{"id":1675,"date":"2026-05-28T08:21:54","date_gmt":"2026-05-28T08:21:54","guid":{"rendered":"https:\/\/lean-app.com\/?p=1675"},"modified":"2026-09-05T10:53:10","modified_gmt":"2026-09-05T10:53:10","slug":"effet-thermique-des-aliments","status":"publish","type":"post","link":"https:\/\/lean-app.com\/da\/effet-thermique-des-aliments\/","title":{"rendered":"Madens termiske effekt (TEF): hvorfor Lean beregner 69 kcal, som de andre apps ignorerer"},"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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.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\/da\/\"><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\/da\/\">Accueil<\/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\/da\/\">Accueil<\/a> &nbsp;\/&nbsp; TEF<\/div>\n  <div class=\"eyebrow\">S\u00f8jle &middot; Stofskiftets videnskab<\/div>\n  <h1 id=\"title\">TEF (Thermic Effect of Food).\n    <span class=\"alt\">Den komplette guide til at forst\u00e5 ford\u00f8jelsens skjulte kalorieforbrug.<\/span>\n  <\/h1>\n  <p class=\"dek\">Ford\u00f8jelsen forbr\u00e6nder kalorier. 20 til 30&nbsp;% af protein, 5 til 10&nbsp;% af kulhydrater, 0 til 3&nbsp;% af fedt. Alle apps ignorerer det. Lean beregner det i realtid p\u00e5 hvert logget m\u00e5ltid.<\/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; L\u00e6setid 10&nbsp;min &middot; Opdateret 28. maj 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      TEF (Thermic Effect of Food) er den energi, din krop bruger p\u00e5 at ford\u00f8je, optage og oms\u00e6tte hvert m\u00e5ltid. Det udg\u00f8r 8 til 15&nbsp;% af dit samlede forbrug. De fleste kalorie-apps beregner det ikke. Lean beregner det p\u00e5 kilokalorien, p\u00e5 hver logget f\u00f8devare.\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>Interaktiv demo<\/small>Tryk p\u00e5 sk\u00e6rmen for at udforske appen<\/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>Interaktiv demo<\/small>Tryk p\u00e5 sk\u00e6rmen<br>pour explorer l&rsquo;app<\/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=\"Retour\">&#8249;<\/button>\n            <div id=\"phoneImg\" class=\"phone-bg tab-depense\" role=\"img\" aria-label=\"Aper&ccedil;u Lean, onglet D&eacute;pense\"><\/div>\n            <div class=\"phone-zones\" id=\"phoneZones\">\n              <div class=\"z\" data-sub=\"BMR\"  style=\"top:11%;height:21%\" role=\"button\" tabindex=\"0\" aria-label=\"D&eacute;tail BMR\"><\/div>\n              <div class=\"z\" data-sub=\"NEAT\" style=\"top:33%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"D&eacute;tail NEAT\"><\/div>\n              <div class=\"z\" data-sub=\"EAT\"  style=\"top:50%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"D&eacute;tail EAT\"><\/div>\n              <div class=\"z\" data-sub=\"TEF\"  style=\"top:67%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"D&eacute;tail TEF\"><\/div>\n            <\/div>\n            <div class=\"phone-navbar\" id=\"phoneNav\" aria-hidden=\"false\">\n              <button data-tab=\"bilan\"     type=\"button\" aria-label=\"Onglet Bilan\"><\/button>\n              <button data-tab=\"kcal\"      type=\"button\" aria-label=\"Onglet Calories\"><\/button>\n              <button data-tab=\"depense\"   type=\"button\" aria-label=\"Onglet D&eacute;pense\"><\/button>\n              <button data-tab=\"strategie\" type=\"button\" aria-label=\"Onglet Strat&eacute;gie\"><\/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\">Bilan<\/button>\n          <button data-tab=\"kcal\"      type=\"button\">Calories<\/button>\n          <button data-tab=\"depense\"   type=\"button\" class=\"on\">Forbrug<\/button>\n          <button data-tab=\"strategie\" type=\"button\">Strategi<\/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>TEF (Thermic Effect of Food) er den energi, der forbr\u00e6ndes for at ford\u00f8je din mad. Det indg\u00e5r i ligningen <b>TDEE = BMR + NEAT + EAT + TEF<\/b>. Det varierer efter dine makroer: protein 20&ndash;30&nbsp;%, kulhydrater 5&ndash;10&nbsp;%, fedt 0&ndash;3&nbsp;%. P\u00e5 et standardm\u00e5ltid efter tr\u00e6ning beregner Lean 69&nbsp;kcal TEF, hvor de andre apps viser 0.<\/p>\n  <\/div>\n<\/section>\n\n<!-- 02. DEFINITION -->\n<h2 class=\"sect\"><span class=\"num\">02 &middot; Definition<\/span>TEF, TDEE's 4. byggesten<\/h2>\n<div class=\"body\">\n<p>Le <b>TEF (Thermic Effect of Food)<\/b> er den energi, din krop bruger p\u00e5 at behandle den mad, du indtager: tygge, ford\u00f8je, optage, oms\u00e6tte. P\u00e5 engelsk taler man ogs\u00e5 om DIT (Diet-Induced Thermogenesis). Det er varmen produceret af dit ford\u00f8jelsessystem ved hvert m\u00e5ltid.<\/p>\n<p>Den indg\u00e5r i stofskiftets grundligning:<\/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>Le <b>BMR<\/b> (Basal Metabolic Rate) er dit forbrug i hvile. <b>NEAT<\/b> (Non-Exercise Activity Thermogenesis) d\u00e6kker dit ikke-sportslige forbrug.<b>EAT<\/b> (Exercise Activity Thermogenesis) d\u00e6kker dine tr\u00e6ningspas. Og <b>TEF<\/b>er varmen genereret af ford\u00f8jelsen. Tilsammen udg\u00f8r de fire din sande TDEE.<\/p>\n<p>Den<b>metaboliske tilpasning<\/b> kommer oveni som multiplikationskoefficient p\u00e5 BMR ved langvarigt kalorieunderskud. Lean-konvention: 100&nbsp;% = optimalt, 90&nbsp;% = 10&nbsp;% tilpasning. Den indg\u00e5r <b>pas<\/b> i TDEE-summen.<\/p>\n<\/div>\n<div class=\"micro-cta\">\n  Se ogs\u00e5: <a href=\"https:\/\/lean-app.com\/da\/neat-depense-non-sportive\/\">NEAT-s\u00f8jle<\/a> &middot; <a href=\"https:\/\/lean-app.com\/da\/metabolisme-de-base\/\">BMR-s\u00f8jle<\/a> &middot; <a href=\"https:\/\/lean-app.com\/da\/depense-energetique-totale-v2\/\">TDEE-s\u00f8jle<\/a> &middot; <a href=\"https:\/\/lean-app.com\/da\/calculateur-tdee\/\">Calculateur TDEE<\/a> &middot; <a href=\"https:\/\/lean-app.com\/da\/calculateur-deficit-calorique\/\">Underskudsberegner<\/a>\n<\/div>\n\n<!-- 03. 69 KCAL D'ECART -->\n<h2 class=\"sect\"><span class=\"num\">03 &middot; Reel effekt<\/span>69&nbsp;kcal ignoreret p\u00e5 et m\u00e5ltid efter tr\u00e6ning<\/h2>\n<div class=\"body\">\n<p>Et konkret eksempel: du kommer hjem fra tr\u00e6ning og spiser 200&nbsp;g grillet kylling, 200&nbsp;g kogte ris, 30&nbsp;g avocado. I alt: 54&nbsp;g protein \/ 55&nbsp;g kulhydrater \/ 12&nbsp;g fedt = <b>537&nbsp;kcal indtaget<\/b>.<\/p>\n<p>Lean anvender de videnskabelige koefficienter p\u00e5 dette m\u00e5ltid:<\/p>\n<\/div>\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>Protein (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 Protein<\/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 beregner<\/span><span class=\"v\">I realtid<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Protein har den h\u00f8jeste TEF: syntese, transaminering, glukoneogenese er ATP-kr\u00e6vende processer.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Kulhydrater (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 Kulhydrater<\/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 beregner<\/span><span class=\"v\">I realtid<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Omdannelse til glykogen eller direkte oxidation. Moderat, men ikke ubetydeligt forbrug.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Fedt (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 Fedt<\/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 beregner<\/span><span class=\"v\">I realtid<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Meget effektiv direkte reesterificering. Den makro, der er billigst at ford\u00f8je.<\/div>\n  <\/div>\n<\/div>\n<div class=\"body\">\n<p><b>Samlet TEF beregnet af Lean: 54 + 18 + 2 = 74&nbsp;kcal<\/b> alene p\u00e5 dette m\u00e5ltid. Konkurrerende apps viser 0. Over et \u00e5r er det titusindvis af kilokalorier ignoreret forbrug, hvilket forklarer uforklarlige plateauer og underskud, der \u00abikke virker\u00bb.<\/p>\n<\/div>\n\n<!-- 04. 3 PROFILS PAR APPORT EN PROTEINES -->\n<h2 class=\"sect\"><span class=\"num\">04 &middot; 3 profiler<\/span>Mere protein = mere TEF: tallene<\/h2>\n<div class=\"body\">\n<p>Tre profiler p\u00e5 en kost med 2&nbsp;500&nbsp;kcal\/dag. Kun makrofordelingen \u00e6ndrer sig. Tallene for samlet TEF illustrerer kostsammens\u00e6tningens enorme betydning.<\/p>\n<\/div>\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>15&nbsp;% protein<\/h4>\n    <div class=\"meta\">Proteinfattig kost &middot; 2&nbsp;500 kcal<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>TEF Protein<\/span><span class=\"v\">75&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>TEF Kulhydrater + Fedt<\/span><span class=\"v\">94&nbsp;kcal<\/span><\/div>\n      <div class=\"rw lean\"><span>Samlet TEF<\/span><span class=\"v\">~169&nbsp;kcal \/ dag<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Boksen \u00abstillesiddende\u00bb i MFP tager ikke h\u00f8jde for kostsammens\u00e6tningen. Denne profil mister 169&nbsp;kcal forbrug, hvis appen ignorerer det.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>25&nbsp;% protein<\/h4>\n    <div class=\"meta\">Standard sportsprofil &middot; 2&nbsp;500 kcal<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>TEF Protein<\/span><span class=\"v\">125&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>TEF Kulhydrater + Fedt<\/span><span class=\"v\">85&nbsp;kcal<\/span><\/div>\n      <div class=\"rw lean\"><span>Samlet TEF<\/span><span class=\"v\">~210&nbsp;kcal \/ dag<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">41&nbsp;kcal ekstra forbrug vs profilen med 15&nbsp;% protein. Svarende til 5 minutters ekstra gang, bare ved at \u00e6ndre makroerne.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>35&nbsp;% protein<\/h4>\n    <div class=\"meta\">Aggressiv cut-profil &middot; 2&nbsp;500 kcal<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>TEF Protein<\/span><span class=\"v\">175&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>TEF Kulhydrater + Fedt<\/span><span class=\"v\">76&nbsp;kcal<\/span><\/div>\n      <div class=\"rw lean\"><span>Samlet TEF<\/span><span class=\"v\">~251&nbsp;kcal \/ dag<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">82&nbsp;kcal mere vs profilen med 15&nbsp;%. Over 30 dage: +2&nbsp;460&nbsp;kcal ekstra forbrug ved identiske kalorier, uden et eneste ekstra pas.<\/div>\n  <\/div>\n<\/div>\n\n<!-- 05. POURQUOI LES APPS ECHOUENT -->\n<h2 class=\"sect\"><span class=\"num\">05 &middot; Hvorfor apps fejler<\/span>Fast koefficient mod makrospecifik beregning<\/h2>\n<div class=\"body\">\n<p>N\u00e5r du s\u00e6tter MyFitnessPal eller Yazio op, bliver du spurgt om dit aktivitetsniveau. En PAL-koefficient anvendes p\u00e5 din BMR. Den koefficient skal \u00abomfatte\u00bb alt, inklusive ford\u00f8jelsen. I praksis er den kalibreret p\u00e5 generiske populationer og afspejler slet ikke din makrosammens\u00e6tning den dag.<\/p>\n<p>Problemet: koefficienten \u00e6ndrer sig ikke den mandag, hvor du spiser 50&nbsp;% protein, versus den s\u00f8ndag, hvor du spiser 20&nbsp;% protein. TEF for disse to dage er radikalt forskellig. Apps ser det ikke. Det g\u00f8r Lean.<\/p>\n<p>Westerterp (2004, PMID&nbsp;15507147) m\u00e5lte ved indirekte kalorimetri, at fejlene ved estimering af TEF via fast koefficient kan n\u00e5 <b>100 til 200&nbsp;kcal om dagen<\/b> afh\u00e6ngigt af den reelle kostsammens\u00e6tning. Det er den st\u00f8rrelsesorden, der forklarer et underskud, der \u00abikke virker\u00bb over flere uger.<\/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 p\u00e5 samme m\u00e5ltid<\/h2>\n<div class=\"body\">\n<p>Det samme m\u00e5ltid efter tr\u00e6ning: 200&nbsp;g kylling, 200&nbsp;g kogte ris, 30&nbsp;g avocado = 537&nbsp;kcal. Det, hver app g\u00f8r med dette m\u00e5ltid:<\/p>\n<\/div>\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>MyFitnessPal (og de fleste apps)<\/h4>\n    <div class=\"meta\">Ingen TEF-beregning p\u00e5 m\u00e5ltiderne<\/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 logget<\/span><span class=\"v\" style=\"color:#FF2D6E\">TEF: 0&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>Metode<\/span><span class=\"v\">Fast PAL-koefficient<\/span><\/div>\n      <div class=\"rw\"><span>Medregnet<\/span><span class=\"v\">Nej<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">MFP, Yazio, Cronometer og de fleste kalorie-apps integrerer ikke TEF i deres forbrugsberegning. Du forbr\u00e6nder 74&nbsp;kcal p\u00e5 at ford\u00f8je dette m\u00e5ltid. Det ved de ikke.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Lean<\/h4>\n    <div class=\"meta\">Makrospecifik TEF-beregning i realtid<\/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 logget<\/span><span class=\"v\" style=\"color:#27AE60\">TEF: 74&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>Metode<\/span><span class=\"v\">P&times;25&nbsp;% + K&times;8&nbsp;% + F&times;2&nbsp;%<\/span><\/div>\n      <div class=\"rw lean\"><span>Medregnet<\/span><span class=\"v\">Ja, ved hvert m\u00e5ltid<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Lean beregner TEF p\u00e5 kilokalorien p\u00e5 hvert logget m\u00e5ltid. Denne TEF l\u00e6gges til din TDEE for dagen og justerer dit kaloriem\u00e5l i realtid.<\/div>\n  <\/div>\n<\/div>\n<div class=\"cta-band\">\n  <div class=\"l\">Lean beregner din TEF i realtid p\u00e5 hvert m\u00e5ltid. Gratis download, 7 dages pr\u00f8veperiode p\u00e5 \u00e5rsabonnementet.<\/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>Hvorfor din BMR p\u00e5virker v\u00e6rdien af TEF<\/h2>\n<div class=\"body\">\n<p>TEF beregnes p\u00e5 de indtagne makroer. Men for at denne beregning kan integreres i en pr\u00e6cis TDEE, skal den BMR, der er grundlaget, v\u00e6re korrekt. Og BMR afh\u00e6nger direkte af din <b>reelle fedtfri masse<\/b>.<\/p>\n<p>Den fysiologiske \u00e5rsag: basalstofskiftet b\u00e6res hovedsageligt af muskler og organer (metabolisk aktivt v\u00e6v), ikke af fedtmassen. To personer p\u00e5 80&nbsp;kg med 12&nbsp;% og 22&nbsp;% fedtprocent har en fedtfri masse p\u00e5 70,4&nbsp;kg vs 62,4&nbsp;kg, alts\u00e5 en BMR-forskel p\u00e5 cirka 170&nbsp;kcal\/dag. Er din TDEE forkert fra grunden, integreres din TEF i en ligning, der allerede er dekalibreret.<\/p>\n<p>Konkret: Lean beregner din BMR p\u00e5 din reelle fedtfri masse via AI BodyScan og integrerer derefter TEF p\u00e5 denne korrekte BMR. K\u00e6defejlen, som apps beg\u00e5r, sker p\u00e5 to niveauer: BMR p\u00e5 totalv\u00e6gt (forkert), derefter 0&nbsp;kcal TEF (ogs\u00e5 forkert). Lean retter begge.<\/p>\n<\/div>\n<div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">BMR beregnet p\u00e5 reel fedtprocent, ikke p\u00e5 totalv\u00e6gt<\/div><p class=\"fd\">Lean bruger sin patenterede egenudviklede model (ikke Harris-Benedict 1919, ikke Mifflin-St Jeor 1990) og indekserer den p\u00e5 din fedtfri masse via AI BodyScan. Denne BMR er fundamentet for alt det andet, inklusive TEF.<\/p><\/div><div class=\"fc\">Pr\u00e6cision<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">TEF integreret i TDEE, ikke lagt til bagefter<\/div><p class=\"fd\">TEF er ikke en separat linje, som du v\u00e6lger at aktivere eller ej. Den er en del af ligningen TDEE = BMR + NEAT + EAT + TEF, integreret fra det f\u00f8rste loggede m\u00e5ltid.<\/p><\/div><div class=\"fc\">Arkitektur<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">TEF genberegnet ved hver profilopdatering<\/div><p class=\"fd\">Taber du 3&nbsp;kg fedt p\u00e5 en m\u00e5ned? Din BMR \u00e6ndrer sig. Og integrationen af TEF i TDEE rekalibreres automatisk i Lean. Apps beholder deres konstant fra tilmeldingen.<\/p><\/div><div class=\"fc\">Dynamisk<\/div><\/div>\n\n<!-- 08. BODYSCAN IA -->\n<h2 class=\"sect\"><span class=\"num\">08 &middot; AI BodyScan<\/span>Den reelle fedtprocent: fundamentet for Leans TEF-beregning<\/h2>\n<div class=\"body\">\n<p>For at TEF kan integreres i en pr\u00e6cis TDEE, skal BMR f\u00f8rst v\u00e6re rigtig. Og til det skal man bruge din reelle fedtprocent. Det er her, Leans AI BodyScan kommer ind.<\/p>\n<p>De fleste apps beregner BMR ud fra totalv\u00e6gten (Harris-Benedict 1919, Mifflin-St Jeor 1990). Lean beregner din BMR p\u00e5 din <b>fedtfri masse estimeret via fedtprocent<\/b>, takket v\u00e6re en <b>mod&egrave;le propri&eacute;taire brevet&eacute;<\/b>. Denne BMR er derefter fundamentet for integrationen af TEF i 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>AI BodyScan<\/b> : reel fedtprocent p\u00e5 5 sekunder, fra et foto<\/p>\n<\/div>\n<div class=\"body\">\n<p>Et foto, 5 sekunder, og Lean kender din fedtprocent pr\u00e6cist. Dette tal f\u00f8der direkte beregningen af din BMR, som igen er fundamentet for integrationen af TEF i din TDEE. Det er den k\u00e6dearkitektur, som de andre apps ikke tilbyder.<\/p>\n<\/div>\n\n<!-- 09. COMMENT LEAN CALCULE LE TEF -->\n<h2 class=\"sect\"><span class=\"num\">09 &middot; Lean &amp; TEF<\/span>Beregning i realtid p\u00e5 hvert logget m\u00e5ltid<\/h2>\n<div class=\"body\">\n<p>Lean beregner TEF ud fra hvert m\u00e5ltid, du logger, og integrerer den i din TDEE for dagen i realtid. Her er den komplette arkitektur:<\/p>\n<\/div>\n<div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">Logning af m\u00e5ltidet (3 metoder)<\/div><p class=\"fd\">Du logger via databasen USDA+OpenFoodFacts, stregkodescanning eller AI-fotoscanning af en ret. Lean henter straks grammene af protein, kulhydrater og fedt.<\/p><\/div><div class=\"fc\">Indtastning<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">TEF-beregning per makro p\u00e5 hver f\u00f8devare<\/div><p class=\"fd\">Lean-motoren anvender: P &times; 25&nbsp;%, K &times; 8&nbsp;%, F &times; 2&nbsp;%. Resultatet beregnes l\u00f8bende for hver f\u00f8devare og akkumuleres derefter over dagen.<\/p><\/div><div class=\"fc\">Beregning<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">Akkumuleret TEF i dagens TDEE<\/div><p class=\"fd\">Dagens akkumulerede TEF l\u00e6gges til BMR + NEAT + EAT for at give din live-TDEE. Din kaloriebalance justeres ved hvert logget m\u00e5ltid.<\/p><\/div><div class=\"fc\">Integration<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">04<\/div><div><div class=\"ft\">Synlig i Forbrug-fanen<\/div><p class=\"fd\">Forbrug-fanen i Lean detaljerer hver TDEE-komponent: BMR, NEAT, EAT, TEF. Du ser pr\u00e6cist, hvor meget ford\u00f8jelsen bidrager til dit forbrug den dag.<\/p><\/div><div class=\"fc\">Transparent<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">05<\/div><div><div class=\"ft\">Direkte effekt p\u00e5 kaloriem\u00e5let<\/div><p class=\"fd\">Lean bruger den TEF-bevidste TDEE til at beregne dit m\u00e5l og dit m\u00e5lunderskud. Et mere proteinrigt m\u00e5ltid \u00f8ger din TEF og dermed din reelle TDEE, hvilket Lean afspejler automatisk.<\/p><\/div><div class=\"fc\">Strategisk<\/div><\/div>\n\n<!-- 10. L'ECRAN TEF -->\n<h2 class=\"sect\"><span class=\"num\">10 &middot; TEF i Lean<\/span>Opf\u00f8lgning af ford\u00f8jelsen i realtid<\/h2>\n<div class=\"body\">\n<p>Forbrug-fanen i Lean detaljerer i realtid hver TDEE-komponent: BMR, NEAT, EAT, TEF. Klik p\u00e5 TEF for at se detaljerne per m\u00e5ltid.<\/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 beregnet i realtid p\u00e5 hvert m\u00e5ltid<\/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; Strategier<\/span>Spis mere protein = forbr\u00e6nd mere under ford\u00f8jelsen<\/h2>\n<div class=\"body\">\n<p>TEF's grundprincip: hver proteinkalorie koster 25&nbsp;% at ford\u00f8je, mod 2&nbsp;% for fedt. <b>Spis mere protein = forbrug mere ved samme kalorier.<\/b> Det er den reelle metaboliske fordel ved en proteinrig kost i cut.<\/p>\n<\/div>\n<div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">+100&nbsp;g protein = +100&nbsp;kcal gratis TEF<\/div><p class=\"fd\">100&nbsp;g ekstra protein (400&nbsp;kcal) genererer cirka 100&nbsp;kcal ekstra TEF. Det er reelt forbrug, uden fysisk anstrengelse, bare ved at \u00e6ndre din kostsammens\u00e6tning.<\/p><\/div><div class=\"fc\">Protein<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">Log alt, selv de sm\u00e5 m\u00e5ltider<\/div><p class=\"fd\">Hver indtastning i Lean udl\u00f8ser TEF-beregningen. En snack p\u00e5 100&nbsp;g skyr (18&nbsp;g protein) genererer ~18&nbsp;kcal TEF. Akkumuleret over 5 m\u00e5ltider er det et reelt forbrug, som apps ikke t\u00e6ller.<\/p><\/div><div class=\"fc\">Fuldst\u00e6ndighed<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">Foretr\u00e6k hele f\u00f8devarer<\/div><p class=\"fd\">Ultraforarbejdede f\u00f8devarer har en lavere TEF, fordi de allerede delvist er \u00abforford\u00f8jet\u00bb industrielt (Barr 2010, PMID&nbsp;20613941). Et helt kyllingebryst har en h\u00f8jere TEF end et forhydrolyseret proteinpulver.<\/p><\/div><div class=\"fc\">Kvalitet<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">04<\/div><div><div class=\"ft\">Regn ikke med fedt for TEF<\/div><p class=\"fd\">Fedt har en TEF p\u00e5 0 til 3&nbsp;%. At \u00f8ge dit fedt booster ikke TEF. Det er makrofordelingen, der t\u00e6ller, ikke det r\u00e5 kalorietotal.<\/p><\/div><div class=\"fc\">Fedt<\/div><\/div>\n\n<!-- 12. MET et macros -->\n<h2 class=\"sect\"><span class=\"num\">12 &middot; Videnskab<\/span>Hvorfor protein forbr\u00e6nder s\u00e5 meget under ford\u00f8jelsen<\/h2>\n<div class=\"body\">\n<p>Svaret er biokemisk. Protein skal nedbrydes til aminosyrer, som derefter enten indg\u00e5r i proteinsyntesen (ATP-omkostning), oxideres (Krebs-cyklus) eller omdannes til glukose (glukoneogenese, endnu h\u00f8jere omkostning). Deamineringen af kv\u00e6lstof (produktion af urinstof) er i sig selv energikr\u00e6vende.<\/p>\n<\/div>\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>Protein: TEF 20&ndash;30&nbsp;%<\/h4>\n    <div class=\"meta\">Kilde: Westerterp 2004, Acheson 2011<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Proteinsyntese<\/span><span class=\"v\">H\u00f8j ATP-omkostning<\/span><\/div>\n      <div class=\"rw\"><span>Deaminering<\/span><span class=\"v\">Produktion af urinstof<\/span><\/div>\n      <div class=\"rw lean\"><span>Lean TEF<\/span><span class=\"v\">25&nbsp;% (medianv\u00e6rdi)<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Det er den \u00abdyreste\u00bb makro at ford\u00f8je. Dens metaboliske omkostning er den h\u00f8jeste af alle makroer.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Kulhydrater: TEF 5&ndash;10&nbsp;%<\/h4>\n    <div class=\"meta\">Kilde: Westerterp 2004<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Glykolyse<\/span><span class=\"v\">Moderat omkostning<\/span><\/div>\n      <div class=\"rw\"><span>Glykogenlagring<\/span><span class=\"v\">Ekstra omkostning<\/span><\/div>\n      <div class=\"rw lean\"><span>Lean TEF<\/span><span class=\"v\">8&nbsp;% (medianv\u00e6rdi)<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Moderat, men ikke ubetydeligt forbrug. Lagring som glykogen koster mere end direkte oxidation.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Fedt: TEF 0&ndash;3&nbsp;%<\/h4>\n    <div class=\"meta\">Kilde: Westerterp 2004<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Reesterificering<\/span><span class=\"v\">Meget lav omkostning<\/span><\/div>\n      <div class=\"rw\"><span>Direkte lagring<\/span><span class=\"v\">N\u00e6sten uden omdannelse<\/span><\/div>\n      <div class=\"rw lean\"><span>Lean TEF<\/span><span class=\"v\">2&nbsp;% (medianv\u00e6rdi)<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Den \u00abbilligste\u00bb makro at ford\u00f8je. Kostfedt kan lagres n\u00e6sten direkte uden st\u00f8rre metabolisk forbrug.<\/div>\n  <\/div>\n<\/div>\n\n<!-- 13. OBJECTIFS SECHE\/BULK\/RECOMP -->\n<h2 class=\"sect\"><span class=\"num\">13 &middot; M\u00e5l<\/span>TEF og strategi ved cut, bulk eller recomp<\/h2>\n<p>N\u00e5r din pr\u00e6cise TEF er kendt, er den praktiske anvendelse direkte. Tre m\u00e5l, tre h\u00e5ndtag.<\/p>\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>Cut (fedttab)<\/h4>\n    <div class=\"meta\">M\u00e5l: maksim\u00e9r TEF uden at ofre makroerne<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>TEF-h\u00e5ndtag<\/span><span class=\"v\">Protein p\u00e5 30&nbsp;%+<\/span><\/div>\n      <div class=\"rw\"><span>Fordel<\/span><span class=\"v\">Ekstra forbrug uden sport<\/span><\/div>\n      <div class=\"rw lean\"><span>Lean beregner<\/span><span class=\"v\">Pr\u00e6cis effekt p\u00e5 underskuddet<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Et h\u00f8jt proteinindtag bevarer muskelmassen OG \u00f8ger TEF. Dobbelt gevinst i cut. V\u00e6rkt\u00f8j: <a href=\"https:\/\/lean-app.com\/da\/calculateur-deficit-calorique\/\" style=\"text-decoration:underline\">beregner for kalorieunderskud<\/a>.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Bulk (muskelopbygning)<\/h4>\n    <div class=\"meta\">M\u00e5l: kontrolleret overskud, minimalt fedtoptag<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>TEF-h\u00e5ndtag<\/span><span class=\"v\">H\u00f8jt protein foretr\u00e6kkes<\/span><\/div>\n      <div class=\"rw\"><span>Fordel<\/span><span class=\"v\">Nettooverskud reduceret af protein-TEF<\/span><\/div>\n      <div class=\"rw lean\"><span>Lean viser<\/span><span class=\"v\">Nettooverskud efter reel TEF<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">I bulk viser Lean det reelle overskud i realtid. Et meget proteinrigt m\u00e5ltid reducerer nettooverskuddet via den ekstra TEF.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Recomp (vedligehold + opbygning)<\/h4>\n    <div class=\"meta\">M\u00e5l: maksimal pr\u00e6cision p\u00e5 indtag og forbrug<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>TEF-h\u00e5ndtag<\/span><span class=\"v\">Pr\u00e6cisionsv\u00e6rkt\u00f8j p\u00e5 kalorien<\/span><\/div>\n      <div class=\"rw\"><span>Fordel<\/span><span class=\"v\">Balance uden tiln\u00e6rmelse<\/span><\/div>\n      <div class=\"rw lean\"><span>Lean beregner<\/span><span class=\"v\">Live-kaloriebalance<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Rekomposition kr\u00e6ver maksimal pr\u00e6cision. En TEF beregnet p\u00e5 kilokalorien er en afg\u00f8rende fordel over for apps, der ignorerer den.<\/div>\n  <\/div>\n<\/div>\n\n<!-- 14. TEF LIVE DANS LEAN -->\n<h2 class=\"sect\"><span class=\"num\">14 &middot; Live-TEF<\/span>Opf\u00f8lgning af ford\u00f8jelsen i Lean<\/h2>\n<div class=\"body\">\n<p>Forbrug-fanen i Lean detaljerer i realtid hver TDEE-komponent: BMR, NEAT, EAT, TEF. Den viste TEF svarer til dine loggede m\u00e5ltider den dag, beregnet p\u00e5 hver makro.<\/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 i realtid, beregnet p\u00e5 dine reelle makroer<\/div>\n\n<!-- 15. LA PYRAMIDE -->\n<h2 class=\"sect\"><span class=\"num\">15 &middot; Pyramiden<\/span>Leans Progressionspyramide<\/h2>\n<div class=\"body\">\n<p>Leans Progressionspyramide rangordner prioriteterne for at n\u00e5 dit kropsm\u00e5l. TEF indg\u00e5r p\u00e5 to etager: det pr\u00e6cise kaloriem\u00e5l (TEF integreret i TDEE) og makron\u00e6ringsstofferne (sammens\u00e6tningen, der bestemmer TEF-niveauet).<\/p>\n<\/div>\n<div class=\"pyramid\" aria-label=\"Leans Progressionspyramide\">\n  <div class=\"level l1\"><span>Vedholdenhed<\/span><span class=\"k\">Bund<\/span><\/div>\n  <div class=\"level l2\"><span>Kaloriem\u00e5l (TDEE + pr\u00e6cis TEF)<\/span><span class=\"k\">Etage 2<\/span><\/div>\n  <div class=\"level l3\"><span>Skridt \/ daglig NEAT<\/span><span class=\"k\">Etage 3<\/span><\/div>\n  <div class=\"level l4\"><span>Makroer (protein = TEF-h\u00e5ndtag)<\/span><span class=\"k\">Top<\/span><\/div>\n<\/div>\n<div class=\"pyramid-cap\">Spring ikke trin over. En pr\u00e6cis TDEE med integreret TEF er etage 2. Men hvis du ikke logger dine m\u00e5ltider regelm\u00e6ssigt, beregnes TEF aldrig.<\/div>\n\n<!-- 16. FAQ -->\n<h2 class=\"sect\"><span class=\"num\">16 &middot; FAQ<\/span>Alt du sp\u00f8rger dig selv om TEF<\/h2>\n\n<details class=\"faq\"><summary>Hvad er madens termiske effekt&nbsp;?<\/summary><div class=\"faq-body\"><p>Le <b>TEF (Thermic Effect of Food)<\/b>, ogs\u00e5 kaldet DIT (Diet-Induced Thermogenesis), er den energi, der bruges p\u00e5 at ford\u00f8je, optage og oms\u00e6tte maden. Den indg\u00e5r i ligningen <b>TDEE = BMR + NEAT + EAT + TEF<\/b> og udg\u00f8r i gennemsnit 8 til 15&nbsp;% af det samlede kalorieforbrug.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>Hvorfor har protein den h\u00f8jeste TEF&nbsp;?<\/summary><div class=\"faq-body\"><p>Protein kr\u00e6ver ATP-kr\u00e6vende biokemiske processer: proteinsyntese, transaminering, deaminering (produktion af urinstof) og nogle gange glukoneogenese. Derfor forbr\u00e6ndes 20 til 30&nbsp;% af proteinkalorierne under ford\u00f8jelsen, mod 5 til 10&nbsp;% for kulhydrater og 0 til 3&nbsp;% for fedt.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>Beregner MyFitnessPal TEF&nbsp;?<\/summary><div class=\"faq-body\"><p>Nej. MyFitnessPal, Yazio, Cronometer og de fleste kalorie-apps integrerer ikke TEF i deres forbrugsberegning. De bruger en fast aktivitetskoefficient (PAL) anvendt p\u00e5 BMR, som skal \u00abomfatte\u00bb ford\u00f8jelsen. I praksis afspejler koefficienten ikke din makrosammens\u00e6tning den dag.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>Hvordan beregner Lean TEF&nbsp;?<\/summary><div class=\"faq-body\"><p>Lean anvender de videnskabelige koefficienter p\u00e5 hvert logget m\u00e5ltid: <b>P &times; 25&nbsp;% + K &times; 8&nbsp;% + F &times; 2&nbsp;%<\/b>. Resultatet integreres i realtid i din TDEE for dagen. P\u00e5 et m\u00e5ltid p\u00e5 537&nbsp;kcal (54&nbsp;g P, 55&nbsp;g K, 12&nbsp;g F) beregner Lean 74&nbsp;kcal TEF.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>Hvor mange kalorier udg\u00f8r TEF om dagen&nbsp;?<\/summary><div class=\"faq-body\"><p>P\u00e5 en kost med 2&nbsp;000 til 2&nbsp;500&nbsp;kcal udg\u00f8r TEF mellem 160 og 250&nbsp;kcal afh\u00e6ngigt af din makrosammens\u00e6tning. Over et \u00e5r er det 58&nbsp;000 til 91&nbsp;000&nbsp;kcal forbrug ignoreret af apps, der ikke beregner den.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>Falder TEF i kalorieunderskud&nbsp;?<\/summary><div class=\"faq-body\"><p>Ja, proportionalt: spiser du f\u00e6rre kalorier, ford\u00f8jer du mindre, og den absolutte TEF falder. Men <b>procentdelen<\/b> forbliver stabil efter dine makroer. I underskud bevarer et h\u00f8jt proteinindtag forholdet TEF\/indtag, ud over at bevare muskelmassen.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>Er TEF det samme som det postprandiale aktive stofskifte&nbsp;?<\/summary><div class=\"faq-body\"><p>Ja, de to begreber betegner samme virkelighed: energien forbr\u00e6ndt af ford\u00f8jelsen. TEF (Thermic Effect of Food) er den mest brugte engelske betegnelse. DIT (Diet-Induced Thermogenesis) eller SDA (Specific Dynamic Action) er de tilsvarende i den europ\u00e6iske litteratur.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>Har forarbejdede f\u00f8devarer en lavere TEF&nbsp;?<\/summary><div class=\"faq-body\"><p>Ja. Barr &amp; Wright (2010, PMID&nbsp;20613941) m\u00e5lte, at m\u00e5ltider baseret p\u00e5 hele f\u00f8devarer genererer en TEF cirka 50&nbsp;% h\u00f8jere end kalorie\u00e6kvivalente m\u00e5ltider baseret p\u00e5 forarbejdede f\u00f8devarer. Forarbejdede f\u00f8devarer er allerede delvist \u00abforford\u00f8jet\u00bb industrielt, hvilket reducerer ford\u00f8jelsesarbejdet og dermed 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>Beregn din TEF p\u00e5 dine reelle makroer<\/h3>\n  <p>P &times; 25&nbsp;% + K &times; 8&nbsp;% + F &times; 2&nbsp;%, p\u00e5 hvert logget m\u00e5ltid. TDEE = BMR + NEAT + EAT + TEF. Patenteret egenudviklet model. 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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. 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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-v16 -->\n<aside class=\"lean-mesh\" style=\"margin:48px auto;max-width:760px;padding:24px 28px;background:#ffffff;border-left:4px solid #FF2D6E;border-radius:0 12px 12px 0;box-shadow:0 6px 24px rgba(20,20,40,0.06);font-family:-apple-system,'SF Pro Text','Segoe UI',Roboto,Arial,sans-serif;color:#1a1a2e;\"><p style=\"margin:0 0 14px;font-size:13px;font-weight:700;letter-spacing:0.06em;text-transform:uppercase;color:#FF2D6E;\">\u00c0 lire aussi<\/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\/da\/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;\">M\u00e9tabolisme de base (BMR) : tout ce qu&rsquo;il faut savoir pour le calculer <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">D\u00e9finition, \u00e9quation TDEE, 4 formules historiques, pourquoi le bodyfat change tout.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/da\/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;\">D\u00e9pense \u00e9nerg\u00e9tique totale (TDEE) : la formule canonique BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Comprends les 4 briques + l&rsquo;adaptation m\u00e9tabolique, sources scientifiques 2025.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/da\/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 : la d\u00e9pense calorique non sportive qui p\u00e8se 15 \u00e0 50% de ton TDEE <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Pas, d\u00e9placements, fidget. Pourquoi Mifflin se trompe en ignorant ton activit\u00e9.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/da\/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 : ta d\u00e9pense sportive vraie, s\u00e9ance par s\u00e9ance <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Les MET corrects, le pi\u00e8ge du double comptage, ce que Garmin et MyFitnessPal ratent.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/da\/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;\">Meilleures applications pour compter les calories en 2026 : 8 apps test\u00e9es <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\/da\/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;\">Quelle alternative \u00e0 MyFitnessPal en 2026 ? 5 apps test\u00e9es <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Comparatif honn\u00eate, pr\u00e9cision TDEE, ergonomie.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/da\/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=\"https:\/\/lean-app.com\/da\/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>Madens termiske effekt (TEF): hvorfor Lean beregner 69 kcal, som de andre apps ignorerer - Lean<\/title>\n<meta name=\"description\" content=\"L&#039;effet thermique des aliments (TEF), c&#039;est 10 % de tes calories br\u00fbl\u00e9es rien qu&#039;en dig\u00e9rant. 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