#414

Its a good question. I think acetate and citrate both have merits. I prefer to take them without the hydrogen ion.

#415

Research Paper:

Temporal nutrition analysis associates dietary regularity and quality with gut microbiome diversity: insights from the Food & You digital cohort, Nature Communications (2025). DOI: 10.1038/s41467-025-63799-z

#416

Do they have the same effect in your glucose and TG as regular old vinegar? I take it because I can see clearly the effect. If you tell me there are other ways I will change no doubt :slight_smile:

#417

Can some one summarized “five everyday”?Skimming through the article I could spot only two!

#418

First, they found that it’s not just the consumption of fruit, vegetables and grains that create a healthy gut microbiota, but whether you eat them regularly or not. While there’s always been a hunch that it’s important to eat good food regularly, encouraged by campaigns such as 'five fruits and vegetables a day,

“This research clearly shows that you cannot binge on vegetables on your healthy day and then eat in an unhealthy way for the rest of the week or month,” said Associate Professor Marcel Salathé, head of the Digital Epidemiology Lab and co-director of the EPFL AI Center.

From CGPT5:

Here’s a summary of the paper “Temporal nutrition analysis associates dietary regularity and quality with gut microbiome diversity” plus a note on what the “five everyday” items are (or likely are) in context.

Summary

Goals and motivation

  • The authors aim to deepen understanding of how not just what we eat, but how regularly we eat it over time, relates to the gut microbiome in humans.
  • Traditional diet studies often use food-frequency questionnaires or 24-hour recalls, which average consumption or rely on recall; these approaches obscure day-to-day variability (i.e. regularity).
  • Using real-time logging of intake via a smartphone (the MyFoodRepo app) in the “Food & You” digital cohort (≈1,000 participants), they collect high-resolution temporal dietary data. They also obtain a microbiome profile via 16S sequencing of a stool sample per participant.
  • They define metrics of diet quality (e.g. Healthy Eating Index, HEI) as well as temporal variability (coefficient of variation, CV) of intake of food groups and nutrients across days, to test associations with microbiome diversity and composition.

Key findings

  1. Diet quality and regularity associate with microbial α-diversity
  • Higher average HEI (i.e. better diet quality) correlates positively with Shannon diversity, and even more strongly when using daily HEI (i.e. daily scores averaged) — meaning day-to-day consistency in diet quality matters. (Nature)
  • Lower variability (i.e. lower CV) in intake of fruits, vegetables, oils/nuts, and various micronutrients is negatively correlated with reduced microbial diversity: high irregularity tends to go with lower diversity. (Nature)
  • In regression models, dietary indices and variation metrics explain on the order of ~20% of variance in alpha diversity.
  1. Taxonomic correlations
  • Certain taxa (e.g. from Lachnospiraceae, Eubacterium_J, Butyribacter) are positively correlated with higher diet quality and regular consumption of fiber, fruit/vegetables, oils & nuts. (Nature)
  • Conversely, taxa correlated with less healthy diets (e.g. fast food, meat, or highly variable intake) include genera such as Negativibacillus, Dysosmobacter, Lawsonibacter etc. (Nature)
  • Log ratio analyses (comparing “positive” vs “negative” taxa) further support strong associations between diet (and its regularity) and microbiome composition. (Nature)
  1. Bidirectional predictability (machine learning)
  • Using microbiome features alone, they train classifiers (XGBoost) to distinguish extreme quartiles (top vs bottom) of various dietary features. They succeed especially for vegetable/fruit intake, coffee, oil-nuts, and daily-HEI regularity (AUC ~0.85–0.9) (Nature)
  • In reverse, using dietary/lifestyle features to predict microbiome diversity still yields meaningful performance — though typically weaker than microbiome → diet direction. (Nature)
  • Interestingly, some variability (CV) metrics are better predictors than raw intake quantities. (Nature)
  1. Stool quality links
  • Among participants who logged stool quality (n ~140), better stool quality (“great”) is positively correlated with higher diet quality, greater diet diversity, regularity in consumption, and some micronutrients (e.g. calcium, phosphorus, folate). (Nature)
  • Conversely, diarrhea proportion is positively associated with irregular intake of oils/nuts, grains, phosphorus, potassium, etc. and negatively with micronutrients and dietary diversity. (Nature)
  • People classified as having “great stool quality” tended to lie in higher HEI quartiles and have higher microbial diversity. (Nature)

Interpretation & implications

  • The authors argue that temporal consistency in diet (i.e. low day-to-day variability) may be just as important as absolute consumption in shaping the gut microbiome.
  • A stable supply of “good” nutrients may help microbial communities maintain stability, richness, and evenness; by contrast, “boom-and-bust” patterns may destabilize or favor opportunistic taxa.
  • This suggests a potential refinement of nutritional guidance: not only what to eat, but how regularly to eat beneficial foods might matter.
  • Limitations include: single time-point microbiome sample (no longitudinal microbiome), self-reported stool quality, shorter tracking duration, possible food-logging errors, and cohort limited to Switzerland. (Nature)

What are the “five everyday” items?

You asked: “identify the ‘five everyday’ items”. I suspect you mean “five everyday” dietary items or food groups that the paper highlights as key regular components. The phrase “five everyday” appears in public health contexts (e.g. “five-a-day” for fruits and vegetables). In this paper, I did not spot a literal label “five everyday” items, but I infer the likely meaning is the five food groups or items that show up most in the predictive or microbial associations.

Based on the paper’s results (and especially the ML classifiers), the following five everyday dietary components emerge as particularly relevant:

  1. Vegetables & fruits — strong correlation with microbial diversity and strong predictability from microbiome.
  2. Oil-nuts (i.e. fats from nuts, seeds, oils) — regular intake shows strong association and predictability.
  3. Coffee — one of the classifiers where microbiome features well predict intake (AUC ~0.9) (Nature)
  4. Meat — appears in their modeling as one of the diet groups with predictive signals.
  5. Diet quality / daily HEI — although not a food group per se, the consistency (regularity) of obtaining higher HEI is one of the key “everyday” metrics they highlight.
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#419

Sorry, but I don’t know. It is a good question. I may experiment some time using a CGM

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#420

Part of this article from Crissman Loomis includes:

What Makes Mediterranean Eating Work

The traditional Mediterranean diet builds on these daily foundations:

  • Whole grains (4-6 servings): +2.9 years per daily ounce
  • Nuts (1 handful): +1.9 years from just 20 grams daily
  • Vegetables (3-4 servings): +1.2 years at optimal intake
  • Legumes (regularly): +1.8 years per quarter-cup daily
  • Fish (3x weekly): +1.5 years per 3-ounce serving
  • Olive oil (2-4 tablespoons): Primary fat source

While minimizing:

  • Processed meat (rarely): Avoids -9.6 years per daily serving
  • Red meat (monthly): Limits to special occasions (-3.6 years daily)
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