 Qatar 0.897 7 Belgium 0.177 36 Costa Rica 0.444 155 South Sudan 0.905 8 France 0.180 41 Cabo Verde 0.474 156 Saudi Arabia 0.926 9 Uruguay 0.189 42 Serbia 0.482 157 Afghanistan 0.935 10 United Kingdom 0.206 43 Bolivia 0.489 158 Sudan 0.957 1a: Top 10 most inclusive countries 1b: Top 10 most inclusive low-and middle-income countries (LMIC) 1c: Top 10 most homophobic countries Rank Country HCI Rank Country HCI Rank Country HCI 1 Sweden 0.112 18 Colombia 0.321 149 Tunisia 0.870 2 Netherlands 0.131 20 Brazil 0.338 150 Burundi 0.873 3 Denmark 0.137 22 South Africa 0.352 151 Iraq 0.878 4 Norway 0.140 25 Mexico 0.369 152 Guinea 0.880 5 Spain 0.163 28 Ecuador 0.400 153 Nigeria 0.884 6 Finland 0.168 35 Romania 0.443 154 Qatar 0.897 7 Belgium 0.177 36 Costa Rica 0.444 155 South Sudan 0.905 8 France 0.180 41 Cabo Verde 0.474 156 Saudi Arabia 0.926 9 Uruguay 0.189 42 Serbia 0.482 157 Afghanistan 0.935 10 United Kingdom 0.206 43 Bolivia 0.489 158 Sudan 0.957 Figure 1 View largeDownload slide Homophobic climate index Figure 1 View largeDownload slide Homophobic climate index The most inclusive countries are essentially in Western Europe and Uruguay. Among the LMIC, Latin America appears as a leading region in promoting inclusion and fighting homophobia. It is worth noting that two African countries, South Africa and Cabo Verde are among the top 10 most inclusive LMIC. The case of South Africa is particularly interesting as it paves the way to a more comprehensive and successful response to the HIV epidemic that could serve as an example in other countries of the region. Homophobia and socioeconomic determinants We performed multivariate regressions, using the country level of homophobia as explanatory variable to predict the value of key socioeconomic and public health outcome variables. It should be reminded that results of these regressions represent correlation and do not necessarily imply causal relationships. Descriptive statistics of the variables are presented in Supplementary annex S4. We found a clear negative relationship between the level of homophobia and income. A 10% change in GDP per capita is associated with a 1% point reduction in the mean homophobic climate index (table 2, model 1). In addition, gender inequality, measured by the share of parliamentary seats held by women, is strongly correlated with higher homophobic climate. One can also note the statistically robust association between the level of homophobia and abuses of human rights. There is a strong negative relationship between the level of homophobia of a country and the level of satisfaction in life of its citizens, measured by the Cantril ladder (figure 2). Table 2 Associations between homophobia and key socioeconomic and public health outcome variables Model 1 Model 2 Model 3 (95% CI) (95% CI) (95% CI) Revenue per capita (ln GDP pc) −0.101  *** −0.033  ** −0.031  ** (−0.119  −0.083) (−0.057  −0.010) (−0.060  −0.003) Share of parliament seats by women (√x) −0.26  ** −0.018  ** (−0.043  −0.008) (−0.035  −0.001) Human rights abuse (√x) 0.054  *** 0.047  *** (0.036  0.072) (0.029  0.064) Satisfaction in life −0.041  ** −0.050  *** (−0.069  −0.013) (−0.079  −0.020) Health expenditures −0.009  ** (−0.016  −0.003) Proportion of MSM among total pop −6.501  *** −5.644  ** (−8.669  −4.342) (−7.918 −3.371) Share of male AIDS death among male HIV+ (√x) 0.507  ** (0.031  0.982) Constant 1.481  *** 1.246  *** 1.086  *** (1.341  1.620) (1.098  1.394) (0.828  1.345) Model fit indices R2 0.49 0.79 0.81 R2 adjusted 0.49 0.78 0.80 F 125.09 100.65 110.27 Prob>f 0.0000 0.0000 0.0000 N 158 147 137 Model 1 Model 2 Model 3 (95% CI) (95% CI) (95% CI) Revenue per capita (ln GDP pc) −0.101  *** −0.033  ** −0.031  ** (−0.119  −0.083) (−0.057  −0.010) (−0.060  −0.003) Share of parliament seats by women (√x) −0.26  ** −0.018  ** (−0.043  −0.008) (−0.035  −0.001) Human rights abuse (√x) 0.054  *** 0.047  *** (0.036  0.072) (0.029  0.064) Satisfaction in life −0.041  ** −0.050  *** (−0.069  −0.013) (−0.079  −0.020) Health expenditures −0.009  ** (−0.016  −0.003) Proportion of MSM among total pop −6.501  *** −5.644  ** (−8.669  −4.342) (−7.918 −3.371) Share of male AIDS death among male HIV+ (√x) 0.507  ** (0.031  0.982) Constant 1.481  *** 1.246  *** 1.086  *** (1.341  1.620) (1.098  1.394) (0.828  1.345) Model fit indices R2 0.49 0.79 0.81 R2 adjusted 0.49 0.78 0.80 F 125.09 100.65 110.27 Prob>f 0.0000 0.0000 0.0000 N 158 147 137 Notes: Bootstrap jackknife regressions, CI confidence intervals. *P < 0.05, **P < 0.01 and ***P < 0.001. Table 2 Associations between homophobia and key socioeconomic and public health outcome variables Model 1 Model 2 Model 3 (95% CI) (95% CI) (95% CI) Revenue per capita (ln GDP pc) −0.101  *** −0.033  ** −0.031  ** (−0.119  −0.083) (−0.057  −0.010) (−0.060  −0.003) Share of parliament seats by women (√x) −0.26  ** −0.018  ** (−0.043  −0.008) (−0.035  −0.001) Human rights abuse (√x) 0.054  *** 0.047  *** (0.036  0.072) (0.029  0.064) Satisfaction in life −0.041  ** −0.050  *** (−0.069  −0.013) (−0.079  −0.020) Health expenditures −0.009  ** (−0.016  −0.003) Proportion of MSM among total pop −6.501  *** −5.644  ** (−8.669  −4.342) (−7.918 −3.371) Share of male AIDS death among male HIV+ (√x) 0.507  ** (0.031  0.982) Constant 1.481  *** 1.246  *** 1.086  *** (1.341  1.620) (1.098  1.394) (0.828  1.345) Model fit indices R2 0.49 0.79 0.81 R2 adjusted 0.49 0.78 0.80 F 125.09 100.65 110.27 Prob>f 0.0000 0.0000 0.0000 N 158 147 137 Model 1 Model 2 Model 3 (95% CI) (95% CI) (95% CI) Revenue per capita (ln GDP pc) −0.101  *** −0.033  ** −0.031  ** (−0.119  −0.083) (−0.057  −0.010) (−0.060  −0.003) Share of parliament seats by women (√x) −0.26  ** −0.018  ** (−0.043  −0.008) (−0.035  −0.001) Human rights abuse (√x) 0.054  *** 0.047  *** (0.036  0.072) (0.029  0.064) Satisfaction in life −0.041  ** −0.050  *** (−0.069  −0.013) (−0.079  −0.020) Health expenditures −0.009  ** (−0.016  −0.003) Proportion of MSM among total pop −6.501  *** −5.644  ** (−8.669  −4.342) (−7.918 −3.371) Share of male AIDS death among male HIV+ (√x) 0.507  ** (0.031  0.982) Constant 1.481  *** 1.246  *** 1.086  *** (1.341  1.620) (1.098  1.394) (0.828  1.345) Model fit indices R2 0.49 0.79 0.81 R2 adjusted 0.49 0.78 0.80 F 125.09 100.65 110.27 Prob>f 0.0000 0.0000 0.0000 N 158 147 137 Notes: Bootstrap jackknife regressions, CI confidence intervals. *P < 0.05, **P < 0.01 and ***P < 0.001. Figure 2 View largeDownload slide Relationship between homophobia and income, human rights abuses, satisfaction in life and gender inequality Figure 2 View largeDownload slide Relationship between homophobia and income, human rights abuses, satisfaction in life and gender inequality It appears from table 2 that homophobia is also negatively associated with the share of MSM among total population; meaning that a larger share of gay men and other MSM among the population is associated with lower degree of homophobia. We found that a 10% point reduction in public health spending as a share of GDP is associated with an increase in the homophobic climate of 9% points (table 2, model 2). Moreover, AIDS-related deaths among men living with HIV are associated homophobia (table 2, model 3). Finally, even after controlling for markers of economic and social inequalities, the level of homophobia at country level is strongly associated with premature death among men. This translates into a 1.7-year reduction in life expectancy among its male population for a 10% point increase of the level of homophobia. See Supplementary annex S5. It should be reminded here that the correlations we identified between the level of homophobia at country-level and different markers of health, social and economic development do not necessarily imply a causal relationship. Discussion In this study, we developed a statistically robust and valid index that translates institutional and social homophobia in most low- and middle-income countries across the globe. This socioecological approach provides a holistic picture of sexual orientation related stigma. We showed that homophobia is associated with lower economic output at country level. Furthermore, the level of homophobia appears to be closely related to lower investment in health and to social inequalities, such as lack of recognition of human rights and gender inequality. We found a negative relationship between the level of homophobia and life expectancy among males and showed that AIDS-related deaths among HIV-positive men are associated with higher level of homophobia. We also found that homophobia is negatively associated with the share of MSM among the total population. This finding raises two caveats: first, a correlation does not imply causality. This point is important to prevent misinterpretation to justify or promote homophobia in order ‘to contain’ the number of men having sex with men. Second and paradoxically, it does not imply that homophobic countries have fewer gay men and other MSM. Instead, it may mean that in these settings, this population group is underreported and underestimated.30–32 Cultural, moral, religious beliefs may prevent men in some countries from coming out of the closet.33 In addition, individuals expecting negative reactions from others due to their differing sexual orientation or gender identity are less likely to report their sexual activity. In highly homophobic countries, gay men and other MSM cannot disclose their sexual orientation without exposing themselves to severe prejudices. Gay men and other MSM may conceal their sexual orientation, or have heterosexual behaviour,34 leading to additional under-reporting. Finally, the definition of homosexuality varies among different settings. In many countries the insertive male partner is not labelled or considered homosexual, only the receptive partner is.35 Two limitations should be noted. First, modelling homophobia at country level implied trade-offs in the identification of variables and proxies that adequately translate the different dimensions of homophobia, in addition to being available for all countries. Country-level analysis also means that variations within countries cannot be captured. The level of homophobia may vary from one city to another and from urban to rural areas. State and non-State actors at country level play a key role in filling these gaps and ensuring that no sexual minority is denied its rights and its access to care. Second, even though we controlled for collinearity, one should keep in mind that the institutional and social homophobia are interrelated to some extent: individuals may live in an environment where social, religious and cultural norms deeply interact with legislation. In other settings, laws and policies may implicitly favour stigma and discrimination against some minorities. Finally, the social homophobia experienced by individuals in some closed societies may provide ground for internalized homonegativity. This favours arguments for a holistic approach when identifying interventions aiming to reduce sexual-orientation related stigma and discrimination. Recent epidemiological evidence shows the increasing incidence of HIV among gay men and other MSM in most countries; new HIV infections rose by almost 12% between 2011 and 2015.36 There is growing evidence that homophobia impedes access to prevention, care and treatment by gay men and other MSM.16,37–40 The availability of this index of homophobia at country level enables the better understanding of the determinants of vulnerability to HIV infection among gay men and other MSM in low- and middle-income countries. The socioecological model developed here provides a robust and valid measure of homophobia that can inform public health decision-making. Increased availability of data in low- and middle-income countries could enable future development of the socioecological approach to measuring homophobia. For example, internalized homonegativity and homophobic violence are important variables that could be considered if more data are made available at country level. Too many people are victims of stigma and discrimination related to sexual orientation and gender identity. Countering homophobia is part of public health policy and all actors with influence, including civil society and policy-makers should promote more inclusive societies. Supplementary data Supplementary data are available at EURPUB online. Acknowledgements We thank Michel Sidibé and Peter Ghys for making this study possible and for supporting it. We also thank Carole Siani and Bruno Ventelou for their invaluable technical inputs. The views expressed in this article are those of the authors and do not necessarily reflect those of their respective institutions. Disclaimers All co-authors contributed to this article in their personal capacity. The views expressed are their own and do not necessarily represent the views of their respective organization. Conflicts of interest: None declared. Key points There is a significant negative correlation between economic development and homophobia. Homophobia is associated with lower life expectancy for males at country level. Males living with HIV are more likely to die from AIDS in homophobic countries. Countering homophobia and other stigma related to sexual orientation and gender identity should be part of public health policy. References 1 Link BG , Phelan JC . Conceptualizing stigma . Annu Rev Sociol 2001 ; 27 : 363 – 85 . Google Scholar CrossRef Search ADS 2 Hatzenbuehler ML . Structural stigma and health. In: Major B , Dovidio JF , Link BG , editors. The Oxford Handbook of Stigma, Discrimination, and Health . Oxford : Oxford University Press ; 2017 : 105 – 21 . 3 Hatzenbuehler ML , Link BG . 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