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.

Allowing Gay Blood Would Increase Safety

The FDA still maintains a lifetime ban on gay and bisexual male blood donors. It is tempting to see this ban as overt homophobia, although I'd like to think that the decision-making body at the FDA has some other rationale in mind, at least in part.
They claim is that the ban increases the safety of the blood supply.

And so we have the ideal set-up, pitting "Safety" against "Homophobia". A battle between Rights, with Science judging the fight.

Is a lifetime ban on gay blood donors safer than allowing gay blood donors to give without restriction? Sure, but that's not an alternative that anyone is advocating for.

Some advocates for changing the policy deferring gay/bi male donors claim that all the blood is tested anyway, so we don't need the ban.
All the blood is tested for HIV, but there are cases where the blood tests negative even though it is infected, and one of those circumstances can be when a person has just been infected, and often the blood is highly infectious during that "window period". So, it is judicious to reject gay/bisexual donors who might have been infected recently. I think the best solution there would be to apply the same criteria used to defer anyone else who might have been infected recently, to say you can't donate for a year after sex with another man, even with a condom.
I've heard two logical arguments for why to exclude gay and bisexual men from donating blood for longer than a one year window - one is that there are extremely rare cases where an established HIV infection would still test negative, and the other is that the blood is tested only for those viruses that are pretty common and that they have good tests for - it isn't possible to test for everything, certainly not things we don't even know exist yet. I think both of these arguments from the side of "Safety" are compelling, but they don't operate in a vacuum.

Nobody is arguing for gay and bisexual men to be able to donate without restriction, so the question is what restriction will maximize "Safety" while reducing the role of "Homophobia" in making blood donor deferral policy? Often this is portrayed as though it is a balancing act, where every reduction in homophobia compromises safety.

But there are good reasons to think that reducing the role of homophobia in blood donor deferral policy would actually increase safety. Notwithstanding all the discussion about "window periods" and emerging infections and so on, there are three important phenomenon going on related to how people respond to a deferral policy that reeks of homophobia. How do people react when confronted with a policy that sounds, smells, and tastes like prejudice?

Frankly, some people are comforted by it. I'm sure there are lots of people who feel like the blood supply is safer because they believe gay and bisexual donors are excluded from it. They may make my stomach churn, but they don't make much difference in my argument.

Most gay and bisexual men are revolted by the policy, and as a result wouldn't touch blood donation with a ten foot needle. Again, not relevant to my argument.

Some gay and bisexual men, however, have learned that the easiest way to negotiate homophobia is to lay low. Keep your voice down and your wrists locked in position. Where this presents a problem is that given the choice between potentially outing oneself or deflecting the question about whether you've had 'sex with another man, even once', some men who should be deferred just slip past the question using the same techniques they've learned in dealing with other homophobic situations. Changing the policy so that it doesn't reflect homophobia (say by changing the deferral criteria to be the same as other HIV risk factors) would actually make the blood supply safer in regards to this group.

The second group I'm thinking of is predominantly heterosexual, but really could potentially include any donor. By including a deferral policy that sounds, smells, and tastes like rank homophobia, it "cheapens" the validity of other deferral policies, leading to people being less careful answering them. What I mean is that when the basis of one deferral policy is so obviously shaky, some potential donors will think that the other criteria (such as which drugs you've taken recently, or travel history) are also not strongly based in the need to keep the blood supply safe, and may be "encouraged" to give a less than honest answer, especially if they feel any social pressure to donate.

The third group I'm concerned about are the people who don't start giving blood at all. And the blood banks are worried about them too. Lots of people become regular donors for life after getting started in high school and college. But young people these days are especially sensitive to the acrid stench of homophobia. So by maintaining this policy that sounds, smells, and tastes like homophobia, the FDA is turning potential donors away in droves. Potential donors who are at very low risk for HIV and other blood-borne pathogens. Potential donors who otherwise would be likely to save dozens of lives over the coming years. There have even been organized efforts to keep blood drives off campuses until the policy changes.

The most dangerous pint of blood is the one that's not there when you need it.

Dear FDA, it's time to bring your deferral policy into the 1990's. Dump the homophobia and increase the safety of the blood supply.

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.

Research Directions

    Hey there blogfriends, I'm super excited because I'm going to have a first-author paper coming out in a few days - about the racial distribution of trees and pavement across the US - and exploring a few reasons that may explain it, like segregation (yes) and poverty (no). It looks like there's going to be some press on it, so keep an eye out.
    And my next first-author paper is getting really close to submission - so it's probably six months to a year from publication. That one's about the influence of living in more segregated cities on the probability of experiencing racial discrimination. That one's pretty interesting - lots of studies within one particular city or another have found that experiences of racial discrimination tend to be less common among Blacks who live in predominantly Black neighborhoods, and more common among Blacks who live in predominantly White neighborhoods. As far as I can tell, ours is the first to look at the degree to which the overall segregated character of the city (and her suburbs) affects reporting of racial discrimination experiences. We're seeing pretty dramatic results in that more segregation results in more experiences of racial discrimination, for Blacks, Hispanics, Whites and Asians.

    But what I'm stymied with at the moment is where to go after my most recent first-author paper - showing that gay men are more likely to be in excellent health than straight men... I'd love to get another paper on TBLG health out there, relatively soon, but it's challenging, because I have to do the work on my own dime and my own time. So here's some ideas, and I'd love to hear your thoughts on what would be most helpful (helpful in any sense - informing policy, improving science, satisfying curiosity - whatever greases your gears).

ONE: Improving Identification of Same-Sex Couples in Large Probability Datasets
    I know. Boring title. But here's why this has been floating my boat lately. When I was working on gay men in excellent health, I looked at the biggest dataset I could lay my hands on, the BRFSS. There were a fair number of same-sex married couples, even before same-sex marriage was legal anywhere in the US, which struck me as odd. Another thing that was odd is that their demographics (how old they were, how many kids they have, whether they served in the military, etc.) were a lot like heterosexually married people. I figured that what was most likely happening was that a small number of heterosexually-married people were accidentally mis-coded - and ended up being counted as same-sex couples. So, I threw them out of the analysis.
    BRFSS is especially vulnerable to this kind of error, but the problem is ubiquitous in any of the large probability samples that get used for research on same-sex couples - and rarely acknowledged.
    So what this project would be about is systematically going through the major datasets and trying to estimate how many of the same-sex couples identified are really same-sex couples, and how many are mis-coded heterosexually-coupled people.
    The main reason that it's important to do this project is that there are a lot of publications out there claiming that same-sex married couples are "just like" heterosexually-married couples. That may be a comforting message, and there's probably something to it, but a likely explanation that is almost never discussed is that a lot of those same-sex married couples are in fact heterosexuals. If we want an accurate picture, we need actual same-sex couples.

TWO: BLG health in relation to voting on marriage restrictions
    OK, so my thesis (never was able to get it published) was about the occurrence of suicide in relation to heteronormativity - the more heteronormative an area is, the higher the suicide rate there - especially for young men. I measured heteronormativity in three ways: the legal status of employment discrimination; how people voted on restricting marriage; how many same-sex couples the Census counted in an area.
     Given that nobody seems to care about employment discrimination any more these days, I figure that I should focus on the voting thing. The way I see it, how people in an area vote on restricting marriage to "one man and one woman" is a pretty good heteronormativity thermometer. There are some complications in that the wording is different from State to State, and the change in public attitudes is so rapid that a 60% endorsement rate today probably corresponds to an 80% endorsement rate in 2004. But assuming I can figure out a way to handle that, the other part is finding a dataset that has good BLG health measures in it.
    For my thesis, I used the overall suicide rate, and I didn't particularly care whether the people who died of self-inflicted injuries were "gay" or not. In fact, I suspect that the highest suicide risk associated with being gay or bisexual is before one declares openly to anyone else, and even before having sex, so it would be kind of silly to try to figure out who's who after they're dead. But I think that's one of the reasons I had trouble getting anyone interested in publishing it - it seems like people want to know how BLG people are affected by homophobia. Well, I'm interested in how heterosexuals are affected also. I very much doubt that it's a zero-sum game where heterosexuals gain some advantage while BLG people pay the price. I suspect it's much more likely that heterosexuals, too, are harmed by heteronormativity. And since there are a lot more of them, it should be even easier to pin that down. But I digress.
    So, I need a dataset that A) is a probability (random) sample of the US, B) has a large sample size (ideally in the 10's of millions, but I'll have to settle for less), C) identifies who is gay, lesbian, bisexual, and heterosexual, D) has a high degree of spatial resolution so I can figure out what the local homophobia "temperature" is, and E) has decent temporal resolution so I can figure out when people were sampled relative to important dates, and F) has decent measures of health in it.
    There are some datasets that come close to fitting the bill, but it's a challenge.

THREE: Transgender health from large population datasets
    There's only one publication out there about transgender health based on a probability sample - from the Massachusetts BRFSS. But there's the potential to do so much more. There are seven States that have asked about transgender identity on BRFSS. I'd love to collect the data from all seven, compare the basic demographics of transgender-identified people across the different question wordings & hypothesize about which questions work best. And then get into the health outcomes, much like the Massachusetts study did, but with much more data. I suspect that all of the question wordings are going to have a significant problem much like the same-sex married people identified in large population datasets - that is, even a very small number of errors in the coding of cisgender people is going to be a major headache. There's really only one way to handle that that I can think of - call them back to verify it - but I really can't see that happening anytime soon.

FOUR: The Real Blood Donors of Gaytown, USA
    There are just so many things wrong with banning gay blood donors. It made sense in 1985 (and frankly, it would have made even more sense earlier). But it doesn't make sense now, and everyone knows it. Including lots of gay men who donate blood anyway, and increasing numbers of young straight people who won't donate because they don't feel right about the discrimination. I'd love to be part of qualitative research on gay men who give blood. Why do they do it? How does it make them feel? What 'rules' about donating have they made for themselves to decide when they should and should not donate?
    There's a lot of interesting policy angles to wrangle through on this issue, but I think getting to know these guys would be really interesting - and informative in coming up with better deferral guidelines.

FIVE: Wage Gap and Death
    Strangely enough, there are only a handful of studies out there measuring how sexism affects health at a population level. Most of them use some sort of complicated mash of different ideas into an "index", and I hate indices - you never know what's really going on in there. So I took a simpler approach, just looking at the wage gap between men and women. It varies a lot - there are some parts of the country where women make almost as much as men, and some parts where men make about twice as much as women. What I expected to see was that women's mortality would be higher in areas where men make more. But I saw something completely different: where men make more relative to women, they live longer, but women's mortality is unrelated to the wage gap. I basically put this project on ice because I can't figure out a narrative that makes sense. But I could go back to it if y'all have fresh ideas.

So let me know, what do you think I should work on? And if you're feeling especially generous, for only $62,000, you get to decide.

Blood

Give Life. Give Blood.
Blood brothers.
"One drop" rule.
Blood on your hands.
What does blood mean to you?

Blood fascinates me. It tastes great, it feels great. It is vibrant and alive like nothing else.

The sweet gush of warm, salty liquer that erupted in my nose after a punk on Thayer Street clocked me 'cuz I said he'd look good in a dress, too. The blood is what made it come alive. I was afraid for my life, and not without reason. The blood, though, that's what told me "this is real". The pain told me too. But the blood, the blood made all of my senses jump into hyperdrive. At the same time, the blood was a secret joy in the midst of the pain.

I don't have a fetish around blood (though hats off if you do). I don't seek it out. But blood is a lovely thing.

And yet.
When I bleed, I'm very conscious to make sure that my blood doesn't come into anyone else's life. I hide the fact that I'm bleeding, and I clean up more carefully than I would, say, sweat or tears. Or for that matter, snot. Or cum.

And blood makes me queasy, too.
I don't think I could watch surgery on TV. Getting blood drawn makes me wince.

Blood has so many fascinating associations. It means so many different things. Often contradictory.

I wish I could talk about giving blood and what it means. But I can't. Not yet.

What does blood mean to you?

Research Worth Reading (3)

There's a myth out there that gay men are self-obsessed and narcissistic, and I for one don't buy it.
David Nimmons, in Chapter 3 of his book Soul Beneath the Skin claims that on the contrary, gay men are actually more likely to get involved in volunteerism and altruistic behaviors, in part basing that on the enormous outpouring of volunteer time and energy devoted to AIDS service organizations.

Well, this is the first quantitative random sample analysis that really tries to get to the issue of whether gay men (and lesbians) are more or less altruistic than straight people. And that goal is what makes it 'research worth reading', in my opinion.
This is one of the few analyses that examines assets, rather than risks; one of a very small number of quantitative analyses to do so. So regardless of the results, regardless of the methodologic challenges, this is an important read in terms of thinking about the health of sexual minority populations.

Self-reported altruistic and reciprocal behavior among homosexually and heterosexually experienced adults: implications for HIV/AIDS service organizations.

Susan D. Cochran, Vickie Mays, Heather Corliss, Tom W. Smith, Joseph Turner

AIDS Care 21(6):675-682. June, 2009

The authors used data already collected as part of the General Social Survey (GSS), a random-dialed telephone survey of the US population conducted annully since the 1960's, a staple dataset for the social sciences.
They looked at four potential measures of altruism across groups of people defined by whether they reported ever having had sex with someone of the same sex, or whether they reported only mixed-sex sexual relationships. The sample size of the GSS is fairly large (they combined 2 years to get 2,031 people), but the number of men and women reporting same sex partners in their lifetimes was pretty small (68 men and 51 women), so they elected not to divide that group farther, but lumped together men who were homosexually active and bisexually active together, and the same for the women.

The GSS asked a 7-item scale intended to measure empathic concern (other-oriented feelings), a 4-item altruistic feelings scale (similar idea, as far as I can tell), a set of 11 altruistic behaviors (things that one does for others that have no self-serving interest, like giving directions to a stranger, even at some risk to one's self, such as donating blood), and 4 reciprocal behaviors (things that one does for another, but do have self-serving aspects as well, like helping someone you know find a job, or lending a friend a considerable amount of money).

They found that gay/bi men (at least in terms of reported sexual behavior) were very similar on all of these measures, in terms of the average. Of course, the average is just the average, it doesn't really say much about the distribution of individuals in the population, meaning there might be a bunch of gay/bi men who are much more altruistic (for example: helped 7 people find jobs, not just one) but that wouldn't be reflected in the average.

The lesbian/bi women were also very similar across all four measures of empathy and altruism.

So, the results are pretty vanilla. Looks like we're about as caring and other-centered as everyone else.

Blood donations
One interesting side note is that they found lots of people in GSS reporting having given blood recently, over 20% of exclusively hetero men, and almost as many of the gay/bi men. That's similar to what I saw in the same dataset and reported on here.
I suspect that there's something wrong with that variable, not because it shows lots of men with same sex sexual behavior giving blood, but because it shows many many more people of all stripes giving blood than actually do.
I don't know what the problem in GSS is about blood donation. Maybe a lot of people are interpreting it to mean gave blood ever in their lives, rather than just in the last year. Maybe a lot of people are interpreting having given a tube of blood for medical tests as having given blood. I don't know.
But at any rate, there are more credible results on blood donation in the National Health and Nutrition Examination Survey, which I reported on here.

Study limitations
The General Social Survey (GSS) is an amazing dataset. They ask tons of questions, and repeat a lot of them year after year. But, it is also very general, and not necessarily designed for whatever analysis you or I might have in mind, so when re-purposing it, it is important to hold in mind that the results may not be what they seem for a variety of reasons.
As is typical for epidemiologists, I'll break them down into three large categories: errors in assessing sexual orientation; errors in assessing altruism; and other factors that may be associated with both sexual orientation and altruism.

errors in assessing sexual orientation
The GSS is a telephone survey, and it is a really long survey. And not everyone pays close attention the whole time they are on the phone. As a result, some people inadvertently give answers that don't actually represent their reality, and in very rare cases, the interviewer records something other than what the respondent said.
All that would be well and good if a little bit of error here and there gets swapped from one group to another, but it gets problematic when one group is much smaller than the other (like sexual minorities). In this sample, 5% of the women and 6.6% of the men reported at least one sexual partner of the same sex in their lifetimes (since age 18). It's possible that maybe 4% of the women and 5% of the men really did have same sex partners, and the other 1-1.5% represent people who were inattentive or miscoded for some reason (this is purely hypothetical, there's no way to know what the error rate really is). So, if that were the case, then gay/bi men and lesbian/bi women would look more like straight people than they should, because a bunch of the people we think are gay/bi/lesbian really aren't (Scout's Law of Fake Queers).
The GSS actually has more opportunity than most datasets to check on this kind of error, because at different points they ask about sexual partners ever in one's lifetime, in the last five years, and in the last year. And there's always people who say they have had no sex in the last five years, but they have in the last year. No way to tell which of those is correct, but they can't both be true, so you can get a sense of the error rate that way. I haven't done that analysis myself, but it could be done.
Another way to check is to see whether the queers identified in this study look like queers identified in other studies. Most demographic studies have found that people who describe themselves as LBG, or who report same sex partners, tend to be slightly younger, more highly educated, and especially less likely to be married. In this study, they were somewhat younger (much younger for the women), but not more highly educated. The LGB people identified in this study were less likely to report being married, but still about 30% reported being married, which is pretty high.
For those reasons, I'm a bit skeptical that the GSS sample has really accurately described the LGB population, I suspect that there's a fair amount of 'slop' from the heteros mixed in with us.

errors in assessing altruism
Another potential source of error is if altruism is not measured accurately. This is an area I'm much less familiar with, in part because I just don't trust scales. The known inaccuracy of the blood donation question gives me some cause to interpret this study cautiously, but that could be a problem mainly with that one question for whatever reason, and not reflect systemically on the other measures in the study.

other factors associated with sexual orientation and altruism
I don't know enough about how altruism is distributed in the population. They separated the population by sex, and that's probably the biggie. There weren't enough people to do stratified analyses across any other variable (like age, educational attainment), but they did do a mathematically smoothed model to try to partially adjust for these factors simultaneously, and found no big difference from the overall results.

Full disclosure: Susan Cochran, the lead author on this study, was also the external reader for my dissertation. She and I have never discussed this paper, though. I don't think seeing her name on the paper made me especially more likely to choose it, I was hooked by the word 'altruism' before I saw that she was associated with it. I do think that knowing that she and Vickie write good research is why I asked her to be my external reader.

more on gay blood donors

A few months back, I posted about the existence of gay blood donors, at least in the General Social Survey.
Now, I have more information from a more authoritative source, with fewer obvious data problems.

The National Health And Nutrition Survey (NHANES) has been periodically conducted, recently on a two year basis.
By combining several surveys together (1988-1994, 1999-2000, 2001-2002, 2003-2004 & 2005-2006), I was able to look at a reasonable number of sexual minority males' blood donation histories in comparison to heterosexual males.

Like GSS, you can break down sexual orientation in different ways in these datasets, each way yields slightly different sample sizes.

sexual orientation identity
Among 75 men who say they are gay, 2 (3%) said that they donated blood in the previous year, and 2 of 56 men who said they were bisexual did (4%), while 214 of 3,873 heterosexually-identifying men gave blood in the previous year (6%).

men who have had sex with men
Among 65 men who have only had sex with men, 2 (3%) said they donated blood in the previous year. 5 of 264 men who had sex with men and women (2%) said they gave blood. 667 of 9,560 men (7%) who have never had sex with a man gave blood.

men who have had sex with a man in the last year
It's one thing for a man who had sex with another man a long time ago to give blood, it's another thing to consider recent sexual activity. Of 117 men who say they had had sex with a man in the last year, 2 said they gave blood (2%), while 209 of 3,626 men who said they had not had sex with a man in the last year did (6%).


Banning gay men isn't working
These figures suggest that the US ban on blood donations from any man who has had sex with a man since 1978 is not working, and should therefore be re-worked in order to create a more sensible donation policy. One that doesn't feel discriminatory. One that doesn't encourage lying. One that isn't so ridiculous that it brings other more reasonable exclusions into doubt. One that doesn't conflate homosexuality with risk.

The numbers from these surveys are more credible than the ones I got from the GSS, which showed an implausibly high rate of blood donations regardless of sexual orientation.
NHANES is based on an in-person survey (the NHANES people literally drive up to your house with an 18-wheeler containing a mobile medical examination center), rather than the random digit dialing of the GSS.

My interest in pulling these data together is merely to document the existence of gay/bi blood donors, and that it is not an especially rare phenomenon, not to say exactly how many gay/bi men donate blood (or straight men for that matter). For that, we'd need even larger samples...

gay blood donors exist

Gay blood ban
It's my belief that the ban on gay blood donations should be overturned.
The ban is patently discriminatory, based on stereotypes, but justified under the mantle of medical science. It's just one example of how rank prejudice is remade as scientific, sanitized, made to appear ethical.
Technically, the ban is on a man who has "had sex with another man, even once, since 1978". There is no ban on women who have had sex with a man, although there are specific categories of male sexual partners that trigger excluding a potential donor from giving, if she has had sex with them in the last 12 months.

Does the ban "work"?
Does the ban in fact keep gay men from giving blood? The simple answer: no.
The more complicated answer: in the General Social Survey, respondents were asked (in 2002 and 2004) whether they had donated blood in the past year, and also several questions about the sex of their sexual partners. Here are the results, using three different definitions of sexual partners...

Among 36 men who reported at least one male sexual partner in the last year, 6 (17%) said they gave blood in the last year. This is somewhat lower than the 22% of 826 men with exclusively female partner(s) who said they gave blood.

Among 43 men who reported at least one male sexual partner in the last five years, 6 (14%) said they gave blood in the last year, while 21% of 884 men who had sex only with female partner(s) said they gave blood.

Among 58 men who reported sex with at least one male sexual partner since their 18th birthday, 4 (7%) reported giving blood in the last year, while 21% of the 942 men who reported no male sexual partners since turning 18 reported giving blood.

There are good reasons for being a bit skeptical about these data, but more on that later...

Adverse consequences
If the ban on gay blood donors doesn't "work", then is it worth maintaining? What are the consequences of maintaining a patently discriminatory policy?

1) An unjust ban on gay blood donors encourages lying. Anyone (straight or gay) who sees the exclusion of gay men as discriminatory will begin to question the validity of the other screening questions, perhaps taking liberties with answering screening questions that have a valid basis for protecting the blood supply.

2) It justifies discrimination in other areas. The fact that most people believe the screening questions on the blood donation form have some scientific or medical basis makes it appear as though this form of discrimination is beyond questioning. Justification of discrimination in one setting encourages people to justify for discrimination in other areas (even on a different basis).

3) The ban makes it unclear how a gay man should approach donating blood. By having an outlandishly discriminatory donor exclusion policy, blood banks are in effect encouraging each gay blood donor to make up, in his own opinion, when it is safe enough for him to give blood. Whereas a policy in line with the other donor exclusion policies would set a more realistic set of limits that gay blood donors would be more likely to honor.
A consequence of this is that the ban on gay blood donors may in fact make the blood supply less safe.

4) The ban reduces the potential pool of donors, in more ways than is immediately apparent.
4a) It is well documented that gay men are more likely to give altruistically in a variety of ways, thus the ban cuts out a segment of the population that would otherwise be eager to give. Although gay men represent a small proportion of all potential donors, and even though many gay men would be excluded for medically justified reasons (such as having unprotected anal sex in the last six months), the exclusion of a motivated group of potential donors may not be a great idea.
4b) The blatantly discriminatory nature of the ban on gay blood donors has already started to lead to a wider backlash. Some straight men, and women of all sexual orientations, get a bitter taste in their mouth from the obvious discrimination of banning men who've had sex with even one man, even once, since 1978. This bitter taste shrinks the pool of potential donors, probably in much larger numbers than the gay men excluded from giving currently.
4c) College campuses, settings where many people initiate a lifetime habit of giving blood, are also settings where action is likely to be taken against discriminatory policies, and in fact blood drives have been canceled on several college campuses already, with the promise for such action to expand in the future. Can the blood supply afford to lose all these potential future donors?

who are the gay blood donors?
I don't know. I'd love to talk to a few to get a better sense of what motivates a gay man to give blood. How does giving blood relate to a man's sense of well-being? How does being refused the opportunity to do so without lying relate to a man's health? Are gay blood donors much more scrupulous about the other screening questions to compensate for lying on one question? Or are they more likely to overlook the other questions?

data limitations
the number of men who report male sexual partners is already pretty small in the GSS (36-58, depending on which question), and the number of these men who report giving blood is even smaller, 4-6. So, it is possible (if unlikely) that these are all data errors. That is, it is at least theoretically possible that 6 respondents weren't paying close attention when asked either about giving blood, their sexual history, or both questions, and gave answers at variance with their actual experience. Or, the telephone interviewer may have slipped when entering the number corresponding to the person's answer.
In addition, there are good reasons to think that the proportion of people saying that they gave blood is considerably higher than the number who actually did give blood. For one thing, a small handful said that they gave blood monthly, even weekly. Blood centers generally ask donors to wait at least two months between donations, so these answers are highly suspect. The other thing is that over 20% of the GSS respondents reported donating blood, but probably no more than 10% of the population actually does donate blood.
However, my point was merely to document that gay blood donors exist, not to give a precise estimate of how many gay men are blood donors. Better data would be needed to make that estimate.