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.

Sunday, November 4, 2012


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.
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

New reader? Skip to The Highlight Reel...

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?

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 friendly and 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.

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.

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!

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.

Thursday, September 27, 2012

Who needs to move?

There's an interesting phrase that pops up frequently in the literature on racial segregation - it is a phrase that is used to give an intuitive interpretation of the most frequently used measure of residential segregation, the dissimilarity index. It goes like this:
The dissimilarity index can be interpreted as the proportion of the minority population who would need to move in order to achieve full integration.
Without getting into the math, the dissimilarity index measures the degree of segregation of racial groups across the neighborhoods of a metropolitan area. It is a single measure for the whole city and the suburbs connected to it through employment, shopping, entertainment & recreation commuting. It summarizes the degree to which each racial/ethnic group lives in exclusive neighborhoods (full segregation) vs. every neighborhood has exactly the same distribution of racial/ethnic groups as the whole metro area (full integration).
When you do dig into the details of the math, an equally plausible interpretation would be:
The dissimilarity index can be interpreted as the proportion of the White population who would need to move in order to achieve full integration.
Which begs the question, why is it more intuitive to think about the minority population needing to move to achieve full integration, and so strange to think about the White population needing to move to get to the same goal? Why is it more acceptable to countenance (even in purely abstract terms) the widespread uprooting of Black and Brown lives?

When you stop to think about it, the historical processes that generated our current highly segregated residential patterns were largely driven by Whites leaving urban neighborhoods and plowing productive farmland into new spacious suburban neighborhoods. So if anything, the most logical way to reverse segregation, to retrace the steps, would be for Whites to move back into city centers, rather than further hollowing out extremely segregated metropolitan areas like Detroit, Milwaukee, Cleveland & Buffalo.
Milwaukee - 84% segregated

Charlotte - 61% segregated

Sunday, September 23, 2012

Segregation & Discrimination

I just finished a draft of a paper trying to get at the question of whether you're more likely to experience discrimination in a highly segregated city than a less highly segregated one.
And the results have me a bit confused.

The biggest problem in trying to answer that question is that the right dataset doesn't yet exist. Ideally, you'd want to know what people, in particular racial/ethnic minorities, experience in different cities.
There are a lot of studies now that have asked people about their experiences with racial discrimination, but they are almost all done within one city, or at least they are not a random sample across multiple cities. And as far as I can tell, nobody has yet done that kind of survey work. The closest I've been able to get to the the BRFSS, which has asked a consistent set of questions about experiences of racial discrimination in about a third of the states over the last decade.

But at least one half of the equation is pretty well mapped out.
Detroit is one of the most segregated cities in the country - can you tell where 8 Mile Road is in the map?
So is Chicago, which has a different pattern - Blacks and Hispanics radiating out in slices, surrounded by starkly White neighborhoods, with the North Shore also predominantly White.

For a less highly segregated city, check out Plano, Texas (no city in the US is close to what one might call integrated). Blacks and Whites live together downtown, and Whites and Hispanics are pretty well mixed throughout the city.

At any rate, when I pulled together the best data I could from BRFSS, it appears as though Blacks aren't really much more likely to report being discriminated against in very highly segregated cities compared to less highly segregated cities. But Hispanics and Asians are more likely to report various forms of racial discrimination if they live in very highly segregated cities than in less highly segregated cities. Any theories?

Another complicating factor is that a lot of people who do experience racial discrimination either aren't aware of it, or don't report it in these surveys. For instance, Blacks with very low levels of education are much less likely to report being discriminated against, while those with college degrees are the most likely to.
So it is possible that the reason I'm not seeing much (if any) increase in highly segregated cities among Blacks is that Blacks in very highly segregated settings may be less likely to perceive unfair treatment as out of the ordinary or worth noting.

I'd be curious to hear your thoughts. And sorry I can't share the numbers yet...

Sunday, September 9, 2012

The Curious Case of Gay Men in Excellent Health

I'm giving a very short talk (15 mins) at the Gay and Lesbian Medical Association meeting in San Francisco on Saturday September 22nd at 10:15AM in the Commonwealth room on the second floor of the Westin Hotel, 50 3rd Street, downtown. You can just walk in. Please do, it would be lovely to see you.

Here's a rough draft:

Hi. Welcome. Say hello to your neighbors. Swap names. Get friendly.
This morning, I'm going to break out of the usual background-hypotheses-results-conclusions format a bit. I'm going to use a more narrative format - something closer to telling a story. So curl up and gather 'round. This is a story of inconvenient data that wouldn't go away. And a story about what happened when I settled down to listen to what it had to say.

I've broken it up into roughly three sections, the first I'm calling "the knock on the door", the second "explaining the mystery", and the third section will be trying to develop lessons, morals if you will, from the tale.

In 2006, shortly after I moved to California from my beloved Rhode Island, I decided to undertake a project to document health disparities affecting gay men, lesbians and bisexuals. There were already a bunch of studies documenting one or another specific health outcome at a time, I wanted to use a consistent methodology to track a bunch of health outcomes, including the ones we didn't expect to be different, like arthritis.
But a curious thing happened when I looked at the first health outcome in the first dataset: general health in the California Health Interview Survey.
When I graphed it out, I saw the same thing that others had already published on, that gay and bisexual men were more likely to report being in poor health (the red bars at the bottom of the graph) than heterosexual men.
But it's pretty obvious that that's not the dominant trend there - gay men in particular are more likely to report being in "excellent" and "very good" health than either bisexuals or heterosexuals.
And with everything I knew about gay men's health, that just didn't make sense. Between HIV infection, depression & suicidality, eating disorders, smoking, and so on, there's no reason that gay men should be more likely to be in excellent health.

So I did what any decent epidemiologist would do. I wrote it off and didn't give it a second thought.

Until the next year, when the next wave of the California Health Interview Survey came out. I pored over the study, and again the same findings - gay men more likely to report being in poor health (as expected), but also more likely to report being in excellent or very good health than heterosexuals.
At this point, I had to use the next level of defense to dispense with these unexpected findings. Rather than simply ignore them, I assured myself that "general health" is a squishy endpoint - it's very subjective - so who knows what it means anyway.

More datasets were coming on-line that asked questions about sexual orientation and health outcomes, so when I got my grubby mitts into the New York City Community Health Surveys, I started out with the general health question, and men who had sex with men were more likely to report being in excellent health there too. General health might be a squishy endpoint, but I knew that there were a lot of studies showing that it was a very strong predictor of mortality, and tracked very closely with other population health measures, even if it doesn't mean much for a given individual. So I had to up the ante, and pull out the big guns to dismiss the fact that both of these surveys presented such contrary findings. It must be due to sampling bias - the gay men are probably younger - that would explain it. No need to get excited.

But at this point, I definitely had my eye open, and started looking in as many datasets as I could lay my hands on. Like the unemployment survey...
The unemployment survey doesn't ask if you're gay or lesbian, but it does ask who you live with and how you're related - so you can identify men living with male partners and women living with female partners. Not ideal, but the advantage is the huge sample size. The unemployment survey calls about 50,000 people a month. So pulling several years together, I found over a thousand men in male couples. Here again, men in male couples were more likely to report being in excellent health.
To be fair, there were also studies that didn't follow the pattern - the General Social Survey for one, and a study from the Philadelphia area. But the general trend was definitely clear after looking in about a dozen studies, especially in the largest and best-conducted studies.

Explaining the Mystery...
I talked with a lot of friends, relatives, co-workers, strangers at gay health meetings, and tried to figure out what might explain this unexpected finding. Despite HIV infection rates, despite depression, despite smoking and substances misuse, somehow gay men were reporting excellent health more often. What could explain it?
The first set of explanations I looked into was whether it could be explained by demographic differences. Gay men, or at least men who will say they are gay to a stranger on the phone, tend to be younger and more highly educated than the general male population. They are more likely to live in large cities. Those could all be tested.
The second set of explanations was more psychological, and much harder to tease apart with available data. What if "excellent" means something different to gay men than to straight men? Maybe gay men, many of whom have seen death up close and far too personal, have a greater appreciation for their own health, and thus are more likely to report being in excellent health than a straight man in comparable health.
Maybe gay men have grown so accustomed to being told that gay men are sick and unhealthy by society at large, and medicine in particular, but see their own lives as being in better shape than the stereotypical gay man, and thus report being in excellent health to a greater degree than a comparable straight man. I could only get at these indirectly.
The third set of explanations was that maybe, just maybe, gay men were in fact healthier than straight men, that we are doing something different from straight men - doing something healthier than straight men. Like going to the gym more. One explanation that came up here was that gay men were healthier because they had fewer kids. I didn't quite understand the logic of that, but it kept coming up, so I looked into it.

The best dataset I had access to that would enable looking into these questions was the BRFSS - the Behavioral Risk Factor Surveillance Study. The BRFSS is a random-digit dial survey of a few hundred thousand people every year, from every state, the District of Columbia, Guam, Puerto Rico and the Virgin Islands. Like the unemployment survey, it asks who you live with and whether you're married or in an unmarried partnership, so it's possible to identify who is in a male couple vs. a mixed-sex couple.
For reasons I really don't have time to go into, you can't look at married same-sex couples in BRFSS, basically because a few straight married couples mis-identify themselves as same-sex, and even a tiny number of mis-identified straight couples mangles the same-sex married group.
So, here the men in male couples are more likely to be in excellent health than men in mixed-sex couples.

The first thing I looked into was whether demographics could explain the difference - the men in male couples were younger on average, and younger people are more lilely to report excellent health. Men in male couples were also much more likely to be highly educated, and social class is a very strong predictor of health.

And in fact when you standardize, so that everyone is weighted as though they have exactly the same age and educational attainment, the difference between men in male couples and men in married mixed-sex couples virtually disappears. But the men in male couples are still more likely to report excellent health than the men who, like them, are in "un-married" couples. Further adjusting for a range of other demographics - like race/ethnicity, income, employment status, veteran status, children in the home, state of residence or urbanicity didn't make any appreciable difference once age and education were accounted for.
So, demographics are part of the story. But men in male couples were still about 20% more likely to be in excellent health than men in mixed-sex un-married couples.

I didn't have a good way to directly test the second set of explanations - maybe "excellent" means something different for gay men than straight men? The best I could do was compare across men whose health was comparable, as best as I could figure it out from the available data, and when you control for asthma, arthritis, cardiovascular disease, diabetes, high blood pressure, high cholesterol, smoking, drinking, exercise, body mass index, and fruit and vegetable intake, the groups get more similar. But, the survey doesn't ask HIV status, and I'm not really sure that your health can really be summarized easily with that short list of factors. In short, I'm hesitant to say that this rule in or out that "excellent" health means something different for gay men than straight men, but there is definitely not strong evidence for that explanation.

Among the third set of explanations, it becomes possible to ask what gay men do differently. One of the few health advantages that has been consistently identified in the literature is that gay men are less likely to be obese than straight men - and the opposite is the case for lesbians, who tend to be heavier than straight women. Insert your own wry comment about "the male gaze" here.
And in fact, when you standardize for body mass index in addition to age and education, the differences between men in male couples and men in mixed-sex couples get very small indeed - about 12% more likely to be in excellent health. So that's pretty strong evidence that gay men are in fact doing something different.
And that something different is healthy. A lot of the gay health world has cast a disparaging eye at gym culture. Body dysmorphic disorder, beauty obsession, all kinds of pathologizing terms. And I don't mean to dismiss those phenomena as not problematic, but I think it's worth taking a step back to recognize that whatever it is that gay men are doing to their bodies differently than straight men, it has, on the whole, made us healthier.

The Moral of the Story
Stepping back to the beginning of the story, I want you to recall that it was very hard for me to recognize that there might be something interesting going on here, because the findings did not fit the dominant paradigm of gay health these days - it wasn't a health disparity, but apparently a health advantage. And minority groups aren't supposed to have health advantages. That's why the 'Hispanic Paradox' is called a 'paradox' instead of common sense.
So, what do we miss when we have trouble seeing health advantages?
Before tackling that, I want to step to the other side of that question and ask what we get from identifying health disparities? Curiously enough, we get a sense of satisfaction - health disparities confirm the idea that minority health is adversely affected by societal hostilities and incivilities. But there is more to it than that- identifying and promoting health disparities is an important modality for raising awareness and garnering resources. Raising awareness in the target community to encourage enhanced screening or whatever, and raising awareness in the eyes of funding agencies gets more resources to address the health disparities.
So seeing, describing, and promoting health advantages would seem to be at cross-purposes. First of all, if we, as a minority, are healthier, that flies in the face of being a minority that deserves special consideration. If we are healthier, then we don't need resources devoted to our health.

But I think that is a misguided interpretation. Like every other minority group, we have a mix of health disparities and health advantages. And in all likelihood, many more health similarities than either of those. So telling only the story of health disparities tells a very partial and inaccurate story about who we are, what we need, and especially what resources we can bring to the table. It is a story that focuses exclusively on the negative. It can be discouraging.
Perhaps paradoxically, it is also a narrative that perfectly fits our most potent political adversaries as well. The American Family Association, Exodus, NARTH, and others happily gobble up every health disparity we identify and claim that it proves that we are "inherently disordered", and thus unworthy of basic dignity, let alone legal protections.
So, if health disparities are a bit of a "Black box", confirming one's preconceptions rather than pointing us towards solutions, what are the alternative approaches to minority health?

First, acknowledge the health similarities and health advantages.
Second, learn what we can about why the health advantages, in particular, exist. Asking "how are you healthy?" disrupts the health disparity narrative. Whatever we learn about what's going right can potentially be leveraged to address the health disparities that we are so concerned about.

Third, let's study causes, not effects. Health disparities are effects. If we think that societal homophobia causes the health disparities, then let's measure the effects of societal homophobia directly.

Fourth, let's intervene in the causes directly, not just raise awareness of the carnage that homophobia has caused.

Saturday, September 1, 2012

Research Worth Reading: the Regnerus Study

OK, I'm probably not going to make a lot of friends with this posting, but I think most people read this blog because they want to hear my contrarian viewpoints, not because they agree with me.

By now pretty much everyone's heard of the "Regnerus Study" or the "Family Structure Study". Praised by the religious right & a scorpion in the boot of the gay movement, the study leaves precious few without a strong opinion. If you have no idea what it's about, a good summary of the study and the controversy surrounding it was written by William Saletan at Slate.

I spend a lot of time listening to broadcasts from the religious right: Bryan Fischer at American Family Radio, Liberty Counsel, Family Research Council, National Organization for Marriage, etc. You may drink coffee to get up & going - I listen to these folks.
I think it's important to understand where they are coming from, to understand what arguments they use, what they assume to be true, what they believe about people like me, etc. Often people seem to think these folks are crazy, stupid, or both. I don't think that they are, for the most part. The major spokespeople are far from crazy or stupid. However, they are strong partisans, and have interpreted the Regnerus study with a very partisan bias. They have claimed that it proves that children do best when raised by their biologic mother and father, and that children raised by gay or lesbian parents do worse in most areas than children of single parents. It proves no such thing, but I think it is a valuable addition to the discussion.

As many others have pointed out before me, the study does not have a sample of children raised by gay or lesbian parents upon which to make these claims. They asked a bunch of adults some questions about their parents, and classified anyone who claimed to know that their parent had had a same-sex experience as having been raised by gay or lesbian parents. The study had less than a handful of respondents who had been raised by same-sex parents from infancy.

Many people who I agree with on the substance of family studies have said that the Regnerus study should be pulled, that it is fraudulent and academically dishonest. I don't think it is. I think he clearly and accurately described what he did, and although I encourage people to vehemently disagree with his interpretations and conclusions, that the methodology of the study is not inherently flawed, and was not dishonestly presented in publication. As a result, I don't think it should be pulled.

The controversy around this piece has got me thinking in a lot of different directions, so I hope you'll forgive the scattered nature of the next few paragraphs.

Reaction A: Lots of crap gets published. I'd say over 98% of the studies I read have major methodologic weaknesses, and/or come to conclusions not supported by the underlying data they report. And don't get me started on plagiarism - that problem is out of control, and can even be found in esteemed academic publications. When I started trying to write a series on 'research worth reading' about gay health, it was a real struggle to find anything worth encouraging others to read. I went through hundreds of abstracts, read dozens of papers, and came down to a small handful of papers I thought were 'worth reading'.
Which is a far cry from saying that there isn't a lot to learn from all the crud that gets published.
But it does make me reticent to say that the Regnerus study, with all its flaws, is out of bounds when compared to the vast majority of academic publications. Is it 'worth reading' from the perspective that it skillfully addresses the underlying research question with precisely targeted methodology and conclusions that are well founded in the work itself? No on all counts. But, it is worth reading because it presents a very different perspective than most of the family structure studies out there currently, and it provides a methodologic contrast to them that makes it worth thinking about how to build from the methodologic weakness of the entire field something that would be more reliable.
So, if the Regnerus study frosts your buns, as it should, get off your duff and do a better study. The gauntlet has been thrown down & there's no way to force them to pick it up again and say 'my bad'.

Reaction B: Religious right commentators have claimed that there is a strong liberal bias in this field, and that any study like Regnerus's that challenges the pro-LGBT bias is unlikely to get a fair chance at publication. I'm afraid that they may be right on the first of these, although I doubt the latter.
The larger field of marriage and family structure studies has been very heteronormative with respect to lesbian and gay families, to the point that even when there is a same-sex household included in these studies it usually gets classified as a mixed-sex household because the researchers don't even consider the possibility that there might be same-sex households. But among the small number of studies that do acknowledge same-sex parents, this small subfield has been conducted and interpreted largely by partisans on our side of the debate.
I don't know how many anti-gay studies have been precluded from publication, but I doubt it is very many, if any. It is more likely that these studies just haven't been done. A couple possible reasons: 1) our adversaries often claim that it is obvious common sense that lesbian or gay parents are harmful, so there is no reason to confirm common sense (I'm not agreeing with that, just trying to explain why I think only one anti-gay study has been done so far). 2) Lots of people on the right say that they are tired of talking about homosexuality - by which they mean they wish we would just go away and not ever be part of their lives - ouch! But that sentiment, that they are tired of talking about us, carries through to why they would be unlikely to do a scientific study of family structure, valid or otherwise. Why would you invest time and effort into such a study if you were tired of thinking about it and just wished it would go away? 3) Putting the time and effort into such a study thus requires a significant investment in a heteronormative worldview, an obsession that is unusual in society in general, and academia in particular. Gay and lesbian researchers have an obvious interest in this sort of work, but it takes a heterosexual with a real bone to pick to become similarly invested.

Reaction C: I've been perplexed by the widely-held beliefs among the religious right that they are being persecuted by homosexual activists, and that our gains in society have come at their expense. I know that there's no conspiracy to reign in the religious right because I've seen first-hand how LGBT folks organize. We are way too fractious to pull something like that off intentionally. By the same token, I'm deeply suspicious of claims that "the church" or "the Mormons" are acting in concert as often as we think they are.
In the 90's I tried to do a lot of activism around victimization, and I really think that is a self-defeating way to go. It makes you more paranoid and can become self-fulfilling. So my word to both sides - leave the persecution stuff off the table - it doesn't help anyone.

Reaction D: I wonder how a study on family structure could be done in a methodologically convincing way. It's not easy. Regnerus tried (and failed) to get something close to a random sampling of the general population. That's a tough approach to use because children of lesbian and gay parents are still pretty uncommon, and that's the main reason his method failed. The approach mainly used by our side is to find families headed by same-sex parents and try to find a comparable comparison group of mixed-sex-headed families. That's a tough approach because it is very hard to be sure that the comparison group really is comparable. I think the best approach that might be feasible in the short-term would be to piggy-back on some other very large random sample of Americans and do a follow-up survey with all the same-sex-headed households and a matched sample of mixed-sex-headed households. The Current Population Survey would be, I think, an ideal vehicle for such a call-back survey. They interview about 50,000 Americans every month, so there might just be enough same-sex-headed households contacted through that survey to make it feasible. The Behavioral Risk Factor Surveillance System might work too, but it would be a huge logistic challenge to get permission from each state to call people back. The American Community Survey could work too, but because that is done by the Census, we would first need to get Congress to admit that same-sex marriages do in fact exist, and are worth studying.

Reaction E: Why is it important to compare the children of same-sex to mixed-sex households? I'll admit that it is interesting from an academic perspective, but I think most of the interest is generated by the desire to use evidence in policy debates. But should it matter?
A lot of the debate so far has centered on whether the children of same-sex couples are more likely to "turn" lesbian or gay themselves. Most of the studies on 'our' side have claimed that the answer to that question was no -- because our opponents were so fiercely complaining about gay contagion. But I think it's safe to say that the evidence is that kids of lesbian and gay parents are in fact more likely to realize that they are gay, lesbian, and especially bisexual. In 2009, I heard a great talk by Clifford Rosky which really pushed the audience to ask, "So what?". So what if gay, lesbian, and bisexual kids are more comfortable, more self-realized, after growing up in our households? Isn't that a good thing? (The Regnerus study counts being openly GLB as a 'negative' outcome, by the way!)
And that leads me to wonder what possible relevance the Regnerus study, or the studies on our side, should have in regards to public policy. Of course it would be easy and convenient if the children of same-sex parents were equal in all regards to the parents of mixed-sex parents. But would it really matter if that weren't the case? Shouldn't we expect that the children of same-sex parents would be worse off in some ways and better off in others? And even if the impossible were true: that children of same-sex parents were, on average, worse off in every possible measure, should that preclude every same-sex couple from having children or being able to marry? I'm struggling to see the relevance. The children of wealthy parents are much more likely to be diagnosed with autism - should we sterilize the rich?

No easy way I can see to wrap this all up. Thanks for listening, and feel free to chime in!

Sunday, July 15, 2012

Day Four: Laramie WY->Avoca IA

 Started out the day in Laramie – I debated whether or not to visit the fence where Matthew Shepard was found, but in the end decided I didn’t have the stomach for it.
I continued to stay off the main roads as much as possible, seeing some awesome high country in Wyoming before crossing over to Nebraska at Torrington.
Nebraska started out blistering hot and only got worse.  I followed route 30, which runs near route 80 most of the time, and is roughly where the Oregon Trail was. It also runs parallel to a set of railroad tracks that were the busiest I’ve seen.

Every day, 52 trains of at least 100 cars packed with coal come down out of the mountains, and 52 empty trains return there to pick up more. I waved to one of the conductors, and to my surprise and delight, he tooted the horn in return.

Route 30 through Nebraska is, I have to say, the most depressing thing I’ve seen in a while. I’ve always been fascinated with urban decay, but seeing one small town after another devastated was tough to take. Main streets without a single open shop. Many towns consisting of a huge set of grain elevators and a few shacks crowded nearby on barely paved streets.

By the time we got to Grand Isle, I had to try something else, so I got on the main road and sped along through Lincoln and Omaha, landing in Iowa after nightfall.

I try to hit the welcome center at each state border, but often I cross on a minor road, so I’ve only hit a few so far: Colorado, Wyoming, and Iowa. It’s actually surprisingly nice to be welcomed to each state by smiling people, and I like to collect maps from each state and mark out my route to help me remember what I saw and experienced.

Tuna has been quite the trooper, hardly complaining at all after the first day. Her arthritis has been acting up a bit, but not too badly. We’re still titrating the rymadil to figure out the minimal effective dosage.

Day Three: Nephi UT-> Laramie, WY

Blue Mountain, Eastern Utah

Blue Mountain, East Utah

Northwest Colorado

Northwest Colorado

Northwest Colorado


Rabbit Ears Pass, North Colorado

Day Two: Reno NV->Nephi UT

 Started out East from Reno, headed into big sky country, absolutely gorgeous long views.

These two are from the middle of Nevada somewhere...

Thursday, July 12, 2012

Day One: San Francisco->Berkeley->Sacramento->Reno

Today was the first day of our trip back East. I packed last night, and then piled everything into the truck this morning. Got a happy surprise from my pal Duncan who was in the Bay Area, we got together for lunch with his brother and step-dad in Berkeley, my first burger of the day.

Itching to hit the road, we set off for Sacramento, and met up with Daniel for my second burger of the day. Both were delicious (well all three if you count Daniel). Sacramento was brutally hot for my taste, and so I was eager to get up into the Sierras to find some cool weather.

The road was steep for my truck, and we spent a lot of time in third gear, with the hazards blinking. Finally crested at Donner's Pass. The memorial plaque there was pretty vague about what went down with the Donner Party, but it was chilling to be reminded of it all.

The Sierras did bring cooler temperatures, but a forest fire in the area filled the entire region with some pretty noxious fine particulate matter, and I am afraid I'll have a rough night sleeping with the scent hanging in the air tonight. Alas, I didn't really get to see the Sierras because we hit the foothills at sunset and it was too dark to make anything out.

Finally pulled in to the Motel 6 in Reno - here's the view of the casinos from my window. I have to say I'm none too impressed with Nevada so far. Prominent billboards advertising DUI defense attorneys, bankruptcy, etc. For a liberty-loving state, seems like there's a lot of lawyers involved.

Eager to see what tomorrow brings. I've seen northern Nevada from planes, and on Google Earth - the terrain looks really strange, so I'm looking forward to getting a closer perspective.

Sunday, June 10, 2012

Hawai'i and Alaska

    This is the fourth in a series of maps showing how people have voted on gay rights at a fine level of detail.
    In this post, I showing maps of the first two states to vote on restricting marriage to "one man and one woman" - Hawai'i and Alaska.
    In 1993, a Hawai'ian court found that denying similar gender couples the opportunity to marry was in violation of the equal protections guaranteed by the Constitution. After various legal wrangling issues that are too complicated for me to understand, in 1998 the Hawai'ian legislature put the following provision up as a state constitutional amendment, in order to prevent similar gender marriages from occurring.
    It passed by one of the widest margins of any such amendments seen, with 285,384 (69%) of the 403,211 votes cast. As you can see in the map below, the vote was pretty uniform across the state, with most polling places voting 60% to 75% in favor.

    In Alaska, a similar measure was also referred to the people for ratification to amend the state's constitution in 1998 (I'm still not sure why Alaska was so eager to get on board, or why so many other states held off until later years).
    This measure also passed easily, with 152,965 (68%) of the 224,596 votes cast. As in Hawai'i, there was very little regional difference in how people voted on the measure. The inset of Anchorage shows that voters in the state's largest city were no less likely to support restricting marriage. Don't read too much into the large patches of different colors in the North & the panhandle, these are because very few people live in these areas (often fewer than 20 votes cast).

    In 2007, the legislature put a non-binding question in front of the voters - basically asking "Hey, we want to make sure that no same-sex partners of state, county, or municipal government workers can get any health care, life insurance, inheritance or anything like that through spousal employment benefits, even if the local government wants to give those benefits - you cool with that?"
    And indeed, the voters were cool with that. The measure passed with 60,896 (53%) of the 115,338 votes cast. As far as I know, the Alaska legislature did not go on to propose such a constitutional amendment to deny employment benefits - perhaps they figured out that it would be an easy call for pretty much any judge to see that it wouldn't pass constitutional muster.
    In contrast to the vote 9 years earlier, there is a lot more regional heterogeneity in how Alaskans voted on this measure, and you an see a pretty strong gradient from North to South in Anchorage itself. I don't know jack about Anchorage, so I'd be curious if this looks "about right" to anyone with local knowledge. Again, you shouldn't read too much into the large patches in rural areas.

    In 2012, Anchorage residents had the opportunity to add sexual orientation to the anti-discrimination statute in the city code. The measure failed, getting only 30,208 (43%) of the 70,431 votes cast. There were some shockingly inflammatory ads run by a group against the measure (for allowing discrimination) that certainly helped tip the balance.