Note: I deleted and re-posted this comment since I felt it was missing key context and I was misinterpreting you previously.
What I specifically said is that in isolation, the graph we have been discussing better fits the SMTM hypothesis than your hypothesis. Bringing in a separate graph that you think better supports your hypothesis than SMTM’s has zero bearing on the claim that I made, which is exclusively and entirely about the one graph we have been discussing. This new comment with this new graph reads to me as changing the subject, not making a rebuttal.
To be clear, I said I was “confused”, not that I disagreed because of additional evidence. But I did misinterpret what you were saying, ultimately. So, let me try again.
I don’t know how to reconcile any differences between the chart I brought up and the chart you mentioned. Note that they’re drawn from the same data, so in theory my chart is showing is simply how BMI moves through time, whereas yours is showing the same thing but under a different transformation; namely, it shows the proportion of people who are above a certain BMI threshold.
My rough guess is, and my initial implicit assumption was, that the two charts are simply consistent and the original point I made about shifting a normal distribution still holds, and the apparent shift is mostly an illusion, with the caveat that there’s a slight acceleration (as shown in the chart I brought up). The reason why I brought up the chart is because I assumed you agreed that they were consistent, but simply thought that the acceleration in BMI was large. I wanted to say: “I don’t agree. See how it looks when you just follow BMI through time. There’s barely any acceleration!”
No worries! I am approaching this debate in a collaborative spirit. I may have been misunderstanding you as well.
What I see when I examine the second graph you have shown, again in isolation, is that it does indeed look very much like the results of the “shifted normal” model you described earlier. Or rather, of that process happening twice, with a sort of temporary tapering off around 1940. Although if I’m understanding right, the earlier pre-60s part is pure extrapolation. This graph clearly fits your and Natalia’s hypothesis and not SMTM’s, we see nothing of particular significance around 1980.
As you say, the next question becomes how to decide which to put more weight on. Do we like the statistical heft of Komlos and Brabec, or do we think they’re just using fancy statistics to erase a crucial feature of the raw data? I don’t know how to arbitrate that question. But I would be sympathetic to an interpreter who said they were convinced by the sophisticated statistical model and viewed the apparent “elbow” in the raw data as more likely an artifact than a real feature of the true trend, and I’m sure Komlos and Brabec know much better than me what they’re about.
My way of proceeding would be to say “looking at the raw data, it does look like there’s a sharp change around 1980, but that might be an artifact. Looking at a sophisticated curve-fitting model of similar data, that feature vanishes. We might put 80% weight on the sophisticated modeling and 20% on the raw data, and note that the raw data itself isn’t so incompatible with a “shifted normal” interpretation, maybe 70⁄30.” Overall, I’m inclined to put maybe 85% credence in the “shifted normal” interpretation in which there was no big event in obesity around 1980, and 15% credence that a real ” elbow feature” is being obscured by the statistical smoothing.
Note: I deleted and re-posted this comment since I felt it was missing key context and I was misinterpreting you previously.
To be clear, I said I was “confused”, not that I disagreed because of additional evidence. But I did misinterpret what you were saying, ultimately. So, let me try again.
I don’t know how to reconcile any differences between the chart I brought up and the chart you mentioned. Note that they’re drawn from the same data, so in theory my chart is showing is simply how BMI moves through time, whereas yours is showing the same thing but under a different transformation; namely, it shows the proportion of people who are above a certain BMI threshold.
My rough guess is, and my initial implicit assumption was, that the two charts are simply consistent and the original point I made about shifting a normal distribution still holds, and the apparent shift is mostly an illusion, with the caveat that there’s a slight acceleration (as shown in the chart I brought up). The reason why I brought up the chart is because I assumed you agreed that they were consistent, but simply thought that the acceleration in BMI was large. I wanted to say: “I don’t agree. See how it looks when you just follow BMI through time. There’s barely any acceleration!”
Sorry about the misinterpretation.
No worries! I am approaching this debate in a collaborative spirit. I may have been misunderstanding you as well.
What I see when I examine the second graph you have shown, again in isolation, is that it does indeed look very much like the results of the “shifted normal” model you described earlier. Or rather, of that process happening twice, with a sort of temporary tapering off around 1940. Although if I’m understanding right, the earlier pre-60s part is pure extrapolation. This graph clearly fits your and Natalia’s hypothesis and not SMTM’s, we see nothing of particular significance around 1980.
As you say, the next question becomes how to decide which to put more weight on. Do we like the statistical heft of Komlos and Brabec, or do we think they’re just using fancy statistics to erase a crucial feature of the raw data? I don’t know how to arbitrate that question. But I would be sympathetic to an interpreter who said they were convinced by the sophisticated statistical model and viewed the apparent “elbow” in the raw data as more likely an artifact than a real feature of the true trend, and I’m sure Komlos and Brabec know much better than me what they’re about.
My way of proceeding would be to say “looking at the raw data, it does look like there’s a sharp change around 1980, but that might be an artifact. Looking at a sophisticated curve-fitting model of similar data, that feature vanishes. We might put 80% weight on the sophisticated modeling and 20% on the raw data, and note that the raw data itself isn’t so incompatible with a “shifted normal” interpretation, maybe 70⁄30.” Overall, I’m inclined to put maybe 85% credence in the “shifted normal” interpretation in which there was no big event in obesity around 1980, and 15% credence that a real ” elbow feature” is being obscured by the statistical smoothing.