{"id":1675,"date":"2026-05-28T08:21:54","date_gmt":"2026-05-28T08:21:54","guid":{"rendered":"https:\/\/lean-app.com\/?p=1675"},"modified":"2026-09-08T18:17:32","modified_gmt":"2026-09-08T18:17:32","slug":"effet-thermique-des-aliments","status":"publish","type":"post","link":"https:\/\/lean-app.com\/pt\/effet-thermique-des-aliments\/","title":{"rendered":"Efeito t\u00e9rmico dos alimentos (TEF): por que o Lean calcula 69 kcal que os outros apps ignoram"},"content":{"rendered":"<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp\" fetchpriority=\"low\">\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 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.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 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.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}\n\n\/* Calculator-specific styles, scoped #lvm-shell *\/\n#lvm-shell .calc-board{display:grid;grid-template-columns:1fr;gap:18px;margin:32px 0}\n@media(min-width:780px){#lvm-shell .calc-board{grid-template-columns:1fr 1fr;gap:24px}}\n#lvm-shell .calc-inputs{background:#FAF7F2;border-radius:14px;padding:22px;border:1px solid var(--rule-soft)}\n#lvm-shell .calc-inputs h3{font-family:var(--font-display);font-size:18px;font-weight:600;margin:0 0 16px;color:var(--ink);letter-spacing:-.01em}\n#lvm-shell .calc-row{margin:0 0 14px}\n#lvm-shell .calc-row label{display:block;font-size:13px;color:var(--muted);margin-bottom:6px;font-weight:500}\n#lvm-shell .calc-row input,#lvm-shell .calc-row select{width:100%;padding:11px 13px;border:1px solid var(--rule);border-radius:9px;font-size:16px;background:#fff;color:var(--ink);font-family:var(--font-text);box-sizing:border-box}\n#lvm-shell .calc-row input:focus,#lvm-shell .calc-row select:focus{outline:2px solid var(--pink);outline-offset:1px;border-color:var(--pink)}\n#lvm-shell .calc-sex{display:flex;gap:8px}\n#lvm-shell .calc-sex label{flex:1;display:flex;align-items:center;justify-content:center;gap:6px;padding:11px 8px;background:#fff;border:1px solid var(--rule);border-radius:9px;cursor:pointer;margin:0;font-size:14px;font-weight:500;color:var(--ink)}\n#lvm-shell .calc-sex input{display:none}\n#lvm-shell .calc-sex input:checked + span{color:var(--pink);font-weight:600}\n#lvm-shell .calc-sex label:has(input:checked){border-color:var(--pink);background:var(--pink-soft)}\n#lvm-shell .calc-bf{display:flex;align-items:center;gap:10px}\n#lvm-shell .calc-bf input[type=range]{flex:1;accent-color:var(--pink);height:6px}\n#lvm-shell .calc-bf .bf-val{font-weight:600;color:var(--pink);min-width:42px;font-family:var(--font-mono);font-size:15px}\n#lvm-shell .calc-results{display:grid;grid-template-columns:1fr;gap:12px}\n#lvm-shell .calc-card{background:#fff;border:1px solid var(--rule);border-radius:14px;padding:18px 20px}\n#lvm-shell .calc-card.lean{border-left:4px solid var(--pink);background:linear-gradient(90deg,var(--pink-soft),#fff 30%)}\n#lvm-shell .calc-card .label{font-size:11px;font-weight:600;text-transform:uppercase;letter-spacing:.08em;color:var(--muted);font-family:var(--font-mono)}\n#lvm-shell .calc-card .formula{font-size:13px;color:var(--dim);margin-top:2px}\n#lvm-shell .calc-card .result{font-family:var(--font-display);font-size:34px;font-weight:600;letter-spacing:-.025em;margin-top:8px;color:var(--ink);line-height:1}\n#lvm-shell .calc-card .result .unit{font-size:14px;font-weight:500;color:var(--muted);margin-left:6px;letter-spacing:0}\n#lvm-shell .calc-card.lean .result{color:var(--pink)}\n#lvm-shell .calc-delta{margin-top:10px;padding:12px 14px;background:#fff;border:1px dashed var(--pink);border-radius:10px;font-size:14px;color:var(--ink)}\n#lvm-shell .calc-delta b{color:var(--pink);font-family:var(--font-mono)}\n#lvm-shell .calc-note{margin-top:14px;font-size:13px;color:var(--muted);line-height:1.5}\n#lvm-shell .calc-note a{color:var(--pink);text-decoration:underline}\n\n\/* Statement block *\/\n#lvm-shell .statement{margin:54px 0;padding:48px 32px;background:#FAF7F2;border-radius:18px;text-align:center}\n#lvm-shell .statement p{font-family:var(--font-display);font-size:34px;line-height:1.2;font-weight:500;letter-spacing:-.025em;color:var(--ink);margin:0;max-width:680px;margin-inline:auto}\n#lvm-shell .statement .accent{color:var(--pink)}\n@media(max-width:640px){#lvm-shell .statement{padding:38px 22px}#lvm-shell .statement p{font-size:24px}}\n\n\/* Profil cards (no scrollable table) *\/\n#lvm-shell .profile-grid{display:grid;grid-template-columns:1fr;gap:16px;margin:32px 0}\n#lvm-shell .profile-card{background:#fff;border:1px solid var(--rule);border-radius:14px;padding:20px 22px}\n#lvm-shell .profile-card h4{font-family:var(--font-display);font-size:17px;font-weight:600;margin:0 0 4px;color:var(--ink)}\n#lvm-shell .profile-card .meta{font-size:13px;color:var(--muted);margin-bottom:14px}\n#lvm-shell .profile-card .rows{display:grid;grid-template-columns:1fr;gap:6px}\n#lvm-shell .profile-card .rw{display:grid;grid-template-columns:1fr auto;gap:10px;padding:8px 12px;background:#FAF7F2;border-radius:8px;font-size:14px;align-items:center}\n#lvm-shell .profile-card .rw .v{font-family:var(--font-mono);font-weight:600;color:var(--ink);font-size:13px}\n#lvm-shell .profile-card .rw.lean{background:var(--pink-soft);border-left:3px solid var(--pink)}\n#lvm-shell .profile-card .rw.lean .v{color:var(--pink)}\n#lvm-shell .profile-card .delta{font-size:12px;color:var(--dim);margin-top:8px}\n\n\/* Comparator cards (3 formulas pros\/cons) *\/\n#lvm-shell .compar-grid{display:grid;grid-template-columns:1fr;gap:16px;margin:24px 0}\n#lvm-shell .compar-card{background:#fff;border:1px solid var(--rule);border-radius:14px;padding:22px}\n#lvm-shell .compar-card.lean{border-left:4px solid var(--pink)}\n#lvm-shell .compar-card h4{font-family:var(--font-display);font-size:18px;font-weight:600;margin:0 0 4px;color:var(--ink)}\n#lvm-shell .compar-card .year{font-size:12px;color:var(--muted);font-family:var(--font-mono);margin-bottom:14px;letter-spacing:.04em}\n#lvm-shell .compar-card .desc{font-size:14px;line-height:1.55;color:var(--ink-2);margin:0 0 12px}\n#lvm-shell .compar-card .pros,#lvm-shell .compar-card .cons{margin:6px 0;font-size:13px;line-height:1.5}\n#lvm-shell .compar-card .pros{color:var(--green)}\n#lvm-shell .compar-card .cons{color:var(--red)}\n#lvm-shell .compar-card .pros b,#lvm-shell .compar-card .cons b{display:inline-block;width:18px}\n\n\/* Pyramide section *\/\n#lvm-shell .pyramide-illust{margin:40px auto 8px;display:flex;flex-direction:column;align-items:center;gap:14px;max-width:220px}\n#lvm-shell .pyramide-illust img{width:100%;border-radius:18px;box-shadow:0 12px 32px rgba(20,20,40,.12)}\n#lvm-shell .pyramide-cap{font-size:13px;color:var(--muted);text-align:center;line-height:1.5}\n#lvm-shell .pyramide-cap b{display:block;color:var(--ink);font-weight:600;margin-bottom:3px}\n\n\/* FAQ details *\/\n#lvm-shell details.faq{background:#fff;border:1px solid var(--rule);border-radius:10px;margin:8px 0;overflow:hidden}\n#lvm-shell details.faq summary{padding:16px 20px;font-weight:600;font-size:16px;color:var(--ink);cursor:pointer;list-style:none;position:relative;padding-right:48px;font-family:var(--font-display);letter-spacing:-.01em}\n#lvm-shell details.faq summary::-webkit-details-marker{display:none}\n#lvm-shell details.faq summary::after{content:\"+\";position:absolute;right:20px;top:50%;transform:translateY(-50%);color:var(--pink);font-size:22px;font-weight:300;line-height:1}\n#lvm-shell details.faq[open] summary::after{content:\"\u2212\"}\n#lvm-shell details.faq .faq-body{padding:0 20px 18px;font-size:15px;line-height:1.65;color:var(--ink-2)}\n#lvm-shell details.faq .faq-body p{margin:0 0 8px}\n\n\/* Sources *\/\n#lvm-shell .sources{margin:48px 0 32px;padding:24px;background:#FAF7F2;border-radius:14px;font-size:13px;line-height:1.6;color:var(--muted)}\n#lvm-shell .sources h4{font-family:var(--font-display);font-size:14px;font-weight:600;margin:0 0 10px;color:var(--ink);text-transform:uppercase;letter-spacing:.06em}\n#lvm-shell .sources a{color:var(--pink);text-decoration:none}\n#lvm-shell .sources a:hover{text-decoration:underline}\n#lvm-shell .sources ol{margin:0;padding-left:22px}\n#lvm-shell .sources li{margin:4px 0}\n\n\/* BodyScan illust *\/\n#lvm-shell .bodyscan-illust{margin:40px auto 8px;display:flex;flex-direction:column;align-items:center;gap:14px;max-width:220px}\n#lvm-shell .bodyscan-illust .mini-phone{max-width:200px;padding:3px;border:1px solid rgba(255,255,255,.07);border-radius:22px;background:linear-gradient(145deg,#2a2a2a,#0e0e0e);box-shadow:0 18px 36px rgba(0,0,0,.14);position:relative}\n#lvm-shell .bodyscan-illust .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 .bodyscan-illust .mini-phone .scr{border-radius:18px;overflow:hidden;background:#FAF0E6;aspect-ratio:9\/19.5}\n#lvm-shell .bodyscan-illust .mini-phone .scr img{width:100%;height:100%;object-fit:cover;display:block}\n#lvm-shell .bodyscan-cap{font-size:13px;color:var(--muted);text-align:center;line-height:1.5}\n#lvm-shell .bodyscan-cap b{display:block;color:var(--ink);font-weight:600;margin-bottom:3px}\n\n\/* Body copy paragraphs *\/\n#lvm-shell h2.sect{font-family:var(--font-display);font-size:34px;font-weight:600;letter-spacing:-.03em;margin:64px 0 16px;line-height:1.15;color:var(--ink)}\n#lvm-shell h2.sect .num{font-family:var(--font-mono);font-size:13px;font-weight:500;color:var(--pink);display:block;text-transform:uppercase;letter-spacing:.08em;margin-bottom:6px;-webkit-font-smoothing:antialiased}\n#lvm-shell h3.sub{font-family:var(--font-display);font-size:22px;font-weight:600;margin:32px 0 12px;color:var(--ink);letter-spacing:-.015em}\n#lvm-shell .body p{margin:0 0 18px;font-size:17px;line-height:1.7;color:var(--ink-2)}\n#lvm-shell .body p b{color:var(--ink);font-weight:600}\n\n\/* CTA band *\/\n#lvm-shell .get-band{margin:48px 0 24px;padding:42px 32px;background:linear-gradient(135deg,#fff,#FAF7F2);border:1px solid var(--rule);border-radius:18px;text-align:center}\n#lvm-shell .get-band h3{font-family:var(--font-display);font-size:30px;font-weight:600;margin:0 0 6px;color:var(--ink);letter-spacing:-.025em}\n#lvm-shell .get-band p{margin:0 0 22px;font-size:16px;color:var(--muted);line-height:1.5}\n#lvm-shell .get-band .stores{display:flex;gap:12px;justify-content:center;flex-wrap:wrap;align-items:center}\n#lvm-shell .get-band .stores img{height:54px;width:auto;border-radius:10px}\n@media(max-width:640px){#lvm-shell .get-band h3{font-size:22px}}\n\n#lvm-shell .micro-cta{margin:24px 0;padding:18px 22px;background:var(--pink-soft);border-left:3px solid var(--pink);border-radius:0 10px 10px 0;font-size:15px;line-height:1.55}\n#lvm-shell .micro-cta a{color:var(--pink);font-weight:600;text-decoration:none}\n#lvm-shell .micro-cta a:hover{text-decoration:underline}\n<\/style>\n\n<style id=\"lvm-collision-reset\">\n\/* Hard reset for global theme styles *\/\nbody.postid-1675 #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-1675 #lvm-shell .wrap,\nbody.postid-1675 #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-1675 #lvm-shell .wrap,\n  body.postid-1675 #lvm-shell main.wrap{padding-left:18px!important;padding-right:18px!important}\n}\nhtml, body{overflow-x:hidden!important}\nbody.postid-1675 #lvm-shell{overflow-x:hidden;max-width:100vw}\nbody.postid-1675 #lvm-shell *{max-width:100%}\nbody.postid-1675 #lvm-shell .nav-row{max-width:100vw;box-sizing:border-box}\nbody.postid-1675 #lvm-shell.force-show .rev{opacity:1!important;transform:none!important}\n\n\/* === A.1 PHONE BACKGROUND CLASSES === *\/\nbody.postid-1675 #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-1675 #lvm-shell .phone-bg.tab-depense{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp)}\nbody.postid-1675 #lvm-shell .phone-bg.tab-bilan{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp)}\nbody.postid-1675 #lvm-shell .phone-bg.tab-kcal{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp)}\nbody.postid-1675 #lvm-shell .phone-bg.tab-strategie{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp)}\nbody.postid-1675 #lvm-shell .phone-bg.sub-BMR{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp)}\nbody.postid-1675 #lvm-shell .phone-bg.sub-NEAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp)}\nbody.postid-1675 #lvm-shell .phone-bg.sub-EAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp)}\nbody.postid-1675 #lvm-shell .phone-bg.sub-TEF{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp)}\n\n\/* === CTA BANDS MOBILE === *\/\n@media (max-width:760px){\n  body.postid-1675 #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-1675 #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-1675 #lvm-shell .cta-band .stores{width:100%!important;justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1675 #lvm-shell .cta-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1675 #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-1675 #lvm-shell .get-band{padding:38px 22px!important}\n  body.postid-1675 #lvm-shell .get-band .stores{justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1675 #lvm-shell .get-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1675 #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-1675 #lvm-shell .get-band h3{font-size:26px!important;line-height:1.2!important}\n  body.postid-1675 #lvm-shell .get-band p{font-size:15px!important}\n}\n\n\/* === MINI-PHONES === *\/\n@media (max-width:760px){\n  body.postid-1675 #lvm-shell .mini-row{gap:6px!important;margin:24px 0!important;grid-template-columns:repeat(3,1fr)!important}\n  body.postid-1675 #lvm-shell .mini-phone{max-width:100px!important;padding:2px!important;border-radius:14px!important;border-width:1px!important}\n  body.postid-1675 #lvm-shell .mini-phone .notch{width:30px!important;height:8px!important;border-radius:0 0 5px 5px!important}\n  body.postid-1675 #lvm-shell .mini-phone .scr{border-radius:11px!important}\n  body.postid-1675 #lvm-shell .mini-cap{font-size:10px!important;margin-top:8px!important}\n  body.postid-1675 #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-1675 #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-1675 #lvm-shell .tap-hint.desktop{display:none!important}\n  body.postid-1675 #lvm-shell .tap-hint.hidden{display:none!important;height:0!important;margin:0!important;padding:0!important}\n}\n\n\/* === A.6 BODYSCAN ILLUST === *\/\nbody.postid-1675 #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-1675 #lvm-shell .bodyscan-illust .mini-phone{max-width:200px!important;padding:3px!important;border-radius:22px!important;border-width:1px!important}\n@media (max-width:760px){\n  body.postid-1675 #lvm-shell .bodyscan-illust{max-width:180px!important}\n  body.postid-1675 #lvm-shell .bodyscan-illust .mini-phone{max-width:160px!important}\n}\n\n\/* Fix CompressX picture wrappers *\/\n#lvm-shell picture{display:block;max-width:100%}\n#lvm-shell picture img{display:block;max-width:100%;height:auto}\n#lvm-shell .bodyscan-illust .mini-phone{background:transparent;padding:0;border:none;box-shadow:none;border-radius:0}\n#lvm-shell .bodyscan-illust .mini-phone .notch{display:none}\n<\/style>\n\n<div id=\"lvm-shell\" class=\"force-show\">\n\n<nav class=\"nav\"><div class=\"nav-row\">\n  <a class=\"nav-brand\" href=\"https:\/\/lean-app.com\/pt\/\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"Lean\" width=\"28\" height=\"28\"><span>Lean<\/span><\/a>\n  <div class=\"nav-spacer\"><\/div>\n  <a class=\"nav-link\" href=\"https:\/\/lean-app.com\/pt\/\">In\u00edcio<\/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=pillar-tef\" target=\"_blank\" rel=\"noopener\" aria-label=\"App Store\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\"><\/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=pillar-tef\" target=\"_blank\" rel=\"noopener\" aria-label=\"Google Play\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\"><\/a>\n  <\/div>\n<\/div><\/nav>\n\n<main class=\"wrap\">\n\n<!-- HERO -->\n<section class=\"hero\" aria-labelledby=\"title\">\n  <div class=\"crumb\"><a href=\"https:\/\/lean-app.com\/pt\/\">In\u00edcio<\/a> &nbsp;\/&nbsp; TEF<\/div>\n  <div class=\"eyebrow\">Pilar &middot; Ci\u00eancia do metabolismo<\/div>\n  <h1 id=\"title\">TEF (Thermic Effect of Food).\n    <span class=\"alt\">O guia completo para entender o gasto cal\u00f3rico oculto da digest\u00e3o.<\/span>\n  <\/h1>\n  <p class=\"dek\">A digest\u00e3o queima calorias. De 20 a 30&nbsp;% das prote\u00ednas, de 5 a 10&nbsp;% dos carboidratos, de 0 a 3&nbsp;% das gorduras. Todos os apps ignoram isso. O Lean o calcula em tempo real em cada refei\u00e7\u00e3o registrada.<\/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 10&nbsp;min &middot; Atualizado em 28 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=pillar-tef\" target=\"_blank\" rel=\"noopener\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"T&eacute;l&eacute;charger sur l&rsquo;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=pillar-tef\" 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  <div class=\"hero-bottom\">\n    <div class=\"hero-lead\">\n      O TEF (Thermic Effect of Food) \u00e9 a energia gasta pelo seu corpo para digerir, absorver e metabolizar cada refei\u00e7\u00e3o. Ele representa de 8 a 15&nbsp;% do seu gasto total. A maioria dos apps de calorias n\u00e3o o calcula. O Lean o calcula na quilocaloria, em cada alimento registrado.\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>Demo interativa<\/small>Toque na tela para explorar o app<\/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>Demo 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  <div class=\"snippet rev\">\n    <div class=\"lbl\">Resposta r\u00e1pida<\/div>\n    <p>O TEF (Thermic Effect of Food) \u00e9 a energia queimada para digerir seus alimentos. Ele entra na equa\u00e7\u00e3o <b>TDEE = BMR + NEAT + EAT + TEF<\/b>. Ele varia segundo seus macros: prote\u00ednas 20&ndash;30&nbsp;%, carboidratos 5&ndash;10&nbsp;%, gorduras 0&ndash;3&nbsp;%. Em uma refei\u00e7\u00e3o padr\u00e3o p\u00f3s-treino, o Lean calcula 69&nbsp;kcal de TEF onde os outros apps mostram 0.<\/p>\n  <\/div>\n<\/section>\n\n<!-- 02. DEFINITION -->\n<h2 class=\"sect\"><span class=\"num\">02 &middot; Defini\u00e7\u00e3o<\/span>TEF, o 4.\u00ba tijolo do TDEE<\/h2>\n<div class=\"body\">\n<p>O <b>TEF (Thermic Effect of Food)<\/b> \u00e9 a energia gasta pelo seu corpo para processar os alimentos que voc\u00ea ingere: mastigar, digerir, absorver, metabolizar. Em ingl\u00eas, fala-se tamb\u00e9m em DIT (Diet-Induced Thermogenesis). \u00c9 o calor produzido pelo seu sistema digestivo a cada refei\u00e7\u00e3o.<\/p>\n<p>Ele se insere na equa\u00e7\u00e3o fundamental do metabolismo:<\/p>\n<\/div>\n<div class=\"statement\" style=\"margin:28px 0\"><p><b style=\"color:var(--pink);font-variant-numeric:tabular-nums\">TDEE = BMR + NEAT + EAT + TEF<\/b><\/p><\/div>\n<div class=\"body\">\n<p>O <b>BMR<\/b> (Basal Metabolic Rate) \u00e9 seu gasto em repouso. O <b>NEAT<\/b> (Non-Exercise Activity Thermogenesis) cobre seu gasto n\u00e3o esportivo. O<b>EAT<\/b> (Exercise Activity Thermogenesis) cobre seus treinos. E o <b>TEF<\/b>, \u00e9 o calor gerado pela digest\u00e3o. Juntos, os quatro comp\u00f5em seu verdadeiro TDEE.<\/p>\n<p>A<b>adapta\u00e7\u00e3o metab\u00f3lica<\/b> vem al\u00e9m como coeficiente multiplicador do BMR em d\u00e9ficit cal\u00f3rico prolongado. Conven\u00e7\u00e3o Lean: 100&nbsp;% = ideal, 90&nbsp;% = 10&nbsp;% de adapta\u00e7\u00e3o. Ela n\u00e3o entra <b>passos<\/b> na soma do TDEE.<\/p>\n<\/div>\n<div class=\"micro-cta\">\n  Veja tamb\u00e9m: <a href=\"https:\/\/lean-app.com\/pt\/neat-depense-non-sportive\/\">Pilar NEAT<\/a> u00b7 <a href=\"https:\/\/lean-app.com\/pt\/metabolisme-de-base\/\">Pilar BMR<\/a> u00b7 <a href=\"https:\/\/lean-app.com\/pt\/depense-energetique-totale-v2\/\">Pilar TDEE<\/a> u00b7 <a href=\"https:\/\/lean-app.com\/pt\/calculateur-tdee\/\">Calculadora TDEE<\/a> u00b7 <a href=\"https:\/\/lean-app.com\/pt\/calculateur-deficit-calorique\/\">Calculadora de d\u00e9ficit<\/a>\n<\/div>\n\n<!-- 03. 69 KCAL D'ECART -->\n<h2 class=\"sect\"><span class=\"num\">03 &middot; Impacto real<\/span>69&nbsp;kcal ignoradas em uma refei\u00e7\u00e3o p\u00f3s-treino<\/h2>\n<div class=\"body\">\n<p>Um exemplo concreto: voc\u00ea volta do treino e come 200&nbsp;g de frango grelhado, 200&nbsp;g de arroz cozido, 30&nbsp;g de abacate. Total: 54&nbsp;g de prote\u00ednas \/ 55&nbsp;g de carboidratos \/ 12&nbsp;g de gorduras = <b>537&nbsp;kcal consumidas<\/b>.<\/p>\n<p>O Lean aplica os coeficientes cient\u00edficos a essa refei\u00e7\u00e3o:<\/p>\n<\/div>\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>Prote\u00ednas (54&nbsp;g)<\/h4>\n    <div class=\"meta\">54&nbsp;g &times; 4&nbsp;kcal\/g &times; 25&nbsp;%<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>TEF Prote\u00ednas<\/span><span class=\"v\" style=\"color:#FA256C\">54&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>Westerterp 2004<\/span><span class=\"v\">20&ndash;30&nbsp;%<\/span><\/div>\n      <div class=\"rw lean\"><span>O Lean calcula<\/span><span class=\"v\">Em tempo real<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">As prote\u00ednas t\u00eam o TEF mais alto: s\u00edntese, transamina\u00e7\u00e3o, gliconeog\u00eanese s\u00e3o processos custosos em ATP.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Carboidratos (55&nbsp;g)<\/h4>\n    <div class=\"meta\">55&nbsp;g &times; 4&nbsp;kcal\/g &times; 8&nbsp;%<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>TEF Carboidratos<\/span><span class=\"v\" style=\"color:#B8860B\">18&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>Westerterp 2004<\/span><span class=\"v\">5&ndash;10&nbsp;%<\/span><\/div>\n      <div class=\"rw lean\"><span>O Lean calcula<\/span><span class=\"v\">Em tempo real<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Convers\u00e3o em glicog\u00eanio ou oxida\u00e7\u00e3o direta. Gasto moderado mas n\u00e3o nulo.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Gorduras (12&nbsp;g)<\/h4>\n    <div class=\"meta\">12&nbsp;g &times; 9&nbsp;kcal\/g &times; 2&nbsp;%<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>TEF Gorduras<\/span><span class=\"v\" style=\"color:#7B52AC\">2&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>Westerterp 2004<\/span><span class=\"v\">0&ndash;3&nbsp;%<\/span><\/div>\n      <div class=\"rw lean\"><span>O Lean calcula<\/span><span class=\"v\">Em tempo real<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Reesterifica\u00e7\u00e3o direta muito eficiente. O macro menos custoso de digerir.<\/div>\n  <\/div>\n<\/div>\n<div class=\"body\">\n<p><b>Total TEF calculado pelo Lean: 54 + 18 + 2 = 74&nbsp;kcal<\/b> s\u00f3 nessa refei\u00e7\u00e3o. Os apps concorrentes mostram 0. Em um ano, s\u00e3o dezenas de milhares de quilocalorias de gasto ignorado, o que explica os plat\u00f4s inexplicados e os d\u00e9ficits que \u00ab&nbsp;n\u00e3o funcionam&nbsp;\u00bb.<\/p>\n<\/div>\n\n<!-- 04. 3 PROFILS PAR APPORT EN PROTEINES -->\n<h2 class=\"sect\"><span class=\"num\">04 &middot; 3 perfis<\/span>Mais prote\u00ednas = mais TEF: os n\u00fameros<\/h2>\n<div class=\"body\">\n<p>Tr\u00eas perfis com uma alimenta\u00e7\u00e3o de 2&nbsp;500&nbsp;kcal\/dia. S\u00f3 a distribui\u00e7\u00e3o dos macros muda. Os n\u00fameros de TEF total ilustram o enorme impacto da composi\u00e7\u00e3o da alimenta\u00e7\u00e3o.<\/p>\n<\/div>\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>15&nbsp;% prote\u00ednas<\/h4>\n    <div class=\"meta\">Alimenta\u00e7\u00e3o pobre em prote\u00ednas &middot; 2&nbsp;500 kcal<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>TEF Prote\u00ednas<\/span><span class=\"v\">75&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>TEF Carboidratos + Gorduras<\/span><span class=\"v\">94&nbsp;kcal<\/span><\/div>\n      <div class=\"rw lean\"><span>TEF total<\/span><span class=\"v\">~169&nbsp;kcal \/ dia<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">A caixa \u00ab&nbsp;sedent\u00e1rio&nbsp;\u00bb no MFP n\u00e3o leva em conta a composi\u00e7\u00e3o alimentar. Esse perfil perde 169&nbsp;kcal de gasto se o app o ignora.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>25&nbsp;% prote\u00ednas<\/h4>\n    <div class=\"meta\">Perfil esportista padr\u00e3o &middot; 2&nbsp;500 kcal<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>TEF Prote\u00ednas<\/span><span class=\"v\">125&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>TEF Carboidratos + Gorduras<\/span><span class=\"v\">85&nbsp;kcal<\/span><\/div>\n      <div class=\"rw lean\"><span>TEF total<\/span><span class=\"v\">~210&nbsp;kcal \/ dia<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">41&nbsp;kcal de gasto adicional vs perfil 15&nbsp;% prote\u00ednas. O equivalente a 5 minutos a mais de caminhada, s\u00f3 mudando os macros.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>35&nbsp;% prote\u00ednas<\/h4>\n    <div class=\"meta\">Perfil cutting agressivo &middot; 2&nbsp;500 kcal<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>TEF Prote\u00ednas<\/span><span class=\"v\">175&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>TEF Carboidratos + Gorduras<\/span><span class=\"v\">76&nbsp;kcal<\/span><\/div>\n      <div class=\"rw lean\"><span>TEF total<\/span><span class=\"v\">~251&nbsp;kcal \/ dia<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">82&nbsp;kcal a mais vs perfil 15&nbsp;%. Em 30 dias: +2&nbsp;460&nbsp;kcal de gasto adicional com calorias id\u00eanticas, sem um \u00fanico treino adicional.<\/div>\n  <\/div>\n<\/div>\n\n<!-- 05. POURQUOI LES APPS ECHOUENT -->\n<h2 class=\"sect\"><span class=\"num\">05 &middot; Por que os apps falham<\/span>Coeficiente fixo contra c\u00e1lculo macroespec\u00edfico<\/h2>\n<div class=\"body\">\n<p>Quando voc\u00ea configura o MyFitnessPal ou o Yazio, perguntam seu n\u00edvel de atividade. Um coeficiente PAL se aplica ao seu BMR. Sup\u00f5e-se que esse coeficiente \u00ab&nbsp;engloba&nbsp;\u00bb tudo, inclusive a digest\u00e3o. Na pr\u00e1tica, ele \u00e9 calibrado sobre popula\u00e7\u00f5es gen\u00e9ricas e n\u00e3o reflete em nada sua composi\u00e7\u00e3o de macros do dia.<\/p>\n<p>O problema: esse coeficiente n\u00e3o muda na segunda em que voc\u00ea come 50&nbsp;% de prote\u00ednas versus o domingo em que come 20&nbsp;% de prote\u00ednas. O TEF desses dois dias \u00e9 radicalmente diferente. Os apps n\u00e3o veem isso. O Lean, sim.<\/p>\n<p>Westerterp (2004, PMID&nbsp;15507147) mediu por calorimetria indireta que os erros de estimativa do TEF via coeficiente fixo podem chegar a <b>100 a 200&nbsp;kcal por dia<\/b> segundo a composi\u00e7\u00e3o alimentar real. \u00c9 a ordem de grandeza que explica um d\u00e9ficit que \u00ab&nbsp;n\u00e3o funciona&nbsp;\u00bb durante v\u00e1rias semanas.<\/p>\n<\/div>\n\n<!-- 06. MFP VS LEAN -->\n<h2 class=\"sect\"><span class=\"num\">06 &middot; MFP vs Lean<\/span>0&nbsp;kcal vs 74&nbsp;kcal na mesma refei\u00e7\u00e3o<\/h2>\n<div class=\"body\">\n<p>A mesma refei\u00e7\u00e3o p\u00f3s-treino: 200&nbsp;g de frango, 200&nbsp;g de arroz cozido, 30&nbsp;g de abacate = 537&nbsp;kcal. O que cada app faz com essa refei\u00e7\u00e3o:<\/p>\n<\/div>\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>MyFitnessPal (e a maioria dos apps)<\/h4>\n    <div class=\"meta\">Sem c\u00e1lculo de TEF nas refei\u00e7\u00f5es<\/div>\n    <div style=\"margin:12px auto;max-width:130px\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2025\/07\/analyse-nutrition-calcul-tef-lean-app-551x1024.png\" alt=\"Analyse nutritionnelle dans Lean avec calcul du TEF\" style=\"width:100%;border-radius:16px;box-shadow:0 4px 16px rgba(0,0,0,.12)\" loading=\"lazy\"><\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>537 kcal registradas<\/span><span class=\"v\" style=\"color:#FF2D6E\">TEF: 0&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>M\u00e9todo<\/span><span class=\"v\">Coeficiente PAL fixo<\/span><\/div>\n      <div class=\"rw\"><span>Levado em conta<\/span><span class=\"v\">N\u00e3o<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">MFP, Yazio, Cronometer e a maioria dos apps de calorias n\u00e3o integram o TEF no seu c\u00e1lculo de gasto. Voc\u00ea queima 74&nbsp;kcal digerindo essa refei\u00e7\u00e3o. Eles n\u00e3o sabem disso.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Lean<\/h4>\n    <div class=\"meta\">C\u00e1lculo de TEF macroespec\u00edfico em tempo real<\/div>\n    <div style=\"margin:12px auto;max-width:130px\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2025\/07\/focus-depense-digestion-tef-lean-app-523x1024.png\" alt=\"Focus sur la d&eacute;pense TEF dans l&rsquo;application Lean\" style=\"width:100%;border-radius:16px;box-shadow:0 4px 16px rgba(0,0,0,.12)\" loading=\"lazy\"><\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>537 kcal registradas<\/span><span class=\"v\" style=\"color:#27AE60\">TEF: 74&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>M\u00e9todo<\/span><span class=\"v\">P&times;25&nbsp;% + C&times;8&nbsp;% + G&times;2&nbsp;%<\/span><\/div>\n      <div class=\"rw lean\"><span>Levado em conta<\/span><span class=\"v\">Sim, a cada refei\u00e7\u00e3o<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">O Lean calcula o TEF na quilocaloria em cada refei\u00e7\u00e3o registrada. Esse TEF se soma ao seu TDEE do dia e ajusta seu objetivo cal\u00f3rico em tempo real.<\/div>\n  <\/div>\n<\/div>\n<div class=\"cta-band\">\n  <div class=\"l\">O Lean calcula seu TEF em tempo real em cada refei\u00e7\u00e3o. Download gratuito, teste de 7 dias no plano anual.<\/div>\n  <div class=\"stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=pillar-tef-cta1\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"T&eacute;l&eacute;charger sur l&rsquo;App Store\" height=\"42\" loading=\"lazy\"><\/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=pillar-tef-cta1\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Disponible sur Google Play\" height=\"42\" loading=\"lazy\"><\/a>\n  <\/div>\n<\/div>\n\n<!-- 07. BMR CHANGE TOUT POUR LE TEF -->\n<h2 class=\"sect\"><span class=\"num\">07 &middot; BMR &amp; TEF<\/span>Por que seu BMR influencia o valor do TEF<\/h2>\n<div class=\"body\">\n<p>O TEF \u00e9 calculado sobre os macros ingeridos. Mas para que esse c\u00e1lculo seja integrado em um TDEE preciso, ainda \u00e9 preciso que o BMR que serve de base seja exato. E o BMR depende diretamente da sua <b>massa magra real<\/b>.<\/p>\n<p>A raz\u00e3o fisiol\u00f3gica: o metabolismo basal \u00e9 sustentado principalmente pelos m\u00fasculos e \u00f3rg\u00e3os (tecido metabolicamente ativo), n\u00e3o pela massa gorda. Dois indiv\u00edduos de 80&nbsp;kg com 12&nbsp;% e 22&nbsp;% de gordura corporal t\u00eam uma massa magra de 70,4&nbsp;kg vs 62,4&nbsp;kg, ou seja, uma diferen\u00e7a de BMR de cerca de 170&nbsp;kcal\/dia. Se seu TDEE est\u00e1 errado desde a base, seu TEF acaba integrado em uma equa\u00e7\u00e3o j\u00e1 descalibrada.<\/p>\n<p>Concretamente: o Lean calcula seu BMR sobre sua massa magra real via BodyScan IA, e depois integra o TEF sobre esse BMR exato. O erro em cadeia que os apps cometem ocorre em dois n\u00edveis: BMR sobre peso total (errado), e depois 0&nbsp;kcal de TEF (errado tamb\u00e9m). O Lean corrige os dois.<\/p>\n<\/div>\n<div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">BMR calculado sobre gordura corporal real, n\u00e3o sobre peso total<\/div><p class=\"fd\">O Lean usa seu modelo propriet\u00e1rio patenteado (nem Harris-Benedict 1919, nem Mifflin-St Jeor 1990) e o indexa \u00e0 sua massa magra via BodyScan IA. Esse BMR serve de funda\u00e7\u00e3o para todo o resto, inclusive o TEF.<\/p><\/div><div class=\"fc\">Precis\u00e3o<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">TEF integrado no TDEE, n\u00e3o adicionado depois<\/div><p class=\"fd\">O TEF n\u00e3o \u00e9 uma linha separada que voc\u00ea decide ativar ou n\u00e3o. Ele faz parte da equa\u00e7\u00e3o TDEE = BMR + NEAT + EAT + TEF, integrada desde a primeira refei\u00e7\u00e3o registrada.<\/p><\/div><div class=\"fc\">Arquitetura<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">TEF recalculado a cada atualiza\u00e7\u00e3o do perfil<\/div><p class=\"fd\">Voc\u00ea perde 3&nbsp;kg de gordura em um m\u00eas? Seu BMR muda. E a integra\u00e7\u00e3o do TEF no TDEE \u00e9 automaticamente recalibrada no Lean. Os apps mant\u00eam sua constante desde o cadastro.<\/p><\/div><div class=\"fc\">Din\u00e2mico<\/div><\/div>\n\n<!-- 08. BODYSCAN IA -->\n<h2 class=\"sect\"><span class=\"num\">08 &middot; BodyScan IA<\/span>A gordura corporal real: a funda\u00e7\u00e3o do c\u00e1lculo de TEF do Lean<\/h2>\n<div class=\"body\">\n<p>Para que o TEF seja integrado em um TDEE preciso, primeiro \u00e9 preciso que o BMR esteja certo. E para isso, \u00e9 preciso sua gordura corporal real. \u00c9 aqui que entra o BodyScan IA do Lean.<\/p>\n<p>A maioria dos apps calcula o BMR em fun\u00e7\u00e3o do peso total (Harris-Benedict 1919, Mifflin-St Jeor 1990). O Lean calcula seu BMR sobre sua <b>massa magra estimada via gordura corporal<\/b>, gra\u00e7as a um <b>modelo propriet\u00e1rio patenteado<\/b>. Esse BMR serve depois de funda\u00e7\u00e3o para a integra\u00e7\u00e3o do TEF no TDEE.<\/p>\n<\/div>\n<div class=\"bodyscan-illust\" style=\"margin:40px auto 8px;display:flex;flex-direction:column;align-items:center;gap:14px;max-width:220px\">\n  <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2025\/07\/resultat-bodyfat-ia-homme-lean-app-1-514x1024.png\" alt=\"BodyScan AI Lean result: bodyfat in 5 seconds from a photo\" width=\"514\" height=\"1024\" style=\"width:100%;height:auto;border-radius:24px;box-shadow:0 8px 32px rgba(0,0,0,0.15)\" loading=\"lazy\" decoding=\"async\">\n  <p class=\"bodyscan-cap\" style=\"max-width:220px;font-size:13px;line-height:1.5;text-align:center\"><b>BodyScan IA<\/b> : gordura corporal real em 5 segundos, a partir de uma foto<\/p>\n<\/div>\n<div class=\"body\">\n<p>Uma foto, 5 segundos, e o Lean conhece sua gordura corporal com precis\u00e3o. Esse n\u00famero alimenta diretamente o c\u00e1lculo do seu BMR, que por sua vez serve de funda\u00e7\u00e3o para a integra\u00e7\u00e3o do TEF no seu TDEE. \u00c9 a arquitetura em cadeia que os outros apps n\u00e3o oferecem.<\/p>\n<\/div>\n\n<!-- 09. COMMENT LEAN CALCULE LE TEF -->\n<h2 class=\"sect\"><span class=\"num\">09 &middot; Lean &amp; TEF<\/span>C\u00e1lculo em tempo real em cada refei\u00e7\u00e3o registrada<\/h2>\n<div class=\"body\">\n<p>O Lean calcula o TEF a partir de cada refei\u00e7\u00e3o que voc\u00ea registra, e o integra no seu TDEE do dia em tempo real. Esta \u00e9 a arquitetura completa:<\/p>\n<\/div>\n<div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">Registro da refei\u00e7\u00e3o (3 m\u00e9todos)<\/div><p class=\"fd\">Voc\u00ea registra pela base USDA+OpenFoodFacts, pelo scan de c\u00f3digo de barras ou pelo scan de foto por IA de um prato. O Lean recupera imediatamente os gramas de prote\u00ednas, carboidratos e gorduras.<\/p><\/div><div class=\"fc\">Registro<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">C\u00e1lculo do TEF por macro em cada alimento<\/div><p class=\"fd\">O motor Lean aplica: P &times; 25&nbsp;%, C &times; 8&nbsp;%, G &times; 2&nbsp;%. O resultado \u00e9 calculado na hora para cada alimento, depois acumulado ao longo do dia.<\/p><\/div><div class=\"fc\">C\u00e1lculo<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">TEF acumulado no TDEE do dia<\/div><p class=\"fd\">O TEF acumulado do dia se soma ao BMR + NEAT + EAT para dar seu TDEE ao vivo. Seu balan\u00e7o cal\u00f3rico se ajusta a cada refei\u00e7\u00e3o registrada.<\/p><\/div><div class=\"fc\">Integra\u00e7\u00e3o<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">04<\/div><div><div class=\"ft\">Vis\u00edvel na aba Gasto<\/div><p class=\"fd\">A aba Gasto do Lean detalha cada componente do TDEE: BMR, NEAT, EAT, TEF. Voc\u00ea v\u00ea exatamente quanto a digest\u00e3o contribui para seu gasto do dia.<\/p><\/div><div class=\"fc\">Transparente<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">05<\/div><div><div class=\"ft\">Impacto direto no objetivo cal\u00f3rico<\/div><p class=\"fd\">O Lean usa o TDEE consciente do TEF para calcular seu objetivo e seu d\u00e9ficit alvo. Uma refei\u00e7\u00e3o mais proteica aumenta seu TEF e portanto seu TDEE real, o que o Lean reflete automaticamente.<\/p><\/div><div class=\"fc\">Estrat\u00e9gico<\/div><\/div>\n\n<!-- 10. L'ECRAN TEF -->\n<h2 class=\"sect\"><span class=\"num\">10 &middot; TEF no Lean<\/span>O acompanhamento da digest\u00e3o em tempo real<\/h2>\n<div class=\"body\">\n<p>A aba Gasto do Lean detalha em tempo real cada componente do TDEE: BMR, NEAT, EAT, TEF. Toque em TEF para ver o detalhe por refei\u00e7\u00e3o.<\/p>\n<\/div>\n<div style=\"max-width:130px;margin:24px auto\">\n  <div class=\"mini-phone\" style=\"max-width:130px\"><div class=\"notch\"><\/div><div class=\"scr\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp\" alt=\"TEF et digestion dans Lean\" loading=\"lazy\"><\/div><\/div>\n<\/div>\n<div class=\"mini-cap\"><strong>Lean<\/strong> &middot; TEF calculado em tempo real em cada refei\u00e7\u00e3o<\/div>\n<div style=\"text-align:center;margin:24px 0\">\n  <img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2025\/08\/suivi-calories-digestion-tef-lean-app-1024x370.png\" alt=\"Suivi des calories de digestion (TEF) dans l&rsquo;application Lean\" style=\"max-width:480px;width:100%;border-radius:16px;box-shadow:0 6px 24px rgba(0,0,0,.10)\" loading=\"lazy\">\n<\/div>\n\n<!-- 11. STRATEGIES D'OPTIMISATION TEF -->\n<h2 class=\"sect\"><span class=\"num\">11 &middot; Estrat\u00e9gias<\/span>Comer mais prote\u00ednas = queimar mais ao digerir<\/h2>\n<div class=\"body\">\n<p>O princ\u00edpio fundamental do TEF: cada caloria de prote\u00edna custa 25&nbsp;% para digerir, contra 2&nbsp;% para as gorduras. <b>Comer mais prote\u00ednas = gastar mais com as mesmas calorias.<\/b> \u00c9 a vantagem metab\u00f3lica real de uma alimenta\u00e7\u00e3o proteica no cutting.<\/p>\n<\/div>\n<div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">+100&nbsp;g de prote\u00ednas = +100&nbsp;kcal de TEF gr\u00e1tis<\/div><p class=\"fd\">100&nbsp;g de prote\u00ednas adicionais (400&nbsp;kcal) geram cerca de 100&nbsp;kcal de TEF adicional. \u00c9 gasto real, sem esfor\u00e7o f\u00edsico, s\u00f3 mudando sua composi\u00e7\u00e3o alimentar.<\/p><\/div><div class=\"fc\">Prote\u00ednas<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">Registre tudo, at\u00e9 as refei\u00e7\u00f5es pequenas<\/div><p class=\"fd\">Cada entrada no Lean aciona o c\u00e1lculo do TEF. Um lanche de 100&nbsp;g de queijo cottage (18&nbsp;g de prote\u00ednas) gera ~18&nbsp;kcal de TEF. Acumulado em 5 refei\u00e7\u00f5es, \u00e9 um gasto real que os apps n\u00e3o contam.<\/p><\/div><div class=\"fc\">Exaustividade<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">Prefira os alimentos integrais<\/div><p class=\"fd\">Os alimentos ultraprocessados t\u00eam um TEF mais baixo porque j\u00e1 est\u00e3o em parte \u00ab&nbsp;pr\u00e9-digeridos&nbsp;\u00bb industrialmente (Barr 2010, PMID&nbsp;20613941). Um peito de frango inteiro tem um TEF mais alto do que um p\u00f3 de prote\u00edna pr\u00e9-hidrolisado.<\/p><\/div><div class=\"fc\">Qualidade<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">04<\/div><div><div class=\"ft\">N\u00e3o conte com as gorduras para o TEF<\/div><p class=\"fd\">As gorduras t\u00eam um TEF de 0 a 3&nbsp;%. Aumentar suas gorduras n\u00e3o impulsiona o TEF. \u00c9 a distribui\u00e7\u00e3o dos macros que conta, n\u00e3o o total cal\u00f3rico bruto.<\/p><\/div><div class=\"fc\">Gorduras<\/div><\/div>\n\n<!-- 12. MET et macros -->\n<h2 class=\"sect\"><span class=\"num\">12 &middot; Ci\u00eancia<\/span>Por que as prote\u00ednas queimam tanto na digest\u00e3o<\/h2>\n<div class=\"body\">\n<p>A resposta \u00e9 bioqu\u00edmica. As prote\u00ednas precisam ser decompostas em amino\u00e1cidos, que depois s\u00e3o integrados na s\u00edntese proteica (custo em ATP), oxidados (ciclo de Krebs) ou transformados em glicose (gliconeog\u00eanese, custo ainda mais alto). A desamina\u00e7\u00e3o do nitrog\u00eanio (produ\u00e7\u00e3o de ureia) \u00e9 ela mesma custosa em energia.<\/p>\n<\/div>\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>Prote\u00ednas: TEF 20&ndash;30&nbsp;%<\/h4>\n    <div class=\"meta\">Fonte: Westerterp 2004, Acheson 2011<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>S\u00edntese proteica<\/span><span class=\"v\">Custo ATP elevado<\/span><\/div>\n      <div class=\"rw\"><span>Desamina\u00e7\u00e3o<\/span><span class=\"v\">Produ\u00e7\u00e3o de ureia<\/span><\/div>\n      <div class=\"rw lean\"><span>TEF Lean<\/span><span class=\"v\">25&nbsp;% (valor mediano)<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">\u00c9 o macro mais \u00ab&nbsp;caro&nbsp;\u00bb de digerir. Seu custo metab\u00f3lico \u00e9 o mais alto de todos os macros.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Carboidratos: TEF 5&ndash;10&nbsp;%<\/h4>\n    <div class=\"meta\">Fonte: Westerterp 2004<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Glic\u00f3lise<\/span><span class=\"v\">Moderadamente custoso<\/span><\/div>\n      <div class=\"rw\"><span>Armazenamento de glicog\u00eanio<\/span><span class=\"v\">Custo adicional<\/span><\/div>\n      <div class=\"rw lean\"><span>TEF Lean<\/span><span class=\"v\">8&nbsp;% (valor mediano)<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Gasto moderado mas n\u00e3o nulo. O armazenamento em glicog\u00eanio custa mais do que a oxida\u00e7\u00e3o direta.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Gorduras: TEF 0&ndash;3&nbsp;%<\/h4>\n    <div class=\"meta\">Fonte: Westerterp 2004<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Reesterifica\u00e7\u00e3o<\/span><span class=\"v\">Muito pouco custoso<\/span><\/div>\n      <div class=\"rw\"><span>Armazenamento direto<\/span><span class=\"v\">Quase sem transforma\u00e7\u00e3o<\/span><\/div>\n      <div class=\"rw lean\"><span>TEF Lean<\/span><span class=\"v\">2&nbsp;% (valor mediano)<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">O macro menos \u00ab&nbsp;caro&nbsp;\u00bb de digerir. As gorduras alimentares s\u00e3o quase diretamente armazen\u00e1veis sem grande gasto metab\u00f3lico.<\/div>\n  <\/div>\n<\/div>\n\n<!-- 13. OBJECTIFS SECHE\/BULK\/RECOMP -->\n<h2 class=\"sect\"><span class=\"num\">13 &middot; Objetivos<\/span>TEF e estrat\u00e9gia segundo cutting, bulk ou recomposi\u00e7\u00e3o<\/h2>\n<p>Uma vez conhecido seu TEF preciso, a aplica\u00e7\u00e3o pr\u00e1tica \u00e9 direta. Tr\u00eas objetivos, tr\u00eas alavancas.<\/p>\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>Cutting (perda de gordura)<\/h4>\n    <div class=\"meta\">Objetivo: maximizar o TEF sem sacrificar os macros<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Alavanca TEF<\/span><span class=\"v\">Prote\u00ednas a 30&nbsp;%+<\/span><\/div>\n      <div class=\"rw\"><span>Vantagem<\/span><span class=\"v\">Gasto adicional sem esporte<\/span><\/div>\n      <div class=\"rw lean\"><span>O Lean calcula<\/span><span class=\"v\">Impacto exato no d\u00e9ficit<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Uma ingest\u00e3o proteica elevada preserva a massa muscular E aumenta o TEF. Benef\u00edcio duplo no cutting. Ferramenta: <a href=\"https:\/\/lean-app.com\/pt\/calculateur-deficit-calorique\/\" style=\"text-decoration:underline\">calculadora de d\u00e9ficit cal\u00f3rico<\/a>.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Bulk (ganho de m\u00fasculo)<\/h4>\n    <div class=\"meta\">Objetivo: super\u00e1vit controlado, ganho de gordura m\u00ednimo<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Alavanca TEF<\/span><span class=\"v\">Prote\u00ednas altas preferidas<\/span><\/div>\n      <div class=\"rw\"><span>Vantagem<\/span><span class=\"v\">Super\u00e1vit l\u00edquido reduzido pelo TEF proteico<\/span><\/div>\n      <div class=\"rw lean\"><span>O Lean mostra<\/span><span class=\"v\">Super\u00e1vit l\u00edquido ap\u00f3s TEF real<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">No bulk, o Lean mostra o super\u00e1vit real em tempo real. Uma refei\u00e7\u00e3o muito proteica reduz o super\u00e1vit l\u00edquido pelo TEF adicional.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Recomposi\u00e7\u00e3o (manuten\u00e7\u00e3o + constru\u00e7\u00e3o)<\/h4>\n    <div class=\"meta\">Objetivo: precis\u00e3o m\u00e1xima em ingest\u00e3o e gasto<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Alavanca TEF<\/span><span class=\"v\">Ferramenta de precis\u00e3o na kcal<\/span><\/div>\n      <div class=\"rw\"><span>Vantagem<\/span><span class=\"v\">Equil\u00edbrio sem aproxima\u00e7\u00e3o<\/span><\/div>\n      <div class=\"rw lean\"><span>O Lean calcula<\/span><span class=\"v\">Balan\u00e7o cal\u00f3rico ao vivo<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">A recomposi\u00e7\u00e3o exige precis\u00e3o m\u00e1xima. Um TEF calculado na quilocaloria \u00e9 uma vantagem decisiva diante dos apps que o ignoram.<\/div>\n  <\/div>\n<\/div>\n\n<!-- 14. TEF LIVE DANS LEAN -->\n<h2 class=\"sect\"><span class=\"num\">14 &middot; TEF ao vivo<\/span>O acompanhamento da digest\u00e3o no Lean<\/h2>\n<div class=\"body\">\n<p>A aba Gasto do Lean detalha em tempo real cada componente do TDEE: BMR, NEAT, EAT, TEF. O TEF mostrado corresponde \u00e0s suas refei\u00e7\u00f5es registradas do dia, calculado sobre cada macro.<\/p>\n<\/div>\n<div style=\"max-width:130px;margin:24px auto\">\n  <div class=\"mini-phone\" style=\"max-width:130px\"><div class=\"notch\"><\/div><div class=\"scr\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp\" alt=\"TEF dans Lean, d&eacute;pense de digestion\" loading=\"lazy\"><\/div><\/div>\n<\/div>\n<div class=\"mini-cap\"><strong>Lean<\/strong> &middot; TEF em tempo real, calculado sobre seus macros reais<\/div>\n\n<!-- 15. LA PYRAMIDE -->\n<h2 class=\"sect\"><span class=\"num\">15 &middot; A Pir\u00e2mide<\/span>Pir\u00e2mide de Progress\u00e3o Lean<\/h2>\n<div class=\"body\">\n<p>A Pir\u00e2mide de Progress\u00e3o Lean hierarquiza as prioridades para atingir seu objetivo corporal. O TEF interv\u00e9m em dois n\u00edveis: o objetivo cal\u00f3rico preciso (TEF integrado no TDEE) e os macronutrientes (composi\u00e7\u00e3o que determina o n\u00edvel de TEF).<\/p>\n<\/div>\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 (TDEE + TEF preciso)<\/span><span class=\"k\">N\u00edvel 2<\/span><\/div>\n  <div class=\"level l3\"><span>Passos \/ NEAT di\u00e1rio<\/span><span class=\"k\">N\u00edvel 3<\/span><\/div>\n  <div class=\"level l4\"><span>Macros (prote\u00ednas = alavanca TEF)<\/span><span class=\"k\">Topo<\/span><\/div>\n<\/div>\n<div class=\"pyramid-cap\">N\u00e3o queimar etapas. Um TDEE preciso com TEF integrado \u00e9 o n\u00edvel 2. Mas se voc\u00ea n\u00e3o registra suas refei\u00e7\u00f5es regularmente, o TEF nunca \u00e9 calculado.<\/div>\n\n<!-- 16. FAQ -->\n<h2 class=\"sect\"><span class=\"num\">16 &middot; FAQ<\/span>Tudo o que voc\u00ea se pergunta sobre o TEF<\/h2>\n\n<details class=\"faq\"><summary>O que \u00e9 o efeito t\u00e9rmico dos alimentos?<\/summary><div class=\"faq-body\"><p>O <b>TEF (Thermic Effect of Food)<\/b>, tamb\u00e9m chamado DIT (Diet-Induced Thermogenesis), \u00e9 a energia gasta para digerir, absorver e metabolizar os alimentos. Ele entra na equa\u00e7\u00e3o <b>TDEE = BMR + NEAT + EAT + TEF<\/b> e representa em m\u00e9dia de 8 a 15&nbsp;% do gasto cal\u00f3rico total.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>Por que as prote\u00ednas t\u00eam o TEF mais alto?<\/summary><div class=\"faq-body\"><p>As prote\u00ednas exigem processos bioqu\u00edmicos custosos em ATP: s\u00edntese proteica, transamina\u00e7\u00e3o, desamina\u00e7\u00e3o (produ\u00e7\u00e3o de ureia) e \u00e0s vezes gliconeog\u00eanese. \u00c9 por isso que de 20 a 30&nbsp;% das calorias proteicas s\u00e3o queimadas na digest\u00e3o, contra 5 a 10&nbsp;% para os carboidratos e 0 a 3&nbsp;% para as gorduras.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>O MyFitnessPal calcula o TEF?<\/summary><div class=\"faq-body\"><p>N\u00e3o. MyFitnessPal, Yazio, Cronometer e a maioria dos apps de calorias n\u00e3o integram o TEF no seu c\u00e1lculo de gasto. Eles usam um coeficiente de atividade fixo (PAL) aplicado ao BMR, que supostamente \u00ab&nbsp;engloba&nbsp;\u00bb a digest\u00e3o. Na pr\u00e1tica, esse coeficiente n\u00e3o reflete sua composi\u00e7\u00e3o de macros do dia.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>Como o Lean calcula o TEF?<\/summary><div class=\"faq-body\"><p>O Lean aplica os coeficientes cient\u00edficos a cada refei\u00e7\u00e3o registrada: <b>P &times; 25&nbsp;% + C &times; 8&nbsp;% + G &times; 2&nbsp;%<\/b>. O resultado \u00e9 integrado em tempo real no seu TDEE do dia. Em uma refei\u00e7\u00e3o de 537&nbsp;kcal (54&nbsp;g P, 55&nbsp;g C, 12&nbsp;g G), o Lean calcula 74&nbsp;kcal de TEF.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>Quantas calorias representa o TEF por dia?<\/summary><div class=\"faq-body\"><p>Com uma alimenta\u00e7\u00e3o de 2&nbsp;000 a 2&nbsp;500&nbsp;kcal, o TEF representa entre 160 e 250&nbsp;kcal segundo sua composi\u00e7\u00e3o de macros. Em um ano, s\u00e3o de 58&nbsp;000 a 91&nbsp;000&nbsp;kcal de gasto ignorado pelos apps que n\u00e3o o calculam.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>O TEF diminui em d\u00e9ficit cal\u00f3rico?<\/summary><div class=\"faq-body\"><p>Sim, proporcionalmente: se voc\u00ea come menos calorias, digere menos e o TEF absoluto diminui. Mas a <b>porcentagem<\/b> permanece est\u00e1vel segundo seus macros. Em d\u00e9ficit, manter uma ingest\u00e3o proteica elevada preserva a raz\u00e3o TEF\/ingest\u00e3o, al\u00e9m de preservar a massa muscular.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>O TEF \u00e9 a mesma coisa que o metabolismo ativo p\u00f3s-prandial?<\/summary><div class=\"faq-body\"><p>Sim, os dois termos designam a mesma realidade: a energia queimada pela digest\u00e3o. TEF (Thermic Effect of Food) \u00e9 o termo angl\u00f3fono mais usado. DIT (Diet-Induced Thermogenesis) ou ADE (A\u00e7\u00e3o Din\u00e2mica Espec\u00edfica) s\u00e3o os equivalentes na literatura europeia e lus\u00f3fona.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>Os alimentos processados t\u00eam um TEF mais baixo?<\/summary><div class=\"faq-body\"><p>Sim. Barr &amp; Wright (2010, PMID&nbsp;20613941) mediram que as refei\u00e7\u00f5es \u00e0 base de alimentos integrais geram um TEF cerca de 50&nbsp;% mais alto do que refei\u00e7\u00f5es equivalentes em calorias \u00e0 base de alimentos processados. Os alimentos processados j\u00e1 est\u00e3o em parte \u00ab&nbsp;pr\u00e9-digeridos&nbsp;\u00bb industrialmente, o que reduz o trabalho digestivo e portanto o TEF.<\/p><\/div><\/details>\n\n<!-- 17. SOURCES -->\n<div class=\"sources\">\n  <h4>Fontes cient\u00edficas<\/h4>\n  <ol>\n    <li>Westerterp KR. Diet induced thermogenesis. <em>Nutr Metab (Lond)<\/em>. 2004;1(1):5. <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/15507147\/\" target=\"_blank\" rel=\"noopener\">PubMed 15507147<\/a><\/li>\n    <li>Acheson KJ. Protein choices targeting thermogenesis and metabolism. <em>Am J Clin Nutr<\/em>. 2011;93(3):525-534. <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/21235280\/\" target=\"_blank\" rel=\"noopener\">PubMed 21235280<\/a><\/li>\n    <li>Tappy L. Thermic effect of food and sympathetic nervous system activity in lean and obese subjects. <em>Crit Rev Clin Lab Sci<\/em>. 1996;33(6):435-444. <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/8701638\/\" target=\"_blank\" rel=\"noopener\">PubMed 8701638<\/a><\/li>\n    <li>Barr SB, Wright JC. Postprandial energy expenditure in whole-food and processed-food meals. <em>Food Nutr Res<\/em>. 2010;54. <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/20613941\/\" target=\"_blank\" rel=\"noopener\">PubMed 20613941<\/a><\/li>\n    <li>Levine JA. Non-exercise activity thermogenesis (NEAT). <em>Best Pract Res Clin Endocrinol Metab<\/em>. 2002;16(4):679-702. <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/12468415\/\" target=\"_blank\" rel=\"noopener\">PubMed 12468415<\/a><\/li>\n  <\/ol>\n<\/div>\n\n<!-- GET-BAND -->\n<div class=\"get-band\">\n  <h3>Calcule seu TEF sobre seus macros reais<\/h3>\n  <p>P &times; 25&nbsp;% + C &times; 8&nbsp;% + G &times; 2&nbsp;%, em cada refei\u00e7\u00e3o registrada. TDEE = BMR + NEAT + EAT + TEF. Modelo propriet\u00e1rio patenteado. Download gratuito, teste de 7 dias no plano anual.<\/p>\n  <div class=\"stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=pillar-tef-footer\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"T&eacute;l&eacute;charger sur l&rsquo;App Store\" loading=\"lazy\"><\/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=pillar-tef-footer\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Disponible sur Google Play\" loading=\"lazy\"><\/a>\n  <\/div>\n<\/div>\n\n<\/main>\n\n<script>(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  var tabMap = {\n    bilan:    {drill:false},\n    kcal:     {drill:false},\n    depense:  {drill:true},\n    strategie:{drill:false}\n  };\n  var currentTab = 'depense';\n  function setActive(tab){\n    topTabs.forEach(function(b){ b.classList.toggle('on', b.dataset.tab===tab); });\n  }\n  function showTab(tab){\n    var t = tabMap[tab]; if(!t) return;\n    currentTab = tab;\n    phoneImg.style.opacity = 0;\n    setTimeout(function(){\n      phoneImg.className = 'phone-bg tab-' + tab;\n      phoneImg.style.opacity = 1;\n      zones.style.display = t.drill ? 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Il repr\u00e9sente 8 \u00e0 15 % de la d\u00e9pense calorique totale et entre dans TDEE = BMR + NEAT + EAT + TEF.\"}},{\"@type\":\"Question\",\"name\":\"Pourquoi les prot\u00e9ines ont-elles le TEF le plus \u00e9lev\u00e9 ?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Les prot\u00e9ines n\u00e9cessitent synth\u00e8se, transaminaison et d\u00e9samination. Co\u00fbt en ATP \u00e9lev\u00e9 : 20 \u00e0 30 % des calories prot\u00e9iques sont br\u00fcl\u00e9es \u00e0 la digestion.\"}},{\"@type\":\"Question\",\"name\":\"MyFitnessPal calcule-t-il le TEF ?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Non. MFP, Yazio, Cronometer et la plupart des apps n'int\u00e8grent pas le TEF. Ils utilisent un coefficient PAL fixe qui ne refl\u00e8te pas ta composition en macros du jour.\"}},{\"@type\":\"Question\",\"name\":\"Comment Lean calcule-t-il le TEF ?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Lean applique P \u00d7 25 % + G \u00d7 8 % + L \u00d7 2 % sur chaque repas log\u00e9. Le r\u00e9sultat est int\u00e9gr\u00e9 en temps r\u00e9el dans ton TDEE du jour.\"}},{\"@type\":\"Question\",\"name\":\"Combien de calories repr\u00e9sente le TEF par jour ?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Sur 2 000 \u00e0 2 500 kcal, entre 160 et 250 kcal selon ta composition en macros. Sur une ann\u00e9e, c'est des dizaines de milliers de kcal ignor\u00e9es par les apps qui ne le calculent pas.\"}},{\"@type\":\"Question\",\"name\":\"Le TEF diminue-t-il en d\u00e9ficit calorique ?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Le TEF absolu diminue avec les apports, mais le pourcentage reste stable selon tes macros. Maintenir un apport prot\u00e9ique \u00e9lev\u00e9 pr\u00e9serve le ratio TEF\/apport.\"}},{\"@type\":\"Question\",\"name\":\"Les aliments transform\u00e9s ont-ils un TEF plus faible ?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Oui. Barr & Wright (2010) ont mesur\u00e9 que les repas base d'aliments entiers g\u00e9n\u00e8rent un TEF environ 50 % plus \u00e9lev\u00e9 que des repas \u00e9quivalents base d'aliments transform\u00e9s.\"}},{\"@type\":\"Question\",\"name\":\"TEF et DIT, c'est la m\u00eame chose ?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Oui, TEF (Thermic Effect of Food) et DIT (Diet-Induced Thermogenesis) d\u00e9signent la m\u00eame r\u00e9alit\u00e9. TEF est plus utilis\u00e9 dans la litt\u00e9rature anglophone.\"}}]},{\"@type\":\"MobileApplication\",\"name\":\"Lean\",\"operatingSystem\":\"iOS, Android\",\"applicationCategory\":\"HealthApplication\",\"description\":\"Lean calcule ton TEF en temps r\u00e9el sur chaque repas. TDEE complet : BMR + NEAT + EAT + TEF sur bodyfat r\u00e9el.\",\"aggregateRating\":{\"@type\":\"AggregateRating\",\"ratingValue\":\"4.7\",\"ratingCount\":\"1000\",\"bestRating\":\"5\"},\"offers\":{\"@type\":\"Offer\",\"price\":\"0\",\"priceCurrency\":\"EUR\"},\"downloadUrl\":\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\"}]}\n<\/script>\n\n<\/div>\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\/neat-depense-non-sportive\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">NEAT: o gasto cal\u00f3rico n\u00e3o esportivo que pesa 15 a 50% do seu TDEE <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Passos, deslocamentos, fidget. Por que Mifflin erra ao ignorar sua atividade.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/pt\/eat\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">EAT: seu gasto esportivo real, sess\u00e3o por sess\u00e3o <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Os MET corretos, a armadilha da contagem dupla, o que Garmin e MyFitnessPal deixam passar.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/pt\/meilleures-applications-calories-2026\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Melhores aplicativos para contar calorias em 2026: 8 apps testados <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Lean, MFP, Cronometer, Yazio, Lifesum, FatSecret, Noom, Foodvisor.<\/span><\/a><\/li><li><a href=\"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\/calculateur-deficit-calorique\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Calculadora de d\u00e9ficit cal\u00f3rico: a abordagem certa para o cutting <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">D\u00e9ficit sobre seu TDEE real bodyfat-aware. 3 ritmos: lento\/moderado\/agressivo.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/pt\/calculer-vraie-depense-calorique\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Como calcular seu gasto cal\u00f3rico real: o guia completo <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">BMR sobre gordura corporal real, NEAT por passos, EAT por treino, TEF por macros, adapta\u00e7\u00e3o.<\/span><\/a><\/li><\/ul><\/aside>","protected":false},"excerpt":{"rendered":"<p>Lean Accueil Accueil &nbsp;\/&nbsp; TEF Pilier &middot; Science du m&eacute;tabolisme TEF (Thermic Effect of Food). Le guide complet pour comprendre la d&eacute;pense calorique cach&eacute;e de la digestion. La digestion br&ucirc;le des calories. 20 &agrave; 30&nbsp;% des prot&eacute;ines, 5 &agrave; 10&nbsp;% des glucides, 0 &agrave; 3&nbsp;% des lipides. Toutes les apps l&rsquo;ignorent. Lean le calcule en [&hellip;]<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-lvm-blank","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1675","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Efeito t\u00e9rmico dos alimentos (TEF): c\u00e1lculo e exemplos - Lean<\/title>\n<meta name=\"description\" content=\"O efeito t\u00e9rmico dos alimentos (TEF) \u00e9 10 % do teu gasto. 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