{"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":"2026-09-05T10:54:09","modified_gmt":"2026-09-05T10:54:09","slug":"lean-vs-foodvisor","status":"publish","type":"post","link":"https:\/\/lean-app.com\/nl\/lean-vs-foodvisor\/","title":{"rendered":"Lean vs Foodvisor: AI-fotoscan tegenover je echte verbruik"},"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\/nl\/\" aria-label=\"Accueil Lean\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/>\n      <span>Lean<\/span>\n    <\/a>\n    <span class=\"nav-spacer\"><\/span>\n    <a class=\"nav-link\" href=\"https:\/\/lean-app.com\/nl\/tdee-calculator\/\">TDEE-calculator<\/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=\"T\u00e9l\u00e9charger sur l'App Store\">\n        <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" 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=\"Disponible sur Google Play\">\n        <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" 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\/nl\/\">Home<\/a> &nbsp;\/&nbsp; Lean vs Foodvisor<\/div>\n  <div class=\"eyebrow\">Vergelijking &middot; Voeding &amp; TDEE<\/div>\n  <h1 id=\"title\">Lean vs Foodvisor.\n    <span class=\"alt\">De pionier van de fotoscan tegenover de enige die je TDEE continu opnieuw samenstelt.<\/span>\n  <\/h1>\n  <p class=\"dek\">Foodvisor ziet je bord. Lean ziet je echte verbruik. Twee AI&rsquo;s, twee helften van het probleem.<\/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>Het Lean-team<\/strong> &middot; Leestijd 12&nbsp;min &middot; Bijgewerkt op 15 augustus 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 is de Franse pionier van de fotoscan van maaltijden: je fotografeert je bord, de AI herkent de voedingsmiddelen en schat de porties. Op die helft van het probleem is de eer verdiend. Maar de andere helft, je verbruik, blijft er een populatieformule (Mifflin-St Jeor 1990), plus een statische activiteitsvermenigvuldiger die je \u00e9\u00e9n keer kiest bij de inschrijving. Zonder gemeten echt vetpercentage, zonder metabole adaptatie. Het duel Lean vs Foodvisor gaat dus niet over de foto: het gaat over wat de app met het cijfer doet, over 3 maanden serieuze 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>Interactieve demo<\/small>Tik op het scherm om de app te verkennen<\/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>Interactieve demo<\/small>Tik op het scherm<br>om de app te verkennen<\/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=\"Aper\u00e7u de l'application Lean avec drilldown du TDEE\">\n          <div class=\"notch\"><\/div>\n          <div class=\"phone-screen\">\n            <button class=\"phone-back\" id=\"phoneBack\" aria-label=\"Terug\">&#8249;<\/button>\n            <div id=\"phoneImg\" class=\"phone-bg tab-depense\" role=\"img\" aria-label=\"Aper\u00e7u Lean, onglet D\u00e9pense\"><\/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=\"D\u00e9tail BMR\"><\/div>\n              <div class=\"z\" data-sub=\"NEAT\" style=\"top:33%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"D\u00e9tail NEAT\"><\/div>\n              <div class=\"z\" data-sub=\"EAT\"  style=\"top:50%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"D\u00e9tail EAT\"><\/div>\n              <div class=\"z\" data-sub=\"TEF\"  style=\"top:67%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"D\u00e9tail TEF\"><\/div>\n            <\/div>\n            <div class=\"phone-navbar\" id=\"phoneNav\" aria-hidden=\"false\">\n              <button data-tab=\"bilan\"     type=\"button\" aria-label=\"Onglet Bilan\"><\/button>\n              <button data-tab=\"kcal\"      type=\"button\" aria-label=\"Onglet Calories\"><\/button>\n              <button data-tab=\"depense\"   type=\"button\" aria-label=\"Tabblad Verbruik\"><\/button>\n              <button data-tab=\"strategie\" type=\"button\" aria-label=\"Onglet Strat\u00e9gie\"><\/button>\n            <\/div>\n          <\/div>\n        <\/div>\n        <div class=\"phone-tabs\" role=\"tablist\" aria-label=\"Naviguer dans l'app Lean\">\n          <button data-tab=\"bilan\"     type=\"button\">Balans<\/button>\n          <button data-tab=\"kcal\"      type=\"button\">Calorie\u00ebn<\/button>\n          <button data-tab=\"depense\"   type=\"button\" class=\"on\">Verbruik<\/button>\n          <button data-tab=\"strategie\" type=\"button\">Strategie<\/button>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"snippet rev\">\n    <div class=\"lbl\">Snel antwoord<\/div>\n    <p>Foodvisor heeft de fotoscan van maaltijden in Frankrijk uitgevonden en blijft een referentie om te identificeren wat je eet: foto, herkenning van voedingsmiddelen, schatting van porties. Aan de verbruikskant daarentegen steunt Foodvisor op een populatieformule (Mifflin-St Jeor 1990, zonder gemeten vetpercentage) en een statische activiteitsvermenigvuldiger gekozen bij de inschrijving. Lean pakt het probleem in de andere richting aan: elk onderdeel van de TDEE herberekenen (<span data-term=\"BMR\">BMR<span class=\"tt\">Basal Metabolic Rate. Energie verbruikt in rust. Bij Lean berekend op de echte vetvrije massa via AI BodyScan.<\/span><\/span> op echt vetpercentage via een gepatenteerd eigen model, <span data-term=\"NEAT\">NEAT<span class=\"tt\">Non-Exercise Activity Thermogenesis. Verbruik door stappen en dagelijkse activiteiten buiten de sport.<\/span><\/span> per stappen, <span data-term=\"EAT\">EAT<span class=\"tt\">Exercise Activity Thermogenesis. Verbruik door je trainingen, berekend via MET.<\/span><\/span> per MET, <span data-term=\"TEF\">TEF<span class=\"tt\">Thermic Effect of Food. Energie verbruikt door de vertering. Hangt af van de ingenomen macro&rsquo;s.<\/span><\/span> op macro&rsquo;s) en de BMR continu te moduleren met de metabole adaptatie, zonder co\u00ebffici\u00ebnt om te kiezen.<\/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; De vaststelling<\/span><\/div>\n  <h2 id=\"constat\">Foodvisor ziet je bord, niet je echte verbruik<\/h2>\n  <p>Als je dit leest, heb je Foodvisor waarschijnlijk al ge\u00efnstalleerd. Je hebt het precies gekozen voor wat niemand v\u00f3\u00f3r hem deed: je bord fotograferen en de AI de kip, de rijst, de saus laten herkennen en de porties laten schatten zonder de weegschaal erbij te halen. Je hebt je gewicht, lengte, leeftijd en geslacht ingevuld, en je activiteitsniveau gekozen uit een statische lijst. De app toonde je een caloriedoel, zeg 2&nbsp;250&nbsp;kcal om af te vallen.<\/p>\n  <p>Je hebt het spel meegespeeld. Je hebt je maaltijden gescand, de porties gecorrigeerd als de AI twijfelde, dag na dag een nette invoer bijgehouden. De eerste 6 weken werkt het. Je verliest. Je bent blij. Dan, rond week 8, bevriest de weegschaal. Je trekt de teugels aan. Je gaat naar 2&nbsp;000&nbsp;kcal. Opnieuw beweegt er niets.<\/p>\n\n  <div class=\"statement\">\n    <div class=\"num\">&minus;10 tot &minus;15&nbsp;%<\/div>\n    <div class=\"lbl\">gemeten daling van de TDEE na 4 tot 6 weken tekort op &minus;500&nbsp;kcal\/dag. Foodvisor detecteert het niet. Je caloriedoel blijft bevroren op je activiteitsniveau van 100&nbsp;dagen geleden.<\/div>\n  <\/div>\n\n  <p>Stel dat Foodvisor je een TDEE van 2&nbsp;500&nbsp;kcal toont. Je eet 2&nbsp;250 (theoretisch tekort van 250&nbsp;kcal). Maar in werkelijkheid is je <a class=\"inline\" href=\"https:\/\/lean-app.com\/nl\/depense-energetique-totale-v2\/\">TDEE is gezakt naar 2&nbsp;200&nbsp;kcal<\/a> door de metabole adaptatie. Je zit in een overschot van 50&nbsp;kcal zonder het te weten. Geen enkele kans om te blijven verliezen, zelfs met de netste invoer op de markt.<\/p>\n  <p>De belofte van Foodvisor is duidelijk en wordt waargemaakt: je weet wat er op je bord ligt zonder iets te wegen. Dat is waardevol. Wat Foodvisor niet doet, is <a class=\"inline\" href=\"https:\/\/lean-app.com\/nl\/comment-compter-ses-calories\/\">je verbruik herberekenen<\/a> in de loop van de weken in tekort. En precies daar stopt de belofte, terwijl dat de hefboom is die gewicht doet verliezen.<\/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; Probleem 1<\/span><\/div>\n  <h2 id=\"p1\">De BMR-formule uit 1990, zonder gemeten vetpercentage<\/h2>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figuur 1 &middot; Man 1m80, 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=\"Comparaison BMR Mifflin-St Jeor 2500 kcal vs mod\u00e8le propri\u00e9taire brevet\u00e9 Lean 2000 kcal, \u00e9cart de 500 kcal\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>Geschatte BMR.<\/strong> Het gepatenteerde eigen model van Lean houdt rekening met de vetvrije massa. Mifflin-St Jeor (populatieformule, zonder vetpercentage) niet. Verschil van 500&nbsp;kcal, het equivalent van een hele lunch.<\/p>\n  <\/div>\n\n  <p>Om je basaal metabolisme te berekenen (de BMR, de energie die je in rust verbrandt), vertrekt Foodvisor van je profiel: gewicht, lengte, leeftijd, geslacht. Dat is de logica van bijna alle consumentencalorietrackers, ge\u00ebrfd van populatieformules zoals Mifflin-St Jeor. En laten we eerlijk zijn: het is beter dan Harris-Benedict 1919, die andere apps nog gebruiken.<\/p>\n  <p>Mifflin-St Jeor, dat is 1990 (PubMed 2305711). De steekproef is groot (498 proefpersonen), de methodologie van indirecte calorimetrie is serieus, de formule is gekalibreerd op een moderne populatie: 10 \u00d7 gewicht (kg) + 6,25 \u00d7 lengte (cm) \u2212 5 \u00d7 leeftijd \u2212 161 (vrouwen) of +5 (mannen).<\/p>\n  <p>Het probleem is niet de gekozen formule. Het probleem is wat geen enkele formule van dit type kan zien: <strong>ze houdt alleen rekening met het gewicht. Niet met het vetpercentage. Niet met de vetvrije massa.<\/strong> Geen enkel veld in de onboarding van Foodvisor vraagt je vetpercentage, en er bestaat geen meting in de app.<\/p>\n  <p>Sinds de jaren 80 weten we echter dat <strong>vetmassa heel weinig energie verbruikt<\/strong> vergeleken met de rest van het lichaam. De lever, de hersenen, het hart, de nieren en vooral de spieren zijn de echte verbruikers. Vetmassa is inert. Iemand met 30&nbsp;% vet verbrandt lang niet zoveel als iemand met 10&nbsp;% vet, zelfs bij gelijk gewicht.<\/p>\n  <p>Frankenfield 2013 (PubMed 23631843) vergeleek Mifflin-St Jeor met de referentie van indirecte calorimetrie bij obese en niet-obese cohorten. Resultaat: 87&nbsp;% nauwkeurigheid bij niet-obese personen, en slechts <strong>75&nbsp;% bij obese personen<\/strong>. Een recentere studie (PMC11820646) toont dat Mifflin bij een BMI boven 35 er <strong>250 tot 315&nbsp;kcal per dag<\/strong>naast zit. Dat is het equivalent van een hele snack in de berekening van een tekort.<\/p>\n  <p>500&nbsp;kcal is niet niks. Als de app je zegt \u00ab&nbsp;je BMR is 2&nbsp;500&nbsp;\u00bb en hij in werkelijkheid 2&nbsp;000 is, is alles wat volgt fout: je tekortdoel, je projectie van wekelijks verlies, je macroverdeling berekend als percentage van de TDEE. En geen enkele foto van een bord, hoe goed herkend ook, corrigeert een fout doel.<\/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\">Bodyfat r\u00e9el<strong>Foto, 5 seconden<\/strong><\/div>\n  <\/div>\n\n  <div class=\"statement\">\n    <div class=\"num\">400&nbsp;kcal<\/div>\n    <div class=\"lbl\">verschil tussen twee mannen van 80&nbsp;kg, de ene met 10&nbsp;% vet (BMR 1&nbsp;900), de andere met 30&nbsp;% (BMR 1&nbsp;500). Een gewichtsformule toont hun hetzelfde cijfer.<\/div>\n  <\/div>\n\n  <p>Tussentijdse conclusie: als een app je BMR uitsluitend berekent op basis van je gewicht, lengte, leeftijd en geslacht, kan het resultaat niet ge\u00efndividualiseerd zijn. Het is wiskundig onmogelijk. Zelfs met de beste bordherkenning aan de invoerkant.<\/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; Probleem 2<\/span><\/div>\n  <h2 id=\"p2\">De activiteitsvermenigvuldiger, eens en voor altijd gekozen<\/h2>\n  <p>Hier wordt het ernstig. En dit is waarschijnlijk het punt dat niemand je heeft uitgelegd.<\/p>\n  <p>Zodra je BMR is geschat, moet Foodvisor naar de totale TDEE. De <a class=\"inline\" href=\"https:\/\/lean-app.com\/nl\/depense-energetique-totale-v2\/\">TDEE is de BMR + al de rest<\/a> : het verbruik door stappen, dagelijkse activiteiten, sport en vertering. Alles wat geen basaal metabolisme is.<\/p>\n  <p>Hoe doet Foodvisor dat? Zoals bijna alle trackers: het vraagt je, bij de inschrijving, je activiteitsniveau te kiezen uit een statische lijst. Die factoren heten in de sportwetenschap <strong>PAL-niveaus<\/strong> (Physical Activity Level), en dat is gewoon een vermenigvuldiger toegepast op je BMR:<\/p>\n  <ul>\n    <li>Zittend (PAL 1,2): kantoor, weinig wandelen<\/li>\n    <li>Licht actief (PAL 1,375): af en toe wandelen<\/li>\n    <li>Actief (PAL 1,55): 3 tot 5 keer per week sport<\/li>\n    <li>Zeer actief (PAL 1,725): bijna dagelijks intensieve sport<\/li>\n    <li>Extreem actief (PAL 1,9): zeer intensieve sport of fysiek werk<\/li>\n  <\/ul>\n  <p>En afhankelijk van je keuze vermenigvuldigt de app je BMR met de bijbehorende co\u00ebffici\u00ebnt. Dat is alles. Dat is alles wat er achter je dagelijkse caloriedoel zit. Een vakje dat JIJ \u00e9\u00e9n keer hebt aangevinkt bij de inschrijving. Vaak zes maanden geleden. Sindsdien onveranderd.<\/p>\n  <p>En daar zit de stille valkuil: die benadering is <strong>hyper onvolmaakt<\/strong>. Het verschil tussen een dag waarop je aan de bank gekluisterd Netflix kijkt en een dag waarop je met je kinderen naar Disneyland gaat en 15&nbsp;km loopt, <strong>is meer dan 1&nbsp;000&nbsp;kcal<\/strong>. Geen van de 5 vakjes vangt dat.<\/p>\n  <p>Foodvisor kan je activiteit nochtans volgen: de app kan je stappen tellen en je trainingen registreren. Maar die gegevens dienen vooral om je activiteit te tonen, niet om een volledige TDEE opnieuw samen te stellen: je caloriedoel blijft rusten op de vermenigvuldiger gekozen bij de onboarding, en het sportverbruik wordt erbij opgeteld zonder dat NEAT en EAT netjes worden gescheiden.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figuur 2 &middot; 7 echte dagen<\/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=\"Variabilit\u00e9 quotidienne de la d\u00e9pense calorique sur 7 jours, contre 2400 kcal fixes selon Foodvisor\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>Echt verbruik<\/strong> gemeten over 7&nbsp;dagen bij een Lean-gebruiker. De groene lijn is wat Foodvisor toonde (2&nbsp;400&nbsp;kcal vast, statische vermenigvuldiger \u00d7 BMR). De roze annotaties tonen waarom elke dag beweegt.<\/p>\n  <\/div>\n\n  <p>Je kunt je activiteitsniveau niet herleiden tot een statisch vakje. Misschien ben je actief in de weken dat je weinig thuiswerkt, en zittend in de weken dat je het kantoor niet verlaat. Misschien ben je actief in de zomer en zittend in de winter. Misschien ben je actief van dinsdag tot vrijdag en zittend in het weekend.<\/p>\n  <p>Welk vakje ga je deze week aanvinken? De waarheid is dat geen van de 5 juist zal zijn. En dus geeft Foodvisor je een TDEE die systematisch losstaat van de realiteit.<\/p>\n  <p>Het kernpunt van dit artikel: zelfs met een perfecte BMR-formule zou de statische vermenigvuldiger volstaan om alles kapot te maken. Je kunt geen <a class=\"inline\" href=\"https:\/\/lean-app.com\/nl\/neat-depense-non-sportive\/\">NEAT<\/a>, een EAT en een <a class=\"inline\" href=\"https:\/\/lean-app.com\/nl\/effet-thermique-des-aliments\/\">TEF<\/a> met \u00e9\u00e9n vermenigvuldiger toegepast op de BMR. Dat is conceptueel absurd.<\/p>\n  <p>Je hebt het begrepen: <strong>een BMR-formule zonder vetpercentage, plus een statische benadering van al de rest, dat geeft heel weinig kans om je doelen over 3 tot 6 maanden te bereiken.<\/strong> Hoe net de invoer aan de bordkant ook is.<\/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\">Bekijk je echte TDEE, uitgesplitst in 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; Probleem 3<\/span><\/div>\n  <h2 id=\"p3\">De metabole adaptatie, nooit gemodelleerd<\/h2>\n  <p>Dit is de eindbaas. Het subtielste begrip. En waarschijnlijk het belangrijkste.<\/p>\n  <p>Als je in een calorietekort zit, begrijpt je lichaam dat het minder energie krijgt dan voorheen. Om zich te beschermen, schakelt het over op de spaarstand. Precies zoals de energiebesparingsmodus van je iPhone: alles blijft werken, maar met minder energie. Je BMR daalt. Je NEAT daalt. Je EAT daalt.<\/p>\n  <p>Dat noemen we metabole adaptatie. De wetenschappelijke literatuur is duidelijk en reproduceerbaar: M\u00fcller 2015 (PubMed 26399868, herziening Minnesota), Doucet 2001 (PubMed 11430776), Nunes 2020 (PMC7484122) over 6 weken tekort. Dit zijn de cijfers:<\/p>\n  <ul>\n    <li>Tekort van &minus;250&nbsp;kcal per dag, gedurende 2 tot 8 weken: adaptatie van <strong>5 tot 10&nbsp;%<\/strong> (TDEE zakt naar 90-95&nbsp;% van het beginniveau)<\/li>\n    <li>Tekort van &minus;500&nbsp;kcal per dag: <strong>10 tot 15&nbsp;%<\/strong> adaptatie (TDEE zakt naar 85-90&nbsp;%)<\/li>\n    <li>Tekort van &minus;750&nbsp;kcal per dag: <strong>15 tot 25&nbsp;%<\/strong> adaptatie (TDEE zakt naar 75-85&nbsp;%)<\/li>\n  <\/ul>\n  <p>Lean-conventie: 100&nbsp;% = optimaal, 90&nbsp;% = 10&nbsp;% adaptatie. En omdat NEAT, EAT en TEF allemaal rechtstreeks afhangen van de BMR, wordt bijna de hele TDEE be\u00efnvloed.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figuur 3 &middot; 8 weken in tekort<\/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 qui chute de 2500 \u00e0 2150 kcal sur 8 semaines, contre 2500 fixe selon Foodvisor\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>Echte TDEE<\/strong> over 8 weken tekort op &minus;500&nbsp;kcal\/dag. De roze curve daalt. De Foodvisor-lijn blijft vlak. In week 6 zit je al op onderhoud. Zonder iets te hebben veranderd.<\/p>\n  <\/div>\n\n  <p>Concreet: als je een tekort van 10&nbsp;% had gepland op een TDEE van 2&nbsp;500 (dus 2&nbsp;250 per dag eten), en je lichaam past zich 10&nbsp;% aan, dan is je echte TDEE gezakt naar 2&nbsp;250. Je zit op onderhoud. Je verliest niet meer.<\/p>\n  <p>De valkuil is dat het sluipend gaat. In het begin verlies je. Je bent blij. Je gaat door. Maar week na week stapelt de adaptatie zich op. En op een gegeven moment, zonder iets aan je tracking te hebben veranderd, <strong>stop je met verliezen<\/strong>.<\/p>\n  <p>95&nbsp;% van de mensen maakt dit mee zonder het te begrijpen. Ze geven hun wilskracht de schuld. Ze wijten het aan hun \u00ab&nbsp;kapotte metabolisme&nbsp;\u00bb. Ze beginnen aan strengere di\u00ebten, wat de adaptatie verergert. Spiraal.<\/p>\n  <p>Foodvisor berekent de metabole adaptatie nooit. Het geeft je een vast caloriedoel zolang je je gewicht en je activiteitsniveau niet handmatig bijwerkt. Je kunt je borden met voorbeeldige regelmaat scannen, maar als je na 6 weken cut stagneert, heeft de app geen idee waarom.<\/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-oplossing<\/span><\/div>\n  <h2 id=\"solution\">Hoe Lean elk van de 3 problemen oplost<\/h2>\n  <p>Foodvisor heeft een standaard gezet voor de fotoscan van een gerecht, en zijn herkenning van de Franse keuken blijft uitstekend. Het probleem is niet wat het op je bord ziet, het is wat het van je lichaam niet ziet: het verbruik blijft geschat door een populatieformule vermenigvuldigd met een activiteitsniveau. Lean doet beide: AI-fotoscan <em>en<\/em> meting van elk onderdeel van de TDEE (BMR&nbsp;+&nbsp;NEAT&nbsp;+&nbsp;EAT&nbsp;+&nbsp;TEF) plus de metabole adaptatie. Dit zijn de details.<\/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\">Stap 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\">Stap 2<strong>BMR herberekend<\/strong><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n    <div>\n      <div class=\"m-tag\">De BMR op echt vetpercentage<\/div>\n      <h3>Gepatenteerd eigen model, gebaseerd op vetvrije massa<\/h3>\n      <p>Perfect de binnenkomende calorie\u00ebn tellen heeft geen zin als de uitgaande calorie\u00ebn er 300&nbsp;kcal naast zitten. Lean berekent het metabolisme op je <strong>masse maigre<\/strong>, de enige die in rust echt verbruikt, en niet op je ruwe gewicht.<\/p>\n      <p>Le <strong>AI BodyScan<\/strong> past op je lichaam toe wat Foodvisor op je bord toepast: een foto, een model getraind op een bank van DEXA-scans, je vetpercentage in enkele seconden, wekelijks te herhalen.<\/p>\n      <p>Geen huidplooimeter, geen impedantieweegschaal, geen DEXA. Dezelfde eenvoud als een maaltijdscan, toegepast op je lichaamssamenstelling.<\/p>\n    <\/div>\n  <\/div>\n\n  <div class=\"method flip\">\n    <div>\n      <div class=\"m-tag\">Geen activiteitsco\u00ebffici\u00ebnt<\/div>\n      <h3>NEAT, EAT, TEF apart berekend<\/h3>\n      <p><strong>NEAT.<\/strong> Je echte stappen komen binnen via HealthKit (iOS) of Google Fit (Android) en worden calorie\u00ebn volgens je metabolisme. Het is de meest variabele post van de dag, en die welke een opgegeven activiteitsniveau volledig afvlakt.<\/p>\n      <p><strong>EAT.<\/strong> Elke training wordt berekend per MET op je echte inspanningstijd, rusttijden uitgesloten. Een uur krachttraining als een uur hardlopen tellen vervalst de balans met honderden kcal per week.<\/p>\n      <p><strong>TEF.<\/strong> Foodvisor identificeert je voedingsmiddelen, Lean haalt er de verteringskost uit: 20 tot 30&nbsp;% van de calorie\u00ebn voor eiwitten, 5 tot 10&nbsp;% voor koolhydraten, 1 tot 3&nbsp;% voor vetten, in plaats van het forfait van 10&nbsp;% dat overal wordt toegepast.<\/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\">Automatische metabole adaptatie<\/div>\n      <h3>Een wereldprimeur in een consumentenapp<\/h3>\n      <p><strong>De metabole adaptatie.<\/strong> Geen enkele maaltijdscan detecteert dat je metabolisme na acht weken 12&nbsp;% is vertraagd. Lean schat het volgens de gepubliceerde marges (M\u00fcller 2015, Doucet 2001) en corrigeert je doel dienovereenkomstig.<\/p>\n      <p>Voorbij 10 tot 15&nbsp;% adaptatie kan de app een terugkeer naar onderhoud aanraden om het metabolisme opnieuw op gang te brengen voordat je verdergaat.<\/p>\n      <p>Geen activiteitsvermenigvuldiger om te kiezen. Elk onderdeel wordt gemeten, week na week.<\/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\">Methode<strong>Metabole adaptatie<\/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; Vergelijkende tabel<\/span><\/div>\n  <h2 id=\"tab\">Lean tegenover Foodvisor, criterium per criterium<\/h2>\n  <p>Eerlijke lezing van de sterke en zwakke punten van elke app. Geen enkel criterium gaat over de prijs.<\/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=\"Vergelijking Lean tegenover Foodvisor\">\n    <div class=\"table-row head\" role=\"row\">\n      <div role=\"columnheader\">Criterium<\/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-formule<\/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> Gepatenteerd eigen model (vetvrije massa)<\/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> Populatieformule (Mifflin-St Jeor 1990)<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Houdt rekening met vetpercentage<\/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, gemeten in de app<\/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> Nee, alleen gewicht-lengte-leeftijd-geslacht<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Meting van het vetpercentage in de 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> 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> Nee<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">NEAT (stappen, activiteit buiten de 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> Elke dag berekend op echte stappen<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Stappen gevolgd, maar doel rust op de statische vermenigvuldiger<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">EAT (verbruik door inspanning)<\/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, effectieve tijd<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Trainingen geregistreerd, opgeteld bij een bevroren doel<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">TEF (vertering)<\/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> Berekend op basis van macro&rsquo;s, ge\u00efntegreerd in de 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> Niet ge\u00efntegreerd in de verbruiksberekening<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Metabole adaptatie<\/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> Automatisch, week na week<\/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> Nee<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Activiteitsco\u00ebffici\u00ebnt te kiezen<\/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> Nee, berekend op echte gegevens<\/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, statische vermenigvuldiger gekozen bij de inschrijving<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">AI-fotoscan van een gerecht<\/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, onbeperkt<\/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, de historische pionier (2018)<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Visuele herkenning van voedingsmiddelen<\/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-fotoscan<\/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> Referentie van de FR-markt, jaren training<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Barcodescan<\/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\">Voedingsdatabase<\/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, gecureerd<\/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> Brede database, Franse producten goed gedekt<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Coaching door di\u00ebtisten<\/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> Buiten scope, de app begeleidt via de Progressiepiramide<\/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, gediplomeerde di\u00ebtisten (apart aanbod)<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Aanbeveling calorietekort<\/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> Aangepast aan de echte 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> Vast doel, handmatige herberekening vereist<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Franse 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, geboren in Parijs<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Reputatie en grootte van het publiek<\/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+ gebruikers, jonge 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> Erkende pionier van de fotoscan, grote bekendheid in Frankrijk<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Bedrijfsmodel<\/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 dagen gratis proberen op het jaarabonnement<\/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 versie, coaching optioneel<\/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 methodes om een maaltijd te tracken<\/h2>\n  <p>Foodvisor heeft bewezen dat een foto handmatige invoer kon vervangen. Lean neemt dat idee over en verbreedt het: drie registratiemethodes naargelang de context, om op de lange termijn vol te houden.<\/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\">Methode 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\">Methode 2<strong>Barcode<\/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\">Methode 3<strong>AI-fotoscan<\/strong><\/div>\n    <\/div>\n  <\/div>\n\n  <ol>\n    <li><strong>Zoeken in de database.<\/strong> Gecureerde database, USDA + OpenFoodFacts. Geen communityruis, geen \u00ab&nbsp;Gebraden kip&nbsp;\u00bb 47 keer ingevoerd door 47 verschillende gebruikers met 47 verschillende waarden.<\/li>\n    <li><strong>Barcodescan.<\/strong> Standaard. Je scant je pak pasta, je krijgt de macro&rsquo;s.<\/li>\n    <li><strong>AI-fotoscan van een gerecht.<\/strong> Je fotografeert je bord, de AI herkent de voedingsmiddelen, je krijgt de calorie\u00ebn en macro&rsquo;s per voedingsmiddel. De reflex die je al hebt als je van Foodvisor komt: die houd je gewoon.<\/li>\n  <\/ol>\n  <p>De AI-fotoscan van Lean speelt dezelfde rol als die van Foodvisor voor maaltijden buitenshuis. Het verschil zit elders: wat Lean vervolgens met die calorie\u00ebn doet, door ze te confronteren met een gemeten en niet geschat verbruik.<\/p>\n  <p>Naast de maaltijd toont Lean een TDEE die in de loop van de dag wordt bijgewerkt op basis van je stappen. Een bord perfect scannen tegenover een bevroren caloriedoel volstaat niet.<\/p>\n  <p>En daarboven, de Progressiepiramide:<\/p>\n\n  <div class=\"pyramid\" aria-label=\"Lean-Progressiepiramide\">\n    <div class=\"level l1\"><span>Therapietrouw<\/span><span class=\"k\">Basis<\/span><\/div>\n    <div class=\"level l2\"><span>Caloriedoel<\/span><span class=\"k\">Verdieping 2<\/span><\/div>\n    <div class=\"level l3\"><span>Stappen \/ NEAT<\/span><span class=\"k\">Verdieping 3<\/span><\/div>\n    <div class=\"level l4\"><span>Macronutri\u00ebnten<\/span><span class=\"k\">Top<\/span><\/div>\n  <\/div>\n  <div class=\"pyramid-cap\">Sla geen stappen over. Als je niet regelmatig trackt, heeft het geen zin om je macro&rsquo;s tot op de procent te optimaliseren.<\/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; Eerlijkheid<\/span><\/div>\n  <h2 id=\"foodvisor-better\">Wat Foodvisor beter doet<\/h2>\n  <p>Lean is niet perfect, en Foodvisor heeft meerdere echte sterke punten die erkend moeten worden. Eerlijke lezing, criterium per criterium, op de assen waar de pionier voorblijft. Geen van die assen is bijkomstig: het zijn echte pijlers van de Foodvisor-belofte.<\/p>\n\n  <div class=\"scorecard rev\" aria-label=\"Scorecard Foodvisor face \u00e0 Lean sur 4 axes\">\n    <div class=\"scorecard-head\">\n      <div class=\"h-crit\">As<\/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\">Visuele herkenning van een bord<\/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\">Automatische schatting van porties<\/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\">Menselijke coaching (gediplomeerde di\u00ebtisten)<\/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\">Voorsprong in fotoscan (FR-markt)<\/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>Eerlijke lezing.<\/strong> Op bordherkenning heeft Foodvisor de categorie in Frankrijk in 2018 gecre\u00eberd en zijn AI heeft jaren training voorsprong: identificatie van voedingsmiddelen, schatting van porties zonder weegschaal, omgaan met samengestelde gerechten. Dat is zijn historische speelveld en daar blijft het de referentie. Op menselijke begeleiding biedt Foodvisor een opvolging door gediplomeerde di\u00ebtisten rechtstreeks in de app: Lean biedt dat niet, en pretendeert het niet te vervangen. De AI-fotoscan van Lean is modern, onbeperkt en ruimschoots voldoende voor dagelijks gebruik, maar Lean claimt geen voorsprong op dat terrein.<\/p>\n  <p>Als je hoofdinvalshoek de meest doorontwikkelde bordherkenning is, of een menselijke coaching ge\u00efntegreerd in de app, is Foodvisor relevanter dan Lean. Als je invalshoek de precisie van de <a class=\"inline\" href=\"https:\/\/lean-app.com\/nl\/tdee-calculator\/\">TDEE-berekening<\/a>, het wekelijks gemeten vetpercentage via AI BodyScan, en de automatische metabole adaptatie is, is dat precies wat in de 3 vorige secties net is aangetoond. Sommigen laten beide apps parallel draaien tot ze kiezen, en dat is volkomen verdedigbaar.<\/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; Voor wie<\/span><\/div>\n  <h2 id=\"forwho\">Voor wie Lean gemaakt is<\/h2>\n  <p>4 profielen. Als je jezelf in minstens \u00e9\u00e9n herkent, is Lean waarschijnlijk voor jou gemaakt.<\/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>Je hebt Foodvisor serieus gebruikt en bent niet afgevallen<\/h4>\n        <p>Je hebt je borden gescand, de porties gecorrigeerd, wekenlang een eerlijk tekort gevolgd, en je stagneert. De foto is niet de schuldige, het is het bevroren doel berekend zonder vetpercentage. Lean corrigeert dat bij de wortel via de BMR op echt vetpercentage.<\/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>Je stagneert na meerdere weken cut<\/h4>\n        <p>Een plateau dat na 4 tot 8 weken blijft duren. Dat is de metabole adaptatie. Lean berekent die automatisch en stelt je doel elke week bij.<\/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>Je wilt je metabolisme begrijpen<\/h4>\n        <p>Lean toont elk onderdeel (BMR, NEAT, EAT, TEF) en legt de adaptatie daarna apart uit, in plaats van alles achter \u00e9\u00e9n cijfer te verbergen. Je ziet waar elke kcal verbruik vandaan komt.<\/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>Je wilt een tracking die 12 maanden standhoudt<\/h4>\n        <p>AI-fotoscan + gecureerde database + barcode dekken alle gebruikssituaties, van het onbewerkte voedingsmiddel tot de pizza in het restaurant. Dat maakt het verschil tussen volhouden en opgeven.<\/p>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>Foodvisor blijft relevanter voor<\/strong>&nbsp;: menselijke coaching door gediplomeerde di\u00ebtisten rechtstreeks in de app, en de meest doorontwikkelde bordherkenning van de Franse markt. De precisie van de verbruiksberekening en de metabole adaptatie maken gewoon geen deel uit van zijn hoofdbelofte.<\/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; Migratie<\/span><\/div>\n  <h2 id=\"migrate\">In 3 minuten overstappen van Foodvisor naar Lean (of beide gebruiken)<\/h2>\n\n  <div class=\"steps\">\n    <div class=\"step\"><div class=\"sn\">01<\/div><h4>Download Lean<\/h4><p>App Store of Play Store. Inschrijving in 30 seconden.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">02<\/div><h4>AI BodyScan<\/h4><p>E\u00e9n foto, 5 seconden. Je krijgt je vetpercentage.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">03<\/div><h4>Gewicht &amp; lengte<\/h4><p>Je vult je gewicht en lengte in. Dat is alles.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">04<\/div><h4>Lean berekent<\/h4><p>BMR op echt vetpercentage, NEAT via HealthKit \/ Google Fit (echte stappen), EAT per MET, TEF op macro&rsquo;s, plus de metabole adaptatie die de BMR moduleert. Automatisch.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">05<\/div><h4>Track een maaltijd<\/h4><p>Foto, barcode of database. Je kent de handeling al.<\/p><\/div>\n  <\/div>\n\n  <p style=\"margin-top:24px\"><strong>Belangrijke opmerking.<\/strong> Lean importeert je Foodvisor-geschiedenis niet automatisch, en ook je favoriete voedingsmiddelen niet. Als je opvolging met een Foodvisor-di\u00ebtist voor jou telt, belet niets je om beide te houden tijdens de overgang: Foodvisor voor de menselijke begeleiding, Lean voor de TDEE en de dagelijkse tracking. De HealthKit \/ Google Health Connect-synchronisatie neemt het meteen over voor je stappen en je activiteitsgeschiedenis.<\/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 en begin nu meteen met de AI BodyScan. Gratis inschrijving.<\/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; Wat Lean ontgrendelt<\/span><\/div>\n  <h2 id=\"deblock-h\">Wat Lean doet, en wat Foodvisor niet doet (op het verbruik)<\/h2>\n  <p>Zes functies gericht op het verbruik, niet te vinden bij Foodvisor. Ze vloeien allemaal voort uit hetzelfde principe: elk onderdeel van de TDEE nauwkeurig berekenen, niet benaderen.<\/p>\n\n  <div class=\"feat-stack\">\n    <div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">Onbeperkte AI BodyScan<\/div><p class=\"fd\">Je echte vetpercentage, gemeten vanaf een simpele foto, wekelijks herhaald. Het is het gegeven dat de hele BMR-berekening verandert. Geen enkele andere consumentenapp biedt dat.<\/p><\/div><div class=\"fc\">Vetpercentage<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">Automatische metabole adaptatie<\/div><p class=\"fd\">Je TDEE wordt week na week bijgesteld volgens de wetenschappelijk vastgestelde cijfers. Je vermijdt de plateaus die niemand kan verklaren.<\/p><\/div><div class=\"fc\">Adaptatie<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">Live uitgesplitste TDEE<\/div><p class=\"fd\">BMR + NEAT + EAT + TEF elk apart getoond, bijgewerkt in de loop van de dag. Geen bevroren cijfer om 8 uur &rsquo;s ochtends meer. Je ziet je caloriebalans live.<\/p><\/div><div class=\"fc\">Live<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">04<\/div><div><div class=\"ft\">NEAT op echte stappen, zonder co\u00ebffici\u00ebnt<\/div><p class=\"fd\">Je stappen, gemeten door je telefoon, voeden elke dag rechtstreeks de TDEE-berekening. Geen vakje zittend of actief om aan te vinken, nooit.<\/p><\/div><div class=\"fc\">NEAT<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">05<\/div><div><div class=\"ft\">TEF berekend op je macro&rsquo;s<\/div><p class=\"fd\">Vertering is geen forfait van 10&nbsp;%. Eiwitten 20 tot 30&nbsp;%, koolhydraten 5 tot 10&nbsp;%, vetten 1 tot 3&nbsp;%. Lean maakt de berekening bij elke maaltijd en integreert ze in de TDEE.<\/p><\/div><div class=\"fc\">TEF<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">06<\/div><div><div class=\"ft\">Volledige geschiedenis en trends<\/div><p class=\"fd\">Volg je trends in gewicht, vetpercentage en vetvrije massa over maanden. Begrijp je cycli. Herken de fases waarin je vooruitgaat en die waarin je stagneert.<\/p><\/div><div class=\"fc\">Geschiedenis<\/div><\/div>\n  <\/div>\n\n  <p style=\"margin-top:26px\">Je installeert de app gratis, je test zonder verplichting en je beslist daarna of de tool bij je doel past.<\/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\">Veelgestelde vragen<\/h2>\n  <div class=\"faq\">\n    <details><summary>Foodvisor heeft de fotoscan van maaltijden uitgevonden, waarom het met Lean vergelijken?<\/summary><div class=\"ans\">Omdat de belofte van een tracker niet stopt bij het bord. Foodvisor is de historische referentie van fotoherkenning in Frankrijk, maar zijn caloriedoel rust op een populatieformule (Mifflin-St Jeor 1990, zonder gemeten vetpercentage) en een statische activiteitsvermenigvuldiger gekozen bij de inschrijving. Het zijn twee helften van hetzelfde probleem: Foodvisor blinkt uit in wat binnenkomt, Lean in wat wordt verbruikt.<\/div><\/details>\n    <details><summary>Waarom berekent Foodvisor de BMR niet op het echte vetpercentage?<\/summary><div class=\"ans\">Omdat er geen meting van het vetpercentage in de app bestaat, en populatieformules alleen gewicht, lengte, leeftijd en geslacht gebruiken. Lean integreert de AI BodyScan om je vetpercentage vanaf een simpele foto te meten, wekelijks te herhalen, wat een BMR op basis van de echte vetvrije massa mogelijk maakt via een gepatenteerd eigen model.<\/div><\/details>\n    <details><summary>Is de fotoscan van Lean evenwaardig aan die van Foodvisor?<\/summary><div class=\"ans\">Foodvisor behoudt de voorsprong en jaren training in bordherkenning, in het bijzonder de schatting van porties. De AI-fotoscan van Lean identificeert voedingsmiddelen, calorie\u00ebn en macro&rsquo;s met een vergelijkbare precisie voor dagelijks gebruik, en is onbeperkt. Op dat criterium doen beide hun werk. Het echte verschil tussen de twee apps zit in de berekening van het verbruik.<\/div><\/details>\n    <details><summary>Foodvisor telt mijn stappen, volstaat dat voor de NEAT?<\/summary><div class=\"ans\">Stappen tellen en ze in de berekening integreren zijn twee verschillende dingen. Bij Foodvisor blijft het caloriedoel rusten op de statische activiteitsvermenigvuldiger gekozen bij de inschrijving. Lean berekent de NEAT rechtstreeks op basis van de echte stappen die elke dag worden gemeten, zonder co\u00ebffici\u00ebnt om te kiezen, en scheidt ze netjes van het sportverbruik (EAT).<\/div><\/details>\n    <details><summary>Is Lean gratis of betaald?<\/summary><div class=\"ans\">Lean is Premium, met 7 dagen gratis proberen op het jaarabonnement. Je downloadt, je test de AI BodyScan, de AI-fotoscan van een gerecht, de TDEE-recompositie, zonder verplichting. Als de tool bij je doel past, ga je door. Zo niet, dan schakel je de verlenging uit voor het einde van de proefperiode.<\/div><\/details>\n    <details><summary>Kun je Lean en Foodvisor parallel gebruiken?<\/summary><div class=\"ans\">Ja, vooral tijdens de overgang. Sommigen houden Foodvisor voor de coaching met een di\u00ebtist en gebruiken Lean dagelijks voor de TDEE, de recompositie en de tracking. De inspanning van dubbele invoer is re\u00ebel: op termijn kiest de meerderheid de app die hun caloriedoel stuurt, en dat is precies het terrein waarop Lean is gebouwd om het nauwkeurigst te zijn.<\/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; Conclusie<\/span><\/div>\n  <h2 id=\"conclu\">Het bord is geregeld. Het verbruik niet.<\/h2>\n  <p>Het is niet Foodvisor tegen Lean in marketing. Het is de invoer tegenover de uitvoer, twee helften van dezelfde vergelijking.<\/p>\n  <p>Foodvisor heeft de linkerhelft opgelost: weten wat je eet, zonder weegschaal, dankzij de meest doorontwikkelde fotoscan van de Franse markt. Maar voor de rechterhelft, je verbruik, steunt Foodvisor op een populatieformule uit 1990 zonder gemeten vetpercentage, een bevroren activiteitsvermenigvuldiger die je \u00e9\u00e9n keer aanvinkt bij de inschrijving, en geen metabole adaptatie. De combinatie van die drie maakt elke nauwkeurige calorieopvolging onmogelijk na enkele weken cut. Dat is wiskunde.<\/p>\n  <p>Lean is voor die helft gebouwd: BMR gebaseerd op de <a class=\"inline\" href=\"https:\/\/lean-app.com\/nl\/depense-energetique-totale-v2\/\">echte vetpercentage<\/a> (gemeten via AI BodyScan) via een gepatenteerd eigen model, <a class=\"inline\" href=\"https:\/\/lean-app.com\/nl\/neat-depense-non-sportive\/\">NEAT op echte stappen<\/a>, EAT per sport en MET, <a class=\"inline\" href=\"https:\/\/lean-app.com\/nl\/effet-thermique-des-aliments\/\">TEF op macro&rsquo;s<\/a>, plus de metabole adaptatie die de BMR week na week moduleert. Elk onderdeel nauwkeurig berekend, zonder magische co\u00ebffici\u00ebnt. En de fotoreflex die je bij Foodvisor hebt aangeleerd, houd je: de AI-fotoscan is ge\u00efntegreerd, onbeperkt.<\/p>\n  <p>Als je Foodvisor serieus hebt geprobeerd en niet de resultaten hebt gekregen die je hoopte tijdens je cut, ligt het probleem niet bij jou, en ook niet bij de foto. Het probleem is de bevroren TDEE onder de motorkap. Wissel de motor, houd de reflex.<\/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 is gratis te downloaden<\/h3>\n  <p>iOS en Android. De AI BodyScan werkt met een simpele foto. Geen huidplooimeter, geen impedantieweegschaal, geen 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=\"T\u00e9l\u00e9charger Lean sur l'App Store\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"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=\"T\u00e9l\u00e9charger Lean sur Google Play\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" 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\">Verder lezen<\/span><\/div>\n  <h3 id=\"links\" style=\"margin-top:0\">Interne links<\/h3>\n  <ul>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/nl\/tdee-calculator\/\">Gratis online TDEE-calculator<\/a> &middot; webversie, zonder inschrijving, dezelfde logica als de app (BMR + NEAT + EAT + TEF).<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/nl\/depense-energetique-totale-v2\/\">De TDEE in detail begrijpen (BMR, NEAT, EAT, TEF, adaptatie)<\/a> &middot; diepgaand wetenschappelijk artikel.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/nl\/comment-compter-ses-calories\/\">Hoe je je calorie\u00ebn correct telt<\/a> &middot; praktische gids voor beginners.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/nl\/neat-depense-non-sportive\/\">NEAT: verbruik per stap en activiteit buiten de sport<\/a>.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/nl\/effet-thermique-des-aliments\/\">TEF: de vertering verbrandt calorie\u00ebn<\/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\">Bronnen<\/span><\/div>\n  <h3 id=\"src\" style=\"margin-top:0;color:var(--ink)\">Bibliografie<\/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 gepubliceerd op 15 augustus 2026. Regelmatig bijgewerkt met feedback van gebruikers en nieuwe relevante studies. 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data-wpmeteor-nooptimize=\"true\">\n(function shrinkAnnotationsOnMobile(){\n  if (typeof window.Chart === 'undefined') { return setTimeout(shrinkAnnotationsOnMobile, 100); }\n  var isMobile = window.matchMedia && window.matchMedia('(max-width:540px)').matches;\n  if (!isMobile) return;\n  function apply(){\n    ['chartBMR','chartNEAT','chartAdapt'].forEach(function(id){\n      var c = window.Chart.getChart(id);\n      if (!c) return;\n      var anns = c.options && c.options.plugins && c.options.plugins.annotation && c.options.plugins.annotation.annotations;\n      if (!anns) return;\n      Object.keys(anns).forEach(function(k){\n        var a = anns[k];\n        if (a.type !== 'label' || !a.font) return;\n        if (a.font.size >= 20) { a.font.size = 14; }\n        else if (a.font.size >= 14) { a.font.size = 12; }\n      });\n      try { c.update('none'); } catch(e){}\n    });\n  }\n  var tries = 0;\n  function tryApply(){\n    apply();\n    tries++;\n    if (tries < 20) setTimeout(tryApply, 300);\n  }\n  tryApply();\n})();\n<\/script>\n\n\n\n<!-- lean-mesh-v16 -->\n<aside class=\"lean-mesh\" style=\"margin:48px auto;max-width:760px;padding:24px 28px;background:#ffffff;border-left:4px solid #FF2D6E;border-radius:0 12px 12px 0;box-shadow:0 6px 24px rgba(20,20,40,0.06);font-family:-apple-system,'SF Pro Text','Segoe UI',Roboto,Arial,sans-serif;color:#1a1a2e;\"><p style=\"margin:0 0 14px;font-size:13px;font-weight:700;letter-spacing:0.06em;text-transform:uppercase;color:#FF2D6E;\">Lees ook<\/p><ul style=\"list-style:none;padding:0;margin:0;display:grid;grid-template-columns:1fr;gap:10px;\"><li><a href=\"https:\/\/lean-app.com\/nl\/metabolisme-de-base\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Basaal metabolisme (BMR): alles wat je moet weten om het te berekenen <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Definitie, TDEE-vergelijking, 4 historische formules, waarom het vetpercentage alles verandert.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/nl\/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;\">Totaal energieverbruik (TDEE): de canonieke formule BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Begrijp de 4 bouwstenen + de metabole adaptatie, wetenschappelijke bronnen 2025.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/nl\/eat\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">EAT: je echte sportverbruik, training per training <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">De juiste MET, de valkuil van dubbeltelling, wat Garmin en MyFitnessPal missen.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/nl\/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 beste apps om calorie\u00ebn te tellen in 2026: 8 apps getest <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\/nl\/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;\">Welk alternatief voor MyFitnessPal in 2026? 5 apps getest <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Eerlijke vergelijking, TDEE-precisie, ergonomie.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/nl\/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 vergelijkingen van Lean tegenover de grote calorie-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\/nl\/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 tegenover MyFitnessPal: de TDEE-formule die alles verandert <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Waarom MFP zich vergist over je echte calorieverbruik.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/nl\/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-calculator: de canonieke formule BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Calculator die rekening houdt met vetpercentage, met uitsplitsing van de 4 metabole bouwstenen.<\/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-fotoscan tegenover je echte verbruik<\/title>\n<meta name=\"description\" content=\"Foodvisor heeft de fotoscan van maaltijden uitgevonden. 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