The biggest pitfall I see with this is we’re extrapolating from large doses of air pollution to very tiny ones.
Clearly we have enough evidence to say that smoking a pack a day or living in a smog-filled city will cut years off your life. But we would need truly gigantic samples to show that blowing birthday candles or broiling fish once a week will cut weeks off your life.
Instead these conclusions are being derived on linear extrapolations from large air particulate doses. Yet many things in biology follow the principal of hormesis, where a small dose or a toxin may be harmless or even helpful.
Similar models have been used for years and are still the gold standard when predicting the health effects of radiation exposure. Yet mountains of evidence show that radiation workers, who are regularly exposed to small dosages of otherwise harmful regulation do not have anywhere near the cancer rates we’d expect from the linear extrapolation models.
Sorry for the pendantry: it sounds like you mean linear interpolation, rather than extrapolation. Extrapolation is where you project outside the range of previously collected data, and is particularly likely to result in false conclusions. Interpolation is where you estimate a value inside the range of collected data from points around it, and is usually a lot less dangerous. But I agree with your point that, in this case, it does seem pretty baseless.
But the article is extrapolating, not interpolating.
Extrapolation is when you're extending to outside of the measured data range. In this case, the measurements were all of large values, and it's extrapolating (linearly) to small values. Just because the values being extrapolated to are smaller, rather than larger, doesn't make it interpolation.
Which is precisely why this has the risk of false conclusions, like you say.
Could you give some citations for studies on radiation workers? The permissible doses in most countries are extremely low and there are not that many people working in the industry. This makes me wonder they manage to achieve statistically significant results.
Clearly we have enough evidence to say that smoking a pack a day or living in a smog-filled city will cut years off your life. But we would need truly gigantic samples to show that blowing birthday candles or broiling fish once a week will cut weeks off your life.
Instead these conclusions are being derived on linear extrapolations from large air particulate doses. Yet many things in biology follow the principal of hormesis, where a small dose or a toxin may be harmless or even helpful.
Similar models have been used for years and are still the gold standard when predicting the health effects of radiation exposure. Yet mountains of evidence show that radiation workers, who are regularly exposed to small dosages of otherwise harmful regulation do not have anywhere near the cancer rates we’d expect from the linear extrapolation models.