{"id":1241,"date":"2026-05-21T18:28:26","date_gmt":"2026-05-21T18:28:26","guid":{"rendered":"https:\/\/lean-app.com\/?p=1241"},"modified":"2026-09-08T18:17:56","modified_gmt":"2026-09-08T18:17:56","slug":"lean-vs-myfitnesspal","status":"publish","type":"post","link":"https:\/\/lean-app.com\/es\/lean-vs-myfitnesspal\/","title":{"rendered":"Lean vs MyFitnessPal: la f\u00f3rmula TDEE que lo cambia todo"},"content":{"rendered":"<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp\" 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18px;border-radius:14px;color:#fff;font-family:var(--font-display);font-weight:500;font-size:15px;letter-spacing:-.01em;display:flex;justify-content:space-between;align-items:center;box-shadow:0 6px 18px rgba(0,0,0,.06)}\n#lvm-shell .pyramid .level .k{font-family:var(--font-mono);font-size:10px;text-transform:uppercase;letter-spacing:.08em;opacity:.75}\n#lvm-shell .pyramid .l1{background:#0E0E10;width:100%}\n#lvm-shell .pyramid .l2{background:#1D1D1F;width:84%}\n#lvm-shell .pyramid .l3{background:#3a3a3c;width:68%}\n#lvm-shell .pyramid .l4{background:var(--pink);width:52%}\n#lvm-shell .pyramid-cap{text-align:center;font-size:13px;color:var(--muted);margin-top:14px}\n\n\/* Section 7 honnetete : scorecard horizontal bars *\/\n#lvm-shell .scorecard{margin:30px 0 10px;border:1px solid var(--rule);border-radius:20px;padding:28px 26px;background:#fff}\n#lvm-shell .scorecard-head{display:grid;grid-template-columns:1.4fr 1fr 1fr;column-gap:28px;align-items:center;padding-bottom:18px;margin-bottom:8px;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell .scorecard-head .h-crit{font-family:var(--font-mono);font-size:11px;font-weight:500;text-transform:uppercase;letter-spacing:.08em;color:var(--muted)}\n#lvm-shell .scorecard-head .h-brand{display:flex;align-items:center;gap:8px;font-family:var(--font-display);font-size:14px;font-weight:600;color:var(--ink)}\n#lvm-shell .scorecard-head .h-brand img{width:22px;height:22px;border-radius:5px;object-fit:cover}\n#lvm-shell .scorecard-row{display:grid;grid-template-columns:1.4fr 1fr 1fr;column-gap:28px;align-items:center;padding:14px 0;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell .scorecard-row:last-child{border-bottom:0}\n#lvm-shell .scorecard-row .crit{font-size:14px;color:var(--ink);font-weight:500;padding-right:14px}\n#lvm-shell .scorecard-row .bar{display:flex;flex-direction:row-reverse;align-items:center;gap:10px}\n#lvm-shell .scorecard-row .bar .b{flex:1;height:8px;border-radius:99px;background:var(--rule-soft);overflow:hidden;position:relative}\n#lvm-shell .scorecard-row .bar .b > i{display:block;height:100%;border-radius:99px;transition:width 1s cubic-bezier(.22,.61,.36,1)}\n#lvm-shell .scorecard-row .bar.lean .b > i{background:var(--pink)}\n#lvm-shell .scorecard-row .bar.mfp .b > i{background:var(--mfp)}\n#lvm-shell .scorecard-row .bar .v{font-family:var(--font-mono);font-size:12px;font-weight:600;color:var(--ink);min-width:32px;text-align:left}\n\n\/* Section 8 pour qui : persona checklist *\/\n#lvm-shell .persona{margin:28px 0 10px;display:grid;grid-template-columns:1fr;gap:14px}\n#lvm-shell .persona-it{display:grid;grid-template-columns:54px 1fr;gap:16px;padding:22px 24px;background:#fff;border:1px solid var(--rule);border-radius:18px;align-items:center}\n#lvm-shell .persona-it.match{background:var(--pink-soft);border-color:rgba(255,45,110,.25)}\n#lvm-shell .persona-it .pic{width:54px;height:54px;border-radius:50%;display:flex;align-items:center;justify-content:center;background:var(--rule-soft);position:relative;font-family:var(--font-mono);font-size:13px;font-weight:600;color:var(--ink)}\n#lvm-shell .persona-it.match .pic{background:var(--pink);color:#fff}\n#lvm-shell .persona-it .pic svg{width:24px;height:24px}\n#lvm-shell .persona-it h4{margin:0 0 4px;font-size:17px;letter-spacing:-.01em}\n#lvm-shell .persona-it p{margin:0;font-size:14px;color:var(--muted);line-height:1.55}\n#lvm-shell .persona-it.match h4{color:var(--ink)}\n\n\/* Section 9 migration : timeline steps *\/\n#lvm-shell .steps{display:grid;grid-template-columns:repeat(5,1fr);gap:14px;margin:28px 0;position:relative}\n#lvm-shell .steps::before{content:\"\";position:absolute;top:14px;left:7px;right:calc(20% - 18px);height:1px;background:linear-gradient(90deg,var(--pink) 0%,var(--rule-soft) 100%);z-index:0}\n#lvm-shell .step{position:relative;padding-top:24px;z-index:1}\n#lvm-shell .step::before{content:\"\";position:absolute;top:8px;left:0;width:14px;height:14px;border-radius:50%;background:var(--pink);border:3px solid #fff;box-shadow:0 0 0 1px var(--rule)}\n#lvm-shell .step .sn{font-family:var(--font-mono);font-size:11px;color:var(--pink);font-weight:600;letter-spacing:.08em}\n#lvm-shell .step h4{margin:6px 0 6px;font-size:15px;letter-spacing:-.01em}\n#lvm-shell .step p{font-size:13px;color:var(--muted);line-height:1.5;margin:0}\n\n\/* Section 10 debloque : feature stack numbered XL *\/\n#lvm-shell .feat-stack{margin:30px 0 10px;border-top:1px solid var(--rule)}\n#lvm-shell .feat-it{display:grid;grid-template-columns:auto 1fr auto;gap:24px;padding:26px 0;border-bottom:1px solid var(--rule);align-items:center}\n#lvm-shell .feat-it .fn{font-family:var(--font-display);font-size:48px;font-weight:600;color:var(--pink);line-height:1;letter-spacing:-.04em;width:74px}\n#lvm-shell .feat-it .ft{font-family:var(--font-display);font-size:22px;font-weight:600;color:var(--ink);letter-spacing:-.015em;line-height:1.25;margin-bottom:6px}\n#lvm-shell .feat-it .fd{font-size:15px;color:var(--muted);line-height:1.55;margin:0}\n#lvm-shell .feat-it .fc{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.08em;color:var(--muted);font-weight:500}\n#lvm-shell .feat-it:last-child{border-bottom:0}\n\n#lvm-shell .faq{margin:22px 0}\n#lvm-shell .faq details{border-bottom:1px solid var(--rule);padding:20px 0}\n#lvm-shell .faq details:first-of-type{border-top:1px solid var(--rule)}\n#lvm-shell .faq summary{cursor:pointer;list-style:none;display:flex;justify-content:space-between;align-items:center;gap:18px;font-family:var(--font-display);font-size:20px;font-weight:500;letter-spacing:-.015em;color:var(--ink)}\n#lvm-shell .faq summary::-webkit-details-marker{display:none}\n#lvm-shell .faq summary::after{content:\"+\";font-size:24px;color:var(--muted);font-weight:300;line-height:1;transition:transform .25s, color .25s}\n#lvm-shell .faq details[open] summary::after{transform:rotate(45deg);color:var(--pink)}\n#lvm-shell .faq details[open] summary{color:var(--pink)}\n#lvm-shell .faq .ans{margin-top:14px;font-size:16px;color:var(--muted);line-height:1.65}\n\n#lvm-shell .get-band{background:var(--paper-2);border-radius:24px;padding:48px 36px;margin:60px 0 40px;text-align:center}\n#lvm-shell .get-band .kicker{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;color:var(--pink);font-weight:600;letter-spacing:.1em;margin-bottom:14px}\n#lvm-shell .get-band h3{font-size:36px;margin:0 0 14px;letter-spacing:-.025em}\n#lvm-shell .get-band p{font-size:16px;color:var(--muted);max-width:480px;margin:0 auto 26px}\n#lvm-shell .get-band .stores{display:flex;justify-content:center;gap:14px;flex-wrap:wrap}\n#lvm-shell .get-band .stores a{line-height:0;transition:transform .15s}\n#lvm-shell .get-band .stores a:hover{transform:translateY(-3px)}\n#lvm-shell .get-band .stores img{height:60px;width:auto;border-radius:11px}\n\n#lvm-shell .sources{font-size:14px;color:var(--muted);line-height:1.7}\n#lvm-shell .sources ol{padding-left:22px}\n#lvm-shell .sources li{margin-bottom:8px}\n\n#lvm-shell footer{padding:50px 0 60px;border-top:1px solid var(--rule);margin-top:40px}\n#lvm-shell footer .row{display:flex;justify-content:space-between;align-items:center;gap:18px;flex-wrap:wrap}\n#lvm-shell footer .kicker{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.08em;color:var(--pink);font-weight:600}\n#lvm-shell footer p{font-size:13px;color:var(--muted);margin:8px 0 0}\n#lvm-shell footer .stores{display:flex;gap:8px}\n#lvm-shell footer .stores img{height:34px;width:auto;border-radius:6px}\n\n#lvm-shell .rev{opacity:0;transform:translateY(12px);transition:opacity .8s cubic-bezier(.22,.61,.36,1),transform .8s cubic-bezier(.22,.61,.36,1)}\n#lvm-shell .rev.on{opacity:1;transform:translateY(0)}\n@media (prefers-reduced-motion:reduce){#lvm-shell .rev{transition:none;opacity:1;transform:none}}\n\n@media (max-width:760px){\n  #lvm-shell .nav-row{padding:8px 18px;gap:8px}\n  #lvm-shell .nav-link{display:none}\n  #lvm-shell .nav-stores img{height:24px}\n  #lvm-shell .wrap{padding:0 22px}\n  #lvm-shell .hero{padding:34px 0 0}\n  #lvm-shell h1{font-size:46px;letter-spacing:-.035em}\n  #lvm-shell h1 .alt{font-size:.55em;margin-top:10px}\n  #lvm-shell .dek{font-size:20px}\n  #lvm-shell .hero-stores img{height:42px}\n  #lvm-shell .hero-bottom{grid-template-columns:1fr;gap:28px;margin:30px 0 40px;padding-top:24px;align-items:stretch}\n  #lvm-shell .phone-wrap{order:-1}\n  #lvm-shell .phone{width:240px}\n  #lvm-shell .tap-hint.desktop{display:none}\n  #lvm-shell .tap-hint.mobile{display:block;position:relative;left:auto;top:auto;text-align:center;margin:0 auto 10px;width:100%}\n  #lvm-shell .tap-hint.mobile .th-arrow{position:relative;display:block;margin:6px auto 0;width:34px;height:34px;transform:none;color:var(--pink)}\n  #lvm-shell .snippet{padding:24px 22px}\n  #lvm-shell .snippet p{font-size:18px}\n  #lvm-shell section{padding:48px 0}\n  #lvm-shell h2{font-size:34px;letter-spacing:-.03em}\n  #lvm-shell h3{font-size:24px}\n  #lvm-shell .section-label{margin-bottom:22px}\n  #lvm-shell .statement{padding:24px 0;margin:32px 0}\n  #lvm-shell .statement .num{font-size:44px}\n  #lvm-shell .statement .lbl{font-size:19px}\n  #lvm-shell .fig{padding:20px 14px 14px;border-radius:16px}\n  #lvm-shell .cv-wrap{height:310px}\n  #lvm-shell .method{grid-template-columns:1fr;gap:20px}\n  #lvm-shell .method.flip{grid-template-columns:1fr}\n  #lvm-shell .method.flip .m-phone{order:0}\n  #lvm-shell .mini-row{grid-template-columns:repeat(3,1fr);gap:10px}\n  #lvm-shell .mini-phone{padding:3px;border-radius:18px;border-width:1px;max-width:110px}\n  #lvm-shell .mini-phone .notch{width:42px;height:11px;border-radius:0 0 8px 8px}\n  #lvm-shell .mini-phone .scr{border-radius:15px}\n  #lvm-shell .mini-cap{font-size:10px}\n  #lvm-shell .mini-cap strong{font-size:13px}\n  #lvm-shell .duo-row{grid-template-columns:repeat(2,1fr);gap:12px}\n  #lvm-shell .duo-row .mini-phone{max-width:130px}\n  #lvm-shell .steps{grid-template-columns:1fr;gap:18px}\n  #lvm-shell .steps::before{display:none}\n  #lvm-shell .step{padding-top:0;padding-left:24px}\n  #lvm-shell .step::before{top:6px;left:0}\n  #lvm-shell .table-row{grid-template-columns:1.4fr .9fr .9fr}\n  #lvm-shell .table-row > .crit{padding:13px 12px;font-size:13px}\n  #lvm-shell .table-row > .cell{padding:13px 10px;font-size:12px;gap:8px}\n  #lvm-shell .table-row.head > div{padding:14px 12px;font-size:10px;gap:7px}\n  #lvm-shell .table-row.head .brand-cell img{width:20px;height:20px}\n  #lvm-shell .get-band{padding:36px 22px;border-radius:18px;margin:40px 0 30px}\n  #lvm-shell .get-band h3{font-size:28px}\n  #lvm-shell .get-band .stores img{height:50px}\n  #lvm-shell .cta-band{padding:22px;gap:14px}\n  #lvm-shell .cta-band .l{font-size:16px;min-width:0}\n  #lvm-shell .cta-band .stores img{height:38px}\n  #lvm-shell .faq summary{font-size:18px;gap:14px}\n  #lvm-shell .pyramid{max-width:100%}\n  #lvm-shell .pyramid .level{padding:11px 14px;font-size:14px}\n  #lvm-shell .scorecard{padding:20px 16px;border-radius:16px}\n  #lvm-shell .scorecard-head{grid-template-columns:1.2fr 1fr 1fr;column-gap:14px}\n  #lvm-shell .scorecard-head .h-brand{font-size:12px;gap:5px}\n  #lvm-shell .scorecard-head .h-brand img{width:18px;height:18px}\n  #lvm-shell .scorecard-row{grid-template-columns:1.2fr 1fr 1fr;column-gap:14px;padding:12px 0}\n  #lvm-shell .scorecard-row .crit{font-size:13px;padding-right:8px}\n  #lvm-shell .scorecard-row .bar{gap:6px}\n  #lvm-shell .scorecard-row .bar .v{font-size:11px;min-width:26px}\n  #lvm-shell .persona-it{grid-template-columns:44px 1fr;gap:12px;padding:16px 16px;border-radius:14px}\n  #lvm-shell .persona-it .pic{width:44px;height:44px;font-size:12px}\n  #lvm-shell .persona-it h4{font-size:15px}\n  #lvm-shell .persona-it p{font-size:13px}\n  #lvm-shell .feat-it{grid-template-columns:auto 1fr;gap:14px;padding:20px 0}\n  #lvm-shell .feat-it .fn{font-size:36px;width:54px}\n  #lvm-shell .feat-it .ft{font-size:18px}\n  #lvm-shell .feat-it .fd{font-size:13px}\n  #lvm-shell .feat-it .fc{display:none}\n}\n@media (max-width:480px){\n  #lvm-shell .phone-tabs{gap:5px}\n  #lvm-shell .phone-tabs button{padding:5px 8px;font-size:10px}\n  #lvm-shell .nav-stores{gap:4px}\n  #lvm-shell .nav-stores img{height:22px}\n  #lvm-shell .hero-stores img{height:40px}\n  #lvm-shell .crumb{font-size:12px}\n  #lvm-shell .table-row{grid-template-columns:1.3fr .85fr .85fr}\n  #lvm-shell .table-row > .crit{padding:11px 9px;font-size:12px}\n  #lvm-shell .table-row > .cell{padding:11px 8px;font-size:11px;gap:6px}\n  #lvm-shell .table-row.head > div{padding:11px 9px;font-size:9px;gap:5px}\n}<\/style>\n\n<style id=\"lvm-collision-reset\">\n\/* Hard reset for global theme styles that collide with our content *\/\nbody.postid-1241 #lvm-shell .hero{display:block!important;align-items:initial!important;justify-content:initial!important;text-align:left!important;flex-direction:initial!important;padding:54px 0 0!important}\nbody.postid-1241 #lvm-shell .wrap,\nbody.postid-1241 #lvm-shell main.wrap{display:block!important;max-width:760px!important;margin-left:auto!important;margin-right:auto!important;padding-left:28px!important;padding-right:28px!important}\n@media (max-width:820px){\n  body.postid-1241 #lvm-shell .wrap,\n  body.postid-1241 #lvm-shell main.wrap{padding-left:18px!important;padding-right:18px!important}\n}\nhtml, body{overflow-x:hidden!important}\nbody.postid-1241 #lvm-shell{overflow-x:hidden;max-width:100vw}\nbody.postid-1241 #lvm-shell *{max-width:100%}\nbody.postid-1241 #lvm-shell .nav-row{max-width:100vw;box-sizing:border-box}\nbody.postid-1241 #lvm-shell.force-show .rev{opacity:1!important;transform:none!important}\n\n\/* === A.1 PHONE BACKGROUND CLASSES === *\/\nbody.postid-1241 #lvm-shell .phone-bg{position:absolute;inset:0;width:100%;height:100%;background-size:cover;background-position:center top;background-repeat:no-repeat;transition:opacity .28s ease;background-color:#FAF0E6}\nbody.postid-1241 #lvm-shell .phone-bg.tab-depense{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp)}\nbody.postid-1241 #lvm-shell .phone-bg.tab-bilan{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp)}\nbody.postid-1241 #lvm-shell .phone-bg.tab-kcal{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp)}\nbody.postid-1241 #lvm-shell .phone-bg.tab-strategie{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp)}\nbody.postid-1241 #lvm-shell .phone-bg.sub-BMR{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp)}\nbody.postid-1241 #lvm-shell .phone-bg.sub-NEAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp)}\nbody.postid-1241 #lvm-shell .phone-bg.sub-EAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp)}\nbody.postid-1241 #lvm-shell .phone-bg.sub-TEF{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp)}\n\n\/* === v11.3 CTA BANDS MOBILE (badges plus gros + centrage) === *\/\n@media (max-width:760px){\n  body.postid-1241 #lvm-shell .cta-band{flex-direction:column!important;align-items:center!important;text-align:center!important;padding:26px 22px!important;gap:20px!important}\n  body.postid-1241 #lvm-shell .cta-band .l{min-width:0!important;width:100%!important;font-size:16px!important;line-height:1.5!important;text-align:center!important}\n  body.postid-1241 #lvm-shell .cta-band .stores{width:100%!important;justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1241 #lvm-shell .cta-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1241 #lvm-shell .cta-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1241 #lvm-shell .cta-band .stores img{height:56px!important;width:100%!important;max-width:170px!important;object-fit:contain!important;object-position:center!important;border-radius:10px!important}\n  body.postid-1241 #lvm-shell .get-band{padding:38px 22px!important}\n  body.postid-1241 #lvm-shell .get-band .stores{justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1241 #lvm-shell .get-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1241 #lvm-shell .get-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1241 #lvm-shell .get-band .stores img{height:56px!important;width:100%!important;max-width:170px!important;object-fit:contain!important;object-position:center!important;border-radius:10px!important}\n  body.postid-1241 #lvm-shell .get-band h3{font-size:26px!important;line-height:1.2!important}\n  body.postid-1241 #lvm-shell .get-band p{font-size:15px!important}\n}\n\n\/* === v11.2 BRAND BANNER above table responsive === *\/\n@media (max-width:760px){\n  body.postid-1241 #lvm-shell .brand-banner img{width:54px!important;height:54px!important}\n  body.postid-1241 #lvm-shell .brand-banner > div{padding:16px 12px!important;gap:8px!important}\n  body.postid-1241 #lvm-shell .brand-banner > div > div{font-size:15px!important}\n}\n\n\/* === v11.4 SCORECARD partie 7: redesign mobile === *\/\n@media (max-width:760px){\n  body.postid-1241 #lvm-shell .scorecard{padding:18px 16px!important;border-radius:16px!important}\n  body.postid-1241 #lvm-shell .scorecard-head{display:none!important}\n  body.postid-1241 #lvm-shell .scorecard-row{\n    display:block!important;\n    padding:14px 0!important;\n    border-bottom:1px solid #E8E2D6!important;\n  }\n  body.postid-1241 #lvm-shell .scorecard-row .crit{\n    display:block!important;\n    font-size:13px!important;\n    font-weight:600!important;\n    color:#0E0E10!important;\n    margin-bottom:10px!important;\n    padding-right:0!important;\n  }\n  body.postid-1241 #lvm-shell .scorecard-row .bar{\n    display:grid!important;\n    grid-template-columns:54px 1fr 32px!important;\n    column-gap:8px!important;\n    align-items:center!important;\n    padding:5px 0!important;\n    flex-direction:initial!important;\n    position:relative!important;\n  }\n  body.postid-1241 #lvm-shell .scorecard-row .bar::before{\n    content:attr(data-brand)!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:11px!important;\n    font-weight:600!important;\n    text-transform:uppercase!important;\n    letter-spacing:.05em!important;\n    color:#0E0E10!important;\n  }\n  body.postid-1241 #lvm-shell .scorecard-row .bar.lean::before{color:#FF2D6E!important}\n  body.postid-1241 #lvm-shell .scorecard-row .bar.mfp::before{color:#5B7FFF!important}\n  body.postid-1241 #lvm-shell .scorecard-row .bar .b{\n    height:10px!important;\n    width:100%!important;\n    border-radius:99px!important;\n    position:relative!important;\n    background:#EFEAE0!important;\n    overflow:hidden!important;\n  }\n  body.postid-1241 #lvm-shell .scorecard-row .bar .b > i{\n    display:block!important;\n    height:100%!important;\n    border-radius:99px!important;\n  }\n  body.postid-1241 #lvm-shell .scorecard-row .bar .v{\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:12px!important;\n    font-weight:700!important;\n    color:#0E0E10!important;\n    min-width:0!important;\n    text-align:right!important;\n  }\n}\n\n\/* === A.2 CHARTS MOBILE === *\/\n@media (max-width:760px){\n  \/* v13: charts FULL WIDTH (less card padding) + plus hauts pour vraie respiration *\/\n  body.postid-1241 #lvm-shell .cv-wrap{height:380px!important;min-height:360px!important;max-height:420px!important;width:100%!important}\n  body.postid-1241 #lvm-shell .cv-wrap canvas{width:100%!important;height:100%!important;display:block!important}\n  body.postid-1241 #lvm-shell .fig{padding:16px 4px 14px!important;margin:24px -4px 14px!important;overflow:visible!important}\n  body.postid-1241 #lvm-shell .fig-head{padding:0 12px!important;flex-wrap:wrap!important;gap:6px!important;margin-bottom:10px!important}\n  body.postid-1241 #lvm-shell .fig-body{padding:0 2px!important}\n  body.postid-1241 #lvm-shell .fig-cap{padding:0 12px!important;font-size:13px!important;margin-top:10px!important}\n}\n@media (max-width:480px){\n  body.postid-1241 #lvm-shell .cv-wrap{height:360px!important;min-height:340px!important;max-height:380px!important}\n  body.postid-1241 #lvm-shell .fig{padding:14px 2px 12px!important;margin:20px -6px 12px!important;border-radius:14px!important}\n  body.postid-1241 #lvm-shell .fig-body{padding:0!important}\n}\n\n\/* === v11.2 TABLEAU MOBILE STACKED CARDS avec mini-tags Lean\/MFP === *\/\n@media (max-width:760px){\n  body.postid-1241 #lvm-shell .table{border-radius:14px!important}\n  body.postid-1241 #lvm-shell .table-row.head{display:none!important}\n  body.postid-1241 #lvm-shell .table-row{\n    display:grid!important;\n    grid-template-columns:1fr 1fr!important;\n    grid-template-areas:\"crit crit\" \"lean mfp\"!important;\n    gap:0!important;\n    min-height:0!important;\n  }\n  body.postid-1241 #lvm-shell .table-row > .crit{\n    grid-area:crit!important;background:#0E0E10!important;color:#fff!important;\n    padding:11px 14px!important;font-size:13px!important;font-weight:600!important;\n    letter-spacing:-0.1px!important;border-right:0!important;line-height:1.35!important;\n    font-family:-apple-system,BlinkMacSystemFont,'SF Pro Display',sans-serif!important;text-transform:none!important;\n  }\n  body.postid-1241 #lvm-shell .table-row > .cell.lean{\n    grid-area:lean!important;border-right:1px solid #E8E2D6!important;\n    position:relative!important;background:#FFF1F5!important;padding-top:30px!important;\n  }\n  body.postid-1241 #lvm-shell .table-row > .cell:not(.lean):not(.crit){\n    grid-area:mfp!important;background:#F5F5F7!important;padding-top:30px!important;\n    position:relative!important;\n  }\n  body.postid-1241 #lvm-shell .table-row > .cell.lean::before{\n    content:\"LEAN\"!important;position:absolute!important;top:8px!important;left:12px!important;\n    right:auto!important;bottom:auto!important;width:auto!important;height:auto!important;\n    background:transparent!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:10px!important;font-weight:700!important;letter-spacing:.07em!important;\n    color:#FF2D6E!important;\n  }\n  body.postid-1241 #lvm-shell .table-row > .cell:not(.lean):not(.crit)::before{\n    content:\"MFP\"!important;position:absolute!important;top:8px!important;left:12px!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:10px!important;font-weight:700!important;letter-spacing:.07em!important;\n    color:#5B7FFF!important;\n  }\n  body.postid-1241 #lvm-shell .table-row > .cell{\n    padding:12px 12px!important;font-size:13px!important;line-height:1.4!important;\n    align-items:flex-start!important;gap:7px!important;\n  }\n  body.postid-1241 #lvm-shell .icn{flex-shrink:0!important;margin-top:1px!important}\n}\n\n\/* === A.5 MINI-LOGOS partie 7 (triplet NEAT\/EAT\/TEF) === *\/\n@media (max-width:760px){\n  body.postid-1241 #lvm-shell .mini-row{gap:6px!important;margin:24px 0!important;grid-template-columns:repeat(3,1fr)!important}\n  body.postid-1241 #lvm-shell .mini-phone{max-width:100px!important;padding:2px!important;border-radius:14px!important;border-width:1px!important}\n  body.postid-1241 #lvm-shell .mini-phone.tiny{max-width:96px!important;padding:2px!important;border-radius:13px!important}\n  body.postid-1241 #lvm-shell .mini-phone .notch{width:30px!important;height:8px!important;border-radius:0 0 5px 5px!important}\n  body.postid-1241 #lvm-shell .mini-phone .scr{border-radius:11px!important}\n  body.postid-1241 #lvm-shell .mini-cap{font-size:10px!important;margin-top:8px!important}\n  body.postid-1241 #lvm-shell .mini-cap strong{font-size:12px!important;margin-top:2px!important}\n}\n\n\/* === MOCKUP TAP HINT MOBILE === *\/\n@media (max-width:760px){\n  body.postid-1241 #lvm-shell .tap-hint.mobile{position:relative!important;width:100%!important;left:auto!important;top:auto!important;text-align:center!important;margin:0 auto 14px!important;display:block!important}\n  body.postid-1241 #lvm-shell .tap-hint.desktop{display:none!important}\n  body.postid-1241 #lvm-shell .tap-hint.hidden{display:none!important;height:0!important;margin:0!important;padding:0!important}\n}\n\n\/* === A.6 BODYSCAN ILLUST partie BMR (override mobile mini-phone) === *\/\nbody.postid-1241 #lvm-shell .bodyscan-illust{margin:40px auto 8px!important;display:flex!important;flex-direction:column!important;align-items:center!important;gap:14px!important;max-width:220px!important}\nbody.postid-1241 #lvm-shell .bodyscan-illust .mini-phone{max-width:200px!important;padding:3px!important;border-radius:22px!important;border-width:1px!important}\nbody.postid-1241 #lvm-shell .bodyscan-illust .mini-phone .notch{width:40px!important;height:11px!important;border-radius:0 0 7px 7px!important}\nbody.postid-1241 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:18px!important}\n@media (max-width:760px){\n  body.postid-1241 #lvm-shell .bodyscan-illust{max-width:180px!important}\n  body.postid-1241 #lvm-shell .bodyscan-illust .mini-phone{max-width:160px!important;padding:3px!important;border-radius:20px!important}\n  body.postid-1241 #lvm-shell .bodyscan-illust .mini-phone .notch{width:34px!important;height:9px!important;border-radius:0 0 6px 6px!important}\n  body.postid-1241 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:16px!important}\n}\n<\/style>\n<script data-wpmeteor-nooptimize=\"true\">\n(function(){\n  \/* Hard fallback: force .rev visible after 2s if IntersectionObserver doesn't fire *\/\n  setTimeout(function(){\n    var shell = document.getElementById('lvm-shell');\n    if(!shell) return;\n    var anyOn = shell.querySelector('.rev.on');\n    if(!anyOn){ shell.classList.add('force-show'); }\n  }, 2000);\n\n  \/* ResizeObserver fallback: ensure charts resize correctly *\/\n  if (typeof ResizeObserver !== 'undefined'){\n    var observer = new ResizeObserver(function(entries){\n      entries.forEach(function(entry){\n        var canvas = entry.target.querySelector('canvas');\n        if (!canvas || !window.Chart) return;\n        var inst = window.Chart.getChart(canvas);\n        if (inst) { try { inst.resize(); } catch(e){} }\n      });\n    });\n    document.querySelectorAll('#lvm-shell .cv-wrap').forEach(function(w){ observer.observe(w); });\n  }\n})();\n<\/script>\n<div id=\"lvm-shell\"><div class=\"progress\" aria-hidden=\"true\"><i id=\"progBar\"><\/i><\/div>\n\n<header class=\"nav\">\n  <div class=\"nav-row\">\n    <a class=\"nav-brand\" href=\"https:\/\/lean-app.com\/es\/\" aria-label=\"Inicio Lean\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/>\n      <span>Lean<\/span>\n    <\/a>\n    <span class=\"nav-spacer\"><\/span>\n    <a class=\"nav-link\" href=\"https:\/\/lean-app.com\/es\/tdee-calculator\/\">Calculadora TDEE<\/a>\n    <div class=\"nav-stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" target=\"_blank\" rel=\"noopener\" aria-label=\"Descargar en el App Store\">\n        <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/>\n      <\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" target=\"_blank\" rel=\"noopener\" aria-label=\"Disponible en Google Play\">\n        <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/>\n      <\/a>\n    <\/div>\n  <\/div>\n<\/header>\n\n<main class=\"wrap\">\n\n<section class=\"hero\" aria-labelledby=\"title\">\n  <div class=\"crumb\"><a href=\"https:\/\/lean-app.com\/es\/\">Inicio<\/a> &nbsp;\/&nbsp; Lean vs MyFitnessPal<\/div>\n  <div class=\"eyebrow\">Comparativa &middot; Nutrici\u00f3n &amp; TDEE<\/div>\n  <h1 id=\"title\">Lean vs MyFitnessPal.\n    <span class=\"alt\">La f\u00f3rmula TDEE que lo cambia todo. 1919 frente a 2025, en ciencia.<\/span>\n  <\/h1>\n  <p class=\"dek\">Por qu\u00e9 MyFitnessPal se equivoca con el 80&nbsp;% de los usuarios, y la alternativa que hace lo que MFP no sabe hacer.<\/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 12&nbsp;min &middot; Actualizado el 21 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=vs-mfp\" target=\"_blank\" rel=\"noopener\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"T\u00e9l\u00e9charger sur l'App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" target=\"_blank\" rel=\"noopener\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Disponible sur Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <span class=\"or\">Descarga gratuita<\/span>\n  <\/div>\n\n  <div class=\"hero-bottom\">\n    <div class=\"hero-lead\">\n      MyFitnessPal calcula tu TDEE con una f\u00f3rmula de 1919 (Harris-Benedict) sin grasa corporal, m\u00e1s un coeficiente de actividad casi aleatorio, e ignora la adaptaci\u00f3n metab\u00f3lica. Tu objetivo puede estar mal en 500 a 800&nbsp;kcal. Lean recalcula cada componente con precisi\u00f3n, sin coeficiente que elegir.\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>Demostraci\u00f3n interactiva<\/small>Toca la pantalla para explorar la aplicaci\u00f3n<\/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>Demostraci\u00f3n 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 general de la aplicaci\u00f3n 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 por la aplicaci\u00f3n 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\n  <div class=\"snippet rev\">\n    <div class=\"lbl\">Respuesta r\u00e1pida<\/div>\n    <p>MyFitnessPal calcula tu TDEE con una f\u00f3rmula de 1919 (Harris-Benedict) sin grasa corporal, m\u00e1s un coeficiente de actividad casi aleatorio, e ignora la adaptaci\u00f3n metab\u00f3lica. Tu objetivo cal\u00f3rico puede estar mal en 500 a 800&nbsp;kcal. Lean recalcula cada componente (<span data-term=\"BMR\">BMR<span class=\"tt\">Basal Metabolic Rate. Energ\u00eda gastada en reposo. En Lean, calculada sobre la masa magra real mediante BodyScan IA.<\/span><\/span> sobre grasa corporal real, <span data-term=\"NEAT\">NEAT<span class=\"tt\">Non-Exercise Activity Thermogenesis. Gasto ligado a los pasos y a las actividades cotidianas fuera del deporte.<\/span><\/span> por pasos, <span data-term=\"EAT\">EAT<span class=\"tt\">Exercise Activity Thermogenesis. Gasto ligado a tus sesiones de deporte, calculado mediante MET.<\/span><\/span> por MET, <span data-term=\"TEF\">TEF<span class=\"tt\">Thermic Effect of Food. Energ\u00eda gastada por la digesti\u00f3n. Depende de los macros ingeridos.<\/span><\/span> por macros, adaptaci\u00f3n metab\u00f3lica autom\u00e1tica) sin coeficiente de actividad que elegir.<\/p>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"constat\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">00 &middot; La constataci\u00f3n<\/span><\/div>\n  <h2 id=\"constat\">Por qu\u00e9 el 80&nbsp;% de los usuarios de MFP no pierden peso a pesar de un \u00ab&nbsp;d\u00e9ficit&nbsp;\u00bb<\/h2>\n  <p>Si lees esto, probablemente has pasado por ah\u00ed. Descargaste MyFitnessPal, rellenaste tu perfil, la app te dijo \u00ab&nbsp;tu <span data-term=\"TDEE\">TDEE<span class=\"tt\">Total Daily Energy Expenditure. La f\u00f3rmula BMR + NEAT + EAT + TEF, m\u00e1s la adaptaci\u00f3n metab\u00f3lica que modula el BMR.<\/span><\/span> es de 2&nbsp;500&nbsp;kcal al d\u00eda, come 2&nbsp;250&nbsp;kcal para perder peso&nbsp;\u00bb. Lo hiciste. Religiosamente. Pesaste tus alimentos. Incluso pasaste a Premium. Y al final del mes, est\u00e1s en el mismo peso. O un poco m\u00e1s pesado.<\/p>\n  <p>Te dices: \u00ab&nbsp;habr\u00e9 registrado mal, habr\u00e9 subestimado mis calor\u00edas&nbsp;\u00bb. Aprietas las tuercas. Bajas a 2&nbsp;000&nbsp;kcal. Otra vez, nada.<\/p>\n\n  <div class=\"statement\">\n    <div class=\"num\">80&nbsp;%<\/div>\n    <div class=\"lbl\">de los usuarios de MFP se estancan a pesar de un d\u00e9ficit te\u00f3rico. El problema no es su fuerza de voluntad. Es el c\u00e1lculo de su TDEE.<\/div>\n  <\/div>\n\n  <p>Imaginemos que MFP te muestra un TDEE de 2&nbsp;500&nbsp;kcal. Comes 2&nbsp;250 (d\u00e9ficit te\u00f3rico de 250&nbsp;kcal). Pero en realidad, tu <a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/depense-energetique-totale-v2\/\">TDEE es de 2&nbsp;200&nbsp;kcal<\/a>. Pues no hay ninguna posibilidad, y digo bien <strong>ninguna posibilidad<\/strong>, de que pierdas peso. Est\u00e1s en super\u00e1vit de 50&nbsp;kcal sin saberlo.<\/p>\n  <p>Por eso es crucial, hiperimportante, <a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/comment-compter-ses-calories\/\">calcular perfectamente tu gasto<\/a>. Y es exactamente ah\u00ed donde MyFitnessPal falla.<\/p>\n<\/section>\n\n<section aria-labelledby=\"p1\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">01 &middot; Problema 1<\/span><\/div>\n  <h2 id=\"p1\">La f\u00f3rmula BMR de 1919<\/h2>\n  <p>Para calcular tu metabolismo basal (el BMR, la energ\u00eda que quemas en reposo), MyFitnessPal utiliza la ecuaci\u00f3n de Harris-Benedict. O su derivada directa, Mifflin-St Jeor. Seg\u00fan las versiones de la app.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figura 1 &middot; Hombre 1,80 m, 120&nbsp;kg, 30&nbsp;% BF<\/span><span class=\"r\">kcal<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\" style=\"position:relative;width:100%;height:380px;min-height:340px\"><canvas id=\"chartBMR\" aria-label=\"Comparaci\u00f3n BMR Harris-Benedict 2500 kcal vs modelo propietario patentado Lean 2000 kcal, diferencia de 500 kcal\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>BMR estimado.<\/strong> El modelo propietario patentado Lean tiene en cuenta la masa magra. Harris-Benedict (MFP), no. Diferencia de 500&nbsp;kcal, el equivalente a un almuerzo entero.<\/p>\n  <\/div>\n\n  <p>Harris-Benedict es de 1919. Estamos a la salida de la Primera Guerra Mundial. Dos investigadores toman a 239 personas, en una sola ciudad (Boston), las tumban en una cama con una m\u00e1scara para calcular el ox\u00edgeno consumido, y sacan una f\u00f3rmula que depende del peso, la altura, la edad y el sexo.<\/p>\n  <p>Para la \u00e9poca, era innovador. En 2025, es inutilizable. Tres razones:<\/p>\n  <ol>\n    <li><strong>La muestra es rid\u00edcula<\/strong>&nbsp;: 239 personas, de una sola ciudad estadounidense, en 1918. En una \u00e9poca en la que hab\u00eda mucho menos sobrepeso que hoy, en la que los niveles hormonales y la composici\u00f3n corporal media no ten\u00edan nada que ver con los nuestros.<\/li>\n    <li><strong>El instrumento de medici\u00f3n era impreciso<\/strong>&nbsp;: la calorimetr\u00eda indirecta de la \u00e9poca ten\u00eda un margen de error enorme. Estudios m\u00e1s modernos han mostrado que Harris-Benedict sobreestima sistem\u00e1ticamente el metabolismo basal.<\/li>\n    <li><strong>El defecto conceptual<\/strong>&nbsp;: la f\u00f3rmula solo tiene en cuenta el peso. Ni la grasa corporal. Ni la masa magra.<\/li>\n  <\/ol>\n  <p>Pero desde los a\u00f1os 80 se sabe que <strong>la masa grasa gasta muy poca energ\u00eda<\/strong> comparada con el resto del cuerpo. El h\u00edgado, el cerebro, el coraz\u00f3n, los ri\u00f1ones y sobre todo los m\u00fasculos son los verdaderos consumidores. La masa grasa es inerte. Una persona con un 30&nbsp;% de grasa corporal no quema ni de lejos lo mismo que una persona con un 10&nbsp;%, incluso a igual peso.<\/p>\n\n  <p>500&nbsp;kcal no es poca cosa. Si MFP te dice \u00ab&nbsp;tu BMR es de 2&nbsp;500&nbsp;\u00bb y en realidad es de 2&nbsp;000, todo lo que sigue est\u00e1 mal.<\/p>\n\n  <div class=\"bodyscan-illust\" style=\"margin:40px auto 8px;display:flex;flex-direction:column;align-items:center;gap:14px;max-width:200px\">\n    <div class=\"mini-phone\" style=\"max-width:200px\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-bodyscan-result.webp\" alt=\"BodyScan IA Lean : bodyfat mesur\u00e9 par photo en 5 secondes\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n    <div class=\"mini-cap\">Grasa corporal real<strong>Foto, 5 segundos<\/strong><\/div>\n  <\/div>\n\n  <div class=\"statement\">\n    <div class=\"num\">400&nbsp;kcal<\/div>\n    <div class=\"lbl\">de diferencia entre dos hombres de 80&nbsp;kg, uno al 10&nbsp;% de grasa corporal (BMR 1&nbsp;900), el otro al 30&nbsp;% (BMR 1&nbsp;500). MFP les da la misma cifra.<\/div>\n  <\/div>\n\n  <p>Conclusi\u00f3n parcial: si una app calcula tu BMR \u00fanicamente a partir de tu peso, tu altura, tu edad y tu sexo, huye. Es matem\u00e1ticamente imposible obtener un resultado fiable.<\/p>\n<\/section>\n\n<section aria-labelledby=\"p2\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">02 &middot; Problema 2<\/span><\/div>\n  <h2 id=\"p2\">El coeficiente de actividad \u00ab&nbsp;casi aleatorio&nbsp;\u00bb<\/h2>\n  <p>Aqu\u00ed es donde la cosa se pone grave. Y probablemente es el punto que nadie te ha explicado.<\/p>\n  <p>Una vez que MFP ha calculado tu BMR (err\u00f3neamente), tiene que estimar tu TDEE total. El <a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/depense-energetique-totale-v2\/\">TDEE, es el BMR + todo lo dem\u00e1s<\/a>&nbsp;: el gasto ligado a los pasos, a las actividades cotidianas, al deporte y a la digesti\u00f3n. Todo lo que no es metabolismo basal.<\/p>\n  <p>\u00bfC\u00f3mo lo hace MyFitnessPal? Te pide marcar una casilla:<\/p>\n  <ul><li>Sedentario<\/li><li>Poco activo<\/li><li>Activo<\/li><li>Muy activo<\/li><\/ul>\n  <p>Y seg\u00fan tu elecci\u00f3n, multiplica tu BMR por un coeficiente (t\u00edpicamente 1,2&nbsp;\/ 1,375&nbsp;\/ 1,55&nbsp;\/ 1,725). Eso es todo. Eso es todo lo que hay detr\u00e1s de tu objetivo cal\u00f3rico diario. Una casilla que T\u00da marcaste una sola vez en el momento del registro. A menudo hace seis meses. Sin moverse desde entonces.<\/p>\n  <p>Y ah\u00ed est\u00e1 el esc\u00e1ndalo silencioso: esa aproximaci\u00f3n es <strong>hiperimperfecta<\/strong>. La diferencia entre un d\u00eda en el que est\u00e1s pegado al sof\u00e1 viendo Netflix y un d\u00eda en el que vas a Disneyland con tus hijos y caminas 15&nbsp;km, <strong>son m\u00e1s de 1&nbsp;000&nbsp;kcal<\/strong>.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figura 2 &middot; 7 d\u00edas reales<\/span><span class=\"r\">kcal\/d\u00eda<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\" style=\"position:relative;width:100%;height:380px;min-height:340px\"><canvas id=\"chartNEAT\" aria-label=\"Variabilidad diaria del gasto cal\u00f3rico en 7 d\u00edas, frente a 2400 kcal fijas seg\u00fan MyFitnessPal\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>Gasto real<\/strong> medido durante 7&nbsp;d\u00edas en un usuario de Lean. La l\u00ednea gris es lo que mostraba MFP (2&nbsp;400&nbsp;kcal fijas). Las anotaciones rosas muestran por qu\u00e9 cada d\u00eda se mueve.<\/p>\n  <\/div>\n\n  <p>No puedes reducir tu nivel de actividad a una casilla est\u00e1tica. Quiz\u00e1 eres activo las semanas en que teletrabajas poco, y sedentario las que no sales de la oficina. Quiz\u00e1 eres activo en verano y sedentario en invierno. Quiz\u00e1 eres activo de martes a viernes y sedentario el fin de semana.<\/p>\n  <p>\u00bfQu\u00e9 casilla vas a marcar esta semana? La verdad es que ninguna de las 4 ser\u00e1 correcta. Y por tanto MFP te va a dar un TDEE sistem\u00e1ticamente desconectado de la realidad.<\/p>\n  <p>Es casi aleatorio. Incluso es un poco mejor que un sorteo, pero no mucho.<\/p>\n  <p>El punto clave de este art\u00edculo: incluso si MyFitnessPal tuviera una f\u00f3rmula BMR perfecta (que no es el caso), el coeficiente de actividad bastar\u00eda para romperlo todo. No puedes estimar un <a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/neat-depense-non-sportive\/\">NEAT<\/a>, un EAT y un <a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/effet-thermique-des-aliments\/\">TEF<\/a> con un multiplicador \u00fanico aplicado al BMR. Es conceptualmente absurdo.<\/p>\n  <p>Lo habr\u00e1s entendido: <strong>una f\u00f3rmula BMR completamente falseada, m\u00e1s una aproximaci\u00f3n de las otras partidas de gasto, no da ninguna posibilidad de alcanzar tus objetivos.<\/strong><\/p>\n\n  <div class=\"cta-band rev\" style=\"display:flex;align-items:center;justify-content:space-between;gap:20px;flex-wrap:wrap;padding:26px 28px;margin:40px 0;background:#FAF5EE;border:1px solid #E8E2D6;border-radius:16px\">\n    <div class=\"l\" style=\"flex:1;min-width:240px;font-size:18px;line-height:1.4;font-weight:500;color:#0E0E10\">Ver tu TDEE real, desglosado en BMR + NEAT + EAT + TEF. Descarga gratuita.<\/div>\n    <div class=\"stores\" style=\"display:flex;gap:10px;align-items:center;flex-wrap:wrap\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"p3\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">03 &middot; Problema 3<\/span><\/div>\n  <h2 id=\"p3\">La adaptaci\u00f3n metab\u00f3lica ignorada<\/h2>\n  <p>Es el jefe final. La noci\u00f3n m\u00e1s fina. Y probablemente la m\u00e1s importante.<\/p>\n  <p>Cuando est\u00e1s en d\u00e9ficit cal\u00f3rico, tu cuerpo entiende que recibe menos energ\u00eda que antes. Para protegerse, pasa a modo ahorro. Exactamente como el modo de bajo consumo de tu iPhone: todo sigue funcionando, pero usando menos energ\u00eda. Tu BMR baja. Tu NEAT baja. Tu EAT baja.<\/p>\n  <p>Es lo que se llama adaptaci\u00f3n metab\u00f3lica. Estas son las cifras:<\/p>\n  <ul>\n    <li>D\u00e9ficit de &minus;250&nbsp;kcal al d\u00eda, durante 2 a 8 semanas: adaptaci\u00f3n metab\u00f3lica del <strong>del 5 al 10&nbsp;%<\/strong><\/li>\n    <li>D\u00e9ficit de &minus;500&nbsp;kcal al d\u00eda: <strong>10 a 15&nbsp;%<\/strong><\/li>\n    <li>D\u00e9ficit de &minus;750&nbsp;kcal al d\u00eda: <strong>15 a 25&nbsp;%<\/strong><\/li>\n  <\/ul>\n  <p>Y como el NEAT, el EAT y el TEF dependen todos del BMR, es casi todo tu TDEE el que se ve afectado.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figura 3 &middot; 8 semanas en d\u00e9ficit<\/span><span class=\"r\">kcal\/d\u00eda<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\" style=\"position:relative;width:100%;height:380px;min-height:340px\"><canvas id=\"chartAdapt\" aria-label=\"TDEE que cae de 2500 a 2150 kcal en 8 semanas, frente a 2500 fijas seg\u00fan MFP\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>TDEE real<\/strong> en 8 semanas de d\u00e9ficit a &minus;500&nbsp;kcal\/d\u00eda. La curva rosa baja. La l\u00ednea gris de MFP se queda plana. En la semana 6, ya est\u00e1s en mantenimiento. Sin haber cambiado nada.<\/p>\n  <\/div>\n\n  <p>Concretamente: si hab\u00edas previsto un d\u00e9ficit del 10&nbsp;% sobre un TDEE de 2&nbsp;500 (es decir, comer 2&nbsp;250 al d\u00eda), y tu cuerpo se adapta un 10&nbsp;%, tu TDEE real ha pasado a 2&nbsp;250. Est\u00e1s en mantenimiento. Ya no pierdes.<\/p>\n  <p>La trampa es que es insidioso. Al principio, pierdes. Est\u00e1s contento. Sigues. Pero semana a semana, la adaptaci\u00f3n se acumula. Y en un momento dado, sin haber cambiado nada en tu tracking, <strong>dejas de perder<\/strong>.<\/p>\n  <p>El 95&nbsp;% de la gente pasa por ah\u00ed sin entenderlo. Culpan a su fuerza de voluntad. Culpan a su \u00ab&nbsp;metabolismo roto&nbsp;\u00bb. Vuelven a dietas m\u00e1s duras, lo que agrava la adaptaci\u00f3n. Espiral.<\/p>\n  <p>MyFitnessPal nunca calcula la adaptaci\u00f3n metab\u00f3lica. Te da un objetivo fijo y est\u00e1tico. Cuando te estancas tras 6 semanas, la app no tiene ni idea del porqu\u00e9.<\/p>\n<\/section>\n\n<section aria-labelledby=\"solution\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">04 &middot; Soluci\u00f3n Lean<\/span><\/div>\n  <h2 id=\"solution\">C\u00f3mo Lean resuelve cada uno de los 3 problemas<\/h2>\n  <p>Lean no se construy\u00f3 como un clon mejorado de MyFitnessPal. Lean se construy\u00f3 como la app que habr\u00edamos querido para seguir en serio la teor\u00eda del TDEE completo. Concretamente, as\u00ed es como Lean trata cada componente.<\/p>\n\n  <div class=\"method\">\n    <div class=\"m-phone\">\n      <div class=\"duo-row\">\n        <div>\n          <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-bodyscan-result.webp\" alt=\"R\u00e9sultat BodyScan IA : pourcentage de masse grasse mesur\u00e9 par photo\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\">Etapa 1<strong>BodyScan IA<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp\" alt=\"\u00c9cran BMR Lean : m\u00e9tabolisme de base calcul\u00e9 sur la masse maigre\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\">Etapa 2<strong>BMR recalculado<\/strong><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n    <div>\n      <div class=\"m-tag\">M.01 &middot; El BMR sobre grasa corporal real<\/div>\n      <h3>Modelo propietario patentado, basado en la masa magra<\/h3>\n      <p>Lean utiliza un <strong>modelo propietario patentado<\/strong> que depende directamente de la masa magra, no del peso bruto. Para eso, la app necesita tu grasa corporal. Y ah\u00ed atacamos lo m\u00e1s pesado hist\u00f3ricamente: \u00bfc\u00f3mo medir tu grasa corporal sin ir a pagar 100&nbsp;\u20ac a la semana por un DEXA?<\/p>\n      <p>Respuesta Lean: el <strong>BodyScan IA<\/strong>. Haces una foto, la app la pasa por un modelo entrenado con un banco masivo de esc\u00e1neres DEXA, y obtienes tu grasa corporal estimada en unos segundos. Puedes repetirlo cada semana. El BMR se recalcula autom\u00e1ticamente.<\/p>\n      <p>Adi\u00f3s al plic\u00f3metro (impreciso), adi\u00f3s a la b\u00e1scula de impedanciometr\u00eda (la estafa del siglo), adi\u00f3s al DEXA (perfecto pero inaccesible). Una foto, 5 segundos.<\/p>\n    <\/div>\n  <\/div>\n\n  <div class=\"method flip\">\n    <div>\n      <div class=\"m-tag\">M.02 &middot; Sin coeficiente de actividad<\/div>\n      <h3>NEAT, EAT, TEF calculados por separado<\/h3>\n      <p><strong>NEAT.<\/strong> Lean recupera tu n\u00famero de pasos reales mediante HealthKit (iOS) o Google Fit (Android). Sin declaraci\u00f3n. Sin \u00ab&nbsp;yo creo que camino bastante&nbsp;\u00bb. Tus pasos, medidos por los aceler\u00f3metros muy precisos de tu smartphone. El <a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/neat-depense-non-sportive\/\">NEAT se calcula cruzando esos pasos con tu BMR<\/a>.<\/p>\n      <p><strong>EAT.<\/strong> Para cada sesi\u00f3n de deporte, seleccionas el deporte en una lista (musculaci\u00f3n, carrera, tenis, nataci\u00f3n, etc.), y Lean utiliza el MET (Metabolic Equivalent Task) de ese deporte para calcular el gasto real. Introduces el tiempo <strong>efectivo<\/strong> de deporte (no el tiempo total con las pausas: el error que cometen el 100&nbsp;% de los relojes conectados). \u00bfUna sesi\u00f3n de musculaci\u00f3n de 1&nbsp;050&nbsp;kcal seg\u00fan tu Apple Watch? La realidad est\u00e1 m\u00e1s cerca de 200&nbsp;kcal. Lean rechaza esa deriva.<\/p>\n      <p><strong>TEF.<\/strong> La digesti\u00f3n quema energ\u00eda, y no es una tarifa fija del 10&nbsp;%. <a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/effet-thermique-des-aliments\/\">Las prote\u00ednas cuestan del 20 al 30&nbsp;%<\/a> de sus calor\u00edas en la digesti\u00f3n. Los carbohidratos del 5 al 10&nbsp;%. Las grasas del 1 al 3&nbsp;%. Lean calcula tu TEF real a partir de tus macros. Con 3&nbsp;000&nbsp;kcal\/d\u00eda, puede representar 100&nbsp;kcal de diferencia seg\u00fan la composici\u00f3n de tu dieta.<\/p>\n    <\/div>\n    <div class=\"m-phone\">\n      <div class=\"mini-row\" style=\"margin:0;gap:10px\">\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp\" alt=\"\u00c9cran NEAT Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">NEAT<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp\" alt=\"\u00c9cran EAT Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">EAT<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp\" alt=\"\u00c9cran TEF Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">TEF<\/strong><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"method flip\">\n    <div>\n      <div class=\"m-tag\">M.03 &middot; Adaptaci\u00f3n metab\u00f3lica autom\u00e1tica<\/div>\n      <h3>Una primicia mundial en una app de consumo<\/h3>\n      <p>Lean es, que sepamos, la primera app en calcular autom\u00e1ticamente la adaptaci\u00f3n metab\u00f3lica. A medida que avanzan tus semanas en d\u00e9ficit, la app ajusta tu TDEE a la baja seg\u00fan las cifras cient\u00edficamente establecidas. No tienes que hacer nada. Solo ves tu objetivo cal\u00f3rico reajustarse suavemente, sin sorpresas.<\/p>\n      <p>Cuando alcanzas del 10 al 15&nbsp;% de adaptaci\u00f3n, la app puede aconsejarte una vuelta al mantenimiento para reiniciar tu BMR antes de volver al d\u00e9ficit. Ciclo, meseta, ciclo. Como en los protocolos reales.<\/p>\n      <p>Ning\u00fan coeficiente de actividad que elegir. Ninguna casilla est\u00e1tica. Solo cada componente calculado con precisi\u00f3n, semana a semana.<\/p>\n    <\/div>\n    <div class=\"m-phone\">\n      <div class=\"mini-phone solo\" style=\"max-width:240px!important;width:240px;padding:6px!important;border-radius:24px!important;border-width:2px!important\"><div class=\"notch\" style=\"width:60px!important;height:14px!important;border-radius:0 0 9px 9px!important\"><\/div><div class=\"scr\" style=\"border-radius:18px!important\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp\" alt=\"\u00c9cran d\u00e9pense totale Lean avec adaptation m\u00e9tabolique\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">M\u00e9todo<strong>Adaptaci\u00f3n metab\u00f3lica<\/strong><\/div>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"tab\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">05 &middot; Tabla comparativa<\/span><\/div>\n  <h2 id=\"tab\">Lean vs MyFitnessPal, criterio por criterio<\/h2>\n  <p>Lectura honesta de las fortalezas y debilidades de cada app. Ning\u00fan criterio se refiere al precio.<\/p>\n\n  <div class=\"brand-banner\" style=\"display:grid;grid-template-columns:1fr 1fr;gap:16px;margin:24px 0 18px;padding:0\">\n  <div style=\"background:#FFF1F5;border:1.5px solid #FF2D6E;border-radius:14px;padding:20px 18px;display:flex;flex-direction:column;align-items:center;text-align:center;gap:10px\">\n    <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"Lean\" width=\"64\" height=\"64\" loading=\"lazy\" decoding=\"async\" style=\"width:64px;height:64px;border-radius:14px;display:block;object-fit:cover\" \/>\n    <div style=\"font-family:-apple-system,BlinkMacSystemFont,'SF Pro Display',sans-serif;font-size:18px;font-weight:700;color:#FF2D6E;letter-spacing:-0.2px\">Lean<\/div>\n  <\/div>\n  <div style=\"background:#F5F5F7;border:1.5px solid #D1D1D6;border-radius:14px;padding:20px 18px;display:flex;flex-direction:column;align-items:center;text-align:center;gap:10px\">\n    <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-myfitnesspal.webp\" alt=\"MyFitnessPal\" width=\"64\" height=\"64\" loading=\"lazy\" decoding=\"async\" style=\"width:64px;height:64px;border-radius:14px;display:block;object-fit:cover\" \/>\n    <div style=\"font-family:-apple-system,BlinkMacSystemFont,'SF Pro Display',sans-serif;font-size:18px;font-weight:700;color:#0E0E10;letter-spacing:-0.2px\">MyFitnessPal<\/div>\n  <\/div>\n<\/div>\n<div class=\"table\" role=\"table\" aria-label=\"Comparativa Lean vs MyFitnessPal\">\n    <div class=\"table-row head\" role=\"row\">\n      <div role=\"columnheader\">Criterio<\/div>\n      <div class=\"brand-cell lean\" role=\"columnheader\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> <span>Lean<\/span><\/div>\n      <div class=\"brand-cell\" role=\"columnheader\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-myfitnesspal.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> <span>MyFitnessPal<\/span><\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">F\u00f3rmula BMR<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Modelo propietario patentado (masa magra)<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Mifflin-St Jeor (solo peso)<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Tiene en cuenta la grasa corporal<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> S\u00ed<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Medici\u00f3n de la grasa corporal en la app<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> BodyScan IA mediante foto<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">NEAT (pasos, actividad fuera del deporte)<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Calculado sobre los pasos reales<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Agregado en el coeficiente<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">EAT (gasto del ejercicio)<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Por deporte mediante MET, tiempo efectivo<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Estimaciones a tanto alzado poco fiables<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">TEF (digesti\u00f3n)<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Calculado seg\u00fan macros<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No calculado<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Adaptaci\u00f3n metab\u00f3lica<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Autom\u00e1tica, semana a semana<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Coeficiente de actividad a elegir<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> No, calculado sobre datos reales<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> S\u00ed, 4 casillas est\u00e1ticas<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Escaneo fotogr\u00e1fico con IA de un plato<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> S\u00ed, ilimitado<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Limitado<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Escaneo de c\u00f3digo de barras<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> S\u00ed<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> S\u00ed<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Base de datos de alimentos<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> USDA + OpenFoodFacts, curada<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Comunitaria, hasta 10&nbsp;000 variantes del mismo alimento<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Recomendaci\u00f3n de d\u00e9ficit cal\u00f3rico<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Adaptada al TDEE real<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Estimaci\u00f3n fija<\/div>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"tracking\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">06 &middot; Tracking<\/span><\/div>\n  <h2 id=\"tracking\">3 m\u00e9todos para registrar una comida<\/h2>\n  <p>Registrar tus calor\u00edas est\u00e1 bien. <a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/comment-compter-ses-calories\/\">Hacerlo durante 12 meses es otra cosa<\/a>. El principio n.\u00ba 1, <strong>antes que la ciencia, antes que los macros, antes que nada<\/strong>, es la adherencia. Si el m\u00e9todo de registro te harta, lo dejas al cabo de 3 semanas. Lean ofrece 3 m\u00e9todos para registrar una comida:<\/p>\n\n  <div class=\"mini-row\">\n    <div>\n      <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-database.webp\" alt=\"Recherche dans la base de donn\u00e9es USDA + OpenFoodFacts\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">M\u00e9todo 1<strong>Base de datos<\/strong><\/div>\n    <\/div>\n    <div>\n      <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-codebarre.webp\" alt=\"Scan de code-barres dans Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">M\u00e9todo 2<strong>C\u00f3digo de barras<\/strong><\/div>\n    <\/div>\n    <div>\n      <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-scania.webp\" alt=\"Scan photo IA d'un plat\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">M\u00e9todo 3<strong>Escaneo fotogr\u00e1fico con IA<\/strong><\/div>\n    <\/div>\n  <\/div>\n\n  <ol>\n    <li><strong>B\u00fasqueda en la base de datos.<\/strong> Base curada, USDA + OpenFoodFacts. Sin ruido comunitario, sin \u00ab&nbsp;Pollo asado&nbsp;\u00bb introducido 47 veces por 47 usuarios distintos con 47 valores distintos.<\/li>\n    <li><strong>Escaneo de c\u00f3digo de barras.<\/strong> Est\u00e1ndar. Escaneas tu paquete de pasta, obtienes los macros.<\/li>\n    <li><strong>Escaneo fotogr\u00e1fico con IA de un plato.<\/strong> Fotograf\u00edas tu plato, la IA detecta los alimentos, obtienes las calor\u00edas y los macros por alimento.<\/li>\n  <\/ol>\n  <p>El escaneo fotogr\u00e1fico con IA es el game changer de la adherencia. Cuando comes fuera, en el restaurante, en casa de amigos, es superpr\u00e1ctico. Una foto, cierras la app, disfrutas de tu velada. S\u00ed, es menos preciso que un pesaje al gramo con una b\u00e1scula de cocina. Pero en 12 meses, es lo que marca la diferencia entre aguantar y abandonar. Y aguantar es lo que cuenta.<\/p>\n  <p>M\u00e1s all\u00e1 del registro por comida, Lean muestra un <strong>TDEE en vivo que se actualiza durante el d\u00eda<\/strong>. Cuanto m\u00e1s caminas, m\u00e1s aumenta tu gasto, m\u00e1s se ajusta tu objetivo cal\u00f3rico del d\u00eda. Ves tu balance cal\u00f3rico en directo. Es m\u00e1s motivador que una cifra congelada a las 8 de la ma\u00f1ana.<\/p>\n  <p>Y por encima de todo eso, est\u00e1 la <strong>Pir\u00e1mide de Progresi\u00f3n<\/strong>. Es una pantalla de la app que jerarquiza lo que cuenta:<\/p>\n\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<\/span><span class=\"k\">Nivel 2<\/span><\/div>\n    <div class=\"level l3\"><span>Pasos \/ NEAT<\/span><span class=\"k\">Nivel 3<\/span><\/div>\n    <div class=\"level l4\"><span>Macronutrientes<\/span><span class=\"k\">Cima<\/span><\/div>\n  <\/div>\n  <div class=\"pyramid-cap\">No quemar etapas. Si no eres regular en el tracking, optimizar los macros al uno por ciento no sirve de nada.<\/div>\n<\/section>\n\n<section aria-labelledby=\"mfp-better\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">07 &middot; Honestidad<\/span><\/div>\n  <h2 id=\"mfp-better\">Lo que MyFitnessPal hace mejor<\/h2>\n  <p>Lean no es perfecto, MFP tiene algunas ventajas que hay que reconocer. Lectura honesta, criterio por criterio, en los ejes donde MFP sigue por delante.<\/p>\n\n  <div class=\"scorecard rev\" aria-label=\"Scorecard MFP vs Lean en 4 ejes secundarios\">\n    <div class=\"scorecard-head\">\n      <div class=\"h-crit\">Eje<\/div>\n      <div class=\"h-brand\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-myfitnesspal.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> MyFitnessPal<\/div>\n      <div class=\"h-brand\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> Lean<\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Notoriedad &amp; tutoriales online<\/div>\n      <div class=\"bar mfp\" data-brand=\"MFP\"><div class=\"b\"><i style=\"width:95%\"><\/i><\/div><div class=\"v\">9,5<\/div><\/div>\n      <div class=\"bar lean\" data-brand=\"LEAN\"><div class=\"b\"><i style=\"width:40%\"><\/i><\/div><div class=\"v\">4,0<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Tama\u00f1o de la base de datos<\/div>\n      <div class=\"bar mfp\" data-brand=\"MFP\"><div class=\"b\"><i style=\"width:90%\"><\/i><\/div><div class=\"v\">9,0<\/div><\/div>\n      <div class=\"bar lean\" data-brand=\"LEAN\"><div class=\"b\"><i style=\"width:75%\"><\/i><\/div><div class=\"v\">7,5<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Comunidad \/ feed social<\/div>\n      <div class=\"bar mfp\" data-brand=\"MFP\"><div class=\"b\"><i style=\"width:80%\"><\/i><\/div><div class=\"v\">8,0<\/div><\/div>\n      <div class=\"bar lean\" data-brand=\"LEAN\"><div class=\"b\"><i style=\"width:20%\"><\/i><\/div><div class=\"v\">2,0<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Integraciones con apps de terceros<\/div>\n      <div class=\"bar mfp\" data-brand=\"MFP\"><div class=\"b\"><i style=\"width:85%\"><\/i><\/div><div class=\"v\">8,5<\/div><\/div>\n      <div class=\"bar lean\" data-brand=\"LEAN\"><div class=\"b\"><i style=\"width:70%\"><\/i><\/div><div class=\"v\">7,0<\/div><\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>Lectura honesta.<\/strong> En notoriedad y feed social, MFP sigue por delante. En tama\u00f1o bruto de la base de datos de alimentos, MFP tiene m\u00e1s entradas (pero los 14 millones de entradas son comunitarias y ruidosas, hasta 10&nbsp;000 variantes del mismo alimento). En integraciones de terceros, MFP tiene un ecosistema m\u00e1s amplio. Lean se integra con HealthKit y Google Fit, lo que cubre el 95&nbsp;% de los casos.<\/p>\n  <p>En resumen, si todo lo que quieres es un diario alimentario aproximado sin objetivo preciso, MFP basta de sobra. Si buscas perder grasa met\u00f3dicamente con un <a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/tdee-calculator\/\">TDEE preciso<\/a>, MFP no basta, y es lo que acaba de demostrarse en las 3 secciones anteriores.<\/p>\n<\/section>\n\n<section aria-labelledby=\"forwho\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">08 &middot; Para qui\u00e9n<\/span><\/div>\n  <h2 id=\"forwho\">Para qui\u00e9n est\u00e1 hecho Lean<\/h2>\n  <p>4 perfiles. Si te reconoces en al menos uno, Lean probablemente est\u00e1 hecho para ti.<\/p>\n\n  <div class=\"persona\">\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>Has probado MFP en serio y no has perdido<\/h4>\n        <p>Has aplicado un d\u00e9ficit honesto durante semanas, sin resultado. La causa es muy probablemente el TDEE falseado. Lean corrige de ra\u00edz mediante el BMR sobre grasa corporal real.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>Te estancas tras varias semanas de definici\u00f3n<\/h4>\n        <p>Meseta que se eterniza tras 4 a 8 semanas. Es la adaptaci\u00f3n metab\u00f3lica. Lean la calcula autom\u00e1ticamente y reajusta tu objetivo cada semana.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>Quieres entender tu metabolismo<\/h4>\n        <p>Lean muestra cada componente (BMR, NEAT, EAT, TEF, adaptaci\u00f3n) en lugar de esconderlo todo detr\u00e1s de una cifra \u00fanica. Ves de d\u00f3nde viene cada kcal de gasto.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>Quieres un tracking que dure 12 meses<\/h4>\n        <p>Escaneo fotogr\u00e1fico con IA + base curada + c\u00f3digo de barras cubren todos los usos, del alimento crudo a la pizza en el restaurante. Es lo que marca la diferencia entre aguantar y abandonar.<\/p>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>MyFitnessPal puede bastar para<\/strong>&nbsp;: quienes solo quieren un diario alimentario sin precisi\u00f3n particular, o quienes aprecian el lado social y comunitario.<\/p>\n<\/section>\n\n<section aria-labelledby=\"migrate\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">09 &middot; Migraci\u00f3n<\/span><\/div>\n  <h2 id=\"migrate\">Migrar de MyFitnessPal a Lean en 5 minutos<\/h2>\n\n  <div class=\"steps\">\n    <div class=\"step\"><div class=\"sn\">01<\/div><h4>Descarga Lean<\/h4><p>App Store o Play Store. Registro en 30 segundos.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">02<\/div><h4>BodyScan IA<\/h4><p>Una foto, 5 segundos. Obtienes tu grasa corporal.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">03<\/div><h4>Peso &amp; altura<\/h4><p>Introduce tu peso y tu altura. Eso es todo.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">04<\/div><h4>Lean calcula<\/h4><p>BMR, NEAT (HealthKit \/ Google Fit), EAT, TEF, adaptaci\u00f3n. Autom\u00e1tico.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">05<\/div><h4>Registra una comida<\/h4><p>Foto, c\u00f3digo de barras o base de datos. Entiende el flujo.<\/p><\/div>\n  <\/div>\n\n  <p style=\"margin-top:24px\"><strong>Nota importante.<\/strong> Lean no ofrece importaci\u00f3n autom\u00e1tica de tus datos de MyFitnessPal. Es voluntario. La base de MFP la introducen a mano los usuarios, as\u00ed que es ruidosa. Preferimos empezar limpios, con una base curada USDA + OpenFoodFacts, en lugar de heredar el ruido.<\/p>\n\n  <div class=\"cta-band rev\" style=\"display:flex;align-items:center;justify-content:space-between;gap:20px;flex-wrap:wrap;padding:26px 28px;margin:40px 0;background:#FAF5EE;border:1px solid #E8E2D6;border-radius:16px\">\n    <div class=\"l\" style=\"flex:1;min-width:240px;font-size:18px;line-height:1.4;font-weight:500;color:#0E0E10\">Descarga Lean y empieza el BodyScan IA ahora mismo. Registro gratuito.<\/div>\n    <div class=\"stores\" style=\"display:flex;gap:10px;align-items:center;flex-wrap:wrap\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"deblock-h\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">10 &middot; Lo que Lean desbloquea<\/span><\/div>\n  <h2 id=\"deblock-h\">Lo que Lean hace, y que MFP nunca har\u00e1<\/h2>\n  <p>Seis funcionalidades que no existen en ning\u00fan otro tracker de consumo. Todas derivan del mismo principio: calcular cada componente del TDEE con precisi\u00f3n, no aproximarlo.<\/p>\n\n  <div class=\"feat-stack\">\n    <div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">BodyScan IA ilimitado<\/div><p class=\"fd\">Tu grasa corporal real, medida a partir de una simple foto, repetida cada semana. Es el dato que cambia todo el c\u00e1lculo del BMR. Ninguna otra app de consumo ofrece esto.<\/p><\/div><div class=\"fc\">Grasa corporal<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">Escaneo fotogr\u00e1fico con IA de un plato ilimitado<\/div><p class=\"fd\">Registra tu comida en el restaurante en 2 segundos. Sin b\u00e1scula, sin introducci\u00f3n manual. El game changer de la adherencia a 12 meses.<\/p><\/div><div class=\"fc\">Adherencia<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">Adaptaci\u00f3n metab\u00f3lica autom\u00e1tica<\/div><p class=\"fd\">Tu TDEE se reajusta semana a semana seg\u00fan las cifras cient\u00edficamente establecidas. Evitas los estancamientos que nadie sabe explicar.<\/p><\/div><div class=\"fc\">Adaptaci\u00f3n<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">04<\/div><div><div class=\"ft\">TDEE desglosado en vivo<\/div><p class=\"fd\">BMR + NEAT + EAT + TEF mostrados cada uno, actualizados durante el d\u00eda. Se acab\u00f3 la cifra congelada a las 8 de la ma\u00f1ana. Ves tu balance cal\u00f3rico en directo.<\/p><\/div><div class=\"fc\">En vivo<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">05<\/div><div><div class=\"ft\">Historial completo y tendencias<\/div><p class=\"fd\">Sigue tus tendencias de peso, grasa corporal, masa magra durante meses. Entiende tus ciclos. Detecta las fases en las que progresas y en las que te estancas.<\/p><\/div><div class=\"fc\">Historial<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">06<\/div><div><div class=\"ft\">3 m\u00e9todos de tracking unificados<\/div><p class=\"fd\">Foto, c\u00f3digo de barras, base curada. Ninguna otra app ofrece los tres con tal precisi\u00f3n. Eliges el m\u00e9todo seg\u00fan el contexto.<\/p><\/div><div class=\"fc\">Tracking<\/div><\/div>\n  <\/div>\n\n  <p style=\"margin-top:26px\">Instalas la app gratis, pruebas sin compromiso y luego decides si la herramienta encaja con tu objetivo.<\/p>\n<\/section>\n\n<section aria-labelledby=\"faq-h\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">11 &middot; FAQ<\/span><\/div>\n  <h2 id=\"faq-h\">Preguntas frecuentes<\/h2>\n  <div class=\"faq\">\n    <details><summary>\u00bfMifflin-St Jeor es mejor que Harris-Benedict?<\/summary><div class=\"ans\">Marginalmente. Mifflin-St Jeor (1990) es una actualizaci\u00f3n de Harris-Benedict con una muestra ligeramente m\u00e1s moderna. Pero hereda el mismo defecto conceptual: sin grasa corporal como entrada. Es solo una versi\u00f3n repintada del mismo error. MFP usa Mifflin-St Jeor desde hace unos a\u00f1os, lo que es mejor que Harris-Benedict, pero no corrige el problema fundamental.<\/div><\/details>\n    <details><summary>\u00bfHace falta realmente conocer tu grasa corporal?<\/summary><div class=\"ans\">S\u00ed. Sin grasa corporal, tu BMR puede estar mal en 400&nbsp;kcal (ver el ejemplo de los dos hombres de 80&nbsp;kg, uno al 10&nbsp;%, el otro al 30&nbsp;%). Nunca perder\u00e1s peso en serio sin ese dato. Medirlo cada semana con el BodyScan IA lleva 5 segundos.<\/div><\/details>\n    <details><summary>\u00bfEl coeficiente de actividad no funciona en absoluto?<\/summary><div class=\"ans\">Para una estimaci\u00f3n ultraaproximada a 6 meses, puede dar una vaga tendencia. Para alcanzar un objetivo preciso (p\u00e9rdida de grasa, ganancia de masa limpia), es insuficiente. La variabilidad diaria del gasto es demasiado grande para captarla con una casilla est\u00e1tica.<\/div><\/details>\n    <details><summary>\u00bfQu\u00e9 es exactamente la adaptaci\u00f3n metab\u00f3lica?<\/summary><div class=\"ans\">Es la bajada espont\u00e1nea de tu gasto cal\u00f3rico cuando est\u00e1s en d\u00e9ficit prolongado. Modo de ahorro de energ\u00eda. Para un d\u00e9ficit de &minus;500&nbsp;kcal\/d\u00eda, tu TDEE puede bajar del 10 al 15&nbsp;% en 4 a 6 semanas. Si una app no lo sabe, te estancas sin entender por qu\u00e9.<\/div><\/details>\n    <details><summary>\u00bfCu\u00e1nto tiempo para ver un resultado con Lean?<\/summary><div class=\"ans\">Todo depende del d\u00e9ficit aplicado. Para un d\u00e9ficit razonable de &minus;250 a &minus;500&nbsp;kcal\/d\u00eda, deber\u00edas ver una p\u00e9rdida de 0,3 a 0,6&nbsp;kg por semana. La gran diferencia con MFP: con Lean tu TDEE se conoce con precisi\u00f3n, as\u00ed que tu d\u00e9ficit se aplica realmente, sin sorpresa estad\u00edstica.<\/div><\/details>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"conclu\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">12 &middot; Conclusi\u00f3n<\/span><\/div>\n  <h2 id=\"conclu\">1919 frente a 2025<\/h2>\n  <p>No es MyFitnessPal contra Lean en marketing. Es 1919 frente a 2025 en ciencia.<\/p>\n  <p>MFP usa una f\u00f3rmula de la salida de la Primera Guerra Mundial, m\u00e1s un coeficiente de actividad casi aleatorio, e ignora la adaptaci\u00f3n metab\u00f3lica. La combinaci\u00f3n de los tres hace imposible cualquier estimaci\u00f3n precisa. Es matem\u00e1tico.<\/p>\n  <p>Lean se construy\u00f3 para hacer exactamente lo contrario: BMR basado en la <a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/depense-energetique-totale-v2\/\">grasa corporal real<\/a> (medido por BodyScan IA) mediante un modelo propietario patentado, <a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/neat-depense-non-sportive\/\">NEAT por pasos reales<\/a>, EAT por deporte y MET, <a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/effet-thermique-des-aliments\/\">TEF por macros<\/a>, adaptaci\u00f3n metab\u00f3lica autom\u00e1tica. Cada componente calculado con precisi\u00f3n, sin coeficiente m\u00e1gico.<\/p>\n  <p>Si has probado MFP en serio y no has tenido los resultados que esperabas, el problema no eres t\u00fa. El problema est\u00e1 bajo el cap\u00f3. Cambia de app.<\/p>\n<\/section>\n\n<div class=\"get-band rev\" style=\"background:#F1E9DC;border-radius:24px;padding:48px 36px;margin:60px 0 40px;text-align:center\">\n  <div class=\"kicker\">Descarga<\/div>\n  <h3>Lean se puede descargar gratis<\/h3>\n  <p>iOS y Android. El BodyScan IA funciona con una simple foto. Sin plic\u00f3metro, sin b\u00e1scula de impedancia, sin DEXA.<\/p>\n  <div class=\"stores\" style=\"display:flex;gap:10px;align-items:center;flex-wrap:wrap\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" target=\"_blank\" rel=\"noopener\" aria-label=\"Descargar Lean en la App Store\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" target=\"_blank\" rel=\"noopener\" aria-label=\"Descargar Lean en Google Play\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/>\n    <\/a>\n  <\/div>\n<\/div>\n\n<section aria-labelledby=\"links\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">Para ir m\u00e1s lejos<\/span><\/div>\n  <h3 id=\"links\" style=\"margin-top:0\">Enlaces internos<\/h3>\n  <ul>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/tdee-calculator\/\">Calculadora TDEE gratuita en l\u00ednea<\/a> &middot; versi\u00f3n web, sin registro, misma l\u00f3gica que la app (BMR + NEAT + EAT + TEF).<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/depense-energetique-totale-v2\/\">Entender el TDEE en detalle (BMR, NEAT, EAT, TEF, adaptaci\u00f3n)<\/a> &middot; art\u00edculo cient\u00edfico de fondo.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/comment-compter-ses-calories\/\">C\u00f3mo contar tus calor\u00edas correctamente<\/a> &middot; gu\u00eda pr\u00e1ctica para principiantes.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/neat-depense-non-sportive\/\">NEAT&nbsp;: gasto por pasos y actividad fuera del deporte<\/a>.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/effet-thermique-des-aliments\/\">TEF&nbsp;: la digesti\u00f3n quema calor\u00edas<\/a>.<\/li>\n  <\/ul>\n<\/section>\n\n<section aria-labelledby=\"src\" class=\"sources\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">Fuentes<\/span><\/div>\n  <h3 id=\"src\" style=\"margin-top:0;color:var(--ink)\">Bibliograf\u00eda<\/h3>\n  <ol>\n    <li>Harris J.A., Benedict F.G. (1919). A Biometric Study of Basal Metabolism in Man. Carnegie Institution of Washington.<\/li>\n    <li>Mifflin M.D. et al. (1990). A new predictive equation for resting energy expenditure in healthy individuals. American Journal of Clinical Nutrition.<\/li>\n    <li>Shcherbina A. et al. (Stanford University, 2017). Accuracy in Wrist-Worn Wearable Devices for Measuring Heart Rate and Energy Expenditure.<\/li>\n    <li>Westerterp K.R. (2004). Diet induced thermogenesis. Nutrition and Metabolism.<\/li>\n    <li>Rosenbaum M., Leibel R.L. (2010). Adaptive thermogenesis in humans. International Journal of Obesity.<\/li>\n    <li>M\u00fcller M.J., Bosy-Westphal A. (2013). Adaptive thermogenesis with weight loss in humans. Obesity.<\/li>\n  <\/ol>\n<\/section>\n\n<\/main>\n\n<footer>\n  <div class=\"wrap\">\n    <div class=\"row\">\n      <div>\n        <div class=\"kicker\">Lean &middot; lean-app.com<\/div>\n        <p>Art\u00edculo publicado el 21 de mayo de 2026. Actualizado regularmente con las opiniones de los usuarios y los nuevos estudios relevantes. Lean est\u00e1 disponible en iOS y Android.<\/p>\n      <\/div>\n      <div class=\"stores\" style=\"display:flex;gap:10px;align-items:center;flex-wrap:wrap\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n        <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-mfp\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n      <\/div>\n    <\/div>\n  <\/div>\n<\/footer>\n\n<script data-wpmeteor-nooptimize=\"true\">\n(function(){\n  var bar = document.getElementById('progBar');\n  function up(){\n    var h = document.documentElement;\n    var sc = (h.scrollTop)\/Math.max(1,(h.scrollHeight - h.clientHeight));\n    bar.style.transform = 'scaleX(' + Math.max(0,Math.min(1,sc)) + ')';\n  }\n  document.addEventListener('scroll', up, {passive:true});\n  up();\n})();\n\n(function(){\n  if (!('IntersectionObserver' in window)) {\n    document.querySelectorAll('.rev').forEach(function(n){n.classList.add('on')});\n    return;\n  }\n  var obs = new IntersectionObserver(function(entries){\n    entries.forEach(function(e){\n      if (e.isIntersecting) { e.target.classList.add('on'); obs.unobserve(e.target); }\n    });\n  }, {threshold:0.12});\n  document.querySelectorAll('.rev').forEach(function(n){ obs.observe(n); });\n})();\n\n(function(){\n  var phoneImg = document.getElementById('phoneImg');\n  var phoneBack = document.getElementById('phoneBack');\n  var zones = document.getElementById('phoneZones');\n  var topTabs = document.querySelectorAll('.phone-tabs button');\n  var navTaps = document.querySelectorAll('.phone-navbar button');\n\n  var tabMap = {\n    bilan:    {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp',     drill:false},\n    kcal:     {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp',      drill:false},\n    depense:  {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp',   drill:true},\n    strategie:{src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp', drill:false}\n  };\n  var subMap = {\n    BMR:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp',\n    NEAT: 'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp',\n    EAT:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp',\n    TEF:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp'\n  };\n  var currentTab = 'depense';\n\n  function setActive(tab){\n    topTabs.forEach(function(b){ b.classList.toggle('on', b.dataset.tab===tab); });\n  }\n  function showTab(tab){\n    var t = tabMap[tab]; if(!t) return;\n    currentTab = tab;\n    phoneImg.style.opacity = 0;\n    setTimeout(function(){\n      phoneImg.className = 'phone-bg tab-' + tab;\n      phoneImg.style.opacity = 1;\n      zones.style.display = t.drill ? 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Le hicimos la pregunta 291 veces a 5 IA <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">291 respuestas, 5 IA, 6 perfiles id\u00e9nticos: hasta 1 260 kcal de diferencia para la misma persona, y ning\u00fan seguimiento al d\u00eda siguiente.<\/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\/comparatifs\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Todas las comparativas de Lean frente a las grandes apps de calor\u00edas <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Hub: MyFitnessPal, Yazio, Cronometer, Lifesum, FatSecret, Noom.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/lean-vs-yazio\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean frente a Yazio: precisi\u00f3n cient\u00edfica vs ergonom\u00eda europea <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Comparativa BMR, NEAT, EAT, TEF, adaptaci\u00f3n.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/lean-vs-foodvisor\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean frente a Foodvisor: pionero del escaneo de fotos vs gasto real <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Foodvisor ve tu plato. Lean recompone tu TDEE de forma continua.<\/span><\/a><\/li><\/ul><\/aside>","protected":false},"excerpt":{"rendered":"<p>MyFitnessPal calcule votre TDEE avec une formule de 1919, sans bodyfat ni adaptation m\u00e9tabolique. Lean fait tout ce que MFP ne sait pas faire. Comparatif honn\u00eate.<\/p>","protected":false},"author":1,"featured_media":1242,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"single-lvm-blank","format":"standard","meta":{"footnotes":""},"categories":[13],"tags":[],"class_list":["post-1241","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-comparateurs"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Lean vs MyFitnessPal: la f\u00f3rmula TDEE que lo cambia todo - Lean<\/title>\n<meta name=\"description\" content=\"Por qu\u00e9 MyFitnessPal calcula mal tu gasto cal\u00f3rico: BMR con f\u00f3rmula de 1919, sin adaptaci\u00f3n metab\u00f3lica, NEAT\/EAT fijos. 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