{"id":1241,"date":"2026-05-21T18:28:26","date_gmt":"2026-05-21T18:28:26","guid":{"rendered":"https:\/\/lean-app.com\/?p=1241"},"modified":"2026-09-08T18:17:56","modified_gmt":"2026-09-08T18:17:56","slug":"lean-vs-myfitnesspal","status":"publish","type":"post","link":"https:\/\/lean-app.com\/pt\/lean-vs-myfitnesspal\/","title":{"rendered":"Lean vs MyFitnessPal: a f\u00f3rmula TDEE que muda tudo"},"content":{"rendered":"<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp\" fetchpriority=\"low\">\n<script data-wpmeteor-nooptimize=\"true\" src=\"https:\/\/cdn.jsdelivr.net\/npm\/chart.js@4.4.4\/dist\/chart.umd.min.js\"><\/script>\n<script data-wpmeteor-nooptimize=\"true\" src=\"https:\/\/cdn.jsdelivr.net\/npm\/chartjs-plugin-annotation@3.1.0\/dist\/chartjs-plugin-annotation.min.js\"><\/script>\n<style id=\"lvm-shell-styles\">#lvm-shell{\n  --bg:#FFFFFF; --paper:#F7F6F2; --paper-2:#F1EFE7;\n  --ink:#0E0E10; --ink-2:#1D1D1F; --muted:#6E6E73; --dim:#86868B;\n  --rule:#E8E6DF; --rule-soft:#EFEDE5;\n  --pink:#FF2D6E; --pink-soft:rgba(255,45,110,0.06);\n  --mfp:#A8A192;\n  --green:#0F8F5C; --red:#D02E2E; --amber:#C8A019;\n  --font-display:-apple-system,\"SF Pro Display\",system-ui,\"Helvetica Neue\",sans-serif;\n  --font-text:-apple-system,\"SF Pro Text\",system-ui,sans-serif;\n  --font-mono:ui-monospace,\"SF Mono\",Menlo,Consolas,monospace;\n}\n#lvm-shell *{box-sizing:border-box;-webkit-text-size-adjust:100%}\n#lvm-shell, #lvm-shell{margin:0;padding:0;background:var(--bg);color:var(--ink-2);font-family:var(--font-text);font-size:17px;line-height:1.7;-webkit-font-smoothing:antialiased}\n#lvm-shell ::selection{background:rgba(255,45,110,0.18);color:var(--ink)}\n#lvm-shell img{max-width:100%;display:block}\n#lvm-shell a{color:inherit}\n\n#lvm-shell .progress{position:fixed;top:0;left:0;right:0;height:2px;background:transparent;z-index:1000}\n#lvm-shell .progress > i{display:block;height:100%;width:100%;background:var(--pink);transform-origin:0 50%;transform:scaleX(0);transition:transform .05s linear}\n\n#lvm-shell .nav{position:sticky;top:0;z-index:50;background:rgba(255,255,255,.86);backdrop-filter:saturate(180%) blur(14px);-webkit-backdrop-filter:saturate(180%) blur(14px);border-bottom:1px solid var(--rule)}\n#lvm-shell .nav-row{max-width:1160px;margin:0 auto;display:flex;align-items:center;gap:14px;padding:10px 22px}\n#lvm-shell .nav-brand{display:flex;align-items:center;gap:9px;text-decoration:none;color:var(--ink)}\n#lvm-shell .nav-brand img{width:28px;height:28px;border-radius:7px;object-fit:cover}\n#lvm-shell .nav-brand span{font-family:var(--font-display);font-weight:600;font-size:18px;letter-spacing:-.01em}\n#lvm-shell .nav-spacer{flex:1}\n#lvm-shell .nav-link{color:var(--muted);text-decoration:none;font-size:14px}\n#lvm-shell .nav-link:hover{color:var(--ink)}\n#lvm-shell .nav-stores{display:flex;gap:6px;align-items:center}\n#lvm-shell .nav-stores a{display:block;line-height:0}\n#lvm-shell .nav-stores img{height:28px;width:auto;border-radius:5px;transition:transform .15s}\n#lvm-shell .nav-stores a:hover img{transform:translateY(-1px)}\n\n#lvm-shell .wrap{max-width:760px;margin:0 auto;padding:0 28px}\n\n#lvm-shell .hero{padding:54px 0 0}\n#lvm-shell .crumb{font-size:13px;color:var(--muted);margin-bottom:18px}\n#lvm-shell .crumb a{text-decoration:none;color:var(--muted)}\n#lvm-shell .crumb a:hover{color:var(--ink)}\n#lvm-shell .eyebrow{font-family:var(--font-mono);font-size:12px;font-weight:500;text-transform:uppercase;letter-spacing:.06em;color:var(--pink);margin-bottom:18px}\n#lvm-shell h1{font-family:var(--font-display);font-weight:600;font-size:72px;line-height:1.0;letter-spacing:-.04em;color:var(--ink);margin:0 0 22px}\n#lvm-shell h1 .alt{display:block;font-weight:500;color:var(--muted);font-size:.66em;line-height:1.15;margin-top:14px;letter-spacing:-.03em}\n#lvm-shell .dek{font-family:var(--font-display);font-size:24px;line-height:1.4;font-weight:400;color:var(--ink-2);letter-spacing:-.015em;margin:0 0 22px;max-width:680px}\n\n#lvm-shell .byline{display:flex;align-items:center;gap:10px;font-size:14px;color:var(--muted);margin-bottom:14px}\n#lvm-shell .byline .by-logo{width:26px;height:26px;border-radius:6px;object-fit:cover;flex-shrink:0;background:transparent;border:0}\n#lvm-shell .byline strong{color:var(--ink);font-weight:600;font-family:var(--font-display)}\n\n#lvm-shell .hero-stores{display:flex;gap:10px;margin:22px 0 18px;flex-wrap:wrap;align-items:center}\n#lvm-shell .hero-stores a{display:block;line-height:0;transition:transform .15s}\n#lvm-shell .hero-stores a:hover{transform:translateY(-2px)}\n#lvm-shell .hero-stores img{height:46px;width:auto;border-radius:9px}\n#lvm-shell .hero-stores .or{font-size:13px;color:var(--muted)}\n\n#lvm-shell .hero-bottom{display:grid;grid-template-columns:1.3fr 1fr;gap:48px;align-items:center;margin:38px 0 60px;padding-top:28px;border-top:1px solid var(--rule-soft)}\n#lvm-shell .hero-lead{font-family:var(--font-display);font-size:21px;line-height:1.5;color:var(--ink-2);font-weight:400}\n\n#lvm-shell .phone-wrap{display:flex;justify-content:center}\n#lvm-shell .phone{\n  position:relative;\n  width:280px;\n  background:linear-gradient(145deg,#2a2a2a,#0e0e0e);\n  border-radius:42px;\n  padding:5px;\n  border:1.5px solid rgba(255,255,255,.07);\n  box-shadow:0 30px 60px rgba(0,0,0,.18), 0 2px 6px rgba(0,0,0,.08);\n}\n#lvm-shell .phone .notch{\n  position:absolute;top:0;left:50%;transform:translateX(-50%);\n  width:96px;height:24px;background:#0a0a0a;border-radius:0 0 16px 16px;z-index:10;\n}\n#lvm-shell .phone-screen{\n  position:relative;\n  border-radius:34px;overflow:hidden;\n  background:#FAF0E6;\n  aspect-ratio:9\/19.5;\n}\n#lvm-shell .phone-screen img{\n  width:100%;height:100%;object-fit:cover;display:block;\n  transition:opacity .28s ease;\n}\n#lvm-shell .phone-zones{position:absolute;inset:0;z-index:15;pointer-events:none}\n#lvm-shell .phone-zones .z{position:absolute;left:4%;right:4%;cursor:pointer;background:transparent;border:0;padding:0;pointer-events:auto}\n#lvm-shell .phone-zones .z:focus-visible{outline:2px solid var(--pink);outline-offset:-4px;border-radius:6px}\n#lvm-shell .phone-navbar{position:absolute;left:0;right:0;bottom:0;height:9%;z-index:16;display:grid;grid-template-columns:repeat(4,1fr)}\n#lvm-shell .phone-navbar button{background:transparent;border:0;padding:0;cursor:pointer}\n#lvm-shell .phone-navbar button:focus-visible{outline:2px solid var(--pink);outline-offset:-3px;border-radius:6px}\n#lvm-shell .phone-back{\n  position:absolute;top:10px;left:10px;z-index:20;\n  width:30px;height:30px;border-radius:50%;\n  border:0;background:rgba(255,255,255,.78);backdrop-filter:blur(8px);\n  color:var(--ink);font-size:18px;font-weight:600;line-height:1;cursor:pointer;\n  display:none;align-items:center;justify-content:center;\n  box-shadow:0 2px 6px rgba(0,0,0,.12);\n}\n#lvm-shell .phone-back.on{display:flex}\n\n#lvm-shell .phone-cap{margin-top:14px;text-align:center;font-size:12px;color:var(--muted);font-family:var(--font-mono);text-transform:uppercase;letter-spacing:.06em}\n#lvm-shell .phone-stage{position:relative}\n#lvm-shell .tap-hint{position:absolute;z-index:30;pointer-events:none;animation:hintFloat 2.6s ease-in-out infinite}\n#lvm-shell .tap-hint .th-pill{display:inline-block;font-family:var(--font-display);font-size:15px;font-weight:600;color:#fff;line-height:1.25;letter-spacing:-.005em;background:var(--pink);padding:10px 16px;border-radius:14px;box-shadow:0 14px 32px rgba(255,45,110,.32);white-space:nowrap}\n#lvm-shell .tap-hint .th-pill small{display:block;font-size:11px;font-weight:500;color:rgba(255,255,255,.85);text-transform:uppercase;letter-spacing:.08em;margin-bottom:3px}\n#lvm-shell .tap-hint .th-arrow{position:absolute;color:var(--pink)}\n#lvm-shell .tap-hint.desktop{left:-204px;top:4px;text-align:right}\n#lvm-shell .tap-hint.desktop .th-arrow{right:-86px;top:58px;width:104px;height:34px;transform:none}\n#lvm-shell .tap-hint.mobile{display:none}\n#lvm-shell .tap-hint.hidden{opacity:0;transform:translateY(-6px);transition:opacity .35s ease, transform .35s ease;animation:none}\n@keyframes hintFloat{\n  0%, 100%{transform:translateY(0)}\n  50%{transform:translateY(-7px)}\n}\n@media (prefers-reduced-motion:reduce){#lvm-shell .tap-hint{animation:none}}\n#lvm-shell .phone-tabs{display:flex;justify-content:center;gap:8px;margin-top:10px;flex-wrap:nowrap}\n#lvm-shell .phone-tabs button{\n  background:transparent;border:1px solid var(--rule);color:var(--muted);\n  padding:6px 11px;border-radius:999px;font-size:11px;cursor:pointer;\n  font-family:var(--font-text);transition:all .15s;white-space:nowrap;\n}\n#lvm-shell .phone-tabs button:hover{color:var(--ink);border-color:var(--ink)}\n#lvm-shell .phone-tabs button.on{background:var(--ink);color:#fff;border-color:var(--ink)}\n\n#lvm-shell .snippet{background:var(--paper);border-radius:18px;padding:30px 32px;margin:48px 0 0;border:1px solid var(--rule-soft)}\n#lvm-shell .snippet .lbl{font-family:var(--font-mono);font-size:11px;font-weight:500;text-transform:uppercase;letter-spacing:.08em;color:var(--muted);margin-bottom:14px}\n#lvm-shell .snippet p{margin:0;font-family:var(--font-display);font-size:21px;line-height:1.45;color:var(--ink);font-weight:500;letter-spacing:-.012em}\n\n#lvm-shell section{padding:64px 0;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell section:last-of-type{border-bottom:0}\n#lvm-shell .section-label{display:flex;align-items:center;gap:14px;margin-bottom:30px}\n#lvm-shell .section-label .bar{width:24px;height:1px;background:var(--pink)}\n#lvm-shell .section-label .num{font-family:var(--font-mono);font-size:12px;font-weight:500;text-transform:uppercase;letter-spacing:.06em;color:var(--pink)}\n#lvm-shell h2{font-family:var(--font-display);font-weight:600;font-size:48px;line-height:1.05;letter-spacing:-.035em;color:var(--ink);margin:0 0 24px}\n#lvm-shell h3{font-family:var(--font-display);font-weight:600;font-size:32px;line-height:1.15;letter-spacing:-.025em;color:var(--ink);margin:36px 0 16px}\n#lvm-shell h4{font-family:var(--font-display);font-weight:500;font-size:20px;line-height:1.3;letter-spacing:-.015em;color:var(--ink);margin:24px 0 10px}\n#lvm-shell p{margin:0 0 22px;color:var(--ink-2)}\n#lvm-shell strong{color:var(--ink);font-weight:600}\n#lvm-shell ul, #lvm-shell ol{margin:0 0 22px;padding-left:22px;color:var(--ink-2)}\n#lvm-shell li{margin-bottom:8px}\n#lvm-shell a.inline{color:var(--pink);text-decoration:underline;text-decoration-thickness:1px;text-underline-offset:3px}\n#lvm-shell a.inline:hover{text-decoration-thickness:2px}\n\n#lvm-shell .statement{margin:48px 0;padding:32px 0;border-top:1px solid var(--rule);border-bottom:1px solid var(--rule);text-align:left}\n#lvm-shell .statement .num{font-family:var(--font-display);font-size:60px;font-weight:600;line-height:1;letter-spacing:-.04em;color:var(--pink);margin-bottom:14px}\n#lvm-shell .statement .lbl{font-family:var(--font-display);font-size:23px;line-height:1.35;font-weight:500;color:var(--ink);letter-spacing:-.012em}\n\n#lvm-shell .fig{margin:32px 0 18px;background:#fff;border:1px solid var(--rule);border-radius:20px;padding:28px 22px 20px;position:relative;overflow:hidden}\n#lvm-shell .fig-head{display:flex;justify-content:space-between;align-items:baseline;margin-bottom:18px}\n#lvm-shell .fig-head .l{font-family:var(--font-mono);font-size:11px;font-weight:500;text-transform:uppercase;letter-spacing:.08em;color:var(--muted)}\n#lvm-shell .fig-head .r{font-family:var(--font-mono);font-size:11px;font-weight:600;color:var(--ink);text-transform:uppercase;letter-spacing:.08em}\n#lvm-shell .fig-body{position:relative}\n#lvm-shell .fig-cap{margin:18px 4px 0;font-size:14px;color:var(--muted);line-height:1.5}\n#lvm-shell .fig-cap strong{color:var(--ink);font-weight:600}\n#lvm-shell .cv-wrap{position:relative;height:360px}\n\n#lvm-shell [data-term]{position:relative;cursor:help;border-bottom:1px dotted var(--dim)}\n#lvm-shell [data-term]:hover{color:var(--ink)}\n#lvm-shell .tt{position:absolute;left:50%;bottom:calc(100% + 12px);transform:translateX(-50%);min-width:200px;max-width:300px;background:#0c0c0c;color:#fff;font-size:13px;line-height:1.45;padding:11px 14px;border-radius:10px;box-shadow:0 12px 36px rgba(0,0,0,.32);opacity:0;visibility:hidden;transition:opacity .15s, visibility .15s;z-index:120;pointer-events:none;font-weight:400;font-family:var(--font-text)}\n#lvm-shell .tt::after{content:\"\";position:absolute;top:100%;left:50%;transform:translateX(-50%);border:6px solid transparent;border-top-color:#0c0c0c}\n#lvm-shell [data-term]:hover .tt, #lvm-shell [data-term]:focus .tt{opacity:1;visibility:visible}\n\n#lvm-shell .table{margin:24px 0;border:1px solid var(--rule);border-radius:16px;overflow:hidden;background:#fff}\n#lvm-shell .table-row{display:grid;grid-template-columns:1.55fr 1fr 1fr;border-bottom:1px solid var(--rule-soft);min-height:60px}\n#lvm-shell .table-row:last-child{border-bottom:0}\n#lvm-shell .table-row.head{background:var(--ink);color:#fff;border-bottom:0}\n#lvm-shell .table-row.head > div{padding:18px 18px;display:flex;align-items:center;gap:10px;font-family:var(--font-mono);font-size:11px;font-weight:500;text-transform:uppercase;letter-spacing:.07em}\n#lvm-shell .table-row.head .brand-cell{justify-content:flex-start}\n#lvm-shell .table-row.head .brand-cell img{width:24px;height:24px;border-radius:6px;background:#fff;object-fit:cover}\n#lvm-shell .table-row.head .brand-cell.lean{color:#FFB8CE}\n#lvm-shell .table-row > .crit{padding:16px 18px;font-size:14px;color:var(--ink);font-weight:500;display:flex;align-items:center;border-right:1px solid var(--rule-soft)}\n#lvm-shell .table-row > .cell{padding:16px 14px;font-size:13px;line-height:1.45;color:var(--ink-2);display:flex;align-items:center;gap:10px;border-right:1px solid var(--rule-soft)}\n#lvm-shell .table-row > .cell:last-child{border-right:0}\n#lvm-shell .table-row > .cell.lean{background:var(--pink-soft);position:relative}\n#lvm-shell .table-row > .cell.lean::before{content:\"\";position:absolute;left:0;top:0;bottom:0;width:2px;background:var(--pink)}\n#lvm-shell .icn{width:18px;height:18px;border-radius:50%;display:inline-flex;align-items:center;justify-content:center;flex-shrink:0;font-size:13px;font-weight:600;color:#fff}\n#lvm-shell .icn.ok{background:var(--green)}\n#lvm-shell .icn.no{background:var(--red)}\n#lvm-shell .icn.mid{background:var(--amber)}\n#lvm-shell .icn svg{width:11px;height:11px}\n\n#lvm-shell .mini-row{display:grid;grid-template-columns:repeat(3,1fr);gap:22px;margin:28px 0}\n#lvm-shell .mini-phone{position:relative;background:linear-gradient(145deg,#2a2a2a,#0e0e0e);border-radius:22px;padding:3px;border:1px solid rgba(255,255,255,.05);box-shadow:0 14px 32px rgba(0,0,0,.16);max-width:160px;margin:0 auto;width:100%}\n#lvm-shell .mini-phone .notch{position:absolute;top:0;left:50%;transform:translateX(-50%);width:40px;height:11px;background:#0a0a0a;border-radius:0 0 7px 7px;z-index:5}\n#lvm-shell .mini-phone .scr{border-radius:18px;overflow:hidden;background:#FAF0E6;aspect-ratio:9\/19.5}\n#lvm-shell .mini-phone .scr img{width:100%;height:100%;object-fit:cover}\n#lvm-shell .mini-phone.tiny{max-width:148px;padding:2px;border-radius:20px;border-width:1px}\n#lvm-shell .mini-phone.tiny .notch{width:30px;height:8px;border-radius:0 0 5px 5px}\n#lvm-shell .mini-phone.tiny .scr{border-radius:17px}\n#lvm-shell .mini-cap{text-align:center;margin-top:12px;font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.07em;color:var(--muted)}\n#lvm-shell .mini-cap strong{display:block;color:var(--ink);margin-top:4px;font-family:var(--font-display);font-size:14px;font-weight:500;letter-spacing:-.01em;text-transform:none}\n\n#lvm-shell .duo-row{display:grid;grid-template-columns:repeat(2,1fr);gap:20px;margin:18px 0 0}\n#lvm-shell .duo-row .mini-phone{max-width:180px}\n\n#lvm-shell .method{display:grid;grid-template-columns:1fr 1.4fr;gap:36px;align-items:center;margin:42px 0}\n#lvm-shell .method.flip{grid-template-columns:1.4fr 1fr}\n#lvm-shell .method.flip .m-phone{order:2}\n#lvm-shell .method .m-tag{font-family:var(--font-mono);font-size:11px;font-weight:600;text-transform:uppercase;letter-spacing:.08em;color:var(--pink);margin-bottom:8px}\n#lvm-shell .method h3{margin-top:0}\n#lvm-shell .method p{font-size:16px;color:var(--muted);line-height:1.7}\n\n#lvm-shell .cta-band{margin:40px 0;padding:26px 28px;background:var(--paper);border-radius:16px;display:flex;align-items:center;justify-content:space-between;gap:20px;flex-wrap:wrap;border:1px solid var(--rule-soft)}\n#lvm-shell .cta-band .l{font-family:var(--font-display);font-size:18px;line-height:1.35;font-weight:500;color:var(--ink);flex:1;min-width:240px;letter-spacing:-.01em}\n#lvm-shell .cta-band .stores{display:flex;gap:10px;align-items:center}\n#lvm-shell .cta-band .stores a{line-height:0;transition:transform .15s}\n#lvm-shell .cta-band .stores a:hover{transform:translateY(-2px)}\n#lvm-shell .cta-band .stores img{height:42px;width:auto;border-radius:9px}\n\n#lvm-shell .pyramid{margin:30px auto;max-width:440px}\n#lvm-shell .pyramid .level{margin:6px auto;padding:13px 18px;border-radius:14px;color:#fff;font-family:var(--font-display);font-weight:500;font-size:15px;letter-spacing:-.01em;display:flex;justify-content:space-between;align-items:center;box-shadow:0 6px 18px rgba(0,0,0,.06)}\n#lvm-shell .pyramid .level .k{font-family:var(--font-mono);font-size:10px;text-transform:uppercase;letter-spacing:.08em;opacity:.75}\n#lvm-shell .pyramid .l1{background:#0E0E10;width:100%}\n#lvm-shell .pyramid .l2{background:#1D1D1F;width:84%}\n#lvm-shell .pyramid .l3{background:#3a3a3c;width:68%}\n#lvm-shell .pyramid .l4{background:var(--pink);width:52%}\n#lvm-shell .pyramid-cap{text-align:center;font-size:13px;color:var(--muted);margin-top:14px}\n\n\/* Section 7 honnetete : scorecard horizontal bars *\/\n#lvm-shell .scorecard{margin:30px 0 10px;border:1px solid var(--rule);border-radius:20px;padding:28px 26px;background:#fff}\n#lvm-shell .scorecard-head{display:grid;grid-template-columns:1.4fr 1fr 1fr;column-gap:28px;align-items:center;padding-bottom:18px;margin-bottom:8px;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell .scorecard-head .h-crit{font-family:var(--font-mono);font-size:11px;font-weight:500;text-transform:uppercase;letter-spacing:.08em;color:var(--muted)}\n#lvm-shell .scorecard-head .h-brand{display:flex;align-items:center;gap:8px;font-family:var(--font-display);font-size:14px;font-weight:600;color:var(--ink)}\n#lvm-shell .scorecard-head .h-brand img{width:22px;height:22px;border-radius:5px;object-fit:cover}\n#lvm-shell .scorecard-row{display:grid;grid-template-columns:1.4fr 1fr 1fr;column-gap:28px;align-items:center;padding:14px 0;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell .scorecard-row:last-child{border-bottom:0}\n#lvm-shell .scorecard-row .crit{font-size:14px;color:var(--ink);font-weight:500;padding-right:14px}\n#lvm-shell .scorecard-row .bar{display:flex;flex-direction:row-reverse;align-items:center;gap:10px}\n#lvm-shell .scorecard-row .bar .b{flex:1;height:8px;border-radius:99px;background:var(--rule-soft);overflow:hidden;position:relative}\n#lvm-shell .scorecard-row .bar .b > i{display:block;height:100%;border-radius:99px;transition:width 1s cubic-bezier(.22,.61,.36,1)}\n#lvm-shell .scorecard-row .bar.lean .b > i{background:var(--pink)}\n#lvm-shell .scorecard-row .bar.mfp .b > i{background:var(--mfp)}\n#lvm-shell .scorecard-row .bar .v{font-family:var(--font-mono);font-size:12px;font-weight:600;color:var(--ink);min-width:32px;text-align:left}\n\n\/* Section 8 pour qui : persona checklist *\/\n#lvm-shell .persona{margin:28px 0 10px;display:grid;grid-template-columns:1fr;gap:14px}\n#lvm-shell .persona-it{display:grid;grid-template-columns:54px 1fr;gap:16px;padding:22px 24px;background:#fff;border:1px solid var(--rule);border-radius:18px;align-items:center}\n#lvm-shell .persona-it.match{background:var(--pink-soft);border-color:rgba(255,45,110,.25)}\n#lvm-shell .persona-it .pic{width:54px;height:54px;border-radius:50%;display:flex;align-items:center;justify-content:center;background:var(--rule-soft);position:relative;font-family:var(--font-mono);font-size:13px;font-weight:600;color:var(--ink)}\n#lvm-shell .persona-it.match .pic{background:var(--pink);color:#fff}\n#lvm-shell .persona-it .pic svg{width:24px;height:24px}\n#lvm-shell .persona-it h4{margin:0 0 4px;font-size:17px;letter-spacing:-.01em}\n#lvm-shell .persona-it p{margin:0;font-size:14px;color:var(--muted);line-height:1.55}\n#lvm-shell .persona-it.match h4{color:var(--ink)}\n\n\/* Section 9 migration : timeline steps *\/\n#lvm-shell .steps{display:grid;grid-template-columns:repeat(5,1fr);gap:14px;margin:28px 0;position:relative}\n#lvm-shell .steps::before{content:\"\";position:absolute;top:14px;left:7px;right:calc(20% - 18px);height:1px;background:linear-gradient(90deg,var(--pink) 0%,var(--rule-soft) 100%);z-index:0}\n#lvm-shell .step{position:relative;padding-top:24px;z-index:1}\n#lvm-shell .step::before{content:\"\";position:absolute;top:8px;left:0;width:14px;height:14px;border-radius:50%;background:var(--pink);border:3px solid #fff;box-shadow:0 0 0 1px var(--rule)}\n#lvm-shell .step .sn{font-family:var(--font-mono);font-size:11px;color:var(--pink);font-weight:600;letter-spacing:.08em}\n#lvm-shell .step h4{margin:6px 0 6px;font-size:15px;letter-spacing:-.01em}\n#lvm-shell .step p{font-size:13px;color:var(--muted);line-height:1.5;margin:0}\n\n\/* Section 10 debloque : feature stack numbered XL *\/\n#lvm-shell .feat-stack{margin:30px 0 10px;border-top:1px solid var(--rule)}\n#lvm-shell .feat-it{display:grid;grid-template-columns:auto 1fr auto;gap:24px;padding:26px 0;border-bottom:1px solid var(--rule);align-items:center}\n#lvm-shell .feat-it .fn{font-family:var(--font-display);font-size:48px;font-weight:600;color:var(--pink);line-height:1;letter-spacing:-.04em;width:74px}\n#lvm-shell .feat-it .ft{font-family:var(--font-display);font-size:22px;font-weight:600;color:var(--ink);letter-spacing:-.015em;line-height:1.25;margin-bottom:6px}\n#lvm-shell .feat-it .fd{font-size:15px;color:var(--muted);line-height:1.55;margin:0}\n#lvm-shell .feat-it .fc{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.08em;color:var(--muted);font-weight:500}\n#lvm-shell .feat-it:last-child{border-bottom:0}\n\n#lvm-shell .faq{margin:22px 0}\n#lvm-shell .faq details{border-bottom:1px solid var(--rule);padding:20px 0}\n#lvm-shell .faq details:first-of-type{border-top:1px solid var(--rule)}\n#lvm-shell .faq summary{cursor:pointer;list-style:none;display:flex;justify-content:space-between;align-items:center;gap:18px;font-family:var(--font-display);font-size:20px;font-weight:500;letter-spacing:-.015em;color:var(--ink)}\n#lvm-shell .faq summary::-webkit-details-marker{display:none}\n#lvm-shell .faq summary::after{content:\"+\";font-size:24px;color:var(--muted);font-weight:300;line-height:1;transition:transform .25s, color .25s}\n#lvm-shell .faq details[open] summary::after{transform:rotate(45deg);color:var(--pink)}\n#lvm-shell .faq details[open] summary{color:var(--pink)}\n#lvm-shell .faq .ans{margin-top:14px;font-size:16px;color:var(--muted);line-height:1.65}\n\n#lvm-shell .get-band{background:var(--paper-2);border-radius:24px;padding:48px 36px;margin:60px 0 40px;text-align:center}\n#lvm-shell .get-band .kicker{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;color:var(--pink);font-weight:600;letter-spacing:.1em;margin-bottom:14px}\n#lvm-shell .get-band h3{font-size:36px;margin:0 0 14px;letter-spacing:-.025em}\n#lvm-shell .get-band p{font-size:16px;color:var(--muted);max-width:480px;margin:0 auto 26px}\n#lvm-shell .get-band .stores{display:flex;justify-content:center;gap:14px;flex-wrap:wrap}\n#lvm-shell .get-band .stores a{line-height:0;transition:transform .15s}\n#lvm-shell .get-band .stores a:hover{transform:translateY(-3px)}\n#lvm-shell .get-band .stores img{height:60px;width:auto;border-radius:11px}\n\n#lvm-shell .sources{font-size:14px;color:var(--muted);line-height:1.7}\n#lvm-shell .sources ol{padding-left:22px}\n#lvm-shell .sources li{margin-bottom:8px}\n\n#lvm-shell footer{padding:50px 0 60px;border-top:1px solid var(--rule);margin-top:40px}\n#lvm-shell footer .row{display:flex;justify-content:space-between;align-items:center;gap:18px;flex-wrap:wrap}\n#lvm-shell footer .kicker{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.08em;color:var(--pink);font-weight:600}\n#lvm-shell footer p{font-size:13px;color:var(--muted);margin:8px 0 0}\n#lvm-shell footer .stores{display:flex;gap:8px}\n#lvm-shell footer .stores img{height:34px;width:auto;border-radius:6px}\n\n#lvm-shell .rev{opacity:0;transform:translateY(12px);transition:opacity .8s cubic-bezier(.22,.61,.36,1),transform .8s cubic-bezier(.22,.61,.36,1)}\n#lvm-shell .rev.on{opacity:1;transform:translateY(0)}\n@media (prefers-reduced-motion:reduce){#lvm-shell .rev{transition:none;opacity:1;transform:none}}\n\n@media (max-width:760px){\n  #lvm-shell .nav-row{padding:8px 18px;gap:8px}\n  #lvm-shell .nav-link{display:none}\n  #lvm-shell .nav-stores img{height:24px}\n  #lvm-shell .wrap{padding:0 22px}\n  #lvm-shell .hero{padding:34px 0 0}\n  #lvm-shell h1{font-size:46px;letter-spacing:-.035em}\n  #lvm-shell h1 .alt{font-size:.55em;margin-top:10px}\n  #lvm-shell .dek{font-size:20px}\n  #lvm-shell .hero-stores img{height:42px}\n  #lvm-shell .hero-bottom{grid-template-columns:1fr;gap:28px;margin:30px 0 40px;padding-top:24px;align-items:stretch}\n  #lvm-shell .phone-wrap{order:-1}\n  #lvm-shell .phone{width:240px}\n  #lvm-shell .tap-hint.desktop{display:none}\n  #lvm-shell .tap-hint.mobile{display:block;position:relative;left:auto;top:auto;text-align:center;margin:0 auto 10px;width:100%}\n  #lvm-shell .tap-hint.mobile .th-arrow{position:relative;display:block;margin:6px auto 0;width:34px;height:34px;transform:none;color:var(--pink)}\n  #lvm-shell .snippet{padding:24px 22px}\n  #lvm-shell .snippet p{font-size:18px}\n  #lvm-shell section{padding:48px 0}\n  #lvm-shell h2{font-size:34px;letter-spacing:-.03em}\n  #lvm-shell h3{font-size:24px}\n  #lvm-shell .section-label{margin-bottom:22px}\n  #lvm-shell .statement{padding:24px 0;margin:32px 0}\n  #lvm-shell .statement .num{font-size:44px}\n  #lvm-shell .statement .lbl{font-size:19px}\n  #lvm-shell .fig{padding:20px 14px 14px;border-radius:16px}\n  #lvm-shell .cv-wrap{height:310px}\n  #lvm-shell .method{grid-template-columns:1fr;gap:20px}\n  #lvm-shell .method.flip{grid-template-columns:1fr}\n  #lvm-shell .method.flip .m-phone{order:0}\n  #lvm-shell .mini-row{grid-template-columns:repeat(3,1fr);gap:10px}\n  #lvm-shell .mini-phone{padding:3px;border-radius:18px;border-width:1px;max-width:110px}\n  #lvm-shell .mini-phone .notch{width:42px;height:11px;border-radius:0 0 8px 8px}\n  #lvm-shell .mini-phone .scr{border-radius:15px}\n  #lvm-shell .mini-cap{font-size:10px}\n  #lvm-shell .mini-cap strong{font-size:13px}\n  #lvm-shell .duo-row{grid-template-columns:repeat(2,1fr);gap:12px}\n  #lvm-shell .duo-row .mini-phone{max-width:130px}\n  #lvm-shell .steps{grid-template-columns:1fr;gap:18px}\n  #lvm-shell .steps::before{display:none}\n  #lvm-shell .step{padding-top:0;padding-left:24px}\n  #lvm-shell .step::before{top:6px;left:0}\n  #lvm-shell .table-row{grid-template-columns:1.4fr .9fr .9fr}\n  #lvm-shell .table-row > .crit{padding:13px 12px;font-size:13px}\n  #lvm-shell .table-row > .cell{padding:13px 10px;font-size:12px;gap:8px}\n  #lvm-shell .table-row.head > div{padding:14px 12px;font-size:10px;gap:7px}\n  #lvm-shell .table-row.head .brand-cell img{width:20px;height:20px}\n  #lvm-shell .get-band{padding:36px 22px;border-radius:18px;margin:40px 0 30px}\n  #lvm-shell .get-band h3{font-size:28px}\n  #lvm-shell .get-band .stores img{height:50px}\n  #lvm-shell .cta-band{padding:22px;gap:14px}\n  #lvm-shell .cta-band .l{font-size:16px;min-width:0}\n  #lvm-shell .cta-band .stores img{height:38px}\n  #lvm-shell .faq summary{font-size:18px;gap:14px}\n  #lvm-shell .pyramid{max-width:100%}\n  #lvm-shell .pyramid .level{padding:11px 14px;font-size:14px}\n  #lvm-shell .scorecard{padding:20px 16px;border-radius:16px}\n  #lvm-shell .scorecard-head{grid-template-columns:1.2fr 1fr 1fr;column-gap:14px}\n  #lvm-shell .scorecard-head .h-brand{font-size:12px;gap:5px}\n  #lvm-shell .scorecard-head .h-brand img{width:18px;height:18px}\n  #lvm-shell .scorecard-row{grid-template-columns:1.2fr 1fr 1fr;column-gap:14px;padding:12px 0}\n  #lvm-shell .scorecard-row .crit{font-size:13px;padding-right:8px}\n  #lvm-shell .scorecard-row .bar{gap:6px}\n  #lvm-shell .scorecard-row .bar .v{font-size:11px;min-width:26px}\n  #lvm-shell .persona-it{grid-template-columns:44px 1fr;gap:12px;padding:16px 16px;border-radius:14px}\n  #lvm-shell .persona-it .pic{width:44px;height:44px;font-size:12px}\n  #lvm-shell .persona-it h4{font-size:15px}\n  #lvm-shell .persona-it p{font-size:13px}\n  #lvm-shell .feat-it{grid-template-columns:auto 1fr;gap:14px;padding:20px 0}\n  #lvm-shell .feat-it .fn{font-size:36px;width:54px}\n  #lvm-shell .feat-it .ft{font-size:18px}\n  #lvm-shell .feat-it .fd{font-size:13px}\n  #lvm-shell .feat-it .fc{display:none}\n}\n@media (max-width:480px){\n  #lvm-shell .phone-tabs{gap:5px}\n  #lvm-shell .phone-tabs button{padding:5px 8px;font-size:10px}\n  #lvm-shell .nav-stores{gap:4px}\n  #lvm-shell .nav-stores img{height:22px}\n  #lvm-shell .hero-stores img{height:40px}\n  #lvm-shell .crumb{font-size:12px}\n  #lvm-shell .table-row{grid-template-columns:1.3fr .85fr .85fr}\n  #lvm-shell .table-row > .crit{padding:11px 9px;font-size:12px}\n  #lvm-shell .table-row > .cell{padding:11px 8px;font-size:11px;gap:6px}\n  #lvm-shell .table-row.head > div{padding:11px 9px;font-size:9px;gap:5px}\n}<\/style>\n\n<style id=\"lvm-collision-reset\">\n\/* Hard reset for global theme styles that collide with our content *\/\nbody.postid-1241 #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-1241 #lvm-shell .wrap,\nbody.postid-1241 #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-1241 #lvm-shell .wrap,\n  body.postid-1241 #lvm-shell main.wrap{padding-left:18px!important;padding-right:18px!important}\n}\nhtml, body{overflow-x:hidden!important}\nbody.postid-1241 #lvm-shell{overflow-x:hidden;max-width:100vw}\nbody.postid-1241 #lvm-shell *{max-width:100%}\nbody.postid-1241 #lvm-shell .nav-row{max-width:100vw;box-sizing:border-box}\nbody.postid-1241 #lvm-shell.force-show .rev{opacity:1!important;transform:none!important}\n\n\/* === A.1 PHONE BACKGROUND CLASSES === *\/\nbody.postid-1241 #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-1241 #lvm-shell .phone-bg.tab-depense{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp)}\nbody.postid-1241 #lvm-shell .phone-bg.tab-bilan{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp)}\nbody.postid-1241 #lvm-shell .phone-bg.tab-kcal{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp)}\nbody.postid-1241 #lvm-shell .phone-bg.tab-strategie{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp)}\nbody.postid-1241 #lvm-shell .phone-bg.sub-BMR{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp)}\nbody.postid-1241 #lvm-shell .phone-bg.sub-NEAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp)}\nbody.postid-1241 #lvm-shell .phone-bg.sub-EAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp)}\nbody.postid-1241 #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-1241 #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-1241 #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-1241 #lvm-shell .cta-band .stores{width:100%!important;justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1241 #lvm-shell .cta-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1241 #lvm-shell .cta-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1241 #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-1241 #lvm-shell .get-band{padding:38px 22px!important}\n  body.postid-1241 #lvm-shell .get-band .stores{justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1241 #lvm-shell .get-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1241 #lvm-shell .get-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1241 #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-1241 #lvm-shell .get-band h3{font-size:26px!important;line-height:1.2!important}\n  body.postid-1241 #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-1241 #lvm-shell .brand-banner img{width:54px!important;height:54px!important}\n  body.postid-1241 #lvm-shell .brand-banner > div{padding:16px 12px!important;gap:8px!important}\n  body.postid-1241 #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-1241 #lvm-shell .scorecard{padding:18px 16px!important;border-radius:16px!important}\n  body.postid-1241 #lvm-shell .scorecard-head{display:none!important}\n  body.postid-1241 #lvm-shell .scorecard-row{\n    display:block!important;\n    padding:14px 0!important;\n    border-bottom:1px solid #E8E2D6!important;\n  }\n  body.postid-1241 #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-1241 #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-1241 #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-1241 #lvm-shell .scorecard-row .bar.lean::before{color:#FF2D6E!important}\n  body.postid-1241 #lvm-shell .scorecard-row .bar.mfp::before{color:#5B7FFF!important}\n  body.postid-1241 #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-1241 #lvm-shell .scorecard-row .bar .b > i{\n    display:block!important;\n    height:100%!important;\n    border-radius:99px!important;\n  }\n  body.postid-1241 #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-1241 #lvm-shell .cv-wrap{height:380px!important;min-height:360px!important;max-height:420px!important;width:100%!important}\n  body.postid-1241 #lvm-shell .cv-wrap canvas{width:100%!important;height:100%!important;display:block!important}\n  body.postid-1241 #lvm-shell .fig{padding:16px 4px 14px!important;margin:24px -4px 14px!important;overflow:visible!important}\n  body.postid-1241 #lvm-shell .fig-head{padding:0 12px!important;flex-wrap:wrap!important;gap:6px!important;margin-bottom:10px!important}\n  body.postid-1241 #lvm-shell .fig-body{padding:0 2px!important}\n  body.postid-1241 #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-1241 #lvm-shell .cv-wrap{height:360px!important;min-height:340px!important;max-height:380px!important}\n  body.postid-1241 #lvm-shell .fig{padding:14px 2px 12px!important;margin:20px -6px 12px!important;border-radius:14px!important}\n  body.postid-1241 #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-1241 #lvm-shell .table{border-radius:14px!important}\n  body.postid-1241 #lvm-shell .table-row.head{display:none!important}\n  body.postid-1241 #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-1241 #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-1241 #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-1241 #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-1241 #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-1241 #lvm-shell .table-row > .cell:not(.lean):not(.crit)::before{\n    content:\"MFP\"!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:#5B7FFF!important;\n  }\n  body.postid-1241 #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-1241 #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-1241 #lvm-shell .mini-row{gap:6px!important;margin:24px 0!important;grid-template-columns:repeat(3,1fr)!important}\n  body.postid-1241 #lvm-shell .mini-phone{max-width:100px!important;padding:2px!important;border-radius:14px!important;border-width:1px!important}\n  body.postid-1241 #lvm-shell .mini-phone.tiny{max-width:96px!important;padding:2px!important;border-radius:13px!important}\n  body.postid-1241 #lvm-shell .mini-phone .notch{width:30px!important;height:8px!important;border-radius:0 0 5px 5px!important}\n  body.postid-1241 #lvm-shell .mini-phone .scr{border-radius:11px!important}\n  body.postid-1241 #lvm-shell .mini-cap{font-size:10px!important;margin-top:8px!important}\n  body.postid-1241 #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-1241 #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-1241 #lvm-shell .tap-hint.desktop{display:none!important}\n  body.postid-1241 #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-1241 #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-1241 #lvm-shell .bodyscan-illust .mini-phone{max-width:200px!important;padding:3px!important;border-radius:22px!important;border-width:1px!important}\nbody.postid-1241 #lvm-shell .bodyscan-illust .mini-phone .notch{width:40px!important;height:11px!important;border-radius:0 0 7px 7px!important}\nbody.postid-1241 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:18px!important}\n@media (max-width:760px){\n  body.postid-1241 #lvm-shell .bodyscan-illust{max-width:180px!important}\n  body.postid-1241 #lvm-shell .bodyscan-illust .mini-phone{max-width:160px!important;padding:3px!important;border-radius:20px!important}\n  body.postid-1241 #lvm-shell .bodyscan-illust .mini-phone .notch{width:34px!important;height:9px!important;border-radius:0 0 6px 6px!important}\n  body.postid-1241 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:16px!important}\n}\n<\/style>\n<script data-wpmeteor-nooptimize=\"true\">\n(function(){\n  \/* Hard fallback: force .rev visible after 2s if IntersectionObserver doesn't fire *\/\n  setTimeout(function(){\n    var shell = document.getElementById('lvm-shell');\n    if(!shell) return;\n    var anyOn = shell.querySelector('.rev.on');\n    if(!anyOn){ shell.classList.add('force-show'); }\n  }, 2000);\n\n  \/* ResizeObserver fallback: ensure charts resize correctly *\/\n  if (typeof ResizeObserver !== 'undefined'){\n    var observer = new ResizeObserver(function(entries){\n      entries.forEach(function(entry){\n        var canvas = entry.target.querySelector('canvas');\n        if (!canvas || !window.Chart) return;\n        var inst = window.Chart.getChart(canvas);\n        if (inst) { try { inst.resize(); } catch(e){} }\n      });\n    });\n    document.querySelectorAll('#lvm-shell .cv-wrap').forEach(function(w){ observer.observe(w); });\n  }\n})();\n<\/script>\n<div id=\"lvm-shell\"><div class=\"progress\" aria-hidden=\"true\"><i id=\"progBar\"><\/i><\/div>\n\n<header class=\"nav\">\n  <div class=\"nav-row\">\n    <a class=\"nav-brand\" href=\"https:\/\/lean-app.com\/pt\/\" aria-label=\"In\u00edcio 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?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" 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\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/>\n      <\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" 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\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/>\n      <\/a>\n    <\/div>\n  <\/div>\n<\/header>\n\n<main class=\"wrap\">\n\n<section class=\"hero\" aria-labelledby=\"title\">\n  <div class=\"crumb\"><a href=\"https:\/\/lean-app.com\/pt\/\">In\u00edcio<\/a> &nbsp;\/&nbsp; Lean vs MyFitnessPal<\/div>\n  <div class=\"eyebrow\">Comparativo &middot; Nutri\u00e7\u00e3o &amp; TDEE<\/div>\n  <h1 id=\"title\">Lean vs MyFitnessPal.\n    <span class=\"alt\">A f\u00f3rmula TDEE que muda tudo. 1919 frente a 2025, em ci\u00eancia.<\/span>\n  <\/h1>\n  <p class=\"dek\">Por que o MyFitnessPal erra com 80&nbsp;% dos usu\u00e1rios, e a alternativa que faz o que o MFP n\u00e3o sabe fazer.<\/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; Leitura 12&nbsp;min &middot; Atualizado em 21 de maio de 2026<\/span>\n  <\/div>\n  <div class=\"hero-stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" target=\"_blank\" rel=\"noopener\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"T\u00e9l\u00e9charger sur l'App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" 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      O MyFitnessPal calcula seu TDEE com uma f\u00f3rmula de 1919 (Harris-Benedict) sem gordura corporal, mais um coeficiente de atividade quase aleat\u00f3rio, e ignora a adapta\u00e7\u00e3o metab\u00f3lica. Seu objetivo pode estar errado em 500 a 800&nbsp;kcal. O Lean recalcula cada componente com precis\u00e3o, sem coeficiente a escolher.\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=\"Vis\u00e3o geral do app Lean com detalhamento do TDEE\">\n          <div class=\"notch\"><\/div>\n          <div class=\"phone-screen\">\n            <button class=\"phone-back\" id=\"phoneBack\" aria-label=\"Voltar\">&#8249;<\/button>\n            <div id=\"phoneImg\" class=\"phone-bg tab-depense\" role=\"img\" aria-label=\"Vis\u00e3o geral Lean, aba Gasto\"><\/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=\"Detalhe BMR\"><\/div>\n              <div class=\"z\" data-sub=\"NEAT\" style=\"top:33%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"Detalhe NEAT\"><\/div>\n              <div class=\"z\" data-sub=\"EAT\"  style=\"top:50%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"Detalhe EAT\"><\/div>\n              <div class=\"z\" data-sub=\"TEF\"  style=\"top:67%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"Detalhe TEF\"><\/div>\n            <\/div>\n            <div class=\"phone-navbar\" id=\"phoneNav\" aria-hidden=\"false\">\n              <button data-tab=\"bilan\"     type=\"button\" aria-label=\"Aba Balan\u00e7o\"><\/button>\n              <button data-tab=\"kcal\"      type=\"button\" aria-label=\"Aba Calorias\"><\/button>\n              <button data-tab=\"depense\"   type=\"button\" aria-label=\"Aba Gasto\"><\/button>\n              <button data-tab=\"strategie\" type=\"button\" aria-label=\"Aba Estrat\u00e9gia\"><\/button>\n            <\/div>\n          <\/div>\n        <\/div>\n        <div class=\"phone-tabs\" role=\"tablist\" aria-label=\"Navegar no 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\">Resposta r\u00e1pida<\/div>\n    <p>O MyFitnessPal calcula seu TDEE com uma f\u00f3rmula de 1919 (Harris-Benedict) sem gordura corporal, mais um coeficiente de atividade quase aleat\u00f3rio, e ignora a adapta\u00e7\u00e3o metab\u00f3lica. Seu objetivo cal\u00f3rico pode estar errado em 500 a 800&nbsp;kcal. O Lean recalcula cada componente (<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> sobre gordura corporal real, <span data-term=\"NEAT\">NEAT<span class=\"tt\">Non-Exercise Activity Thermogenesis. Gasto ligado aos passos e \u00e0s atividades cotidianas fora do esporte.<\/span><\/span> por passos, <span data-term=\"EAT\">EAT<span class=\"tt\">Exercise Activity Thermogenesis. Gasto ligado aos seus treinos, calculado via MET.<\/span><\/span> por MET, <span data-term=\"TEF\">TEF<span class=\"tt\">Thermic Effect of Food. Energia gasta pela digest\u00e3o. Depende dos macros ingeridos.<\/span><\/span> por macros, adapta\u00e7\u00e3o metab\u00f3lica autom\u00e1tica) sem coeficiente de atividade a escolher.<\/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; A constata\u00e7\u00e3o<\/span><\/div>\n  <h2 id=\"constat\">Por que 80&nbsp;% dos usu\u00e1rios do MFP n\u00e3o perdem peso apesar de um \u00ab&nbsp;d\u00e9ficit&nbsp;\u00bb<\/h2>\n  <p>Se voc\u00ea est\u00e1 lendo isso, provavelmente j\u00e1 passou por a\u00ed. Voc\u00ea baixou o MyFitnessPal, preencheu seu perfil, o app disse \u00ab&nbsp;seu <span data-term=\"TDEE\">TDEE<span class=\"tt\">Total Daily Energy Expenditure. A f\u00f3rmula BMR + NEAT + EAT + TEF, mais a adapta\u00e7\u00e3o metab\u00f3lica que modula o BMR.<\/span><\/span> \u00e9 de 2&nbsp;500&nbsp;kcal por dia, coma 2&nbsp;250&nbsp;kcal para perder peso&nbsp;\u00bb. Voc\u00ea fez isso. Religiosamente. Pesou seus alimentos. At\u00e9 virou Premium. E no fim do m\u00eas, est\u00e1 no mesmo peso. Ou um pouco mais pesado.<\/p>\n  <p>Voc\u00ea pensa: \u00ab&nbsp;devo ter registrado mal, devo ter subestimado minhas calorias&nbsp;\u00bb. Aperta o cinto. Desce para 2&nbsp;000&nbsp;kcal. De novo, nada.<\/p>\n\n  <div class=\"statement\">\n    <div class=\"num\">80&nbsp;%<\/div>\n    <div class=\"lbl\">dos usu\u00e1rios do MFP estagnam apesar de um d\u00e9ficit te\u00f3rico. O problema n\u00e3o \u00e9 a for\u00e7a de vontade deles. \u00c9 o c\u00e1lculo do seu TDEE.<\/div>\n  <\/div>\n\n  <p>Imagine que o MFP mostra um TDEE de 2&nbsp;500&nbsp;kcal. Voc\u00ea come 2&nbsp;250 (d\u00e9ficit te\u00f3rico de 250&nbsp;kcal). Mas na realidade, seu <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/depense-energetique-totale-v2\/\">TDEE \u00e9 de 2&nbsp;200&nbsp;kcal<\/a>. Pois n\u00e3o h\u00e1 nenhuma chance, e digo bem <strong>nenhuma chance<\/strong>, de voc\u00ea perder peso. Voc\u00ea est\u00e1 em super\u00e1vit de 50&nbsp;kcal sem saber.<\/p>\n  <p>\u00c9 por isso que \u00e9 crucial, hiperimportante, <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/comment-compter-ses-calories\/\">calcular perfeitamente seu gasto<\/a>. E \u00e9 exatamente a\u00ed que o MyFitnessPal falha.<\/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; Problema 1<\/span><\/div>\n  <h2 id=\"p1\">A f\u00f3rmula BMR de 1919<\/h2>\n  <p>Para calcular seu metabolismo basal (o BMR, a energia que voc\u00ea queima em repouso), o MyFitnessPal usa a equa\u00e7\u00e3o de Harris-Benedict. Ou sua derivada direta, Mifflin-St Jeor. Segundo as vers\u00f5es do app.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figura 1 &middot; Homem 1,80 m, 120&nbsp;kg, 30&nbsp;% BF<\/span><span class=\"r\">kcal<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\" style=\"position:relative;width:100%;height:380px;min-height:340px\"><canvas id=\"chartBMR\" aria-label=\"Compara\u00e7\u00e3o BMR Harris-Benedict 2500 kcal vs modelo propriet\u00e1rio patenteado Lean 2000 kcal, diferen\u00e7a de 500 kcal\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>BMR estimado.<\/strong> O modelo propriet\u00e1rio patenteado Lean leva em conta a massa magra. Harris-Benedict (MFP), n\u00e3o. Diferen\u00e7a de 500&nbsp;kcal, o equivalente a um almo\u00e7o inteiro.<\/p>\n  <\/div>\n\n  <p>Harris-Benedict \u00e9 de 1919. Estamos na sa\u00edda da Primeira Guerra Mundial. Dois pesquisadores pegam 239 pessoas, em uma \u00fanica cidade (Boston), deitam-nas em uma cama com uma m\u00e1scara para calcular o oxig\u00eanio consumido, e tiram uma f\u00f3rmula que depende do peso, da altura, da idade e do sexo.<\/p>\n  <p>Para a \u00e9poca, era inovador. Em 2025, \u00e9 inutiliz\u00e1vel. Tr\u00eas raz\u00f5es:<\/p>\n  <ol>\n    <li><strong>A amostra \u00e9 rid\u00edcula<\/strong>&nbsp;: 239 pessoas, de uma \u00fanica cidade americana, em 1918. Em uma \u00e9poca em que havia muito menos sobrepeso do que hoje, em que os n\u00edveis hormonais e a composi\u00e7\u00e3o corporal m\u00e9dia n\u00e3o tinham nada a ver com os nossos.<\/li>\n    <li><strong>O instrumento de medi\u00e7\u00e3o era impreciso<\/strong>&nbsp;: a calorimetria indireta da \u00e9poca tinha uma margem de erro enorme. Estudos mais modernos mostraram que Harris-Benedict superestima sistematicamente o metabolismo basal.<\/li>\n    <li><strong>O defeito conceitual<\/strong>&nbsp;: a f\u00f3rmula s\u00f3 leva em conta o peso. Nem a gordura corporal. Nem a massa magra.<\/li>\n  <\/ol>\n  <p>Mas desde os anos 80 se sabe que <strong>a massa gorda gasta muito pouca energia<\/strong> comparada ao resto do corpo. O f\u00edgado, o c\u00e9rebro, o cora\u00e7\u00e3o, os rins e sobretudo os m\u00fasculos s\u00e3o os verdadeiros consumidores. A massa gorda \u00e9 inerte. Uma pessoa com 30&nbsp;% de gordura corporal n\u00e3o queima nem de longe o mesmo que uma pessoa com 10&nbsp;%, mesmo com o mesmo peso.<\/p>\n\n  <p>500&nbsp;kcal n\u00e3o \u00e9 pouca coisa. Se o MFP diz \u00ab&nbsp;seu BMR \u00e9 de 2&nbsp;500&nbsp;\u00bb e na realidade \u00e9 de 2&nbsp;000, tudo o que vem depois est\u00e1 errado.<\/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\">Gordura corporal real<strong>Foto, 5 segundos<\/strong><\/div>\n  <\/div>\n\n  <div class=\"statement\">\n    <div class=\"num\">400&nbsp;kcal<\/div>\n    <div class=\"lbl\">de diferen\u00e7a entre dois homens de 80&nbsp;kg, um com 10&nbsp;% de gordura corporal (BMR 1&nbsp;900), o outro com 30&nbsp;% (BMR 1&nbsp;500). O MFP d\u00e1 a eles o mesmo n\u00famero.<\/div>\n  <\/div>\n\n  <p>Conclus\u00e3o parcial: se um app calcula seu BMR unicamente a partir do seu peso, da sua altura, da sua idade e do seu sexo, fuja. \u00c9 matematicamente imposs\u00edvel ter um resultado confi\u00e1vel.<\/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; Problema 2<\/span><\/div>\n  <h2 id=\"p2\">O coeficiente de atividade \u00ab&nbsp;quase aleat\u00f3rio&nbsp;\u00bb<\/h2>\n  <p>\u00c9 aqui que a coisa fica grave. E provavelmente \u00e9 o ponto que ningu\u00e9m te explicou.<\/p>\n  <p>Uma vez que o MFP calculou seu BMR (erradamente), ele precisa estimar seu TDEE total. O <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/depense-energetique-totale-v2\/\">TDEE, \u00e9 o BMR + todo o resto<\/a>&nbsp;: o gasto ligado aos passos, \u00e0s atividades cotidianas, ao esporte e \u00e0 digest\u00e3o. Tudo o que n\u00e3o \u00e9 metabolismo basal.<\/p>\n  <p>Como o MyFitnessPal faz isso? Ele pede para voc\u00ea marcar uma caixa:<\/p>\n  <ul><li>Sedent\u00e1rio<\/li><li>Pouco ativo<\/li><li>Ativo<\/li><li>Muito ativo<\/li><\/ul>\n  <p>E segundo sua escolha, ele multiplica seu BMR por um coeficiente (tipicamente 1,2&nbsp;\/ 1,375&nbsp;\/ 1,55&nbsp;\/ 1,725). \u00c9 s\u00f3 isso. \u00c9 tudo o que h\u00e1 por tr\u00e1s do seu objetivo cal\u00f3rico di\u00e1rio. Uma caixa que VOC\u00ca marcou uma \u00fanica vez no momento do cadastro. Muitas vezes seis meses atr\u00e1s. Sem mudar desde ent\u00e3o.<\/p>\n  <p>E a\u00ed est\u00e1 o esc\u00e2ndalo silencioso: essa aproxima\u00e7\u00e3o \u00e9 <strong>hiperimperfeita<\/strong>. A diferen\u00e7a entre um dia em que voc\u00ea fica grudado no sof\u00e1 vendo Netflix e um dia em que vai \u00e0 Disneyland com seus filhos e anda 15&nbsp;km, <strong>s\u00e3o mais de 1&nbsp;000&nbsp;kcal<\/strong>.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figura 2 &middot; 7 dias reais<\/span><span class=\"r\">kcal\/dia<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\" style=\"position:relative;width:100%;height:380px;min-height:340px\"><canvas id=\"chartNEAT\" aria-label=\"Variabilidade di\u00e1ria do gasto cal\u00f3rico em 7 dias, contra 2400 kcal fixas segundo o MyFitnessPal\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>Gasto real<\/strong> medido durante 7&nbsp;dias em um usu\u00e1rio do Lean. A linha cinza \u00e9 o que o MFP mostrava (2&nbsp;400&nbsp;kcal fixas). As anota\u00e7\u00f5es rosa mostram por que cada dia se mexe.<\/p>\n  <\/div>\n\n  <p>Voc\u00ea n\u00e3o pode reduzir seu n\u00edvel de atividade a uma caixa est\u00e1tica. Talvez voc\u00ea seja ativo nas semanas em que faz pouco home office, e sedent\u00e1rio nas que n\u00e3o sai do escrit\u00f3rio. Talvez seja ativo no ver\u00e3o e sedent\u00e1rio no inverno. Talvez seja ativo de ter\u00e7a a sexta e sedent\u00e1rio no fim de semana.<\/p>\n  <p>Qual caixa voc\u00ea vai marcar esta semana? A verdade \u00e9 que nenhuma das 4 ser\u00e1 correta. E portanto o MFP vai te dar um TDEE sistematicamente desconectado da realidade.<\/p>\n  <p>\u00c9 quase aleat\u00f3rio. \u00c9 at\u00e9 um pouco melhor do que um sorteio, mas n\u00e3o muito.<\/p>\n  <p>O ponto-chave deste artigo: mesmo que o MyFitnessPal tivesse uma f\u00f3rmula BMR perfeita (o que n\u00e3o \u00e9 o caso), o coeficiente de atividade bastaria para quebrar tudo. Voc\u00ea n\u00e3o pode estimar um <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/neat-depense-non-sportive\/\">NEAT<\/a>, um EAT e um <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/effet-thermique-des-aliments\/\">TEF<\/a> com um multiplicador \u00fanico aplicado ao BMR. \u00c9 conceitualmente absurdo.<\/p>\n  <p>Voc\u00ea j\u00e1 entendeu: <strong>uma f\u00f3rmula BMR completamente falseada, mais uma aproxima\u00e7\u00e3o das outras rubricas de gasto, n\u00e3o d\u00e1 nenhuma chance de atingir seus objetivos.<\/strong><\/p>\n\n  <div class=\"cta-band rev\" style=\"display:flex;align-items:center;justify-content:space-between;gap:20px;flex-wrap:wrap;padding:26px 28px;margin:40px 0;background:#FAF5EE;border:1px solid #E8E2D6;border-radius:16px\">\n    <div class=\"l\" style=\"flex:1;min-width:240px;font-size:18px;line-height:1.4;font-weight:500;color:#0E0E10\">Ver seu TDEE real, decomposto em BMR + NEAT + EAT + TEF. Download gratuito.<\/div>\n    <div class=\"stores\" style=\"display:flex;gap:10px;align-items:center;flex-wrap:wrap\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"p3\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">03 &middot; Problema 3<\/span><\/div>\n  <h2 id=\"p3\">A adapta\u00e7\u00e3o metab\u00f3lica ignorada<\/h2>\n  <p>\u00c9 o chef\u00e3o final. A no\u00e7\u00e3o mais fina. E provavelmente a mais importante.<\/p>\n  <p>Quando voc\u00ea est\u00e1 em d\u00e9ficit cal\u00f3rico, seu corpo entende que recebe menos energia do que antes. Para se proteger, ele passa para o modo economia. Exatamente como o modo de economia de energia do seu iPhone: tudo continua funcionando, mas usando menos energia. Seu BMR cai. Seu NEAT cai. Seu EAT cai.<\/p>\n  <p>\u00c9 o que se chama adapta\u00e7\u00e3o metab\u00f3lica. Estes s\u00e3o os n\u00fameros:<\/p>\n  <ul>\n    <li>D\u00e9ficit de &minus;250&nbsp;kcal por dia, durante 2 a 8 semanas: adapta\u00e7\u00e3o metab\u00f3lica de <strong>de 5 a 10&nbsp;%<\/strong><\/li>\n    <li>D\u00e9ficit de &minus;500&nbsp;kcal por dia: <strong>10 a 15&nbsp;%<\/strong><\/li>\n    <li>D\u00e9ficit de &minus;750&nbsp;kcal por dia: <strong>15 a 25&nbsp;%<\/strong><\/li>\n  <\/ul>\n  <p>E como o NEAT, o EAT e o TEF dependem todos do BMR, \u00e9 quase todo o seu TDEE que \u00e9 afetado.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figura 3 &middot; 8 semanas em d\u00e9ficit<\/span><span class=\"r\">kcal\/dia<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\" style=\"position:relative;width:100%;height:380px;min-height:340px\"><canvas id=\"chartAdapt\" aria-label=\"TDEE que cai de 2500 para 2150 kcal em 8 semanas, contra 2500 fixas segundo o MFP\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>TDEE real<\/strong> em 8 semanas de d\u00e9ficit a &minus;500&nbsp;kcal\/dia. A curva rosa desce. A linha cinza do MFP fica plana. Na semana 6, voc\u00ea j\u00e1 est\u00e1 na manuten\u00e7\u00e3o. Sem ter mudado nada.<\/p>\n  <\/div>\n\n  <p>Concretamente: se voc\u00ea previu um d\u00e9ficit de 10&nbsp;% sobre um TDEE de 2&nbsp;500 (ou seja, comer 2&nbsp;250 por dia), e seu corpo se adapta em 10&nbsp;%, seu TDEE real passou a 2&nbsp;250. Voc\u00ea est\u00e1 na manuten\u00e7\u00e3o. N\u00e3o perde mais.<\/p>\n  <p>A armadilha \u00e9 que \u00e9 insidioso. No in\u00edcio, voc\u00ea perde. Fica contente. Continua. Mas semana ap\u00f3s semana, a adapta\u00e7\u00e3o se acumula. E em algum momento, sem ter mudado nada no seu tracking, <strong>voc\u00ea para de perder<\/strong>.<\/p>\n  <p>95&nbsp;% das pessoas passam por isso sem entender. Culpam a for\u00e7a de vontade. Culpam o \u00ab&nbsp;metabolismo quebrado&nbsp;\u00bb. Voltam para dietas mais duras, o que agrava a adapta\u00e7\u00e3o. Espiral.<\/p>\n  <p>O MyFitnessPal nunca calcula a adapta\u00e7\u00e3o metab\u00f3lica. Ele te d\u00e1 um objetivo fixo e est\u00e1tico. Quando voc\u00ea estagna ap\u00f3s 6 semanas, o app n\u00e3o tem a menor ideia do porqu\u00ea.<\/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; Solu\u00e7\u00e3o Lean<\/span><\/div>\n  <h2 id=\"solution\">Como o Lean resolve cada um dos 3 problemas<\/h2>\n  <p>O Lean n\u00e3o foi constru\u00eddo como um clone melhorado do MyFitnessPal. O Lean foi constru\u00eddo como o app que gostar\u00edamos de ter para seguir a s\u00e9rio a teoria do TDEE completo. Concretamente, \u00e9 assim que o Lean trata cada componente.<\/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\">Passo 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\">Passo 2<strong>BMR recalculado<\/strong><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n    <div>\n      <div class=\"m-tag\">M.01 &middot; O BMR sobre gordura corporal real<\/div>\n      <h3>Modelo propriet\u00e1rio patenteado, baseado na massa magra<\/h3>\n      <p>O Lean usa um <strong>modelo propriet\u00e1rio patenteado<\/strong> que depende diretamente da massa magra, n\u00e3o do peso bruto. Para isso, o app precisa da sua gordura corporal. E a\u00ed atacamos a coisa mais chata historicamente: como medir sua gordura corporal sem pagar 100&nbsp;\u20ac por semana por um DEXA?<\/p>\n      <p>Resposta Lean: o <strong>BodyScan IA<\/strong>. Voc\u00ea tira uma foto, o app a passa por um modelo treinado em um banco massivo de scans DEXA, e voc\u00ea obt\u00e9m sua gordura corporal estimada em alguns segundos. Pode refazer toda semana. O BMR \u00e9 recalculado automaticamente.<\/p>\n      <p>Adeus adip\u00f4metro (impreciso), adeus balan\u00e7a de bioimped\u00e2ncia (o golpe do s\u00e9culo), adeus DEXA (perfeito mas inacess\u00edvel). Uma foto, 5 segundos.<\/p>\n    <\/div>\n  <\/div>\n\n  <div class=\"method flip\">\n    <div>\n      <div class=\"m-tag\">M.02 &middot; Sem coeficiente de atividade<\/div>\n      <h3>NEAT, EAT, TEF calculados separadamente<\/h3>\n      <p><strong>NEAT.<\/strong> O Lean recupera seu n\u00famero de passos reais via HealthKit (iOS) ou Google Fit (Android). Sem declara\u00e7\u00e3o. Sem \u00ab&nbsp;eu acho que ando bastante&nbsp;\u00bb. Seus passos, medidos pelos aceler\u00f4metros muito precisos do seu smartphone. O <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/neat-depense-non-sportive\/\">NEAT \u00e9 calculado cruzando esses passos com seu BMR<\/a>.<\/p>\n      <p><strong>EAT.<\/strong> Para cada treino, voc\u00ea seleciona o esporte em uma lista (muscula\u00e7\u00e3o, corrida, t\u00eanis, nata\u00e7\u00e3o etc.), e o Lean usa o MET (Metabolic Equivalent Task) desse esporte para calcular o gasto real. Voc\u00ea informa o tempo <strong>efetivo<\/strong> de esporte (n\u00e3o o tempo total com as pausas: o erro que 100&nbsp;% dos rel\u00f3gios conectados cometem). Um treino de muscula\u00e7\u00e3o a 1&nbsp;050&nbsp;kcal segundo seu Apple Watch? A realidade est\u00e1 mais perto de 200&nbsp;kcal. O Lean recusa essa deriva.<\/p>\n      <p><strong>TEF.<\/strong> A digest\u00e3o queima energia, e n\u00e3o \u00e9 uma taxa fixa de 10&nbsp;%. <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/effet-thermique-des-aliments\/\">As prote\u00ednas custam de 20 a 30&nbsp;%<\/a> de suas calorias na digest\u00e3o. Os carboidratos de 5 a 10&nbsp;%. As gorduras de 1 a 3&nbsp;%. O Lean calcula seu TEF real a partir dos seus macros. Com 3&nbsp;000&nbsp;kcal\/dia, isso pode representar 100&nbsp;kcal de diferen\u00e7a segundo a composi\u00e7\u00e3o da sua dieta.<\/p>\n    <\/div>\n    <div class=\"m-phone\">\n      <div class=\"mini-row\" style=\"margin:0;gap:10px\">\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp\" alt=\"\u00c9cran NEAT Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">NEAT<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp\" alt=\"\u00c9cran EAT Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">EAT<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp\" alt=\"\u00c9cran TEF Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">TEF<\/strong><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"method flip\">\n    <div>\n      <div class=\"m-tag\">M.03 &middot; Adapta\u00e7\u00e3o metab\u00f3lica autom\u00e1tica<\/div>\n      <h3>Uma primeira mundial em um app de consumo<\/h3>\n      <p>O Lean \u00e9, que saibamos, o primeiro app a calcular automaticamente a adapta\u00e7\u00e3o metab\u00f3lica. \u00c0 medida que suas semanas em d\u00e9ficit avan\u00e7am, o app ajusta seu TDEE para baixo segundo os n\u00fameros cientificamente estabelecidos. Voc\u00ea n\u00e3o precisa fazer nada. S\u00f3 v\u00ea seu objetivo cal\u00f3rico se reajustar suavemente, sem surpresa.<\/p>\n      <p>Quando voc\u00ea atinge de 10 a 15&nbsp;% de adapta\u00e7\u00e3o, o app pode te aconselhar um retorno \u00e0 manuten\u00e7\u00e3o para reiniciar seu BMR antes de voltar ao d\u00e9ficit. Ciclo, plat\u00f4, ciclo. Como nos protocolos de verdade.<\/p>\n      <p>Nenhum coeficiente de atividade a escolher. Nenhuma caixa est\u00e1tica. S\u00f3 cada componente calculado com precis\u00e3o, semana ap\u00f3s semana.<\/p>\n    <\/div>\n    <div class=\"m-phone\">\n      <div class=\"mini-phone solo\" style=\"max-width:240px!important;width:240px;padding:6px!important;border-radius:24px!important;border-width:2px!important\"><div class=\"notch\" style=\"width:60px!important;height:14px!important;border-radius:0 0 9px 9px!important\"><\/div><div class=\"scr\" style=\"border-radius:18px!important\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp\" alt=\"\u00c9cran d\u00e9pense totale Lean avec adaptation m\u00e9tabolique\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">M\u00e9todo<strong>Adapta\u00e7\u00e3o metab\u00f3lica<\/strong><\/div>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"tab\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">05 &middot; Tabela comparativa<\/span><\/div>\n  <h2 id=\"tab\">Lean vs MyFitnessPal, crit\u00e9rio por crit\u00e9rio<\/h2>\n  <p>Leitura honesta dos pontos fortes e fracos de cada app. Nenhum crit\u00e9rio se refere ao pre\u00e7o.<\/p>\n\n  <div class=\"brand-banner\" style=\"display:grid;grid-template-columns:1fr 1fr;gap:16px;margin:24px 0 18px;padding:0\">\n  <div style=\"background:#FFF1F5;border:1.5px solid #FF2D6E;border-radius:14px;padding:20px 18px;display:flex;flex-direction:column;align-items:center;text-align:center;gap:10px\">\n    <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"Lean\" width=\"64\" height=\"64\" loading=\"lazy\" decoding=\"async\" style=\"width:64px;height:64px;border-radius:14px;display:block;object-fit:cover\" \/>\n    <div style=\"font-family:-apple-system,BlinkMacSystemFont,'SF Pro Display',sans-serif;font-size:18px;font-weight:700;color:#FF2D6E;letter-spacing:-0.2px\">Lean<\/div>\n  <\/div>\n  <div style=\"background:#F5F5F7;border:1.5px solid #D1D1D6;border-radius:14px;padding:20px 18px;display:flex;flex-direction:column;align-items:center;text-align:center;gap:10px\">\n    <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-myfitnesspal.webp\" alt=\"MyFitnessPal\" width=\"64\" height=\"64\" loading=\"lazy\" decoding=\"async\" style=\"width:64px;height:64px;border-radius:14px;display:block;object-fit:cover\" \/>\n    <div style=\"font-family:-apple-system,BlinkMacSystemFont,'SF Pro Display',sans-serif;font-size:18px;font-weight:700;color:#0E0E10;letter-spacing:-0.2px\">MyFitnessPal<\/div>\n  <\/div>\n<\/div>\n<div class=\"table\" role=\"table\" aria-label=\"Comparativo Lean vs MyFitnessPal\">\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\/lvm-logo-myfitnesspal.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> <span>MyFitnessPal<\/span><\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">F\u00f3rmula 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> Modelo propriet\u00e1rio patenteado (massa magra)<\/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 (s\u00f3 peso)<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Leva em conta a gordura corporal<\/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> Sim<\/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> N\u00e3o<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Medi\u00e7\u00e3o da gordura corporal no 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 foto<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> N\u00e3o<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">NEAT (passos, atividade fora do esporte)<\/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> Calculado sobre os passos reais<\/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> Agregado no coeficiente<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">EAT (gasto do exerc\u00edcio)<\/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> Por esporte via MET, tempo efetivo<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Estimativas fixas pouco confi\u00e1veis<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">TEF (digest\u00e3o)<\/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> Calculado segundo macros<\/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> N\u00e3o calculado<\/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> Autom\u00e1tica, semana a semana<\/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> N\u00e3o<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Coeficiente de atividade a escolher<\/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> N\u00e3o, calculado sobre dados reais<\/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> Sim, 4 caixas est\u00e1ticas<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Scan de foto por IA de um prato<\/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> Sim, ilimitado<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Limitado<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Scan de c\u00f3digo de barras<\/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> Sim<\/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> Sim<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Base de dados de alimentos<\/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, curada<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Comunit\u00e1ria, at\u00e9 10&nbsp;000 variantes do mesmo alimento<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Recomenda\u00e7\u00e3o de d\u00e9ficit cal\u00f3rico<\/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> Adaptada ao TDEE real<\/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> Estimativa fixa<\/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\u00e9todos para registrar uma refei\u00e7\u00e3o<\/h2>\n  <p>Registrar suas calorias \u00e9 bom. <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/comment-compter-ses-calories\/\">Fazer isso durante 12 meses \u00e9 outra hist\u00f3ria<\/a>. O princ\u00edpio n.\u00ba 1, <strong>antes da ci\u00eancia, antes dos macros, antes de tudo<\/strong>, \u00e9 a ader\u00eancia. Se o m\u00e9todo de registro te cansa, voc\u00ea para depois de 3 semanas. O Lean oferece 3 m\u00e9todos para registrar uma refei\u00e7\u00e3o:<\/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\u00e9todo 1<strong>Base de dados<\/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\u00e9todo 2<strong>C\u00f3digo de barras<\/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\u00e9todo 3<strong>Scan de foto por IA<\/strong><\/div>\n    <\/div>\n  <\/div>\n\n  <ol>\n    <li><strong>Busca na base de dados.<\/strong> Base curada, USDA + OpenFoodFacts. Sem ru\u00eddo comunit\u00e1rio, sem \u00ab&nbsp;Frango assado&nbsp;\u00bb inserido 47 vezes por 47 usu\u00e1rios diferentes com 47 valores diferentes.<\/li>\n    <li><strong>Scan de c\u00f3digo de barras.<\/strong> Padr\u00e3o. Voc\u00ea escaneia seu pacote de macarr\u00e3o, obt\u00e9m os macros.<\/li>\n    <li><strong>Scan de foto por IA de um prato.<\/strong> Voc\u00ea fotografa seu prato, a IA detecta os alimentos, voc\u00ea obt\u00e9m as calorias e os macros por alimento.<\/li>\n  <\/ol>\n  <p>O scan de foto por IA \u00e9 o game changer da ader\u00eancia. Quando voc\u00ea come fora, no restaurante, na casa de amigos, \u00e9 superpr\u00e1tico. Uma foto, voc\u00ea fecha o app, aproveita sua noite. Sim, \u00e9 menos preciso do que uma pesagem na grama com uma balan\u00e7a de cozinha. Mas em 12 meses, \u00e9 o que faz a diferen\u00e7a entre aguentar e abandonar. E aguentar \u00e9 o que conta.<\/p>\n  <p>Al\u00e9m do registro por refei\u00e7\u00e3o, o Lean mostra um <strong>TDEE ao vivo que se atualiza durante o dia<\/strong>. Quanto mais voc\u00ea anda, mais seu gasto aumenta, mais seu objetivo cal\u00f3rico do dia se ajusta. Voc\u00ea v\u00ea seu balan\u00e7o cal\u00f3rico ao vivo. \u00c9 mais motivador do que um n\u00famero congelado \u00e0s 8 da manh\u00e3.<\/p>\n  <p>E acima de tudo isso, h\u00e1 a <strong>Ficha Cassegrain &middot; 298 escaneamentos<\/strong>. \u00c9 uma tela do app que hierarquiza o que conta:<\/p>\n\n  <div class=\"pyramid\" aria-label=\"Pir\u00e2mide de Progress\u00e3o Lean\">\n    <div class=\"level l1\"><span>Ader\u00eancia<\/span><span class=\"k\">Base<\/span><\/div>\n    <div class=\"level l2\"><span>Objetivo cal\u00f3rico<\/span><span class=\"k\">N\u00edvel 2<\/span><\/div>\n    <div class=\"level l3\"><span>Passos \/ NEAT<\/span><span class=\"k\">N\u00edvel 3<\/span><\/div>\n    <div class=\"level l4\"><span>Macronutrientes<\/span><span class=\"k\">Topo<\/span><\/div>\n  <\/div>\n  <div class=\"pyramid-cap\">N\u00e3o queimar etapas. Se voc\u00ea n\u00e3o \u00e9 regular no tracking, otimizar os macros no um por cento n\u00e3o serve para nada.<\/div>\n<\/section>\n\n<section aria-labelledby=\"mfp-better\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">07 &middot; Honestidade<\/span><\/div>\n  <h2 id=\"mfp-better\">O que o MyFitnessPal faz melhor<\/h2>\n  <p>O Lean n\u00e3o \u00e9 perfeito, o MFP tem algumas vantagens que \u00e9 preciso reconhecer. Leitura honesta, crit\u00e9rio por crit\u00e9rio, nos eixos em que o MFP continua na frente.<\/p>\n\n  <div class=\"scorecard rev\" aria-label=\"Scorecard MFP vs Lean em 4 eixos secund\u00e1rios\">\n    <div class=\"scorecard-head\">\n      <div class=\"h-crit\">Eixo<\/div>\n      <div class=\"h-brand\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-myfitnesspal.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> MyFitnessPal<\/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\">Notoriedade &amp; tutoriais online<\/div>\n      <div class=\"bar mfp\" data-brand=\"MFP\"><div class=\"b\"><i style=\"width:95%\"><\/i><\/div><div class=\"v\">9,5<\/div><\/div>\n      <div class=\"bar lean\" data-brand=\"LEAN\"><div class=\"b\"><i style=\"width:40%\"><\/i><\/div><div class=\"v\">4,0<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Tamanho da base de dados<\/div>\n      <div class=\"bar mfp\" data-brand=\"MFP\"><div class=\"b\"><i style=\"width:90%\"><\/i><\/div><div class=\"v\">9,0<\/div><\/div>\n      <div class=\"bar lean\" data-brand=\"LEAN\"><div class=\"b\"><i style=\"width:75%\"><\/i><\/div><div class=\"v\">7,5<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Comunidade \/ feed social<\/div>\n      <div class=\"bar mfp\" data-brand=\"MFP\"><div class=\"b\"><i style=\"width:80%\"><\/i><\/div><div class=\"v\">8,0<\/div><\/div>\n      <div class=\"bar lean\" data-brand=\"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\">Integra\u00e7\u00f5es com apps de terceiros<\/div>\n      <div class=\"bar mfp\" data-brand=\"MFP\"><div class=\"b\"><i style=\"width:85%\"><\/i><\/div><div class=\"v\">8,5<\/div><\/div>\n      <div class=\"bar lean\" data-brand=\"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>Leitura honesta.<\/strong> Em notoriedade e feed social, o MFP continua na frente. Em tamanho bruto da base de dados de alimentos, o MFP tem mais entradas (mas os 14 milh\u00f5es de entradas s\u00e3o comunit\u00e1rias e ruidosas, at\u00e9 10&nbsp;000 variantes do mesmo alimento). Em integra\u00e7\u00f5es de terceiros, o MFP tem um ecossistema mais amplo. O Lean se integra com HealthKit e Google Fit, o que cobre 95&nbsp;% dos casos.<\/p>\n  <p>Resumindo, se tudo o que voc\u00ea quer \u00e9 um di\u00e1rio alimentar grosseiro sem objetivo preciso, o MFP basta de sobra. Se voc\u00ea busca perder gordura metodicamente com um <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/tdee-calculator\/\">TDEE preciso<\/a>, o MFP n\u00e3o basta, e \u00e9 o que acaba de ser demonstrado nas 3 se\u00e7\u00f5es anteriores.<\/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; Para quem<\/span><\/div>\n  <h2 id=\"forwho\">Para quem o Lean foi feito<\/h2>\n  <p>4 perfis. Se voc\u00ea se reconhece em pelo menos um, o Lean provavelmente foi feito para voc\u00ea.<\/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>Voc\u00ea tentou o MFP a s\u00e9rio e n\u00e3o perdeu<\/h4>\n        <p>Voc\u00ea aplicou um d\u00e9ficit honesto durante semanas, sem resultado. A causa \u00e9 muito provavelmente o TDEE falseado. O Lean corrige na raiz via o BMR sobre gordura corporal real.<\/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>Voc\u00ea estagna ap\u00f3s v\u00e1rias semanas de cutting<\/h4>\n        <p>Plat\u00f4 que se eterniza ap\u00f3s 4 a 8 semanas. \u00c9 a adapta\u00e7\u00e3o metab\u00f3lica. O Lean a calcula automaticamente e reajusta seu objetivo toda semana.<\/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>Voc\u00ea quer entender seu metabolismo<\/h4>\n        <p>O Lean mostra cada componente (BMR, NEAT, EAT, TEF, adapta\u00e7\u00e3o) em vez de esconder tudo atr\u00e1s de um n\u00famero \u00fanico. Voc\u00ea v\u00ea de onde vem cada kcal de gasto.<\/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>Voc\u00ea quer um tracking que dure 12 meses<\/h4>\n        <p>Scan de foto por IA + base curada + c\u00f3digo de barras cobrem todos os usos, do alimento cru \u00e0 pizza no restaurante. \u00c9 o que faz a diferen\u00e7a entre aguentar e desistir.<\/p>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>O MyFitnessPal pode bastar para<\/strong>&nbsp;: quem s\u00f3 quer um di\u00e1rio alimentar sem precis\u00e3o particular, ou quem gosta do lado social e comunit\u00e1rio.<\/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\">Migrar do MyFitnessPal para o Lean em 5 minutos<\/h2>\n\n  <div class=\"steps\">\n    <div class=\"step\"><div class=\"sn\">01<\/div><h4>Baixe o Lean<\/h4><p>App Store ou Play Store. Cadastro em 30 segundos.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">02<\/div><h4>BodyScan IA<\/h4><p>Uma foto, 5 segundos. Voc\u00ea obt\u00e9m sua gordura corporal.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">03<\/div><h4>Peso &amp; altura<\/h4><p>Informe seu peso e sua altura. \u00c9 s\u00f3 isso.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">04<\/div><h4>O Lean calcula<\/h4><p>BMR, NEAT (HealthKit \/ Google Fit), EAT, TEF, adapta\u00e7\u00e3o. Autom\u00e1tico.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">05<\/div><h4>Registre uma refei\u00e7\u00e3o<\/h4><p>Foto, c\u00f3digo de barras ou base de dados. Entenda o fluxo.<\/p><\/div>\n  <\/div>\n\n  <p style=\"margin-top:24px\"><strong>Nota importante.<\/strong> O Lean n\u00e3o oferece importa\u00e7\u00e3o autom\u00e1tica dos seus dados do MyFitnessPal. \u00c9 proposital. A base do MFP \u00e9 inserida \u00e0 m\u00e3o pelos usu\u00e1rios, portanto ruidosa. Preferimos recome\u00e7ar limpos, com uma base curada USDA + OpenFoodFacts, em vez de herdar o ru\u00eddo.<\/p>\n\n  <div class=\"cta-band rev\" style=\"display:flex;align-items:center;justify-content:space-between;gap:20px;flex-wrap:wrap;padding:26px 28px;margin:40px 0;background:#FAF5EE;border:1px solid #E8E2D6;border-radius:16px\">\n    <div class=\"l\" style=\"flex:1;min-width:240px;font-size:18px;line-height:1.4;font-weight:500;color:#0E0E10\">Baixe o Lean e comece o BodyScan IA agora mesmo. Cadastro gratuito.<\/div>\n    <div class=\"stores\" style=\"display:flex;gap:10px;align-items:center;flex-wrap:wrap\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"deblock-h\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">10 &middot; O que o Lean desbloqueia<\/span><\/div>\n  <h2 id=\"deblock-h\">O que o Lean faz, e que o MFP nunca far\u00e1<\/h2>\n  <p>Seis funcionalidades que n\u00e3o existem em nenhum outro tracker de consumo. Todas derivam do mesmo princ\u00edpio: calcular cada componente do TDEE com precis\u00e3o, n\u00e3o aproxim\u00e1-lo.<\/p>\n\n  <div class=\"feat-stack\">\n    <div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">BodyScan IA ilimitado<\/div><p class=\"fd\">Sua gordura corporal real, medida a partir de uma simples foto, refeita toda semana. \u00c9 o dado que muda todo o c\u00e1lculo do BMR. Nenhum outro app de consumo oferece isso.<\/p><\/div><div class=\"fc\">Gordura corporal<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">Scan de foto por IA de um prato ilimitado<\/div><p class=\"fd\">Registre sua refei\u00e7\u00e3o no restaurante em 2 segundos. Sem balan\u00e7a, sem entrada manual. O game changer da ader\u00eancia em 12 meses.<\/p><\/div><div class=\"fc\">Ader\u00eancia<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">Adapta\u00e7\u00e3o metab\u00f3lica autom\u00e1tica<\/div><p class=\"fd\">Seu TDEE se reajusta semana a semana segundo os n\u00fameros cientificamente estabelecidos. Voc\u00ea evita os plat\u00f4s que ningu\u00e9m sabe explicar.<\/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 decomposto ao vivo<\/div><p class=\"fd\">BMR + NEAT + EAT + TEF mostrados cada um, atualizados durante o dia. Chega de n\u00famero congelado \u00e0s 8 da manh\u00e3. Voc\u00ea v\u00ea seu balan\u00e7o cal\u00f3rico ao vivo.<\/p><\/div><div class=\"fc\">Ao vivo<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">05<\/div><div><div class=\"ft\">Hist\u00f3rico completo e tend\u00eancias<\/div><p class=\"fd\">Acompanhe suas tend\u00eancias de peso, gordura corporal, massa magra ao longo de meses. Entenda seus ciclos. Identifique as fases em que voc\u00ea progride e aquelas em que estagna.<\/p><\/div><div class=\"fc\">Hist\u00f3rico<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">06<\/div><div><div class=\"ft\">3 m\u00e9todos de tracking unificados<\/div><p class=\"fd\">Foto, c\u00f3digo de barras, base curada. Nenhum outro app oferece os tr\u00eas com tal precis\u00e3o. Voc\u00ea escolhe o m\u00e9todo segundo o contexto.<\/p><\/div><div class=\"fc\">Tracking<\/div><\/div>\n  <\/div>\n\n  <p style=\"margin-top:26px\">Voc\u00ea instala o app gratuitamente, testa sem compromisso e depois decide se a ferramenta combina com seu objetivo.<\/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>Mifflin-St Jeor \u00e9 melhor do que Harris-Benedict?<\/summary><div class=\"ans\">Marginalmente. Mifflin-St Jeor (1990) \u00e9 uma atualiza\u00e7\u00e3o de Harris-Benedict com uma amostra ligeiramente mais moderna. Mas herda o mesmo defeito conceitual: sem gordura corporal como entrada. \u00c9 s\u00f3 uma vers\u00e3o repintada do mesmo erro. O MFP usa Mifflin-St Jeor h\u00e1 alguns anos, o que \u00e9 melhor do que Harris-Benedict, mas n\u00e3o corrige o problema fundamental.<\/div><\/details>\n    <details><summary>\u00c9 realmente preciso conhecer sua gordura corporal?<\/summary><div class=\"ans\">Sim. Sem gordura corporal, seu BMR pode estar errado em 400&nbsp;kcal (veja o exemplo dos dois homens de 80&nbsp;kg, um com 10&nbsp;%, o outro com 30&nbsp;%). Voc\u00ea nunca perder\u00e1 peso a s\u00e9rio sem esse dado. Medi-lo toda semana com o BodyScan IA leva 5 segundos.<\/div><\/details>\n    <details><summary>O coeficiente de atividade n\u00e3o funciona de jeito nenhum?<\/summary><div class=\"ans\">Para uma estimativa ultragrosseira em 6 meses, pode dar uma vaga tend\u00eancia. Para atingir um objetivo preciso (perda de gordura, ganho de massa limpa), \u00e9 insuficiente. A variabilidade di\u00e1ria do gasto \u00e9 grande demais para ser captada por uma caixa est\u00e1tica.<\/div><\/details>\n    <details><summary>O que \u00e9 exatamente a adapta\u00e7\u00e3o metab\u00f3lica?<\/summary><div class=\"ans\">\u00c9 a queda espont\u00e2nea do seu gasto cal\u00f3rico quando voc\u00ea est\u00e1 em d\u00e9ficit prolongado. Modo de economia de energia. Para um d\u00e9ficit de &minus;500&nbsp;kcal\/dia, seu TDEE pode cair de 10 a 15&nbsp;% em 4 a 6 semanas. Se um app n\u00e3o sabe disso, voc\u00ea estagna sem entender por qu\u00ea.<\/div><\/details>\n    <details><summary>Quanto tempo para ver um resultado com o Lean?<\/summary><div class=\"ans\">Tudo depende do d\u00e9ficit aplicado. Para um d\u00e9ficit razo\u00e1vel de &minus;250 a &minus;500&nbsp;kcal\/dia, voc\u00ea deve ver uma perda de 0,3 a 0,6&nbsp;kg por semana. A grande diferen\u00e7a com o MFP: com o Lean seu TDEE \u00e9 conhecido com precis\u00e3o, portanto seu d\u00e9ficit \u00e9 realmente aplicado, sem surpresa estat\u00edstica.<\/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; Conclus\u00e3o<\/span><\/div>\n  <h2 id=\"conclu\">1919 diante de 2025<\/h2>\n  <p>N\u00e3o \u00e9 MyFitnessPal contra Lean em marketing. \u00c9 1919 diante de 2025 em ci\u00eancia.<\/p>\n  <p>O MFP usa uma f\u00f3rmula da sa\u00edda da Primeira Guerra Mundial, mais um coeficiente de atividade quase aleat\u00f3rio, e ignora a adapta\u00e7\u00e3o metab\u00f3lica. A combina\u00e7\u00e3o dos tr\u00eas torna qualquer estimativa precisa imposs\u00edvel. \u00c9 matem\u00e1tico.<\/p>\n  <p>O Lean foi constru\u00eddo para fazer exatamente o inverso: BMR baseado na <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/depense-energetique-totale-v2\/\">gordura corporal real<\/a> (medido por BodyScan IA) via um modelo propriet\u00e1rio patenteado, <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/neat-depense-non-sportive\/\">NEAT por passos reais<\/a>, EAT por esporte e MET, <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/effet-thermique-des-aliments\/\">TEF por macros<\/a>, adapta\u00e7\u00e3o metab\u00f3lica autom\u00e1tica. Cada componente calculado com precis\u00e3o, sem coeficiente m\u00e1gico.<\/p>\n  <p>Se voc\u00ea tentou o MFP a s\u00e9rio e n\u00e3o teve os resultados que esperava, o problema n\u00e3o \u00e9 voc\u00ea. O problema est\u00e1 debaixo do cap\u00f4. Mude de app.<\/p>\n<\/section>\n\n<div class=\"get-band rev\" style=\"background:#F1E9DC;border-radius:24px;padding:48px 36px;margin:60px 0 40px;text-align:center\">\n  <div class=\"kicker\">Download<\/div>\n  <h3>A Lean pode ser baixada gratuitamente<\/h3>\n  <p>iOS e Android. O BodyScan IA funciona com uma simples foto. Sem adip\u00f4metro, sem balan\u00e7a de bioimped\u00e2ncia, sem DEXA.<\/p>\n  <div class=\"stores\" style=\"display:flex;gap:10px;align-items:center;flex-wrap:wrap\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" target=\"_blank\" rel=\"noopener\" aria-label=\"Baixar o Lean 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\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" target=\"_blank\" rel=\"noopener\" aria-label=\"Baixar o Lean 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\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/>\n    <\/a>\n  <\/div>\n<\/div>\n\n<section aria-labelledby=\"links\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">Para ir al\u00e9m<\/span><\/div>\n  <h3 id=\"links\" style=\"margin-top:0\">Links internos<\/h3>\n  <ul>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/tdee-calculator\/\">Calculadora TDEE gratuita online<\/a> &middot; vers\u00e3o web, sem cadastro, mesma l\u00f3gica do app (BMR + NEAT + EAT + TEF).<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/depense-energetique-totale-v2\/\">Entender o TDEE em detalhe (BMR, NEAT, EAT, TEF, adapta\u00e7\u00e3o)<\/a> &middot; artigo cient\u00edfico de fundo.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/comment-compter-ses-calories\/\">Como contar suas calorias corretamente<\/a> &middot; guia pr\u00e1tico para iniciantes.<\/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)\">Bibliografia<\/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>Shcherbina A. et al. (Stanford University, 2017). Accuracy in Wrist-Worn Wearable Devices for Measuring Heart Rate and Energy Expenditure.<\/li>\n    <li>Westerterp K.R. (2004). Diet induced thermogenesis. Nutrition and Metabolism.<\/li>\n    <li>Rosenbaum M., Leibel R.L. (2010). Adaptive thermogenesis in humans. International Journal of Obesity.<\/li>\n    <li>M\u00fcller M.J., Bosy-Westphal A. (2013). Adaptive thermogenesis with weight loss in humans. Obesity.<\/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>Artigo publicado em 21 de maio de 2026. Atualizado regularmente com o feedback dos usu\u00e1rios e os novos estudos relevantes. O Lean est\u00e1 dispon\u00edvel para iOS e Android.<\/p>\n      <\/div>\n      <div class=\"stores\" style=\"display:flex;gap:10px;align-items:center;flex-wrap:wrap\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n        <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n      <\/div>\n    <\/div>\n  <\/div>\n<\/footer>\n\n<script data-wpmeteor-nooptimize=\"true\">\n(function(){\n  var bar = document.getElementById('progBar');\n  function up(){\n    var h = document.documentElement;\n    var sc = (h.scrollTop)\/Math.max(1,(h.scrollHeight - h.clientHeight));\n    bar.style.transform = 'scaleX(' + Math.max(0,Math.min(1,sc)) + ')';\n  }\n  document.addEventListener('scroll', up, {passive:true});\n  up();\n})();\n\n(function(){\n  if (!('IntersectionObserver' in window)) {\n    document.querySelectorAll('.rev').forEach(function(n){n.classList.add('on')});\n    return;\n  }\n  var obs = new IntersectionObserver(function(entries){\n    entries.forEach(function(e){\n      if (e.isIntersecting) { e.target.classList.add('on'); obs.unobserve(e.target); }\n    });\n  }, {threshold:0.12});\n  document.querySelectorAll('.rev').forEach(function(n){ obs.observe(n); });\n})();\n\n(function(){\n  var phoneImg = document.getElementById('phoneImg');\n  var phoneBack = document.getElementById('phoneBack');\n  var zones = document.getElementById('phoneZones');\n  var topTabs = document.querySelectorAll('.phone-tabs button');\n  var navTaps = document.querySelectorAll('.phone-navbar button');\n\n  var tabMap = {\n    bilan:    {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 ? 'block' : 'none';\n      phoneBack.classList.remove('on');\n    }, 150);\n    setActive(tab);\n  }\n  function showSub(sub){\n    var src = subMap[sub]; if(!src) return;\n    phoneImg.style.opacity = 0;\n    setTimeout(function(){\n      phoneImg.className = 'phone-bg sub-' + sub;\n      phoneImg.style.opacity = 1;\n      zones.style.display = 'none';\n      phoneBack.classList.add('on');\n    }, 150);\n  }\n\n  var hintD = document.getElementById('tapHintDesktop');\n  var hintM = document.getElementById('tapHintMobile');\n  function hideHints(){\n    if (hintD) hintD.classList.add('hidden');\n    if (hintM) hintM.classList.add('hidden');\n  }\n\n  topTabs.forEach(function(b){ b.addEventListener('click', function(){ hideHints(); showTab(b.dataset.tab); }); });\n  navTaps.forEach(function(b){ b.addEventListener('click', function(){ hideHints(); showTab(b.dataset.tab); }); });\n  zones.querySelectorAll('.z').forEach(function(z){\n    z.addEventListener('click', function(){ hideHints(); showSub(z.dataset.sub); });\n    z.addEventListener('keydown', function(e){\n      if (e.key==='Enter' || e.key===' ') { e.preventDefault(); hideHints(); showSub(z.dataset.sub); }\n    });\n  });\n  phoneBack.addEventListener('click', function(){ hideHints(); showTab(currentTab); });\n})();\n\n(function chartInit(){\n  if (typeof Chart === 'undefined' || !window['chartjs-plugin-annotation']) { return setTimeout(chartInit, 60); }\n  var PINK = '#FF2D6E';\n  var LEAN_LANG = (((document.documentElement && document.documentElement.lang)||'').toLowerCase().indexOf('en')===0 || location.pathname.indexOf('\/en\/')===0) ? 'en' : 'fr';\n  function T(fr,en){return LEAN_LANG==='en'?en:fr;}\n\n  var MFP  = '#A8A192';\n  var INK  = '#0E0E10';\n  var MUTE = '#6E6E73';\n  var RULE = '#E8E6DF';\n\n  Chart.defaults.font.family = '-apple-system, \"SF Pro Text\", system-ui, sans-serif';\n  Chart.defaults.color = MUTE;\n\n  \/\/ Plugin custom : trait pointille noir reliant le sommet de la barre MFP (2500) au sommet de la barre Lean (2000) pour le chart BMR\n  var bmrDeltaLine = {\n    id: 'bmrDeltaLine',\n    afterDatasetsDraw: function(chart){\n      var meta = chart.getDatasetMeta(0);\n      if (!meta || !meta.data || meta.data.length < 2) return;\n      var b1 = meta.data[0], b2 = meta.data[1];\n      if (!b1 || !b2) return;\n      var ctx = chart.ctx;\n      var x1 = b1.x, y1 = b1.y;\n      var x2 = b2.x, y2 = b2.y;\n      ctx.save();\n      ctx.strokeStyle = INK;\n      ctx.lineWidth = 1.5;\n      ctx.setLineDash([6,4]);\n      ctx.beginPath();\n      ctx.moveTo(x1, y1);\n      ctx.lineTo(x2, y1);   \/\/ segment horizontal en haut de la barre MFP\n      ctx.moveTo(x2, y1);\n      ctx.lineTo(x2, y2);   \/\/ segment vertical jusqu'au sommet de la barre Lean\n      ctx.stroke();\n      ctx.restore();\n    }\n  };\n\n  \/\/ v13.0: eager init (was lazy IntersectionObserver, caused screenshot\/timing issues)\n  function buildAll(){\n    if (document.getElementById('chartBMR'))   { try { buildBMR(); }   catch(e){ console.error('buildBMR', e); } }\n    if (document.getElementById('chartNEAT'))  { try { buildNEAT(); }  catch(e){ console.error('buildNEAT', e); } }\n    if (document.getElementById('chartAdapt')) { try { buildAdapt(); } catch(e){ console.error('buildAdapt', e); } }\n  }\n  if (document.readyState === 'loading') {\n    document.addEventListener('DOMContentLoaded', function(){ requestAnimationFrame(buildAll); });\n  } else {\n    requestAnimationFrame(buildAll);\n  }\n\n  \/\/ Animation des barres horizontales scorecard\n  var scoreObs = new IntersectionObserver(function(entries){\n    entries.forEach(function(e){\n      if (!e.isIntersecting) return;\n      e.target.querySelectorAll('.bar .b > i').forEach(function(i){\n        var w = i.style.width;\n        i.style.width = '0%';\n        requestAnimationFrame(function(){ requestAnimationFrame(function(){ i.style.width = w; }); });\n      });\n      scoreObs.unobserve(e.target);\n    });\n  }, {threshold:0.25});\n  document.querySelectorAll('.scorecard').forEach(function(n){ scoreObs.observe(n); });\n\n  function fmt(n){return LEAN_LANG==='en'?n.toLocaleString('en-US'):n.toLocaleString('fr-FR').replace(',',' ');}\n\n  function buildBMR(){\n    var ctx = document.getElementById('chartBMR').getContext('2d');\n    new Chart(ctx, {\n      type: 'bar',\n      data: {\n        labels: T(['MFP \u00b7 Harris-Benedict\\n1919', 'LEAN \u00b7 calcul sur\\nta masse maigre'],['MFP \u00b7 Harris-Benedict\\n1919', 'LEAN \u00b7 based on\\nyour lean mass']),\n        datasets: [{\n          data: [2500, 2000],\n          backgroundColor: [MFP, PINK],\n          borderRadius: 6,\n          maxBarThickness: 110\n        }]\n      },\n      plugins: [bmrDeltaLine],\n      options: {\n        responsive:true, maintainAspectRatio:false, devicePixelRatio: Math.max(2, window.devicePixelRatio||2),\n        animation:{duration:900, easing:'easeOutQuart'},\n        layout:{padding:{top:56, bottom:6, left:14, right:14}},\n        plugins:{\n          legend:{display:false},\n          tooltip:{enabled:false},\n          annotation:{\n            annotations:{\n              lblMFP:{type:'label',xValue:0,yValue:2670,content:['2 500'],font:{family:'-apple-system',size:24,weight:'700'},color:INK},\n              lblLEAN:{type:'label',xValue:1,yValue:2170,content:['2 000'],font:{family:'-apple-system',size:24,weight:'700'},color:PINK},\n              delta:{type:'label',xValue:0.5,yValue:2750,content:['\u2212500 kcal'],font:{family:'-apple-system',size:12,weight:'600'},color:'#fff',backgroundColor:INK,borderRadius:14,padding:{x:11,y:5},xAdjust:0,yAdjust:5\/*v17OV*\/}\n            }\n          }\n        },\n        scales:{\n          x:{grid:{display:false,drawBorder:false},ticks:{font:{size:11},color:MUTE,callback:function(v,i){return this.getLabelForValue(v).split('\\n');}},border:{display:false}},\n          y:{beginAtZero:true,max:2900,position:'right',grid:{color:RULE,borderDash:[4,4],drawBorder:false},border:{display:false},ticks:{font:{size:11},color:MUTE,stepSize:1000,callback:function(v){return v===0?'0':fmt(v);}}}\n        }\n      }\n    });\n  }\n\n  function buildNEAT(){\n    var ctx = document.getElementById('chartNEAT').getContext('2d');\n    var labels = T(['Lun','Mar','Mer','Jeu','Ven','Sam','Dim'],['Mon','Tue','Wed','Thu','Fri','Sat','Sun']);\n    var real   = [2100, 2350, 2080, 2950, 2200, 3200, 1800];\n    new Chart(ctx, {\n      type: 'line',\n      data: {\n        labels: labels,\n        datasets: [\n          {label:T('Lean \u00b7 d\u00e9pense r\u00e9elle','Lean \u00b7 actual expenditure'),data:real,borderColor:PINK,backgroundColor:'rgba(255,45,110,0.08)',borderWidth:2.5,pointRadius:5,pointBackgroundColor:'#fff',pointBorderColor:PINK,pointBorderWidth:2,tension:0.35,fill:true},\n          {label:T('MFP \u00b7 objectif fixe 2 400 kcal','MFP \u00b7 flat 2,400 kcal target'),data:[2400,2400,2400,2400,2400,2400,2400],borderColor:MFP,borderWidth:2.5,borderDash:[8,5],pointRadius:0,tension:0,fill:false}\n        ]\n      },\n      options: {\n        responsive:true, maintainAspectRatio:false, devicePixelRatio: Math.max(2, window.devicePixelRatio||2),\n        animation:{duration:1000, easing:'easeOutQuart'},\n        layout:{padding:{top:function(c){return c.chart.width>=540?80:18;},bottom:function(c){return c.chart.width>=540?34:22;},left:function(c){return c.chart.width>=540?32:8;},right:function(c){return c.chart.width>=540?64:6;}}},\n        plugins:{\n          legend:{display:true, position:'top', align:'start', labels:{boxWidth:14, boxHeight:2, color:MUTE, font:{size:12}, padding:14, usePointStyle:false}},\n          tooltip:{backgroundColor:'#0c0c0c',titleColor:'#fff',bodyColor:'#fff',cornerRadius:8,padding:10,displayColors:false,callbacks:{label:function(c){return fmt(c.parsed.y)+' kcal';}}},\n          annotation:{annotations:{\n            peakSam:{type:'label',xValue:5,yValue:3450,content:function(c){return c.chart.width>=540?T(['Disneyland 15 km','+800 kcal'],['Disneyland 15 km','+800 kcal']):T(['Disneyland','+800 kcal'],['Disneyland','+800 kcal']);},font:{family:'-apple-system',size:10,weight:'600'},color:'#fff',backgroundColor:PINK,borderRadius:10,padding:{x:9,y:5},textAlign:'center',xAdjust:function(c){return c.chart.width>=540?-26:-32;}},\n            peakJeu:{type:'label',xValue:3,yValue:function(c){return c.chart.width>=540?3300:2800;},content:function(c){return c.chart.width>=540?T(['Footing + bureau debout'],['Jogging + standing desk']):T(['Footing','bureau debout'],['Jogging','standing desk']);},font:{family:'-apple-system',size:10,weight:'600'},color:'#fff',backgroundColor:INK,borderRadius:10,padding:{x:9,y:5}},\n            dipDim:{type:'label',xValue:6,yValue:1620,content:function(c){return c.chart.width>=540?T(['Canap\u00e9 Netflix','\u2212600 kcal'],['Netflix on the couch','\u2212600 kcal']):T(['Canap\u00e9','\u2212600 kcal'],['Couch','\u2212600 kcal']);},font:{family:'-apple-system',size:10,weight:'600'},color:'#fff',backgroundColor:'#5a5a5e',borderRadius:10,padding:{x:9,y:5},textAlign:'center',xAdjust:function(c){return c.chart.width>=540?-46:-28;}},\n            mfpTag:{type:'label',xValue:function(c){return c.chart.width>=540?0.55:1.0;},yValue:function(c){return c.chart.width>=540?2510:2750;},content:function(c){return c.chart.width>=540?T(['MFP fixe : 2 400'],['MFP flat: 2,400']):T(['MFP fixe','2 400'],['MFP flat','2,400']);},font:{family:'-apple-system',size:10,weight:'600'},color:'#fff',backgroundColor:MFP,borderRadius:10,padding:{x:9,y:4}}\n          }}\n        },\n        scales:{\n          x:{grid:{display:false,drawBorder:false},ticks:{font:{size:11},color:MUTE},border:{display:false}},\n          y:{min:1400,max:3800,position:'right',grid:{color:RULE,borderDash:[4,4],drawBorder:false},border:{display:false},ticks:{font:{size:11},color:MUTE,stepSize:500,callback:function(v){return fmt(v);}}}\n        }\n      }\n    });\n  }\n\n  function buildAdapt(){\n    var ctx = document.getElementById('chartAdapt').getContext('2d');\n    var labels = T(['S.1','S.2','S.3','S.4','S.5','S.6','S.7','S.8'],['W.1','W.2','W.3','W.4','W.5','W.6','W.7','W.8']);\n    var lean = [2500, 2470, 2420, 2350, 2280, 2230, 2180, 2150];\n    var mfp  = [2500, 2500, 2500, 2500, 2500, 2500, 2500, 2500];\n    new Chart(ctx, {\n      type:'line',\n      data:{labels:labels,datasets:[\n        {label:T('Lean \u00b7 TDEE r\u00e9elle adapt\u00e9e','Lean \u00b7 actual adapted TDEE'),data:lean,borderColor:PINK,backgroundColor:'rgba(255,45,110,0.10)',borderWidth:2.5,pointRadius:4,pointBackgroundColor:'#fff',pointBorderColor:PINK,pointBorderWidth:2,tension:0.35,fill:true},\n        {label:T('MFP \u00b7 objectif fig\u00e9','MFP \u00b7 frozen target'),data:mfp,borderColor:MFP,borderWidth:2.5,borderDash:[8,5],pointRadius:0,tension:0,fill:false}\n      ]},\n      options:{\n        responsive:true, maintainAspectRatio:false, devicePixelRatio: Math.max(2, window.devicePixelRatio||2),\n        animation:{duration:1100, easing:'easeOutQuart'},\n        layout:{padding:{top:function(c){return c.chart.width>=540?72:18;},bottom:function(c){return c.chart.width>=540?28:22;},left:function(c){return c.chart.width>=540?64:8;},right:function(c){return c.chart.width>=540?64:6;}}},\n        plugins:{\n          legend:{display:true,position:'top',align:'start',labels:{boxWidth:14,boxHeight:2,color:MUTE,font:{size:12},padding:14}},\n          tooltip:{backgroundColor:'#0c0c0c',titleColor:'#fff',bodyColor:'#fff',cornerRadius:8,padding:10,displayColors:false,callbacks:{label:function(c){return fmt(c.parsed.y)+' kcal';}}},\n          annotation:{annotations:{\n            adaptTag:{type:'label',xValue:function(c){return c.chart.width>=540?5.6:3.5;},yValue:function(c){return c.chart.width>=540?2100:2300;},content:function(c){return c.chart.width>=540?T(['Adaptation m\u00e9tabolique','\u221214 %'],['Metabolic adaptation','\u221214%']):T(['Adaptation','m\u00e9tabolique','\u221214 %'],['Metabolic','adaptation','\u221214%']);},font:{family:'-apple-system',size:10,weight:'600'},color:'#fff',backgroundColor:PINK,borderRadius:10,padding:{x:9,y:5},textAlign:'center'},\n            mfpStill:{type:'label',xValue:function(c){return c.chart.width>=540?0.7:1.3;},yValue:2570,content:function(c){return c.chart.width>=540?T(['MFP : 2 500 fig\u00e9'],['MFP: 2,500 frozen']):T(['MFP fig\u00e9','2 500'],['MFP frozen','2,500']);},font:{family:'-apple-system',size:10,weight:'600'},color:'#fff',backgroundColor:MFP,borderRadius:10,padding:{x:9,y:4}},\n            start:{type:'label',xValue:0,yValue:2630,content:['2 500'],font:{family:'-apple-system',size:14,weight:'700'},color:INK,xAdjust:22,xAdjust:22,yAdjust:-13\/*v17OV*\/},\n            end:{type:'label',xValue:7,yValue:2080,content:['2 150'],font:{family:'-apple-system',size:14,weight:'700'},color:PINK,xAdjust:-22}\n          }}\n        },\n        scales:{\n          x:{grid:{display:false,drawBorder:false},ticks:{font:{size:11},color:MUTE},border:{display:false}},\n          y:{min:2000,max:2700,position:'right',grid:{color:RULE,borderDash:[4,4],drawBorder:false},border:{display:false},ticks:{font:{size:11},color:MUTE,stepSize:200,callback:function(v){return fmt(v);}}}\n        }\n      }\n    });\n  }\n})();\n<\/script><\/div>\n<script data-wpmeteor-nooptimize=\"true\">\n(function shrinkAnnotationsOnMobile(){\n  if (typeof window.Chart === 'undefined') { return setTimeout(shrinkAnnotationsOnMobile, 100); }\n  var isMobile = window.matchMedia && window.matchMedia('(max-width:540px)').matches;\n  if (!isMobile) return;\n  function apply(){\n    ['chartBMR','chartNEAT','chartAdapt'].forEach(function(id){\n      var c = window.Chart.getChart(id);\n      if (!c) return;\n      var anns = c.options && c.options.plugins && c.options.plugins.annotation && c.options.plugins.annotation.annotations;\n      if (!anns) return;\n      Object.keys(anns).forEach(function(k){\n        var a = anns[k];\n        if (a.type !== 'label' || !a.font) return;\n        \/\/ Numeric labels are small text. Big fonts (>=14) get shrunk to 13.\n        if (a.font.size >= 20) { a.font.size = 14; }\n        else if (a.font.size >= 14) { a.font.size = 12; }\n      });\n      try { c.update('none'); } catch(e){}\n    });\n  }\n  \/\/ Try a few times to catch all charts as they instantiate\n  var tries = 0;\n  function tryApply(){\n    apply();\n    tries++;\n    if (tries < 20) setTimeout(tryApply, 300);\n  }\n  tryApply();\n})();\n<\/script>\n\n\n\n<!-- lean-mesh-v19 -->\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=\"https:\/\/lean-app.com\/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 \u00e9 preciso 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 TDEE, 4 f\u00f3rmulas hist\u00f3ricas, por que a gordura corporal muda tudo.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/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 os 4 blocos + a adapta\u00e7\u00e3o metab\u00f3lica, fontes cient\u00edficas 2025.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/pt\/comparatifs-croises\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">MyFitnessPal ou Yazio? 12 duelos de apps de calorias comparados <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">O veredito de cada duelo de relance: quem ganha em qu\u00ea, e o que nenhum dos dois calcula.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/pt\/perdre-du-poids-avec-chatgpt\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Perder peso com ChatGPT funciona? Fizemos a pergunta 291 vezes a 5 IAs <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">291 respostas, 5 IAs, 6 perfis id\u00eanticos: at\u00e9 1 260 kcal de diferen\u00e7a para a mesma pessoa, e nenhum acompanhamento no dia seguinte.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/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;\">Qual alternativa ao MyFitnessPal em 2026? 5 apps testados <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Comparativo honesto, precis\u00e3o do TDEE, ergonomia.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/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 do Lean frente aos grandes apps 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=\"https:\/\/lean-app.com\/pt\/lean-vs-yazio\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean contra o Yazio: precis\u00e3o cient\u00edfica vs ergonomia europeia <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Comparativo BMR, NEAT, EAT, TEF, adapta\u00e7\u00e3o.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/pt\/lean-vs-foodvisor\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean contra o Foodvisor: pioneiro do scan de fotos vs gasto real <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">O Foodvisor v\u00ea o seu prato. O Lean recomp\u00f5e o seu TDEE continuamente.<\/span><\/a><\/li><\/ul><\/aside>","protected":false},"excerpt":{"rendered":"<p>MyFitnessPal calcule votre TDEE avec une formule de 1919, sans bodyfat ni adaptation m\u00e9tabolique. Lean fait tout ce que MFP ne sait pas faire. Comparatif honn\u00eate.<\/p>","protected":false},"author":1,"featured_media":1242,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"single-lvm-blank","format":"standard","meta":{"footnotes":""},"categories":[13],"tags":[],"class_list":["post-1241","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-comparateurs"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Lean vs MyFitnessPal: a f\u00f3rmula TDEE que muda tudo - Lean<\/title>\n<meta name=\"description\" content=\"Por que o MyFitnessPal calcula mal seu gasto cal\u00f3rico: BMR com f\u00f3rmula de 1919, sem adapta\u00e7\u00e3o metab\u00f3lica, NEAT\/EAT fixos. Comparativo detalhado Lean vs MFP.\" \/>\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-myfitnesspal\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Lean vs MyFitnessPal: a f\u00f3rmula TDEE que muda tudo - Lean\" \/>\n<meta property=\"og:description\" content=\"Por que o MyFitnessPal calcula mal seu gasto cal\u00f3rico: BMR com f\u00f3rmula de 1919, sem adapta\u00e7\u00e3o metab\u00f3lica, NEAT\/EAT fixos. Comparativo detalhado Lean vs MFP.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/lean-app.com\/pt\/lean-vs-myfitnesspal\/\" \/>\n<meta property=\"og:site_name\" content=\"Lean\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/share\/1GXD3qyMBy\/?mibextid=wwXIfr\" \/>\n<meta property=\"article:published_time\" content=\"2026-05-21T18:28:26+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-09-08T18:17:56+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-og-image.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1200\" \/>\n\t<meta property=\"og:image:height\" content=\"630\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"L&#039;\u00e9quipe Lean\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"L&#039;\u00e9quipe Lean\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"22 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/\"},\"author\":{\"@id\":\"https:\/\/lean-app.com\/#organization\"},\"headline\":\"Lean vs MyFitnessPal : la formule TDEE qui change tout\",\"datePublished\":\"2026-05-21T18:28:26+00:00\",\"dateModified\":\"2026-09-08T18:17:56+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/\"},\"wordCount\":4516,\"publisher\":{\"@id\":\"https:\/\/lean-app.com\/#organization\"},\"image\":{\"@id\":\"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-og-image.png\",\"articleSection\":[\"Comparateurs\"],\"inLanguage\":\"pt-BR\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/\",\"url\":\"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/\",\"name\":\"Lean vs MyFitnessPal : la formule TDEE qui change tout - Lean\",\"isPartOf\":{\"@id\":\"https:\/\/lean-app.com\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-og-image.png\",\"datePublished\":\"2026-05-21T18:28:26+00:00\",\"dateModified\":\"2026-09-08T18:17:56+00:00\",\"description\":\"Pourquoi MyFitnessPal calcule mal ta d\u00e9pense calorique : BMR sur formule de 1919, pas d'adaptation m\u00e9tabolique, NEAT\/EAT fixes. Comparatif d\u00e9taill\u00e9 Lean vs MFP.\",\"breadcrumb\":{\"@id\":\"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/#breadcrumb\"},\"inLanguage\":\"pt-BR\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"pt-BR\",\"@id\":\"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/#primaryimage\",\"url\":\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-og-image.png\",\"contentUrl\":\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-og-image.png\",\"width\":1200,\"height\":630},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/lean-app.com\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Lean vs MyFitnessPal : la formule TDEE qui change tout\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/lean-app.com\/#website\",\"url\":\"https:\/\/lean-app.com\/\",\"name\":\"Lean\",\"description\":\"T\u00e9l\u00e9charge, essaye GRATUITEMENT l&#039;application et prends en main ton corps \u00c0 VIE.\",\"publisher\":{\"@id\":\"https:\/\/lean-app.com\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/lean-app.com\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"pt-BR\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/lean-app.com\/#organization\",\"name\":\"Lean\",\"url\":\"https:\/\/lean-app.com\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"pt-BR\",\"@id\":\"https:\/\/lean-app.com\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/lean-app.com\/wp-content\/uploads\/2025\/08\/Logo-for-Lean-App-the-best-calorie-and-TDEE-tracking-application.png\",\"contentUrl\":\"https:\/\/lean-app.com\/wp-content\/uploads\/2025\/08\/Logo-for-Lean-App-the-best-calorie-and-TDEE-tracking-application.png\",\"width\":1672,\"height\":1484,\"caption\":\"Lean\"},\"image\":{\"@id\":\"https:\/\/lean-app.com\/#\/schema\/logo\/image\/\"},\"sameAs\":[\"https:\/\/www.facebook.com\/share\/1GXD3qyMBy\/?mibextid=wwXIfr\",\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\",\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\",\"https:\/\/app.dealroom.co\/companies\/lean_calorie_tracker\",\"https:\/\/alternativeto.net\/software\/lean-calorie-tracker\/\"]}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Lean vs MyFitnessPal: a f\u00f3rmula TDEE que muda tudo - Lean","description":"Por que o MyFitnessPal calcula mal seu gasto cal\u00f3rico: BMR com f\u00f3rmula de 1919, sem adapta\u00e7\u00e3o metab\u00f3lica, NEAT\/EAT fixos. Comparativo detalhado Lean vs MFP.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/lean-app.com\/pt\/lean-vs-myfitnesspal\/","og_locale":"pt_BR","og_type":"article","og_title":"Lean vs MyFitnessPal: a f\u00f3rmula TDEE que muda tudo - Lean","og_description":"Por que o MyFitnessPal calcula mal seu gasto cal\u00f3rico: BMR com f\u00f3rmula de 1919, sem adapta\u00e7\u00e3o metab\u00f3lica, NEAT\/EAT fixos. Comparativo detalhado Lean vs MFP.","og_url":"https:\/\/lean-app.com\/pt\/lean-vs-myfitnesspal\/","og_site_name":"Lean","article_publisher":"https:\/\/www.facebook.com\/share\/1GXD3qyMBy\/?mibextid=wwXIfr","article_published_time":"2026-05-21T18:28:26+00:00","article_modified_time":"2026-09-08T18:17:56+00:00","og_image":[{"width":1200,"height":630,"url":"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-og-image.png","type":"image\/png"}],"author":"L'\u00e9quipe Lean","twitter_card":"summary_large_image","twitter_misc":{"Written by":"L'\u00e9quipe Lean","Est. reading time":"22 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/#article","isPartOf":{"@id":"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/"},"author":{"@id":"https:\/\/lean-app.com\/#organization"},"headline":"Lean vs MyFitnessPal : la formule TDEE qui change tout","datePublished":"2026-05-21T18:28:26+00:00","dateModified":"2026-09-08T18:17:56+00:00","mainEntityOfPage":{"@id":"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/"},"wordCount":4516,"publisher":{"@id":"https:\/\/lean-app.com\/#organization"},"image":{"@id":"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/#primaryimage"},"thumbnailUrl":"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-og-image.png","articleSection":["Comparateurs"],"inLanguage":"pt-BR"},{"@type":"WebPage","@id":"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/","url":"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/","name":"Lean vs MyFitnessPal: a f\u00f3rmula TDEE que muda tudo - Lean","isPartOf":{"@id":"https:\/\/lean-app.com\/#website"},"primaryImageOfPage":{"@id":"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/#primaryimage"},"image":{"@id":"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/#primaryimage"},"thumbnailUrl":"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-og-image.png","datePublished":"2026-05-21T18:28:26+00:00","dateModified":"2026-09-08T18:17:56+00:00","description":"Por que o MyFitnessPal calcula mal seu gasto cal\u00f3rico: BMR com f\u00f3rmula de 1919, sem adapta\u00e7\u00e3o metab\u00f3lica, NEAT\/EAT fixos. Comparativo detalhado Lean vs MFP.","breadcrumb":{"@id":"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/#breadcrumb"},"inLanguage":"pt-BR","potentialAction":[{"@type":"ReadAction","target":["https:\/\/lean-app.com\/lean-vs-myfitnesspal\/"]}]},{"@type":"ImageObject","inLanguage":"pt-BR","@id":"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/#primaryimage","url":"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-og-image.png","contentUrl":"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-og-image.png","width":1200,"height":630},{"@type":"BreadcrumbList","@id":"https:\/\/lean-app.com\/lean-vs-myfitnesspal\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/lean-app.com\/"},{"@type":"ListItem","position":2,"name":"Lean vs MyFitnessPal : la formule TDEE qui change tout"}]},{"@type":"WebSite","@id":"https:\/\/lean-app.com\/#website","url":"https:\/\/lean-app.com\/","name":"Lean","description":"Baixe, teste o aplicativo GRATUITAMENTE e assuma o controle do seu corpo PARA SEMPRE.","publisher":{"@id":"https:\/\/lean-app.com\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/lean-app.com\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"pt-BR"},{"@type":"Organization","@id":"https:\/\/lean-app.com\/#organization","name":"Lean","url":"https:\/\/lean-app.com\/","logo":{"@type":"ImageObject","inLanguage":"pt-BR","@id":"https:\/\/lean-app.com\/#\/schema\/logo\/image\/","url":"https:\/\/lean-app.com\/wp-content\/uploads\/2025\/08\/Logo-for-Lean-App-the-best-calorie-and-TDEE-tracking-application.png","contentUrl":"https:\/\/lean-app.com\/wp-content\/uploads\/2025\/08\/Logo-for-Lean-App-the-best-calorie-and-TDEE-tracking-application.png","width":1672,"height":1484,"caption":"Lean"},"image":{"@id":"https:\/\/lean-app.com\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/www.facebook.com\/share\/1GXD3qyMBy\/?mibextid=wwXIfr","https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646","https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite","https:\/\/app.dealroom.co\/companies\/lean_calorie_tracker","https:\/\/alternativeto.net\/software\/lean-calorie-tracker\/"]}]}},"_links":{"self":[{"href":"https:\/\/lean-app.com\/pt\/wp-json\/wp\/v2\/posts\/1241","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lean-app.com\/pt\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lean-app.com\/pt\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lean-app.com\/pt\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/lean-app.com\/pt\/wp-json\/wp\/v2\/comments?post=1241"}],"version-history":[{"count":0,"href":"https:\/\/lean-app.com\/pt\/wp-json\/wp\/v2\/posts\/1241\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/lean-app.com\/pt\/wp-json\/wp\/v2\/media\/1242"}],"wp:attachment":[{"href":"https:\/\/lean-app.com\/pt\/wp-json\/wp\/v2\/media?parent=1241"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lean-app.com\/pt\/wp-json\/wp\/v2\/categories?post=1241"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lean-app.com\/pt\/wp-json\/wp\/v2\/tags?post=1241"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}