{"id":1675,"date":"2026-05-28T08:21:54","date_gmt":"2026-05-28T08:21:54","guid":{"rendered":"https:\/\/lean-app.com\/?p=1675"},"modified":"2026-09-08T18:17:32","modified_gmt":"2026-09-08T18:17:32","slug":"effet-thermique-des-aliments","status":"publish","type":"post","link":"https:\/\/lean-app.com\/es\/effet-thermique-des-aliments\/","title":{"rendered":"Efecto t\u00e9rmico de los alimentos (TEF): por qu\u00e9 Lean calcula 69 kcal que las otras apps ignoran"},"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 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.phone-stage{position:relative}\n#lvm-shell .tap-hint{position:absolute;z-index:30;pointer-events:none;animation:hintFloat 2.6s ease-in-out infinite}\n#lvm-shell .tap-hint .th-pill{display:inline-block;font-family:var(--font-display);font-size:15px;font-weight:600;color:#fff;line-height:1.25;letter-spacing:-.005em;background:var(--pink);padding:10px 16px;border-radius:14px;box-shadow:0 14px 32px rgba(255,45,110,.32);white-space:nowrap}\n#lvm-shell .tap-hint .th-pill small{display:block;font-size:11px;font-weight:500;color:rgba(255,255,255,.85);text-transform:uppercase;letter-spacing:.08em;margin-bottom:3px}\n#lvm-shell .tap-hint .th-arrow{position:absolute;color:var(--pink)}\n#lvm-shell .tap-hint.desktop{left:-204px;top:4px;text-align:right}\n#lvm-shell .tap-hint.desktop .th-arrow{right:-86px;top:58px;width:104px;height:34px;transform:none}\n#lvm-shell .tap-hint.mobile{display:none}\n#lvm-shell .tap-hint.hidden{opacity:0;transform:translateY(-6px);transition:opacity .35s ease, 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.lbl{font-family:var(--font-mono);font-size:11px;font-weight:500;text-transform:uppercase;letter-spacing:.08em;color:var(--muted);margin-bottom:14px}\n#lvm-shell .snippet p{margin:0;font-family:var(--font-display);font-size:21px;line-height:1.45;color:var(--ink);font-weight:500;letter-spacing:-.012em}\n\n#lvm-shell section{padding:64px 0;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell section:last-of-type{border-bottom:0}\n#lvm-shell .section-label{display:flex;align-items:center;gap:14px;margin-bottom:30px}\n#lvm-shell .section-label .bar{width:24px;height:1px;background:var(--pink)}\n#lvm-shell .section-label .num{font-family:var(--font-mono);font-size:12px;font-weight:500;text-transform:uppercase;letter-spacing:.06em;color:var(--pink)}\n#lvm-shell h2{font-family:var(--font-display);font-weight:600;font-size:48px;line-height:1.05;letter-spacing:-.035em;color:var(--ink);margin:0 0 24px}\n#lvm-shell 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.fig-cap strong{color:var(--ink);font-weight:600}\n#lvm-shell .cv-wrap{position:relative;height:360px}\n\n#lvm-shell [data-term]{position:relative;cursor:help;border-bottom:1px dotted var(--dim)}\n#lvm-shell [data-term]:hover{color:var(--ink)}\n#lvm-shell .tt{position:absolute;left:50%;bottom:calc(100% + 12px);transform:translateX(-50%);min-width:200px;max-width:300px;background:#0c0c0c;color:#fff;font-size:13px;line-height:1.45;padding:11px 14px;border-radius:10px;box-shadow:0 12px 36px rgba(0,0,0,.32);opacity:0;visibility:hidden;transition:opacity .15s, visibility .15s;z-index:120;pointer-events:none;font-weight:400;font-family:var(--font-text)}\n#lvm-shell .tt::after{content:\"\";position:absolute;top:100%;left:50%;transform:translateX(-50%);border:6px solid transparent;border-top-color:#0c0c0c}\n#lvm-shell [data-term]:hover .tt, #lvm-shell [data-term]:focus .tt{opacity:1;visibility:visible}\n\n#lvm-shell .table{margin:24px 0;border:1px solid var(--rule);border-radius:16px;overflow:hidden;background:#fff}\n#lvm-shell .table-row{display:grid;grid-template-columns:1.55fr 1fr 1fr;border-bottom:1px solid var(--rule-soft);min-height:60px}\n#lvm-shell .table-row:last-child{border-bottom:0}\n#lvm-shell .table-row.head{background:var(--ink);color:#fff;border-bottom:0}\n#lvm-shell .table-row.head > div{padding:18px 18px;display:flex;align-items:center;gap:10px;font-family:var(--font-mono);font-size:11px;font-weight:500;text-transform:uppercase;letter-spacing:.07em}\n#lvm-shell .table-row.head .brand-cell{justify-content:flex-start}\n#lvm-shell .table-row.head .brand-cell img{width:24px;height:24px;border-radius:6px;background:#fff;object-fit:cover}\n#lvm-shell .table-row.head .brand-cell.lean{color:#FFB8CE}\n#lvm-shell .table-row > .crit{padding:16px 18px;font-size:14px;color:var(--ink);font-weight:500;display:flex;align-items:center;border-right:1px solid var(--rule-soft)}\n#lvm-shell .table-row > .cell{padding:16px 14px;font-size:13px;line-height:1.45;color:var(--ink-2);display:flex;align-items:center;gap:10px;border-right:1px solid var(--rule-soft)}\n#lvm-shell .table-row > .cell:last-child{border-right:0}\n#lvm-shell .table-row > .cell.lean{background:var(--pink-soft);position:relative}\n#lvm-shell .table-row > .cell.lean::before{content:\"\";position:absolute;left:0;top:0;bottom:0;width:2px;background:var(--pink)}\n#lvm-shell .icn{width:18px;height:18px;border-radius:50%;display:inline-flex;align-items:center;justify-content:center;flex-shrink:0;font-size:13px;font-weight:600;color:#fff}\n#lvm-shell .icn.ok{background:var(--green)}\n#lvm-shell .icn.no{background:var(--red)}\n#lvm-shell .icn.mid{background:var(--amber)}\n#lvm-shell .icn svg{width:11px;height:11px}\n\n#lvm-shell .mini-row{display:grid;grid-template-columns:repeat(3,1fr);gap:22px;margin:28px 0}\n#lvm-shell .mini-phone{position:relative;background:linear-gradient(145deg,#2a2a2a,#0e0e0e);border-radius:22px;padding:3px;border:1px solid rgba(255,255,255,.05);box-shadow:0 14px 32px rgba(0,0,0,.16);max-width:160px;margin:0 auto;width:100%}\n#lvm-shell .mini-phone .notch{position:absolute;top:0;left:50%;transform:translateX(-50%);width:40px;height:11px;background:#0a0a0a;border-radius:0 0 7px 7px;z-index:5}\n#lvm-shell .mini-phone .scr{border-radius:18px;overflow:hidden;background:#FAF0E6;aspect-ratio:9\/19.5}\n#lvm-shell .mini-phone .scr img{width:100%;height:100%;object-fit:cover}\n#lvm-shell .mini-phone.tiny{max-width:148px;padding:2px;border-radius:20px;border-width:1px}\n#lvm-shell .mini-phone.tiny .notch{width:30px;height:8px;border-radius:0 0 5px 5px}\n#lvm-shell .mini-phone.tiny .scr{border-radius:17px}\n#lvm-shell .mini-cap{text-align:center;margin-top:12px;font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.07em;color:var(--muted)}\n#lvm-shell .mini-cap strong{display:block;color:var(--ink);margin-top:4px;font-family:var(--font-display);font-size:14px;font-weight:500;letter-spacing:-.01em;text-transform:none}\n\n#lvm-shell .duo-row{display:grid;grid-template-columns:repeat(2,1fr);gap:20px;margin:18px 0 0}\n#lvm-shell .duo-row .mini-phone{max-width:180px}\n\n#lvm-shell .method{display:grid;grid-template-columns:1fr 1.4fr;gap:36px;align-items:center;margin:42px 0}\n#lvm-shell .method.flip{grid-template-columns:1.4fr 1fr}\n#lvm-shell .method.flip .m-phone{order:2}\n#lvm-shell .method .m-tag{font-family:var(--font-mono);font-size:11px;font-weight:600;text-transform:uppercase;letter-spacing:.08em;color:var(--pink);margin-bottom:8px}\n#lvm-shell .method h3{margin-top:0}\n#lvm-shell .method p{font-size:16px;color:var(--muted);line-height:1.7}\n\n#lvm-shell .cta-band{margin:40px 0;padding:26px 28px;background:var(--paper);border-radius:16px;display:flex;align-items:center;justify-content:space-between;gap:20px;flex-wrap:wrap;border:1px solid var(--rule-soft)}\n#lvm-shell .cta-band .l{font-family:var(--font-display);font-size:18px;line-height:1.35;font-weight:500;color:var(--ink);flex:1;min-width:240px;letter-spacing:-.01em}\n#lvm-shell .cta-band .stores{display:flex;gap:10px;align-items:center}\n#lvm-shell .cta-band .stores a{line-height:0;transition:transform .15s}\n#lvm-shell .cta-band .stores a:hover{transform:translateY(-2px)}\n#lvm-shell .cta-band .stores img{height:42px;width:auto;border-radius:9px}\n\n#lvm-shell .pyramid{margin:30px auto;max-width:440px}\n#lvm-shell .pyramid .level{margin:6px auto;padding:13px 18px;border-radius:14px;color:#fff;font-family:var(--font-display);font-weight:500;font-size:15px;letter-spacing:-.01em;display:flex;justify-content:space-between;align-items:center;box-shadow:0 6px 18px rgba(0,0,0,.06)}\n#lvm-shell .pyramid .level .k{font-family:var(--font-mono);font-size:10px;text-transform:uppercase;letter-spacing:.08em;opacity:.75}\n#lvm-shell .pyramid .l1{background:#0E0E10;width:100%}\n#lvm-shell .pyramid .l2{background:#1D1D1F;width:84%}\n#lvm-shell .pyramid .l3{background:#3a3a3c;width:68%}\n#lvm-shell .pyramid .l4{background:var(--pink);width:52%}\n#lvm-shell .pyramid-cap{text-align:center;font-size:13px;color:var(--muted);margin-top:14px}\n\n\/* Section 7 honnetete : scorecard horizontal bars *\/\n#lvm-shell .scorecard{margin:30px 0 10px;border:1px solid var(--rule);border-radius:20px;padding:28px 26px;background:#fff}\n#lvm-shell .scorecard-head{display:grid;grid-template-columns:1.4fr 1fr 1fr;column-gap:28px;align-items:center;padding-bottom:18px;margin-bottom:8px;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell .scorecard-head .h-crit{font-family:var(--font-mono);font-size:11px;font-weight:500;text-transform:uppercase;letter-spacing:.08em;color:var(--muted)}\n#lvm-shell .scorecard-head .h-brand{display:flex;align-items:center;gap:8px;font-family:var(--font-display);font-size:14px;font-weight:600;color:var(--ink)}\n#lvm-shell .scorecard-head .h-brand img{width:22px;height:22px;border-radius:5px;object-fit:cover}\n#lvm-shell .scorecard-row{display:grid;grid-template-columns:1.4fr 1fr 1fr;column-gap:28px;align-items:center;padding:14px 0;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell .scorecard-row:last-child{border-bottom:0}\n#lvm-shell .scorecard-row .crit{font-size:14px;color:var(--ink);font-weight:500;padding-right:14px}\n#lvm-shell .scorecard-row .bar{display:flex;flex-direction:row-reverse;align-items:center;gap:10px}\n#lvm-shell .scorecard-row .bar .b{flex:1;height:8px;border-radius:99px;background:var(--rule-soft);overflow:hidden;position:relative}\n#lvm-shell .scorecard-row .bar .b > i{display:block;height:100%;border-radius:99px;transition:width 1s cubic-bezier(.22,.61,.36,1)}\n#lvm-shell .scorecard-row .bar.lean .b > i{background:var(--pink)}\n#lvm-shell .scorecard-row .bar.mfp .b > i{background:var(--mfp)}\n#lvm-shell .scorecard-row .bar .v{font-family:var(--font-mono);font-size:12px;font-weight:600;color:var(--ink);min-width:32px;text-align:left}\n\n\/* Section 8 pour qui : persona checklist *\/\n#lvm-shell .persona{margin:28px 0 10px;display:grid;grid-template-columns:1fr;gap:14px}\n#lvm-shell .persona-it{display:grid;grid-template-columns:54px 1fr;gap:16px;padding:22px 24px;background:#fff;border:1px solid var(--rule);border-radius:18px;align-items:center}\n#lvm-shell .persona-it.match{background:var(--pink-soft);border-color:rgba(255,45,110,.25)}\n#lvm-shell .persona-it .pic{width:54px;height:54px;border-radius:50%;display:flex;align-items:center;justify-content:center;background:var(--rule-soft);position:relative;font-family:var(--font-mono);font-size:13px;font-weight:600;color:var(--ink)}\n#lvm-shell .persona-it.match .pic{background:var(--pink);color:#fff}\n#lvm-shell .persona-it .pic svg{width:24px;height:24px}\n#lvm-shell .persona-it h4{margin:0 0 4px;font-size:17px;letter-spacing:-.01em}\n#lvm-shell .persona-it p{margin:0;font-size:14px;color:var(--muted);line-height:1.55}\n#lvm-shell .persona-it.match h4{color:var(--ink)}\n\n\/* Section 9 migration : timeline steps *\/\n#lvm-shell .steps{display:grid;grid-template-columns:repeat(5,1fr);gap:14px;margin:28px 0;position:relative}\n#lvm-shell .steps::before{content:\"\";position:absolute;top:14px;left:7px;right:calc(20% - 18px);height:1px;background:linear-gradient(90deg,var(--pink) 0%,var(--rule-soft) 100%);z-index:0}\n#lvm-shell .step{position:relative;padding-top:24px;z-index:1}\n#lvm-shell .step::before{content:\"\";position:absolute;top:8px;left:0;width:14px;height:14px;border-radius:50%;background:var(--pink);border:3px solid #fff;box-shadow:0 0 0 1px var(--rule)}\n#lvm-shell .step .sn{font-family:var(--font-mono);font-size:11px;color:var(--pink);font-weight:600;letter-spacing:.08em}\n#lvm-shell .step h4{margin:6px 0 6px;font-size:15px;letter-spacing:-.01em}\n#lvm-shell .step p{font-size:13px;color:var(--muted);line-height:1.5;margin:0}\n\n\/* Section 10 debloque : feature stack numbered XL *\/\n#lvm-shell .feat-stack{margin:30px 0 10px;border-top:1px solid var(--rule)}\n#lvm-shell .feat-it{display:grid;grid-template-columns:auto 1fr auto;gap:24px;padding:26px 0;border-bottom:1px solid var(--rule);align-items:center}\n#lvm-shell .feat-it .fn{font-family:var(--font-display);font-size:48px;font-weight:600;color:var(--pink);line-height:1;letter-spacing:-.04em;width:74px}\n#lvm-shell .feat-it .ft{font-family:var(--font-display);font-size:22px;font-weight:600;color:var(--ink);letter-spacing:-.015em;line-height:1.25;margin-bottom:6px}\n#lvm-shell .feat-it .fd{font-size:15px;color:var(--muted);line-height:1.55;margin:0}\n#lvm-shell .feat-it .fc{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.08em;color:var(--muted);font-weight:500}\n#lvm-shell .feat-it:last-child{border-bottom:0}\n\n#lvm-shell .faq{margin:22px 0}\n#lvm-shell .faq details{border-bottom:1px solid var(--rule);padding:20px 0}\n#lvm-shell .faq details:first-of-type{border-top:1px solid var(--rule)}\n#lvm-shell .faq summary{cursor:pointer;list-style:none;display:flex;justify-content:space-between;align-items:center;gap:18px;font-family:var(--font-display);font-size:20px;font-weight:500;letter-spacing:-.015em;color:var(--ink)}\n#lvm-shell .faq summary::-webkit-details-marker{display:none}\n#lvm-shell .faq summary::after{content:\"+\";font-size:24px;color:var(--muted);font-weight:300;line-height:1;transition:transform .25s, color .25s}\n#lvm-shell .faq details[open] summary::after{transform:rotate(45deg);color:var(--pink)}\n#lvm-shell .faq details[open] summary{color:var(--pink)}\n#lvm-shell .faq .ans{margin-top:14px;font-size:16px;color:var(--muted);line-height:1.65}\n\n#lvm-shell .get-band{background:var(--paper-2);border-radius:24px;padding:48px 36px;margin:60px 0 40px;text-align:center}\n#lvm-shell .get-band .kicker{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;color:var(--pink);font-weight:600;letter-spacing:.1em;margin-bottom:14px}\n#lvm-shell .get-band h3{font-size:36px;margin:0 0 14px;letter-spacing:-.025em}\n#lvm-shell .get-band p{font-size:16px;color:var(--muted);max-width:480px;margin:0 auto 26px}\n#lvm-shell .get-band .stores{display:flex;justify-content:center;gap:14px;flex-wrap:wrap}\n#lvm-shell .get-band .stores a{line-height:0;transition:transform .15s}\n#lvm-shell .get-band .stores a:hover{transform:translateY(-3px)}\n#lvm-shell .get-band .stores img{height:60px;width:auto;border-radius:11px}\n\n#lvm-shell .sources{font-size:14px;color:var(--muted);line-height:1.7}\n#lvm-shell .sources ol{padding-left:22px}\n#lvm-shell .sources li{margin-bottom:8px}\n\n#lvm-shell footer{padding:50px 0 60px;border-top:1px solid var(--rule);margin-top:40px}\n#lvm-shell footer .row{display:flex;justify-content:space-between;align-items:center;gap:18px;flex-wrap:wrap}\n#lvm-shell footer .kicker{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.08em;color:var(--pink);font-weight:600}\n#lvm-shell footer p{font-size:13px;color:var(--muted);margin:8px 0 0}\n#lvm-shell footer .stores{display:flex;gap:8px}\n#lvm-shell footer .stores img{height:34px;width:auto;border-radius:6px}\n\n#lvm-shell .rev{opacity:0;transform:translateY(12px);transition:opacity .8s cubic-bezier(.22,.61,.36,1),transform .8s cubic-bezier(.22,.61,.36,1)}\n#lvm-shell .rev.on{opacity:1;transform:translateY(0)}\n@media (prefers-reduced-motion:reduce){#lvm-shell .rev{transition:none;opacity:1;transform:none}}\n\n@media (max-width:760px){\n  #lvm-shell .nav-row{padding:8px 18px;gap:8px}\n  #lvm-shell .nav-link{display:none}\n  #lvm-shell .nav-stores img{height:24px}\n  #lvm-shell .wrap{padding:0 22px}\n  #lvm-shell .hero{padding:34px 0 0}\n  #lvm-shell h1{font-size:46px;letter-spacing:-.035em}\n  #lvm-shell h1 .alt{font-size:.55em;margin-top:10px}\n  #lvm-shell .dek{font-size:20px}\n  #lvm-shell .hero-stores img{height:42px}\n  #lvm-shell .hero-bottom{grid-template-columns:1fr;gap:28px;margin:30px 0 40px;padding-top:24px;align-items:stretch}\n  #lvm-shell .phone-wrap{order:-1}\n  #lvm-shell .phone{width:240px}\n  #lvm-shell .tap-hint.desktop{display:none}\n  #lvm-shell .tap-hint.mobile{display:block;position:relative;left:auto;top:auto;text-align:center;margin:0 auto 10px;width:100%}\n  #lvm-shell .tap-hint.mobile .th-arrow{position:relative;display:block;margin:6px auto 0;width:34px;height:34px;transform:none;color:var(--pink)}\n  #lvm-shell .snippet{padding:24px 22px}\n  #lvm-shell .snippet p{font-size:18px}\n  #lvm-shell section{padding:48px 0}\n  #lvm-shell h2{font-size:34px;letter-spacing:-.03em}\n  #lvm-shell h3{font-size:24px}\n  #lvm-shell .section-label{margin-bottom:22px}\n  #lvm-shell .statement{padding:24px 0;margin:32px 0}\n  #lvm-shell .statement .num{font-size:44px}\n  #lvm-shell .statement .lbl{font-size:19px}\n  #lvm-shell .fig{padding:20px 14px 14px;border-radius:16px}\n  #lvm-shell .cv-wrap{height:310px}\n  #lvm-shell .method{grid-template-columns:1fr;gap:20px}\n  #lvm-shell .method.flip{grid-template-columns:1fr}\n  #lvm-shell .method.flip .m-phone{order:0}\n  #lvm-shell .mini-row{grid-template-columns:repeat(3,1fr);gap:10px}\n  #lvm-shell .mini-phone{padding:3px;border-radius:18px;border-width:1px;max-width:110px}\n  #lvm-shell .mini-phone .notch{width:42px;height:11px;border-radius:0 0 8px 8px}\n  #lvm-shell .mini-phone .scr{border-radius:15px}\n  #lvm-shell .mini-cap{font-size:10px}\n  #lvm-shell .mini-cap strong{font-size:13px}\n  #lvm-shell .duo-row{grid-template-columns:repeat(2,1fr);gap:12px}\n  #lvm-shell .duo-row .mini-phone{max-width:130px}\n  #lvm-shell .steps{grid-template-columns:1fr;gap:18px}\n  #lvm-shell .steps::before{display:none}\n  #lvm-shell .step{padding-top:0;padding-left:24px}\n  #lvm-shell .step::before{top:6px;left:0}\n  #lvm-shell .table-row{grid-template-columns:1.4fr .9fr .9fr}\n  #lvm-shell .table-row > .crit{padding:13px 12px;font-size:13px}\n  #lvm-shell .table-row > .cell{padding:13px 10px;font-size:12px;gap:8px}\n  #lvm-shell .table-row.head > div{padding:14px 12px;font-size:10px;gap:7px}\n  #lvm-shell .table-row.head .brand-cell img{width:20px;height:20px}\n  #lvm-shell .get-band{padding:36px 22px;border-radius:18px;margin:40px 0 30px}\n  #lvm-shell .get-band h3{font-size:28px}\n  #lvm-shell .get-band .stores img{height:50px}\n  #lvm-shell .cta-band{padding:22px;gap:14px}\n  #lvm-shell .cta-band .l{font-size:16px;min-width:0}\n  #lvm-shell .cta-band .stores img{height:38px}\n  #lvm-shell .faq summary{font-size:18px;gap:14px}\n  #lvm-shell .pyramid{max-width:100%}\n  #lvm-shell .pyramid .level{padding:11px 14px;font-size:14px}\n  #lvm-shell .scorecard{padding:20px 16px;border-radius:16px}\n  #lvm-shell .scorecard-head{grid-template-columns:1.2fr 1fr 1fr;column-gap:14px}\n  #lvm-shell .scorecard-head .h-brand{font-size:12px;gap:5px}\n  #lvm-shell .scorecard-head .h-brand img{width:18px;height:18px}\n  #lvm-shell .scorecard-row{grid-template-columns:1.2fr 1fr 1fr;column-gap:14px;padding:12px 0}\n  #lvm-shell .scorecard-row .crit{font-size:13px;padding-right:8px}\n  #lvm-shell .scorecard-row .bar{gap:6px}\n  #lvm-shell .scorecard-row .bar .v{font-size:11px;min-width:26px}\n  #lvm-shell .persona-it{grid-template-columns:44px 1fr;gap:12px;padding:16px 16px;border-radius:14px}\n  #lvm-shell .persona-it .pic{width:44px;height:44px;font-size:12px}\n  #lvm-shell .persona-it h4{font-size:15px}\n  #lvm-shell .persona-it p{font-size:13px}\n  #lvm-shell .feat-it{grid-template-columns:auto 1fr;gap:14px;padding:20px 0}\n  #lvm-shell .feat-it .fn{font-size:36px;width:54px}\n  #lvm-shell .feat-it .ft{font-size:18px}\n  #lvm-shell .feat-it .fd{font-size:13px}\n  #lvm-shell .feat-it .fc{display:none}\n}\n@media (max-width:480px){\n  #lvm-shell .phone-tabs{gap:5px}\n  #lvm-shell .phone-tabs button{padding:5px 8px;font-size:10px}\n  #lvm-shell .nav-stores{gap:4px}\n  #lvm-shell .nav-stores img{height:22px}\n  #lvm-shell .hero-stores img{height:40px}\n  #lvm-shell .crumb{font-size:12px}\n  #lvm-shell .table-row{grid-template-columns:1.3fr .85fr .85fr}\n  #lvm-shell .table-row > .crit{padding:11px 9px;font-size:12px}\n  #lvm-shell .table-row > .cell{padding:11px 8px;font-size:11px;gap:6px}\n  #lvm-shell .table-row.head > div{padding:11px 9px;font-size:9px;gap:5px}\n}\n\n\/* Calculator-specific styles, scoped #lvm-shell *\/\n#lvm-shell .calc-board{display:grid;grid-template-columns:1fr;gap:18px;margin:32px 0}\n@media(min-width:780px){#lvm-shell .calc-board{grid-template-columns:1fr 1fr;gap:24px}}\n#lvm-shell .calc-inputs{background:#FAF7F2;border-radius:14px;padding:22px;border:1px solid var(--rule-soft)}\n#lvm-shell .calc-inputs h3{font-family:var(--font-display);font-size:18px;font-weight:600;margin:0 0 16px;color:var(--ink);letter-spacing:-.01em}\n#lvm-shell .calc-row{margin:0 0 14px}\n#lvm-shell .calc-row label{display:block;font-size:13px;color:var(--muted);margin-bottom:6px;font-weight:500}\n#lvm-shell .calc-row input,#lvm-shell .calc-row select{width:100%;padding:11px 13px;border:1px solid var(--rule);border-radius:9px;font-size:16px;background:#fff;color:var(--ink);font-family:var(--font-text);box-sizing:border-box}\n#lvm-shell .calc-row input:focus,#lvm-shell .calc-row select:focus{outline:2px solid var(--pink);outline-offset:1px;border-color:var(--pink)}\n#lvm-shell .calc-sex{display:flex;gap:8px}\n#lvm-shell .calc-sex label{flex:1;display:flex;align-items:center;justify-content:center;gap:6px;padding:11px 8px;background:#fff;border:1px solid var(--rule);border-radius:9px;cursor:pointer;margin:0;font-size:14px;font-weight:500;color:var(--ink)}\n#lvm-shell .calc-sex input{display:none}\n#lvm-shell .calc-sex input:checked + span{color:var(--pink);font-weight:600}\n#lvm-shell .calc-sex label:has(input:checked){border-color:var(--pink);background:var(--pink-soft)}\n#lvm-shell .calc-bf{display:flex;align-items:center;gap:10px}\n#lvm-shell .calc-bf input[type=range]{flex:1;accent-color:var(--pink);height:6px}\n#lvm-shell .calc-bf .bf-val{font-weight:600;color:var(--pink);min-width:42px;font-family:var(--font-mono);font-size:15px}\n#lvm-shell .calc-results{display:grid;grid-template-columns:1fr;gap:12px}\n#lvm-shell .calc-card{background:#fff;border:1px solid var(--rule);border-radius:14px;padding:18px 20px}\n#lvm-shell .calc-card.lean{border-left:4px solid var(--pink);background:linear-gradient(90deg,var(--pink-soft),#fff 30%)}\n#lvm-shell .calc-card .label{font-size:11px;font-weight:600;text-transform:uppercase;letter-spacing:.08em;color:var(--muted);font-family:var(--font-mono)}\n#lvm-shell .calc-card .formula{font-size:13px;color:var(--dim);margin-top:2px}\n#lvm-shell .calc-card .result{font-family:var(--font-display);font-size:34px;font-weight:600;letter-spacing:-.025em;margin-top:8px;color:var(--ink);line-height:1}\n#lvm-shell .calc-card .result .unit{font-size:14px;font-weight:500;color:var(--muted);margin-left:6px;letter-spacing:0}\n#lvm-shell .calc-card.lean .result{color:var(--pink)}\n#lvm-shell .calc-delta{margin-top:10px;padding:12px 14px;background:#fff;border:1px dashed var(--pink);border-radius:10px;font-size:14px;color:var(--ink)}\n#lvm-shell .calc-delta b{color:var(--pink);font-family:var(--font-mono)}\n#lvm-shell .calc-note{margin-top:14px;font-size:13px;color:var(--muted);line-height:1.5}\n#lvm-shell .calc-note a{color:var(--pink);text-decoration:underline}\n\n\/* Statement block *\/\n#lvm-shell .statement{margin:54px 0;padding:48px 32px;background:#FAF7F2;border-radius:18px;text-align:center}\n#lvm-shell .statement p{font-family:var(--font-display);font-size:34px;line-height:1.2;font-weight:500;letter-spacing:-.025em;color:var(--ink);margin:0;max-width:680px;margin-inline:auto}\n#lvm-shell .statement .accent{color:var(--pink)}\n@media(max-width:640px){#lvm-shell .statement{padding:38px 22px}#lvm-shell .statement p{font-size:24px}}\n\n\/* Profil cards (no scrollable table) *\/\n#lvm-shell .profile-grid{display:grid;grid-template-columns:1fr;gap:16px;margin:32px 0}\n#lvm-shell .profile-card{background:#fff;border:1px solid var(--rule);border-radius:14px;padding:20px 22px}\n#lvm-shell .profile-card h4{font-family:var(--font-display);font-size:17px;font-weight:600;margin:0 0 4px;color:var(--ink)}\n#lvm-shell .profile-card .meta{font-size:13px;color:var(--muted);margin-bottom:14px}\n#lvm-shell .profile-card .rows{display:grid;grid-template-columns:1fr;gap:6px}\n#lvm-shell .profile-card .rw{display:grid;grid-template-columns:1fr auto;gap:10px;padding:8px 12px;background:#FAF7F2;border-radius:8px;font-size:14px;align-items:center}\n#lvm-shell .profile-card .rw .v{font-family:var(--font-mono);font-weight:600;color:var(--ink);font-size:13px}\n#lvm-shell .profile-card .rw.lean{background:var(--pink-soft);border-left:3px solid var(--pink)}\n#lvm-shell .profile-card .rw.lean .v{color:var(--pink)}\n#lvm-shell .profile-card .delta{font-size:12px;color:var(--dim);margin-top:8px}\n\n\/* Comparator cards (3 formulas pros\/cons) *\/\n#lvm-shell .compar-grid{display:grid;grid-template-columns:1fr;gap:16px;margin:24px 0}\n#lvm-shell .compar-card{background:#fff;border:1px solid var(--rule);border-radius:14px;padding:22px}\n#lvm-shell .compar-card.lean{border-left:4px solid var(--pink)}\n#lvm-shell .compar-card h4{font-family:var(--font-display);font-size:18px;font-weight:600;margin:0 0 4px;color:var(--ink)}\n#lvm-shell .compar-card .year{font-size:12px;color:var(--muted);font-family:var(--font-mono);margin-bottom:14px;letter-spacing:.04em}\n#lvm-shell .compar-card .desc{font-size:14px;line-height:1.55;color:var(--ink-2);margin:0 0 12px}\n#lvm-shell .compar-card .pros,#lvm-shell .compar-card .cons{margin:6px 0;font-size:13px;line-height:1.5}\n#lvm-shell .compar-card .pros{color:var(--green)}\n#lvm-shell .compar-card .cons{color:var(--red)}\n#lvm-shell .compar-card .pros b,#lvm-shell .compar-card .cons b{display:inline-block;width:18px}\n\n\/* Pyramide section *\/\n#lvm-shell .pyramide-illust{margin:40px auto 8px;display:flex;flex-direction:column;align-items:center;gap:14px;max-width:220px}\n#lvm-shell .pyramide-illust img{width:100%;border-radius:18px;box-shadow:0 12px 32px rgba(20,20,40,.12)}\n#lvm-shell .pyramide-cap{font-size:13px;color:var(--muted);text-align:center;line-height:1.5}\n#lvm-shell .pyramide-cap b{display:block;color:var(--ink);font-weight:600;margin-bottom:3px}\n\n\/* FAQ details *\/\n#lvm-shell details.faq{background:#fff;border:1px solid var(--rule);border-radius:10px;margin:8px 0;overflow:hidden}\n#lvm-shell details.faq summary{padding:16px 20px;font-weight:600;font-size:16px;color:var(--ink);cursor:pointer;list-style:none;position:relative;padding-right:48px;font-family:var(--font-display);letter-spacing:-.01em}\n#lvm-shell details.faq summary::-webkit-details-marker{display:none}\n#lvm-shell details.faq summary::after{content:\"+\";position:absolute;right:20px;top:50%;transform:translateY(-50%);color:var(--pink);font-size:22px;font-weight:300;line-height:1}\n#lvm-shell details.faq[open] summary::after{content:\"\u2212\"}\n#lvm-shell details.faq .faq-body{padding:0 20px 18px;font-size:15px;line-height:1.65;color:var(--ink-2)}\n#lvm-shell details.faq .faq-body p{margin:0 0 8px}\n\n\/* Sources *\/\n#lvm-shell .sources{margin:48px 0 32px;padding:24px;background:#FAF7F2;border-radius:14px;font-size:13px;line-height:1.6;color:var(--muted)}\n#lvm-shell .sources h4{font-family:var(--font-display);font-size:14px;font-weight:600;margin:0 0 10px;color:var(--ink);text-transform:uppercase;letter-spacing:.06em}\n#lvm-shell .sources a{color:var(--pink);text-decoration:none}\n#lvm-shell .sources a:hover{text-decoration:underline}\n#lvm-shell .sources ol{margin:0;padding-left:22px}\n#lvm-shell .sources li{margin:4px 0}\n\n\/* BodyScan illust *\/\n#lvm-shell .bodyscan-illust{margin:40px auto 8px;display:flex;flex-direction:column;align-items:center;gap:14px;max-width:220px}\n#lvm-shell .bodyscan-illust .mini-phone{max-width:200px;padding:3px;border:1px solid rgba(255,255,255,.07);border-radius:22px;background:linear-gradient(145deg,#2a2a2a,#0e0e0e);box-shadow:0 18px 36px rgba(0,0,0,.14);position:relative}\n#lvm-shell .bodyscan-illust .mini-phone .notch{position:absolute;top:0;left:50%;transform:translateX(-50%);width:40px;height:11px;background:#0a0a0a;border-radius:0 0 7px 7px;z-index:5}\n#lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:18px;overflow:hidden;background:#FAF0E6;aspect-ratio:9\/19.5}\n#lvm-shell .bodyscan-illust .mini-phone .scr img{width:100%;height:100%;object-fit:cover;display:block}\n#lvm-shell .bodyscan-cap{font-size:13px;color:var(--muted);text-align:center;line-height:1.5}\n#lvm-shell .bodyscan-cap b{display:block;color:var(--ink);font-weight:600;margin-bottom:3px}\n\n\/* Body copy paragraphs *\/\n#lvm-shell h2.sect{font-family:var(--font-display);font-size:34px;font-weight:600;letter-spacing:-.03em;margin:64px 0 16px;line-height:1.15;color:var(--ink)}\n#lvm-shell h2.sect .num{font-family:var(--font-mono);font-size:13px;font-weight:500;color:var(--pink);display:block;text-transform:uppercase;letter-spacing:.08em;margin-bottom:6px;-webkit-font-smoothing:antialiased}\n#lvm-shell h3.sub{font-family:var(--font-display);font-size:22px;font-weight:600;margin:32px 0 12px;color:var(--ink);letter-spacing:-.015em}\n#lvm-shell .body p{margin:0 0 18px;font-size:17px;line-height:1.7;color:var(--ink-2)}\n#lvm-shell .body p b{color:var(--ink);font-weight:600}\n\n\/* CTA band *\/\n#lvm-shell .get-band{margin:48px 0 24px;padding:42px 32px;background:linear-gradient(135deg,#fff,#FAF7F2);border:1px solid var(--rule);border-radius:18px;text-align:center}\n#lvm-shell .get-band h3{font-family:var(--font-display);font-size:30px;font-weight:600;margin:0 0 6px;color:var(--ink);letter-spacing:-.025em}\n#lvm-shell .get-band p{margin:0 0 22px;font-size:16px;color:var(--muted);line-height:1.5}\n#lvm-shell .get-band .stores{display:flex;gap:12px;justify-content:center;flex-wrap:wrap;align-items:center}\n#lvm-shell .get-band .stores img{height:54px;width:auto;border-radius:10px}\n@media(max-width:640px){#lvm-shell .get-band h3{font-size:22px}}\n\n#lvm-shell .micro-cta{margin:24px 0;padding:18px 22px;background:var(--pink-soft);border-left:3px solid var(--pink);border-radius:0 10px 10px 0;font-size:15px;line-height:1.55}\n#lvm-shell .micro-cta a{color:var(--pink);font-weight:600;text-decoration:none}\n#lvm-shell .micro-cta a:hover{text-decoration:underline}\n<\/style>\n\n<style id=\"lvm-collision-reset\">\n\/* Hard reset for global theme styles *\/\nbody.postid-1675 #lvm-shell .hero{display:block!important;align-items:initial!important;justify-content:initial!important;text-align:left!important;flex-direction:initial!important;padding:54px 0 0!important}\nbody.postid-1675 #lvm-shell .wrap,\nbody.postid-1675 #lvm-shell main.wrap{display:block!important;max-width:760px!important;margin-left:auto!important;margin-right:auto!important;padding-left:28px!important;padding-right:28px!important}\n@media (max-width:820px){\n  body.postid-1675 #lvm-shell .wrap,\n  body.postid-1675 #lvm-shell main.wrap{padding-left:18px!important;padding-right:18px!important}\n}\nhtml, body{overflow-x:hidden!important}\nbody.postid-1675 #lvm-shell{overflow-x:hidden;max-width:100vw}\nbody.postid-1675 #lvm-shell *{max-width:100%}\nbody.postid-1675 #lvm-shell .nav-row{max-width:100vw;box-sizing:border-box}\nbody.postid-1675 #lvm-shell.force-show .rev{opacity:1!important;transform:none!important}\n\n\/* === A.1 PHONE BACKGROUND CLASSES === *\/\nbody.postid-1675 #lvm-shell .phone-bg{position:absolute;inset:0;width:100%;height:100%;background-size:cover;background-position:center top;background-repeat:no-repeat;transition:opacity .28s ease;background-color:#FAF0E6}\nbody.postid-1675 #lvm-shell .phone-bg.tab-depense{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp)}\nbody.postid-1675 #lvm-shell .phone-bg.tab-bilan{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp)}\nbody.postid-1675 #lvm-shell .phone-bg.tab-kcal{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp)}\nbody.postid-1675 #lvm-shell .phone-bg.tab-strategie{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp)}\nbody.postid-1675 #lvm-shell .phone-bg.sub-BMR{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp)}\nbody.postid-1675 #lvm-shell .phone-bg.sub-NEAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp)}\nbody.postid-1675 #lvm-shell .phone-bg.sub-EAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp)}\nbody.postid-1675 #lvm-shell .phone-bg.sub-TEF{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp)}\n\n\/* === CTA BANDS MOBILE === *\/\n@media (max-width:760px){\n  body.postid-1675 #lvm-shell .cta-band{flex-direction:column!important;align-items:center!important;text-align:center!important;padding:26px 22px!important;gap:20px!important}\n  body.postid-1675 #lvm-shell .cta-band .l{min-width:0!important;width:100%!important;font-size:16px!important;line-height:1.5!important;text-align:center!important}\n  body.postid-1675 #lvm-shell .cta-band .stores{width:100%!important;justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1675 #lvm-shell .cta-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1675 #lvm-shell .cta-band .stores img{height:56px!important;width:100%!important;max-width:170px!important;object-fit:contain!important;object-position:center!important;border-radius:10px!important}\n  body.postid-1675 #lvm-shell .get-band{padding:38px 22px!important}\n  body.postid-1675 #lvm-shell .get-band .stores{justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1675 #lvm-shell .get-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1675 #lvm-shell .get-band .stores img{height:56px!important;width:100%!important;max-width:170px!important;object-fit:contain!important;object-position:center!important;border-radius:10px!important}\n  body.postid-1675 #lvm-shell .get-band h3{font-size:26px!important;line-height:1.2!important}\n  body.postid-1675 #lvm-shell .get-band p{font-size:15px!important}\n}\n\n\/* === MINI-PHONES === *\/\n@media (max-width:760px){\n  body.postid-1675 #lvm-shell .mini-row{gap:6px!important;margin:24px 0!important;grid-template-columns:repeat(3,1fr)!important}\n  body.postid-1675 #lvm-shell .mini-phone{max-width:100px!important;padding:2px!important;border-radius:14px!important;border-width:1px!important}\n  body.postid-1675 #lvm-shell .mini-phone .notch{width:30px!important;height:8px!important;border-radius:0 0 5px 5px!important}\n  body.postid-1675 #lvm-shell .mini-phone .scr{border-radius:11px!important}\n  body.postid-1675 #lvm-shell .mini-cap{font-size:10px!important;margin-top:8px!important}\n  body.postid-1675 #lvm-shell .mini-cap strong{font-size:12px!important;margin-top:2px!important}\n}\n\n\/* === MOCKUP TAP HINT MOBILE === *\/\n@media (max-width:760px){\n  body.postid-1675 #lvm-shell .tap-hint.mobile{position:relative!important;width:100%!important;left:auto!important;top:auto!important;text-align:center!important;margin:0 auto 14px!important;display:block!important}\n  body.postid-1675 #lvm-shell .tap-hint.desktop{display:none!important}\n  body.postid-1675 #lvm-shell .tap-hint.hidden{display:none!important;height:0!important;margin:0!important;padding:0!important}\n}\n\n\/* === A.6 BODYSCAN ILLUST === *\/\nbody.postid-1675 #lvm-shell .bodyscan-illust{margin:40px auto 8px!important;display:flex!important;flex-direction:column!important;align-items:center!important;gap:14px!important;max-width:220px!important}\nbody.postid-1675 #lvm-shell .bodyscan-illust .mini-phone{max-width:200px!important;padding:3px!important;border-radius:22px!important;border-width:1px!important}\n@media (max-width:760px){\n  body.postid-1675 #lvm-shell .bodyscan-illust{max-width:180px!important}\n  body.postid-1675 #lvm-shell .bodyscan-illust .mini-phone{max-width:160px!important}\n}\n\n\/* Fix CompressX picture wrappers *\/\n#lvm-shell picture{display:block;max-width:100%}\n#lvm-shell picture img{display:block;max-width:100%;height:auto}\n#lvm-shell .bodyscan-illust .mini-phone{background:transparent;padding:0;border:none;box-shadow:none;border-radius:0}\n#lvm-shell .bodyscan-illust .mini-phone .notch{display:none}\n<\/style>\n\n<div id=\"lvm-shell\" class=\"force-show\">\n\n<nav class=\"nav\"><div class=\"nav-row\">\n  <a class=\"nav-brand\" href=\"https:\/\/lean-app.com\/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\">Pilar &middot; Ciencia del metabolismo<\/div>\n  <h1 id=\"title\">TEF (Thermic Effect of Food).\n    <span class=\"alt\">La gu\u00eda completa para entender el gasto cal\u00f3rico oculto de la digesti\u00f3n.<\/span>\n  <\/h1>\n  <p class=\"dek\">La digesti\u00f3n quema calor\u00edas. Del 20 al 30&nbsp;% de las prote\u00ednas, del 5 al 10&nbsp;% de los carbohidratos, del 0 al 3&nbsp;% de las grasas. Todas las apps lo ignoran. Lean lo calcula en tiempo real en cada comida registrada.<\/p>\n  <div class=\"byline\">\n    <img class=\"by-logo\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/>\n    <span><strong>El equipo Lean<\/strong> &middot; Lectura 10&nbsp;min &middot; Actualizado el 28 de mayo de 2026<\/span>\n  <\/div>\n  <div class=\"hero-stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=pillar-tef\" target=\"_blank\" rel=\"noopener\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"T&eacute;l&eacute;charger sur l&rsquo;App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=pillar-tef\" target=\"_blank\" rel=\"noopener\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Disponible sur Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <span class=\"or\">Descarga gratuita<\/span>\n  <\/div>\n  <div class=\"hero-bottom\">\n    <div class=\"hero-lead\">\n      El TEF (Thermic Effect of Food) es la energ\u00eda que gasta tu cuerpo para digerir, absorber y metabolizar cada comida. Representa del 8 al 15&nbsp;% de tu gasto total. La mayor\u00eda de las apps de calor\u00edas no lo calculan. Lean lo calcula a la kilocalor\u00eda, en cada alimento registrado.\n    <\/div>\n    <div class=\"phone-wrap rev\">\n      <div class=\"phone-stage\">\n        <div class=\"tap-hint mobile\" id=\"tapHintMobile\" aria-hidden=\"true\">\n          <span class=\"th-pill\"><small>Demo interactiva<\/small>Toca la pantalla para explorar la app<\/span>\n          <svg class=\"th-arrow\" viewbox=\"0 0 24 24\" fill=\"none\" aria-hidden=\"true\">\n            <path d=\"M12 4 L12 20 M5 13 L12 20 L19 13\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/>\n          <\/svg>\n        <\/div>\n        <div class=\"tap-hint desktop\" id=\"tapHintDesktop\" aria-hidden=\"true\">\n          <span class=\"th-pill\"><small>Demo interactiva<\/small>Toca la pantalla<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=\"Vista previa de la app Lean con desglose del 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=\"Navegar en la 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\">Gasto<\/button>\n          <button data-tab=\"strategie\" type=\"button\">Estrategia<\/button>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n  <div class=\"snippet rev\">\n    <div class=\"lbl\">Respuesta r\u00e1pida<\/div>\n    <p>El TEF (Thermic Effect of Food) es la energ\u00eda quemada para digerir tus alimentos. Entra en la ecuaci\u00f3n <b>TDEE = BMR + NEAT + EAT + TEF<\/b>. Var\u00eda seg\u00fan tus macros: prote\u00ednas 20&ndash;30&nbsp;%, carbohidratos 5&ndash;10&nbsp;%, grasas 0&ndash;3&nbsp;%. En una comida est\u00e1ndar post-entrenamiento, Lean calcula 69&nbsp;kcal de TEF donde las otras apps muestran 0.<\/p>\n  <\/div>\n<\/section>\n\n<!-- 02. DEFINITION -->\n<h2 class=\"sect\"><span class=\"num\">02 &middot; Definici\u00f3n<\/span>TEF, el 4.\u00ba ladrillo del TDEE<\/h2>\n<div class=\"body\">\n<p>El <b>TEF (Thermic Effect of Food)<\/b> es la energ\u00eda que gasta tu cuerpo para procesar los alimentos que ingieres: masticar, digerir, absorber, metabolizar. En ingl\u00e9s tambi\u00e9n se habla de DIT (Diet-Induced Thermogenesis). Es el calor producido por tu sistema digestivo en cada comida.<\/p>\n<p>Se inserta en la ecuaci\u00f3n fundamental del metabolismo:<\/p>\n<\/div>\n<div class=\"statement\" style=\"margin:28px 0\"><p><b style=\"color:var(--pink);font-variant-numeric:tabular-nums\">TDEE = BMR + NEAT + EAT + TEF<\/b><\/p><\/div>\n<div class=\"body\">\n<p>El <b>BMR<\/b> (Basal Metabolic Rate) es tu gasto en reposo. El <b>NEAT<\/b> (Non-Exercise Activity Thermogenesis) cubre tu gasto no deportivo. El<b>EAT<\/b> (Exercise Activity Thermogenesis) cubre tus sesiones de deporte. Y el <b>TEF<\/b>, es el calor generado por la digesti\u00f3n. Juntos, los cuatro componen tu verdadero TDEE.<\/p>\n<p>La<b>adaptaci\u00f3n metab\u00f3lica<\/b> viene adem\u00e1s como coeficiente multiplicador del BMR en d\u00e9ficit cal\u00f3rico prolongado. Convenci\u00f3n Lean: 100&nbsp;% = \u00f3ptimo, 90&nbsp;% = 10&nbsp;% de adaptaci\u00f3n. No entra <b>pasos<\/b> en la suma del TDEE.<\/p>\n<\/div>\n<div class=\"micro-cta\">\n  Ver tambi\u00e9n: <a href=\"https:\/\/lean-app.com\/es\/neat-depense-non-sportive\/\">Pilar NEAT<\/a> u00b7 <a href=\"https:\/\/lean-app.com\/es\/metabolisme-de-base\/\">Pilar BMR<\/a> u00b7 <a href=\"https:\/\/lean-app.com\/es\/depense-energetique-totale-v2\/\">Pilar TDEE<\/a> u00b7 <a href=\"https:\/\/lean-app.com\/es\/calculateur-tdee\/\">Calculadora TDEE<\/a> u00b7 <a href=\"https:\/\/lean-app.com\/es\/calculateur-deficit-calorique\/\">Calculadora de d\u00e9ficit<\/a>\n<\/div>\n\n<!-- 03. 69 KCAL D'ECART -->\n<h2 class=\"sect\"><span class=\"num\">03 &middot; Impacto real<\/span>69&nbsp;kcal ignoradas en una comida post-entrenamiento<\/h2>\n<div class=\"body\">\n<p>Un ejemplo concreto: vuelves de entrenar y comes 200&nbsp;g de pollo a la plancha, 200&nbsp;g de arroz cocido, 30&nbsp;g de aguacate. Total: 54&nbsp;g de prote\u00ednas \/ 55&nbsp;g de carbohidratos \/ 12&nbsp;g de grasas = <b>537&nbsp;kcal consumidas<\/b>.<\/p>\n<p>Lean aplica los coeficientes cient\u00edficos a esta comida:<\/p>\n<\/div>\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>Prote\u00ednas (54&nbsp;g)<\/h4>\n    <div class=\"meta\">54&nbsp;g &times; 4&nbsp;kcal\/g &times; 25&nbsp;%<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>TEF Prote\u00ednas<\/span><span class=\"v\" style=\"color:#FA256C\">54&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>Westerterp 2004<\/span><span class=\"v\">20&ndash;30&nbsp;%<\/span><\/div>\n      <div class=\"rw lean\"><span>Lean calcula<\/span><span class=\"v\">En tiempo real<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Las prote\u00ednas tienen el TEF m\u00e1s alto: s\u00edntesis, transaminaci\u00f3n, gluconeog\u00e9nesis son procesos costosos en ATP.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Carbohidratos (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 Carbohidratos<\/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 calcula<\/span><span class=\"v\">En tiempo real<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Conversi\u00f3n en gluc\u00f3geno u oxidaci\u00f3n directa. Gasto moderado pero no nulo.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Grasas (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 Grasas<\/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 calcula<\/span><span class=\"v\">En tiempo real<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Reesterificaci\u00f3n directa muy eficiente. El macro menos costoso de digerir.<\/div>\n  <\/div>\n<\/div>\n<div class=\"body\">\n<p><b>Total TEF calculado por Lean: 54 + 18 + 2 = 74&nbsp;kcal<\/b> solo en esta comida. Las apps de la competencia muestran 0. En un a\u00f1o, son decenas de miles de kilocalor\u00edas de gasto ignorado, lo que explica los estancamientos inexplicados y los d\u00e9ficits que \u00ab&nbsp;no funcionan&nbsp;\u00bb.<\/p>\n<\/div>\n\n<!-- 04. 3 PROFILS PAR APPORT EN PROTEINES -->\n<h2 class=\"sect\"><span class=\"num\">04 &middot; 3 perfiles<\/span>M\u00e1s prote\u00ednas = m\u00e1s TEF: las cifras<\/h2>\n<div class=\"body\">\n<p>Tres perfiles con una alimentaci\u00f3n de 2&nbsp;500&nbsp;kcal\/d\u00eda. Solo cambia el reparto de macros. Las cifras de TEF total ilustran el enorme impacto de la composici\u00f3n de la alimentaci\u00f3n.<\/p>\n<\/div>\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>15&nbsp;% prote\u00ednas<\/h4>\n    <div class=\"meta\">Alimentaci\u00f3n pobre en prote\u00ednas &middot; 2&nbsp;500 kcal<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>TEF Prote\u00ednas<\/span><span class=\"v\">75&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>TEF Carbohidratos + Grasas<\/span><span class=\"v\">94&nbsp;kcal<\/span><\/div>\n      <div class=\"rw lean\"><span>TEF total<\/span><span class=\"v\">~169&nbsp;kcal \/ d\u00eda<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">La casilla \u00ab&nbsp;sedentario&nbsp;\u00bb en MFP no tiene en cuenta la composici\u00f3n alimentaria. Este perfil pierde 169&nbsp;kcal de gasto si la app lo ignora.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>25&nbsp;% prote\u00ednas<\/h4>\n    <div class=\"meta\">Perfil deportista est\u00e1ndar &middot; 2&nbsp;500 kcal<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>TEF Prote\u00ednas<\/span><span class=\"v\">125&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>TEF Carbohidratos + Grasas<\/span><span class=\"v\">85&nbsp;kcal<\/span><\/div>\n      <div class=\"rw lean\"><span>TEF total<\/span><span class=\"v\">~210&nbsp;kcal \/ d\u00eda<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">41&nbsp;kcal de gasto adicional frente al perfil 15&nbsp;% prote\u00ednas. El equivalente a 5 minutos m\u00e1s de caminata, solo cambiando los macros.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>35&nbsp;% prote\u00ednas<\/h4>\n    <div class=\"meta\">Perfil definici\u00f3n agresiva &middot; 2&nbsp;500 kcal<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>TEF Prote\u00ednas<\/span><span class=\"v\">175&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>TEF Carbohidratos + Grasas<\/span><span class=\"v\">76&nbsp;kcal<\/span><\/div>\n      <div class=\"rw lean\"><span>TEF total<\/span><span class=\"v\">~251&nbsp;kcal \/ d\u00eda<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">82&nbsp;kcal m\u00e1s frente al perfil 15&nbsp;%. En 30 d\u00edas: +2&nbsp;460&nbsp;kcal de gasto adicional a calor\u00edas id\u00e9nticas, sin una sola sesi\u00f3n adicional.<\/div>\n  <\/div>\n<\/div>\n\n<!-- 05. POURQUOI LES APPS ECHOUENT -->\n<h2 class=\"sect\"><span class=\"num\">05 &middot; Por qu\u00e9 fallan las apps<\/span>Coeficiente fijo frente a c\u00e1lculo macroespec\u00edfico<\/h2>\n<div class=\"body\">\n<p>Cuando configuras MyFitnessPal o Yazio, te preguntan tu nivel de actividad. Un coeficiente PAL se aplica a tu BMR. Se supone que ese coeficiente \u00ab&nbsp;engloba&nbsp;\u00bb todo, incluida la digesti\u00f3n. En la pr\u00e1ctica, est\u00e1 calibrado sobre poblaciones gen\u00e9ricas y no refleja en absoluto tu composici\u00f3n de macros del d\u00eda.<\/p>\n<p>El problema: ese coeficiente no cambia el lunes en que comes un 50&nbsp;% de prote\u00ednas frente al domingo en que comes un 20&nbsp;% de prote\u00ednas. El TEF de esos dos d\u00edas es radicalmente diferente. Las apps no lo ven. Lean, s\u00ed.<\/p>\n<p>Westerterp (2004, PMID&nbsp;15507147) midi\u00f3 por calorimetr\u00eda indirecta que los errores de estimaci\u00f3n del TEF mediante coeficiente fijo pueden alcanzar <b>100 a 200&nbsp;kcal al d\u00eda<\/b> seg\u00fan la composici\u00f3n alimentaria real. Es el orden de magnitud que explica un d\u00e9ficit que \u00ab&nbsp;no funciona&nbsp;\u00bb durante varias semanas.<\/p>\n<\/div>\n\n<!-- 06. MFP VS LEAN -->\n<h2 class=\"sect\"><span class=\"num\">06 &middot; MFP vs Lean<\/span>0&nbsp;kcal vs 74&nbsp;kcal en la misma comida<\/h2>\n<div class=\"body\">\n<p>La misma comida post-entrenamiento: 200&nbsp;g de pollo, 200&nbsp;g de arroz cocido, 30&nbsp;g de aguacate = 537&nbsp;kcal. Lo que cada app hace con esta comida:<\/p>\n<\/div>\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>MyFitnessPal (y la mayor\u00eda de las apps)<\/h4>\n    <div class=\"meta\">Sin c\u00e1lculo del TEF en las comidas<\/div>\n    <div style=\"margin:12px auto;max-width:130px\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2025\/07\/analyse-nutrition-calcul-tef-lean-app-551x1024.png\" alt=\"Analyse nutritionnelle dans Lean avec calcul du TEF\" style=\"width:100%;border-radius:16px;box-shadow:0 4px 16px rgba(0,0,0,.12)\" loading=\"lazy\"><\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>537 kcal registradas<\/span><span class=\"v\" style=\"color:#FF2D6E\">TEF: 0&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>M\u00e9todo<\/span><span class=\"v\">Coeficiente PAL fijo<\/span><\/div>\n      <div class=\"rw\"><span>Tenido en cuenta<\/span><span class=\"v\">No<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">MFP, Yazio, Cronometer y la mayor\u00eda de las apps de calor\u00edas no integran el TEF en su c\u00e1lculo del gasto. Quemas 74&nbsp;kcal digiriendo esta comida. Ellas no lo saben.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Lean<\/h4>\n    <div class=\"meta\">C\u00e1lculo del TEF macroespec\u00edfico en tiempo real<\/div>\n    <div style=\"margin:12px auto;max-width:130px\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2025\/07\/focus-depense-digestion-tef-lean-app-523x1024.png\" alt=\"Focus sur la d&eacute;pense TEF dans l&rsquo;application Lean\" style=\"width:100%;border-radius:16px;box-shadow:0 4px 16px rgba(0,0,0,.12)\" loading=\"lazy\"><\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>537 kcal registradas<\/span><span class=\"v\" style=\"color:#27AE60\">TEF: 74&nbsp;kcal<\/span><\/div>\n      <div class=\"rw\"><span>M\u00e9todo<\/span><span class=\"v\">P&times;25&nbsp;% + C&times;8&nbsp;% + G&times;2&nbsp;%<\/span><\/div>\n      <div class=\"rw lean\"><span>Tenido en cuenta<\/span><span class=\"v\">S\u00ed, en cada comida<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Lean calcula el TEF a la kilocalor\u00eda en cada comida registrada. Ese TEF se a\u00f1ade a tu TDEE del d\u00eda y ajusta tu objetivo cal\u00f3rico en tiempo real.<\/div>\n  <\/div>\n<\/div>\n<div class=\"cta-band\">\n  <div class=\"l\">Lean calcula tu TEF en tiempo real en cada comida. Descarga gratuita, prueba de 7 d\u00edas en el plan anual.<\/div>\n  <div class=\"stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=pillar-tef-cta1\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"T&eacute;l&eacute;charger sur l&rsquo;App Store\" height=\"42\" loading=\"lazy\"><\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=pillar-tef-cta1\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Disponible sur Google Play\" height=\"42\" loading=\"lazy\"><\/a>\n  <\/div>\n<\/div>\n\n<!-- 07. BMR CHANGE TOUT POUR LE TEF -->\n<h2 class=\"sect\"><span class=\"num\">07 &middot; BMR &amp; TEF<\/span>Por qu\u00e9 tu BMR influye en el valor del TEF<\/h2>\n<div class=\"body\">\n<p>El TEF se calcula sobre los macros ingeridos. Pero para que ese c\u00e1lculo se integre en un TDEE preciso, hace falta que el BMR que sirve de base sea exacto. Y el BMR depende directamente de tu <b>masa magra real<\/b>.<\/p>\n<p>La raz\u00f3n fisiol\u00f3gica: el metabolismo basal lo sostienen principalmente los m\u00fasculos y los \u00f3rganos (tejido metab\u00f3licamente activo), no la masa grasa. Dos personas de 80&nbsp;kg con 12&nbsp;% y 22&nbsp;% de grasa corporal tienen una masa magra de 70,4&nbsp;kg vs 62,4&nbsp;kg, es decir, una diferencia de BMR de unas 170&nbsp;kcal\/d\u00eda. Si tu TDEE est\u00e1 mal desde la base, tu TEF acaba integrado en una ecuaci\u00f3n ya descalibrada.<\/p>\n<p>Concretamente: Lean calcula tu BMR sobre tu masa magra real mediante BodyScan IA, y luego integra el TEF sobre ese BMR exacto. El error en cadena que cometen las apps se produce a dos niveles: BMR sobre peso total (falso), y luego 0&nbsp;kcal de TEF (falso tambi\u00e9n). Lean corrige los dos.<\/p>\n<\/div>\n<div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">BMR calculado sobre grasa corporal real, no sobre peso total<\/div><p class=\"fd\">Lean utiliza su modelo propietario patentado (ni Harris-Benedict 1919, ni Mifflin-St Jeor 1990) y lo indexa a tu masa magra mediante BodyScan IA. Ese BMR sirve de base a todo lo dem\u00e1s, incluido el TEF.<\/p><\/div><div class=\"fc\">Precisi\u00f3n<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">TEF integrado en el TDEE, no a\u00f1adido a posteriori<\/div><p class=\"fd\">El TEF no es una l\u00ednea aparte que decides activar o no. Forma parte de la ecuaci\u00f3n TDEE = BMR + NEAT + EAT + TEF, integrada desde la primera comida registrada.<\/p><\/div><div class=\"fc\">Arquitectura<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">TEF recalculado con cada actualizaci\u00f3n del perfil<\/div><p class=\"fd\">\u00bfPierdes 3&nbsp;kg de grasa en un mes? Tu BMR cambia. Y la integraci\u00f3n del TEF en el TDEE se recalibra autom\u00e1ticamente en Lean. Las apps mantienen su constante desde el registro.<\/p><\/div><div class=\"fc\">Din\u00e1mico<\/div><\/div>\n\n<!-- 08. BODYSCAN IA -->\n<h2 class=\"sect\"><span class=\"num\">08 &middot; BodyScan IA<\/span>La grasa corporal real: la base del c\u00e1lculo del TEF de Lean<\/h2>\n<div class=\"body\">\n<p>Para que el TEF se integre en un TDEE preciso, primero hace falta que el BMR sea correcto. Y para eso, hace falta tu grasa corporal real. Aqu\u00ed es donde interviene el BodyScan IA de Lean.<\/p>\n<p>La mayor\u00eda de las apps calculan el BMR en funci\u00f3n del peso total (Harris-Benedict 1919, Mifflin-St Jeor 1990). Lean calcula tu BMR sobre tu <b>masa magra estimada mediante la grasa corporal<\/b>, gracias a un <b>modelo propietario patentado<\/b>. Ese BMR sirve despu\u00e9s de base a la integraci\u00f3n del TEF en el 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> : grasa corporal real en 5 segundos, a partir de una foto<\/p>\n<\/div>\n<div class=\"body\">\n<p>Una foto, 5 segundos, y Lean conoce tu grasa corporal con precisi\u00f3n. Esa cifra alimenta directamente el c\u00e1lculo de tu BMR, que a su vez sirve de base a la integraci\u00f3n del TEF en tu TDEE. Es la arquitectura en cadena que las otras apps no ofrecen.<\/p>\n<\/div>\n\n<!-- 09. COMMENT LEAN CALCULE LE TEF -->\n<h2 class=\"sect\"><span class=\"num\">09 &middot; Lean &amp; TEF<\/span>C\u00e1lculo en tiempo real en cada comida registrada<\/h2>\n<div class=\"body\">\n<p>Lean calcula el TEF a partir de cada comida que registras, y lo integra en tu TDEE del d\u00eda en tiempo real. Esta es la arquitectura completa:<\/p>\n<\/div>\n<div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">Registro de la comida (3 m\u00e9todos)<\/div><p class=\"fd\">Registras mediante la base USDA+OpenFoodFacts, el escaneo de c\u00f3digo de barras o el escaneo fotogr\u00e1fico con IA de un plato. Lean recupera inmediatamente los gramos de prote\u00ednas, carbohidratos y grasas.<\/p><\/div><div class=\"fc\">Registro<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">C\u00e1lculo del TEF por macro en cada alimento<\/div><p class=\"fd\">El motor Lean aplica: P &times; 25&nbsp;%, C &times; 8&nbsp;%, G &times; 2&nbsp;%. El resultado se calcula al vuelo para cada alimento y luego se acumula a lo largo del d\u00eda.<\/p><\/div><div class=\"fc\">C\u00e1lculo<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">TEF acumulado en el TDEE del d\u00eda<\/div><p class=\"fd\">El TEF acumulado del d\u00eda se a\u00f1ade al BMR + NEAT + EAT para dar tu TDEE en vivo. Tu balance cal\u00f3rico se ajusta con cada comida registrada.<\/p><\/div><div class=\"fc\">Integraci\u00f3n<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">04<\/div><div><div class=\"ft\">Visible en la pesta\u00f1a Gasto<\/div><p class=\"fd\">La pesta\u00f1a Gasto de Lean detalla cada componente del TDEE: BMR, NEAT, EAT, TEF. Ves exactamente cu\u00e1nto contribuye la digesti\u00f3n a tu gasto del d\u00eda.<\/p><\/div><div class=\"fc\">Transparente<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">05<\/div><div><div class=\"ft\">Impacto directo en el objetivo cal\u00f3rico<\/div><p class=\"fd\">Lean utiliza el TDEE consciente del TEF para calcular tu objetivo y tu d\u00e9ficit meta. Una comida m\u00e1s proteica aumenta tu TEF y por tanto tu TDEE real, lo que Lean refleja autom\u00e1ticamente.<\/p><\/div><div class=\"fc\">Estrat\u00e9gico<\/div><\/div>\n\n<!-- 10. L'ECRAN TEF -->\n<h2 class=\"sect\"><span class=\"num\">10 &middot; TEF en Lean<\/span>El seguimiento de la digesti\u00f3n en tiempo real<\/h2>\n<div class=\"body\">\n<p>La pesta\u00f1a Gasto de Lean detalla en tiempo real cada componente del TDEE: BMR, NEAT, EAT, TEF. Pulsa en TEF para ver el detalle por comida.<\/p>\n<\/div>\n<div style=\"max-width:130px;margin:24px auto\">\n  <div class=\"mini-phone\" style=\"max-width:130px\"><div class=\"notch\"><\/div><div class=\"scr\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp\" alt=\"TEF et digestion dans Lean\" loading=\"lazy\"><\/div><\/div>\n<\/div>\n<div class=\"mini-cap\"><strong>Lean<\/strong> &middot; TEF calculado en tiempo real en cada comida<\/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; Estrategias<\/span>Comer m\u00e1s prote\u00ednas = quemar m\u00e1s al digerir<\/h2>\n<div class=\"body\">\n<p>El principio fundamental del TEF: cada calor\u00eda de prote\u00edna cuesta un 25&nbsp;% digerirla, frente a un 2&nbsp;% para las grasas. <b>Comer m\u00e1s prote\u00ednas = gastar m\u00e1s a igualdad de calor\u00edas.<\/b> Es la ventaja metab\u00f3lica real de una alimentaci\u00f3n proteica en definici\u00f3n.<\/p>\n<\/div>\n<div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">+100&nbsp;g de prote\u00ednas = +100&nbsp;kcal de TEF gratis<\/div><p class=\"fd\">100&nbsp;g de prote\u00ednas adicionales (400&nbsp;kcal) generan unas 100&nbsp;kcal de TEF adicional. Es gasto real, sin esfuerzo f\u00edsico, solo cambiando tu composici\u00f3n alimentaria.<\/p><\/div><div class=\"fc\">Prote\u00ednas<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">Registra todo, incluso las comidas peque\u00f1as<\/div><p class=\"fd\">Cada entrada en Lean activa el c\u00e1lculo del TEF. Un snack de 100&nbsp;g de queso fresco batido (18&nbsp;g de prote\u00ednas) genera ~18&nbsp;kcal de TEF. Acumulado en 5 tomas, es un gasto real que las apps no cuentan.<\/p><\/div><div class=\"fc\">Exhaustividad<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">Prefiere los alimentos enteros<\/div><p class=\"fd\">Los alimentos ultraprocesados tienen un TEF m\u00e1s bajo porque ya est\u00e1n en parte \u00ab&nbsp;predigeridos&nbsp;\u00bb industrialmente (Barr 2010, PMID&nbsp;20613941). Una pechuga de pollo entera tiene un TEF m\u00e1s alto que una prote\u00edna en polvo prehidrolizada.<\/p><\/div><div class=\"fc\">Calidad<\/div><\/div>\n<div class=\"feat-it\"><div class=\"fn\">04<\/div><div><div class=\"ft\">No cuentes con las grasas para el TEF<\/div><p class=\"fd\">Las grasas tienen un TEF del 0 al 3&nbsp;%. Aumentar tus grasas no impulsa el TEF. Lo que cuenta es el reparto de macros, no el total cal\u00f3rico bruto.<\/p><\/div><div class=\"fc\">Grasas<\/div><\/div>\n\n<!-- 12. MET et macros -->\n<h2 class=\"sect\"><span class=\"num\">12 &middot; Ciencia<\/span>Por qu\u00e9 las prote\u00ednas queman tanto en la digesti\u00f3n<\/h2>\n<div class=\"body\">\n<p>La respuesta es bioqu\u00edmica. Las prote\u00ednas deben descomponerse en amino\u00e1cidos, que luego se integran en la s\u00edntesis proteica (coste en ATP), se oxidan (ciclo de Krebs) o se transforman en glucosa (gluconeog\u00e9nesis, coste a\u00fan m\u00e1s alto). La desaminaci\u00f3n del nitr\u00f3geno (producci\u00f3n de urea) es en s\u00ed misma costosa en energ\u00eda.<\/p>\n<\/div>\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>Prote\u00ednas: TEF 20&ndash;30&nbsp;%<\/h4>\n    <div class=\"meta\">Fuente: Westerterp 2004, Acheson 2011<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>S\u00edntesis proteica<\/span><span class=\"v\">Coste ATP elevado<\/span><\/div>\n      <div class=\"rw\"><span>Desaminaci\u00f3n<\/span><span class=\"v\">Producci\u00f3n de urea<\/span><\/div>\n      <div class=\"rw lean\"><span>TEF Lean<\/span><span class=\"v\">25&nbsp;% (valor mediano)<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Es el macro m\u00e1s \u00ab&nbsp;caro&nbsp;\u00bb de digerir. Su coste metab\u00f3lico es el m\u00e1s alto de todos los macros.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Carbohidratos: TEF 5&ndash;10&nbsp;%<\/h4>\n    <div class=\"meta\">Fuente: Westerterp 2004<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Gluc\u00f3lisis<\/span><span class=\"v\">Moderadamente costoso<\/span><\/div>\n      <div class=\"rw\"><span>Almacenamiento de gluc\u00f3geno<\/span><span class=\"v\">Coste adicional<\/span><\/div>\n      <div class=\"rw lean\"><span>TEF Lean<\/span><span class=\"v\">8&nbsp;% (valor mediano)<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Gasto moderado pero no nulo. El almacenamiento en gluc\u00f3geno cuesta m\u00e1s que la oxidaci\u00f3n directa.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Grasas: TEF 0&ndash;3&nbsp;%<\/h4>\n    <div class=\"meta\">Fuente: Westerterp 2004<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Reesterificaci\u00f3n<\/span><span class=\"v\">Muy poco costoso<\/span><\/div>\n      <div class=\"rw\"><span>Almacenamiento directo<\/span><span class=\"v\">Casi sin transformaci\u00f3n<\/span><\/div>\n      <div class=\"rw lean\"><span>TEF Lean<\/span><span class=\"v\">2&nbsp;% (valor mediano)<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">El macro menos \u00ab&nbsp;caro&nbsp;\u00bb de digerir. Las grasas alimentarias son casi directamente almacenables sin gran gasto metab\u00f3lico.<\/div>\n  <\/div>\n<\/div>\n\n<!-- 13. OBJECTIFS SECHE\/BULK\/RECOMP -->\n<h2 class=\"sect\"><span class=\"num\">13 &middot; Objetivos<\/span>TEF y estrategia seg\u00fan definici\u00f3n, volumen o recomposici\u00f3n<\/h2>\n<p>Una vez conocido tu TEF preciso, la aplicaci\u00f3n pr\u00e1ctica es directa. Tres objetivos, tres palancas.<\/p>\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>Definici\u00f3n (p\u00e9rdida de grasa)<\/h4>\n    <div class=\"meta\">Objetivo: maximizar el TEF sin sacrificar los macros<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Palanca TEF<\/span><span class=\"v\">Prote\u00ednas al 30&nbsp;%+<\/span><\/div>\n      <div class=\"rw\"><span>Ventaja<\/span><span class=\"v\">Gasto adicional sin deporte<\/span><\/div>\n      <div class=\"rw lean\"><span>Lean calcula<\/span><span class=\"v\">Impacto exacto en el d\u00e9ficit<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Un aporte proteico elevado preserva la masa muscular Y aumenta el TEF. Doble beneficio en definici\u00f3n. Herramienta: <a href=\"https:\/\/lean-app.com\/es\/calculateur-deficit-calorique\/\" style=\"text-decoration:underline\">calculadora de d\u00e9ficit cal\u00f3rico<\/a>.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Volumen (ganancia de m\u00fasculo)<\/h4>\n    <div class=\"meta\">Objetivo: super\u00e1vit controlado, ganancia de grasa m\u00ednima<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Palanca TEF<\/span><span class=\"v\">Prote\u00ednas altas preferidas<\/span><\/div>\n      <div class=\"rw\"><span>Ventaja<\/span><span class=\"v\">Super\u00e1vit neto reducido por el TEF proteico<\/span><\/div>\n      <div class=\"rw lean\"><span>Lean muestra<\/span><span class=\"v\">Super\u00e1vit neto tras el TEF real<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">En volumen, Lean muestra el super\u00e1vit real en tiempo real. Una comida muy proteica reduce el super\u00e1vit neto mediante el TEF adicional.<\/div>\n  <\/div>\n  <div class=\"profile-card\">\n    <h4>Recomposici\u00f3n (mantenimiento + construcci\u00f3n)<\/h4>\n    <div class=\"meta\">Objetivo: precisi\u00f3n m\u00e1xima en ingestas y gasto<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Palanca TEF<\/span><span class=\"v\">Herramienta de precisi\u00f3n a la kcal<\/span><\/div>\n      <div class=\"rw\"><span>Ventaja<\/span><span class=\"v\">Equilibrio sin aproximaci\u00f3n<\/span><\/div>\n      <div class=\"rw lean\"><span>Lean calcula<\/span><span class=\"v\">Balance cal\u00f3rico en vivo<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">La recomposici\u00f3n exige una precisi\u00f3n m\u00e1xima. Un TEF calculado a la kilocalor\u00eda es una ventaja decisiva frente a las apps que lo ignoran.<\/div>\n  <\/div>\n<\/div>\n\n<!-- 14. TEF LIVE DANS LEAN -->\n<h2 class=\"sect\"><span class=\"num\">14 &middot; TEF en vivo<\/span>El seguimiento de la digesti\u00f3n en Lean<\/h2>\n<div class=\"body\">\n<p>La pesta\u00f1a Gasto de Lean detalla en tiempo real cada componente del TDEE: BMR, NEAT, EAT, TEF. El TEF mostrado corresponde a tus comidas registradas del d\u00eda, calculado sobre cada macro.<\/p>\n<\/div>\n<div style=\"max-width:130px;margin:24px auto\">\n  <div class=\"mini-phone\" style=\"max-width:130px\"><div class=\"notch\"><\/div><div class=\"scr\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp\" alt=\"TEF dans Lean, d&eacute;pense de digestion\" loading=\"lazy\"><\/div><\/div>\n<\/div>\n<div class=\"mini-cap\"><strong>Lean<\/strong> &middot; TEF en tiempo real, calculado sobre tus macros reales<\/div>\n\n<!-- 15. LA PYRAMIDE -->\n<h2 class=\"sect\"><span class=\"num\">15 &middot; La Pir\u00e1mide<\/span>Pir\u00e1mide de Progresi\u00f3n Lean<\/h2>\n<div class=\"body\">\n<p>La Pir\u00e1mide de Progresi\u00f3n Lean jerarquiza las prioridades para alcanzar tu objetivo corporal. El TEF interviene en dos niveles: el objetivo cal\u00f3rico preciso (TEF integrado en el TDEE) y los macronutrientes (composici\u00f3n que determina el nivel de TEF).<\/p>\n<\/div>\n<div class=\"pyramid\" aria-label=\"Pir\u00e1mide de Progresi\u00f3n Lean\">\n  <div class=\"level l1\"><span>Adherencia<\/span><span class=\"k\">Base<\/span><\/div>\n  <div class=\"level l2\"><span>Objetivo cal\u00f3rico (TDEE + TEF preciso)<\/span><span class=\"k\">Nivel 2<\/span><\/div>\n  <div class=\"level l3\"><span>Pasos \/ NEAT diario<\/span><span class=\"k\">Nivel 3<\/span><\/div>\n  <div class=\"level l4\"><span>Macros (prote\u00ednas = palanca TEF)<\/span><span class=\"k\">Cima<\/span><\/div>\n<\/div>\n<div class=\"pyramid-cap\">No quemar etapas. Un TDEE preciso con TEF integrado es el nivel 2. Pero si no registras tus comidas con regularidad, el TEF nunca se calcula.<\/div>\n\n<!-- 16. FAQ -->\n<h2 class=\"sect\"><span class=\"num\">16 &middot; FAQ<\/span>Todo lo que te preguntas sobre el TEF<\/h2>\n\n<details class=\"faq\"><summary>\u00bfQu\u00e9 es el efecto t\u00e9rmico de los alimentos?<\/summary><div class=\"faq-body\"><p>El <b>TEF (Thermic Effect of Food)<\/b>, tambi\u00e9n llamado DIT (Diet-Induced Thermogenesis), es la energ\u00eda gastada para digerir, absorber y metabolizar los alimentos. Entra en la ecuaci\u00f3n <b>TDEE = BMR + NEAT + EAT + TEF<\/b> y representa de media del 8 al 15&nbsp;% del gasto cal\u00f3rico total.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>\u00bfPor qu\u00e9 las prote\u00ednas tienen el TEF m\u00e1s alto?<\/summary><div class=\"faq-body\"><p>Las prote\u00ednas requieren procesos bioqu\u00edmicos costosos en ATP: s\u00edntesis proteica, transaminaci\u00f3n, desaminaci\u00f3n (producci\u00f3n de urea) y a veces gluconeog\u00e9nesis. Por eso del 20 al 30&nbsp;% de las calor\u00edas proteicas se queman en la digesti\u00f3n, frente al 5 al 10&nbsp;% para los carbohidratos y al 0 al 3&nbsp;% para las grasas.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>\u00bfMyFitnessPal calcula el TEF?<\/summary><div class=\"faq-body\"><p>No. MyFitnessPal, Yazio, Cronometer y la mayor\u00eda de las apps de calor\u00edas no integran el TEF en su c\u00e1lculo del gasto. Utilizan un coeficiente de actividad fijo (PAL) aplicado al BMR, que se supone \u00ab&nbsp;engloba&nbsp;\u00bb la digesti\u00f3n. En la pr\u00e1ctica, ese coeficiente no refleja tu composici\u00f3n de macros del d\u00eda.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>\u00bfC\u00f3mo calcula Lean el TEF?<\/summary><div class=\"faq-body\"><p>Lean aplica los coeficientes cient\u00edficos a cada comida registrada: <b>P &times; 25&nbsp;% + C &times; 8&nbsp;% + G &times; 2&nbsp;%<\/b>. El resultado se integra en tiempo real en tu TDEE del d\u00eda. En una comida de 537&nbsp;kcal (54&nbsp;g P, 55&nbsp;g C, 12&nbsp;g G), Lean calcula 74&nbsp;kcal de TEF.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>\u00bfCu\u00e1ntas calor\u00edas representa el TEF al d\u00eda?<\/summary><div class=\"faq-body\"><p>Con una alimentaci\u00f3n de 2&nbsp;000 a 2&nbsp;500&nbsp;kcal, el TEF representa entre 160 y 250&nbsp;kcal seg\u00fan tu composici\u00f3n de macros. En un a\u00f1o, son de 58&nbsp;000 a 91&nbsp;000&nbsp;kcal de gasto ignorado por las apps que no lo calculan.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>\u00bfEl TEF disminuye en d\u00e9ficit cal\u00f3rico?<\/summary><div class=\"faq-body\"><p>S\u00ed, proporcionalmente: si comes menos calor\u00edas, digieres menos y el TEF absoluto disminuye. Pero el <b>porcentaje<\/b> se mantiene estable seg\u00fan tus macros. En d\u00e9ficit, mantener un aporte proteico elevado preserva la ratio TEF\/ingesta, adem\u00e1s de preservar la masa muscular.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>\u00bfEl TEF es lo mismo que el metabolismo activo posprandial?<\/summary><div class=\"faq-body\"><p>S\u00ed, los dos t\u00e9rminos designan la misma realidad: la energ\u00eda quemada por la digesti\u00f3n. TEF (Thermic Effect of Food) es el t\u00e9rmino anglosaj\u00f3n m\u00e1s utilizado. DIT (Diet-Induced Thermogenesis) o ADE (Acci\u00f3n Din\u00e1mica Espec\u00edfica) son los equivalentes en la literatura europea y espa\u00f1ola.<\/p><\/div><\/details>\n\n<details class=\"faq\"><summary>\u00bfLos alimentos procesados tienen un TEF m\u00e1s bajo?<\/summary><div class=\"faq-body\"><p>S\u00ed. Barr &amp; Wright (2010, PMID&nbsp;20613941) midieron que las comidas a base de alimentos enteros generan un TEF aproximadamente un 50&nbsp;% m\u00e1s alto que comidas equivalentes en calor\u00edas a base de alimentos procesados. Los alimentos procesados ya est\u00e1n en parte \u00ab&nbsp;predigeridos&nbsp;\u00bb industrialmente, lo que reduce el trabajo digestivo y por tanto el TEF.<\/p><\/div><\/details>\n\n<!-- 17. SOURCES -->\n<div class=\"sources\">\n  <h4>Fuentes cient\u00edficas<\/h4>\n  <ol>\n    <li>Westerterp KR. Diet induced thermogenesis. <em>Nutr Metab (Lond)<\/em>. 2004;1(1):5. <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/15507147\/\" target=\"_blank\" rel=\"noopener\">PubMed 15507147<\/a><\/li>\n    <li>Acheson KJ. Protein choices targeting thermogenesis and metabolism. <em>Am J Clin Nutr<\/em>. 2011;93(3):525-534. <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/21235280\/\" target=\"_blank\" rel=\"noopener\">PubMed 21235280<\/a><\/li>\n    <li>Tappy L. Thermic effect of food and sympathetic nervous system activity in lean and obese subjects. <em>Crit Rev Clin Lab Sci<\/em>. 1996;33(6):435-444. <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/8701638\/\" target=\"_blank\" rel=\"noopener\">PubMed 8701638<\/a><\/li>\n    <li>Barr SB, Wright JC. Postprandial energy expenditure in whole-food and processed-food meals. <em>Food Nutr Res<\/em>. 2010;54. <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/20613941\/\" target=\"_blank\" rel=\"noopener\">PubMed 20613941<\/a><\/li>\n    <li>Levine JA. Non-exercise activity thermogenesis (NEAT). <em>Best Pract Res Clin Endocrinol Metab<\/em>. 2002;16(4):679-702. <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/12468415\/\" target=\"_blank\" rel=\"noopener\">PubMed 12468415<\/a><\/li>\n  <\/ol>\n<\/div>\n\n<!-- GET-BAND -->\n<div class=\"get-band\">\n  <h3>Calcula tu TEF sobre tus macros reales<\/h3>\n  <p>P &times; 25&nbsp;% + C &times; 8&nbsp;% + G &times; 2&nbsp;%, en cada comida registrada. TDEE = BMR + NEAT + EAT + TEF. Modelo propietario patentado. Descarga gratuita, prueba de 7 d\u00edas en el plan anual.<\/p>\n  <div class=\"stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=pillar-tef-footer\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"T&eacute;l&eacute;charger sur l&rsquo;App Store\" loading=\"lazy\"><\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=pillar-tef-footer\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Disponible sur Google Play\" loading=\"lazy\"><\/a>\n  <\/div>\n<\/div>\n\n<\/main>\n\n<script>(function(){\n  var phoneImg = document.getElementById('phoneImg');\n  var phoneBack = document.getElementById('phoneBack');\n  var zones = document.getElementById('phoneZones');\n  var topTabs = document.querySelectorAll('.phone-tabs button');\n  var navTaps = document.querySelectorAll('.phone-navbar button');\n  var tabMap = {\n    bilan:    {drill:false},\n    kcal:     {drill:false},\n    depense:  {drill:true},\n    strategie:{drill:false}\n  };\n  var currentTab = 'depense';\n  function setActive(tab){\n    topTabs.forEach(function(b){ b.classList.toggle('on', b.dataset.tab===tab); });\n  }\n  function showTab(tab){\n    var t = tabMap[tab]; if(!t) return;\n    currentTab = tab;\n    phoneImg.style.opacity = 0;\n    setTimeout(function(){\n      phoneImg.className = 'phone-bg tab-' + tab;\n      phoneImg.style.opacity = 1;\n      zones.style.display = t.drill ? 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Il repr\u00e9sente 8 \u00e0 15 % de la d\u00e9pense calorique totale et entre dans TDEE = BMR + NEAT + EAT + TEF.\"}},{\"@type\":\"Question\",\"name\":\"Pourquoi les prot\u00e9ines ont-elles le TEF le plus \u00e9lev\u00e9 ?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Les prot\u00e9ines n\u00e9cessitent synth\u00e8se, transaminaison et d\u00e9samination. Co\u00fbt en ATP \u00e9lev\u00e9 : 20 \u00e0 30 % des calories prot\u00e9iques sont br\u00fcl\u00e9es \u00e0 la digestion.\"}},{\"@type\":\"Question\",\"name\":\"MyFitnessPal calcule-t-il le TEF ?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Non. MFP, Yazio, Cronometer et la plupart des apps n'int\u00e8grent pas le TEF. 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Maintenir un apport prot\u00e9ique \u00e9lev\u00e9 pr\u00e9serve le ratio TEF\/apport.\"}},{\"@type\":\"Question\",\"name\":\"Les aliments transform\u00e9s ont-ils un TEF plus faible ?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Oui. Barr & Wright (2010) ont mesur\u00e9 que les repas base d'aliments entiers g\u00e9n\u00e8rent un TEF environ 50 % plus \u00e9lev\u00e9 que des repas \u00e9quivalents base d'aliments transform\u00e9s.\"}},{\"@type\":\"Question\",\"name\":\"TEF et DIT, c'est la m\u00eame chose ?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"Oui, TEF (Thermic Effect of Food) et DIT (Diet-Induced Thermogenesis) d\u00e9signent la m\u00eame r\u00e9alit\u00e9. TEF est plus utilis\u00e9 dans la litt\u00e9rature anglophone.\"}}]},{\"@type\":\"MobileApplication\",\"name\":\"Lean\",\"operatingSystem\":\"iOS, Android\",\"applicationCategory\":\"HealthApplication\",\"description\":\"Lean calcule ton TEF en temps r\u00e9el sur chaque repas. TDEE complet : BMR + NEAT + EAT + TEF sur bodyfat r\u00e9el.\",\"aggregateRating\":{\"@type\":\"AggregateRating\",\"ratingValue\":\"4.7\",\"ratingCount\":\"1000\",\"bestRating\":\"5\"},\"offers\":{\"@type\":\"Offer\",\"price\":\"0\",\"priceCurrency\":\"EUR\"},\"downloadUrl\":\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\"}]}\n<\/script>\n\n<\/div>\n\n\n<!-- lean-mesh-v19 -->\n<aside class=\"lean-mesh\" style=\"margin:48px auto;max-width:760px;padding:24px 28px;background:#ffffff;border-left:4px solid #FF2D6E;border-radius:0 12px 12px 0;box-shadow:0 6px 24px rgba(20,20,40,0.06);font-family:-apple-system,'SF Pro Text','Segoe UI',Roboto,Arial,sans-serif;color:#1a1a2e;\"><p style=\"margin:0 0 14px;font-size:13px;font-weight:700;letter-spacing:0.06em;text-transform:uppercase;color:#FF2D6E;\">Lecturas relacionadas<\/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\/es\/metabolisme-de-base\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Metabolismo basal (BMR): todo lo que hay que saber para calcularlo <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Definici\u00f3n, ecuaci\u00f3n TDEE, 4 f\u00f3rmulas hist\u00f3ricas, por qu\u00e9 la grasa corporal lo cambia todo.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/depense-energetique-totale-v2\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Gasto energ\u00e9tico total (TDEE): la f\u00f3rmula can\u00f3nica BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Entiende los 4 bloques + la adaptaci\u00f3n metab\u00f3lica, fuentes cient\u00edficas 2025.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/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: el gasto cal\u00f3rico no deportivo que pesa del 15 al 50% de tu TDEE <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Pasos, desplazamientos, fidget. Por qu\u00e9 Mifflin se equivoca al ignorar tu actividad.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/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=\"https:\/\/lean-app.com\/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: 8 apps 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=\"https:\/\/lean-app.com\/es\/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;\">\u00bfQu\u00e9 alternativa a MyFitnessPal en 2026? 5 apps probadas <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Comparativa honesta, precisi\u00f3n del TDEE, ergonom\u00eda.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/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;\">Calculadora de d\u00e9ficit cal\u00f3rico: el enfoque correcto para una definici\u00f3n <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">D\u00e9ficit sobre tu TDEE real bodyfat-aware. 3 ritmos: lento\/moderado\/agresivo.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/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;\">C\u00f3mo calcular tu gasto cal\u00f3rico real: la gu\u00eda completa <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">BMR sobre grasa corporal real, NEAT por pasos, EAT por sesi\u00f3n, TEF por macros, adaptaci\u00f3n.<\/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>Efecto t\u00e9rmico de los alimentos (TEF): c\u00e1lculo y ejemplos - Lean<\/title>\n<meta name=\"description\" content=\"El efecto t\u00e9rmico de los alimentos (TEF) es el 10 % de tu gasto. 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