{"id":1947,"date":"2026-08-23T20:43:53","date_gmt":"2026-08-23T20:43:53","guid":{"rendered":"https:\/\/lean-app.com\/?p=1947"},"modified":"2026-09-05T10:39:09","modified_gmt":"2026-09-05T10:39:09","slug":"etude-base-donnees-calories","status":"publish","type":"post","link":"https:\/\/lean-app.com\/no\/etude-base-donnees-calories\/","title":{"rendered":"Vi analyserte 857 655 produkter solgt i Frankrike: det kaloriskanneren din ikke forteller deg"},"content":{"rendered":"<script data-wpmeteor-nooptimize=\"true\" type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"Dataset\",\n  \"name\": \"Coh\u00e9rence calorique des produits alimentaires vendus en France (OpenFoodFacts, ao\u00fbt 2026)\",\n  \"description\": \"Agr\u00e9gats issus de l'analyse de 857 655 produits vendus en France depuis le dump public OpenFoodFacts du 23 ao\u00fbt 2026 : compl\u00e9tude des fiches et coh\u00e9rence entre calories d\u00e9clar\u00e9es et calories recalcul\u00e9es depuis les macronutriments (facteurs Atwater, r\u00e8glement INCO 1169\/2011).\",\n  \"url\": \"https:\/\/lean-app.com\/etude-base-donnees-calories\/\",\n  \"creator\": {\"@type\": \"Organization\", \"name\": \"L'\u00e9quipe Lean\", \"url\": \"https:\/\/lean-app.com\/\"},\n  \"identifier\": [\"https:\/\/doi.org\/10.5281\/zenodo.22284416\", \"https:\/\/doi.org\/10.6084\/m9.figshare.33432244\"],\n  \"sameAs\": [\"https:\/\/zenodo.org\/records\/22284416\", \"https:\/\/figshare.com\/articles\/preprint\/33432244\", \"https:\/\/osf.io\/tczvj\/\", \"https:\/\/www.wikidata.org\/wiki\/Q141267884\"],\n  \"isBasedOn\": \"https:\/\/world.openfoodfacts.org\/data\",\n  \"license\": \"https:\/\/opendatacommons.org\/licenses\/odbl\/1-0\/\",\n  \"temporalCoverage\": \"2026-08-23\",\n  \"spatialCoverage\": \"France\",\n  \"variableMeasured\": [\"energy-kcal_100g\", \"proteins_100g\", \"carbohydrates_100g\", \"fat_100g\", \"fiber_100g\", \"alcohol_100g\", \"polyols_100g\"]\n}\n<\/script>\n<script data-wpmeteor-nooptimize=\"true\" type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [\n    {\"@type\": \"Question\", \"name\": \"Pourquoi analyser OpenFoodFacts et pas USDA ?\",\n     \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Pour les produits \u00e0 code-barres vendus en France, la source de r\u00e9f\u00e9rence des trackers est OpenFoodFacts. USDA couvre les aliments bruts et le march\u00e9 am\u00e9ricain. L'\u00e9tude porte sur ce que renvoie r\u00e9ellement un scan en France.\"}},\n    {\"@type\": \"Question\", \"name\": \"Faut-il arr\u00eater de scanner ses aliments ?\",\n     \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Non. Le scan reste le moyen le plus rapide de logger. La bonne pratique : v\u00e9rifier que les macros affich\u00e9es sont coh\u00e9rentes avec les calories. Si prot\u00e9ines, glucides et lipides ne collent pas aux kcal, la fiche est fausse.\"}},\n    {\"@type\": \"Question\", \"name\": \"Les applications corrigent-elles ces erreurs ?\",\n     \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"La base OpenFoodFacts est collaborative et vit en continu : 4 des 6 pires fiches identifi\u00e9es dans le dump avaient d\u00e9j\u00e0 \u00e9t\u00e9 corrig\u00e9es en ligne au moment de l'\u00e9tude. Mais une application qui a synchronis\u00e9 une fiche fausse peut la garder en cache longtemps apr\u00e8s la correction.\"}},\n    {\"@type\": \"Question\", \"name\": \"La base de Lean est-elle diff\u00e9rente ?\",\n     \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Lean croise la base USDA pour les aliments bruts et OpenFoodFacts pour les produits \u00e0 code-barres, et propose le scan photo IA qui estime l'assiette sans d\u00e9pendre d'une fiche. Surtout, Lean concentre la pr\u00e9cision l\u00e0 o\u00f9 l'erreur est invisible : le calcul de la d\u00e9pense (TDEE = BMR + NEAT + EAT + TEF).\"}}\n  ]\n}\n<\/script>\n<style id=\"lvm-shell-styles\">#lvm-shell{\n  --bg:#FFFFFF; --paper:#F7F6F2; --paper-2:#F1EFE7;\n  --ink:#0E0E10; --ink-2:#1D1D1F; --muted:#6E6E73; --dim:#86868B;\n  --rule:#E8E6DF; --rule-soft:#EFEDE5;\n  --pink:#FF2D6E; --pink-soft:rgba(255,45,110,0.06);\n  --mfp:#6ABF6C;\n  --green:#0F8F5C; --red:#D02E2E; --amber:#C8A019;\n  --font-display:-apple-system,\"SF Pro Display\",system-ui,\"Helvetica Neue\",sans-serif;\n  --font-text:-apple-system,\"SF Pro Text\",system-ui,sans-serif;\n  --font-mono:ui-monospace,\"SF Mono\",Menlo,Consolas,monospace;\n}\n#lvm-shell *{box-sizing:border-box;-webkit-text-size-adjust:100%}\n#lvm-shell, #lvm-shell{margin:0;padding:0;background:var(--bg);color:var(--ink-2);font-family:var(--font-text);font-size:17px;line-height:1.7;-webkit-font-smoothing:antialiased}\n#lvm-shell 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strong{display:block;color:var(--ink);margin-top:4px;font-family:var(--font-display);font-size:14px;font-weight:500;letter-spacing:-.01em;text-transform:none}\n\n#lvm-shell .duo-row{display:grid;grid-template-columns:repeat(2,1fr);gap:20px;margin:18px 0 0}\n#lvm-shell .duo-row .mini-phone{max-width:180px}\n\n#lvm-shell .method{display:grid;grid-template-columns:1fr 1.4fr;gap:36px;align-items:center;margin:42px 0}\n#lvm-shell .method.flip{grid-template-columns:1.4fr 1fr}\n#lvm-shell .method.flip .m-phone{order:2}\n#lvm-shell .method .m-tag{font-family:var(--font-mono);font-size:11px;font-weight:600;text-transform:uppercase;letter-spacing:.08em;color:var(--pink);margin-bottom:8px}\n#lvm-shell .method h3{margin-top:0}\n#lvm-shell .method p{font-size:16px;color:var(--muted);line-height:1.7}\n\n#lvm-shell .cta-band{margin:40px 0;padding:26px 28px;background:var(--paper);border-radius:16px;display:flex;align-items:center;justify-content:space-between;gap:20px;flex-wrap:wrap;border:1px solid var(--rule-soft)}\n#lvm-shell .cta-band .l{font-family:var(--font-display);font-size:18px;line-height:1.35;font-weight:500;color:var(--ink);flex:1;min-width:240px;letter-spacing:-.01em}\n#lvm-shell .cta-band .stores{display:flex;gap:10px;align-items:center}\n#lvm-shell .cta-band .stores a{line-height:0;transition:transform .15s}\n#lvm-shell .cta-band .stores a:hover{transform:translateY(-2px)}\n#lvm-shell .cta-band .stores img{height:42px;width:auto;border-radius:9px}\n\n#lvm-shell .pyramid{margin:30px auto;max-width:440px}\n#lvm-shell .pyramid .level{margin:6px auto;padding:13px 18px;border-radius:14px;color:#fff;font-family:var(--font-display);font-weight:500;font-size:15px;letter-spacing:-.01em;display:flex;justify-content:space-between;align-items:center;box-shadow:0 6px 18px rgba(0,0,0,.06)}\n#lvm-shell .pyramid .level .k{font-family:var(--font-mono);font-size:10px;text-transform:uppercase;letter-spacing:.08em;opacity:.75}\n#lvm-shell .pyramid .l1{background:#0E0E10;width:100%}\n#lvm-shell .pyramid .l2{background:#1D1D1F;width:84%}\n#lvm-shell .pyramid .l3{background:#3a3a3c;width:68%}\n#lvm-shell .pyramid .l4{background:var(--pink);width:52%}\n#lvm-shell .pyramid-cap{text-align:center;font-size:13px;color:var(--muted);margin-top:14px}\n\n\/* Section 7 honnetete : scorecard horizontal bars *\/\n#lvm-shell .scorecard{margin:30px 0 10px;border:1px solid var(--rule);border-radius:20px;padding:28px 26px;background:#fff}\n#lvm-shell .scorecard-head{display:grid;grid-template-columns:1.4fr 1fr 1fr;column-gap:28px;align-items:center;padding-bottom:18px;margin-bottom:8px;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell .scorecard-head .h-crit{font-family:var(--font-mono);font-size:11px;font-weight:500;text-transform:uppercase;letter-spacing:.08em;color:var(--muted)}\n#lvm-shell .scorecard-head .h-brand{display:flex;align-items:center;gap:8px;font-family:var(--font-display);font-size:14px;font-weight:600;color:var(--ink)}\n#lvm-shell .scorecard-head .h-brand img{width:22px;height:22px;border-radius:5px;object-fit:cover}\n#lvm-shell .scorecard-row{display:grid;grid-template-columns:1.4fr 1fr 1fr;column-gap:28px;align-items:center;padding:14px 0;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell .scorecard-row:last-child{border-bottom:0}\n#lvm-shell .scorecard-row .crit{font-size:14px;color:var(--ink);font-weight:500;padding-right:14px}\n#lvm-shell .scorecard-row .bar{display:flex;flex-direction:row-reverse;align-items:center;gap:10px}\n#lvm-shell .scorecard-row .bar .b{flex:1;height:8px;border-radius:99px;background:var(--rule-soft);overflow:hidden;position:relative}\n#lvm-shell .scorecard-row .bar .b > i{display:block;height:100%;border-radius:99px;transition:width 1s cubic-bezier(.22,.61,.36,1)}\n#lvm-shell .scorecard-row .bar.lean .b > i{background:var(--pink)}\n#lvm-shell .scorecard-row .bar.mfp .b > i{background:var(--mfp)}\n#lvm-shell .scorecard-row .bar .v{font-family:var(--font-mono);font-size:12px;font-weight:600;color:var(--ink);min-width:32px;text-align:left}\n\n\/* Section 8 pour qui : persona checklist *\/\n#lvm-shell .persona{margin:28px 0 10px;display:grid;grid-template-columns:1fr;gap:14px}\n#lvm-shell .persona-it{display:grid;grid-template-columns:54px 1fr;gap:16px;padding:22px 24px;background:#fff;border:1px solid var(--rule);border-radius:18px;align-items:center}\n#lvm-shell .persona-it.match{background:var(--pink-soft);border-color:rgba(255,45,110,.25)}\n#lvm-shell .persona-it .pic{width:54px;height:54px;border-radius:50%;display:flex;align-items:center;justify-content:center;background:var(--rule-soft);position:relative;font-family:var(--font-mono);font-size:13px;font-weight:600;color:var(--ink)}\n#lvm-shell .persona-it.match .pic{background:var(--pink);color:#fff}\n#lvm-shell .persona-it .pic svg{width:24px;height:24px}\n#lvm-shell .persona-it h4{margin:0 0 4px;font-size:17px;letter-spacing:-.01em}\n#lvm-shell .persona-it p{margin:0;font-size:14px;color:var(--muted);line-height:1.55}\n#lvm-shell .persona-it.match h4{color:var(--ink)}\n\n\/* Section 9 migration : timeline steps *\/\n#lvm-shell .steps{display:grid;grid-template-columns:repeat(5,1fr);gap:14px;margin:28px 0;position:relative}\n#lvm-shell .steps::before{content:\"\";position:absolute;top:14px;left:7px;right:calc(20% - 18px);height:1px;background:linear-gradient(90deg,var(--pink) 0%,var(--rule-soft) 100%);z-index:0}\n#lvm-shell .step{position:relative;padding-top:24px;z-index:1}\n#lvm-shell .step::before{content:\"\";position:absolute;top:8px;left:0;width:14px;height:14px;border-radius:50%;background:var(--pink);border:3px solid #fff;box-shadow:0 0 0 1px var(--rule)}\n#lvm-shell .step .sn{font-family:var(--font-mono);font-size:11px;color:var(--pink);font-weight:600;letter-spacing:.08em}\n#lvm-shell .step h4{margin:6px 0 6px;font-size:15px;letter-spacing:-.01em}\n#lvm-shell .step p{font-size:13px;color:var(--muted);line-height:1.5;margin:0}\n\n\/* Section 10 debloque : feature stack numbered XL *\/\n#lvm-shell .feat-stack{margin:30px 0 10px;border-top:1px solid var(--rule)}\n#lvm-shell .feat-it{display:grid;grid-template-columns:auto 1fr auto;gap:24px;padding:26px 0;border-bottom:1px solid var(--rule);align-items:center}\n#lvm-shell .feat-it .fn{font-family:var(--font-display);font-size:48px;font-weight:600;color:var(--pink);line-height:1;letter-spacing:-.04em;width:74px}\n#lvm-shell .feat-it .ft{font-family:var(--font-display);font-size:22px;font-weight:600;color:var(--ink);letter-spacing:-.015em;line-height:1.25;margin-bottom:6px}\n#lvm-shell .feat-it .fd{font-size:15px;color:var(--muted);line-height:1.55;margin:0}\n#lvm-shell .feat-it .fc{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.08em;color:var(--muted);font-weight:500}\n#lvm-shell .feat-it:last-child{border-bottom:0}\n\n#lvm-shell .faq{margin:22px 0}\n#lvm-shell .faq details{border-bottom:1px solid var(--rule);padding:20px 0}\n#lvm-shell .faq details:first-of-type{border-top:1px solid var(--rule)}\n#lvm-shell .faq summary{cursor:pointer;list-style:none;display:flex;justify-content:space-between;align-items:center;gap:18px;font-family:var(--font-display);font-size:20px;font-weight:500;letter-spacing:-.015em;color:var(--ink)}\n#lvm-shell .faq summary::-webkit-details-marker{display:none}\n#lvm-shell .faq summary::after{content:\"+\";font-size:24px;color:var(--muted);font-weight:300;line-height:1;transition:transform .25s, color .25s}\n#lvm-shell .faq details[open] summary::after{transform:rotate(45deg);color:var(--pink)}\n#lvm-shell .faq details[open] summary{color:var(--pink)}\n#lvm-shell .faq .ans{margin-top:14px;font-size:16px;color:var(--muted);line-height:1.65}\n\n#lvm-shell .get-band{background:var(--paper-2);border-radius:24px;padding:48px 36px;margin:60px 0 40px;text-align:center}\n#lvm-shell .get-band .kicker{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;color:var(--pink);font-weight:600;letter-spacing:.1em;margin-bottom:14px}\n#lvm-shell .get-band h3{font-size:36px;margin:0 0 14px;letter-spacing:-.025em}\n#lvm-shell .get-band p{font-size:16px;color:var(--muted);max-width:480px;margin:0 auto 26px}\n#lvm-shell .get-band .stores{display:flex;justify-content:center;gap:14px;flex-wrap:wrap}\n#lvm-shell .get-band .stores a{line-height:0;transition:transform .15s}\n#lvm-shell .get-band .stores a:hover{transform:translateY(-3px)}\n#lvm-shell .get-band .stores img{height:60px;width:auto;border-radius:11px}\n\n#lvm-shell .sources{font-size:14px;color:var(--muted);line-height:1.7}\n#lvm-shell .sources ol{padding-left:22px}\n#lvm-shell .sources li{margin-bottom:8px}\n\n#lvm-shell footer{padding:50px 0 60px;border-top:1px solid var(--rule);margin-top:40px}\n#lvm-shell footer .row{display:flex;justify-content:space-between;align-items:center;gap:18px;flex-wrap:wrap}\n#lvm-shell footer .kicker{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.08em;color:var(--pink);font-weight:600}\n#lvm-shell footer p{font-size:13px;color:var(--muted);margin:8px 0 0}\n#lvm-shell footer .stores{display:flex;gap:8px}\n#lvm-shell footer .stores img{height:34px;width:auto;border-radius:6px}\n\n#lvm-shell .rev{opacity:0;transform:translateY(12px);transition:opacity .8s cubic-bezier(.22,.61,.36,1),transform .8s cubic-bezier(.22,.61,.36,1)}\n#lvm-shell .rev.on{opacity:1;transform:translateY(0)}\n@media (prefers-reduced-motion:reduce){#lvm-shell .rev{transition:none;opacity:1;transform:none}}\n\n@media (max-width:760px){\n  #lvm-shell .nav-row{padding:8px 18px;gap:8px}\n  #lvm-shell .nav-link{display:none}\n  #lvm-shell .nav-stores img{height:24px}\n  #lvm-shell .wrap{padding:0 22px}\n  #lvm-shell .hero{padding:34px 0 0}\n  #lvm-shell h1{font-size:46px;letter-spacing:-.035em}\n  #lvm-shell h1 .alt{font-size:.55em;margin-top:10px}\n  #lvm-shell .dek{font-size:20px}\n  #lvm-shell .hero-stores img{height:42px}\n  #lvm-shell .hero-bottom{grid-template-columns:1fr;gap:28px;margin:30px 0 40px;padding-top:24px;align-items:stretch}\n  #lvm-shell .phone-wrap{order:-1}\n  #lvm-shell .phone{width:240px}\n  #lvm-shell .tap-hint.desktop{display:none}\n  #lvm-shell .tap-hint.mobile{display:block;position:relative;left:auto;top:auto;text-align:center;margin:0 auto 10px;width:100%}\n  #lvm-shell .tap-hint.mobile .th-arrow{position:relative;display:block;margin:6px auto 0;width:34px;height:34px;transform:none;color:var(--pink)}\n  #lvm-shell .snippet{padding:24px 22px}\n  #lvm-shell .snippet p{font-size:18px}\n  #lvm-shell section{padding:48px 0}\n  #lvm-shell h2{font-size:34px;letter-spacing:-.03em}\n  #lvm-shell h3{font-size:24px}\n  #lvm-shell .section-label{margin-bottom:22px}\n  #lvm-shell .statement{padding:24px 0;margin:32px 0}\n  #lvm-shell .statement .num{font-size:44px}\n  #lvm-shell .statement .lbl{font-size:19px}\n  #lvm-shell .fig{padding:20px 14px 14px;border-radius:16px}\n  #lvm-shell .cv-wrap{height:310px}\n  #lvm-shell .method{grid-template-columns:1fr;gap:20px}\n  #lvm-shell .method.flip{grid-template-columns:1fr}\n  #lvm-shell .method.flip .m-phone{order:0}\n  #lvm-shell .mini-row{grid-template-columns:repeat(3,1fr);gap:10px}\n  #lvm-shell .mini-phone{padding:3px;border-radius:18px;border-width:1px;max-width:110px}\n  #lvm-shell .mini-phone .notch{width:42px;height:11px;border-radius:0 0 8px 8px}\n  #lvm-shell .mini-phone .scr{border-radius:15px}\n  #lvm-shell .mini-cap{font-size:10px}\n  #lvm-shell .mini-cap strong{font-size:13px}\n  #lvm-shell .duo-row{grid-template-columns:repeat(2,1fr);gap:12px}\n  #lvm-shell .duo-row .mini-phone{max-width:130px}\n  #lvm-shell .steps{grid-template-columns:1fr;gap:18px}\n  #lvm-shell .steps::before{display:none}\n  #lvm-shell .step{padding-top:0;padding-left:24px}\n  #lvm-shell .step::before{top:6px;left:0}\n  #lvm-shell .table-row{grid-template-columns:1.4fr .9fr .9fr}\n  #lvm-shell .table-row > .crit{padding:13px 12px;font-size:13px}\n  #lvm-shell .table-row > .cell{padding:13px 10px;font-size:12px;gap:8px}\n  #lvm-shell .table-row.head > div{padding:14px 12px;font-size:10px;gap:7px}\n  #lvm-shell .table-row.head .brand-cell img{width:20px;height:20px}\n  #lvm-shell .get-band{padding:36px 22px;border-radius:18px;margin:40px 0 30px}\n  #lvm-shell .get-band h3{font-size:28px}\n  #lvm-shell .get-band .stores img{height:50px}\n  #lvm-shell .cta-band{padding:22px;gap:14px}\n  #lvm-shell .cta-band .l{font-size:16px;min-width:0}\n  #lvm-shell .cta-band .stores img{height:38px}\n  #lvm-shell .faq summary{font-size:18px;gap:14px}\n  #lvm-shell .pyramid{max-width:100%}\n  #lvm-shell .pyramid .level{padding:11px 14px;font-size:14px}\n  #lvm-shell .scorecard{padding:20px 16px;border-radius:16px}\n  #lvm-shell .scorecard-head{grid-template-columns:1.2fr 1fr 1fr;column-gap:14px}\n  #lvm-shell .scorecard-head .h-brand{font-size:12px;gap:5px}\n  #lvm-shell .scorecard-head .h-brand img{width:18px;height:18px}\n  #lvm-shell .scorecard-row{grid-template-columns:1.2fr 1fr 1fr;column-gap:14px;padding:12px 0}\n  #lvm-shell .scorecard-row .crit{font-size:13px;padding-right:8px}\n  #lvm-shell .scorecard-row .bar{gap:6px}\n  #lvm-shell .scorecard-row .bar .v{font-size:11px;min-width:26px}\n  #lvm-shell .persona-it{grid-template-columns:44px 1fr;gap:12px;padding:16px 16px;border-radius:14px}\n  #lvm-shell .persona-it .pic{width:44px;height:44px;font-size:12px}\n  #lvm-shell .persona-it h4{font-size:15px}\n  #lvm-shell .persona-it p{font-size:13px}\n  #lvm-shell .feat-it{grid-template-columns:auto 1fr;gap:14px;padding:20px 0}\n  #lvm-shell .feat-it .fn{font-size:36px;width:54px}\n  #lvm-shell .feat-it .ft{font-size:18px}\n  #lvm-shell .feat-it .fd{font-size:13px}\n  #lvm-shell .feat-it .fc{display:none}\n}\n@media (max-width:480px){\n  #lvm-shell .phone-tabs{gap:5px}\n  #lvm-shell .phone-tabs button{padding:5px 8px;font-size:10px}\n  #lvm-shell .nav-stores{gap:4px}\n  #lvm-shell .nav-stores img{height:22px}\n  #lvm-shell .hero-stores img{height:40px}\n  #lvm-shell .crumb{font-size:12px}\n  #lvm-shell .table-row{grid-template-columns:1.3fr .85fr .85fr}\n  #lvm-shell .table-row > .crit{padding:11px 9px;font-size:12px}\n  #lvm-shell .table-row > .cell{padding:11px 8px;font-size:11px;gap:6px}\n  #lvm-shell .table-row.head > div{padding:11px 9px;font-size:9px;gap:5px}\n}\n\/* === Etude OFF === *\/\n#lvm-shell .bignum{font-family:var(--font-display);font-weight:600;font-size:88px;letter-spacing:-.045em;line-height:1;color:var(--pink);margin:8px 0 4px;font-variant-numeric:tabular-nums}\n#lvm-shell .bignum small{display:block;font-size:20px;color:var(--muted);font-weight:500;letter-spacing:-.01em;margin-top:10px;line-height:1.4}\n#lvm-shell .stat-grid{display:grid;grid-template-columns:repeat(3,1fr);gap:14px;margin:30px 0}\n#lvm-shell .stat-card{background:var(--paper);border:1px solid var(--rule-soft);border-radius:16px;padding:22px 20px}\n#lvm-shell .stat-card .n{font-family:var(--font-display);font-weight:600;font-size:34px;letter-spacing:-.03em;color:var(--ink);font-variant-numeric:tabular-nums}\n#lvm-shell .stat-card .n.pink{color:var(--pink)}\n#lvm-shell .stat-card .t{font-size:13.5px;color:var(--muted);margin-top:6px;line-height:1.5}\n#lvm-shell .metho{background:var(--paper);border:1px solid var(--rule-soft);border-left:4px solid var(--pink);border-radius:0 16px 16px 0;padding:24px 26px;margin:30px 0}\n#lvm-shell .metho h3{font-family:var(--font-display);font-size:17px;font-weight:600;margin:0 0 12px;letter-spacing:-.01em}\n#lvm-shell .metho ul{margin:0;padding-left:20px;font-size:15px;color:var(--muted);line-height:1.7}\n#lvm-shell .metho li{margin:4px 0}\n#lvm-shell .metho code{font-family:var(--font-mono);font-size:13.5px;background:var(--paper-2);padding:1px 6px;border-radius:5px;color:var(--ink-2)}\n#lvm-shell .prod-cards{display:grid;gap:14px;margin:28px 0}\n#lvm-shell .prod-card{display:flex;align-items:center;gap:18px;background:var(--paper);border:1px solid var(--rule-soft);border-radius:16px;padding:18px 22px;flex-wrap:wrap}\n#lvm-shell .prod-card .who{flex:1;min-width:200px}\n#lvm-shell .prod-card .who b{font-family:var(--font-display);font-size:16.5px;letter-spacing:-.01em;color:var(--ink);display:block}\n#lvm-shell .prod-card .who span{font-size:13px;color:var(--muted)}\n#lvm-shell .prod-card .vals{display:flex;align-items:center;gap:14px;font-variant-numeric:tabular-nums}\n#lvm-shell .prod-card .fiche{font-family:var(--font-display);font-size:24px;font-weight:600;color:var(--ink);letter-spacing:-.02em}\n#lvm-shell .prod-card .fleche{color:var(--dim);font-size:17px}\n#lvm-shell .prod-card .reel{font-family:var(--font-display);font-size:24px;font-weight:600;color:var(--pink);letter-spacing:-.02em}\n#lvm-shell .prod-card .unit{font-size:11.5px;color:var(--dim);display:block;text-align:center;font-family:var(--font-mono);text-transform:uppercase;letter-spacing:.05em;margin-top:2px}\n@media (max-width:640px){\n  #lvm-shell .bignum{font-size:56px}\n  #lvm-shell .bignum small{font-size:16px}\n  #lvm-shell .stat-grid{grid-template-columns:1fr}\n  #lvm-shell .prod-card .fiche, #lvm-shell .prod-card .reel{font-size:20px}\n  #lvm-shell .cta-band{flex-direction:column;align-items:flex-start}\n  #lvm-shell .cta-band .l{min-width:100%;flex:none}\n}\n<\/style>\n\n<style id=\"lvm-collision-reset\">\nbody.postid-1947 #lvm-shell .hero{display:block!important;align-items:initial!important;justify-content:initial!important;text-align:left!important;flex-direction:initial!important;padding:54px 0 0!important}\nbody.postid-1947 #lvm-shell .wrap,\nbody.postid-1947 #lvm-shell 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.l{min-width:0!important;width:100%!important;font-size:16px!important;line-height:1.5!important;text-align:center!important}\n  body.postid-1947 #lvm-shell .cta-band .stores{width:100%!important;justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1947 #lvm-shell .cta-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1947 #lvm-shell .cta-band .stores img{height:56px!important;width:100%!important;max-width:170px!important;object-fit:contain!important;object-position:center!important;border-radius:10px!important}\n}\n<\/style>\n<div id=\"lvm-shell\">\n<div class=\"progress\" aria-hidden=\"true\"><i id=\"progBar\"><\/i><\/div>\n\n<header class=\"nav\">\n  <div class=\"nav-row\">\n    <a class=\"nav-brand\" href=\"https:\/\/lean-app.com\/no\/\" aria-label=\"Accueil Lean\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/>\n      <span>Lean<\/span>\n    <\/a>\n    <span class=\"nav-spacer\"><\/span>\n    <a class=\"nav-link\" href=\"https:\/\/lean-app.com\/no\/tdee-calculator\/\">TDEE-kalkulator<\/a>\n    <div class=\"nav-stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=etude-off\" target=\"_blank\" rel=\"noopener\" aria-label=\"T\u00e9l\u00e9charger sur l'App Store\">\n        <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/>\n      <\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=etude-off\" target=\"_blank\" rel=\"noopener\" aria-label=\"Disponible sur Google Play\">\n        <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/>\n      <\/a>\n    <\/div>\n  <\/div>\n<\/header>\n\n<main class=\"wrap\">\n\n<section class=\"hero\" aria-labelledby=\"title\">\n  <div class=\"crumb\"><a href=\"https:\/\/lean-app.com\/no\/\">Hjem<\/a> &nbsp;\/&nbsp; Studie av kaloridatabasen<\/div>\n  <div class=\"eyebrow\">Original studie &middot; Offentlige data<\/div>\n  <h1 id=\"title\">857&nbsp;655 produkter analysert.\n    <span class=\"alt\">Det kaloriskanneren din ikke forteller deg.<\/span>\n  <\/h1>\n  <p class=\"dek\">Hver strekkodeskanning i Frankrike sp\u00f8r den samme basen. Vi har analysert den i sin helhet. Mer enn \u00e9n av tre skanninger gir en manglende, ufullstendig eller inkonsistent data.<\/p>\n  <div class=\"byline\">\n    <img class=\"by-logo\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"26\" height=\"26\" loading=\"lazy\" decoding=\"async\" \/>\n    <span>Av <strong>Lean-teamet<\/strong> &middot; publisert 24. august 2026 &middot; lesetid 7 min<\/span>\n  <\/div>\n  <div class=\"hero-stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=etude-off\" target=\"_blank\" rel=\"noopener\" aria-label=\"T\u00e9l\u00e9charger Lean sur l'App Store\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"T\u00e9l\u00e9charger sur l'App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=etude-off\" target=\"_blank\" rel=\"noopener\" aria-label=\"T\u00e9l\u00e9charger Lean sur Google Play\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Disponible sur Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"s1\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">01<\/span><\/div>\n  <h2 id=\"s1\">Hvorfor denne studien<\/h2>\n  <p>N\u00e5r du skanner en strekkode i en kaloritracker i Frankrike, MyFitnessPal, Yazio, Lifesum eller Lean, kommer dataen mer eller mindre fra samme kilde: <a href=\"https:\/\/world.openfoodfacts.org\/\" target=\"_blank\" rel=\"noopener\">OpenFoodFacts<\/a>, en formidabel fransk samarbeidsbase under \u00e5pen ODbL-lisens. Millioner av produktoppf\u00f8ringer, fylt ut av frivillige bidragsytere.<\/p>\n  <p>En samarbeidsbase, det er styrken og begrensningen: hvem som helst kan opprette eller endre en oppf\u00f8ring, og ingen sjekker systematisk. Ingen hadde tallfestet den reelle p\u00e5liteligheten i det skanningen din gir. Vi lastet derfor ned den komplette offentlige dumpen fra 23. august 2026 og testet hvert produkt solgt i Frankrike.<\/p>\n  <div class=\"stat-grid\">\n    <div class=\"stat-card\"><div class=\"n\">4 535 553<\/div><div class=\"t\">produkter i den globale basen per 23. august 2026<\/div><\/div>\n    <div class=\"stat-card\"><div class=\"n\">1 265 726<\/div><div class=\"t\">produkter referert som solgt i Frankrike<\/div><\/div>\n    <div class=\"stat-card\"><div class=\"n pink\">857 655<\/div><div class=\"t\">analyserbare produkter: kalorier og de 3 makroene oppgitt<\/div><\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"s2\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">02<\/span><\/div>\n  <h2 id=\"s2\">Metoden: hver oppf\u00f8ring testet mot seg selv<\/h2>\n  <p>Ingen lab trengs for \u00e5 oppdage en feil oppf\u00f8ring: det holder \u00e5 konfrontere den med seg selv. Kaloriene i en matvare utledes av makron\u00e6ringsstoffene med Atwater-faktorene, de samme som EU-forordningen INCO p\u00e5legger produsentene: 4&nbsp;kcal per gram protein, 4 per gram karbohydrater, 9 per gram fett.<\/p>\n  <p>Hvis en oppf\u00f8ring viser 100&nbsp;kcal, men de egne makroene gir 250, er \u00e9n av de to linjene feil. Og appen din viser deg en av dem uten \u00e5 blunke.<\/p>\n  <div class=\"metho\">\n    <h3>Komplett metodikk<\/h3>\n    <ul>\n      <li>Offisiell OpenFoodFacts-dump fra 23. august 2026 (ODbL-lisens), omfang Frankrike<\/li>\n      <li>Omberegning: <code>4&times;proteiner + 4&times;karbohydrater + 9&times;fett<\/code>, pluss 7&nbsp;kcal\/g alkohol, 2&nbsp;kcal\/g fiber og 2,4&nbsp;kcal\/g polyoler (erytritol: 0), i samsvar med INCO-forordning 1169\/2011<\/li>\n      <li>Oppf\u00f8ring regnet som inkonsistent bare hvis avviket overstiger b\u00e5de 10&nbsp;% og 30&nbsp;kcal\/100g: st\u00f8yen fra vann og te p\u00e5 2&nbsp;kcal er utelukket<\/li>\n      <li>16 364 avvikende oppf\u00f8ringer forkastet (kalorier utenfor 1-950&nbsp;kcal\/100g, umulige makroer)<\/li>\n      <li>Hvert eksempel sitert p\u00e5 denne siden er sjekket p\u00e5 nytt i den nettbaserte oppf\u00f8ringen p\u00e5 publiseringsdagen<\/li>\n    <\/ul>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"s3\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">03<\/span><\/div>\n  <h2 id=\"s3\">Resultat 1: nesten 1 av 3 oppf\u00f8ringer er ufullstendig<\/h2>\n  <div class=\"bignum\">31 %<small>av FR-produktene uten komplette data<\/small><\/div>\n  <p>391 707 produkter solgt i Frankrike har ikke kalorier oppgitt, eller ikke de tre makron\u00e6ringsstoffene sine. Konkret: du skanner, og appen viser 0&nbsp;kcal, eller kalorier uten proteiner eller karbohydrater. Du tror du logger, du logger tomhet.<\/p>\n  <figure class=\"fig rev\">\n    <div class=\"cv-wrap\" style=\"position:relative;width:100%;height:400px;min-height:360px\"><canvas id=\"chartDonut\" aria-label=\"R\u00e9partition des 1 265 726 produits fran\u00e7ais par fiabilit\u00e9 de fiche\" role=\"img\"><\/canvas><\/div>\n    <figcaption>Skjebnen til en skanning i Frankrike, p\u00e5 1 265 726 produkter.<\/figcaption>\n  <\/figure>\n  <p>Det er den mest lumske feilen, fordi den ikke ser ut som en feil: oppf\u00f8ringen vises, produktet har et navn, et bilde. Det mangler bare det viktigste.<\/p>\n<\/section>\n\n<section aria-labelledby=\"s4\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">04<\/span><\/div>\n  <h2 id=\"s4\">Resultat 2: 46 757 produkter med inkonsistente kalorier<\/h2>\n  <p>Av de 857 655 komplette oppf\u00f8ringene viser 46 757 kalorier som er uforenlige med de egne makroene, med minst 10&nbsp;% og 30&nbsp;kcal per 100&nbsp;g. Hvert punkt i grafen nedenfor er et ekte produkt: p\u00e5 x-aksen det oppf\u00f8ringen oppgir, p\u00e5 y-aksen det makroene gir. En \u00e6rlig oppf\u00f8ring havner p\u00e5 diagonalen.<\/p>\n  <figure class=\"fig rev\">\n    <div class=\"cv-wrap\" style=\"position:relative;width:100%;height:460px;min-height:420px\"><canvas id=\"chartScatter\" aria-label=\"Calories d\u00e9clar\u00e9es contre calories recalcul\u00e9es, \u00e9chantillon de 1 370 produits\" role=\"img\"><\/canvas><\/div>\n    <figcaption>1 370 ekte produkter: oppgitt vs beregnet p\u00e5 nytt fra makroene.<\/figcaption>\n  <\/figure>\n  <p>Fordelingen av avvikene viser at basen er massivt korrekt, og deretter g\u00e5r ut i en lang hale: de feilaktige oppf\u00f8ringene er ikke litt feil, de er sv\u00e6rt feil.<\/p>\n  <figure class=\"fig rev\">\n    <div class=\"cv-wrap\" style=\"position:relative;width:100%;height:360px;min-height:320px\"><canvas id=\"chartHisto\" aria-label=\"Distribution des \u00e9carts relatifs entre calories d\u00e9clar\u00e9es et recalcul\u00e9es\" role=\"img\"><\/canvas><\/div>\n    <figcaption>Fordeling av avvikene, logaritmisk skala.<\/figcaption>\n  <\/figure>\n  <figure class=\"fig rev\">\n    <div class=\"cv-wrap\" style=\"position:relative;width:100%;height:360px;min-height:320px\"><canvas id=\"chartSeuils\" aria-label=\"Inkonsistente produkter per avviksterskel\" role=\"img\"><\/canvas><\/div>\n    <figcaption>Inkonsistente produkter per avviksterskel, base 857 655 oppf\u00f8ringer.<\/figcaption>\n  <\/figure>\n  <p>18 251 produkter, alts\u00e5 to av fem materielt inkonsistente, bommer <em>fra enkelt til dobbelt eller mer<\/em>. P\u00e5 det niv\u00e5et er det ikke lenger en un\u00f8yaktighet, det er en data som snur dagens kaloribalanse.<\/p>\n  <p>Ved \u00e5 legge sammen ufullstendige og inkonsistente oppf\u00f8ringer: <strong>mer enn \u00e9n av tre skanninger i Frankrike gir en manglende, ufullstendig eller inkonsistent data<\/strong>.<\/p>\n<\/section>\n\n<section aria-labelledby=\"s5\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">05<\/span><\/div>\n  <h2 id=\"s5\">Produkter du har i skapet ditt<\/h2>\n  <p>Hver oppf\u00f8ring nedenfor er sjekket p\u00e5 nytt p\u00e5 nett p\u00e5 publiseringsdagen. Til venstre det OpenFoodFacts-oppf\u00f8ringen viser, til h\u00f8yre det de egne makroene gir:<\/p>\n  <div class=\"prod-cards\">\n    <div class=\"prod-card\"><div class=\"who\"><b>Le Beurre Tendre<\/b><span>oppf\u00f8ring for produktet Elle&amp;Vire &middot; 535 skanninger<\/span><\/div><div class=\"vals\"><span><span class=\"fiche\">375<\/span><span class=\"unit\">oppf\u00f8ring<\/span><\/span><span class=\"fleche\">&rarr;<\/span><span><span class=\"reel\">744<\/span><span class=\"unit\">makroer<\/span><\/span><\/div><\/div>\n    <div class=\"prod-card\"><div class=\"who\"><b>Yaos Yaourt \u00e0 la Grecque<\/b><span>oppf\u00f8ring for produktet Nestl\u00e9 &middot; 271 skanninger<\/span><\/div><div class=\"vals\"><span><span class=\"fiche\">50<\/span><span class=\"unit\">oppf\u00f8ring<\/span><\/span><span class=\"fleche\">&rarr;<\/span><span><span class=\"reel\">98<\/span><span class=\"unit\">makroer<\/span><\/span><\/div><\/div>\n    <div class=\"prod-card\"><div class=\"who\"><b>Sweet &amp; Salty Nut sjokolade<\/b><span>oppf\u00f8ring for produktet Nature Valley &middot; 338 skanninger<\/span><\/div><div class=\"vals\"><span><span class=\"fiche\">647<\/span><span class=\"unit\">oppf\u00f8ring<\/span><\/span><span class=\"fleche\">&rarr;<\/span><span><span class=\"reel\">140<\/span><span class=\"unit\">makroer<\/span><\/span><\/div><\/div>\n    <div class=\"prod-card\"><div class=\"who\"><b>Ratatouille \u00e0 la Proven\u00e7ale<\/b><span>oppf\u00f8ring for produktet Cassegrain &middot; 298 skanninger<\/span><\/div><div class=\"vals\"><span><span class=\"fiche\">38<\/span><span class=\"unit\">oppf\u00f8ring<\/span><\/span><span class=\"fleche\">&rarr;<\/span><span><span class=\"reel\">72<\/span><span class=\"unit\">makroer<\/span><\/span><\/div><\/div>\n  <\/div>\n  <p>Skoleeksempelet: linsene \u00e0 l&rsquo;Auvergnate fra Raynal &amp; Roquelaure finnes under <strong>to ulike oppf\u00f8ringer<\/strong>. Den ene viser 48&nbsp;kcal\/100g, den andre 207. Den reelle verdien er rundt 99. Avhengig av strekkoden appen din fanger, tror du at du spiser halvparten eller det dobbelte av virkeligheten.<\/p>\n  <p>En bruker som sm\u00f8rer 30&nbsp;g av sm\u00f8ret ovenfor, underteller 110&nbsp;kcal. Hver dag. I den tro at han gj\u00f8r det riktig.<\/p>\n  <div class=\"cta-band rev\">\n    <div class=\"l\">Lean sjekker konsistensen i oppf\u00f8ringene og skanner ogs\u00e5 tallerkenen din via foto, uten \u00e5 v\u00e6re avhengig av en strekkode.<\/div>\n    <div class=\"stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=etude-off\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=etude-off\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"s6\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">06<\/span><\/div>\n  <h2 id=\"s6\">De mest ber\u00f8rte kategoriene<\/h2>\n  <p>Inkonsistensen er ikke tilfeldig fordelt, og ironien i rangeringen er grusom: den mest ber\u00f8rte kategorien i hele basen er den idrettsut\u00f8vere sporer mest. <strong>Mer enn \u00e9n av fem proteinbarer (20,8&nbsp;%) har en inkonsistent oppf\u00f8ring.<\/strong><\/p>\n  <figure class=\"fig rev\">\n    <div class=\"cv-wrap\" style=\"position:relative;width:100%;height:460px;min-height:420px\"><canvas id=\"chartBubble\" aria-label=\"Cat\u00e9gories : volume de produits, taux et nombre de fiches incoh\u00e9rentes\" role=\"img\"><\/canvas><\/div>\n    <figcaption>Hver boble er en kategori; st\u00f8rrelsen, dens inkonsistente oppf\u00f8ringer.<\/figcaption>\n  <\/figure>\n  <p>Komplekse oppskrifter og berikede produkter konsentrerer feilene: proteinbarer, konfekt, godteri, oster. Enkle produkter klarer seg bedre.<\/p>\n  <figure class=\"fig rev\">\n    <div class=\"cv-wrap\" style=\"position:relative;width:100%;height:380px;min-height:340px\"><canvas id=\"chartCats\" aria-label=\"Taux d'incoh\u00e9rence par cat\u00e9gorie\" role=\"img\"><\/canvas><\/div>\n    <figcaption>Andel inkonsistente oppf\u00f8ringer per kategori (min. 1 000 produkter).<\/figcaption>\n  <\/figure>\n  <p>En \u00e6rlig merknad: godteri, konfekt og barer forklares delvis av s\u00f8tningsstoffer. N\u00e5r en oppf\u00f8ring ikke oppgir polyolene sine, overvurderer omberegningen avviket. Vi har korrigert alt som var oppgitt; resten gjenspeiler ogs\u00e5 dette hullet i oppgivelsen, som lurer appen din p\u00e5 n\u00f8yaktig samme m\u00e5te.<\/p>\n<\/section>\n\n<section aria-labelledby=\"s7\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">07<\/span><\/div>\n  <h2 id=\"s7\">Hva det endrer for loggingen din<\/h2>\n  <p>F\u00f8rst, det det ikke betyr: man skal ikke slutte \u00e5 skanne, og OpenFoodFacts forblir et bemerkelsesverdig prosjekt som lever og korrigeres kontinuerlig. Kurven nedenfor viser det: oppf\u00f8ringene opprettet i 2020-2021 er de minst p\u00e5litelige (opptil 7,5&nbsp;% inkonsistens), og kvaliteten har bedret seg klart siden 2023.<\/p>\n  <figure class=\"fig rev\">\n    <div class=\"cv-wrap\" style=\"position:relative;width:100%;height:340px;min-height:300px\"><canvas id=\"chartYears\" aria-label=\"Taux de fiches incoh\u00e9rentes selon l'ann\u00e9e de cr\u00e9ation de la fiche\" role=\"img\"><\/canvas><\/div>\n    <figcaption>Inkonsistensrate etter oppf\u00f8ringens opprettelses\u00e5r.<\/figcaption>\n  <\/figure>\n  <p>Fire av de seks verste oppf\u00f8ringene i dumpen var allerede korrigert p\u00e5 nett da vi sjekket. Men appen din har kanskje synkronisert den feilaktige versjonen, og de hundretusenvis av oppf\u00f8ringene opprettet i de verste \u00e5rene er fortsatt i basen.<\/p>\n  <p>To reflekser \u00e5 huske:<\/p>\n  <p><strong>1. Skanningen er et hastighetsverkt\u00f8y, ikke et sannhetsverkt\u00f8y.<\/strong> Etter en skanning holder et blikk p\u00e5 makroene: hvis proteiner, karbohydrater og fett ikke stemmer med de viste kaloriene, er oppf\u00f8ringen feil. Det er n\u00f8yaktig testen i denne studien, og den tar to sekunder.<\/p>\n  <p><strong>2. Den usynlige feilen ligger ikke p\u00e5 tallerkenen din, den ligger i forbruket ditt.<\/strong> En oppf\u00f8ring som er 110&nbsp;kcal feil, korrigeres p\u00e5 ti sekunder n\u00e5r den er oppdaget. Et kaloriforbruk som er 300&nbsp;kcal per dag feil, synes aldri: det er begravd i \u00abaktivitetsmultiplikatoren\u00bb appen din fikk deg til \u00e5 velge ved registreringen. Det er der Lean konsentrerer presisjonen sin: <a href=\"https:\/\/lean-app.com\/no\/depense-energetique-totale-v2\/\">TDEE = BMR + NEAT + EAT + TEF<\/a>, med en BMR beregnet p\u00e5 din <a href=\"https:\/\/lean-app.com\/no\/calcul-metabolisme-de-base\/\">reelle fettprosent<\/a> og en <a href=\"https:\/\/lean-app.com\/no\/calculateur-neat\/\">NEAT p\u00e5 de reelle skrittene dine<\/a>, ikke p\u00e5 en avkrysset boks.<\/p>\n  <div class=\"cta-band rev\">\n    <div class=\"l\">Bli Lean, forbli Lean: den eneste appen som beregner forbruket ditt p\u00e5 m\u00e5linger, ikke p\u00e5 bokser.<\/div>\n    <div class=\"stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=etude-off\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=etude-off\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"s9\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">08<\/span><\/div>\n  <h2 id=\"s9\">Vitenskapelige deponeringer og sitering<\/h2>\n  <p>Denne studien er deponert i uavhengige \u00e5pne arkiver, med en varig identifikator (DOI) og de komplette PDF-ene p\u00e5 fransk og engelsk. Hver deponering kan sjekkes uten \u00e5 g\u00e5 via dette nettstedet:<\/p>\n  <div class=\"prod-cards\">\n    <div class=\"prod-card\"><div class=\"who\"><b>Zenodo (CERN)<\/b><span>DOI 10.5281\/zenodo.22284416 &middot; referansedeponering, PDF FR + EN<\/span><\/div><div class=\"vals\"><a href=\"https:\/\/doi.org\/10.5281\/zenodo.22284416\" target=\"_blank\" rel=\"noopener\">\u00c5pne deponeringen &rarr;<\/a><\/div><\/div>\n    <div class=\"prod-card\"><div class=\"who\"><b>Figshare<\/b><span>DOI 10.6084\/m9.figshare.33432244 &middot; preprint, PDF FR + EN<\/span><\/div><div class=\"vals\"><a href=\"https:\/\/doi.org\/10.6084\/m9.figshare.33432244\" target=\"_blank\" rel=\"noopener\">\u00c5pne deponeringen &rarr;<\/a><\/div><\/div>\n    <div class=\"prod-card\"><div class=\"who\"><b>OSF (Center for Open Science)<\/b><span>offentlig prosjekt tczvj &middot; metodikk og filer<\/span><\/div><div class=\"vals\"><a href=\"https:\/\/osf.io\/tczvj\/\" target=\"_blank\" rel=\"noopener\">\u00c5pne prosjektet &rarr;<\/a><\/div><\/div>\n    <div class=\"prod-card\"><div class=\"who\"><b>data.gouv.fr<\/b><span>erkl\u00e6rt gjenbruk av datasettet Open Food Facts<\/span><\/div><div class=\"vals\"><a href=\"https:\/\/www.data.gouv.fr\/fr\/reuses\/etude-coherence-interne-des-donnees-caloriques-dopen-food-facts\/\" target=\"_blank\" rel=\"noopener\">Se gjenbruken &rarr;<\/a><\/div><\/div>\n  <\/div>\n  <p><strong>For \u00e5 sitere denne studien:<\/strong> Lean-teamet (2026). 857 655 produkter analysert: intern konsistens i kaloridata i Open Food Facts. Zenodo. https:\/\/doi.org\/10.5281\/zenodo.22284416<\/p>\n<\/section>\n\n<section aria-labelledby=\"s8\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">FAQ<\/span><\/div>\n  <h2 id=\"s8\">Questions fr\u00e9quentes<\/h2>\n  <div class=\"faq\">\n    <details><summary>Hvorfor OpenFoodFacts og ikke USDA?<\/summary><div class=\"ans\">For produkter med strekkode solgt i Frankrike er trackernes referansekilde OpenFoodFacts. USDA dekker r\u00e5varer og det amerikanske markedet. Denne studien handler om det en skanning i Frankrike faktisk gir.<\/div><\/details>\n    <details><summary>B\u00f8r man slutte \u00e5 skanne maten sin?<\/summary><div class=\"ans\">Nei. Skanningen forblir den raskeste m\u00e5ten \u00e5 logge p\u00e5. God praksis: sjekk at de viste makroene er konsistente med kaloriene. To sekunder som unng\u00e5r de verste oppf\u00f8ringene.<\/div><\/details>\n    <details><summary>Retter applikasjonene disse feilene?<\/summary><div class=\"ans\">Basen lever kontinuerlig og korrigeres, det er styrken i samarbeidet. Men en app som har synkronisert en feilaktig oppf\u00f8ring, kan beholde den i cache lenge etter korreksjonen p\u00e5 nett.<\/div><\/details>\n    <details><summary>Kan man gjenbruke tallene fra denne studien?<\/summary><div class=\"ans\">Ja, fritt, ved \u00e5 sitere \u00abLean-studie, august 2026\u00bb med en lenke til denne siden. Kildedataene tilh\u00f8rer OpenFoodFacts (ODbL-lisens) og metodikken v\u00e5r er beskrevet i sin helhet ovenfor.<\/div><\/details>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"src\" class=\"sources rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">Kilder<\/span><\/div>\n  <ol>\n    <li>OpenFoodFacts, offisiell dump fra 23. august 2026, <a href=\"https:\/\/world.openfoodfacts.org\/data\" target=\"_blank\" rel=\"noopener\">world.openfoodfacts.org\/data<\/a>, ODbL-lisens.<\/li>\n    <li>Forordning (EU) nr. 1169\/2011 (INCO), vedlegg XIV: energiomregningsfaktorer.<\/li>\n    <li>Atwater W.O. &amp; Bryant A.P. (1900). The availability and fuel value of food materials.<\/li>\n    <li>Merrill A.L. &amp; Watt B.K. (1973). Energy value of foods, USDA Agriculture Handbook No. 74.<\/li>\n  <\/ol>\n<\/section>\n\n<\/main>\n\n<footer>\n  <div class=\"wrap\">\n    <div class=\"row\">\n      <div>\n        <div class=\"kicker\">Lean &middot; lean-app.com<\/div>\n        <p>Studie publisert 24. august 2026. Oppdateres jevnlig med tilbakemeldinger fra brukere og nye relevante studier. Lean er tilgjengelig p\u00e5 iOS og Android.<\/p>\n      <\/div>\n      <div class=\"stores\">\n        <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=etude-off\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n        <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=etude-off\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n      <\/div>\n    <\/div>\n  <\/div>\n<\/footer>\n<script data-wpmeteor-nooptimize=\"true\">\n(function(){\n  var bar = document.getElementById('progBar');\n  function up(){\n    var h = document.documentElement;\n    var sc = (h.scrollTop)\/Math.max(1,(h.scrollHeight - h.clientHeight));\n    bar.style.transform = 'scaleX(' + Math.max(0,Math.min(1,sc)) + ')';\n  }\n  document.addEventListener('scroll', up, {passive:true});\n  up();\n})();\n\n(function(){\n  if (!('IntersectionObserver' in window)) {\n    document.querySelectorAll('.rev').forEach(function(n){n.classList.add('on')});\n    return;\n  }\n  var obs = new IntersectionObserver(function(entries){\n    entries.forEach(function(e){\n      if (e.isIntersecting) { e.target.classList.add('on'); obs.unobserve(e.target); }\n    });\n  }, {threshold:0.12});\n  document.querySelectorAll('.rev').forEach(function(n){ obs.observe(n); });\n})();\n<\/script>\n\n<script data-wpmeteor-nooptimize=\"true\">\n\/\/ === Charts etude OFF ===\n(function chartInit(){\n  if (typeof Chart === 'undefined') { return setTimeout(chartInit, 60); }\n  var LEAN_LANG = document.documentElement.lang || 'fr';\n  function T(fr, en){ return LEAN_LANG.indexOf('en') === 0 ? en : fr; }\n  var PINK = '#FF2D6E', INK = '#0E0E10', MUTED = '#6E6E73', RULE = '#E8E6DF';\n  var PINKS = ['rgba(255,45,110,1)','rgba(255,45,110,0.82)','rgba(255,45,110,0.66)','rgba(255,45,110,0.52)','rgba(255,45,110,0.4)','rgba(255,45,110,0.3)','rgba(255,45,110,0.24)','rgba(255,45,110,0.18)'];\n  Chart.defaults.font.family = '-apple-system, \"SF Pro Text\", system-ui, sans-serif';\n  var DPR = Math.max(2, window.devicePixelRatio || 2);\n  function nf(v){ return v.toLocaleString('fr-FR'); }\n  function pinkGrad(ctx, alphaTop){\n    var g = ctx.createLinearGradient(0, 0, 0, ctx.canvas.clientHeight || 360);\n    g.addColorStop(0, 'rgba(255,45,110,' + alphaTop + ')');\n    g.addColorStop(1, 'rgba(255,45,110,0.02)');\n    return g;\n  }\n\n  \/\/ 1. 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Ce que ton scanner de calories ne te dit pas. Chaque scan de code-barres en France interroge la m\u00eame base. Nous l&rsquo;avons analys\u00e9e en entier. Plus d&rsquo;un scan sur trois renvoie une donn\u00e9e absente, incompl\u00e8te ou incoh\u00e9rente. [&hellip;]<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-lvm-blank","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1947","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Vi analyserte 857 655 produkter solgt i Frankrike: det kaloriskanneren din ikke forteller deg - Lean<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/lean-app.com\/no\/etude-base-donnees-calories\/\" \/>\n<meta property=\"og:locale\" content=\"nb_NO\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Vi analyserte 857 655 produkter solgt i Frankrike: det kaloriskanneren din ikke forteller deg - Lean\" \/>\n<meta property=\"og:description\" content=\"Lean Calculateur TDEE Accueil &nbsp;\/&nbsp; \u00c9tude base de donn\u00e9es calories \u00c9tude originale &middot; Donn\u00e9es publiques 857&nbsp;655 produits analys\u00e9s. Ce que ton scanner de calories ne te dit pas. Chaque scan de code-barres en France interroge la m\u00eame base. Nous l&rsquo;avons analys\u00e9e en entier. Plus d&rsquo;un scan sur trois renvoie une donn\u00e9e absente, incompl\u00e8te ou incoh\u00e9rente. 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Ce que ton scanner de calories ne te dit pas. Chaque scan de code-barres en France interroge la m\u00eame base. Nous l&rsquo;avons analys\u00e9e en entier. Plus d&rsquo;un scan sur trois renvoie une donn\u00e9e absente, incompl\u00e8te ou incoh\u00e9rente. 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