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

Reflections on Proposition 8 Trial

I've had the privilege of sitting in for part of the proposition 8 trial (Perry v. Schwarzenegger), yesterday and this morning.
The trial has been incredibly interesting, although I have to say, the parts I sat in on were kind of slow.

I'm not a big fan of similar-gender marriage as a goal. And I'm dubious about the chances that this trial will succeed. But I have to say, it is doing an amazing job of revealing what the debate over similar-gender marriage is really all about: the prejudice that Evangelicals (and various allies) have against queers.

I'm convinced that this wouldn't be a big issue item on "the gay agenda" if the Evangelicals hadn't shoved it on us. An excellent book Courting Justice describes how individual queers have for decades (at least back to 1963, if not before) have tried to get some sort of official recognition of similar-gender marriage rights in the courts. But the issue didn't take off for the wider queer population.

Even after the Hawai'i decision in 1993, it still didn't take off. Even in 1998, when Alaska and Hawai'i were the first states to vote to restrict marriage, the wider gay community wouldn't touch marriage. A few people wanted it, but many of us thought of it as a badge of heterosexuality, a cowardly dodge from realizing one's full queer potential. A very bizarre "right" to demand.

But by 2000 there were the beginnings of a shift, and by 2004, it was absolutely clear we were being attacked with this thing, and we'd better start defending ourselves. Tell someone loud enough that they can't do something, and you know what they'll want to do next.

immutability, identity/behavior/desire
At any rate, here we are, many not excited about similar-gender marriage, but pissed off by being attacked as pedophiles, unfit parents, mentally deranged, sinful, and the certain cause for the ruin of Western Civilization.
In today's grueling 5+ hour cross-examination, Prop 8 lawyer Nielson badgered anti-prop 8 witness Gregory Herek with hundreds of variations on the same theme, trying to get him to say that homosexuality is neither definable nor immutable.
It is fairly clear that what the pro-prop 8 side was trying to do today is to make two claims. First, that homosexuality can't be clearly and unambiguously defined in the same way for all contexts, so homosexuals shouldn't be considered for equal protection under the U.S. constitution.
Second, that people's sexual orientation can change over time, and if so, which "class" a person fits in is ambiguous, making it impossible to consider equal protection under the U.S. constitution.

This seems like a pretty risky strategy on their part, since the exact same logic would lead one to conclude that religious affiliation should not be a basis for seeking equal protection. After all, one of the central tenets of Evangelical Christianity is that one's religious affiliation can change, and even ought to change in order to become 'saved'. Furthermore, it is not possible to define religious affiliation in clear and un-ambiguous terms.
Nielson hammered away at the themes of "identity, behavior, and desire" or words to that effect, as being multiple dimensions along which one could define sexual orientation, for research purposes.
Identity: "What do you call yourself?"
Behavior: "What have you done?"
Desire: "What do you want?"
A nearly-perfect analogy could be applied to religious affiliation, and the first two dimensions are routinely differentiated by sociologists studying religious affiliation. So should religious affiliation not be considered for equal protection because some people might define themselves as "Catholic", but not attend services, while others would decline to identify any particular denomination while attending services regularly?

Also, another category traditionally considered for equal protection would also fall apart under this logic, namely marital status. One's marital status can change over time (by becoming married, or becoming widowed, separated or divorced). Should it not be protected as a result? In this case, it is a change that is clearly under conscious choice (one certainly hopes that marriage doesn't happen by accident, or for unknown reasons).

The plaintiffs lawyers, for reasons I don't understand, haven't yet gone for the jugular on these points. Why not freely admit that sexual orientation changes over time, and is devilishly difficult to define in unambiguos terms? That doesn't seem to have much to do with whether a "class" of people should be protected from discrimination. Then come right back at 'em. Instead, the plantiff's witnesses have mentioned, from time to time, that ethnicity and race aren't easy to define either, and what "class" one "belongs" in can change over time. True, but the analogies between religious affiliation and sexual orientation seem more apt to me, and have the added advantage of putting it right back on their plate.

why get hung up on choice?
Another issue that Nielson fought over with Dr. Herek was the degree to which people's changing sexual orientation is under conscious control. Knowing what I know now, I would choose to be gay. But back in high school, when I was struggling to figure it out, I would have done anything to "choose" heterosexuality. It would have been easy. It would have made my parents happy. Heck, I even tried to be heterosexual - on my second "date" the girl laughed out loud when I said I thought it was a date, saying "But Bill, you're gay!" Sigh, I miss Rachelanna.

But back to the issue at hand, I think it's perhaps too easy to say that Evangelicals often believe homosexuality is a choice (conscious or otherwise) because their understanding of the Bible is that it is a sin, and that much like stealing, one may choose to "do" or not "do" no matter how strong the urge.

But I wonder if there isn't another reason that's just as strong. By enacting and re-enacting, and re-enacting, and re-enacting stories about "coming to the Lord", Evangelicals narrate to themselves and each other a story of conscious choice about a fundamental aspect of their being. I've listened to enough religious right radio to know that spontaneous conversion isn't nearly as common as stories of spontaneous conversion, which are ubiquitous.
Perhaps the belief that homosexuality is chosen reflects these continuously repeated narratives about choosing to be saved. Perhaps insisting that homosexuality is chosen despite all available evidence is really another means to re-inforce their own narrative of choice in matters religious.

In the past, I've pondered the fact that gay men tend to reinforce innate-ness and lack of choice in their coming-out stories. Mirroring the process above, when we tell and re-tell our stories to one another, these characteristics of innate, unchosen immutability become more and more central to our sense of self and identity. I think that's a lot of how I became gay, anyway.
I was Bill, then I became gay Bill. I didn't become gay out of being straight, I became gay out of unformed nothing-ness because it was the social construct available to me that best fit who I was, innately. In another setting, I might well have become celibate, or str8, or something like it, depending on what was available to me in the way of social role narratives.
Now that my gay identity is fully formed, I no longer need to tell coming-out stories to reinforce my sense of who I am, and rarely do. Part of that is that everyone who needs to know already knows, but mostly it's because I don't need to tell that story any more to know who I am.

Hate crime statistics
Yesterday, one of the prop 8 lawyers tried to run an event in the Oppression Olympics by comparing the number of crimes reported as being bias-motivated around sexual orientation to the number reported as being bias-motivated against Judaism.
I was shocked when the witness seemed to fall for it. He ended up giving a fairly reasonable response, but the premise that these numbers would be in any way comparable I find ludicrous.
As I covered at length in a previous post, the numbers of reported bias-motivated crimes appear to indicate, if anything, an environment that is relatively less hostile to queers.
Perhaps a minor point, but I was surprised that the plantiffs' lawyers didn't seem to latch on to it.

History in the making
The most exciting thing about it, for me, was the feeling of being at the moment of "history in the making". This trial is big. In the league of the Scopes monkey trial, Bowers v. Hardwick, Lawrence v. Texas. It may not be Roe v. Wade or Brown v. Board of Education, but it's up there, a massive culmination of social forces distilled into one bundle (that this Supreme Court will likely fumble). It will be a major reference in the evolution of queer history, no matter the result.
When similar-gender marriages were first issued in Massachusetts, I went up to Boston and sat on the steps of City Hall, chatting with a handsome stranger. I was moved far more than I thought I would be.
When similar-gender marriages were re-legalized in California, I went to City Hall, and snapped hundreds of photos, mostly of a pair of handsome strangers getting hitched. I was moved to tears repeatedly that day.
I feel fortunate, to have been in the right place at the right time, to bear witness these momentous events.

Cool Word Trick

Don't ask me how I know, because I don't know how, but copied work in a student's paper just jumps off the page. I usually detect it in under two seconds, and not because I'm looking for it, it just looks wrong immediately.

At first, when I was looking for the original source that a student copied from, I would guess what the most unique combination of words was, picking two or three multi-syllabic scientific-sounding words, and then do an internet search for them.
But I noticed a curious thing. In most cases, those unique words I was looking for often weren't particularly unique. But what did tend to be very unique was the "packaging" of banal words around them.

I've been shocked to find that, given about 5-6 words in sequence, it is almost always possible to find the one unique occurrence in the history of the English language that those particular words occurred in that particular order.

So now, I just type in the first 5-6 words of a sentence, no matter how banal and mundane the sentence structure sounds, and it almost always uniquely identifies the source. Neat trick, eh?
Try it at home. Grab a few words from anywhere nearby. Type them into your favorite web search. Watch the magic unfold.
See how many words you can get rid of, especially the words that sound most unique, and still have that one source pop up to the top of your list. (Hint: using quotes around the words to hold them in their original order makes it a lot easier.)

Somebody needs to write a paper about this phenomenon.

Obesity is NOT levelling off in the US

If anything, we're getting fatter faster.

Over the past few days, I've been seeing and listening to reports in credible news sources, the New York Times and National Public Radio, repeating a claim by CDC researchers that the obesity epidemic in the U.S. is leveling off.

I was suspicious. I had heard essentially the same story two years ago and found that claim to be less than credible, so I decided to investigate more closely.

So here's the data as they present it - the red line that they want you to focus on represents the proportion of the adult population who are overweight, but not obese - you can see that in recent years it has turned down a bit. But the blue and green lines, which represent obese (but not extremely obese), and extremely obese have been increasing, with no sign of slowing down whatsoever.

I used exactly the same data, from the same table in their report to generate this graph.
You can see a little more clearly here (at least I think), that the proportion of people who are overweight, obese, or extremely obese has been increasing, not leveling off.

Taking a closer look at the last few years, the proportion of the population that was some degree of overweight in 1999-2000 was 69.5%. It increased 1.6% to 71.1% in 2001-2002, 0.3% to 71.4% in 2003-2004, and 2.1% to 73.5% in 2005-2006. So the latest two years of data show the largest increase in overweight in the U.S. population so far documented. (the steepness of the little lines between the bars on the graph tell the same story)

So how could the esteemed news agencies I mentioned at the top of the blog gotten the story completely wrong? Not only that, but they were able to find a plethora of obesity experts to proffer explanations and predictions based on the erroneous conclusion that the obesity epidemic in the U.S. is leveling off.

There were two fundamental misunderstandings, as far as I can excavate: first, almost everyone involved seems to have mis-understood the term "statistical significance", and second, there seems to have been a widespread (excuse the pun) misunderstanding of looking at changes in the middle of the weight distribution.

As to mis-understanding the term "statistical significance", here is the sentence from the original CDC report:
The NHANES 2005-2006 data for persons age 20 years and over suggest an increase, between the late 1980s and today, in obesity in the United States, with the estimated age-adjusted prevalence moving upward from a previous level of 23 percent in NHANES III (1988-94) to approximately 34 percent. The change between 2003-2004 and 2005-2006, however, was not statistically significant. {emphasis added}

This little phrase "not statistically significant" was mis-interpreted to mean "no change", that is, a leveling off, between the data collected in 2003/2004 and that collected in 2005/2006.
Interestingly enough, that exact same mis-interpretation was made when comparing the 2001/2002 data to the 2003/2004 data in this CDC report. Apparently, the last time they got it right was in comparing the 1988-1994 data to the 1999-2002 data, when they didn't invoke the problematic concept of statistical significance at all, in this CDC report.

But obesity rates didn't level off in their data - as I showed above - in fact it was the largest increase seen yet in this data set.

The other mis-interpretation seems to have arisen from how this report discussed being overweight as something distinct from being obese, and being obese as something distinct from being "extremely" obese. That is, when the broke up the overweight population into three sub-groups, the proportion of people who are "just" overweight has decreased in the last few years (the red line in the top graph)
Here's the offending sentence from the original report cited above:
Although the prevalence of obesity has more than doubled since 1980, the prevalence of overweight has remained stable over the same time period.

Which only makes sense if you completely ignore the fact that lots more people are becoming more than "just" overweight (i.e. obese), and many fewer people have been at a "normal" weight (the tan bars in my re-graphing). That is, they have pulled the middle of a rapidly shifting distribution out and claimed that it isn't changing, but that is misleading because the size of the weight distribution on either side of it is changing dramatically.


I'm afraid I may sound like some punctuation-correcting nag, nipping at the heels of our most esteemed news outlets for some petty transgression all the while making it sound like the English language is on the verge of collapse into a ruin of uninterpretable gibberish.

But this isn't a punctuation or spelling error. It's getting the story completely backwards.
And I don't really blame the NYT or NPR for screwing it up. They were, after all, following the lead of our most esteemed public health agency. They were able to find plenty of esteemed experts willing to line up and go on at length about the implications of this erroneous interpretation of the findings.

I trace it back to the deeply ingrained mis-training that scientists get about what the phrase "statistical significance" means. When the British eugenicists who were followers of Darwin coined the phrase "statistical significance" in the late 1800's, they intended it to mean (at least as far as I can interpret their meaning over 100 years later) something like "significant in a statistical sense only, and quite possibly not in any other sense". So to them the phrase "not statistically significant" wouldn't have had any particular meaning at all, perhaps a study that was "not statistically significant" wasn't looking at a big difference. Perhaps there was some sort of bias hiding a real difference. Perhaps there just wasn't enough of a sample size to reveal the real difference in a statistically striking manner.
At any rate, over the years and in order to simplify the concept of "statistical significance", it has been taught as "an unlikely probability of a finding arising from chance alone", and the phrase "not statistically significance" has increasing become mis-interpreted as meaning "no difference".

And that, my friends, is why you'll find that I seldom, if ever, use the phrase "statistical significance" - because in the end it doesn't really mean anything - it's only about the statistical interpretation of a dataset, which is only one small window for understanding and interpreting numbers.

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...