Is sitting the new smoking? The excellent Tony “Dr K” Komaroff says yes, and I have great respect for his work on that website. I read the original paper (standing up and pacing about the office, of course) and felt that it was all just a bit too linear for my taste. What I’d really like to see on these data are additive / semi-parametric models of some form or other, graphically presented for us. I expect that the benefit is not a straight line function of time spent standing/stepping. Also, I suspect that activity at one time of the day is not the same as activity at another and would like to see that explored. And all in all, it’s such an interesting and important topic, it just seemed to me to be obscured unnecessarily by the stats, viz:
“Associations are described as regression coefficients (beta) or relative rates for log-transformed outcomes with 95% confidence intervals, and are plotted on a log scale, with beta rescaled as (beta+mean)/mean”
- mean? what mean?
- what log scale? the axis isn’t labelled
- log-transforms are cool because you get a multiplicative effect; why not use that to your advantage and describe a 10% reduction in triglycerides rather than RR=0.90?
The effects are for a 2 hour change per day (every day!) from sitting to standing, or sitting to stepping. Is that a meaningful change for most people? It sounds pretty ambitious! So, if I do 1 hour, do I get a 5% reduction (or, let’s be more mathematically aware, a 100*(1-sqrt(0.9))=5.1% reduction)? And we come back to the semi-parametric model of some form or other. There are so many cool models you can use, Generalized Additive Models being the most obvious candidate that comes to mind, why not do that sort of thing next time you face the Curse Of Linearity?
Now, for me, the real problem here is the disconnection between understanding the context of the analysis and then actually doing it. The experts who conducted the research certainly know that health benefits and biochemistry changes do not carry on and on and on as you pile in more minutes of standing up. Of course they know that! So then why do they go off and do totally dumb-arse things like this? At what point between starting up the computer and submitting the paper did they disengage the brain and go into a sort of auto-pilot torpor? I find it incredible. You want to know about effective feature selection in statistical modelling? Try thinking!