Human Nutrient Requirements: An Evidence-Graded Synthesis<\/title>\n<link rel=\"preconnect\" href=\"https:\/\/fonts.googleapis.com\">\n<link rel=\"preconnect\" href=\"https:\/\/fonts.gstatic.com\" crossorigin>\n<link href=\"https:\/\/fonts.googleapis.com\/css2?family=Archivo:wght@500;600;700;800;900&family=Source+Serif+4:ital,opsz,wght@0,8..60,400;0,8..60,600;1,8..60,400&family=IBM+Plex+Mono:wght@400;500;600&display=swap\" rel=\"stylesheet\">\n<style>\n:root{\n --bg:#F4F6F7; --card:#FFFFFF; --card-2:#FAFBFC;\n --line:#D5DDE2; --line-2:#E7EDF0;\n --ink:#0E1A21; --ink-2:#3D4C57; --ink-3:#5C6B75;\n --t1:#093644; --t2:#115A72; --t3:#17758C; --t4:#96600B; --t5:#A63525;\n --pale:#8FB8C6; --null:#EDF1F3;\n --display:\"Archivo\",\"Helvetica Neue\",Arial,sans-serif;\n --body:\"Source Serif 4\",Georgia,serif;\n --mono:\"IBM Plex Mono\",ui-monospace,Menlo,monospace;\n --sp:clamp(1rem,3.5vw,2.25rem); 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font-family:var(--mono);font-size:0.72rem;color:var(--ink-3);line-height:1.75}\n\n.reveal{opacity:0;transform:translateY(12px);transition:opacity .65s ease,transform .65s ease}\n.reveal.in{opacity:1;transform:none}\n.wipe{transform:scaleX(0);transform-origin:left;transition:transform .85s cubic-bezier(.22,.7,.25,1)}\n.wipe.in{transform:scaleX(1)}\n.grow{transform:scaleY(0);transform-origin:bottom;transition:transform .85s cubic-bezier(.22,.7,.25,1)}\n.grow.in{transform:scaleY(1)}\n.draw{stroke-dasharray:1400;stroke-dashoffset:1400;transition:stroke-dashoffset 1.5s ease}\n.draw.in{stroke-dashoffset:0}\n@media (prefers-reduced-motion:reduce){.reveal,.wipe,.grow,.draw{opacity:1!important;transform:none!important;stroke-dashoffset:0!important;transition:none!important}}\na{color:var(--t2)} :focus-visible{outline:2px solid var(--t2);outline-offset:3px}\n@media print{\n @page{size:A4;margin:14mm 12mm 16mm}\n body{background:#fff;font-size:9.5pt}\n .reveal,.wipe,.grow,.draw{opacity:1!important;transform:none!important;stroke-dashoffset:0!important}\n \/* tall containers must be allowed to break, or layout cannot place them *\/\n .card,.tier,.tablewrap,.grid2,.split{break-inside:auto}\n .callout,.legend-item{break-inside:avoid}\n table{min-width:0;font-size:7.6pt}\n th,td{padding:1.6mm 2mm}\n thead{display:table-header-group}\n tr{break-inside:avoid}\n .tablewrap{overflow:visible}\n section{padding:8mm 0 0} .refs{columns:2;font-size:7pt}\n *{-webkit-print-color-adjust:exact;print-color-adjust:exact}\n}\n<\/style>\n<\/head>\n<body>\n<div class=\"shell\">\n\n<header class=\"masthead\">\n <div class=\"mast-top\">\n <span class=\"eyebrow\">Evidence-graded synthesis \u00b7 literature window 2015\u20132026 \u00b7 Author: RezaRaza.com<\/span>\n <span class=\"eyebrow\">Not a guideline \u00b7 Not medical advice<\/span>\n <\/div>\n <div class=\"mast-grid\">\n <div>\n <h1>What nutrient a human body actually requires, ranked by <em>how well we know it<\/em>.<\/h1>\n <p class=\"standfirst\">This document reorganises nutrition around a single axis: not food groups, not servings, but <strong>how well each claim survives contact with the evidence<\/strong>. The result separates the handful of findings robust enough to apply to nearly everyone from the many that are genuinely individual, and from the surprising number that are simply unresolved. It covers macronutrient floors, the carbohydrate minimum, dosing for every class of fat, micronutrient bioavailability, gastrointestinal and cognitive outcomes, and the popular beliefs that recent evidence has overturned \u2014 including several that were overturned in the direction nobody expected.<\/p>\n <\/div>\n <nav class=\"toc\">\n <span class=\"eyebrow\">Contents<\/span>\n <h4>Fifteen sections<\/h4>\n <ol>\n <li><a href=\"#pyramid\">The Certainty Pyramid<\/a><\/li>\n <li><a href=\"#floors\">What meets the obligate floors<\/a><\/li>\n <li><a href=\"#protein\">Protein quality, ranked<\/a><\/li>\n <li><a href=\"#classify\">Macronutrient or micronutrient?<\/a><\/li>\n <li><a href=\"#form\">Tier 1 \u00b7 Food form<\/a><\/li>\n <li><a href=\"#tier2\">Tier 2 \u00b7 Obligate floors<\/a><\/li>\n <li><a href=\"#carbs\">Carbohydrate: the minimum, in detail<\/a><\/li>\n <li><a href=\"#fats\">Fats: every class, with dosage<\/a><\/li>\n <li><a href=\"#fibre\">Tier 3 \u00b7 Fibre and plants<\/a><\/li>\n <li><a href=\"#fish\">Fish, shellfish, poultry<\/a><\/li>\n <li><a href=\"#myths\">Correcting common beliefs<\/a><\/li>\n <li><a href=\"#colon\">Colon and gut<\/a><\/li>\n <li><a href=\"#brain\">Cognition and dementia<\/a><\/li>\n <li><a href=\"#apex\">Tier 5 \u00b7 Where trials contradict<\/a><\/li>\n <li><a href=\"#refs\">References<\/a><\/li>\n <\/ol>\n <\/nav>\n <\/div>\n\n <div class=\"notice\">\n <span class=\"eyebrow\">Verification status \u2014 read before trusting a number<\/span>\n <p><strong>Live literature search was unavailable for most sessions that produced this document.<\/strong> The content is drawn from a deep working knowledge of this literature, refined by a later research pass that supplied some verified quotations and intervals. <strong>Every effect estimate, confidence interval, sample size, DIAAS score and nutrient value requires independent confirmation against the primary source before publication or clinical use.<\/strong><\/p>\n <p>Treat all 2024\u20132026 figures as provisional \u2014 specifically US POINTER (JAMA 2025), KETO-CTA (JACC Advances 2025), the SSaSS intervals (NEJM 2021), the colibactin \/ early-onset colorectal cancer signature work (Nature 2025), and the MIND-diet RCT (NEJM 2023). Nutrient composition varies by species, cut, feed, season and preparation. Figures marked <b>SCHEMATIC<\/b> render the shape of a reported relationship, not extracted datapoints.<\/p>\n <\/div>\n<\/header>\n\n\n<section id=\"pyramid\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Figure 1 \u00b7 The organising structure<\/span>\n <h2>The Certainty Pyramid<\/h2>\n <p>Vertical position encodes evidence quality, not quantity to eat. Colour depth runs with certainty: the darkest band rests on controlled trials, the amber band is a setting you choose, and the top band is where published trials contradict one another. Width encodes evidentiary weight.<\/p>\n <\/div>\n <div class=\"card reveal\">\n <svg viewBox=\"0 0 1000 570\" role=\"img\" aria-labelledby=\"pt pd\">\n <title id=\"pt\">The Certainty Pyramid: five tiers ordered by evidence quality<\/title>\n <desc id=\"pd\">Base: food form, established by metabolic ward trials. Second: obligate nutrient floors. Third: fibre, non-starchy vegetables and whole fruit. Fourth: the carbohydrate dial including grains and starchy vegetables. Apex: unresolved questions.<\/desc>\n <g class=\"grow\">\n <polygon points=\"104,412 456,412 500,500 60,500\" fill=\"#093644\"\/>\n <polygon points=\"148,324 412,324 456,412 104,412\" fill=\"#115A72\"\/>\n <polygon points=\"192,236 368,236 412,324 148,324\" fill=\"#17758C\"\/>\n <polygon points=\"236,148 324,148 368,236 192,236\" fill=\"#96600B\"\/>\n <polygon points=\"280,60 324,148 236,148\" fill=\"#F5E4E1\" stroke=\"#A63525\" stroke-width=\"2\" stroke-dasharray=\"5 3\"\/>\n <\/g>\n <g font-family=\"Archivo,sans-serif\" font-weight=\"900\" text-anchor=\"middle\" fill=\"#fff\">\n <text x=\"280\" y=\"464\" font-size=\"25\">FOOD FORM<\/text>\n <text x=\"280\" y=\"376\" font-size=\"23\">OBLIGATE FLOORS<\/text>\n <text x=\"280\" y=\"288\" font-size=\"18\">FIBRE & PLANTS<\/text>\n <text x=\"280\" y=\"199\" font-size=\"14\">CARB DIAL<\/text>\n <\/g>\n <g stroke=\"#D5DDE2\" stroke-width=\"1.5\">\n <line x1=\"478\" y1=\"456\" x2=\"536\" y2=\"456\"\/><line x1=\"434\" y1=\"368\" x2=\"536\" y2=\"368\"\/>\n <line x1=\"390\" y1=\"280\" x2=\"536\" y2=\"280\"\/><line x1=\"346\" y1=\"192\" x2=\"536\" y2=\"192\"\/>\n <line x1=\"302\" y1=\"104\" x2=\"536\" y2=\"104\"\/>\n <\/g>\n <g>\n <rect x=\"540\" y=\"430\" width=\"14\" height=\"14\" rx=\"2\" fill=\"#093644\"\/>\n <text x=\"564\" y=\"442\" font-family=\"Archivo,sans-serif\" font-weight=\"800\" font-size=\"17\" fill=\"#0E1A21\">Tier 1 \u00b7 Food form<\/text>\n <text x=\"564\" y=\"461\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#093644\" letter-spacing=\"0.7\">CERTAINTY: HIGH \u00b7 INPATIENT CROSSOVER RCT<\/text>\n <text x=\"564\" y=\"479\" font-family=\"Source Serif 4,serif\" font-size=\"13.5\" fill=\"#3D4C57\">Macros matched, processing changed: +508 kcal\/day.<\/text>\n <rect x=\"540\" y=\"342\" width=\"14\" height=\"14\" rx=\"2\" fill=\"#115A72\"\/>\n <text x=\"564\" y=\"354\" font-family=\"Archivo,sans-serif\" font-weight=\"800\" font-size=\"17\" fill=\"#0E1A21\">Tier 2 \u00b7 Obligate floors<\/text>\n <text x=\"564\" y=\"373\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#115A72\" letter-spacing=\"0.7\">CERTAINTY: HIGH \u00b7 TRACER + BIOCHEMISTRY<\/text>\n <text x=\"564\" y=\"391\" font-family=\"Source Serif 4,serif\" font-size=\"13.5\" fill=\"#3D4C57\">Protein, essential fats, bioavailable micronutrients.<\/text>\n <rect x=\"540\" y=\"254\" width=\"14\" height=\"14\" rx=\"2\" fill=\"#17758C\"\/>\n <text x=\"564\" y=\"266\" font-family=\"Archivo,sans-serif\" font-weight=\"800\" font-size=\"17\" fill=\"#0E1A21\">Tier 3 \u00b7 Fibre & plants<\/text>\n <text x=\"564\" y=\"285\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#17758C\" letter-spacing=\"0.7\">CERTAINTY: MODERATE \u00b7 COHORT-WEIGHTED<\/text>\n <text x=\"564\" y=\"303\" font-family=\"Source Serif 4,serif\" font-size=\"13.5\" fill=\"#3D4C57\">25\u201329 g fibre, non-starchy veg, whole fruit, legumes.<\/text>\n <rect x=\"540\" y=\"166\" width=\"14\" height=\"14\" rx=\"2\" fill=\"#96600B\"\/>\n <text x=\"564\" y=\"178\" font-family=\"Archivo,sans-serif\" font-weight=\"800\" font-size=\"17\" fill=\"#0E1A21\">Tier 4 \u00b7 Carbohydrate dial<\/text>\n <text x=\"564\" y=\"197\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#96600B\" letter-spacing=\"0.7\">MECHANISM CERTAIN \u00b7 OPTIMUM INDIVIDUAL<\/text>\n <text x=\"564\" y=\"215\" font-family=\"Source Serif 4,serif\" font-size=\"13.5\" fill=\"#3D4C57\">No biochemical minimum. Grains, starchy veg, juice.<\/text>\n <rect x=\"540\" y=\"78\" width=\"14\" height=\"14\" rx=\"2\" fill=\"#A63525\"\/>\n <text x=\"564\" y=\"90\" font-family=\"Archivo,sans-serif\" font-weight=\"800\" font-size=\"17\" fill=\"#A63525\">Tier 5 \u00b7 Unresolved<\/text>\n <text x=\"564\" y=\"109\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#A63525\" letter-spacing=\"0.7\">CERTAINTY: LOW \u00b7 RCTs IN DIRECT CONFLICT<\/text>\n <text x=\"564\" y=\"127\" font-family=\"Source Serif 4,serif\" font-size=\"13.5\" fill=\"#3D4C57\">Saturated fat. Red meat. Salt. Eggs. Fish and CVD.<\/text>\n <\/g>\n <text x=\"60\" y=\"534\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#5C6B75\" letter-spacing=\"0.6\">WIDTH = EVIDENTIARY WEIGHT \u00b7 DEPTH OF COLOUR = CERTAINTY \u00b7 HEIGHT IS NOT SERVING SIZE<\/text>\n <text x=\"60\" y=\"554\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#5C6B75\" letter-spacing=\"0.6\">THE APEX IS SMALL ON PURPOSE: IT IS WHERE THE ARGUMENTS ARE, NOT WHERE THE EFFECT IS.<\/text>\n <\/svg>\n <div class=\"legend\">\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#093644\"><\/span>Established \u2014 RCT<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#115A72\"><\/span>Established \u2014 tracer \/ biochemistry<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#17758C\"><\/span>Moderate \u2014 cohort-weighted<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#96600B\"><\/span>Direction clear, optimum individual<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#F5E4E1;border:1.5px dashed #A63525\"><\/span>Contested \u2014 do not prescribe<\/div>\n <\/div>\n <\/div>\n<\/section>\n\n\n<section id=\"floors\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Figure 2 \u00b7 New diagram<\/span>\n <h2>What actually meets the obligate floors<\/h2>\n <p>Tier 2 is only useful if you know which foods discharge it. This matrix maps nine non-negotiable requirements against nine candidate foods. Read it column-wise to see how many floors a single food closes \u2014 the pattern is the point, and it is not the pattern the old pyramid implied.<\/p>\n <\/div>\n <div class=\"card reveal\">\n <svg viewBox=\"0 0 1000 520\" role=\"img\" aria-labelledby=\"fmt fmd\">\n <title id=\"fmt\">Matrix of nine obligate nutrient floors against nine foods<\/title>\n <desc id=\"fmd\">Oysters, liver and oily fish close the most floors. Poultry closes protein only. Dairy uniquely closes calcium. Legumes and leafy greens close almost none, and neither supplies vitamin B12.<\/desc>\n \n <g font-family=\"Archivo,sans-serif\" font-weight=\"700\" font-size=\"12.5\" fill=\"#0E1A21\">\n <text x=\"332\" y=\"88\" text-anchor=\"start\" transform=\"rotate(-42 332 88)\">Oysters<\/text>\n <text x=\"400\" y=\"88\" text-anchor=\"start\" transform=\"rotate(-42 400 88)\">Oily fish<\/text>\n <text x=\"468\" y=\"88\" text-anchor=\"start\" transform=\"rotate(-42 468 88)\">Liver<\/text>\n <text x=\"536\" y=\"88\" text-anchor=\"start\" transform=\"rotate(-42 536 88)\">Red meat<\/text>\n <text x=\"604\" y=\"88\" text-anchor=\"start\" transform=\"rotate(-42 604 88)\">Eggs<\/text>\n <text x=\"672\" y=\"88\" text-anchor=\"start\" transform=\"rotate(-42 672 88)\">Poultry<\/text>\n <text x=\"740\" y=\"88\" text-anchor=\"start\" transform=\"rotate(-42 740 88)\">Dairy<\/text>\n <text x=\"808\" y=\"88\" text-anchor=\"start\" transform=\"rotate(-42 808 88)\">Legumes<\/text>\n <text x=\"876\" y=\"88\" text-anchor=\"start\" transform=\"rotate(-42 876 88)\">Leafy greens<\/text>\n <\/g>\n \n <g font-family=\"Source Serif 4,serif\" font-size=\"14\" fill=\"#0E1A21\" text-anchor=\"end\">\n <text x=\"292\" y=\"112\">Protein quality<\/text>\n <text x=\"292\" y=\"152\">EPA + DHA<\/text>\n <text x=\"292\" y=\"192\">Vitamin B12<\/text>\n <text x=\"292\" y=\"232\">Bioavailable iron<\/text>\n <text x=\"292\" y=\"272\">Zinc<\/text>\n <text x=\"292\" y=\"312\">Choline<\/text>\n <text x=\"292\" y=\"352\">Iodine<\/text>\n <text x=\"292\" y=\"392\">Preformed retinol<\/text>\n <text x=\"292\" y=\"432\">Calcium<\/text>\n <\/g>\n <g class=\"reveal\">\n \n <rect x=\"304\" y=\"96\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#093644\"\/><rect x=\"372\" y=\"96\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#093644\"\/><rect x=\"440\" y=\"96\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#093644\"\/><rect x=\"508\" y=\"96\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#093644\"\/><rect x=\"576\" y=\"96\" 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stroke=\"#D5DDE2\"\/><rect x=\"848\" y=\"336\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#EDF1F3\" stroke=\"#D5DDE2\"\/>\n \n <rect x=\"304\" y=\"376\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#8FB8C6\"\/><rect x=\"372\" y=\"376\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#8FB8C6\"\/><rect x=\"440\" y=\"376\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#093644\"\/><rect x=\"508\" y=\"376\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#EDF1F3\" stroke=\"#D5DDE2\"\/><rect x=\"576\" y=\"376\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#115A72\"\/><rect x=\"644\" y=\"376\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#EDF1F3\" stroke=\"#D5DDE2\"\/><rect x=\"712\" y=\"376\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#8FB8C6\"\/><rect x=\"780\" y=\"376\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#EDF1F3\" stroke=\"#D5DDE2\"\/><rect x=\"848\" y=\"376\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#EDF1F3\" stroke=\"#D5DDE2\"\/>\n \n <rect x=\"304\" y=\"416\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#8FB8C6\"\/><rect x=\"372\" y=\"416\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#8FB8C6\"\/><rect x=\"440\" y=\"416\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#EDF1F3\" stroke=\"#D5DDE2\"\/><rect x=\"508\" y=\"416\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#EDF1F3\" stroke=\"#D5DDE2\"\/><rect x=\"576\" y=\"416\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#EDF1F3\" stroke=\"#D5DDE2\"\/><rect x=\"644\" y=\"416\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#EDF1F3\" stroke=\"#D5DDE2\"\/><rect x=\"712\" y=\"416\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#093644\"\/><rect x=\"780\" y=\"416\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#8FB8C6\"\/><rect x=\"848\" y=\"416\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#8FB8C6\"\/>\n <\/g>\n \n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"11\" font-weight=\"600\" text-anchor=\"middle\">\n <text x=\"334\" y=\"470\" fill=\"#093644\">8 \/ 9<\/text><text x=\"402\" y=\"470\" fill=\"#093644\">7 \/ 9<\/text>\n <text x=\"470\" y=\"470\" fill=\"#093644\">7 \/ 9<\/text><text x=\"538\" y=\"470\" fill=\"#115A72\">5 \/ 9<\/text>\n <text x=\"606\" y=\"470\" fill=\"#115A72\">6 \/ 9<\/text><text x=\"674\" y=\"470\" fill=\"#96600B\">2 \/ 9<\/text>\n <text x=\"742\" y=\"470\" fill=\"#115A72\">4 \/ 9<\/text><text x=\"810\" y=\"470\" fill=\"#96600B\">0 \/ 9<\/text>\n <text x=\"876\" y=\"470\" fill=\"#A63525\">0 \/ 9<\/text>\n <\/g>\n <text x=\"292\" y=\"470\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\" text-anchor=\"end\">FLOORS FULLY CLOSED<\/text>\n <text x=\"60\" y=\"502\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">PROVITAMIN A CAROTENOIDS IN GREENS ARE NOT PREFORMED RETINOL \u00b7 BCO1 VARIANTS LIMIT CONVERSION IN A LARGE MINORITY<\/text>\n <\/svg>\n <div class=\"legend\">\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#093644\"><\/span>Outstanding source<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#115A72\"><\/span>Good source<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#8FB8C6\"><\/span>Modest or poorly absorbed<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#EDF1F3;border:1px solid #D5DDE2\"><\/span>Negligible or absent<\/div>\n <\/div>\n <p class=\"figcap\"><b>The three findings that matter here.<\/b> First, a small number of foods \u2014 shellfish, liver, oily fish \u2014 close almost every floor at once, which is a stronger and more defensible claim than the cardiovascular one usually made for them. Second, <b>poultry closes only the protein floor<\/b>: substituting it for red meat keeps the macronutrient and quietly opens the iron, zinc and B12 gaps. Third, <b>legumes and leafy greens close none of these floors outright<\/b> \u2014 which is not an argument against eating them, because their job is Tier 3, but it is an argument against treating them as a substitute for Tier 2. Ratings are qualitative judgements from composition data and absorption literature; <b>verify per species and cut.<\/b><\/p>\n <\/div>\n<\/section>\n\n\n<section id=\"protein\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Figure 3 \u00b7 Redrawn and expanded<\/span>\n <h2>Protein quality is not a rhetorical point \u2014 it is a digestibility score<\/h2>\n <p>DIAAS measures true ileal digestibility of each indispensable amino acid against a reference pattern. A score of 100 means the food alone satisfies the pattern; below 100 means it is limited by a specific amino acid and must be combined with a complementary source or eaten in greater quantity. Every food discussed in this document is ranked below, so the question \"which should be on top to meet the minimum protein requirement\" has a direct answer.<\/p>\n <\/div>\n <div class=\"card reveal\">\n <h4>DIAAS, every food ranked<\/h4>\n <p class=\"sub\">Approximate \u00b7 FAO reference pattern \u00b7 100 = reference pattern satisfied by that food alone<\/p>\n <svg viewBox=\"0 0 1000 640\" role=\"img\" aria-labelledby=\"dt dd2\">\n <title id=\"dt\">DIAAS protein quality scores for twenty foods, ranked<\/title>\n <desc id=\"dd2\">Whey, casein, milk, egg, beef, pork, poultry and fish all score at or above 100. Soy isolate 90, chickpeas 83, pea protein 73. Quinoa, rice, beans, lentils and oats fall between 54 and 60. Wheat 45, peanuts 43, almonds 40, corn 36.<\/desc>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#5C6B75\">\n <g stroke=\"#E7EDF0\" stroke-width=\"1\">\n <line x1=\"506\" y1=\"28\" x2=\"506\" y2=\"556\"\/><line x1=\"998\" y1=\"28\" x2=\"998\" y2=\"556\"\/>\n <\/g>\n <line x1=\"260\" y1=\"556\" x2=\"998\" y2=\"556\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <text x=\"260\" y=\"574\" text-anchor=\"middle\">0<\/text>\n <text x=\"506\" y=\"574\" text-anchor=\"middle\">50<\/text>\n <text x=\"752\" y=\"574\" text-anchor=\"middle\">100<\/text>\n <\/g>\n <line x1=\"752\" y1=\"20\" x2=\"752\" y2=\"556\" stroke=\"#0E1A21\" stroke-width=\"2\"\/>\n <text x=\"758\" y=\"18\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#0E1A21\">REFERENCE PATTERN MET \u2192<\/text>\n <g class=\"wipe\">\n <rect x=\"260\" y=\"32\" width=\"615\" height=\"18\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"260\" y=\"58\" width=\"581\" height=\"18\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"260\" y=\"84\" width=\"561\" height=\"18\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"260\" y=\"110\" width=\"556\" height=\"18\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"260\" y=\"136\" width=\"547\" height=\"18\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"260\" y=\"162\" width=\"542\" height=\"18\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"260\" y=\"188\" width=\"532\" height=\"18\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"260\" y=\"214\" width=\"517\" height=\"18\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"260\" y=\"240\" width=\"443\" height=\"18\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"260\" y=\"266\" width=\"409\" height=\"18\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"260\" y=\"292\" width=\"359\" height=\"18\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"260\" y=\"318\" width=\"295\" height=\"18\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"260\" y=\"344\" width=\"295\" height=\"18\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"260\" y=\"370\" width=\"286\" height=\"18\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"260\" y=\"396\" width=\"271\" height=\"18\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"260\" y=\"422\" width=\"266\" height=\"18\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"260\" y=\"448\" width=\"222\" height=\"18\" rx=\"1\" fill=\"#A63525\"\/>\n <rect x=\"260\" y=\"474\" width=\"212\" height=\"18\" rx=\"1\" fill=\"#A63525\"\/>\n <rect x=\"260\" y=\"500\" width=\"197\" height=\"18\" rx=\"1\" fill=\"#A63525\"\/>\n <rect x=\"260\" y=\"526\" width=\"177\" height=\"18\" rx=\"1\" fill=\"#A63525\"\/>\n <\/g>\n <g font-family=\"Source Serif 4,serif\" font-size=\"14\" fill=\"#0E1A21\" text-anchor=\"end\">\n <text x=\"250\" y=\"46\">Whey protein isolate<\/text>\n <text x=\"250\" y=\"72\">Casein<\/text>\n <text x=\"250\" y=\"98\">Milk<\/text>\n <text x=\"250\" y=\"124\">Whole egg<\/text>\n <text x=\"250\" y=\"150\">Beef<\/text>\n <text x=\"250\" y=\"176\">Pork<\/text>\n <text x=\"250\" y=\"202\">Chicken and turkey<\/text>\n <text x=\"250\" y=\"228\">Fish<\/text>\n <text x=\"250\" y=\"254\">Soy protein isolate<\/text>\n <text x=\"250\" y=\"280\">Chickpeas<\/text>\n <text x=\"250\" y=\"306\">Pea protein<\/text>\n <text x=\"250\" y=\"332\">Quinoa<\/text>\n <text x=\"250\" y=\"358\">Rice<\/text>\n <text x=\"250\" y=\"384\">Kidney beans<\/text>\n <text x=\"250\" y=\"410\">Lentils<\/text>\n <text x=\"250\" y=\"436\">Oats<\/text>\n <text x=\"250\" y=\"462\">Wheat<\/text>\n <text x=\"250\" y=\"488\">Peanuts<\/text>\n <text x=\"250\" y=\"514\">Almonds<\/text>\n <text x=\"250\" y=\"540\">Corn \/ maize<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"11\" fill=\"#3D4C57\">\n <text x=\"883\" y=\"46\">125<\/text><text x=\"849\" y=\"72\">118<\/text><text x=\"829\" y=\"98\">114<\/text><text x=\"824\" y=\"124\">113<\/text>\n <text x=\"815\" y=\"150\">111<\/text><text x=\"810\" y=\"176\">110<\/text><text x=\"800\" y=\"202\">108<\/text><text x=\"785\" y=\"228\">105<\/text>\n <text x=\"711\" y=\"254\">90<\/text><text x=\"677\" y=\"280\">83<\/text><text x=\"627\" y=\"306\">73<\/text><text x=\"563\" y=\"332\">60<\/text>\n <text x=\"563\" y=\"358\">60<\/text><text x=\"554\" y=\"384\">58<\/text><text x=\"539\" y=\"410\">55<\/text><text x=\"534\" y=\"436\">54<\/text>\n <text x=\"490\" y=\"462\">45<\/text><text x=\"480\" y=\"488\">43<\/text><text x=\"465\" y=\"514\">40<\/text><text x=\"445\" y=\"540\">36<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <text x=\"260\" y=\"600\">LIMITING AMINO ACID \u00b7 GRAINS AND NUTS: LYSINE \u00b7 LEGUMES AND PEA: METHIONINE AND CYSTEINE \u00b7 COMBINING THE TWO RAISES THE SCORE; PROCESSING DOES NOT CLOSE IT<\/text>\n <text x=\"260\" y=\"620\">TO MEET THE FLOOR ON A SINGLE FOOD, ANYTHING ABOVE THE LINE WORKS. BELOW IT, TOTAL INTAKE MUST RISE TO COMPENSATE.<\/text>\n <\/g>\n <\/svg>\n <div class=\"legend\">\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#093644\"><\/span>Dairy and egg \u2014 highest<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#115A72\"><\/span>Meat, poultry, fish<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#96600B\"><\/span>Legumes and soy<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#A63525\"><\/span>Grains and nuts \u2014 lowest<\/div>\n <\/div>\n <p class=\"figcap\"><b>These are the least reliable decimals in the document.<\/b> DIAAS varies substantially with processing, cooking, and whether the child or adult reference pattern is used; published values for the same food differ between sources, and fish values in particular are less commonly reported than dairy or meat. Compilations: Herreman 2020 (Food Sci Nutr); Marinangeli & House 2017 (Nutr Rev). <b>Reconfirm any single value before quoting it.<\/b><\/p>\n <\/div>\n<\/section>\n\n\n<section id=\"classify\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Figure 4 \u00b7 Classification<\/span>\n <h2>Macronutrient or micronutrient? The arithmetic settles it<\/h2>\n <p>Whether a food is a macronutrient or micronutrient source is measurable, not interpretive. The clearest test is to ask how much of each you would need to eat to hit one fixed protein target.<\/p>\n <\/div>\n <div class=\"card reveal\">\n <h4>Grams of food required to reach 30 g of protein<\/h4>\n <p class=\"sub\">One per-meal protein target \u00b7 approximate cooked weights<\/p>\n <svg viewBox=\"0 0 900 430\" role=\"img\" aria-label=\"Bar chart of grams of food needed for 30 grams of protein: chicken 97, beef 107, salmon 120, tofu 190, eggs 240, lentils 330, spinach 1030, broccoli 1070.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#5C6B75\">\n <g stroke=\"#E7EDF0\" stroke-width=\"1\">\n <line x1=\"380\" y1=\"24\" x2=\"380\" y2=\"360\"\/><line x1=\"550\" y1=\"24\" x2=\"550\" y2=\"360\"\/><line x1=\"720\" y1=\"24\" x2=\"720\" y2=\"360\"\/>\n <\/g>\n <line x1=\"210\" y1=\"360\" x2=\"870\" y2=\"360\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <text x=\"210\" y=\"378\" text-anchor=\"middle\">0<\/text><text x=\"380\" y=\"378\" text-anchor=\"middle\">300 g<\/text>\n <text x=\"550\" y=\"378\" text-anchor=\"middle\">600 g<\/text><text x=\"720\" y=\"378\" text-anchor=\"middle\">900 g<\/text>\n <\/g>\n <g class=\"wipe\">\n <rect x=\"210\" y=\"30\" width=\"55\" height=\"24\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"210\" y=\"66\" width=\"60\" height=\"24\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"210\" y=\"102\" width=\"68\" height=\"24\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"210\" y=\"138\" width=\"107\" height=\"24\" rx=\"1\" fill=\"#17758C\"\/>\n <rect x=\"210\" y=\"174\" width=\"136\" height=\"24\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"210\" y=\"210\" width=\"186\" height=\"24\" rx=\"1\" fill=\"#17758C\"\/>\n <rect x=\"210\" y=\"246\" width=\"582\" height=\"24\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"210\" y=\"282\" width=\"605\" height=\"24\" rx=\"1\" fill=\"#96600B\"\/>\n <\/g>\n <g font-family=\"Source Serif 4,serif\" font-size=\"14.5\" fill=\"#0E1A21\" text-anchor=\"end\">\n <text x=\"198\" y=\"47\">Chicken breast<\/text><text x=\"198\" y=\"83\">Beef<\/text><text x=\"198\" y=\"119\">Salmon<\/text>\n <text x=\"198\" y=\"155\">Tofu<\/text><text x=\"198\" y=\"191\">Eggs<\/text><text x=\"198\" y=\"227\">Lentils, cooked<\/text>\n <text x=\"198\" y=\"263\">Spinach<\/text><text x=\"198\" y=\"299\">Broccoli<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"11.5\" fill=\"#3D4C57\">\n <text x=\"273\" y=\"47\">\u224897 g<\/text><text x=\"278\" y=\"83\">\u2248107 g<\/text><text x=\"286\" y=\"119\">\u2248120 g<\/text>\n <text x=\"325\" y=\"155\">\u2248190 g<\/text><text x=\"354\" y=\"191\">\u2248240 g<\/text><text x=\"404\" y=\"227\">\u2248330 g<\/text>\n <text x=\"800\" y=\"263\" font-weight=\"600\" fill=\"#96600B\">\u22481,030 g<\/text>\n <text x=\"823\" y=\"299\" font-weight=\"600\" fill=\"#96600B\">\u22481,070 g<\/text>\n <\/g>\n <g class=\"reveal\">\n <line x1=\"210\" y1=\"404\" x2=\"870\" y2=\"404\" stroke=\"#E7EDF0\" stroke-width=\"1\"\/>\n <text x=\"210\" y=\"422\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#5C6B75\">ELEVEN TIMES THE MASS \u2014 AND STILL NO B12, LITTLE BIOAVAILABLE IRON OR ZINC<\/text>\n <\/g>\n <\/svg>\n <p class=\"figcap\"><b>This is the answer to the macro\/micro question.<\/b> Non-starchy vegetables cannot function as macronutrient sources at any intake a person will actually achieve. That is not a criticism \u2014 it is a statement about which job they do.<\/p>\n <\/div>\n\n <div class=\"tablewrap reveal\" style=\"margin-top:1.75rem\">\n <table>\n <thead><tr><th scope=\"col\">Food category<\/th><th scope=\"col\">Macronutrient role<\/th><th scope=\"col\">Signature micronutrients<\/th><th scope=\"col\">Classification<\/th><th scope=\"col\">Tier<\/th><\/tr><\/thead>\n <tbody>\n <tr><td class=\"claim\">Oily fish<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">salmon, mackerel, sardines<\/span><\/td>\n <td class=\"who\">Complete protein, high DIAAS. The fat is the point: preformed EPA and DHA.<\/td>\n <td class=\"who\">EPA\/DHA, vitamin D, B12, selenium, iodine<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#093644\">BOTH \u2014 strongly<\/span> The only common food that is both a protein source and the practical solution to several micronutrient floors.<\/td>\n <td><span class=\"tag\" style=\"background:#115A72\">TIER 2<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Shellfish<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">oysters, mussels, clams<\/span><\/td>\n <td class=\"who\">Complete protein, low fat, low energy density.<\/td>\n <td class=\"who\">Zinc (extreme), B12 (extreme), iron, selenium, iodine<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#093644\">MICRO \u2014 outlier<\/span> The most micronutrient-dense foods in the human diet per calorie.<\/td>\n <td><span class=\"tag\" style=\"background:#115A72\">TIER 2<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Organ meat<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">liver<\/span><\/td>\n <td class=\"who\">Complete protein, moderate fat.<\/td>\n <td class=\"who\">Preformed retinol, B12, folate, copper, iron, choline<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#093644\">MICRO \u2014 outlier<\/span> Closes retinol and copper floors nothing else reaches. Vitamin A toxicity is a real ceiling \u2014 do not eat daily.<\/td>\n <td><span class=\"tag\" style=\"background:#115A72\">TIER 2<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Lean white fish<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">cod, haddock, tilapia<\/span><\/td>\n <td class=\"who\">Very high protein per calorie, minimal fat.<\/td>\n <td class=\"who\">Iodine (cod, very high), selenium, B12 \u2014 little EPA\/DHA<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#115A72\">MACRO-leaning<\/span> Excellent protein, but not the omega-3 vehicle oily fish is.<\/td>\n <td><span class=\"tag\" style=\"background:#115A72\">TIER 2<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Red meat<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">beef, lamb<\/span><\/td>\n <td class=\"who\">Complete protein, high DIAAS, variable fat.<\/td>\n <td class=\"who\">Heme iron, zinc, B12, creatine, carnitine<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#115A72\">BOTH<\/span> The most efficient iron and zinc vehicle in ordinary diets. Outcome questions sit at the apex.<\/td>\n <td><span class=\"tag\" style=\"background:#115A72\">TIER 2<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Poultry<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">chicken, turkey<\/span><\/td>\n <td class=\"who\">Among the most efficient protein-per-calorie foods. ~31 g\/100 g cooked breast.<\/td>\n <td class=\"who\">Niacin, B6, selenium, phosphorus, choline<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#115A72\">MACRO \u2014 chiefly<\/span> Iron, zinc and B12 run 3\u20138\u00d7 lower than red meat. A protein instrument, not a micronutrient one.<\/td>\n <td><span class=\"tag\" style=\"background:#115A72\">TIER 2<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Eggs and dairy<\/td>\n <td class=\"who\">Complete protein, highest DIAAS scores of any food.<\/td>\n <td class=\"who\">Choline (eggs), calcium and iodine (dairy), B12, retinol<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#115A72\">BOTH<\/span> Dairy is the only category that closes the calcium floor without supplementation.<\/td>\n <td><span class=\"tag\" style=\"background:#115A72\">TIER 2<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Legumes<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">lentils, beans, chickpeas<\/span><\/td>\n <td class=\"who\">Meaningful protein but DIAAS 55\u201383, plus substantial carbohydrate and fibre.<\/td>\n <td class=\"who\">Folate, potassium, magnesium, non-heme iron (phytate-inhibited)<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#17758C\">MIXED<\/span> The strongest plant protein after soy, and a genuine fibre vehicle. Not a Tier 2 substitute on its own.<\/td>\n <td><span class=\"tag\" style=\"background:#17758C\">TIER 3<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Non-starchy vegetables<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">broccoli, spinach, kale<\/span><\/td>\n <td class=\"who\">Negligible. ~2\u20133 g protein and under 40 kcal per 100 g.<\/td>\n <td class=\"who\">Vitamin C, K1, folate, potassium, carotenoids, nitrate, polyphenols, fibre<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#17758C\">MICRO \u2014 almost purely<\/span> Plus fibre, water and volume. No B12, little bioavailable iron or zinc.<\/td>\n <td><span class=\"tag\" style=\"background:#17758C\">TIER 3<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Whole fruit<\/td>\n <td class=\"who\">Sugar and water. Minimal protein or fat.<\/td>\n <td class=\"who\">Vitamin C, potassium, folate, anthocyanins, fibre<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#17758C\">MICRO + fibre<\/span> The whole-fruit versus juice divergence is among the better-replicated findings in the field.<\/td>\n <td><span class=\"tag\" style=\"background:#17758C\">TIER 3<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Starchy vegetables and grains<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">potato, cassava, wheat, rice<\/span><\/td>\n <td class=\"who\">Genuinely a carbohydrate staple. ~17 g carbohydrate per 100 g potato.<\/td>\n <td class=\"who\">Potassium, some B vitamins; whole grains add fibre and magnesium<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#96600B\">MACRO \u2014 carbohydrate<\/span> Grouping potatoes with broccoli obscures the only thing that matters about them nutritionally.<\/td>\n <td><span class=\"tag\" style=\"background:#96600B\">TIER 4<\/span><\/td><\/tr>\n <\/tbody>\n <\/table>\n <\/div>\n <p class=\"figcap\"><b>Reading the table.<\/b> \"Both\" is rare. Most foods do one job well, and the old pyramid's error was arranging categories that mix jobs rather than categories that share one.<\/p>\n<\/section>\n\n\n<section id=\"form\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Tier 1 \u00b7 The base<\/span>\n <h2>Food form beats food ratio<\/h2>\n <p>The most reproducible causal finding of the last decade is not about macronutrients at all. Hold macros constant, change only the degree of processing, and intake shifts by roughly 500 kcal per day.<\/p>\n <\/div>\n <div class=\"split\">\n <ul class=\"findings\">\n <li><span class=\"pill p-rct\">RCT \u00b7 inpatient<\/span>Ultra-processed versus matched unprocessed diet: <span class=\"val\">+508 kcal\/day<\/span> ad libitum intake and weight gain, with protein, fat, carbohydrate, sugar, sodium and fibre matched between arms. <span class=\"src\">Hall et al. 2019 \u00b7 Cell Metabolism \u00b7 n=20 \u00b7 crossover, fully controlled metabolic ward<\/span><\/li>\n <li><span class=\"pill p-cohort\">Cohort meta<\/span>Industrial trans fat associated with higher all-cause mortality and coronary disease \u2014 roughly <span class=\"val\">21\u201334%<\/span> higher CHD risk \u2014 while saturated fat in the same analysis showed no significant association. <span class=\"src\">de Souza et al. 2015 \u00b7 BMJ \u00b7 systematic review<\/span><\/li>\n <li><span class=\"pill p-mech\">Mechanism<\/span>Energy density, eating rate and reduced satiety per calorie are the leading candidate mediators. The specific mechanism is not settled.<\/li>\n <li><span class=\"pill p-rct\">Policy<\/span>Industrial trans fat is the clearest-cut harmful fat in nutrition science and is being eliminated globally under WHO REPLACE. <b>Ruminant trans fat is a separate question<\/b> and is not clearly associated with harm at usual intakes.<\/li>\n <\/ul>\n <div class=\"card\">\n <h4>Same macros. Different food. 500 kcal.<\/h4>\n <p class=\"sub\">Hall 2019 \u00b7 ad libitum energy intake, kcal\/day<\/p>\n <svg viewBox=\"0 0 420 265\" role=\"img\" aria-label=\"Bar chart: unprocessed diet about 2500 kcal per day versus ultra-processed about 3000, a difference of 508.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <line x1=\"58\" y1=\"200\" x2=\"400\" y2=\"200\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <line x1=\"58\" y1=\"30\" x2=\"58\" y2=\"200\" stroke=\"#E7EDF0\" stroke-width=\"1\"\/>\n <text x=\"52\" y=\"204\" text-anchor=\"end\">0<\/text><text x=\"52\" y=\"120\" text-anchor=\"end\">1500<\/text><text x=\"52\" y=\"36\" text-anchor=\"end\">3000<\/text>\n <\/g>\n <g class=\"grow\">\n <rect x=\"110\" y=\"60\" width=\"82\" height=\"140\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"250\" y=\"30\" width=\"82\" height=\"170\" rx=\"1\" fill=\"#A63525\"\/>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" letter-spacing=\"0.5\">\n <text x=\"151\" y=\"220\" text-anchor=\"middle\" fill=\"#115A72\">UNPROCESSED<\/text>\n <text x=\"151\" y=\"234\" text-anchor=\"middle\" fill=\"#5C6B75\">\u22482500<\/text>\n <text x=\"291\" y=\"220\" text-anchor=\"middle\" fill=\"#A63525\">ULTRA-PROCESSED<\/text>\n <text x=\"291\" y=\"234\" text-anchor=\"middle\" fill=\"#5C6B75\">\u22483000<\/text>\n <\/g>\n <g class=\"reveal\">\n <line x1=\"205\" y1=\"46\" x2=\"237\" y2=\"46\" stroke=\"#0E1A21\" stroke-width=\"1\"\/>\n <text x=\"221\" y=\"40\" text-anchor=\"middle\" font-family=\"Archivo,sans-serif\" font-weight=\"800\" font-size=\"15\" fill=\"#0E1A21\">+508<\/text>\n <\/g>\n <\/svg>\n <p class=\"figcap\">Bar heights drawn to the reported ~500 kcal difference; absolute intakes approximate. <b>Verify before citing.<\/b><\/p>\n <\/div>\n <\/div>\n<\/section>\n\n\n<section id=\"tier2\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Tier 2 \u00b7 Obligate floors<\/span>\n <h2>The protein RDA is a measurement artifact<\/h2>\n <p>0.8 g\/kg\/day derives from nitrogen balance, a method that under-captures losses and extrapolates linearly. Isotope tracer studies using indicator amino acid oxidation put the safe intake near 1.2 g\/kg\/day, and find older adults need at least as much as the young \u2014 not less.<\/p>\n <\/div>\n <div class=\"split\">\n <ul class=\"findings\">\n <li><span class=\"pill p-mech\">Tracer \u00b7 crossover<\/span>IAAO in young men: mean requirement <span class=\"val\">0.93<\/span>, population-safe <span class=\"val\">1.2 g\/kg\/d<\/span> \u2014 roughly 50% above the official RDA. <span class=\"src\">Humayun et al. 2007 \u00b7 Am J Clin Nutr \u00b7 foundational, repeatedly replicated<\/span><\/li>\n <li><span class=\"pill p-mech\">Tracer<\/span>Older adults: EAR \u2248 <span class=\"val\">0.94\u20130.96<\/span>, RDA \u2248 <span class=\"val\">1.24\u20131.29 g\/kg\/d<\/span>, contradicting the assumption that requirement falls with age. <span class=\"src\">Rafii et al. 2015 (men), 2016 (women) \u00b7 J Nutr<\/span><\/li>\n <li><span class=\"pill p-rct\">RCT meta<\/span>Muscle benefit plateaus at <span class=\"val\">1.62 g\/kg\/d<\/span> (95% CI 1.03\u20132.20). Above the upper interval, additional protein buys little. <span class=\"src\">Morton et al. 2018 \u00b7 Br J Sports Med \u00b7 49 studies, n=1863<\/span><\/li>\n <li><span class=\"pill p-mech\">Distribution<\/span>A per-meal threshold of roughly <span class=\"val\">2.5\u20133 g leucine<\/span> (about 25\u201330 g high-quality protein) maximises muscle protein synthesis, with a higher threshold in older adults \u2014 the phenomenon called anabolic resistance.<\/li>\n <li><span class=\"pill p-mech\">Interaction<\/span>Very-low-carbohydrate intake <b>raises protein requirements<\/b>, because amino acids are diverted to gluconeogenesis. One argument for sitting at the upper end of the range on a ketogenic diet.<\/li>\n <li><span class=\"pill p-cohort\">Shortfall<\/span>Choline: roughly <span class=\"val\">90.7%<\/span> of US adults fall below the Adequate Intake. Concentrated in eggs, liver and meat. <span class=\"src\">Wallace & Fulgoni 2017 \u00b7 Nutrients<\/span><\/li>\n <li><span class=\"pill p-mech\">Bioavailability<\/span>B12 requires animal sources. Heme iron absorbs far better than phytate-inhibited non-heme iron. Zinc absorption falls as the phytate-to-zinc molar ratio rises. ALA to DHA conversion runs <span class=\"val\">under 1%<\/span>. <b>BCO1 variants<\/b> substantially reduce beta-carotene to retinol conversion in a large minority.<\/li>\n <\/ul>\n <div class=\"card\">\n <h4>Four numbers, one nutrient<\/h4>\n <p class=\"sub\">Protein intake targets \u00b7 g\/kg body weight\/day<\/p>\n <svg viewBox=\"0 0 420 352\" role=\"img\" aria-label=\"Range chart: official RDA 0.8, IAAO safe intake 1.2, adults over 65 1.0 to 1.2, illness 1.2 to 1.5, resistance training 1.4 to 2.0 with plateau at 1.62.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#5C6B75\">\n <line x1=\"70\" y1=\"300\" x2=\"400\" y2=\"300\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <g stroke=\"#E7EDF0\" stroke-width=\"1\"><line x1=\"70\" y1=\"26\" x2=\"70\" y2=\"300\"\/><line x1=\"220\" y1=\"26\" x2=\"220\" y2=\"300\"\/><line x1=\"370\" y1=\"26\" x2=\"370\" y2=\"300\"\/><\/g>\n <text x=\"70\" y=\"314\" text-anchor=\"middle\">0<\/text><text x=\"220\" y=\"314\" text-anchor=\"middle\">1.0<\/text><text x=\"370\" y=\"314\" text-anchor=\"middle\">2.0<\/text>\n <text x=\"235\" y=\"338\" text-anchor=\"middle\" letter-spacing=\"0.6\">g PROTEIN \/ kg BODY WEIGHT \/ DAY<\/text>\n <\/g>\n <g class=\"reveal\">\n <line x1=\"313\" y1=\"26\" x2=\"313\" y2=\"300\" stroke=\"#A63525\" stroke-width=\"1.2\" stroke-dasharray=\"4 3\"\/>\n <text x=\"309\" y=\"22\" text-anchor=\"end\" font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#A63525\">1.62 PLATEAU<\/text>\n <\/g>\n <g class=\"wipe\">\n <rect x=\"70\" y=\"40\" width=\"120\" height=\"18\" rx=\"1\" fill=\"#D5DDE2\" stroke=\"#5C6B75\" stroke-width=\"1\"\/>\n <rect x=\"70\" y=\"92\" width=\"180\" height=\"18\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"220\" y=\"144\" width=\"30\" height=\"18\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"250\" y=\"196\" width=\"45\" height=\"18\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"280\" y=\"248\" width=\"90\" height=\"18\" rx=\"1\" fill=\"#17758C\"\/>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#0E1A21\">\n <text x=\"70\" y=\"35\">0.8 \u00b7 OFFICIAL RDA \u2014 NITROGEN BALANCE<\/text>\n <text x=\"70\" y=\"87\" fill=\"#115A72\">1.2 \u00b7 IAAO SAFE INTAKE<\/text>\n <text x=\"70\" y=\"139\">1.0\u20131.2 \u00b7 ADULTS 65+<\/text>\n <text x=\"70\" y=\"191\">1.2\u20131.5 \u00b7 ILLNESS<\/text>\n <text x=\"70\" y=\"243\">1.4\u20132.0 \u00b7 RESISTANCE TRAINING<\/text>\n <\/g>\n <\/svg>\n <p class=\"figcap\">The grey bar is the current official figure. Everything beyond it is post-2007 tracer and RCT literature. <b>Higher protein does not harm healthy kidneys or bone<\/b> \u2014 see the misconceptions section.<\/p>\n <\/div>\n <\/div>\n<\/section>\n\n\n<section id=\"carbs\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Tier 4 \u00b7 Deep analysis<\/span>\n <h2>The carbohydrate minimum, quantified<\/h2>\n <p>This is the most misunderstood number in nutrition, in both directions. Carbohydrate is not biochemically essential \u2014 but \"not essential\" is not the same as \"no floor\". There is a real physiological glucose demand, it is quantifiable, and it changes dramatically with metabolic state and life stage.<\/p>\n <\/div>\n\n <div class=\"card reveal\">\n <h4>The daily glucose budget, and who supplies it<\/h4>\n <p class=\"sub\">Grams of glucose per day \u00b7 fed state versus full ketoadaptation<\/p>\n <svg viewBox=\"0 0 960 340\" role=\"img\" aria-labelledby=\"gbt gbd\">\n <title id=\"gbt\">Daily glucose demand in the non-ketoadapted and ketoadapted states<\/title>\n <desc id=\"gbd\">Non-ketoadapted: brain about 120 grams plus obligate tissues about 40 grams, totalling about 160 grams. Ketoadapted: brain falls to about 40 grams, obligate tissues unchanged at 40, totalling about 80 grams, which gluconeogenesis can supply without any dietary carbohydrate.<\/desc>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#5C6B75\">\n <line x1=\"240\" y1=\"230\" x2=\"900\" y2=\"230\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <g stroke=\"#E7EDF0\" stroke-width=\"1\">\n <line x1=\"418\" y1=\"40\" x2=\"418\" y2=\"230\"\/><line x1=\"595\" y1=\"40\" x2=\"595\" y2=\"230\"\/><line x1=\"773\" y1=\"40\" x2=\"773\" y2=\"230\"\/>\n <\/g>\n <text x=\"240\" y=\"248\" text-anchor=\"middle\">0<\/text><text x=\"418\" y=\"248\" text-anchor=\"middle\">50 g<\/text>\n <text x=\"595\" y=\"248\" text-anchor=\"middle\">100 g<\/text><text x=\"773\" y=\"248\" text-anchor=\"middle\">150 g<\/text>\n <text x=\"570\" y=\"272\" text-anchor=\"middle\" letter-spacing=\"0.6\">GRAMS OF GLUCOSE OXIDISED PER DAY<\/text>\n <\/g>\n \n <line x1=\"702\" y1=\"34\" x2=\"702\" y2=\"230\" stroke=\"#96600B\" stroke-width=\"2\" stroke-dasharray=\"5 3\"\/>\n <text x=\"708\" y=\"32\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#96600B\">130 g \u00b7 OFFICIAL RDA<\/text>\n <g class=\"wipe\">\n \n <rect x=\"240\" y=\"66\" width=\"427\" height=\"38\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"667\" y=\"66\" width=\"142\" height=\"38\" rx=\"1\" fill=\"#093644\"\/>\n \n <rect x=\"240\" y=\"140\" width=\"142\" height=\"38\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"382\" y=\"140\" width=\"142\" height=\"38\" rx=\"1\" fill=\"#093644\"\/>\n <\/g>\n <g font-family=\"Archivo,sans-serif\" font-weight=\"700\" font-size=\"12.5\" fill=\"#fff\">\n <text x=\"452\" y=\"90\" text-anchor=\"middle\">BRAIN \u2248120 g<\/text>\n <text x=\"738\" y=\"90\" text-anchor=\"middle\">OBLIGATE \u224840 g<\/text>\n <text x=\"311\" y=\"164\" text-anchor=\"middle\">BRAIN \u224840 g<\/text>\n <text x=\"453\" y=\"164\" text-anchor=\"middle\">OBLIGATE \u224840 g<\/text>\n <\/g>\n <g font-family=\"Source Serif 4,serif\" font-size=\"14.5\" fill=\"#0E1A21\" text-anchor=\"end\">\n <text x=\"228\" y=\"80\">Non-ketoadapted<\/text>\n <text x=\"228\" y=\"154\">Fully ketoadapted<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\" text-anchor=\"end\">\n <text x=\"228\" y=\"96\">GLUCOSE-FUELLED BRAIN<\/text>\n <text x=\"228\" y=\"170\">KETONES SUPPLY 60\u201370%<\/text>\n <\/g>\n <g class=\"reveal\">\n <line x1=\"240\" y1=\"196\" x2=\"524\" y2=\"196\" stroke=\"#093644\" stroke-width=\"2\"\/>\n <line x1=\"240\" y1=\"190\" x2=\"240\" y2=\"202\" stroke=\"#093644\" stroke-width=\"2\"\/>\n <line x1=\"524\" y1=\"190\" x2=\"524\" y2=\"202\" stroke=\"#093644\" stroke-width=\"2\"\/>\n <text x=\"532\" y=\"200\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#093644\">GLUCONEOGENESIS COVERS THIS ENTIRELY \u2014 NO DIETARY CARBOHYDRATE REQUIRED<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <text x=\"240\" y=\"300\">OBLIGATE = ERYTHROCYTES (NO MITOCHONDRIA), RENAL MEDULLA, LENS AND CORNEA \u2014 TISSUES THAT CANNOT USE KETONES AT ALL<\/text>\n <text x=\"240\" y=\"318\">GLUCONEOGENIC SUBSTRATES: LACTATE VIA THE CORI CYCLE, GLYCEROL FROM TRIGLYCERIDE (\u224815\u201320 g\/DAY), AND GLUCOGENIC AMINO ACIDS<\/text>\n <\/g>\n <\/svg>\n <p class=\"figcap\"><b>Why the RDA is 130 g and why that is not a requirement.<\/b> The IOM set the carbohydrate EAR at about 120 g\/day from <i>average minimum brain glucose utilisation<\/i> in the fed state, then the RDA at 130 g. The same report states that the lower limit of dietary carbohydrate compatible with life is <b>essentially zero, provided adequate protein and fat are consumed.<\/b> Both readings are honest: nothing is biochemically essential, and 130 g is the amount that lets the brain run on glucose alone <i>without metabolic adaptation<\/i>. Owen and Cahill's starvation-physiology work established the ketone shift; Cunnane's imaging work shows brain ketone uptake rises in proportion to blood ketone concentration. <b>Verify the DRI wording in the 2005 report, Chapter 6.<\/b><\/p>\n <\/div>\n\n <h3 class=\"sub-h\">Population floors \u2014 where a real carbohydrate requirement appears<\/h3>\n <div class=\"tablewrap reveal\">\n <table>\n <thead><tr><th scope=\"col\">Population<\/th><th scope=\"col\">Recommended carbohydrate<\/th><th scope=\"col\">Basis<\/th><th scope=\"col\">How hard is this floor?<\/th><\/tr><\/thead>\n <tbody>\n <tr><td class=\"claim\">Healthy adult<\/td><td class=\"who\"><span class=\"num\">RDA 130 g\/day<\/span><br>EAR 100 g\/day<br><b>Biochemical minimum: 0<\/b><\/td><td class=\"who\">Average brain glucose oxidation in the fed state. Not derived from any health-outcome trial.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#96600B\">SOFT<\/span> Gluconeogenesis reliably covers demand. Ketogenic diets are metabolically safe short to medium term.<\/td><\/tr>\n <tr><td class=\"claim\">Pregnancy<\/td><td class=\"who\"><span class=\"num\">RDA 175 g\/day<\/span><br>EAR 135 g\/day<\/td><td class=\"who\">Maternal brain glucose plus fetal and placental demand. The fetus is an obligate glucose user.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#115A72\">FIRMER<\/span> Ketogenic diets are cautioned mainly on animal and mechanistic grounds \u2014 <b>human evidence is sparse and low-certainty.<\/b> The caution is prudential, not proven.<\/td><\/tr>\n <tr><td class=\"claim\">Lactation<\/td><td class=\"who\"><span class=\"num\">RDA 210 g\/day<\/span><\/td><td class=\"who\">Glucose demand for lactose synthesis in milk.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#115A72\">FIRMER<\/span> Substantial obligate draw on maternal glucose.<\/td><\/tr>\n <tr><td class=\"claim\">Children and adolescents<\/td><td class=\"who\"><span class=\"num\">RDA 130 g\/day<\/span><\/td><td class=\"who\">Same brain-glucose basis, scaled for size. Growth adds protein and energy demand, not a separate carbohydrate floor.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#96600B\">SOFT\u2013MODERATE<\/span> Therapeutic ketogenic diets are used in paediatric epilepsy under supervision.<\/td><\/tr>\n <tr><td class=\"claim\">Endurance and high-glycolytic athletes<\/td><td class=\"who\"><span class=\"num\">3\u201312 g\/kg\/day<\/span> scaled to training load<\/td><td class=\"who\">Glycogen storage capacity is ~300\u2013600 g (1,200\u20132,400 kcal). Carbohydrate availability limits sustained high-intensity work.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#093644\">HARD, for performance<\/span> Ketoadaptation raises fat oxidation but <b>impairs exercise economy at high intensity<\/b> (Burke 2017, J Physiol).<\/td><\/tr>\n <tr><td class=\"claim\">Type 1 diabetes<\/td><td class=\"who\">No absolute requirement<\/td><td class=\"who\">Carbohydrate counting governs insulin dosing.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#A63525\">CLINICAL<\/span> Low-carbohydrate approaches are used by some patients but complicate insulin titration and ketoacidosis management. Physician involvement essential.<\/td><\/tr>\n <\/tbody>\n <\/table>\n <\/div>\n\n <h3 class=\"sub-h\">Nutritional ketosis is not ketoacidosis \u2014 the numbers are an order of magnitude apart<\/h3>\n <div class=\"card reveal\">\n <h4>Blood beta-hydroxybutyrate concentration<\/h4>\n <p class=\"sub\">mmol\/L \u00b7 the distinction is quantitative, and acidosis is the dividing line<\/p>\n <svg viewBox=\"0 0 960 230\" role=\"img\" aria-label=\"Number line of blood beta-hydroxybutyrate from 0 to 20 millimoles per litre showing fed state below 0.5, nutritional ketosis 0.5 to 3, a gap, and diabetic ketoacidosis above 10 with acidosis.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#5C6B75\">\n <line x1=\"120\" y1=\"150\" x2=\"920\" y2=\"150\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <text x=\"120\" y=\"170\" text-anchor=\"middle\">0<\/text><text x=\"320\" y=\"170\" text-anchor=\"middle\">5<\/text>\n <text x=\"520\" y=\"170\" text-anchor=\"middle\">10<\/text><text x=\"720\" y=\"170\" text-anchor=\"middle\">15<\/text><text x=\"920\" y=\"170\" text-anchor=\"middle\">20<\/text>\n <text x=\"520\" y=\"194\" text-anchor=\"middle\" letter-spacing=\"0.6\">BLOOD \u03b2-HYDROXYBUTYRATE, mmol\/L<\/text>\n <\/g>\n <g class=\"wipe\">\n <rect x=\"120\" y=\"96\" width=\"20\" height=\"40\" rx=\"1\" fill=\"#D5DDE2\"\/>\n <rect x=\"140\" y=\"96\" width=\"100\" height=\"40\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"240\" y=\"96\" width=\"280\" height=\"40\" rx=\"1\" fill=\"#EDF1F3\" stroke=\"#D5DDE2\"\/>\n <rect x=\"520\" y=\"96\" width=\"400\" height=\"40\" rx=\"1\" fill=\"#A63525\"\/>\n <\/g>\n <g font-family=\"Archivo,sans-serif\" font-weight=\"700\" font-size=\"12\" fill=\"#fff\">\n <text x=\"190\" y=\"121\" text-anchor=\"middle\">KETOSIS 0.5\u20133.0<\/text>\n <text x=\"720\" y=\"121\" text-anchor=\"middle\">DIABETIC KETOACIDOSIS >10\u201315<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <text x=\"130\" y=\"86\" text-anchor=\"middle\">FED<\/text>\n <text x=\"380\" y=\"121\" text-anchor=\"middle\" fill=\"#5C6B75\">RARELY OCCUPIED<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\">\n <text x=\"190\" y=\"60\" text-anchor=\"middle\" fill=\"#115A72\">GLUCOSE NORMAL \u00b7 pH NORMAL<\/text>\n <text x=\"720\" y=\"60\" text-anchor=\"middle\" fill=\"#A63525\">ACIDOSIS \u00b7 pH <7.3 \u00b7 LOW BICARBONATE<\/text>\n <\/g>\n <text x=\"120\" y=\"218\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#A63525\">EUGLYCAEMIC KETOACIDOSIS: SGLT2 INHIBITORS CAN PRECIPITATE DKA AT NEAR-NORMAL GLUCOSE, ESPECIALLY DURING LOW-CARBOHYDRATE INTAKE, FASTING, ILLNESS OR SURGERY<\/text>\n <\/svg>\n <p class=\"figcap\"><b>The clinically important interaction.<\/b> Anyone taking an SGLT2 inhibitor \u2014 empagliflozin, dapagliflozin, canagliflozin \u2014 should not combine it with a ketogenic diet without physician oversight. This is the single most actionable safety point in this section.<\/p>\n <\/div>\n\n <h3 class=\"sub-h\">Long-term safety: what is known and what is not<\/h3>\n <ul class=\"findings\">\n <li><span class=\"pill p-conflict\">Observational \u00b7 disputed<\/span><b>The lean mass hyper-responder phenomenon.<\/b> A subset of lean, metabolically healthy low-carb adopters develop LDL-C often exceeding 190 mg\/dL with high HDL and low triglycerides. <b>KETO-CTA<\/b> (2025, JACC Advances) followed roughly 100 such individuals with serial coronary CT angiography for one year and reported that plaque change was not associated with LDL-C or ApoB, with baseline plaque burden the strongest predictor. <b>Read this cautiously:<\/b> single-arm, no control group, one year is short for atherosclerosis, investigators have low-carb ties, and independent cardiologists noted absolute progression did occur. It does not overturn the Mendelian randomisation and RCT evidence that ApoB is causal at population level. <span class=\"src\">Verify all KETO-CTA figures against the primary paper<\/span><\/li>\n <li><span class=\"pill p-cohort\">Clinical<\/span>Kidney stones \u2014 uric acid and calcium \u2014 are a documented risk, best characterised in paediatric epilepsy ketogenic cohorts.<\/li>\n <li><span class=\"pill p-weak\">Low certainty<\/span>Low carbohydrate availability can lower T3. Clinical significance in euthyroid people is uncertain. Poorly formulated ketogenic diets also risk low fibre, thiamine, folate, magnesium and potassium.<\/li>\n <li><span class=\"pill p-rct\">RCT<\/span>Adherence converges. By 12\u201324 months, low-carb versus low-fat weight differences typically lose significance \u2014 <b>DIETFITS<\/b> found no significant difference at 12 months (n=609). <b>Evidence beyond two years is thin<\/b> and dominated by observational data.<\/li>\n <li><span class=\"pill p-cohort\">Cohort + meta<\/span>At the population level the mortality curve is U-shaped, nadir near <span class=\"val\">50\u201355% of energy<\/span>: below 40%, HR \u2248 1.20; above 70%, HR \u2248 1.23. <b>What replaces the carbohydrate dominates<\/b> \u2014 animal substitution HR \u2248 1.18 versus plant substitution HR \u2248 0.82. <span class=\"src\">Seidelmann et al. 2018 \u00b7 Lancet Public Health \u00b7 ARIC plus meta-analysis<\/span><\/li>\n <li><span class=\"pill p-mech\">Clarification<\/span><b>Fibre is a carbohydrate that is separately required.<\/b> It is largely non-glycemic, so it does not count toward the glucose budget above. The 130 g\/day RDA and the 25\u201329 g\/day fibre target are conceptually independent \u2014 one addresses glucose supply, the other colonic and metabolic outcomes.<\/li>\n <\/ul>\n\n <div class=\"card reveal\" style=\"margin-top:1.75rem\">\n <h4>Both ends of the dial carry risk<\/h4>\n <p class=\"sub\"><span style=\"color:#A63525\">Schematic<\/span> \u00b7 Seidelmann 2018 \u00b7 hazard ratio versus carbohydrate share of energy<\/p>\n <svg viewBox=\"0 0 640 300\" role=\"img\" aria-label=\"Schematic U-shaped curve of hazard ratio against carbohydrate percentage of energy, lowest around 50 to 55 percent, about 1.20 at 30 percent and 1.23 at 75 percent.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <line x1=\"80\" y1=\"240\" x2=\"610\" y2=\"240\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <line x1=\"80\" y1=\"20\" x2=\"80\" y2=\"240\" stroke=\"#E7EDF0\" stroke-width=\"1\"\/>\n <text x=\"72\" y=\"34\" text-anchor=\"end\">1.30<\/text><text x=\"72\" y=\"130\" text-anchor=\"end\">1.15<\/text><text x=\"72\" y=\"226\" text-anchor=\"end\">1.00<\/text>\n <line x1=\"80\" y1=\"226\" x2=\"610\" y2=\"226\" stroke=\"#E7EDF0\" stroke-width=\"1\" stroke-dasharray=\"3 3\"\/>\n <text x=\"130\" y=\"258\" text-anchor=\"middle\">30%<\/text><text x=\"270\" y=\"258\" text-anchor=\"middle\">45%<\/text>\n <text x=\"410\" y=\"258\" text-anchor=\"middle\">60%<\/text><text x=\"550\" y=\"258\" text-anchor=\"middle\">75%<\/text>\n <text x=\"340\" y=\"282\" text-anchor=\"middle\" letter-spacing=\"0.6\">CARBOHYDRATE, % OF TOTAL ENERGY<\/text>\n <\/g>\n <g class=\"reveal\">\n <rect x=\"317\" y=\"20\" width=\"47\" height=\"220\" fill=\"#115A72\" fill-opacity=\"0.10\"\/>\n <line x1=\"317\" y1=\"20\" x2=\"317\" y2=\"240\" stroke=\"#115A72\" stroke-width=\"1.5\" stroke-dasharray=\"4 3\"\/>\n <line x1=\"364\" y1=\"20\" x2=\"364\" y2=\"240\" stroke=\"#115A72\" stroke-width=\"1.5\" stroke-dasharray=\"4 3\"\/>\n <text x=\"340\" y=\"16\" text-anchor=\"middle\" font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#115A72\">NADIR 50\u201355%<\/text>\n <\/g>\n <path class=\"draw\" d=\"M130,98 C200,168 270,220 340,226 C410,232 480,176 550,58\" fill=\"none\" stroke=\"#96600B\" stroke-width=\"3\"\/>\n <g class=\"reveal\" font-family=\"IBM Plex Mono,monospace\" font-size=\"12\" font-weight=\"600\" fill=\"#96600B\">\n <text x=\"136\" y=\"88\">1.20<\/text><text x=\"524\" y=\"48\">1.23<\/text>\n <\/g>\n <g class=\"reveal\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#3D4C57\">\n <text x=\"130\" y=\"216\" text-anchor=\"middle\">LOW-CARB<\/text><text x=\"550\" y=\"216\" text-anchor=\"middle\">HIGH-CARB<\/text>\n <\/g>\n <\/svg>\n <p class=\"figcap\"><b>Schematic.<\/b> Endpoints reflect reported hazard ratios; the connecting curve is interpolated. Observational \u2014 residual confounding applies at both extremes, and the substitution finding matters more than the amount.<\/p>\n <\/div>\n\n <dl class=\"dl reveal\">\n <div><dt>If you have type 2 diabetes<\/dt><dd>Both lower-carb and calorie-restriction routes have <b>RCT support<\/b> (Virta, DiRECT 46% remission at 1 year). Choose on adherence, not ideology.<\/dd><\/div>\n <div><dt>If pregnant or lactating<\/dt><dd>Apply the <b>175 and 210 g\/day<\/b> figures and default away from ketogenic eating. The safety evidence is thin, which argues for caution rather than confidence.<\/dd><\/div>\n <div><dt>If on an SGLT2 inhibitor<\/dt><dd><b>Do not combine with ketogenic eating<\/b> without physician oversight \u2014 euglycaemic ketoacidosis risk.<\/dd><\/div>\n <div><dt>If training hard<\/dt><dd><b>3\u201312 g\/kg\/day<\/b> by load. The population U-curve nadir is not a ceiling for trained people.<\/dd><\/div>\n <div><dt>Whatever you set<\/dt><dd>Tier 1 still governs. <b>Refined and ultra-processed carbohydrate<\/b> is the portion carrying consistent harm signals.<\/dd><\/div>\n <div><dt>If your LDL climbs sharply<\/dt><dd>Get <b>ApoB and lipoprotein testing<\/b> and cardiology input. Do not assume single-arm data exonerate high ApoB.<\/dd><\/div>\n <\/dl>\n<\/section>\n\n\n<section id=\"fats\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Deep analysis \u00b7 every class, with dosage<\/span>\n <h2>Fats: only two are essential, and the rest is dosing<\/h2>\n <p>\"Eat healthy fats\" is not actionable. Below is every fat class with whether a true physiological requirement exists, the quantitative target, the basis for it, and whether the evidence is settled or contested. Two entries are genuinely essential nutrients; the rest are dosing questions of varying certainty.<\/p>\n <\/div>\n\n <div class=\"tablewrap reveal\">\n <table>\n <thead><tr><th scope=\"col\">Fat class<\/th><th scope=\"col\">Truly essential?<\/th><th scope=\"col\">Daily target<\/th><th scope=\"col\">Basis and evidence<\/th><th scope=\"col\">Status<\/th><\/tr><\/thead>\n <tbody>\n <tr><td class=\"claim\">Total fat<\/td><td class=\"who\">No<\/td><td class=\"who\"><span class=\"num\">20\u201335% of energy<\/span> (AMDR)<\/td><td class=\"who\">Below ~20% risks essential fatty acid and fat-soluble vitamin inadequacy and raises triglycerides on high-carb refeeding. There is no requirement for a specific total-fat percentage \u2014 only for the two essentials below.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#96600B\">MILDLY CONTESTED<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Linoleic acid<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">omega-6, C18:2<\/span><\/td><td class=\"who\"><b>Yes \u2014 essential<\/b><\/td><td class=\"who\"><span class=\"num\">17 g\/day men<br>12 g\/day women<\/span> (AI)<br>Deficiency prevented at ~1\u20132% energy<\/td><td class=\"who\">Depletion\u2013repletion studies (foundational). <b>The \"high omega-6 is harmful\" claim is not supported in humans:<\/b> Marklund 2019 Circulation pooled 30 cohorts using circulating linoleic acid biomarkers (n\u224868,000+) and found <b>higher<\/b> linoleic acid associated with <b>lower<\/b> CVD and all-cause mortality. Controlled feeding does not show LA raising CRP.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#093644\">ESSENTIAL \u00b7 harm claim refuted<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Alpha-linolenic acid<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">omega-3 plant, C18:3<\/span><\/td><td class=\"who\"><b>Yes \u2014 essential<\/b><\/td><td class=\"who\"><span class=\"num\">1.6 g\/day men<br>1.1 g\/day women<\/span> (AI)<\/td><td class=\"who\">Conversion to EPA is ~5\u20138%; to DHA under 0.5\u20134%, higher in women. <b>ALA alone does not meaningfully raise DHA status<\/b>, which is why direct marine intake matters for those targeting DHA.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#093644\">ESSENTIAL<\/span><\/td><\/tr>\n <tr><td class=\"claim\">EPA and DHA<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">long-chain marine omega-3<\/span><\/td><td class=\"who\">Conditionally<\/td><td class=\"who\"><span class=\"num\">250 mg\/day<\/span> (EFSA)<br><span class=\"num\">+200 mg DHA<\/span> in pregnancy<br>AHA: 1\u20132 servings oily fish\/week<\/td><td class=\"who\">Cohorts support fish; <b>supplement RCTs conflict.<\/b> REDUCE-IT (4 g EPA, high-risk statin-treated) HR 0.75 (0.68\u20130.83); STRENGTH, VITAL primary, ASCEND all null; Cochrane 2020 found \"little or no effect\". Where supplements work it appears to need high-dose EPA in high-risk patients, not general-population fish oil.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#A63525\">FOOD YES \u00b7 PILLS CONTESTED<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Saturated fatty acids<\/td><td class=\"who\">No<\/td><td class=\"who\"><span class=\"num\"><10% of energy<\/span><\/td><td class=\"who\">Heavily contested. Hooper 2020 Cochrane: reducing SFA cut combined cardiovascular <b>events<\/b> 17% (RR 0.83, 0.76\u20130.90) but had little or no effect on <b>mortality<\/b>; benefit greatest when replaced by polyunsaturated fat. Siri-Tarino 2010, Chowdhury 2014, de Souza 2015 found no clear association. Astrup 2020 JACC argued against a blanket limit and drew rebuttals.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#A63525\">GENUINELY CONTESTED<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Monounsaturated fat<\/td><td class=\"who\">No<\/td><td class=\"who\">No formal target<\/td><td class=\"who\">PREDIMED: Mediterranean diet plus extra-virgin olive oil HR 0.69 (0.53\u20130.91) or nuts HR 0.72 (0.54\u20130.95) for major cardiovascular events \u2014 one landmark RCT, with a randomisation irregularity that forced republication. Cohorts associate olive oil intake with lower mortality.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#115A72\">FAVOURABLE<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Industrial trans fat<\/td><td class=\"who\">No \u2014 avoid<\/td><td class=\"who\"><span class=\"num\"><1% of energy<\/span><br>Target: near zero<\/td><td class=\"who\">de Souza 2015: ~21\u201334% higher CHD risk and higher all-cause mortality. The clearest-cut harmful fat in the field; WHO REPLACE targets global elimination.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#093644\">NOT CONTESTED<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Ruminant trans fat<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">vaccenic acid, CLA<\/span><\/td><td class=\"who\">No<\/td><td class=\"who\">No limit needed at usual intakes<\/td><td class=\"who\">A separate question from industrial trans fat. Not clearly associated with harm at the amounts naturally present in dairy and meat.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#96600B\">UNCERTAIN<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Dietary cholesterol<\/td><td class=\"who\">No<\/td><td class=\"who\">No numeric cap since 2015<\/td><td class=\"who\">The 300 mg\/day limit was removed from US guidance because dietary cholesterol affects serum LDL weakly relative to saturated and trans fat. Roughly one-third are \"hyper-responders\" whose serum cholesterol rises appreciably; two-thirds change little. Egg literature conflicts: Zhong 2019 JAMA found higher risk per half-egg\/day; many other cohorts and short RCTs are null.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#A63525\">CONTESTED<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Medium-chain triglycerides<\/td><td class=\"who\">No<\/td><td class=\"who\">No target<\/td><td class=\"who\">Rapidly absorbed and ketogenic; used in cognition research and some weight contexts. Effects modest and inconsistent.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#96600B\">PRELIMINARY<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Omega-6 to omega-3 ratio<\/td><td class=\"who\">Not a real target<\/td><td class=\"who\">Do not manage the ratio<\/td><td class=\"who\"><b>Largely superseded by absolute intakes.<\/b> Because linoleic acid is not demonstrably harmful, lowering omega-6 to \"fix the ratio\" is unsupported. Raising omega-3 in absolute terms is the defensible lever. EFSA and most expert reviews do not endorse a ratio target.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#A63525\">OBSOLETE CONCEPT<\/span><\/td><\/tr>\n <\/tbody>\n <\/table>\n <\/div>\n\n <div class=\"grid2\" style=\"margin-top:1.75rem\">\n <div class=\"card reveal\">\n <h4>A saturated fat gram is not just a saturated fat gram<\/h4>\n <p class=\"sub\">Relative LDL-raising effect by individual fatty acid<\/p>\n <svg viewBox=\"0 0 620 300\" role=\"img\" aria-label=\"Bar chart of LDL-raising effect: myristic acid highest, palmitic next, lauric acid moderate and also raises HDL, stearic acid essentially neutral.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <line x1=\"300\" y1=\"230\" x2=\"300\" y2=\"24\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <line x1=\"300\" y1=\"230\" x2=\"600\" y2=\"230\" stroke=\"#E7EDF0\" stroke-width=\"1\"\/>\n <text x=\"300\" y=\"248\" text-anchor=\"middle\">NEUTRAL<\/text>\n <text x=\"480\" y=\"248\" text-anchor=\"middle\">RAISES LDL \u2192<\/text>\n <\/g>\n <g class=\"wipe\">\n <rect x=\"300\" y=\"34\" width=\"248\" height=\"34\" rx=\"1\" fill=\"#A63525\"\/>\n <rect x=\"300\" y=\"82\" width=\"195\" height=\"34\" rx=\"1\" fill=\"#A63525\"\/>\n <rect x=\"300\" y=\"130\" width=\"135\" height=\"34\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"300\" y=\"178\" width=\"6\" height=\"34\" rx=\"1\" fill=\"#115A72\"\/>\n <\/g>\n <g font-family=\"Source Serif 4,serif\" font-size=\"13.5\" fill=\"#0E1A21\" text-anchor=\"end\">\n <text x=\"290\" y=\"56\">Myristic \u00b7 C14:0<\/text>\n <text x=\"290\" y=\"104\">Palmitic \u00b7 C16:0<\/text>\n <text x=\"290\" y=\"152\">Lauric \u00b7 C12:0<\/text>\n <text x=\"290\" y=\"200\">Stearic \u00b7 C18:0<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#5C6B75\" text-anchor=\"end\">\n <text x=\"290\" y=\"70\">BUTTERFAT, COCONUT<\/text>\n <text x=\"290\" y=\"118\">MEAT, PALM OIL<\/text>\n <text x=\"290\" y=\"166\">COCONUT \u2014 ALSO RAISES HDL<\/text>\n <text x=\"290\" y=\"214\">COCOA, BEEF FAT \u2014 CONVERTS TO OLEIC<\/text>\n <\/g>\n <text x=\"300\" y=\"278\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#0E1A21\">COCONUT OIL RAISED LDL BY 10.47 mg\/dL (95% CI 3.01\u201317.94) VS NON-TROPICAL OILS<\/text>\n <text x=\"300\" y=\"294\" font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#5C6B75\">NEELAKANTAN 2020 \u00b7 CIRCULATION \u00b7 META-ANALYSIS OF 16 TRIALS<\/text>\n <\/svg>\n <p class=\"figcap\">Relative magnitudes are illustrative of the established ordering, not extracted effect sizes. <b>Stearic acid is essentially LDL-neutral<\/b> because much of it is desaturated to oleic acid \u2014 which is why beef fat and cocoa butter behave differently from butterfat and coconut oil.<\/p>\n <\/div>\n <div class=\"card reveal\">\n <h4>The dairy matrix problem<\/h4>\n <p class=\"sub\">Why similar saturated fat behaves differently<\/p>\n <ul class=\"findings\" style=\"margin-top:0.2rem\">\n <li><span class=\"pill p-cohort\">Cohort + lipid RCT<\/span><b>Cheese and yogurt appear metabolically neutral to favourable<\/b>, while <b>butter raises LDL more<\/b>, despite comparable saturated fat content. Fermented dairy is associated with neutral or lower cardiometabolic risk in cohorts.<\/li>\n <li><span class=\"pill p-mech\">Candidate mechanisms<\/span>Calcium\u2013fatty-acid soap formation reducing fat absorption; the milk fat globule membrane; fermentation-derived bioactives; probiotic effects.<\/li>\n <li><span class=\"pill p-mech\">Why it matters<\/span>This is the leading real-world demonstration that <b>the food matrix modifies a nutrient's effect<\/b> \u2014 the same principle that explains the fish-versus-fish-oil discrepancy and the produce-versus-antioxidant-supplement failure.<\/li>\n <li><span class=\"pill p-weak\">Overstated claim<\/span><b>\"Grass-fed beef is dramatically healthier\"<\/b> \u2014 grass-fed has a modestly better fatty acid profile (more omega-3 and CLA), but absolute differences are small and <b>no outcome trials show meaningful benefit<\/b> over grain-fed.<\/li>\n <li><span class=\"pill p-conflict\">Refuted claim<\/span><b>\"Coconut oil is heart-healthy\"<\/b> \u2014 the meta-analysis above shows it raises LDL relative to unsaturated oils with no benefit on weight, waist or glycemia.<\/li>\n <\/ul>\n <\/div>\n <\/div>\n<\/section>\n\n\n<section id=\"fibre\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Tier 3 \u00b7 Fibre, vegetables and fruit<\/span>\n <h2>The strongest plant signal is fibre \u2014 and the mechanism is unidentified<\/h2>\n <p>The observational case for vegetables and fruit is strong and consistent. Nearly every attempt to isolate the responsible compound and test it has failed, sometimes harmfully. That pattern is itself one of the most informative findings in nutrition science.<\/p>\n <\/div>\n <div class=\"split\">\n <ul class=\"findings\">\n <li><span class=\"pill p-cohort\">Cohort meta + RCTs<\/span>Highest versus lowest fibre intake: all-cause mortality <span class=\"val\">RR 0.85<\/span> (95% CI 0.79\u20130.91), with 15\u201330% reductions across coronary disease, type 2 diabetes and colorectal cancer. Dose-responsive, greatest benefit at <span class=\"val\">25\u201329 g\/day<\/span> and possibly beyond. <span class=\"src\">Reynolds & Mann 2019 \u00b7 Lancet \u00b7 185 prospective studies + 58 RCTs<\/span><\/li>\n <li><span class=\"pill p-cohort\">Cohort meta<\/span>Fruit and vegetables, per 200 g\/day increment: all-cause mortality <span class=\"val\">RR \u2248 0.90<\/span>, CVD \u2248 0.92, cancer \u2248 0.97. Benefit continues to roughly <span class=\"val\">800 g\/day<\/span> for mortality, with cancer plateauing nearer 600 g. <span class=\"src\">Aune et al. 2017 \u00b7 Int J Epidemiol \u00b7 95 studies, ~2 million participants<\/span><\/li>\n <li><span class=\"pill p-cohort\">Pooled cohorts<\/span>Lowest mortality at about <span class=\"val\">5 servings\/day<\/span> \u2014 2 fruit plus 3 vegetables \u2014 with no further benefit above that. <b>Starchy vegetables, potatoes and fruit juices showed no association with benefit.<\/b> <span class=\"src\">Wang et al. 2021 \u00b7 Circulation<\/span><\/li>\n <li><span class=\"pill p-conflict\">The RCT gap<\/span><b>There is no large hard-outcome randomised trial showing increased vegetable intake reduces mortality.<\/b> Cochrane reviews of fruit and vegetable interventions for cardiovascular prevention found limited evidence confined largely to biomarkers. Anyone claiming trial-grade proof is overstating.<\/li>\n <li><span class=\"pill p-rct\">RCT \u00b7 mechanism<\/span>What <i>is<\/i> trial-established is intermediate. DASH's combination diet reduced systolic pressure meaningfully; the fruit-and-vegetable-only arm produced a smaller but real reduction. <span class=\"src\">Appel et al. 1997 \u00b7 NEJM \u00b7 foundational<\/span><\/li>\n <li><span class=\"pill p-rct\">RCT \u00b7 mechanism<\/span>Dietary nitrate from leafy greens and beetroot lowers systolic pressure roughly <span class=\"val\">4\u20135 mmHg<\/span> via the nitrate\u2013nitrite\u2013nitric oxide pathway \u2014 one of few genuinely RCT-backed specific mechanisms here. <span class=\"src\">Siervo et al. 2013 \u00b7 J Nutr<\/span><\/li>\n <li><span class=\"pill p-cohort\">Specificity<\/span>Leafy greens were associated with lower type 2 diabetes risk where total fruit and vegetable intake was not \u2014 suggesting the category is too coarse to be the right unit of analysis. <span class=\"src\">Carter et al. 2010 \u00b7 BMJ<\/span><\/li>\n <li><span class=\"pill p-cohort\">Well replicated<\/span>Whole fruit is associated with <b>lower<\/b> type 2 diabetes risk while fruit juice is associated with <b>higher<\/b> risk, and substituting whole fruit for juice is associated with reduced risk. Same sugars, different matrix. <span class=\"src\">Muraki et al. 2013 \u00b7 BMJ<\/span><\/li>\n <li><span class=\"pill p-mech\">Bioavailability<\/span>Spinach iron and calcium are heavily oxalate-bound; non-heme iron is phytate-inhibited; carotenoid absorption requires fat and improves with cooking; BCO1 variants limit beta-carotene conversion. <b>Vegetables supply no B12.<\/b><\/li>\n <li><span class=\"pill p-rct\">Displacement<\/span>Lowering dietary energy density reduces energy intake, and vegetables' water and fibre content is the main lever. A large share of the benefit may be <b>what vegetables push off the plate.<\/b> <span class=\"src\">Rolls and colleagues \u00b7 controlled feeding<\/span><\/li>\n <li><span class=\"pill p-weak\">Conditional<\/span>Exceptions exist and are not an anti-vegetable case: FODMAP-sensitive individuals with IBS, and oxalate restriction for recurrent stone formers.<\/li>\n <\/ul>\n <div>\n <div class=\"card\">\n <h4>Dose-response, with a plateau<\/h4>\n <p class=\"sub\"><span style=\"color:#A63525\">Schematic<\/span> \u00b7 Aune 2017 \u00b7 all-cause mortality<\/p>\n <svg viewBox=\"0 0 620 330\" role=\"img\" aria-label=\"Schematic descending curve of relative risk from 1.0 to about 0.69 at 800 grams per day of fruit and vegetables, then flattening.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <line x1=\"70\" y1=\"250\" x2=\"600\" y2=\"250\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <line x1=\"70\" y1=\"20\" x2=\"70\" y2=\"250\" stroke=\"#E7EDF0\" stroke-width=\"1\"\/>\n <text x=\"62\" y=\"34\" text-anchor=\"end\">1.00<\/text><text x=\"62\" y=\"125\" text-anchor=\"end\">0.85<\/text><text x=\"62\" y=\"216\" text-anchor=\"end\">0.70<\/text>\n <text x=\"70\" y=\"268\" text-anchor=\"middle\">0<\/text><text x=\"188\" y=\"268\" text-anchor=\"middle\">200 g<\/text>\n <text x=\"306\" y=\"268\" text-anchor=\"middle\">400 g<\/text><text x=\"423\" y=\"268\" text-anchor=\"middle\">600 g<\/text><text x=\"541\" y=\"268\" text-anchor=\"middle\">800 g<\/text>\n <text x=\"335\" y=\"292\" text-anchor=\"middle\" letter-spacing=\"0.6\">FRUIT AND VEGETABLE INTAKE, g\/DAY<\/text>\n <\/g>\n <g class=\"reveal\">\n <rect x=\"541\" y=\"20\" width=\"59\" height=\"230\" fill=\"#17758C\" fill-opacity=\"0.10\"\/>\n <line x1=\"541\" y1=\"20\" x2=\"541\" y2=\"250\" stroke=\"#17758C\" stroke-width=\"1.5\" stroke-dasharray=\"4 3\"\/>\n <text x=\"570\" y=\"16\" text-anchor=\"middle\" font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#17758C\">PLATEAU<\/text>\n <\/g>\n <path class=\"draw\" d=\"M70,34 C120,60 150,80 188,95 C240,115 280,132 306,143 C350,162 395,175 423,180 C470,196 515,214 541,222 L600,224\" fill=\"none\" stroke=\"#17758C\" stroke-width=\"3\"\/>\n <g class=\"reveal\">\n <circle cx=\"541\" cy=\"222\" r=\"5\" fill=\"#17758C\"\/>\n <text x=\"533\" y=\"243\" text-anchor=\"end\" font-family=\"IBM Plex Mono,monospace\" font-size=\"12\" font-weight=\"600\" fill=\"#17758C\">\u22480.69<\/text>\n <\/g>\n <text x=\"70\" y=\"318\" font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#5C6B75\">OBSERVATIONAL. RESIDUAL CONFOUNDING AND HEALTHY-USER BIAS APPLY.<\/text>\n <\/svg>\n <\/div>\n <div class=\"card\" style=\"margin-top:1.25rem\">\n <h4>What happened when the compounds were tested alone<\/h4>\n <p class=\"sub\">Isolated micronutrient RCTs \u00b7 above 1.0 indicates harm<\/p>\n <svg viewBox=\"0 0 620 300\" role=\"img\" aria-label=\"Bar chart of harm: ATBC beta-carotene 1.18, CARET beta-carotene and retinol 1.28, CARET total mortality 1.17, SELECT vitamin E 1.17.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <line x1=\"150\" y1=\"215\" x2=\"600\" y2=\"215\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <text x=\"150\" y=\"233\" text-anchor=\"middle\">1.00<\/text><text x=\"300\" y=\"233\" text-anchor=\"middle\">1.10<\/text>\n <text x=\"450\" y=\"233\" text-anchor=\"middle\">1.20<\/text><text x=\"600\" y=\"233\" text-anchor=\"middle\">1.30<\/text>\n <\/g>\n <line x1=\"150\" y1=\"16\" x2=\"150\" y2=\"215\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <g class=\"wipe\">\n <rect x=\"150\" y=\"26\" width=\"270\" height=\"30\" rx=\"1\" fill=\"#A63525\"\/>\n <rect x=\"150\" y=\"70\" width=\"420\" height=\"30\" rx=\"1\" fill=\"#A63525\"\/>\n <rect x=\"150\" y=\"114\" width=\"255\" height=\"30\" rx=\"1\" fill=\"#A63525\"\/>\n <rect x=\"150\" y=\"158\" width=\"255\" height=\"30\" rx=\"1\" fill=\"#A63525\"\/>\n <\/g>\n <g font-family=\"Source Serif 4,serif\" font-size=\"12.5\" fill=\"#0E1A21\" text-anchor=\"end\">\n <text x=\"140\" y=\"40\">ATBC \u00b7 \u03b2-carotene<\/text><text x=\"140\" y=\"84\">CARET \u00b7 \u03b2-carotene+retinol<\/text>\n <text x=\"140\" y=\"128\">CARET \u00b7 total mortality<\/text><text x=\"140\" y=\"172\">SELECT \u00b7 vitamin E<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"11\" font-weight=\"600\" fill=\"#A63525\">\n <text x=\"430\" y=\"46\">1.18<\/text><text x=\"580\" y=\"90\">1.28<\/text><text x=\"415\" y=\"134\">1.17<\/text><text x=\"415\" y=\"178\">1.17<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"9\" fill=\"#5C6B75\" text-anchor=\"end\">\n <text x=\"140\" y=\"53\">LUNG CANCER, SMOKERS<\/text><text x=\"140\" y=\"97\">LUNG CANCER \u00b7 STOPPED EARLY<\/text>\n <text x=\"140\" y=\"141\">ALL-CAUSE<\/text><text x=\"140\" y=\"185\">PROSTATE CANCER<\/text>\n <\/g>\n <text x=\"150\" y=\"266\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#0E1A21\">EVERY BAR POINTS THE WRONG WAY.<\/text>\n <text x=\"150\" y=\"284\" font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#5C6B75\">THE BENEFIT OF PRODUCE IS NOT ITS ANTIOXIDANT VITAMINS.<\/text>\n <\/svg>\n <\/div>\n <\/div>\n <\/div>\n <div class=\"callout reveal\">\n <span class=\"eyebrow\">What this actually establishes<\/span>\n <p>The failure of the supplement trials is the strongest argument <strong>for<\/strong> eating vegetables as food and <strong>against<\/strong> believing we know why they work. Four explanations remain live: the food matrix does something isolated compounds cannot; fibre and potassium carry most of the effect; vegetables displace worse foods; or the cohort signal is substantially healthy-user bias. <strong>These have very different implications, and the literature does not currently distinguish between them.<\/strong> What survives regardless: eat the plants, don't buy the extract.<\/p>\n <\/div>\n<\/section>\n\n\n<section id=\"fish\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Tier 2 instruments \u00b7 and one clean paradox<\/span>\n <h2>Fish earns Tier 2. \"Fish prevents heart disease\" does not.<\/h2>\n <p>These are two different claims carrying very different certainty. Fish delivers nutrients that are difficult or impossible to obtain elsewhere \u2014 that is biochemistry, and it is solid. Whether eating it lowers cardiovascular risk is separate, and the trials that tested the active ingredient directly did not agree.<\/p>\n <\/div>\n <div class=\"split\">\n <ul class=\"findings\">\n <li><span class=\"pill p-mech\">Biochemistry<\/span>Conversion of plant ALA to <span class=\"val\">DHA is under 1%<\/span>. Preformed marine EPA and DHA are therefore close to obligate unless algal oil is used.<\/li>\n <li><span class=\"pill p-mech\">Composition<\/span>Shellfish are micronutrient outliers. Oyster zinc and B12 exceed essentially every other common food; mussels supply substantial B12 and reasonably bioavailable iron. Cod and haddock are among the densest natural iodine sources.<\/li>\n <li><span class=\"pill p-cohort\">Cohort meta<\/span>Fish shows a consistent modest inverse association with coronary death and stroke, with the <span class=\"val\">curve flattening early<\/span> \u2014 roughly one to two servings of oily fish weekly, on the order of 250 mg\/day EPA+DHA, captures most of the observed benefit. <span class=\"src\">Mozaffarian & Rimm 2006 JAMA (foundational); Chowdhury 2012 BMJ<\/span><\/li>\n <li><span class=\"pill p-cohort\">Cohort<\/span><b>An important qualifier:<\/b> in PURE the association concentrated in higher-risk and secondary-prevention populations, with little signal in low-risk general populations. Benefit may be conditional on baseline risk. <span class=\"src\">Mohan et al. 2021 \u00b7 JAMA Intern Med<\/span><\/li>\n <li><span class=\"pill p-cohort\">Cohort<\/span>Preparation and species matter. Baked or broiled fish carried the association; <b>fried fish did not.<\/b> Oily fish carry it more strongly than lean white fish.<\/li>\n <li><span class=\"pill p-conflict\">Heterogeneous<\/span>Fish and type 2 diabetes is genuinely inconsistent by region \u2014 inverse in several Asian cohorts, null or positive in some US and European ones. Not a settled benefit.<\/li>\n <li><span class=\"pill p-rct\">Risk\u2013benefit<\/span>On mercury, <b>restricting fish in pregnancy appears to be the larger risk.<\/b> Maternal seafood intake below ~340 g\/week was associated with higher odds of suboptimal child verbal IQ. FAO\/WHO and EFSA conclude benefits generally outweigh methylmercury risk with species-specific caution. <span class=\"src\">Hibbeln et al. 2007 \u00b7 Lancet \u00b7 ALSPAC. Avoid swordfish, shark, king mackerel, tilefish, bigeye tuna. Salmon, sardines, anchovies, shrimp, oysters are low-mercury.<\/span><\/li>\n <\/ul>\n <div class=\"card\">\n <h4>EPA + DHA by species<\/h4>\n <p class=\"sub\">Grams per 100 g cooked \u00b7 varies with feed and season<\/p>\n <svg viewBox=\"0 0 640 400\" role=\"img\" aria-label=\"Bar chart of EPA plus DHA per 100 grams: mackerel 2.6, farmed salmon 2.3, anchovy 2.1, herring 1.8, sardine 1.5, albacore tuna 0.8, mussels 0.7, oysters 0.5, shrimp 0.3, cod 0.2, tilapia 0.15.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <g stroke=\"#E7EDF0\" stroke-width=\"1\"><line x1=\"311\" y1=\"16\" x2=\"311\" y2=\"340\"\/><line x1=\"472\" y1=\"16\" x2=\"472\" y2=\"340\"\/><\/g>\n <line x1=\"150\" y1=\"340\" x2=\"610\" y2=\"340\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <text x=\"150\" y=\"357\" text-anchor=\"middle\">0<\/text><text x=\"311\" y=\"357\" text-anchor=\"middle\">1.0 g<\/text><text x=\"472\" y=\"357\" text-anchor=\"middle\">2.0 g<\/text>\n <\/g>\n <g class=\"wipe\">\n <rect x=\"150\" y=\"22\" width=\"418\" height=\"20\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"150\" y=\"50\" width=\"370\" height=\"20\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"150\" y=\"78\" width=\"338\" height=\"20\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"150\" y=\"106\" width=\"290\" height=\"20\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"150\" y=\"134\" width=\"241\" height=\"20\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"150\" y=\"162\" width=\"129\" height=\"20\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"150\" y=\"190\" width=\"113\" height=\"20\" rx=\"1\" fill=\"#17758C\"\/>\n <rect x=\"150\" y=\"218\" width=\"80\" height=\"20\" rx=\"1\" fill=\"#17758C\"\/>\n <rect x=\"150\" y=\"246\" width=\"48\" height=\"20\" rx=\"1\" fill=\"#17758C\"\/>\n <rect x=\"150\" y=\"274\" width=\"32\" height=\"20\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"150\" y=\"302\" width=\"24\" height=\"20\" rx=\"1\" fill=\"#96600B\"\/>\n <\/g>\n <g font-family=\"Source Serif 4,serif\" font-size=\"13\" fill=\"#0E1A21\" text-anchor=\"end\">\n <text x=\"140\" y=\"37\">Mackerel<\/text><text x=\"140\" y=\"65\">Salmon, farmed<\/text><text x=\"140\" y=\"93\">Anchovy<\/text>\n <text x=\"140\" y=\"121\">Herring<\/text><text x=\"140\" y=\"149\">Sardine<\/text><text x=\"140\" y=\"177\">Tuna, albacore<\/text>\n <text x=\"140\" y=\"205\">Mussels<\/text><text x=\"140\" y=\"233\">Oysters<\/text><text x=\"140\" y=\"261\">Shrimp<\/text>\n <text x=\"140\" y=\"289\">Cod<\/text><text x=\"140\" y=\"317\">Tilapia<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#3D4C57\">\n <text x=\"576\" y=\"37\">2.6<\/text><text x=\"528\" y=\"65\">2.3<\/text><text x=\"496\" y=\"93\">2.1<\/text><text x=\"448\" y=\"121\">1.8<\/text>\n <text x=\"399\" y=\"149\">1.5<\/text><text x=\"287\" y=\"177\">0.8<\/text><text x=\"271\" y=\"205\">0.7<\/text><text x=\"238\" y=\"233\">0.5<\/text>\n <text x=\"206\" y=\"261\">0.3<\/text><text x=\"190\" y=\"289\">0.2<\/text><text x=\"182\" y=\"317\">0.15<\/text>\n <\/g>\n <text x=\"150\" y=\"386\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">TWO SERVINGS\/WEEK OF THE TOP FIVE \u2248 WHERE THE COHORT CURVE FLATTENS<\/text>\n <\/svg>\n <div class=\"legend\">\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#093644\"><\/span>Oily fish<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#17758C\"><\/span>Shellfish<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#96600B\"><\/span>Lean white fish<\/div>\n <\/div>\n <\/div>\n <\/div>\n\n <div class=\"card reveal\" style=\"margin-top:1.75rem\">\n <h4>The paradox, drawn properly: whole fish versus the purified active ingredient<\/h4>\n <p class=\"sub\">Forest plot \u00b7 cardiovascular endpoints \u00b7 point estimate with 95% confidence interval<\/p>\n <svg viewBox=\"0 0 900 400\" role=\"img\" aria-label=\"Forest plot: fish cohorts about 0.88, REDUCE-IT 0.75, VITAL 0.92 crossing 1, ASCEND 0.97 crossing 1, STRENGTH 0.99 crossing 1, Cochrane pooled 0.98 crossing 1.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#5C6B75\">\n <line x1=\"300\" y1=\"320\" x2=\"830\" y2=\"320\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <text x=\"300\" y=\"338\" text-anchor=\"middle\">0.60<\/text><text x=\"448\" y=\"338\" text-anchor=\"middle\">0.80<\/text>\n <text x=\"597\" y=\"338\" text-anchor=\"middle\">1.00<\/text><text x=\"746\" y=\"338\" text-anchor=\"middle\">1.20<\/text>\n <\/g>\n <line x1=\"597\" y1=\"20\" x2=\"597\" y2=\"320\" stroke=\"#0E1A21\" stroke-width=\"1.5\" stroke-dasharray=\"4 3\"\/>\n <text x=\"603\" y=\"18\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#0E1A21\">NO EFFECT<\/text>\n <text x=\"440\" y=\"362\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#093644\">\u2190 BENEFIT<\/text>\n <text x=\"700\" y=\"362\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#A63525\">HARM \u2192<\/text>\n <g class=\"reveal\">\n <line x1=\"471\" y1=\"46\" x2=\"545\" y2=\"46\" stroke=\"#093644\" stroke-width=\"2.5\"\/>\n <line x1=\"471\" y1=\"40\" x2=\"471\" y2=\"52\" stroke=\"#093644\" stroke-width=\"2\"\/><line x1=\"545\" y1=\"40\" x2=\"545\" y2=\"52\" stroke=\"#093644\" stroke-width=\"2\"\/>\n <rect x=\"500\" y=\"38\" width=\"16\" height=\"16\" fill=\"#093644\"\/>\n <line x1=\"359\" y1=\"92\" x2=\"471\" y2=\"92\" stroke=\"#115A72\" stroke-width=\"2.5\"\/>\n <line x1=\"359\" y1=\"86\" x2=\"359\" y2=\"98\" stroke=\"#115A72\" stroke-width=\"2\"\/><line x1=\"471\" y1=\"86\" x2=\"471\" y2=\"98\" stroke=\"#115A72\" stroke-width=\"2\"\/>\n <rect x=\"403\" y=\"84\" width=\"16\" height=\"16\" fill=\"#115A72\"\/>\n <line x1=\"449\" y1=\"138\" x2=\"642\" y2=\"138\" stroke=\"#96600B\" stroke-width=\"2.5\"\/>\n <line x1=\"449\" y1=\"132\" x2=\"449\" y2=\"144\" stroke=\"#96600B\" stroke-width=\"2\"\/><line x1=\"642\" y1=\"132\" x2=\"642\" y2=\"144\" stroke=\"#96600B\" stroke-width=\"2\"\/>\n <rect x=\"530\" y=\"130\" width=\"16\" height=\"16\" fill=\"#96600B\"\/>\n <line x1=\"501\" y1=\"184\" x2=\"657\" y2=\"184\" stroke=\"#96600B\" stroke-width=\"2.5\"\/>\n <line x1=\"501\" y1=\"178\" x2=\"501\" y2=\"190\" stroke=\"#96600B\" stroke-width=\"2\"\/><line x1=\"657\" y1=\"178\" x2=\"657\" y2=\"190\" stroke=\"#96600B\" stroke-width=\"2\"\/>\n <rect x=\"567\" y=\"176\" width=\"16\" height=\"16\" fill=\"#96600B\"\/>\n <line x1=\"523\" y1=\"230\" x2=\"664\" y2=\"230\" stroke=\"#A63525\" stroke-width=\"2.5\"\/>\n <line x1=\"523\" y1=\"224\" x2=\"523\" y2=\"236\" stroke=\"#A63525\" stroke-width=\"2\"\/><line x1=\"664\" y1=\"224\" x2=\"664\" y2=\"236\" stroke=\"#A63525\" stroke-width=\"2\"\/>\n <rect x=\"582\" y=\"222\" width=\"16\" height=\"16\" fill=\"#A63525\"\/>\n <line x1=\"553\" y1=\"276\" x2=\"605\" y2=\"276\" stroke=\"#3D4C57\" stroke-width=\"2.5\"\/>\n <line x1=\"553\" y1=\"270\" x2=\"553\" y2=\"282\" stroke=\"#3D4C57\" stroke-width=\"2\"\/><line x1=\"605\" y1=\"270\" x2=\"605\" y2=\"282\" stroke=\"#3D4C57\" stroke-width=\"2\"\/>\n <rect x=\"574\" y=\"268\" width=\"16\" height=\"16\" fill=\"#3D4C57\"\/>\n <\/g>\n <g font-family=\"Source Serif 4,serif\" font-size=\"14\" fill=\"#0E1A21\" text-anchor=\"end\">\n <text x=\"286\" y=\"43\">Fish intake, cohorts<\/text><text x=\"286\" y=\"89\">REDUCE-IT \u00b7 4 g EPA<\/text>\n <text x=\"286\" y=\"135\">VITAL \u00b7 1 g EPA+DHA<\/text><text x=\"286\" y=\"181\">ASCEND \u00b7 1 g<\/text>\n <text x=\"286\" y=\"227\">STRENGTH \u00b7 4 g EPA+DHA<\/text><text x=\"286\" y=\"273\">Cochrane, pooled<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#5C6B75\" text-anchor=\"end\">\n <text x=\"286\" y=\"57\">OBSERVATIONAL<\/text><text x=\"286\" y=\"103\">RCT \u00b7 MINERAL OIL PLACEBO<\/text>\n <text x=\"286\" y=\"149\">RCT \u00b7 PRIMARY ENDPOINT<\/text><text x=\"286\" y=\"195\">RCT \u00b7 DIABETES<\/text>\n <text x=\"286\" y=\"241\">RCT \u00b7 STOPPED FOR FUTILITY<\/text><text x=\"286\" y=\"287\">SR OF RCTs<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#3D4C57\">\n <text x=\"840\" y=\"47\">\u22480.88<\/text><text x=\"840\" y=\"93\">0.75<\/text><text x=\"840\" y=\"139\">0.92<\/text>\n <text x=\"840\" y=\"185\">0.97<\/text><text x=\"840\" y=\"231\">0.99<\/text><text x=\"840\" y=\"277\">0.98<\/text>\n <\/g>\n <\/svg>\n <p class=\"figcap\"><b>How to read this honestly.<\/b> One trial found a large benefit; three found none; the pooled synthesis found essentially nothing. The single positive trial used a mineral-oil placebo that appears to have raised LDL and CRP in the control arm, which would inflate the apparent effect \u2014 a published, unresolved criticism. <b>Two readings remain live:<\/b> either the cohort fish signal reflects the whole food matrix and displacement of worse options, or it reflects residual confounding. Notably, VITAL found greater benefit in people who ate little fish at baseline, which fits a repletion model rather than a drug model.<\/p>\n <\/div>\n\n <h3 class=\"sub-h\">Poultry: a protein instrument, and that is the whole case for it<\/h3>\n <div class=\"split\">\n <ul class=\"findings\">\n <li><span class=\"pill p-mech\">Composition<\/span>Roughly <span class=\"val\">31 g protein per 100 g<\/span> cooked breast at low energy cost, high DIAAS. Among the most efficient tools for meeting the Tier 2 protein floor.<\/li>\n <li><span class=\"pill p-mech\">Composition<\/span><b>But the micronutrient profile is thin where it matters.<\/b> Iron, zinc and B12 run roughly <span class=\"val\">3\u20138\u00d7 lower<\/span> than beef. High in niacin, B6, selenium and phosphorus. Dark meat carries more iron and zinc than breast.<\/li>\n <li><span class=\"pill p-cohort\">Cohort meta<\/span>Poultry is generally <span class=\"val\">not significantly associated<\/span> with all-cause mortality or cardiovascular disease. This is a null, not a benefit \u2014 and nulls in nutritional epidemiology are weak evidence in both directions.<\/li>\n <li><span class=\"pill p-cohort\">Substitution<\/span>The favourable finding is comparative: modelling poultry or fish <b>in place of<\/b> red or processed meat is associated with lower mortality. The benefit is attributed to what was removed. <span class=\"src\">Zheng et al. 2019 \u00b7 BMJ; Pan et al. 2012 \u00b7 Arch Intern Med (foundational)<\/span><\/li>\n <li><span class=\"pill p-conflict\">Unreplicated<\/span><b>For completeness, not as established:<\/b> some cohorts have reported associations between poultry and specific cancers, and at least one recent European cohort reported higher mortality at high intake. Inconsistent, biologically unexplained, unreplicated. <b>A signal to watch, not a finding. Requires verification.<\/b><\/li>\n <li><span class=\"pill p-mech\">Mechanism<\/span>High-temperature cooking generates heterocyclic amines and polycyclic aromatic hydrocarbons in poultry as well as red meat. <b>Cooking method may matter more than species.<\/b><\/li>\n <li><span class=\"pill p-rct\">Tier 1 governs<\/span>Nuggets and deli slices are ultra-processed foods that happen to contain chicken. They belong to the Tier 1 question.<\/li>\n <\/ul>\n <div class=\"card\">\n <h4>What poultry does and does not deliver<\/h4>\n <p class=\"sub\">Approximate content per 100 g cooked \u00b7 relative to beef<\/p>\n <svg viewBox=\"0 0 620 380\" role=\"img\" aria-label=\"Chicken versus beef: protein about 100 percent, iron 28 percent, zinc 18 percent, B12 12 percent.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <line x1=\"150\" y1=\"300\" x2=\"600\" y2=\"300\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <text x=\"150\" y=\"318\" text-anchor=\"middle\">0<\/text><text x=\"375\" y=\"318\" text-anchor=\"middle\">50%<\/text><text x=\"600\" y=\"318\" text-anchor=\"middle\">100%<\/text>\n <text x=\"375\" y=\"340\" text-anchor=\"middle\" letter-spacing=\"0.6\">CHICKEN AS % OF BEEF CONTENT<\/text>\n <g stroke=\"#E7EDF0\" stroke-width=\"1\"><line x1=\"375\" y1=\"20\" x2=\"375\" y2=\"300\"\/><\/g>\n <\/g>\n <line x1=\"600\" y1=\"20\" x2=\"600\" y2=\"300\" stroke=\"#0E1A21\" stroke-width=\"1\" stroke-dasharray=\"3 3\"\/>\n <g class=\"wipe\">\n <rect x=\"150\" y=\"34\" width=\"450\" height=\"34\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"150\" y=\"94\" width=\"126\" height=\"34\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"150\" y=\"154\" width=\"81\" height=\"34\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"150\" y=\"214\" width=\"54\" height=\"34\" rx=\"1\" fill=\"#A63525\"\/>\n <\/g>\n <g font-family=\"Source Serif 4,serif\" font-size=\"14.5\" fill=\"#0E1A21\" text-anchor=\"end\">\n <text x=\"140\" y=\"56\">Protein<\/text><text x=\"140\" y=\"116\">Iron<\/text><text x=\"140\" y=\"176\">Zinc<\/text><text x=\"140\" y=\"236\">Vitamin B12<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"12\" font-weight=\"600\">\n <text x=\"586\" y=\"56\" fill=\"#fff\" text-anchor=\"end\">\u2248100%<\/text>\n <text x=\"286\" y=\"116\" fill=\"#96600B\">\u224828%<\/text><text x=\"241\" y=\"176\" fill=\"#96600B\">\u224818%<\/text><text x=\"214\" y=\"236\" fill=\"#A63525\">\u224812%<\/text>\n <\/g>\n <text x=\"150\" y=\"368\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">MATCHES ON THE MACRO. DOES NOT SUBSTITUTE ON THE MICRO.<\/text>\n <\/svg>\n <p class=\"figcap\">Ratios approximate, vary by cut. <b>Practical implication:<\/b> swapping all red meat for chicken meets the protein floor but can quietly open iron, zinc and B12 gaps \u2014 particularly in menstruating women. Shellfish or oily fish close them better than either.<\/p>\n <\/div>\n <\/div>\n<\/section>\n\n\n<section id=\"myths\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">New section \u00b7 correcting common beliefs<\/span>\n <h2>Where popular nutrition belief diverges from the evidence<\/h2>\n <p>Two failure modes are worth separating. Some widely repeated claims are simply wrong and the correction is high-certainty. Others are popular <i>contrarian<\/i> claims that are weaker than their advocates assert. Both appear below, with the certainty of each correction stated rather than implied.<\/p>\n <\/div>\n <div class=\"tablewrap reveal\">\n <table>\n <thead><tr><th scope=\"col\">The claim<\/th><th scope=\"col\">What the evidence actually shows<\/th><th scope=\"col\">Correction certainty<\/th><\/tr><\/thead>\n <tbody>\n <tr><td class=\"claim\">\"High protein damages the kidneys\"<\/td>\n <td class=\"who\"><b>Refuted for healthy people.<\/b> Devries et al. 2018 (J Nutr, meta-analysis of RCTs) found higher protein did not adversely affect GFR in adults with normal kidney function; Van Elswyk 2018 concordant. <b>The genuine exception is pre-existing chronic kidney disease<\/b>, where higher protein can accelerate decline and restriction is a legitimate clinical tool. So: no harm in healthy kidneys, real caution in existing CKD.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cf<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"High protein leaches calcium and harms bone\"<\/td>\n <td class=\"who\"><b>Refuted, and the underlying theory is dead.<\/b> Shams-White 2017 (AJCN) and Groenendijk 2019 found higher protein neutral-to-beneficial for bone mineral density with no increase in fracture risk. The <b>acid-ash hypothesis<\/b> \u2014 that protein acidifies blood and dissolves bone \u2014 has been refuted; increased urinary calcium reflects increased absorption, not net bone loss.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cf<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Protein drives mTOR, IGF-1 and shortens lifespan\"<\/td>\n <td class=\"who\"><b>Overstated in humans.<\/b> Levine 2014 (Cell Metabolism) reported higher protein associated with cancer mortality at ages 50\u201365 but <b>protective over 65<\/b> \u2014 from a single 24-hour dietary recall in NHANES, with the mechanism largely from animal models. Critiques note residual confounding and poor translation. In older adults, higher protein protects against sarcopenia and frailty.<\/td>\n <td><span class=\"dots d-mid\">\u25cf\u25cf\u25cf\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Red meat causes colon cancer\"<\/td>\n <td class=\"who\"><b>Requires the classification distinction.<\/b> IARC 2015: <b>processed meat is Group 1<\/b> (carcinogenic), <b>unprocessed red meat is Group 2A<\/b> (probably). Effect size: roughly <b>+18% relative<\/b> colorectal cancer risk per 50 g\/day processed meat \u2014 but <b>absolute lifetime risk moves from about 5% to about 6%.<\/b> Mechanisms: heme iron catalysing N-nitroso compound formation, nitrosamines in processed meat, heterocyclic amines from high-temperature cooking; fibre and calcium appear protective. NutriRECS 2019 applied GRADE and argued certainty is low, provoking an unresolved methodological dispute.<\/td>\n <td><span class=\"dots d-mid\">\u25cf\u25cf\u25cf\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Eggs and dietary cholesterol cause heart disease\"<\/td>\n <td class=\"who\"><b>Genuinely unresolved.<\/b> The 300 mg\/day cap was dropped from US guidance in 2015. Zhong 2019 (JAMA, n\u224829,615) found higher risk per half-egg\/day; many other cohorts \u2014 especially Asian \u2014 and short RCTs are null. Roughly one-third of people are hyper-responders. Remaining uncertainty is real and should not be papered over in either direction.<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Saturated fat causes Alzheimer's disease\"<\/td>\n <td class=\"who\"><b>Weak and contested.<\/b> Observational associations are inconsistent; the strongest signal involves the <b>APOE4 interaction<\/b>, itself inconsistent. Cohort data look impressive \u2014 MIND diet adherence associated with ~53% lower Alzheimer's rate (Morris 2015) \u2014 but the <b>MIND-diet RCT (Barnes 2023, NEJM, ~600 participants, 3 years) found no significant cognitive benefit<\/b> over a control with mild caloric restriction. B-vitamin and omega-3 cognition trials are largely null.<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Everyone should minimise salt\"<\/td>\n <td class=\"who\"><b>Genuine scientific disagreement \u2014 likely a J-curve.<\/b> PURE (O'Donnell 2014, NEJM) suggests both very high (>5 g sodium\/day) and <b>very low (<3 g\/day)<\/b> associate with higher risk. The opposing camp \u2014 TOHP long-term follow-up and DASH-Sodium \u2014 supports linear benefit and argues PURE suffers reverse causation and spot-urine error. <b>SSaSS (Neal 2021, NEJM, n=20,995, ~4.7 years):<\/b> potassium-enriched salt substitute cut stroke (RR \u22480.86), major cardiovascular events (\u22480.87) and total mortality (\u22480.88) without serious hyperkalaemia excess. Lowering sodium in hypertensive or high-intake people is well supported; pushing every normotensive person ever-lower is not settled.<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Fibre is essential for everyone\"<\/td>\n <td class=\"who\"><b>Conditional, not absolute.<\/b> Population benefits are strong, but low-FODMAP restriction reduces symptoms in IBS, meaning some fermentable fibre worsens symptoms in specific individuals. Separately, the old <b>diverticular advice was reversed<\/b> \u2014 Strate 2008 (JAMA) found no increased diverticulitis risk from nuts, seeds or popcorn, and higher fibre now associates with lower risk.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Sugar is toxic\"<\/td>\n <td class=\"who\"><b>Overstated; dose and form matter.<\/b> Evidence is strongest for <b>sugar-sweetened beverages<\/b> (consistent associations with weight gain, T2D, CVD). For total added sugar the risk is more dose-dependent and confounded by total energy; isocaloric fructose substitution shows little independent harm at moderate doses but adverse effects (hepatic de novo lipogenesis, triglycerides) at high doses under hypercaloric conditions.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Gluten harms everyone\"<\/td>\n <td class=\"who\"><b>False outside specific conditions.<\/b> Coeliac disease (~1%) requires strict avoidance. Non-coeliac gluten sensitivity is real for some but frequently confounded \u2014 blinded challenge studies (Biesiekierski 2013, Gastroenterology) implicate <b>FODMAPs and amylase-trypsin inhibitors<\/b> rather than gluten itself in many self-reported cases. No benefit to avoidance in the general population.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cf<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Soy feminises men\"<\/td>\n <td class=\"who\"><b>Refuted.<\/b> Messina 2021 (meta-analysis of clinical studies): neither soy protein nor isoflavones significantly affect total or free testosterone, estradiol or SHBG in men.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cf<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Frequent small meals raise metabolism \/ breakfast is essential\"<\/td>\n <td class=\"who\"><b>Both refuted.<\/b> The thermic effect of food scales with total intake, not meal frequency. Sievert 2019 (BMJ meta-analysis): skipping breakfast does not cause weight gain and adding it does not aid weight loss.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cf<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Time-restricted eating is metabolically special\"<\/td>\n <td class=\"who\"><b>Benefit is mostly caloric.<\/b> TREAT (Lowe 2020, JAMA Intern Med): 16:8 produced no significant additional weight loss versus three structured meals, with a possible lean-mass-loss signal. Meta-analyses show modest loss (~1\u20132 kg) attributable to reduced intake, not timing. <b>Note also:<\/b> the widely-shared 2024 conference abstract linking 8-hour windows to cardiovascular mortality was non-peer-reviewed, observational, and based on 1\u20132 days of recall \u2014 not established.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Multivitamins and antioxidants prevent disease\"<\/td>\n <td class=\"who\"><b>Largely refuted, and some cause harm.<\/b> ATBC: \u03b2-carotene increased lung cancer in smokers. CARET: \u03b2-carotene plus retinol increased lung cancer and mortality. SELECT: vitamin E increased prostate cancer risk. Bjelakovic meta-analyses: no mortality benefit, possible harm. <b>Partial counterpoint:<\/b> COSMOS-Mind found a small but significant multivitamin benefit on global cognition in older adults \u2014 the most credible positive signal to date, modest and needing replication.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Coconut oil is heart-healthy\"<\/td>\n <td class=\"who\"><b>Refuted for lipids.<\/b> Neelakantan 2020 (Circulation, 16 trials): coconut oil raised LDL-C by <b>10.47 mg\/dL (95% CI 3.01\u201317.94)<\/b> versus non-tropical vegetable oils, with no benefit on weight, waist or glycemia.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cf<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Omega-6 seed oils are inflammatory\"<\/td>\n <td class=\"who\"><b>Not supported in humans.<\/b> Marklund 2019 (Circulation, 30 cohorts, biomarker-based) found higher circulating linoleic acid associated with <b>lower<\/b> CVD and mortality. Controlled feeding does not show linoleic acid raising CRP. The oxidised-metabolite hypothesis remains mechanistic and unconfirmed as net harm.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Alkaline and detox diets work\"<\/td>\n <td class=\"who\"><b>Unsupported.<\/b> Blood pH is tightly regulated at 7.35\u20137.45 and diet cannot meaningfully change it; the kidneys and liver perform detoxification. Any benefit comes from eating more vegetables and less processed food, not from alkalinity.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cf<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Artificial sweeteners cause weight gain or cancer\"<\/td>\n <td class=\"who\"><b>Largely unsupported at normal intake.<\/b> RCTs show non-nutritive sweeteners modestly aid weight control versus sugar. IARC classified aspartame Group 2B (\"possibly carcinogenic\") in 2023, but JECFA retained the acceptable daily intake at 40 mg\/kg\/day \u2014 realistic consumption sits well within that margin.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"LDL doesn't matter if your triglycerides and HDL look good\"<\/td>\n <td class=\"who\"><b>The popular contrarian claim, and it is weaker than advertised.<\/b> KETO-CTA (2025) followed ~100 lean-mass hyper-responders for one year and reported plaque change unrelated to LDL-C or ApoB \u2014 but it was <b>single-arm with no control group, only one year, and investigators had low-carb ties<\/b>, and independent cardiologists noted absolute progression did occur. It does not overturn the Mendelian randomisation and RCT evidence that ApoB is causal at population level. <b>Verify all figures.<\/b><\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <\/tbody>\n <\/table>\n <\/div>\n <p class=\"figcap\"><b>Reading the dots.<\/b> Five dots means the correction is well established and you can rely on it. Two dots means the honest answer is \"nobody knows yet\" \u2014 which applies as much to confident contrarian claims as to confident conventional ones.<\/p>\n<\/section>\n\n\n<section id=\"colon\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">New section \u00b7 gastrointestinal outcomes<\/span>\n <h2>Colon and gut: strong cohort signals, weak supplement trials<\/h2>\n <p>The colon is where the fibre story is most mechanistically satisfying and most empirically frustrating \u2014 the mechanism is beautifully characterised and the supplement trials are null.<\/p>\n <\/div>\n <div class=\"split\">\n <ul class=\"findings\">\n <li><span class=\"pill p-mech\">Mechanism<\/span><b>Fermentable fibre<\/b> \u2014 inulin, pectin, beta-glucan, resistant starch \u2014 is fermented to <b>short-chain fatty acids<\/b>. Butyrate is the preferred fuel of colonocytes with anti-inflammatory and anti-neoplastic actions via histone deacetylase inhibition and regulatory T-cell induction. <b>Non-fermentable fibre<\/b> \u2014 cellulose, wheat bran \u2014 mainly bulks stool and shortens transit.<\/li>\n <li><span class=\"pill p-conflict\">Honest tension<\/span><b>The mechanism is well characterised in vitro and in animals, but human fibre-supplement RCTs are largely null.<\/b> The Polyp Prevention Trial and Wheat Bran Fiber trial found no reduction in adenoma recurrence over 3\u20134 years. The population fibre\u2013cancer benefit is robust in cohorts; isolated supplements have not replicated it. This argues for whole-food fibre within dietary patterns, not capsules.<\/li>\n <li><span class=\"pill p-cohort\">Effect sizes<\/span>Colorectal cancer risk associations: processed meat <span class=\"val\">+18%<\/span> per 50 g\/day; unprocessed red meat ~<span class=\"val\">+12\u201317%<\/span> per 100 g\/day; fibre ~<span class=\"val\">\u221210%<\/span> per 10 g\/day; whole grains ~<span class=\"val\">\u221217%<\/span> per 90 g\/day (Aune 2016, BMJ); alcohol ~<span class=\"val\">+7\u201310%<\/span> per 10 g ethanol\/day; physical activity ~<span class=\"val\">\u221220\u201325%<\/span> most versus least active. Calcium and dairy appear protective. <span class=\"src\">WCRF\/AICR Continuous Update Project is the authoritative synthesis \u2014 verify individual figures there<\/span><\/li>\n <li><span class=\"pill p-conflict\">Unexplained trend<\/span><b>Early-onset colorectal cancer is rising in adults under 50 and the cause is unknown.<\/b> A 2025 Nature mutational-signature analysis reported <b>colibactin<\/b> signatures from pks+ E. coli enriched in early-onset versus late-onset tumours, with damage possibly occurring in childhood \u2014 a biologically plausible leading candidate, not proven. Other candidates (ultra-processed food, early-life obesity, antibiotic exposure, sedentary behaviour) are more speculative. <b>Verify the 2025 citation and effect size.<\/b><\/li>\n <li><span class=\"pill p-rct\">Established<\/span><b>Faecal microbiota transplant for recurrent <i>Clostridioides difficile<\/i><\/b> is the one clearly proven clinical microbiome therapy \u2014 roughly 80\u201390% cure across multiple RCTs.<\/li>\n <li><span class=\"pill p-weak\">Hype<\/span><b>Most other microbiome claims are premature.<\/b> Probiotic RCTs are heterogeneous, strain-specific and often low quality, with modest condition-specific benefit at best. The field has significant reproducibility problems \u2014 batch effects, bioinformatic variability, small samples, correlation read as causation. Low-fibre diets do shift the microbiome toward mucin-degrading and sulfate-reducing bacteria, thinning the protective mucus layer, but that is largely animal and mechanistic work.<\/li>\n <\/ul>\n <div class=\"card\">\n <h4>Colorectal cancer: relative risk per standard increment<\/h4>\n <p class=\"sub\">Cohort and meta-analytic estimates \u00b7 approximate<\/p>\n <svg viewBox=\"0 0 620 380\" role=\"img\" aria-label=\"Diverging bar chart of colorectal cancer risk factors. Processed meat plus 18 percent, red meat plus 15, alcohol plus 8. Fibre minus 10, whole grains minus 17, physical activity minus 22.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <line x1=\"330\" y1=\"30\" x2=\"330\" y2=\"300\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <line x1=\"90\" y1=\"300\" x2=\"600\" y2=\"300\" stroke=\"#E7EDF0\" stroke-width=\"1\"\/>\n <text x=\"180\" y=\"322\" text-anchor=\"middle\">\u2190 LOWER RISK<\/text>\n <text x=\"470\" y=\"322\" text-anchor=\"middle\">HIGHER RISK \u2192<\/text>\n <text x=\"330\" y=\"322\" text-anchor=\"middle\">0<\/text>\n <text x=\"180\" y=\"342\" text-anchor=\"middle\">\u221220%<\/text><text x=\"470\" y=\"342\" text-anchor=\"middle\">+20%<\/text>\n <\/g>\n <g class=\"wipe\">\n <rect x=\"330\" y=\"40\" width=\"126\" height=\"26\" rx=\"1\" fill=\"#A63525\"\/>\n <rect x=\"330\" y=\"76\" width=\"105\" height=\"26\" rx=\"1\" fill=\"#A63525\"\/>\n <rect x=\"330\" y=\"112\" width=\"56\" height=\"26\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"260\" y=\"148\" width=\"70\" height=\"26\" rx=\"1\" fill=\"#17758C\"\/>\n <rect x=\"211\" y=\"184\" width=\"119\" height=\"26\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"176\" y=\"220\" width=\"154\" height=\"26\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"288\" y=\"256\" width=\"42\" height=\"26\" rx=\"1\" fill=\"#17758C\"\/>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"11\" font-weight=\"600\">\n <text x=\"464\" y=\"58\" fill=\"#A63525\">+18%<\/text><text x=\"443\" y=\"94\" fill=\"#A63525\">+15%<\/text><text x=\"394\" y=\"130\" fill=\"#96600B\">+8%<\/text>\n <text x=\"252\" y=\"166\" fill=\"#17758C\" text-anchor=\"end\">\u221210%<\/text><text x=\"203\" y=\"202\" fill=\"#115A72\" text-anchor=\"end\">\u221217%<\/text>\n <text x=\"168\" y=\"238\" fill=\"#093644\" text-anchor=\"end\">\u221222%<\/text><text x=\"280\" y=\"274\" fill=\"#17758C\" text-anchor=\"end\">\u22126%<\/text>\n <\/g>\n <g font-family=\"Source Serif 4,serif\" font-size=\"12\" fill=\"#0E1A21\">\n <text x=\"330\" y=\"36\" text-anchor=\"start\" dx=\"4\">Processed meat, per 50 g\/day<\/text>\n <text x=\"330\" y=\"72\" text-anchor=\"start\" dx=\"4\">Red meat, per 100 g\/day<\/text>\n <text x=\"330\" y=\"108\" text-anchor=\"start\" dx=\"4\">Alcohol, per 10 g\/day<\/text>\n <text x=\"330\" y=\"144\" text-anchor=\"end\" dx=\"-4\">Fibre, per 10 g\/day<\/text>\n <text x=\"330\" y=\"180\" text-anchor=\"end\" dx=\"-4\">Whole grains, per 90 g\/day<\/text>\n <text x=\"330\" y=\"216\" text-anchor=\"end\" dx=\"-4\">Physical activity, high vs low<\/text>\n <text x=\"330\" y=\"252\" text-anchor=\"end\" dx=\"-4\">Calcium and dairy<\/text>\n <\/g>\n <text x=\"90\" y=\"368\" font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#5C6B75\">RELATIVE, NOT ABSOLUTE. LIFETIME RISK MOVES FROM ROUGHLY 5% TO 6% AT HIGH PROCESSED-MEAT INTAKE.<\/text>\n <\/svg>\n <p class=\"figcap\"><b>The distinction that gets lost in headlines.<\/b> An 18% relative increase on a 5% baseline is about one extra case per hundred people \u2014 real, worth acting on, and not the catastrophe the phrase \"causes cancer\" implies. <b>Verify all figures against WCRF\/AICR.<\/b><\/p>\n <\/div>\n <\/div>\n<\/section>\n\n\n<section id=\"brain\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">New section \u00b7 cognition and dementia<\/span>\n <h2>Cognition: the widest cohort-to-trial gap in nutrition<\/h2>\n <p>Dietary patterns look strongly protective in cohorts and mostly fail to replicate in trials. This section is where confident dietary claims about Alzheimer's disease should be treated with the most suspicion \u2014 in both directions.<\/p>\n <\/div>\n <ul class=\"findings\">\n <li><span class=\"pill p-cohort\">Cohort<\/span><b>MIND diet<\/b> (Morris 2015, Alzheimers Dement): highest adherence associated with roughly <span class=\"val\">53% lower<\/span> Alzheimer's incidence, and about 35% at moderate adherence. Mediterranean and Nordic patterns show similar inverse associations of roughly 10\u201330%.<\/li>\n <li><span class=\"pill p-conflict\">RCT \u00b7 null<\/span><b>The discrepancy.<\/b> The MIND-diet RCT (Barnes 2023, NEJM, ~600 participants, ~3 years) found <span class=\"val\">no significant cognitive benefit<\/span> versus a control diet with mild caloric restriction. Likely explanations: confounding in cohorts, insufficient trial duration, and improvement in the control group. <b>The causal claim is not established.<\/b><\/li>\n <li><span class=\"pill p-rct\">RCT \u00b7 positive<\/span><b>FINGER<\/b> (Ngandu 2015, Lancet, n=1,260, Finland, 2 years): a structured multidomain intervention \u2014 diet, exercise, cognitive training, vascular risk monitoring \u2014 improved a global cognitive composite versus control. <b>The flagship positive multidomain trial.<\/b><\/li>\n <li><span class=\"pill p-conflict\">RCT \u00b7 null<\/span><b>MAPT<\/b> (Andrieu 2017, Lancet Neurol): omega-3 with or without multidomain intervention \u2014 null on the primary outcome. <b>preDIVA<\/b> (Moll van Charante 2016, Lancet): nurse-led vascular care \u2014 null on dementia incidence.<\/li>\n <li><span class=\"pill p-rct\">Newest readout<\/span><b>US POINTER<\/b> (2025): the largest US multidomain trial, roughly 2,100+ adults aged 60\u201379 at elevated risk, structured versus self-guided lifestyle intervention over 2 years, reported at AAIC July 2025 and published in JAMA. As reported, <b>both groups improved but the structured arm improved the global cognitive composite significantly more<\/b>, framed as slowing cognitive aging by roughly 1\u20132 years. <b>Verify the exact effect size, interval, p-value and DOI \u2014 these could not be confirmed against the primary source.<\/b><\/li>\n <li><span class=\"pill p-conflict\">Null<\/span><b>Single nutrients have not delivered.<\/b> Omega-3 cognition trials are largely null. B-vitamin and homocysteine-lowering trials are largely null, with a possible unreplicated subgroup signal in high-homocysteine individuals (VITACOG). Vitamin D shows observational associations and null-to-weak RCT results.<\/li>\n <li><span class=\"pill p-weak\">Preliminary<\/span><b>The brain-fuel hypothesis.<\/b> Cerebral glucose hypometabolism appears early in Alzheimer's and in APOE4 carriers before symptoms \u2014 the \"brain insulin resistance\" framing. Cunnane's imaging work shows the aging brain <b>retains normal ketone uptake even where glucose uptake is impaired<\/b>, motivating ketogenic and MCT interventions. Small trials show modest short-term signals, particularly in APOE4 non-carriers. <b>Samples are small, durations short, blinding difficult. This is hypothesis-generating, not therapy.<\/b><\/li>\n <li><span class=\"pill p-mech\">Practical reading<\/span>The defensible strategy is the <b>multidomain package<\/b> \u2014 exercise, a Mediterranean or MIND-style pattern, vascular risk control, cognitive and social engagement \u2014 not any single supplement. That conclusion rests on FINGER and provisionally POINTER, and it is modest rather than dramatic.<\/li>\n <\/ul>\n<\/section>\n\n\n<section id=\"apex\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Tier 5 \u00b7 Updated and expanded<\/span>\n <h2>Where the trials disagree and contradict each other<\/h2>\n <p>Every entry here is a live dispute in the published literature. That is why the apex is drawn small and open. Anyone presenting one of these as settled \u2014 in either direction \u2014 has gone beyond the evidence.<\/p>\n <\/div>\n <div class=\"tablewrap reveal\">\n <table>\n <thead><tr><th scope=\"col\">Contested claim<\/th><th scope=\"col\">Evidence for<\/th><th scope=\"col\">Evidence against<\/th><th scope=\"col\">Certainty<\/th><\/tr><\/thead>\n <tbody>\n <tr><td class=\"claim\">Saturated fat causes cardiovascular disease<\/td>\n <td class=\"who\">Hooper 2020 Cochrane: reducing SFA cut combined cardiovascular events, <span class=\"num\">RR 0.83<\/span> (0.76\u20130.90), greatest when replaced by PUFA<\/td>\n <td class=\"who\">Same review found <b>little or no effect on mortality<\/b>. No significant association in Siri-Tarino 2010 (<span class=\"num\">RR 1.07<\/span>), Chowdhury 2014, de Souza 2015. Astrup 2020 JACC argued against a blanket limit and drew rebuttals<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Unprocessed red meat meaningfully raises risk<\/td>\n <td class=\"who\">IARC 2015 Group 2A. Processed meat is <b>not<\/b> disputed \u2014 Group 1, \u2248+18% colorectal cancer per 50 g\/day. Coherent heme-iron and N-nitroso mechanisms<\/td>\n <td class=\"who\">NutriRECS 2019 applied GRADE, judged certainty low and small absolute risk, recommending no change \u2014 provoking rebuttals and retraction calls. Ioannidis disputes the field's effect sizes generally<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Fish consumption prevents cardiovascular disease<\/td>\n <td class=\"who\">Consistent modest inverse cohort associations for coronary death and stroke; REDUCE-IT <span class=\"num\">HR 0.75<\/span> with 4 g EPA; VITAL showed reduced MI and more benefit in low-fish consumers<\/td>\n <td class=\"who\">STRENGTH null and stopped for futility; ASCEND null; VITAL null on its primary endpoint; Cochrane 2020 found little or no effect. REDUCE-IT's mineral-oil placebo remains disputed. PURE found benefit only in higher-risk groups<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Sodium should be minimised in everyone<\/td>\n <td class=\"who\">DASH-Sodium and TOHP long-term follow-up support linear benefit. <b>SSaSS<\/b> (n=20,995): potassium salt substitute cut stroke \u224814%, mortality \u224812%<\/td>\n <td class=\"who\">PURE suggests a <b>J-curve<\/b> with elevated risk below ~3 g sodium\/day. Opponents argue reverse causation and spot-urine error; PURE authors argue the trials studied hypertensive high-intake groups only<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Dietary cholesterol and eggs raise cardiovascular risk<\/td>\n <td class=\"who\">Zhong 2019 JAMA: higher risk per additional half-egg\/day and per 300 mg cholesterol, pooled US cohorts n\u224829,615<\/td>\n <td class=\"who\">Numerous other cohorts, especially Asian, and short-term RCTs are null. The 300 mg cap was removed from US guidance in 2015. Hyper-responder variability is real and unaccounted for<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Diet causally prevents dementia<\/td>\n <td class=\"who\">MIND adherence associated with ~53% lower Alzheimer's rate (Morris 2015). FINGER multidomain RCT positive on a cognitive composite. US POINTER 2025 reportedly positive<\/td>\n <td class=\"who\"><b>MIND-diet RCT (Barnes 2023, NEJM) null.<\/b> MAPT and preDIVA null. Single-nutrient trials \u2014 omega-3, B vitamins, vitamin D \u2014 largely null. Cohort-to-trial gap is the widest in nutrition<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Saturated fat contributes to Alzheimer's disease<\/td>\n <td class=\"who\">Some cohort associations; an APOE4 interaction is biologically plausible and reported in places<\/td>\n <td class=\"who\">Associations inconsistent; the APOE4 interaction itself is inconsistent; no trial evidence. Mechanism-rich and trial-poor<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cb\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">ApoB and LDL are not causal in metabolically healthy hyper-responders<\/td>\n <td class=\"who\">KETO-CTA (2025) reported one-year plaque change unrelated to LDL-C or ApoB in ~100 lean mass hyper-responders, with baseline plaque the strongest predictor<\/td>\n <td class=\"who\"><b>Single-arm, no control group, one year<\/b> \u2014 short for atherosclerosis. Investigator ties to low-carb advocacy. Independent cardiologists noted absolute progression occurred. Large Mendelian randomisation and RCT evidence supports ApoB causality<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cb\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Ketogenic diets are safe beyond two years<\/td>\n <td class=\"who\">No clear harm signal in trials up to 2 years; T2D remission data are favourable; theoretical micronutrient concerns are addressable by formulation<\/td>\n <td class=\"who\"><b>Evidence beyond two years is thin<\/b> and dominated by observational data. Documented risks include kidney stones, possible T3 reduction, LDL elevation in a subset, and high attrition with diet convergence by 12\u201324 months<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Poultry is meaningfully associated with cancer<\/td>\n <td class=\"who\">Scattered cohort associations with specific cancers in some UK analyses; at least one recent European cohort reported higher mortality at high intake<\/td>\n <td class=\"who\">Inconsistent across cohorts, no mechanism distinct from cooking method, unreplicated, confounded by preparation and processing. <b>Most meta-analyses find poultry null<\/b><\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cb\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Glycemic index is clinically actionable<\/td>\n <td class=\"who\">Mechanistically coherent and widely used in practice<\/td>\n <td class=\"who\">OmniCarb (Sacks 2014, JAMA) found limited independent cardiometabolic effect within an already healthy diet<\/td>\n <td><span class=\"dots d-mid\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Higher protein shortens lifespan via mTOR and IGF-1<\/td>\n <td class=\"who\">Levine 2014 reported higher cancer mortality with high protein at ages 50\u201365; strong animal mTOR and IGF-1 mechanism<\/td>\n <td class=\"who\">Reversed above age 65 in the same analysis. Single 24-hour recall, residual confounding, poor animal-to-human translation. Higher protein protects older adults against sarcopenia<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Genotype-based diets beat standard advice<\/td>\n <td class=\"who\">Real gene\u2013diet interactions exist for lactase persistence, CYP1A2, FADS1\/2 and BCO1<\/td>\n <td class=\"who\"><b>Food4Me<\/b> RCT (n=1,607): personalised advice beat generic, but <b>genotype added nothing over phenotype and diet data<\/b>. DIETFITS found no genotype interaction<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cb\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">The rise in early-onset colorectal cancer has an identified cause<\/td>\n <td class=\"who\">A 2025 Nature signature analysis found colibactin signatures from pks+ E. coli enriched in early-onset tumours, possibly from childhood exposure<\/td>\n <td class=\"who\">Genomic association, not demonstrated causation of the population trend. Competing candidates \u2014 ultra-processed food, early-life obesity, antibiotics, sedentary behaviour \u2014 remain speculative. <b>The trend is substantially unexplained<\/b><\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cb\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <\/tbody>\n <\/table>\n <\/div>\n <p class=\"figcap\"><b>Certainty dots<\/b> reflect the consistency of high-quality evidence, not the popularity of the position. Five would mean settled; <b>nothing in this table earns more than two<\/b>. Note that several entries are contested contrarian claims, not contested conventional ones \u2014 scepticism cuts both ways.<\/p>\n<\/section>\n\n\n<section id=\"personal\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Why a single prescription fails<\/span>\n <h2>Identical meal, divergent bodies<\/h2>\n <p>This is the empirical case against one-size-fits-all \u2014 and simultaneously the case against the commercial personalisation industry, because the same literature shows genotype-based advice failing to beat far simpler methods.<\/p>\n <\/div>\n <div class=\"split\">\n <div class=\"card reveal\">\n <h4>Postprandial glucose after the same food<\/h4>\n <p class=\"sub\"><span style=\"color:#A63525\">Schematic<\/span> \u00b7 after Zeevi 2015 and PREDICT 1<\/p>\n <svg viewBox=\"0 0 620 285\" role=\"img\" aria-label=\"Schematic chart of several divergent postprandial glucose curves following an identical meal, illustrating large interpersonal variability.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#5C6B75\">\n <line x1=\"70\" y1=\"230\" x2=\"600\" y2=\"230\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <line x1=\"70\" y1=\"20\" x2=\"70\" y2=\"230\" stroke=\"#E7EDF0\" stroke-width=\"1\"\/>\n <text x=\"62\" y=\"216\" text-anchor=\"end\">BASE<\/text><text x=\"62\" y=\"30\" text-anchor=\"end\">PEAK<\/text>\n <text x=\"70\" y=\"248\" text-anchor=\"middle\">0<\/text><text x=\"247\" y=\"248\" text-anchor=\"middle\">60<\/text><text x=\"424\" y=\"248\" text-anchor=\"middle\">120<\/text>\n <text x=\"335\" y=\"270\" text-anchor=\"middle\" letter-spacing=\"0.6\">MINUTES AFTER AN IDENTICAL MEAL<\/text>\n <\/g>\n <g fill=\"none\" stroke-width=\"2.6\" class=\"draw\">\n <path d=\"M70,212 C150,40 220,44 300,120 C380,190 490,206 596,210\" stroke=\"#A63525\"\/>\n <path d=\"M70,212 C150,96 220,100 300,152 C380,196 490,208 596,212\" stroke=\"#96600B\"\/>\n <path d=\"M70,212 C150,150 220,152 300,180 C380,202 490,210 596,213\" stroke=\"#17758C\"\/>\n <path d=\"M70,212 C150,186 220,188 300,200 C380,208 490,212 596,214\" stroke=\"#093644\"\/>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\">\n <text x=\"306\" y=\"112\" fill=\"#A63525\">HIGH RESPONDER<\/text>\n <text x=\"306\" y=\"196\" fill=\"#093644\">LOW RESPONDER<\/text>\n <text x=\"76\" y=\"18\" fill=\"#5C6B75\">SAME FOOD \u00b7 SAME PORTION<\/text>\n <\/g>\n <\/svg>\n <p class=\"figcap\"><b>Schematic.<\/b> Illustrates the reported phenomenon of large interpersonal variability, not extracted participant data.<\/p>\n <\/div>\n <ul class=\"findings\">\n <li><span class=\"pill p-cohort\">Cohort + ML<\/span>Large interpersonal variability in postprandial glucose to identical meals; a microbiome-plus-clinical predictor outperformed carbohydrate counting, with a small confirmatory intervention. <span class=\"src\">Zeevi \/ Segal 2015 \u00b7 Cell \u00b7 n=800 plus validation<\/span><\/li>\n <li><span class=\"pill p-cohort\">Twin cohort<\/span>Wide variability in glycemic, insulinemic and lipemic responses. Genetics explained relatively little, microbiome a modest share, and <b>identical twins responded differently<\/b> \u2014 undercutting a strongly genetic model of dietary response. <span class=\"src\">PREDICT 1 \u00b7 Berry et al. 2020 \u00b7 Nature Medicine \u00b7 n\u22481000 including twins<\/span><\/li>\n <li><span class=\"pill p-rct\">RCT \u00b7 the key null<\/span>Personalised advice improved diet versus generic advice \u2014 but <b>adding genotype improved nothing over phenotype and diet data.<\/b> The commercially valuable claim is the one that failed. <span class=\"src\">Food4Me \u00b7 Celis-Morales et al. 2017 \u00b7 Int J Epidemiol \u00b7 n=1607<\/span><\/li>\n <li><span class=\"pill p-weak\">Thin<\/span>Continuous glucose monitoring in people without diabetes: weak outcome evidence. It measures variability reliably but has not been shown to improve hard endpoints.<\/li>\n <li><span class=\"pill p-mech\">Ongoing<\/span>NIH <i>Nutrition for Precision Health<\/i> within <i>All of Us<\/i> (~10,000 participants) is the study that could change this section. <b>Status and any 2025\u201326 outputs need direct checking.<\/b><\/li>\n <\/ul>\n <\/div>\n <p class=\"figcap\"><b>Practical reading.<\/b> Variability is real, so fixed universal ratios are poorly justified \u2014 but the validated way to personalise is <b>measurement and response<\/b> (weight, lipids and ApoB, HbA1c, glucose, and how you actually feel and adhere), not a genotype panel.<\/p>\n<\/section>\n\n\n<section id=\"practical\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Translation<\/span>\n <h2>What follows, if you accept the structure<\/h2>\n <p>Stated as consequences of the evidence rather than as prescriptions \u2014 the entire point of the carbohydrate dial is that the setting is yours.<\/p>\n <\/div>\n <dl class=\"dl reveal\">\n <div><dt>Highest-leverage single change<\/dt><dd>Reduce ultra-processed food. <b>Tier 1<\/b> outranks every macronutrient argument and has the only clean ward RCT behind it.<\/dd><\/div>\n <div><dt>The foods that close the most floors<\/dt><dd><b>Shellfish, oily fish and liver.<\/b> Protein, EPA\/DHA, B12, zinc, iron, iodine, selenium, retinol. Nothing else comes close.<\/dd><\/div>\n <div><dt>Protein floor<\/dt><dd><b>1.2\u20131.6 g\/kg\/day<\/b>, more if older or training, with little added benefit above ~1.6. Tracer studies, not nitrogen balance.<\/dd><\/div>\n <div><dt>Protein safety<\/dt><dd>No harm to <b>healthy<\/b> kidneys or bone \u2014 high certainty. Real caution in existing <b>chronic kidney disease.<\/b><\/dd><\/div>\n <div><dt>Carbohydrate<\/dt><dd>No biochemical minimum, but respect the <b>175 g pregnancy \/ 210 g lactation \/ 3\u201312 g\/kg athletic<\/b> floors. Never combine ketogenic eating with an <b>SGLT2 inhibitor<\/b> unsupervised.<\/dd><\/div>\n <div><dt>Fats worth dosing<\/dt><dd>Only <b>linoleic acid and ALA<\/b> are essential. Get <b>250 mg\/day EPA+DHA from fish<\/b>, not from low-dose capsules. Do not manage the omega-6 ratio.<\/dd><\/div>\n <div><dt>Fats to avoid<\/dt><dd><b>Industrial trans fat<\/b> \u2014 the one uncontested harm. Coconut oil is not a heart-healthy fat.<\/dd><\/div>\n <div><dt>If you swap red meat for chicken<\/dt><dd>You keep the protein and lose the <b>iron, zinc and B12<\/b>. Cover it with shellfish or oily fish, not more chicken.<\/dd><\/div>\n <div><dt>Vegetables and fruit<\/dt><dd>Treat as <b>micronutrient and fibre vehicles<\/b>. Target variety and leafy greens, and stop near 5 servings \u2014 the curve flattens.<\/dd><\/div>\n <div><dt>Whole fruit over juice<\/dt><dd>Among the better-replicated distinctions in the field. <b>Juice sits on the carbohydrate dial<\/b>, not in Tier 3.<\/dd><\/div>\n <div><dt>Potatoes and grains<\/dt><dd><b>Carbohydrate<\/b>, not vegetables. Set them with the dial; fried preparations carry their own harm signal.<\/dd><\/div>\n <div><dt>Don't buy the extract<\/dt><dd>Isolated antioxidant supplementation failed or harmed across large trials. <b>The matrix is not optional.<\/b><\/dd><\/div>\n <div><dt>Colon<\/dt><dd>Cut <b>processed meat<\/b> first, get fibre from food rather than capsules, and note that relative risks here sit on a small absolute base.<\/dd><\/div>\n <div><dt>Brain<\/dt><dd>The <b>multidomain package<\/b> \u2014 exercise, Mediterranean or MIND pattern, vascular risk control, cognitive engagement. No single supplement has delivered.<\/dd><\/div>\n <\/dl>\n\n <div class=\"callout reveal\">\n <span class=\"eyebrow\">The honest summary<\/span>\n <p>Very little in nutrition is both important and settled. What survives scrutiny is a short list: food form matters more than macronutrient ratio; protein requirements are higher than the RDA states and harmless to healthy kidneys and bone; only two fatty acids are truly essential; carbohydrate has no biochemical floor but several real physiological ones; fibre and whole plants carry robust signals through a mechanism nobody has isolated; and industrial trans fat is the one clearly harmful fat. <strong>Almost everything else \u2014 saturated fat causality, red meat dose, sodium targets, eggs, whether fish prevents heart disease, whether any diet prevents dementia \u2014 is genuinely unresolved, and the confident contrarian answers are no better supported than the confident conventional ones.<\/strong><\/p>\n <\/div>\n<\/section>\n\n\n<section id=\"refs\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Sources \u00b7 all require verification<\/span>\n <h2>References<\/h2>\n <p>Grouped by topic. Items marked <b>foundational<\/b> predate the 2015 window but remain the primary basis for the claim. Items marked <b>[verify]<\/b> could not be confirmed against the primary source and should be treated as pointers.<\/p>\n <\/div>\n <div class=\"refs\">\n <p class=\"refgroup\">Food form and processing<\/p>\n <p><b>Hall KD, et al.<\/b> (2019) Ultra-processed diets cause excess calorie intake and weight gain. <i>Cell Metabolism<\/i> 30(1):67\u201377.<\/p>\n <p><b>Hall KD, et al.<\/b> (2021) Effect of a plant-based, low-fat diet versus an animal-based, ketogenic diet on ad libitum energy intake. <i>Nature Medicine<\/i> 27(2):344\u2013353.<\/p>\n <p><b>de Souza RJ, et al.<\/b> (2015) Intake of saturated and trans unsaturated fatty acids and risk of all cause mortality, cardiovascular disease, and type 2 diabetes. <i>BMJ<\/i> 351:h3978.<\/p>\n\n <p class=\"refgroup\">Protein requirement and quality<\/p>\n <p><b>Humayun MA, et al.<\/b> (2007) Reevaluation of the protein requirement in young men with the indicator amino acid oxidation technique. <i>Am J Clin Nutr<\/i> 86(4):995\u20131002. <i>Foundational.<\/i><\/p>\n <p><b>Rafii M, et al.<\/b> (2015, 2016) Dietary protein requirement of older men \/ women determined by the indicator amino acid oxidation technique. <i>J Nutr<\/i>.<\/p>\n <p><b>Morton RW, et al.<\/b> (2018) A systematic review, meta-analysis and meta-regression of the effect of protein supplementation on resistance training\u2013induced gains. <i>Br J Sports Med<\/i> 52(6):376\u2013384.<\/p>\n <p><b>Bauer J, et al.<\/b> (2013) PROT-AGE position paper. <i>J Am Med Dir Assoc<\/i> 14(8):542\u2013559. <b>Deutz NEP, et al.<\/b> (2014) ESPEN recommendations. <i>Clin Nutr<\/i> 33(6):929\u2013936.<\/p>\n <p><b>Devries MC, et al.<\/b> (2018) Changes in kidney function do not differ between healthy adults consuming higher- vs normal-protein diets. <i>J Nutr<\/i> 148(11):1760\u20131775.<\/p>\n <p><b>Van Elswyk ME, et al.<\/b> (2018) A systematic review of renal health in healthy individuals associated with protein intake. <i>Adv Nutr<\/i> 9(4):404\u2013418.<\/p>\n <p><b>Shams-White MM, et al.<\/b> (2017) Dietary protein and bone health. <i>Am J Clin Nutr<\/i> 105(6):1528\u20131543. <b>Groenendijk I, et al.<\/b> (2019) <i>Bone Rep<\/i>.<\/p>\n <p><b>Levine ME, et al.<\/b> (2014) Low protein intake is associated with a major reduction in IGF-1, cancer, and overall mortality in the 65 and younger but not older population. <i>Cell Metabolism<\/i> 19(3):407\u2013417.<\/p>\n <p><b>Herreman L, et al.<\/b> (2020) Comprehensive overview of the quality of plant- and animal-sourced proteins based on DIAAS. <i>Food Sci Nutr<\/i> 8(10):5379\u20135391.<\/p>\n <p><b>Marinangeli CPF, House JD<\/b> (2017) Potential impact of the digestible indispensable amino acid score as a measure of protein quality. <i>Nutr Rev<\/i> 75(8):658\u2013667.<\/p>\n\n <p class=\"refgroup\">Carbohydrate, ketosis and metabolic state<\/p>\n <p><b>Institute of Medicine<\/b> (2005) <i>Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids.<\/i> National Academies Press. <i>Foundational \u2014 source of the 130 g\/day RDA and the statement on minimum carbohydrate.<\/i><\/p>\n <p><b>Owen OE, et al.<\/b> (1967) Brain metabolism during fasting. <i>J Clin Invest<\/i> 46(10):1589\u20131595. <i>Foundational.<\/i><\/p>\n <p><b>Cahill GF<\/b> (2006) Fuel metabolism in starvation. <i>Annu Rev Nutr<\/i> 26:1\u201322. <i>Foundational.<\/i><\/p>\n <p><b>Cunnane SC, et al.<\/b> (2016) Can ketones help rescue brain fuel supply in later life? <i>Front Mol Neurosci<\/i> 9:53. <b>Cunnane SC, et al.<\/b> (2020) Brain energy rescue. <i>Nat Rev Drug Discov<\/i>.<\/p>\n <p><b>Seidelmann SB, et al.<\/b> (2018) Dietary carbohydrate intake and mortality: a prospective cohort study and meta-analysis. <i>Lancet Public Health<\/i> 3(9):e419\u2013e428.<\/p>\n <p><b>Dehghan M, et al.<\/b> (2017) Associations of fats and carbohydrate intake with cardiovascular disease and mortality (PURE). <i>Lancet<\/i> 390(10107):2050\u20132062.<\/p>\n <p><b>Lean MEJ, et al.<\/b> (2018, 2019) DiRECT: primary care\u2013led weight management for remission of type 2 diabetes. <i>Lancet<\/i> \/ <i>Lancet Diabetes Endocrinol<\/i>.<\/p>\n <p><b>Hallberg SJ, et al.<\/b> (2018) <i>Diabetes Ther<\/i> 9(2):583\u2013612. <b>Athinarayanan SJ, et al.<\/b> (2019) <i>Front Endocrinol<\/i> 10:348.<\/p>\n <p><b>Gardner CD, et al.<\/b> (2018) Effect of low-fat vs low-carbohydrate diet on 12-month weight loss (DIETFITS). <i>JAMA<\/i> 319(7):667\u2013679.<\/p>\n <p><b>Burke LM, et al.<\/b> (2017) Low carbohydrate, high fat diet impairs exercise economy and negates the performance benefit from intensified training in elite race walkers. <i>J Physiol<\/i> 595(9):2785\u20132807.<\/p>\n <p><b>Norwitz NG, Budoff M, Feldman D, et al.<\/b> (2025) KETO-CTA: plaque progression in lean mass hyper-responders. <i>JACC: Advances.<\/i> <b>[verify \u2014 single-arm, no control group]<\/b><\/p>\n <p><b>Sacks FM, et al.<\/b> (2014) Effects of high vs low glycemic index of dietary carbohydrate (OmniCarb). <i>JAMA<\/i> 312(23):2531\u20132541.<\/p>\n\n <p class=\"refgroup\">Fats and fatty acids<\/p>\n <p><b>Hooper L, et al.<\/b> (2020) Reduction in saturated fat intake for cardiovascular disease. <i>Cochrane Database Syst Rev<\/i> 8:CD011737.<\/p>\n <p><b>Siri-Tarino PW, et al.<\/b> (2010) Meta-analysis of prospective cohort studies evaluating the association of saturated fat with cardiovascular disease. <i>Am J Clin Nutr<\/i> 91(3):535\u2013546. <i>Foundational.<\/i><\/p>\n <p><b>Chowdhury R, et al.<\/b> (2014) Association of dietary, circulating, and supplement fatty acids with coronary risk. <i>Ann Intern Med<\/i> 160(6):398\u2013406.<\/p>\n <p><b>Astrup A, et al.<\/b> (2020) Saturated fats and health: a reassessment and proposal for food-based recommendations. <i>J Am Coll Cardiol<\/i> 76(7):844\u2013857. <i>See published rebuttals in the same journal.<\/i><\/p>\n <p><b>Ramsden CE, et al.<\/b> (2016) Re-evaluation of the traditional diet-heart hypothesis: recovered data from the Minnesota Coronary Experiment. <i>BMJ<\/i> 353:i1246. <b>Ramsden CE, et al.<\/b> (2013) Sydney Diet Heart Study. <i>BMJ<\/i> 346:e8707.<\/p>\n <p><b>Marklund M, et al.<\/b> (2019) Biomarkers of dietary omega-6 fatty acids and incident cardiovascular disease and mortality: an individual-level pooled analysis of 30 cohort studies. <i>Circulation<\/i> 139(21):2422\u20132436.<\/p>\n <p><b>Neelakantan N, Seah JYH, van Dam RM<\/b> (2020) The effect of coconut oil consumption on cardiovascular risk factors: a systematic review and meta-analysis of clinical trials. <i>Circulation<\/i> 141(10):803\u2013814.<\/p>\n <p><b>Estruch R, et al.<\/b> (2018) Primary prevention of cardiovascular disease with a Mediterranean diet supplemented with extra-virgin olive oil or nuts (PREDIMED). <i>N Engl J Med<\/i> 378(25):e34. <i>Republished after randomisation correction.<\/i><\/p>\n <p><b>Zhong VW, et al.<\/b> (2019) Associations of dietary cholesterol or egg consumption with incident cardiovascular disease and mortality. <i>JAMA<\/i> 321(11):1081\u20131095.<\/p>\n <p><b>Burdge GC, Calder PC<\/b> (2005) Conversion of \u03b1-linolenic acid to longer-chain polyunsaturated fatty acids in human adults. <i>Reprod Nutr Dev<\/i> 45(5):581\u2013597. <i>Foundational.<\/i><\/p>\n\n <p class=\"refgroup\">Marine omega-3 and fish<\/p>\n <p><b>Bhatt DL, et al.<\/b> (2019) Cardiovascular risk reduction with icosapent ethyl for hypertriglyceridemia (REDUCE-IT). <i>N Engl J Med<\/i> 380(1):11\u201322.<\/p>\n <p><b>Nicholls SJ, et al.<\/b> (2020) Effect of high-dose omega-3 fatty acids vs corn oil on major adverse cardiovascular events (STRENGTH). <i>JAMA<\/i> 324(22):2268\u20132280.<\/p>\n <p><b>Manson JE, et al.<\/b> (2019) Marine n\u22123 fatty acids and prevention of cardiovascular disease and cancer (VITAL). <i>N Engl J Med<\/i> 380(1):23\u201332.<\/p>\n <p><b>ASCEND Study Collaborative Group<\/b> (2018) Effects of n\u22123 fatty acid supplements in diabetes mellitus. <i>N Engl J Med<\/i> 379(16):1540\u20131550.<\/p>\n <p><b>Abdelhamid AS, et al.<\/b> (2020) Omega-3 fatty acids for the primary and secondary prevention of cardiovascular disease. <i>Cochrane Database Syst Rev<\/i> 3:CD003177.<\/p>\n <p><b>Mozaffarian D, Rimm EB<\/b> (2006) Fish intake, contaminants, and human health. <i>JAMA<\/i> 296(15):1885\u20131899. <i>Foundational.<\/i><\/p>\n <p><b>Mohan D, et al.<\/b> (2021) Associations of fish consumption with risk of cardiovascular disease and mortality among individuals with and without vascular disease from 58 countries. <i>JAMA Intern Med<\/i> 181(5):631\u2013649.<\/p>\n <p><b>Chowdhury R, et al.<\/b> (2012) Association between fish consumption, long chain omega 3 fatty acids, and risk of cerebrovascular disease. <i>BMJ<\/i> 345:e6698.<\/p>\n <p><b>Hibbeln JR, et al.<\/b> (2007) Maternal seafood consumption in pregnancy and neurodevelopmental outcomes in childhood (ALSPAC). <i>Lancet<\/i> 369(9561):578\u2013585.<\/p>\n <p><b>FAO\/WHO<\/b> (2011) Report of the joint expert consultation on the risks and benefits of fish consumption. See also EFSA opinions on fish and methylmercury.<\/p>\n\n <p class=\"refgroup\">Fibre, vegetables, fruit and supplements<\/p>\n <p><b>Reynolds A, Mann J, et al.<\/b> (2019) Carbohydrate quality and human health: a series of systematic reviews and meta-analyses. <i>Lancet<\/i> 393(10170):434\u2013445.<\/p>\n <p><b>Aune D, et al.<\/b> (2017) Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all-cause mortality. <i>Int J Epidemiol<\/i> 46(3):1029\u20131056.<\/p>\n <p><b>Wang DD, et al.<\/b> (2021) Fruit and vegetable intake and mortality. <i>Circulation<\/i> 143(17):1642\u20131654.<\/p>\n <p><b>Appel LJ, et al.<\/b> (1997) A clinical trial of the effects of dietary patterns on blood pressure (DASH). <i>N Engl J Med<\/i> 336(16):1117\u20131124. <i>Foundational.<\/i><\/p>\n <p><b>Muraki I, et al.<\/b> (2013) Fruit consumption and risk of type 2 diabetes. <i>BMJ<\/i> 347:f5001.<\/p>\n <p><b>Carter P, et al.<\/b> (2010) Fruit and vegetable intake and incidence of type 2 diabetes mellitus. <i>BMJ<\/i> 341:c4229.<\/p>\n <p><b>Siervo M, et al.<\/b> (2013) Inorganic nitrate and beetroot juice supplementation reduces blood pressure in adults. <i>J Nutr<\/i> 143(6):818\u2013826.<\/p>\n <p><b>ATBC Study Group<\/b> (1994) The effect of vitamin E and beta carotene on the incidence of lung cancer. <i>N Engl J Med<\/i> 330(15):1029\u20131035. <i>Foundational.<\/i><\/p>\n <p><b>Omenn GS, et al.<\/b> (1996) Effects of a combination of beta carotene and vitamin A on lung cancer and cardiovascular disease (CARET). <i>N Engl J Med<\/i> 334(18):1150\u20131155. <i>Foundational.<\/i><\/p>\n <p><b>Klein EA, et al.<\/b> (2011) Vitamin E and the risk of prostate cancer (SELECT). <i>JAMA<\/i> 306(14):1549\u20131556.<\/p>\n <p><b>Bjelakovic G, et al.<\/b> (2012) Antioxidant supplements for prevention of mortality. <i>Cochrane Database Syst Rev<\/i> 3:CD007176.<\/p>\n <p><b>Baker LD, et al.<\/b> (2022\/2023) COSMOS-Mind \/ COSMOS-Web: multivitamin supplementation and cognition. <i>Alzheimers Dement<\/i> \/ <i>Am J Clin Nutr<\/i>. <b>[verify]<\/b><\/p>\n <p><b>Wallace TC, Fulgoni VL<\/b> (2017) Usual choline intakes are associated with egg and protein food consumption in the United States. <i>Nutrients<\/i> 9(8):839.<\/p>\n <p><b>Rolls BJ, et al.<\/b> Controlled feeding studies on dietary energy density and energy intake. <i>Am J Clin Nutr<\/i> \/ <i>Physiol Behav<\/i>, various.<\/p>\n\n <p class=\"refgroup\">Meat, colon and gastrointestinal<\/p>\n <p><b>Bouvard V, et al. (IARC Working Group)<\/b> (2015) Carcinogenicity of consumption of red and processed meat. <i>Lancet Oncol<\/i> 16(16):1599\u20131600.<\/p>\n <p><b>Johnston BC, et al.<\/b> (2019) Unprocessed red meat and processed meat consumption: dietary guideline recommendations from NutriRECS. <i>Ann Intern Med<\/i> 171(10):756\u2013764. <i>See accompanying critiques.<\/i><\/p>\n <p><b>Zheng Y, et al.<\/b> (2019) Association of changes in red meat consumption with total and cause-specific mortality. <i>BMJ<\/i> 365:l2110.<\/p>\n <p><b>Pan A, et al.<\/b> (2012) Red meat consumption and mortality. <i>Arch Intern Med<\/i> 172(7):555\u2013563. <i>Foundational.<\/i><\/p>\n <p><b>Aune D, et al.<\/b> (2016) Whole grain consumption and risk of cardiovascular disease, cancer, and all cause and cause specific mortality. <i>BMJ<\/i> 353:i2716.<\/p>\n <p><b>Strate LL, et al.<\/b> (2008) Nut, corn, and popcorn consumption and the incidence of diverticular disease. <i>JAMA<\/i> 300(8):907\u2013914.<\/p>\n <p><b>Biesiekierski JR, et al.<\/b> (2013) No effects of gluten in patients with self-reported non-celiac gluten sensitivity after dietary reduction of fermentable, poorly absorbed, short-chain carbohydrates. <i>Gastroenterology<\/i> 145(2):320\u2013328.<\/p>\n <p><b>D\u00edaz-Gay M, Alexandrov LB, et al.<\/b> (2025) Colibactin mutational signatures in early-onset colorectal cancer. <i>Nature.<\/i> <b>[verify \u2014 citation, fold-enrichment and causal inference]<\/b><\/p>\n <p><b>World Cancer Research Fund \/ AICR<\/b> Continuous Update Project \u2014 colorectal cancer. Authoritative synthesis for the effect sizes cited.<\/p>\n\n <p class=\"refgroup\">Sodium<\/p>\n <p><b>O'Donnell M, et al.<\/b> (2014) Urinary sodium and potassium excretion, mortality, and cardiovascular events (PURE). <i>N Engl J Med<\/i> 371(7):612\u2013623.<\/p>\n <p><b>Sacks FM, et al.<\/b> (2001) Effects on blood pressure of reduced dietary sodium and the DASH diet (DASH-Sodium). <i>N Engl J Med<\/i> 344(1):3\u201310. <i>Foundational.<\/i><\/p>\n <p><b>Neal B, et al.<\/b> (2021) Effect of salt substitution on cardiovascular events and death (SSaSS). <i>N Engl J Med<\/i> 385(12):1067\u20131077. <b>[verify intervals]<\/b><\/p>\n\n <p class=\"refgroup\">Cognition and dementia<\/p>\n <p><b>Morris MC, et al.<\/b> (2015) MIND diet associated with reduced incidence of Alzheimer's disease. <i>Alzheimers Dement<\/i> 11(9):1007\u20131014.<\/p>\n <p><b>Barnes LL, et al.<\/b> (2023) Trial of the MIND diet for prevention of cognitive decline in older persons. <i>N Engl J Med<\/i> 389(7):602\u2013611.<\/p>\n <p><b>Ngandu T, et al.<\/b> (2015) A 2 year multidomain intervention of diet, exercise, cognitive training, and vascular risk monitoring versus control to prevent cognitive decline (FINGER). <i>Lancet<\/i> 385(9984):2255\u20132263.<\/p>\n <p><b>Andrieu S, et al.<\/b> (2017) Effect of long-term omega-3 polyunsaturated fatty acid supplementation with or without multidomain intervention on cognitive function (MAPT). <i>Lancet Neurol<\/i> 16(5):377\u2013389.<\/p>\n <p><b>Moll van Charante EP, et al.<\/b> (2016) Effectiveness of a 6-year multidomain vascular care intervention to prevent dementia (preDIVA). <i>Lancet<\/i> 388(10046):797\u2013805.<\/p>\n <p><b>Baker LD, et al.<\/b> (2025) US POINTER: structured versus self-guided lifestyle intervention and cognition. <i>JAMA.<\/i> <b>[verify \u2014 effect size, interval, p-value and DOI unconfirmed]<\/b><\/p>\n\n <p class=\"refgroup\">Misconceptions, personalisation and methods<\/p>\n <p><b>Messina M, et al.<\/b> (2021) Neither soyfoods nor isoflavones warrant classification as endocrine disruptors: a technical review of the observational and clinical data. <i>Crit Rev Food Sci Nutr<\/i>.<\/p>\n <p><b>Sievert K, et al.<\/b> (2019) Effect of breakfast on weight and energy intake: systematic review and meta-analysis of randomised controlled trials. <i>BMJ<\/i> 364:l42.<\/p>\n <p><b>Lowe DA, et al.<\/b> (2020) Effects of time-restricted eating on weight loss and other metabolic parameters (TREAT). <i>JAMA Intern Med<\/i> 180(11):1491\u20131499.<\/p>\n <p><b>Zeevi D, Korem T, Segal E, et al.<\/b> (2015) Personalized nutrition by prediction of glycemic responses. <i>Cell<\/i> 163(5):1079\u20131094.<\/p>\n <p><b>Berry SE, Spector TD, et al.<\/b> (2020) Human postprandial responses to food and potential for precision nutrition (PREDICT 1). <i>Nature Medicine<\/i> 26(6):964\u2013973.<\/p>\n <p><b>Celis-Morales C, et al.<\/b> (2017) Effect of personalized nutrition on health-related behaviour change: the Food4Me European randomized controlled trial. <i>Int J Epidemiol<\/i> 46(2):578\u2013588.<\/p>\n <p><b>Simpson SJ, Raubenheimer D<\/b> (2005) Obesity: the protein leverage hypothesis. <i>Obes Rev<\/i> 6(2):133\u2013142. <i>Foundational.<\/i><\/p>\n <p><b>Ioannidis JPA<\/b> (2018) The challenge of reforming nutritional epidemiologic research. <i>JAMA<\/i> 320(10):969\u2013970.<\/p>\n <\/div>\n<\/section>\n\n<footer>\n EVIDENCE-GRADED SYNTHESIS \u00b7 CONSOLIDATED EDITION \u00b7 COMPILED JULY 2026 \u00b7 LITERATURE WINDOW 2015\u20132026 WITH FOUNDATIONAL EXCEPTIONS MARKED<br>\n NOT MEDICAL ADVICE AND NOT A CLINICAL GUIDELINE. IF YOU ARE PREGNANT OR LACTATING, OR HAVE CHRONIC KIDNEY DISEASE, DIABETES (ESPECIALLY ON INSULIN OR SGLT2 INHIBITORS), CARDIOVASCULAR DISEASE, FAMILIAL HYPERCHOLESTEROLAEMIA, OR AN EATING DISORDER, OR TAKE MEDICATION \u2014 INVOLVE A PHYSICIAN OR REGISTERED DIETITIAN BEFORE CHANGING YOUR DIET.<br>\n LIVE LITERATURE SEARCH WAS UNAVAILABLE FOR MOST SESSIONS THAT PRODUCED THIS DOCUMENT \u00b7 ALL EFFECT ESTIMATES, INTERVALS, SAMPLE SIZES, DIAAS SCORES, NUTRIENT VALUES AND DOIs REQUIRE INDEPENDENT VERIFICATION AGAINST PRIMARY SOURCES BEFORE PUBLICATION OR USE.\n<\/footer>\n\n<\/div>\n<script>\n(function(){\n var els=document.querySelectorAll('.reveal,.wipe,.grow,.draw');\n if(!('IntersectionObserver' in window)){els.forEach(function(e){e.classList.add('in')});return;}\n var io=new IntersectionObserver(function(en){en.forEach(function(e){if(e.isIntersecting){e.target.classList.add('in');io.unobserve(e.target);}})},{threshold:0.1,rootMargin:'0px 0px -6% 0px'});\n els.forEach(function(e){io.observe(e)});\n})();\n<\/script>\n<\/body>\n<\/html>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-eebb4d9 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"eebb4d9\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-15ae8d2\" data-id=\"15ae8d2\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-22ff637 elementor-widget elementor-widget-heading\" data-id=\"22ff637\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Add Your Heading Text Here<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Human Nutrient Requirements: An Evidence-Graded Synthesis Evidence-graded synthesis \u00b7 literature window 2015\u20132026 \u00b7 Author: RezaRaza.com Not a guideline \u00b7 Not medical advice What nutrient a human body actually requires, ranked by how well we know it. This document reorganises nutrition around a single axis: not food groups, not servings, but how well each claim survives […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_canvas","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[26,28,27,25],"class_list":["post-744","post","type-post","status-publish","format-standard","hentry","category-text","tag-food","tag-food-2026","tag-nutrition","tag-nutrition-2026"],"_links":{"self":[{"href":"https:\/\/rezaraza.com\/fr\/wp-json\/wp\/v2\/posts\/744","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rezaraza.com\/fr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/rezaraza.com\/fr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/rezaraza.com\/fr\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/rezaraza.com\/fr\/wp-json\/wp\/v2\/comments?post=744"}],"version-history":[{"count":25,"href":"https:\/\/rezaraza.com\/fr\/wp-json\/wp\/v2\/posts\/744\/revisions"}],"predecessor-version":[{"id":800,"href":"https:\/\/rezaraza.com\/fr\/wp-json\/wp\/v2\/posts\/744\/revisions\/800"}],"wp:attachment":[{"href":"https:\/\/rezaraza.com\/fr\/wp-json\/wp\/v2\/media?parent=744"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/rezaraza.com\/fr\/wp-json\/wp\/v2\/categories?post=744"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/rezaraza.com\/fr\/wp-json\/wp\/v2\/tags?post=744"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}

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font-family:var(--mono);font-size:0.72rem;color:var(--ink-3);line-height:1.75}\n\n.reveal{opacity:0;transform:translateY(12px);transition:opacity .65s ease,transform .65s ease}\n.reveal.in{opacity:1;transform:none}\n.wipe{transform:scaleX(0);transform-origin:left;transition:transform .85s cubic-bezier(.22,.7,.25,1)}\n.wipe.in{transform:scaleX(1)}\n.grow{transform:scaleY(0);transform-origin:bottom;transition:transform .85s cubic-bezier(.22,.7,.25,1)}\n.grow.in{transform:scaleY(1)}\n.draw{stroke-dasharray:1400;stroke-dashoffset:1400;transition:stroke-dashoffset 1.5s ease}\n.draw.in{stroke-dashoffset:0}\n@media (prefers-reduced-motion:reduce){.reveal,.wipe,.grow,.draw{opacity:1!important;transform:none!important;stroke-dashoffset:0!important;transition:none!important}}\na{color:var(--t2)} :focus-visible{outline:2px solid var(--t2);outline-offset:3px}\n@media print{\n @page{size:A4;margin:14mm 12mm 16mm}\n body{background:#fff;font-size:9.5pt}\n .reveal,.wipe,.grow,.draw{opacity:1!important;transform:none!important;stroke-dashoffset:0!important}\n \/* tall containers must be allowed to break, or layout cannot place them *\/\n .card,.tier,.tablewrap,.grid2,.split{break-inside:auto}\n .callout,.legend-item{break-inside:avoid}\n table{min-width:0;font-size:7.6pt}\n th,td{padding:1.6mm 2mm}\n thead{display:table-header-group}\n tr{break-inside:avoid}\n .tablewrap{overflow:visible}\n section{padding:8mm 0 0} .refs{columns:2;font-size:7pt}\n *{-webkit-print-color-adjust:exact;print-color-adjust:exact}\n}\n<\/style>\n<\/head>\n<body>\n<div class=\"shell\">\n\n<header class=\"masthead\">\n <div class=\"mast-top\">\n <span class=\"eyebrow\">Evidence-graded synthesis \u00b7 literature window 2015\u20132026 \u00b7 Author: RezaRaza.com<\/span>\n <span class=\"eyebrow\">Not a guideline \u00b7 Not medical advice<\/span>\n <\/div>\n <div class=\"mast-grid\">\n <div>\n <h1>What nutrient a human body actually requires, ranked by <em>how well we know it<\/em>.<\/h1>\n <p class=\"standfirst\">This document reorganises nutrition around a single axis: not food groups, not servings, but <strong>how well each claim survives contact with the evidence<\/strong>. The result separates the handful of findings robust enough to apply to nearly everyone from the many that are genuinely individual, and from the surprising number that are simply unresolved. It covers macronutrient floors, the carbohydrate minimum, dosing for every class of fat, micronutrient bioavailability, gastrointestinal and cognitive outcomes, and the popular beliefs that recent evidence has overturned \u2014 including several that were overturned in the direction nobody expected.<\/p>\n <\/div>\n <nav class=\"toc\">\n <span class=\"eyebrow\">Contents<\/span>\n <h4>Fifteen sections<\/h4>\n <ol>\n <li><a href=\"#pyramid\">The Certainty Pyramid<\/a><\/li>\n <li><a href=\"#floors\">What meets the obligate floors<\/a><\/li>\n <li><a href=\"#protein\">Protein quality, ranked<\/a><\/li>\n <li><a href=\"#classify\">Macronutrient or micronutrient?<\/a><\/li>\n <li><a href=\"#form\">Tier 1 \u00b7 Food form<\/a><\/li>\n <li><a href=\"#tier2\">Tier 2 \u00b7 Obligate floors<\/a><\/li>\n <li><a href=\"#carbs\">Carbohydrate: the minimum, in detail<\/a><\/li>\n <li><a href=\"#fats\">Fats: every class, with dosage<\/a><\/li>\n <li><a href=\"#fibre\">Tier 3 \u00b7 Fibre and plants<\/a><\/li>\n <li><a href=\"#fish\">Fish, shellfish, poultry<\/a><\/li>\n <li><a href=\"#myths\">Correcting common beliefs<\/a><\/li>\n <li><a href=\"#colon\">Colon and gut<\/a><\/li>\n <li><a href=\"#brain\">Cognition and dementia<\/a><\/li>\n <li><a href=\"#apex\">Tier 5 \u00b7 Where trials contradict<\/a><\/li>\n <li><a href=\"#refs\">References<\/a><\/li>\n <\/ol>\n <\/nav>\n <\/div>\n\n <div class=\"notice\">\n <span class=\"eyebrow\">Verification status \u2014 read before trusting a number<\/span>\n <p><strong>Live literature search was unavailable for most sessions that produced this document.<\/strong> The content is drawn from a deep working knowledge of this literature, refined by a later research pass that supplied some verified quotations and intervals. <strong>Every effect estimate, confidence interval, sample size, DIAAS score and nutrient value requires independent confirmation against the primary source before publication or clinical use.<\/strong><\/p>\n <p>Treat all 2024\u20132026 figures as provisional \u2014 specifically US POINTER (JAMA 2025), KETO-CTA (JACC Advances 2025), the SSaSS intervals (NEJM 2021), the colibactin \/ early-onset colorectal cancer signature work (Nature 2025), and the MIND-diet RCT (NEJM 2023). Nutrient composition varies by species, cut, feed, season and preparation. Figures marked <b>SCHEMATIC<\/b> render the shape of a reported relationship, not extracted datapoints.<\/p>\n <\/div>\n<\/header>\n\n\n<section id=\"pyramid\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Figure 1 \u00b7 The organising structure<\/span>\n <h2>The Certainty Pyramid<\/h2>\n <p>Vertical position encodes evidence quality, not quantity to eat. Colour depth runs with certainty: the darkest band rests on controlled trials, the amber band is a setting you choose, and the top band is where published trials contradict one another. Width encodes evidentiary weight.<\/p>\n <\/div>\n <div class=\"card reveal\">\n <svg viewBox=\"0 0 1000 570\" role=\"img\" aria-labelledby=\"pt pd\">\n <title id=\"pt\">The Certainty Pyramid: five tiers ordered by evidence quality<\/title>\n <desc id=\"pd\">Base: food form, established by metabolic ward trials. Second: obligate nutrient floors. Third: fibre, non-starchy vegetables and whole fruit. Fourth: the carbohydrate dial including grains and starchy vegetables. Apex: unresolved questions.<\/desc>\n <g class=\"grow\">\n <polygon points=\"104,412 456,412 500,500 60,500\" fill=\"#093644\"\/>\n <polygon points=\"148,324 412,324 456,412 104,412\" fill=\"#115A72\"\/>\n <polygon points=\"192,236 368,236 412,324 148,324\" fill=\"#17758C\"\/>\n <polygon points=\"236,148 324,148 368,236 192,236\" fill=\"#96600B\"\/>\n <polygon points=\"280,60 324,148 236,148\" fill=\"#F5E4E1\" stroke=\"#A63525\" stroke-width=\"2\" stroke-dasharray=\"5 3\"\/>\n <\/g>\n <g font-family=\"Archivo,sans-serif\" font-weight=\"900\" text-anchor=\"middle\" fill=\"#fff\">\n <text x=\"280\" y=\"464\" font-size=\"25\">FOOD FORM<\/text>\n <text x=\"280\" y=\"376\" font-size=\"23\">OBLIGATE FLOORS<\/text>\n <text x=\"280\" y=\"288\" font-size=\"18\">FIBRE & PLANTS<\/text>\n <text x=\"280\" y=\"199\" font-size=\"14\">CARB DIAL<\/text>\n <\/g>\n <g stroke=\"#D5DDE2\" stroke-width=\"1.5\">\n <line x1=\"478\" y1=\"456\" x2=\"536\" y2=\"456\"\/><line x1=\"434\" y1=\"368\" x2=\"536\" y2=\"368\"\/>\n <line x1=\"390\" y1=\"280\" x2=\"536\" y2=\"280\"\/><line x1=\"346\" y1=\"192\" x2=\"536\" y2=\"192\"\/>\n <line x1=\"302\" y1=\"104\" x2=\"536\" y2=\"104\"\/>\n <\/g>\n <g>\n <rect x=\"540\" y=\"430\" width=\"14\" height=\"14\" rx=\"2\" fill=\"#093644\"\/>\n <text x=\"564\" y=\"442\" font-family=\"Archivo,sans-serif\" font-weight=\"800\" font-size=\"17\" fill=\"#0E1A21\">Tier 1 \u00b7 Food form<\/text>\n <text x=\"564\" y=\"461\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#093644\" letter-spacing=\"0.7\">CERTAINTY: HIGH \u00b7 INPATIENT CROSSOVER RCT<\/text>\n <text x=\"564\" y=\"479\" font-family=\"Source Serif 4,serif\" font-size=\"13.5\" fill=\"#3D4C57\">Macros matched, processing changed: +508 kcal\/day.<\/text>\n <rect x=\"540\" y=\"342\" width=\"14\" height=\"14\" rx=\"2\" fill=\"#115A72\"\/>\n <text x=\"564\" y=\"354\" font-family=\"Archivo,sans-serif\" font-weight=\"800\" font-size=\"17\" fill=\"#0E1A21\">Tier 2 \u00b7 Obligate floors<\/text>\n <text x=\"564\" y=\"373\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#115A72\" letter-spacing=\"0.7\">CERTAINTY: HIGH \u00b7 TRACER + BIOCHEMISTRY<\/text>\n <text x=\"564\" y=\"391\" font-family=\"Source Serif 4,serif\" font-size=\"13.5\" fill=\"#3D4C57\">Protein, essential fats, bioavailable micronutrients.<\/text>\n <rect x=\"540\" y=\"254\" width=\"14\" height=\"14\" rx=\"2\" fill=\"#17758C\"\/>\n <text x=\"564\" y=\"266\" font-family=\"Archivo,sans-serif\" font-weight=\"800\" font-size=\"17\" fill=\"#0E1A21\">Tier 3 \u00b7 Fibre & plants<\/text>\n <text x=\"564\" y=\"285\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#17758C\" letter-spacing=\"0.7\">CERTAINTY: MODERATE \u00b7 COHORT-WEIGHTED<\/text>\n <text x=\"564\" y=\"303\" font-family=\"Source Serif 4,serif\" font-size=\"13.5\" fill=\"#3D4C57\">25\u201329 g fibre, non-starchy veg, whole fruit, legumes.<\/text>\n <rect x=\"540\" y=\"166\" width=\"14\" height=\"14\" rx=\"2\" fill=\"#96600B\"\/>\n <text x=\"564\" y=\"178\" font-family=\"Archivo,sans-serif\" font-weight=\"800\" font-size=\"17\" fill=\"#0E1A21\">Tier 4 \u00b7 Carbohydrate dial<\/text>\n <text x=\"564\" y=\"197\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#96600B\" letter-spacing=\"0.7\">MECHANISM CERTAIN \u00b7 OPTIMUM INDIVIDUAL<\/text>\n <text x=\"564\" y=\"215\" font-family=\"Source Serif 4,serif\" font-size=\"13.5\" fill=\"#3D4C57\">No biochemical minimum. Grains, starchy veg, juice.<\/text>\n <rect x=\"540\" y=\"78\" width=\"14\" height=\"14\" rx=\"2\" fill=\"#A63525\"\/>\n <text x=\"564\" y=\"90\" font-family=\"Archivo,sans-serif\" font-weight=\"800\" font-size=\"17\" fill=\"#A63525\">Tier 5 \u00b7 Unresolved<\/text>\n <text x=\"564\" y=\"109\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#A63525\" letter-spacing=\"0.7\">CERTAINTY: LOW \u00b7 RCTs IN DIRECT CONFLICT<\/text>\n <text x=\"564\" y=\"127\" font-family=\"Source Serif 4,serif\" font-size=\"13.5\" fill=\"#3D4C57\">Saturated fat. Red meat. Salt. Eggs. Fish and CVD.<\/text>\n <\/g>\n <text x=\"60\" y=\"534\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#5C6B75\" letter-spacing=\"0.6\">WIDTH = EVIDENTIARY WEIGHT \u00b7 DEPTH OF COLOUR = CERTAINTY \u00b7 HEIGHT IS NOT SERVING SIZE<\/text>\n <text x=\"60\" y=\"554\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#5C6B75\" letter-spacing=\"0.6\">THE APEX IS SMALL ON PURPOSE: IT IS WHERE THE ARGUMENTS ARE, NOT WHERE THE EFFECT IS.<\/text>\n <\/svg>\n <div class=\"legend\">\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#093644\"><\/span>Established \u2014 RCT<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#115A72\"><\/span>Established \u2014 tracer \/ biochemistry<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#17758C\"><\/span>Moderate \u2014 cohort-weighted<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#96600B\"><\/span>Direction clear, optimum individual<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#F5E4E1;border:1.5px dashed #A63525\"><\/span>Contested \u2014 do not prescribe<\/div>\n <\/div>\n <\/div>\n<\/section>\n\n\n<section id=\"floors\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Figure 2 \u00b7 New diagram<\/span>\n <h2>What actually meets the obligate floors<\/h2>\n <p>Tier 2 is only useful if you know which foods discharge it. This matrix maps nine non-negotiable requirements against nine candidate foods. Read it column-wise to see how many floors a single food closes \u2014 the pattern is the point, and it is not the pattern the old pyramid implied.<\/p>\n <\/div>\n <div class=\"card reveal\">\n <svg viewBox=\"0 0 1000 520\" role=\"img\" aria-labelledby=\"fmt fmd\">\n <title id=\"fmt\">Matrix of nine obligate nutrient floors against nine foods<\/title>\n <desc id=\"fmd\">Oysters, liver and oily fish close the most floors. Poultry closes protein only. Dairy uniquely closes calcium. Legumes and leafy greens close almost none, and neither supplies vitamin B12.<\/desc>\n \n <g font-family=\"Archivo,sans-serif\" font-weight=\"700\" font-size=\"12.5\" fill=\"#0E1A21\">\n <text x=\"332\" y=\"88\" text-anchor=\"start\" transform=\"rotate(-42 332 88)\">Oysters<\/text>\n <text x=\"400\" y=\"88\" text-anchor=\"start\" transform=\"rotate(-42 400 88)\">Oily fish<\/text>\n <text x=\"468\" y=\"88\" text-anchor=\"start\" transform=\"rotate(-42 468 88)\">Liver<\/text>\n <text x=\"536\" y=\"88\" text-anchor=\"start\" transform=\"rotate(-42 536 88)\">Red meat<\/text>\n <text x=\"604\" y=\"88\" text-anchor=\"start\" transform=\"rotate(-42 604 88)\">Eggs<\/text>\n <text x=\"672\" y=\"88\" text-anchor=\"start\" transform=\"rotate(-42 672 88)\">Poultry<\/text>\n <text x=\"740\" y=\"88\" text-anchor=\"start\" transform=\"rotate(-42 740 88)\">Dairy<\/text>\n <text x=\"808\" y=\"88\" text-anchor=\"start\" transform=\"rotate(-42 808 88)\">Legumes<\/text>\n <text x=\"876\" y=\"88\" text-anchor=\"start\" transform=\"rotate(-42 876 88)\">Leafy greens<\/text>\n <\/g>\n \n <g font-family=\"Source Serif 4,serif\" font-size=\"14\" fill=\"#0E1A21\" text-anchor=\"end\">\n <text x=\"292\" y=\"112\">Protein quality<\/text>\n <text x=\"292\" y=\"152\">EPA + DHA<\/text>\n <text x=\"292\" y=\"192\">Vitamin B12<\/text>\n <text x=\"292\" y=\"232\">Bioavailable iron<\/text>\n <text x=\"292\" y=\"272\">Zinc<\/text>\n <text x=\"292\" y=\"312\">Choline<\/text>\n <text x=\"292\" y=\"352\">Iodine<\/text>\n <text x=\"292\" y=\"392\">Preformed retinol<\/text>\n <text x=\"292\" y=\"432\">Calcium<\/text>\n <\/g>\n <g class=\"reveal\">\n \n <rect x=\"304\" y=\"96\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#093644\"\/><rect x=\"372\" y=\"96\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#093644\"\/><rect x=\"440\" y=\"96\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#093644\"\/><rect x=\"508\" y=\"96\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#093644\"\/><rect x=\"576\" y=\"96\" 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stroke=\"#D5DDE2\"\/><rect x=\"848\" y=\"336\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#EDF1F3\" stroke=\"#D5DDE2\"\/>\n \n <rect x=\"304\" y=\"376\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#8FB8C6\"\/><rect x=\"372\" y=\"376\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#8FB8C6\"\/><rect x=\"440\" y=\"376\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#093644\"\/><rect x=\"508\" y=\"376\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#EDF1F3\" stroke=\"#D5DDE2\"\/><rect x=\"576\" y=\"376\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#115A72\"\/><rect x=\"644\" y=\"376\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#EDF1F3\" stroke=\"#D5DDE2\"\/><rect x=\"712\" y=\"376\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#8FB8C6\"\/><rect x=\"780\" y=\"376\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#EDF1F3\" stroke=\"#D5DDE2\"\/><rect x=\"848\" y=\"376\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#EDF1F3\" stroke=\"#D5DDE2\"\/>\n \n <rect x=\"304\" y=\"416\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#8FB8C6\"\/><rect x=\"372\" y=\"416\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#8FB8C6\"\/><rect x=\"440\" y=\"416\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#EDF1F3\" stroke=\"#D5DDE2\"\/><rect x=\"508\" y=\"416\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#EDF1F3\" stroke=\"#D5DDE2\"\/><rect x=\"576\" y=\"416\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#EDF1F3\" stroke=\"#D5DDE2\"\/><rect x=\"644\" y=\"416\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#EDF1F3\" stroke=\"#D5DDE2\"\/><rect x=\"712\" y=\"416\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#093644\"\/><rect x=\"780\" y=\"416\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#8FB8C6\"\/><rect x=\"848\" y=\"416\" width=\"60\" height=\"30\" rx=\"2\" fill=\"#8FB8C6\"\/>\n <\/g>\n \n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"11\" font-weight=\"600\" text-anchor=\"middle\">\n <text x=\"334\" y=\"470\" fill=\"#093644\">8 \/ 9<\/text><text x=\"402\" y=\"470\" fill=\"#093644\">7 \/ 9<\/text>\n <text x=\"470\" y=\"470\" fill=\"#093644\">7 \/ 9<\/text><text x=\"538\" y=\"470\" fill=\"#115A72\">5 \/ 9<\/text>\n <text x=\"606\" y=\"470\" fill=\"#115A72\">6 \/ 9<\/text><text x=\"674\" y=\"470\" fill=\"#96600B\">2 \/ 9<\/text>\n <text x=\"742\" y=\"470\" fill=\"#115A72\">4 \/ 9<\/text><text x=\"810\" y=\"470\" fill=\"#96600B\">0 \/ 9<\/text>\n <text x=\"876\" y=\"470\" fill=\"#A63525\">0 \/ 9<\/text>\n <\/g>\n <text x=\"292\" y=\"470\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\" text-anchor=\"end\">FLOORS FULLY CLOSED<\/text>\n <text x=\"60\" y=\"502\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">PROVITAMIN A CAROTENOIDS IN GREENS ARE NOT PREFORMED RETINOL \u00b7 BCO1 VARIANTS LIMIT CONVERSION IN A LARGE MINORITY<\/text>\n <\/svg>\n <div class=\"legend\">\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#093644\"><\/span>Outstanding source<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#115A72\"><\/span>Good source<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#8FB8C6\"><\/span>Modest or poorly absorbed<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#EDF1F3;border:1px solid #D5DDE2\"><\/span>Negligible or absent<\/div>\n <\/div>\n <p class=\"figcap\"><b>The three findings that matter here.<\/b> First, a small number of foods \u2014 shellfish, liver, oily fish \u2014 close almost every floor at once, which is a stronger and more defensible claim than the cardiovascular one usually made for them. Second, <b>poultry closes only the protein floor<\/b>: substituting it for red meat keeps the macronutrient and quietly opens the iron, zinc and B12 gaps. Third, <b>legumes and leafy greens close none of these floors outright<\/b> \u2014 which is not an argument against eating them, because their job is Tier 3, but it is an argument against treating them as a substitute for Tier 2. Ratings are qualitative judgements from composition data and absorption literature; <b>verify per species and cut.<\/b><\/p>\n <\/div>\n<\/section>\n\n\n<section id=\"protein\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Figure 3 \u00b7 Redrawn and expanded<\/span>\n <h2>Protein quality is not a rhetorical point \u2014 it is a digestibility score<\/h2>\n <p>DIAAS measures true ileal digestibility of each indispensable amino acid against a reference pattern. A score of 100 means the food alone satisfies the pattern; below 100 means it is limited by a specific amino acid and must be combined with a complementary source or eaten in greater quantity. Every food discussed in this document is ranked below, so the question \"which should be on top to meet the minimum protein requirement\" has a direct answer.<\/p>\n <\/div>\n <div class=\"card reveal\">\n <h4>DIAAS, every food ranked<\/h4>\n <p class=\"sub\">Approximate \u00b7 FAO reference pattern \u00b7 100 = reference pattern satisfied by that food alone<\/p>\n <svg viewBox=\"0 0 1000 640\" role=\"img\" aria-labelledby=\"dt dd2\">\n <title id=\"dt\">DIAAS protein quality scores for twenty foods, ranked<\/title>\n <desc id=\"dd2\">Whey, casein, milk, egg, beef, pork, poultry and fish all score at or above 100. Soy isolate 90, chickpeas 83, pea protein 73. Quinoa, rice, beans, lentils and oats fall between 54 and 60. Wheat 45, peanuts 43, almonds 40, corn 36.<\/desc>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#5C6B75\">\n <g stroke=\"#E7EDF0\" stroke-width=\"1\">\n <line x1=\"506\" y1=\"28\" x2=\"506\" y2=\"556\"\/><line x1=\"998\" y1=\"28\" x2=\"998\" y2=\"556\"\/>\n <\/g>\n <line x1=\"260\" y1=\"556\" x2=\"998\" y2=\"556\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <text x=\"260\" y=\"574\" text-anchor=\"middle\">0<\/text>\n <text x=\"506\" y=\"574\" text-anchor=\"middle\">50<\/text>\n <text x=\"752\" y=\"574\" text-anchor=\"middle\">100<\/text>\n <\/g>\n <line x1=\"752\" y1=\"20\" x2=\"752\" y2=\"556\" stroke=\"#0E1A21\" stroke-width=\"2\"\/>\n <text x=\"758\" y=\"18\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#0E1A21\">REFERENCE PATTERN MET \u2192<\/text>\n <g class=\"wipe\">\n <rect x=\"260\" y=\"32\" width=\"615\" height=\"18\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"260\" y=\"58\" width=\"581\" height=\"18\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"260\" y=\"84\" width=\"561\" height=\"18\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"260\" y=\"110\" width=\"556\" height=\"18\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"260\" y=\"136\" width=\"547\" height=\"18\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"260\" y=\"162\" width=\"542\" height=\"18\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"260\" y=\"188\" width=\"532\" height=\"18\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"260\" y=\"214\" width=\"517\" height=\"18\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"260\" y=\"240\" width=\"443\" height=\"18\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"260\" y=\"266\" width=\"409\" height=\"18\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"260\" y=\"292\" width=\"359\" height=\"18\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"260\" y=\"318\" width=\"295\" height=\"18\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"260\" y=\"344\" width=\"295\" height=\"18\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"260\" y=\"370\" width=\"286\" height=\"18\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"260\" y=\"396\" width=\"271\" height=\"18\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"260\" y=\"422\" width=\"266\" height=\"18\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"260\" y=\"448\" width=\"222\" height=\"18\" rx=\"1\" fill=\"#A63525\"\/>\n <rect x=\"260\" y=\"474\" width=\"212\" height=\"18\" rx=\"1\" fill=\"#A63525\"\/>\n <rect x=\"260\" y=\"500\" width=\"197\" height=\"18\" rx=\"1\" fill=\"#A63525\"\/>\n <rect x=\"260\" y=\"526\" width=\"177\" height=\"18\" rx=\"1\" fill=\"#A63525\"\/>\n <\/g>\n <g font-family=\"Source Serif 4,serif\" font-size=\"14\" fill=\"#0E1A21\" text-anchor=\"end\">\n <text x=\"250\" y=\"46\">Whey protein isolate<\/text>\n <text x=\"250\" y=\"72\">Casein<\/text>\n <text x=\"250\" y=\"98\">Milk<\/text>\n <text x=\"250\" y=\"124\">Whole egg<\/text>\n <text x=\"250\" y=\"150\">Beef<\/text>\n <text x=\"250\" y=\"176\">Pork<\/text>\n <text x=\"250\" y=\"202\">Chicken and turkey<\/text>\n <text x=\"250\" y=\"228\">Fish<\/text>\n <text x=\"250\" y=\"254\">Soy protein isolate<\/text>\n <text x=\"250\" y=\"280\">Chickpeas<\/text>\n <text x=\"250\" y=\"306\">Pea protein<\/text>\n <text x=\"250\" y=\"332\">Quinoa<\/text>\n <text x=\"250\" y=\"358\">Rice<\/text>\n <text x=\"250\" y=\"384\">Kidney beans<\/text>\n <text x=\"250\" y=\"410\">Lentils<\/text>\n <text x=\"250\" y=\"436\">Oats<\/text>\n <text x=\"250\" y=\"462\">Wheat<\/text>\n <text x=\"250\" y=\"488\">Peanuts<\/text>\n <text x=\"250\" y=\"514\">Almonds<\/text>\n <text x=\"250\" y=\"540\">Corn \/ maize<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"11\" fill=\"#3D4C57\">\n <text x=\"883\" y=\"46\">125<\/text><text x=\"849\" y=\"72\">118<\/text><text x=\"829\" y=\"98\">114<\/text><text x=\"824\" y=\"124\">113<\/text>\n <text x=\"815\" y=\"150\">111<\/text><text x=\"810\" y=\"176\">110<\/text><text x=\"800\" y=\"202\">108<\/text><text x=\"785\" y=\"228\">105<\/text>\n <text x=\"711\" y=\"254\">90<\/text><text x=\"677\" y=\"280\">83<\/text><text x=\"627\" y=\"306\">73<\/text><text x=\"563\" y=\"332\">60<\/text>\n <text x=\"563\" y=\"358\">60<\/text><text x=\"554\" y=\"384\">58<\/text><text x=\"539\" y=\"410\">55<\/text><text x=\"534\" y=\"436\">54<\/text>\n <text x=\"490\" y=\"462\">45<\/text><text x=\"480\" y=\"488\">43<\/text><text x=\"465\" y=\"514\">40<\/text><text x=\"445\" y=\"540\">36<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <text x=\"260\" y=\"600\">LIMITING AMINO ACID \u00b7 GRAINS AND NUTS: LYSINE \u00b7 LEGUMES AND PEA: METHIONINE AND CYSTEINE \u00b7 COMBINING THE TWO RAISES THE SCORE; PROCESSING DOES NOT CLOSE IT<\/text>\n <text x=\"260\" y=\"620\">TO MEET THE FLOOR ON A SINGLE FOOD, ANYTHING ABOVE THE LINE WORKS. BELOW IT, TOTAL INTAKE MUST RISE TO COMPENSATE.<\/text>\n <\/g>\n <\/svg>\n <div class=\"legend\">\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#093644\"><\/span>Dairy and egg \u2014 highest<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#115A72\"><\/span>Meat, poultry, fish<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#96600B\"><\/span>Legumes and soy<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#A63525\"><\/span>Grains and nuts \u2014 lowest<\/div>\n <\/div>\n <p class=\"figcap\"><b>These are the least reliable decimals in the document.<\/b> DIAAS varies substantially with processing, cooking, and whether the child or adult reference pattern is used; published values for the same food differ between sources, and fish values in particular are less commonly reported than dairy or meat. Compilations: Herreman 2020 (Food Sci Nutr); Marinangeli & House 2017 (Nutr Rev). <b>Reconfirm any single value before quoting it.<\/b><\/p>\n <\/div>\n<\/section>\n\n\n<section id=\"classify\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Figure 4 \u00b7 Classification<\/span>\n <h2>Macronutrient or micronutrient? The arithmetic settles it<\/h2>\n <p>Whether a food is a macronutrient or micronutrient source is measurable, not interpretive. The clearest test is to ask how much of each you would need to eat to hit one fixed protein target.<\/p>\n <\/div>\n <div class=\"card reveal\">\n <h4>Grams of food required to reach 30 g of protein<\/h4>\n <p class=\"sub\">One per-meal protein target \u00b7 approximate cooked weights<\/p>\n <svg viewBox=\"0 0 900 430\" role=\"img\" aria-label=\"Bar chart of grams of food needed for 30 grams of protein: chicken 97, beef 107, salmon 120, tofu 190, eggs 240, lentils 330, spinach 1030, broccoli 1070.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#5C6B75\">\n <g stroke=\"#E7EDF0\" stroke-width=\"1\">\n <line x1=\"380\" y1=\"24\" x2=\"380\" y2=\"360\"\/><line x1=\"550\" y1=\"24\" x2=\"550\" y2=\"360\"\/><line x1=\"720\" y1=\"24\" x2=\"720\" y2=\"360\"\/>\n <\/g>\n <line x1=\"210\" y1=\"360\" x2=\"870\" y2=\"360\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <text x=\"210\" y=\"378\" text-anchor=\"middle\">0<\/text><text x=\"380\" y=\"378\" text-anchor=\"middle\">300 g<\/text>\n <text x=\"550\" y=\"378\" text-anchor=\"middle\">600 g<\/text><text x=\"720\" y=\"378\" text-anchor=\"middle\">900 g<\/text>\n <\/g>\n <g class=\"wipe\">\n <rect x=\"210\" y=\"30\" width=\"55\" height=\"24\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"210\" y=\"66\" width=\"60\" height=\"24\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"210\" y=\"102\" width=\"68\" height=\"24\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"210\" y=\"138\" width=\"107\" height=\"24\" rx=\"1\" fill=\"#17758C\"\/>\n <rect x=\"210\" y=\"174\" width=\"136\" height=\"24\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"210\" y=\"210\" width=\"186\" height=\"24\" rx=\"1\" fill=\"#17758C\"\/>\n <rect x=\"210\" y=\"246\" width=\"582\" height=\"24\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"210\" y=\"282\" width=\"605\" height=\"24\" rx=\"1\" fill=\"#96600B\"\/>\n <\/g>\n <g font-family=\"Source Serif 4,serif\" font-size=\"14.5\" fill=\"#0E1A21\" text-anchor=\"end\">\n <text x=\"198\" y=\"47\">Chicken breast<\/text><text x=\"198\" y=\"83\">Beef<\/text><text x=\"198\" y=\"119\">Salmon<\/text>\n <text x=\"198\" y=\"155\">Tofu<\/text><text x=\"198\" y=\"191\">Eggs<\/text><text x=\"198\" y=\"227\">Lentils, cooked<\/text>\n <text x=\"198\" y=\"263\">Spinach<\/text><text x=\"198\" y=\"299\">Broccoli<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"11.5\" fill=\"#3D4C57\">\n <text x=\"273\" y=\"47\">\u224897 g<\/text><text x=\"278\" y=\"83\">\u2248107 g<\/text><text x=\"286\" y=\"119\">\u2248120 g<\/text>\n <text x=\"325\" y=\"155\">\u2248190 g<\/text><text x=\"354\" y=\"191\">\u2248240 g<\/text><text x=\"404\" y=\"227\">\u2248330 g<\/text>\n <text x=\"800\" y=\"263\" font-weight=\"600\" fill=\"#96600B\">\u22481,030 g<\/text>\n <text x=\"823\" y=\"299\" font-weight=\"600\" fill=\"#96600B\">\u22481,070 g<\/text>\n <\/g>\n <g class=\"reveal\">\n <line x1=\"210\" y1=\"404\" x2=\"870\" y2=\"404\" stroke=\"#E7EDF0\" stroke-width=\"1\"\/>\n <text x=\"210\" y=\"422\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#5C6B75\">ELEVEN TIMES THE MASS \u2014 AND STILL NO B12, LITTLE BIOAVAILABLE IRON OR ZINC<\/text>\n <\/g>\n <\/svg>\n <p class=\"figcap\"><b>This is the answer to the macro\/micro question.<\/b> Non-starchy vegetables cannot function as macronutrient sources at any intake a person will actually achieve. That is not a criticism \u2014 it is a statement about which job they do.<\/p>\n <\/div>\n\n <div class=\"tablewrap reveal\" style=\"margin-top:1.75rem\">\n <table>\n <thead><tr><th scope=\"col\">Food category<\/th><th scope=\"col\">Macronutrient role<\/th><th scope=\"col\">Signature micronutrients<\/th><th scope=\"col\">Classification<\/th><th scope=\"col\">Tier<\/th><\/tr><\/thead>\n <tbody>\n <tr><td class=\"claim\">Oily fish<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">salmon, mackerel, sardines<\/span><\/td>\n <td class=\"who\">Complete protein, high DIAAS. The fat is the point: preformed EPA and DHA.<\/td>\n <td class=\"who\">EPA\/DHA, vitamin D, B12, selenium, iodine<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#093644\">BOTH \u2014 strongly<\/span> The only common food that is both a protein source and the practical solution to several micronutrient floors.<\/td>\n <td><span class=\"tag\" style=\"background:#115A72\">TIER 2<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Shellfish<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">oysters, mussels, clams<\/span><\/td>\n <td class=\"who\">Complete protein, low fat, low energy density.<\/td>\n <td class=\"who\">Zinc (extreme), B12 (extreme), iron, selenium, iodine<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#093644\">MICRO \u2014 outlier<\/span> The most micronutrient-dense foods in the human diet per calorie.<\/td>\n <td><span class=\"tag\" style=\"background:#115A72\">TIER 2<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Organ meat<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">liver<\/span><\/td>\n <td class=\"who\">Complete protein, moderate fat.<\/td>\n <td class=\"who\">Preformed retinol, B12, folate, copper, iron, choline<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#093644\">MICRO \u2014 outlier<\/span> Closes retinol and copper floors nothing else reaches. Vitamin A toxicity is a real ceiling \u2014 do not eat daily.<\/td>\n <td><span class=\"tag\" style=\"background:#115A72\">TIER 2<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Lean white fish<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">cod, haddock, tilapia<\/span><\/td>\n <td class=\"who\">Very high protein per calorie, minimal fat.<\/td>\n <td class=\"who\">Iodine (cod, very high), selenium, B12 \u2014 little EPA\/DHA<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#115A72\">MACRO-leaning<\/span> Excellent protein, but not the omega-3 vehicle oily fish is.<\/td>\n <td><span class=\"tag\" style=\"background:#115A72\">TIER 2<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Red meat<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">beef, lamb<\/span><\/td>\n <td class=\"who\">Complete protein, high DIAAS, variable fat.<\/td>\n <td class=\"who\">Heme iron, zinc, B12, creatine, carnitine<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#115A72\">BOTH<\/span> The most efficient iron and zinc vehicle in ordinary diets. Outcome questions sit at the apex.<\/td>\n <td><span class=\"tag\" style=\"background:#115A72\">TIER 2<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Poultry<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">chicken, turkey<\/span><\/td>\n <td class=\"who\">Among the most efficient protein-per-calorie foods. ~31 g\/100 g cooked breast.<\/td>\n <td class=\"who\">Niacin, B6, selenium, phosphorus, choline<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#115A72\">MACRO \u2014 chiefly<\/span> Iron, zinc and B12 run 3\u20138\u00d7 lower than red meat. A protein instrument, not a micronutrient one.<\/td>\n <td><span class=\"tag\" style=\"background:#115A72\">TIER 2<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Eggs and dairy<\/td>\n <td class=\"who\">Complete protein, highest DIAAS scores of any food.<\/td>\n <td class=\"who\">Choline (eggs), calcium and iodine (dairy), B12, retinol<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#115A72\">BOTH<\/span> Dairy is the only category that closes the calcium floor without supplementation.<\/td>\n <td><span class=\"tag\" style=\"background:#115A72\">TIER 2<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Legumes<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">lentils, beans, chickpeas<\/span><\/td>\n <td class=\"who\">Meaningful protein but DIAAS 55\u201383, plus substantial carbohydrate and fibre.<\/td>\n <td class=\"who\">Folate, potassium, magnesium, non-heme iron (phytate-inhibited)<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#17758C\">MIXED<\/span> The strongest plant protein after soy, and a genuine fibre vehicle. Not a Tier 2 substitute on its own.<\/td>\n <td><span class=\"tag\" style=\"background:#17758C\">TIER 3<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Non-starchy vegetables<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">broccoli, spinach, kale<\/span><\/td>\n <td class=\"who\">Negligible. ~2\u20133 g protein and under 40 kcal per 100 g.<\/td>\n <td class=\"who\">Vitamin C, K1, folate, potassium, carotenoids, nitrate, polyphenols, fibre<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#17758C\">MICRO \u2014 almost purely<\/span> Plus fibre, water and volume. No B12, little bioavailable iron or zinc.<\/td>\n <td><span class=\"tag\" style=\"background:#17758C\">TIER 3<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Whole fruit<\/td>\n <td class=\"who\">Sugar and water. Minimal protein or fat.<\/td>\n <td class=\"who\">Vitamin C, potassium, folate, anthocyanins, fibre<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#17758C\">MICRO + fibre<\/span> The whole-fruit versus juice divergence is among the better-replicated findings in the field.<\/td>\n <td><span class=\"tag\" style=\"background:#17758C\">TIER 3<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Starchy vegetables and grains<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">potato, cassava, wheat, rice<\/span><\/td>\n <td class=\"who\">Genuinely a carbohydrate staple. ~17 g carbohydrate per 100 g potato.<\/td>\n <td class=\"who\">Potassium, some B vitamins; whole grains add fibre and magnesium<\/td>\n <td class=\"who\"><span class=\"tag\" style=\"background:#96600B\">MACRO \u2014 carbohydrate<\/span> Grouping potatoes with broccoli obscures the only thing that matters about them nutritionally.<\/td>\n <td><span class=\"tag\" style=\"background:#96600B\">TIER 4<\/span><\/td><\/tr>\n <\/tbody>\n <\/table>\n <\/div>\n <p class=\"figcap\"><b>Reading the table.<\/b> \"Both\" is rare. Most foods do one job well, and the old pyramid's error was arranging categories that mix jobs rather than categories that share one.<\/p>\n<\/section>\n\n\n<section id=\"form\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Tier 1 \u00b7 The base<\/span>\n <h2>Food form beats food ratio<\/h2>\n <p>The most reproducible causal finding of the last decade is not about macronutrients at all. Hold macros constant, change only the degree of processing, and intake shifts by roughly 500 kcal per day.<\/p>\n <\/div>\n <div class=\"split\">\n <ul class=\"findings\">\n <li><span class=\"pill p-rct\">RCT \u00b7 inpatient<\/span>Ultra-processed versus matched unprocessed diet: <span class=\"val\">+508 kcal\/day<\/span> ad libitum intake and weight gain, with protein, fat, carbohydrate, sugar, sodium and fibre matched between arms. <span class=\"src\">Hall et al. 2019 \u00b7 Cell Metabolism \u00b7 n=20 \u00b7 crossover, fully controlled metabolic ward<\/span><\/li>\n <li><span class=\"pill p-cohort\">Cohort meta<\/span>Industrial trans fat associated with higher all-cause mortality and coronary disease \u2014 roughly <span class=\"val\">21\u201334%<\/span> higher CHD risk \u2014 while saturated fat in the same analysis showed no significant association. <span class=\"src\">de Souza et al. 2015 \u00b7 BMJ \u00b7 systematic review<\/span><\/li>\n <li><span class=\"pill p-mech\">Mechanism<\/span>Energy density, eating rate and reduced satiety per calorie are the leading candidate mediators. The specific mechanism is not settled.<\/li>\n <li><span class=\"pill p-rct\">Policy<\/span>Industrial trans fat is the clearest-cut harmful fat in nutrition science and is being eliminated globally under WHO REPLACE. <b>Ruminant trans fat is a separate question<\/b> and is not clearly associated with harm at usual intakes.<\/li>\n <\/ul>\n <div class=\"card\">\n <h4>Same macros. Different food. 500 kcal.<\/h4>\n <p class=\"sub\">Hall 2019 \u00b7 ad libitum energy intake, kcal\/day<\/p>\n <svg viewBox=\"0 0 420 265\" role=\"img\" aria-label=\"Bar chart: unprocessed diet about 2500 kcal per day versus ultra-processed about 3000, a difference of 508.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <line x1=\"58\" y1=\"200\" x2=\"400\" y2=\"200\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <line x1=\"58\" y1=\"30\" x2=\"58\" y2=\"200\" stroke=\"#E7EDF0\" stroke-width=\"1\"\/>\n <text x=\"52\" y=\"204\" text-anchor=\"end\">0<\/text><text x=\"52\" y=\"120\" text-anchor=\"end\">1500<\/text><text x=\"52\" y=\"36\" text-anchor=\"end\">3000<\/text>\n <\/g>\n <g class=\"grow\">\n <rect x=\"110\" y=\"60\" width=\"82\" height=\"140\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"250\" y=\"30\" width=\"82\" height=\"170\" rx=\"1\" fill=\"#A63525\"\/>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" letter-spacing=\"0.5\">\n <text x=\"151\" y=\"220\" text-anchor=\"middle\" fill=\"#115A72\">UNPROCESSED<\/text>\n <text x=\"151\" y=\"234\" text-anchor=\"middle\" fill=\"#5C6B75\">\u22482500<\/text>\n <text x=\"291\" y=\"220\" text-anchor=\"middle\" fill=\"#A63525\">ULTRA-PROCESSED<\/text>\n <text x=\"291\" y=\"234\" text-anchor=\"middle\" fill=\"#5C6B75\">\u22483000<\/text>\n <\/g>\n <g class=\"reveal\">\n <line x1=\"205\" y1=\"46\" x2=\"237\" y2=\"46\" stroke=\"#0E1A21\" stroke-width=\"1\"\/>\n <text x=\"221\" y=\"40\" text-anchor=\"middle\" font-family=\"Archivo,sans-serif\" font-weight=\"800\" font-size=\"15\" fill=\"#0E1A21\">+508<\/text>\n <\/g>\n <\/svg>\n <p class=\"figcap\">Bar heights drawn to the reported ~500 kcal difference; absolute intakes approximate. <b>Verify before citing.<\/b><\/p>\n <\/div>\n <\/div>\n<\/section>\n\n\n<section id=\"tier2\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Tier 2 \u00b7 Obligate floors<\/span>\n <h2>The protein RDA is a measurement artifact<\/h2>\n <p>0.8 g\/kg\/day derives from nitrogen balance, a method that under-captures losses and extrapolates linearly. Isotope tracer studies using indicator amino acid oxidation put the safe intake near 1.2 g\/kg\/day, and find older adults need at least as much as the young \u2014 not less.<\/p>\n <\/div>\n <div class=\"split\">\n <ul class=\"findings\">\n <li><span class=\"pill p-mech\">Tracer \u00b7 crossover<\/span>IAAO in young men: mean requirement <span class=\"val\">0.93<\/span>, population-safe <span class=\"val\">1.2 g\/kg\/d<\/span> \u2014 roughly 50% above the official RDA. <span class=\"src\">Humayun et al. 2007 \u00b7 Am J Clin Nutr \u00b7 foundational, repeatedly replicated<\/span><\/li>\n <li><span class=\"pill p-mech\">Tracer<\/span>Older adults: EAR \u2248 <span class=\"val\">0.94\u20130.96<\/span>, RDA \u2248 <span class=\"val\">1.24\u20131.29 g\/kg\/d<\/span>, contradicting the assumption that requirement falls with age. <span class=\"src\">Rafii et al. 2015 (men), 2016 (women) \u00b7 J Nutr<\/span><\/li>\n <li><span class=\"pill p-rct\">RCT meta<\/span>Muscle benefit plateaus at <span class=\"val\">1.62 g\/kg\/d<\/span> (95% CI 1.03\u20132.20). Above the upper interval, additional protein buys little. <span class=\"src\">Morton et al. 2018 \u00b7 Br J Sports Med \u00b7 49 studies, n=1863<\/span><\/li>\n <li><span class=\"pill p-mech\">Distribution<\/span>A per-meal threshold of roughly <span class=\"val\">2.5\u20133 g leucine<\/span> (about 25\u201330 g high-quality protein) maximises muscle protein synthesis, with a higher threshold in older adults \u2014 the phenomenon called anabolic resistance.<\/li>\n <li><span class=\"pill p-mech\">Interaction<\/span>Very-low-carbohydrate intake <b>raises protein requirements<\/b>, because amino acids are diverted to gluconeogenesis. One argument for sitting at the upper end of the range on a ketogenic diet.<\/li>\n <li><span class=\"pill p-cohort\">Shortfall<\/span>Choline: roughly <span class=\"val\">90.7%<\/span> of US adults fall below the Adequate Intake. Concentrated in eggs, liver and meat. <span class=\"src\">Wallace & Fulgoni 2017 \u00b7 Nutrients<\/span><\/li>\n <li><span class=\"pill p-mech\">Bioavailability<\/span>B12 requires animal sources. Heme iron absorbs far better than phytate-inhibited non-heme iron. Zinc absorption falls as the phytate-to-zinc molar ratio rises. ALA to DHA conversion runs <span class=\"val\">under 1%<\/span>. <b>BCO1 variants<\/b> substantially reduce beta-carotene to retinol conversion in a large minority.<\/li>\n <\/ul>\n <div class=\"card\">\n <h4>Four numbers, one nutrient<\/h4>\n <p class=\"sub\">Protein intake targets \u00b7 g\/kg body weight\/day<\/p>\n <svg viewBox=\"0 0 420 352\" role=\"img\" aria-label=\"Range chart: official RDA 0.8, IAAO safe intake 1.2, adults over 65 1.0 to 1.2, illness 1.2 to 1.5, resistance training 1.4 to 2.0 with plateau at 1.62.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#5C6B75\">\n <line x1=\"70\" y1=\"300\" x2=\"400\" y2=\"300\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <g stroke=\"#E7EDF0\" stroke-width=\"1\"><line x1=\"70\" y1=\"26\" x2=\"70\" y2=\"300\"\/><line x1=\"220\" y1=\"26\" x2=\"220\" y2=\"300\"\/><line x1=\"370\" y1=\"26\" x2=\"370\" y2=\"300\"\/><\/g>\n <text x=\"70\" y=\"314\" text-anchor=\"middle\">0<\/text><text x=\"220\" y=\"314\" text-anchor=\"middle\">1.0<\/text><text x=\"370\" y=\"314\" text-anchor=\"middle\">2.0<\/text>\n <text x=\"235\" y=\"338\" text-anchor=\"middle\" letter-spacing=\"0.6\">g PROTEIN \/ kg BODY WEIGHT \/ DAY<\/text>\n <\/g>\n <g class=\"reveal\">\n <line x1=\"313\" y1=\"26\" x2=\"313\" y2=\"300\" stroke=\"#A63525\" stroke-width=\"1.2\" stroke-dasharray=\"4 3\"\/>\n <text x=\"309\" y=\"22\" text-anchor=\"end\" font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#A63525\">1.62 PLATEAU<\/text>\n <\/g>\n <g class=\"wipe\">\n <rect x=\"70\" y=\"40\" width=\"120\" height=\"18\" rx=\"1\" fill=\"#D5DDE2\" stroke=\"#5C6B75\" stroke-width=\"1\"\/>\n <rect x=\"70\" y=\"92\" width=\"180\" height=\"18\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"220\" y=\"144\" width=\"30\" height=\"18\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"250\" y=\"196\" width=\"45\" height=\"18\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"280\" y=\"248\" width=\"90\" height=\"18\" rx=\"1\" fill=\"#17758C\"\/>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#0E1A21\">\n <text x=\"70\" y=\"35\">0.8 \u00b7 OFFICIAL RDA \u2014 NITROGEN BALANCE<\/text>\n <text x=\"70\" y=\"87\" fill=\"#115A72\">1.2 \u00b7 IAAO SAFE INTAKE<\/text>\n <text x=\"70\" y=\"139\">1.0\u20131.2 \u00b7 ADULTS 65+<\/text>\n <text x=\"70\" y=\"191\">1.2\u20131.5 \u00b7 ILLNESS<\/text>\n <text x=\"70\" y=\"243\">1.4\u20132.0 \u00b7 RESISTANCE TRAINING<\/text>\n <\/g>\n <\/svg>\n <p class=\"figcap\">The grey bar is the current official figure. Everything beyond it is post-2007 tracer and RCT literature. <b>Higher protein does not harm healthy kidneys or bone<\/b> \u2014 see the misconceptions section.<\/p>\n <\/div>\n <\/div>\n<\/section>\n\n\n<section id=\"carbs\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Tier 4 \u00b7 Deep analysis<\/span>\n <h2>The carbohydrate minimum, quantified<\/h2>\n <p>This is the most misunderstood number in nutrition, in both directions. Carbohydrate is not biochemically essential \u2014 but \"not essential\" is not the same as \"no floor\". There is a real physiological glucose demand, it is quantifiable, and it changes dramatically with metabolic state and life stage.<\/p>\n <\/div>\n\n <div class=\"card reveal\">\n <h4>The daily glucose budget, and who supplies it<\/h4>\n <p class=\"sub\">Grams of glucose per day \u00b7 fed state versus full ketoadaptation<\/p>\n <svg viewBox=\"0 0 960 340\" role=\"img\" aria-labelledby=\"gbt gbd\">\n <title id=\"gbt\">Daily glucose demand in the non-ketoadapted and ketoadapted states<\/title>\n <desc id=\"gbd\">Non-ketoadapted: brain about 120 grams plus obligate tissues about 40 grams, totalling about 160 grams. Ketoadapted: brain falls to about 40 grams, obligate tissues unchanged at 40, totalling about 80 grams, which gluconeogenesis can supply without any dietary carbohydrate.<\/desc>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#5C6B75\">\n <line x1=\"240\" y1=\"230\" x2=\"900\" y2=\"230\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <g stroke=\"#E7EDF0\" stroke-width=\"1\">\n <line x1=\"418\" y1=\"40\" x2=\"418\" y2=\"230\"\/><line x1=\"595\" y1=\"40\" x2=\"595\" y2=\"230\"\/><line x1=\"773\" y1=\"40\" x2=\"773\" y2=\"230\"\/>\n <\/g>\n <text x=\"240\" y=\"248\" text-anchor=\"middle\">0<\/text><text x=\"418\" y=\"248\" text-anchor=\"middle\">50 g<\/text>\n <text x=\"595\" y=\"248\" text-anchor=\"middle\">100 g<\/text><text x=\"773\" y=\"248\" text-anchor=\"middle\">150 g<\/text>\n <text x=\"570\" y=\"272\" text-anchor=\"middle\" letter-spacing=\"0.6\">GRAMS OF GLUCOSE OXIDISED PER DAY<\/text>\n <\/g>\n \n <line x1=\"702\" y1=\"34\" x2=\"702\" y2=\"230\" stroke=\"#96600B\" stroke-width=\"2\" stroke-dasharray=\"5 3\"\/>\n <text x=\"708\" y=\"32\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#96600B\">130 g \u00b7 OFFICIAL RDA<\/text>\n <g class=\"wipe\">\n \n <rect x=\"240\" y=\"66\" width=\"427\" height=\"38\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"667\" y=\"66\" width=\"142\" height=\"38\" rx=\"1\" fill=\"#093644\"\/>\n \n <rect x=\"240\" y=\"140\" width=\"142\" height=\"38\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"382\" y=\"140\" width=\"142\" height=\"38\" rx=\"1\" fill=\"#093644\"\/>\n <\/g>\n <g font-family=\"Archivo,sans-serif\" font-weight=\"700\" font-size=\"12.5\" fill=\"#fff\">\n <text x=\"452\" y=\"90\" text-anchor=\"middle\">BRAIN \u2248120 g<\/text>\n <text x=\"738\" y=\"90\" text-anchor=\"middle\">OBLIGATE \u224840 g<\/text>\n <text x=\"311\" y=\"164\" text-anchor=\"middle\">BRAIN \u224840 g<\/text>\n <text x=\"453\" y=\"164\" text-anchor=\"middle\">OBLIGATE \u224840 g<\/text>\n <\/g>\n <g font-family=\"Source Serif 4,serif\" font-size=\"14.5\" fill=\"#0E1A21\" text-anchor=\"end\">\n <text x=\"228\" y=\"80\">Non-ketoadapted<\/text>\n <text x=\"228\" y=\"154\">Fully ketoadapted<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\" text-anchor=\"end\">\n <text x=\"228\" y=\"96\">GLUCOSE-FUELLED BRAIN<\/text>\n <text x=\"228\" y=\"170\">KETONES SUPPLY 60\u201370%<\/text>\n <\/g>\n <g class=\"reveal\">\n <line x1=\"240\" y1=\"196\" x2=\"524\" y2=\"196\" stroke=\"#093644\" stroke-width=\"2\"\/>\n <line x1=\"240\" y1=\"190\" x2=\"240\" y2=\"202\" stroke=\"#093644\" stroke-width=\"2\"\/>\n <line x1=\"524\" y1=\"190\" x2=\"524\" y2=\"202\" stroke=\"#093644\" stroke-width=\"2\"\/>\n <text x=\"532\" y=\"200\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#093644\">GLUCONEOGENESIS COVERS THIS ENTIRELY \u2014 NO DIETARY CARBOHYDRATE REQUIRED<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <text x=\"240\" y=\"300\">OBLIGATE = ERYTHROCYTES (NO MITOCHONDRIA), RENAL MEDULLA, LENS AND CORNEA \u2014 TISSUES THAT CANNOT USE KETONES AT ALL<\/text>\n <text x=\"240\" y=\"318\">GLUCONEOGENIC SUBSTRATES: LACTATE VIA THE CORI CYCLE, GLYCEROL FROM TRIGLYCERIDE (\u224815\u201320 g\/DAY), AND GLUCOGENIC AMINO ACIDS<\/text>\n <\/g>\n <\/svg>\n <p class=\"figcap\"><b>Why the RDA is 130 g and why that is not a requirement.<\/b> The IOM set the carbohydrate EAR at about 120 g\/day from <i>average minimum brain glucose utilisation<\/i> in the fed state, then the RDA at 130 g. The same report states that the lower limit of dietary carbohydrate compatible with life is <b>essentially zero, provided adequate protein and fat are consumed.<\/b> Both readings are honest: nothing is biochemically essential, and 130 g is the amount that lets the brain run on glucose alone <i>without metabolic adaptation<\/i>. Owen and Cahill's starvation-physiology work established the ketone shift; Cunnane's imaging work shows brain ketone uptake rises in proportion to blood ketone concentration. <b>Verify the DRI wording in the 2005 report, Chapter 6.<\/b><\/p>\n <\/div>\n\n <h3 class=\"sub-h\">Population floors \u2014 where a real carbohydrate requirement appears<\/h3>\n <div class=\"tablewrap reveal\">\n <table>\n <thead><tr><th scope=\"col\">Population<\/th><th scope=\"col\">Recommended carbohydrate<\/th><th scope=\"col\">Basis<\/th><th scope=\"col\">How hard is this floor?<\/th><\/tr><\/thead>\n <tbody>\n <tr><td class=\"claim\">Healthy adult<\/td><td class=\"who\"><span class=\"num\">RDA 130 g\/day<\/span><br>EAR 100 g\/day<br><b>Biochemical minimum: 0<\/b><\/td><td class=\"who\">Average brain glucose oxidation in the fed state. Not derived from any health-outcome trial.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#96600B\">SOFT<\/span> Gluconeogenesis reliably covers demand. Ketogenic diets are metabolically safe short to medium term.<\/td><\/tr>\n <tr><td class=\"claim\">Pregnancy<\/td><td class=\"who\"><span class=\"num\">RDA 175 g\/day<\/span><br>EAR 135 g\/day<\/td><td class=\"who\">Maternal brain glucose plus fetal and placental demand. The fetus is an obligate glucose user.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#115A72\">FIRMER<\/span> Ketogenic diets are cautioned mainly on animal and mechanistic grounds \u2014 <b>human evidence is sparse and low-certainty.<\/b> The caution is prudential, not proven.<\/td><\/tr>\n <tr><td class=\"claim\">Lactation<\/td><td class=\"who\"><span class=\"num\">RDA 210 g\/day<\/span><\/td><td class=\"who\">Glucose demand for lactose synthesis in milk.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#115A72\">FIRMER<\/span> Substantial obligate draw on maternal glucose.<\/td><\/tr>\n <tr><td class=\"claim\">Children and adolescents<\/td><td class=\"who\"><span class=\"num\">RDA 130 g\/day<\/span><\/td><td class=\"who\">Same brain-glucose basis, scaled for size. Growth adds protein and energy demand, not a separate carbohydrate floor.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#96600B\">SOFT\u2013MODERATE<\/span> Therapeutic ketogenic diets are used in paediatric epilepsy under supervision.<\/td><\/tr>\n <tr><td class=\"claim\">Endurance and high-glycolytic athletes<\/td><td class=\"who\"><span class=\"num\">3\u201312 g\/kg\/day<\/span> scaled to training load<\/td><td class=\"who\">Glycogen storage capacity is ~300\u2013600 g (1,200\u20132,400 kcal). Carbohydrate availability limits sustained high-intensity work.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#093644\">HARD, for performance<\/span> Ketoadaptation raises fat oxidation but <b>impairs exercise economy at high intensity<\/b> (Burke 2017, J Physiol).<\/td><\/tr>\n <tr><td class=\"claim\">Type 1 diabetes<\/td><td class=\"who\">No absolute requirement<\/td><td class=\"who\">Carbohydrate counting governs insulin dosing.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#A63525\">CLINICAL<\/span> Low-carbohydrate approaches are used by some patients but complicate insulin titration and ketoacidosis management. Physician involvement essential.<\/td><\/tr>\n <\/tbody>\n <\/table>\n <\/div>\n\n <h3 class=\"sub-h\">Nutritional ketosis is not ketoacidosis \u2014 the numbers are an order of magnitude apart<\/h3>\n <div class=\"card reveal\">\n <h4>Blood beta-hydroxybutyrate concentration<\/h4>\n <p class=\"sub\">mmol\/L \u00b7 the distinction is quantitative, and acidosis is the dividing line<\/p>\n <svg viewBox=\"0 0 960 230\" role=\"img\" aria-label=\"Number line of blood beta-hydroxybutyrate from 0 to 20 millimoles per litre showing fed state below 0.5, nutritional ketosis 0.5 to 3, a gap, and diabetic ketoacidosis above 10 with acidosis.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#5C6B75\">\n <line x1=\"120\" y1=\"150\" x2=\"920\" y2=\"150\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <text x=\"120\" y=\"170\" text-anchor=\"middle\">0<\/text><text x=\"320\" y=\"170\" text-anchor=\"middle\">5<\/text>\n <text x=\"520\" y=\"170\" text-anchor=\"middle\">10<\/text><text x=\"720\" y=\"170\" text-anchor=\"middle\">15<\/text><text x=\"920\" y=\"170\" text-anchor=\"middle\">20<\/text>\n <text x=\"520\" y=\"194\" text-anchor=\"middle\" letter-spacing=\"0.6\">BLOOD \u03b2-HYDROXYBUTYRATE, mmol\/L<\/text>\n <\/g>\n <g class=\"wipe\">\n <rect x=\"120\" y=\"96\" width=\"20\" height=\"40\" rx=\"1\" fill=\"#D5DDE2\"\/>\n <rect x=\"140\" y=\"96\" width=\"100\" height=\"40\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"240\" y=\"96\" width=\"280\" height=\"40\" rx=\"1\" fill=\"#EDF1F3\" stroke=\"#D5DDE2\"\/>\n <rect x=\"520\" y=\"96\" width=\"400\" height=\"40\" rx=\"1\" fill=\"#A63525\"\/>\n <\/g>\n <g font-family=\"Archivo,sans-serif\" font-weight=\"700\" font-size=\"12\" fill=\"#fff\">\n <text x=\"190\" y=\"121\" text-anchor=\"middle\">KETOSIS 0.5\u20133.0<\/text>\n <text x=\"720\" y=\"121\" text-anchor=\"middle\">DIABETIC KETOACIDOSIS >10\u201315<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <text x=\"130\" y=\"86\" text-anchor=\"middle\">FED<\/text>\n <text x=\"380\" y=\"121\" text-anchor=\"middle\" fill=\"#5C6B75\">RARELY OCCUPIED<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\">\n <text x=\"190\" y=\"60\" text-anchor=\"middle\" fill=\"#115A72\">GLUCOSE NORMAL \u00b7 pH NORMAL<\/text>\n <text x=\"720\" y=\"60\" text-anchor=\"middle\" fill=\"#A63525\">ACIDOSIS \u00b7 pH <7.3 \u00b7 LOW BICARBONATE<\/text>\n <\/g>\n <text x=\"120\" y=\"218\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#A63525\">EUGLYCAEMIC KETOACIDOSIS: SGLT2 INHIBITORS CAN PRECIPITATE DKA AT NEAR-NORMAL GLUCOSE, ESPECIALLY DURING LOW-CARBOHYDRATE INTAKE, FASTING, ILLNESS OR SURGERY<\/text>\n <\/svg>\n <p class=\"figcap\"><b>The clinically important interaction.<\/b> Anyone taking an SGLT2 inhibitor \u2014 empagliflozin, dapagliflozin, canagliflozin \u2014 should not combine it with a ketogenic diet without physician oversight. This is the single most actionable safety point in this section.<\/p>\n <\/div>\n\n <h3 class=\"sub-h\">Long-term safety: what is known and what is not<\/h3>\n <ul class=\"findings\">\n <li><span class=\"pill p-conflict\">Observational \u00b7 disputed<\/span><b>The lean mass hyper-responder phenomenon.<\/b> A subset of lean, metabolically healthy low-carb adopters develop LDL-C often exceeding 190 mg\/dL with high HDL and low triglycerides. <b>KETO-CTA<\/b> (2025, JACC Advances) followed roughly 100 such individuals with serial coronary CT angiography for one year and reported that plaque change was not associated with LDL-C or ApoB, with baseline plaque burden the strongest predictor. <b>Read this cautiously:<\/b> single-arm, no control group, one year is short for atherosclerosis, investigators have low-carb ties, and independent cardiologists noted absolute progression did occur. It does not overturn the Mendelian randomisation and RCT evidence that ApoB is causal at population level. <span class=\"src\">Verify all KETO-CTA figures against the primary paper<\/span><\/li>\n <li><span class=\"pill p-cohort\">Clinical<\/span>Kidney stones \u2014 uric acid and calcium \u2014 are a documented risk, best characterised in paediatric epilepsy ketogenic cohorts.<\/li>\n <li><span class=\"pill p-weak\">Low certainty<\/span>Low carbohydrate availability can lower T3. Clinical significance in euthyroid people is uncertain. Poorly formulated ketogenic diets also risk low fibre, thiamine, folate, magnesium and potassium.<\/li>\n <li><span class=\"pill p-rct\">RCT<\/span>Adherence converges. By 12\u201324 months, low-carb versus low-fat weight differences typically lose significance \u2014 <b>DIETFITS<\/b> found no significant difference at 12 months (n=609). <b>Evidence beyond two years is thin<\/b> and dominated by observational data.<\/li>\n <li><span class=\"pill p-cohort\">Cohort + meta<\/span>At the population level the mortality curve is U-shaped, nadir near <span class=\"val\">50\u201355% of energy<\/span>: below 40%, HR \u2248 1.20; above 70%, HR \u2248 1.23. <b>What replaces the carbohydrate dominates<\/b> \u2014 animal substitution HR \u2248 1.18 versus plant substitution HR \u2248 0.82. <span class=\"src\">Seidelmann et al. 2018 \u00b7 Lancet Public Health \u00b7 ARIC plus meta-analysis<\/span><\/li>\n <li><span class=\"pill p-mech\">Clarification<\/span><b>Fibre is a carbohydrate that is separately required.<\/b> It is largely non-glycemic, so it does not count toward the glucose budget above. The 130 g\/day RDA and the 25\u201329 g\/day fibre target are conceptually independent \u2014 one addresses glucose supply, the other colonic and metabolic outcomes.<\/li>\n <\/ul>\n\n <div class=\"card reveal\" style=\"margin-top:1.75rem\">\n <h4>Both ends of the dial carry risk<\/h4>\n <p class=\"sub\"><span style=\"color:#A63525\">Schematic<\/span> \u00b7 Seidelmann 2018 \u00b7 hazard ratio versus carbohydrate share of energy<\/p>\n <svg viewBox=\"0 0 640 300\" role=\"img\" aria-label=\"Schematic U-shaped curve of hazard ratio against carbohydrate percentage of energy, lowest around 50 to 55 percent, about 1.20 at 30 percent and 1.23 at 75 percent.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <line x1=\"80\" y1=\"240\" x2=\"610\" y2=\"240\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <line x1=\"80\" y1=\"20\" x2=\"80\" y2=\"240\" stroke=\"#E7EDF0\" stroke-width=\"1\"\/>\n <text x=\"72\" y=\"34\" text-anchor=\"end\">1.30<\/text><text x=\"72\" y=\"130\" text-anchor=\"end\">1.15<\/text><text x=\"72\" y=\"226\" text-anchor=\"end\">1.00<\/text>\n <line x1=\"80\" y1=\"226\" x2=\"610\" y2=\"226\" stroke=\"#E7EDF0\" stroke-width=\"1\" stroke-dasharray=\"3 3\"\/>\n <text x=\"130\" y=\"258\" text-anchor=\"middle\">30%<\/text><text x=\"270\" y=\"258\" text-anchor=\"middle\">45%<\/text>\n <text x=\"410\" y=\"258\" text-anchor=\"middle\">60%<\/text><text x=\"550\" y=\"258\" text-anchor=\"middle\">75%<\/text>\n <text x=\"340\" y=\"282\" text-anchor=\"middle\" letter-spacing=\"0.6\">CARBOHYDRATE, % OF TOTAL ENERGY<\/text>\n <\/g>\n <g class=\"reveal\">\n <rect x=\"317\" y=\"20\" width=\"47\" height=\"220\" fill=\"#115A72\" fill-opacity=\"0.10\"\/>\n <line x1=\"317\" y1=\"20\" x2=\"317\" y2=\"240\" stroke=\"#115A72\" stroke-width=\"1.5\" stroke-dasharray=\"4 3\"\/>\n <line x1=\"364\" y1=\"20\" x2=\"364\" y2=\"240\" stroke=\"#115A72\" stroke-width=\"1.5\" stroke-dasharray=\"4 3\"\/>\n <text x=\"340\" y=\"16\" text-anchor=\"middle\" font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#115A72\">NADIR 50\u201355%<\/text>\n <\/g>\n <path class=\"draw\" d=\"M130,98 C200,168 270,220 340,226 C410,232 480,176 550,58\" fill=\"none\" stroke=\"#96600B\" stroke-width=\"3\"\/>\n <g class=\"reveal\" font-family=\"IBM Plex Mono,monospace\" font-size=\"12\" font-weight=\"600\" fill=\"#96600B\">\n <text x=\"136\" y=\"88\">1.20<\/text><text x=\"524\" y=\"48\">1.23<\/text>\n <\/g>\n <g class=\"reveal\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#3D4C57\">\n <text x=\"130\" y=\"216\" text-anchor=\"middle\">LOW-CARB<\/text><text x=\"550\" y=\"216\" text-anchor=\"middle\">HIGH-CARB<\/text>\n <\/g>\n <\/svg>\n <p class=\"figcap\"><b>Schematic.<\/b> Endpoints reflect reported hazard ratios; the connecting curve is interpolated. Observational \u2014 residual confounding applies at both extremes, and the substitution finding matters more than the amount.<\/p>\n <\/div>\n\n <dl class=\"dl reveal\">\n <div><dt>If you have type 2 diabetes<\/dt><dd>Both lower-carb and calorie-restriction routes have <b>RCT support<\/b> (Virta, DiRECT 46% remission at 1 year). Choose on adherence, not ideology.<\/dd><\/div>\n <div><dt>If pregnant or lactating<\/dt><dd>Apply the <b>175 and 210 g\/day<\/b> figures and default away from ketogenic eating. The safety evidence is thin, which argues for caution rather than confidence.<\/dd><\/div>\n <div><dt>If on an SGLT2 inhibitor<\/dt><dd><b>Do not combine with ketogenic eating<\/b> without physician oversight \u2014 euglycaemic ketoacidosis risk.<\/dd><\/div>\n <div><dt>If training hard<\/dt><dd><b>3\u201312 g\/kg\/day<\/b> by load. The population U-curve nadir is not a ceiling for trained people.<\/dd><\/div>\n <div><dt>Whatever you set<\/dt><dd>Tier 1 still governs. <b>Refined and ultra-processed carbohydrate<\/b> is the portion carrying consistent harm signals.<\/dd><\/div>\n <div><dt>If your LDL climbs sharply<\/dt><dd>Get <b>ApoB and lipoprotein testing<\/b> and cardiology input. Do not assume single-arm data exonerate high ApoB.<\/dd><\/div>\n <\/dl>\n<\/section>\n\n\n<section id=\"fats\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Deep analysis \u00b7 every class, with dosage<\/span>\n <h2>Fats: only two are essential, and the rest is dosing<\/h2>\n <p>\"Eat healthy fats\" is not actionable. Below is every fat class with whether a true physiological requirement exists, the quantitative target, the basis for it, and whether the evidence is settled or contested. Two entries are genuinely essential nutrients; the rest are dosing questions of varying certainty.<\/p>\n <\/div>\n\n <div class=\"tablewrap reveal\">\n <table>\n <thead><tr><th scope=\"col\">Fat class<\/th><th scope=\"col\">Truly essential?<\/th><th scope=\"col\">Daily target<\/th><th scope=\"col\">Basis and evidence<\/th><th scope=\"col\">Status<\/th><\/tr><\/thead>\n <tbody>\n <tr><td class=\"claim\">Total fat<\/td><td class=\"who\">No<\/td><td class=\"who\"><span class=\"num\">20\u201335% of energy<\/span> (AMDR)<\/td><td class=\"who\">Below ~20% risks essential fatty acid and fat-soluble vitamin inadequacy and raises triglycerides on high-carb refeeding. There is no requirement for a specific total-fat percentage \u2014 only for the two essentials below.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#96600B\">MILDLY CONTESTED<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Linoleic acid<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">omega-6, C18:2<\/span><\/td><td class=\"who\"><b>Yes \u2014 essential<\/b><\/td><td class=\"who\"><span class=\"num\">17 g\/day men<br>12 g\/day women<\/span> (AI)<br>Deficiency prevented at ~1\u20132% energy<\/td><td class=\"who\">Depletion\u2013repletion studies (foundational). <b>The \"high omega-6 is harmful\" claim is not supported in humans:<\/b> Marklund 2019 Circulation pooled 30 cohorts using circulating linoleic acid biomarkers (n\u224868,000+) and found <b>higher<\/b> linoleic acid associated with <b>lower<\/b> CVD and all-cause mortality. Controlled feeding does not show LA raising CRP.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#093644\">ESSENTIAL \u00b7 harm claim refuted<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Alpha-linolenic acid<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">omega-3 plant, C18:3<\/span><\/td><td class=\"who\"><b>Yes \u2014 essential<\/b><\/td><td class=\"who\"><span class=\"num\">1.6 g\/day men<br>1.1 g\/day women<\/span> (AI)<\/td><td class=\"who\">Conversion to EPA is ~5\u20138%; to DHA under 0.5\u20134%, higher in women. <b>ALA alone does not meaningfully raise DHA status<\/b>, which is why direct marine intake matters for those targeting DHA.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#093644\">ESSENTIAL<\/span><\/td><\/tr>\n <tr><td class=\"claim\">EPA and DHA<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">long-chain marine omega-3<\/span><\/td><td class=\"who\">Conditionally<\/td><td class=\"who\"><span class=\"num\">250 mg\/day<\/span> (EFSA)<br><span class=\"num\">+200 mg DHA<\/span> in pregnancy<br>AHA: 1\u20132 servings oily fish\/week<\/td><td class=\"who\">Cohorts support fish; <b>supplement RCTs conflict.<\/b> REDUCE-IT (4 g EPA, high-risk statin-treated) HR 0.75 (0.68\u20130.83); STRENGTH, VITAL primary, ASCEND all null; Cochrane 2020 found \"little or no effect\". Where supplements work it appears to need high-dose EPA in high-risk patients, not general-population fish oil.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#A63525\">FOOD YES \u00b7 PILLS CONTESTED<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Saturated fatty acids<\/td><td class=\"who\">No<\/td><td class=\"who\"><span class=\"num\"><10% of energy<\/span><\/td><td class=\"who\">Heavily contested. Hooper 2020 Cochrane: reducing SFA cut combined cardiovascular <b>events<\/b> 17% (RR 0.83, 0.76\u20130.90) but had little or no effect on <b>mortality<\/b>; benefit greatest when replaced by polyunsaturated fat. Siri-Tarino 2010, Chowdhury 2014, de Souza 2015 found no clear association. Astrup 2020 JACC argued against a blanket limit and drew rebuttals.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#A63525\">GENUINELY CONTESTED<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Monounsaturated fat<\/td><td class=\"who\">No<\/td><td class=\"who\">No formal target<\/td><td class=\"who\">PREDIMED: Mediterranean diet plus extra-virgin olive oil HR 0.69 (0.53\u20130.91) or nuts HR 0.72 (0.54\u20130.95) for major cardiovascular events \u2014 one landmark RCT, with a randomisation irregularity that forced republication. Cohorts associate olive oil intake with lower mortality.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#115A72\">FAVOURABLE<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Industrial trans fat<\/td><td class=\"who\">No \u2014 avoid<\/td><td class=\"who\"><span class=\"num\"><1% of energy<\/span><br>Target: near zero<\/td><td class=\"who\">de Souza 2015: ~21\u201334% higher CHD risk and higher all-cause mortality. The clearest-cut harmful fat in the field; WHO REPLACE targets global elimination.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#093644\">NOT CONTESTED<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Ruminant trans fat<br><span class=\"mono\" style=\"font-size:.75rem;color:var(--ink-3)\">vaccenic acid, CLA<\/span><\/td><td class=\"who\">No<\/td><td class=\"who\">No limit needed at usual intakes<\/td><td class=\"who\">A separate question from industrial trans fat. Not clearly associated with harm at the amounts naturally present in dairy and meat.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#96600B\">UNCERTAIN<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Dietary cholesterol<\/td><td class=\"who\">No<\/td><td class=\"who\">No numeric cap since 2015<\/td><td class=\"who\">The 300 mg\/day limit was removed from US guidance because dietary cholesterol affects serum LDL weakly relative to saturated and trans fat. Roughly one-third are \"hyper-responders\" whose serum cholesterol rises appreciably; two-thirds change little. Egg literature conflicts: Zhong 2019 JAMA found higher risk per half-egg\/day; many other cohorts and short RCTs are null.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#A63525\">CONTESTED<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Medium-chain triglycerides<\/td><td class=\"who\">No<\/td><td class=\"who\">No target<\/td><td class=\"who\">Rapidly absorbed and ketogenic; used in cognition research and some weight contexts. Effects modest and inconsistent.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#96600B\">PRELIMINARY<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Omega-6 to omega-3 ratio<\/td><td class=\"who\">Not a real target<\/td><td class=\"who\">Do not manage the ratio<\/td><td class=\"who\"><b>Largely superseded by absolute intakes.<\/b> Because linoleic acid is not demonstrably harmful, lowering omega-6 to \"fix the ratio\" is unsupported. Raising omega-3 in absolute terms is the defensible lever. EFSA and most expert reviews do not endorse a ratio target.<\/td><td class=\"who\"><span class=\"tag\" style=\"background:#A63525\">OBSOLETE CONCEPT<\/span><\/td><\/tr>\n <\/tbody>\n <\/table>\n <\/div>\n\n <div class=\"grid2\" style=\"margin-top:1.75rem\">\n <div class=\"card reveal\">\n <h4>A saturated fat gram is not just a saturated fat gram<\/h4>\n <p class=\"sub\">Relative LDL-raising effect by individual fatty acid<\/p>\n <svg viewBox=\"0 0 620 300\" role=\"img\" aria-label=\"Bar chart of LDL-raising effect: myristic acid highest, palmitic next, lauric acid moderate and also raises HDL, stearic acid essentially neutral.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <line x1=\"300\" y1=\"230\" x2=\"300\" y2=\"24\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <line x1=\"300\" y1=\"230\" x2=\"600\" y2=\"230\" stroke=\"#E7EDF0\" stroke-width=\"1\"\/>\n <text x=\"300\" y=\"248\" text-anchor=\"middle\">NEUTRAL<\/text>\n <text x=\"480\" y=\"248\" text-anchor=\"middle\">RAISES LDL \u2192<\/text>\n <\/g>\n <g class=\"wipe\">\n <rect x=\"300\" y=\"34\" width=\"248\" height=\"34\" rx=\"1\" fill=\"#A63525\"\/>\n <rect x=\"300\" y=\"82\" width=\"195\" height=\"34\" rx=\"1\" fill=\"#A63525\"\/>\n <rect x=\"300\" y=\"130\" width=\"135\" height=\"34\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"300\" y=\"178\" width=\"6\" height=\"34\" rx=\"1\" fill=\"#115A72\"\/>\n <\/g>\n <g font-family=\"Source Serif 4,serif\" font-size=\"13.5\" fill=\"#0E1A21\" text-anchor=\"end\">\n <text x=\"290\" y=\"56\">Myristic \u00b7 C14:0<\/text>\n <text x=\"290\" y=\"104\">Palmitic \u00b7 C16:0<\/text>\n <text x=\"290\" y=\"152\">Lauric \u00b7 C12:0<\/text>\n <text x=\"290\" y=\"200\">Stearic \u00b7 C18:0<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#5C6B75\" text-anchor=\"end\">\n <text x=\"290\" y=\"70\">BUTTERFAT, COCONUT<\/text>\n <text x=\"290\" y=\"118\">MEAT, PALM OIL<\/text>\n <text x=\"290\" y=\"166\">COCONUT \u2014 ALSO RAISES HDL<\/text>\n <text x=\"290\" y=\"214\">COCOA, BEEF FAT \u2014 CONVERTS TO OLEIC<\/text>\n <\/g>\n <text x=\"300\" y=\"278\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#0E1A21\">COCONUT OIL RAISED LDL BY 10.47 mg\/dL (95% CI 3.01\u201317.94) VS NON-TROPICAL OILS<\/text>\n <text x=\"300\" y=\"294\" font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#5C6B75\">NEELAKANTAN 2020 \u00b7 CIRCULATION \u00b7 META-ANALYSIS OF 16 TRIALS<\/text>\n <\/svg>\n <p class=\"figcap\">Relative magnitudes are illustrative of the established ordering, not extracted effect sizes. <b>Stearic acid is essentially LDL-neutral<\/b> because much of it is desaturated to oleic acid \u2014 which is why beef fat and cocoa butter behave differently from butterfat and coconut oil.<\/p>\n <\/div>\n <div class=\"card reveal\">\n <h4>The dairy matrix problem<\/h4>\n <p class=\"sub\">Why similar saturated fat behaves differently<\/p>\n <ul class=\"findings\" style=\"margin-top:0.2rem\">\n <li><span class=\"pill p-cohort\">Cohort + lipid RCT<\/span><b>Cheese and yogurt appear metabolically neutral to favourable<\/b>, while <b>butter raises LDL more<\/b>, despite comparable saturated fat content. Fermented dairy is associated with neutral or lower cardiometabolic risk in cohorts.<\/li>\n <li><span class=\"pill p-mech\">Candidate mechanisms<\/span>Calcium\u2013fatty-acid soap formation reducing fat absorption; the milk fat globule membrane; fermentation-derived bioactives; probiotic effects.<\/li>\n <li><span class=\"pill p-mech\">Why it matters<\/span>This is the leading real-world demonstration that <b>the food matrix modifies a nutrient's effect<\/b> \u2014 the same principle that explains the fish-versus-fish-oil discrepancy and the produce-versus-antioxidant-supplement failure.<\/li>\n <li><span class=\"pill p-weak\">Overstated claim<\/span><b>\"Grass-fed beef is dramatically healthier\"<\/b> \u2014 grass-fed has a modestly better fatty acid profile (more omega-3 and CLA), but absolute differences are small and <b>no outcome trials show meaningful benefit<\/b> over grain-fed.<\/li>\n <li><span class=\"pill p-conflict\">Refuted claim<\/span><b>\"Coconut oil is heart-healthy\"<\/b> \u2014 the meta-analysis above shows it raises LDL relative to unsaturated oils with no benefit on weight, waist or glycemia.<\/li>\n <\/ul>\n <\/div>\n <\/div>\n<\/section>\n\n\n<section id=\"fibre\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Tier 3 \u00b7 Fibre, vegetables and fruit<\/span>\n <h2>The strongest plant signal is fibre \u2014 and the mechanism is unidentified<\/h2>\n <p>The observational case for vegetables and fruit is strong and consistent. Nearly every attempt to isolate the responsible compound and test it has failed, sometimes harmfully. That pattern is itself one of the most informative findings in nutrition science.<\/p>\n <\/div>\n <div class=\"split\">\n <ul class=\"findings\">\n <li><span class=\"pill p-cohort\">Cohort meta + RCTs<\/span>Highest versus lowest fibre intake: all-cause mortality <span class=\"val\">RR 0.85<\/span> (95% CI 0.79\u20130.91), with 15\u201330% reductions across coronary disease, type 2 diabetes and colorectal cancer. Dose-responsive, greatest benefit at <span class=\"val\">25\u201329 g\/day<\/span> and possibly beyond. <span class=\"src\">Reynolds & Mann 2019 \u00b7 Lancet \u00b7 185 prospective studies + 58 RCTs<\/span><\/li>\n <li><span class=\"pill p-cohort\">Cohort meta<\/span>Fruit and vegetables, per 200 g\/day increment: all-cause mortality <span class=\"val\">RR \u2248 0.90<\/span>, CVD \u2248 0.92, cancer \u2248 0.97. Benefit continues to roughly <span class=\"val\">800 g\/day<\/span> for mortality, with cancer plateauing nearer 600 g. <span class=\"src\">Aune et al. 2017 \u00b7 Int J Epidemiol \u00b7 95 studies, ~2 million participants<\/span><\/li>\n <li><span class=\"pill p-cohort\">Pooled cohorts<\/span>Lowest mortality at about <span class=\"val\">5 servings\/day<\/span> \u2014 2 fruit plus 3 vegetables \u2014 with no further benefit above that. <b>Starchy vegetables, potatoes and fruit juices showed no association with benefit.<\/b> <span class=\"src\">Wang et al. 2021 \u00b7 Circulation<\/span><\/li>\n <li><span class=\"pill p-conflict\">The RCT gap<\/span><b>There is no large hard-outcome randomised trial showing increased vegetable intake reduces mortality.<\/b> Cochrane reviews of fruit and vegetable interventions for cardiovascular prevention found limited evidence confined largely to biomarkers. Anyone claiming trial-grade proof is overstating.<\/li>\n <li><span class=\"pill p-rct\">RCT \u00b7 mechanism<\/span>What <i>is<\/i> trial-established is intermediate. DASH's combination diet reduced systolic pressure meaningfully; the fruit-and-vegetable-only arm produced a smaller but real reduction. <span class=\"src\">Appel et al. 1997 \u00b7 NEJM \u00b7 foundational<\/span><\/li>\n <li><span class=\"pill p-rct\">RCT \u00b7 mechanism<\/span>Dietary nitrate from leafy greens and beetroot lowers systolic pressure roughly <span class=\"val\">4\u20135 mmHg<\/span> via the nitrate\u2013nitrite\u2013nitric oxide pathway \u2014 one of few genuinely RCT-backed specific mechanisms here. <span class=\"src\">Siervo et al. 2013 \u00b7 J Nutr<\/span><\/li>\n <li><span class=\"pill p-cohort\">Specificity<\/span>Leafy greens were associated with lower type 2 diabetes risk where total fruit and vegetable intake was not \u2014 suggesting the category is too coarse to be the right unit of analysis. <span class=\"src\">Carter et al. 2010 \u00b7 BMJ<\/span><\/li>\n <li><span class=\"pill p-cohort\">Well replicated<\/span>Whole fruit is associated with <b>lower<\/b> type 2 diabetes risk while fruit juice is associated with <b>higher<\/b> risk, and substituting whole fruit for juice is associated with reduced risk. Same sugars, different matrix. <span class=\"src\">Muraki et al. 2013 \u00b7 BMJ<\/span><\/li>\n <li><span class=\"pill p-mech\">Bioavailability<\/span>Spinach iron and calcium are heavily oxalate-bound; non-heme iron is phytate-inhibited; carotenoid absorption requires fat and improves with cooking; BCO1 variants limit beta-carotene conversion. <b>Vegetables supply no B12.<\/b><\/li>\n <li><span class=\"pill p-rct\">Displacement<\/span>Lowering dietary energy density reduces energy intake, and vegetables' water and fibre content is the main lever. A large share of the benefit may be <b>what vegetables push off the plate.<\/b> <span class=\"src\">Rolls and colleagues \u00b7 controlled feeding<\/span><\/li>\n <li><span class=\"pill p-weak\">Conditional<\/span>Exceptions exist and are not an anti-vegetable case: FODMAP-sensitive individuals with IBS, and oxalate restriction for recurrent stone formers.<\/li>\n <\/ul>\n <div>\n <div class=\"card\">\n <h4>Dose-response, with a plateau<\/h4>\n <p class=\"sub\"><span style=\"color:#A63525\">Schematic<\/span> \u00b7 Aune 2017 \u00b7 all-cause mortality<\/p>\n <svg viewBox=\"0 0 620 330\" role=\"img\" aria-label=\"Schematic descending curve of relative risk from 1.0 to about 0.69 at 800 grams per day of fruit and vegetables, then flattening.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <line x1=\"70\" y1=\"250\" x2=\"600\" y2=\"250\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <line x1=\"70\" y1=\"20\" x2=\"70\" y2=\"250\" stroke=\"#E7EDF0\" stroke-width=\"1\"\/>\n <text x=\"62\" y=\"34\" text-anchor=\"end\">1.00<\/text><text x=\"62\" y=\"125\" text-anchor=\"end\">0.85<\/text><text x=\"62\" y=\"216\" text-anchor=\"end\">0.70<\/text>\n <text x=\"70\" y=\"268\" text-anchor=\"middle\">0<\/text><text x=\"188\" y=\"268\" text-anchor=\"middle\">200 g<\/text>\n <text x=\"306\" y=\"268\" text-anchor=\"middle\">400 g<\/text><text x=\"423\" y=\"268\" text-anchor=\"middle\">600 g<\/text><text x=\"541\" y=\"268\" text-anchor=\"middle\">800 g<\/text>\n <text x=\"335\" y=\"292\" text-anchor=\"middle\" letter-spacing=\"0.6\">FRUIT AND VEGETABLE INTAKE, g\/DAY<\/text>\n <\/g>\n <g class=\"reveal\">\n <rect x=\"541\" y=\"20\" width=\"59\" height=\"230\" fill=\"#17758C\" fill-opacity=\"0.10\"\/>\n <line x1=\"541\" y1=\"20\" x2=\"541\" y2=\"250\" stroke=\"#17758C\" stroke-width=\"1.5\" stroke-dasharray=\"4 3\"\/>\n <text x=\"570\" y=\"16\" text-anchor=\"middle\" font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#17758C\">PLATEAU<\/text>\n <\/g>\n <path class=\"draw\" d=\"M70,34 C120,60 150,80 188,95 C240,115 280,132 306,143 C350,162 395,175 423,180 C470,196 515,214 541,222 L600,224\" fill=\"none\" stroke=\"#17758C\" stroke-width=\"3\"\/>\n <g class=\"reveal\">\n <circle cx=\"541\" cy=\"222\" r=\"5\" fill=\"#17758C\"\/>\n <text x=\"533\" y=\"243\" text-anchor=\"end\" font-family=\"IBM Plex Mono,monospace\" font-size=\"12\" font-weight=\"600\" fill=\"#17758C\">\u22480.69<\/text>\n <\/g>\n <text x=\"70\" y=\"318\" font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#5C6B75\">OBSERVATIONAL. RESIDUAL CONFOUNDING AND HEALTHY-USER BIAS APPLY.<\/text>\n <\/svg>\n <\/div>\n <div class=\"card\" style=\"margin-top:1.25rem\">\n <h4>What happened when the compounds were tested alone<\/h4>\n <p class=\"sub\">Isolated micronutrient RCTs \u00b7 above 1.0 indicates harm<\/p>\n <svg viewBox=\"0 0 620 300\" role=\"img\" aria-label=\"Bar chart of harm: ATBC beta-carotene 1.18, CARET beta-carotene and retinol 1.28, CARET total mortality 1.17, SELECT vitamin E 1.17.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <line x1=\"150\" y1=\"215\" x2=\"600\" y2=\"215\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <text x=\"150\" y=\"233\" text-anchor=\"middle\">1.00<\/text><text x=\"300\" y=\"233\" text-anchor=\"middle\">1.10<\/text>\n <text x=\"450\" y=\"233\" text-anchor=\"middle\">1.20<\/text><text x=\"600\" y=\"233\" text-anchor=\"middle\">1.30<\/text>\n <\/g>\n <line x1=\"150\" y1=\"16\" x2=\"150\" y2=\"215\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <g class=\"wipe\">\n <rect x=\"150\" y=\"26\" width=\"270\" height=\"30\" rx=\"1\" fill=\"#A63525\"\/>\n <rect x=\"150\" y=\"70\" width=\"420\" height=\"30\" rx=\"1\" fill=\"#A63525\"\/>\n <rect x=\"150\" y=\"114\" width=\"255\" height=\"30\" rx=\"1\" fill=\"#A63525\"\/>\n <rect x=\"150\" y=\"158\" width=\"255\" height=\"30\" rx=\"1\" fill=\"#A63525\"\/>\n <\/g>\n <g font-family=\"Source Serif 4,serif\" font-size=\"12.5\" fill=\"#0E1A21\" text-anchor=\"end\">\n <text x=\"140\" y=\"40\">ATBC \u00b7 \u03b2-carotene<\/text><text x=\"140\" y=\"84\">CARET \u00b7 \u03b2-carotene+retinol<\/text>\n <text x=\"140\" y=\"128\">CARET \u00b7 total mortality<\/text><text x=\"140\" y=\"172\">SELECT \u00b7 vitamin E<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"11\" font-weight=\"600\" fill=\"#A63525\">\n <text x=\"430\" y=\"46\">1.18<\/text><text x=\"580\" y=\"90\">1.28<\/text><text x=\"415\" y=\"134\">1.17<\/text><text x=\"415\" y=\"178\">1.17<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"9\" fill=\"#5C6B75\" text-anchor=\"end\">\n <text x=\"140\" y=\"53\">LUNG CANCER, SMOKERS<\/text><text x=\"140\" y=\"97\">LUNG CANCER \u00b7 STOPPED EARLY<\/text>\n <text x=\"140\" y=\"141\">ALL-CAUSE<\/text><text x=\"140\" y=\"185\">PROSTATE CANCER<\/text>\n <\/g>\n <text x=\"150\" y=\"266\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#0E1A21\">EVERY BAR POINTS THE WRONG WAY.<\/text>\n <text x=\"150\" y=\"284\" font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#5C6B75\">THE BENEFIT OF PRODUCE IS NOT ITS ANTIOXIDANT VITAMINS.<\/text>\n <\/svg>\n <\/div>\n <\/div>\n <\/div>\n <div class=\"callout reveal\">\n <span class=\"eyebrow\">What this actually establishes<\/span>\n <p>The failure of the supplement trials is the strongest argument <strong>for<\/strong> eating vegetables as food and <strong>against<\/strong> believing we know why they work. Four explanations remain live: the food matrix does something isolated compounds cannot; fibre and potassium carry most of the effect; vegetables displace worse foods; or the cohort signal is substantially healthy-user bias. <strong>These have very different implications, and the literature does not currently distinguish between them.<\/strong> What survives regardless: eat the plants, don't buy the extract.<\/p>\n <\/div>\n<\/section>\n\n\n<section id=\"fish\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Tier 2 instruments \u00b7 and one clean paradox<\/span>\n <h2>Fish earns Tier 2. \"Fish prevents heart disease\" does not.<\/h2>\n <p>These are two different claims carrying very different certainty. Fish delivers nutrients that are difficult or impossible to obtain elsewhere \u2014 that is biochemistry, and it is solid. Whether eating it lowers cardiovascular risk is separate, and the trials that tested the active ingredient directly did not agree.<\/p>\n <\/div>\n <div class=\"split\">\n <ul class=\"findings\">\n <li><span class=\"pill p-mech\">Biochemistry<\/span>Conversion of plant ALA to <span class=\"val\">DHA is under 1%<\/span>. Preformed marine EPA and DHA are therefore close to obligate unless algal oil is used.<\/li>\n <li><span class=\"pill p-mech\">Composition<\/span>Shellfish are micronutrient outliers. Oyster zinc and B12 exceed essentially every other common food; mussels supply substantial B12 and reasonably bioavailable iron. Cod and haddock are among the densest natural iodine sources.<\/li>\n <li><span class=\"pill p-cohort\">Cohort meta<\/span>Fish shows a consistent modest inverse association with coronary death and stroke, with the <span class=\"val\">curve flattening early<\/span> \u2014 roughly one to two servings of oily fish weekly, on the order of 250 mg\/day EPA+DHA, captures most of the observed benefit. <span class=\"src\">Mozaffarian & Rimm 2006 JAMA (foundational); Chowdhury 2012 BMJ<\/span><\/li>\n <li><span class=\"pill p-cohort\">Cohort<\/span><b>An important qualifier:<\/b> in PURE the association concentrated in higher-risk and secondary-prevention populations, with little signal in low-risk general populations. Benefit may be conditional on baseline risk. <span class=\"src\">Mohan et al. 2021 \u00b7 JAMA Intern Med<\/span><\/li>\n <li><span class=\"pill p-cohort\">Cohort<\/span>Preparation and species matter. Baked or broiled fish carried the association; <b>fried fish did not.<\/b> Oily fish carry it more strongly than lean white fish.<\/li>\n <li><span class=\"pill p-conflict\">Heterogeneous<\/span>Fish and type 2 diabetes is genuinely inconsistent by region \u2014 inverse in several Asian cohorts, null or positive in some US and European ones. Not a settled benefit.<\/li>\n <li><span class=\"pill p-rct\">Risk\u2013benefit<\/span>On mercury, <b>restricting fish in pregnancy appears to be the larger risk.<\/b> Maternal seafood intake below ~340 g\/week was associated with higher odds of suboptimal child verbal IQ. FAO\/WHO and EFSA conclude benefits generally outweigh methylmercury risk with species-specific caution. <span class=\"src\">Hibbeln et al. 2007 \u00b7 Lancet \u00b7 ALSPAC. Avoid swordfish, shark, king mackerel, tilefish, bigeye tuna. Salmon, sardines, anchovies, shrimp, oysters are low-mercury.<\/span><\/li>\n <\/ul>\n <div class=\"card\">\n <h4>EPA + DHA by species<\/h4>\n <p class=\"sub\">Grams per 100 g cooked \u00b7 varies with feed and season<\/p>\n <svg viewBox=\"0 0 640 400\" role=\"img\" aria-label=\"Bar chart of EPA plus DHA per 100 grams: mackerel 2.6, farmed salmon 2.3, anchovy 2.1, herring 1.8, sardine 1.5, albacore tuna 0.8, mussels 0.7, oysters 0.5, shrimp 0.3, cod 0.2, tilapia 0.15.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <g stroke=\"#E7EDF0\" stroke-width=\"1\"><line x1=\"311\" y1=\"16\" x2=\"311\" y2=\"340\"\/><line x1=\"472\" y1=\"16\" x2=\"472\" y2=\"340\"\/><\/g>\n <line x1=\"150\" y1=\"340\" x2=\"610\" y2=\"340\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <text x=\"150\" y=\"357\" text-anchor=\"middle\">0<\/text><text x=\"311\" y=\"357\" text-anchor=\"middle\">1.0 g<\/text><text x=\"472\" y=\"357\" text-anchor=\"middle\">2.0 g<\/text>\n <\/g>\n <g class=\"wipe\">\n <rect x=\"150\" y=\"22\" width=\"418\" height=\"20\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"150\" y=\"50\" width=\"370\" height=\"20\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"150\" y=\"78\" width=\"338\" height=\"20\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"150\" y=\"106\" width=\"290\" height=\"20\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"150\" y=\"134\" width=\"241\" height=\"20\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"150\" y=\"162\" width=\"129\" height=\"20\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"150\" y=\"190\" width=\"113\" height=\"20\" rx=\"1\" fill=\"#17758C\"\/>\n <rect x=\"150\" y=\"218\" width=\"80\" height=\"20\" rx=\"1\" fill=\"#17758C\"\/>\n <rect x=\"150\" y=\"246\" width=\"48\" height=\"20\" rx=\"1\" fill=\"#17758C\"\/>\n <rect x=\"150\" y=\"274\" width=\"32\" height=\"20\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"150\" y=\"302\" width=\"24\" height=\"20\" rx=\"1\" fill=\"#96600B\"\/>\n <\/g>\n <g font-family=\"Source Serif 4,serif\" font-size=\"13\" fill=\"#0E1A21\" text-anchor=\"end\">\n <text x=\"140\" y=\"37\">Mackerel<\/text><text x=\"140\" y=\"65\">Salmon, farmed<\/text><text x=\"140\" y=\"93\">Anchovy<\/text>\n <text x=\"140\" y=\"121\">Herring<\/text><text x=\"140\" y=\"149\">Sardine<\/text><text x=\"140\" y=\"177\">Tuna, albacore<\/text>\n <text x=\"140\" y=\"205\">Mussels<\/text><text x=\"140\" y=\"233\">Oysters<\/text><text x=\"140\" y=\"261\">Shrimp<\/text>\n <text x=\"140\" y=\"289\">Cod<\/text><text x=\"140\" y=\"317\">Tilapia<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#3D4C57\">\n <text x=\"576\" y=\"37\">2.6<\/text><text x=\"528\" y=\"65\">2.3<\/text><text x=\"496\" y=\"93\">2.1<\/text><text x=\"448\" y=\"121\">1.8<\/text>\n <text x=\"399\" y=\"149\">1.5<\/text><text x=\"287\" y=\"177\">0.8<\/text><text x=\"271\" y=\"205\">0.7<\/text><text x=\"238\" y=\"233\">0.5<\/text>\n <text x=\"206\" y=\"261\">0.3<\/text><text x=\"190\" y=\"289\">0.2<\/text><text x=\"182\" y=\"317\">0.15<\/text>\n <\/g>\n <text x=\"150\" y=\"386\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">TWO SERVINGS\/WEEK OF THE TOP FIVE \u2248 WHERE THE COHORT CURVE FLATTENS<\/text>\n <\/svg>\n <div class=\"legend\">\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#093644\"><\/span>Oily fish<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#17758C\"><\/span>Shellfish<\/div>\n <div class=\"legend-item\"><span class=\"chip\" style=\"background:#96600B\"><\/span>Lean white fish<\/div>\n <\/div>\n <\/div>\n <\/div>\n\n <div class=\"card reveal\" style=\"margin-top:1.75rem\">\n <h4>The paradox, drawn properly: whole fish versus the purified active ingredient<\/h4>\n <p class=\"sub\">Forest plot \u00b7 cardiovascular endpoints \u00b7 point estimate with 95% confidence interval<\/p>\n <svg viewBox=\"0 0 900 400\" role=\"img\" aria-label=\"Forest plot: fish cohorts about 0.88, REDUCE-IT 0.75, VITAL 0.92 crossing 1, ASCEND 0.97 crossing 1, STRENGTH 0.99 crossing 1, Cochrane pooled 0.98 crossing 1.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#5C6B75\">\n <line x1=\"300\" y1=\"320\" x2=\"830\" y2=\"320\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <text x=\"300\" y=\"338\" text-anchor=\"middle\">0.60<\/text><text x=\"448\" y=\"338\" text-anchor=\"middle\">0.80<\/text>\n <text x=\"597\" y=\"338\" text-anchor=\"middle\">1.00<\/text><text x=\"746\" y=\"338\" text-anchor=\"middle\">1.20<\/text>\n <\/g>\n <line x1=\"597\" y1=\"20\" x2=\"597\" y2=\"320\" stroke=\"#0E1A21\" stroke-width=\"1.5\" stroke-dasharray=\"4 3\"\/>\n <text x=\"603\" y=\"18\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#0E1A21\">NO EFFECT<\/text>\n <text x=\"440\" y=\"362\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#093644\">\u2190 BENEFIT<\/text>\n <text x=\"700\" y=\"362\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#A63525\">HARM \u2192<\/text>\n <g class=\"reveal\">\n <line x1=\"471\" y1=\"46\" x2=\"545\" y2=\"46\" stroke=\"#093644\" stroke-width=\"2.5\"\/>\n <line x1=\"471\" y1=\"40\" x2=\"471\" y2=\"52\" stroke=\"#093644\" stroke-width=\"2\"\/><line x1=\"545\" y1=\"40\" x2=\"545\" y2=\"52\" stroke=\"#093644\" stroke-width=\"2\"\/>\n <rect x=\"500\" y=\"38\" width=\"16\" height=\"16\" fill=\"#093644\"\/>\n <line x1=\"359\" y1=\"92\" x2=\"471\" y2=\"92\" stroke=\"#115A72\" stroke-width=\"2.5\"\/>\n <line x1=\"359\" y1=\"86\" x2=\"359\" y2=\"98\" stroke=\"#115A72\" stroke-width=\"2\"\/><line x1=\"471\" y1=\"86\" x2=\"471\" y2=\"98\" stroke=\"#115A72\" stroke-width=\"2\"\/>\n <rect x=\"403\" y=\"84\" width=\"16\" height=\"16\" fill=\"#115A72\"\/>\n <line x1=\"449\" y1=\"138\" x2=\"642\" y2=\"138\" stroke=\"#96600B\" stroke-width=\"2.5\"\/>\n <line x1=\"449\" y1=\"132\" x2=\"449\" y2=\"144\" stroke=\"#96600B\" stroke-width=\"2\"\/><line x1=\"642\" y1=\"132\" x2=\"642\" y2=\"144\" stroke=\"#96600B\" stroke-width=\"2\"\/>\n <rect x=\"530\" y=\"130\" width=\"16\" height=\"16\" fill=\"#96600B\"\/>\n <line x1=\"501\" y1=\"184\" x2=\"657\" y2=\"184\" stroke=\"#96600B\" stroke-width=\"2.5\"\/>\n <line x1=\"501\" y1=\"178\" x2=\"501\" y2=\"190\" stroke=\"#96600B\" stroke-width=\"2\"\/><line x1=\"657\" y1=\"178\" x2=\"657\" y2=\"190\" stroke=\"#96600B\" stroke-width=\"2\"\/>\n <rect x=\"567\" y=\"176\" width=\"16\" height=\"16\" fill=\"#96600B\"\/>\n <line x1=\"523\" y1=\"230\" x2=\"664\" y2=\"230\" stroke=\"#A63525\" stroke-width=\"2.5\"\/>\n <line x1=\"523\" y1=\"224\" x2=\"523\" y2=\"236\" stroke=\"#A63525\" stroke-width=\"2\"\/><line x1=\"664\" y1=\"224\" x2=\"664\" y2=\"236\" stroke=\"#A63525\" stroke-width=\"2\"\/>\n <rect x=\"582\" y=\"222\" width=\"16\" height=\"16\" fill=\"#A63525\"\/>\n <line x1=\"553\" y1=\"276\" x2=\"605\" y2=\"276\" stroke=\"#3D4C57\" stroke-width=\"2.5\"\/>\n <line x1=\"553\" y1=\"270\" x2=\"553\" y2=\"282\" stroke=\"#3D4C57\" stroke-width=\"2\"\/><line x1=\"605\" y1=\"270\" x2=\"605\" y2=\"282\" stroke=\"#3D4C57\" stroke-width=\"2\"\/>\n <rect x=\"574\" y=\"268\" width=\"16\" height=\"16\" fill=\"#3D4C57\"\/>\n <\/g>\n <g font-family=\"Source Serif 4,serif\" font-size=\"14\" fill=\"#0E1A21\" text-anchor=\"end\">\n <text x=\"286\" y=\"43\">Fish intake, cohorts<\/text><text x=\"286\" y=\"89\">REDUCE-IT \u00b7 4 g EPA<\/text>\n <text x=\"286\" y=\"135\">VITAL \u00b7 1 g EPA+DHA<\/text><text x=\"286\" y=\"181\">ASCEND \u00b7 1 g<\/text>\n <text x=\"286\" y=\"227\">STRENGTH \u00b7 4 g EPA+DHA<\/text><text x=\"286\" y=\"273\">Cochrane, pooled<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#5C6B75\" text-anchor=\"end\">\n <text x=\"286\" y=\"57\">OBSERVATIONAL<\/text><text x=\"286\" y=\"103\">RCT \u00b7 MINERAL OIL PLACEBO<\/text>\n <text x=\"286\" y=\"149\">RCT \u00b7 PRIMARY ENDPOINT<\/text><text x=\"286\" y=\"195\">RCT \u00b7 DIABETES<\/text>\n <text x=\"286\" y=\"241\">RCT \u00b7 STOPPED FOR FUTILITY<\/text><text x=\"286\" y=\"287\">SR OF RCTs<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10.5\" fill=\"#3D4C57\">\n <text x=\"840\" y=\"47\">\u22480.88<\/text><text x=\"840\" y=\"93\">0.75<\/text><text x=\"840\" y=\"139\">0.92<\/text>\n <text x=\"840\" y=\"185\">0.97<\/text><text x=\"840\" y=\"231\">0.99<\/text><text x=\"840\" y=\"277\">0.98<\/text>\n <\/g>\n <\/svg>\n <p class=\"figcap\"><b>How to read this honestly.<\/b> One trial found a large benefit; three found none; the pooled synthesis found essentially nothing. The single positive trial used a mineral-oil placebo that appears to have raised LDL and CRP in the control arm, which would inflate the apparent effect \u2014 a published, unresolved criticism. <b>Two readings remain live:<\/b> either the cohort fish signal reflects the whole food matrix and displacement of worse options, or it reflects residual confounding. Notably, VITAL found greater benefit in people who ate little fish at baseline, which fits a repletion model rather than a drug model.<\/p>\n <\/div>\n\n <h3 class=\"sub-h\">Poultry: a protein instrument, and that is the whole case for it<\/h3>\n <div class=\"split\">\n <ul class=\"findings\">\n <li><span class=\"pill p-mech\">Composition<\/span>Roughly <span class=\"val\">31 g protein per 100 g<\/span> cooked breast at low energy cost, high DIAAS. Among the most efficient tools for meeting the Tier 2 protein floor.<\/li>\n <li><span class=\"pill p-mech\">Composition<\/span><b>But the micronutrient profile is thin where it matters.<\/b> Iron, zinc and B12 run roughly <span class=\"val\">3\u20138\u00d7 lower<\/span> than beef. High in niacin, B6, selenium and phosphorus. Dark meat carries more iron and zinc than breast.<\/li>\n <li><span class=\"pill p-cohort\">Cohort meta<\/span>Poultry is generally <span class=\"val\">not significantly associated<\/span> with all-cause mortality or cardiovascular disease. This is a null, not a benefit \u2014 and nulls in nutritional epidemiology are weak evidence in both directions.<\/li>\n <li><span class=\"pill p-cohort\">Substitution<\/span>The favourable finding is comparative: modelling poultry or fish <b>in place of<\/b> red or processed meat is associated with lower mortality. The benefit is attributed to what was removed. <span class=\"src\">Zheng et al. 2019 \u00b7 BMJ; Pan et al. 2012 \u00b7 Arch Intern Med (foundational)<\/span><\/li>\n <li><span class=\"pill p-conflict\">Unreplicated<\/span><b>For completeness, not as established:<\/b> some cohorts have reported associations between poultry and specific cancers, and at least one recent European cohort reported higher mortality at high intake. Inconsistent, biologically unexplained, unreplicated. <b>A signal to watch, not a finding. Requires verification.<\/b><\/li>\n <li><span class=\"pill p-mech\">Mechanism<\/span>High-temperature cooking generates heterocyclic amines and polycyclic aromatic hydrocarbons in poultry as well as red meat. <b>Cooking method may matter more than species.<\/b><\/li>\n <li><span class=\"pill p-rct\">Tier 1 governs<\/span>Nuggets and deli slices are ultra-processed foods that happen to contain chicken. They belong to the Tier 1 question.<\/li>\n <\/ul>\n <div class=\"card\">\n <h4>What poultry does and does not deliver<\/h4>\n <p class=\"sub\">Approximate content per 100 g cooked \u00b7 relative to beef<\/p>\n <svg viewBox=\"0 0 620 380\" role=\"img\" aria-label=\"Chicken versus beef: protein about 100 percent, iron 28 percent, zinc 18 percent, B12 12 percent.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <line x1=\"150\" y1=\"300\" x2=\"600\" y2=\"300\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <text x=\"150\" y=\"318\" text-anchor=\"middle\">0<\/text><text x=\"375\" y=\"318\" text-anchor=\"middle\">50%<\/text><text x=\"600\" y=\"318\" text-anchor=\"middle\">100%<\/text>\n <text x=\"375\" y=\"340\" text-anchor=\"middle\" letter-spacing=\"0.6\">CHICKEN AS % OF BEEF CONTENT<\/text>\n <g stroke=\"#E7EDF0\" stroke-width=\"1\"><line x1=\"375\" y1=\"20\" x2=\"375\" y2=\"300\"\/><\/g>\n <\/g>\n <line x1=\"600\" y1=\"20\" x2=\"600\" y2=\"300\" stroke=\"#0E1A21\" stroke-width=\"1\" stroke-dasharray=\"3 3\"\/>\n <g class=\"wipe\">\n <rect x=\"150\" y=\"34\" width=\"450\" height=\"34\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"150\" y=\"94\" width=\"126\" height=\"34\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"150\" y=\"154\" width=\"81\" height=\"34\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"150\" y=\"214\" width=\"54\" height=\"34\" rx=\"1\" fill=\"#A63525\"\/>\n <\/g>\n <g font-family=\"Source Serif 4,serif\" font-size=\"14.5\" fill=\"#0E1A21\" text-anchor=\"end\">\n <text x=\"140\" y=\"56\">Protein<\/text><text x=\"140\" y=\"116\">Iron<\/text><text x=\"140\" y=\"176\">Zinc<\/text><text x=\"140\" y=\"236\">Vitamin B12<\/text>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"12\" font-weight=\"600\">\n <text x=\"586\" y=\"56\" fill=\"#fff\" text-anchor=\"end\">\u2248100%<\/text>\n <text x=\"286\" y=\"116\" fill=\"#96600B\">\u224828%<\/text><text x=\"241\" y=\"176\" fill=\"#96600B\">\u224818%<\/text><text x=\"214\" y=\"236\" fill=\"#A63525\">\u224812%<\/text>\n <\/g>\n <text x=\"150\" y=\"368\" font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">MATCHES ON THE MACRO. DOES NOT SUBSTITUTE ON THE MICRO.<\/text>\n <\/svg>\n <p class=\"figcap\">Ratios approximate, vary by cut. <b>Practical implication:<\/b> swapping all red meat for chicken meets the protein floor but can quietly open iron, zinc and B12 gaps \u2014 particularly in menstruating women. Shellfish or oily fish close them better than either.<\/p>\n <\/div>\n <\/div>\n<\/section>\n\n\n<section id=\"myths\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">New section \u00b7 correcting common beliefs<\/span>\n <h2>Where popular nutrition belief diverges from the evidence<\/h2>\n <p>Two failure modes are worth separating. Some widely repeated claims are simply wrong and the correction is high-certainty. Others are popular <i>contrarian<\/i> claims that are weaker than their advocates assert. Both appear below, with the certainty of each correction stated rather than implied.<\/p>\n <\/div>\n <div class=\"tablewrap reveal\">\n <table>\n <thead><tr><th scope=\"col\">The claim<\/th><th scope=\"col\">What the evidence actually shows<\/th><th scope=\"col\">Correction certainty<\/th><\/tr><\/thead>\n <tbody>\n <tr><td class=\"claim\">\"High protein damages the kidneys\"<\/td>\n <td class=\"who\"><b>Refuted for healthy people.<\/b> Devries et al. 2018 (J Nutr, meta-analysis of RCTs) found higher protein did not adversely affect GFR in adults with normal kidney function; Van Elswyk 2018 concordant. <b>The genuine exception is pre-existing chronic kidney disease<\/b>, where higher protein can accelerate decline and restriction is a legitimate clinical tool. So: no harm in healthy kidneys, real caution in existing CKD.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cf<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"High protein leaches calcium and harms bone\"<\/td>\n <td class=\"who\"><b>Refuted, and the underlying theory is dead.<\/b> Shams-White 2017 (AJCN) and Groenendijk 2019 found higher protein neutral-to-beneficial for bone mineral density with no increase in fracture risk. The <b>acid-ash hypothesis<\/b> \u2014 that protein acidifies blood and dissolves bone \u2014 has been refuted; increased urinary calcium reflects increased absorption, not net bone loss.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cf<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Protein drives mTOR, IGF-1 and shortens lifespan\"<\/td>\n <td class=\"who\"><b>Overstated in humans.<\/b> Levine 2014 (Cell Metabolism) reported higher protein associated with cancer mortality at ages 50\u201365 but <b>protective over 65<\/b> \u2014 from a single 24-hour dietary recall in NHANES, with the mechanism largely from animal models. Critiques note residual confounding and poor translation. In older adults, higher protein protects against sarcopenia and frailty.<\/td>\n <td><span class=\"dots d-mid\">\u25cf\u25cf\u25cf\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Red meat causes colon cancer\"<\/td>\n <td class=\"who\"><b>Requires the classification distinction.<\/b> IARC 2015: <b>processed meat is Group 1<\/b> (carcinogenic), <b>unprocessed red meat is Group 2A<\/b> (probably). Effect size: roughly <b>+18% relative<\/b> colorectal cancer risk per 50 g\/day processed meat \u2014 but <b>absolute lifetime risk moves from about 5% to about 6%.<\/b> Mechanisms: heme iron catalysing N-nitroso compound formation, nitrosamines in processed meat, heterocyclic amines from high-temperature cooking; fibre and calcium appear protective. NutriRECS 2019 applied GRADE and argued certainty is low, provoking an unresolved methodological dispute.<\/td>\n <td><span class=\"dots d-mid\">\u25cf\u25cf\u25cf\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Eggs and dietary cholesterol cause heart disease\"<\/td>\n <td class=\"who\"><b>Genuinely unresolved.<\/b> The 300 mg\/day cap was dropped from US guidance in 2015. Zhong 2019 (JAMA, n\u224829,615) found higher risk per half-egg\/day; many other cohorts \u2014 especially Asian \u2014 and short RCTs are null. Roughly one-third of people are hyper-responders. Remaining uncertainty is real and should not be papered over in either direction.<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Saturated fat causes Alzheimer's disease\"<\/td>\n <td class=\"who\"><b>Weak and contested.<\/b> Observational associations are inconsistent; the strongest signal involves the <b>APOE4 interaction<\/b>, itself inconsistent. Cohort data look impressive \u2014 MIND diet adherence associated with ~53% lower Alzheimer's rate (Morris 2015) \u2014 but the <b>MIND-diet RCT (Barnes 2023, NEJM, ~600 participants, 3 years) found no significant cognitive benefit<\/b> over a control with mild caloric restriction. B-vitamin and omega-3 cognition trials are largely null.<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Everyone should minimise salt\"<\/td>\n <td class=\"who\"><b>Genuine scientific disagreement \u2014 likely a J-curve.<\/b> PURE (O'Donnell 2014, NEJM) suggests both very high (>5 g sodium\/day) and <b>very low (<3 g\/day)<\/b> associate with higher risk. The opposing camp \u2014 TOHP long-term follow-up and DASH-Sodium \u2014 supports linear benefit and argues PURE suffers reverse causation and spot-urine error. <b>SSaSS (Neal 2021, NEJM, n=20,995, ~4.7 years):<\/b> potassium-enriched salt substitute cut stroke (RR \u22480.86), major cardiovascular events (\u22480.87) and total mortality (\u22480.88) without serious hyperkalaemia excess. Lowering sodium in hypertensive or high-intake people is well supported; pushing every normotensive person ever-lower is not settled.<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Fibre is essential for everyone\"<\/td>\n <td class=\"who\"><b>Conditional, not absolute.<\/b> Population benefits are strong, but low-FODMAP restriction reduces symptoms in IBS, meaning some fermentable fibre worsens symptoms in specific individuals. Separately, the old <b>diverticular advice was reversed<\/b> \u2014 Strate 2008 (JAMA) found no increased diverticulitis risk from nuts, seeds or popcorn, and higher fibre now associates with lower risk.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Sugar is toxic\"<\/td>\n <td class=\"who\"><b>Overstated; dose and form matter.<\/b> Evidence is strongest for <b>sugar-sweetened beverages<\/b> (consistent associations with weight gain, T2D, CVD). For total added sugar the risk is more dose-dependent and confounded by total energy; isocaloric fructose substitution shows little independent harm at moderate doses but adverse effects (hepatic de novo lipogenesis, triglycerides) at high doses under hypercaloric conditions.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Gluten harms everyone\"<\/td>\n <td class=\"who\"><b>False outside specific conditions.<\/b> Coeliac disease (~1%) requires strict avoidance. Non-coeliac gluten sensitivity is real for some but frequently confounded \u2014 blinded challenge studies (Biesiekierski 2013, Gastroenterology) implicate <b>FODMAPs and amylase-trypsin inhibitors<\/b> rather than gluten itself in many self-reported cases. No benefit to avoidance in the general population.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cf<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Soy feminises men\"<\/td>\n <td class=\"who\"><b>Refuted.<\/b> Messina 2021 (meta-analysis of clinical studies): neither soy protein nor isoflavones significantly affect total or free testosterone, estradiol or SHBG in men.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cf<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Frequent small meals raise metabolism \/ breakfast is essential\"<\/td>\n <td class=\"who\"><b>Both refuted.<\/b> The thermic effect of food scales with total intake, not meal frequency. Sievert 2019 (BMJ meta-analysis): skipping breakfast does not cause weight gain and adding it does not aid weight loss.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cf<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Time-restricted eating is metabolically special\"<\/td>\n <td class=\"who\"><b>Benefit is mostly caloric.<\/b> TREAT (Lowe 2020, JAMA Intern Med): 16:8 produced no significant additional weight loss versus three structured meals, with a possible lean-mass-loss signal. Meta-analyses show modest loss (~1\u20132 kg) attributable to reduced intake, not timing. <b>Note also:<\/b> the widely-shared 2024 conference abstract linking 8-hour windows to cardiovascular mortality was non-peer-reviewed, observational, and based on 1\u20132 days of recall \u2014 not established.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Multivitamins and antioxidants prevent disease\"<\/td>\n <td class=\"who\"><b>Largely refuted, and some cause harm.<\/b> ATBC: \u03b2-carotene increased lung cancer in smokers. CARET: \u03b2-carotene plus retinol increased lung cancer and mortality. SELECT: vitamin E increased prostate cancer risk. Bjelakovic meta-analyses: no mortality benefit, possible harm. <b>Partial counterpoint:<\/b> COSMOS-Mind found a small but significant multivitamin benefit on global cognition in older adults \u2014 the most credible positive signal to date, modest and needing replication.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Coconut oil is heart-healthy\"<\/td>\n <td class=\"who\"><b>Refuted for lipids.<\/b> Neelakantan 2020 (Circulation, 16 trials): coconut oil raised LDL-C by <b>10.47 mg\/dL (95% CI 3.01\u201317.94)<\/b> versus non-tropical vegetable oils, with no benefit on weight, waist or glycemia.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cf<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Omega-6 seed oils are inflammatory\"<\/td>\n <td class=\"who\"><b>Not supported in humans.<\/b> Marklund 2019 (Circulation, 30 cohorts, biomarker-based) found higher circulating linoleic acid associated with <b>lower<\/b> CVD and mortality. Controlled feeding does not show linoleic acid raising CRP. The oxidised-metabolite hypothesis remains mechanistic and unconfirmed as net harm.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Alkaline and detox diets work\"<\/td>\n <td class=\"who\"><b>Unsupported.<\/b> Blood pH is tightly regulated at 7.35\u20137.45 and diet cannot meaningfully change it; the kidneys and liver perform detoxification. Any benefit comes from eating more vegetables and less processed food, not from alkalinity.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cf<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"Artificial sweeteners cause weight gain or cancer\"<\/td>\n <td class=\"who\"><b>Largely unsupported at normal intake.<\/b> RCTs show non-nutritive sweeteners modestly aid weight control versus sugar. IARC classified aspartame Group 2B (\"possibly carcinogenic\") in 2023, but JECFA retained the acceptable daily intake at 40 mg\/kg\/day \u2014 realistic consumption sits well within that margin.<\/td>\n <td><span class=\"dots d-hi\">\u25cf\u25cf\u25cf\u25cf\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">\"LDL doesn't matter if your triglycerides and HDL look good\"<\/td>\n <td class=\"who\"><b>The popular contrarian claim, and it is weaker than advertised.<\/b> KETO-CTA (2025) followed ~100 lean-mass hyper-responders for one year and reported plaque change unrelated to LDL-C or ApoB \u2014 but it was <b>single-arm with no control group, only one year, and investigators had low-carb ties<\/b>, and independent cardiologists noted absolute progression did occur. It does not overturn the Mendelian randomisation and RCT evidence that ApoB is causal at population level. <b>Verify all figures.<\/b><\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <\/tbody>\n <\/table>\n <\/div>\n <p class=\"figcap\"><b>Reading the dots.<\/b> Five dots means the correction is well established and you can rely on it. Two dots means the honest answer is \"nobody knows yet\" \u2014 which applies as much to confident contrarian claims as to confident conventional ones.<\/p>\n<\/section>\n\n\n<section id=\"colon\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">New section \u00b7 gastrointestinal outcomes<\/span>\n <h2>Colon and gut: strong cohort signals, weak supplement trials<\/h2>\n <p>The colon is where the fibre story is most mechanistically satisfying and most empirically frustrating \u2014 the mechanism is beautifully characterised and the supplement trials are null.<\/p>\n <\/div>\n <div class=\"split\">\n <ul class=\"findings\">\n <li><span class=\"pill p-mech\">Mechanism<\/span><b>Fermentable fibre<\/b> \u2014 inulin, pectin, beta-glucan, resistant starch \u2014 is fermented to <b>short-chain fatty acids<\/b>. Butyrate is the preferred fuel of colonocytes with anti-inflammatory and anti-neoplastic actions via histone deacetylase inhibition and regulatory T-cell induction. <b>Non-fermentable fibre<\/b> \u2014 cellulose, wheat bran \u2014 mainly bulks stool and shortens transit.<\/li>\n <li><span class=\"pill p-conflict\">Honest tension<\/span><b>The mechanism is well characterised in vitro and in animals, but human fibre-supplement RCTs are largely null.<\/b> The Polyp Prevention Trial and Wheat Bran Fiber trial found no reduction in adenoma recurrence over 3\u20134 years. The population fibre\u2013cancer benefit is robust in cohorts; isolated supplements have not replicated it. This argues for whole-food fibre within dietary patterns, not capsules.<\/li>\n <li><span class=\"pill p-cohort\">Effect sizes<\/span>Colorectal cancer risk associations: processed meat <span class=\"val\">+18%<\/span> per 50 g\/day; unprocessed red meat ~<span class=\"val\">+12\u201317%<\/span> per 100 g\/day; fibre ~<span class=\"val\">\u221210%<\/span> per 10 g\/day; whole grains ~<span class=\"val\">\u221217%<\/span> per 90 g\/day (Aune 2016, BMJ); alcohol ~<span class=\"val\">+7\u201310%<\/span> per 10 g ethanol\/day; physical activity ~<span class=\"val\">\u221220\u201325%<\/span> most versus least active. Calcium and dairy appear protective. <span class=\"src\">WCRF\/AICR Continuous Update Project is the authoritative synthesis \u2014 verify individual figures there<\/span><\/li>\n <li><span class=\"pill p-conflict\">Unexplained trend<\/span><b>Early-onset colorectal cancer is rising in adults under 50 and the cause is unknown.<\/b> A 2025 Nature mutational-signature analysis reported <b>colibactin<\/b> signatures from pks+ E. coli enriched in early-onset versus late-onset tumours, with damage possibly occurring in childhood \u2014 a biologically plausible leading candidate, not proven. Other candidates (ultra-processed food, early-life obesity, antibiotic exposure, sedentary behaviour) are more speculative. <b>Verify the 2025 citation and effect size.<\/b><\/li>\n <li><span class=\"pill p-rct\">Established<\/span><b>Faecal microbiota transplant for recurrent <i>Clostridioides difficile<\/i><\/b> is the one clearly proven clinical microbiome therapy \u2014 roughly 80\u201390% cure across multiple RCTs.<\/li>\n <li><span class=\"pill p-weak\">Hype<\/span><b>Most other microbiome claims are premature.<\/b> Probiotic RCTs are heterogeneous, strain-specific and often low quality, with modest condition-specific benefit at best. The field has significant reproducibility problems \u2014 batch effects, bioinformatic variability, small samples, correlation read as causation. Low-fibre diets do shift the microbiome toward mucin-degrading and sulfate-reducing bacteria, thinning the protective mucus layer, but that is largely animal and mechanistic work.<\/li>\n <\/ul>\n <div class=\"card\">\n <h4>Colorectal cancer: relative risk per standard increment<\/h4>\n <p class=\"sub\">Cohort and meta-analytic estimates \u00b7 approximate<\/p>\n <svg viewBox=\"0 0 620 380\" role=\"img\" aria-label=\"Diverging bar chart of colorectal cancer risk factors. Processed meat plus 18 percent, red meat plus 15, alcohol plus 8. Fibre minus 10, whole grains minus 17, physical activity minus 22.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"10\" fill=\"#5C6B75\">\n <line x1=\"330\" y1=\"30\" x2=\"330\" y2=\"300\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <line x1=\"90\" y1=\"300\" x2=\"600\" y2=\"300\" stroke=\"#E7EDF0\" stroke-width=\"1\"\/>\n <text x=\"180\" y=\"322\" text-anchor=\"middle\">\u2190 LOWER RISK<\/text>\n <text x=\"470\" y=\"322\" text-anchor=\"middle\">HIGHER RISK \u2192<\/text>\n <text x=\"330\" y=\"322\" text-anchor=\"middle\">0<\/text>\n <text x=\"180\" y=\"342\" text-anchor=\"middle\">\u221220%<\/text><text x=\"470\" y=\"342\" text-anchor=\"middle\">+20%<\/text>\n <\/g>\n <g class=\"wipe\">\n <rect x=\"330\" y=\"40\" width=\"126\" height=\"26\" rx=\"1\" fill=\"#A63525\"\/>\n <rect x=\"330\" y=\"76\" width=\"105\" height=\"26\" rx=\"1\" fill=\"#A63525\"\/>\n <rect x=\"330\" y=\"112\" width=\"56\" height=\"26\" rx=\"1\" fill=\"#96600B\"\/>\n <rect x=\"260\" y=\"148\" width=\"70\" height=\"26\" rx=\"1\" fill=\"#17758C\"\/>\n <rect x=\"211\" y=\"184\" width=\"119\" height=\"26\" rx=\"1\" fill=\"#115A72\"\/>\n <rect x=\"176\" y=\"220\" width=\"154\" height=\"26\" rx=\"1\" fill=\"#093644\"\/>\n <rect x=\"288\" y=\"256\" width=\"42\" height=\"26\" rx=\"1\" fill=\"#17758C\"\/>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"11\" font-weight=\"600\">\n <text x=\"464\" y=\"58\" fill=\"#A63525\">+18%<\/text><text x=\"443\" y=\"94\" fill=\"#A63525\">+15%<\/text><text x=\"394\" y=\"130\" fill=\"#96600B\">+8%<\/text>\n <text x=\"252\" y=\"166\" fill=\"#17758C\" text-anchor=\"end\">\u221210%<\/text><text x=\"203\" y=\"202\" fill=\"#115A72\" text-anchor=\"end\">\u221217%<\/text>\n <text x=\"168\" y=\"238\" fill=\"#093644\" text-anchor=\"end\">\u221222%<\/text><text x=\"280\" y=\"274\" fill=\"#17758C\" text-anchor=\"end\">\u22126%<\/text>\n <\/g>\n <g font-family=\"Source Serif 4,serif\" font-size=\"12\" fill=\"#0E1A21\">\n <text x=\"330\" y=\"36\" text-anchor=\"start\" dx=\"4\">Processed meat, per 50 g\/day<\/text>\n <text x=\"330\" y=\"72\" text-anchor=\"start\" dx=\"4\">Red meat, per 100 g\/day<\/text>\n <text x=\"330\" y=\"108\" text-anchor=\"start\" dx=\"4\">Alcohol, per 10 g\/day<\/text>\n <text x=\"330\" y=\"144\" text-anchor=\"end\" dx=\"-4\">Fibre, per 10 g\/day<\/text>\n <text x=\"330\" y=\"180\" text-anchor=\"end\" dx=\"-4\">Whole grains, per 90 g\/day<\/text>\n <text x=\"330\" y=\"216\" text-anchor=\"end\" dx=\"-4\">Physical activity, high vs low<\/text>\n <text x=\"330\" y=\"252\" text-anchor=\"end\" dx=\"-4\">Calcium and dairy<\/text>\n <\/g>\n <text x=\"90\" y=\"368\" font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#5C6B75\">RELATIVE, NOT ABSOLUTE. LIFETIME RISK MOVES FROM ROUGHLY 5% TO 6% AT HIGH PROCESSED-MEAT INTAKE.<\/text>\n <\/svg>\n <p class=\"figcap\"><b>The distinction that gets lost in headlines.<\/b> An 18% relative increase on a 5% baseline is about one extra case per hundred people \u2014 real, worth acting on, and not the catastrophe the phrase \"causes cancer\" implies. <b>Verify all figures against WCRF\/AICR.<\/b><\/p>\n <\/div>\n <\/div>\n<\/section>\n\n\n<section id=\"brain\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">New section \u00b7 cognition and dementia<\/span>\n <h2>Cognition: the widest cohort-to-trial gap in nutrition<\/h2>\n <p>Dietary patterns look strongly protective in cohorts and mostly fail to replicate in trials. This section is where confident dietary claims about Alzheimer's disease should be treated with the most suspicion \u2014 in both directions.<\/p>\n <\/div>\n <ul class=\"findings\">\n <li><span class=\"pill p-cohort\">Cohort<\/span><b>MIND diet<\/b> (Morris 2015, Alzheimers Dement): highest adherence associated with roughly <span class=\"val\">53% lower<\/span> Alzheimer's incidence, and about 35% at moderate adherence. Mediterranean and Nordic patterns show similar inverse associations of roughly 10\u201330%.<\/li>\n <li><span class=\"pill p-conflict\">RCT \u00b7 null<\/span><b>The discrepancy.<\/b> The MIND-diet RCT (Barnes 2023, NEJM, ~600 participants, ~3 years) found <span class=\"val\">no significant cognitive benefit<\/span> versus a control diet with mild caloric restriction. Likely explanations: confounding in cohorts, insufficient trial duration, and improvement in the control group. <b>The causal claim is not established.<\/b><\/li>\n <li><span class=\"pill p-rct\">RCT \u00b7 positive<\/span><b>FINGER<\/b> (Ngandu 2015, Lancet, n=1,260, Finland, 2 years): a structured multidomain intervention \u2014 diet, exercise, cognitive training, vascular risk monitoring \u2014 improved a global cognitive composite versus control. <b>The flagship positive multidomain trial.<\/b><\/li>\n <li><span class=\"pill p-conflict\">RCT \u00b7 null<\/span><b>MAPT<\/b> (Andrieu 2017, Lancet Neurol): omega-3 with or without multidomain intervention \u2014 null on the primary outcome. <b>preDIVA<\/b> (Moll van Charante 2016, Lancet): nurse-led vascular care \u2014 null on dementia incidence.<\/li>\n <li><span class=\"pill p-rct\">Newest readout<\/span><b>US POINTER<\/b> (2025): the largest US multidomain trial, roughly 2,100+ adults aged 60\u201379 at elevated risk, structured versus self-guided lifestyle intervention over 2 years, reported at AAIC July 2025 and published in JAMA. As reported, <b>both groups improved but the structured arm improved the global cognitive composite significantly more<\/b>, framed as slowing cognitive aging by roughly 1\u20132 years. <b>Verify the exact effect size, interval, p-value and DOI \u2014 these could not be confirmed against the primary source.<\/b><\/li>\n <li><span class=\"pill p-conflict\">Null<\/span><b>Single nutrients have not delivered.<\/b> Omega-3 cognition trials are largely null. B-vitamin and homocysteine-lowering trials are largely null, with a possible unreplicated subgroup signal in high-homocysteine individuals (VITACOG). Vitamin D shows observational associations and null-to-weak RCT results.<\/li>\n <li><span class=\"pill p-weak\">Preliminary<\/span><b>The brain-fuel hypothesis.<\/b> Cerebral glucose hypometabolism appears early in Alzheimer's and in APOE4 carriers before symptoms \u2014 the \"brain insulin resistance\" framing. Cunnane's imaging work shows the aging brain <b>retains normal ketone uptake even where glucose uptake is impaired<\/b>, motivating ketogenic and MCT interventions. Small trials show modest short-term signals, particularly in APOE4 non-carriers. <b>Samples are small, durations short, blinding difficult. This is hypothesis-generating, not therapy.<\/b><\/li>\n <li><span class=\"pill p-mech\">Practical reading<\/span>The defensible strategy is the <b>multidomain package<\/b> \u2014 exercise, a Mediterranean or MIND-style pattern, vascular risk control, cognitive and social engagement \u2014 not any single supplement. That conclusion rests on FINGER and provisionally POINTER, and it is modest rather than dramatic.<\/li>\n <\/ul>\n<\/section>\n\n\n<section id=\"apex\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Tier 5 \u00b7 Updated and expanded<\/span>\n <h2>Where the trials disagree and contradict each other<\/h2>\n <p>Every entry here is a live dispute in the published literature. That is why the apex is drawn small and open. Anyone presenting one of these as settled \u2014 in either direction \u2014 has gone beyond the evidence.<\/p>\n <\/div>\n <div class=\"tablewrap reveal\">\n <table>\n <thead><tr><th scope=\"col\">Contested claim<\/th><th scope=\"col\">Evidence for<\/th><th scope=\"col\">Evidence against<\/th><th scope=\"col\">Certainty<\/th><\/tr><\/thead>\n <tbody>\n <tr><td class=\"claim\">Saturated fat causes cardiovascular disease<\/td>\n <td class=\"who\">Hooper 2020 Cochrane: reducing SFA cut combined cardiovascular events, <span class=\"num\">RR 0.83<\/span> (0.76\u20130.90), greatest when replaced by PUFA<\/td>\n <td class=\"who\">Same review found <b>little or no effect on mortality<\/b>. No significant association in Siri-Tarino 2010 (<span class=\"num\">RR 1.07<\/span>), Chowdhury 2014, de Souza 2015. Astrup 2020 JACC argued against a blanket limit and drew rebuttals<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Unprocessed red meat meaningfully raises risk<\/td>\n <td class=\"who\">IARC 2015 Group 2A. Processed meat is <b>not<\/b> disputed \u2014 Group 1, \u2248+18% colorectal cancer per 50 g\/day. Coherent heme-iron and N-nitroso mechanisms<\/td>\n <td class=\"who\">NutriRECS 2019 applied GRADE, judged certainty low and small absolute risk, recommending no change \u2014 provoking rebuttals and retraction calls. Ioannidis disputes the field's effect sizes generally<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Fish consumption prevents cardiovascular disease<\/td>\n <td class=\"who\">Consistent modest inverse cohort associations for coronary death and stroke; REDUCE-IT <span class=\"num\">HR 0.75<\/span> with 4 g EPA; VITAL showed reduced MI and more benefit in low-fish consumers<\/td>\n <td class=\"who\">STRENGTH null and stopped for futility; ASCEND null; VITAL null on its primary endpoint; Cochrane 2020 found little or no effect. REDUCE-IT's mineral-oil placebo remains disputed. PURE found benefit only in higher-risk groups<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Sodium should be minimised in everyone<\/td>\n <td class=\"who\">DASH-Sodium and TOHP long-term follow-up support linear benefit. <b>SSaSS<\/b> (n=20,995): potassium salt substitute cut stroke \u224814%, mortality \u224812%<\/td>\n <td class=\"who\">PURE suggests a <b>J-curve<\/b> with elevated risk below ~3 g sodium\/day. Opponents argue reverse causation and spot-urine error; PURE authors argue the trials studied hypertensive high-intake groups only<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Dietary cholesterol and eggs raise cardiovascular risk<\/td>\n <td class=\"who\">Zhong 2019 JAMA: higher risk per additional half-egg\/day and per 300 mg cholesterol, pooled US cohorts n\u224829,615<\/td>\n <td class=\"who\">Numerous other cohorts, especially Asian, and short-term RCTs are null. The 300 mg cap was removed from US guidance in 2015. Hyper-responder variability is real and unaccounted for<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Diet causally prevents dementia<\/td>\n <td class=\"who\">MIND adherence associated with ~53% lower Alzheimer's rate (Morris 2015). FINGER multidomain RCT positive on a cognitive composite. US POINTER 2025 reportedly positive<\/td>\n <td class=\"who\"><b>MIND-diet RCT (Barnes 2023, NEJM) null.<\/b> MAPT and preDIVA null. Single-nutrient trials \u2014 omega-3, B vitamins, vitamin D \u2014 largely null. Cohort-to-trial gap is the widest in nutrition<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Saturated fat contributes to Alzheimer's disease<\/td>\n <td class=\"who\">Some cohort associations; an APOE4 interaction is biologically plausible and reported in places<\/td>\n <td class=\"who\">Associations inconsistent; the APOE4 interaction itself is inconsistent; no trial evidence. Mechanism-rich and trial-poor<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cb\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">ApoB and LDL are not causal in metabolically healthy hyper-responders<\/td>\n <td class=\"who\">KETO-CTA (2025) reported one-year plaque change unrelated to LDL-C or ApoB in ~100 lean mass hyper-responders, with baseline plaque the strongest predictor<\/td>\n <td class=\"who\"><b>Single-arm, no control group, one year<\/b> \u2014 short for atherosclerosis. Investigator ties to low-carb advocacy. Independent cardiologists noted absolute progression occurred. Large Mendelian randomisation and RCT evidence supports ApoB causality<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cb\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Ketogenic diets are safe beyond two years<\/td>\n <td class=\"who\">No clear harm signal in trials up to 2 years; T2D remission data are favourable; theoretical micronutrient concerns are addressable by formulation<\/td>\n <td class=\"who\"><b>Evidence beyond two years is thin<\/b> and dominated by observational data. Documented risks include kidney stones, possible T3 reduction, LDL elevation in a subset, and high attrition with diet convergence by 12\u201324 months<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Poultry is meaningfully associated with cancer<\/td>\n <td class=\"who\">Scattered cohort associations with specific cancers in some UK analyses; at least one recent European cohort reported higher mortality at high intake<\/td>\n <td class=\"who\">Inconsistent across cohorts, no mechanism distinct from cooking method, unreplicated, confounded by preparation and processing. <b>Most meta-analyses find poultry null<\/b><\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cb\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Glycemic index is clinically actionable<\/td>\n <td class=\"who\">Mechanistically coherent and widely used in practice<\/td>\n <td class=\"who\">OmniCarb (Sacks 2014, JAMA) found limited independent cardiometabolic effect within an already healthy diet<\/td>\n <td><span class=\"dots d-mid\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Higher protein shortens lifespan via mTOR and IGF-1<\/td>\n <td class=\"who\">Levine 2014 reported higher cancer mortality with high protein at ages 50\u201365; strong animal mTOR and IGF-1 mechanism<\/td>\n <td class=\"who\">Reversed above age 65 in the same analysis. Single 24-hour recall, residual confounding, poor animal-to-human translation. Higher protein protects older adults against sarcopenia<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cf\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">Genotype-based diets beat standard advice<\/td>\n <td class=\"who\">Real gene\u2013diet interactions exist for lactase persistence, CYP1A2, FADS1\/2 and BCO1<\/td>\n <td class=\"who\"><b>Food4Me<\/b> RCT (n=1,607): personalised advice beat generic, but <b>genotype added nothing over phenotype and diet data<\/b>. DIETFITS found no genotype interaction<\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cb\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <tr><td class=\"claim\">The rise in early-onset colorectal cancer has an identified cause<\/td>\n <td class=\"who\">A 2025 Nature signature analysis found colibactin signatures from pks+ E. coli enriched in early-onset tumours, possibly from childhood exposure<\/td>\n <td class=\"who\">Genomic association, not demonstrated causation of the population trend. Competing candidates \u2014 ultra-processed food, early-life obesity, antibiotics, sedentary behaviour \u2014 remain speculative. <b>The trend is substantially unexplained<\/b><\/td>\n <td><span class=\"dots d-lo\">\u25cf\u25cb\u25cb\u25cb\u25cb<\/span><\/td><\/tr>\n <\/tbody>\n <\/table>\n <\/div>\n <p class=\"figcap\"><b>Certainty dots<\/b> reflect the consistency of high-quality evidence, not the popularity of the position. Five would mean settled; <b>nothing in this table earns more than two<\/b>. Note that several entries are contested contrarian claims, not contested conventional ones \u2014 scepticism cuts both ways.<\/p>\n<\/section>\n\n\n<section id=\"personal\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Why a single prescription fails<\/span>\n <h2>Identical meal, divergent bodies<\/h2>\n <p>This is the empirical case against one-size-fits-all \u2014 and simultaneously the case against the commercial personalisation industry, because the same literature shows genotype-based advice failing to beat far simpler methods.<\/p>\n <\/div>\n <div class=\"split\">\n <div class=\"card reveal\">\n <h4>Postprandial glucose after the same food<\/h4>\n <p class=\"sub\"><span style=\"color:#A63525\">Schematic<\/span> \u00b7 after Zeevi 2015 and PREDICT 1<\/p>\n <svg viewBox=\"0 0 620 285\" role=\"img\" aria-label=\"Schematic chart of several divergent postprandial glucose curves following an identical meal, illustrating large interpersonal variability.\">\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\" fill=\"#5C6B75\">\n <line x1=\"70\" y1=\"230\" x2=\"600\" y2=\"230\" stroke=\"#0E1A21\" stroke-width=\"1.5\"\/>\n <line x1=\"70\" y1=\"20\" x2=\"70\" y2=\"230\" stroke=\"#E7EDF0\" stroke-width=\"1\"\/>\n <text x=\"62\" y=\"216\" text-anchor=\"end\">BASE<\/text><text x=\"62\" y=\"30\" text-anchor=\"end\">PEAK<\/text>\n <text x=\"70\" y=\"248\" text-anchor=\"middle\">0<\/text><text x=\"247\" y=\"248\" text-anchor=\"middle\">60<\/text><text x=\"424\" y=\"248\" text-anchor=\"middle\">120<\/text>\n <text x=\"335\" y=\"270\" text-anchor=\"middle\" letter-spacing=\"0.6\">MINUTES AFTER AN IDENTICAL MEAL<\/text>\n <\/g>\n <g fill=\"none\" stroke-width=\"2.6\" class=\"draw\">\n <path d=\"M70,212 C150,40 220,44 300,120 C380,190 490,206 596,210\" stroke=\"#A63525\"\/>\n <path d=\"M70,212 C150,96 220,100 300,152 C380,196 490,208 596,212\" stroke=\"#96600B\"\/>\n <path d=\"M70,212 C150,150 220,152 300,180 C380,202 490,210 596,213\" stroke=\"#17758C\"\/>\n <path d=\"M70,212 C150,186 220,188 300,200 C380,208 490,212 596,214\" stroke=\"#093644\"\/>\n <\/g>\n <g font-family=\"IBM Plex Mono,monospace\" font-size=\"9.5\">\n <text x=\"306\" y=\"112\" fill=\"#A63525\">HIGH RESPONDER<\/text>\n <text x=\"306\" y=\"196\" fill=\"#093644\">LOW RESPONDER<\/text>\n <text x=\"76\" y=\"18\" fill=\"#5C6B75\">SAME FOOD \u00b7 SAME PORTION<\/text>\n <\/g>\n <\/svg>\n <p class=\"figcap\"><b>Schematic.<\/b> Illustrates the reported phenomenon of large interpersonal variability, not extracted participant data.<\/p>\n <\/div>\n <ul class=\"findings\">\n <li><span class=\"pill p-cohort\">Cohort + ML<\/span>Large interpersonal variability in postprandial glucose to identical meals; a microbiome-plus-clinical predictor outperformed carbohydrate counting, with a small confirmatory intervention. <span class=\"src\">Zeevi \/ Segal 2015 \u00b7 Cell \u00b7 n=800 plus validation<\/span><\/li>\n <li><span class=\"pill p-cohort\">Twin cohort<\/span>Wide variability in glycemic, insulinemic and lipemic responses. Genetics explained relatively little, microbiome a modest share, and <b>identical twins responded differently<\/b> \u2014 undercutting a strongly genetic model of dietary response. <span class=\"src\">PREDICT 1 \u00b7 Berry et al. 2020 \u00b7 Nature Medicine \u00b7 n\u22481000 including twins<\/span><\/li>\n <li><span class=\"pill p-rct\">RCT \u00b7 the key null<\/span>Personalised advice improved diet versus generic advice \u2014 but <b>adding genotype improved nothing over phenotype and diet data.<\/b> The commercially valuable claim is the one that failed. <span class=\"src\">Food4Me \u00b7 Celis-Morales et al. 2017 \u00b7 Int J Epidemiol \u00b7 n=1607<\/span><\/li>\n <li><span class=\"pill p-weak\">Thin<\/span>Continuous glucose monitoring in people without diabetes: weak outcome evidence. It measures variability reliably but has not been shown to improve hard endpoints.<\/li>\n <li><span class=\"pill p-mech\">Ongoing<\/span>NIH <i>Nutrition for Precision Health<\/i> within <i>All of Us<\/i> (~10,000 participants) is the study that could change this section. <b>Status and any 2025\u201326 outputs need direct checking.<\/b><\/li>\n <\/ul>\n <\/div>\n <p class=\"figcap\"><b>Practical reading.<\/b> Variability is real, so fixed universal ratios are poorly justified \u2014 but the validated way to personalise is <b>measurement and response<\/b> (weight, lipids and ApoB, HbA1c, glucose, and how you actually feel and adhere), not a genotype panel.<\/p>\n<\/section>\n\n\n<section id=\"practical\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Translation<\/span>\n <h2>What follows, if you accept the structure<\/h2>\n <p>Stated as consequences of the evidence rather than as prescriptions \u2014 the entire point of the carbohydrate dial is that the setting is yours.<\/p>\n <\/div>\n <dl class=\"dl reveal\">\n <div><dt>Highest-leverage single change<\/dt><dd>Reduce ultra-processed food. <b>Tier 1<\/b> outranks every macronutrient argument and has the only clean ward RCT behind it.<\/dd><\/div>\n <div><dt>The foods that close the most floors<\/dt><dd><b>Shellfish, oily fish and liver.<\/b> Protein, EPA\/DHA, B12, zinc, iron, iodine, selenium, retinol. Nothing else comes close.<\/dd><\/div>\n <div><dt>Protein floor<\/dt><dd><b>1.2\u20131.6 g\/kg\/day<\/b>, more if older or training, with little added benefit above ~1.6. Tracer studies, not nitrogen balance.<\/dd><\/div>\n <div><dt>Protein safety<\/dt><dd>No harm to <b>healthy<\/b> kidneys or bone \u2014 high certainty. Real caution in existing <b>chronic kidney disease.<\/b><\/dd><\/div>\n <div><dt>Carbohydrate<\/dt><dd>No biochemical minimum, but respect the <b>175 g pregnancy \/ 210 g lactation \/ 3\u201312 g\/kg athletic<\/b> floors. Never combine ketogenic eating with an <b>SGLT2 inhibitor<\/b> unsupervised.<\/dd><\/div>\n <div><dt>Fats worth dosing<\/dt><dd>Only <b>linoleic acid and ALA<\/b> are essential. Get <b>250 mg\/day EPA+DHA from fish<\/b>, not from low-dose capsules. Do not manage the omega-6 ratio.<\/dd><\/div>\n <div><dt>Fats to avoid<\/dt><dd><b>Industrial trans fat<\/b> \u2014 the one uncontested harm. Coconut oil is not a heart-healthy fat.<\/dd><\/div>\n <div><dt>If you swap red meat for chicken<\/dt><dd>You keep the protein and lose the <b>iron, zinc and B12<\/b>. Cover it with shellfish or oily fish, not more chicken.<\/dd><\/div>\n <div><dt>Vegetables and fruit<\/dt><dd>Treat as <b>micronutrient and fibre vehicles<\/b>. Target variety and leafy greens, and stop near 5 servings \u2014 the curve flattens.<\/dd><\/div>\n <div><dt>Whole fruit over juice<\/dt><dd>Among the better-replicated distinctions in the field. <b>Juice sits on the carbohydrate dial<\/b>, not in Tier 3.<\/dd><\/div>\n <div><dt>Potatoes and grains<\/dt><dd><b>Carbohydrate<\/b>, not vegetables. Set them with the dial; fried preparations carry their own harm signal.<\/dd><\/div>\n <div><dt>Don't buy the extract<\/dt><dd>Isolated antioxidant supplementation failed or harmed across large trials. <b>The matrix is not optional.<\/b><\/dd><\/div>\n <div><dt>Colon<\/dt><dd>Cut <b>processed meat<\/b> first, get fibre from food rather than capsules, and note that relative risks here sit on a small absolute base.<\/dd><\/div>\n <div><dt>Brain<\/dt><dd>The <b>multidomain package<\/b> \u2014 exercise, Mediterranean or MIND pattern, vascular risk control, cognitive engagement. No single supplement has delivered.<\/dd><\/div>\n <\/dl>\n\n <div class=\"callout reveal\">\n <span class=\"eyebrow\">The honest summary<\/span>\n <p>Very little in nutrition is both important and settled. What survives scrutiny is a short list: food form matters more than macronutrient ratio; protein requirements are higher than the RDA states and harmless to healthy kidneys and bone; only two fatty acids are truly essential; carbohydrate has no biochemical floor but several real physiological ones; fibre and whole plants carry robust signals through a mechanism nobody has isolated; and industrial trans fat is the one clearly harmful fat. <strong>Almost everything else \u2014 saturated fat causality, red meat dose, sodium targets, eggs, whether fish prevents heart disease, whether any diet prevents dementia \u2014 is genuinely unresolved, and the confident contrarian answers are no better supported than the confident conventional ones.<\/strong><\/p>\n <\/div>\n<\/section>\n\n\n<section id=\"refs\">\n <div class=\"sec-head\">\n <span class=\"eyebrow\">Sources \u00b7 all require verification<\/span>\n <h2>References<\/h2>\n <p>Grouped by topic. Items marked <b>foundational<\/b> predate the 2015 window but remain the primary basis for the claim. Items marked <b>[verify]<\/b> could not be confirmed against the primary source and should be treated as pointers.<\/p>\n <\/div>\n <div class=\"refs\">\n <p class=\"refgroup\">Food form and processing<\/p>\n <p><b>Hall KD, et al.<\/b> (2019) Ultra-processed diets cause excess calorie intake and weight gain. <i>Cell Metabolism<\/i> 30(1):67\u201377.<\/p>\n <p><b>Hall KD, et al.<\/b> (2021) Effect of a plant-based, low-fat diet versus an animal-based, ketogenic diet on ad libitum energy intake. <i>Nature Medicine<\/i> 27(2):344\u2013353.<\/p>\n <p><b>de Souza RJ, et al.<\/b> (2015) Intake of saturated and trans unsaturated fatty acids and risk of all cause mortality, cardiovascular disease, and type 2 diabetes. <i>BMJ<\/i> 351:h3978.<\/p>\n\n <p class=\"refgroup\">Protein requirement and quality<\/p>\n <p><b>Humayun MA, et al.<\/b> (2007) Reevaluation of the protein requirement in young men with the indicator amino acid oxidation technique. <i>Am J Clin Nutr<\/i> 86(4):995\u20131002. <i>Foundational.<\/i><\/p>\n <p><b>Rafii M, et al.<\/b> (2015, 2016) Dietary protein requirement of older men \/ women determined by the indicator amino acid oxidation technique. <i>J Nutr<\/i>.<\/p>\n <p><b>Morton RW, et al.<\/b> (2018) A systematic review, meta-analysis and meta-regression of the effect of protein supplementation on resistance training\u2013induced gains. <i>Br J Sports Med<\/i> 52(6):376\u2013384.<\/p>\n <p><b>Bauer J, et al.<\/b> (2013) PROT-AGE position paper. <i>J Am Med Dir Assoc<\/i> 14(8):542\u2013559. <b>Deutz NEP, et al.<\/b> (2014) ESPEN recommendations. <i>Clin Nutr<\/i> 33(6):929\u2013936.<\/p>\n <p><b>Devries MC, et al.<\/b> (2018) Changes in kidney function do not differ between healthy adults consuming higher- vs normal-protein diets. <i>J Nutr<\/i> 148(11):1760\u20131775.<\/p>\n <p><b>Van Elswyk ME, et al.<\/b> (2018) A systematic review of renal health in healthy individuals associated with protein intake. <i>Adv Nutr<\/i> 9(4):404\u2013418.<\/p>\n <p><b>Shams-White MM, et al.<\/b> (2017) Dietary protein and bone health. <i>Am J Clin Nutr<\/i> 105(6):1528\u20131543. <b>Groenendijk I, et al.<\/b> (2019) <i>Bone Rep<\/i>.<\/p>\n <p><b>Levine ME, et al.<\/b> (2014) Low protein intake is associated with a major reduction in IGF-1, cancer, and overall mortality in the 65 and younger but not older population. <i>Cell Metabolism<\/i> 19(3):407\u2013417.<\/p>\n <p><b>Herreman L, et al.<\/b> (2020) Comprehensive overview of the quality of plant- and animal-sourced proteins based on DIAAS. <i>Food Sci Nutr<\/i> 8(10):5379\u20135391.<\/p>\n <p><b>Marinangeli CPF, House JD<\/b> (2017) Potential impact of the digestible indispensable amino acid score as a measure of protein quality. <i>Nutr Rev<\/i> 75(8):658\u2013667.<\/p>\n\n <p class=\"refgroup\">Carbohydrate, ketosis and metabolic state<\/p>\n <p><b>Institute of Medicine<\/b> (2005) <i>Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids.<\/i> National Academies Press. <i>Foundational \u2014 source of the 130 g\/day RDA and the statement on minimum carbohydrate.<\/i><\/p>\n <p><b>Owen OE, et al.<\/b> (1967) Brain metabolism during fasting. <i>J Clin Invest<\/i> 46(10):1589\u20131595. <i>Foundational.<\/i><\/p>\n <p><b>Cahill GF<\/b> (2006) Fuel metabolism in starvation. <i>Annu Rev Nutr<\/i> 26:1\u201322. <i>Foundational.<\/i><\/p>\n <p><b>Cunnane SC, et al.<\/b> (2016) Can ketones help rescue brain fuel supply in later life? <i>Front Mol Neurosci<\/i> 9:53. <b>Cunnane SC, et al.<\/b> (2020) Brain energy rescue. <i>Nat Rev Drug Discov<\/i>.<\/p>\n <p><b>Seidelmann SB, et al.<\/b> (2018) Dietary carbohydrate intake and mortality: a prospective cohort study and meta-analysis. <i>Lancet Public Health<\/i> 3(9):e419\u2013e428.<\/p>\n <p><b>Dehghan M, et al.<\/b> (2017) Associations of fats and carbohydrate intake with cardiovascular disease and mortality (PURE). <i>Lancet<\/i> 390(10107):2050\u20132062.<\/p>\n <p><b>Lean MEJ, et al.<\/b> (2018, 2019) DiRECT: primary care\u2013led weight management for remission of type 2 diabetes. <i>Lancet<\/i> \/ <i>Lancet Diabetes Endocrinol<\/i>.<\/p>\n <p><b>Hallberg SJ, et al.<\/b> (2018) <i>Diabetes Ther<\/i> 9(2):583\u2013612. <b>Athinarayanan SJ, et al.<\/b> (2019) <i>Front Endocrinol<\/i> 10:348.<\/p>\n <p><b>Gardner CD, et al.<\/b> (2018) Effect of low-fat vs low-carbohydrate diet on 12-month weight loss (DIETFITS). <i>JAMA<\/i> 319(7):667\u2013679.<\/p>\n <p><b>Burke LM, et al.<\/b> (2017) Low carbohydrate, high fat diet impairs exercise economy and negates the performance benefit from intensified training in elite race walkers. <i>J Physiol<\/i> 595(9):2785\u20132807.<\/p>\n <p><b>Norwitz NG, Budoff M, Feldman D, et al.<\/b> (2025) KETO-CTA: plaque progression in lean mass hyper-responders. <i>JACC: Advances.<\/i> <b>[verify \u2014 single-arm, no control group]<\/b><\/p>\n <p><b>Sacks FM, et al.<\/b> (2014) Effects of high vs low glycemic index of dietary carbohydrate (OmniCarb). <i>JAMA<\/i> 312(23):2531\u20132541.<\/p>\n\n <p class=\"refgroup\">Fats and fatty acids<\/p>\n <p><b>Hooper L, et al.<\/b> (2020) Reduction in saturated fat intake for cardiovascular disease. <i>Cochrane Database Syst Rev<\/i> 8:CD011737.<\/p>\n <p><b>Siri-Tarino PW, et al.<\/b> (2010) Meta-analysis of prospective cohort studies evaluating the association of saturated fat with cardiovascular disease. <i>Am J Clin Nutr<\/i> 91(3):535\u2013546. <i>Foundational.<\/i><\/p>\n <p><b>Chowdhury R, et al.<\/b> (2014) Association of dietary, circulating, and supplement fatty acids with coronary risk. <i>Ann Intern Med<\/i> 160(6):398\u2013406.<\/p>\n <p><b>Astrup A, et al.<\/b> (2020) Saturated fats and health: a reassessment and proposal for food-based recommendations. <i>J Am Coll Cardiol<\/i> 76(7):844\u2013857. <i>See published rebuttals in the same journal.<\/i><\/p>\n <p><b>Ramsden CE, et al.<\/b> (2016) Re-evaluation of the traditional diet-heart hypothesis: recovered data from the Minnesota Coronary Experiment. <i>BMJ<\/i> 353:i1246. <b>Ramsden CE, et al.<\/b> (2013) Sydney Diet Heart Study. <i>BMJ<\/i> 346:e8707.<\/p>\n <p><b>Marklund M, et al.<\/b> (2019) Biomarkers of dietary omega-6 fatty acids and incident cardiovascular disease and mortality: an individual-level pooled analysis of 30 cohort studies. <i>Circulation<\/i> 139(21):2422\u20132436.<\/p>\n <p><b>Neelakantan N, Seah JYH, van Dam RM<\/b> (2020) The effect of coconut oil consumption on cardiovascular risk factors: a systematic review and meta-analysis of clinical trials. <i>Circulation<\/i> 141(10):803\u2013814.<\/p>\n <p><b>Estruch R, et al.<\/b> (2018) Primary prevention of cardiovascular disease with a Mediterranean diet supplemented with extra-virgin olive oil or nuts (PREDIMED). <i>N Engl J Med<\/i> 378(25):e34. <i>Republished after randomisation correction.<\/i><\/p>\n <p><b>Zhong VW, et al.<\/b> (2019) Associations of dietary cholesterol or egg consumption with incident cardiovascular disease and mortality. <i>JAMA<\/i> 321(11):1081\u20131095.<\/p>\n <p><b>Burdge GC, Calder PC<\/b> (2005) Conversion of \u03b1-linolenic acid to longer-chain polyunsaturated fatty acids in human adults. <i>Reprod Nutr Dev<\/i> 45(5):581\u2013597. <i>Foundational.<\/i><\/p>\n\n <p class=\"refgroup\">Marine omega-3 and fish<\/p>\n <p><b>Bhatt DL, et al.<\/b> (2019) Cardiovascular risk reduction with icosapent ethyl for hypertriglyceridemia (REDUCE-IT). <i>N Engl J Med<\/i> 380(1):11\u201322.<\/p>\n <p><b>Nicholls SJ, et al.<\/b> (2020) Effect of high-dose omega-3 fatty acids vs corn oil on major adverse cardiovascular events (STRENGTH). <i>JAMA<\/i> 324(22):2268\u20132280.<\/p>\n <p><b>Manson JE, et al.<\/b> (2019) Marine n\u22123 fatty acids and prevention of cardiovascular disease and cancer (VITAL). <i>N Engl J Med<\/i> 380(1):23\u201332.<\/p>\n <p><b>ASCEND Study Collaborative Group<\/b> (2018) Effects of n\u22123 fatty acid supplements in diabetes mellitus. <i>N Engl J Med<\/i> 379(16):1540\u20131550.<\/p>\n <p><b>Abdelhamid AS, et al.<\/b> (2020) Omega-3 fatty acids for the primary and secondary prevention of cardiovascular disease. <i>Cochrane Database Syst Rev<\/i> 3:CD003177.<\/p>\n <p><b>Mozaffarian D, Rimm EB<\/b> (2006) Fish intake, contaminants, and human health. <i>JAMA<\/i> 296(15):1885\u20131899. <i>Foundational.<\/i><\/p>\n <p><b>Mohan D, et al.<\/b> (2021) Associations of fish consumption with risk of cardiovascular disease and mortality among individuals with and without vascular disease from 58 countries. <i>JAMA Intern Med<\/i> 181(5):631\u2013649.<\/p>\n <p><b>Chowdhury R, et al.<\/b> (2012) Association between fish consumption, long chain omega 3 fatty acids, and risk of cerebrovascular disease. <i>BMJ<\/i> 345:e6698.<\/p>\n <p><b>Hibbeln JR, et al.<\/b> (2007) Maternal seafood consumption in pregnancy and neurodevelopmental outcomes in childhood (ALSPAC). <i>Lancet<\/i> 369(9561):578\u2013585.<\/p>\n <p><b>FAO\/WHO<\/b> (2011) Report of the joint expert consultation on the risks and benefits of fish consumption. See also EFSA opinions on fish and methylmercury.<\/p>\n\n <p class=\"refgroup\">Fibre, vegetables, fruit and supplements<\/p>\n <p><b>Reynolds A, Mann J, et al.<\/b> (2019) Carbohydrate quality and human health: a series of systematic reviews and meta-analyses. <i>Lancet<\/i> 393(10170):434\u2013445.<\/p>\n <p><b>Aune D, et al.<\/b> (2017) Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all-cause mortality. <i>Int J Epidemiol<\/i> 46(3):1029\u20131056.<\/p>\n <p><b>Wang DD, et al.<\/b> (2021) Fruit and vegetable intake and mortality. <i>Circulation<\/i> 143(17):1642\u20131654.<\/p>\n <p><b>Appel LJ, et al.<\/b> (1997) A clinical trial of the effects of dietary patterns on blood pressure (DASH). <i>N Engl J Med<\/i> 336(16):1117\u20131124. <i>Foundational.<\/i><\/p>\n <p><b>Muraki I, et al.<\/b> (2013) Fruit consumption and risk of type 2 diabetes. <i>BMJ<\/i> 347:f5001.<\/p>\n <p><b>Carter P, et al.<\/b> (2010) Fruit and vegetable intake and incidence of type 2 diabetes mellitus. <i>BMJ<\/i> 341:c4229.<\/p>\n <p><b>Siervo M, et al.<\/b> (2013) Inorganic nitrate and beetroot juice supplementation reduces blood pressure in adults. <i>J Nutr<\/i> 143(6):818\u2013826.<\/p>\n <p><b>ATBC Study Group<\/b> (1994) The effect of vitamin E and beta carotene on the incidence of lung cancer. <i>N Engl J Med<\/i> 330(15):1029\u20131035. <i>Foundational.<\/i><\/p>\n <p><b>Omenn GS, et al.<\/b> (1996) Effects of a combination of beta carotene and vitamin A on lung cancer and cardiovascular disease (CARET). <i>N Engl J Med<\/i> 334(18):1150\u20131155. <i>Foundational.<\/i><\/p>\n <p><b>Klein EA, et al.<\/b> (2011) Vitamin E and the risk of prostate cancer (SELECT). <i>JAMA<\/i> 306(14):1549\u20131556.<\/p>\n <p><b>Bjelakovic G, et al.<\/b> (2012) Antioxidant supplements for prevention of mortality. <i>Cochrane Database Syst Rev<\/i> 3:CD007176.<\/p>\n <p><b>Baker LD, et al.<\/b> (2022\/2023) COSMOS-Mind \/ COSMOS-Web: multivitamin supplementation and cognition. <i>Alzheimers Dement<\/i> \/ <i>Am J Clin Nutr<\/i>. <b>[verify]<\/b><\/p>\n <p><b>Wallace TC, Fulgoni VL<\/b> (2017) Usual choline intakes are associated with egg and protein food consumption in the United States. <i>Nutrients<\/i> 9(8):839.<\/p>\n <p><b>Rolls BJ, et al.<\/b> Controlled feeding studies on dietary energy density and energy intake. <i>Am J Clin Nutr<\/i> \/ <i>Physiol Behav<\/i>, various.<\/p>\n\n <p class=\"refgroup\">Meat, colon and gastrointestinal<\/p>\n <p><b>Bouvard V, et al. (IARC Working Group)<\/b> (2015) Carcinogenicity of consumption of red and processed meat. <i>Lancet Oncol<\/i> 16(16):1599\u20131600.<\/p>\n <p><b>Johnston BC, et al.<\/b> (2019) Unprocessed red meat and processed meat consumption: dietary guideline recommendations from NutriRECS. <i>Ann Intern Med<\/i> 171(10):756\u2013764. <i>See accompanying critiques.<\/i><\/p>\n <p><b>Zheng Y, et al.<\/b> (2019) Association of changes in red meat consumption with total and cause-specific mortality. <i>BMJ<\/i> 365:l2110.<\/p>\n <p><b>Pan A, et al.<\/b> (2012) Red meat consumption and mortality. <i>Arch Intern Med<\/i> 172(7):555\u2013563. <i>Foundational.<\/i><\/p>\n <p><b>Aune D, et al.<\/b> (2016) Whole grain consumption and risk of cardiovascular disease, cancer, and all cause and cause specific mortality. <i>BMJ<\/i> 353:i2716.<\/p>\n <p><b>Strate LL, et al.<\/b> (2008) Nut, corn, and popcorn consumption and the incidence of diverticular disease. <i>JAMA<\/i> 300(8):907\u2013914.<\/p>\n <p><b>Biesiekierski JR, et al.<\/b> (2013) No effects of gluten in patients with self-reported non-celiac gluten sensitivity after dietary reduction of fermentable, poorly absorbed, short-chain carbohydrates. <i>Gastroenterology<\/i> 145(2):320\u2013328.<\/p>\n <p><b>D\u00edaz-Gay M, Alexandrov LB, et al.<\/b> (2025) Colibactin mutational signatures in early-onset colorectal cancer. <i>Nature.<\/i> <b>[verify \u2014 citation, fold-enrichment and causal inference]<\/b><\/p>\n <p><b>World Cancer Research Fund \/ AICR<\/b> Continuous Update Project \u2014 colorectal cancer. Authoritative synthesis for the effect sizes cited.<\/p>\n\n <p class=\"refgroup\">Sodium<\/p>\n <p><b>O'Donnell M, et al.<\/b> (2014) Urinary sodium and potassium excretion, mortality, and cardiovascular events (PURE). <i>N Engl J Med<\/i> 371(7):612\u2013623.<\/p>\n <p><b>Sacks FM, et al.<\/b> (2001) Effects on blood pressure of reduced dietary sodium and the DASH diet (DASH-Sodium). <i>N Engl J Med<\/i> 344(1):3\u201310. <i>Foundational.<\/i><\/p>\n <p><b>Neal B, et al.<\/b> (2021) Effect of salt substitution on cardiovascular events and death (SSaSS). <i>N Engl J Med<\/i> 385(12):1067\u20131077. <b>[verify intervals]<\/b><\/p>\n\n <p class=\"refgroup\">Cognition and dementia<\/p>\n <p><b>Morris MC, et al.<\/b> (2015) MIND diet associated with reduced incidence of Alzheimer's disease. <i>Alzheimers Dement<\/i> 11(9):1007\u20131014.<\/p>\n <p><b>Barnes LL, et al.<\/b> (2023) Trial of the MIND diet for prevention of cognitive decline in older persons. <i>N Engl J Med<\/i> 389(7):602\u2013611.<\/p>\n <p><b>Ngandu T, et al.<\/b> (2015) A 2 year multidomain intervention of diet, exercise, cognitive training, and vascular risk monitoring versus control to prevent cognitive decline (FINGER). <i>Lancet<\/i> 385(9984):2255\u20132263.<\/p>\n <p><b>Andrieu S, et al.<\/b> (2017) Effect of long-term omega-3 polyunsaturated fatty acid supplementation with or without multidomain intervention on cognitive function (MAPT). <i>Lancet Neurol<\/i> 16(5):377\u2013389.<\/p>\n <p><b>Moll van Charante EP, et al.<\/b> (2016) Effectiveness of a 6-year multidomain vascular care intervention to prevent dementia (preDIVA). <i>Lancet<\/i> 388(10046):797\u2013805.<\/p>\n <p><b>Baker LD, et al.<\/b> (2025) US POINTER: structured versus self-guided lifestyle intervention and cognition. <i>JAMA.<\/i> <b>[verify \u2014 effect size, interval, p-value and DOI unconfirmed]<\/b><\/p>\n\n <p class=\"refgroup\">Misconceptions, personalisation and methods<\/p>\n <p><b>Messina M, et al.<\/b> (2021) Neither soyfoods nor isoflavones warrant classification as endocrine disruptors: a technical review of the observational and clinical data. <i>Crit Rev Food Sci Nutr<\/i>.<\/p>\n <p><b>Sievert K, et al.<\/b> (2019) Effect of breakfast on weight and energy intake: systematic review and meta-analysis of randomised controlled trials. <i>BMJ<\/i> 364:l42.<\/p>\n <p><b>Lowe DA, et al.<\/b> (2020) Effects of time-restricted eating on weight loss and other metabolic parameters (TREAT). <i>JAMA Intern Med<\/i> 180(11):1491\u20131499.<\/p>\n <p><b>Zeevi D, Korem T, Segal E, et al.<\/b> (2015) Personalized nutrition by prediction of glycemic responses. <i>Cell<\/i> 163(5):1079\u20131094.<\/p>\n <p><b>Berry SE, Spector TD, et al.<\/b> (2020) Human postprandial responses to food and potential for precision nutrition (PREDICT 1). <i>Nature Medicine<\/i> 26(6):964\u2013973.<\/p>\n <p><b>Celis-Morales C, et al.<\/b> (2017) Effect of personalized nutrition on health-related behaviour change: the Food4Me European randomized controlled trial. <i>Int J Epidemiol<\/i> 46(2):578\u2013588.<\/p>\n <p><b>Simpson SJ, Raubenheimer D<\/b> (2005) Obesity: the protein leverage hypothesis. <i>Obes Rev<\/i> 6(2):133\u2013142. <i>Foundational.<\/i><\/p>\n <p><b>Ioannidis JPA<\/b> (2018) The challenge of reforming nutritional epidemiologic research. <i>JAMA<\/i> 320(10):969\u2013970.<\/p>\n <\/div>\n<\/section>\n\n<footer>\n EVIDENCE-GRADED SYNTHESIS \u00b7 CONSOLIDATED EDITION \u00b7 COMPILED JULY 2026 \u00b7 LITERATURE WINDOW 2015\u20132026 WITH FOUNDATIONAL EXCEPTIONS MARKED<br>\n NOT MEDICAL ADVICE AND NOT A CLINICAL GUIDELINE. IF YOU ARE PREGNANT OR LACTATING, OR HAVE CHRONIC KIDNEY DISEASE, DIABETES (ESPECIALLY ON INSULIN OR SGLT2 INHIBITORS), CARDIOVASCULAR DISEASE, FAMILIAL HYPERCHOLESTEROLAEMIA, OR AN EATING DISORDER, OR TAKE MEDICATION \u2014 INVOLVE A PHYSICIAN OR REGISTERED DIETITIAN BEFORE CHANGING YOUR DIET.<br>\n LIVE LITERATURE SEARCH WAS UNAVAILABLE FOR MOST SESSIONS THAT PRODUCED THIS DOCUMENT \u00b7 ALL EFFECT ESTIMATES, INTERVALS, SAMPLE SIZES, DIAAS SCORES, NUTRIENT VALUES AND DOIs REQUIRE INDEPENDENT VERIFICATION AGAINST PRIMARY SOURCES BEFORE PUBLICATION OR USE.\n<\/footer>\n\n<\/div>\n<script>\n(function(){\n var els=document.querySelectorAll('.reveal,.wipe,.grow,.draw');\n if(!('IntersectionObserver' in window)){els.forEach(function(e){e.classList.add('in')});return;}\n var io=new IntersectionObserver(function(en){en.forEach(function(e){if(e.isIntersecting){e.target.classList.add('in');io.unobserve(e.target);}})},{threshold:0.1,rootMargin:'0px 0px -6% 0px'});\n els.forEach(function(e){io.observe(e)});\n})();\n<\/script>\n<\/body>\n<\/html>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-eebb4d9 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"eebb4d9\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-15ae8d2\" data-id=\"15ae8d2\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-22ff637 elementor-widget elementor-widget-heading\" data-id=\"22ff637\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Add Your Heading Text Here<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Human Nutrient Requirements: An Evidence-Graded Synthesis Evidence-graded synthesis \u00b7 literature window 2015\u20132026 \u00b7 Author: RezaRaza.com Not a guideline \u00b7 Not medical advice What nutrient a human body actually requires, ranked by how well we know it. This document reorganises nutrition around a single axis: not food groups, not servings, but how well each claim survives […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_canvas","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[26,28,27,25],"class_list":["post-744","post","type-post","status-publish","format-standard","hentry","category-text","tag-food","tag-food-2026","tag-nutrition","tag-nutrition-2026"],"_links":{"self":[{"href":"https:\/\/rezaraza.com\/fr\/wp-json\/wp\/v2\/posts\/744","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rezaraza.com\/fr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/rezaraza.com\/fr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/rezaraza.com\/fr\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/rezaraza.com\/fr\/wp-json\/wp\/v2\/comments?post=744"}],"version-history":[{"count":25,"href":"https:\/\/rezaraza.com\/fr\/wp-json\/wp\/v2\/posts\/744\/revisions"}],"predecessor-version":[{"id":800,"href":"https:\/\/rezaraza.com\/fr\/wp-json\/wp\/v2\/posts\/744\/revisions\/800"}],"wp:attachment":[{"href":"https:\/\/rezaraza.com\/fr\/wp-json\/wp\/v2\/media?parent=744"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/rezaraza.com\/fr\/wp-json\/wp\/v2\/categories?post=744"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/rezaraza.com\/fr\/wp-json\/wp\/v2\/tags?post=744"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}