{"id":1425,"date":"2026-05-24T15:29:31","date_gmt":"2026-05-24T15:29:31","guid":{"rendered":"https:\/\/lean-app.com\/?p=1425"},"modified":"2026-08-22T18:00:19","modified_gmt":"2026-08-22T18:00:19","slug":"lean-vs-noom","status":"publish","type":"post","link":"https:\/\/lean-app.com\/pt\/lean-vs-noom\/","title":{"rendered":"Lean face \u00e0 Noom : coaching psychologique face \u00e0 la pr\u00e9cision m\u00e9tabolique"},"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\" 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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-1425 #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-1425 #lvm-shell .wrap,\nbody.postid-1425 #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-1425 #lvm-shell .wrap,\n  body.postid-1425 #lvm-shell main.wrap{padding-left:18px!important;padding-right:18px!important}\n}\nhtml, body{overflow-x:hidden!important}\nbody.postid-1425 #lvm-shell{overflow-x:hidden;max-width:100vw}\nbody.postid-1425 #lvm-shell *{max-width:100%}\nbody.postid-1425 #lvm-shell .nav-row{max-width:100vw;box-sizing:border-box}\nbody.postid-1425 #lvm-shell.force-show .rev{opacity:1!important;transform:none!important}\n\n\/* === A.1 PHONE BACKGROUND CLASSES === *\/\nbody.postid-1425 #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-1425 #lvm-shell .phone-bg.tab-depense{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.tab-bilan{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.tab-kcal{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.tab-strategie{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.sub-BMR{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.sub-NEAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp)}\nbody.postid-1425 #lvm-shell .phone-bg.sub-EAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp)}\nbody.postid-1425 #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 (badges plus gros + centrage) === *\/\n@media (max-width:760px){\n  body.postid-1425 #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-1425 #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-1425 #lvm-shell .cta-band .stores{width:100%!important;justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1425 #lvm-shell .cta-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1425 #lvm-shell .cta-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1425 #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-1425 #lvm-shell .get-band{padding:38px 22px!important}\n  body.postid-1425 #lvm-shell .get-band .stores{justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1425 #lvm-shell .get-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1425 #lvm-shell .get-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1425 #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-1425 #lvm-shell .get-band h3{font-size:26px!important;line-height:1.2!important}\n  body.postid-1425 #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-1425 #lvm-shell .brand-banner img{width:54px!important;height:54px!important}\n  body.postid-1425 #lvm-shell .brand-banner > div{padding:16px 12px!important;gap:8px!important}\n  body.postid-1425 #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-1425 #lvm-shell .scorecard{padding:18px 16px!important;border-radius:16px!important}\n  body.postid-1425 #lvm-shell .scorecard-head{display:none!important}\n  body.postid-1425 #lvm-shell .scorecard-row{\n    display:block!important;\n    padding:14px 0!important;\n    border-bottom:1px solid #E8E2D6!important;\n  }\n  body.postid-1425 #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-1425 #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-1425 #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-1425 #lvm-shell .scorecard-row .bar.lean::before{color:#FF2D6E!important}\n  body.postid-1425 #lvm-shell .scorecard-row .bar.mfp::before{color:#5B7FFF!important}\n  body.postid-1425 #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-1425 #lvm-shell .scorecard-row .bar .b > i{\n    display:block!important;\n    height:100%!important;\n    border-radius:99px!important;\n  }\n  body.postid-1425 #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  \/* v13: charts FULL WIDTH (less card padding) + plus hauts pour vraie respiration *\/\n  body.postid-1425 #lvm-shell .cv-wrap{height:380px!important;min-height:360px!important;max-height:420px!important;width:100%!important}\n  body.postid-1425 #lvm-shell .cv-wrap canvas{width:100%!important;height:100%!important;display:block!important}\n  body.postid-1425 #lvm-shell .fig{padding:16px 4px 14px!important;margin:24px -4px 14px!important;overflow:visible!important}\n  body.postid-1425 #lvm-shell .fig-head{padding:0 12px!important;flex-wrap:wrap!important;gap:6px!important;margin-bottom:10px!important}\n  body.postid-1425 #lvm-shell .fig-body{padding:0 2px!important}\n  body.postid-1425 #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-1425 #lvm-shell .cv-wrap{height:360px!important;min-height:340px!important;max-height:380px!important}\n  body.postid-1425 #lvm-shell .fig{padding:14px 2px 12px!important;margin:20px -6px 12px!important;border-radius:14px!important}\n  body.postid-1425 #lvm-shell .fig-body{padding:0!important}\n}\n\n\/* === v11.2 TABLEAU MOBILE STACKED CARDS avec mini-tags Lean\/MFP === *\/\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .table{border-radius:14px!important}\n  body.postid-1425 #lvm-shell .table-row.head{display:none!important}\n  body.postid-1425 #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-1425 #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-1425 #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-1425 #lvm-shell .table-row > .cell:not(.lean):not(.crit){\n    grid-area:mfp!important;background:#F5F5F7!important;padding-top:30px!important;\n    position:relative!important;\n  }\n  body.postid-1425 #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-1425 #lvm-shell .table-row > .cell:not(.lean):not(.crit)::before{\n    content:\"NOOM\"!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:#FF6E5E!important;\n  }\n  body.postid-1425 #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-1425 #lvm-shell .icn{flex-shrink:0!important;margin-top:1px!important}\n}\n\n\/* === A.5 MINI-LOGOS partie 7 (triplet NEAT\/EAT\/TEF) === *\/\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .mini-row{gap:6px!important;margin:24px 0!important;grid-template-columns:repeat(3,1fr)!important}\n  body.postid-1425 #lvm-shell .mini-phone{max-width:100px!important;padding:2px!important;border-radius:14px!important;border-width:1px!important}\n  body.postid-1425 #lvm-shell .mini-phone.tiny{max-width:96px!important;padding:2px!important;border-radius:13px!important}\n  body.postid-1425 #lvm-shell .mini-phone .notch{width:30px!important;height:8px!important;border-radius:0 0 5px 5px!important}\n  body.postid-1425 #lvm-shell .mini-phone .scr{border-radius:11px!important}\n  body.postid-1425 #lvm-shell .mini-cap{font-size:10px!important;margin-top:8px!important}\n  body.postid-1425 #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-1425 #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-1425 #lvm-shell .tap-hint.desktop{display:none!important}\n  body.postid-1425 #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 (override mobile mini-phone) === *\/\nbody.postid-1425 #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-1425 #lvm-shell .bodyscan-illust .mini-phone{max-width:200px!important;padding:3px!important;border-radius:22px!important;border-width:1px!important}\nbody.postid-1425 #lvm-shell .bodyscan-illust .mini-phone .notch{width:40px!important;height:11px!important;border-radius:0 0 7px 7px!important}\nbody.postid-1425 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:18px!important}\n@media (max-width:760px){\n  body.postid-1425 #lvm-shell .bodyscan-illust{max-width:180px!important}\n  body.postid-1425 #lvm-shell .bodyscan-illust .mini-phone{max-width:160px!important;padding:3px!important;border-radius:20px!important}\n  body.postid-1425 #lvm-shell .bodyscan-illust .mini-phone .notch{width:34px!important;height:9px!important;border-radius:0 0 6px 6px!important}\n  body.postid-1425 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:16px!important}\n}\n<\/style>\n\n\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\/pt\/\" 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\/pt\/tdee-calculator\/\">Calculadora TDEE<\/a>\n    <div class=\"nav-stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\" aria-label=\"Baixar na App Store\">\n        <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/>\n      <\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\" aria-label=\"Dispon\u00edvel no Google Play\">\n        <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/>\n      <\/a>\n    <\/div>\n  <\/div>\n<\/header>\n\n<main class=\"wrap\">\n\n<section class=\"hero\" aria-labelledby=\"title\">\n  <div class=\"crumb\"><a href=\"https:\/\/lean-app.com\/pt\/\">In\u00edcio<\/a> &nbsp;\/&nbsp; Lean vs Noom<\/div>\n  <div class=\"eyebrow\">Comparatif &middot; Nutrition &amp; TDEE<\/div>\n  <h1 id=\"title\">Lean face \u00e0 Noom.\n    <span class=\"alt\">Coaching psychologique face \u00e0 la pr\u00e9cision m\u00e9tabolique.<\/span>\n  <\/h1>\n  <p class=\"dek\">Noom vend du coaching comportemental pour changer tes habitudes. Lean voit ta d\u00e9pense r\u00e9elle. Deux promesses qui ne jouent pas sur le m\u00eame terrain.<\/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>A equipe Lean<\/strong> &middot; Lecture 12&nbsp;min &middot; Mis \u00e0 jour 24 mai 2026<\/span>\n  <\/div>\n  <div class=\"hero-stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" 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\" 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\">Download gratuito<\/span>\n  <\/div>\n\n  <div class=\"hero-bottom\">\n    <div class=\"hero-lead\">\n      Noom est connu pour son quiz d&rsquo;inscription long et personnalis\u00e9, ses cours quotidiens de psychologie alimentaire, sa classification d&rsquo;aliments vert\/jaune\/rouge et l&rsquo;acc\u00e8s \u00e0 un coach humain. Une vraie force pour l&rsquo;adh\u00e9rence et le travail sur les habitudes. Mais sa formule TDEE reste Mifflin-St Jeor 1990, plus un facteur d&rsquo;activit\u00e9 statique que tu coches une seule fois lors du quiz d&rsquo;inscription. Sans bodyfat r\u00e9el mesur\u00e9 dans l&rsquo;app, sans adaptation m\u00e9tabolique. Sur 3 mois de cut s\u00e9rieux, l&rsquo;\u00e9cart se creuse.\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>Demonstra\u00e7\u00e3o interativa<\/small>Toque na tela para explorar o aplicativo<\/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>Demonstra\u00e7\u00e3o interativa<\/small>Toque na tela<br>para explorar o aplicativo<\/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=\"Retour\">&#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=\"Onglet D\u00e9pense\"><\/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\">Balan\u00e7o<\/button>\n          <button data-tab=\"kcal\"      type=\"button\">Calorias<\/button>\n          <button data-tab=\"depense\"   type=\"button\" class=\"on\">Gasto<\/button>\n          <button data-tab=\"strategie\" type=\"button\">Estrat\u00e9gia<\/button>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"snippet rev\">\n    <div class=\"lbl\">R\u00e9ponse rapide<\/div>\n    <p>Noom calcule ton TDEE avec Mifflin-St Jeor 1990 (sans bodyfat mesur\u00e9 dans l&rsquo;app) et un facteur d&rsquo;activit\u00e9 statique choisi au moment du quiz d&rsquo;inscription. La force r\u00e9elle de Noom est ailleurs : un quiz personnalis\u00e9 qui cr\u00e9e un fort engagement initial, des cours quotidiens de psychologie alimentaire, une classification vert\/jaune\/rouge des aliments et l&rsquo;acc\u00e8s \u00e0 un coach humain qui travaille sur l&rsquo;adh\u00e9rence. Lean prend un parti diff\u00e9rent : recalculer chaque composant du TDEE (<span data-term=\"BMR\">BMR<span class=\"tt\">Basal Metabolic Rate. Energia gasta em repouso. Na Lean, calculada sobre a massa magra real via BodyScan IA.<\/span><\/span> sur bodyfat r\u00e9el via un mod\u00e8le propri\u00e9taire brevet\u00e9, <span data-term=\"NEAT\">NEAT<span class=\"tt\">Non-Exercise Activity Thermogenesis. D\u00e9pense li\u00e9e aux pas et activit\u00e9s quotidiennes hors sport.<\/span><\/span> par pas, <span data-term=\"EAT\">EAT<span class=\"tt\">Exercise Activity Thermogenesis. D\u00e9pense li\u00e9e aux s\u00e9ances de sport, calcul\u00e9e via MET.<\/span><\/span> par MET, <span data-term=\"TEF\">TEF<span class=\"tt\">Thermic Effect of Food. \u00c9nergie d\u00e9pens\u00e9e par la digestion. D\u00e9pend des macros ing\u00e9r\u00e9es.<\/span><\/span> par macros) et moduler le BMR par l&rsquo;adaptation m\u00e9tabolique en continu, sans coefficient \u00e0 choisir.<\/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; Le constat<\/span><\/div>\n  <h2 id=\"constat\">Noom vend du coaching, pas ton adaptation m\u00e9tabolique<\/h2>\n  <p>Si tu lis \u00e7a, tu as probablement d\u00e9j\u00e0 install\u00e9 Noom. Tu as fait le quiz d&rsquo;inscription long, ces 20 minutes de questions tr\u00e8s personnelles sur ton histoire avec le poids, tes blocages, tes \u00e9motions, tes habitudes. Tu t&rsquo;es senti compris. Tu as renseign\u00e9 ton poids, ta taille, ton \u00e2ge, ton sexe, et choisi ton niveau d&rsquo;activit\u00e9 dans une liste statique. L&rsquo;app t&rsquo;a affich\u00e9 un objectif calorique, mettons 1&nbsp;500&nbsp;kcal pour perdre du poids.<\/p>\n  <p>Tu as suivi les cours quotidiens de 5 \u00e0 10 minutes sur la psychologie alimentaire. Tu as classifi\u00e9 tes repas en vert, jaune, rouge. Tu as \u00e9chang\u00e9 avec ton coach humain les jours difficiles. Les 6 premi\u00e8res semaines, \u00e7a fonctionne. Tu perds. Tu es content. Puis vers la semaine 8, la balance se fige. Tu serres la vis. Tu descends \u00e0 1&nbsp;350&nbsp;kcal. L\u00e0 encore, rien ne bouge.<\/p>\n\n  <div class=\"statement\">\n    <div class=\"num\">&minus;10 \u00e0 &minus;15&nbsp;%<\/div>\n    <div class=\"lbl\">de baisse mesur\u00e9e du TDEE apr\u00e8s 4 \u00e0 6 semaines de d\u00e9ficit \u00e0 &minus;500&nbsp;kcal\/jour. Noom ne le d\u00e9tecte pas. Ton objectif calorique reste fig\u00e9 sur le facteur d&rsquo;activit\u00e9 que tu as coch\u00e9 au quiz d&rsquo;inscription, il y a 100&nbsp;jours.<\/div>\n  <\/div>\n\n  <p>Imaginons que Noom t&rsquo;affiche un TDEE de 2&nbsp;000&nbsp;kcal. Tu manges 1&nbsp;500 (d\u00e9ficit th\u00e9orique de 500&nbsp;kcal). Mais en r\u00e9alit\u00e9, ton <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/depense-energetique-totale-v2\/\">TDEE est descendu \u00e0 1&nbsp;700&nbsp;kcal<\/a> \u00e0 cause de l&rsquo;adaptation m\u00e9tabolique. Tu es \u00e0 seulement 200&nbsp;kcal de d\u00e9ficit r\u00e9el, pas 500. La perte ralentit drastiquement. Aucun cours quotidien Noom ne peut corriger \u00e7a, parce que le probl\u00e8me n&rsquo;est pas dans ta t\u00eate, il est dans l&rsquo;\u00e9quation.<\/p>\n  <p>La promesse Noom est claire et tenue sur sa partie comportementale : tu te sens accompagn\u00e9, tu travailles tes d\u00e9clencheurs \u00e9motionnels, tu apprends \u00e0 classifier la qualit\u00e9 de tes choix. C&rsquo;est pr\u00e9cieux pour l&rsquo;adh\u00e9rence. Ce que Noom ne fait pas, c&rsquo;est <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/comment-compter-ses-calories\/\">recalculer ta d\u00e9pense<\/a> au fil des semaines de d\u00e9ficit. Et c&rsquo;est exactement l\u00e0 o\u00f9 la promesse \u00ab\u00a0calorie tracker\u00a0\u00bb s&rsquo;arr\u00eate, alors que c&rsquo;est le levier qui fait perdre du poids.<\/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; Probl\u00e8me 1<\/span><\/div>\n  <h2 id=\"p1\">La formule BMR de 1990, sans bodyfat mesur\u00e9 dans l&rsquo;app<\/h2>\n  <p>Derri\u00e8re les cours quotidiens et la classification des aliments, Noom doit bien poser un chiffre&nbsp;: ton m\u00e9tabolisme de base, l&rsquo;\u00e9nergie br\u00fbl\u00e9e au repos. Il l&rsquo;obtient avec l&rsquo;\u00e9quation de Mifflin-St Jeor, celle qu&rsquo;utilise l&rsquo;\u00e9crasante majorit\u00e9 des trackers grand public.<\/p>\n  <p>Mifflin-St Jeor date de 1990. Sur le papier c&rsquo;est un progr\u00e8s&nbsp;: 498 sujets, calorim\u00e9trie indirecte, population plus repr\u00e9sentative que les travaux de 1919. Noom l&rsquo;applique telle quelle, sans variante.<\/p>\n  <p>Certains concurrents proposent au moins une porte de sortie, l&rsquo;\u00e9quation Katch-McArdle, qui travaille sur la masse maigre si tu saisis ton taux de masse grasse. Noom n&rsquo;offre pas cette option&nbsp;: pas de champ bodyfat, pas de calcul alternatif. Le coaching s&rsquo;appuie donc sur une estimation que rien ne vient corriger.<\/p>\n  <p>Le progr\u00e8s de 1990 sur 1919 est r\u00e9el mais marginal, car le d\u00e9faut de fond ne bouge pas&nbsp;: l&rsquo;\u00e9quation ne conna\u00eet que ton poids. Ni ton bodyfat, ni ta masse maigre.<\/p>\n  <p>Or la masse grasse consomme tr\u00e8s peu d&rsquo;\u00e9nergie au repos. Ce sont les organes et les muscles qui d\u00e9pensent&nbsp;: le foie, le cerveau, le c\u0153ur, les reins. Deux corps de m\u00eame poids avec des compositions diff\u00e9rentes n&rsquo;ont donc pas le m\u00eame m\u00e9tabolisme.<\/p>\n  <p>Frankenfield 2013 (PubMed 23631843) a confront\u00e9 Mifflin-St Jeor \u00e0 la calorim\u00e9trie indirecte de r\u00e9f\u00e9rence&nbsp;: 87&nbsp;% de pr\u00e9cision chez les sujets non ob\u00e8ses, mais seulement 68&nbsp;% chez les sujets ob\u00e8ses, avec des \u00e9carts atteignant 330&nbsp;kcal par jour.<\/p>\n\n  <p style=\"margin-bottom:8px\"><strong>Exemple chiffr\u00e9.<\/strong> Femme de 1m65, 85&nbsp;kg, 38&nbsp;% de bodyfat&nbsp;:<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figure 1<\/span><span class=\"r\">kcal<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\"><canvas id=\"chartBMR\" aria-label=\"Comparaison BMR Mifflin-St Jeor 1670 kcal vs mod\u00e8le propri\u00e9taire brevet\u00e9 Lean 1340 kcal, \u00e9cart de 330 kcal\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>BMR estim\u00e9<\/strong> pour une femme de 1m65, 85&nbsp;kg, 38&nbsp;% de bodyfat. Le mod\u00e8le propri\u00e9taire brevet\u00e9 Lean prend en compte la masse maigre. Mifflin-St Jeor (Noom par d\u00e9faut, sans option masse maigre), non. \u00c9cart de 330&nbsp;kcal, soit l&rsquo;\u00e9quivalent d&rsquo;un repas l\u00e9ger entier.<\/p>\n  <\/div>\n\n  <p>330&nbsp;kcal d&rsquo;erreur, c&rsquo;est la diff\u00e9rence entre un d\u00e9ficit qui fonctionne et un plateau inexpliqu\u00e9. Aucun accompagnement comportemental, aussi bon soit-il, ne rattrape un objectif calorique faux d\u00e8s le d\u00e9part&nbsp;: il te rendra simplement plus assidu sur la mauvaise cible.<\/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>Photo, 5 secondes<\/strong><\/div>\n  <\/div>\n\n  <div class=\"statement\">\n    <div class=\"num\">400&nbsp;kcal<\/div>\n    <div class=\"lbl\">d&rsquo;\u00e9cart entre deux femmes de 75&nbsp;kg, l&rsquo;une \u00e0 22&nbsp;% de bodyfat (BMR 1&nbsp;650), l&rsquo;autre \u00e0 38&nbsp;% (BMR 1&nbsp;250). Noom leur donne le m\u00eame chiffre, sans option masse maigre.<\/div>\n  <\/div>\n\n  <p>La conclusion est arithm\u00e9tique&nbsp;: une app qui ne conna\u00eet que ton poids, ta taille, ton \u00e2ge et ton sexe ne peut pas individualiser ton m\u00e9tabolisme. Il lui manque la variable qui compte.<\/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; Probl\u00e8me 2<\/span><\/div>\n  <h2 id=\"p2\">Le facteur d&rsquo;activit\u00e9, choisi une fois pour toute<\/h2>\n  <p>C&rsquo;est le maillon que le coaching ne peut pas compenser.<\/p>\n  <p>Une fois le m\u00e9tabolisme de base estim\u00e9, Noom doit en d\u00e9duire ta d\u00e9pense totale&nbsp;: le BMR plus les pas, les activit\u00e9s du quotidien, les s\u00e9ances et la digestion.<\/p>\n  <p>La m\u00e9thode tient en une question du questionnaire d&rsquo;inscription&nbsp;: choisis ton niveau d&rsquo;activit\u00e9 dans une liste. Ce coefficient s&rsquo;appelle PAL, pour Physical Activity Level.<\/p>\n  <ul>\n    <li>S\u00e9dentaire (PAL 1,25) : bureau, peu de marche<\/li>\n    <li>L\u00e9g\u00e8rement actif (PAL 1,4) : marche occasionnelle, peu de sport<\/li>\n    <li>Actif (PAL 1,6) : marche r\u00e9guli\u00e8re, sport 3 \u00e0 5 fois par semaine<\/li>\n    <li>Tr\u00e8s actif (PAL 1,8) : sport intense quasi quotidien ou travail physique<\/li>\n  <\/ul>\n  <p>Le BMR est ensuite multipli\u00e9 par ce nombre. C&rsquo;est tout le m\u00e9canisme derri\u00e8re ton objectif quotidien&nbsp;: une case coch\u00e9e le premier jour, jamais rediscut\u00e9e ensuite.<\/p>\n  <p>L&rsquo;approximation est grossi\u00e8re. Entre un dimanche sur le canap\u00e9 et une journ\u00e9e debout \u00e0 marcher, l&rsquo;\u00e9cart r\u00e9el d\u00e9passe largement ce qu&rsquo;un coefficient unique peut repr\u00e9senter.<\/p>\n  <p>Noom se synchronise correctement avec Apple Health et Google Fit et r\u00e9cup\u00e8re tes pas. Un bonus calorique peut s&rsquo;ajouter quand une s\u00e9ance est d\u00e9tect\u00e9e. Mais le socle du calcul reste le multiplicateur choisi \u00e0 l&rsquo;inscription.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figure 2 &middot; 7 jours r\u00e9els<\/span><span class=\"r\">kcal\/jour<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\"><canvas id=\"chartNEAT\" aria-label=\"Variabilit\u00e9 quotidienne de la d\u00e9pense calorique sur 7 jours, contre 2000 kcal fixes selon Noom\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>D\u00e9pense r\u00e9elle<\/strong> mesur\u00e9e sur 7&nbsp;jours pour une utilisatrice Lean. La ligne grise est ce que Noom affichait (2&nbsp;000&nbsp;kcal fixe, PAL Actif \u00d7 BMR). Les annotations roses montrent pourquoi chaque jour bouge.<\/p>\n  <\/div>\n\n  <p>Ton activit\u00e9 ne tient pas dans une case. Tu peux \u00eatre tr\u00e8s actif la semaine o\u00f9 tu encha\u00eenes les d\u00e9placements, et s\u00e9dentaire celle o\u00f9 tu travailles \u00e0 distance.<\/p>\n  <p>Quelle case cocher, alors&nbsp;? Aucune n&rsquo;est juste, et le TDEE affich\u00e9 reste durablement d\u00e9cal\u00e9 du r\u00e9el.<\/p>\n  <p>C&rsquo;est le point central&nbsp;: m\u00eame avec une \u00e9quation de m\u00e9tabolisme moderne, un PAL statique suffit \u00e0 fausser l&rsquo;ensemble. On ne d\u00e9duit pas le NEAT, l&rsquo;EAT et le TEF d&rsquo;un multiplicateur unique.<\/p>\n  <p>Un m\u00e9tabolisme estim\u00e9 sans mesure de composition corporelle, plus une d\u00e9pense d&rsquo;activit\u00e9 approxim\u00e9e par un coefficient fig\u00e9&nbsp;: les chances que l&rsquo;objectif final soit juste sont faibles.<\/p>\n\n  <div class=\"cta-band rev\">\n    <div class=\"l\">Voir ton TDEE r\u00e9elle, d\u00e9compos\u00e9e en BMR + NEAT + EAT + TEF. T\u00e9l\u00e9chargement gratuit.<\/div>\n    <div class=\"stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"p3\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">03 &middot; Probl\u00e8me 3<\/span><\/div>\n  <h2 id=\"p3\">L&rsquo;adaptation m\u00e9tabolique, jamais mod\u00e9lis\u00e9e<\/h2>\n  <p>C&rsquo;est le point aveugle que ni les cours quotidiens ni les coachs ne couvrent.<\/p>\n  <p>En d\u00e9ficit prolong\u00e9, ton corps constate qu&rsquo;il re\u00e7oit moins d&rsquo;\u00e9nergie et r\u00e9duit sa consommation. Comme un t\u00e9l\u00e9phone qui passe en mode \u00e9conomie&nbsp;: tout continue de tourner, mais au ralenti.<\/p>\n  <p>C&rsquo;est l&rsquo;adaptation m\u00e9tabolique, et la litt\u00e9rature est constante&nbsp;: M\u00fcller 2015 (PubMed 26399868, r\u00e9analyse de l&rsquo;\u00e9tude du Minnesota), Doucet 2001 sur le d\u00e9ficit prolong\u00e9, Nunes 2020 (PMC7484122). Les fourchettes publi\u00e9es vont de 5 \u00e0 25&nbsp;% du m\u00e9tabolisme de base.<\/p>\n  <ul>\n    <li>D\u00e9ficit de &minus;250&nbsp;kcal par jour, sur 2 \u00e0 8 semaines : adaptation de <strong>5 \u00e0 10&nbsp;%<\/strong> (TDEE descend \u00e0 90-95&nbsp;% du niveau initial)<\/li>\n    <li>D\u00e9ficit de &minus;500&nbsp;kcal par jour : <strong>10 \u00e0 15&nbsp;%<\/strong> d&rsquo;adaptation (TDEE descend \u00e0 85-90&nbsp;%)<\/li>\n    <li>D\u00e9ficit de &minus;750&nbsp;kcal par jour : <strong>15 \u00e0 25&nbsp;%<\/strong> d&rsquo;adaptation (TDEE descend \u00e0 75-85&nbsp;%)<\/li>\n  <\/ul>\n  <p>Convention Lean&nbsp;: 100&nbsp;% signifie un m\u00e9tabolisme optimal, 90&nbsp;% une adaptation de 10&nbsp;%. Et comme le NEAT, l&rsquo;EAT et le TEF se calculent tous \u00e0 partir du BMR, c&rsquo;est l&rsquo;ensemble du TDEE qui se d\u00e9place.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figure 3 &middot; 8 semaines en d\u00e9ficit<\/span><span class=\"r\">kcal\/jour<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\"><canvas id=\"chartAdapt\" aria-label=\"TDEE qui chute de 2000 \u00e0 1720 kcal sur 8 semaines, contre 2000 fixe selon Noom\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>TDEE r\u00e9el<\/strong> sur 8 semaines de d\u00e9ficit \u00e0 &minus;500&nbsp;kcal\/jour. La courbe rose descend. La ligne Noom reste plate. \u00c0 semaine 6, tu es d\u00e9j\u00e0 \u00e0 la maintenance. Sans rien avoir chang\u00e9.<\/p>\n  <\/div>\n\n  <p>Un exemple chiffr\u00e9&nbsp;: tu vises un d\u00e9ficit de 25&nbsp;% sur un TDEE de 2&nbsp;000&nbsp;kcal, donc 1&nbsp;500&nbsp;kcal par jour. Ton corps s&rsquo;adapte de 14&nbsp;%, ton TDEE r\u00e9el tombe \u00e0 1&nbsp;720. Il ne te reste que 220&nbsp;kcal de d\u00e9ficit&nbsp;: la perte s&rsquo;arr\u00eate, sans que tu aies chang\u00e9 quoi que ce soit.<\/p>\n  <p>Ce qui rend le ph\u00e9nom\u00e8ne redoutable, c&rsquo;est sa lenteur. Les premi\u00e8res semaines fonctionnent, tu es confiant, tu continues. L&rsquo;adaptation se cumule en silence jusqu&rsquo;au jour o\u00f9 la balance se fige.<\/p>\n  <p>C&rsquo;est pr\u00e9cis\u00e9ment le moment o\u00f9 un accompagnement comportemental se retourne contre toi. Le coach t&rsquo;expliquera que le plateau est normal, qu&rsquo;il faut pers\u00e9v\u00e9rer, revoir tes habitudes. Alors que le probl\u00e8me n&rsquo;est ni ta discipline ni ta motivation&nbsp;: c&rsquo;est le chiffre cible qui a boug\u00e9, et personne ne l&rsquo;a mesur\u00e9.<\/p>\n  <p>Noom ne mod\u00e9lise pas ce ph\u00e9nom\u00e8ne. Ton objectif calorique reste fig\u00e9 tant que tu ne mets pas \u00e0 jour ton poids \u00e0 la main. Tu peux suivre tous les cours et classer chaque aliment&nbsp;: si la cible est fausse, la m\u00e9thode ne peut pas te rattraper.<\/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; Solution Lean<\/span><\/div>\n  <h2 id=\"solution\">Comment Lean r\u00e9sout chacun des 3 probl\u00e8mes<\/h2>\n  <p>Noom et Lean ne jouent pas sur le m\u00eame terrain. Noom mise sur la psychologie du comportement&nbsp;: cours quotidiens, coachs humains, classification des aliments. C&rsquo;est coh\u00e9rent, et pour certains profils c&rsquo;est exactement ce qu&rsquo;il faut. Mais un accompagnement comportemental pos\u00e9 sur un objectif calorique faux reste un accompagnement vers la mauvaise cible. Lean travaille l&rsquo;autre moiti\u00e9 du probl\u00e8me&nbsp;: rendre ce chiffre juste, en mesurant chaque composant du TDEE (BMR&nbsp;+&nbsp;NEAT&nbsp;+&nbsp;EAT&nbsp;+&nbsp;TEF) plus l&rsquo;adaptation m\u00e9tabolique. Voici comment.<\/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\">Etapa 1<strong>BodyScan IA<\/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\">Etapa 2<strong>BMR recalcul\u00e9<\/strong><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n    <div>\n      <div class=\"m-tag\">Le BMR sur bodyfat r\u00e9el<\/div>\n      <h3>Mod\u00e8le propri\u00e9taire brevet\u00e9, bas\u00e9 sur la masse maigre<\/h3>\n      <p>Le coaching de Noom part d&rsquo;un objectif calorique calcul\u00e9 sur ton poids. Lean part de ta <strong>masse maigre<\/strong>, parce que c&rsquo;est elle qui consomme au repos&nbsp;: \u00e0 poids identique, deux personnes n&rsquo;ont pas le m\u00eame m\u00e9tabolisme. Encore faut-il conna\u00eetre son taux de masse grasse sans passer par un DEXA en clinique.<\/p>\n      <p>D&rsquo;o\u00f9 le <strong>BodyScan IA<\/strong>&nbsp;: une photo, analys\u00e9e par un mod\u00e8le entra\u00een\u00e9 sur une banque de scans DEXA, et ton bodyfat s&rsquo;affiche en quelques secondes. Refait chaque semaine, il met \u00e0 jour ton m\u00e9tabolisme automatiquement. Aucun coach humain ne peut produire cette mesure \u00e0 cette fr\u00e9quence.<\/p>\n      <p>Exit la pince \u00e0 pli cutan\u00e9, la balance \u00e0 imp\u00e9dance et ses \u00e9carts selon l&rsquo;hydratation, le DEXA et son prix. Une photo par semaine suffit.<\/p>\n    <\/div>\n  <\/div>\n\n  <div class=\"method flip\">\n    <div>\n      <div class=\"m-tag\">Pas de coefficient d&rsquo;activit\u00e9<\/div>\n      <h3>NEAT, EAT, TEF calculados separadamente<\/h3>\n      <p><strong>NEAT.<\/strong> Tes pas r\u00e9els arrivent via HealthKit (iOS) ou Google Fit (Android). L\u00e0 o\u00f9 un programme de coaching te demande de d\u00e9crire ton niveau d&rsquo;activit\u00e9, Lean lit les acc\u00e9l\u00e9rom\u00e8tres de ton t\u00e9l\u00e9phone et convertit ces pas en calories selon ton m\u00e9tabolisme. La diff\u00e9rence entre une journ\u00e9e \u00e0 4&nbsp;000 pas et une \u00e0 14&nbsp;000 se voit imm\u00e9diatement dans ton objectif du jour.<\/p>\n      <p><strong>EAT.<\/strong> Tu choisis ton sport et Lean applique le MET correspondant \u00e0 ton temps d&rsquo;effort r\u00e9el. Une heure de musculation avec ses temps de repos ne co\u00fbte pas une heure de course continue&nbsp;: les compter pareil fausse le bilan de plusieurs centaines de kcal par semaine.<\/p>\n      <p><strong>TEF.<\/strong> La digestion consomme de l&rsquo;\u00e9nergie, et pas au m\u00eame tarif selon les macros&nbsp;: 20 \u00e0 30&nbsp;% pour les prot\u00e9ines, 5 \u00e0 10&nbsp;% pour les glucides, 1 \u00e0 3&nbsp;% pour les lipides. Lean calcule ce poste sur ce que tu as r\u00e9ellement mang\u00e9, au lieu du forfait de 10&nbsp;% appliqu\u00e9 partout ailleurs.<\/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\">\n    <div class=\"m-phone\">\n      <div class=\"mini-phone\" style=\"max-width:170px\"><div class=\"notch\"><\/div><div class=\"scr\"><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\">M\u00e9thode<strong>Adaptation auto<\/strong><\/div>\n    <\/div>\n    <div>\n      <div class=\"m-tag\">Adaptation m\u00e9tabolique automatique<\/div>\n      <h3>Une premi\u00e8re mondiale sur app grand public<\/h3>\n      <p><strong>L&rsquo;adaptation m\u00e9tabolique.<\/strong> C&rsquo;est le point aveugle de tout programme comportemental&nbsp;: au bout de quelques semaines de d\u00e9ficit, ton m\u00e9tabolisme ralentit, et aucune motivation ne compense un objectif calorique devenu faux. Lean ajuste ton TDEE \u00e0 la baisse selon les fourchettes publi\u00e9es (M\u00fcller 2015, Doucet 2001), semaine apr\u00e8s semaine.<\/p>\n      <p>Au-del\u00e0 de 10 \u00e0 15&nbsp;% d&rsquo;adaptation, l&rsquo;app peut recommander un retour \u00e0 la maintenance pour relancer le m\u00e9tabolisme avant de repartir. C&rsquo;est ce que fait un pr\u00e9parateur, sauf que Lean le calcule sur tes donn\u00e9es.<\/p>\n      <p>Aucun niveau d&rsquo;activit\u00e9 \u00e0 d\u00e9clarer, aucune case coch\u00e9e une fois pour toutes. Chaque brique est mesur\u00e9e, chaque semaine.<\/p>\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; Tableau comparatif<\/span><\/div>\n  <h2 id=\"tab\">Lean face \u00e0 Noom, crit\u00e8re par crit\u00e8re<\/h2>\n  <p>Lecture honn\u00eate des forces et faiblesses de chaque app. Aucun crit\u00e8re ne porte sur le prix.<\/p>\n\n  <div class=\"table\" role=\"table\" aria-label=\"Comparatif Lean face \u00e0 Noom\">\n    <div class=\"table-row head\" role=\"row\">\n      <div role=\"columnheader\">Crit\u00e9rio<\/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\/05\/logo-noom-real.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> <span>Noom<\/span><\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Formule BMR<\/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> Mod\u00e8le propri\u00e9taire brevet\u00e9 (masse maigre)<\/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> Mifflin-St Jeor 1990, sans option masse maigre<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Prend en compte le bodyfat<\/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> Oui, mesur\u00e9 dans l&rsquo;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> Non, aucune saisie bodyfat possible<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Mesure du bodyfat dans l&rsquo;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> BodyScan IA via photo<\/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> Non<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">NEAT (pas, activit\u00e9 hors 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> Calcul\u00e9e sur les pas r\u00e9els chaque jour<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Sync HealthKit, add-on calorique exercice, mais hors recompute TDEE<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">EAT (d\u00e9pense exercice)<\/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> Par sport via MET, temps effectif<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> S\u00e9lection sport simple, base d&rsquo;exercices standard<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">TEF (digestion)<\/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> Calcul\u00e9e selon macros, int\u00e9gr\u00e9e au 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> Non, macros affich\u00e9s sans calcul TEF<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Adapta\u00e7\u00e3o metab\u00f3lica<\/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> Automatique, semaine par semaine<\/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> Non<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Coefficient d&rsquo;activit\u00e9 \u00e0 choisir<\/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> Non, calcul\u00e9 sur donn\u00e9es r\u00e9elles<\/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> Oui, niveau statique choisi via le quiz d&rsquo;inscription<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Scan photo IA d&rsquo;un plat<\/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> Oui, illimit\u00e9<\/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> Non, saisie manuelle ou code-barres<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Scan code-barres<\/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> Oui<\/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> Oui<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Base de donn\u00e9es alimentaire<\/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, cur\u00e9e<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Base propri\u00e9taire + classification vert\/jaune\/rouge<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Recommandation d\u00e9ficit calorique<\/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> Adapt\u00e9e au TDEE r\u00e9el<\/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> Objectif fixe, recalcul manuel requis<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Coaching humain et th\u00e9rapie comportementale<\/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> Hors scope, focus calcul TDEE<\/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> Coachs humains, groupes, cours quotidiens<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Classification d&rsquo;aliments vert\/jaune\/rouge<\/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> Hors scope<\/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> R\u00e9f\u00e9rence p\u00e9dagogique grand public<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Couverture EU et localisation<\/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> FR, EN, ES, PT, IT, DE, PL, HU<\/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> EN, ES, DE et autres, fond\u00e9e \u00e0 NYC 2008<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">R\u00e9putation et taille audience<\/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+ users, jeune app FR<\/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> 4.5\/5, 50M+ t\u00e9l\u00e9chargements, audience femmes 35-55<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Modelo de neg\u00f3cio<\/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, essai gratuit 7 jours sur l&rsquo;annuel<\/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> Abonnement payant, p\u00e9riode d&rsquo;essai courte<\/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 m\u00e9thodes pour tracker un repas<\/h2>\n  <p>Un programme de coaching tient sur la dur\u00e9e si le geste quotidien est simple. C&rsquo;est exactement le pari de Lean sur le tracking&nbsp;: trois fa\u00e7ons d&rsquo;enregistrer un repas, pour qu&rsquo;aucune situation ne devienne une excuse pour abandonner.<\/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\">M\u00e9thode 1<strong>Base de donn\u00e9es<\/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\">M\u00e9thode 2<strong>Code-barres<\/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\">M\u00e9thode 3<strong>Scan photo IA<\/strong><\/div>\n    <\/div>\n  <\/div>\n\n  <ol>\n    <li><strong>Recherche dans la base de donn\u00e9es.<\/strong> Base cur\u00e9e, USDA + OpenFoodFacts. Pas de bruit communautaire, pas de \u00ab&nbsp;Poulet r\u00f4ti&nbsp;\u00bb rentr\u00e9 47 fois par 47 utilisateurs diff\u00e9rents avec 47 valeurs diff\u00e9rentes.<\/li>\n    <li><strong>Scan de code-barres.<\/strong> Standard. Tu scannes ton paquet de p\u00e2tes, tu obtiens les macros.<\/li>\n    <li><strong>Scan photo IA d&rsquo;un plat.<\/strong> Tu prends en photo ton assiette, l&rsquo;IA d\u00e9tecte les aliments, tu obtiens les calories et les macros par aliment. Noom ne propose pas cette fonctionnalit\u00e9.<\/li>\n  <\/ol>\n  <p>Le scan photo IA sert surtout quand tu manges dehors. Noom te demandera de qualifier ton plat par couleur&nbsp;; Lean te demande une photo, et tu passes \u00e0 autre chose. Sur un d\u00e9jeuner d&rsquo;affaires ou un d\u00eener chez des amis, la diff\u00e9rence de friction est d\u00e9cisive.<\/p>\n  <p>Au-dessus du repas, Lean affiche un TDEE qui bouge pendant la journ\u00e9e&nbsp;: plus tu marches, plus ton objectif calorique monte. Un programme hebdomadaire fixe ne peut pas restituer cette variation quotidienne.<\/p>\n  <p>Et pour hi\u00e9rarchiser ce qui compte vraiment, la Pyramide de Progression&nbsp;:<\/p>\n\n  <div class=\"pyramid\" aria-label=\"Pyramide de Progression Lean\">\n    <div class=\"level l1\"><span>Adh\u00e9rence<\/span><span class=\"k\">Base<\/span><\/div>\n    <div class=\"level l2\"><span>Objectif calorique<\/span><span class=\"k\">\u00c9tage 2<\/span><\/div>\n    <div class=\"level l3\"><span>Pas \/ NEAT<\/span><span class=\"k\">\u00c9tage 3<\/span><\/div>\n    <div class=\"level l4\"><span>Macronutriments<\/span><span class=\"k\">Sommet<\/span><\/div>\n  <\/div>\n  <div class=\"pyramid-cap\">Ne pas br\u00fbler les \u00e9tapes. Si tu n&rsquo;es pas r\u00e9gulier dans le tracking, optimiser les macros au pourcent pr\u00e8s ne sert \u00e0 rien.<\/div>\n<\/section>\n\n<section aria-labelledby=\"noom-better\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">07 &middot; Honn\u00eatet\u00e9<\/span><\/div>\n  <h2 id=\"noom-better\">Ce que Noom fait mieux<\/h2>\n  <p>Lean n&rsquo;est pas parfait, et Noom a plusieurs vraies forces qu&rsquo;il faut reconna\u00eetre. Lecture honn\u00eate, crit\u00e8re par crit\u00e8re, sur les axes o\u00f9 Noom reste devant. Aucun de ces axes n&rsquo;est secondaire : ce sont des piliers r\u00e9els de la promesse Noom, et ce qui explique son adoption massive sur la cible femmes 35-55 sur sujet long-term weight loss.<\/p>\n\n  <div class=\"scorecard rev\" aria-label=\"Scorecard Noom face \u00e0 Lean sur 4 axes psychologie et adh\u00e9rence\">\n    <div class=\"scorecard-head\">\n      <div class=\"h-crit\">Axe<\/div>\n      <div class=\"h-brand\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/logo-noom-real.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> Noom<\/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\">Coaching humain et th\u00e9rapie comportementale<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:94%\"><\/i><\/div><div class=\"v\">9,4<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:20%\"><\/i><\/div><div class=\"v\">2,0<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Cours quotidiens de psychologie alimentaire<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:92%\"><\/i><\/div><div class=\"v\">9,2<\/div><\/div>\n      <div class=\"bar 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\">Classification vert\/jaune\/rouge intuitive<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:88%\"><\/i><\/div><div class=\"v\">8,8<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:30%\"><\/i><\/div><div class=\"v\">3,0<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Travail sur l&rsquo;adh\u00e9rence long terme<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:90%\"><\/i><\/div><div class=\"v\">9,0<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:70%\"><\/i><\/div><div class=\"v\">7,0<\/div><\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>Lecture honn\u00eate.<\/strong> Sur le coaching humain, Noom est la r\u00e9f\u00e9rence grand public : ton coach \u00e9change avec toi par chat, les groupes de soutien (communaut\u00e9 Noom) tournent en continu, et c&rsquo;est un vrai accompagnement \u00e9motionnel pour qui en a besoin. Sur les cours quotidiens de psychologie alimentaire (5 \u00e0 10 minutes chaque jour, inspir\u00e9s de la TCC, th\u00e9rapie cognitivo-comportementale), Noom a investi massivement et c&rsquo;est unique sur le march\u00e9 : aucun autre tracker calorique ne propose ce contenu p\u00e9dagogique structur\u00e9. Sur la classification vert\/jaune\/rouge, c&rsquo;est un m\u00e9canisme intuitif qui fait gagner du temps \u00e0 l&rsquo;utilisatrice et qui marche bien pour les profils qui ne veulent pas plonger dans les macros. Sur l&rsquo;adh\u00e9rence long terme, Chin 2016 et de nombreuses m\u00e9ta-analyses sur la th\u00e9rapie comportementale appliqu\u00e9e \u00e0 la perte de poids montrent des gains significatifs \u00e0 6 et 12 mois. Noom capitalise scientifiquement sur cet axe.<\/p>\n  <p>Si ton angle principal est le travail psychologique sur les habitudes alimentaires, si tu as besoin d&rsquo;un coach humain pour tenir, ou si la classification vert\/jaune\/rouge t&rsquo;aide \u00e0 faire des choix sans calculer, Noom est plus pertinent que Lean. Si ton angle est la pr\u00e9cision du <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/tdee-calculator\/\">calcul TDEE<\/a>, le bodyfat mesur\u00e9 chaque semaine via BodyScan IA, et l&rsquo;adaptation m\u00e9tabolique automatique, c&rsquo;est exactement ce qui vient d&rsquo;\u00eatre d\u00e9montr\u00e9 dans les 3 sections pr\u00e9c\u00e9dentes. Beaucoup d&rsquo;utilisateurs font tourner Lean pour la mesure et Noom en parall\u00e8le pour le coaching psychologique, c&rsquo;est tout \u00e0 fait d\u00e9fendable.<\/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; Pour qui<\/span><\/div>\n  <h2 id=\"forwho\">Pour qui Lean est-il fait<\/h2>\n  <p>Quatre profils. Si l&rsquo;un d&rsquo;eux te correspond, Lean a des chances de te convenir.<\/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>Tu as suivi Noom s\u00e9rieusement et tu n&rsquo;as pas perdu<\/h4>\n        <p>Tu as fait le quiz, suivi les cours, class\u00e9 tes repas par couleur, \u00e9chang\u00e9 avec ton coach, et tenu plusieurs semaines sans que la courbe suive vraiment.<\/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>Tu stagnes apr\u00e8s plusieurs semaines de cut<\/h4>\n        <p>Le plateau s&rsquo;installe apr\u00e8s quatre \u00e0 huit semaines. C&rsquo;est la signature de l&rsquo;adaptation m\u00e9tabolique&nbsp;: Lean la calcule et corrige ton objectif au lieu de te renvoyer \u00e0 ta motivation.<\/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>Tu veux comprendre ton m\u00e9tabolisme<\/h4>\n        <p>Tu veux voir le d\u00e9tail du calcul&nbsp;: BMR, NEAT, EAT et TEF affich\u00e9s s\u00e9par\u00e9ment, adaptation expliqu\u00e9e \u00e0 part, plut\u00f4t qu&rsquo;un chiffre unique comment\u00e9 par un coach.<\/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>Tu veux un tracking qui dure 12 mois<\/h4>\n        <p>Tu manges souvent dehors et tu as besoin d&rsquo;un enregistrement rapide&nbsp;: photo, base cur\u00e9e ou code-barres selon le contexte.<\/p>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>Noom reste plus pertinent pour<\/strong>&nbsp;: travailler psychologiquement sur les habitudes alimentaires, profiter d&rsquo;un coach humain et de groupes de soutien, suivre des cours quotidiens de th\u00e9rapie cognitivo-comportementale appliqu\u00e9s \u00e0 la perte de poids, ou s&rsquo;appuyer sur la classification vert\/jaune\/rouge pour faire des choix sans calculer. La pr\u00e9cision du calcul TDEE et l&rsquo;adaptation m\u00e9tabolique ne font juste pas partie de sa promesse principale.<\/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; Migra\u00e7\u00e3o<\/span><\/div>\n  <h2 id=\"migrate\">Passer de Noom \u00e0 Lean (ou utiliser les deux) en 3 minutes<\/h2>\n\n  <div class=\"steps\">\n    <div class=\"step\"><div class=\"sn\">01<\/div><h4>T\u00e9l\u00e9charge Lean<\/h4><p>App Store ou Play Store. Inscription en trente secondes, sans questionnaire de vingt minutes.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">02<\/div><h4>BodyScan IA<\/h4><p>Une photo, cinq secondes&nbsp;: ton taux de masse grasse s&rsquo;affiche.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">03<\/div><h4>Poids &amp; taille<\/h4><p>Tu saisis ton poids et ta taille. Rien d&rsquo;autre n&rsquo;est demand\u00e9.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">04<\/div><h4>Lean calcule<\/h4><p>BMR sur masse maigre r\u00e9elle, NEAT depuis tes pas via HealthKit ou Google Fit, EAT par MET, TEF sur tes macros, et l&rsquo;adaptation m\u00e9tabolique qui module le tout semaine apr\u00e8s semaine.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">05<\/div><h4>Tracke un repas<\/h4><p>Photo, code-barres ou base de donn\u00e9es&nbsp;: tu choisis selon le repas.<\/p><\/div>\n  <\/div>\n\n  <p style=\"margin-top:24px\"><strong>Note importante.<\/strong> Lean n&rsquo;importe pas ton historique Noom automatiquement, ni tes \u00e9changes avec ton coach humain. Si tu appr\u00e9cies le coaching psychologique Noom et les cours quotidiens, beaucoup d&rsquo;utilisateurs continuent \u00e0 utiliser Noom pour le travail comportemental et les groupes de soutien, tout en utilisant Lean au quotidien pour le calcul TDEE et le tracking pr\u00e9cis. La sync HealthKit \/ Google Health Connect, elle, prend le relais imm\u00e9diatement pour tes pas et ton historique d&rsquo;activit\u00e9.<\/p>\n\n  <div class=\"cta-band rev\">\n    <div class=\"l\">T\u00e9l\u00e9charger Lean et commencer le BodyScan IA d\u00e8s maintenant. Inscription gratuite.<\/div>\n    <div class=\"stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"deblock-h\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">10 &middot; Ce que Lean d\u00e9bloque<\/span><\/div>\n  <h2 id=\"deblock-h\">Ce que Lean fait, et que Noom ne fait pas (sur le TDEE)<\/h2>\n  <p>Six fonctionnalit\u00e9s absentes des trackers grand public. Elles reposent toutes sur le m\u00eame choix&nbsp;: mesurer chaque composant du TDEE plut\u00f4t que l&rsquo;estimer, puis l&rsquo;habiller de p\u00e9dagogie.<\/p>\n\n  <div class=\"feat-stack\">\n    <div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">BodyScan IA illimit\u00e9<\/div><p class=\"fd\">Ton taux de masse grasse, obtenu depuis une photo et actualis\u00e9 chaque semaine. C&rsquo;est la variable qui rend le m\u00e9tabolisme individuel, et aucun programme de coaching ne la mesure.<\/p><\/div><div class=\"fc\">Bodyfat<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">Scan photo IA d&rsquo;un plat illimit\u00e9<\/div><p class=\"fd\">Un repas au restaurant enregistr\u00e9 en deux secondes, sans balance ni saisie. La friction en moins qui fait tenir sur douze mois, sans avoir besoin qu&rsquo;un coach te relance.<\/p><\/div><div class=\"fc\">Adh\u00e9rence<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">Adaptation m\u00e9tabolique automatique<\/div><p class=\"fd\">Ton TDEE se corrige semaine apr\u00e8s semaine selon les fourchettes publi\u00e9es. Les plateaux qu&rsquo;un accompagnement attribue \u00e0 la motivation trouvent ici leur explication chiffr\u00e9e.<\/p><\/div><div class=\"fc\">Adapta\u00e7\u00e3o<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">04<\/div><div><div class=\"ft\">TDEE d\u00e9compos\u00e9e live<\/div><p class=\"fd\">BMR, NEAT, EAT et TEF affich\u00e9s s\u00e9par\u00e9ment et mis \u00e0 jour dans la journ\u00e9e. Ton objectif bouge avec ton activit\u00e9 r\u00e9elle, au lieu d&rsquo;\u00eatre arr\u00eat\u00e9 au r\u00e9veil.<\/p><\/div><div class=\"fc\">Live<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">05<\/div><div><div class=\"ft\">Historique complet et tendances<\/div><p class=\"fd\">Tes tendances de poids, de masse grasse et de masse maigre sur plusieurs mois. Tu identifies tes cycles au lieu de r\u00e9agir \u00e0 la pes\u00e9e du jour.<\/p><\/div><div class=\"fc\">Historique<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">06<\/div><div><div class=\"ft\">3 m\u00e9thodes de tracking unifi\u00e9es<\/div><p class=\"fd\">Une hi\u00e9rarchie claire de ce qui compte&nbsp;: l&rsquo;adh\u00e9rence d&rsquo;abord, puis l&rsquo;objectif calorique, puis les pas. De quoi savoir quoi ajuster quand \u00e7a bloque.<\/p><\/div><div class=\"fc\">Tracking<\/div><\/div>\n  <\/div>\n\n  <p style=\"margin-top:26px\">Tu installes l&rsquo;app gratuitement, tu testes sans engagement, tu d\u00e9cides ensuite si l&rsquo;outil colle \u00e0 ton objectif.<\/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\">Perguntas frequentes<\/h2>\n  <div class=\"faq\">\n    <details><summary>Noom est connu pour son coaching psychologique, pourquoi le comparer \u00e0 Lean sur le TDEE&nbsp;?<\/summary><div class=\"ans\">Noom est r\u00e9put\u00e9 pour son approche comportementale (cours quotidiens inspir\u00e9s de la TCC, coachs humains, classification d&rsquo;aliments vert\/jaune\/rouge). C&rsquo;est une vraie force pour l&rsquo;adh\u00e9rence et le travail psychologique sur l&rsquo;alimentation. Mais le moteur calorique sous-jacent reste Mifflin-St Jeor 1990 sans bodyfat, plus un facteur d&rsquo;activit\u00e9 statique choisi via le quiz d&rsquo;inscription. Sur le TDEE, le moteur est basique. Lean recalcule chaque jour ton BMR sur ton bodyfat r\u00e9el mesur\u00e9 par BodyScan IA, et module par l&rsquo;adaptation m\u00e9tabolique. Les deux apps ne jouent pas sur le m\u00eame terrain.<\/div><\/details>\n    <details><summary>Pourquoi Noom ne calcule pas le BMR sur le bodyfat r\u00e9el&nbsp;?<\/summary><div class=\"ans\">Noom applique Mifflin-St Jeor 1990 par d\u00e9faut sans option masse-maigre. Aucune mesure de bodyfat n&rsquo;est int\u00e9gr\u00e9e dans l&rsquo;app, et aucune \u00e9quation type Katch-McArdle n&rsquo;est propos\u00e9e m\u00eame en param\u00e8tres avanc\u00e9s. La cons\u00e9quence est m\u00e9canique : deux utilisatrices de m\u00eame poids mais avec 22 et 38 pour cent de bodyfat obtiennent le m\u00eame BMR Noom, alors que leur d\u00e9pense r\u00e9elle peut diff\u00e9rer de 400 kcal par jour. Lean int\u00e8gre le BodyScan IA pour mesurer ton bodyfat depuis une simple photo, \u00e0 refaire chaque semaine.<\/div><\/details>\n    <details><summary>La classification vert\/jaune\/rouge de Noom est-elle une vraie mesure m\u00e9tabolique&nbsp;?<\/summary><div class=\"ans\">Non. Le syst\u00e8me vert\/jaune\/rouge classe les aliments par densit\u00e9 calorique (l\u00e9gumes en vert, f\u00e9culents en jaune, gras et sucres en rouge). C&rsquo;est un outil p\u00e9dagogique de comportement alimentaire, pas une mesure de d\u00e9pense \u00e9nerg\u00e9tique. C&rsquo;est efficace pour faire prendre conscience des choix, mais \u00e7a n&rsquo;influence pas le calcul TDEE. Sur ton m\u00e9tabolisme r\u00e9el, Noom reste sur Mifflin 1990 plus quelques cases d&rsquo;activit\u00e9 statique. La classification couleur ne modifie pas l&rsquo;objectif calorique calcul\u00e9.<\/div><\/details>\n    <details><summary>Noom importe les pas via HealthKit, \u00e7a suffit pour la NEAT&nbsp;?<\/summary><div class=\"ans\">Noom importe les pas et l&rsquo;activit\u00e9 via Apple Health et Google Fit, mais les utilise pour estimer une d\u00e9pense exercice ajout\u00e9e \u00e0 l&rsquo;objectif calorique journalier. Le facteur d&rsquo;activit\u00e9 statique choisi au quiz d&rsquo;inscription reste la base du calcul TDEE. Lean, \u00e0 l&rsquo;inverse, calcule la NEAT directement \u00e0 partir des pas r\u00e9els mesur\u00e9s chaque jour, sans coefficient \u00e0 choisir.<\/div><\/details>\n    <details><summary>Le coaching humain Noom remplace-t-il un calcul TDEE pr\u00e9cis&nbsp;?<\/summary><div class=\"ans\">Le coaching humain Noom est une vraie valeur ajout\u00e9e pour l&rsquo;adh\u00e9rence et le travail psychologique sur les habitudes. Chin 2016 et de nombreuses m\u00e9ta-analyses montrent que la th\u00e9rapie comportementale am\u00e9liore la perte de poids \u00e0 6 et 12 mois. Mais le coaching n&rsquo;agit pas sur l&rsquo;\u00e9quation TDEE sous-jacente. Si ton objectif calorique est calcul\u00e9 sur Mifflin 1990 sans bodyfat et un PAL statique, ton coach ne va pas corriger l&rsquo;\u00e9quation, il va t&rsquo;encourager \u00e0 tenir un d\u00e9ficit potentiellement faux. Le coaching est un multiplicateur d&rsquo;adh\u00e9rence, pas un substitut \u00e0 la mesure objective.<\/div><\/details>\n    <details><summary>Peut-on utiliser Lean et Noom en parall\u00e8le&nbsp;?<\/summary><div class=\"ans\">Oui, c&rsquo;est d\u00e9fendable. Si tu appr\u00e9cies le coaching humain Noom, les cours quotidiens et la p\u00e9dagogie comportementale, tu peux conserver Noom pour l&rsquo;aspect psychologique et habitudes. Lean prend en charge le moteur m\u00e9tabolique pr\u00e9cis (BMR sur bodyfat r\u00e9el, NEAT, EAT, TEF, adaptation). Les bases de donn\u00e9es sont diff\u00e9rentes (USDA + OpenFoodFacts c\u00f4t\u00e9 Lean, base propri\u00e9taire c\u00f4t\u00e9 Noom) donc l&rsquo;effort de double saisie est r\u00e9el : c&rsquo;est un trade-off \u00e0 arbitrer selon tes priorit\u00e9s.<\/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; Conclusion<\/span><\/div>\n  <h2 id=\"conclu\">Coaching face \u00e0 mesure<\/h2>\n  <p>Ce n&rsquo;est pas Noom face \u00e0 Lean en marketing. C&rsquo;est le coaching psychologique face \u00e0 la pr\u00e9cision m\u00e9tabolique, deux promesses diff\u00e9rentes.<\/p>\n  <p>Noom reste l&rsquo;une des meilleures apps grand public pour le travail comportemental sur l&rsquo;alimentation, et personne dans le grand public ne fait mieux sur les cours quotidiens de psychologie alimentaire et l&rsquo;accompagnement par coach humain. Mais pour ton TDEE, Noom utilise Mifflin-St Jeor 1990 sans bodyfat mesur\u00e9 dans l&rsquo;app, plus un facteur d&rsquo;activit\u00e9 fig\u00e9 que tu coches une seule fois pendant le quiz d&rsquo;inscription, et ignore l&rsquo;adaptation m\u00e9tabolique. Le combo des trois rend tout suivi calorique pr\u00e9cis impossible au-del\u00e0 de quelques semaines de cut. C&rsquo;est math\u00e9matique. Aucun coach humain ne corrige une \u00e9quation qu&rsquo;il ne voit pas.<\/p>\n  <p>Lean a \u00e9t\u00e9 construit pour faire exactement l&rsquo;inverse&nbsp;: BMR bas\u00e9 sur le <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/depense-energetique-totale-v2\/\">gordura corporal real<\/a> (mesur\u00e9 par BodyScan IA) via un mod\u00e8le propri\u00e9taire brevet\u00e9, <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/neat-depense-non-sportive\/\">NEAT par pas r\u00e9els<\/a>, EAT par sport et MET, <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/effet-thermique-des-aliments\/\">TEF par macros<\/a>, plus l&rsquo;adaptation m\u00e9tabolique qui module le BMR semaine apr\u00e8s semaine. Chaque composant calcul\u00e9 pr\u00e9cis\u00e9ment, sans coefficient magique, sans wrapping psychologique.<\/p>\n  <p>Noom reste tr\u00e8s solide sur le coaching comportemental et l&rsquo;accompagnement humain. Les meilleurs r\u00e9sultats viennent souvent de combiner les deux : mesurer juste (Lean) ET agir avec discipline (parfois aid\u00e9 par un coach Noom). Si tu as essay\u00e9 Noom s\u00e9rieusement et que tu n&rsquo;as pas eu les r\u00e9sultats que tu esp\u00e9rais sur ton cut, le probl\u00e8me n&rsquo;est pas toi, ni Noom sur sa promesse psychologique. Le probl\u00e8me est le TDEE fig\u00e9 sous le capot. Change le moteur, garde le coach en parall\u00e8le si tu en as besoin.<\/p>\n<\/section>\n\n<div class=\"get-band rev\">\n  <div class=\"kicker\">Download<\/div>\n  <h3>A Lean pode ser baixada gratuitamente<\/h3>\n  <p>iOS et Android. Le BodyScan IA fonctionne avec une simple photo. Pas de pince \u00e0 pli cutan\u00e9, pas de balance imp\u00e9dance, pas de DEXA.<\/p>\n  <div class=\"stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" 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\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" 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\" \/>\n    <\/a>\n  <\/div>\n<\/div>\n\n<section aria-labelledby=\"links\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">Para ir al\u00e9m<\/span><\/div>\n  <h3 id=\"links\" style=\"margin-top:0\">Maillage interne<\/h3>\n  <ul>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/tdee-calculator\/\">Calculadora TDEE gratuita online<\/a> &middot; version web, sans inscription, m\u00eame logique que l&rsquo;app (BMR + NEAT + EAT + TEF).<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/depense-energetique-totale-v2\/\">Comprendre la TDEE en d\u00e9tail (BMR, NEAT, EAT, TEF, adaptation)<\/a> &middot; article scientifique de fond.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/comment-compter-ses-calories\/\">Como contar suas calorias corretamente<\/a> &middot; guide pratique pour d\u00e9butants.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/neat-depense-non-sportive\/\">NEAT&nbsp;: gasto por passos e atividade fora do esporte<\/a>.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/effet-thermique-des-aliments\/\">TEF&nbsp;: a digest\u00e3o queima calorias<\/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\">Fontes<\/span><\/div>\n  <h3 id=\"src\" style=\"margin-top:0;color:var(--ink)\">Bibliographie<\/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. et al. (1990). A new predictive equation for resting energy expenditure in healthy individuals. American Journal of Clinical Nutrition.<\/li>\n    <li>Katch V.L., McArdle W.D. (1973). Prediction of body density from simple anthropometric measurements in college-age men and women. Human Biology.<\/li>\n    <li>Chin S.O. et al. (2016). Successful weight reduction and maintenance by using a smartphone application in those with overweight and obesity. Scientific Reports, behavioral therapy and weight loss.<\/li>\n    <li>Frankenfield D.C. et al. (2013). Validation of Mifflin-St Jeor equation in obese and non-obese populations. PubMed 23631843.<\/li>\n    <li>M\u00fcller M.J., Bosy-Westphal A. (2015). Adaptive thermogenesis with weight loss in humans. Obesity, revisite Minnesota. PubMed 26399868.<\/li>\n    <li>Doucet E. et al. (2001). Evidence for the existence of adaptive thermogenesis during weight loss. British Journal of Nutrition.<\/li>\n    <li>Westerterp K.R. (2004). Diet induced thermogenesis. Nutrition and Metabolism.<\/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>Article publi\u00e9 le 24 mai 2026. Mis \u00e0 jour r\u00e9guli\u00e8rement avec les retours d&rsquo;utilisateurs et les nouvelles \u00e9tudes pertinentes. Lean est disponible sur iOS et Android.<\/p>\n      <\/div>\n      <div class=\"stores\">\n        <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n        <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n      <\/div>\n    <\/div>\n  <\/div>\n<\/footer>\n\n<script>\n(function(){\n  var bar = document.getElementById('progBar');\n  function up(){\n    var h = document.documentElement;\n    var sc = (h.scrollTop)\/Math.max(1,(h.scrollHeight - h.clientHeight));\n    bar.style.transform = 'scaleX(' + Math.max(0,Math.min(1,sc)) + ')';\n  }\n  document.addEventListener('scroll', up, {passive:true});\n  up();\n})();\n\n(function(){\n  if (!('IntersectionObserver' in window)) {\n    document.querySelectorAll('.rev').forEach(function(n){n.classList.add('on')});\n    return;\n  }\n  var obs = new IntersectionObserver(function(entries){\n    entries.forEach(function(e){\n      if (e.isIntersecting) { e.target.classList.add('on'); obs.unobserve(e.target); }\n    });\n  }, {threshold:0.12});\n  document.querySelectorAll('.rev').forEach(function(n){ obs.observe(n); });\n})();\n\n(function(){\n  var phoneImg = document.getElementById('phoneImg');\n  var phoneBack = document.getElementById('phoneBack');\n  var zones = document.getElementById('phoneZones');\n  var topTabs = document.querySelectorAll('.phone-tabs button');\n  var navTaps = document.querySelectorAll('.phone-navbar button');\n\n  var tabMap = {\n    bilan:    {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp',     drill:false},\n    kcal:     {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp',      drill:false},\n    depense:  {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp',   drill:true},\n    strategie:{src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp', drill:false}\n  };\n  var subMap = {\n    BMR:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp',\n    NEAT: 'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp',\n    EAT:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp',\n    TEF:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp'\n  };\n  var currentTab = 'depense';\n\n  function setActive(tab){\n    topTabs.forEach(function(b){ b.classList.toggle('on', b.dataset.tab===tab); });\n  }\n  function showTab(tab){\n    var t = tabMap[tab]; if(!t) return;\n    currentTab = tab;\n    phoneImg.style.opacity = 0;\n    setTimeout(function(){\n      phoneImg.className = 'phone-bg tab-' + tab;\n      phoneImg.style.opacity = 1;\n      zones.style.display = t.drill ? 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-->\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;\">Leia tamb\u00e9m<\/p><ul style=\"list-style:none;padding:0;margin:0;display:grid;grid-template-columns:1fr;gap:10px;\"><li><a href=\"\/pt\/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;\">Metabolismo basal (BMR): tudo o que voc\u00ea precisa saber para calcul\u00e1-lo <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Defini\u00e7\u00e3o, equa\u00e7\u00e3o do TDEE, 4 f\u00f3rmulas hist\u00f3ricas, por que a gordura corporal muda tudo.<\/span><\/a><\/li><li><a href=\"\/pt\/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;\">Gasto energ\u00e9tico total (TDEE): a f\u00f3rmula can\u00f4nica BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Entenda as 4 pe\u00e7as + a adapta\u00e7\u00e3o metab\u00f3lica, fontes cient\u00edficas 2025.<\/span><\/a><\/li><li><a href=\"\/pt\/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: seu gasto esportivo real, sess\u00e3o por sess\u00e3o <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Os MET corretos, a armadilha da contagem dupla, o que Garmin e MyFitnessPal deixam passar.<\/span><\/a><\/li><li><a href=\"\/pt\/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;\">Melhores aplicativos para contar calorias em 2026: 8 aplicativos testados <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=\"\/pt\/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;\">Alternativa ao MyFitnessPal em 2026: as 5 op\u00e7\u00f5es reais testadas <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Comparatif honn\u00eate, pr\u00e9cision TDEE, ergonomie.<\/span><\/a><\/li><li><a href=\"\/pt\/comparatifs\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Todos os comparativos da Lean com os principais aplicativos de calorias <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=\"\/pt\/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 frente ao MyFitnessPal: a f\u00f3rmula TDEE que muda tudo <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Por que o MFP erra no seu gasto cal\u00f3rico real.<\/span><\/a><\/li><li><a href=\"\/pt\/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;\">Calculateur TDEE : la formule canonique BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Calculateur bodyfat-aware avec breakdown des 4 briques m\u00e9taboliques.<\/span><\/a><\/li><\/ul><\/aside>","protected":false},"excerpt":{"rendered":"<p>Lean Calculateur TDEE Accueil &nbsp;\/&nbsp; Lean vs Noom Comparatif &middot; Nutrition &amp; TDEE Lean face \u00e0 Noom. Coaching psychologique face \u00e0 la pr\u00e9cision m\u00e9tabolique. Noom vend du coaching comportemental pour changer tes habitudes. Lean voit ta d\u00e9pense r\u00e9elle. Deux promesses qui ne jouent pas sur le m\u00eame terrain. L&rsquo;\u00e9quipe Lean &middot; Lecture 12&nbsp;min &middot; Mis [&hellip;]<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-lvm-blank","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1425","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Lean face \u00e0 Noom : coaching psychologique face \u00e0 la pr\u00e9cision m\u00e9tabolique - Lean<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/lean-app.com\/pt\/lean-vs-noom\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Lean face \u00e0 Noom : coaching psychologique face \u00e0 la pr\u00e9cision m\u00e9tabolique - Lean\" \/>\n<meta property=\"og:description\" content=\"Lean Calculateur TDEE Accueil &nbsp;\/&nbsp; Lean vs Noom Comparatif &middot; Nutrition &amp; TDEE Lean face \u00e0 Noom. 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