Way back in 2016, I reported on a small study that showed glyceamic responses to food varied markedly between individuals, and raised a number of questions about what that means for those of us who count carbs, factor in the glycemic index to calculate a bolus and are taught to expect results in accordance with the published data on glycemic load.
One of the researchers involved in this study, Eran Elinav from Weizmann Institute of Science was a presenter at this year’s Australasian Diabetes Congress. It was great to hear from the presenter directly, essentially this confirmed and elaborated on the study published back in 2016, in summary:
In line with few small-scale studies that previously examined individual PPGRs (post-prandial glycemic response) (Vega-López et al., 2007, Vrolix and Mensink, 2010), we demonstrate on 800 individuals that the PPGR of different people to the same food can greatly vary. The most compelling evidence for this observation is the controlled setting of standardized meals, provided to all participants in replicates. This high interpersonal variability suggests that at least with regard to PPGRs, approaches that grade dietary ingredients as universally “good” or “bad” based on their average PPGR in the population may have limited utility for an individual.https://www.cell.com/cell/fulltext/S0092-8674(15)01481-6?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0092867415014816%3Fshowall%3Dtrue
Dr Elinav seemed to have the glycemic index in his sights, he noted that the glycemic index that has been calculated for foods is based on the glycemic responses of, in many cases, only about 10 people, these responses are then averaged out to lable the food as high, medium or low GI.
To summarise the work from the Weismann institute, it showed that for 800 participants and 1000s of meals, glycemic response to the same food is markedly different between people. It is consistent within an individual, but what spikes one person’s blood sugar does not necessarily spike another’s. As an example, I understood from Dr ELinav’s presentation that breads are usually ranked according to their glycemic index and yet this ranking didn’t hold true for individuals, some people’s blood sugar spiked more from sourdough bread than white bread, more from wholemeal than white.
So foods could be divided into ‘good’ and ‘bad’ for individuals but NOT in any generalised way. So those confident lists of good and bad, of high and low GI, of glycemic load etc-can be taken with a bit of a grain of salt.
It appears that glycemic response is influenced by gut microbiome but how much your microbiome is influenced by what you eat versus is innate is still debatable-it’s apparently not as simple as taking probiotics. For example, when people who are obese lose weight all their biochemical indicators improve EXCEPT gut microbiome markers for obesity remain. Apparently fecal transplantations have been observed to ‘cure’ obesity! This is not available as a treatment yet-but (don’t try this at home folks) there are people trying DIY versions of this. Uck I’m all for DIY in D tech but this seems a step (or two) too far.
My takeaways from the session were:
Watch this space there is SO much we don’t know about diet -glyceamic responses, weight gain and loss, how gut health influences and is influenced our responses to food. As yet we are not at the stage of being able to offer individualised WEIGHT LOSS diets-so don’t rush off and pay lots to get this done-yet! I’m hoping there will be a lot more research done to help us get a bit further in untangling the complexities of metabolic responses to food-it’s not as simple as traffic light cook books and ticks on packaged food.
Mostly though I just thought, this seems like the same old same old, we’re pretty much on our own and it’s all trial and error. CGM appears to be a really useful tool to monitor your own glycemic response-so trust your CGM or your finger pricks to give you information to act on re your responses to food.