Coming out as a blood donor

I've been a surreptitious blood donor for 14 years.

It all started after 9/11. I was stricken with grief. The enormity of the tragedy taking place in New York City weighed heavily and I wanted to do something, anything, to help with the recovery.
A few days later, there was a blood drive at school, and I thought long and hard about donating. I desperately wanted to do something useful, but I also knew it would mean lying to do it.
Eventually, I decided that giving blood would be more important than the lie I'd have to tell to give it. It never felt right, lying, and I'm relieved that I won't have to do it ever again.

Giving blood is an important part of my life. I'm humbled by the idea that parting with a pint or two here and there can help others get through the worst day of their lives.
And frankly, selfishly, it feels good to feel 'healthy', that my body has something of value for others. That's not a message that gay men get often enough.

At this point, some of you may be shouting at the screen, wondering how I could be so irresponsible as to endanger the blood supply. I've seen what HIV can do. I've lost friends to it. I've seen what the meds can do. Believe me, I'm under no illusion that HIV is something minor. Sure it's treatable, perhaps even managable at this point, but I could never live with myself if I thought there was even a fraction of a chance I could give HIV to someone through a blood donation.
At the same time, the rule that the blood donation system used is ridiculous - permanent deferment for any man who has had sex with a man since 1978.

So, I had to make up my own rules. I decided to go with six months since last having sex, and then an HIV test just to make sure, before allowing myself to donate.
I guess I have sex so infrequently that waiting six months isn't a big deal. There were even a few opportunities I passed up because my (secret) identity as a blood donor wasn't worth putting on hold.

Speaking of secret identities, it was quite jarring to go back into the closet to give blood. And to stay in the closet about being a blood donor everywhere else. I wanted to ask for the pink gauze to wrap up my arm after the donation, but had to bite my tongue. I had to make sure I wore the t-shirts that they give you inside out, and I couldn't accept as a gift in exchange for donation anything that would visibly associate me with being a donor.

I frequently struggled with who, how and when to "come out" as a donor in the rest of my life. Half of me wanted to come out fully and fight against the injustice of the gay donor ban. Half of my wanted to fly under the radar and help as many people anonymously as I could with my donations. I can't say I ever felt like I made the "right" choice there, often flying a bit close to the sun trying to do both at once.

For those members of my family, my friends, my coworkers, I'm sorry I didn't feel comfortable coming out to you as a blood donor - I hope you won't feel betrayed that I kept this to myself. And of course to the nurses at the dontation centers I've given at, I apologize for lying right to your face.
But to the mucky-mucks at the FDA - screw you. You've made my life uncomfortable and duplicitous and prevented many valuable donations from being received by others.

Gentle readers, I'm curious to hear your thoughts.

Data Unicorns

How many unicorns are in your data? Sounds like a silly question. But there can be some major problems when we don't think to ask it. Because every dataset has what appear to be unicorns in it - impossible combinations of data made possible because of infrequent errors.

Rob Kelly, Blackout Tattoo Studio, Hong Kong

Usually it's not a problem because the unicorns make up a really small proportion of your sample. And if the data combination is in fact impossible, or makes up a tiny proportion of what you're really interested in, you can just ignore them, or even try to "correct" them if you have additional information. But when you're interested in a rare phenomenon, it can be hard to tell the difference between unicorns and the real cases you're interested in.

Gay Blood Donors

Take, for instance, a paper I've been working on for years about estimating how many gay blood donors there are.

If the American Red Cross's procedures were followed to the letter, there shouldn't be any because any man who has "had sex with a man, even once, since 1978" is supposed to be excluded. In other words, any apparent gay blood donors should be unicorns –impossible data combinations.

We know that there are some, because every once in a while, someone tests positive during the blood donation screening process, and when they go back to interview the donor, some donors admit to "having sex with a man, even once, since 1978". But we have no idea how many HIV- gay blood donors there are, how many men who are giving on a regular basis without incident, despite the ban.
So, I've been looking at various datasets trying to get a rough idea of how many gay blood donors there are, trying to make the point that the ban on gay male donors isn't just discriminatory, it's also ineffective. And if we could talk with the men who are giving blood regularly without incident, maybe we could develop new exclusion criteria based on what they are doing.

It sounds simple enough, look up how many gay men there are in these datasets, and count how many of them are giving blood. But here's the problem. There are errors in counting who's a gay man, and also errors in counting who gives blood. So, any heterosexual male blood donor who is inaccurately coded as gay or bisexual will appear to be a gay/bi blood donor. As will any gay/bisexual non-donor who is accidentially coded as a blood donor. Let's start out with some plausible (but made up) numbers to illustrate...

Let's give ourselves a decent-sized dataset, with 100,000 men in it. Suppose that 95% of the male population has not "had sex with a man since 1978", and 5% of them have given blood. That's 4,750 straight men who are blood donors.
In the 1970's the Census did a big study where they interviewed people twice, and found that in about 0.2% of the cases, the two interviews resulted in a different sex for the respondent - about one in 500. So, what if 0.2% of these 4,750 guys who are giving blood without bending the rules at all get mis-coded as gay or bisexual - that's about 9 cases of what appear to be excludable blood donors.
Let's just make a guess that instead of 5% of heterosexual men giving blood, that 0.5% of gay/bisexual men do. Then we've got 100,000 x 5% x 0.5% = 25 cases of gay/bi men who are giving blood despite the ban.
So, all told, it looks like there are 34 gay/bi blood donors, but only 74% of them really are gay/bi blood donors.
But what if 0.06% of gay/bi men are really giving blood? Then there would be 3 real gay/bi blood donors, but there would appear to be 12, and only 25% of them would really be gay/bi blood donors. Most of the time, we'd be looking at unicorns.
What's frustrating is that I can't tell the difference between these two scenarios. I can't tell if my unicorn ratio is only 24%, or if it's 75%.

There's another problem, too - with the blood donation questions. Sometimes, people want to inflate their sense of altruism, and they'll say they gave blood in the last year even if it was closer to two years ago. That I can live with, but an even bigger problem is that people get confused by the wording of the question, and they say they've given blood even if all they did was have a blood test at the doctor's office. So, there are some surveys where the blood donation rate appears to be upwards of 25%.
Let's assume that 5% of the population (gay or straight) who haven't given blood say that they have because they mis-understood the question (or that the interviewer was inattentive and hit the wrong button).
Then the number of straight men who say they've given blood would be 10%, not 5%, or 9,500. And if 0.2% of them were mis-classified as gay/bisexual, that would be 19 men who appear to be gay/bisexual blood donors. Then, if we take 5% of the gay/bisexual men as being mis-classified as being blood donors, that would be another 250 men who really aren't blood donors, but appear to be. In that case, if there are really 25 gay/bisexual blood donors, they would make up only 9% of the 294 men who appear to be gay/bisexual blood donors, and if there were really only 3 gay/bisexual blood donors, they would be 1% of the 272 who appear to be blood donors, or in other words, 99% unicorns.
And just to underscore the point, that's coming from errors of 0.2% and 5%.

There is a way to sort through this mess. You'd just need to call the men who appear to be gay/bi blood donors and ask them to clarify on a second interview. The number who would be inaccurately coded twice would be really small, because the relevant error rates are small (0.2% and 5%). But it is unlikely that anyone will do that kind of call-back.

Unicorns Ahead

There are a number of other contexts where we should expect to see unicorns in LGBT health research.
One is transgender health. There are a number of States that have been asking BRFSS respondents if they are transgender, and it looks like about 1 in 500 say that they are. But we need to be very careful in researching this population, because if the 1970's Census estimates hold, it's probably not unreasonable to think that 0.2% of the population will inadvertently be coded as being transgender, and that could easily be most of the people identified as transgender in these surveys. Again, the easiest solution is to call people back to verify. But in the absence of a call-back survey, we won't know whether 70% of the people identified as trans are actually trans, or if only 7% are.
Another group heavily influenced by unicorns is married same-sex couples. Before 2004, almost all people identified as married same-sex couples in the United States were unicorns, because it wasn't a legal status available to anyone. Another analysis I'm working on shows that the proportion of people identified in surveys as married same-sex couples who are really married same-sex couples can be as low as 10%, and rarely gets above 50%, but it's getting better in states where marriage is legal.

TBLG Data Geek Nirvana is Coming - Are We Ready?

The year is 2015. An unprecedented amount of data is now available about the health, socioeconomic conditions, and familial relationships of bisexual-, lesbian-, and gay-identified Americans. We now have the opportunity to describe these populations in great detail.

Routine questions intended to allow people to identify as trans have been tested and deployed in a number of surveys, and our ability to describe the trans-identified populations of the United States is light-years ahead of where we were in the dark ages of 2011 when a tenuous estimate of the size of the trans-identified population was first reported from population-based surveys.

Although a fairly wide variety of national surveys had collected sexual orientation data since the mid-1990's, it was a haphazard process in which surveys would add a question on sexual orientation largely based on lobbying by lesbian and gay researchers with strong personal relationships with survey administrators. Not only that, but the idiosyncratic method meant that there was little, if any, co-ordination between surveys, and each one asked about sexual orientation in it's own slightly peculiar way, leading to much methodological navel-gazing, and debates about which results were different because of question wording vs. which differences were the result of population differences, or some other factor.

Then, in 2011, given a push from a prestigious Institute of Medicine report, the ground shifted.

Rather than the default position being that one had to justify adding questions about sexual orientation to a skeptical research committee, survey administrators would now feel pressure to justify _not_ including sexual orientation questions, and have to get creative about how to reliably assess transgender identity in general population studies.

Furthermore, a growing consensus about the precise wording used to assess sexual orientation and gender identity had developed, leading to a much greater ability to compare results across studies, and even to combine multiple studies together in order to overcome the problem of not having sufficient numbers of sexual and gender minority individuals, and also to enable analyses of ever more tightly defined sub-populations - such as elderly Asian-American lesbian and bisexual women, bisexuals in their 20's and those in their 50's, heterosexually-identified men who profess same-sex attraction but have not had sex with another man, and so on.

Not only that, but the National Institutes of Health had made substantial investments in supporting analyses of this data bonanza, and had also invested in programs designed to provide up-and-coming students of this field with mentoring and training to an unprecedented degree.


In short, TBLG data geek Nirvana had arrived!


Since that scenario, or one not far from it, is likely to be in our 5-10 year future, it is worth spending a bit of time getting past the salivating, and doing some serious critical thinking about some potential side effects, so that they can be anticipated and prepared for, rather than an unanticipated surprise and source of frustration.
And that's why I'm writing this piece. I'm as eager as the next TBLG researcher to get my hands on the tsunami of data headed our way. We all want to surf that wave, rather than get pummeled by it.

It's going to be great, and...
I want to think about the "and..." part for a minute.

I have been able to anticipate a few side effects of this coming wave, but I don't want to claim that I can see the future. Some of these may not happen. Undoubtedly other things I haven't considered will catch me by surprise.

The more research, the better.
Well, it depends on the research. See my previous posts for more on this. In short, it depends on what the goals of that research are. More than likely, we're going to see a huge expansion of rather thoughtless research. Specifically in terms of health research, we're going to see a lot more "health disparities" research oriented towards only adverse health disparities. We're going to see a lot of "intersectionality" research oriented towards showing cumulative disparity and adversity. Both of these approaches will miss the interesting exceptions: what health advantages do TBLG populations have? When does the assumption of cumulative adversity inherent to much intersectionality work fail to capture the points of resistance and resilience that provide opportunities for effective health promotion and community pride?

Who will be the gatekeepers?
"Nobody" is the short answer. Which we should welcome with open arms. Expanding access to data about TBLG people will be the inevitable result of this process of asking more questions. The thing to watch out for here is that people who have not in the past had any particular interest in TBLG populations will be chiming in for the first time, and making rookie mistakes in interpreting what they look for, what they find, and how they report it. The other phenomenon to wacth out for related to this is people who have had an interest in TBLG populations, but will now feel empowered to look at data across a variety of disciplines other than where they have spent most of their time to date. Of course that is to be welcomed and encouraged, but there will be bumps along the way.

A shift in prerogative
Survey administrators will feel the shift from having to justify adding sexual orientation and gender identity items to surveys to including these questions unless there is a strong reason not to. Similarly, people analyzing these surveys and studies will feel an expectation that they should at least try to see if there are differences across categories of sexual orientation.
And, when they do these exploratory analyses, a variety of possibilities may arise. They may see a disparity that it truly there and is significant in a statistical sense. Since the idea of disparity and deficit fits well with assumptions about the social order, these exploratory analyses are more likely to get published than health similarities or health advantages that are truly there and also significant in a statistical aspect (technically a similarity can't be significant, but the point is that if no difference is seen in a large sample, that is evidence of little difference). Disparites that are truly there, but not significant in a statistical sense may also be commented on, and disparities that are observed as statistically significant, but in reality aren't disparities at all are also likely to be reported out as adverse health disparities. The probability that a health advantage that is not significant would be reported is, I propose, vanishingly small.
As a result, we are likely to see reports of a wide variety of health disparities, many of which will be "real", and also many of which will be spurious findings that are less likely to be replicated in other groups of people. But we won't be able to tell which is which until replication studies are done. And the way science works, debunking a falsely significant finding that jibes with the overall assumption of TBLG people being deficient can take several, even dozens of failed attempts to reproduce that finding in other populations.
Conversely, findings that go against the notion of inherent deficit (health similarities and advantages) will be viewed as tentative, and may require dozens of significant findings before being viewed as worthy of comment.

The upshot of all that is that as we shift from analyses designed to examine TBLG health from a theoretically-oriented perspective to a time when routine, but atheoretical analysis of these populations become commonplace, we should expect to see a large increase in spurious findings of TBLG deficits.

How Come Queer Health Research Can Only See Unhealthy Queers?

Recently, the prestigious Institute of Medicine came out with a tremendous compendium, The Health of Lesbian, Gay, Bisexual, and Transgender (LGBT) People: Building a Foundation for Better Understanding.
The goal of the book was to describe the state of knowledge on queer health, identify priorities for future health research, and make specific recommendations to the US National Institutes of Health.
And as far is goes, it does these tasks very well. The literature review is very thorough and will be useful for anyone writing a grant, among other things. The chapter on context is a great 30 minute romp through our nation's homophobic history.
The recommendations it makes are, in my opinion, a mixed bag, from laudable goals to some that I really can't get behind at all. All are the inevitable result of the mainstreaming of queer health research and bringing it into the NIH funding model.

If you've followed this blog in the past, you probably can guess that I don't think it goes far enough. I have to admit that I have not yet been able to read each and every sentence in the thing. It's huge. But I have read the executive summary, the intro and the recommendations, and I doubt that there is anything buried in the rest of the document that would alter my critique. (I hope I'm wrong, and look forward to being pleasantly surprised).
I also have to say that lots of this report makes for wonderful reading. If I had more time to devote to this, I would balance a lot of this criticism with things that the report does really well, like acknowledge that homophobia hurts straight people too.
I'm going to break my critique down into two sections. The first will address two broad deficiencies of the report: a failure to fully appreciate the health similarities and even advantages of TBLG people. What do we do well, for ourselves, one another, and for the society at large. A failure to understand the role of social context in the lives of queer populations except in a very limited and limiting way. Second, I'm going to tackle the recommendations one at a time..

Where's the Health?
Given that the report draws on the most frequently published research, it should have come as no surprise that the report concentrates heavily on health disparities in a very particular (and peculiar) sense. In virtually every case, "health disparities" means a health outcome (like depression, asthma, etc.) that we do worse on than heterosexuals. Very little attention is paid to those areas where we do about the same, and none (that I've found yet) of the things that we do better on than straights.
For example, gay men tend to have lower body mass index than straight men, but you won't find that anywhere in this document. Instead you'll find that lesbians are more likely to be heavy than heterosexual women repeated in at least three places, and a complete silence on the health advantage of gay men in this area.

Why focus only on adverse health disparities? As near as I can figure it, the rationale for focusing exclusively on adverse health disparities is that these fit nicely into the narrative that homophobia is bad, and homophobia affects TBLG people by making them less healthy in a variety of ways. Fair enough, but if homophobia is the thing making many of us sick, why not measure homophobia directly?

What's the danger of focusing exclusively on adverse health disparities?
1) It's not an accurate portrayal.
2) It's demoralizing - it reinforces the very effects of homophobia by making 'health' seem unattainable for queers.
3) It makes the radical religious nuts in this country smile from ear to ear - they love pulling out data about how unhealthy we are when they try to deny us various civil liberties (if not our existence entirely).
4) It doesn't explicitly differentiate whether these disparities are due to homophobia (as we would like to think), or whether they are due to some inherent, inborn insufficiency (as the nuts would like to think). Both interpretations are supported by these data.
5) We can't learn anything from the health advantages that we can build upon and use to improve the health of our communities if we can't call 'em when we seem 'em.
6) We can't really offer anything useful to other populations (heterosexuals, as well as other minority groups) as success strategies, if all we identify and talk about are what's adversely affecting us.
7) We can't learn how homophobia affects heterosexuals with this approach.

By analogy, the first century or so of research into health disparities affecting racial and ethnic minorities has largely fallen into the same trap, of spinning out a relentlessly monotonous string of adverse health disparities. These health disparities get interpreted by most of us as evidence that racism affects health adversely, and by bigots as evidence that they were right all along. Health disparities allow both interpretations.
A nearly exclusive focus on adverse health disparities has prevented us from seeing what it is that racial and ethnic minorities do well, what lessons can be learned to promote the health within these communities, and what lessons can be exported to the wider population as well?
For decades, epidemiologists have pondered and shrugged off the "Hispanic paradox", which is that many of the adverse health disparities one sees when comparing Blacks to Whites are not there when comparing Hispanics to Whites. And in many cases, (such as birth weight and longevity), Hispanics' health generally exceeds that of Whites in this country. Not looking into health similarities and advantages has really stalled both understanding the true nature of racism and how it operates in the US (it's a lot more complicated than 'being a minority'), and also being able to build on the record of strength that various communities have already demonstrated despite or perhaps because of living in a racially hostile social climate.

So, when this report focuses so exclusively on adverse health disparities, it really does us all a disservice. It's not an accurate picture of our health. It is demoralizing and depressing to read that litany. It supports our most adamant opponents' views of us. It doesn't get to the root cause. It doesn't show us what we've done well for ourselves, each other, or the communities (geographic, not identity-based) that we live in. It doesn't point (efficiently) to solutions. It doesn't address the degree to which cis-gender heterosexuals are affected by the same forces.

Social Context Involuted
I had the great honor to listen to a panel discuss the report at the 10th anniversary celebration for the Williams Institute on Friday. Stephen Russell was one of the panelists, and he really brought home the message that the report had been insufficiently curious about the role of social context in the document. I was practically giddy with excitement as he spoke, because I no longer felt like the lone curmudgeon in the room. Not that Stephen was a curmudgeon, not at all, I just was beginning to feel out of place as speaker after speaker lauded the report rather uncritically.

What do I mean by "insufficiently curious about the role of social context"? Well, I mean that the report does talk about the importance of social context, and much more so than the other documents of this type. One of the "cross-cutting perspectives" that the report recommends be used to understand TBLG health issues is:

A social ecological perspective--An individual's health is affected by community and social circumstances. LGBT health research should consider both the individual and the various contexts, including interpersonal relationships, in which the individual lives. (Summary, page S-6)

Not only that, they devote an entire chapter to describing the historical and social context of homophobia in these United States that is well worth reading.
Not only that, but also they have a terrific discussion of how stigma operates at various levels.

But, notice what happens in that definition of a social ecological perspective above - the definition sounds very inclusive of understanding how homophobia operates in the social environment, but the single specific context they mention is a highly individualized one "interpersonal relationships". Likewise, there are several points in the article which confuse "structural" with "institutional" or even "interpersonal" levels, where the interactions between patient and provider are characterized as "structural".

And when they get to the recommendations, this trick of collapsing social context down to the most proximal surroundings of a person happens every time the concept is mentioned. And nowhere in the recommendations is it suggested that a goal for understanding LGBT health should be to develop or use measures of heteronormativity and/or homophobia at any level beyond how it affects individuals in these very limited, proximal contexts.

I decided to do a bit of a quantitative analysis of this bias in the document (sorry my qual friends, I just don't know how to do your style well). I searched for the terms "stigma", "discrimination", "prejudice", "homophobia", "heterosexism", "heteronormativity", "homonegativity", and slight variations on these words.
The terms "stigma" (and "stigmatizing", etc.), "discrimintation" (and "discriminatory", etc.), and "prejudice" (and "prejudicial",etc.) occurred fairly often, including in the recommendations section. "Homophobia" and its kin occurred considerably less often, most often in the chapter on context, and the literature review, when other authors were being cited. It was completely absent from the recommendations, as were the other terms in my search list. About half of the occurrences of the term "homophobia" were in the titles of papers cited in the reference section.
OK, so they focused on "stigma" and "discrimination" in the parts of the document where they were proactively describing what they thought should be done in the future.
But every time these terms were mentioned in these sections, it was as though stigma and discrimination just happen to people, that there is no identified source. We should of course be measuring the experiences of discrimination and stigma that affect our health, but shouldn't we also try to identify those who do the discriminating? Those who perpetuate the stigmas?

Otherwise we run the risk of repeating what has been done in the "perceptions of racial discrimination" literature, where the source of that discrimination is rarely named (except in general terms like "at work" or "in health care"), and the use of the term "perceptions" invites the interpretation that this is somehow all in people's heads, that they are perceiving discriminatory acts whether or not they were intended to be discriminatory, and rarely delves into the pervasive issue of discriminatory actions that are not perceived as such (doesn't everyone get watched in those big mirrors when you're shopping?).

The Recommendations
The report has seven recommendations. Here's my take on them (wow that sounds egotistical. But it is egotistical, so I might was well own it instead of pretending that I represent a broad swath of TBLG opinion on these issues).
In general, these recommendations are written on behalf of people researching TBLG health, who are invested in the model of getting funding from the government to do so, written to the government agency that they seek to influence (and which itself seeks to be influenced).
As a result, they tend to look out for the interests of the researchers, even when these interests may conflict with those of many individuals in TBLG communities (although they are generally in concert), and they are intended to be appealing to a government funding agency that is notoriously shy about engaging in politically-charged areas.

The first recommendation is that "NIH should implement a research agenda designed to advance knowledge and understanding of LGBT health", which sounds pretty innocuous. What else should a group of researchers appealing to a government agency for more funding start out with. And who could object to more research?
I guess for me it comes down to what research are we getting more of? Demoralizing work on adverse health disparities (of which I would classify almost all the items listed in their specific recommendations in table 7-1, aside from the demographic items), or a richer exploration of health similarities and health advantages as well? Research that is highly individualized, dominated by the well-established methods of mass survey techniques, or research that starts with what we want to learn, then develops the methods most suitable to achieving those goals.
This part of my critique applies to the vast bulk of health research funded by the NIH, and isn't specific to TBLG health research at all.
More research, sure... but how about the right research?
There are lots of sub-recommendations under this one which I can't get into right now. Some of these have the potential to be great ("social influences on the lives of LGBT people"), and some leave me cold ("inequities in health care"), but that's for another day.

The second recommendation is that "Data on sexual orientation and gender identity should be
collected in federally funded surveys administered by the Department of
Health and Human Services and in other relevant federally funded surveys". More data = good... mostly. This one gets my unqualified support. The more surveys ask about us, the more we will be fairly represented. With sexual orientation, this is pretty easy, because the questions are there. Gender identity is a bit more difficult, because very little is known about how questions about gender identity perform in general population surveys. There are some dangers here, though. It is likely that the first few surveys that ask about gender identity will "get it wrong", but not in the way you're thinking - the biggest problem will be that a small number of people who have never given their gender a conscious second thought will answer the question incorrectly and be counted as transgender. As a result, a substantial proportion of the transgender-identified population will actually be inattentive or confused cis-gender folks, maybe even half or more.
But, as Gary Gates told me, if you don't have any questions on there, there won't be the incentive to fix them and make them more accurate.

The third recommendation "Data on sexual orientation and gender identity should be
collected in electronic health records" seems ill-advised to me. The research potential of asking these questions is phenomenal, but I'm not at all convinced that there are sufficient protections around this (or any) medical information to make it a standard field. And even when the information is protected sufficiently, there are many circumstances where being "out" on one's medical forms can be downright dangerous. I understand the potential for benefits in terms of getting more appropriate care, but that assumes that appropriate care is available, and that we even have a good sense of what appropriate care would consist of. I'm not convinced that we do know what TBLG appropriate care means in a broad enough set of circumstances to warrant having this information collected routinely on medical records. Should people who feel that it is important to their care have it recorded in their charts? Of course! But do we really want a young trans lesbian in Colorado Springs having that information on her record when she walks into see a provider she's never been to before?

The fourth recommendation is to "NIH should support the development and
standardization of sexual orientation and gender identity measures". Yes, of course. But at the same time, there is a risk that these standardized questions (much like the OMB directed race/ethnicity questions) will result in less curiosity about how people self-identify, and re-inforce the "normality" and reality of a small set of mutually exclusive categories. I still think it's a good recommendation. I just worry about cookie-cutter inclusion of the question in an un-thinking manner all over the place.

The fifth recommendation, that "NIH should support methodological research that
relates to LGBT health" is one I am fond of, but I think that is because I am really into methodology and want to see a certain set of methods (especially ecologic methods) built up, although most of it will probably be devoted to trying to turn various forms of "convenience" sampling into "probability" sampling. Boh-ring!

The sixth recommendation, "A comprehensive research training approach should be
created to strengthen LGBT health research at NIH" Sure, why not.

The seventh recommendation scares the pants off me. "NIH should encourage grant applicants to address explicitly the inclusion or exclusion of sexual and gender minorities in their samples". Sure there are abuses where TBLG people are inadvertently (and in some cases very intentionally) excluded from various research projects. But the discrimination we face in this regard is tiny compared to the historical discrimination against women and racial/ethnic minorities in particular in clinical trials. And a similar remedy for this past exclusion has had limited success and some strange side-effects (see Stephen Epstein's book Inclusion: The Politics of DIfference in Medical Research).
This formulation makes it sound like participating in health research is a civil right, and while exclusion from trials without a good basis should be discouraged, I'm not sure that adding another administrative check-box on the NIH grant forms will really achieve that goal, it may raise false hopes of being able to study TBLG folks in the vast majority of health studies. Perhaps most worrisome, by drawing attention to sexual orientation and gender identity as categories across which one should compare results, we are on the verge of being flooded with falsely positive chance findings that will crop up in various studies and which may or may not be able to be shoved back into the bottle with future research (as examples of this, I would cite the "gay gene" and "gay brain" studies, which, no matter how many times they have been subsequently disproven, still hang in the public imagination as valid). Another example of this (I can't remember if Epstein gets into it or if it came up after his book was published) was the spurious finding that an HIV vaccine candidate appeared not to work over-all, but did appear to work in a bizarre atheoretical grouping of African-American and Asian-American men. That finding was widely reported on, despite obviously being irrelevant to how the vaccine worked. It was a statistical fluke. And how often should we expect a statistical fluke? About 1 in 20 times. So if we start encouraging people to look at every possible health-related thing in every study, one in twenty statistical flukes is going to start adding up into an avalanche pretty darn quick.
In my opinion, if recommendation 7 is implemented, then a lot of researchers who have never given a second thought to TBLG issues are going to feel not only empowered to do these analyses, but encouraged to do them, and we're going to be up to our eyeballs in damage-control mode beating back spurious research results.

It Gets Better

Today I took a stand against gay youth suicide.
Sort of.
Don't get me wrong, I'm not in any way in favor of youth suicide, gay or otherwise.

I was inspired by the "It Gets Better" campaign, and when I heard that they were doing some shooting today within a few blocks of where I live, I decided to go over and lend a hand.
The most popular of the videos in this series presents Dan Savage and his partner Terry, with the aim of telling queer (or pre-queer) kids in high school that it may be rough now, but it gets better.



But I was also concerned about a couple of themes in this video that didn't sit well with me.

For one, I remember when people told me "don't worry, just wait. It gets better."
There is nothing more frustrating to a t(w)eenager than telling them to wait and sit on their hands. It makes it sound like everything it out of their control. All you have to do it wait - but waiting may be the one thing a young person cannot do well.
When people told me to wait and that "it gets better", I wrote them off as out of touch and out of options.

For another, I think it is potentially quite damaging to suggest that the best thing a queer (or pre-queer) kid can do is nothing, to sit back and wait for things to get better. What about coming out? What about taking a little bit of control over their lives? What about living authentically? I don't think that Savage and crew are suggesting that the best thing to do is nothing, but it's easy to read that message out of what they are saying.

Another thing that bugged me was the suggestion that the best thing you can do is tough it out, then leave everything behind and move to the big city. Well, the truth is, the big city sucks for a lot of people. I can't tell you how many people I've talked to living in San Francisco who moved here thinking that they would fall into the lap of a sweet landlady bearing magic brownies and get swept up into a fabulous and unstoppable social life, only to find that, just like everywhere else, you've got to build your social network from the ground up.
And when you don't have a solid grounding of who you are, the big city can chew you up and spit you out faster than you can say "doublemint".

OK, enough with the negativity!

So, I decided to go on over to the taping, and do my best to shift the message, a little bit. I wrote out a couple pages about what I wanted to say on my phone while walking over there, read & re-read it, and then shoved the phone in my pocket & spoke into the camera. I don't remember exactly what I said, but it was something like this:

Hi, I'm Bill. And you are awesome.

It will get better. It will. But that's not much help to you now.

There's a couple things you can do to make it better now.

One is that you can write, and read, about everything. Reading about history, how people have overcome amazing obstacles in the past.

And you can make things better now. For yourself and others.

To make things better, be yourself. When you are you, authentically you, then it doesn't matter what other people think or say.

And one more thing. 'It gets better' doesn't mean you have to leave everything you know and love behind and go to the big city. To be honest, the big city can be a pretty lousy place for young people.

But all across this country, from Portland Oregon to Portland Maine, from Austin Texas to Helena Montana, there are great queer communities. And when you do something to make things better, you make your home town better, too.

Things have been changing so fast in this country, all over the country.

So, it will get better. You can make it better.

I don't know if they will use it, or how they will edit it, but if it makes the cut, I'll post the video here.

More theory...
My thesis was about gay youth suicide. Well, actually, it was and it wasn't.
I was frustrated by seeing people amplify the statistics about gay youth suicide up into the scariest monster possible. Their intent was good - they wanted to draw attention to the plight of queer youth in order to do something to prevent suicide.
But, then the question is what do you do? Most of the boys who are struggling the hardest are not open about their sexuality, many may be completely unaware that they have a sexual orientation at all. Some of them don't want to be gay and are trying to find another way to be in the world.
So reaching out to queer youth is good for all kinds of reasons - but preventing suicide may be the least of them.
What is likely to be a lot more effective is changing the culture we live in so that it produces less stress in the first place.
So that's why I did my thesis about measuring heteronormativity in the social environment, and specific ways to improve the social environment (like passing gay rights laws), rather than trying to identify the individual-level risk factors that affect queer and pre-queer youth.

Legal Pot. Public Health. Queers.

Pot is going to be legalized in California. No matter what your stance on the voter proposition, legal marijuana is coming, and Public Health will probably be in the mix in ways it has not been until now. I myself haven't decided how I will vote, but that's not the point. My point is that as marijuana slowly moves from the eagle eyes of law enforcement, public health is the natural next step for surveillance, monitoring, and control.

A couple weeks ago, I had a great conversation with a former (and future?) student about, among other things, what will happen once pot is legalized in California. He's been involved in the efforts to identify tobacco use as a health concern for gay men, lesbians, bisexuals and trans folks for many years, and we were wondering about how the activists who have built such a strong network around tobacco and smoking will react to legal joints in California.
Will the queer tobacco activists see themselves as primarily focused on tobacco (including smokeless tobacco like snuff & snus), or on smoking, which could potentially include pot, or both (which could possibly include vaporizers, brownies, etc.). Or will the idea of sounding like a negative Nancy on pot mean that we will just ignore the health consequences of smoking marijuana on queer folks?

Then, the other thing that got me thinking was looking into the environmental impacts of growing pot, because I'm looking for good material for my upcoming class on environmental health, and I figured that topic might engage some of the students.

At any rate, there are a lot of issues to think about there...
One can hope that the legalization of marijuana in California will lead to more environmental growing conditions - fewer diesel-powered generators, fewer diesel spills, less pesticides and more sustainable farming practices all around. But if there is an increased demand with no change in Federal enforcement efforts, there will still be a lot of pressure to grow pot in ways that are extremely damaging to the environment. What will the role of public health and environmental health be in developing policy and regulations? Will "organic" pot be certified by the same rules as USDA has developed for food?

For many years now, marijuana has been promoted as "medicinal". I'm sure it is for many people. But there are unintended consequences of promoting marijuana as medicine.
For one thing, a lot of people seem to be convinced that smoking marijuana is healthy, is good for you, even if you're not treating any health condition with it.
For another, a lot of people seem to think that smoking marijuana is just not dangerous compared to smoking tobacco.

If marijuana has been promoted as good for you, and now it becomes legal, it is complicated to modulate that message to be honest about ways in which it is not good for you, too.

So, where does public health come in on legal marijuana? We've gotten a pass because regulating marijuana has been the province of law enforcement. The "soft power" of Public Health has not been called on, and the research, as stunted at the field has been, is very polarized, with some researchers claiming that marijuana has virtually no down side, and others saying that marijuana smoke is more hazardous than tobacco smoke, and most researchers just not making much of it one way or another, because being illegal, it is assumed to be a bad thing anyway.

But that brings up another point - it is really hard to get any decent epidemiologic data on the health effects of smoking marijuana. On the one hand, the illegality of pot has led to the polarization above: the researchers are often so devoted to one side of the debate or the other that it is hard to trust their work. On the other, the illegality of pot makes asking questions about people's use a bit more ethically complicated, and also hard to trust people's self-reports of engaging in an illegal activity. And then on the third hand, there's the simple fact that most (but certainly not all) people who smoke marijuana also smoke tobacco, which makes teasing apart the effects of marijuana on health very tricky.

So where am I after thinking about all this?
Not much farther from where I began. I don't see myself likely to get very engaged in this debate. But, I will be interested to see what happens as the desire for society to somehow curb and contain the use of this substance moves from law enforcement to public health. And I will be curious to see how the message that "marijuana is medicine" gets tagged with the small print we're now familiar with from ads for pharmaceutical drugs, and tobacco products, for that matter. What will the Surgeon General's warning be? What will the breathless, low volume pitch-man sound like when rattling off the unpleasant side effects? And when will the large cohort studies needed to answer the fundamental health questions get funded?

Internalized Homophobia - Why Measure it?

Recently I saw an article that suggested that measuring internalized homophobia might be a waste of time.

I was intrigued. I have to admit, I've never been a big fan of internalized homophobia. Measuring it, I mean. But I never stopped to think out why the idea made me a bit queasy.

Maybe I should back up a bit. One of the leading theories about how homophobia affects people is that homophobia operates simultaneously at multiple levels: societally, institutionally, interpersonally, and internally.

Multiple levels of homophobia
At the societal level, homophobia (often called heteronormativity in this context), is the shared set of beliefs and assumptions about who ought to be porking whom. But more than that, it is a nexus of assumptions about what family structure and kinship should look like, about what gendered identities are possible and how they should be expressed. That's one reason why the debate over same sex marriage has been so contentious within the gay community - one the one hand it is about equality of opportunity, on the other, marriage is practically the very definition of heteronormative values.

Institutionally, homophobia can be expressed in official policy, or less official actions that intentionally treat sexual minorities differently than heterosexuals, or that result indirectly in the same effect.

Interpersonal homophobia is probably what most people think of when they hear "homophobia" - it's the disparaging words, the punch in the nose (then the gut, the groin, the kick when you're already on the ground, need I go on?). Interpersonal homophobia is the expression of prejudice from one person directed at another.

Internalized homophobia can mean a couple different things depending on who you're asking. Usually it refers to a form of self-loathing among gay men, lesbians, and bisexuals, the internal application of societal views on homosexuality on oneself. Sometimes people talk about internalized homophobia in anyone, including heterosexuals, as the result of internalizing the societal homophobia as being what one believes about homosexual and bisexual people.

So all these levels are in constant interaction with each other as well. A person is unlikely to let off a string of interpersonally homophobic slurs unless they have internalized societal views about homosexuality. They are unlikely to internalize these assumptions unless there is a shared ethos of homophobia in which that person lives, or grew up, and so on.

And all these can be in conflict with one another. For instance, one may live in a relatively non-homophobic society (like Rhode Island) with relatively few institutional policies that hinder people with same sex desire, but be in a more homophobic institution within this (such as a Catholic school), which nonetheless has a strong tradition of supporting individuals within the institution, and exposing them to very little interpersonal homophobia, so long as they maintain an internalized sense that their homosexuality is wrong.

So what's wrong with measuring internalized homophobia?
Based on the above, I obviously think that internalized homophobia is an important part of how homophobia/heteronormativity affect people. If nobody internalized homophobic assumptions, then it could not survive at a societal level either.
So why not measure it?

The article I read said that measures of internalized homophobia had very little predictive value for why some gay men get HIV and others don't. Not only that, but what predictive capacity it once had is rapidly diminishing. So, their argument was that it doesn't predict much, so measuring internalized homophobia may be a bit of a futile exercise.

But that wasn't entirely satisfying to me as a reason to avoid measuring it. So what if internalized homophobia has relatively little impact on HIV transmission - maybe it still plays a big role in some other health issue, like depression.

No, what I've decided bugs me about measuring internalized homophobia is the "internalized" part. I mean, describing "internalized homophobia" as a major health risk may in some sense be an important mechanism, but what sort of intervention does it lead to? How does one use that information to try to prevent disease, or better yet, promote health?

By describing "internalized homophobia" as a major health threat to sexual minority populations, the implication is that there are some of us who are in trouble (those of us who have internalized societal degradation as just), and others of us who are fine (we've coughed up the furball of societal hatred). Then what? Either the people who have internalized societal homophobia need some sort of intervention (which is paternalizing if that person is not actively seeking help), or they have some how brought these problems on themselves, failed to do what they need to do to take care of themselves.

The problem, as I see it, is that a focus on "internalized homophobia" focuses the potential for interventions internally, and doesn't take into account the full spectrum of the levels at which homophobia operates. Focusing on identifying and intervening with individuals who have internalized homophobia in no way explicitly challenges the broader social context within which these internalization processes occur.

-------------------------

Michael E. Newcomb, Brian Mustanski. (2009). Moderators of the relationship between internalized homophobia and risky sexual behavior in men who have sex with men: a meta-analysis. Archives of Sexual Behavior Epub aread of print 04 Nov 2009.

Michael W. Ross, B. R. Simon Rosser, Derek Smolenski. (2010). The importance of measuring internalized homophobia/homonegativity. Archives of Sexual Behavior Epub ahead of print 12 May 2010.

Transit ads to make your eyes sing.

Like it or not, advertising is a big part of our visual environment.

San Francisco is a city that advertisers love to target. We are trendsetters, I suppose, so the ads often get quite aggressive in order to capture our jaded attentions.
I've seen pillars mounted with palm fronds (selling what, I can't remember), lavish inside views of the first class cabins of some upstart airline, all kinds of eye-catching stuff. And I have to admit, as much as I resent having my attention grabbed for profit, a lot of it is fun and playful.

But that's downtown. Up at Castro, your eyes are much more likely to be met by the sad empty face of a meth addict warning you not to follow in his footsteps.

The Castro is an international destination for gay men, and yet our visual environment is a long series of sad, unhappy, preachy, demeaning advertisements designed to remind us of how precarious our lives are, how we are one short step from misery and pain.
Well, at least until you emerge onto the street level, and your eyes are met with a series of bulges and slick colors designed to turn your money into alcohol.

So, when I came across these ads this morning on my way to work, I was happily surprised. I've seen these same ads on the BART, but in this context, they are obviously designed to appeal to a gay (male) audience, first by their location, and particularly because of the color scheme, the lollipop bright red-orange-yellow-green-blue-violet rainbow flag of smiling children, with a heavy dose of bubblegum pink tying it all together. These ads aren't cheap, the production values are high, and they spent a good bit of effort custom sizing everything for this particular space.

So I find myself wondering two really different things:
First, with the evangelical Right itching for a fight over adoption, why did adoptionSF.org decide to take the risk of catering to gay potential adoptive parents in such a blatant manner?

But the thing that's really got my head spinning is this. These ads are so different from any health-oriented ads I've seen in San Francisco. The first obvious difference is that they are up-beat. The second thing is that they are asserting quite forcefully that we have talents and capacities that are desperately needed.

Now, I don't know exactly what an ad campaign about gay men's health that was up-beat and urged us to exercise our talents and capacities would look like. But I'm hungry to see it.

Seeing Healthy Gay Men

I've been invited to take part in a panel discussion on Wednesday. Here's a preview of my talk. I'd love feedback on the flow, grammar, anything to make it roll off the tongue easier. I don't have a lot of time to deliver the talk, and I want to get some key ideas out there clearly.

SEEING HEALTHY GAY MEN
Introduce yourself to the person next to you, just your name. Hold their hand, and look right into their eyes, take a good deep look. Think about how healthy this person is. Through all of life's adversities, here is this healthy person in front of you.

What I've just asked you to do is very different from how I, as a public health researcher, look at gay men. To put it bluntly, in public health, we don't see healthy gay men.

First of all, we are not accustomed to look at health in anyone, queer or bland. We almost always look at sickness and death, and very rarely at health. Sickness is easier to measure than health. Sickness is seen as objective, while 'health' and 'well-being' are subjective states. Death is the most objective health outcome, and thus the most trustworthy object of study. So it's nothing special about gay men. We're not used to seeing anyone as healthy.

But there other reasons that public health, broadly written, is not used to seeing healthy gay men.

One of these is that a little over a hundred years ago, the fields of medicine (and later psychology) tried to exercise authority over homosexuality, to claim it as their turf, a claim widely supported by homosexuals at the time. It was a humane alternative to being regarded as the embodiment of sin, or being treated like a criminal.
Old habits die hard, and it has been hard to let go of these 'humane' impulses, despite the official depathologization of homosexuality in 1975.

Another reason that public health has a hard time seeing healthy gay men is that we actually have a lot invested in gay men being ill. That may sound strange at first, but think about it - citing health disparities is how we raise awareness about the health challenges facing us. Playing up health disparities is how we get money for programs. It's often how we make claims that legal protections are needed, how we describe ourselves in media stories to gather support.
So seeing healthy gay men risks upsetting the apple cart, derailing the gravy train, if you will.
And then there's the right wing. Not only are we a threat when we're sick, but if we're not sick, then we don't need "special" protections. We just can't win with those guys.

The last reason that public health has a hard time seeing healthy gay men that I want to raise is the perceived 'failure' of HIV prevention. While it would make sense to look at the relatively small number of new infections these days compared to the early 1980's and claim a great deal of success in HIV prevention, there is a tendency in public health circles to treat each and every new infection as a failure.
After all, we know a lot more about the biology and psychology of how HIV is transmitted. Hundreds of millions, probably billions of dollars have been spent on research and prevention efforts in the US, so even a single new infection represents some sort of failure in our prevention efforts.
Often implicit in our conversations about the 'failure' that each new infection implies is some blame directed at the man who got infected, and perhaps towards the man who infected him. Were these guys high? Careless? Selfish? Immature? Maybe they were just looking for love in a harsh world. Maybe they were possessed by the worst affliction a gay man can have in the eyes of public health: being a bug-chaser. All of these explanations imply that the infection was enabled by an individual weakness. So we are used to seeing gay men as sick, or at least as perpetually 'at risk'. And any attempt to break free from a life constantly 'at risk' must be a little crazy.

There may be other reasons that we public health types have trouble seeing gay men, but these are some of the big ones: 1) public health has a hard time seeing anyone as healthy, 2) the historical disciplinary claim of medicine and psychology implies that there is something inherently pathological about homosexuality, even though an explicit claim of pathology would be rejected in most circles. 3) seeing healthy gay men undercuts our ability to raise awareness within the community, and funds for services from public and private granting agencies, and 4) how else does one explain 'failures' in HIV prevention?

EVIDENCE OF HEALTHY GAY MEN
And so, a little over a year ago, when I came across evidence that gay men might well be healthier that straight men, I was dubious.
I was looking at data from the 2003/2005 California Health Interview Survey, the idea I had was to systematically go through the CHIS, documenting the disparity of each health outcome for gay and bisexual men relative to straight men, and for lesbians and bisexual women relative to straight women.
The first one on the list was pretty boring, at least from an epidemiologic standpoint: "in general, would you say your health is excellent, very good, good, fair, or poor?" Although this is by far the most common question on health surveys, analytically, we usually treat it like a throw-away question, basically a way to build rapport with the person on the other end of the phone before getting in to the more personal and revealing questions.
I expected to see what others before me had seen, that gay and bisexual men were more likely to report "poor" overall health. And they were in this dataset, too. But more striking was that gay men were also more likely to report being in excellent health. And that difference was larger.

But like I said, I was skeptical. Maybe it was a statistical fluke. I did what any sensible epidemiologist would do. I ignored it and moved on.

But, it stuck in the back of my mind.
When the 2007 data came on-line a short while later, I took another look, and the same pattern held. So now, I began to wonder if there might be something to it, these healthy gay men, not less healthy than straight men as everything had led me to expect, not equally healthy as straight men, but actually more likely to be healthy.
So then I began to look at other datasets. In most datasets, but not all, gay men were more likely to report excellent health.
I was still dubious.
Perhaps gay men were more likely to be in excellent health because they were younger, more educated, affluent. In most studies, men who say they are gay tend to be younger, more educated, affluent, and these things also tend to produce better health. So now I needed to find a dataset that was large enough to break people down by age and socioeconomic position.
I found two very large datasets, the Current Population Survey, and the Behavioral Risk Factor Surveillance System.
In both of these datasets, gay men were more likely to be in excellent health than straight men in all age groups, and within all levels of educational attainment. The BRFSS dataset was so large that I could stratify by both age and educational attainment simultaneously. Same result.
So now I knew it wasn't a fluke, it wasn't just because men who say they are gay to a stranger on the phone are just demographically healthier. Gay men were actually more likely to report being in excellent health.

Once I'd convinced myself that gay men are more likely to be in excellent health, that it was a 'real' finding, the next question is "Why?".
With all the HIV, STD's, alcohol abuse, drugs, depression and anxiety, even suicide documented in the literature, it still baffles the public health mind.
I'm going to leave the question "Why?" open, and move on instead to a related question: "So What?".
If gay men are more likely to be in excellent health, what are the implications of that?
One implication is that in the face of the long, oft-repeated litany of health-related faults, some gay men have found a way to thrive, arguably with no assistance from us in public health.
Perhaps we can learn from these healthy gay men. But that requires being able to see healthy gay men, and then to talk with them, and ask the right questions.
The salutogenic (health-creating) processes that these men have undertaken could be a blueprint for the rest of us, a novel approach to addressing the troublesome health disparities that gay men face.

Another implication is that gay men may well be doing some things 'right' that heterosexuals could do well to emulate. Perhaps the ways that we gay men have learned to structure our lives, with strong friendship networks, provides space for us to excel. Perhaps our more nuanced approach to monogamy and relationship structures gives us permission to be truer to ourselves and the ones we love. Pure speculation on my part, but if more of us are in excellent health despite all the social forces arrayed against us, we've got to be doing something right, and maybe if we knew what that something was, it would help society at large.

{I haven't quite figured out how to wrap it up yet}

Healthy Gay Men

After I Left AIDS - Part III (more thesis)

I didn't want to study suicide.

Mainly because suicide is a bummer of a topic. It reminded me of unpleasant memories from adolescence. And whenever I talk about it, the first thing everyone does is get quiet - then they get concerned about my well-being. Which is nice and all, and I appreciate it, but after working on this stuff for a few years, I would forget the level of emotional charge the topic has, and get really excited about some finer point of data analysis, and come off sounding callous when really all I wanted to share was this exciting little piece of the puzzle.

On the other hand, epidemiologic studies of suicide go way back (to Durkheim in 1897, and before him Morselli in 1881), and unlike most health conditions associated with sexual orientation, suicide has been measured in a consistent way across the whole population for an extended period of time. So, in a sense I was stuck with it as the only health outcome that had both geographic and temporal scope, which is what I needed to look at normative heterosexuality.

So anyway, as I mentioned before, I wanted to look at how heteronormativity (a shared set of assumptions about sex, gender, and who ought to be having sex with whom) affected suicide rates.
At first, I wanted to find a data set where I could could compare gay men, lesbians, and bisexuals to heterosexuals. But the death certificates don't have that kind of information. And as I got to thinking about it, even if they did, how reliable could it be?
And that got me to thinking, maybe the sexual orientation of these people is really beside the point. Perhaps the stresses associated with dealing with assumptions of heterosexuality are greatest among people who don't identify as "gay" anyway.

So, the first study I did was to look at gay rights laws as a measure of heteronormativity, the idea being that in order to enact a gay rights law, politicians have to believe that public opinion is such that they'd be better off protecting sexual minorities from discrimination than not. The first gay rights laws were enacted in 1973, in San Diego and Austin, I believe. In 1981, Wisconsin was the first state to pass a gay rights law, and by 2003, most of the country's population lived in a jurisdiction with a gay rights law. (the gray map there has a nifty time-lapse).
I looked at three levels of gay rights protections, in order to get something like a dose-response curve - the red areas had no protections whatsoever, the green areas were protections for public sector workers only, and the blue areas had protections for both public sector and private sector workers.

And the results here are pretty compelling - at least for White males, particularly adolescents, young men, and the elderly.
Each color in this graph represents a different age group. So, among White males aged 15-19, suicide rates were 179 per million in areas with no gay rights protections, 155 in areas with protections limited to the public sector, and 131 in areas with protections for all workplaces. The only group without a step-wise dose-response was White men aged 45-64.

Among White women, the first thing to notice is that suicide is less frequent, and also doesn't increase among elderly white women, unlike men. The decline in suicide rates with increasing levels of gay rights protections is also not so pronounced, but there are declines in each of the age groups under 45.

Suicide is less common among Black men than White men in the US, but is still pretty high. And unlike White men, the peak incidence of suicide is in younger age groups. But what is strikingly different is that the highest suicide incidence among Black males is in areas with the highest levels of gay rights protections, which suggests to that public opinion among Black populations about homosexuality may not be strictly related to public opinion among White populations from the same area, and presumably the enactment of gay rights protections is, in most jurisdictions, reflective mostly of White public opinion. I'd love to do an analysis based on what might be a better measure of heteronormative assumptions in Black communities. Any ideas?

Among Black females, the incidence of suicide is lower than the other populations above, and like White females, declines among older women.
The differences between areas with and without gay rights protections are not large, but in general, suicide rates among Black women tend to be slightly higher in areas with gay rights protections. So these results also raise questions about whether gay rights laws are a good measure of heteronormativity for all populations. Or alternately, if the social forces leading to suicide are perhaps not identical among White and Black populations - perhaps heteronormative assumptions cause more distress in White populations, particularly among White males, while economic issues and racial discrimination play a larger role in Black populations.

Another consideration is that perhaps the stresses induced by heteronormativity are largely related to the performance of masculinity, which is why men turn violent against themselves under these pressures. Perhaps men under heteronormative pressures also direct violence outwards towards the women closest to them, and thus homicide, rather than suicide, might be a more strongly related outcome among women. That's foreshadowing to an analysis I'm thinking about doing next...

The patterns I noted are virtually unchanged after adjusting for a wide variety of potential confounders, namely population density, region of the country, unemployment rate, poverty rate, and measures of social isolation (proportion living alone, proportion who moved in the last five years).
Also, when I looked only at those areas that changed status (went from no protections to having gay rights protections), the same trends held up, so in order to explain these results, some other factor would have to be changing at the same times in the same places, which seems like too much of a coincidence to be possible.

The trends above are very similar when I looked at how people vote on the restriction of marriage to "one man and one woman" as a measure of heteronormativity, but as I mentioned before, the strong trend towards people being less likely to endorse a restrictive definition of marriage makes this measure a bit more complicated, so I'm trying to figure out how best to represent it.

After I Left AIDS - Part II (Thesis)

So, after I left AIDS, I got thinking about how homophobia, as a societal norm, affects health. Not just queers' health, but how it also affects the health of the whole population.

In my last post, I talked a bit about my journey through thinking about health disparities, and how nobody seemed to be measuring the causes of these disparities. That leads directly to my doctoral thesis, which was about how to measure normative heterosexuality, and from there, estimating the impact of it on suicide. Not just on "gay" suicide, but suicide in the whole population, and also in various sub-populations defined by sex, age, and race/ethnicity.

So, following the lead of thinking about residential segregation by race/ethnicity, and income inequities, I began thinking about how to measure normative heterosexuality, the presumed cause of the health disparites that epidemiologists had begun to document with greater and greater precision.
How do you measure the degree to which a group of people (a large group of people) share a rigid set of beliefs about sex, gender, who ought to be having sex with whom, and how? My first thought was that the frequency of hate crimes directed against gay men would be a good measure. If this set of rigid beliefs dominated a social setting, then the informal "enforcement" of those beliefs would be enacted through the commission of bias-motivated crimes, presumably mostly by young men with "something to prove".

When I pulled the data down off the FBI's Uniform Crime Reporting (UCR) System, I quickly realized something was amiss. San Francisco had by far the highest number of anti-gay hate crimes in the country, and several Southern and Mountian states reported not a single one.

I've put more recent statistics by state in a table, based on numbers from 2004 to 2008, the five most recently reported. Basically the same trend holds - bias-motivated crime tends to be higher in places we think of as gay-friendly, and extremely low in the deep South. Then there are also strange jurisdictional oddities - Pennsylvania for example appears to have an extraordinarily low rate of bias-motivated violent crime.

The way I've come to understand this data is that it represents not the phenomenon of crime occurring, but rather on two phenomena: 1) how comfortable victims feel about reporting a bias-motivation to law enforcement, and 2) local law enforcement customs and legal constraints about recording and validating these reports. If it was just the first of these, then one could use the reporting of hate crime as a measure of homophobia at a societal level, that is the more hate crime reported in an area is evidence of how little homophobia there is there, as perverse as that sounds. But alas that second factor, particularly the bit about jurisdictional quirks in how different local law enforcement agencies deal with the reports that are made to them, really throws the whole thing off.

So, I couldn't use hate crime statistics. But maybe I could use the presence or absence of a law for reporting hate crime statistics that specifically included sexual orientation. Or, how about the presence or absence of a law prohibiting discrimination on the basis of sexual orientation?

So, the next thing I looked at was which states had gay rights laws, and when they were enacted. Various of the states have enacted gay rights laws over the years, the first being Wisconsin in 1981, a few more in the late 1980's, and a lot during the 1990's. Recently, state-by-state gains have slowed considerably, as gay activists have pressed for a national law (ENDA), or been distracted by the marriage thingy.
The point for my purposes is that the enactment of state-wide gay rights laws has been a pretty hotly-contested issue, debated for years within each state's legislature, rather than by a small cadre of legalistic judges, or the flash of public opinion of a referendum. As a result, the enactment of a gay rights law represents something of a local watershed, the point in time at which the balance of adverse consequences for elected officials switches from a net negative to a net positive.
So, looking at the enactment of gay rights laws seemed to hold promise, at least from a theoretical perspective, as a good measure of the broad social environment of a State in regards to the level of normative heterosexuality.

Another potential measure of normative heterosexuality to be considered is public opinion polling. The gay rights law thing seems a bit crude - a yes-or-no variable to measure something which I claimed varied by degree from one place to another, and one time to another within those places. Public opinion polling, on the other hand, offered the promise of a finely-tuned measure of normative heterosexuality. There are some relevant questions that have been asked the same way for decades. For instance, Paul Brewer has examined the time trends in how Americans feel about the "wrong"-ness of same-sex sex, which increased during the AIDS years, followed by a precipitous drop recently, the majority of Americans now saying it is not "always wrong" (small consolation that!).
So, public opinion polling looks like it might be a better "thermometer" to gauge how people feel about homosexuality. And there is longitudinal data to work with, so I could look at changes over time.
On the other hand, public opinion polls, by design, ask the smallest number of people possible in order to get accurate results. Thus a "large" national poll might have only 500 respondents. The GSS from which the data above is generated is a good bit larger than that, but still it is only a few thousand in any given year. A few thousand sounds like a lot of people, but what I needed to do was compare across places, not just time. So a few thousand breaks down into a few dozen in some states, and in others, fewer than ten. It would be a stretch to characterize the whole State of Connecticut based on how 15 randomly chosen people answered a question (for the record, I'm pulling that number out of thin air, but that's about what it comes down to).

So I was stuck with public opinion polling, too. Good temporal trends, but lousy in terms of geographic specificity.

A related idea was to look at how people voted on anti-gay referenda, such as the Briggs Initiative in California in 1978, Measure 8 in Oregon in 1988, and Colorado's Amendment 2 in 1992. These explicitly anti-gay referenda had the advantage of high geographic specificity, presumably accurate down to the precinct level, but represented a snap-shot in time. Also, they represented a small number of states, and the questions addressed in each one were quite different.

While I was working on my thesis, though, another opportunity to think about voter referenda came up. The issue of same-sex marriage cropped up. Although same-sex marriage has been contested in U.S. courts since 1970, it had never gotten much notice one way or the other - the Christian right didn't feel threatened by it, and most gay acitivists thought marriage was a non-starter politically, or at any rate a horrid reminder of heterosexuality run amok that should not be emulated.
But in 1998, Hawaii and Alaska voters chimed in on same-sex marriage, a few more did in the 2000 and 2002 elections, and then the 2004 election was swamped with voter initiatives to restrict marriage, in part a cynical manipulation by Republic Party operatives in order to keep their guy at the helm.

These referenda share the problem that opinion polling data have, in that they are a snap-shot in time (except for a few states which have had multiple referenda on this issue), but there were major advantages. For one thing, the question being asked was nearly identical in every state, some slight variation on whether legal recognition of marriage should be restricted to "one man and one woman". As an aside, no state has yet offered to restrict marriage to "one woman and one man" - something to consider when thinking about marriage as a forum for liberty and equity. And, the geographic scope was huge, with most states chiming in on the issue one way or another. The map I made here shows how different areas voted, from strongly in favor of restricting marriage (red) to being against restricting marriage (dark green).
On the whole, this map comports more or less with what one would expect, there's more red in the rural areas, more green in urban centers and on the Pacific coast, and there seems to be a trend towards more green in the Northeast. But there are some unexpected spots, too, such as South Dakota, which was substantially less in favor of restricting marriage than its neighbors Nebraska and North Dakota, And Arizona, which was the first state to reject restricting marriage in 2006 (alas, they went to the dark side in 2008).
So, there are some tricky issues to deal with in using this data. I haven't quite figured out how to make it comparable across time periods.

The final method I've thought of for measuring normative heterosexuality is using counts of same sex couples. The number of same sex couples was counted (albeit inadvertently) by the U.S. Census in 1990. For the 2000 Census, they did a better job of it, and the upcoming 2010 Census is expected to do better yet.
In any event, the number of people who identify themselves as married same-sex partners and un-married same-sex partners in the Census is probably mostly a factor of three forces: 1) How comfortable people in same-sex couples feel identifying themselves as such on the Census forms; 2) The degree of selective in-migration and out-migration of people in same-sex couples (or destined to join one), and 3) The degree of confusion by people in mixed-sex couples who inadvertently identify themselves as same sex partners.
The first two of these factors (net migration and comfort identifing as a same-sex couple) are related to what I want to measure - how accepting an area is of homosexuality. The third factor is a pain in the butt, not in a good way. I've discussed that issue at length before.

So, counting same-sex couples has two huge advantages: it uses the same methodology for the entire United States, and you can get comparable data down the the neighborhood level (census tracts). On the other hand, the data itself has some big caveats - it doesn't identify young people, single people, or couples living in separate residences, and it is essentially useless when considering older people (for reason 3 above). And although there will soon be three time points to compare, the methodology has changed in each Census, and it remains to be seen if the 2010 Census data will be comparable to the 2000 Census data (probably not, but for the reason that the methods are becoming more accurate).

So, in the end, I decided to pursue three measures of normative heterosexuality further:
1) The enactment of gay rights laws,
2) How people voted on referenda to restrict marriage to one man and one woman, and
3) The proportion of same-sex couples identified in the Census.

More to come...