{"id":1947,"date":"2026-08-23T20:43:53","date_gmt":"2026-08-23T20:43:53","guid":{"rendered":"https:\/\/lean-app.com\/?p=1947"},"modified":"2026-08-23T20:47:13","modified_gmt":"2026-08-23T20:47:13","slug":"etude-base-donnees-calories","status":"publish","type":"post","link":"https:\/\/lean-app.com\/es\/etude-base-donnees-calories\/","title":{"rendered":"Nous avons analys\u00e9 857 655 produits vendus en France : ce que ton scanner de calories ne te dit pas"},"content":{"rendered":"<script data-wpmeteor-nooptimize=\"true\" type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"Article\",\n  \"mainEntityOfPage\": {\"@type\": \"WebPage\", \"@id\": \"https:\/\/www.lean-app.com\/etude-base-donnees-calories\/\"},\n  \"headline\": \"Nous avons analys\u00e9 857 655 produits vendus en France : ce que ton scanner de calories ne te dit pas\",\n  \"description\": \"31 % de fiches incompl\u00e8tes, 46 757 produits aux calories incompatibles avec leurs propres macros : l'\u00e9tude compl\u00e8te de la base OpenFoodFacts utilis\u00e9e par les trackers.\",\n  \"image\": [\"https:\/\/www.lean-app.com\/etude-base-donnees-calories\/og\/og-image.png\"],\n  \"inLanguage\": \"fr-FR\",\n  \"datePublished\": \"2026-08-24T09:00:00+02:00\",\n  \"dateModified\": \"2026-08-24T09:00:00+02:00\",\n  \"author\": {\"@type\": \"Organization\", \"name\": \"L'\u00e9quipe Lean\", \"url\": \"https:\/\/www.lean-app.com\/\"},\n  \"publisher\": {\"@type\": \"Organization\", \"name\": \"Lean\", \"url\": \"https:\/\/www.lean-app.com\/\",\n    \"logo\": {\"@type\": \"ImageObject\", \"url\": \"https:\/\/www.lean-app.com\/etude-base-donnees-calories\/icons\/icon-512.png\", \"width\": 512, \"height\": 512}},\n  \"articleSection\": \"\u00c9tudes\",\n  \"keywords\": \"OpenFoodFacts fiabilit\u00e9, calories fausses, scan code-barres calories, base de donn\u00e9es nutritionnelle, \u00e9tude calories\"\n}\n<\/script>\n<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:\/\/www.lean-app.com\/etude-base-donnees-calories\/\",\n  \"creator\": {\"@type\": \"Organization\", \"name\": \"L'\u00e9quipe Lean\", \"url\": \"https:\/\/www.lean-app.com\/\"},\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\": \"BreadcrumbList\",\n  \"itemListElement\": [\n    {\"@type\": \"ListItem\", \"position\": 1, \"name\": \"Accueil\", \"item\": \"https:\/\/www.lean-app.com\/\"},\n    {\"@type\": \"ListItem\", \"position\": 2, \"name\": \"\u00c9tude base de donn\u00e9es calories\", \"item\": \"https:\/\/www.lean-app.com\/etude-base-donnees-calories\/\"}\n  ]\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. 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var(--rule);border-radius:16px;overflow:hidden;background:#fff}\n#lvm-shell .table-row{display:grid;grid-template-columns:1.55fr 1fr 1fr;border-bottom:1px solid var(--rule-soft);min-height:60px}\n#lvm-shell .table-row:last-child{border-bottom:0}\n#lvm-shell .table-row.head{background:var(--ink);color:#fff;border-bottom:0}\n#lvm-shell .table-row.head > div{padding:18px 18px;display:flex;align-items:center;gap:10px;font-family:var(--font-mono);font-size:11px;font-weight:500;text-transform:uppercase;letter-spacing:.07em}\n#lvm-shell .table-row.head .brand-cell{justify-content:flex-start}\n#lvm-shell .table-row.head .brand-cell img{width:24px;height:24px;border-radius:6px;background:#fff;object-fit:cover}\n#lvm-shell .table-row.head .brand-cell.lean{color:#FFB8CE}\n#lvm-shell .table-row > .crit{padding:16px 18px;font-size:14px;color:var(--ink);font-weight:500;display:flex;align-items:center;border-right:1px solid var(--rule-soft)}\n#lvm-shell .table-row > .cell{padding:16px 14px;font-size:13px;line-height:1.45;color:var(--ink-2);display:flex;align-items:center;gap:10px;border-right:1px solid var(--rule-soft)}\n#lvm-shell .table-row > .cell:last-child{border-right:0}\n#lvm-shell .table-row > .cell.lean{background:var(--pink-soft);position:relative}\n#lvm-shell .table-row > .cell.lean::before{content:\"\";position:absolute;left:0;top:0;bottom:0;width:2px;background:var(--pink)}\n#lvm-shell .icn{width:18px;height:18px;border-radius:50%;display:inline-flex;align-items:center;justify-content:center;flex-shrink:0;font-size:13px;font-weight:600;color:#fff}\n#lvm-shell .icn.ok{background:var(--green)}\n#lvm-shell .icn.no{background:var(--red)}\n#lvm-shell .icn.mid{background:var(--amber)}\n#lvm-shell .icn svg{width:11px;height:11px}\n\n#lvm-shell .mini-row{display:grid;grid-template-columns:repeat(3,1fr);gap:22px;margin:28px 0}\n#lvm-shell .mini-phone{position:relative;background:linear-gradient(145deg,#2a2a2a,#0e0e0e);border-radius:22px;padding:3px;border:1px solid rgba(255,255,255,.05);box-shadow:0 14px 32px rgba(0,0,0,.16);max-width:160px;margin:0 auto;width:100%}\n#lvm-shell .mini-phone .notch{position:absolute;top:0;left:50%;transform:translateX(-50%);width:40px;height:11px;background:#0a0a0a;border-radius:0 0 7px 7px;z-index:5}\n#lvm-shell .mini-phone .scr{border-radius:18px;overflow:hidden;background:#FAF0E6;aspect-ratio:9\/19.5}\n#lvm-shell .mini-phone .scr img{width:100%;height:100%;object-fit:cover}\n#lvm-shell .mini-phone.tiny{max-width:148px;padding:2px;border-radius:20px;border-width:1px}\n#lvm-shell .mini-phone.tiny .notch{width:30px;height:8px;border-radius:0 0 5px 5px}\n#lvm-shell .mini-phone.tiny .scr{border-radius:17px}\n#lvm-shell .mini-cap{text-align:center;margin-top:12px;font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.07em;color:var(--muted)}\n#lvm-shell .mini-cap 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 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main.wrap{display:block!important;max-width:760px!important;margin-left:auto!important;margin-right:auto!important;padding-left:28px!important;padding-right:28px!important}\n@media (max-width:820px){\n  body.postid-1947 #lvm-shell .wrap,\n  body.postid-1947 #lvm-shell main.wrap{padding-left:18px!important;padding-right:18px!important}\n}\nhtml, body{overflow-x:hidden!important}\nbody.postid-1947 #lvm-shell{overflow-x:hidden;max-width:100vw}\nbody.postid-1947 #lvm-shell *{max-width:100%}\nbody.postid-1947 #lvm-shell .nav-row{max-width:100vw;box-sizing:border-box}\nbody.postid-1947 #lvm-shell.force-show .rev{opacity:1!important;transform:none!important}\n@media (max-width:760px){\n  body.postid-1947 #lvm-shell .cta-band{flex-direction:column!important;align-items:center!important;text-align:center!important;padding:26px 22px!important;gap:20px!important}\n  body.postid-1947 #lvm-shell .cta-band .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\/es\/\" aria-label=\"Inicio 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\/es\/tdee-calculator\/\">Calculadora TDEE<\/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=\"Descargar en la 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 en 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\/es\/\">Inicio<\/a> &nbsp;\/&nbsp; \u00c9tude base de donn\u00e9es calories<\/div>\n  <div class=\"eyebrow\">\u00c9tude originale &middot; Donn\u00e9es publiques<\/div>\n  <h1 id=\"title\">857&nbsp;655 produits analys\u00e9s.\n    <span class=\"alt\">Ce que ton scanner de calories ne te dit pas.<\/span>\n  <\/h1>\n  <p class=\"dek\">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.<\/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>Par <strong>El equipo Lean<\/strong> &middot; publi\u00e9 le 24 ao\u00fbt 2026 &middot; lecture 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=\"Descargar Lean en la 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=\"Descargar Lean en 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\">Pourquoi cette \u00e9tude<\/h2>\n  <p>Quand tu scannes un code-barres dans un tracker de calories en France, MyFitnessPal, Yazio, Lifesum ou Lean, la donn\u00e9e vient peu ou prou de la m\u00eame source : <a href=\"https:\/\/world.openfoodfacts.org\/\" target=\"_blank\" rel=\"noopener\">OpenFoodFacts<\/a>, formidable base collaborative fran\u00e7aise en licence ouverte ODbL. Des millions de fiches produits, remplies par des contributeurs b\u00e9n\u00e9voles.<\/p>\n  <p>Une base collaborative, c&rsquo;est sa force et sa limite : n&rsquo;importe qui peut cr\u00e9er ou modifier une fiche, et personne ne v\u00e9rifie syst\u00e9matiquement. Personne n&rsquo;avait chiffr\u00e9 la fiabilit\u00e9 r\u00e9elle de ce que ton scan renvoie. Nous avons donc t\u00e9l\u00e9charg\u00e9 le dump public complet du 23 ao\u00fbt 2026 et test\u00e9 chaque produit vendu en France.<\/p>\n  <div class=\"stat-grid\">\n    <div class=\"stat-card\"><div class=\"n\">4 535 553<\/div><div class=\"t\">produits dans la base mondiale au 23 ao\u00fbt 2026<\/div><\/div>\n    <div class=\"stat-card\"><div class=\"n\">1 265 726<\/div><div class=\"t\">produits r\u00e9f\u00e9renc\u00e9s comme vendus en France<\/div><\/div>\n    <div class=\"stat-card\"><div class=\"n pink\">857 655<\/div><div class=\"t\">produits analysables : calories et les 3 macros renseign\u00e9es<\/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\">La m\u00e9thode : chaque fiche test\u00e9e contre elle-m\u00eame<\/h2>\n  <p>Pas besoin de labo pour d\u00e9tecter une fiche fausse : il suffit de la confronter \u00e0 elle-m\u00eame. Les calories d&rsquo;un aliment se d\u00e9duisent de ses macronutriments avec les facteurs d&rsquo;Atwater, ceux-l\u00e0 m\u00eames que le r\u00e8glement europ\u00e9en INCO impose aux industriels : 4&nbsp;kcal par gramme de prot\u00e9ines, 4 par gramme de glucides, 9 par gramme de lipides.<\/p>\n  <p>Si une fiche affiche 100&nbsp;kcal mais que ses propres macros en donnent 250, l&rsquo;une des deux lignes est fausse. Et ton app t&rsquo;affiche l&rsquo;une des deux sans sourciller.<\/p>\n  <div class=\"metho\">\n    <h3>M\u00e9thodologie compl\u00e8te<\/h3>\n    <ul>\n      <li>Dump officiel OpenFoodFacts du 23 ao\u00fbt 2026 (licence ODbL), p\u00e9rim\u00e8tre France<\/li>\n      <li>Recalcul : <code>4&times;prot\u00e9ines + 4&times;glucides + 9&times;lipides<\/code>, plus 7&nbsp;kcal\/g d&rsquo;alcool, 2&nbsp;kcal\/g de fibres et 2,4&nbsp;kcal\/g de polyols (\u00e9rythritol : 0), conform\u00e9ment au r\u00e8glement INCO 1169\/2011<\/li>\n      <li>Fiche compt\u00e9e incoh\u00e9rente seulement si l&rsquo;\u00e9cart d\u00e9passe \u00e0 la fois 10&nbsp;% et 30&nbsp;kcal\/100g : le bruit des eaux et th\u00e9s \u00e0 2&nbsp;kcal est exclu<\/li>\n      <li>16 364 fiches aberrantes \u00e9cart\u00e9es (calories hors 1-950&nbsp;kcal\/100g, macros impossibles)<\/li>\n      <li>Chaque exemple cit\u00e9 dans cette page a \u00e9t\u00e9 rev\u00e9rifi\u00e9 sur la fiche en ligne le jour de la publication<\/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\">R\u00e9sultat 1 : presque 1 fiche sur 3 est incompl\u00e8te<\/h2>\n  <div class=\"bignum\">31 %<small>des produits FR sans donn\u00e9es compl\u00e8tes<\/small><\/div>\n  <p>391 707 produits vendus en France n&rsquo;ont pas de calories renseign\u00e9es, ou pas leurs trois macronutriments. Concr\u00e8tement : tu scannes, et l&rsquo;app affiche 0&nbsp;kcal, ou des calories sans prot\u00e9ines ni glucides. Tu as l&rsquo;impression de tracker, tu logges du vide.<\/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>Le sort d&rsquo;un scan en France, sur 1 265 726 produits.<\/figcaption>\n  <\/figure>\n  <p>C&rsquo;est l&rsquo;erreur la plus sournoise, parce qu&rsquo;elle ne ressemble pas \u00e0 une erreur : la fiche s&rsquo;affiche, le produit a un nom, une photo. Il manque juste l&rsquo;essentiel.<\/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\">R\u00e9sultat 2 : 46 757 produits aux calories incoh\u00e9rentes<\/h2>\n  <p>Sur les 857 655 fiches compl\u00e8tes, 46 757 affichent des calories incompatibles avec leurs propres macros, d&rsquo;au moins 10&nbsp;% et 30&nbsp;kcal aux 100&nbsp;g. Chaque point du graphe ci-dessous est un vrai produit : en abscisse ce que sa fiche d\u00e9clare, en ordonn\u00e9e ce que ses macros donnent. Une fiche honn\u00eate tombe sur la diagonale.<\/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 produits r\u00e9els : d\u00e9clar\u00e9 vs recalcul\u00e9 depuis les macros.<\/figcaption>\n  <\/figure>\n  <p>La distribution des \u00e9carts montre que la base est massivement correcte, puis part en longue tra\u00eene : les fiches fausses ne sont pas l\u00e9g\u00e8rement fausses, elles sont tr\u00e8s fausses.<\/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>Distribution des \u00e9carts, \u00e9chelle logarithmique.<\/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=\"Produits incoh\u00e9rents par seuil d'\u00e9cart\" role=\"img\"><\/canvas><\/div>\n    <figcaption>Produits incoh\u00e9rents par seuil d&rsquo;\u00e9cart, base 857 655 fiches.<\/figcaption>\n  <\/figure>\n  <p>18 251 produits, soit deux incoh\u00e9rents mat\u00e9riels sur cinq, se trompent <em>du simple au double ou plus<\/em>. \u00c0 ce niveau, ce n&rsquo;est plus une impr\u00e9cision, c&rsquo;est une donn\u00e9e qui inverse ton bilan calorique du jour.<\/p>\n  <p>En cumulant fiches incompl\u00e8tes et fiches incoh\u00e9rentes : <strong>plus d&rsquo;un scan sur trois en France renvoie une donn\u00e9e absente, incompl\u00e8te ou incoh\u00e9rente<\/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\">Des produits que tu as dans ton placard<\/h2>\n  <p>Chaque fiche ci-dessous a \u00e9t\u00e9 rev\u00e9rifi\u00e9e en ligne le jour de la publication. \u00c0 gauche ce que la fiche OpenFoodFacts affiche, \u00e0 droite ce que ses propres macros donnent :<\/p>\n  <div class=\"prod-cards\">\n    <div class=\"prod-card\"><div class=\"who\"><b>Le Beurre Tendre<\/b><span>fiche du produit Elle&amp;Vire &middot; 535 scans<\/span><\/div><div class=\"vals\"><span><span class=\"fiche\">375<\/span><span class=\"unit\">fiche<\/span><\/span><span class=\"fleche\">&rarr;<\/span><span><span class=\"reel\">744<\/span><span class=\"unit\">macros<\/span><\/span><\/div><\/div>\n    <div class=\"prod-card\"><div class=\"who\"><b>Yaos Yaourt \u00e0 la Grecque<\/b><span>fiche du produit Nestl\u00e9 &middot; 271 scans<\/span><\/div><div class=\"vals\"><span><span class=\"fiche\">50<\/span><span class=\"unit\">fiche<\/span><\/span><span class=\"fleche\">&rarr;<\/span><span><span class=\"reel\">98<\/span><span class=\"unit\">macros<\/span><\/span><\/div><\/div>\n    <div class=\"prod-card\"><div class=\"who\"><b>Sweet &amp; Salty Nut chocolat<\/b><span>fiche du produit Nature Valley &middot; 338 scans<\/span><\/div><div class=\"vals\"><span><span class=\"fiche\">647<\/span><span class=\"unit\">fiche<\/span><\/span><span class=\"fleche\">&rarr;<\/span><span><span class=\"reel\">140<\/span><span class=\"unit\">macros<\/span><\/span><\/div><\/div>\n    <div class=\"prod-card\"><div class=\"who\"><b>Ratatouille \u00e0 la Proven\u00e7ale<\/b><span>fiche du produit Cassegrain &middot; 298 scans<\/span><\/div><div class=\"vals\"><span><span class=\"fiche\">38<\/span><span class=\"unit\">fiche<\/span><\/span><span class=\"fleche\">&rarr;<\/span><span><span class=\"reel\">72<\/span><span class=\"unit\">macros<\/span><\/span><\/div><\/div>\n  <\/div>\n  <p>Le cas d&rsquo;\u00e9cole : les lentilles cuisin\u00e9es \u00e0 l&rsquo;Auvergnate de Raynal &amp; Roquelaure existent sous <strong>deux fiches diff\u00e9rentes<\/strong>. L&rsquo;une affiche 48&nbsp;kcal\/100g, l&rsquo;autre 207. La vraie valeur est autour de 99. Selon le code-barres que ton app attrape, tu crois manger deux fois moins ou deux fois plus que la r\u00e9alit\u00e9.<\/p>\n  <p>Un utilisateur qui tartine 30&nbsp;g du beurre ci-dessus sous-compte 110&nbsp;kcal. Tous les jours. En croyant bien faire.<\/p>\n  <div class=\"cta-band rev\">\n    <div class=\"l\">Lean v\u00e9rifie la coh\u00e9rence des fiches et scanne aussi ton assiette en photo, sans d\u00e9pendre d&rsquo;un code-barres.<\/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\">Les cat\u00e9gories les plus touch\u00e9es<\/h2>\n  <p>L&rsquo;incoh\u00e9rence n&rsquo;est pas r\u00e9partie au hasard, et l&rsquo;ironie du classement est cruelle : la cat\u00e9gorie la plus touch\u00e9e de toute la base est celle que les sportifs trackent le plus. <strong>Plus d&rsquo;une barre prot\u00e9in\u00e9e sur cinq (20,8&nbsp;%) a une fiche incoh\u00e9rente.<\/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>Chaque bulle est une cat\u00e9gorie ; sa taille, ses fiches incoh\u00e9rentes.<\/figcaption>\n  <\/figure>\n  <p>Les recettes complexes et les produits enrichis concentrent les erreurs : barres prot\u00e9in\u00e9es, confiseries, bonbons, fromages. Les produits simples s&rsquo;en sortent mieux.<\/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>Part de fiches incoh\u00e9rentes par cat\u00e9gorie (min. 1 000 produits).<\/figcaption>\n  <\/figure>\n  <p>Une note d&rsquo;honn\u00eatet\u00e9 : bonbons, confiseries et barres s&rsquo;expliquent en partie par les \u00e9dulcorants. Quand une fiche ne d\u00e9clare pas ses polyols, le recalcul surestime l&rsquo;\u00e9cart. Nous avons corrig\u00e9 tout ce qui \u00e9tait d\u00e9clar\u00e9 ; le r\u00e9sidu refl\u00e8te aussi ce trou de d\u00e9claration, qui trompe ton app exactement de la m\u00eame mani\u00e8re.<\/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\">Ce que \u00e7a change pour ton tracking<\/h2>\n  <p>D&rsquo;abord, ce que \u00e7a ne veut pas dire : il ne faut pas arr\u00eater de scanner, et OpenFoodFacts reste un projet remarquable qui vit et se corrige en continu. La courbe ci-dessous le montre : les fiches cr\u00e9\u00e9es en 2020-2021 sont les moins fiables (jusqu&rsquo;\u00e0 7,5&nbsp;% d&rsquo;incoh\u00e9rence), et la qualit\u00e9 s&rsquo;est nettement redress\u00e9e depuis 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>Taux d&rsquo;incoh\u00e9rence selon l&rsquo;ann\u00e9e de cr\u00e9ation de la fiche.<\/figcaption>\n  <\/figure>\n  <p>Quatre des six pires fiches du dump avaient d\u00e9j\u00e0 \u00e9t\u00e9 corrig\u00e9es en ligne au moment de notre v\u00e9rification. Mais ton app, elle, a peut-\u00eatre synchronis\u00e9 la version fausse, et les centaines de milliers de fiches cr\u00e9\u00e9es aux pires ann\u00e9es sont toujours dans la base.<\/p>\n  <p>Deux r\u00e9flexes \u00e0 retenir :<\/p>\n  <p><strong>1. Le scan est un outil de vitesse, pas de v\u00e9rit\u00e9.<\/strong> Apr\u00e8s un scan, un coup d&rsquo;oeil aux macros suffit : si prot\u00e9ines, glucides et lipides ne collent pas aux calories affich\u00e9es, la fiche est fausse. C&rsquo;est exactement le test de cette \u00e9tude, et il prend deux secondes.<\/p>\n  <p><strong>2. L&rsquo;erreur invisible n&rsquo;est pas dans ton assiette, elle est dans ta d\u00e9pense.<\/strong> Une fiche fausse de 110&nbsp;kcal se corrige en dix secondes une fois rep\u00e9r\u00e9e. Une d\u00e9pense calorique fausse de 300&nbsp;kcal par jour ne se voit jamais : elle est enfouie dans le \u00ab\u00a0multiplicateur d&rsquo;activit\u00e9\u00a0\u00bb que ton app t&rsquo;a fait choisir \u00e0 l&rsquo;inscription. C&rsquo;est l\u00e0 que Lean concentre sa pr\u00e9cision : <a href=\"https:\/\/lean-app.com\/es\/depense-energetique-journaliere-tdee\/\">TDEE = BMR + NEAT + EAT + TEF<\/a>, avec un BMR calcul\u00e9 sur ton <a href=\"https:\/\/lean-app.com\/es\/masse-grasse-bodyscan\/\">bodyfat r\u00e9el<\/a> et un <a href=\"https:\/\/lean-app.com\/es\/calculateur-neat\/\">NEAT sur tes pas r\u00e9els<\/a>, pas sur une case coch\u00e9e.<\/p>\n  <div class=\"cta-band rev\">\n    <div class=\"l\">Devenez Lean, restez-le : la seule app qui calcule ta d\u00e9pense sur des mesures, pas sur des cases.<\/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=\"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>Pourquoi OpenFoodFacts et pas USDA ?<\/summary><div class=\"ans\">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. Cette \u00e9tude porte sur ce que renvoie r\u00e9ellement un scan en France.<\/div><\/details>\n    <details><summary>Faut-il arr\u00eater de scanner ses aliments ?<\/summary><div class=\"ans\">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. Deux secondes qui \u00e9vitent les pires fiches.<\/div><\/details>\n    <details><summary>Les applications corrigent-elles ces erreurs ?<\/summary><div class=\"ans\">La base vit en continu et se corrige, c&rsquo;est la force du collaboratif. Mais une app qui a synchronis\u00e9 une fiche fausse peut la garder en cache longtemps apr\u00e8s la correction en ligne.<\/div><\/details>\n    <details><summary>Peut-on r\u00e9utiliser les chiffres de cette \u00e9tude ?<\/summary><div class=\"ans\">Oui, librement, en citant \u00ab\u00a0\u00c9tude Lean, ao\u00fbt 2026\u00a0\u00bb avec un lien vers cette page. Les donn\u00e9es sources appartiennent \u00e0 OpenFoodFacts (licence ODbL) et notre m\u00e9thodologie est d\u00e9crite int\u00e9gralement ci-dessus.<\/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\">Fuentes<\/span><\/div>\n  <ol>\n    <li>OpenFoodFacts, dump officiel du 23 ao\u00fbt 2026, <a href=\"https:\/\/world.openfoodfacts.org\/data\" target=\"_blank\" rel=\"noopener\">world.openfoodfacts.org\/data<\/a>, licence ODbL.<\/li>\n    <li>R\u00e8glement (UE) n\u00b01169\/2011 (INCO), annexe XIV : facteurs de conversion \u00e9nerg\u00e9tique.<\/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>\u00c9tude publi\u00e9e le 24 ao\u00fbt 2026. Mis \u00e0 jour r\u00e9guli\u00e8rement avec les retours d&rsquo;utilisateurs et les nouvelles \u00e9tudes pertinentes. Lean est disponible sur iOS et 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>Nous avons analys\u00e9 857 655 produits vendus en France : ce que ton scanner de calories ne te dit pas - 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\/es\/etude-base-donnees-calories\/\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Nous avons analys\u00e9 857 655 produits vendus en France : ce que ton scanner de calories ne te dit pas - 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. 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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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