A study that has just been published in The Lancet proposes a short questionnaire (11 questions for men , a different 9 questions for women) to assess your risk of dying within the next five years. If you want to complete the questionnaire and calculate your “Ubble age” you can just click here. One of the questions is:
How would you describe your usual walking speed?
- Slow pace
- Steady average pace
- Brisk pace
- None of the above
With the clear implication that your walking speed affects your risk of dying. What a godsend for our field. If merely asking people to categorise their walking speed on this four point ordinal scale works then imagine how much more accurate that prediction would be if we actually measured it? I can imagine gait analysis services all over the world opening up their doors to supplement their incomes by calculating people’s death risk on the basis of walking speed. More seriously I wonder how long it will be before we see this article being cited as part of the evidence base for proposals to support further research into the link between walking speed and longevity. It’s published in a very highly rated journal.
But let’s unpick the study a little bit. It is based on data from the UK Biobank project. Half a million participants thought to be representative of the UK population were enrolled and 655 measures of demographics, health and lifestyle were recorded. These individuals have then been tracked for five years to see which ones died. On this basis the 655 measures were ranked by how strongly they predicted death. Some of these are obviously very highly associated (there are for example several different ways of measuring smoking) so the authors have selected a range of the strongest unrelated predictors of death on which to base their questions. So far so good – there is a robust scientific methodology which selects walking speed as one of the strongest predictors of death.
But one of the wonderful aspects of this study is that the data has been presented in a format that allows you to probe the data on which the study is actually based. It is based on the hazard ratio which is the risk of dying for each answer divided by the “reference” answer (in this case walking at “steady average pace”)
The table looks like this:
Category | Hazard ratio [95% CI] | Deaths | P-value |
Steady average pace | 1.0 (reference) | 2653 | Reference |
None of the above | 2.7 [1.9-3.8] | 33 | 1.5 x 10-8 |
Slow pace | 2.8 [2.6-3.0] | 1275 | 3.3 x 10-198 |
Brisk pace | 0.7 [0.6-0.7] | 1165 | 1.8 x 10-28 |
Unable to walk | 4.6 [3.7-5.6] | 98 | 2.9 x 10-49 |
Note that brisk walking reduces risk of dying to 70% of the reference value but that slow walking increases it to 280%. Slow walking is thus a much stronger sign that you are more likely to die than brisk walking is that you are less likely to die. This is confirmed to a certain extent by the p-values. With such a large study getting high p-values is almost inevitable so I’d ignore the absolute values, but the relative values show that that the association with slow walking is much stronger than that with brisk walking.
And why do people walk slowly? Well most people who walk slowly will do so because they have a health condition that prevents them from walking at a “steady average pace”. It shouldn’t really surprise us that people with pre-existing medical conditions are more likely to die than those without. This is confirmed by the final row of the table above which shows that the risk shoots up even higher for people who are unable to walk at all (indicative of a much more serious health condition).
To my mind the most sensible interpretation of this observation is that walking speed is important as an indirect indicator of a pre-existing medical condition rather than a parameter of strong predictive value in its own right. This is backed up by the observation that the strongest single predictor or death is the extremely simple question – “In general how would you rate your overall health?”. People who consider themselves healthy are less likely to die than those who don’t!
This is further confirmed by restricting the analysis to “all cause mortality in healthy individuals” in which case the prediction value of walking speed falls off dramatically and lines up with a range of other fairly weak predictors. (If you do this yourself don’t be fooled by the change of scaling on the vertical axis which hides this to some extent). In other words if you restrict the analysis to people who don’t have a pre-existing medical condition then walking speed is a much weaker predictor of death.
So my suggestion is that we don’t all rush out and set up death predicting services to augment our income – or if we do that we do it extremely cynically and exhort as much money as possible from the people that are gullible enough to pay it.
Very nice post! I agree with your assessment, and have indeed in many interviews given similar responses to reporters, while trying to explain the difference between causality and correlation.
Yes brilliant isn’t it how data mining in National Health Registries can produce such surprising results… The authors conclude it is unnecessary to actually measure gait? Sigh! This is precisely why the use of patient-reported data needs to be scrutinized in an infinitely more rational manner. This is the Lancet. I have even more chilling tales to tell.
Don’t know whether you are likely to have a mother for another 5 years. She’s too old to complete the questionnaire ! Still alive and kicking at present. Mum
This study was a observational study so there were many confounders that might lead you to the wrong conclusion. For example, people who had many underlying diseases were more likely to unable to walk or slow pace. Thus the effect of underlying diseases need to be adjusted to determine the exact effect of walking speed (predictor) on death (outcome).