It's not negatively correlated, they have not measured the effects of >1 egg/day. It doesn't change anything. Saying that the food is healthy is vacuous.
Eating 1 egg per day for the average member of the measured population seems to be healthy. It does not mean eggs by themselves are healthy or unhealthy.
It's not inversely correlated. The relationship is non-linear, how does that bear on their healthiness?
Unlike strawberries where relationship is linear, unlike many other vegetables. Put a healthy exercising population and the correlation disappears, I guess foods are no longer healthy in that case.
> We would like to add to her discussion of the significance of former and occasional drinker biases in this literature and highlight how they can cause both overestimation of cardioprotection and underestimation of cancer risks across the whole drinking continuum. The underlying theory here is that, as a population ages, a selection bias operates whereby individuals with poorer health are more likely to cut down or stop drinking completely. Such individuals are often still classified as ‘abstainers’ and used as a reference against which all current drinkers are compared. In simple terms, they make drinkers at all levels of consumption ‘look good’ by comparison.
Guys above then adjust for the mistake. The benefits disappear. Mortality risk grows as alcohol consumption increases. Yeah, there are people with protective genes, but on a population scale, recommending to go from 0 to N glasses of alcoholic beverage a day is insane.
I have personally increased my alcohol consumption, which was obviously dumb, given that the data was flawed. After this study I don't think I'll have more than couple of drinks per year.
This might suffer from the same issue the alcohol consumption study lacked.
People that aren't consuming eggs might do so because of health issues. Meaning that they are more prone to feel the side effects.
Similar effect happened in the alcohol study, where moderate consumption had a lower mortality than those consuming nothing. It turned out that those abstaining from alcohol were more prone to get side effects immediately. After adjusting for these errors in data reporting, the u-curve disappeared and the relationship was linear (more alcohol you consumed higher the mortality).
I was also, embarrassingly, citing the alcohol study, since then I've realized the first reaction to a paper should be doubt and I'll definitely abstain from acknowledging epidemiological diet studies in the future. Even meta-analyses taking them into account.
One of the best examples is that many meta-analyses conclude that dietary cholesterol does not increase serum cholesterol (proven risk in CVD). Disregarding the fact that many of the aggregated studies do not measure baseline cholesterol, and it is assumed that there's a linear response on serum cholesterol to dietary cholesterol when it's a 20 year old information that response is non-linear.
I'm not surprised. After finishing my degree, I went to optimize a couple of production lines. I didn't get much detail and thought it was for plastic/glass bottles (filling liquids and moving them around - many tiny grabbers, simple movement, not that wide tracks).
After about 2 months of work, and after the production line got parallelized and speed drastically increased I went to see it work.
What I saw shocked me and I immediatelly quit. It was a production line for handling of female and male young and grown chicks. Debeaking, throat slitting. I was absolutely shocked how none of the superiors told me exactly which product was being handled.
After seeing the horrific product of my work I quit.
Since then, I'm not surprised, given what horrors we do to living animals, that we are ready to do them to each other.
I doubted the meaning of my work at university, what did I do? Spend 4 years at college to create killing machines? I didn't think I'd ever do that.
I've noticed that DeepMind completely ignores imitation learning area of research. I never saw them citing any of the fundamental papers, despite a bunch of their reinforcement learning ideas explicitly match those ideas that are now 8+ years old.
Exactly. The amount of energy spent on heating and cooling is huge. Then it's transportation and agriculture. Then somewhere far behind is the whole Internet and efficient electronic devices.
I use the same argument when it comes to bitcoin. That stuff is so tiny in our profiler. Sane thing to do is to optimize the slowest functions.