I'm not. And I doubt more than a handful of people in the US are. And I'm not sure whether that's a good thing or not. On the one hand, I don't want to be alarmist. On the other, If we as a nation value our nuclear weapons so highly that we won't get rid of them, can we reasonably expect that nobody will ever try to use them against us?
When the debate about the Seabrook nuclear power plant was happening, I was of an impressionable age. I lived in Amherst, New Hampshire, and Groton, Massachusetts, just across the border from one another. The gym at my school was labelled as a "fallout shelter" and looked like a bunker. I read a few books about the Manhattan Project and its terrible debut in Hiroshima. I was fascinated by the science and the scientists, and also by the majestic horror that they unleashed. I had dreams about running to that shelter and what might happen as we waited days and weeks for help to arrive.
Unlike people a few years older than me, I had never undergone a 'duck and cover' drill. By that point, they were mocked as silly - inducing unnecessary nightmares in our youth - not to mention useless in the face of a bomb capable of incinerating an entire city. I took some comfort in the fact that Fort Devens was in the next town over. In the event of an all-out exchange, I prayed we wouldn't have a chance of survival.
And yet, we as a nation still maintain an enormous arsenal of nuclear weapons, and devote considerable resources to them. Why? I'll leave that to others for the moment. A great discussion can be found on KQED's Forum here.
Although it has gone out of fashion to speculate about nuclear weapons use, I would argue that it is foolish to be as ill-prepared for it as we are. Unlike the nightmares of my youth, the prospect of an all-out exchange between the US and the Soviet Union has passed. The prospect of an all-out exchange between the US and any current nation is exceedingly remote.But with all the crazy people in this world, the more likely scenario is that someone, somewhere, will be able to put late-1930's technology together with evil intent to deliver a rudimentary nuclear weapon to our doorstep.
A Dirty Little Secret
Nuclear weapons are more survivable than we imagine. The 'duck and cover' drills of the 1950's and 1960's may have indeed been silly. But I suspect that the real reason they went out of fashion isn't because they were futile, or terrifying, but because continuing them made the idea of using nuclear weapons seem plausible. By preparing for nuclear war, we were countenancing the possibility that it might happen, and nobody wanted that. In that light, I want to be clear that claiming nuclear weapons are more survivable than we imagine should in no way make them easier to use.
In college, I read about an epidemiologic follow-up of survivors of the atomic bombings of Hiroshima and Nagasaki, to trace the longer term effects of nuclear weapons exposure (and from a more cynical perspective, to help set regulatory guidelines as to acceptable levels of x-ray exposures in the US). When I taught my epi classes at SFSU, I incorporated this article into teaching about cohort study design.
One thing that was shocking about this study was how many survivors there were. I don't in any way want to minimize the number of deaths, but it was shocking to me to learn that some people who were within 1 kilometer of the blast center survived, and relatively few people 10 kilometers away from the centers of the blasts were killed. Not only that, but the study treated these people beyond 10 kilometers as the 'unexposed cohort' - that the radiation dose one received from the initial blast at a distance of 10 kilometers was not much higher than background. Or in other words, if a Hiroshima-sized bomb went off over the Transamerica building in downtown San Francisco, we in our classroom at SFSU would be considered 'unexposed' in that study design.
Back during the debate about opening the Seabrook plant, there was a lot of scare-mongering using mushroom clouds to illustrate the risk of a nuclear meltdown. But a nuclear power plant can't explode, so I think that hyperbolic representation may have really undercut the cause. What nuclear weapons do share with nuclear power plants in terms of risk is fallout. That is, a nuclear power plant is not going to blow up and cause the explosive damage of a bomb, but both a bomb and a plant have the potential to release a lot of fine dust particles carrying radioactive elements over a relatively wide area. That's the scary part.
The hopeful part is that with a bit of preparation, you can offer yourself a great deal of protection from the fallout. First, close your windows and seal them up with plastic. I know, it sounds silly, but the biggest danger fallout presents is if you breathe it in or swallow it. Your skin is pretty good at dealing with two types of radiation (alpha and beta), but your lungs and stomach are very susceptible. That's because we are constantly bombarded with radiation from the sun, so we've evolved pretty good external defenses. The third type of radiation, gamma radiation, gets less harmful the farther you are away from it. As an analogy, if you hold a light bulb up to your face, it is blinding. In the ceiling, it provides a nice glow, but the light from that bulb is practically useless if you are out in the driveway hunting for a dropped wallet.
So, making your home as air tight as possible makes it harder to breathe in or swallow fallout particles, and by keeping them outside the home, it keeps you farther from the gamma radiation.
Similarly, you want to stay in the middle of the house, away from ground level (where the fallout settles), but also not too near the roof (because it falls there too). And, if you can surround yourself with stuff, even better, because stuff absorbs radiation. Water is a great radiation-absorber, but books, even blankets, will help a little bit. You got a water bed? Awesome place to crash.
You may think that hunkering down in the center of your plastic-wrapped house, surrounded by buckets of water may not be the ideal way to spend the rest of your life, and you'd be right. But there is a saving grace - called "half-life". Radioactive atoms can release radiation at any moment, but on average, half of them will "go off" within a set amount of time. And because a lot of radioactive fallout elements have a short half-life, it is estimated that the danger of fall-out is reduced about 90% within 3 days, and well over 99% within 3 weeks. So, even after only three days of hunkering down, the risks from fallout are considerably lower.
The other thing you'll want to do is pray for rain. Rain is really effective at pulling any remaining fall-out out of the air (so it will be harder to breathe it in), and also does a decent job at washing the radioactive dust off your roof, off the sidewalk, and either into the sewer, or down into the ground a bit. And fallout in the ground is a lot less dangerous than fallout on the ground (imagine taking an x-ray with even a quarter-inch of soil between you and the camera). At that point, the major concern would be from radioactive elements (like iodine-131) that get absorbed from the ground into crops that you (or your cows) eat.
Hope that helps you sleep better tonight....
Friday, January 25, 2013
Monday, November 12, 2012
Minnesota Precinct-Level Marriage Vote Map
New to the blog? Skip to the Highlight Reel.
On November 6, the voters of Minnesota rejected a proposed amendment to their state Constitution:
"Only a union of one man and one woman shall be valid or recognized as a marriage in Minnesota." It got 48% support, but that support is not at all evenly spread across the state.
Red is in favor of the amendment, green opposed.
The overall trend is that the lowest levels of support were in Minneapolis/Saint Paul, with growing support further from the capitol. It also looks like support for the amendment tended to be a bit lower near the lakes than in land-locked rural areas.
And yeah, it was a lot of work to put this together.
On November 6, the voters of Minnesota rejected a proposed amendment to their state Constitution:
"Only a union of one man and one woman shall be valid or recognized as a marriage in Minnesota." It got 48% support, but that support is not at all evenly spread across the state.
Red is in favor of the amendment, green opposed.
The overall trend is that the lowest levels of support were in Minneapolis/Saint Paul, with growing support further from the capitol. It also looks like support for the amendment tended to be a bit lower near the lakes than in land-locked rural areas.
And yeah, it was a lot of work to put this together.
Sunday, November 4, 2012
41.423560%
So this morning while I was walking the dogs, I was thinking about exposure categorization. When your exposure is continuous (i.e. could be a little higher, a little lower, a lot higher, or anywhere in-between), and you prefer categorical analysis (as I do), then it is always arbitrary where you cut the exposure into different levels. You may have a good rationale for choosing a specific method, but it is always a decision you need to make, explicitly.
At any rate, one of the things I like to do is break my exposure up into three or four categories, to get a sense of the consistency of whether there is a dose-response happening (i.e. more exposure->more disease). And when there's no good reason to pick any particular cut-offs, one of the standard things we do is to cut the exposure into thirds - that is, one third of the sample becomes the lowest exposure (reference group), one third becomes the middle exposure group, and one third becomes the higher exposed group. And then you compare the middle group to the reference group and the higher exposure group to the reference group.
But as I was walking, it occurred to me that that's not the most efficient possible way to break things into three pieces, statistically speaking. And that's because the reference group is in two comparisions, and the middle and higher exposure groups are only in one comparison. So, if one could have a slightly larger reference group, then you would get more statistical power, even if there were fewer people in the other two groups.
Off the cuff, I guessed that if you chose 40% to be the reference group, and 30% each for the middle and higher exposure groups, that would probably be a bit more efficient.
So, when I got home, I tried out some ideas. The main thing I was looking for was to get the confidence limits around the two comparisons as small as possible. In order to test that out in a particular (purely theoretical) example, I assumed that I was trying to estimate the difference between proportions, so the standard errors would be simple to calculate, and then I made another assumption, that the "event rate" was identical in all three groups (that is, there is no dose-response whatsoever). That's not really the assumption I want to make, but it's a simple starting point to work from.
Then, I calculated the standard errors using a third-a third-a third cut-points, and then again using 40% for the reference group, and 30% for the other two, and voila, the 40%:30%:30% splits did have smaller standard errors (red line below) than the 33%:33%:33% ones did (blue line below). It doesn't look much different, but when you're trying to squeeze the maximum statistical power out of the data you've got, this would be a cheap & simple way to do something.
And then I got to thinking, if 40:30:30 is better than 33:33:33, then what is the optimum size for the referent group, in this example? After a bit of futzing around, I figured out that it is about 41.423560%, leaving 29.289322% for each of the comparison groups. That's the green line below - imperceptably more efficient than 40:30:30.
At any rate, one of the things I like to do is break my exposure up into three or four categories, to get a sense of the consistency of whether there is a dose-response happening (i.e. more exposure->more disease). And when there's no good reason to pick any particular cut-offs, one of the standard things we do is to cut the exposure into thirds - that is, one third of the sample becomes the lowest exposure (reference group), one third becomes the middle exposure group, and one third becomes the higher exposed group. And then you compare the middle group to the reference group and the higher exposure group to the reference group.
But as I was walking, it occurred to me that that's not the most efficient possible way to break things into three pieces, statistically speaking. And that's because the reference group is in two comparisions, and the middle and higher exposure groups are only in one comparison. So, if one could have a slightly larger reference group, then you would get more statistical power, even if there were fewer people in the other two groups.
Off the cuff, I guessed that if you chose 40% to be the reference group, and 30% each for the middle and higher exposure groups, that would probably be a bit more efficient.
So, when I got home, I tried out some ideas. The main thing I was looking for was to get the confidence limits around the two comparisons as small as possible. In order to test that out in a particular (purely theoretical) example, I assumed that I was trying to estimate the difference between proportions, so the standard errors would be simple to calculate, and then I made another assumption, that the "event rate" was identical in all three groups (that is, there is no dose-response whatsoever). That's not really the assumption I want to make, but it's a simple starting point to work from.
Then, I calculated the standard errors using a third-a third-a third cut-points, and then again using 40% for the reference group, and 30% for the other two, and voila, the 40%:30%:30% splits did have smaller standard errors (red line below) than the 33%:33%:33% ones did (blue line below). It doesn't look much different, but when you're trying to squeeze the maximum statistical power out of the data you've got, this would be a cheap & simple way to do something.
For a four-group categorization, the optimal size for the reference group is 36.60254%, with 21.2324867% in the three comparison groups.
For a five group categorization, the optimal reference group size is exactly 1/3, with 1/6 in each of the other four groups, and for an eight category breakdown (I can't say I recommend splitting so finely), the optimal reference group would be 27.429189%, with 10.36725871% in each of the other 7 groups.
I probably won't pursue this any further because I see stats as the means to the end, and not super interesting in themselves.
If there is a dose-response, these calculations get a bit more complex, and depend on how much of a dose response, the distribution of the exposure, and so on. My guess is that in that case, the optimal size for the reference category would be a bit larger, and there might even be a bit of efficiency gain by making the middle exposure group a tiny bit larger than the higher exposure group.
But enough with the navel-gazing. Time to get back to my paper on how segregation affects how likely one is to experience racially discriminatory events...
Thursday, November 1, 2012
Torture and Truth: Metaphors of Data Analysis
Francis Bacon is credited, rightly or wrongly, with a major turning point in the scientific method - an insistence on empirical, observable evidence, as opposed to reasoning from first principles. He also served in very prominent positions in English politics, and my down-the-hall neighbor, Carolyn Merchant, has done some terrific work tying together his politics and his science, through a lens of how the man thought of women, including the ultimate in feminine mystique - Nature herself. I'm at great risk of mischaracterizing her work, but I'll do my best.
In his writings (in Latin), Bacon frequently used the verb 'vexare' to describe the methods by which Truth could be extracted from Nature. And Carolyn's work shows that how one translates 'vexare' has quite profound implications.
Most modern translations describe 'vexare' as meaning "to vex", which sounds direct, but according to Carolyn, his meaning was probably closer to another interpretation: "to torture", and that several of his early translators in fact rendered 'vexare' as "torture". At the risk of ridiculous oversimplification, did Francis Bacon see the way to provoke the Truth from Nature by vexing her, or by torturing her? Did he imagine Nature giving up her secrets because he, the scientist, had devised a method of constraining her wild unpredictability into a stress position that required her to give up the answer?Because in Bacon's day, and in Bacon's own mind, torture was seen as a valid method used to get the Truth. We now know that torture does nothing of the kind - it causes the tortured to say whatever they think the torturer wants to hear.
Well, the reason I bring all this up is that at the APHA conference, I saw some results that looked as though Data herself had been tortured more than interrogated by the analytic methods applied to her. In contrast, I also saw lots of evidence of researchers who had sat down with Data, asked her some questions, and got some answers they didn't expect. Rather than ignoring her, or turning the screws to get her to change her tune, they listened carefully to what Data had to say. The mark of a suberb scientist, I think, is knowing the line between interrogation and torture - and figuring out when the answer to a research question should be believed, when it should be ignored, and when one needs to change one's own understanding of the world, especially when the answers contradict what we had hoped to hear.
There is an opposing problem as well - very often we get an answer that is so in-line with our pre-conceptions that we run off to publish without taking the time to check and re-check whether that answer is valid. In other words, our interrogation techniques need not be harsh, but we do need due diligence.
I wish I could say that I never torture Data, that when she speaks, I listen. But the reality is that I often have a very strong pre-conception of what Data should say, and when I don't get the answer I want to hear, my first reaction is to wonder - did I hear her correctly? (i.e. was there mis-coding, or a programming error that transposed the unexpected answer for her true response). My second reaction is that maybe she mis-understood what I meant to ask, so I ask the question again using different phrasing (use a linear rather than a logistic model; re-classify the exposure cut-points or the outcome characterization; include a different set of control variables, etc.). These methods are usually not torture - they are reasonable reactions to past experiences where I have made programming errors, where classification matters a great deal, where omission of a key control variable does result in mis-leading results. But crossing the line to torture at this second stage is far too easy to justify, especially when I have a lot invested (in reputation, world-view, justifying how grant money was spent, etc.) in getting the answers I want to hear. It is easy at this stage to try out a variety of techniques to transform the answer I don't want to hear into one that I do.
My third reaction to pesky Data is to say she's wak. Maybe Data got high before being dragged into the interrogation room and is just giving weird answers to satisfy her own impenetrable sense of humor. Or in other words, are there sampling errors, and/or systematic biases in the data that generate unreliable results?
It is only after many attempts, in many ways, to discount results I don't want to hear, that I take seriously the idea that I may have the wrong idea, that there is a completely different narrative that Data wants to tell. I will have wondered from the start what might explain contrary findings, but I won't replace my pre-conceptions until I'm utterly convinced that I've gotten it wrong. And I think that's the right approach - usually I do ask the wrong question, or if I ask the right question, I might well ask a dataset that is not well-equipped to give the right answer. But every once in a while, I listen carefully, and I hear a story that's much more interesting than the one I had in my head from the beginning. And those stories I don't want to hear - turns out they have happy endings too.
OK, I'll admit it, that last line is pure schmaltz. You got a better way to wrap this ramble up with a tidy bow?
Wednesday, October 31, 2012
The Highlight Reel...
Wow! Made a ton of great connections at the APHA meeting and hyped up my blog a bit, so for new readers, I've compiled a list of my favorite, and my readers' favorite postings over the last few years.
Research Worth Reading: A Phenomenological Investigation of the Experience of Taking Part in 'Extreme Sports'. by Carla Willig, City University, London. Journal of Health Psychology 13(5):690-702
Sunday, October 28, 2012
Better Day Than I Expected!
Well, first day at APHA went a lot better than I expected...
Still haven't found the job of my future, but hope springs eternal.
What was a ton of fun was running into a lot of former students, colleagues, and meeting a few social epidemiologists. I was stoked to meet Dr. Camara Jones and chat with the author of the "reactions to race" module I'm writing a paper on at the moment. She was super friendlyand sounded excited about my work with it.
Also met Dawn Richardson & Amy Schulz from Detroit whose work I've cited in that same paper, and after chatting about measures of segregation for a few minutes, she slipped it in that she uses one of my papers for her environmental health class. I was floored! I said if she wanted me to swing by her class, I'd fly out on my own dime, and I would!
Had an unexpectedly engrossing conversation with a woman working on injuries among loggers, shared a bunch of ideas about what might be causing the patterns she's seeing - injury rates seem to be coming down over time, a little bit. It brought up fond memories of Joe Masure, the guy who cut the trees that became our house in Vermont. That man was an artist whose canvas was forests. Alas, he would have been one of her statistics. Of all the anazing, technically challenging work he did, he met his demise sitting down for lunch, and having a branch just fall down on him. A great loss.
And to top the day off, chatted with Susan Cochrane about analyzing experiences of discrimination reported before and after the proposition 8 vote, in relation to how their neighbors voted on it.
SECOND DAY
That conversation about loggers and injuries yesterday has got me thinking I really need to spend more time reading up on and thinking about occupational health. Most of my work has been based on exposures based on where people live, but workers are often exposed to very particular things, and often at very high levels, there's a lot of opportunities there.
One study I've been mulling in the back of my head is the exposure of BART employees to dangerous levels of air pollution. You'd think that with the BART trains being electric, there wouldn't be much pollution, but when I carried an air monitor with me to and from work a few times, the pollution levels inside BART terminals, particularly Embarcadero, were much higher than anywhere else along my route, at home, or in my office. So I think it would be really interesting to plunk a few air monitors in various BART stations, or ask the workers to clip one to their belt for a few weeks, to better characterize their overall exposure levels, and also where and when during their day they get the biggest hit. Another thing that would be good to know is what's in that pollution - the monitor I had just detected small particles, but it doesn't say what those particles are made of. For the most part, it's just the size of the particles that matters for health, but what they are made of can help track down the source. Presumably the levels are highest at Embarcadero because of the Transbay Tunnel, but what in the Transbay is causing so much pollution, and what can be done about it?
Alright.... one more poster session this afternoon, then I'm headed home to make pumpkin soup, pumpkin pie, leek & onion sautee, steam-fried greens, rolls, and fruit salad.
THIRD & FOURTH DAYS
Jeez, it's been a bit of a whirlwind. Made a bunch of great connections, including a couple very bright young stars, like John Blosnich at the VA, and Gilbert Gonzales at U Minnesota. Had a brief conversation with Healther Corliss and Sari Reisner thinking about getting different results from relative vs. absolute comparisons when looking for 'intersectionality' - I may need to write an in-depth blog post on the topic, but to be honest, I'm quite vexed (;-)) about how to resolve those differences. I'm not sure that there is a way to resolve them. For a close analogy to what I'm rambling about here, check out an earlier posting about racial disparities in mortality - the very same evidence shows that they are growing in relative terms and declining in absolute terms. So does that mean that we are making progress, or losing ground, on racial disparities? The short answer is "yes".
Still haven't found the job of my future, but hope springs eternal.
What was a ton of fun was running into a lot of former students, colleagues, and meeting a few social epidemiologists. I was stoked to meet Dr. Camara Jones and chat with the author of the "reactions to race" module I'm writing a paper on at the moment. She was super friendly
Also met Dawn Richardson & Amy Schulz from Detroit whose work I've cited in that same paper, and after chatting about measures of segregation for a few minutes, she slipped it in that she uses one of my papers for her environmental health class. I was floored! I said if she wanted me to swing by her class, I'd fly out on my own dime, and I would!
Had an unexpectedly engrossing conversation with a woman working on injuries among loggers, shared a bunch of ideas about what might be causing the patterns she's seeing - injury rates seem to be coming down over time, a little bit. It brought up fond memories of Joe Masure, the guy who cut the trees that became our house in Vermont. That man was an artist whose canvas was forests. Alas, he would have been one of her statistics. Of all the anazing, technically challenging work he did, he met his demise sitting down for lunch, and having a branch just fall down on him. A great loss.
And to top the day off, chatted with Susan Cochrane about analyzing experiences of discrimination reported before and after the proposition 8 vote, in relation to how their neighbors voted on it.
SECOND DAY
That conversation about loggers and injuries yesterday has got me thinking I really need to spend more time reading up on and thinking about occupational health. Most of my work has been based on exposures based on where people live, but workers are often exposed to very particular things, and often at very high levels, there's a lot of opportunities there.
One study I've been mulling in the back of my head is the exposure of BART employees to dangerous levels of air pollution. You'd think that with the BART trains being electric, there wouldn't be much pollution, but when I carried an air monitor with me to and from work a few times, the pollution levels inside BART terminals, particularly Embarcadero, were much higher than anywhere else along my route, at home, or in my office. So I think it would be really interesting to plunk a few air monitors in various BART stations, or ask the workers to clip one to their belt for a few weeks, to better characterize their overall exposure levels, and also where and when during their day they get the biggest hit. Another thing that would be good to know is what's in that pollution - the monitor I had just detected small particles, but it doesn't say what those particles are made of. For the most part, it's just the size of the particles that matters for health, but what they are made of can help track down the source. Presumably the levels are highest at Embarcadero because of the Transbay Tunnel, but what in the Transbay is causing so much pollution, and what can be done about it?
Alright.... one more poster session this afternoon, then I'm headed home to make pumpkin soup, pumpkin pie, leek & onion sautee, steam-fried greens, rolls, and fruit salad.
THIRD & FOURTH DAYS
Jeez, it's been a bit of a whirlwind. Made a bunch of great connections, including a couple very bright young stars, like John Blosnich at the VA, and Gilbert Gonzales at U Minnesota. Had a brief conversation with Healther Corliss and Sari Reisner thinking about getting different results from relative vs. absolute comparisons when looking for 'intersectionality' - I may need to write an in-depth blog post on the topic, but to be honest, I'm quite vexed (;-)) about how to resolve those differences. I'm not sure that there is a way to resolve them. For a close analogy to what I'm rambling about here, check out an earlier posting about racial disparities in mortality - the very same evidence shows that they are growing in relative terms and declining in absolute terms. So does that mean that we are making progress, or losing ground, on racial disparities? The short answer is "yes".
Saturday, October 27, 2012
Queer Ideas of Health at APHA
The American Public Health Association (APHA) is invading San Francisco this week, and I'm going for the first time in over a decade.
I'm very proud to be an epidemiologist. I'm deeply committed to public health.
And, I can't stand how public health thinks about the public's health these days, the trends that the field has taken lately. Especially in regards to gay health, but really it's much broader than that.
So, I'm trying to gird myself for what I know will be a very frustrating experience - seeing a ton of deeply committed people - deeply committed to doing good in the world - and with a few great exceptions, failing at it.
What I need, from you, is the strength to get through this APHA meeting with grace and charm. I need to listen with open ears, do my little bit to shift how people think about queer health, and most importantly, get a job back East!
But taking a closer look at the talks and posters, it becomes very clear that there is a very odd view of LGBT health being explored at APHA's meeting. I say 'odd' and not 'queer' because the view of LGBT health that comes screaming through the program book is one that focuses almost exclusively on disease and negative health outcomes, and even more troublingly, rarely interrogates homophobia / heteronormativity / stereosexism (my neologism for the view that there are but two sexes), at least does not interrogate these fundamental causes directly.
Health disparities rule the day. Not just in LGBT health, but most definitely in LGBT health. That, and individual-level analyses that can just as easily be interpreted to mean that we are inherently sick or sinful as they can be interpreted to mean that homophobia is unhealthy.
And if there is something good going on in gay health, like gay men being less likely to be obese, it must be because of some deep-seated pathology, like lousy body image.
I'm very proud to be an epidemiologist. I'm deeply committed to public health.
And, I can't stand how public health thinks about the public's health these days, the trends that the field has taken lately. Especially in regards to gay health, but really it's much broader than that.
So, I'm trying to gird myself for what I know will be a very frustrating experience - seeing a ton of deeply committed people - deeply committed to doing good in the world - and with a few great exceptions, failing at it.
What I need, from you, is the strength to get through this APHA meeting with grace and charm. I need to listen with open ears, do my little bit to shift how people think about queer health, and most importantly, get a job back East!
Queer health on the agenda
There is a very active LGBT caucus within the APHA, with programming booked from cover to cover in the program. One could easily attend only the LGBT caucus events and never really interact with the thousands of other programs happening simultaneously. So the good news is we're there, we're taken seriously, we're in leadership roles (openly). That's great progress from the last time I went, when the LGBT caucus was insignificant, essentially a support group. Great sex, though.But taking a closer look at the talks and posters, it becomes very clear that there is a very odd view of LGBT health being explored at APHA's meeting. I say 'odd' and not 'queer' because the view of LGBT health that comes screaming through the program book is one that focuses almost exclusively on disease and negative health outcomes, and even more troublingly, rarely interrogates homophobia / heteronormativity / stereosexism (my neologism for the view that there are but two sexes), at least does not interrogate these fundamental causes directly.
Health disparities rule the day. Not just in LGBT health, but most definitely in LGBT health. That, and individual-level analyses that can just as easily be interpreted to mean that we are inherently sick or sinful as they can be interpreted to mean that homophobia is unhealthy.
And if there is something good going on in gay health, like gay men being less likely to be obese, it must be because of some deep-seated pathology, like lousy body image.
I'm not sure where we went awry. How we came to wear these bizarre prism glasses that only allow us to see such a small fragment of LGBT health. A small fragment? Yes, a small fragment. Because what the average person steeped in LGBT health knows is a laundry list of health outcomes that we do worse on: for gay men: HIV, STD's, depression and suicidality, drugs and alcohol misuse, tobacco dependence, violence victimization, etc. For women, being obese, higher breast cancer risk, drugs and alcohol misuse, tobacco dependence, violence victimization, etc. For trans women, HIV, STD's, lack of access to care, violence victimization, drugs and alcohol misuse, etc. and for trans men, lack of access to care, and probably more, but we forgot to ask who was transmasculine and who was transfeminine, so we can't really say.
If I were then to ask OK, so what about the health advantages that LGBT people enjoy? Most probably would have to think a while before coming up with the fact that gay men are less likely to be obese. And a few might toss off the idea that lesbians, at least "out" lesbians, are less likely to experience an unintended pregnancy. How many would claim that gay men are less likely to perpetrate violence? More likely to volunteer, to provide intimate care for someone not related to them? Less likely to get someone unintentionally pregnant? To enjoy a vibrant, exciting, and life-affirming sex life?
But by far the biggest category is health similarities, and I doubt that anyone could name a single one with confidence. I'd have a lot of trouble with that myself despite thinking about it for a few years now.
At any rate, if you've been reading this blog, you've heard all these arguments before. And I need to make myself cheerful and winsome. Wish me luck.
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