{"id":1352,"date":"2026-05-23T13:43:16","date_gmt":"2026-05-23T13:43:16","guid":{"rendered":"https:\/\/lean-app.com\/?p=1352"},"modified":"2026-09-08T18:18:03","modified_gmt":"2026-09-08T18:18:03","slug":"lean-vs-yazio","status":"publish","type":"post","link":"https:\/\/lean-app.com\/pt\/lean-vs-yazio\/","title":{"rendered":"Lean diante do Yazio: quem calcula realmente seu gasto cal\u00f3rico em 2026?"},"content":{"rendered":"<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp\" 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18px;border-radius:14px;color:#fff;font-family:var(--font-display);font-weight:500;font-size:15px;letter-spacing:-.01em;display:flex;justify-content:space-between;align-items:center;box-shadow:0 6px 18px rgba(0,0,0,.06)}\n#lvm-shell .pyramid .level .k{font-family:var(--font-mono);font-size:10px;text-transform:uppercase;letter-spacing:.08em;opacity:.75}\n#lvm-shell .pyramid .l1{background:#0E0E10;width:100%}\n#lvm-shell .pyramid .l2{background:#1D1D1F;width:84%}\n#lvm-shell .pyramid .l3{background:#3a3a3c;width:68%}\n#lvm-shell .pyramid .l4{background:var(--pink);width:52%}\n#lvm-shell .pyramid-cap{text-align:center;font-size:13px;color:var(--muted);margin-top:14px}\n\n\/* Section 7 honnetete : scorecard horizontal bars *\/\n#lvm-shell .scorecard{margin:30px 0 10px;border:1px solid var(--rule);border-radius:20px;padding:28px 26px;background:#fff}\n#lvm-shell .scorecard-head{display:grid;grid-template-columns:1.4fr 1fr 1fr;column-gap:28px;align-items:center;padding-bottom:18px;margin-bottom:8px;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell .scorecard-head .h-crit{font-family:var(--font-mono);font-size:11px;font-weight:500;text-transform:uppercase;letter-spacing:.08em;color:var(--muted)}\n#lvm-shell .scorecard-head .h-brand{display:flex;align-items:center;gap:8px;font-family:var(--font-display);font-size:14px;font-weight:600;color:var(--ink)}\n#lvm-shell .scorecard-head .h-brand img{width:22px;height:22px;border-radius:5px;object-fit:cover}\n#lvm-shell .scorecard-row{display:grid;grid-template-columns:1.4fr 1fr 1fr;column-gap:28px;align-items:center;padding:14px 0;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell .scorecard-row:last-child{border-bottom:0}\n#lvm-shell .scorecard-row .crit{font-size:14px;color:var(--ink);font-weight:500;padding-right:14px}\n#lvm-shell .scorecard-row .bar{display:flex;flex-direction:row-reverse;align-items:center;gap:10px}\n#lvm-shell .scorecard-row .bar .b{flex:1;height:8px;border-radius:99px;background:var(--rule-soft);overflow:hidden;position:relative}\n#lvm-shell .scorecard-row .bar .b > i{display:block;height:100%;border-radius:99px;transition:width 1s cubic-bezier(.22,.61,.36,1)}\n#lvm-shell .scorecard-row .bar.lean .b > i{background:var(--pink)}\n#lvm-shell .scorecard-row .bar.mfp .b > i{background:var(--mfp)}\n#lvm-shell .scorecard-row .bar .v{font-family:var(--font-mono);font-size:12px;font-weight:600;color:var(--ink);min-width:32px;text-align:left}\n\n\/* Section 8 pour qui : persona checklist *\/\n#lvm-shell .persona{margin:28px 0 10px;display:grid;grid-template-columns:1fr;gap:14px}\n#lvm-shell .persona-it{display:grid;grid-template-columns:54px 1fr;gap:16px;padding:22px 24px;background:#fff;border:1px solid var(--rule);border-radius:18px;align-items:center}\n#lvm-shell .persona-it.match{background:var(--pink-soft);border-color:rgba(255,45,110,.25)}\n#lvm-shell .persona-it .pic{width:54px;height:54px;border-radius:50%;display:flex;align-items:center;justify-content:center;background:var(--rule-soft);position:relative;font-family:var(--font-mono);font-size:13px;font-weight:600;color:var(--ink)}\n#lvm-shell .persona-it.match .pic{background:var(--pink);color:#fff}\n#lvm-shell .persona-it .pic svg{width:24px;height:24px}\n#lvm-shell .persona-it h4{margin:0 0 4px;font-size:17px;letter-spacing:-.01em}\n#lvm-shell .persona-it p{margin:0;font-size:14px;color:var(--muted);line-height:1.55}\n#lvm-shell .persona-it.match h4{color:var(--ink)}\n\n\/* Section 9 migration : timeline steps *\/\n#lvm-shell .steps{display:grid;grid-template-columns:repeat(5,1fr);gap:14px;margin:28px 0;position:relative}\n#lvm-shell .steps::before{content:\"\";position:absolute;top:14px;left:7px;right:calc(20% - 18px);height:1px;background:linear-gradient(90deg,var(--pink) 0%,var(--rule-soft) 100%);z-index:0}\n#lvm-shell .step{position:relative;padding-top:24px;z-index:1}\n#lvm-shell .step::before{content:\"\";position:absolute;top:8px;left:0;width:14px;height:14px;border-radius:50%;background:var(--pink);border:3px solid #fff;box-shadow:0 0 0 1px var(--rule)}\n#lvm-shell .step .sn{font-family:var(--font-mono);font-size:11px;color:var(--pink);font-weight:600;letter-spacing:.08em}\n#lvm-shell .step h4{margin:6px 0 6px;font-size:15px;letter-spacing:-.01em}\n#lvm-shell .step p{font-size:13px;color:var(--muted);line-height:1.5;margin:0}\n\n\/* Section 10 debloque : feature stack numbered XL *\/\n#lvm-shell .feat-stack{margin:30px 0 10px;border-top:1px solid var(--rule)}\n#lvm-shell .feat-it{display:grid;grid-template-columns:auto 1fr auto;gap:24px;padding:26px 0;border-bottom:1px solid var(--rule);align-items:center}\n#lvm-shell .feat-it .fn{font-family:var(--font-display);font-size:48px;font-weight:600;color:var(--pink);line-height:1;letter-spacing:-.04em;width:74px}\n#lvm-shell .feat-it .ft{font-family:var(--font-display);font-size:22px;font-weight:600;color:var(--ink);letter-spacing:-.015em;line-height:1.25;margin-bottom:6px}\n#lvm-shell .feat-it .fd{font-size:15px;color:var(--muted);line-height:1.55;margin:0}\n#lvm-shell .feat-it .fc{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.08em;color:var(--muted);font-weight:500}\n#lvm-shell .feat-it:last-child{border-bottom:0}\n\n#lvm-shell .faq{margin:22px 0}\n#lvm-shell .faq details{border-bottom:1px solid var(--rule);padding:20px 0}\n#lvm-shell .faq details:first-of-type{border-top:1px solid var(--rule)}\n#lvm-shell .faq summary{cursor:pointer;list-style:none;display:flex;justify-content:space-between;align-items:center;gap:18px;font-family:var(--font-display);font-size:20px;font-weight:500;letter-spacing:-.015em;color:var(--ink)}\n#lvm-shell .faq summary::-webkit-details-marker{display:none}\n#lvm-shell .faq summary::after{content:\"+\";font-size:24px;color:var(--muted);font-weight:300;line-height:1;transition:transform .25s, color .25s}\n#lvm-shell .faq details[open] summary::after{transform:rotate(45deg);color:var(--pink)}\n#lvm-shell .faq details[open] summary{color:var(--pink)}\n#lvm-shell .faq .ans{margin-top:14px;font-size:16px;color:var(--muted);line-height:1.65}\n\n#lvm-shell .get-band{background:var(--paper-2);border-radius:24px;padding:48px 36px;margin:60px 0 40px;text-align:center}\n#lvm-shell .get-band .kicker{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;color:var(--pink);font-weight:600;letter-spacing:.1em;margin-bottom:14px}\n#lvm-shell .get-band h3{font-size:36px;margin:0 0 14px;letter-spacing:-.025em}\n#lvm-shell .get-band p{font-size:16px;color:var(--muted);max-width:480px;margin:0 auto 26px}\n#lvm-shell .get-band .stores{display:flex;justify-content:center;gap:14px;flex-wrap:wrap}\n#lvm-shell .get-band .stores a{line-height:0;transition:transform .15s}\n#lvm-shell .get-band .stores a:hover{transform:translateY(-3px)}\n#lvm-shell .get-band .stores img{height:60px;width:auto;border-radius:11px}\n\n#lvm-shell .sources{font-size:14px;color:var(--muted);line-height:1.7}\n#lvm-shell .sources ol{padding-left:22px}\n#lvm-shell .sources li{margin-bottom:8px}\n\n#lvm-shell footer{padding:50px 0 60px;border-top:1px solid var(--rule);margin-top:40px}\n#lvm-shell footer .row{display:flex;justify-content:space-between;align-items:center;gap:18px;flex-wrap:wrap}\n#lvm-shell footer .kicker{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.08em;color:var(--pink);font-weight:600}\n#lvm-shell footer p{font-size:13px;color:var(--muted);margin:8px 0 0}\n#lvm-shell footer .stores{display:flex;gap:8px}\n#lvm-shell footer .stores img{height:34px;width:auto;border-radius:6px}\n\n#lvm-shell .rev{opacity:0;transform:translateY(12px);transition:opacity .8s cubic-bezier(.22,.61,.36,1),transform .8s cubic-bezier(.22,.61,.36,1)}\n#lvm-shell .rev.on{opacity:1;transform:translateY(0)}\n@media (prefers-reduced-motion:reduce){#lvm-shell .rev{transition:none;opacity:1;transform:none}}\n\n@media (max-width:760px){\n  #lvm-shell .nav-row{padding:8px 18px;gap:8px}\n  #lvm-shell .nav-link{display:none}\n  #lvm-shell .nav-stores img{height:24px}\n  #lvm-shell .wrap{padding:0 22px}\n  #lvm-shell .hero{padding:34px 0 0}\n  #lvm-shell h1{font-size:46px;letter-spacing:-.035em}\n  #lvm-shell h1 .alt{font-size:.55em;margin-top:10px}\n  #lvm-shell .dek{font-size:20px}\n  #lvm-shell .hero-stores img{height:42px}\n  #lvm-shell .hero-bottom{grid-template-columns:1fr;gap:28px;margin:30px 0 40px;padding-top:24px;align-items:stretch}\n  #lvm-shell .phone-wrap{order:-1}\n  #lvm-shell .phone{width:240px}\n  #lvm-shell .tap-hint.desktop{display:none}\n  #lvm-shell .tap-hint.mobile{display:block;position:relative;left:auto;top:auto;text-align:center;margin:0 auto 10px;width:100%}\n  #lvm-shell .tap-hint.mobile .th-arrow{position:relative;display:block;margin:6px auto 0;width:34px;height:34px;transform:none;color:var(--pink)}\n  #lvm-shell .snippet{padding:24px 22px}\n  #lvm-shell .snippet p{font-size:18px}\n  #lvm-shell section{padding:48px 0}\n  #lvm-shell h2{font-size:34px;letter-spacing:-.03em}\n  #lvm-shell h3{font-size:24px}\n  #lvm-shell .section-label{margin-bottom:22px}\n  #lvm-shell .statement{padding:24px 0;margin:32px 0}\n  #lvm-shell .statement .num{font-size:44px}\n  #lvm-shell .statement .lbl{font-size:19px}\n  #lvm-shell .fig{padding:20px 14px 14px;border-radius:16px}\n  #lvm-shell .cv-wrap{height:310px}\n  #lvm-shell .method{grid-template-columns:1fr;gap:20px}\n  #lvm-shell .method.flip{grid-template-columns:1fr}\n  #lvm-shell .method.flip .m-phone{order:0}\n  #lvm-shell .mini-row{grid-template-columns:repeat(3,1fr);gap:10px}\n  #lvm-shell .mini-phone{padding:3px;border-radius:18px;border-width:1px;max-width:110px}\n  #lvm-shell .mini-phone .notch{width:42px;height:11px;border-radius:0 0 8px 8px}\n  #lvm-shell .mini-phone .scr{border-radius:15px}\n  #lvm-shell .mini-cap{font-size:10px}\n  #lvm-shell .mini-cap strong{font-size:13px}\n  #lvm-shell .duo-row{grid-template-columns:repeat(2,1fr);gap:12px}\n  #lvm-shell .duo-row .mini-phone{max-width:130px}\n  #lvm-shell .steps{grid-template-columns:1fr;gap:18px}\n  #lvm-shell .steps::before{display:none}\n  #lvm-shell .step{padding-top:0;padding-left:24px}\n  #lvm-shell .step::before{top:6px;left:0}\n  #lvm-shell .table-row{grid-template-columns:1.4fr .9fr .9fr}\n  #lvm-shell .table-row > .crit{padding:13px 12px;font-size:13px}\n  #lvm-shell .table-row > .cell{padding:13px 10px;font-size:12px;gap:8px}\n  #lvm-shell .table-row.head > div{padding:14px 12px;font-size:10px;gap:7px}\n  #lvm-shell .table-row.head .brand-cell img{width:20px;height:20px}\n  #lvm-shell .get-band{padding:36px 22px;border-radius:18px;margin:40px 0 30px}\n  #lvm-shell .get-band h3{font-size:28px}\n  #lvm-shell .get-band .stores img{height:50px}\n  #lvm-shell .cta-band{padding:22px;gap:14px}\n  #lvm-shell .cta-band .l{font-size:16px;min-width:0}\n  #lvm-shell .cta-band .stores img{height:38px}\n  #lvm-shell .faq summary{font-size:18px;gap:14px}\n  #lvm-shell .pyramid{max-width:100%}\n  #lvm-shell .pyramid .level{padding:11px 14px;font-size:14px}\n  #lvm-shell .scorecard{padding:20px 16px;border-radius:16px}\n  #lvm-shell .scorecard-head{grid-template-columns:1.2fr 1fr 1fr;column-gap:14px}\n  #lvm-shell .scorecard-head .h-brand{font-size:12px;gap:5px}\n  #lvm-shell .scorecard-head .h-brand img{width:18px;height:18px}\n  #lvm-shell .scorecard-row{grid-template-columns:1.2fr 1fr 1fr;column-gap:14px;padding:12px 0}\n  #lvm-shell .scorecard-row .crit{font-size:13px;padding-right:8px}\n  #lvm-shell .scorecard-row .bar{gap:6px}\n  #lvm-shell .scorecard-row .bar .v{font-size:11px;min-width:26px}\n  #lvm-shell .persona-it{grid-template-columns:44px 1fr;gap:12px;padding:16px 16px;border-radius:14px}\n  #lvm-shell .persona-it .pic{width:44px;height:44px;font-size:12px}\n  #lvm-shell .persona-it h4{font-size:15px}\n  #lvm-shell .persona-it p{font-size:13px}\n  #lvm-shell .feat-it{grid-template-columns:auto 1fr;gap:14px;padding:20px 0}\n  #lvm-shell .feat-it .fn{font-size:36px;width:54px}\n  #lvm-shell .feat-it .ft{font-size:18px}\n  #lvm-shell .feat-it .fd{font-size:13px}\n  #lvm-shell .feat-it .fc{display:none}\n}\n@media (max-width:480px){\n  #lvm-shell .phone-tabs{gap:5px}\n  #lvm-shell .phone-tabs button{padding:5px 8px;font-size:10px}\n  #lvm-shell .nav-stores{gap:4px}\n  #lvm-shell .nav-stores img{height:22px}\n  #lvm-shell .hero-stores img{height:40px}\n  #lvm-shell .crumb{font-size:12px}\n  #lvm-shell .table-row{grid-template-columns:1.3fr .85fr .85fr}\n  #lvm-shell .table-row > .crit{padding:11px 9px;font-size:12px}\n  #lvm-shell .table-row > .cell{padding:11px 8px;font-size:11px;gap:6px}\n  #lvm-shell .table-row.head > div{padding:11px 9px;font-size:9px;gap:5px}\n}<\/style>\n\n<style id=\"lvm-collision-reset\">\n\/* Hard reset for global theme styles that collide with our content *\/\nbody.postid-1352 #lvm-shell .hero{display:block!important;align-items:initial!important;justify-content:initial!important;text-align:left!important;flex-direction:initial!important;padding:54px 0 0!important}\nbody.postid-1352 #lvm-shell .wrap,\nbody.postid-1352 #lvm-shell main.wrap{display:block!important;max-width:760px!important;margin-left:auto!important;margin-right:auto!important;padding-left:28px!important;padding-right:28px!important}\n@media (max-width:820px){\n  body.postid-1352 #lvm-shell .wrap,\n  body.postid-1352 #lvm-shell main.wrap{padding-left:18px!important;padding-right:18px!important}\n}\nhtml, body{overflow-x:hidden!important}\nbody.postid-1352 #lvm-shell{overflow-x:hidden;max-width:100vw}\nbody.postid-1352 #lvm-shell *{max-width:100%}\nbody.postid-1352 #lvm-shell .nav-row{max-width:100vw;box-sizing:border-box}\nbody.postid-1352 #lvm-shell.force-show .rev{opacity:1!important;transform:none!important}\n\n\/* === A.1 PHONE BACKGROUND CLASSES === *\/\nbody.postid-1352 #lvm-shell .phone-bg{position:absolute;inset:0;width:100%;height:100%;background-size:cover;background-position:center top;background-repeat:no-repeat;transition:opacity .28s ease;background-color:#FAF0E6}\nbody.postid-1352 #lvm-shell .phone-bg.tab-depense{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp)}\nbody.postid-1352 #lvm-shell .phone-bg.tab-bilan{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp)}\nbody.postid-1352 #lvm-shell .phone-bg.tab-kcal{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp)}\nbody.postid-1352 #lvm-shell .phone-bg.tab-strategie{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp)}\nbody.postid-1352 #lvm-shell .phone-bg.sub-BMR{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp)}\nbody.postid-1352 #lvm-shell .phone-bg.sub-NEAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp)}\nbody.postid-1352 #lvm-shell .phone-bg.sub-EAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp)}\nbody.postid-1352 #lvm-shell .phone-bg.sub-TEF{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp)}\n\n\/* === v11.3 CTA BANDS MOBILE (badges plus gros + centrage) === *\/\n@media (max-width:760px){\n  body.postid-1352 #lvm-shell .cta-band{flex-direction:column!important;align-items:center!important;text-align:center!important;padding:26px 22px!important;gap:20px!important}\n  body.postid-1352 #lvm-shell .cta-band .l{min-width:0!important;width:100%!important;font-size:16px!important;line-height:1.5!important;text-align:center!important}\n  body.postid-1352 #lvm-shell .cta-band .stores{width:100%!important;justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1352 #lvm-shell .cta-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1352 #lvm-shell .cta-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1352 #lvm-shell .cta-band .stores img{height:56px!important;width:100%!important;max-width:170px!important;object-fit:contain!important;object-position:center!important;border-radius:10px!important}\n  body.postid-1352 #lvm-shell .get-band{padding:38px 22px!important}\n  body.postid-1352 #lvm-shell .get-band .stores{justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1352 #lvm-shell .get-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1352 #lvm-shell .get-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1352 #lvm-shell .get-band .stores img{height:56px!important;width:100%!important;max-width:170px!important;object-fit:contain!important;object-position:center!important;border-radius:10px!important}\n  body.postid-1352 #lvm-shell .get-band h3{font-size:26px!important;line-height:1.2!important}\n  body.postid-1352 #lvm-shell .get-band p{font-size:15px!important}\n}\n\n\/* === v11.2 BRAND BANNER above table responsive === *\/\n@media (max-width:760px){\n  body.postid-1352 #lvm-shell .brand-banner img{width:54px!important;height:54px!important}\n  body.postid-1352 #lvm-shell .brand-banner > div{padding:16px 12px!important;gap:8px!important}\n  body.postid-1352 #lvm-shell .brand-banner > div > div{font-size:15px!important}\n}\n\n\/* === v11.4 SCORECARD partie 7: redesign mobile === *\/\n@media (max-width:760px){\n  body.postid-1352 #lvm-shell .scorecard{padding:18px 16px!important;border-radius:16px!important}\n  body.postid-1352 #lvm-shell .scorecard-head{display:none!important}\n  body.postid-1352 #lvm-shell .scorecard-row{\n    display:block!important;\n    padding:14px 0!important;\n    border-bottom:1px solid #E8E2D6!important;\n  }\n  body.postid-1352 #lvm-shell .scorecard-row .crit{\n    display:block!important;\n    font-size:13px!important;\n    font-weight:600!important;\n    color:#0E0E10!important;\n    margin-bottom:10px!important;\n    padding-right:0!important;\n  }\n  body.postid-1352 #lvm-shell .scorecard-row .bar{\n    display:grid!important;\n    grid-template-columns:54px 1fr 32px!important;\n    column-gap:8px!important;\n    align-items:center!important;\n    padding:5px 0!important;\n    flex-direction:initial!important;\n    position:relative!important;\n  }\n  body.postid-1352 #lvm-shell .scorecard-row .bar::before{\n    content:attr(data-brand)!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:11px!important;\n    font-weight:600!important;\n    text-transform:uppercase!important;\n    letter-spacing:.05em!important;\n    color:#0E0E10!important;\n  }\n  body.postid-1352 #lvm-shell .scorecard-row .bar.lean::before{color:#FF2D6E!important}\n  body.postid-1352 #lvm-shell .scorecard-row .bar.mfp::before{color:#5B7FFF!important}\n  body.postid-1352 #lvm-shell .scorecard-row .bar .b{\n    height:10px!important;\n    width:100%!important;\n    border-radius:99px!important;\n    position:relative!important;\n    background:#EFEAE0!important;\n    overflow:hidden!important;\n  }\n  body.postid-1352 #lvm-shell .scorecard-row .bar .b > i{\n    display:block!important;\n    height:100%!important;\n    border-radius:99px!important;\n  }\n  body.postid-1352 #lvm-shell .scorecard-row .bar .v{\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:12px!important;\n    font-weight:700!important;\n    color:#0E0E10!important;\n    min-width:0!important;\n    text-align:right!important;\n  }\n}\n\n\/* === A.2 CHARTS MOBILE === *\/\n@media (max-width:760px){\n  \/* v13: charts FULL WIDTH (less card padding) + plus hauts pour vraie respiration *\/\n  body.postid-1352 #lvm-shell .cv-wrap{height:380px!important;min-height:360px!important;max-height:420px!important;width:100%!important}\n  body.postid-1352 #lvm-shell .cv-wrap canvas{width:100%!important;height:100%!important;display:block!important}\n  body.postid-1352 #lvm-shell .fig{padding:16px 4px 14px!important;margin:24px -4px 14px!important;overflow:visible!important}\n  body.postid-1352 #lvm-shell .fig-head{padding:0 12px!important;flex-wrap:wrap!important;gap:6px!important;margin-bottom:10px!important}\n  body.postid-1352 #lvm-shell .fig-body{padding:0 2px!important}\n  body.postid-1352 #lvm-shell .fig-cap{padding:0 12px!important;font-size:13px!important;margin-top:10px!important}\n}\n@media (max-width:480px){\n  body.postid-1352 #lvm-shell .cv-wrap{height:360px!important;min-height:340px!important;max-height:380px!important}\n  body.postid-1352 #lvm-shell .fig{padding:14px 2px 12px!important;margin:20px -6px 12px!important;border-radius:14px!important}\n  body.postid-1352 #lvm-shell .fig-body{padding:0!important}\n}\n\n\/* === v11.2 TABLEAU MOBILE STACKED CARDS avec mini-tags Lean\/MFP === *\/\n@media (max-width:760px){\n  body.postid-1352 #lvm-shell .table{border-radius:14px!important}\n  body.postid-1352 #lvm-shell .table-row.head{display:none!important}\n  body.postid-1352 #lvm-shell .table-row{\n    display:grid!important;\n    grid-template-columns:1fr 1fr!important;\n    grid-template-areas:\"crit crit\" \"lean mfp\"!important;\n    gap:0!important;\n    min-height:0!important;\n  }\n  body.postid-1352 #lvm-shell .table-row > .crit{\n    grid-area:crit!important;background:#0E0E10!important;color:#fff!important;\n    padding:11px 14px!important;font-size:13px!important;font-weight:600!important;\n    letter-spacing:-0.1px!important;border-right:0!important;line-height:1.35!important;\n    font-family:-apple-system,BlinkMacSystemFont,'SF Pro Display',sans-serif!important;text-transform:none!important;\n  }\n  body.postid-1352 #lvm-shell .table-row > .cell.lean{\n    grid-area:lean!important;border-right:1px solid #E8E2D6!important;\n    position:relative!important;background:#FFF1F5!important;padding-top:30px!important;\n  }\n  body.postid-1352 #lvm-shell .table-row > .cell:not(.lean):not(.crit){\n    grid-area:mfp!important;background:#F5F5F7!important;padding-top:30px!important;\n    position:relative!important;\n  }\n  body.postid-1352 #lvm-shell .table-row > .cell.lean::before{\n    content:\"LEAN\"!important;position:absolute!important;top:8px!important;left:12px!important;\n    right:auto!important;bottom:auto!important;width:auto!important;height:auto!important;\n    background:transparent!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:10px!important;font-weight:700!important;letter-spacing:.07em!important;\n    color:#FF2D6E!important;\n  }\n  body.postid-1352 #lvm-shell .table-row > .cell:not(.lean):not(.crit)::before{\n    content:\"YAZIO\"!important;position:absolute!important;top:8px!important;left:12px!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:10px!important;font-weight:700!important;letter-spacing:.07em!important;\n    color:#02BB8C!important;\n  }\n  body.postid-1352 #lvm-shell .table-row > .cell{\n    padding:12px 12px!important;font-size:13px!important;line-height:1.4!important;\n    align-items:flex-start!important;gap:7px!important;\n  }\n  body.postid-1352 #lvm-shell .icn{flex-shrink:0!important;margin-top:1px!important}\n}\n\n\/* === A.5 MINI-LOGOS partie 7 (triplet NEAT\/EAT\/TEF) === *\/\n@media (max-width:760px){\n  body.postid-1352 #lvm-shell .mini-row{gap:6px!important;margin:24px 0!important;grid-template-columns:repeat(3,1fr)!important}\n  body.postid-1352 #lvm-shell .mini-phone{max-width:100px!important;padding:2px!important;border-radius:14px!important;border-width:1px!important}\n  body.postid-1352 #lvm-shell .mini-phone.tiny{max-width:96px!important;padding:2px!important;border-radius:13px!important}\n  body.postid-1352 #lvm-shell .mini-phone .notch{width:30px!important;height:8px!important;border-radius:0 0 5px 5px!important}\n  body.postid-1352 #lvm-shell .mini-phone .scr{border-radius:11px!important}\n  body.postid-1352 #lvm-shell .mini-cap{font-size:10px!important;margin-top:8px!important}\n  body.postid-1352 #lvm-shell .mini-cap strong{font-size:12px!important;margin-top:2px!important}\n}\n\n\/* === MOCKUP TAP HINT MOBILE === *\/\n@media (max-width:760px){\n  body.postid-1352 #lvm-shell .tap-hint.mobile{position:relative!important;width:100%!important;left:auto!important;top:auto!important;text-align:center!important;margin:0 auto 14px!important;display:block!important}\n  body.postid-1352 #lvm-shell .tap-hint.desktop{display:none!important}\n  body.postid-1352 #lvm-shell .tap-hint.hidden{display:none!important;height:0!important;margin:0!important;padding:0!important}\n}\n\n\/* === A.6 BODYSCAN ILLUST partie BMR (override mobile mini-phone) === *\/\nbody.postid-1352 #lvm-shell .bodyscan-illust{margin:40px auto 8px!important;display:flex!important;flex-direction:column!important;align-items:center!important;gap:14px!important;max-width:220px!important}\nbody.postid-1352 #lvm-shell .bodyscan-illust .mini-phone{max-width:200px!important;padding:3px!important;border-radius:22px!important;border-width:1px!important}\nbody.postid-1352 #lvm-shell .bodyscan-illust .mini-phone .notch{width:40px!important;height:11px!important;border-radius:0 0 7px 7px!important}\nbody.postid-1352 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:18px!important}\n@media (max-width:760px){\n  body.postid-1352 #lvm-shell .bodyscan-illust{max-width:180px!important}\n  body.postid-1352 #lvm-shell .bodyscan-illust .mini-phone{max-width:160px!important;padding:3px!important;border-radius:20px!important}\n  body.postid-1352 #lvm-shell .bodyscan-illust .mini-phone .notch{width:34px!important;height:9px!important;border-radius:0 0 6px 6px!important}\n  body.postid-1352 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:16px!important}\n}\n<\/style>\n<script data-wpmeteor-nooptimize=\"true\">\n(function(){\n  \/* Hard fallback: force .rev visible after 2s if IntersectionObserver doesn't fire *\/\n  setTimeout(function(){\n    var shell = document.getElementById('lvm-shell');\n    if(!shell) return;\n    var anyOn = shell.querySelector('.rev.on');\n    if(!anyOn){ shell.classList.add('force-show'); }\n  }, 2000);\n\n  \/* ResizeObserver fallback: ensure charts resize correctly *\/\n  if (typeof ResizeObserver !== 'undefined'){\n    var observer = new ResizeObserver(function(entries){\n      entries.forEach(function(entry){\n        var canvas = entry.target.querySelector('canvas');\n        if (!canvas || !window.Chart) return;\n        var inst = window.Chart.getChart(canvas);\n        if (inst) { try { inst.resize(); } catch(e){} }\n      });\n    });\n    document.querySelectorAll('#lvm-shell .cv-wrap').forEach(function(w){ observer.observe(w); });\n  }\n})();\n<\/script>\n<div id=\"lvm-shell\"><div class=\"progress\" aria-hidden=\"true\"><i id=\"progBar\"><\/i><\/div>\n\n<header class=\"nav\">\n  <div class=\"nav-row\">\n    <a class=\"nav-brand\" href=\"https:\/\/lean-app.com\/pt\/\" aria-label=\"In\u00edcio 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\/pt\/tdee-calculator\/\">Calculadora TDEE<\/a>\n    <div class=\"nav-stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-yazio\" target=\"_blank\" rel=\"noopener\" aria-label=\"Baixar na App Store\">\n        <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/>\n      <\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-yazio\" target=\"_blank\" rel=\"noopener\" aria-label=\"Dispon\u00edvel no Google Play\">\n        <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/>\n      <\/a>\n    <\/div>\n  <\/div>\n<\/header>\n\n<main class=\"wrap\">\n\n<section class=\"hero\" aria-labelledby=\"title\">\n  <div class=\"crumb\"><a href=\"https:\/\/lean-app.com\/pt\/\">In\u00edcio<\/a> &nbsp;\/&nbsp; Lean vs Yazio<\/div>\n  <div class=\"eyebrow\">Comparativo &middot; Nutri\u00e7\u00e3o &amp; TDEE<\/div>\n  <h1 id=\"title\">Lean diante do Yazio.\n    <span class=\"alt\">O tracker de calorias mais amado da Europa diante do \u00fanico que recomp\u00f5e seu TDEE continuamente.<\/span>\n  <\/h1>\n  <p class=\"dek\">O Yazio conta. O Lean calcula. A diferen\u00e7a aparece ap\u00f3s 6 semanas.<\/p>\n  <div class=\"byline\">\n    <img class=\"by-logo\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/>\n    <span><strong>A equipe Lean<\/strong> &middot; Leitura 12&nbsp;min &middot; Atualizado em 21 de maio de 2026<\/span>\n  <\/div>\n  <div class=\"hero-stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-yazio\" target=\"_blank\" rel=\"noopener\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"T\u00e9l\u00e9charger sur l'App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-yazio\" target=\"_blank\" rel=\"noopener\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Disponible sur Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <span class=\"or\">Download gratuito<\/span>\n  <\/div>\n\n  <div class=\"hero-bottom\">\n    <div class=\"hero-lead\">\n      O Yazio \u00e9 enorme e excelente em jejum intermitente e nas mais de 3&nbsp;000 receitas guiadas. Mas sua f\u00f3rmula de TDEE continua sendo Mifflin-St Jeor 1990, mais um n\u00edvel de atividade fixo que voc\u00ea marca uma \u00fanica vez no cadastro (uma das 5 caixas sedent\u00e1rio\/baixo\/moderado\/ativo\/muito ativo). Sem gordura corporal, sem adapta\u00e7\u00e3o metab\u00f3lica. Em 3 meses de cutting s\u00e9rio, a diferen\u00e7a aumenta.\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>Demonstra\u00e7\u00e3o interativa<\/small>Toque na tela para explorar o aplicativo<\/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>Demonstra\u00e7\u00e3o interativa<\/small>Toque na tela<br>para explorar o aplicativo<\/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=\"Vis\u00e3o geral do app Lean com detalhamento do TDEE\">\n          <div class=\"notch\"><\/div>\n          <div class=\"phone-screen\">\n            <button class=\"phone-back\" id=\"phoneBack\" aria-label=\"Voltar\">&#8249;<\/button>\n            <div id=\"phoneImg\" class=\"phone-bg tab-depense\" role=\"img\" aria-label=\"Vis\u00e3o geral Lean, aba 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=\"Detalhe BMR\"><\/div>\n              <div class=\"z\" data-sub=\"NEAT\" style=\"top:33%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"Detalhe NEAT\"><\/div>\n              <div class=\"z\" data-sub=\"EAT\"  style=\"top:50%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"Detalhe EAT\"><\/div>\n              <div class=\"z\" data-sub=\"TEF\"  style=\"top:67%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"Detalhe TEF\"><\/div>\n            <\/div>\n            <div class=\"phone-navbar\" id=\"phoneNav\" aria-hidden=\"false\">\n              <button data-tab=\"bilan\"     type=\"button\" aria-label=\"Aba Balan\u00e7o\"><\/button>\n              <button data-tab=\"kcal\"      type=\"button\" aria-label=\"Aba Calorias\"><\/button>\n              <button data-tab=\"depense\"   type=\"button\" aria-label=\"Aba Gasto\"><\/button>\n              <button data-tab=\"strategie\" type=\"button\" aria-label=\"Aba Estrat\u00e9gia\"><\/button>\n            <\/div>\n          <\/div>\n        <\/div>\n        <div class=\"phone-tabs\" role=\"tablist\" aria-label=\"Navegar no app Lean\">\n          <button data-tab=\"bilan\"     type=\"button\">Balan\u00e7o<\/button>\n          <button data-tab=\"kcal\"      type=\"button\">Calorias<\/button>\n          <button data-tab=\"depense\"   type=\"button\" class=\"on\">Gasto<\/button>\n          <button data-tab=\"strategie\" type=\"button\">Estrat\u00e9gia<\/button>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"snippet rev\">\n    <div class=\"lbl\">Resposta r\u00e1pida<\/div>\n    <p>O Yazio calcula seu TDEE com Mifflin-St Jeor 1990 (sem gordura corporal) e um n\u00edvel de atividade fixo que voc\u00ea marca uma vez no cadastro, entre 5 caixas (sedent\u00e1rio, baixo, moderado, ativo, muito ativo). A f\u00f3rmula \u00e9 mais moderna do que Harris-Benedict 1919 mas herda o mesmo defeito: sem massa magra, sem NEAT medido pelos passos, sem adapta\u00e7\u00e3o metab\u00f3lica. O Lean recalcula cada componente (<span data-term=\"BMR\">BMR<span class=\"tt\">Basal Metabolic Rate. Energia gasta em repouso. Na Lean, calculada sobre a massa magra real via BodyScan IA.<\/span><\/span> sobre gordura corporal real via um modelo propriet\u00e1rio patenteado, <span data-term=\"NEAT\">NEAT<span class=\"tt\">Non-Exercise Activity Thermogenesis. Gasto ligado aos passos e \u00e0s atividades cotidianas fora do esporte.<\/span><\/span> por passos, <span data-term=\"EAT\">EAT<span class=\"tt\">Exercise Activity Thermogenesis. Gasto ligado aos seus treinos, calculado via MET.<\/span><\/span> por MET, <span data-term=\"TEF\">TEF<span class=\"tt\">Thermic Effect of Food. Energia gasta pela digest\u00e3o. Depende dos macros ingeridos.<\/span><\/span> por macros) e modula o BMR pela adapta\u00e7\u00e3o metab\u00f3lica continuamente, sem coeficiente a escolher.<\/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; A constata\u00e7\u00e3o<\/span><\/div>\n  <h2 id=\"constat\">O Yazio te acompanha por 100 dias, at\u00e9 o momento em que seu corpo se adapta<\/h2>\n  <p>Se voc\u00ea est\u00e1 lendo isso, provavelmente j\u00e1 instalou o Yazio. Informou seu peso, sua altura, sua idade, seu sexo. O app pediu para marcar seu n\u00edvel de atividade em uma lista de 5 caixas (sedent\u00e1rio, baixo, moderado, ativo, muito ativo). Mostrou um objetivo cal\u00f3rico, digamos 2&nbsp;250&nbsp;kcal para perder peso. Voc\u00ea seguiu religiosamente. Usou o 16:8, cozinhou as receitas guiadas, escaneou seus c\u00f3digos de barras.<\/p>\n  <p>As primeiras 6 semanas, funciona. Voc\u00ea perde. Fica contente. Depois, por volta da semana 8, a balan\u00e7a congela. Voc\u00ea pensa: \u00ab&nbsp;devo ter relaxado, devo ter registrado mal&nbsp;\u00bb. Aperta o cinto. Desce para 2&nbsp;000&nbsp;kcal. De novo, nada se mexe.<\/p>\n\n  <div class=\"statement\">\n    <div class=\"num\">&minus;10 a &minus;15&nbsp;%<\/div>\n    <div class=\"lbl\">de queda medida do TDEE ap\u00f3s 4 a 6 semanas de d\u00e9ficit a &minus;500&nbsp;kcal\/dia. O Yazio n\u00e3o detecta isso. Seu objetivo cal\u00f3rico fica congelado na sua escolha de 100&nbsp;dias atr\u00e1s.<\/div>\n  <\/div>\n\n  <p>Imagine que o Yazio mostra um TDEE de 2&nbsp;500&nbsp;kcal. Voc\u00ea come 2&nbsp;250 (d\u00e9ficit te\u00f3rico de 250&nbsp;kcal). Mas na realidade, seu <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/depense-energetique-totale-v2\/\">TDEE caiu para 2&nbsp;200&nbsp;kcal<\/a> por causa da adapta\u00e7\u00e3o metab\u00f3lica. Voc\u00ea est\u00e1 em super\u00e1vit de 50&nbsp;kcal sem saber. Nenhuma chance de continuar perdendo.<\/p>\n  <p>\u00c9 por isso que \u00e9 crucial <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/comment-compter-ses-calories\/\">calcular perfeitamente seu gasto<\/a>, e recalcul\u00e1-lo continuamente. E \u00e9 exatamente a\u00ed que o Yazio, como a maioria dos trackers de consumo, fica congelado na estimativa inicial.<\/p>\n<\/section>\n\n<section aria-labelledby=\"p1\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">01 &middot; Problema 1<\/span><\/div>\n  <h2 id=\"p1\">A f\u00f3rmula BMR de 1990, sem gordura corporal<\/h2>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figura 1 &middot; Homem 1,80 m, 120&nbsp;kg, 30&nbsp;% BF<\/span><span class=\"r\">kcal<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\" style=\"position:relative;width:100%;height:380px;min-height:340px\"><canvas id=\"chartBMR\" aria-label=\"Compara\u00e7\u00e3o BMR Mifflin-St Jeor 2500 kcal vs modelo propriet\u00e1rio patenteado Lean 2000 kcal, diferen\u00e7a de 500 kcal\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>BMR estimado.<\/strong> O modelo propriet\u00e1rio patenteado Lean leva em conta a massa magra. Mifflin-St Jeor (Yazio), n\u00e3o. Diferen\u00e7a de 500&nbsp;kcal, o equivalente a um almo\u00e7o inteiro.<\/p>\n  <\/div>\n\n  <p>Para calcular seu metabolismo basal (o BMR, a energia que voc\u00ea queima em repouso), o Yazio usa a equa\u00e7\u00e3o de Mifflin-St Jeor. \u00c9 a f\u00f3rmula can\u00f4nica da maioria dos trackers de calorias de consumo, e \u00e9 preciso ser honesto: \u00e9 melhor do que Harris-Benedict 1919, que outros apps ainda usam.<\/p>\n  <p>Mifflin-St Jeor \u00e9 de 1990. A amostra \u00e9 maior (498 sujeitos), a metodologia de calorimetria indireta \u00e9 mais precisa, a f\u00f3rmula \u00e9 calibrada sobre uma popula\u00e7\u00e3o mais moderna. O Yazio aplica a f\u00f3rmula oficial: 10 \u00d7 peso (kg) + 6,25 \u00d7 altura (cm) \u2212 5 \u00d7 idade \u2212 161 (mulheres) ou +5 (homens).<\/p>\n  <p>Mas a atualiza\u00e7\u00e3o para por a\u00ed. Mifflin (1990) corrige marginalmente Harris-Benedict (1919) na precis\u00e3o m\u00e9dia, mas herda o mesmo defeito conceitual: <strong>a f\u00f3rmula s\u00f3 leva em conta o peso. Nem a gordura corporal. Nem a massa magra.<\/strong><\/p>\n  <p>Mas desde os anos 80 se sabe que <strong>a massa gorda gasta muito pouca energia<\/strong> comparada ao resto do corpo. O f\u00edgado, o c\u00e9rebro, o cora\u00e7\u00e3o, os rins e sobretudo os m\u00fasculos s\u00e3o os verdadeiros consumidores. A massa gorda \u00e9 inerte. Uma pessoa com 30&nbsp;% de gordura corporal n\u00e3o queima nem de longe o mesmo que uma pessoa com 10&nbsp;%, mesmo com o mesmo peso.<\/p>\n  <p>Frankenfield 2013 (PubMed 23631843) comparou Mifflin-St Jeor com a calorimetria indireta de refer\u00eancia em coortes obesas e n\u00e3o obesas. Resultado: precis\u00e3o de 87&nbsp;% nos n\u00e3o obesos, e apenas <strong>75&nbsp;% nos obesos<\/strong>. Um estudo mais recente (PMC11820646) mostra que nos IMC acima de 35, Mifflin erra em <strong>250 a 315&nbsp;kcal por dia<\/strong>. \u00c9 o equivalente a um lanche inteiro no c\u00e1lculo de um d\u00e9ficit.<\/p>\n\n  <p>500&nbsp;kcal n\u00e3o \u00e9 pouca coisa. Se o Yazio diz \u00ab&nbsp;seu BMR \u00e9 de 2&nbsp;500&nbsp;\u00bb e na realidade \u00e9 de 2&nbsp;000, tudo o que vem depois est\u00e1 errado.<\/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\">Gordura 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 diferen\u00e7a entre dois homens de 80&nbsp;kg, um com 10&nbsp;% de gordura corporal (BMR 1&nbsp;900), o outro com 30&nbsp;% (BMR 1&nbsp;500). O Yazio d\u00e1 a eles o mesmo n\u00famero.<\/div>\n  <\/div>\n\n  <p>Conclus\u00e3o parcial: se um app calcula seu BMR unicamente a partir do seu peso, da sua altura, da sua idade e do seu sexo, o resultado n\u00e3o pode ser individualizado. \u00c9 matematicamente imposs\u00edvel.<\/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\">O n\u00edvel de atividade, escolhido de uma vez por todas<\/h2>\n  <p>\u00c9 aqui que a coisa fica grave. E provavelmente \u00e9 o ponto que ningu\u00e9m te explicou.<\/p>\n  <p>Uma vez que o Yazio calculou seu BMR (sem gordura corporal), ele precisa estimar seu TDEE total. O <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/depense-energetique-totale-v2\/\">TDEE, \u00e9 o BMR + todo o resto<\/a> : o gasto ligado aos passos, \u00e0s atividades cotidianas, ao esporte e \u00e0 digest\u00e3o. Tudo o que n\u00e3o \u00e9 metabolismo basal.<\/p>\n  <p>Como o Yazio faz isso? Ele pede, uma \u00fanica vez no momento do cadastro, para marcar uma das 5 caixas que resume sozinha seu estilo de vida. Essas 5 caixas se chamam em ci\u00eancia do esporte <strong>n\u00edveis PAL<\/strong> (Physical Activity Level), \u00e9 s\u00f3 um multiplicador aplicado ao seu BMR:<\/p>\n  <ul>\n    <li>Sedent\u00e1rio (PAL 1,2): escrit\u00f3rio, pouca caminhada<\/li>\n    <li>Atividade baixa (PAL 1,375): caminhada ocasional<\/li>\n    <li>Atividade moderada (PAL 1,55): esporte 3 a 5 vezes por semana<\/li>\n    <li>Ativo (PAL 1,725): esporte intenso quase di\u00e1rio<\/li>\n    <li>Muito ativo (PAL 1,9): esporte muito intenso ou trabalho f\u00edsico<\/li>\n  <\/ul>\n  <p>E segundo sua escolha, ele multiplica seu BMR pelo coeficiente associado. \u00c9 s\u00f3 isso. \u00c9 tudo o que h\u00e1 por tr\u00e1s do seu objetivo cal\u00f3rico di\u00e1rio. Uma caixa que VOC\u00ca marcou uma \u00fanica vez no momento do cadastro. Muitas vezes seis meses atr\u00e1s. Sem mudar desde ent\u00e3o.<\/p>\n  <p>E a\u00ed est\u00e1 a armadilha silenciosa: essa aproxima\u00e7\u00e3o \u00e9 <strong>hiperimperfeita<\/strong>. A diferen\u00e7a entre um dia em que voc\u00ea fica grudado no sof\u00e1 vendo Netflix e um dia em que vai \u00e0 Disneyland com seus filhos e anda 15&nbsp;km, <strong>s\u00e3o mais de 1&nbsp;000&nbsp;kcal<\/strong>. Nenhuma das 5 caixas capta isso.<\/p>\n  <p>O Yazio sincroniza bem com Apple Health e Google Health Connect, e capta seus passos. Mas esses passos alimentam a se\u00e7\u00e3o \u00ab&nbsp;Activities\/Burned&nbsp;\u00bb, n\u00e3o o rec\u00e1lculo do TDEE. Seu objetivo cal\u00f3rico di\u00e1rio continua baseado na caixa PAL escolhida no onboarding.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figura 2 &middot; 7 dias reais<\/span><span class=\"r\">kcal\/dia<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\" style=\"position:relative;width:100%;height:380px;min-height:340px\"><canvas id=\"chartNEAT\" aria-label=\"Variabilidade di\u00e1ria do gasto cal\u00f3rico em 7 dias, contra 2400 kcal fixas segundo o Yazio\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>Gasto real<\/strong> medido durante 7&nbsp;dias em um usu\u00e1rio do Lean. A linha cinza \u00e9 o que o Yazio mostrava (2&nbsp;400&nbsp;kcal fixas, PAL moderado \u00d7 BMR). As anota\u00e7\u00f5es rosa mostram por que cada dia se mexe.<\/p>\n  <\/div>\n\n  <p>Voc\u00ea n\u00e3o pode reduzir seu n\u00edvel de atividade a uma caixa est\u00e1tica. Talvez voc\u00ea seja ativo nas semanas em que faz pouco home office, e sedent\u00e1rio nas que n\u00e3o sai do escrit\u00f3rio. Talvez seja ativo no ver\u00e3o e sedent\u00e1rio no inverno. Talvez seja ativo de ter\u00e7a a sexta e sedent\u00e1rio no fim de semana.<\/p>\n  <p>Qual caixa voc\u00ea vai marcar esta semana? A verdade \u00e9 que nenhuma das 5 ser\u00e1 correta. E portanto o Yazio vai te dar um TDEE sistematicamente desconectado da realidade.<\/p>\n  <p>O ponto-chave deste artigo: mesmo que o Yazio tivesse uma f\u00f3rmula BMR perfeita (o que n\u00e3o \u00e9 o caso), o PAL est\u00e1tico bastaria para quebrar tudo. Voc\u00ea n\u00e3o pode estimar um <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/neat-depense-non-sportive\/\">NEAT<\/a>, um EAT e um <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/effet-thermique-des-aliments\/\">TEF<\/a> com um multiplicador \u00fanico aplicado ao BMR. \u00c9 conceitualmente absurdo.<\/p>\n  <p>Voc\u00ea j\u00e1 entendeu: <strong>uma f\u00f3rmula BMR sem gordura corporal, mais uma aproxima\u00e7\u00e3o PAL est\u00e1tica das outras rubricas de gasto, d\u00e1 muito poucas chances de atingir seus objetivos em 3 a 6 meses.<\/strong><\/p>\n\n  <div class=\"cta-band rev\" style=\"display:flex;align-items:center;justify-content:space-between;gap:20px;flex-wrap:wrap;padding:26px 28px;margin:40px 0;background:#FAF5EE;border:1px solid #E8E2D6;border-radius:16px\">\n    <div class=\"l\" style=\"flex:1;min-width:240px;font-size:18px;line-height:1.4;font-weight:500;color:#0E0E10\">Ver seu TDEE real, decomposto em BMR + NEAT + EAT + TEF. Download gratuito.<\/div>\n    <div class=\"stores\" style=\"display:flex;gap:10px;align-items:center;flex-wrap:wrap\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-yazio\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-yazio\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"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\">A adapta\u00e7\u00e3o metab\u00f3lica, nunca modelada<\/h2>\n  <p>\u00c9 o chef\u00e3o final. A no\u00e7\u00e3o mais fina. E provavelmente a mais importante.<\/p>\n  <p>Quando voc\u00ea est\u00e1 em d\u00e9ficit cal\u00f3rico, seu corpo entende que recebe menos energia do que antes. Para se proteger, ele passa para o modo economia. Exatamente como o modo de economia de energia do seu iPhone: tudo continua funcionando, mas usando menos energia. Seu BMR cai. Seu NEAT cai. Seu EAT cai.<\/p>\n  <p>\u00c9 o que se chama adapta\u00e7\u00e3o metab\u00f3lica. A literatura cient\u00edfica \u00e9 clara e reproduz\u00edvel: M\u00fcller 2015 (PubMed 26399868, revis\u00e3o de Minnesota), Doucet 2001 (PubMed 11430776), Nunes 2020 (PMC7484122) em 6 semanas de d\u00e9ficit. Estes s\u00e3o os n\u00fameros:<\/p>\n  <ul>\n    <li>D\u00e9ficit de &minus;250&nbsp;kcal por dia, durante 2 a 8 semanas: adapta\u00e7\u00e3o de <strong>de 5 a 10&nbsp;%<\/strong> (o TDEE cai para 90-95&nbsp;% do n\u00edvel inicial)<\/li>\n    <li>D\u00e9ficit de &minus;500&nbsp;kcal por dia: <strong>10 a 15&nbsp;%<\/strong> de adapta\u00e7\u00e3o (o TDEE cai para 85-90&nbsp;%)<\/li>\n    <li>D\u00e9ficit de &minus;750&nbsp;kcal por dia: <strong>15 a 25&nbsp;%<\/strong> de adapta\u00e7\u00e3o (o TDEE cai para 75-85&nbsp;%)<\/li>\n  <\/ul>\n  <p>Conven\u00e7\u00e3o Lean: 100&nbsp;% = ideal, 90&nbsp;% = 10&nbsp;% de adapta\u00e7\u00e3o. E como o NEAT, o EAT e o TEF dependem todos diretamente do BMR, \u00e9 quase todo o TDEE que \u00e9 afetado.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figura 3 &middot; 8 semanas em d\u00e9ficit<\/span><span class=\"r\">kcal\/dia<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\" style=\"position:relative;width:100%;height:380px;min-height:340px\"><canvas id=\"chartAdapt\" aria-label=\"TDEE que cai de 2500 para 2150 kcal em 8 semanas, contra 2500 fixas segundo o Yazio\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>TDEE real<\/strong> em 8 semanas de d\u00e9ficit a &minus;500&nbsp;kcal\/dia. A curva rosa desce. A linha do Yazio fica plana. Na semana 6, voc\u00ea j\u00e1 est\u00e1 na manuten\u00e7\u00e3o. Sem ter mudado nada.<\/p>\n  <\/div>\n\n  <p>Concretamente: se voc\u00ea previu um d\u00e9ficit de 10&nbsp;% sobre um TDEE de 2&nbsp;500 (ou seja, comer 2&nbsp;250 por dia), e seu corpo se adapta em 10&nbsp;%, seu TDEE real passou a 2&nbsp;250. Voc\u00ea est\u00e1 na manuten\u00e7\u00e3o. N\u00e3o perde mais.<\/p>\n  <p>A armadilha \u00e9 que \u00e9 insidioso. No in\u00edcio, voc\u00ea perde. Fica contente. Continua. Mas semana ap\u00f3s semana, a adapta\u00e7\u00e3o se acumula. E em algum momento, sem ter mudado nada no seu tracking, <strong>voc\u00ea para de perder<\/strong>.<\/p>\n  <p>95&nbsp;% das pessoas passam por isso sem entender. Culpam a for\u00e7a de vontade. Culpam o \u00ab&nbsp;metabolismo quebrado&nbsp;\u00bb. Voltam para dietas mais duras, o que agrava a adapta\u00e7\u00e3o. Espiral.<\/p>\n  <p>O Yazio nunca calcula a adapta\u00e7\u00e3o metab\u00f3lica. Ele te d\u00e1 um objetivo fixo e est\u00e1tico. Quando voc\u00ea estagna ap\u00f3s 6 semanas, o app n\u00e3o tem a menor ideia do porqu\u00ea.<\/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; Solu\u00e7\u00e3o Lean<\/span><\/div>\n  <h2 id=\"solution\">Como o Lean resolve cada um dos 3 problemas<\/h2>\n  <p>O Yazio conseguiu o que o MyFitnessPal falhou: uma interface clara, sem ru\u00eddo publicit\u00e1rio, e uma vers\u00e3o gratuita realmente utiliz\u00e1vel. O design mudou, a ci\u00eancia n\u00e3o: debaixo do cap\u00f4, encontramos Harris-Benedict e um n\u00edvel de atividade escolhido no cadastro. O Lean investiu exatamente onde o Yazio n\u00e3o se mexeu: o c\u00e1lculo de cada componente do TDEE (BMR&nbsp;+&nbsp;NEAT&nbsp;+&nbsp;EAT&nbsp;+&nbsp;TEF) mais a adapta\u00e7\u00e3o metab\u00f3lica. Veja como.<\/p>\n\n  <div class=\"method\">\n    <div class=\"m-phone\">\n      <div class=\"duo-row\">\n        <div>\n          <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-bodyscan-result.webp\" alt=\"R\u00e9sultat BodyScan IA : pourcentage de masse grasse mesur\u00e9 par photo\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\">Passo 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\">Passo 2<strong>BMR recalculado<\/strong><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n    <div>\n      <div class=\"m-tag\">O BMR sobre gordura corporal real<\/div>\n      <h3>Modelo propriet\u00e1rio patenteado, baseado na massa magra<\/h3>\n      <p>O Yazio calcula seu metabolismo a partir do seu peso, da sua altura e da sua idade. O Lean parte da sua <strong>massa magra<\/strong>, porque \u00e9 ela que queima em repouso: duas pessoas de 80&nbsp;kg, uma com 12&nbsp;% de gordura corporal e a outra com 30&nbsp;%, n\u00e3o t\u00eam o mesmo metabolismo. Faltava medir essa gordura corporal sem DEXA.<\/p>\n      <p>O <strong>BodyScan IA<\/strong> faz isso com uma foto, via um modelo treinado em um banco de scans DEXA. Resultado em alguns segundos, a refazer toda semana, com rec\u00e1lculo autom\u00e1tico do metabolismo por tr\u00e1s.<\/p>\n      <p>Nem adip\u00f4metro, nem balan\u00e7a de bioimped\u00e2ncia sens\u00edvel \u00e0 hidrata\u00e7\u00e3o, nem DEXA em cl\u00ednica. Uma foto semanal.<\/p>\n    <\/div>\n  <\/div>\n\n  <div class=\"method flip\">\n    <div>\n      <div class=\"m-tag\">Sem coeficiente de atividade<\/div>\n      <h3>NEAT, EAT, TEF calculados separadamente<\/h3>\n      <p><strong>NEAT.<\/strong> Seus passos reais chegam do HealthKit (iOS) ou do Google Fit (Android). O \u00ab&nbsp;n\u00edvel de atividade&nbsp;\u00bb que o Yazio pede no cadastro n\u00e3o muda na segunda em que voc\u00ea faz 15&nbsp;000 passos e no domingo em que n\u00e3o sai do sof\u00e1. O Lean l\u00ea o dado em vez de sup\u00f4-lo.<\/p>\n      <p><strong>EAT.<\/strong> Cada treino \u00e9 calculado por MET sobre seu tempo de esfor\u00e7o real. Uma hora de muscula\u00e7\u00e3o, tempos de descanso inclusos, n\u00e3o vale uma hora de corrida cont\u00ednua: a diferen\u00e7a se conta em centenas de kcal por semana.<\/p>\n      <p><strong>TEF.<\/strong> O custo da digest\u00e3o depende dos seus macros: de 20 a 30&nbsp;% para as prote\u00ednas, de 5 a 10&nbsp;% para os carboidratos, de 1 a 3&nbsp;% para as gorduras. O Lean o calcula sobre o que voc\u00ea realmente comeu em vez de aplicar uma taxa fixa de 10&nbsp;%.<\/p>\n    <\/div>\n    <div class=\"m-phone\">\n      <div class=\"mini-row\" style=\"margin:0;gap:10px\">\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp\" alt=\"\u00c9cran NEAT Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">NEAT<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp\" alt=\"\u00c9cran EAT Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">EAT<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp\" alt=\"\u00c9cran TEF Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">TEF<\/strong><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"method flip\">\n    <div>\n      <div class=\"m-tag\">Adapta\u00e7\u00e3o metab\u00f3lica autom\u00e1tica<\/div>\n      <h3>Uma primeira mundial em um app de consumo<\/h3>\n      <p><strong>A adapta\u00e7\u00e3o metab\u00f3lica.<\/strong> Ap\u00f3s algumas semanas de d\u00e9ficit, seu metabolismo desacelera. O Yazio mostra o mesmo objetivo cal\u00f3rico na semana 8 e no primeiro dia: o Lean ajusta o TDEE para baixo segundo as faixas publicadas (M\u00fcller 2015, Doucet 2001).<\/p>\n      <p>Passados 10 a 15&nbsp;% de adapta\u00e7\u00e3o, o app pode recomendar um retorno \u00e0 manuten\u00e7\u00e3o para relan\u00e7ar o metabolismo antes de voltar ao d\u00e9ficit.<\/p>\n      <p>Nenhum n\u00edvel de atividade a marcar. Cada componente \u00e9 medido, semana ap\u00f3s semana.<\/p>\n    <\/div>\n    <div class=\"m-phone\">\n      <div class=\"mini-phone solo\" style=\"max-width:240px!important;width:240px;padding:6px!important;border-radius:24px!important;border-width:2px!important\"><div class=\"notch\" style=\"width:60px!important;height:14px!important;border-radius:0 0 9px 9px!important\"><\/div><div class=\"scr\" style=\"border-radius:18px!important\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp\" alt=\"\u00c9cran d\u00e9pense totale Lean avec adaptation m\u00e9tabolique\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">M\u00e9todo<strong>Adapta\u00e7\u00e3o metab\u00f3lica<\/strong><\/div>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"tab\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">05 &middot; Tabela comparativa<\/span><\/div>\n  <h2 id=\"tab\">Lean diante do Yazio, crit\u00e9rio por crit\u00e9rio<\/h2>\n  <p>Leitura honesta dos pontos fortes e fracos de cada app. Nenhum crit\u00e9rio se refere ao pre\u00e7o.<\/p>\n\n  <div class=\"brand-banner\" style=\"display:grid;grid-template-columns:1fr 1fr;gap:16px;margin:24px 0 18px;padding:0\">\n  <div style=\"background:#FFF1F5;border:1.5px solid #FF2D6E;border-radius:14px;padding:20px 18px;display:flex;flex-direction:column;align-items:center;text-align:center;gap:10px\">\n    <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"Lean\" width=\"64\" height=\"64\" loading=\"lazy\" decoding=\"async\" style=\"width:64px;height:64px;border-radius:14px;display:block;object-fit:cover\" \/>\n    <div style=\"font-family:-apple-system,BlinkMacSystemFont,'SF Pro Display',sans-serif;font-size:18px;font-weight:700;color:#FF2D6E;letter-spacing:-0.2px\">Lean<\/div>\n  <\/div>\n  <div style=\"background:#FFF1ED;border:1.5px solid #FF5252;border-radius:14px;padding:20px 18px;display:flex;flex-direction:column;align-items:center;text-align:center;gap:10px\">\n    <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/logo-yazio-real.webp\" alt=\"Yazio\" width=\"64\" height=\"64\" loading=\"lazy\" decoding=\"async\" style=\"width:64px;height:64px;border-radius:14px;display:block;object-fit:cover\" \/>\n    <div style=\"font-family:-apple-system,BlinkMacSystemFont,'SF Pro Display',sans-serif;font-size:18px;font-weight:700;color:#FF5252;letter-spacing:-0.2px\">Yazio<\/div>\n  <\/div>\n<\/div>\n<div class=\"table\" role=\"table\" aria-label=\"Comparativo Lean diante do Yazio\">\n    <div class=\"table-row head\" role=\"row\">\n      <div role=\"columnheader\">Crit\u00e9rio<\/div>\n      <div class=\"brand-cell lean\" role=\"columnheader\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> <span>Lean<\/span><\/div>\n      <div class=\"brand-cell\" role=\"columnheader\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/logo-yazio-real.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> <span>Yazio<\/span><\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">F\u00f3rmula BMR<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Modelo propriet\u00e1rio patenteado (massa 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, sem gordura corporal<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Leva em conta a gordura 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> Sim<\/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> N\u00e3o<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Medi\u00e7\u00e3o da gordura corporal no 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 via 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> N\u00e3o<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">NEAT (passos, atividade fora do esporte)<\/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 os passos reais todo dia<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Agregado no PAL est\u00e1tico<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">EAT (gasto do exerc\u00edcio)<\/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 esporte via MET, tempo efetivo<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Misturado com o NEAT em \u00ab&nbsp;Activities\/Burned&nbsp;\u00bb<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">TEF (digest\u00e3o)<\/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 segundo macros<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> N\u00e3o calculado<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Adapta\u00e7\u00e3o 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> N\u00e3o<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Coeficiente de atividade a escolher<\/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> N\u00e3o, calculado sobre dados reais<\/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> Sim, n\u00edvel de atividade fixo (5 caixas, 1,2 a 1,9)<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Scan de foto por IA de um prato<\/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> Sim, ilimitado<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Sim, dispon\u00edvel desde junho de 2025<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Scan 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> Sim<\/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> Sim<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Base de dados de alimentos<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> USDA + OpenFoodFacts, curada<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Mais de 4M de itens, forte cobertura EU\/DE<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Recomenda\u00e7\u00e3o 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 ao 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> Estimativa fixa<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Jejum intermitente<\/div>\n      <div class=\"cell lean\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Fora do escopo<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> 20 trackers, 16:8 gr\u00e1tis, programas PRO<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Receitas guiadas<\/div>\n      <div class=\"cell lean\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Fora do escopo<\/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> Mais de 3&nbsp;000 receitas<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Cobertura EU e localiza\u00e7\u00e3o<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> FR, EN, ES, PT, IT, DE, PL, HU<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> L\u00edder EU, 20 idiomas, forte em DE\/AT\/CH<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Reputa\u00e7\u00e3o e tamanho da audi\u00eancia<\/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, mais de 10&nbsp;000 usu\u00e1rios, app jovem<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> 4,6\/5, 100M de usu\u00e1rios, fundado em 2014<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Modelo de neg\u00f3cio<\/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, teste gratuito de 7 dias no plano anual<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Freemium, PRO em teste<\/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 uma refei\u00e7\u00e3o<\/h2>\n  <p>O Yazio entendeu antes de muitos que a ergonomia faz a ader\u00eancia. O Lean leva a mesma l\u00f3gica ao tracking: tr\u00eas m\u00e9todos de registro, para que nenhum contexto vire motivo de abandono.<\/p>\n\n  <div class=\"mini-row\">\n    <div>\n      <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-database.webp\" alt=\"Recherche dans la base de donn\u00e9es USDA + OpenFoodFacts\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">M\u00e9todo 1<strong>Base de dados<\/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>Scan de foto por IA<\/strong><\/div>\n    <\/div>\n  <\/div>\n\n  <ol>\n    <li><strong>Busca na base de dados.<\/strong> Base curada, USDA + OpenFoodFacts. Sem ru\u00eddo comunit\u00e1rio, sem \u00ab&nbsp;Frango assado&nbsp;\u00bb inserido 47 vezes por 47 usu\u00e1rios diferentes com 47 valores diferentes.<\/li>\n    <li><strong>Scan de c\u00f3digo de barras.<\/strong> Padr\u00e3o. Voc\u00ea escaneia seu pacote de macarr\u00e3o, obt\u00e9m os macros.<\/li>\n    <li><strong>Scan de foto por IA de um prato.<\/strong> Voc\u00ea fotografa seu prato, a IA detecta os alimentos, voc\u00ea obt\u00e9m as calorias e os macros por alimento.<\/li>\n  <\/ol>\n  <p>O scan de foto por IA assume quando nem a base nem o c\u00f3digo de barras bastam: um prato caseiro, um prato no restaurante. Uma foto, e est\u00e1 registrado.<\/p>\n  <p>Al\u00e9m da refei\u00e7\u00e3o, o Lean mostra um TDEE que se mexe durante o dia: seus passos fazem seu objetivo cal\u00f3rico subir ao vivo, onde um coeficiente de atividade escolhido no cadastro fica id\u00eantico todos os dias.<\/p>\n  <p>E para hierarquizar, a Pir\u00e2mide de Progress\u00e3o:<\/p>\n\n  <div class=\"pyramid\" aria-label=\"Pir\u00e2mide de Progress\u00e3o Lean\">\n    <div class=\"level l1\"><span>Ader\u00eancia<\/span><span class=\"k\">Base<\/span><\/div>\n    <div class=\"level l2\"><span>Objetivo cal\u00f3rico<\/span><span class=\"k\">N\u00edvel 2<\/span><\/div>\n    <div class=\"level l3\"><span>Passos \/ NEAT<\/span><span class=\"k\">N\u00edvel 3<\/span><\/div>\n    <div class=\"level l4\"><span>Macronutrientes<\/span><span class=\"k\">Topo<\/span><\/div>\n  <\/div>\n  <div class=\"pyramid-cap\">N\u00e3o queimar etapas. Se voc\u00ea n\u00e3o \u00e9 regular no tracking, otimizar os macros no um por cento n\u00e3o serve para nada.<\/div>\n<\/section>\n\n<section aria-labelledby=\"yazio-better\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">07 &middot; Honestidade<\/span><\/div>\n  <h2 id=\"yazio-better\">O que o Yazio faz melhor<\/h2>\n  <p>O Lean n\u00e3o \u00e9 perfeito, e o Yazio tem v\u00e1rios pontos fortes reais que \u00e9 preciso reconhecer. Leitura honesta, crit\u00e9rio por crit\u00e9rio, nos eixos em que o Yazio continua na frente.<\/p>\n\n  <div class=\"scorecard rev\" aria-label=\"Scorecard Yazio diante do Lean em 4 eixos secund\u00e1rios\">\n    <div class=\"scorecard-head\">\n      <div class=\"h-crit\">Eixo<\/div>\n      <div class=\"h-brand\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/logo-yazio-real.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> Yazio<\/div>\n      <div class=\"h-brand\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> Lean<\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Jejum intermitente integrado<\/div>\n      <div class=\"bar mfp\" data-brand=\"YAZIO\"><div class=\"b\"><i style=\"width:95%\"><\/i><\/div><div class=\"v\">9,5<\/div><\/div>\n      <div class=\"bar lean\" data-brand=\"LEAN\"><div class=\"b\"><i style=\"width:45%\"><\/i><\/div><div class=\"v\">4,5<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Receitas guiadas<\/div>\n      <div class=\"bar mfp\" data-brand=\"YAZIO\"><div class=\"b\"><i style=\"width:90%\"><\/i><\/div><div class=\"v\">9,0<\/div><\/div>\n      <div class=\"bar lean\" data-brand=\"LEAN\"><div class=\"b\"><i style=\"width:15%\"><\/i><\/div><div class=\"v\">1,5<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Cobertura EU e localiza\u00e7\u00e3o<\/div>\n      <div class=\"bar mfp\" data-brand=\"YAZIO\"><div class=\"b\"><i style=\"width:90%\"><\/i><\/div><div class=\"v\">9,0<\/div><\/div>\n      <div class=\"bar lean\" data-brand=\"LEAN\"><div class=\"b\"><i style=\"width:80%\"><\/i><\/div><div class=\"v\">8,0<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Tamanho da audi\u00eancia e avalia\u00e7\u00f5es<\/div>\n      <div class=\"bar mfp\" data-brand=\"YAZIO\"><div class=\"b\"><i style=\"width:95%\"><\/i><\/div><div class=\"v\">9,5<\/div><\/div>\n      <div class=\"bar lean\" data-brand=\"LEAN\"><div class=\"b\"><i style=\"width:30%\"><\/i><\/div><div class=\"v\">3,0<\/div><\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>Leitura honesta.<\/strong> Em jejum intermitente, o Yazio \u00e9 refer\u00eancia do mercado de consumo: 20 trackers, 16:8 gr\u00e1tis, programas guiados no PRO. O Lean n\u00e3o te impede de jeito nenhum de praticar o 16:8 ou qualquer outro protocolo de janela alimentar, s\u00f3 que o app n\u00e3o gira em torno disso. Em receitas, mais de 3&nbsp;000 entradas criadas internamente com planejamento semanal, \u00e9 um padr\u00e3o que o Yazio domina. Em cobertura EU e localiza\u00e7\u00e3o, o Lean tamb\u00e9m \u00e9 s\u00f3lido (franc\u00eas, ingl\u00eas, espanhol, portugu\u00eas, italiano, alem\u00e3o, polon\u00eas, h\u00fangaro), o Yazio continua mais forte em DE\/AT\/CH e tem 12 anos de vantagem em notoriedade europeia.<\/p>\n  <p>Se seu foco principal \u00e9 o jejum estruturado ou a pedagogia sobre as janelas alimentares, o Yazio \u00e9 mais relevante do que o Lean. Se seu foco \u00e9 a precis\u00e3o do <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/tdee-calculator\/\">c\u00e1lculo do TDEE<\/a>, a gordura corporal medida toda semana, e a adapta\u00e7\u00e3o metab\u00f3lica autom\u00e1tica, \u00e9 exatamente o que acaba de ser demonstrado nas 3 se\u00e7\u00f5es anteriores.<\/p>\n<\/section>\n\n<section aria-labelledby=\"forwho\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">08 &middot; Para quem<\/span><\/div>\n  <h2 id=\"forwho\">Para quem o Lean foi feito<\/h2>\n  <p>4 perfis. Se voc\u00ea se reconhece em pelo menos um, o Lean provavelmente foi feito para voc\u00ea.<\/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>Voc\u00ea usou o Yazio a s\u00e9rio e n\u00e3o perdeu<\/h4>\n        <p>Voc\u00ea aplicou um d\u00e9ficit honesto durante semanas, sem resultado. A causa \u00e9 muito provavelmente o TDEE falseado. O Lean corrige na raiz via o BMR sobre gordura corporal real.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>Voc\u00ea estagna ap\u00f3s v\u00e1rias semanas de cutting<\/h4>\n        <p>Plat\u00f4 que se eterniza ap\u00f3s 4 a 8 semanas. \u00c9 a adapta\u00e7\u00e3o metab\u00f3lica. O Lean a calcula automaticamente e reajusta seu objetivo toda semana.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>Voc\u00ea quer entender seu metabolismo<\/h4>\n        <p>O Lean mostra cada componente (BMR, NEAT, EAT, TEF) e depois explica a adapta\u00e7\u00e3o \u00e0 parte, em vez de esconder tudo atr\u00e1s de um n\u00famero \u00fanico. Voc\u00ea v\u00ea de onde vem cada kcal de gasto.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>Voc\u00ea quer um tracking que dure 12 meses<\/h4>\n        <p>Scan de foto por IA + base curada + c\u00f3digo de barras cobrem todos os usos, do alimento cru \u00e0 pizza no restaurante. \u00c9 o que faz a diferen\u00e7a entre aguentar e desistir.<\/p>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>O Yazio pode bastar para<\/strong>&nbsp;: o jejum intermitente estruturado, as receitas guiadas, ou um acompanhamento simples sem mergulhar na ci\u00eancia do TDEE. O c\u00e1lculo cal\u00f3rico preciso simplesmente n\u00e3o faz parte da promessa dele.<\/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; Migra\u00e7\u00e3o<\/span><\/div>\n  <h2 id=\"migrate\">Migrar do Yazio para o Lean em 3 minutos<\/h2>\n\n  <div class=\"steps\">\n    <div class=\"step\"><div class=\"sn\">01<\/div><h4>Baixe o Lean<\/h4><p>App Store ou Play Store. Cadastro em 30 segundos.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">02<\/div><h4>BodyScan IA<\/h4><p>Uma foto, 5 segundos. Voc\u00ea obt\u00e9m sua gordura corporal.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">03<\/div><h4>Peso &amp; altura<\/h4><p>Voc\u00ea informa seu peso e sua altura. \u00c9 s\u00f3 isso.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">04<\/div><h4>O Lean calcula<\/h4><p>BMR sobre gordura corporal real, NEAT via HealthKit \/ Google Fit (passos reais), EAT por MET, TEF por macros, mais a adapta\u00e7\u00e3o metab\u00f3lica que modula o BMR. Autom\u00e1tico.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">05<\/div><h4>Registre uma refei\u00e7\u00e3o<\/h4><p>Foto, c\u00f3digo de barras ou base de dados. Voc\u00ea entende o fluxo.<\/p><\/div>\n  <\/div>\n\n  <p style=\"margin-top:24px\"><strong>Nota importante.<\/strong> O Lean n\u00e3o importa suas receitas do Yazio automaticamente. Se quiser recuperar seus pratos favoritos, pode recri\u00e1-los como favoritos no Lean manualmente. A sincroniza\u00e7\u00e3o HealthKit \/ Google Health Connect, por sua vez, assume imediatamente seus passos e seu hist\u00f3rico de atividade.<\/p>\n\n  <div class=\"cta-band rev\" style=\"display:flex;align-items:center;justify-content:space-between;gap:20px;flex-wrap:wrap;padding:26px 28px;margin:40px 0;background:#FAF5EE;border:1px solid #E8E2D6;border-radius:16px\">\n    <div class=\"l\" style=\"flex:1;min-width:240px;font-size:18px;line-height:1.4;font-weight:500;color:#0E0E10\">Baixe o Lean e comece o BodyScan IA agora mesmo. Cadastro gratuito.<\/div>\n    <div class=\"stores\" style=\"display:flex;gap:10px;align-items:center;flex-wrap:wrap\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-yazio\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-yazio\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"deblock-h\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">10 &middot; O que o Lean desbloqueia<\/span><\/div>\n  <h2 id=\"deblock-h\">O que o Lean faz, e que o Yazio nunca far\u00e1<\/h2>\n  <p>Seis funcionalidades que n\u00e3o existem em nenhum outro tracker de consumo. Todas derivam do mesmo princ\u00edpio: calcular cada componente do TDEE com precis\u00e3o, n\u00e3o aproxim\u00e1-lo.<\/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\">Sua gordura corporal real, medida a partir de uma simples foto, refeita toda semana. \u00c9 o dado que muda todo o c\u00e1lculo do BMR. Nenhum outro app de consumo oferece isso.<\/p><\/div><div class=\"fc\">Gordura corporal<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">Scan de foto por IA de um prato ilimitado<\/div><p class=\"fd\">Registre sua refei\u00e7\u00e3o no restaurante em 2 segundos. Sem balan\u00e7a, sem entrada manual. O game changer da ader\u00eancia em 12 meses.<\/p><\/div><div class=\"fc\">Ader\u00eancia<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">Adapta\u00e7\u00e3o metab\u00f3lica autom\u00e1tica<\/div><p class=\"fd\">Seu TDEE se reajusta semana a semana segundo os n\u00fameros cientificamente estabelecidos. Voc\u00ea evita os plat\u00f4s que ningu\u00e9m sabe explicar.<\/p><\/div><div class=\"fc\">Adapta\u00e7\u00e3o<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">04<\/div><div><div class=\"ft\">TDEE decomposto ao vivo<\/div><p class=\"fd\">BMR + NEAT + EAT + TEF mostrados cada um, atualizados durante o dia. Chega de n\u00famero congelado \u00e0s 8 da manh\u00e3. Voc\u00ea v\u00ea seu balan\u00e7o cal\u00f3rico ao vivo.<\/p><\/div><div class=\"fc\">Ao vivo<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">05<\/div><div><div class=\"ft\">Hist\u00f3rico completo e tend\u00eancias<\/div><p class=\"fd\">Acompanhe suas tend\u00eancias de peso, gordura corporal, massa magra ao longo de meses. Entenda seus ciclos. Identifique as fases em que voc\u00ea progride e aquelas em que estagna.<\/p><\/div><div class=\"fc\">Hist\u00f3rico<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">06<\/div><div><div class=\"ft\">3 m\u00e9todos de tracking unificados<\/div><p class=\"fd\">Foto, c\u00f3digo de barras, base curada. Nenhum outro app oferece os tr\u00eas com tal precis\u00e3o. Voc\u00ea escolhe o m\u00e9todo segundo o contexto.<\/p><\/div><div class=\"fc\">Tracking<\/div><\/div>\n  <\/div>\n\n  <p style=\"margin-top:26px\">Voc\u00ea instala o app gratuitamente, testa sem compromisso e depois decide se a ferramenta combina com seu 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\">Perguntas frequentes<\/h2>\n  <div class=\"faq\">\n    <details><summary>O Yazio usa Mifflin-St Jeor, \u00e9 moderno, por que voc\u00ea critica?<\/summary><div class=\"ans\">Mifflin-St Jeor (1990) corrige marginalmente Harris-Benedict (1919) mas herda o mesmo defeito conceitual: sem gordura corporal como entrada. Frankenfield 2013 (PubMed 23631843) mede 75&nbsp;% de precis\u00e3o nos obesos contra 87&nbsp;% nos n\u00e3o obesos. Se sua gordura corporal \u00e9 alta, o erro no seu BMR pode ultrapassar 250 a 315&nbsp;kcal por dia.<\/div><\/details>\n    <details><summary>O Yazio \u00e9 muito bem avaliado (4,6) e tem 100&nbsp;M de usu\u00e1rios, como pode ser ruim?<\/summary><div class=\"ans\">O Yazio \u00e9 excelente na experi\u00eancia do usu\u00e1rio, no jejum intermitente e na biblioteca de receitas guiadas. O que questionamos aqui \u00e9 unicamente a precis\u00e3o do c\u00e1lculo do TDEE, que \u00e9 o cora\u00e7\u00e3o da promessa \u00abcalorie tracker\u00bb. Uma grande audi\u00eancia valida a qualidade do produto de consumo, n\u00e3o valida a precis\u00e3o cient\u00edfica da f\u00f3rmula.<\/div><\/details>\n    <details><summary>E o jejum intermitente no Lean?<\/summary><div class=\"ans\">N\u00e3o de forma nativa. O Lean n\u00e3o oferece nem timer 16:8, nem programa guiado de jejum. Se esse \u00e9 seu foco principal, o Yazio \u00e9 mais relevante. O Lean foi projetado para o c\u00e1lculo do TDEE e a recomposi\u00e7\u00e3o corporal, n\u00e3o para estruturar janelas alimentares.<\/div><\/details>\n    <details><summary>O Yazio sincroniza com Apple Health e Google Fit, n\u00e3o basta para o NEAT?<\/summary><div class=\"ans\">O Yazio capta os passos e a atividade via HealthKit \/ Google Fit, mas os usa para a se\u00e7\u00e3o \u00abAtividades\u00bb e a estimativa das calorias queimadas no esporte, n\u00e3o para recalcular seu TDEE continuamente. O PAL escolhido no cadastro (1,2 \/ 1,375 \/ 1,55 \/ 1,725 \/ 1,9) continua sendo a base do c\u00e1lculo. O Lean, ao contr\u00e1rio, recomp\u00f5e seu NEAT com passos reais todo dia.<\/div><\/details>\n    <details><summary>O Lean \u00e9 freemium ou pago?<\/summary><div class=\"ans\">O Lean \u00e9 Premium, com um teste gratuito de 7 dias na assinatura anual. Voc\u00ea baixa, testa o BodyScan IA, o scan de foto por IA de um prato, a recomposi\u00e7\u00e3o do TDEE, sem compromisso. Se a ferramenta combina com seu objetivo, voc\u00ea continua. Sen\u00e3o, desativa a renova\u00e7\u00e3o antes do fim do per\u00edodo de teste.<\/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; Conclus\u00e3o<\/span><\/div>\n  <h2 id=\"conclu\">1990 diante de 2026<\/h2>\n  <p>N\u00e3o \u00e9 Yazio contra Lean em marketing. \u00c9 1990 diante de 2026 em ci\u00eancia.<\/p>\n  <p>O Yazio usa Mifflin-St Jeor, f\u00f3rmula publicada em 1990, mais um n\u00edvel de atividade fixo que voc\u00ea marca uma \u00fanica vez no cadastro (uma das 5 caixas PAL: 1,2 \/ 1,375 \/ 1,55 \/ 1,725 \/ 1,9), e ignora a adapta\u00e7\u00e3o metab\u00f3lica. A combina\u00e7\u00e3o dos tr\u00eas torna qualquer acompanhamento preciso imposs\u00edvel al\u00e9m de algumas semanas. \u00c9 matem\u00e1tico.<\/p>\n  <p>O Lean foi constru\u00eddo para fazer exatamente o inverso: BMR baseado na <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/depense-energetique-totale-v2\/\">gordura corporal real<\/a> (medido por BodyScan IA) via um modelo propriet\u00e1rio patenteado, <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/neat-depense-non-sportive\/\">NEAT por passos reais<\/a>, EAT por esporte e MET, <a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/effet-thermique-des-aliments\/\">TEF por macros<\/a>, mais a adapta\u00e7\u00e3o metab\u00f3lica que modula o BMR semana ap\u00f3s semana. Cada componente calculado com precis\u00e3o, sem coeficiente m\u00e1gico.<\/p>\n  <p>O Yazio continua muito s\u00f3lido em jejum intermitente e biblioteca de receitas. Se voc\u00ea tentou o Yazio a s\u00e9rio e n\u00e3o teve os resultados que esperava no seu cutting, o problema n\u00e3o \u00e9 voc\u00ea. O problema est\u00e1 debaixo do cap\u00f4. Mude de app.<\/p>\n<\/section>\n\n<div class=\"get-band rev\" style=\"background:#F1E9DC;border-radius:24px;padding:48px 36px;margin:60px 0 40px;text-align:center\">\n  <div class=\"kicker\">Download<\/div>\n  <h3>A Lean pode ser baixada gratuitamente<\/h3>\n  <p>iOS e Android. O BodyScan IA funciona com uma simples foto. Sem adip\u00f4metro, sem balan\u00e7a de bioimped\u00e2ncia, sem DEXA.<\/p>\n  <div class=\"stores\" style=\"display:flex;gap:10px;align-items:center;flex-wrap:wrap\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-yazio\" target=\"_blank\" rel=\"noopener\" aria-label=\"Baixar o Lean na App Store\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-yazio\" target=\"_blank\" rel=\"noopener\" aria-label=\"Baixar o Lean no Google Play\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/>\n    <\/a>\n  <\/div>\n<\/div>\n\n<section aria-labelledby=\"links\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">Para ir al\u00e9m<\/span><\/div>\n  <h3 id=\"links\" style=\"margin-top:0\">Links internos<\/h3>\n  <ul>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/tdee-calculator\/\">Calculadora TDEE gratuita online<\/a> &middot; vers\u00e3o web, sem cadastro, mesma l\u00f3gica do app (BMR + NEAT + EAT + TEF).<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/depense-energetique-totale-v2\/\">Entender o TDEE em detalhe (BMR, NEAT, EAT, TEF, adapta\u00e7\u00e3o)<\/a> &middot; artigo cient\u00edfico de fundo.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/comment-compter-ses-calories\/\">Como contar suas calorias corretamente<\/a> &middot; guia pr\u00e1tico para iniciantes.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/neat-depense-non-sportive\/\">NEAT&nbsp;: gasto por passos e atividade fora do esporte<\/a>.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/pt\/effet-thermique-des-aliments\/\">TEF&nbsp;: a digest\u00e3o queima calorias<\/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\">Fontes<\/span><\/div>\n  <h3 id=\"src\" style=\"margin-top:0;color:var(--ink)\">Bibliografia<\/h3>\n  <ol>\n    <li>Harris J.A., Benedict F.G. (1919). A Biometric Study of Basal Metabolism in Man. Carnegie Institution of Washington.<\/li>\n    <li>Mifflin M.D. et al. (1990). A new predictive equation for resting energy expenditure in healthy individuals. American Journal of Clinical Nutrition.<\/li>\n    <li>Shcherbina A. et al. (Stanford University, 2017). Accuracy in Wrist-Worn Wearable Devices for Measuring Heart Rate and Energy Expenditure.<\/li>\n    <li>Westerterp K.R. (2004). Diet induced thermogenesis. Nutrition and Metabolism.<\/li>\n    <li>Rosenbaum M., Leibel R.L. (2010). Adaptive thermogenesis in humans. International Journal of Obesity.<\/li>\n    <li>M\u00fcller M.J., Bosy-Westphal A. (2013). Adaptive thermogenesis with weight loss in humans. Obesity.<\/li>\n  <\/ol>\n<\/section>\n\n<\/main>\n\n<footer>\n  <div class=\"wrap\">\n    <div class=\"row\">\n      <div>\n        <div class=\"kicker\">Lean &middot; lean-app.com<\/div>\n        <p>Artigo publicado em 23 de maio de 2026. Atualizado regularmente com o feedback dos usu\u00e1rios e os novos estudos relevantes. O Lean est\u00e1 dispon\u00edvel para iOS e Android.<\/p>\n      <\/div>\n      <div class=\"stores\" style=\"display:flex;gap:10px;align-items:center;flex-wrap:wrap\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-yazio\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n        <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-yazio\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n      <\/div>\n    <\/div>\n  <\/div>\n<\/footer>\n\n<script data-wpmeteor-nooptimize=\"true\">\n(function(){\n  var bar = document.getElementById('progBar');\n  function up(){\n    var h = document.documentElement;\n    var sc = (h.scrollTop)\/Math.max(1,(h.scrollHeight - h.clientHeight));\n    bar.style.transform = 'scaleX(' + Math.max(0,Math.min(1,sc)) + ')';\n  }\n  document.addEventListener('scroll', up, {passive:true});\n  up();\n})();\n\n(function(){\n  if (!('IntersectionObserver' in window)) {\n    document.querySelectorAll('.rev').forEach(function(n){n.classList.add('on')});\n    return;\n  }\n  var obs = new IntersectionObserver(function(entries){\n    entries.forEach(function(e){\n      if (e.isIntersecting) { e.target.classList.add('on'); obs.unobserve(e.target); }\n    });\n  }, {threshold:0.12});\n  document.querySelectorAll('.rev').forEach(function(n){ obs.observe(n); });\n})();\n\n(function(){\n  var phoneImg = document.getElementById('phoneImg');\n  var phoneBack = document.getElementById('phoneBack');\n  var zones = document.getElementById('phoneZones');\n  var topTabs = document.querySelectorAll('.phone-tabs button');\n  var navTaps = document.querySelectorAll('.phone-navbar button');\n\n  var tabMap = {\n    bilan:    {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp',     drill:false},\n    kcal:     {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp',      drill:false},\n    depense:  {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp',   drill:true},\n    strategie:{src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp', drill:false}\n  };\n  var subMap = {\n    BMR:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp',\n    NEAT: 'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp',\n    EAT:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp',\n    TEF:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp'\n  };\n  var currentTab = 'depense';\n\n  function setActive(tab){\n    topTabs.forEach(function(b){ b.classList.toggle('on', b.dataset.tab===tab); });\n  }\n  function showTab(tab){\n    var t = tabMap[tab]; if(!t) return;\n    currentTab = tab;\n    phoneImg.style.opacity = 0;\n    setTimeout(function(){\n      phoneImg.className = 'phone-bg tab-' + tab;\n      phoneImg.style.opacity = 1;\n      zones.style.display = t.drill ? 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O Lean recomp\u00f5e o seu TDEE continuamente.<\/span><\/a><\/li><\/ul><\/aside>","protected":false},"excerpt":{"rendered":"<p>Lean Calculateur TDEE Accueil &nbsp;\/&nbsp; Lean vs Yazio Comparatif &middot; Nutrition &amp; TDEE Lean face \u00e0 Yazio. Le tracker calorique le plus aim\u00e9 d&rsquo;Europe face au seul qui recompose ton TDEE en continu. Yazio compte. Lean calcule. La diff\u00e9rence se voit apr\u00e8s 6 semaines. L&rsquo;\u00e9quipe Lean &middot; Lecture 12&nbsp;min &middot; Mis \u00e0 jour 21 mai [&hellip;]<\/p>","protected":false},"author":1,"featured_media":1364,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-lvm-blank","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1352","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Lean vs Yazio: quem realmente calcula seu gasto? - Lean<\/title>\n<meta name=\"description\" content=\"O Yazio aplica Mifflin-St Jeor 1990 + 5 caixas PAL est\u00e1ticas. O Lean recalcula BMR + NEAT + EAT + TEF + adapta\u00e7\u00e3o sobre sua gordura corporal real. 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