I’m basically interested in seeing how various attitudes in regards to charities in general, perceptions of HIV as a problem in America, and attitudes about HIV vulnerable populations affect choice of HIV (or non-HIV) charity.

For more info, check out COCOAExperiment.com. Next up, the perpetual headache that is participant recruitment…

1. 5 months, 2 weeks, and change to be more specific

I’m sorry I’ve neglected you. So much awesome public health news has broken in the last month, and I just haven’t had the time to post it. Between three jobs, full time school, and moving into the city, I’ve barely had time to breathe. I promise I’ll be back though. Come October, you’ll be back in full force.

With all this crazy news about ObamaCare, a lot of facts (and “facts”) are being tossed around. Often, people will use big fancy health care words like “life expectancy” and while we all kind-of-sorta know what life expectancy is, I’m going to really get into it for you. Why? Because life expectancy is one of those things that seems to get twisted and used in all sorts of ways it was never intended.

So, we’ll start off with the basics. What is life expectancy? Life expectancy^[1] is defined as the the average (expected) number of years of life remaining at any given age.

When people say “life expectancy in _________” they are referring to the life expectancy of that country at birth, but you can define life expectancy in other ways as well. For example, life expectancy at age 1 (or at age 5) is often used in countries with very high levels of infant mortality. Why? Well, I have to get all mathy for this so I’m going to turn it into a footnote. Hover over it if you’re really interested.^[2]

So, we’ve defined it as an average. As with any average, this creates helpful comparisons between countries/cities/regions since it is independent of population size. Also with any average, it doesn’t really define the population. The life expectancy in the US just went up to it’s highest point in history at^[3] 77.9 years. That doesn’t mean you’re going to die exactly .1 years before your 78th birthday. In fact, it doesn’t even mean most people die right before their 78th birthday. It means some people died above 77.9, some below 77.9 and maybe a few at 77.9, but when you added them up and divided by the sample size, you get 77.9^[4]

So here comes the fun part. The United States ranked horribly when it comes to this. Horribly. We are ranked 35th–this puts us at slightly higher than Costa Rica and Cuba^[5] and well, well below Japan (82) or Australia (81.6) and even *gasp* Canada (81.2)! Essentially, this puts us below any industrialized country.^[6]

And that is often what gets touted. We have the lowest life expectancy of any industrialized^[7] country in the world.

This is, of course, true; however, it is also slightly misleading. You see, life expectancy is not the most robust measure of a country’s health care system. Cultural, environmental, geographical, social, structural, or legal differences can all affect this measure and health systems have a hard time countering that. It’s a great crude measure, but horrible for direct comparisons.

It’s this exact weakness that has conservatives pouncing all over the Obama plan. Specifically, there is a presentation^[8][9]–too often (mis-)cited by others–which claims that if we removed all violent crime and automobile accident deaths, we would actually be number 1 in the world in terms of life expectancy.

This is simply not correct. If any of those blogs that cited this presentation actually bothered to read the article, they would find that the regression the authors used removed automobile accidents and violent crimes and the US moved up to 17th. Then they “standardized” the US with the rest of the world by factoring in GDP. Given that the US a huge GDP compared to any other country in the world, this bumped us up to number 1 on the list.^[10]

So the idea is if we removed areas where America has a uniquely higher rate–driving accidents and murder–we’re not as bad as the rest of the world and this is a better reflection of the health care system. Now, I’ve got issues with that already, but my first question is why? Why are we suddenly developing this new metric? We already have a metric designed to reflect a good health care system–it’s called amenable mortality. Amenable mortality is the mortality rate of a country that could have been (theoretically) avoided with timely and proper medical attention.^[11]

So there you have it. Life expectancy is the tool being used in this war of ideologies and it’s about the dullest one in the box. Don’t be tricked by this “if you remove violent crime and automobile accidents” business. Complete garbage. Look for articles that cite something useful like amenable mortality, infant mortality^[12], maternal mortality, measures involving access to care, etc.

1. in the context of human health–since it also applies to animals or manufactured goods or whatever
2. This is because life expectancy is the mean of a population and as with any mean, it is very sensitive to extreme ranges–the further away from the expected value you go, the more leverage a single point will have. That is, if your mean is 50 in a population of 10, a single person dying at 1/2 years or living to 150 will largely impact your mean. Because humans more often die at young ages than live to extremely old ages, life expectancy is especially sensitive to infant mortality. Hey, that actually wasn’t very mathy at all. Good job, me.
3. a relatively unimpressive for a developed country
4. If you still don’t get this and need a mental exercise, imagine a coin and value heads as 1 and tails as 2. If you flipped that coin a million times and then averaged out the values, you would get 1.5. Yet, you never flipped 1.5, did you?
5. Granted, Cuba is a very special case in terms of public health, GDP, and life expectancy.
6. I’m sure I could find more recent numbers, but this isn’t a term paper–it’s a blog. Either use my 2006 UN data or do your own research.
7. read: has socialized health care
8. See it here (Warning: PDF).
9. based on this article–again, PDF
10. Read the “note” here for a more articulate response.
11. On that scale, the US is still ranked pretty low–17th or 19th if I remember correctly. I don’t have my textbook with me.
12. There are some issues with this measure as well, but it’s one of the better ones in our limited toolbox.

I also took a month-long course at the University of Cape Town and got to witness a health care system within the context of a truly transitional society. I learned it’s possible to provide free primary care to your entire population. I also learned doing so is difficult. I learned the battle between private and public health providers knows no geographical, cultural, or social boundary. I learned about the difficulties of expansive poverty in the wake of heated violence and racism. I learned that an amazing and beautifully crafted constitution^[4] is meaningless without political and logistical backing.

Well, suffice it to say I learned a lot. It solidified my desire to get a doctorate and go into research.^[5] I’ll keep you updated on any articles that come out of the trip.

1. and another week gallivanting through UAE and Europe
2. 4.7 minutes per survey for raw data plus an additional 30 minutes per 50 surveys for coding
3. 15.7 pounds
4. And South Africa’s is definitely one of the best constitutions I’ve ever read.
5. Though, I am not sure if I’d want to be based in another country for extended periods of time.

Here, I’m working with an organization called Sonke Gender Justice Network working on a project that will (hopefully) provide quantifiable data and put the lives of young South African males in better social context. I don’t want to dive too much into the project until it is up and running, but I’m excited about being back in Africa and running a project as the PI. There’s huge potential for this project to fine tune the unique programs Sonke is currently implementing to the very specific needs of young men.

The entire staff at Sonke has been unbelievably supportive and the mentorship of Dean Peacock^[1] has been invaluable.

That’s my blurb for now. There will be a lack of proper updates until the summer is over. Partly because I’m busy, partly because the internet here is unreliable, but mostly because I need a break.

[Photo: mine.]

1. 2007 Men’s Health Man of the Year, btw. I cannot help but poke a little fun at him about this. On his long list of wonderful accomplishments and awards, this one is undoubtedly the sexiest.

So, first, I couldn’t move all the comments over. Sorry. If you left a comment and it is gone now, it has nothing to do with me censoring you. I’m also missing a few posts that I just couldn’t bring back. The posts also didn’t come with their tags so I’m slowly filling those in. Lastly, I’ve still got to tweak this theme–I like the overall presentation, but some of it is just weird.

I was way behind schedule on this one, so I apologize to my two readers. Two jobs, full time school, midterms, finals, papers, presentations, and life–what else can I say?

Your regular blogging will continue.

I like how it was done (high level genetic analysis) and I like the potential of using GIS to track not only endemic diseases (such as malaria) but also contagious diseases. I think a similar map in Africa would be equally impressive–showing the spread of HIV through truck drivers or other highly transient populations.

[Image courtesy of The Shane H via Flickr.]

Here is his latest video. He presents HIV statistics in a way only gapminder can (and he doesn’t even use the full potential of gapminder). Nothing in the video (as far as substance) should surprise or shock anybody interested in global health, but it’s always nice to see it on paper.

Check out his other talks on TED (or any of the talks) if this is the kind of thing that interests you. I’ve watched at least 200 and I’ve never seen one I thought was boring–ok… that’s a lie. But the vast majority of them are pretty amazing.

[Photo from Rico San via Flickr.]