All carbs pretty much are equal, it tends to be the amount of fiber that comes with the carb that changes things. This study was about fructose, not sugar in general, and we've known for a long time that fructose behaves differently from other carbs due to the way it is metabolized in the liver.
Anecdotally-empirically, a lot of Type 2's have found carbs, fiber or no fiber, are just bad news. For at least those with a specific variation of Type 2 (still as-yet not clearly understood, but there is growing consensus that there are many different "sub-types" of Type 1 and Type 2, each of which responding well to different treatment protocols), it doesn't matter how much fiber you eat with a scoop of carbs once the metabolic syndrome manifests itself with a high enough insulin resistance response.
With enough carbs (as few as 50g for some) the end result at that stage of the condition is still a highly-adverse event, a high blood sugar spike above 100 mg/dL. Even if the spike is controlled down within 1-2 hours, there is a lot of accumulating evidence that it isn't the duration or absolute value of high blood sugars, but the spikes (the occurrence of any delta in the first place) themselves that cause cellular damage.
In a few years, we will hopefully start accumulating a flood of highly-granular, anonymized biometric sampling data, ideally tagged with true/false flags of known and suspected genetic markers (but not enough DNA data to individually dox someone). Has someone solved the problem of publishing biometrics with tagged DNA data, and be able to update the DNA tags as our understanding of genetic markers improves over time, without risking doxxing an individual from the genetic marker tags?
Sure, I wasn't talking about diabetic people.
> In a few years, we will hopefully start accumulating a flood of highly-granular, anonymized biometric sampling data, ideally tagged with true/false flags of known and suspected genetic markers (but not enough DNA data to individually dox someone). Has someone solved the problem of publishing biometrics with tagged DNA data, and be able to update the DNA tags as our understanding of genetic markers improves over time, without risking doxxing an individual from the genetic marker tags?
I also hope that this is the future. Unfortunately we're probably not going to do much better than HIPAA when this technology is widely available and being used. I'm not sure how to prevent the GATTACA side effects, but it feels like the health advances might be worth it.
The "normal" threshold for an oral glucose tolerance test (OGTT) at 2 hours post-load (75g glucose after fasting) is 140mg/dL. Where is this research indicating that a spike above 100mg/dL is "highly-adverse"? All the research I have seen, and the position of the ADA, is that it is normal to go well above that after a heavy carb load.
I have seen claims by Dr. Richard Bernstein and his adherents that the ADA is wrong and that "normal" is much lower and flatter than they claim. I have seen no supporting research on this, and even active criticism of that idea fro various medical researchers.
Can you link to anything about that?
Polhill TS, Saad S, Poronnik S, Fulcher GR, Pollock CR. Short-term peaks in glucose promote renal fibrogenesis independently of total glucose exposure. Am J Physiol Renal Physiol. 2004 Aug;287(2):F268-73.
I don't really think these studies show that acute blood sugar level elevation is causing the damage you are talking about. The first one talks about how TII diabetics tend to have lower β-cell count and higher apoptosis frequency, but that doesn't mean they go through waves of apoptosis more frequently (ie: during blood sugar spikes), it means that they have a lower life span. The study doesn't establish causality, so it's unclear whether diabetics have lower β-cell count because they are diabetic, or whether lower β-cell causes diabetes. It is a great study though, pretty well designed and building on kind of amazing resources from the Mayo Clinic.
The second study is interesting but extremely limited due to the fact that it was does in vitro. The problem is that it's talking about kidney fibrosis, or scarring of the kidney due to inability to regenerate. But when you remove much of the kidney and the surrounding body and then attack the kidney with glucose of course there is damage. That doesn't mean that in vivo the body can't deal with it. Kidneys do have a hard time regenerating, so it's an interesting foundational study, but I'd hardly call it "a lot of accumulating evidence."
I'll readily grant this can reasonably be construed as suggestive but not "a lot of accumulating evidence", my bad for phrasing it improperly. To me this line of research is raising interesting questions warranting further digging, in a "hm, I wasn't expecting that result going by the received wisdom" way.
Following the sporadic posts of Type 2 patients in online forums self-reporting success at getting off conventional treatment protocols, what appears to come up in common among them is what is currently considered (by the ADA and similar outfits in other nations) radically aggressive methodology to blood glucose control; <100 mg/dL post-prandial is not considered out of line in that crowd, and they avoid spikes as much as possible. A very small number have been at it for 20+ years and well into their 60-70's, and are reporting no long-term disabilities commonly associated with advanced stages of the metabolic disorder. They tend to be in very low (<50 mg/day) carb or even ultra-low (<20 mg/day) carb regimens, or constant ketosis, or varying fasting cycles, with varying amounts of exercise, or a combination of all of the above, with lot of nuances thrown in by each individual. A lot of what they practice directly goes against published large institutional guidelines, but it is really difficult to argue against the end results in their comprehensive blood panels and other bio-markers, so it is a fascinating case to me of the impact of an N=1 / DIY / Quantified Self ethos that increasingly more people are embracing with the aid of increasingly better technology. I find it really exciting that increasingly more laypeople are empirically "science'ing the shit out of this" (to paraphrase "The Martian") with a continuous hypothesis-test-adjust loop upon themselves. It is definitely not science by any conventional means, but as haphazard as it is, it is yielding in a startling number of cases exceptionally better results than the average and mean Type 2 patient experience.
I want to be clear though: there is certainly evidence that very high blood sugar causes significant damage, sometimes permanent, I'm not contesting that. How high "very high" is varies, and as far as I know doesn't really happen in people who aren't diabetic. All I'm saying is I don't think blood sugar spikes are bad for non-diabetics, but they certainly are for diabetics.
See http://33bits.org/2009/12/02/the-entropy-of-a-dna-profile/
Today we hand medical researchers large databases pre-filled with the data they seek.
As we move into a world of increasingly ubiquitous biometric monitoring, asymptotically trending towards real-time, could the data gathering be flipped around instead? Individuals become the only ones who own their detailed DNA profile (the profile with billions of base pairs stored), held on either a personal device with suitable encrypted backups (ideal) or held on their behalf by a trusted service (encrypted with a key only the individual holds). Researchers send out requests for specific data ("weekly blood pressure of males between 20-60, with these genetic markers, starting now/5-years-ago"). Individuals either manually approve matching requests or set up approval "subscriptions"/rules. Requests matched with data sources get anonymized data of course.
Researchers not only can get data this way, they get a continuous, crowd-sourced data feed. Longitudinal studies might get easier to set up through this kind of channel. There isn't a way to ID someone by their feed and the researchers' requested, limited matching genetic markers alone, unless an attacker systematically breaks into multiple research databases, and starts building a Palantir-like correlation amongst all the hacked databases; that dramatically raises the detection risk to the attacker. Another attack is an overly-broad set of genetic markers in a single request, and those requests can be auto-denied before even getting into the brokering system. Short-term, we can prohibit the collection of any part of the 13-base-pair CODIS markers, though long-term we have to assume that CODIS or its future successors will eventually expand to a larger set of markers (and in the far, far future, possibly the entire sequenced genome).
Nobody is ever going to know what the chemical composition of a potato is, it's just a potato. Fibre, water, protein content is "carbs" when it's in a potato.
There are plenty of different molecules, such as Sucrose, Glucose, etc, which are all forms of carbohydrate molecules.
But when people refer to "carbs", they're not referring to the chemical molecule, but most likely processed carbohydrates such as bread.
Hopefully that's more clear
[1] http://www.ehow.com/about_4613535_chemical-makeup-potato.htm...
You're right though, it probably would've been more helpful for me to say carbohydrates in general.
sucrose = glucose + fructose - water
lactose = glucose + galactose - water
maltose = glucose + glucose - water
Based on this study, I would guess that replacing all HFCS with an equivalent-sweetness amount of regular corn syrup (all glucose) would immediately result in significant improvements to the public health, even though the sweetened products would have more calories per serving.