{"id":1424,"date":"2026-05-24T15:29:25","date_gmt":"2026-05-24T15:29:25","guid":{"rendered":"https:\/\/lean-app.com\/?p=1424"},"modified":"2026-09-08T18:18:21","modified_gmt":"2026-09-08T18:18:21","slug":"lean-vs-fatsecret","status":"publish","type":"post","link":"https:\/\/lean-app.com\/es\/lean-vs-fatsecret\/","title":{"rendered":"Lean frente a FatSecret: precisi\u00f3n premium frente al tracker gratuito"},"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-1424 #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-1424 #lvm-shell .wrap,\nbody.postid-1424 #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-1424 #lvm-shell .wrap,\n  body.postid-1424 #lvm-shell main.wrap{padding-left:18px!important;padding-right:18px!important}\n}\nhtml, body{overflow-x:hidden!important}\nbody.postid-1424 #lvm-shell{overflow-x:hidden;max-width:100vw}\nbody.postid-1424 #lvm-shell *{max-width:100%}\nbody.postid-1424 #lvm-shell .nav-row{max-width:100vw;box-sizing:border-box}\nbody.postid-1424 #lvm-shell.force-show .rev{opacity:1!important;transform:none!important}\n\n\/* === A.1 PHONE BACKGROUND CLASSES === *\/\nbody.postid-1424 #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-1424 #lvm-shell .phone-bg.tab-depense{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp)}\nbody.postid-1424 #lvm-shell .phone-bg.tab-bilan{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp)}\nbody.postid-1424 #lvm-shell .phone-bg.tab-kcal{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp)}\nbody.postid-1424 #lvm-shell .phone-bg.tab-strategie{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp)}\nbody.postid-1424 #lvm-shell .phone-bg.sub-BMR{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp)}\nbody.postid-1424 #lvm-shell .phone-bg.sub-NEAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp)}\nbody.postid-1424 #lvm-shell .phone-bg.sub-EAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp)}\nbody.postid-1424 #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-1424 #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-1424 #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-1424 #lvm-shell .cta-band .stores{width:100%!important;justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1424 #lvm-shell .cta-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1424 #lvm-shell .cta-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1424 #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-1424 #lvm-shell .get-band{padding:38px 22px!important}\n  body.postid-1424 #lvm-shell .get-band .stores{justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1424 #lvm-shell .get-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1424 #lvm-shell .get-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1424 #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-1424 #lvm-shell .get-band h3{font-size:26px!important;line-height:1.2!important}\n  body.postid-1424 #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-1424 #lvm-shell .brand-banner img{width:54px!important;height:54px!important}\n  body.postid-1424 #lvm-shell .brand-banner > div{padding:16px 12px!important;gap:8px!important}\n  body.postid-1424 #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-1424 #lvm-shell .scorecard{padding:18px 16px!important;border-radius:16px!important}\n  body.postid-1424 #lvm-shell .scorecard-head{display:none!important}\n  body.postid-1424 #lvm-shell .scorecard-row{\n    display:block!important;\n    padding:14px 0!important;\n    border-bottom:1px solid #E8E2D6!important;\n  }\n  body.postid-1424 #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-1424 #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-1424 #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-1424 #lvm-shell .scorecard-row .bar.lean::before{color:#FF2D6E!important}\n  body.postid-1424 #lvm-shell .scorecard-row .bar.mfp::before{color:#5B7FFF!important}\n  body.postid-1424 #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-1424 #lvm-shell .scorecard-row .bar .b > i{\n    display:block!important;\n    height:100%!important;\n    border-radius:99px!important;\n  }\n  body.postid-1424 #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-1424 #lvm-shell .cv-wrap{height:380px!important;min-height:360px!important;max-height:420px!important;width:100%!important}\n  body.postid-1424 #lvm-shell .cv-wrap canvas{width:100%!important;height:100%!important;display:block!important}\n  body.postid-1424 #lvm-shell .fig{padding:16px 4px 14px!important;margin:24px -4px 14px!important;overflow:visible!important}\n  body.postid-1424 #lvm-shell .fig-head{padding:0 12px!important;flex-wrap:wrap!important;gap:6px!important;margin-bottom:10px!important}\n  body.postid-1424 #lvm-shell .fig-body{padding:0 2px!important}\n  body.postid-1424 #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-1424 #lvm-shell .cv-wrap{height:360px!important;min-height:340px!important;max-height:380px!important}\n  body.postid-1424 #lvm-shell .fig{padding:14px 2px 12px!important;margin:20px -6px 12px!important;border-radius:14px!important}\n  body.postid-1424 #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-1424 #lvm-shell .table{border-radius:14px!important}\n  body.postid-1424 #lvm-shell .table-row.head{display:none!important}\n  body.postid-1424 #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-1424 #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-1424 #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-1424 #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-1424 #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-1424 #lvm-shell .table-row > .cell:not(.lean):not(.crit)::before{\n    content:\"FATSECRET\"!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:#2E7BE5!important;\n  }\n  body.postid-1424 #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-1424 #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-1424 #lvm-shell .mini-row{gap:6px!important;margin:24px 0!important;grid-template-columns:repeat(3,1fr)!important}\n  body.postid-1424 #lvm-shell .mini-phone{max-width:100px!important;padding:2px!important;border-radius:14px!important;border-width:1px!important}\n  body.postid-1424 #lvm-shell .mini-phone.tiny{max-width:96px!important;padding:2px!important;border-radius:13px!important}\n  body.postid-1424 #lvm-shell .mini-phone .notch{width:30px!important;height:8px!important;border-radius:0 0 5px 5px!important}\n  body.postid-1424 #lvm-shell .mini-phone .scr{border-radius:11px!important}\n  body.postid-1424 #lvm-shell .mini-cap{font-size:10px!important;margin-top:8px!important}\n  body.postid-1424 #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-1424 #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-1424 #lvm-shell .tap-hint.desktop{display:none!important}\n  body.postid-1424 #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-1424 #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-1424 #lvm-shell .bodyscan-illust .mini-phone{max-width:200px!important;padding:3px!important;border-radius:22px!important;border-width:1px!important}\nbody.postid-1424 #lvm-shell .bodyscan-illust .mini-phone .notch{width:40px!important;height:11px!important;border-radius:0 0 7px 7px!important}\nbody.postid-1424 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:18px!important}\n@media (max-width:760px){\n  body.postid-1424 #lvm-shell .bodyscan-illust{max-width:180px!important}\n  body.postid-1424 #lvm-shell .bodyscan-illust .mini-phone{max-width:160px!important;padding:3px!important;border-radius:20px!important}\n  body.postid-1424 #lvm-shell .bodyscan-illust .mini-phone .notch{width:34px!important;height:9px!important;border-radius:0 0 6px 6px!important}\n  body.postid-1424 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:16px!important}\n}\n<\/style>\n\n\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\" 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\" \/>\n      <\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" 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\" \/>\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 FatSecret<\/div>\n  <div class=\"eyebrow\">Comparativa &middot; Nutrici\u00f3n &amp; TDEE<\/div>\n  <h1 id=\"title\">Lean frente a FatSecret.\n    <span class=\"alt\">Precisi\u00f3n Premium frente a la base comunitaria gratuita.<\/span>\n  <\/h1>\n  <p class=\"dek\">FatSecret es gratis y tiene una gran comunidad. Lean ve tu gasto real sobre una base oficial. Dos promesas que no juegan en el mismo terreno.<\/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 24 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\" 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\" 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      FatSecret es conocido por su modelo 100 % gratuito financiado por publicidad, su enorme comunidad activa y su cobertura multipa\u00eds. Es un diario alimentario masivo, presente en m\u00e1s de 50 pa\u00edses. Pero su f\u00f3rmula del TDEE sigue siendo Mifflin-St Jeor 1990, m\u00e1s un factor de actividad est\u00e1tico que marcas una sola vez en el registro (sedentary, lightly active, active, very active, extremely active). Sin grasa corporal real medida en la app, sin adaptaci\u00f3n metab\u00f3lica. Su base de alimentos es crowdsourced, con desviaciones de precisi\u00f3n documentadas.\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>FatSecret calcula tu TDEE con Mifflin-St Jeor 1990 (sin grasa corporal medida en la app) y un factor de actividad est\u00e1tico elegido en el registro entre 5 casillas (sedentary, lightly active, active, very active, extremely active). La fuerza real de FatSecret est\u00e1 en otra parte: un modelo 100 % gratuito financiado por publicidad, una gran comunidad activa, el intercambio de comidas y recetas, presencia en m\u00e1s de 50 pa\u00edses. Lean toma un partido diferente: recalcular cada componente del TDEE (<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 modular el BMR con la adaptaci\u00f3n metab\u00f3lica de forma continua, con una base de alimentos apoyada en USDA y OpenFoodFacts.<\/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\">FatSecret te ofrece la gratuidad, no la precisi\u00f3n de tu gasto<\/h2>\n  <p>Probablemente ya eres usuario de FatSecret, y lo elegiste por lo que mejor hace: un diario alimentario completo, sin suscripci\u00f3n, con el lector de c\u00f3digos de barras incluido.<\/p>\n  <p>Has escaneado productos, buscado alimentos en la base, retomado recetas compartidas por la comunidad. El seguimiento de las ingestas funciona.<\/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. FatSecret no lo detecta. Tu objetivo cal\u00f3rico se queda congelado en tu factor de actividad de hace 100&nbsp;d\u00edas.<\/div>\n  <\/div>\n\n  <p>Tomemos un caso concreto. FatSecret anuncia un TDEE de 2&nbsp;500&nbsp;kcal, comes 2&nbsp;250, crees estar a 250&nbsp;kcal de d\u00e9ficit. Si tu gasto real es de 2&nbsp;280, tu d\u00e9ficit efectivo cae a 30&nbsp;kcal: la b\u00e1scula no se mover\u00e1.<\/p>\n  <p>La promesa de FatSecret es clara y se cumple: un diario gratuito, una comunidad, una base que cubre muchos mercados. Simplemente no se refiere a la precisi\u00f3n del gasto.<\/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 medida en la app<\/h2>\n  <p>FatSecret tambi\u00e9n tiene que estimar tu metabolismo basal para darte un objetivo. Usa Mifflin-St Jeor, est\u00e1ndar de facto del sector desde hace tres d\u00e9cadas.<\/p>\n  <p>La ecuaci\u00f3n data de 1990: 498 sujetos, calorimetr\u00eda indirecta, calibraci\u00f3n sobre una poblaci\u00f3n m\u00e1s moderna que los trabajos de 1919. Es una base honesta, y gratuita de implementar, lo que explica su presencia casi universal.<\/p>\n  <p>Donde otras apps ofrecen como opci\u00f3n la ecuaci\u00f3n Katch-McArdle, calculada sobre la masa magra, FatSecret se limita a la f\u00f3rmula b\u00e1sica. Ning\u00fan campo para introducir tu porcentaje de grasa, ning\u00fan c\u00e1lculo alternativo: es la contrapartida asumida de un producto sin suscripci\u00f3n.<\/p>\n  <p>La ganancia de 1990 sobre 1919 sigue siendo peque\u00f1a, porque el problema conceptual est\u00e1 intacto: la f\u00f3rmula solo mira tu peso. No tu composici\u00f3n corporal.<\/p>\n  <p>La masa grasa no consume casi nada en reposo. Las verdaderas partidas de gasto son los \u00f3rganos y los m\u00fasculos: h\u00edgado, cerebro, coraz\u00f3n, ri\u00f1ones. A igual peso, dos cuerpos diferentes queman de forma diferente.<\/p>\n  <p>Frankenfield 2013 (PubMed 23631843) midi\u00f3 la desviaci\u00f3n frente a la calorimetr\u00eda indirecta: 87&nbsp;% de precisi\u00f3n en los no obesos, 68&nbsp;% en los obesos, con derivas de hasta 330&nbsp;kcal al d\u00eda.<\/p>\n\n  <p style=\"margin-bottom:8px\"><strong>Ejemplo con cifras.<\/strong> Hombre de 1,80 m, 120&nbsp;kg, 30&nbsp;% de grasa corporal:<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figura 1<\/span><span class=\"r\">kcal<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\"><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> para un hombre de 1,80 m, 120&nbsp;kg, 30&nbsp;% de grasa corporal. El modelo propietario patentado Lean tiene en cuenta la masa magra. Mifflin-St Jeor (FatSecret por defecto, sin opci\u00f3n de masa magra), no. Diferencia de 500&nbsp;kcal, es decir, el equivalente a un almuerzo entero.<\/p>\n  <\/div>\n\n  <p>Un error de 330&nbsp;kcal transforma un d\u00e9ficit te\u00f3rico en mantenimiento real. El tracking es gratis, el error tambi\u00e9n, pero se paga en semanas de progreso perdidas.<\/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). FatSecret les da la misma cifra, sin opci\u00f3n de masa magra.<\/div>\n  <\/div>\n\n  <p>Matem\u00e1ticamente, una ecuaci\u00f3n alimentada solo con el peso no puede producir un resultado individualizado. Gratuita o de pago, es ciega a lo que marca la diferencia.<\/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 factor de actividad, elegido de una vez por todas, y la base crowdsourced<\/h2>\n  <p>Aqu\u00ed es donde la gratuidad muestra su l\u00edmite t\u00e9cnico.<\/p>\n  <p>Tras estimar tu metabolismo basal, FatSecret tiene que calcular tu gasto total: el BMR m\u00e1s los pasos, los gestos cotidianos, el deporte y la digesti\u00f3n.<\/p>\n  <p>La soluci\u00f3n elegida es la m\u00e1s econ\u00f3mica de implementar: una \u00fanica elecci\u00f3n de nivel de actividad en el momento del registro. Es el coeficiente PAL.<\/p>\n  <ul>\n    <li>Sedentary (PAL 1,2): oficina, poca caminata<\/li>\n    <li>Lightly Active (PAL 1,375): caminata ocasional, poco deporte<\/li>\n    <li>Active (PAL 1,55): caminata regular, deporte 3 a 5 veces por semana<\/li>\n    <li>Very Active (PAL 1,725): deporte intenso casi diario<\/li>\n    <li>Extremely Active (PAL 1,9): deporte muy intenso o trabajo f\u00edsico pesado<\/li>\n  <\/ul>\n  <p>Tu metabolismo se multiplica por ese coeficiente, y el resultado se convierte en tu objetivo diario. Una sola entrada, v\u00e1lida indefinidamente.<\/p>\n  <p>La desviaci\u00f3n respecto a la realidad es considerable. Un d\u00eda inm\u00f3vil y un d\u00eda de 15&nbsp;000 pasos no se distinguen en nada en ese c\u00e1lculo.<\/p>\n  <p>FatSecret sabe importar tus pasos desde Apple Health o Google Fit, y puede acreditar una sesi\u00f3n detectada. Pero la base del c\u00e1lculo sigue siendo el coeficiente declarado al principio.<\/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\"><canvas id=\"chartNEAT\" aria-label=\"Variabilidad diaria del gasto cal\u00f3rico en 7 d\u00edas, frente a 2400 kcal fijas seg\u00fan FatSecret\"><\/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 FatSecret (2&nbsp;400&nbsp;kcal fijas, PAL Active \u00d7 BMR). Las anotaciones rosas muestran por qu\u00e9 cada d\u00eda se mueve.<\/p>\n  <\/div>\n\n  <p>Un nivel de actividad no es una constante. Var\u00eda de una semana a otra, seg\u00fan tu trabajo, el tiempo, tu forma del momento.<\/p>\n  <p>Ninguna de las casillas propuestas corresponde por tanto de forma duradera a tu realidad, y el objetivo cal\u00f3rico queda desplazado permanentemente.<\/p>\n  <p>Es el verdadero cerrojo: incluso con una mejor ecuaci\u00f3n de metabolismo, un PAL congelado bastar\u00eda para falsear el resultado. El NEAT, el EAT y el TEF no se deducen de un multiplicador \u00fanico.<\/p>\n  <p><strong>A ese problema se a\u00f1ade la calidad de la base de alimentos.<\/strong> FatSecret muestra una base masiva gracias a su comunidad, pero esa base es crowdsourced: los usuarios a\u00f1aden los alimentos, las marcas, las recetas. Varios estudios sobre bases de alimentos generadas por usuarios han documentado desviaciones de m\u00e1s o menos un 20 por ciento en las calor\u00edas de las entradas populares, debido a duplicados, porciones mal introducidas, valores cal\u00f3ricos copiados aproximadamente. Puedes escribir \u00ab&nbsp;pollo asado&nbsp;\u00bb y obtener 30 entradas distintas con kcal que van del simple al doble. Lean zanja: base apoyada en <strong>USDA y OpenFoodFacts<\/strong>, fuentes oficiales verificadas, y escaneo fotogr\u00e1fico con IA de un plato para los alimentos fuera de la base.<\/p>\n  <p>Un metabolismo sin medici\u00f3n de la composici\u00f3n corporal, m\u00e1s una actividad resumida en una casilla marcada una vez: el objetivo final tiene pocas posibilidades de acertar.<\/p>\n\n  <div class=\"cta-band rev\">\n    <div class=\"l\">Ver tu TDEE real, desglosado en BMR + NEAT + EAT + TEF. Descarga gratuita.<\/div>\n    <div class=\"stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" 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\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" 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\" \/><\/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 la variable de la que ninguna app gratuita habla, y con raz\u00f3n: modelizarla exige ingenier\u00eda continua.<\/p>\n  <p>Cuando comes menos durante semanas, tu organismo reduce su gasto para protegerse. El principio es el del modo ahorro de un tel\u00e9fono: nada se detiene, todo se ralentiza.<\/p>\n  <p>Este mecanismo tiene un nombre, la adaptaci\u00f3n metab\u00f3lica, y est\u00e1 documentado: M\u00fcller 2015 (PubMed 26399868, rean\u00e1lisis de Minnesota), Doucet 2001, Nunes 2020 (PMC7484122). La magnitud publicada va del 5 al 25&nbsp;% del metabolismo basal.<\/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;% corresponde a un metabolismo intacto, 90&nbsp;% a una adaptaci\u00f3n del 10&nbsp;%. Como el NEAT, el EAT y el TEF derivan del BMR, todo el TDEE se desplaza.<\/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\"><canvas id=\"chartAdapt\" aria-label=\"TDEE que cae de 2500 a 2150 kcal en 8 semanas, frente a 2500 fijas seg\u00fan FatSecret\"><\/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 FatSecret se queda plana. En la semana 6, ya est\u00e1s en mantenimiento. Sin haber cambiado nada.<\/p>\n  <\/div>\n\n  <p>Concretamente: d\u00e9ficit del 25&nbsp;% buscado sobre un TDEE de 2&nbsp;000&nbsp;kcal, es decir, 1&nbsp;500&nbsp;kcal al d\u00eda. Tras una adaptaci\u00f3n del 14&nbsp;%, el TDEE real ya es solo de 1&nbsp;720&nbsp;kcal. El d\u00e9ficit efectivo cae a 220&nbsp;kcal, y la p\u00e9rdida se detiene.<\/p>\n  <p>La trampa est\u00e1 en la progresividad. Las primeras semanas dan resultados, lo que valida el m\u00e9todo a tus ojos. La brecha se agranda despu\u00e9s sin se\u00f1al visible, hasta el bloqueo.<\/p>\n  <p>La mayor\u00eda de la gente atribuye entonces esa meseta a su fuerza de voluntad o a un \u00ab&nbsp;metabolismo roto&nbsp;\u00bb. Una app gratuita no puede sacarlos del error: nunca midi\u00f3 la variable en cuesti\u00f3n.<\/p>\n  <p>FatSecret no calcula la adaptaci\u00f3n metab\u00f3lica. Tu objetivo sigue siendo el mismo en la semana 8 que el primer d\u00eda, salvo actualizaci\u00f3n manual de tu peso. La gratuidad no es el problema: la ausencia de medici\u00f3n s\u00ed lo es.<\/p>\n<\/section>\n\n<section aria-labelledby=\"solution\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">04 &middot; Soluci\u00f3n Lean<\/span><\/div>\n  <h2 id=\"solution\">C\u00f3mo Lean resuelve cada uno de los 3 problemas<\/h2>\n  <p>Lean no se pens\u00f3 como un FatSecret de pago. La gratuidad total de FatSecret es una elecci\u00f3n real, asumida, y nadie se la quita. Pero un modelo 100&nbsp;% gratuito impone sus limitaciones: una base de alimentos alimentada por los propios usuarios, y un motor de c\u00e1lculo congelado desde hace una d\u00e9cada porque hacerlo evolucionar cuesta ingenier\u00eda. Lean hace la apuesta inversa: medir cada componente del TDEE (BMR&nbsp;+&nbsp;NEAT&nbsp;+&nbsp;EAT&nbsp;+&nbsp;TEF), con la adaptaci\u00f3n metab\u00f3lica que modula el BMR semana a semana. As\u00ed es como, ladrillo a ladrillo.<\/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>Donde FatSecret te pide tu peso y deduce tu metabolismo, Lean parte de tu <strong>masa magra<\/strong>. El matiz es decisivo: el m\u00fasculo consume energ\u00eda en reposo, la grasa casi nada. Queda el problema hist\u00f3rico: \u00bfc\u00f3mo conocer tu porcentaje de grasa sin pagar un DEXA en cl\u00ednica cada semana?<\/p>\n      <p>La respuesta de Lean cabe en una foto. El <strong>BodyScan IA<\/strong> analiza tu imagen mediante un modelo entrenado con un banco de esc\u00e1neres DEXA y devuelve tu grasa corporal en unos segundos. Lo repites cada semana, tu metabolismo se recalcula solo. Es precisamente el tipo de funcionalidad que un modelo gratuito no puede financiar.<\/p>\n      <p>Se acabaron el plic\u00f3metro y su margen de error, la b\u00e1scula de impedancia y sus variaciones seg\u00fan tu hidrataci\u00f3n, el DEXA y su coste. Una foto, cinco segundos, cada semana.<\/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). Nada que declarar, nada que estimar: son los aceler\u00f3metros de tu tel\u00e9fono los que cuentan. Lean cruza despu\u00e9s esos pasos con tu metabolismo para convertir tu actividad diaria en calor\u00edas, mientras que una casilla \u00ab&nbsp;moderadamente activo&nbsp;\u00bb aplica el mismo multiplicador a un repartidor y a un teletrabajador.<\/p>\n      <p><strong>EAT.<\/strong> Eliges tu deporte en una lista (musculaci\u00f3n, carrera, tenis, nataci\u00f3n) y Lean aplica el MET correspondiente a tu tiempo real de esfuerzo. Una sesi\u00f3n de musculaci\u00f3n de una hora con tiempos de descanso no vale lo que una hora de carrera continua: contar las dos igual es equivocarse en varios cientos de kcal a la semana.<\/p>\n      <p><strong>TEF.<\/strong> Digerir cuesta energ\u00eda, y ese coste depende de lo que comes: del 20 al 30&nbsp;% de las calor\u00edas para las prote\u00ednas, del 5 al 10&nbsp;% para los carbohidratos, del 1 al 3&nbsp;% para las grasas. Lean calcula esta partida sobre tus macros reales en lugar de aplicar una tarifa fija del 10&nbsp;% id\u00e9ntica para todos.<\/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\">\n    <div class=\"m-phone\">\n      <div class=\"mini-phone\" style=\"max-width:170px\"><div class=\"notch\"><\/div><div class=\"scr\"><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 auto<\/strong><\/div>\n    <\/div>\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> Es el ladrillo que ninguna app de consumo modeliza, gratuita o de pago. Semana a semana en d\u00e9ficit, tu metabolismo se ralentiza: Lean ajusta tu TDEE a la baja seg\u00fan las horquillas publicadas (M\u00fcller 2015, Doucet 2001), en lugar de mostrarte el mismo objetivo cal\u00f3rico en la semana 8 que el primer d\u00eda.<\/p>\n      <p>Pasado el 10 al 15&nbsp;% de adaptaci\u00f3n, la app puede recomendarte una vuelta al mantenimiento para relanzar tu metabolismo antes de volver al d\u00e9ficit. Es el protocolo que siguen los preparadores, automatizado.<\/p>\n      <p>Ning\u00fan coeficiente de actividad que marcar, ninguna casilla congelada en el registro. Cada componente se mide, semana a semana.<\/p>\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 FatSecret, 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=\"table\" role=\"table\" aria-label=\"Comparativa Lean frente a FatSecret\">\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-fatsecret-real.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> <span>FatSecret<\/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 opci\u00f3n de masa magra<\/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, medido en la app<\/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, ninguna introducci\u00f3n de grasa corporal posible<\/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 mid\">&minus;<\/span> Sincronizaci\u00f3n HealthKit, complemento cal\u00f3rico de ejercicio, pero sin rec\u00e1lculo del TDEE<\/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> Selecci\u00f3n de deporte simple, base de ejercicios est\u00e1ndar<\/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, integrado en el TDEE<\/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, macros mostrados sin c\u00e1lculo del TEF<\/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, 5 casillas est\u00e1ticas (sedentary a extremely active, PAL 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 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, introducci\u00f3n manual, c\u00f3digo de barras o foto manual de la etiqueta<\/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, fuentes oficiales verificadas<\/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> Crowdsourced, duplicados y desviaciones cal\u00f3ricas documentadas<\/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> Objetivo fijo, rec\u00e1lculo manual necesario<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Intercambio comunitario (comidas, recetas)<\/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, foco en el c\u00e1lculo del TDEE<\/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> Comunidad activa, recetas compartidas<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Cobertura multipa\u00eds<\/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> Presente en m\u00e1s de 50 pa\u00edses, multiling\u00fce<\/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> 4,5\/5, m\u00e1s de 100M de descargas acumuladas, audiencia amplia<\/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> Gratis financiado por publicidad, Premium opcional<\/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>Una app gratuita solo tiene inter\u00e9s si todav\u00eda la usas dentro de seis meses. Lean ofrece por tanto tres formas de registrar una comida, para que la fricci\u00f3n nunca sea la raz\u00f3n del 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 cambia sobre todo las comidas fuera de casa. Donde la base comunitaria de FatSecret te hace elegir entre quince versiones del mismo plato introducidas por quince usuarios, una foto basta y pasas a lo siguiente.<\/p>\n  <p>M\u00e1s all\u00e1 de la comida, Lean muestra un TDEE que se actualiza durante el d\u00eda: cada millar de pasos eleva tu objetivo cal\u00f3rico. Un total congelado por la ma\u00f1ana no puede reflejar eso.<\/p>\n  <p>Y por encima, la Pir\u00e1mide de Progresi\u00f3n jerarquiza lo que cuenta:<\/p>\n\n  <div class=\"pyramid\" aria-label=\"Pir\u00e1mide de Progresi\u00f3n Lean\">\n    <div class=\"level l1\"><span>Adherencia<\/span><span class=\"k\">Base<\/span><\/div>\n    <div class=\"level l2\"><span>Objetivo cal\u00f3rico<\/span><span class=\"k\">Nivel 2<\/span><\/div>\n    <div class=\"level l3\"><span>Pasos \/ NEAT<\/span><span class=\"k\">Nivel 3<\/span><\/div>\n    <div class=\"level l4\"><span>Macronutrientes<\/span><span class=\"k\">Cima<\/span><\/div>\n  <\/div>\n  <div class=\"pyramid-cap\">No quemar etapas. Si no eres regular en el tracking, optimizar los macros al uno por ciento no sirve de nada.<\/div>\n<\/section>\n\n<section aria-labelledby=\"fatsecret-better\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">07 &middot; Honestidad<\/span><\/div>\n  <h2 id=\"fatsecret-better\">Lo que FatSecret hace mejor<\/h2>\n  <p>Lean no es perfecto, y FatSecret tiene varias fortalezas reales que hay que reconocer. Lectura honesta, criterio por criterio, en los ejes donde FatSecret sigue por delante. Ninguno de estos ejes es secundario: son pilares reales de la promesa de FatSecret, y lo que explica su adopci\u00f3n masiva en el gran p\u00fablico preocupado por la gratuidad.<\/p>\n\n  <div class=\"scorecard rev\" aria-label=\"Scorecard FatSecret frente a Lean en 4 ejes gratuidad y comunidad\">\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-fatsecret-real.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> FatSecret<\/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\">Modelo 100 % gratuito (financiado por publicidad)<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:95%\"><\/i><\/div><div class=\"v\">9,5<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:25%\"><\/i><\/div><div class=\"v\">2,5<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Cobertura multipa\u00eds<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:92%\"><\/i><\/div><div class=\"v\">9,2<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:65%\"><\/i><\/div><div class=\"v\">6,5<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Comunidad (intercambio de comidas y recetas)<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:88%\"><\/i><\/div><div class=\"v\">8,8<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:20%\"><\/i><\/div><div class=\"v\">2,0<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Tama\u00f1o bruto del cat\u00e1logo de alimentos<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:90%\"><\/i><\/div><div class=\"v\">9,0<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:72%\"><\/i><\/div><div class=\"v\">7,2<\/div><\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>Lectura honesta.<\/strong> En el modelo gratuito, FatSecret es la referencia del mercado: todo es accesible sin paywall, financiado por la publicidad mostrada en la app. Ninguna funcionalidad cr\u00edtica del tracking cal\u00f3rico est\u00e1 bloqueada detr\u00e1s de un Premium. Es un verdadero diferenciador, sobre todo para los usuarios que empiezan o que quieren un diario sin compromiso. En cobertura multipa\u00eds, FatSecret est\u00e1 presente en m\u00e1s de 50 pa\u00edses con versiones localizadas y bases de alimentos adaptadas (marcas locales, platos regionales). Ninguna otra app de consumo ha invertido tanto en la expansi\u00f3n geogr\u00e1fica. En comunidad, FatSecret ha construido durante 15 a\u00f1os una red activa de usuarios que comparten sus comidas, sus recetas, sus trucos, sus logros. Es un mecanismo de adherencia que pocas apps reproducen. En tama\u00f1o del cat\u00e1logo de alimentos, FatSecret muestra varios millones de entradas, lo que cubre alimentos muy espec\u00edficos que bases m\u00e1s restringidas no tendr\u00e1n.<\/p>\n  <p>Si tu enfoque principal es no pagar nada para seguir tus calor\u00edas, si quieres acceso en un pa\u00eds donde pocas apps est\u00e1n localizadas, o si la dimensi\u00f3n comunitaria te ayuda a aguantar, FatSecret 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 mediante BodyScan IA, la adaptaci\u00f3n metab\u00f3lica autom\u00e1tica y una base de alimentos apoyada en USDA y OpenFoodFacts en lugar de crowdsourced, es exactamente lo que acaba de demostrarse en las 3 secciones anteriores. Muchos usuarios usan Lean para la medici\u00f3n y FatSecret en paralelo para la cobertura de alimentos raros, es totalmente defendible.<\/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>Cuatro perfiles. Si uno de ellos te corresponde, Lean tiene posibilidades de convenirte.<\/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>Usas FatSecret desde hace tiempo y no has perdido<\/h4>\n        <p>Usas FatSecret desde hace tiempo, aprecias su gratuidad, pero dudas de la cifra mostrada frente a tus esfuerzos.<\/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>La meseta se instala tras cuatro a ocho semanas sin que nada haya cambiado en tu seguimiento. Es la adaptaci\u00f3n metab\u00f3lica, que Lean calcula e integra en tu objetivo.<\/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>Quieres entender de d\u00f3nde viene tu objetivo: cada componente mostrado por separado, en lugar de un total salido de una f\u00f3rmula y de una casilla marcada.<\/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>Quieres registrar r\u00e1pido sin navegar entre quince versiones del mismo plato: foto, base curada o c\u00f3digo de barras.<\/p>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>FatSecret sigue siendo m\u00e1s relevante para<\/strong>&nbsp;: no pagar nada por tu diario cal\u00f3rico, disfrutar de una comunidad activa que comparte comidas y recetas, o acceder a un cat\u00e1logo multipa\u00eds muy amplio. La precisi\u00f3n del c\u00e1lculo del TDEE y la adaptaci\u00f3n metab\u00f3lica simplemente no forman parte de su promesa principal.<\/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\">Pasar de FatSecret a Lean (o usar los dos) 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 treinta segundos.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">02<\/div><h4>BodyScan IA<\/h4><p>Una foto, cinco segundos: tu porcentaje de grasa aparece, sin material.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">03<\/div><h4>Peso &amp; altura<\/h4><p>Introduces tu peso y tu altura. Es todo lo que hace falta para empezar.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">04<\/div><h4>Lean calcula<\/h4><p>BMR sobre masa magra real, NEAT a partir de tus pasos mediante HealthKit o Google Fit, EAT por MET, TEF sobre tus macros, m\u00e1s la adaptaci\u00f3n metab\u00f3lica aplicada a lo largo de las semanas.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">05<\/div><h4>Registra una comida<\/h4><p>Foto, c\u00f3digo de barras o base curada: tres formas de registrar, sin duplicados que clasificar.<\/p><\/div>\n  <\/div>\n\n  <p style=\"margin-top:24px\"><strong>Nota importante.<\/strong> Lean no importa tu historial de FatSecret autom\u00e1ticamente, ni tus recetas personalizadas. Si todav\u00eda usas la comunidad de FatSecret para descubrir recetas o encontrar un alimento local raro en su cat\u00e1logo tan amplio, muchos usuarios siguen consultando FatSecret como complemento, usando Lean a diario para el c\u00e1lculo del TDEE y el tracking preciso. 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\">\n    <div class=\"l\">Descarga Lean y empieza el BodyScan IA ahora mismo. Registro gratuito.<\/div>\n    <div class=\"stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" 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\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" 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\" \/><\/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 FatSecret no hace (en el TDEE)<\/h2>\n  <p>Seis funcionalidades que ning\u00fan tracker gratuito ofrece, por una raz\u00f3n simple: exigen una medici\u00f3n continua, no solo una base de datos.<\/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 porcentaje de grasa medido a partir de una foto, cada semana. Es el dato que individualiza el metabolismo, y no se obtiene por introducci\u00f3n manual.<\/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\">Una comida registrada en dos segundos por foto, sin buscar la entrada correcta entre quince versiones introducidas por la comunidad.<\/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 los valores publicados. La meseta del segundo mes deja de ser un misterio.<\/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 y TEF mostrados de forma distinta y actualizados durante el d\u00eda, en lugar de un total congelado calculado de una vez por todas.<\/p><\/div><div class=\"fc\">En vivo<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">05<\/div><div><div class=\"ft\">Base de alimentos oficial<\/div><p class=\"fd\">Tus tendencias de peso, grasa corporal y masa magra durante varios meses, para distinguir un verdadero estancamiento de una fluctuaci\u00f3n de agua.<\/p><\/div><div class=\"fc\">Base<\/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\">Una jerarqu\u00eda de prioridades: adherencia, luego objetivo cal\u00f3rico, luego pasos. Sabes qu\u00e9 corregir primero.<\/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>FatSecret es gratis con una gran comunidad, \u00bfpor qu\u00e9 compararlo con Lean en el TDEE?<\/summary><div class=\"ans\">FatSecret es conocido por su modelo 100 % gratuito financiado por publicidad, su enorme comunidad activa y su base de alimentos masiva (m\u00e1s de 50 pa\u00edses, intercambio de comidas y recetas por los usuarios). Es su fuerza. Pero su promesa cal\u00f3rica se basa en Mifflin-St Jeor 1990 sin grasa corporal, m\u00e1s un factor de actividad est\u00e1tico a elegir entre 5 casillas en el registro (sedentary, lightly active, active, very active, extremely active). Y su base de alimentos es crowdsourced, con desviaciones de precisi\u00f3n documentadas (entradas duplicadas, calor\u00edas incorrectas, marcas mal informadas). Lean recalcula cada d\u00eda tu BMR sobre tu grasa corporal real medida por BodyScan IA, y apoya su base en USDA + OpenFoodFacts. Las dos apps no juegan en el mismo terreno: gratuidad comunitaria frente a precisi\u00f3n Premium.<\/div><\/details>\n    <details><summary>\u00bfPor qu\u00e9 FatSecret no calcula el BMR sobre la grasa corporal real?<\/summary><div class=\"ans\">FatSecret aplica Mifflin-St Jeor 1990 por defecto sin opci\u00f3n de masa magra. Ninguna medici\u00f3n de grasa corporal est\u00e1 integrada en la app, y ninguna ecuaci\u00f3n tipo Katch-McArdle se ofrece ni siquiera en los ajustes avanzados. La consecuencia es mec\u00e1nica: dos usuarios del mismo peso pero con un 10 y un 30 por ciento de grasa corporal obtienen el mismo BMR FatSecret, cuando su gasto real puede diferir en 400 a 500 kcal al d\u00eda. Lean integra el BodyScan IA para medir tu grasa corporal a partir de una simple foto, a repetir cada semana.<\/div><\/details>\n    <details><summary>\u00bfLa base de alimentos crowdsourced de FatSecret es fiable?<\/summary><div class=\"ans\">FatSecret muestra una base de alimentos masiva gracias a su comunidad, que a\u00f1ade alimentos, marcas y recetas. Es su fuerza en t\u00e9rminos de cobertura. El reverso: las entradas duplicadas son numerosas, los valores cal\u00f3ricos var\u00edan de una entrada a otra para el mismo alimento, y la verificaci\u00f3n rigurosa no es sistem\u00e1tica. Varios estudios sobre bases de alimentos generadas por usuarios han documentado desviaciones de m\u00e1s o menos un 20 por ciento en las calor\u00edas de las entradas populares. Lean apoya su base en USDA y OpenFoodFacts, fuentes oficiales verificadas, y a\u00f1ade el escaneo fotogr\u00e1fico con IA de un plato para los alimentos fuera de la base.<\/div><\/details>\n    <details><summary>FatSecret importa los pasos mediante HealthKit, \u00bfbasta para el NEAT?<\/summary><div class=\"ans\">FatSecret sincroniza Apple Health y Google Fit para los pasos y algunas sesiones, y puede a\u00f1adir un complemento cal\u00f3rico para los ejercicios detectados. Pero el c\u00e1lculo del TDEE de fondo sigue basado en el factor de actividad elegido en el registro entre 5 casillas (sedentary, lightly active, active, very active, extremely active). El NEAT medido d\u00eda a d\u00eda no recompone el gasto total. Lean calcula el NEAT directamente a partir de los pasos reales medidos cada d\u00eda, sin coeficiente que elegir.<\/div><\/details>\n    <details><summary>\u00bfLean es gratis 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    <details><summary>\u00bfSe pueden usar Lean y FatSecret en paralelo?<\/summary><div class=\"ans\">S\u00ed, es defendible si aprecias la comunidad de FatSecret para compartir tus comidas y tus recetas, o si quieres mantener un respaldo gratuito para introducir un alimento encontrado en su base. Lean se ocupa del motor metab\u00f3lico (BMR sobre grasa corporal real, NEAT, EAT, TEF, adaptaci\u00f3n), FatSecret te aporta un diario comunitario y una cobertura multipa\u00eds amplia. Es un trade-off entre precisi\u00f3n y cobertura comunitaria.<\/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 un duelo de marketing. Es la gratuidad comunitaria frente a la precisi\u00f3n del gasto: dos promesas distintas.<\/p>\n  <p>FatSecret sigue siendo la mejor opci\u00f3n para seguir tus calor\u00edas sin pagar nada, con una comunidad activa y una cobertura amplia.<\/p>\n  <p>Lean responde a la otra necesidad: un metabolismo calculado sobre la masa magra medida por BodyScan IA mediante un modelo propietario patentado, un NEAT sacado de tus pasos reales, un EAT por MET, un TEF sobre tus macros, y la adaptaci\u00f3n metab\u00f3lica seguida semana a semana.<\/p>\n  <p>La gratuidad, la comunidad y la cobertura internacional siguen siendo puntos fuertes de FatSecret. Si lo has usado en serio y tu progreso se ha detenido sin explicaci\u00f3n, el problema est\u00e1 probablemente en el lado del gasto.<\/p>\n<\/section>\n\n<div class=\"get-band rev\">\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: ni plic\u00f3metro, ni b\u00e1scula de impedancia, ni DEXA.<\/p>\n  <div class=\"stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" 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\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" 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\" \/>\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>Frankenfield D.C. et al. (2013). Validation of Mifflin-St Jeor equation in obese and non-obese populations. PubMed 23631843.<\/li>\n    <li>M\u00fcller M.J., Bosy-Westphal A. (2013). Adaptive thermogenesis with weight loss in humans. Obesity. PubMed 26399868.<\/li>\n    <li>Doucet E. et al. (2001). Evidence for the existence of adaptive thermogenesis during weight loss. British Journal of Nutrition. PubMed 11319656.<\/li>\n    <li>Nunes C.L. et al. (2020). Metabolic adaptation and energy compensation following weight loss. PMC7484122.<\/li>\n    <li>Westerterp K.R. (2004). Diet induced thermogenesis. Nutrition and Metabolism.<\/li>\n    <li>USDA FoodData Central. National Nutrient Database for Standard Reference. fdc.nal.usda.gov.<\/li>\n    <li>OpenFoodFacts. Base de datos de alimentos colaborativa abierta y verificada. openfoodfacts.org.<\/li>\n    <li>Estudios sobre la precisi\u00f3n de las bases de alimentos crowdsourced (variabilidad documentada de m\u00e1s o menos un 20 por ciento en las entradas populares).<\/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 24 de mayo de 2026, actualizado regularmente con las opiniones de los usuarios y los nuevos estudios relevantes. Lean est\u00e1 disponible en iOS y Android.<\/p>\n      <\/div>\n      <div class=\"stores\">\n        <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" 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\" \/><\/a>\n        <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" 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\" \/><\/a>\n      <\/div>\n    <\/div>\n  <\/div>\n<\/footer>\n\n<script>\n(function(){\n  var bar = document.getElementById('progBar');\n  function up(){\n    var h = document.documentElement;\n    var sc = (h.scrollTop)\/Math.max(1,(h.scrollHeight - h.clientHeight));\n    bar.style.transform = 'scaleX(' + Math.max(0,Math.min(1,sc)) + ')';\n  }\n  document.addEventListener('scroll', up, {passive:true});\n  up();\n})();\n\n(function(){\n  if (!('IntersectionObserver' in window)) {\n    document.querySelectorAll('.rev').forEach(function(n){n.classList.add('on')});\n    return;\n  }\n  var obs = new IntersectionObserver(function(entries){\n    entries.forEach(function(e){\n      if (e.isIntersecting) { e.target.classList.add('on'); obs.unobserve(e.target); }\n    });\n  }, {threshold:0.12});\n  document.querySelectorAll('.rev').forEach(function(n){ obs.observe(n); });\n})();\n\n(function(){\n  var phoneImg = document.getElementById('phoneImg');\n  var phoneBack = document.getElementById('phoneBack');\n  var zones = document.getElementById('phoneZones');\n  var topTabs = document.querySelectorAll('.phone-tabs button');\n  var navTaps = document.querySelectorAll('.phone-navbar button');\n\n  var tabMap = {\n    bilan:    {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp',     drill:false},\n    kcal:     {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp',      drill:false},\n    depense:  {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp',   drill:true},\n    strategie:{src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp', drill:false}\n  };\n  var subMap = {\n    BMR:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp',\n    NEAT: 'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp',\n    EAT:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp',\n    TEF:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp'\n  };\n  var currentTab = 'depense';\n\n  function setActive(tab){\n    topTabs.forEach(function(b){ b.classList.toggle('on', b.dataset.tab===tab); });\n  }\n  function showTab(tab){\n    var t = tabMap[tab]; if(!t) return;\n    currentTab = tab;\n    phoneImg.style.opacity = 0;\n    setTimeout(function(){\n      phoneImg.className = 'phone-bg tab-' + tab;\n      phoneImg.style.opacity = 1;\n      zones.style.display = t.drill ? 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16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Metabolismo basal (BMR): todo lo que hay que saber para calcularlo <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Definici\u00f3n, ecuaci\u00f3n TDEE, 4 f\u00f3rmulas hist\u00f3ricas, por qu\u00e9 la grasa corporal lo cambia todo.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/depense-energetique-totale-v2\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Gasto energ\u00e9tico total (TDEE): la f\u00f3rmula can\u00f3nica BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Entiende los 4 bloques + la adaptaci\u00f3n metab\u00f3lica, fuentes cient\u00edficas 2025.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/comparatifs-croises\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">\u00bfMyFitnessPal o Yazio? 12 duelos de apps de calor\u00edas comparados <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">El veredicto de cada duelo de un vistazo: qui\u00e9n gana en qu\u00e9, y lo que ninguna de las dos calcula.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/meilleures-applications-calories-2026\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Mejores aplicaciones para contar calor\u00edas en 2026: 8 apps probadas <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Lean, MFP, Cronometer, Yazio, Lifesum, FatSecret, Noom, Foodvisor.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/alternative-myfitnesspal\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">\u00bfQu\u00e9 alternativa a MyFitnessPal en 2026? 5 apps probadas <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Comparativa honesta, precisi\u00f3n del TDEE, ergonom\u00eda.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/comparatifs\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Todas las comparativas de Lean frente a las grandes apps de calor\u00edas <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Hub: MyFitnessPal, Yazio, Cronometer, Lifesum, FatSecret, Noom.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/lean-vs-myfitnesspal\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean frente a MyFitnessPal: la f\u00f3rmula TDEE que lo cambia todo <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Por qu\u00e9 MFP se equivoca en tu gasto cal\u00f3rico real.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/lean-vs-foodvisor\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean frente a Foodvisor: pionero del escaneo de fotos vs gasto real <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Foodvisor ve tu plato. Lean recompone tu TDEE de forma continua.<\/span><\/a><\/li><\/ul><\/aside>","protected":false},"excerpt":{"rendered":"<p>Lean Calculateur TDEE Accueil &nbsp;\/&nbsp; Lean vs FatSecret Comparatif &middot; Nutrition &amp; TDEE Lean face \u00e0 FatSecret. Pr\u00e9cision Premium face \u00e0 la base communautaire gratuite. FatSecret est gratuit et a une grosse communaut\u00e9. Lean voit ta d\u00e9pense r\u00e9elle sur une base officielle. Deux promesses qui ne jouent pas sur le m\u00eame terrain. L&rsquo;\u00e9quipe Lean &middot; [&hellip;]<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-lvm-blank","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1424","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Lean vs FatSecret: \u00bfgratis o preciso? - Lean<\/title>\n<meta name=\"description\" content=\"FatSecret es la \u00fanica app 100 % gratuita con esc\u00e1ner, Lean calcula tu gasto a partir de tu grasa corporal real. 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