You can calculate conditional probabilities based on chances of quitting and not quitting cigarettes in the future.
Linearity is a more interesting issue. There the model of cancer being caused by a single mutation. In that model a single cigarette has a certain chance of creating a single mutation.
If you deeply believe in that model you can justify linearity to some extend.
In reality cancer however seems more complicated. But it’s hard to calculate the micromorts of a single cigarette. We don’t have a good theory for doing so.
It similar to other regulation of substances that harm us. We can measure in a lab how much of a substance you need to give rats to kill 50% of them.
It’s plausible that a 1/1000 of that substance can still do harm to the rats but we have no clear way of finding out.
We just have models that try to use the existing data to produce risk estimates that are as good as possible.
Then we use those estimates to make policy. The models are best we have at the moment so they seem to be better than nothing.
You can calculate conditional probabilities based on chances of quitting and not quitting cigarettes in the future.
This would make micromorts very situation dependent which would diminish their value as a statistical tool. Ex smokers would get far more micromorts from a single cigarette than people who’re just trying smoking.
In the case of smoking, a certain number of pack years become a permanent but still a diminishable risk factor past certain age. Before that age, both COPD and cancer risk can revert back to normal levels if you quit smoking. This makes perfect sense in a model where the body is able to repair itself but the repair mechanisms can be overwhelmed with a sufficient stimulus.
Using a linear model pretty much ignores the body’s ability to heal itself and the ability to remove harmful substances.
We can measure in a lab how much of a substance you need to give rats to kill 50% of them. It’s plausible that a 1/1000 of that substance can still do harm to the rats but we have no clear way of finding out.
Many substances are useful with the right dosage, and lethal with an overdose.
This would make micromorts very situation dependent which would diminish their value as a statistical tool.
Even an acitivity like driving a car is situation dependent. Careful drivers have a different risk than reckless ones. At the same time the table doesn’t show you separate values.
This makes perfect sense in a model where the body is able to repair itself but the repair mechanisms can be overwhelmed with a sufficient stimulus.
I agree with that model, but I would point out that there are plenty of people out there who consider the bodies ability to heal itself from cancer pretty nonexistent.
It does assume linearity but not irreversibly.
You can calculate conditional probabilities based on chances of quitting and not quitting cigarettes in the future.
Linearity is a more interesting issue. There the model of cancer being caused by a single mutation. In that model a single cigarette has a certain chance of creating a single mutation. If you deeply believe in that model you can justify linearity to some extend.
In reality cancer however seems more complicated. But it’s hard to calculate the micromorts of a single cigarette. We don’t have a good theory for doing so.
It similar to other regulation of substances that harm us. We can measure in a lab how much of a substance you need to give rats to kill 50% of them. It’s plausible that a 1/1000 of that substance can still do harm to the rats but we have no clear way of finding out.
We just have models that try to use the existing data to produce risk estimates that are as good as possible. Then we use those estimates to make policy. The models are best we have at the moment so they seem to be better than nothing.
This would make micromorts very situation dependent which would diminish their value as a statistical tool. Ex smokers would get far more micromorts from a single cigarette than people who’re just trying smoking.
In the case of smoking, a certain number of pack years become a permanent but still a diminishable risk factor past certain age. Before that age, both COPD and cancer risk can revert back to normal levels if you quit smoking. This makes perfect sense in a model where the body is able to repair itself but the repair mechanisms can be overwhelmed with a sufficient stimulus.
Using a linear model pretty much ignores the body’s ability to heal itself and the ability to remove harmful substances.
Many substances are useful with the right dosage, and lethal with an overdose.
Even an acitivity like driving a car is situation dependent. Careful drivers have a different risk than reckless ones. At the same time the table doesn’t show you separate values.
I agree with that model, but I would point out that there are plenty of people out there who consider the bodies ability to heal itself from cancer pretty nonexistent.