Beige Food One
I am sorry that it took me a long time to work through this series and get it posted on the site. I was unsure where I would go with it. Ultra-processed food, fatness and ill health have been covered off in countless heavily referenced works on this site. The request for this series was specific in how to navigate treatment teams and on how to deal with how much they generate anxiety in the patient by constantly hammering on the need for a “healthy diet.”
The vast majority of practitioners do not review the research; they glance at abstracts and conclusions.[1] For the minority who might read the odd paper, they often confusing correlations with causation. Practitioners fall prey to the shortcut of reading the conclusion of a study while failing to review the limitations section or incorporating how researchers themselves are expressing cultural, and not scientific, views in their concluding remarks.
The Traps Practitioners and Laypeople Face
As an example, here’s a systematic review and meta-analysis of randomized controlled trials (RCTs) from 2025 on the different dietary patterns on glucose management in diabetes mellitus type 1 and the conclusion they draw is as follows:
“Maintaining a high-fiber diet while restricting other carbohydrates may improve glycemic control in individuals with type 1 diabetes.”
The word “may” is doing all the heavy lifting. When you read the paper in its entirety, you find that for the 35 RCTs that met the inclusion criteria, only three of them were deemed to provide results of moderate certainty. Due to bias, publication bias, imprecision, inconsistency and indirectness, most trials provided low to very low certainty of the accuracy in their results. [3]
If you can find a single medical practitioner who will advise someone presenting with TD1 (diabetes mellitus type 1) and a co-existing eating disorder that they not apply a restricted carbohydrate diet I’d like to meet them. Not only is the data supporting a restricted carbohydrate diet for TD1 rife with bias, inconsistency, indirectness, imprecision and publication bias, but a patient with a co-existing eating disorder is absolutely harmed by restricting any macronutrient from their diet.
There was another systematic review from 2018 on low-carbohydrate diets and those with TD1 that I reviewed. The researchers concluded that their review suggested “an urgent need for more primary studies.”[4] Why would that be? Because yet again they had a pile of low-quality data.
Why would it be that researchers keep doing studies, systematic reviews and meta-analyses on data that is repeatedly not yielding the desired outcomes? The problem lies in desiring the outcomes in the first place.
It would be so awesome if something as completely in our control as the food we consume, was the magical way in which we could avoid disease in the first place and cure disease should it appear. Researchers, practitioners and patients are all human beings and we desire those outcomes, but that doesn’t make it so.
It does appear as though the studies show low carbohydrate diets can lower HbA1c (hemoglobin A1C). HbA1c screening reveals your average blood glucose level. Of course, you know the devil is in the details when it comes to using these kinds of biomarkers as clinical endpoints. [Biomarkers]
Lowering HbA1c is not synonymous with glycemic control. Glycemic control is an expression of stable glycemic levels within a specific range. Just because we might be able to lower HbA1c by removing carbohydrates does not mean we are pulling on any levers that will improve morbidity or mortality outcomes (meaning increased ill health and death).
Increased morbidity and mortality outcomes for TD1 and TD2 are correlated with the glycemic trend. So not even glycemic control is a valid marker for assessing morbidity and mortality outcomes for diabetes.
If the trend is variable and the person is older than 55, then that is a predictor for a greater risk of morbidity and mortality outcomes. If the trend is rising and the person is older than 70, then that is a predictor for a greater risk of morbidity and mortality outcomes. [5] If the trend is lowering, then that’s a predictor for greater risk of morbidity and mortality for all ages. Keep in the mind the hazard ratios for those increased risks of ill health or death are very small: an increased risk of 1.1 to 1.5 times with the baseline set at 1.0.[6]
Lowering HbA1c might be something you could do by removing carbohydrates from your diet, but why do that? The number of peer reviewed published papers that boldly conflate the lowering of biomarker levels like HbA1c with improving that glycemic stability trendline is, um, a lot.
Have you ever worn a pulse oximeter on your finger and then used your breathing and a conscious effort to relax to lower your heart rate? That’s a pretty harmless way in which we can affect a biomarker. Controlling your breathing, your thoughts and your heart rate is the bedrock of applying regular meditation practices to improve overall quality of life and stress management.
Feeling in control is not a bad thing per se, and it may even have some tenuous connection to improved morbidity and mortality outcomes. But some people have very negative outcomes attempting meditation and that is true of trying to control any biomarker results as well. It’s complicated and unpredictable, and many things in modern medicine are going to give you little more than the subjective feeling that you are in control of the outcomes, when in fact you’re not.
I have used TD1 in this section to walk through the serious gaps in research papers that are drawn in the conclusions when compared to what the data actually reveals in the analyses themselves. This process can be repeated with every chronic condition and dietary manipulation that I have considered to date.
Next section will arrive on Hallowe’en.
Image in outline preview Flickr.com: Rafael Edward
Matar M, Massaad C, Itani A, Kreidly S, Chedid G, Salameh P, Nakib H. Attitudes and practices toward medical literature: a cross-sectional study at LAU Medical Center-Rizk. Future Science OA. 2025 Dec 31;11(1):2526314.
ibid.
Zeng J, Beck M, Barouti AA, Löfvenborg JE, Carlsson S, Lampousi AM. Effects of different dietary patterns on glucose management in type 1 diabetes: a systematic review and meta-analysis of randomized controlled trials. eClinicalMedicine. 2025 May 1;83.
Turton JL, Raab R, Rooney KB. Low-carbohydrate diets for type 1 diabetes mellitus: A systematic review. PloS one. 2018 Mar 29;13(3):e0194987.
Cahn A, Zuker I, Eilenberg R, Uziel M, Tsadok MA, Raz I, Lutski M. Machine learning based study of longitudinal HbA1c trends and their association with all‐cause mortality: analyses from a national diabetes registry. Diabetes/Metabolism Research and Reviews. 2022 Jan;38(1):e3485.
Skriver MV, Sandbæk A, Kristensen JK, Støvring H. Relationship of HbA1c variability, absolute changes in HbA1c, and all-cause mortality in type 2 diabetes: a Danish population-based prospective observational study. BMJ open diabetes research & care. 2015 Jan 30;3(1).
