I’ve always been struck by the imprecision of how the terms “low-glycemic-index diet” and “low-glycemic-load diet” are used. In theory, these are diets that reduce post-meal blood glucose and their benefits derive from this property. In practice, they often differ from typical diets in multiple ways. If a “low-glycemic diet” is also higher in fiber and protein and/or lower in palatability, calorie density, and carbohydrate, can we really attribute its beneficial effects to its impact on blood glucose per se? To gain a better understanding of the depth and pervasiveness of this problem, I did a scientific literature search for randomized controlled trials of low-glycemic-index/load diets, selected the first ten I found, examined the details of the assigned diets, and evaluated the findings.
Methods
I performed a search in Google Scholar using the search terms “randomized trial low glycemic”. I scanned down the list until I had identified the first ten studies that met the following criteria:
- Randomized controlled trial
- Compares a low-glycemic-index or low-glycemic-load diet to a control diet
- Title describes the low-glycemic diet only according to its glycemic index/load, not other diet characteristics (e.g., high protein, legumes)
- Any length (single meal to long-term diet trial)
I extracted the following information from each study:
- First author
- Year published
- Title
- Summary of subject characteristics
- Length of intervention
- Diet summary
- Detailed diet description
- Was the between-diet comparison well controlled for glycemic index/load? Yes = differences in glycemic index/load were achieved without substantial differences in the types of foods consumed. Moderate = the types of foods differed substantially between groups, but major nutritional characteristics like protein and fiber intake were well controlled. No = major nutritional characteristics like protein and fiber intake differed between groups.
- Outcome of the intervention
My primary outcome was how well each diet was controlled for dietary variables other than glycemic index/load.
Results
I compiled a table of the findings here. Trials were published between 2004 and 2011, and were all highly cited (105 to 413 citations according to Google Scholar). They lasted between 4 weeks and 18 months, and 6 of 10 involved subjects with diabetes.
Among the ten trials, five were clearly not controlled for glycemic index/load (“no”), four were moderately well controlled (“moderately”), none were well controlled (“yes”), and one didn’t provide enough information to judge.
Overall, the results of the trials suggest that low-glycemic diets can be helpful for blood glucose control in diabetes, but their effects are modest in people without diabetes. They are not very effective for weight or fat loss (relative to control diets, which varied) and they seem to have little impact on birth outcomes in the context of gestational diabetes.
Discussion
In this limited but unbiased sample of highly cited papers on low-glycemic diets, I found that none isolated glycemic index/load as a variable, 40 percent were moderately well controlled for glycemic index/load, and 50 percent were poorly controlled for glycemic index/load. Another way of stating this is that all of the diet comparisons differed in ways other than glycemic index/load, and five of them differed in major ways that are likely to be confounding.
This is only a problem if we attribute the outcomes of these studies to glycemic index/load per se. If we all understand that “low-glycemic diet” often means “beans, nuts, fresh fruit, and slow-digesting whole grains that may improve health via multiple mechanisms relative to typical diets”, there’s no problem. This is the interpretation I believe is most accurate, but it’s not what I see in most discussions of these studies.
The findings of this brief literature survey suggest that we should be cautious about attributing the effects of low-glycemic diets to their impact on glycemia per se.
Interesting. Wonder what a more comprehensive search of the literature would yield
Hi Zad,
I have seen short-term GI/GL studies that were well controlled, e.g. comparing different types of rice to one another, different types of potatoes, or isolated starch with different GIs. I don’t think my quick analysis suggests that there are no well-controlled GI/GL studies, but it does suggest that poorly controlled ones are common, particularly among those of longer duration.
Did any of the studies evaluate the effectiveness of carb counting?
https://www.novomedlink.com/content/dam/novonordisk/novomedlink/resources/generaldocuments/CountingCarbandMeal_EG.pdf
This approach to blood glucose control enforces low glycemic dieting, if the system of carb exchange counting is adhered to. But it is complex, and it would be hard to control for a scientific study.
Hi thhq,
I don’t recall any of them mentioning carb counting in their methods.
there are also many roots to be added to your low-GI list. Also, some roots, such as sweet potatoes, are devoid of fructose. that helps the liver and ultimately helps prevent fatty liver.
“Overall, the results of the trials suggest that low-glycemic diets can be helpful for blood glucose control in diabetes, but their effects are modest in people without diabetes”
If you measure their diabetes control ability solely by glucose metrics (glucose spikes, post-prandial AUCs, HbA1c etc…) then yes, you should expect only a modest effect of low-GI siets on people without diabetes – but this is because these people still have, by definition, “normal” glucose control.
Blood glucose alone is the wrong way to quantify diabetes, you’re looking at an end-stage marker. It’s much better to see markers that occur higher up the causal chain, like the 1st and 2nd phase insulin response and hence their level of insulin resistance. Lookin at insulin markers, you may well see that low GI diets have more pronounced (positive) effects.
PS: I don’t think Low GI is well-defined nor a goal. I think a much better goal is to avoid carby foods that rapidly get absorb along the digestive track resulting in altered incretin and thus metabolic responses leading to over-partitioning (more fat, less other stuff). Basically, aim for intact macromolecular starch networks, not flour products
I’m pretty sure Dr Guyenet wasn’t quantifying diabetes by blood glucose alone. I’m sure he is aware of the multitude of other factors that contribute to insulin resistance. What i took from the article was the efficacy of low GI diets is not as glamorous as it is portrayed in the media, and that a low GI diet is not a hugely effective fat loss tool.
Obviously, i am not endorsing the majority of CHO to come from high GI source, refined or otherwise, just that there are other factors affecting blood glucose levels than the glycemic response of a food, activity level, overall calorie intake etc..
General agreement on diabetes is that glycemic index is not all that useful. All those carbs eventually enter the blood stream so you have to inject that much insulin anyway. What you eat with that low-glycemic food greatly changes that index number. Low-glycemic foods just take a lot longer to absorb.
Notably, pasta and pizza are low-glycemic and a headache to time our insulins. Many have to split the dose and inject before meals and an hour or two after meals. In a sense we need to estimate how quickly foods absorb which means keeping track of GI. But it is the totality of the various foods in the meal, not any particular food and its GI.
Are you Type 1 or Type 2?
When I was diagnosed Type 2 I started carb counting and eating three small meals/three snacks. The effect of the counting was reduced glycemic load, by severely restricting high GI starchy and sugary foods. The effect of the small meals was to reduce the post prandial glycemic spikes. I was never on insulin, and only used metformin for a week or two.
Carb counting turned into calorie counting very quickly, and I lost 20% of my body weight. After losing weight my insulin sensitivity came back and I stopped counting carbs.
T2, insulin dependent. Tightly controlled – keeps retinopathy at bay.
Note – the various ‘types’ of diabetes hides more factors than it enlightens. For many diabetics of all types there is a derangement of glucose metabolism. Also complications are not all that tied to average BGs or A1Cs. Very low carbs helps, but is no substitute for insulin for many T2s.
Can you actually dream up a way to actually control for all the important variables?
I can’t.
There’s too many possible confounders to really control for. Short of locking people in a metabolic chamber, randomizing, crossing over, blinding, doing extreme diets, including and not including ‘snacking’, including and not including cardio, including and not including weight training, varying the intensity of both kinds of exercise, etc. how can we ever say *for certain*?
Hi Daniel,
It’s possible to get pretty good control. For example, different types of rice (e.g. Basmati vs. Japanese sticky rice) have very different glycemic index but are almost identical otherwise. You could assign rice-heavy diets with different types of rice.
But the other strategy is to not worry about completely controlling for glycemic index, and then not attribute the effects you observe to the glycemic index. What’s problematic is when you don’t isolate GI and then attribute between-group differences to GI.