Half a pound of coffee, surely.

]]>What’s wrong with “microthanatos”?

“Microlife” is even worse, since it uses an English root — hardly appropriate for an international scientific concept. “Microbios” would work far better.

]]>- The examples suggest that it is defined in terms of 1 millionth of the subject’s
*residual*life expectancy, not total. This produces confusing and counter-intuitive results when addressed to older people. For example, for many types of risk exposures, an exposure at 22 years causes several times greater reduction in mean life expectancy than an identical exposure does at 80. (This is the case for cigarettes.) However if it reduces the life expectancy of the 22 year old by 1½ hours, and that of an 80 year old by ½ hour, these would be quoted as 3 umt and 7½ umt, incorrectly making it sound much more dangerous for the older person. - Some of the claims for actual values are nonsense. For example, for cigarettes Prof. Spiegelhalter
*… [makes] the simplifying assumption that each cigarette contributes equally to the risk.*This is not simplifiction, it is wrong. There does not exist a simple linear relationship between number of cigarettes consumed and reduced life expectancy. This isn’t to say that people shouldn’t be warned that it is very unwise to smoke and a good idea to quit; but it is false to say that “each cigarette loses 15 minutes of your life”, and stating falsehoods doesn’t help the argument. - The one for BMI is even worse. To force it into this proportionality model, he ignores several key features of the paper he cites. In particular, he grinds his microlife values out of a reported hazard ratio using a calculation based on Gompertz’ appromximation; all the while missing that the cited article’s figures (especially Fig.7) give the result directly. Those figures, however, would have been a little unsatisfactory: they show that i) the relationship is not remotely linear; ii) for BMI ranges below 22, it is
*negative*i.e. losing weight shortens life expectancy; and iii) most importantly, for BMI below 35 (the supposed boundary between “moderately obese” and “severely obese”), the relationship is weak with both a small slope and weak correlation; nearly all the upswing is actually in the severely obese zone. To characterise this as “each 5 kg of overweight reduces life expectancy by 1 umt” is a completely false representation of the results in the cited paper. - Presumably this sentence is a typo: “
*This means he is losing around 350 days life-expectancy, 16,500 microlives, for every day he is overweight.*” (If that was the case he would be dead in two months.) **But my worst gripe by far:**The real problem — and a perennial problem in many epidemiological studies — is that there is large uncertainty in the results and it is rarely reported to the public nor to policy makers. In this BMI data, the 95% confidence intervals for the two BMI zones used by Prof. Spiegelhalter actually overlap by around 60%. Based on this data, we cannot state with confidence that a 1.75 m tall man who lowers his mass from 78 to 73 kg will thereby probably live 350 days longer. On the contrary, we do not even have very high confidence that he will increase his life expectancy*at all*; in fact there’s even about a 10% chance that losing weight will actually*lower*his life expectancy. This is one of the a perennial bug-bears of epidemiology: results are published at very low confidence levels, or with confidence intervals that overlap “no effect”, or without even calculating confidences; and are then made to seem important by multiplying a large “exposed” population by a highly uncertain number that is close to zero and may in fact be zero. The result is that people have learned to ignore epidemiological Cassandras not because they do not understand risk; but because they are fed up with an endless series of contradictory proclamations that are rarely substantiated.

- Microlife is a measure of life
*expectancy*, not a measure of how long you will actually live. It no more tries to measure when you will die than saying that the average life expectancy of a man in the US is 75 means that all men in the US are expected to live until 75 and then drop dead.

This may not tell how long *you* will live, but this is very useful when calculating mortality rates for everything from medicine to life insurance.

- You cannot use micromorts in this fashion. It is not clear from the article, but micromorts are a measure of the probability of
*immediate*death. Since your risk of dying*immediately*from smoking a cigarette is very low, micromorts would tell you that smoking is very safe. Microlifes, however, can tell you the average life expectancy of people who have smoked X number of cigarettes and thus calculate*on the average*how much shorter their lives were because of their smoking compared to those who did not smoke. Individuals would live longer or shorter than that for a variety of reasons.

If I were to devise a poison with a 100% fatality rate, but it took exactly 10 years to take effect, and would do nothing until then, a micromort would declare the poison harmless. A microlife, however, could be used to tell you how much life life a group of people who took the poison would lose *on the average*.

@ Craig

Of course you can’t determine how long George Burns would live based upon these figures. These are averages, not measures that apply to individuals. It no more tells you when a particular person will die than the odds on a roulette wheel tell you who will win.

]]>Given the relation between probabilities in a large population and outcomes for a single individual, this might be your most well-founded doubt ever.

]]>If the Smart Alex said,

*`Why do you say mass? It’s constant (if Einstein is right say mass? Surely you mean weight?’*

He would be right about Einstein but wrong about the way we measure things…

The idea behind our current thinking on standards is to come up with just one or two fundementaly agreed methods such as counting and measuring a length. These are derived from logic via mathmatics for the likes of counting. However you end up with a problem of ratios and what your agreed standard is for “1 unit of measure” so you need primary standards that can converted to others by what are currently belived to be universal constants such as the speed of light.

But there is an issue of scale with the primary method of counting… You have to be able to have things being “singular” and “visable” to count them both of which generaly don’t apply to atoms (even though the origins of the word from Greek would haave you thinking otherwise).

So with an agreement on time for which natural (almost) Universaly visable objects are good to 1 part in 10^14 stability wise, you can measure frequency (so many cycles per second) as this is related to Wavelength in a vacuum and relatavistic effects of gravity we can calculate a length by time.

Now how do we take length to mass? when you cannot count atoms, well we do it via volume and density but all substances are compressable (even the stuff in black holes) it depends on gravity…

As the irritating advert (in the UK for insurance) with the meercat says “Simpeellss”.

]]>You forgot to link! ]]>

At which time the Alex will reply “Why do you say mass? It’s constant (if Einstein is right) regardless of gravity. Surely you mean weight?”

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