{"id":1760,"date":"2026-08-15T22:24:56","date_gmt":"2026-08-15T22:24:56","guid":{"rendered":"https:\/\/lean-app.com\/lean-vs-foodvisor\/"},"modified":"2026-09-08T18:18:33","modified_gmt":"2026-09-08T18:18:33","slug":"lean-vs-foodvisor","status":"publish","type":"post","link":"https:\/\/lean-app.com\/da\/lean-vs-foodvisor\/","title":{"rendered":"Lean vs Foodvisor: AI-fotoscanning over for dit reelle forbrug"},"content":{"rendered":"<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp\" 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.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}<\/style>\n\n<style id=\"lvm-collision-reset\">\n\/* Hard reset for global theme styles that collide with our content *\/\nbody.postid-1760 #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-1760 #lvm-shell .wrap,\nbody.postid-1760 #lvm-shell 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-1760 #lvm-shell .wrap,\n  body.postid-1760 #lvm-shell main.wrap{padding-left:18px!important;padding-right:18px!important}\n}\nhtml, body{overflow-x:hidden!important}\nbody.postid-1760 #lvm-shell{overflow-x:hidden;max-width:100vw}\nbody.postid-1760 #lvm-shell *{max-width:100%}\nbody.postid-1760 #lvm-shell .nav-row{max-width:100vw;box-sizing:border-box}\nbody.postid-1760 #lvm-shell.force-show .rev{opacity:1!important;transform:none!important}\n\n\/* === A.1 PHONE BACKGROUND CLASSES === *\/\nbody.postid-1760 #lvm-shell .phone-bg{position:absolute;inset:0;width:100%;height:100%;background-size:cover;background-position:center top;background-repeat:no-repeat;transition:opacity .28s ease;background-color:#FAF0E6}\nbody.postid-1760 #lvm-shell .phone-bg.tab-depense{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp)}\nbody.postid-1760 #lvm-shell .phone-bg.tab-bilan{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp)}\nbody.postid-1760 #lvm-shell .phone-bg.tab-kcal{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp)}\nbody.postid-1760 #lvm-shell .phone-bg.tab-strategie{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp)}\nbody.postid-1760 #lvm-shell .phone-bg.sub-BMR{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp)}\nbody.postid-1760 #lvm-shell .phone-bg.sub-NEAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp)}\nbody.postid-1760 #lvm-shell .phone-bg.sub-EAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp)}\nbody.postid-1760 #lvm-shell .phone-bg.sub-TEF{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp)}\n\n\/* === v11.3 CTA BANDS MOBILE === *\/\n@media (max-width:760px){\n  body.postid-1760 #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-1760 #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-1760 #lvm-shell .cta-band .stores{width:100%!important;justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1760 #lvm-shell .cta-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1760 #lvm-shell .cta-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1760 #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  body.postid-1760 #lvm-shell .get-band{padding:38px 22px!important}\n  body.postid-1760 #lvm-shell .get-band .stores{justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1760 #lvm-shell .get-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1760 #lvm-shell .get-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1760 #lvm-shell .get-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  body.postid-1760 #lvm-shell .get-band h3{font-size:26px!important;line-height:1.2!important}\n  body.postid-1760 #lvm-shell .get-band p{font-size:15px!important}\n}\n\n\/* === v11.2 BRAND BANNER above table responsive === *\/\n@media (max-width:760px){\n  body.postid-1760 #lvm-shell .brand-banner img{width:54px!important;height:54px!important}\n  body.postid-1760 #lvm-shell .brand-banner > div{padding:16px 12px!important;gap:8px!important}\n  body.postid-1760 #lvm-shell .brand-banner > div > div{font-size:15px!important}\n}\n\n\/* === v11.4 SCORECARD partie 7 : redesign mobile === *\/\n@media (max-width:760px){\n  body.postid-1760 #lvm-shell .scorecard{padding:18px 16px!important;border-radius:16px!important}\n  body.postid-1760 #lvm-shell .scorecard-head{display:none!important}\n  body.postid-1760 #lvm-shell .scorecard-row{\n    display:block!important;\n    padding:14px 0!important;\n    border-bottom:1px solid #E8E2D6!important;\n  }\n  body.postid-1760 #lvm-shell .scorecard-row .crit{\n    display:block!important;\n    font-size:13px!important;\n    font-weight:600!important;\n    color:#0E0E10!important;\n    margin-bottom:10px!important;\n    padding-right:0!important;\n  }\n  body.postid-1760 #lvm-shell .scorecard-row .bar{\n    display:grid!important;\n    grid-template-columns:54px 1fr 32px!important;\n    column-gap:8px!important;\n    align-items:center!important;\n    padding:5px 0!important;\n    flex-direction:initial!important;\n    position:relative!important;\n  }\n  body.postid-1760 #lvm-shell .scorecard-row .bar::before{\n    content:attr(data-brand)!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:11px!important;\n    font-weight:600!important;\n    text-transform:uppercase!important;\n    letter-spacing:.05em!important;\n    color:#0E0E10!important;\n  }\n  body.postid-1760 #lvm-shell .scorecard-row .bar.lean::before{color:#FF2D6E!important}\n  body.postid-1760 #lvm-shell .scorecard-row .bar.mfp::before{color:#6ABF6C!important}\n  body.postid-1760 #lvm-shell .scorecard-row .bar .b{\n    height:10px!important;\n    width:100%!important;\n    border-radius:99px!important;\n    position:relative!important;\n    background:#EFEAE0!important;\n    overflow:hidden!important;\n  }\n  body.postid-1760 #lvm-shell .scorecard-row .bar .b > i{\n    display:block!important;\n    height:100%!important;\n    border-radius:99px!important;\n  }\n  body.postid-1760 #lvm-shell .scorecard-row .bar .v{\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:12px!important;\n    font-weight:700!important;\n    color:#0E0E10!important;\n    min-width:0!important;\n    text-align:right!important;\n  }\n}\n\n\/* === A.2 CHARTS MOBILE === *\/\n@media (max-width:760px){\n  body.postid-1760 #lvm-shell .cv-wrap{height:380px!important;min-height:360px!important;max-height:420px!important;width:100%!important}\n  body.postid-1760 #lvm-shell .cv-wrap canvas{width:100%!important;height:100%!important;display:block!important}\n  body.postid-1760 #lvm-shell .fig{padding:16px 4px 14px!important;margin:24px -4px 14px!important;overflow:visible!important}\n  body.postid-1760 #lvm-shell .fig-head{padding:0 12px!important;flex-wrap:wrap!important;gap:6px!important;margin-bottom:10px!important}\n  body.postid-1760 #lvm-shell .fig-body{padding:0 2px!important}\n  body.postid-1760 #lvm-shell .fig-cap{padding:0 12px!important;font-size:13px!important;margin-top:10px!important}\n}\n@media (max-width:480px){\n  body.postid-1760 #lvm-shell .cv-wrap{height:360px!important;min-height:340px!important;max-height:380px!important}\n  body.postid-1760 #lvm-shell .fig{padding:14px 2px 12px!important;margin:20px -6px 12px!important;border-radius:14px!important}\n  body.postid-1760 #lvm-shell .fig-body{padding:0!important}\n}\n\n\/* === v11.2 TABLEAU MOBILE STACKED CARDS avec mini-tags Lean\/Foodvisor === *\/\n@media (max-width:760px){\n  body.postid-1760 #lvm-shell .table{border-radius:14px!important}\n  body.postid-1760 #lvm-shell .table-row.head{display:none!important}\n  body.postid-1760 #lvm-shell .table-row{\n    display:grid!important;\n    grid-template-columns:1fr 1fr!important;\n    grid-template-areas:\"crit crit\" \"lean mfp\"!important;\n    gap:0!important;\n    min-height:0!important;\n  }\n  body.postid-1760 #lvm-shell .table-row > .crit{\n    grid-area:crit!important;background:#0E0E10!important;color:#fff!important;\n    padding:11px 14px!important;font-size:13px!important;font-weight:600!important;\n    letter-spacing:-0.1px!important;border-right:0!important;line-height:1.35!important;\n    font-family:-apple-system,BlinkMacSystemFont,'SF Pro Display',sans-serif!important;text-transform:none!important;\n  }\n  body.postid-1760 #lvm-shell .table-row > .cell.lean{\n    grid-area:lean!important;border-right:1px solid #E8E2D6!important;\n    position:relative!important;background:#FFF1F5!important;padding-top:30px!important;\n  }\n  body.postid-1760 #lvm-shell .table-row > .cell:not(.lean):not(.crit){\n    grid-area:mfp!important;background:#EFF7EF!important;padding-top:30px!important;\n    position:relative!important;\n  }\n  body.postid-1760 #lvm-shell .table-row > .cell.lean::before{\n    content:\"LEAN\"!important;position:absolute!important;top:8px!important;left:12px!important;\n    right:auto!important;bottom:auto!important;width:auto!important;height:auto!important;\n    background:transparent!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:10px!important;font-weight:700!important;letter-spacing:.07em!important;\n    color:#FF2D6E!important;\n  }\n  body.postid-1760 #lvm-shell .table-row > .cell:not(.lean):not(.crit)::before{\n    content:\"FOODVISOR\"!important;position:absolute!important;top:8px!important;left:12px!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:10px!important;font-weight:700!important;letter-spacing:.07em!important;\n    color:#6ABF6C!important;\n  }\n  body.postid-1760 #lvm-shell .table-row > .cell{\n    padding:12px 12px!important;font-size:13px!important;line-height:1.4!important;\n    align-items:flex-start!important;gap:7px!important;\n  }\n  body.postid-1760 #lvm-shell .icn{flex-shrink:0!important;margin-top:1px!important}\n}\n\n\/* === A.5 MINI-LOGOS triplet NEAT\/EAT\/TEF === *\/\n@media (max-width:760px){\n  body.postid-1760 #lvm-shell .mini-row{gap:6px!important;margin:24px 0!important;grid-template-columns:repeat(3,1fr)!important}\n  body.postid-1760 #lvm-shell .mini-phone{max-width:100px!important;padding:2px!important;border-radius:14px!important;border-width:1px!important}\n  body.postid-1760 #lvm-shell .mini-phone.tiny{max-width:96px!important;padding:2px!important;border-radius:13px!important}\n  body.postid-1760 #lvm-shell .mini-phone .notch{width:30px!important;height:8px!important;border-radius:0 0 5px 5px!important}\n  body.postid-1760 #lvm-shell .mini-phone .scr{border-radius:11px!important}\n  body.postid-1760 #lvm-shell .mini-cap{font-size:10px!important;margin-top:8px!important}\n  body.postid-1760 #lvm-shell .mini-cap strong{font-size:12px!important;margin-top:2px!important}\n}\n\n\/* === MOCKUP TAP HINT MOBILE === *\/\n@media (max-width:760px){\n  body.postid-1760 #lvm-shell .tap-hint.mobile{position:relative!important;width:100%!important;left:auto!important;top:auto!important;text-align:center!important;margin:0 auto 14px!important;display:block!important}\n  body.postid-1760 #lvm-shell .tap-hint.desktop{display:none!important}\n  body.postid-1760 #lvm-shell .tap-hint.hidden{display:none!important;height:0!important;margin:0!important;padding:0!important}\n}\n\n\/* === A.6 BODYSCAN ILLUST partie BMR === *\/\nbody.postid-1760 #lvm-shell .bodyscan-illust{margin:40px auto 8px!important;display:flex!important;flex-direction:column!important;align-items:center!important;gap:14px!important;max-width:220px!important}\nbody.postid-1760 #lvm-shell .bodyscan-illust .mini-phone{max-width:200px!important;padding:3px!important;border-radius:22px!important;border-width:1px!important}\nbody.postid-1760 #lvm-shell .bodyscan-illust .mini-phone .notch{width:40px!important;height:11px!important;border-radius:0 0 7px 7px!important}\nbody.postid-1760 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:18px!important}\n@media (max-width:760px){\n  body.postid-1760 #lvm-shell .bodyscan-illust{max-width:180px!important}\n  body.postid-1760 #lvm-shell .bodyscan-illust .mini-phone{max-width:160px!important;padding:3px!important;border-radius:20px!important}\n  body.postid-1760 #lvm-shell .bodyscan-illust .mini-phone .notch{width:34px!important;height:9px!important;border-radius:0 0 6px 6px!important}\n  body.postid-1760 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:16px!important}\n}\n<\/style>\n<script data-wpmeteor-nooptimize=\"true\">\n(function(){\n  \/* Hard fallback: force .rev visible after 2s if IntersectionObserver doesn't fire *\/\n  setTimeout(function(){\n    var shell = document.getElementById('lvm-shell');\n    if(!shell) return;\n    var anyOn = shell.querySelector('.rev.on');\n    if(!anyOn){ shell.classList.add('force-show'); }\n  }, 2000);\n\n  \/* ResizeObserver fallback: ensure charts resize correctly *\/\n  if (typeof ResizeObserver !== 'undefined'){\n    var observer = new ResizeObserver(function(entries){\n      entries.forEach(function(entry){\n        var canvas = entry.target.querySelector('canvas');\n        if (!canvas || !window.Chart) return;\n        var inst = window.Chart.getChart(canvas);\n        if (inst) { try { inst.resize(); } catch(e){} }\n      });\n    });\n    document.querySelectorAll('#lvm-shell .cv-wrap').forEach(function(w){ observer.observe(w); });\n  }\n})();\n<\/script>\n<div id=\"lvm-shell\"><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\/da\/\" aria-label=\"Lean forside\">\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\/da\/tdee-calculator\/\">TDEE-beregner<\/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=vs-foodvisor\" target=\"_blank\" rel=\"noopener\" aria-label=\"Download i 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\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/>\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=vs-foodvisor\" target=\"_blank\" rel=\"noopener\" aria-label=\"Tilg\u00e6ngelig p\u00e5 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\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/>\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\/da\/\">Hjem<\/a> &nbsp;\/&nbsp; Lean vs Foodvisor<\/div>\n  <div class=\"eyebrow\">Sammenligning &middot; Ern\u00e6ring &amp; TDEE<\/div>\n  <h1 id=\"title\">Lean vs Foodvisor.\n    <span class=\"alt\">Fotoscanningens pioner over for den eneste, der l\u00f8bende genopbygger din TDEE.<\/span>\n  <\/h1>\n  <p class=\"dek\">Foodvisor ser din tallerken. Lean ser dit reelle forbrug. To AI'er, to halvdele af problemet.<\/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=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/>\n    <span><strong>Lean-teamet<\/strong> &middot; L\u00e6setid 12&nbsp;min &middot; Opdateret 15. august 2026<\/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=vs-foodvisor\" target=\"_blank\" rel=\"noopener\">\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=vs-foodvisor\" target=\"_blank\" rel=\"noopener\">\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    <span class=\"or\">Gratis download<\/span>\n  <\/div>\n\n  <div class=\"hero-bottom\">\n    <div class=\"hero-lead\">\n      Foodvisor er den franske pioner inden for fotoscanning af m\u00e5ltider: du fotograferer din tallerken, AI'en genkender f\u00f8devarerne og estimerer portionerne. P\u00e5 den halvdel af problemet er \u00e6ren fortjent. Men den anden halvdel, dit forbrug, er stadig en populationsformel (Mifflin-St Jeor 1990), plus en statisk aktivitetsmultiplikator valgt \u00e9n enkelt gang ved tilmeldingen. Uden reel m\u00e5lt fedtprocent, uden metabolisk tilpasning. Kampen Lean vs Foodvisor afg\u00f8res alts\u00e5 ikke p\u00e5 fotoet: den afg\u00f8res p\u00e5 det, appen g\u00f8r med tallet, over 3 m\u00e5neders seri\u00f8st cut.\n    <\/div>\n    <div class=\"phone-wrap rev\">\n      <div class=\"phone-stage\">\n        <div class=\"tap-hint mobile\" id=\"tapHintMobile\" aria-hidden=\"true\">\n          <span class=\"th-pill\"><small>Interaktiv demo<\/small>Tryk p\u00e5 sk\u00e6rmen for at udforske appen<\/span>\n          <svg class=\"th-arrow\" viewbox=\"0 0 24 24\" fill=\"none\" aria-hidden=\"true\">\n            <path d=\"M12 4 L12 20 M5 13 L12 20 L19 13\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/>\n          <\/svg>\n        <\/div>\n        <div class=\"tap-hint desktop\" id=\"tapHintDesktop\" aria-hidden=\"true\">\n          <span class=\"th-pill\"><small>Interaktiv demo<\/small>Tryk p\u00e5 sk\u00e6rmen<br>for at udforske appen<\/span>\n          <svg class=\"th-arrow\" viewbox=\"0 0 104 34\" fill=\"none\" aria-hidden=\"true\">\n            <path d=\"M4 9 C 34 1, 64 20, 94 27\" stroke=\"currentColor\" stroke-width=\"2.6\" fill=\"none\" stroke-linecap=\"round\"\/>\n            <path d=\"M86 20 L 94 27 L 84 30\" stroke=\"currentColor\" stroke-width=\"2.6\" fill=\"none\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/>\n          <\/svg>\n        <\/div>\n        <div class=\"phone\" id=\"phone\" role=\"img\" aria-label=\"Oversigt over Lean-appen med drilldown af TDEE\">\n          <div class=\"notch\"><\/div>\n          <div class=\"phone-screen\">\n            <button class=\"phone-back\" id=\"phoneBack\" aria-label=\"Tilbage\">&#8249;<\/button>\n            <div id=\"phoneImg\" class=\"phone-bg tab-depense\" role=\"img\" aria-label=\"Lean-oversigt, Forbrug-fanen\"><\/div>\n            <div class=\"phone-zones\" id=\"phoneZones\">\n              <div class=\"z\" data-sub=\"BMR\"  style=\"top:11%;height:21%\" role=\"button\" tabindex=\"0\" aria-label=\"BMR-detaljer\"><\/div>\n              <div class=\"z\" data-sub=\"NEAT\" style=\"top:33%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"NEAT-detaljer\"><\/div>\n              <div class=\"z\" data-sub=\"EAT\"  style=\"top:50%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"EAT-detaljer\"><\/div>\n              <div class=\"z\" data-sub=\"TEF\"  style=\"top:67%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"TEF-detaljer\"><\/div>\n            <\/div>\n            <div class=\"phone-navbar\" id=\"phoneNav\" aria-hidden=\"false\">\n              <button data-tab=\"bilan\"     type=\"button\" aria-label=\"Oversigt-fanen\"><\/button>\n              <button data-tab=\"kcal\"      type=\"button\" aria-label=\"Kalorier-fanen\"><\/button>\n              <button data-tab=\"depense\"   type=\"button\" aria-label=\"Forbrug-fanen\"><\/button>\n              <button data-tab=\"strategie\" type=\"button\" aria-label=\"Strategi-fanen\"><\/button>\n            <\/div>\n          <\/div>\n        <\/div>\n        <div class=\"phone-tabs\" role=\"tablist\" aria-label=\"Naviger i Lean-appen\">\n          <button data-tab=\"bilan\"     type=\"button\">Oversigt<\/button>\n          <button data-tab=\"kcal\"      type=\"button\">Kalorier<\/button>\n          <button data-tab=\"depense\"   type=\"button\" class=\"on\">Forbrug<\/button>\n          <button data-tab=\"strategie\" type=\"button\">Strategi<\/button>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"snippet rev\">\n    <div class=\"lbl\">Hurtigt svar<\/div>\n    <p>Foodvisor opfandt fotoscanning af m\u00e5ltider i Frankrig og er stadig en reference til at identificere det, du spiser: foto, genkendelse af f\u00f8devarer, estimering af portioner. P\u00e5 forbrugssiden bygger Foodvisor derimod p\u00e5 en populationsformel (Mifflin-St Jeor 1990, uden m\u00e5lt fedtprocent) og en statisk aktivitetsmultiplikator valgt ved tilmeldingen. Lean tager problemet fra den anden side: at genberegne hver TDEE-komponent (<span data-term=\"BMR\">BMR<span class=\"tt\">Basal Metabolic Rate. Energi brugt i hvile. Hos Lean beregnet p\u00e5 den reelle fedtfri masse via AI BodyScan.<\/span><\/span> p\u00e5 reel fedtprocent via en patenteret egenudviklet model, <span data-term=\"NEAT\">NEAT<span class=\"tt\">Non-Exercise Activity Thermogenesis. Forbrug fra skridt og daglige aktiviteter uden for sport.<\/span><\/span> per skridt, <span data-term=\"EAT\">EAT<span class=\"tt\">Exercise Activity Thermogenesis. Forbrug fra dine tr\u00e6ningspas, beregnet via MET.<\/span><\/span> per MET, <span data-term=\"TEF\">TEF<span class=\"tt\">Thermic Effect of Food. Energi brugt p\u00e5 ford\u00f8jelsen. Afh\u00e6nger af de indtagne makroer.<\/span><\/span> fra makroer) og modulere BMR med den metaboliske tilpasning kontinuerligt, uden koefficient at v\u00e6lge.<\/p>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"constat\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">00 &middot; Konstateringen<\/span><\/div>\n  <h2 id=\"constat\">Foodvisor ser din tallerken, ikke dit reelle forbrug<\/h2>\n  <p>L\u00e6ser du dette, har du sandsynligvis allerede installeret Foodvisor. Du valgte den pr\u00e6cis for det, ingen gjorde f\u00f8r den: fotografere din tallerken og lade AI'en genkende kyllingen, risen, saucen og estimere portionerne uden at finde v\u00e6gten frem. Du indtastede din v\u00e6gt, din h\u00f8jde, din alder, dit k\u00f8n og valgte dit aktivitetsniveau p\u00e5 en statisk liste. Appen viste dig et kaloriem\u00e5l, lad os sige 2&nbsp;250&nbsp;kcal for at tabe dig.<\/p>\n  <p>Du spillede med. Du scannede dine m\u00e5ltider, rettede portionerne, n\u00e5r AI'en var i tvivl, holdt en ren indtastning dag efter dag. De f\u00f8rste 6 uger virker det. Du taber dig. Du er glad. S\u00e5 omkring uge 8 fryser v\u00e6gten. Du strammer skruen. Du g\u00e5r ned til 2&nbsp;000&nbsp;kcal. Igen rykker intet sig.<\/p>\n\n  <div class=\"statement\">\n    <div class=\"num\">&minus;10 til &minus;15&nbsp;%<\/div>\n    <div class=\"lbl\">m\u00e5lt fald i TDEE efter 4 til 6 ugers underskud p\u00e5 &minus;500&nbsp;kcal\/dag. Foodvisor opdager det ikke. Dit kaloriem\u00e5l forbliver frosset p\u00e5 dit aktivitetsniveau fra 100&nbsp;dage siden.<\/div>\n  <\/div>\n\n  <p>Lad os sige, at Foodvisor viser dig en TDEE p\u00e5 2&nbsp;500&nbsp;kcal. Du spiser 2&nbsp;250 (teoretisk underskud p\u00e5 250&nbsp;kcal). Men i virkeligheden er din <a class=\"inline\" href=\"https:\/\/lean-app.com\/da\/depense-energetique-totale-v2\/\">TDEE er faldet til 2&nbsp;200&nbsp;kcal<\/a> p\u00e5 grund af den metaboliske tilpasning. Du er i overskud p\u00e5 50&nbsp;kcal uden at vide det. Ingen chance for at forts\u00e6tte med at tabe dig, selv med markedets reneste indtastning.<\/p>\n  <p>Foodvisors l\u00f8fte er klart og holdes: du ved, hvad der er p\u00e5 din tallerken, uden at veje noget. Det er v\u00e6rdifuldt. Det, Foodvisor ikke g\u00f8r, er at <a class=\"inline\" href=\"https:\/\/lean-app.com\/da\/comment-compter-ses-calories\/\">genberegne dit forbrug<\/a> i takt med ugerne i underskud. Og det er pr\u00e6cis der, l\u00f8ftet stopper, selv om det er det h\u00e5ndtag, der f\u00e5r dig til at tabe dig.<\/p>\n<\/section>\n\n<section aria-labelledby=\"p1\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">01 &middot; Problem 1<\/span><\/div>\n  <h2 id=\"p1\">BMR-formlen fra 1990, uden m\u00e5lt fedtprocent<\/h2>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figur 1 &middot; Mand 1,80 m, 120&nbsp;kg, 30&nbsp;% BF<\/span><span class=\"r\">kcal<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\" style=\"position:relative;width:100%;height:380px;min-height:340px\"><canvas id=\"chartBMR\" aria-label=\"BMR-sammenligning Mifflin-St Jeor 2500 kcal vs Leans patenterede egenudviklede model 2000 kcal, forskel p\u00e5 500 kcal\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>Estimeret BMR.<\/strong> Leans patenterede egenudviklede model tager h\u00f8jde for den fedtfri masse. Mifflin-St Jeor (populationsformel, uden fedtprocent) g\u00f8r ikke. Forskel p\u00e5 500&nbsp;kcal, svarende til en hel frokost.<\/p>\n  <\/div>\n\n  <p>For at beregne dit basalstofskifte (BMR, den energi du forbr\u00e6nder i hvile) tager Foodvisor udgangspunkt i din profil: v\u00e6gt, h\u00f8jde, alder, k\u00f8n. Det er logikken i n\u00e6sten alle forbruger-kalorietrackere, arvet fra populationsformler som Mifflin-St Jeor. Og man m\u00e5 v\u00e6re \u00e6rlig: det er bedre end Harris-Benedict 1919, som andre apps stadig bruger.<\/p>\n  <p>Mifflin-St Jeor er fra 1990 (PubMed 2305711). Stikpr\u00f8ven er stor (498 fors\u00f8gspersoner), metoden med indirekte kalorimetri er seri\u00f8s, formlen er kalibreret p\u00e5 en moderne population: 10 \u00d7 v\u00e6gt (kg) + 6,25 \u00d7 h\u00f8jde (cm) \u2212 5 \u00d7 alder \u2212 161 (kvinder) eller +5 (m\u00e6nd).<\/p>\n  <p>Problemet er ikke den valgte formel. Problemet er det, ingen formel af den type kan se: <strong>den tager kun h\u00f8jde for v\u00e6gten. Ikke fedtprocenten. Ikke den fedtfri masse.<\/strong> Intet felt i Foodvisors onboarding sp\u00f8rger om din fedtprocent, og ingen m\u00e5ling findes i appen.<\/p>\n  <p>Men siden 1980'erne har man vidst, at <strong>fedtmassen bruger meget lidt energi<\/strong> sammenlignet med resten af kroppen. Leveren, hjernen, hjertet, nyrerne og is\u00e6r musklerne er de reelle forbrugsposter. Fedtmassen er inaktiv. En person med 30&nbsp;% fedtprocent forbr\u00e6nder slet ikke lige s\u00e5 meget som en person med 10&nbsp;% fedtprocent, selv ved samme v\u00e6gt.<\/p>\n  <p>Frankenfield 2013 (PubMed 23631843) sammenlignede Mifflin-St Jeor med referencemetoden indirekte kalorimetri p\u00e5 overv\u00e6gtige og ikke-overv\u00e6gtige kohorter. Resultat: 87&nbsp;% pr\u00e6cision hos ikke-overv\u00e6gtige, og kun <strong>75&nbsp;% hos overv\u00e6gtige<\/strong>. Et nyere studie (PMC11820646) viser, at ved BMI over 35 tager Mifflin fejl med <strong>250 til 315&nbsp;kcal om dagen<\/strong>. Det svarer til en hel snack i beregningen af et underskud.<\/p>\n  <p>500&nbsp;kcal er ikke ingenting. Siger appen \u00abdin BMR er 2&nbsp;500\u00bb, og den i virkeligheden er 2&nbsp;000, er alt, hvad der f\u00f8lger, forkert: dit underskudsm\u00e5l, din prognose for ugentligt tab, din makrofordeling beregnet i procent af TDEE. Og intet tallerkenfoto, uanset hvor godt genkendt, retter et forkert m\u00e5l.<\/p>\n\n  <div class=\"bodyscan-illust\" style=\"margin:40px auto 8px;display:flex;flex-direction:column;align-items:center;gap:14px;max-width:200px\">\n    <div class=\"mini-phone\" style=\"max-width:200px\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-bodyscan-result.webp\" alt=\"BodyScan IA Lean : bodyfat mesur\u00e9 par photo en 5 secondes\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n    <div class=\"mini-cap\">Reel fedtprocent<strong>Foto, 5 sekunder<\/strong><\/div>\n  <\/div>\n\n  <div class=\"statement\">\n    <div class=\"num\">400&nbsp;kcal<\/div>\n    <div class=\"lbl\">forskel mellem to m\u00e6nd p\u00e5 80&nbsp;kg, den ene med 10&nbsp;% fedtprocent (BMR 1&nbsp;900), den anden med 30&nbsp;% (BMR 1&nbsp;500). En v\u00e6gtbaseret formel viser dem samme tal.<\/div>\n  <\/div>\n\n  <p>Delkonklusion: hvis en app beregner din BMR udelukkende ud fra din v\u00e6gt, h\u00f8jde, alder og k\u00f8n, kan resultatet ikke v\u00e6re individualiseret. Det er matematisk umuligt. Selv med den bedste tallerkengenkendelse som input.<\/p>\n<\/section>\n\n<section aria-labelledby=\"p2\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">02 &middot; Problem 2<\/span><\/div>\n  <h2 id=\"p2\">Aktivitetsmultiplikatoren, valgt \u00e9n gang for alle<\/h2>\n  <p>Det er her, det bliver alvorligt. Og det er sandsynligvis den pointe, ingen har forklaret dig.<\/p>\n  <p>N\u00e5r din BMR er estimeret, skal Foodvisor g\u00e5 videre til den samlede TDEE. <a class=\"inline\" href=\"https:\/\/lean-app.com\/da\/depense-energetique-totale-v2\/\">TDEE er BMR + alt det andet<\/a> : forbruget fra skridt, daglige aktiviteter, sport og ford\u00f8jelse. Alt, der ikke er basalstofskifte.<\/p>\n  <p>Hvordan g\u00f8r Foodvisor det&nbsp;? Som n\u00e6sten alle trackere: den beder dig ved tilmeldingen v\u00e6lge dit aktivitetsniveau p\u00e5 en statisk liste. Disse faktorer kaldes i idr\u00e6tsvidenskaben <strong>PAL-niveauer<\/strong> (Physical Activity Level), det er bare en multiplikator anvendt p\u00e5 din BMR:<\/p>\n  <ul>\n    <li>Stillesiddende (PAL 1,2): kontor, lidt gang<\/li>\n    <li>Let aktiv (PAL 1,375): lejlighedsvis gang<\/li>\n    <li>Aktiv (PAL 1,55): sport 3 til 5 gange om ugen<\/li>\n    <li>Meget aktiv (PAL 1,725): intens sport n\u00e6sten dagligt<\/li>\n    <li>Ekstremt aktiv (PAL 1,9): meget intens sport eller fysisk arbejde<\/li>\n  <\/ul>\n  <p>Og afh\u00e6ngigt af dit valg ganger appen din BMR med den tilh\u00f8rende koefficient. Det er alt. Det er alt, hvad der ligger bag dit daglige kaloriem\u00e5l. En boks, DU har krydset af \u00e9n enkelt gang ved tilmeldingen. Ofte for seks m\u00e5neder siden. U\u00e6ndret siden.<\/p>\n  <p>Og her er den tavse f\u00e6lde: denne tiln\u00e6rmelse er <strong>hyper-ufuldkommen<\/strong>. Forskellen mellem en dag, hvor du er klistret til sofaen foran Netflix, og en dag, hvor du tager i Disneyland med dine b\u00f8rn og g\u00e5r 15&nbsp;km, <strong>det er mere end 1&nbsp;000&nbsp;kcal<\/strong>. Ingen af de 5 bokse fanger det.<\/p>\n  <p>Foodvisor kan ellers godt f\u00f8lge din aktivitet: appen kan t\u00e6lle dine skridt og registrere dine pas. Men de data bruges mest til at vise din aktivitet, ikke til at genopbygge en komplet TDEE: dit kaloriem\u00e5l hviler stadig p\u00e5 multiplikatoren valgt ved onboarding, og sportsforbruget l\u00e6gges til, uden at NEAT og EAT adskilles ordentligt.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figur 2 &middot; 7 reelle dage<\/span><span class=\"r\">kcal\/dag<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\" style=\"position:relative;width:100%;height:380px;min-height:340px\"><canvas id=\"chartNEAT\" aria-label=\"Daglig variation i kalorieforbruget over 7 dage, mod 2400 kcal fast if\u00f8lge Foodvisor\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>Reelt forbrug<\/strong> m\u00e5lt over 7&nbsp;dage for en Lean-bruger. Den gr\u00f8nne linje er det, Foodvisor viste (2&nbsp;400&nbsp;kcal fast, statisk multiplikator \u00d7 BMR). De lyser\u00f8de annotationer viser, hvorfor hver dag bev\u00e6ger sig.<\/p>\n  <\/div>\n\n  <p>Du kan ikke reducere dit aktivitetsniveau til en statisk boks. Du er m\u00e5ske aktiv de uger, hvor du arbejder lidt hjemmefra, og stillesiddende dem, hvor du ikke forlader kontoret. Du er m\u00e5ske aktiv om sommeren og stillesiddende om vinteren. Du er m\u00e5ske aktiv tirsdag til fredag og stillesiddende i weekenden.<\/p>\n  <p>Hvilken boks vil du krydse af i denne uge? Sandheden er, at ingen af de 5 vil v\u00e6re korrekt. Og derfor giver Foodvisor dig en TDEE, der systematisk er afkoblet fra virkeligheden.<\/p>\n  <p>Artiklens n\u00f8glepointe: selv med en perfekt BMR-formel ville den statiske multiplikator v\u00e6re nok til at \u00f8del\u00e6gge alt. Du kan ikke estimere en <a class=\"inline\" href=\"https:\/\/lean-app.com\/da\/neat-depense-non-sportive\/\">NEAT<\/a>, en EAT og en <a class=\"inline\" href=\"https:\/\/lean-app.com\/da\/effet-thermique-des-aliments\/\">TEF<\/a> med \u00e9n enkelt multiplikator anvendt p\u00e5 BMR. Det er konceptuelt absurd.<\/p>\n  <p>Du har forst\u00e5et det: <strong>en BMR-formel uden fedtprocent plus en statisk tiln\u00e6rmelse af alt det andet giver meget f\u00e5 chancer for at n\u00e5 dine m\u00e5l over 3 til 6 m\u00e5neder.<\/strong> Uanset hvor ren indtastningen p\u00e5 tallerkensiden er.<\/p>\n\n  <div class=\"cta-band rev\" style=\"display:flex;align-items:center;justify-content:space-between;gap:20px;flex-wrap:wrap;padding:26px 28px;margin:40px 0;background:#FAF5EE;border:1px solid #E8E2D6;border-radius:16px\">\n    <div class=\"l\" style=\"flex:1;min-width:240px;font-size:18px;line-height:1.4;font-weight:500;color:#0E0E10\">Se din reelle TDEE, opdelt i BMR + NEAT + EAT + TEF. Gratis download.<\/div>\n    <div class=\"stores\" style=\"display:flex;gap:10px;align-items:center;flex-wrap:wrap\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-foodvisor\" 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\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/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=vs-foodvisor\" 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\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"p3\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">03 &middot; Problem 3<\/span><\/div>\n  <h2 id=\"p3\">Den metaboliske tilpasning, aldrig modelleret<\/h2>\n  <p>Det er den endelige boss. Det fineste begreb. Og sandsynligvis det vigtigste.<\/p>\n  <p>N\u00e5r du er i kalorieunderskud, forst\u00e5r din krop, at den f\u00e5r mindre energi end f\u00f8r. For at beskytte sig skifter den til sparetilstand. Pr\u00e6cis som str\u00f8msparetilstand p\u00e5 din iPhone: alt fungerer stadig, men med mindre energi. Din BMR falder. Din NEAT falder. Din EAT falder.<\/p>\n  <p>Det kaldes metabolisk tilpasning. Den videnskabelige litteratur er klar og reproducerbar: M\u00fcller 2015 (PubMed 26399868, genbes\u00f8g af Minnesota), Doucet 2001 (PubMed 11430776), Nunes 2020 (PMC7484122) over 6 ugers underskud. Her er tallene:<\/p>\n  <ul>\n    <li>Underskud p\u00e5 &minus;250&nbsp;kcal om dagen i 2 til 8 uger: tilpasning p\u00e5 <strong>5 til 10&nbsp;%<\/strong> (TDEE falder til 90-95&nbsp;% af udgangsniveauet)<\/li>\n    <li>Underskud p\u00e5 &minus;500&nbsp;kcal om dagen: <strong>10 til 15&nbsp;%<\/strong> tilpasning (TDEE falder til 85-90&nbsp;%)<\/li>\n    <li>Underskud p\u00e5 &minus;750&nbsp;kcal om dagen: <strong>15 til 25&nbsp;%<\/strong> tilpasning (TDEE falder til 75-85&nbsp;%)<\/li>\n  <\/ul>\n  <p>Lean-konvention: 100&nbsp;% = optimalt, 90&nbsp;% = 10&nbsp;% tilpasning. Og da NEAT, EAT og TEF alle afh\u00e6nger direkte af BMR, er det n\u00e6sten hele TDEE, der p\u00e5virkes.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figur 3 &middot; 8 uger i underskud<\/span><span class=\"r\">kcal\/dag<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\" style=\"position:relative;width:100%;height:380px;min-height:340px\"><canvas id=\"chartAdapt\" aria-label=\"TDEE, der falder fra 2500 til 2150 kcal over 8 uger, mod 2500 fast if\u00f8lge Foodvisor\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>Reel TDEE<\/strong> over 8 ugers underskud p\u00e5 &minus;500&nbsp;kcal\/dag. Den lyser\u00f8de kurve falder. Foodvisor-linjen forbliver flad. I uge 6 er du allerede p\u00e5 vedligehold. Uden at have \u00e6ndret noget.<\/p>\n  <\/div>\n\n  <p>Konkret: havde du planlagt et underskud p\u00e5 10&nbsp;% p\u00e5 en TDEE p\u00e5 2&nbsp;500 (alts\u00e5 spise 2&nbsp;250 om dagen), og din krop tilpasser sig med 10&nbsp;%, er din reelle TDEE faldet til 2&nbsp;250. Du er p\u00e5 vedligehold. Du taber dig ikke l\u00e6ngere.<\/p>\n  <p>F\u00e6lden er, at det er snigende. I starten taber du dig. Du er glad. Du forts\u00e6tter. Men uge efter uge akkumuleres tilpasningen. Og p\u00e5 et tidspunkt, uden at have \u00e6ndret noget i din tracking, <strong>holder du op med at tabe dig<\/strong>.<\/p>\n  <p>95&nbsp;% af folk g\u00e5r igennem det uden at forst\u00e5 det. De bebrejder deres viljestyrke. De skyder skylden p\u00e5 deres \u00ab\u00f8delagte stofskifte\u00bb. De kaster sig ud i h\u00e5rdere di\u00e6ter, hvilket forv\u00e6rrer tilpasningen. Spiral.<\/p>\n  <p>Foodvisor beregner aldrig den metaboliske tilpasning. Den giver dig et fast kaloriem\u00e5l, s\u00e5 l\u00e6nge du ikke manuelt opdaterer din v\u00e6gt og dit aktivitetsniveau. Du kan scanne dine tallerkener med eksemplarisk regelm\u00e6ssighed, men n\u00e5r du stagnerer efter 6 ugers cut, aner appen ikke hvorfor.<\/p>\n<\/section>\n\n<section aria-labelledby=\"solution\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">04 &middot; Lean-l\u00f8sningen<\/span><\/div>\n  <h2 id=\"solution\">S\u00e5dan l\u00f8ser Lean hvert af de 3 problemer<\/h2>\n  <p>Foodvisor har sat en standard for fotoscanning af en ret, og dens genkendelse af fransk mad er stadig fremragende. Problemet er ikke det, den ser p\u00e5 din tallerken, det er det, den ikke ser af din krop&nbsp;: forbruget estimeres stadig med en populationsformel ganget med et aktivitetsniveau. Lean g\u00f8r begge dele&nbsp;: AI-fotoscanning <em>og<\/em> m\u00e5ling af hver TDEE-komponent (BMR&nbsp;+&nbsp;NEAT&nbsp;+&nbsp;EAT&nbsp;+&nbsp;TEF) plus den metaboliske tilpasning. Her er detaljerne.<\/p>\n\n  <div class=\"method\">\n    <div class=\"m-phone\">\n      <div class=\"duo-row\">\n        <div>\n          <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-bodyscan-result.webp\" alt=\"R\u00e9sultat BodyScan IA : pourcentage de masse grasse mesur\u00e9 par photo\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\">Trin 1<strong>AI BodyScan<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp\" alt=\"\u00c9cran BMR Lean : m\u00e9tabolisme de base calcul\u00e9 sur la masse maigre\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\">Trin 2<strong>BMR genberegnet<\/strong><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n    <div>\n      <div class=\"m-tag\">BMR p\u00e5 reel fedtprocent<\/div>\n      <h3>Patenteret egenudviklet model, baseret p\u00e5 fedtfri masse<\/h3>\n      <p>At t\u00e6lle indtagne kalorier perfekt nytter ikke, hvis de forbrugte kalorier er 300&nbsp;kcal forkerte. Lean beregner stofskiftet p\u00e5 din <strong>fedtfri masse<\/strong>, den eneste, der reelt forbruger i hvile, og ikke p\u00e5 din r\u00e5 v\u00e6gt.<\/p>\n      <p>Den <strong>AI BodyScan<\/strong> anvender p\u00e5 din krop det, Foodvisor anvender p\u00e5 din tallerken&nbsp;: et foto, en model tr\u00e6net p\u00e5 en bank af DEXA-scanninger, din fedtprocent p\u00e5 f\u00e5 sekunder, gentaget hver uge.<\/p>\n      <p>Ingen hudfoldsm\u00e5ler, ingen impedansv\u00e6gt, ingen DEXA. Samme enkelhed som en m\u00e5ltidsscanning, anvendt p\u00e5 din kropssammens\u00e6tning.<\/p>\n    <\/div>\n  <\/div>\n\n  <div class=\"method flip\">\n    <div>\n      <div class=\"m-tag\">Ingen aktivitetskoefficient<\/div>\n      <h3>NEAT, EAT, TEF beregnet hver for sig<\/h3>\n      <p><strong>NEAT.<\/strong> Dine reelle skridt kommer via HealthKit (iOS) eller Google Fit (Android) og bliver til kalorier efter dit stofskifte. Det er dagens mest variable post, og den, som et erkl\u00e6ret aktivitetsniveau fuldst\u00e6ndig udj\u00e6vner.<\/p>\n      <p><strong>EAT.<\/strong> Hvert pas s\u00e6ttes i tal med MET p\u00e5 din reelle anstrengelsestid, pauser udelukket. At t\u00e6lle en times styrketr\u00e6ning som en times l\u00f8b forvrider regnskabet med flere hundrede kcal om ugen.<\/p>\n      <p><strong>TEF.<\/strong> Foodvisor identificerer dine f\u00f8devarer, Lean udleder ford\u00f8jelsesomkostningen af dem&nbsp;: 20 til 30&nbsp;% af kalorierne for protein, 5 til 10&nbsp;% for kulhydrater, 1 til 3&nbsp;% for fedt, i stedet for den faste sats p\u00e5 10&nbsp;%, der anvendes overalt.<\/p>\n    <\/div>\n    <div class=\"m-phone\">\n      <div class=\"mini-row\" style=\"margin:0;gap:10px\">\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp\" alt=\"\u00c9cran NEAT Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">NEAT<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp\" alt=\"\u00c9cran EAT Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">EAT<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp\" alt=\"\u00c9cran TEF Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">TEF<\/strong><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"method flip\">\n    <div>\n      <div class=\"m-tag\">Automatisk metabolisk tilpasning<\/div>\n      <h3>En verdensnyhed i en forbruger-app<\/h3>\n      <p><strong>Den metaboliske tilpasning.<\/strong> Ingen m\u00e5ltidsscanning opdager, at dit stofskifte er bremset 12&nbsp;% efter otte uger. Lean estimerer det efter de publicerede intervaller (M\u00fcller 2015, Doucet 2001) og retter dit m\u00e5l derefter.<\/p>\n      <p>Ud over 10 til 15&nbsp;% tilpasning kan appen r\u00e5de til en tilbagevenden til vedligehold for at s\u00e6tte gang i stofskiftet igen, f\u00f8r du forts\u00e6tter.<\/p>\n      <p>Ingen aktivitetsmultiplikator at v\u00e6lge. Hver komponent m\u00e5les, uge efter uge.<\/p>\n    <\/div>\n    <div class=\"m-phone\">\n      <div class=\"mini-phone solo\" style=\"max-width:240px!important;width:240px;padding:6px!important;border-radius:24px!important;border-width:2px!important\"><div class=\"notch\" style=\"width:60px!important;height:14px!important;border-radius:0 0 9px 9px!important\"><\/div><div class=\"scr\" style=\"border-radius:18px!important\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp\" alt=\"\u00c9cran d\u00e9pense totale Lean avec adaptation m\u00e9tabolique\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">Metode<strong>Metabolisk tilpasning<\/strong><\/div>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"tab\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">05 &middot; Sammenligningstabel<\/span><\/div>\n  <h2 id=\"tab\">Lean over for Foodvisor, kriterium for kriterium<\/h2>\n  <p>\u00c6rlig gennemgang af hver apps styrker og svagheder. Intet kriterium handler om prisen.<\/p>\n\n  <div class=\"brand-banner\" style=\"display:grid;grid-template-columns:1fr 1fr;gap:16px;margin:24px 0 18px;padding:0\">\n  <div style=\"background:#FFF1F5;border:1.5px solid #FF2D6E;border-radius:14px;padding:20px 18px;display:flex;flex-direction:column;align-items:center;text-align:center;gap:10px\">\n    <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"Lean\" width=\"64\" height=\"64\" loading=\"lazy\" decoding=\"async\" style=\"width:64px;height:64px;border-radius:14px;display:block;object-fit:cover\" \/>\n    <div style=\"font-family:-apple-system,BlinkMacSystemFont,'SF Pro Display',sans-serif;font-size:18px;font-weight:700;color:#FF2D6E;letter-spacing:-0.2px\">Lean<\/div>\n  <\/div>\n  <div style=\"background:#EFF7EF;border:1.5px solid #6ABF6C;border-radius:14px;padding:20px 18px;display:flex;flex-direction:column;align-items:center;text-align:center;gap:10px\">\n    <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/08\/fv-logo-foodvisor.jpg\" alt=\"Foodvisor\" width=\"64\" height=\"64\" loading=\"lazy\" decoding=\"async\" style=\"width:64px;height:64px;border-radius:14px;display:block;object-fit:cover\" \/>\n    <div style=\"font-family:-apple-system,BlinkMacSystemFont,'SF Pro Display',sans-serif;font-size:18px;font-weight:700;color:#6ABF6C;letter-spacing:-0.2px\">Foodvisor<\/div>\n  <\/div>\n<\/div>\n<div class=\"table\" role=\"table\" aria-label=\"Sammenligning Lean over for Foodvisor\">\n    <div class=\"table-row head\" role=\"row\">\n      <div role=\"columnheader\">Kriterium<\/div>\n      <div class=\"brand-cell lean\" role=\"columnheader\"><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\" \/> <span>Lean<\/span><\/div>\n      <div class=\"brand-cell\" role=\"columnheader\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/08\/fv-logo-foodvisor.jpg\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> <span>Foodvisor<\/span><\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">BMR-formel<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Patenteret egenudviklet model (fedtfri masse)<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Populationsformel (Mifflin-St Jeor 1990)<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Tager h\u00f8jde for fedtprocent<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Ja, m\u00e5lt i appen<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Nej, kun v\u00e6gt-h\u00f8jde-alder-k\u00f8n<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">M\u00e5ling af fedtprocent i appen<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> AI BodyScan via foto<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Nej<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">NEAT (skridt, aktivitet uden for sport)<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Beregnet p\u00e5 reelle skridt hver dag<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Skridt fulgt, men m\u00e5l baseret p\u00e5 den statiske multiplikator<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">EAT (tr\u00e6ningsforbrug)<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Per sport via MET, effektiv tid<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Pas registreret, lagt til et fastl\u00e5st m\u00e5l<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">TEF (ford\u00f8jelse)<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Beregnet efter makroer, integreret i TDEE<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Ikke integreret i forbrugsberegningen<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Metabolisk tilpasning<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Automatisk, uge for uge<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Nej<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Aktivitetskoefficient at v\u00e6lge<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Nej, beregnet p\u00e5 reelle data<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Ja, statisk multiplikator valgt ved tilmeldingen<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">AI-fotoscanning af en ret<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Ja, ubegr\u00e6nset<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Ja, den historiske pioner (2018)<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Visuel genkendelse af f\u00f8devarer<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Ja, moderne AI-fotoscanning<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Reference p\u00e5 det franske marked, \u00e5rs tr\u00e6ning<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Stregkodescanning<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Ja<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Ja<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">F\u00f8devaredatabase<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> USDA + OpenFoodFacts, kurateret<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Stor base, franske produkter godt d\u00e6kket<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Coaching af di\u00e6tister<\/div>\n      <div class=\"cell lean\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Uden for scope, appen guider via Progressionspyramiden<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Ja, uddannede di\u00e6tister (dedikeret tilbud)<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Anbefaling af kalorieunderskud<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Tilpasset den reelle TDEE<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Fast m\u00e5l, manuel genberegning p\u00e5kr\u00e6vet<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Fransk app<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Ja<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Ja, f\u00f8dt i Paris<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Omd\u00f8mme og publikumsst\u00f8rrelse<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> 4.7\/5, 10&nbsp;000+ brugere, ung fransk app<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Anerkendt pioner inden for fotoscanning, st\u00e6rkt kendskab i Frankrig<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Forretningsmodel<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Premium, 7 dages gratis pr\u00f8veperiode p\u00e5 \u00e5rsabonnementet<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Gratis version, coaching som tilvalg<\/div>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"tracking\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">06 &middot; Tracking<\/span><\/div>\n  <h2 id=\"tracking\">3 metoder til at tracke et m\u00e5ltid<\/h2>\n  <p>Foodvisor beviste, at et foto kunne erstatte manuel indtastning. Lean tager den id\u00e9 og udvider den&nbsp;: tre registreringsmetoder efter situationen, for at holde ved p\u00e5 sigt.<\/p>\n\n  <div class=\"mini-row\">\n    <div>\n      <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-database.webp\" alt=\"Recherche dans la base de donn\u00e9es USDA + OpenFoodFacts\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">Metode 1<strong>Database<\/strong><\/div>\n    <\/div>\n    <div>\n      <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-codebarre.webp\" alt=\"Scan de code-barres dans Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">Metode 2<strong>Stregkode<\/strong><\/div>\n    <\/div>\n    <div>\n      <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-scania.webp\" alt=\"Scan photo IA d'un plat\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">Metode 3<strong>AI-fotoscanning<\/strong><\/div>\n    <\/div>\n  <\/div>\n\n  <ol>\n    <li><strong>S\u00f8gning i databasen.<\/strong> Kurateret base, USDA + OpenFoodFacts. Ingen community-st\u00f8j, ingen \u00abStegt kylling\u00bb indtastet 47 gange af 47 forskellige brugere med 47 forskellige v\u00e6rdier.<\/li>\n    <li><strong>Stregkodescanning.<\/strong> Standard. Du scanner din pastapakke, du f\u00e5r makroerne.<\/li>\n    <li><strong>AI-fotoscanning af en ret.<\/strong> Du tager et foto af din tallerken, AI'en genkender f\u00f8devarerne, du f\u00e5r kalorier og makroer per f\u00f8devare. Den refleks, du allerede har, hvis du kommer fra Foodvisor: den beholder du, som den er.<\/li>\n  <\/ol>\n  <p>Leans AI-fotoscanning spiller samme rolle som Foodvisors til m\u00e5ltider ude. Forskellen ligger et andet sted&nbsp;: det, Lean derefter g\u00f8r med de kalorier, ved at holde dem op mod et m\u00e5lt, ikke estimeret, forbrug.<\/p>\n  <p>Ud over m\u00e5ltidet viser Lean en TDEE, der opdateres i l\u00f8bet af dagen efter dine skridt. At scanne en tallerken perfekt over for et fastl\u00e5st kaloriem\u00e5l er ikke nok.<\/p>\n  <p>Og ovenover, Progressionspyramiden&nbsp;:<\/p>\n\n  <div class=\"pyramid\" aria-label=\"Leans Progressionspyramide\">\n    <div class=\"level l1\"><span>Vedholdenhed<\/span><span class=\"k\">Bund<\/span><\/div>\n    <div class=\"level l2\"><span>Kaloriem\u00e5l<\/span><span class=\"k\">Etage 2<\/span><\/div>\n    <div class=\"level l3\"><span>Skridt \/ NEAT<\/span><span class=\"k\">Etage 3<\/span><\/div>\n    <div class=\"level l4\"><span>Makron\u00e6ringsstoffer<\/span><span class=\"k\">Top<\/span><\/div>\n  <\/div>\n  <div class=\"pyramid-cap\">Spring ikke trin over. Hvis du ikke er regelm\u00e6ssig i din tracking, nytter det ikke at optimere makroerne p\u00e5 procenten.<\/div>\n<\/section>\n\n<section aria-labelledby=\"foodvisor-better\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">07 &middot; \u00c6rlighed<\/span><\/div>\n  <h2 id=\"foodvisor-better\">Det Foodvisor g\u00f8r bedre<\/h2>\n  <p>Lean er ikke perfekt, og Foodvisor har flere reelle styrker, man m\u00e5 anerkende. \u00c6rlig gennemgang, kriterium for kriterium, p\u00e5 de akser, hvor pioneren stadig er foran. Ingen af disse akser er sekund\u00e6re: det er reelle s\u00f8jler i Foodvisors l\u00f8fte.<\/p>\n\n  <div class=\"scorecard rev\" aria-label=\"Scorecard Foodvisor over for Lean p\u00e5 4 akser\">\n    <div class=\"scorecard-head\">\n      <div class=\"h-crit\">Akse<\/div>\n      <div class=\"h-brand\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/08\/fv-logo-foodvisor.jpg\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> Foodvisor<\/div>\n      <div class=\"h-brand\"><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\" \/> Lean<\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Visuel genkendelse af en tallerken<\/div>\n      <div class=\"bar mfp\" data-brand=\"FOODVISOR\"><div class=\"b\"><i style=\"width:95%\"><\/i><\/div><div class=\"v\">9,5<\/div><\/div>\n      <div class=\"bar lean\" data-brand=\"LEAN\"><div class=\"b\"><i style=\"width:80%\"><\/i><\/div><div class=\"v\">8,0<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Automatisk estimering af portioner<\/div>\n      <div class=\"bar mfp\" data-brand=\"FOODVISOR\"><div class=\"b\"><i style=\"width:90%\"><\/i><\/div><div class=\"v\">9,0<\/div><\/div>\n      <div class=\"bar lean\" data-brand=\"LEAN\"><div class=\"b\"><i style=\"width:75%\"><\/i><\/div><div class=\"v\">7,5<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Menneskelig coaching (uddannede di\u00e6tister)<\/div>\n      <div class=\"bar mfp\" data-brand=\"FOODVISOR\"><div class=\"b\"><i style=\"width:92%\"><\/i><\/div><div class=\"v\">9,2<\/div><\/div>\n      <div class=\"bar lean\" data-brand=\"LEAN\"><div class=\"b\"><i style=\"width:25%\"><\/i><\/div><div class=\"v\">2,5<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Forspring p\u00e5 fotoscanning (fransk marked)<\/div>\n      <div class=\"bar mfp\" data-brand=\"FOODVISOR\"><div class=\"b\"><i style=\"width:95%\"><\/i><\/div><div class=\"v\">9,5<\/div><\/div>\n      <div class=\"bar lean\" data-brand=\"LEAN\"><div class=\"b\"><i style=\"width:40%\"><\/i><\/div><div class=\"v\">4,0<\/div><\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>\u00c6rlig gennemgang.<\/strong> P\u00e5 tallerkengenkendelse skabte Foodvisor kategorien i Frankrig i 2018, og dens AI har \u00e5rs forspring i tr\u00e6ning: identifikation af f\u00f8devarer, estimering af portioner uden v\u00e6gt, h\u00e5ndtering af sammensatte retter. Det er dens historiske hjemmebane, og den er stadig referencen der. P\u00e5 menneskelig st\u00f8tte tilbyder Foodvisor opf\u00f8lgning af uddannede di\u00e6tister direkte i appen: Lean tilbyder det ikke og h\u00e6vder ikke at erstatte det. Leans AI-fotoscanning er moderne, ubegr\u00e6nset og rigeligt til daglig brug, men Lean g\u00f8r ikke krav p\u00e5 forspring p\u00e5 det omr\u00e5de.<\/p>\n  <p>Er din hovedvinkel den mest indarbejdede tallerkenidentifikation muligt, eller menneskelig coaching integreret i appen, er Foodvisor mere relevant end Lean. Er din vinkel pr\u00e6cisionen i <a class=\"inline\" href=\"https:\/\/lean-app.com\/da\/tdee-calculator\/\">TDEE-beregning<\/a>, fedtprocenten m\u00e5lt hver uge via AI BodyScan og den automatiske metaboliske tilpasning, er det pr\u00e6cis det, der lige er blevet p\u00e5vist i de 3 foreg\u00e5ende afsnit. Nogle k\u00f8rer de to apps parallelt, mens de v\u00e6lger, og det er fuldt forsvarligt.<\/p>\n<\/section>\n\n<section aria-labelledby=\"forwho\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">08 &middot; Til hvem<\/span><\/div>\n  <h2 id=\"forwho\">Hvem Lean er lavet til<\/h2>\n  <p>4 profiler. Kan du genkende dig selv i mindst \u00e9n, er Lean sandsynligvis lavet til dig.<\/p>\n\n  <div class=\"persona\">\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>Du har brugt Foodvisor seri\u00f8st og har ikke tabt dig<\/h4>\n        <p>Du har scannet dine tallerkener, rettet portionerne, holdt et \u00e6rligt underskud i uger, og du stagnerer. Det er ikke fotoet, der er skyld, det er det fastl\u00e5ste m\u00e5l beregnet uden fedtprocent. Lean retter ved roden via BMR p\u00e5 reel fedtprocent.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>Du stagnerer efter flere ugers cut<\/h4>\n        <p>Plateau, der tr\u00e6kker ud efter 4 til 8 uger. Det er den metaboliske tilpasning. Lean beregner den automatisk og justerer dit m\u00e5l hver uge.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>Du vil forst\u00e5 dit stofskifte<\/h4>\n        <p>Lean viser hver komponent (BMR, NEAT, EAT, TEF) og forklarer derefter tilpasningen separat, i stedet for at gemme alt bag et enkelt tal. Du ser, hvor hver forbrugt kcal kommer fra.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>Du vil have en tracking, der holder 12 m\u00e5neder<\/h4>\n        <p>AI-fotoscanning + kurateret base + stregkode d\u00e6kker alle brugssituationer, fra den r\u00e5 f\u00f8devare til pizzaen p\u00e5 restauranten. Det er det, der g\u00f8r forskellen mellem at holde ved og give op.<\/p>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>Foodvisor er stadig mere relevant til<\/strong>&nbsp;: menneskelig coaching af uddannede di\u00e6tister direkte i appen, og den mest indarbejdede tallerkengenkendelse p\u00e5 det franske marked. Pr\u00e6cisionen i forbrugsberegningen og den metaboliske tilpasning er bare ikke en del af dens hovedl\u00f8fte.<\/p>\n<\/section>\n\n<section aria-labelledby=\"migrate\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">09 &middot; Migration<\/span><\/div>\n  <h2 id=\"migrate\">Skift fra Foodvisor til Lean (eller brug begge) p\u00e5 3 minutter<\/h2>\n\n  <div class=\"steps\">\n    <div class=\"step\"><div class=\"sn\">01<\/div><h4>Download Lean<\/h4><p>App Store eller Play Store. Tilmelding p\u00e5 30 sekunder.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">02<\/div><h4>AI BodyScan<\/h4><p>Et foto, 5 sekunder. Du f\u00e5r din fedtprocent.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">03<\/div><h4>V\u00e6gt &amp; h\u00f8jde<\/h4><p>Du indtaster din v\u00e6gt og din h\u00f8jde. Det er alt.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">04<\/div><h4>Lean beregner<\/h4><p>BMR p\u00e5 reel fedtprocent, NEAT via HealthKit \/ Google Fit (reelle skridt), EAT per MET, TEF fra makroer, plus den metaboliske tilpasning, der modulerer BMR. Automatisk.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">05<\/div><h4>Track et m\u00e5ltid<\/h4><p>Foto, stregkode eller database. Du kender allerede handlingen.<\/p><\/div>\n  <\/div>\n\n  <p style=\"margin-top:24px\"><strong>Vigtig note.<\/strong> Lean importerer ikke din Foodvisor-historik automatisk, heller ikke dine yndlingsf\u00f8devarer. Betyder din opf\u00f8lgning med en Foodvisor-di\u00e6tist noget for dig, er der intet, der forhindrer dig i at beholde begge under overgangen: Foodvisor til den menneskelige st\u00f8tte, Lean til TDEE og den daglige tracking. HealthKit \/ Google Health Connect-synkroniseringen tager derimod straks over for dine skridt og din aktivitetshistorik.<\/p>\n\n  <div class=\"cta-band rev\" style=\"display:flex;align-items:center;justify-content:space-between;gap:20px;flex-wrap:wrap;padding:26px 28px;margin:40px 0;background:#FAF5EE;border:1px solid #E8E2D6;border-radius:16px\">\n    <div class=\"l\" style=\"flex:1;min-width:240px;font-size:18px;line-height:1.4;font-weight:500;color:#0E0E10\">Download Lean og start AI BodyScan nu. Gratis tilmelding.<\/div>\n    <div class=\"stores\" style=\"display:flex;gap:10px;align-items:center;flex-wrap:wrap\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-foodvisor\" 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\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/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=vs-foodvisor\" 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\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"deblock-h\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">10 &middot; Det Lean l\u00e5ser op<\/span><\/div>\n  <h2 id=\"deblock-h\">Det Lean g\u00f8r, og som Foodvisor ikke g\u00f8r (p\u00e5 forbruget)<\/h2>\n  <p>Seks funktioner centreret om forbruget, som ikke findes hos Foodvisor. De udspringer alle af samme princip&nbsp;: at beregne hver TDEE-komponent pr\u00e6cist, ikke at tiln\u00e6rme den.<\/p>\n\n  <div class=\"feat-stack\">\n    <div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">Ubegr\u00e6nset AI BodyScan<\/div><p class=\"fd\">Din reelle fedtprocent, m\u00e5lt fra et simpelt foto, gentaget hver uge. Det er den data, der \u00e6ndrer hele BMR-beregningen. Ingen anden forbruger-app tilbyder det.<\/p><\/div><div class=\"fc\">Fedtprocent<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">Automatisk metabolisk tilpasning<\/div><p class=\"fd\">Din TDEE justeres uge efter uge efter de videnskabeligt fastlagte tal. Du undg\u00e5r de plateauer, ingen kan forklare.<\/p><\/div><div class=\"fc\">Tilpasning<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">Live opdelt TDEE<\/div><p class=\"fd\">BMR + NEAT + EAT + TEF vist hver for sig, opdateret i l\u00f8bet af dagen. Ikke flere tal frosset kl. 8 om morgenen. Du ser din kaloriebalance live.<\/p><\/div><div class=\"fc\">Live<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">04<\/div><div><div class=\"ft\">NEAT p\u00e5 reelle skridt, uden koefficient<\/div><p class=\"fd\">Dine skridt, m\u00e5lt af din telefon, fodrer direkte TDEE-beregningen hver dag. Ingen boks stillesiddende eller aktiv at krydse af, nogensinde.<\/p><\/div><div class=\"fc\">NEAT<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">05<\/div><div><div class=\"ft\">TEF beregnet p\u00e5 dine makroer<\/div><p class=\"fd\">Ford\u00f8jelsen er ikke en fast sats p\u00e5 10&nbsp;%. Protein 20 til 30&nbsp;%, kulhydrater 5 til 10&nbsp;%, fedt 1 til 3&nbsp;%. Lean laver beregningen ved hvert m\u00e5ltid og integrerer den i TDEE.<\/p><\/div><div class=\"fc\">TEF<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">06<\/div><div><div class=\"ft\">Komplet historik og tendenser<\/div><p class=\"fd\">F\u00f8lg dine tendenser for v\u00e6gt, fedtprocent og fedtfri masse over m\u00e5neder. Forst\u00e5 dine cyklusser. Find faserne, hvor du g\u00f8r fremskridt, og dem, hvor du stagnerer.<\/p><\/div><div class=\"fc\">Historik<\/div><\/div>\n  <\/div>\n\n  <p style=\"margin-top:26px\">Du installerer appen gratis, du tester uden binding, og du beslutter derefter, om v\u00e6rkt\u00f8jet passer til dit m\u00e5l.<\/p>\n<\/section>\n\n<section aria-labelledby=\"faq-h\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">11 &middot; FAQ<\/span><\/div>\n  <h2 id=\"faq-h\">Ofte stillede sp\u00f8rgsm\u00e5l<\/h2>\n  <div class=\"faq\">\n    <details><summary>Foodvisor opfandt fotoscanning af m\u00e5ltider, hvorfor sammenligne den med Lean&nbsp;?<\/summary><div class=\"ans\">Fordi en trackers l\u00f8fte ikke stopper ved tallerkenen. Foodvisor er den historiske reference for fotogenkendelse i Frankrig, men dens kaloriem\u00e5l bygger p\u00e5 en populationsformel (Mifflin-St Jeor 1990, uden m\u00e5lt fedtprocent) og en statisk aktivitetsmultiplikator valgt ved tilmeldingen. Det er to halvdele af samme problem&nbsp;: Foodvisor er fremragende p\u00e5 det, der kommer ind, Lean p\u00e5 det, der forbruges.<\/div><\/details>\n    <details><summary>Hvorfor beregner Foodvisor ikke BMR p\u00e5 reel fedtprocent&nbsp;?<\/summary><div class=\"ans\">Fordi ingen fedtprocentm\u00e5ling findes i appen, og populationsformlerne kun bruger v\u00e6gt, h\u00f8jde, alder og k\u00f8n. Lean integrerer AI BodyScan til at m\u00e5le din fedtprocent fra et simpelt foto, gentaget hver uge, hvilket giver en BMR baseret p\u00e5 den reelle fedtfri masse via en patenteret egenudviklet model.<\/div><\/details>\n    <details><summary>Er Leans fotoscanning lige s\u00e5 god som Foodvisors&nbsp;?<\/summary><div class=\"ans\">Foodvisor beholder forspringet og \u00e5rs tr\u00e6ning i tallerkengenkendelse, is\u00e6r i estimering af portioner. Leans AI-fotoscanning identificerer f\u00f8devarer, kalorier og makroer med sammenlignelig pr\u00e6cision til daglig brug, og den er ubegr\u00e6nset. P\u00e5 det kriterium g\u00f8r begge jobbet. Den reelle forskel mellem de to apps afg\u00f8res p\u00e5 beregningen af forbruget.<\/div><\/details>\n    <details><summary>Foodvisor t\u00e6ller mine skridt, er det nok til NEAT&nbsp;?<\/summary><div class=\"ans\">At t\u00e6lle skridt og at integrere dem i beregningen er to forskellige ting. Hos Foodvisor hviler kaloriem\u00e5let stadig p\u00e5 den statiske aktivitetsmultiplikator valgt ved tilmeldingen. Lean beregner NEAT direkte ud fra de reelle skridt m\u00e5lt hver dag, uden koefficient at v\u00e6lge, og adskiller den ordentligt fra sportsforbruget (EAT).<\/div><\/details>\n    <details><summary>Er Lean gratis eller betalt&nbsp;?<\/summary><div class=\"ans\">Lean er Premium med 7 dages gratis pr\u00f8veperiode p\u00e5 \u00e5rsabonnementet. Du downloader, du tester AI BodyScan, AI-fotoscanning af en ret, TDEE-rekomposition, uden binding. Passer v\u00e6rkt\u00f8jet til dit m\u00e5l, forts\u00e6tter du. Ellers sl\u00e5r du fornyelsen fra, f\u00f8r pr\u00f8veperioden udl\u00f8ber.<\/div><\/details>\n    <details><summary>Kan man bruge Lean og Foodvisor parallelt&nbsp;?<\/summary><div class=\"ans\">Ja, is\u00e6r i overgangen. Nogle beholder Foodvisor til coachingen med en di\u00e6tist og bruger Lean dagligt til TDEE, rekomposition og tracking. Indsatsen med dobbelt indtastning er reel&nbsp;: p\u00e5 sigt v\u00e6lger de fleste den app, der styrer deres kaloriem\u00e5l, og det er pr\u00e6cis det omr\u00e5de, hvor Lean er bygget til at v\u00e6re mest pr\u00e6cis.<\/div><\/details>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"conclu\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">12 &middot; Konklusion<\/span><\/div>\n  <h2 id=\"conclu\">Tallerkenen er p\u00e5 plads. Forbruget er det ikke.<\/h2>\n  <p>Det er ikke Foodvisor over for Lean i markedsf\u00f8ring. Det er input over for output, to halvdele af samme ligning.<\/p>\n  <p>Foodvisor har l\u00f8st den venstre halvdel&nbsp;: at vide, hvad du spiser, uden v\u00e6gt, takket v\u00e6re den mest indarbejdede fotoscanning p\u00e5 det franske marked. Men til den h\u00f8jre halvdel, dit forbrug, bygger Foodvisor p\u00e5 en populationsformel fra 1990 uden m\u00e5lt fedtprocent, en fastl\u00e5st aktivitetsmultiplikator, du krydser af \u00e9n enkelt gang ved tilmeldingen, og ingen metabolisk tilpasning. Kombinationen af de tre g\u00f8r enhver pr\u00e6cis kalorieopf\u00f8lgning umulig ud over nogle f\u00e5 ugers cut. Det er matematik.<\/p>\n  <p>Lean er bygget til den halvdel&nbsp;: BMR baseret p\u00e5 <a class=\"inline\" href=\"https:\/\/lean-app.com\/da\/depense-energetique-totale-v2\/\">reelle fedtprocent<\/a> (m\u00e5lt med AI BodyScan) via en patenteret egenudviklet model, <a class=\"inline\" href=\"https:\/\/lean-app.com\/da\/neat-depense-non-sportive\/\">NEAT fra reelle skridt<\/a>, EAT per sport og MET, <a class=\"inline\" href=\"https:\/\/lean-app.com\/da\/effet-thermique-des-aliments\/\">TEF fra makroer<\/a>, plus den metaboliske tilpasning, der modulerer BMR uge efter uge. Hver komponent beregnet pr\u00e6cist, uden magisk koefficient. Og den fotorefleks, du fik hos Foodvisor, beholder du&nbsp;: AI-fotoscanning er integreret, ubegr\u00e6nset.<\/p>\n  <p>Har du pr\u00f8vet Foodvisor seri\u00f8st og ikke f\u00e5et de resultater, du h\u00e5bede p\u00e5 i dit cut, er problemet ikke dig, og heller ikke fotoet. Problemet er den frosne TDEE under motorhjelmen. Skift motoren, behold refleksen.<\/p>\n<\/section>\n\n<div class=\"get-band rev\" style=\"background:#F1E9DC;border-radius:24px;padding:48px 36px;margin:60px 0 40px;text-align:center\">\n  <div class=\"kicker\">Download<\/div>\n  <h3>Lean kan downloades gratis<\/h3>\n  <p>iOS og Android. AI BodyScan fungerer med et simpelt foto. Ingen hudfoldsm\u00e5ler, ingen impedansv\u00e6gt, ingen DEXA.<\/p>\n  <div class=\"stores\" style=\"display:flex;gap:10px;align-items:center;flex-wrap:wrap\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-foodvisor\" target=\"_blank\" rel=\"noopener\" aria-label=\"Download Lean i 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\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/>\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=vs-foodvisor\" target=\"_blank\" rel=\"noopener\" aria-label=\"Download Lean p\u00e5 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\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/>\n    <\/a>\n  <\/div>\n<\/div>\n\n<section aria-labelledby=\"links\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">G\u00e5 videre<\/span><\/div>\n  <h3 id=\"links\" style=\"margin-top:0\">Intern linkning<\/h3>\n  <ul>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/da\/tdee-calculator\/\">Gratis TDEE-beregner online<\/a> &middot; webversion, uden tilmelding, samme logik som appen (BMR + NEAT + EAT + TEF).<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/da\/depense-energetique-totale-v2\/\">Forst\u00e5 TDEE i detaljer (BMR, NEAT, EAT, TEF, tilpasning)<\/a> &middot; dybdeg\u00e5ende videnskabelig artikel.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/da\/comment-compter-ses-calories\/\">S\u00e5dan t\u00e6ller du dine kalorier korrekt<\/a> &middot; praktisk guide for begyndere.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/da\/neat-depense-non-sportive\/\">NEAT&nbsp;: forbrug per skridt og aktivitet uden for sport<\/a>.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/da\/effet-thermique-des-aliments\/\">TEF&nbsp;: ford\u00f8jelsen forbr\u00e6nder kalorier<\/a>.<\/li>\n  <\/ul>\n<\/section>\n\n<section aria-labelledby=\"src\" class=\"sources\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">Kilder<\/span><\/div>\n  <h3 id=\"src\" style=\"margin-top:0;color:var(--ink)\">Bibliografi<\/h3>\n  <ol>\n    <li>Harris J.A., Benedict F.G. (1919). A Biometric Study of Basal Metabolism in Man. Carnegie Institution of Washington.<\/li>\n    <li>Mifflin M.D., St Jeor S.T. et al. (1990). A new predictive equation for resting energy expenditure in healthy individuals. American Journal of Clinical Nutrition. <a class=\"inline\" href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/2305711\/\" target=\"_blank\" rel=\"noopener\">PubMed 2305711<\/a>.<\/li>\n    <li>Frankenfield D.C. (2013). Bias and accuracy of resting metabolic rate equations in non-obese and obese adults. Clinical Nutrition. <a class=\"inline\" href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/23631843\/\" target=\"_blank\" rel=\"noopener\">PubMed 23631843<\/a>.<\/li>\n    <li>Westerterp K.R. (2004). Diet induced thermogenesis. Nutrition &amp; Metabolism. <a class=\"inline\" href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/15507147\/\" target=\"_blank\" rel=\"noopener\">PubMed 15507147<\/a>.<\/li>\n    <li>M\u00fcller M.J. et al. (2015). Metabolic adaptation to caloric restriction and subsequent refeeding: the Minnesota Starvation Experiment revisited. American Journal of Clinical Nutrition. <a class=\"inline\" href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/26399868\/\" target=\"_blank\" rel=\"noopener\">PubMed 26399868<\/a>.<\/li>\n    <li>Doucet E. et al. (2001). Evidence for the existence of adaptive thermogenesis during weight loss. British Journal of Nutrition. <a class=\"inline\" href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/11430776\/\" target=\"_blank\" rel=\"noopener\">PubMed 11430776<\/a>.<\/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>Artikel publiceret 15. august 2026. Opdateres regelm\u00e6ssigt med brugerfeedback og nye relevante studier. Lean f\u00e5s til iOS og Android.<\/p>\n      <\/div>\n      <div class=\"stores\" style=\"display:flex;gap:10px;align-items:center;flex-wrap:wrap\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-foodvisor\" 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\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/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=vs-foodvisor\" 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\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n      <\/div>\n    <\/div>\n  <\/div>\n<\/footer>\n\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\n(function(){\n  var phoneImg = document.getElementById('phoneImg');\n  var phoneBack = document.getElementById('phoneBack');\n  var zones = document.getElementById('phoneZones');\n  var topTabs = document.querySelectorAll('.phone-tabs button');\n  var navTaps = document.querySelectorAll('.phone-navbar button');\n\n  var tabMap = {\n    bilan:    {drill:false},\n    kcal:     {drill:false},\n    depense:  {drill:true},\n    strategie:{drill:false}\n  };\n  var subMap = {BMR:1, NEAT:1, EAT:1, TEF:1};\n  var currentTab = 'depense';\n\n  function setActive(tab){\n    topTabs.forEach(function(b){ b.classList.toggle('on', b.dataset.tab===tab); });\n  }\n  function showTab(tab){\n    var t = tabMap[tab]; if(!t) return;\n    currentTab = tab;\n    phoneImg.style.opacity = 0;\n    setTimeout(function(){\n      phoneImg.className = 'phone-bg tab-' + tab;\n      phoneImg.style.opacity = 1;\n      zones.style.display = t.drill ? 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style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Definition, TDEE-ligning, 4 historiske formler, hvorfor fedtprocenten \u00e6ndrer alt.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/da\/depense-energetique-totale-v2\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Samlet energiforbrug (TDEE): den kanoniske formel BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Forst\u00e5 de 4 byggesten + den metaboliske tilpasning, videnskabelige kilder 2025.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/da\/comparatifs-croises\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">MyFitnessPal eller Yazio? 12 dueller mellem kalorie-apps sammenlignet <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Dommen i hver duel med \u00e9t blik&nbsp;: hvem vinder p\u00e5 hvad, og det, ingen af de to beregner.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/da\/meilleures-applications-calories-2026\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">De bedste apps til at t\u00e6lle kalorier i 2026: 8 apps testet <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Lean, MFP, Cronometer, Yazio, Lifesum, FatSecret, Noom, Foodvisor.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/da\/alternative-myfitnesspal\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Hvilket alternativ til MyFitnessPal i 2026? 5 apps testet <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">\u00c6rlig sammenligning, TDEE-pr\u00e6cision, ergonomi.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/da\/comparatifs\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Alle Lean-sammenligninger over for de store kalorie-apps <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Hub: MyFitnessPal, Yazio, Cronometer, Lifesum, FatSecret, Noom.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/da\/lean-vs-myfitnesspal\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean over for MyFitnessPal: TDEE-formlen, der \u00e6ndrer alt <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Hvorfor MFP tager fejl af dit reelle kalorieforbrug.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/da\/calculateur-tdee\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">TDEE-beregner: den kanoniske formel BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Fedtprocentbevidst beregner med opdeling af de 4 metaboliske byggesten.<\/span><\/a><\/li><\/ul><\/aside>","protected":false},"excerpt":{"rendered":"<p>Lean Calculateur TDEE Accueil &nbsp;\/&nbsp; Lean vs Foodvisor Comparatif &middot; Nutrition &amp; TDEE Lean vs Foodvisor. Le pionnier du scan photo face au seul qui recompose ton TDEE en continu. Foodvisor voit ton assiette. Lean voit ta d\u00e9pense r\u00e9elle. Deux IA, deux moiti\u00e9s du probl\u00e8me. L&rsquo;\u00e9quipe Lean &middot; Lecture 12&nbsp;min &middot; Mis \u00e0 jour 15 [&hellip;]<\/p>","protected":false},"author":1,"featured_media":1763,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-lvm-blank","format":"standard","meta":{"footnotes":""},"categories":[13],"tags":[],"class_list":["post-1760","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-comparateurs"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Lean vs Foodvisor: AI-fotoscanning over for dit reelle forbrug<\/title>\n<meta name=\"description\" content=\"Foodvisor opfandt fotoscanning af m\u00e5ltider. Men dit forbrug er stadig en formel fra 1990 uden fedtprocent. 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