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Blood glucose is easy to measure, but not always easy to interpret. This Premium-only episode brings together insights from several previous guests to examine blood glucose responses in more detail.

We discuss the misuse of clinical thresholds, the difference between OGTT results and free-living CGM data, and whether "flatter" glucose curves are actually better in normoglycemic people.

The episode also covers when repeated high glucose excursions may be worth investigating, how sugar intake should be interpreted in context, and why skeletal muscle and exercise play such an important role in glucose regulation.

Overall, the aim is to clarify what glucose responses can tell us, what they cannot tell us, and how to avoid pathologizing normal physiology.

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When considering the health impact of foods, it is important to consider "compared to what?". Increasing the amount of a certain food or nutrient in the diet, typically implies a displacement of another.

While comparisons are more obvious in trials, in epidemiology food substitution models can be useful to help us determine the health effects of increasing/decreasing intake of a food, food group or nutrient.

However, these models are often misinterpreted and miscommunicated as if they are a game of "rock, paper, scissors", where one food beats another, and the losing food must be removed from the diet or considered harmful to health.

In this episode we discuss the problem of treating substitution analyses as food-ranking contests, rather than context-dependent comparisons shaped by the comparator, the unit of substitution, the baseline diet, and the outcome being studied.

• [01:30] Misuse of "compared to what?"
• [06:39] What substitution models do
• [10:43] Specified vs unspecified substitution
• [16:57] Why the units used matter
• [26:45] Example: organic vs conventional produce
• [31:22] When substitutions are useful
• [34:35] If legumes beat fish, does that mean fish intake should be zero?
• [44:31] Naive vs bias-adjusted: artificial sweeteners case study
• [49:14] Checklist: how to interpret food substitution analyses

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• Episode #472: Compared To What?
• Episode #589: Causal Inference in Nutrition Science – Daniel Ibsen, PhD

Unprocessed red meat and cancer risk remains one of the most debated topics in nutrition science, partly because the evidence is often presented in overly simplistic terms.

The key question is not whether to adopt a vague "balanced" position on red meat, but whether the evidence clearly identifies intake levels at which colorectal cancer risk increases and whether controlled human trials support plausible mechanisms for that risk.

A second issue is whether claims that fibre, vegetables, or an otherwise "healthy diet" can neutralise high red meat intake are actually supported by the mechanistic evidence, or whether they overstate what dietary context can plausibly offset.

In this episode, Danny and Alan examine the evidence base by moving beyond the usual epidemiology-only debate. They discuss why regional intake patterns and dose thresholds matter, then explore controlled human feeding studies showing how higher red meat intake can increase endogenous N-nitroso compound formation, faecal water genotoxicity, and other mechanistic biomarkers linked to colorectal carcinogenesis.

• [01:11] Defining the exposure and outcome
• [02:34] Carcinogen labels explained
• [07:54] Epidemiology and dose thresholds
• [14:04] Interpreting null findings
• [19:09] Bingham 1996 nitroso study
• [25:20] Hughes dose response trial
• [33:49] Cross 2003 heme iron mechanism
• [42:55] Fecal water genotoxicity
• [55:42] Tumor mutational signatures
• [59:38] What we can conclude now
• [01:04:10] Practical intake recommendations
• [01:08:41] Key ideas segment (premium-only)

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