August 22, 2011

Spooky action at a distance?

In this week’s Stat of the Week the misinterpretation is not primarily the fault of the individual media outlet, since it was present in the original source.  Still, if a press release or a wire service story told you that the Wallabies had a new training regimen that would improve their game without making them fitter, faster, tougher in the scrum, more accurate with kicking, or better at putting in the elbow, you’d ask questions.  We’d like to see science journalism eventually get up to the standard of sports journalism.

The Herald reported “a new study suggests [TV’s] damaging effects may even rank alongside those from smoking and obesity”. If you look at the British Journal of Sports Medicine, that’s what the authors actually say. They go on to say “TV viewing time may have adverse health consequences that rival those of lack of physical activity, obesity and smoking; every single hour of TV viewed may shorten life by as much as 22 min”. The implication that TV has an effect separate from physical activity and obesity, just as it is separate from the effect of smoking, is reinforced when they say that the associations were adjusted for a whole bunch of cardiovascular risk factors: cholesterol, blood pressure, age, gender, weight, blood glucose, etc.   The implied claim is that TV kills in a way that isn’t explained by any of these risk factors: it’s not that TV-watching uses up fewer calories, or that you are more likely to snack while watching.  Perhaps the mechanism is that watching too much TV makes you believe all the health-related advertising and medical news?

The journal, in its blog, says that the real story was about sedentary lifestyles vs exercise.  They are shocked — shocked — to find that there might be sensational news coverage of the article. However, they do note:“The blast of news coverage also suggests that creative research angles on behavioral health impacts are useful in grabbing the public imagination.” Indeed.

The really strange thing about the paper, though, is the 22 minutes of life lost per hour of TV.  Looking at the confidence intervals shows that there is huge uncertainty (the range is from 20 seconds to 45 minutes), but it still doesn’t really make sense.  Some of this is just correlation vs causation — in reality, not everyone who spends the evening in front of the TV would spend the time jogging, or even playing golf, if their Sky subscription were cut off.   The other component is the model used for years-of-life lost.  The researchers didn’t actually do anything with individual participant data from the AusDiab study. They took the results of a previous analysis (which didn’t get nearly as much coverage) and added in the assumption that the effect of TV weakened with age.  Under that assumption, the effect must be a lot larger for younger people than it appears, and since younger people have more minutes of life to lose, that increases the average cost of TV.  The assumption was described  by the authors as if it was a universal fact, and it’s true that several important risk factors follow this pattern — one reason is that there are more things to die of at older ages, which applies here, but another is that, eg, low blood pressure in older people happens for bad reasons as well as good, and that doesn’t apply here.  In any case the attenuation assumption is doing a lot of the work, and it is only weakly connected to any actual data.

The original study estimated a relative risk of death for each hour per day of TV as 1.11.  A large Finnish Norwegian study estimates that smoking 1-4 cigarettes per day gives a relative risk for death of about 1.5, which would be the same as nearly five hours of TV watching, even if we could be sure that the relative risk in the TV study was causal.


Thomas Lumley (@tslumley) is Professor of Biostatistics at the University of Auckland. His research interests include semiparametric models, survey sampling, statistical computing, foundations of statistics, and whatever methodological problems his medical collaborators come up with. He also blogs at Biased and Inefficient See all posts by Thomas Lumley »

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