{"id":1352,"date":"2026-05-23T13:43:16","date_gmt":"2026-05-23T13:43:16","guid":{"rendered":"https:\/\/lean-app.com\/?p=1352"},"modified":"2026-09-08T18:18:03","modified_gmt":"2026-09-08T18:18:03","slug":"lean-vs-yazio","status":"publish","type":"post","link":"https:\/\/lean-app.com\/es\/lean-vs-yazio\/","title":{"rendered":"Lean frente a Yazio: \u00bfqui\u00e9n calcula realmente tu gasto cal\u00f3rico en 2026?"},"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-1352 #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-1352 #lvm-shell .wrap,\nbody.postid-1352 #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-1352 #lvm-shell .wrap,\n  body.postid-1352 #lvm-shell main.wrap{padding-left:18px!important;padding-right:18px!important}\n}\nhtml, body{overflow-x:hidden!important}\nbody.postid-1352 #lvm-shell{overflow-x:hidden;max-width:100vw}\nbody.postid-1352 #lvm-shell *{max-width:100%}\nbody.postid-1352 #lvm-shell .nav-row{max-width:100vw;box-sizing:border-box}\nbody.postid-1352 #lvm-shell.force-show .rev{opacity:1!important;transform:none!important}\n\n\/* === A.1 PHONE BACKGROUND CLASSES === *\/\nbody.postid-1352 #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-1352 #lvm-shell .phone-bg.tab-depense{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp)}\nbody.postid-1352 #lvm-shell .phone-bg.tab-bilan{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp)}\nbody.postid-1352 #lvm-shell .phone-bg.tab-kcal{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp)}\nbody.postid-1352 #lvm-shell .phone-bg.tab-strategie{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp)}\nbody.postid-1352 #lvm-shell .phone-bg.sub-BMR{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp)}\nbody.postid-1352 #lvm-shell .phone-bg.sub-NEAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp)}\nbody.postid-1352 #lvm-shell .phone-bg.sub-EAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp)}\nbody.postid-1352 #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-1352 #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-1352 #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-1352 #lvm-shell .cta-band .stores{width:100%!important;justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1352 #lvm-shell .cta-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1352 #lvm-shell .cta-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1352 #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-1352 #lvm-shell .get-band{padding:38px 22px!important}\n  body.postid-1352 #lvm-shell .get-band .stores{justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1352 #lvm-shell .get-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1352 #lvm-shell .get-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1352 #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-1352 #lvm-shell .get-band h3{font-size:26px!important;line-height:1.2!important}\n  body.postid-1352 #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-1352 #lvm-shell .brand-banner img{width:54px!important;height:54px!important}\n  body.postid-1352 #lvm-shell .brand-banner > div{padding:16px 12px!important;gap:8px!important}\n  body.postid-1352 #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-1352 #lvm-shell .scorecard{padding:18px 16px!important;border-radius:16px!important}\n  body.postid-1352 #lvm-shell .scorecard-head{display:none!important}\n  body.postid-1352 #lvm-shell .scorecard-row{\n    display:block!important;\n    padding:14px 0!important;\n    border-bottom:1px solid #E8E2D6!important;\n  }\n  body.postid-1352 #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-1352 #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-1352 #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-1352 #lvm-shell .scorecard-row .bar.lean::before{color:#FF2D6E!important}\n  body.postid-1352 #lvm-shell .scorecard-row .bar.mfp::before{color:#5B7FFF!important}\n  body.postid-1352 #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-1352 #lvm-shell .scorecard-row .bar .b > i{\n    display:block!important;\n    height:100%!important;\n    border-radius:99px!important;\n  }\n  body.postid-1352 #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-1352 #lvm-shell .cv-wrap{height:380px!important;min-height:360px!important;max-height:420px!important;width:100%!important}\n  body.postid-1352 #lvm-shell .cv-wrap canvas{width:100%!important;height:100%!important;display:block!important}\n  body.postid-1352 #lvm-shell .fig{padding:16px 4px 14px!important;margin:24px -4px 14px!important;overflow:visible!important}\n  body.postid-1352 #lvm-shell .fig-head{padding:0 12px!important;flex-wrap:wrap!important;gap:6px!important;margin-bottom:10px!important}\n  body.postid-1352 #lvm-shell .fig-body{padding:0 2px!important}\n  body.postid-1352 #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-1352 #lvm-shell .cv-wrap{height:360px!important;min-height:340px!important;max-height:380px!important}\n  body.postid-1352 #lvm-shell .fig{padding:14px 2px 12px!important;margin:20px -6px 12px!important;border-radius:14px!important}\n  body.postid-1352 #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-1352 #lvm-shell .table{border-radius:14px!important}\n  body.postid-1352 #lvm-shell .table-row.head{display:none!important}\n  body.postid-1352 #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-1352 #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-1352 #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-1352 #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-1352 #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-1352 #lvm-shell .table-row > .cell:not(.lean):not(.crit)::before{\n    content:\"YAZIO\"!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:#02BB8C!important;\n  }\n  body.postid-1352 #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-1352 #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-1352 #lvm-shell .mini-row{gap:6px!important;margin:24px 0!important;grid-template-columns:repeat(3,1fr)!important}\n  body.postid-1352 #lvm-shell .mini-phone{max-width:100px!important;padding:2px!important;border-radius:14px!important;border-width:1px!important}\n  body.postid-1352 #lvm-shell .mini-phone.tiny{max-width:96px!important;padding:2px!important;border-radius:13px!important}\n  body.postid-1352 #lvm-shell .mini-phone .notch{width:30px!important;height:8px!important;border-radius:0 0 5px 5px!important}\n  body.postid-1352 #lvm-shell .mini-phone .scr{border-radius:11px!important}\n  body.postid-1352 #lvm-shell .mini-cap{font-size:10px!important;margin-top:8px!important}\n  body.postid-1352 #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-1352 #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-1352 #lvm-shell .tap-hint.desktop{display:none!important}\n  body.postid-1352 #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-1352 #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-1352 #lvm-shell .bodyscan-illust .mini-phone{max-width:200px!important;padding:3px!important;border-radius:22px!important;border-width:1px!important}\nbody.postid-1352 #lvm-shell .bodyscan-illust .mini-phone .notch{width:40px!important;height:11px!important;border-radius:0 0 7px 7px!important}\nbody.postid-1352 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:18px!important}\n@media (max-width:760px){\n  body.postid-1352 #lvm-shell .bodyscan-illust{max-width:180px!important}\n  body.postid-1352 #lvm-shell .bodyscan-illust .mini-phone{max-width:160px!important;padding:3px!important;border-radius:20px!important}\n  body.postid-1352 #lvm-shell .bodyscan-illust .mini-phone .notch{width:34px!important;height:9px!important;border-radius:0 0 6px 6px!important}\n  body.postid-1352 #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-yazio\" 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-yazio\" 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 Yazio<\/div>\n  <div class=\"eyebrow\">Comparativa &middot; Nutrici\u00f3n &amp; TDEE<\/div>\n  <h1 id=\"title\">Lean frente a Yazio.\n    <span class=\"alt\">El tracker de calor\u00edas m\u00e1s querido de Europa frente al \u00fanico que recompone tu TDEE de forma continua.<\/span>\n  <\/h1>\n  <p class=\"dek\">Yazio cuenta. Lean calcula. La diferencia se ve tras 6 semanas.<\/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-yazio\" 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-yazio\" 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      Yazio es enorme y excelente en ayuno intermitente y en sus m\u00e1s de 3&nbsp;000 recetas guiadas. Pero su f\u00f3rmula del TDEE sigue siendo Mifflin-St Jeor 1990, m\u00e1s un nivel de actividad fijo que marcas una sola vez en el registro (una de las 5 casillas sedentario\/bajo\/moderado\/activo\/muy activo). Sin grasa corporal, sin adaptaci\u00f3n metab\u00f3lica. En 3 meses de definici\u00f3n seria, la brecha se agranda.\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>Yazio calcula tu TDEE con Mifflin-St Jeor 1990 (sin grasa corporal) y un nivel de actividad fijo que marcas una vez en el registro, entre 5 casillas (sedentario, bajo, moderado, activo, muy activo). La f\u00f3rmula es m\u00e1s moderna que Harris-Benedict 1919 pero hereda el mismo defecto: sin masa magra, sin NEAT medido por los pasos, sin adaptaci\u00f3n metab\u00f3lica. 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 mediante un modelo propietario patentado, <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) y modula el BMR con la adaptaci\u00f3n metab\u00f3lica de forma continua, sin coeficiente 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\">Yazio te acompa\u00f1a durante 100 d\u00edas, hasta el momento en que tu cuerpo se adapta<\/h2>\n  <p>Si lees esto, probablemente ya has instalado Yazio. Has introducido tu peso, tu altura, tu edad, tu sexo. La app te pidi\u00f3 marcar tu nivel de actividad en una lista de 5 casillas (sedentario, bajo, moderado, activo, muy activo). Te mostr\u00f3 un objetivo cal\u00f3rico, digamos 2&nbsp;250&nbsp;kcal para perder peso. Lo seguiste religiosamente. Usaste el 16:8, cocinaste las recetas guiadas, escaneaste tus c\u00f3digos de barras.<\/p>\n  <p>Las primeras 6 semanas, funciona. Pierdes. Est\u00e1s contento. Luego, hacia la semana 8, la b\u00e1scula se congela. Te dices: \u00ab&nbsp;me habr\u00e9 relajado, habr\u00e9 registrado mal&nbsp;\u00bb. Aprietas las tuercas. Bajas a 2&nbsp;000&nbsp;kcal. Otra vez, nada se mueve.<\/p>\n\n  <div class=\"statement\">\n    <div class=\"num\">&minus;10 a &minus;15&nbsp;%<\/div>\n    <div class=\"lbl\">de bajada medida del TDEE tras 4 a 6 semanas de d\u00e9ficit a &minus;500&nbsp;kcal\/d\u00eda. Yazio no lo detecta. Tu objetivo cal\u00f3rico se queda congelado en tu elecci\u00f3n de hace 100&nbsp;d\u00edas.<\/div>\n  <\/div>\n\n  <p>Imaginemos que Yazio 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 ha bajado a 2&nbsp;200&nbsp;kcal<\/a> por la adaptaci\u00f3n metab\u00f3lica. Est\u00e1s en super\u00e1vit de 50&nbsp;kcal sin saberlo. Ninguna posibilidad de seguir perdiendo.<\/p>\n  <p>Por eso es crucial <a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/comment-compter-ses-calories\/\">calcular perfectamente tu gasto<\/a>, y recalcularlo de forma continua. Y es exactamente ah\u00ed donde Yazio, como la mayor\u00eda de los trackers de consumo, se queda congelado en la estimaci\u00f3n inicial.<\/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 1990, sin grasa corporal<\/h2>\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 Mifflin-St Jeor 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. Mifflin-St Jeor (Yazio), no. Diferencia de 500&nbsp;kcal, el equivalente a un almuerzo entero.<\/p>\n  <\/div>\n\n  <p>Para calcular tu metabolismo basal (el BMR, la energ\u00eda que quemas en reposo), Yazio utiliza la ecuaci\u00f3n de Mifflin-St Jeor. Es la f\u00f3rmula can\u00f3nica de la mayor\u00eda de los trackers de calor\u00edas de consumo, y hay que ser honesto: es mejor que Harris-Benedict 1919, que otras apps todav\u00eda usan.<\/p>\n  <p>Mifflin-St Jeor es de 1990. La muestra es m\u00e1s amplia (498 sujetos), la metodolog\u00eda de calorimetr\u00eda indirecta es m\u00e1s precisa, la f\u00f3rmula est\u00e1 calibrada sobre una poblaci\u00f3n m\u00e1s moderna. Yazio aplica la f\u00f3rmula oficial: 10 \u00d7 peso (kg) + 6,25 \u00d7 altura (cm) \u2212 5 \u00d7 edad \u2212 161 (mujeres) o +5 (hombres).<\/p>\n  <p>Pero la actualizaci\u00f3n se detiene ah\u00ed. Mifflin (1990) corrige marginalmente Harris-Benedict (1919) en la precisi\u00f3n media, pero hereda el mismo defecto conceptual: <strong>la f\u00f3rmula solo tiene en cuenta el peso. Ni la grasa corporal. Ni la masa magra.<\/strong><\/p>\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  <p>Frankenfield 2013 (PubMed 23631843) compar\u00f3 Mifflin-St Jeor con la calorimetr\u00eda indirecta de referencia en cohortes obesas y no obesas. Resultado: precisi\u00f3n del 87&nbsp;% en los no obesos, y solo <strong>75&nbsp;% en los obesos<\/strong>. Un estudio m\u00e1s reciente (PMC11820646) muestra que en los IMC superiores a 35, Mifflin se equivoca en <strong>250 a 315&nbsp;kcal al d\u00eda<\/strong>. Es el equivalente a un tentempi\u00e9 entero en el c\u00e1lculo de un d\u00e9ficit.<\/p>\n\n  <p>500&nbsp;kcal no es poca cosa. Si Yazio 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). Yazio 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, el resultado no puede individualizarse. Es matem\u00e1ticamente imposible.<\/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 nivel de actividad, elegido de una vez por todas<\/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 Yazio ha calculado tu BMR (sin grasa corporal), 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> : 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 Yazio? Te pide, una sola vez en el momento del registro, marcar una de las 5 casillas que resume por s\u00ed sola tu estilo de vida. Esas 5 casillas se llaman en ciencias del deporte <strong>niveles PAL<\/strong> (Physical Activity Level), es solo un multiplicador aplicado a tu BMR:<\/p>\n  <ul>\n    <li>Sedentario (PAL 1,2): oficina, poca caminata<\/li>\n    <li>Actividad baja (PAL 1,375): caminata ocasional<\/li>\n    <li>Actividad moderada (PAL 1,55): deporte 3 a 5 veces por semana<\/li>\n    <li>Activo (PAL 1,725): deporte intenso casi diario<\/li>\n    <li>Muy activo (PAL 1,9): deporte muy intenso o trabajo f\u00edsico<\/li>\n  <\/ul>\n  <p>Y seg\u00fan tu elecci\u00f3n, multiplica tu BMR por el coeficiente asociado. 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 la trampa silenciosa: 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>. Ninguna de las 5 casillas capta eso.<\/p>\n  <p>Yazio sincroniza bien con Apple Health y Google Health Connect, y capta tus pasos. Pero esos pasos alimentan la secci\u00f3n \u00ab&nbsp;Activities\/Burned&nbsp;\u00bb, no el rec\u00e1lculo del TDEE. Tu objetivo cal\u00f3rico diario sigue basado en la casilla PAL elegida en el onboarding.<\/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 Yazio\"><\/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 Yazio (2&nbsp;400&nbsp;kcal fijas, PAL moderado \u00d7 BMR). 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 5 ser\u00e1 correcta. Y por tanto Yazio te va a dar un TDEE sistem\u00e1ticamente desconectado de la realidad.<\/p>\n  <p>El punto clave de este art\u00edculo: incluso si Yazio tuviera una f\u00f3rmula BMR perfecta (que no es el caso), el PAL est\u00e1tico 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 sin grasa corporal, m\u00e1s una aproximaci\u00f3n PAL est\u00e1tica de las otras partidas de gasto, da muy pocas posibilidades de alcanzar tus objetivos en 3 a 6 meses.<\/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-yazio\" 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-yazio\" 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, nunca modelizada<\/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. La literatura cient\u00edfica es clara y reproducible: M\u00fcller 2015 (PubMed 26399868, revisi\u00f3n de Minnesota), Doucet 2001 (PubMed 11430776), Nunes 2020 (PMC7484122) en 6 semanas de d\u00e9ficit. 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 del <strong>del 5 al 10&nbsp;%<\/strong> (el TDEE baja al 90-95&nbsp;% del nivel inicial)<\/li>\n    <li>D\u00e9ficit de &minus;500&nbsp;kcal al d\u00eda: <strong>10 a 15&nbsp;%<\/strong> de adaptaci\u00f3n (el TDEE baja al 85-90&nbsp;%)<\/li>\n    <li>D\u00e9ficit de &minus;750&nbsp;kcal al d\u00eda: <strong>15 a 25&nbsp;%<\/strong> de adaptaci\u00f3n (el TDEE baja al 75-85&nbsp;%)<\/li>\n  <\/ul>\n  <p>Convenci\u00f3n Lean: 100&nbsp;% = \u00f3ptimo, 90&nbsp;% = 10&nbsp;% de adaptaci\u00f3n. Y como el NEAT, el EAT y el TEF dependen todos directamente del BMR, es casi todo el 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 Yazio\"><\/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 de Yazio 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>Yazio 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>Yazio logr\u00f3 lo que MyFitnessPal fall\u00f3: una interfaz clara, sin ruido publicitario, y una versi\u00f3n gratuita realmente utilizable. El dise\u00f1o se movi\u00f3, la ciencia no: bajo el cap\u00f3, encontramos Harris-Benedict y un nivel de actividad elegido en el registro. Lean invirti\u00f3 exactamente donde Yazio no se movi\u00f3: el c\u00e1lculo de cada componente del TDEE (BMR&nbsp;+&nbsp;NEAT&nbsp;+&nbsp;EAT&nbsp;+&nbsp;TEF) m\u00e1s la adaptaci\u00f3n metab\u00f3lica. As\u00ed es como.<\/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\">El BMR sobre grasa corporal real<\/div>\n      <h3>Modelo propietario patentado, basado en la masa magra<\/h3>\n      <p>Yazio calcula tu metabolismo a partir de tu peso, tu altura y tu edad. Lean parte de tu <strong>masa magra<\/strong>, porque es ella la que quema en reposo: dos personas de 80&nbsp;kg, una al 12&nbsp;% de grasa corporal y la otra al 30&nbsp;%, no tienen el mismo metabolismo. Faltaba medir esa grasa corporal sin DEXA.<\/p>\n      <p>El <strong>BodyScan IA<\/strong> lo hace con una foto, mediante un modelo entrenado con un banco de esc\u00e1neres DEXA. Resultado en unos segundos, a repetir cada semana, con rec\u00e1lculo autom\u00e1tico del metabolismo detr\u00e1s.<\/p>\n      <p>Ni plic\u00f3metro, ni b\u00e1scula de impedancia sensible a la hidrataci\u00f3n, ni DEXA en cl\u00ednica. Una foto semanal.<\/p>\n    <\/div>\n  <\/div>\n\n  <div class=\"method flip\">\n    <div>\n      <div class=\"m-tag\">Sin coeficiente de actividad<\/div>\n      <h3>NEAT, EAT, TEF calculados por separado<\/h3>\n      <p><strong>NEAT.<\/strong> Tus pasos reales llegan desde HealthKit (iOS) o Google Fit (Android). El \u00ab&nbsp;nivel de actividad&nbsp;\u00bb que Yazio te pide en el registro no cambia el lunes en que haces 15&nbsp;000 pasos y el domingo en que no dejas el sof\u00e1. Lean lee el dato en lugar de suponerlo.<\/p>\n      <p><strong>EAT.<\/strong> Cada sesi\u00f3n se calcula por MET sobre tu tiempo de esfuerzo real. Una hora de musculaci\u00f3n, descansos incluidos, no vale lo que una hora de carrera continua: la diferencia se cuenta en cientos de kcal por semana.<\/p>\n      <p><strong>TEF.<\/strong> El coste de la digesti\u00f3n depende de tus macros: del 20 al 30&nbsp;% para las prote\u00ednas, del 5 al 10&nbsp;% para los carbohidratos, del 1 al 3&nbsp;% para las grasas. Lean lo calcula sobre lo que realmente has comido en lugar de aplicar una tarifa fija del 10&nbsp;%.<\/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\">Adaptaci\u00f3n metab\u00f3lica autom\u00e1tica<\/div>\n      <h3>Una primicia mundial en una app de consumo<\/h3>\n      <p><strong>La adaptaci\u00f3n metab\u00f3lica.<\/strong> Tras unas semanas de d\u00e9ficit, tu metabolismo se ralentiza. Yazio muestra el mismo objetivo cal\u00f3rico en la semana 8 que el primer d\u00eda: Lean ajusta el TDEE a la baja seg\u00fan las horquillas publicadas (M\u00fcller 2015, Doucet 2001).<\/p>\n      <p>Pasado el 10 al 15&nbsp;% de adaptaci\u00f3n, la app puede recomendar una vuelta al mantenimiento para relanzar el metabolismo antes de volver al d\u00e9ficit.<\/p>\n      <p>Ning\u00fan nivel de actividad que marcar. Cada componente se mide, 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 frente a Yazio, 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:#FFF1ED;border:1.5px solid #FF5252;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\/logo-yazio-real.webp\" alt=\"Yazio\" 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:#FF5252;letter-spacing:-0.2px\">Yazio<\/div>\n  <\/div>\n<\/div>\n<div class=\"table\" role=\"table\" aria-label=\"Comparativa Lean frente a Yazio\">\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\/logo-yazio-real.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> <span>Yazio<\/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 1990, sin grasa corporal<\/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 cada d\u00eda<\/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 PAL est\u00e1tico<\/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> Mezclado con el NEAT en \u00ab&nbsp;Activities\/Burned&nbsp;\u00bb<\/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, nivel de actividad fijo (5 casillas, 1,2 a 1,9)<\/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 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, disponible desde junio de 2025<\/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 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> M\u00e1s de 4M de \u00edtems, fuerte cobertura EU\/DE<\/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 class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Ayuno intermitente<\/div>\n      <div class=\"cell lean\"><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> Fuera de alcance<\/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> 20 trackers, 16:8 gratis, programas PRO<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Recetas guiadas<\/div>\n      <div class=\"cell lean\"><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> Fuera de alcance<\/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> M\u00e1s de 3&nbsp;000 recetas<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Cobertura EU y localizaci\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> FR, EN, ES, PT, IT, DE, PL, HU<\/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> L\u00edder EU, 20 idiomas, fuerte en DE\/AT\/CH<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Reputaci\u00f3n y tama\u00f1o de audiencia<\/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> 4,7\/5, m\u00e1s de 10&nbsp;000 usuarios, app joven<\/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> 4,6\/5, 100M de usuarios, fundada en 2014<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Modelo de negocio<\/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> Premium, prueba gratuita de 7 d\u00edas en el plan anual<\/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> Freemium, PRO en prueba<\/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>Yazio entendi\u00f3 antes que muchos que la ergonom\u00eda hace la adherencia. Lean lleva la misma l\u00f3gica al tracking: tres m\u00e9todos de registro, para que ning\u00fan contexto se convierta en un motivo de abandono.<\/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 toma el relevo cuando ni la base ni el c\u00f3digo de barras bastan: un plato casero, un plato en el restaurante. Una foto, y queda registrado.<\/p>\n  <p>M\u00e1s all\u00e1 de la comida, Lean muestra un TDEE que se mueve durante el d\u00eda: tus pasos hacen subir tu objetivo cal\u00f3rico en directo, donde un coeficiente de actividad elegido en el registro sigue id\u00e9ntico todos los d\u00edas.<\/p>\n  <p>Y para jerarquizar, la Pir\u00e1mide de Progresi\u00f3n:<\/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=\"yazio-better\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">07 &middot; Honestidad<\/span><\/div>\n  <h2 id=\"yazio-better\">Lo que Yazio hace mejor<\/h2>\n  <p>Lean no es perfecto, y Yazio tiene varias fortalezas reales que hay que reconocer. Lectura honesta, criterio por criterio, en los ejes donde Yazio sigue por delante.<\/p>\n\n  <div class=\"scorecard rev\" aria-label=\"Scorecard Yazio frente a 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\/logo-yazio-real.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> Yazio<\/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\">Ayuno intermitente integrado<\/div>\n      <div class=\"bar mfp\" data-brand=\"YAZIO\"><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:45%\"><\/i><\/div><div class=\"v\">4,5<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Recetas guiadas<\/div>\n      <div class=\"bar mfp\" data-brand=\"YAZIO\"><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:15%\"><\/i><\/div><div class=\"v\">1,5<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Cobertura EU y localizaci\u00f3n<\/div>\n      <div class=\"bar mfp\" data-brand=\"YAZIO\"><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:80%\"><\/i><\/div><div class=\"v\">8,0<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Tama\u00f1o de audiencia y rese\u00f1as<\/div>\n      <div class=\"bar mfp\" data-brand=\"YAZIO\"><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:30%\"><\/i><\/div><div class=\"v\">3,0<\/div><\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>Lectura honesta.<\/strong> En ayuno intermitente, Yazio es referente del mercado de consumo: 20 trackers, 16:8 gratis, programas guiados en PRO. Lean no te impide en absoluto practicar el 16:8 o cualquier otro protocolo de ventana de alimentaci\u00f3n, simplemente la app no gira en torno a eso. En recetas, m\u00e1s de 3&nbsp;000 entradas creadas internamente con planificaci\u00f3n semanal, es un est\u00e1ndar que Yazio domina. En cobertura EU y localizaci\u00f3n, Lean tambi\u00e9n es s\u00f3lido (franc\u00e9s, ingl\u00e9s, espa\u00f1ol, portugu\u00e9s, italiano, alem\u00e1n, polaco, h\u00fangaro), Yazio sigue siendo m\u00e1s fuerte en DE\/AT\/CH y tiene 12 a\u00f1os de ventaja en notoriedad europea.<\/p>\n  <p>Si tu enfoque principal es el ayuno estructurado o la pedagog\u00eda sobre las ventanas de alimentaci\u00f3n, Yazio es m\u00e1s relevante que Lean. Si tu enfoque es la precisi\u00f3n del <a class=\"inline\" href=\"https:\/\/lean-app.com\/es\/tdee-calculator\/\">c\u00e1lculo del TDEE<\/a>, la grasa corporal medida cada semana, y la adaptaci\u00f3n metab\u00f3lica autom\u00e1tica, es exactamente 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 usado Yazio 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) y luego explica la adaptaci\u00f3n aparte, 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>Yazio puede bastar para<\/strong>&nbsp;: el ayuno intermitente estructurado, las recetas guiadas, o un seguimiento simple sin sumergirse en la ciencia del TDEE. El c\u00e1lculo cal\u00f3rico preciso simplemente no forma parte de su promesa.<\/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 Yazio a Lean en 3 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>Introduces 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 sobre grasa corporal real, NEAT mediante HealthKit \/ Google Fit (pasos reales), EAT por MET, TEF por macros, m\u00e1s la adaptaci\u00f3n metab\u00f3lica que modula el BMR. 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. Entiendes el flujo.<\/p><\/div>\n  <\/div>\n\n  <p style=\"margin-top:24px\"><strong>Nota importante.<\/strong> Lean no importa tus recetas de Yazio autom\u00e1ticamente. Si quieres recuperar tus platos favoritos, puedes recrearlos como favoritos en Lean manualmente. La sincronizaci\u00f3n HealthKit \/ Google Health Connect, en cambio, toma el relevo inmediatamente para tus pasos y tu historial de actividad.<\/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-yazio\" 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-yazio\" 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 Yazio 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>Yazio usa Mifflin-St Jeor, es moderno, \u00bfpor qu\u00e9 lo criticas?<\/summary><div class=\"ans\">Mifflin-St Jeor (1990) corrige marginalmente Harris-Benedict (1919) pero hereda el mismo defecto conceptual: sin grasa corporal como entrada. Frankenfield 2013 (PubMed 23631843) mide un 75&nbsp;% de precisi\u00f3n en los obesos frente a un 87&nbsp;% en los no obesos. Si tu grasa corporal es alta, el error en tu BMR puede superar las 250 a 315&nbsp;kcal al d\u00eda.<\/div><\/details>\n    <details><summary>Yazio est\u00e1 muy bien valorado (4,6) y tiene 100&nbsp;M de usuarios, \u00bfc\u00f3mo puede ser malo?<\/summary><div class=\"ans\">Yazio es excelente en experiencia de usuario, ayuno intermitente y biblioteca de recetas guiadas. Lo que cuestionamos aqu\u00ed es \u00fanicamente la precisi\u00f3n del c\u00e1lculo del TDEE, que es el n\u00facleo de la promesa \u00abcalorie tracker\u00bb. Una gran audiencia valida la calidad del producto de consumo, no valida la precisi\u00f3n cient\u00edfica de la f\u00f3rmula.<\/div><\/details>\n    <details><summary>\u00bfY el ayuno intermitente en Lean?<\/summary><div class=\"ans\">No de forma nativa. Lean no ofrece ni temporizador 16:8, ni programa guiado de ayuno. Si es tu enfoque principal, Yazio es m\u00e1s relevante. Lean est\u00e1 dise\u00f1ado para el c\u00e1lculo del TDEE y la recomposici\u00f3n corporal, no para estructurar ventanas de alimentaci\u00f3n.<\/div><\/details>\n    <details><summary>Yazio sincroniza con Apple Health y Google Fit, \u00bfno basta para el NEAT?<\/summary><div class=\"ans\">Yazio capta los pasos y la actividad mediante HealthKit \/ Google Fit, pero los usa para la secci\u00f3n \u00abActividades\u00bb y la estimaci\u00f3n de las calor\u00edas quemadas en el deporte, no para recalcular tu TDEE de forma continua. El PAL elegido en el registro (1,2 \/ 1,375 \/ 1,55 \/ 1,725 \/ 1,9) sigue siendo la base del c\u00e1lculo. Lean, al contrario, recompone tu NEAT con pasos reales cada d\u00eda.<\/div><\/details>\n    <details><summary>\u00bfLean es freemium o de pago?<\/summary><div class=\"ans\">Lean es Premium, con una prueba gratuita de 7 d\u00edas en la suscripci\u00f3n anual. Descargas, pruebas el BodyScan IA, el escaneo fotogr\u00e1fico con IA de un plato, la recomposici\u00f3n del TDEE, sin compromiso. Si la herramienta encaja con tu objetivo, sigues. Si no, desactivas la renovaci\u00f3n antes del final del periodo de prueba.<\/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\">1990 frente a 2026<\/h2>\n  <p>No es Yazio contra Lean en marketing. Es 1990 frente a 2026 en ciencia.<\/p>\n  <p>Yazio usa Mifflin-St Jeor, f\u00f3rmula publicada en 1990, m\u00e1s un nivel de actividad fijo que marcas una sola vez en el registro (una de las 5 casillas PAL: 1,2 \/ 1,375 \/ 1,55 \/ 1,725 \/ 1,9), e ignora la adaptaci\u00f3n metab\u00f3lica. La combinaci\u00f3n de los tres hace imposible cualquier seguimiento preciso m\u00e1s all\u00e1 de unas semanas. 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>, m\u00e1s la adaptaci\u00f3n metab\u00f3lica que modula el BMR semana a semana. Cada componente calculado con precisi\u00f3n, sin coeficiente m\u00e1gico.<\/p>\n  <p>Yazio sigue siendo muy s\u00f3lido en ayuno intermitente y biblioteca de recetas. Si has probado Yazio en serio y no has tenido los resultados que esperabas en tu definici\u00f3n, 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-yazio\" 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-yazio\" 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 23 de mayo de 2026. Actualizado regularmente con las opiniones de los usuarios y los nuevos estudios relevantes. 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Lean recompone tu TDEE de forma continua.<\/span><\/a><\/li><\/ul><\/aside>","protected":false},"excerpt":{"rendered":"<p>Lean Calculateur TDEE Accueil &nbsp;\/&nbsp; Lean vs Yazio Comparatif &middot; Nutrition &amp; TDEE Lean face \u00e0 Yazio. Le tracker calorique le plus aim\u00e9 d&rsquo;Europe face au seul qui recompose ton TDEE en continu. Yazio compte. Lean calcule. La diff\u00e9rence se voit apr\u00e8s 6 semaines. L&rsquo;\u00e9quipe Lean &middot; Lecture 12&nbsp;min &middot; Mis \u00e0 jour 21 mai [&hellip;]<\/p>","protected":false},"author":1,"featured_media":1364,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-lvm-blank","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1352","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Lean vs Yazio: \u00bfqui\u00e9n calcula de verdad tu gasto? - Lean<\/title>\n<meta name=\"description\" content=\"Yazio aplica Mifflin-St Jeor 1990 + 5 casillas PAL est\u00e1ticas. Lean recalcula BMR + NEAT + EAT + TEF + adaptaci\u00f3n sobre tu grasa corporal real. 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