{"id":1675,"date":"2026-05-28T08:21:54","date_gmt":"2026-05-28T08:21:54","guid":{"rendered":"https:\/\/lean-app.com\/?p=1675"},"modified":"2026-08-20T12:34:59","modified_gmt":"2026-08-20T12:34:59","slug":"effet-thermique-des-aliments","status":"publish","type":"post","link":"https:\/\/lean-app.com\/es\/effet-thermique-des-aliments\/","title":{"rendered":"Effet thermique des aliments (TEF) : pourquoi Lean calcule 69\u00a0kcal que les autres apps ignorent"},"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 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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\/es\/\"><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\/es\/\">Inicio<\/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\/es\/\">Inicio<\/a> &nbsp;\/&nbsp; TEF<\/div>\n  <div class=\"eyebrow\">Pilier &middot; Science du m&eacute;tabolisme<\/div>\n  <h1 id=\"title\">TEF (Thermic Effect of Food).\n    <span class=\"alt\">Le guide complet pour comprendre la d&eacute;pense calorique cach&eacute;e de la digestion.<\/span>\n  <\/h1>\n  <p class=\"dek\">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 temps r&eacute;el sur chaque repas log&eacute;.<\/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>L&rsquo;&eacute;quipe Lean<\/strong> &middot; Lecture 10&nbsp;min &middot; Mis &agrave; jour 28 mai 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\">T&eacute;l&eacute;chargement gratuit<\/span>\n  <\/div>\n  <div class=\"hero-bottom\">\n    <div class=\"hero-lead\">\n      Le TEF (Thermic Effect of Food) est l&rsquo;&eacute;nergie d&eacute;pens&eacute;e par ton corps pour dig\u00e9rer, absorber et m&eacute;taboliser chaque repas. Il repr&eacute;sente 8 &agrave; 15&nbsp;% de ta d&eacute;pense totale. La plupart des apps calorie ne le calculent pas. Lean le calcule &agrave; la kilocalorie pr&egrave;s, sur chaque aliment log&eacute;.\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>D&eacute;mo interactive<\/small>Touchez l&rsquo;&eacute;cran pour explorer l&rsquo;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>D&eacute;mo interactive<\/small>Touchez l&rsquo;&eacute;cran<br>para explorar la aplicaci\u00f3n<\/span>\n          <svg class=\"th-arrow\" viewbox=\"0 0 104 34\" fill=\"none\" aria-hidden=\"true\">\n            <path d=\"M4 9 C 34 1, 64 20, 94 27\" stroke=\"currentColor\" stroke-width=\"2.6\" fill=\"none\" stroke-linecap=\"round\"\/>\n            <path d=\"M86 20 L 94 27 L 84 30\" stroke=\"currentColor\" stroke-width=\"2.6\" fill=\"none\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/>\n          <\/svg>\n        <\/div>\n        <div class=\"phone\" id=\"phone\" role=\"img\" aria-label=\"Aper&ccedil;u de l&rsquo;application Lean avec drilldown du TDEE\">\n          <div class=\"notch\"><\/div>\n          <div class=\"phone-screen\">\n            <button class=\"phone-back\" id=\"phoneBack\" aria-label=\"Volver\">&#8249;<\/button>\n            <div id=\"phoneImg\" class=\"phone-bg tab-depense\" role=\"img\" aria-label=\"Vista Lean, pesta\u00f1a 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=\"Detalle BMR\"><\/div>\n              <div class=\"z\" data-sub=\"NEAT\" style=\"top:33%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"Detalle NEAT\"><\/div>\n              <div class=\"z\" data-sub=\"EAT\"  style=\"top:50%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"Detalle EAT\"><\/div>\n              <div class=\"z\" data-sub=\"TEF\"  style=\"top:67%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"Detalle TEF\"><\/div>\n            <\/div>\n            <div class=\"phone-navbar\" id=\"phoneNav\" aria-hidden=\"false\">\n              <button data-tab=\"bilan\"     type=\"button\" aria-label=\"Pesta\u00f1a Balance\"><\/button>\n              <button data-tab=\"kcal\"      type=\"button\" aria-label=\"Pesta\u00f1a Calor\u00edas\"><\/button>\n              <button data-tab=\"depense\"   type=\"button\" aria-label=\"Pesta\u00f1a Gasto\"><\/button>\n              <button data-tab=\"strategie\" type=\"button\" aria-label=\"Pesta\u00f1a Estrategia\"><\/button>\n            <\/div>\n          <\/div>\n        <\/div>\n        <div class=\"phone-tabs\" role=\"tablist\" aria-label=\"Naviguer dans l&rsquo;app Lean\">\n          <button data-tab=\"bilan\"     type=\"button\">Balance<\/button>\n          <button data-tab=\"kcal\"      type=\"button\">Calor\u00edas<\/button>\n          <button data-tab=\"depense\"   type=\"button\" class=\"on\">D&eacute;pense<\/button>\n          <button data-tab=\"strategie\" type=\"button\">Strat&eacute;gie<\/button>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n  <div class=\"snippet rev\">\n    <div class=\"lbl\">R&eacute;ponse rapide<\/div>\n    <p>Le TEF (Thermic Effect of Food) est l&rsquo;&eacute;nergie br&ucirc;l&eacute;e pour dig\u00e9rer tes aliments. Il entre dans l&rsquo;&eacute;quation <b>TDEE = BMR + NEAT + EAT + TEF<\/b>. Il varie selon tes macros : prot&eacute;ines 20&ndash;30&nbsp;%, glucides 5&ndash;10&nbsp;%, lipides 0&ndash;3&nbsp;%. Sur un repas standard post-training, Lean calcule 69&nbsp;kcal de TEF l&agrave; o&ugrave; les autres apps affichent 0.<\/p>\n  <\/div>\n<\/section>\n\n<!-- 02. DEFINITION -->\n<h2 class=\"sect\"><span class=\"num\">02 &middot; D&eacute;finition<\/span>TEF, la 4e brique du TDEE<\/h2>\n<div class=\"body\">\n<p>El <b>TEF (Thermic Effect of Food)<\/b> est l&rsquo;&eacute;nergie d&eacute;pens&eacute;e par ton corps pour traiter les aliments que tu ing\u00e8res : m&acirc;cher, dig\u00e9rer, absorber, m&eacute;taboliser. En anglais, on parle aussi de DIT (Diet-Induced Thermogenesis). C&rsquo;est la chaleur produite par ton syst&egrave;me digestif &agrave; chaque repas.<\/p>\n<p>Il s&rsquo;ins&egrave;re dans l&rsquo;&eacute;quation fondamentale du m&eacute;tabolisme :<\/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>El <b>BMR<\/b> (Basal Metabolic Rate) est ta d&eacute;pense au repos. Le <b>NEAT<\/b> (Non-Exercise Activity Thermogenesis) couvre ta d&eacute;pense non sportive. L&rsquo;<b>EAT<\/b> (Exercise Activity Thermogenesis) couvre tes s&eacute;ances de sport. Et le <b>TEF<\/b>, c&rsquo;est la chaleur g&eacute;n&eacute;r&eacute;e par la digestion. Ensemble, les quatre composent ton vrai TDEE.<\/p>\n<p>L&rsquo;<b>adaptation m&eacute;tabolique<\/b> vient en plus comme coefficient multiplicateur du BMR en d&eacute;ficit calorique prolong&eacute;. Convention Lean : 100&nbsp;% = optimal, 90&nbsp;% = 10&nbsp;% d&rsquo;adaptation. Elle n&rsquo;entre <b>pas<\/b> dans la somme TDEE.<\/p>\n<\/div>\n<div class=\"micro-cta\">\n  Voir aussi : <a href=\"\/es\/neat-depense-non-sportive\/\">Pilier NEAT<\/a> &middot; <a href=\"\/es\/metabolisme-de-base\/\">Pilier BMR<\/a> &middot; <a href=\"\/es\/depense-energetique-totale-v2\/\">Pilier TDEE<\/a> &middot; <a href=\"\/es\/calculateur-tdee\/\">Calculadora TDEE<\/a> &middot; <a href=\"\/es\/calculateur-deficit-calorique\/\">Calculateur d&eacute;ficit<\/a>\n<\/div>\n\n<!-- 03. 69 KCAL D'ECART -->\n<h2 class=\"sect\"><span class=\"num\">03 &middot; Impact r&eacute;el<\/span>69&nbsp;kcal ignor&eacute;es sur un repas post-training<\/h2>\n<div class=\"body\">\n<p>Un exemple concret : tu rentres de s&eacute;ance et tu manges 200&nbsp;g de poulet grillet, 200&nbsp;g de riz cuit, 30&nbsp;g d&rsquo;avocat. Total : 54&nbsp;g de prot&eacute;ines \/ 55&nbsp;g de glucides \/ 12&nbsp;g de lipides = <b>537&nbsp;kcal consomm&eacute;es<\/b>.<\/p>\n<p>Lean applique les coefficients scientifiques sur ce repas :<\/p>\n<\/div>\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>Prot&eacute;ines (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 Prot&eacute;ines<\/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>Lean calcule<\/span><span class=\"v\">En temps r&eacute;el<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Les prot&eacute;ines ont le TEF le plus &eacute;lev&eacute; : synth&egrave;se, transaminaison, glucon&eacute;og&egrave;nese sont des processus co&ucirc;teux en ATP.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Glucides (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 Glucides<\/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>Lean calcule<\/span><span class=\"v\">En temps r&eacute;el<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Conversion en glycog&egrave;ne ou oxydation directe. D&eacute;pense mod&eacute;r&eacute;e mais non nulle.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Lipides (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 Lipides<\/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>Lean calcule<\/span><span class=\"v\">En temps r&eacute;el<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">R&eacute;esst&eacute;rification directe tr&egrave;s efficace. Le macro le moins co&ucirc;teux &agrave; dig\u00e9rer.<\/div>\n  <\/div>\n<\/div>\n<div class=\"body\">\n<p><b>Total TEF calcul&eacute; par Lean : 54 + 18 + 2 = 74&nbsp;kcal<\/b> sur ce seul repas. Les apps concurrentes affichent 0. Sur une ann&eacute;e, c&rsquo;est des dizaines de milliers de kilocalories de d&eacute;pense ignor&eacute;e, ce qui explique les plateaux inexpliqu&eacute;s et les d&eacute;ficits qui &laquo;&nbsp;ne marchent pas&nbsp;&raquo;.<\/p>\n<\/div>\n\n<!-- 04. 3 PROFILS PAR APPORT EN PROTEINES -->\n<h2 class=\"sect\"><span class=\"num\">04 &middot; 3 profils<\/span>Plus de prot&eacute;ines = plus de TEF : les chiffres<\/h2>\n<div class=\"body\">\n<p>Trois profils sur une alimentation &agrave; 2&nbsp;500&nbsp;kcal\/jour. Seule la r&eacute;partition des macros change. Les chiffres de TEF total illustrent l&rsquo;impact &eacute;norme de la composition de l&rsquo;alimentation.<\/p>\n<\/div>\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>15&nbsp;% prot&eacute;ines<\/h4>\n    <div class=\"meta\">Alimentation pauvre en prot&eacute;ines &middot; 2&nbsp;500 kcal<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>TEF Prot&eacute;ines<\/span><span class=\"v\">75&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>TEF Glucides + Lipides<\/span><span class=\"v\">94&nbsp;kcal<\/span><\/div>\n      <div class=\"rw lean\"><span>TEF total<\/span><span class=\"v\">~169&nbsp;kcal \/ j<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">La case &laquo;&nbsp;s&eacute;dentaire&nbsp;&raquo; dans MFP ne tient pas compte de la composition alimentaire. Ce profil perd 169&nbsp;kcal de d&eacute;pense si l&rsquo;app l&rsquo;ignore.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>25&nbsp;% prot&eacute;ines<\/h4>\n    <div class=\"meta\">Profil sportif standard &middot; 2&nbsp;500 kcal<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>TEF Prot&eacute;ines<\/span><span class=\"v\">125&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>TEF Glucides + Lipides<\/span><span class=\"v\">85&nbsp;kcal<\/span><\/div>\n      <div class=\"rw lean\"><span>TEF total<\/span><span class=\"v\">~210&nbsp;kcal \/ j<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">41&nbsp;kcal de d&eacute;pense suppl&eacute;mentaire vs profil 15&nbsp;% prot&eacute;ines. L&rsquo;&eacute;quivalent de 5 minutes de marche suppl&eacute;mentaire, juste en changeant les macros.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>35&nbsp;% prot&eacute;ines<\/h4>\n    <div class=\"meta\">Profil s&egrave;che agressive &middot; 2&nbsp;500 kcal<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>TEF Prot&eacute;ines<\/span><span class=\"v\">175&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>TEF Glucides + Lipides<\/span><span class=\"v\">76&nbsp;kcal<\/span><\/div>\n      <div class=\"rw lean\"><span>TEF total<\/span><span class=\"v\">~251&nbsp;kcal \/ j<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">82&nbsp;kcal de plus vs profil 15&nbsp;%. Sur 30 jours : +2&nbsp;460&nbsp;kcal de d&eacute;pense suppl&eacute;mentaire &agrave; calories identiques, sans une seule s&eacute;ance suppl&eacute;mentaire.<\/div>\n  <\/div>\n<\/div>\n\n<!-- 05. POURQUOI LES APPS ECHOUENT -->\n<h2 class=\"sect\"><span class=\"num\">05 &middot; Pourquoi les apps &eacute;chouent<\/span>Coefficient fixe contre calcul macro-sp&eacute;cifique<\/h2>\n<div class=\"body\">\n<p>Quand tu configures MyFitnessPal ou Yazio, on te demande ton niveau d&rsquo;activit&eacute;. Un coefficient PAL s&rsquo;applique &agrave; ton BMR. Ce coefficient est cens&eacute; &laquo;&nbsp;englober&nbsp;&raquo; tout, y compris la digestion. En pratique, il est calibr&eacute; sur des populations g&eacute;n&eacute;riques et ne refl&egrave;te pas du tout ta composition en macros du jour.<\/p>\n<p>Le probl&egrave;me : ce coefficient ne change pas le lundi o&ugrave; tu manges 50&nbsp;% de prot&eacute;ines versus le dimanche o&ugrave; tu manges 20&nbsp;% de prot&eacute;ines. Le TEF de ces deux journ&eacute;es est radicalement diff&eacute;rent. Les apps ne le voient pas. Lean, si.<\/p>\n<p>Westerterp (2004, PMID&nbsp;15507147) a mesur&eacute; par calorim&eacute;trie indirecte que les erreurs d&rsquo;estimation du TEF via coefficient fixe peuvent atteindre <b>100 &agrave; 200&nbsp;kcal par jour<\/b> selon la composition alimentaire r&eacute;elle. C&rsquo;est l&rsquo;ordre de grandeur qui explique un d&eacute;ficit qui &laquo;&nbsp;ne marche pas&nbsp;&raquo; sur plusieurs semaines.<\/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 sur le m&ecirc;me repas<\/h2>\n<div class=\"body\">\n<p>Le m&ecirc;me repas post-training : 200&nbsp;g poulet, 200&nbsp;g riz cuit, 30&nbsp;g avocat = 537&nbsp;kcal. Ce que chaque app fait de ce repas :<\/p>\n<\/div>\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>MyFitnessPal (et la plupart des apps)<\/h4>\n    <div class=\"meta\">Pas de calcul TEF sur les repas<\/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 log&eacute;es<\/span><span class=\"v\" style=\"color:#FF2D6E\">TEF : 0&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>M&eacute;thode<\/span><span class=\"v\">Coefficient PAL fixe<\/span><\/div>\n      <div class=\"rw\"><span>Pris en compte<\/span><span class=\"v\">No<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">MFP, Yazio, Cronometer et la plupart des apps calorie n&rsquo;int&egrave;grent pas le TEF dans leur calcul de d&eacute;pense. Tu br&ucirc;les 74&nbsp;kcal &agrave; dig\u00e9rer ce repas. Elles ne le savent pas.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Lean<\/h4>\n    <div class=\"meta\">Calcul TEF macro-sp&eacute;cifique en temps r&eacute;el<\/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 log&eacute;es<\/span><span class=\"v\" style=\"color:#27AE60\">TEF : 74&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>M&eacute;thode<\/span><span class=\"v\">P&times;25&nbsp;% + G&times;8&nbsp;% + L&times;2&nbsp;%<\/span><\/div>\n      <div class=\"rw lean\"><span>Pris en compte<\/span><span class=\"v\">Oui, &agrave; chaque repas<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Lean calcule le TEF &agrave; la kilocalorie pr&egrave;s sur chaque repas log&eacute;. Ce TEF s&rsquo;ajoute &agrave; ton TDEE du jour et ajuste ton objectif calorique en temps r&eacute;el.<\/div>\n  <\/div>\n<\/div>\n<div class=\"cta-band\">\n  <div class=\"l\">Lean calcule ton TEF en temps r&eacute;el sur chaque repas. T&eacute;l&eacute;chargement gratuit, essai 7 jours sur l&rsquo;annuel.<\/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>Pourquoi ton BMR influe sur la valeur du TEF<\/h2>\n<div class=\"body\">\n<p>Le TEF est calcul&eacute; sur les macros ing\u00e9r&eacute;es. Mais pour que ce calcul soit int&eacute;gr&eacute; dans un TDEE pr&eacute;cis, encore faut-il que le BMR qui sert de base soit exact. Or le BMR d&eacute;pend directement de ta <b>masse maigre r&eacute;elle<\/b>.<\/p>\n<p>La raison physiologique : le m&eacute;tabolisme de base est principalement tenu par les muscles et les organes (tissu m&eacute;taboliquement actif), pas par la masse grasse. Deux individus de 80&nbsp;kg avec 12&nbsp;% et 22&nbsp;% de bodyfat ont une masse maigre de 70,4&nbsp;kg vs 62,4&nbsp;kg, soit un &eacute;cart de BMR d&rsquo;environ 170&nbsp;kcal\/j. Si ton TDEE est faux d&egrave;s la base, ton TEF se retrouve int&eacute;gr&eacute; dans une &eacute;quation d&eacute;j&agrave; d&eacute;calibr&eacute;e.<\/p>\n<p>Concr&egrave;tement : Lean calcule ton BMR sur ta masse maigre r&eacute;elle via BodyScan IA, puis int&egrave;gre le TEF sur ce BMR exact. L&rsquo;erreur de cha&icirc;ne que font les apps se produit &agrave; deux niveaux : BMR sur poids total (faux), puis 0&nbsp;kcal de TEF (faux aussi). Lean corrige les deux.<\/p>\n<\/div>\n<div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">BMR calcul&eacute; sur bodyfat r&eacute;el, pas sur poids total<\/div><p class=\"fd\">Lean utilise son mod&egrave;le propri&eacute;taire brevet&eacute; (pas Harris-Benedict 1919, pas Mifflin-St Jeor 1990) et l&rsquo;indexe sur ta masse maigre via BodyScan IA. Ce BMR sert de fondation &agrave; tout le reste, y compris le TEF.<\/p><\/div><div class=\"fc\">Pr&eacute;cision<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">TEF int&eacute;gr&eacute; dans le TDEE, pas ajout&eacute; apr&egrave;s coup<\/div><p class=\"fd\">Le TEF n&rsquo;est pas une ligne s&eacute;par&eacute;e que tu d&eacute;cides d&rsquo;activer ou non. Il fait partie de l&rsquo;&eacute;quation TDEE = BMR + NEAT + EAT + TEF, int&eacute;gr&eacute;e d&egrave;s le premier repas log&eacute;.<\/p><\/div><div class=\"fc\">Architecture<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">TEF recalcul&eacute; &agrave; chaque mise &agrave; jour du profil<\/div><p class=\"fd\">Tu perds 3&nbsp;kg de gras en un mois ? Ton BMR change. Et l&rsquo;int&eacute;gration du TEF dans le TDEE est automatiquement recalibr&eacute;e dans Lean. Les apps gardent leur constant depuis l&rsquo;inscription.<\/p><\/div><div class=\"fc\">Dynamique<\/div><\/div>\n\n<!-- 08. BODYSCAN IA -->\n<h2 class=\"sect\"><span class=\"num\">08 &middot; BodyScan IA<\/span>Le bodyfat r&eacute;el : la fondation du calcul TEF de Lean<\/h2>\n<div class=\"body\">\n<p>Pour que le TEF soit int&eacute;gr&eacute; dans un TDEE pr&eacute;cis, il faut d&rsquo;abord que le BMR soit juste. Et pour &ccedil;a, il faut ton bodyfat r&eacute;el. C&rsquo;est ici qu&rsquo;intervient le BodyScan IA de Lean.<\/p>\n<p>La plupart des apps calculent le BMR en fonction du poids total (Harris-Benedict 1919, Mifflin-St Jeor 1990). Lean calcule ton BMR sur ta <b>masse maigre estim&eacute;e via bodyfat<\/b>, gr&acirc;ce &agrave; un <b>mod&egrave;le propri&eacute;taire brevet&eacute;<\/b>. Ce BMR sert ensuite de fondation &agrave; l&rsquo;int&eacute;gration du TEF dans le 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> : bodyfat r&eacute;el en 5 secondes, depuis une photo<\/p>\n<\/div>\n<div class=\"body\">\n<p>Une photo, 5 secondes, et Lean conna&icirc;t ton bodyfat avec pr&eacute;cision. Ce chiffre alimente directement le calcul de ton BMR, qui sert &agrave; son tour de fondation &agrave; l&rsquo;int&eacute;gration du TEF dans ton TDEE. C&rsquo;est l&rsquo;architecture en cha&icirc;ne que les autres apps ne proposent pas.<\/p>\n<\/div>\n\n<!-- 09. COMMENT LEAN CALCULE LE TEF -->\n<h2 class=\"sect\"><span class=\"num\">09 &middot; Lean &amp; TEF<\/span>Calcul en temps r&eacute;el sur chaque repas log&eacute;<\/h2>\n<div class=\"body\">\n<p>Lean calcule le TEF &agrave; partir de chaque repas que tu log, et l&rsquo;int&egrave;gre dans ton TDEE du jour en temps r&eacute;el. Voici l&rsquo;architecture compl&egrave;te :<\/p>\n<\/div>\n<div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">Logging du repas (3 m&eacute;thodes)<\/div><p class=\"fd\">Tu log via la base USDA+OpenFoodFacts, le scan code-barres ou le scan photo IA d&rsquo;un plat. Lean r&eacute;cup&egrave;re imm&eacute;diatement les grammes de prot&eacute;ines, glucides et lipides.<\/p><\/div><div class=\"fc\">Saisie<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">Calcul TEF par macro sur chaque aliment<\/div><p class=\"fd\">Le moteur Lean applique : P &times; 25&nbsp;%, G &times; 8&nbsp;%, L &times; 2&nbsp;%. Le r&eacute;sultat est calcul&eacute; &agrave; la vol&eacute;e pour chaque aliment, puis cumul&eacute; sur la journ&eacute;e.<\/p><\/div><div class=\"fc\">Calcul<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">TEF cumul&eacute; dans le TDEE du jour<\/div><p class=\"fd\">Le TEF cumul&eacute; de la journ&eacute;e s&rsquo;ajoute au BMR + NEAT + EAT pour donner ton TDEE live. Ta balance calorique s&rsquo;ajuste &agrave; chaque repas log&eacute;.<\/p><\/div><div class=\"fc\">Int&eacute;gration<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">04<\/div><div><div class=\"ft\">Visible dans l&rsquo;onglet D&eacute;pense<\/div><p class=\"fd\">L&rsquo;onglet D&eacute;pense de Lean d&eacute;taille chaque composant du TDEE : BMR, NEAT, EAT, TEF. Tu vois exactement combien la digestion contribue &agrave; ta d&eacute;pense du jour.<\/p><\/div><div class=\"fc\">Transparent<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">05<\/div><div><div class=\"ft\">Impact direct sur l&rsquo;objectif calorique<\/div><p class=\"fd\">Lean utilise le TDEE TEF-aware pour calculer ton objectif et ton d&eacute;ficit cible. Un repas plus prot&eacute;in&eacute; augmente ton TEF et donc ton TDEE r&eacute;el, ce que Lean refl&egrave;te automatiquement.<\/p><\/div><div class=\"fc\">Strat&eacute;gique<\/div><\/div>\n\n<!-- 10. L'ECRAN TEF -->\n<h2 class=\"sect\"><span class=\"num\">10 &middot; TEF dans Lean<\/span>Le suivi de la digestion en temps r&eacute;el<\/h2>\n<div class=\"body\">\n<p>L&rsquo;onglet D&eacute;pense de Lean d&eacute;taille en temps r&eacute;el chaque composant du TDEE : BMR, NEAT, EAT, TEF. Clique sur TEF pour voir le d&eacute;tail par repas.<\/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 calcul&eacute; en temps r&eacute;el sur chaque repas<\/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; Strat&eacute;gies<\/span>Manger plus de prot&eacute;ines = br&ucirc;ler plus en dig\u00e9rant<\/h2>\n<div class=\"body\">\n<p>Le principe fondamental du TEF : chaque calorie de prot&eacute;ine co&ucirc;te 25&nbsp;% &agrave; dig\u00e9rer, contre 2&nbsp;% pour les lipides. <b>Manger plus de prot&eacute;ines = d&eacute;penser plus &agrave; calories &eacute;gales.<\/b> C&rsquo;est l&rsquo;avantage m&eacute;tabolique r&eacute;el d&rsquo;une alimentation prot&eacute;in&eacute;e en s&egrave;che.<\/p>\n<\/div>\n<div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">+100&nbsp;g de prot&eacute;ines = +100&nbsp;kcal de TEF gratuit<\/div><p class=\"fd\">100&nbsp;g de prot&eacute;ines suppl&eacute;mentaires (400&nbsp;kcal) g&eacute;n&egrave;rent environ 100&nbsp;kcal de TEF suppl&eacute;mentaire. C&rsquo;est de la d&eacute;pense r&eacute;elle, sans effort physique, juste en changeant ta composition alimentaire.<\/p><\/div><div class=\"fc\">Prot&eacute;ines<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">Log tout, m&ecirc;me les petits repas<\/div><p class=\"fd\">Chaque entr&eacute;e dans Lean d&eacute;clenche le calcul TEF. Un snack de 100&nbsp;g de fromage blanc (18&nbsp;g de prot&eacute;ines) g&eacute;n&egrave;re ~18&nbsp;kcal de TEF. Cumul&eacute; sur 5 prises alimentaires, c&rsquo;est une d&eacute;pense r&eacute;elle que les apps ne comptent pas.<\/p><\/div><div class=\"fc\">Exhaustivit&eacute;<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">Pr&eacute;f&egrave;re les aliments entiers<\/div><p class=\"fd\">Les aliments ultra-transform&eacute;s ont un TEF plus faible car d&eacute;j&agrave; en partie &laquo;&nbsp;pr&eacute;-dig\u00e9r&eacute;s&nbsp;&raquo; industriellement (Barr 2010, PMID&nbsp;20613941). Un blanc de poulet entier a un TEF plus &eacute;lev&eacute; qu&rsquo;une poudre de prot&eacute;ines pr&eacute;-hydrolysat&eacute;e.<\/p><\/div><div class=\"fc\">Qualit&eacute;<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">04<\/div><div><div class=\"ft\">Ne compte pas sur les lipides pour le TEF<\/div><p class=\"fd\">Les graisses ont un TEF de 0 &agrave; 3&nbsp;%. Augmenter tes lipides ne booste pas le TEF. C&rsquo;est la r&eacute;partition des macros qui compte, pas le total calorique brut.<\/p><\/div><div class=\"fc\">Lipides<\/div><\/div>\n\n<!-- 12. MET et macros -->\n<h2 class=\"sect\"><span class=\"num\">12 &middot; Science<\/span>Pourquoi les prot&eacute;ines br&ucirc;lent autant &agrave; la digestion<\/h2>\n<div class=\"body\">\n<p>La r&eacute;ponse est biochimique. Les prot&eacute;ines doivent &ecirc;tre d&eacute;compos&eacute;es en acides amin&eacute;s, qui sont ensuite soit int&eacute;gr&eacute;s dans la synth&egrave;se prot&eacute;ique (co&ucirc;t en ATP), soit oxyd&eacute;s (cycle de Krebs), soit transform&eacute;s en glucose (glucon&eacute;og&egrave;nese, co&ucirc;t encore plus &eacute;lev&eacute;). La d&eacute;samination de l&rsquo;azote (production d&rsquo;ur&eacute;e) est elle-m&ecirc;me co&ucirc;teuse en &eacute;nergie.<\/p>\n<\/div>\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>Prot&eacute;ines : TEF 20&ndash;30&nbsp;%<\/h4>\n    <div class=\"meta\">Source : Westerterp 2004, Acheson 2011<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Synth&egrave;se prot&eacute;ique<\/span><span class=\"v\">Co&ucirc;t ATP &eacute;lev&eacute;<\/span><\/div>\n      <div class=\"rw\"><span>D&eacute;samination<\/span><span class=\"v\">Production d&rsquo;ur&eacute;e<\/span><\/div>\n      <div class=\"rw lean\"><span>TEF Lean<\/span><span class=\"v\">25&nbsp;% (valeur m&eacute;diane)<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">C&rsquo;est le macro le plus &laquo;&nbsp;ch&egrave;re&nbsp;&raquo; &agrave; dig\u00e9rer. Son co&ucirc;t m&eacute;tabolique est le plus &eacute;lev&eacute; de tous les macros.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Glucides : TEF 5&ndash;10&nbsp;%<\/h4>\n    <div class=\"meta\">Source : Westerterp 2004<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Glycolyse<\/span><span class=\"v\">Mod&eacute;r&eacute;ment co&ucirc;teux<\/span><\/div>\n      <div class=\"rw\"><span>Stockage glycog&egrave;ne<\/span><span class=\"v\">Co&ucirc;t suppl&eacute;mentaire<\/span><\/div>\n      <div class=\"rw lean\"><span>TEF Lean<\/span><span class=\"v\">8&nbsp;% (valeur m&eacute;diane)<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">D&eacute;pense mod&eacute;r&eacute;e mais non nulle. Le stockage en glycog&egrave;ne co&ucirc;te plus que l&rsquo;oxydation directe.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Lipides : TEF 0&ndash;3&nbsp;%<\/h4>\n    <div class=\"meta\">Source : Westerterp 2004<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>R&eacute;esst&eacute;rification<\/span><span class=\"v\">Tr&egrave;s peu co&ucirc;teux<\/span><\/div>\n      <div class=\"rw\"><span>Stockage direct<\/span><span class=\"v\">Quasi sans transformation<\/span><\/div>\n      <div class=\"rw lean\"><span>TEF Lean<\/span><span class=\"v\">2&nbsp;% (valeur m&eacute;diane)<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Le macro le moins &laquo;&nbsp;ch&egrave;re&nbsp;&raquo; &agrave; dig\u00e9rer. Les graisses alimentaires sont quasi directement stockables sans grande d&eacute;pense m&eacute;tabolique.<\/div>\n  <\/div>\n<\/div>\n\n<!-- 13. OBJECTIFS SECHE\/BULK\/RECOMP -->\n<h2 class=\"sect\"><span class=\"num\">13 &middot; Objectifs<\/span>TEF et strat&eacute;gie selon s&egrave;che, bulk ou recomp<\/h2>\n<p>Une fois ton TEF pr&eacute;cis connu, l&rsquo;application pratique est directe. Trois objectifs, trois leviers.<\/p>\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>S&egrave;che (perte de gras)<\/h4>\n    <div class=\"meta\">Objectif : maximiser le TEF sans sacrifier les macros<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Levier TEF<\/span><span class=\"v\">Prot&eacute;ines &agrave; 30&nbsp;%+<\/span><\/div>\n      <div class=\"rw\"><span>Avantage<\/span><span class=\"v\">D&eacute;pense suppl&eacute;mentaire sans sport<\/span><\/div>\n      <div class=\"rw lean\"><span>Lean calcule<\/span><span class=\"v\">Impact exact sur le d&eacute;ficit<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Un apport prot&eacute;ique &eacute;lev&eacute; pr&eacute;serve la masse musculaire ET augmente le TEF. Double b&eacute;n&eacute;fice en s&egrave;che. Outil : <a href=\"\/es\/calculateur-deficit-calorique\/\" style=\"text-decoration:underline\">calculateur de d&eacute;ficit calorique<\/a>.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Bulk (prise de muscle)<\/h4>\n    <div class=\"meta\">Objectif : surplus contr&ocirc;l&eacute;, gain de gras minimal<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Levier TEF<\/span><span class=\"v\">Prot&eacute;ines &eacute;lev&eacute;es pr&eacute;f&eacute;r&eacute;es<\/span><\/div>\n      <div class=\"rw\"><span>Avantage<\/span><span class=\"v\">Surplus net r&eacute;duit par le TEF prot&eacute;ique<\/span><\/div>\n      <div class=\"rw lean\"><span>Lean affiche<\/span><span class=\"v\">Surplus net apr&egrave;s TEF r&eacute;el<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">En bulk, Lean affiche le surplus r&eacute;el en temps r&eacute;el. Un repas tr&egrave;s prot&eacute;in&eacute; r&eacute;duit le surplus net via le TEF suppl&eacute;mentaire.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Recomp (maintien + construction)<\/h4>\n    <div class=\"meta\">Objectif : pr&eacute;cision maximale sur apports et d&eacute;pense<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Levier TEF<\/span><span class=\"v\">Outil de pr&eacute;cision &agrave; la kcal<\/span><\/div>\n      <div class=\"rw\"><span>Avantage<\/span><span class=\"v\">&Eacute;quilibre sans approximation<\/span><\/div>\n      <div class=\"rw lean\"><span>Lean calcule<\/span><span class=\"v\">Balance calorique live<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">La recomposition exige une pr&eacute;cision maximale. Un TEF calcul&eacute; &agrave; la kilocalorie pr&egrave;s est un avantage d&eacute;cisif face aux apps qui l&rsquo;ignorent.<\/div>\n  <\/div>\n<\/div>\n\n<!-- 14. TEF LIVE DANS LEAN -->\n<h2 class=\"sect\"><span class=\"num\">14 &middot; TEF live<\/span>Le suivi de la digestion dans Lean<\/h2>\n<div class=\"body\">\n<p>L&rsquo;onglet D&eacute;pense de Lean d&eacute;taille en temps r&eacute;el chaque composant du TDEE : BMR, NEAT, EAT, TEF. Le TEF affich&eacute; correspond &agrave; tes repas log&eacute;s de la journ&eacute;e, calcul&eacute; sur chaque 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 en temps r&eacute;el, calcul&eacute; sur tes macros r&eacute;els<\/div>\n\n<!-- 15. LA PYRAMIDE -->\n<h2 class=\"sect\"><span class=\"num\">15 &middot; La Pyramide<\/span>Pyramide de Progression Lean<\/h2>\n<div class=\"body\">\n<p>La Pyramide de Progression Lean hi&eacute;rarchise les priorit&eacute;s pour atteindre ton objectif corporel. Le TEF y intervient &agrave; deux &eacute;tages : l&rsquo;objectif calorique pr&eacute;cis (TEF int&eacute;gr&eacute; dans le TDEE) et les macronutriments (composition qui d&eacute;termine le niveau de TEF).<\/p>\n<\/div>\n<div class=\"pyramid\" aria-label=\"Pyramide de Progression Lean\">\n  <div class=\"level l1\"><span>Adh&eacute;rence<\/span><span class=\"k\">Base<\/span><\/div>\n  <div class=\"level l2\"><span>Objectif calorique (TDEE + TEF pr&eacute;cis)<\/span><span class=\"k\">&Eacute;tage 2<\/span><\/div>\n  <div class=\"level l3\"><span>Pas \/ NEAT quotidien<\/span><span class=\"k\">&Eacute;tage 3<\/span><\/div>\n  <div class=\"level l4\"><span>Macros (prot&eacute;ines = levier TEF)<\/span><span class=\"k\">Sommet<\/span><\/div>\n<\/div>\n<div class=\"pyramid-cap\">Ne pas br&ucirc;ler les &eacute;tapes. Un TDEE pr&eacute;cis avec TEF int&eacute;gr&eacute; est l&rsquo;&eacute;tage 2. Mais si tu ne log pas tes repas r&eacute;guli&egrave;rement, le TEF n&rsquo;est jamais calcul&eacute;.<\/div>\n\n<!-- 16. FAQ -->\n<h2 class=\"sect\"><span class=\"num\">16 &middot; FAQ<\/span>Tout ce que tu te demandes sur le TEF<\/h2>\n\n<details class=\"faq\"><summary>Qu&rsquo;est-ce que l&rsquo;effet thermique des aliments&nbsp;?<\/summary><div class=\"faq-body\"><p>El <b>TEF (Thermic Effect of Food)<\/b>, aussi appel&eacute; DIT (Diet-Induced Thermogenesis), est l&rsquo;&eacute;nergie d&eacute;pens&eacute;e pour dig\u00e9rer, absorber et m&eacute;taboliser les aliments. Il entre dans l&rsquo;&eacute;quation <b>TDEE = BMR + NEAT + EAT + TEF<\/b> et repr&eacute;sente en moyenne 8 &agrave; 15&nbsp;% de la d&eacute;pense calorique totale.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>Pourquoi les prot&eacute;ines ont-elles le TEF le plus &eacute;lev&eacute;&nbsp;?<\/summary><div class=\"faq-body\"><p>Les prot&eacute;ines n&eacute;cessitent des processus biochimiques co&ucirc;teux en ATP : synth&egrave;se prot&eacute;ique, transaminaison, d&eacute;samination (production d&rsquo;ur&eacute;e), et parfois glucon&eacute;og&egrave;nese. C&rsquo;est pourquoi 20 &agrave; 30&nbsp;% des calories prot&eacute;iques sont br&ucirc;l&eacute;es &agrave; la digestion, contre 5 &agrave; 10&nbsp;% pour les glucides et 0 &agrave; 3&nbsp;% pour les lipides.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>MyFitnessPal calcule-t-il le TEF&nbsp;?<\/summary><div class=\"faq-body\"><p>Non. MyFitnessPal, Yazio, Cronometer et la plupart des apps calorie n&rsquo;int&egrave;grent pas le TEF dans leur calcul de d&eacute;pense. Ils utilisent un coefficient d&rsquo;activit&eacute; fixe (PAL) appliqu&eacute; au BMR, cens&eacute; &laquo;&nbsp;englober&nbsp;&raquo; la digestion. En pratique, ce coefficient ne refl&egrave;te pas ta composition en macros du jour.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>Comment Lean calcule-t-il le TEF&nbsp;?<\/summary><div class=\"faq-body\"><p>Lean applique les coefficients scientifiques sur chaque repas log&eacute; : <b>P &times; 25&nbsp;% + G &times; 8&nbsp;% + L &times; 2&nbsp;%<\/b>. Le r&eacute;sultat est int&eacute;gr&eacute; en temps r&eacute;el dans ton TDEE du jour. Sur un repas de 537&nbsp;kcal (54&nbsp;g P, 55&nbsp;g G, 12&nbsp;g L), Lean calcule 74&nbsp;kcal de TEF.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>Combien de calories repr&eacute;sente le TEF par jour&nbsp;?<\/summary><div class=\"faq-body\"><p>Sur une alimentation de 2&nbsp;000 &agrave; 2&nbsp;500&nbsp;kcal, le TEF repr&eacute;sente entre 160 et 250&nbsp;kcal selon ta composition en macros. Sur une ann&eacute;e, c&rsquo;est 58&nbsp;000 &agrave; 91&nbsp;000&nbsp;kcal de d&eacute;pense ignor&eacute;e par les apps qui ne le calculent pas.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>Le TEF diminue-t-il en d&eacute;ficit calorique&nbsp;?<\/summary><div class=\"faq-body\"><p>Oui, proportionnellement : si tu manges moins de calories, tu dig\u00e8res moins et le TEF absolu diminue. Mais le <b>pourcentage<\/b> reste stable selon tes macros. En d&eacute;ficit, maintenir un apport prot&eacute;ique &eacute;lev&eacute; pr&eacute;serve le ratio TEF\/apport, en plus de pr&eacute;server la masse musculaire.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>Le TEF est-il la m&ecirc;me chose que le m&eacute;tabolisme actif post-prandial&nbsp;?<\/summary><div class=\"faq-body\"><p>Oui, les deux termes d&eacute;signent la m&ecirc;me r&eacute;alit&eacute; : l&rsquo;&eacute;nergie br&ucirc;l&eacute;e par la digestion. TEF (Thermic Effect of Food) est le terme anglophone le plus utilis&eacute;. DIT (Diet-Induced Thermogenesis) ou ARS (Action Sp&eacute;cifique des Aliments) sont les &eacute;quivalents dans la litt&eacute;rature europ&eacute;enne et fran&ccedil;aise.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>Les aliments transform&eacute;s ont-ils un TEF plus faible&nbsp;?<\/summary><div class=\"faq-body\"><p>Oui. Barr &amp; Wright (2010, PMID&nbsp;20613941) ont mesur&eacute; que les repas base d&rsquo;aliments entiers g&eacute;n&egrave;rent un TEF environ 50&nbsp;% plus &eacute;lev&eacute; que des repas &eacute;quivalents en calories base d&rsquo;aliments transform&eacute;s. Les aliments transform&eacute;s sont d&eacute;j&agrave; en partie &laquo;&nbsp;pr&eacute;-dig\u00e9r&eacute;s&nbsp;&raquo; industriellement, ce qui r&eacute;duit le travail digestif et donc le TEF.<\/p><\/div><\/details>\n\n<!-- 17. SOURCES -->\n<div class=\"sources\">\n  <h4>Sources scientifiques<\/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 ton TEF sur tes macros r&eacute;els<\/h3>\n  <p>P &times; 25&nbsp;% + G &times; 8&nbsp;% + L &times; 2&nbsp;%, sur chaque repas log&eacute;. TDEE = BMR + NEAT + EAT + TEF. Mod&egrave;le propri&eacute;taire brevet&eacute;. T&eacute;l&eacute;chargement gratuit, essai de 7 jours sur l&rsquo;annuel.<\/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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Por qu\u00e9 Mifflin se equivoca al ignorar tu actividad.<\/span><\/a><\/li><li><a href=\"\/es\/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&nbsp;: tu gasto deportivo real, sesi\u00f3n por sesi\u00f3n <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Los MET correctos, la trampa del doble conteo, lo que Garmin y MyFitnessPal pasan por alto.<\/span><\/a><\/li><li><a href=\"\/es\/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;\">Mejores aplicaciones para contar calor\u00edas en 2026&nbsp;: 8 aplicaciones probadas <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=\"\/es\/lean-vs-myfitnesspal\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean frente a MyFitnessPal&nbsp;: la f\u00f3rmula TDEE que lo cambia todo <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Por qu\u00e9 MFP se equivoca en tu gasto cal\u00f3rico real.<\/span><\/a><\/li><li><a href=\"\/es\/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;\">Calculateur de d\u00e9ficit calorique : la bonne approche pour une s\u00e8che <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">D\u00e9ficit sur ton vrai TDEE bodyfat-aware. 3 rythmes lent\/mod\u00e9r\u00e9\/agressif.<\/span><\/a><\/li><li><a href=\"\/es\/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;\">Comment calculer ta vraie d\u00e9pense calorique : le guide complet <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">BMR sur bodyfat r\u00e9el, NEAT par pas, EAT par s\u00e9ance, TEF par macros, adaptation.<\/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>Effet thermique des aliments (TEF) : pourquoi Lean calcule 69\u00a0kcal que les autres apps ignorent - Lean<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/lean-app.com\/es\/effet-thermique-des-aliments\/\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Effet thermique des aliments (TEF) : pourquoi Lean calcule 69\u00a0kcal que les autres apps ignorent - Lean\" \/>\n<meta property=\"og:description\" content=\"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. 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