I know that most people suck at logic, statistics, and a bunch of other things without which they are easy marks for bad arguments and misleading numbers. It would be nice, however, if major media outlets and publications had at least a basic grasp of how to interpret data like non-morons.

In "Ladies Last", National Geographic presents a map of the gender gap in life expectancy in the United States. Interesting and interactive map. Well done. And here's the analysis:

How long do you have? It depends on gender and geography. In the U.S., women live longer—81 years on average, 76 for men—but a recent study by the Institute for Health Metrics and Evaluation reveals a troubling trend. Though men's life spans have increased by 4.6 years since 1989, women have gained only 2.7 years, perhaps because a larger percentage of women have lacked adequate treatment for high blood pressure and cholesterol. "This is a wake-up call," says study co-author Ali Mokdad.

Wait, what? That's the dumbest thing I've ever seen, and I've seen Rick Perry.

To recap, female life expectancy has increased to 81 while men lag behind at 76, but we should be alarmed that women only gained 2.7 years to 4.6 for men since 1989. So the only thing that has decreased is the female advantage in life expectancy. While they used to outlive men by eight years, now it's only five. Absolute life expectancy for both genders has grown.

Using the magic of inductive reasoning, there appear to be some fairly obvious explanations.

1. In 1989, most of the WWII age cohort was alive and made up a substantial portion of the total population. Now many of them have died and subsequent generations – ones in which 500,000 men did not die young due to war – have outnumbered them. In 1940, women outlived men by 1 year. By 1989 that had grown to nearly 8 years. HMMM.

2. There has been a staggering decline since 1989 in highly dangerous, male-dominated, and historically common types of work. Coal mining and logging come to mind immediately, given how the gap has shrunken precipitously in the Pacific Northwest and Appalachia on the interactive map. Not only are those industries in decline, but productivity and mechanization allow fewer people to do more work.

3. There are mountains of evidence that American men are far more reluctant to get medical attention than women, making them easy victims for otherwise preventable or treatable problems.

4. Men are far more likely to die from "unnatural" causes like violence, road accidents, and suicide than women.

5. Math. Life expectancy is roughly bounded at the high end. In other words, it can't just increase infinitely and the marginal cost of increasing it once we reach the 80s is quite high. Imagine that I run the 100m in 15 seconds but you run it in 10. If we both work our asses off for a year, I'll probably improve to 12.5 seconds, while you'll be lucky to trim down to 9.9 seconds. By starting out closer to the theoretical upper limit of how fast a human can run, of course you're going to show less of a "gain" compared to someone who is lagging far behind.

But faced with all of these really, really obvious potential explanations and data that shows women still outlive men by a sizable margin, the writer (and the author of the damn study) conclude that the best explanation is women getting too few prescriptions for Lipitor.


20 thoughts on “DATA ABUSE”

  • Ed, you are clearly a person who believes that all women must eventually die, and you should be ashamed for thinking such hateful thoughts. To hear misogynists like you talk, "death" is just "inevitable." Those of us who are more enlightened know better.

  • That article doesn't cite which study exactly, but if it's the study I'm thinking of, the life expectancies are measured against international standards. More American women fell behind the best international life expectancies than American men did.

    Do you have so little faith in scientists that you really think they haven't factored in all those issues?

  • Duckbilledplacelot says:

    Sooo…pop science journalism isn't the best, you're saying? Also, speaking of misconstrued data, aren't you the guy who recently claimed that we know how to permanently lose significant amounts of weight? Like, scientifically, based on something or other? I beg of you, show me that study..

  • Middle Seaman says:

    We don't know what is the limit against which the math argument works. It's probable that in 20 years, 100 will be a regularly attainable age. In that case, both men and women are far from converging.

    Any conclusion based only on the gap in expectancy between men and women is baseless. Just because a gap narrows means nothing.

  • @duckbilledplacealot

    Bludgeoning the blog host with his own rhetorical failures isn't a nice way to start the week.

  • c u n d gulag says:

    And the "Fix the Debt" crowd will be using these statistics like these to explain why, while we can always afford profit-making wars and occupations, we have to end Earned Benefits programs (aka: "enititlements" to those sociopaths) – or, even better privatize them.

  • The IMHE is serious business, so I assuming that this is an example of complex, nuanced analysis being truncated and forced into a ridiculous blurb.

    Any conclusion based only on the gap in expectancy between men and women is baseless. Just because a gap narrows means nothing.


  • I love when logical fallacies inherently emerge from statistical data. As a social science researcher in-the-making, this is one of the many reasons why I don't enjoy analyzing quantitative data. When it leaves academia, it becomes fallacious far too often.

  • As a coauthor of the study to which this article refers and a regular reader and big fan of your blog, I feel like I need to comment for the first time ever.

    Life expectancy is a useful metric because it is an easy concept to grasp, but it is hard to fully appreciate how they are calculated. It answers the question 'How long can a person expect to live if they are born today given the current probabilities of death?' Because we use current probabilities of death, WWII doesn't factor into 1989 life expectancy at all. Your second point is well taken, but that doesn't account for everything. We see this trend across all levels of socioeconomic status and education.

    Your 3rd and 4th point don't have anything to do with trends over time, so that doesn't address the point the author is trying to make, which is that women are faring worse than men as time goes on and this is mostly due to preventable causes of death and higher levels of exposure to known risk factors. From the press release when the paper was published, "Nationwide, women fare more poorly than men. The researchers found that women in 1,373 counties

  • mothereffer cut me off —- – about 40% of US counties – fell more than five years behind the nations with the best life expectancies. Men in about half as many counties – 661 total – fell that far. "

    I completely and totally appreciate the message that people are idiots when it comes to interpreting numbers, but it is important to remember that some are not.

  • Here's a tool from the study source's home page that was interesting to play with:

    Part of the problem I have with "U.S. numbers" is that there are simply too many minor factors, too many groups with wildly different results. People of color don't live as long as whites, except for Asians, who often live longer. Poor people used to die more from harsh jobs, but lived longer if they made it to retirement, thanks to poverty habits of moderation, abstinence, and activity. Now it's rich people who last longer thanks to gyms, leafy greens, and access to healthcare versus poor peoples' TV, pizza, and access to cheap drugs.

    But that's not universal. What is? In a small country, it makes sense to speak of national health statistics, especially if you have a country that is mostly monocultural, monoracial, and even across the board. Norway is the size of New Mexico, and we can't even talk about New Mexico broadly due to the rural/urban differences, Native American / white / Hispanic differences, and extremes of wealth and poverty.

    But charts are still fun, so also I recommend, which allows side-by-side comparison of the U.S. and other countries in terms of consumption, health, life expectancy, health care, and other fun facts. Or horribly depressing, embarrassing facts, if you want to be accurate.

  • I was sure you were going to attack the first sentence: "How long do you have? It depends on gender and geography."

    While my life expectancy is probably correlated with my gender and geography, I doubt it's dependent on these factors. Unless I live downstream from a fracking waste pond and/or I get uterine cancer -I suppose then my life expectancy would be very dependent on my geography and gender…

  • My wife will run to the doctor if she stubs her toe, the first time I went in at least 20 years was when I had a heart attack.

  • Duckbilledplacelot says:

    @wyldpirate Yes, I'm sure being nice is exactly why we all come to Gin&Tacos.

    @E* Don't worry; if Keystone goes through, we might all live downstream from fracking soon!

  • @ coauthor: many thanks! Now I just have to keep in mind that knowing some meaningful distinctions does not mean I know all the pertinent factors. There's always more I don't know….

  • There is an overall trend in the U.S. where the lifestyles of men and women have been converging.

    The popular metric for gender equity focuses on women's ability to achieve in traditionally 'masculine' pursuits. Women now having the same 'opportunity' to fight in combat, is a recent example.

    This particular method for measuring gender equity could account for some of the shrinking gap in life expectancy.

    Maybe the closing life expectancy gap is showing the opposite as well. Maybe, men are capable of living as healthy of a lifestyle as women.

  • There was an article in Science a few years back about the life expectancy limit and how that limit seems to keep moving up, despite predictions that, this time for sure, we are approaching the actual limit. I'm not Ray Kurzweil, so I'm willing to believe there is a limit, but I'm open to discussion as to how close we are.

  • But….but…I want to confuse an increasing average lifespan with an increasing maximum! Then I can believe that I will live FOREVER!

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