ETA: I misinterpreted the above comment. I thought they were talking about the data, rather than the specific graph. See discussion below.
My visual inspection makes me think that, in isolation, the graph better fits the SMTM hypothesis than your hypothesis
And I’m quite confused by that, because of the chart below (and the other ones for different demographic groups). I am not saying that this single fact proves much in isolation. It doesn’t disprove SMTM, for sure. But when I read your qualitative description of the shift that we’re supposed to find in this data, and then compare it to what I see in the chart, I just don’t get the sense that you’re describing it well. Honestly I don’t know what’s going on here.
[ETA: note that the x-axis is the cohort birth year. And it’s the output of a statistical model created using NCHS data collected between 1959 and 2006. And also, this model uses the same data as the other chart.]
To be super clear, I am exclusively considering the one graph that I started this comment chain with and am not making any other claims whatsoever about the rest of the data. 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.
This might seem unreasonable, but I think it’s extremely important that we be able to see truly what a specific piece of evidence tells us in isolation. We should not let other pieces of evidence distort what we see. We should form our synthetic interpretation on the basis of truly seeing each individual piece for what it is, and then building up our interpretation from there. When I look individually at the one graph we’ve been discussing and don’t consider the rest, I see an abrupt change between two different linear paths more than I see a smooth exponential increase.
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.
I think that, when you cite that chart, it’s useful for readers if you point out that it’s the output of a statistical model created using NCHS data collected between 1959 and 2006.
ETA: I misinterpreted the above comment. I thought they were talking about the data, rather than the specific graph. See discussion below.
And I’m quite confused by that, because of the chart below (and the other ones for different demographic groups). I am not saying that this single fact proves much in isolation. It doesn’t disprove SMTM, for sure. But when I read your qualitative description of the shift that we’re supposed to find in this data, and then compare it to what I see in the chart, I just don’t get the sense that you’re describing it well. Honestly I don’t know what’s going on here.
[ETA: note that the x-axis is the cohort birth year. And it’s the output of a statistical model created using NCHS data collected between 1959 and 2006. And also, this model uses the same data as the other chart.]
To be super clear, I am exclusively considering the one graph that I started this comment chain with and am not making any other claims whatsoever about the rest of the data. 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.
This might seem unreasonable, but I think it’s extremely important that we be able to see truly what a specific piece of evidence tells us in isolation. We should not let other pieces of evidence distort what we see. We should form our synthetic interpretation on the basis of truly seeing each individual piece for what it is, and then building up our interpretation from there. When I look individually at the one graph we’ve been discussing and don’t consider the rest, I see an abrupt change between two different linear paths more than I see a smooth exponential increase.
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.
I think that, when you cite that chart, it’s useful for readers if you point out that it’s the output of a statistical model created using NCHS data collected between 1959 and 2006.
OK, I’ll add that to my comment.