{"id":1352,"date":"2026-05-23T13:43:16","date_gmt":"2026-05-23T13:43:16","guid":{"rendered":"https:\/\/lean-app.com\/?p=1352"},"modified":"2026-05-24T15:38:37","modified_gmt":"2026-05-24T15:38:37","slug":"lean-vs-yazio","status":"publish","type":"post","link":"https:\/\/lean-app.com\/en\/lean-vs-yazio\/","title":{"rendered":"Lean vs Yazio: who really calculates your calorie expenditure in 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 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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\/en\/\" aria-label=\"Lean home\">\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\/en\/tdee-calculator\/\">TDEE Calculator<\/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=\"Download on the 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=\"Get it on 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\/en\/\">Home<\/a> &nbsp;\/&nbsp; Lean vs Yazio<\/div>\n  <div class=\"eyebrow\">Comparison &middot; Nutrition &amp; TDEE<\/div>\n  <h1 id=\"title\">Lean vs Yazio.\n    <span class=\"alt\">Europe&rsquo;s most-loved calorie tracker vs the only one that recomputes your TDEE continuously.<\/span>\n  <\/h1>\n  <p class=\"dek\">Yazio counts. Lean computes. The difference shows up after 6 weeks.<\/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>The Lean team<\/strong> &middot; 12&nbsp;min read &middot; Updated May 21, 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\">Free download<\/span>\n  <\/div>\n\n  <div class=\"hero-bottom\">\n    <div class=\"hero-lead\">\n      Yazio is massive and excellent on intermittent fasting and 3,000+ guided recipes. But its TDEE formula is still Mifflin-St Jeor 1990, plus a frozen activity level you tick once at signup (one of 5 boxes: sedentary\/low\/moderate\/active\/very active). No bodyfat, no metabolic adaptation. Over 3 months of a serious cut, the gap widens.\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>Interactive demo<\/small>Tap the screen to explore the app<\/span>\n          <svg class=\"th-arrow\" viewbox=\"0 0 24 24\" fill=\"none\" aria-hidden=\"true\">\n            <path d=\"M12 4 L12 20 M5 13 L12 20 L19 13\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/>\n          <\/svg>\n        <\/div>\n        <div class=\"tap-hint desktop\" id=\"tapHintDesktop\" aria-hidden=\"true\">\n          <span class=\"th-pill\"><small>Interactive demo<\/small>Tap the screen<br>to explore the app<\/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=\"Preview of the Lean app with TDEE drill-down\">\n          <div class=\"notch\"><\/div>\n          <div class=\"phone-screen\">\n            <button class=\"phone-back\" id=\"phoneBack\" aria-label=\"Back\">&#8249;<\/button>\n            <div id=\"phoneImg\" class=\"phone-bg tab-depense\" role=\"img\" aria-label=\"Lean preview, Expenditure tab\"><\/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=\"BMR detail\"><\/div>\n              <div class=\"z\" data-sub=\"NEAT\" style=\"top:33%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"NEAT detail\"><\/div>\n              <div class=\"z\" data-sub=\"EAT\"  style=\"top:50%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"EAT detail\"><\/div>\n              <div class=\"z\" data-sub=\"TEF\"  style=\"top:67%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"TEF detail\"><\/div>\n            <\/div>\n            <div class=\"phone-navbar\" id=\"phoneNav\" aria-hidden=\"false\">\n              <button data-tab=\"bilan\"     type=\"button\" aria-label=\"Summary tab\"><\/button>\n              <button data-tab=\"kcal\"      type=\"button\" aria-label=\"Calories tab\"><\/button>\n              <button data-tab=\"depense\"   type=\"button\" aria-label=\"Expenditure tab\"><\/button>\n              <button data-tab=\"strategie\" type=\"button\" aria-label=\"Strategy tab\"><\/button>\n            <\/div>\n          <\/div>\n        <\/div>\n        <div class=\"phone-tabs\" role=\"tablist\" aria-label=\"Navigate the Lean app\">\n          <button data-tab=\"bilan\"     type=\"button\">Overview<\/button>\n          <button data-tab=\"kcal\"      type=\"button\">Calories<\/button>\n          <button data-tab=\"depense\"   type=\"button\" class=\"on\">Expenditure<\/button>\n          <button data-tab=\"strategie\" type=\"button\">Strategy<\/button>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"snippet rev\">\n    <div class=\"lbl\">Quick answer<\/div>\n    <p>Yazio computes your TDEE with Mifflin-St Jeor 1990 (no bodyfat) and a frozen activity level you tick once at signup, among 5 boxes (sedentary, low, moderate, active, very active). The formula is more modern than Harris-Benedict 1919 but inherits the same flaw: no lean mass, no NEAT measured by real steps, no metabolic adaptation. Lean recomputes every component (<span data-term=\"BMR\">BMR<span class=\"tt\">Basal Metabolic Rate. Energy expended at rest. In Lean, calculated on actual lean mass via BodyScan AI.<\/span><\/span> on real bodyfat via a patented proprietary model, <span data-term=\"NEAT\">NEAT<span class=\"tt\">Non-Exercise Activity Thermogenesis. Expenditure from steps and daily activities outside of sport.<\/span><\/span> from steps, <span data-term=\"EAT\">EAT<span class=\"tt\">Exercise Activity Thermogenesis. Expenditure from your sport sessions, calculated via MET.<\/span><\/span> via MET, <span data-term=\"TEF\">TEF<span class=\"tt\">Thermic Effect of Food. Energy spent on digestion. Depends on the macros you eat.<\/span><\/span> from macros) and modulates the BMR via metabolic adaptation continuously, with no coefficient to pick.<\/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; The reality<\/span><\/div>\n  <h2 id=\"constat\">Yazio tracks you for 100 days, until your body adapts<\/h2>\n  <p>If you&rsquo;re reading this, you&rsquo;ve probably already installed Yazio. You entered your weight, height, age, sex. The app asked you to pick your activity level from 5 boxes (sedentary, low, moderate, active, very active). It gave you a calorie goal, say 2,250&nbsp;kcal to lose weight. You followed it religiously. You ran 16:8, you cooked the guided recipes, you scanned your barcodes.<\/p>\n  <p>The first 6 weeks, it works. You lose weight. You&rsquo;re happy. Then around week 8, the scale freezes. You tell yourself: &ldquo;I must have slacked off, I must have miscounted.&rdquo; You tighten the screws. You drop to 2,000&nbsp;kcal. Still nothing moves.<\/p>\n\n  <div class=\"statement\">\n    <div class=\"num\">&minus;10 to &minus;15&nbsp;%<\/div>\n    <div class=\"lbl\">measured TDEE drop after 4 to 6 weeks of a &minus;500&nbsp;kcal\/day deficit. Yazio doesn&rsquo;t detect it. Your calorie goal stays frozen on the choice you made 100&nbsp;days ago.<\/div>\n  <\/div>\n\n  <p>Say Yazio shows you a TDEE of 2,500&nbsp;kcal. You eat 2,250 (theoretical deficit of 250&nbsp;kcal). But in reality, your <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/total-daily-energy-expenditure-tdee\/\">TDEE has dropped to 2,200&nbsp;kcal<\/a> because of metabolic adaptation. You&rsquo;re in a 50&nbsp;kcal surplus without knowing it. Zero chance to keep losing.<\/p>\n  <p>That&rsquo;s why it&rsquo;s critical to <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/comment-compter-ses-calories\/\">compute your expenditure precisely<\/a>, and to recompute it continuously. And that&rsquo;s exactly where Yazio, like most mainstream trackers, stays frozen on the initial estimate.<\/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; Problem 1<\/span><\/div>\n  <h2 id=\"p1\">The 1990 BMR formula, no bodyfat<\/h2>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figure 1 &middot; Man, 5'11\", 265 lb, 30% 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=\"BMR comparison: Mifflin-St Jeor 2500 kcal vs Lean patented proprietary model 2000 kcal, 500 kcal gap\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>Estimated BMR.<\/strong> Lean&rsquo;s patented proprietary model accounts for lean mass. Mifflin-St Jeor (Yazio) does not. A 500&nbsp;kcal gap, equivalent to a full lunch.<\/p>\n  <\/div>\n\n  <p>To compute your basal metabolic rate (the BMR, the energy you burn at rest), Yazio uses the Mifflin-St Jeor equation. It&rsquo;s the canonical formula behind most mainstream calorie trackers, and to be fair: it&rsquo;s better than Harris-Benedict 1919, which other apps still use.<\/p>\n  <p>Mifflin-St Jeor is from 1990. Larger sample (498 subjects), more accurate indirect calorimetry methodology, formula calibrated on a more modern population. Yazio applies the official formula: 10 \u00d7 weight (kg) + 6.25 \u00d7 height (cm) \u2212 5 \u00d7 age \u2212 161 (women) or +5 (men).<\/p>\n  <p>But the update stops there. Mifflin (1990) marginally fixes Harris-Benedict (1919) on average accuracy, but inherits the same conceptual flaw: <strong>the formula only accounts for weight. Not bodyfat. Not lean mass.<\/strong><\/p>\n  <p>Yet since the 1980s, we've known that <strong>fat mass burns very little energy<\/strong> compared to the rest of the body. The liver, brain, heart, kidneys, and especially muscles are the real energy sinks. Fat mass is inert. Someone at 30% bodyfat does not burn anywhere near as much as someone at 10% bodyfat, even at identical weight.<\/p>\n  <p>Frankenfield 2013 (PubMed 23631843) compared Mifflin-St Jeor to reference indirect calorimetry across obese and non-obese cohorts. Result: 87&nbsp;% accuracy in non-obese subjects, and only <strong>75&nbsp;% in obese subjects<\/strong>. A more recent study (PMC11820646) shows that for BMIs above 35, Mifflin is off by <strong>250 to 315&nbsp;kcal per day<\/strong>. That&rsquo;s a full snack&rsquo;s worth of error in your deficit calculation.<\/p>\n\n  <p>500&nbsp;kcal is not nothing. If Yazio tells you &ldquo;your BMR is 2,500&rdquo; when it&rsquo;s actually 2,000, everything downstream is wrong.<\/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\">Real bodyfat<strong>Photo, 5 seconds<\/strong><\/div>\n  <\/div>\n\n  <div class=\"statement\">\n    <div class=\"num\">400 kcal<\/div>\n    <div class=\"lbl\">gap between two men of 80&nbsp;kg, one at 10&nbsp;% bodyfat (BMR 1,900), the other at 30&nbsp;% (BMR 1,500). Yazio gives them the same number.<\/div>\n  <\/div>\n\n  <p>Partial conclusion: if an app computes your BMR using only your weight, height, age and sex, the result cannot be individualized. It&rsquo;s mathematically impossible.<\/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; Problem 2<\/span><\/div>\n  <h2 id=\"p2\">The activity level, picked once and for all<\/h2>\n  <p>This is where it gets serious. And it&rsquo;s probably the point nobody ever explained to you.<\/p>\n  <p>Once Yazio has computed your BMR (no bodyfat), it has to estimate your total TDEE. The <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/total-daily-energy-expenditure-tdee\/\">TDEE is BMR plus everything else<\/a> : expenditure from steps, daily activities, sport, and digestion. Everything that isn't basal metabolism.<\/p>\n  <p>How does Yazio do it? It asks you, just once at signup, to tick one of 5 boxes that&rsquo;s supposed to summarize your entire lifestyle. In sports science, these 5 boxes are called <strong>PAL levels<\/strong> (Physical Activity Level), it&rsquo;s just a multiplier applied to your BMR:<\/p>\n  <ul>\n    <li>Sedentary (PAL 1.2): desk job, little walking<\/li>\n    <li>Low activity (PAL 1.375): occasional walking<\/li>\n    <li>Moderate activity (PAL 1.55): sport 3 to 5 times per week<\/li>\n    <li>Active (PAL 1.725): intense sport almost daily<\/li>\n    <li>Very active (PAL 1.9): very intense sport or physical work<\/li>\n  <\/ul>\n  <p>And based on your pick, it multiplies your BMR by the associated coefficient. That&rsquo;s it. That&rsquo;s the entire engine behind your daily calorie goal. One box that YOU ticked once at signup. Often six months ago. Frozen ever since.<\/p>\n  <p>And here&rsquo;s the silent trap: this approximation is <strong>wildly imperfect<\/strong>. The difference between a day stuck on the couch watching Netflix and a day at Disneyland walking 15&nbsp;km with your kids <strong>over 1,000 kcal<\/strong>. None of the 5 boxes captures that.<\/p>\n  <p>Yazio does sync with Apple Health and Google Health Connect, and captures your steps. But those steps feed the &ldquo;Activities\/Burned&rdquo; section, not the TDEE recomputation. Your daily calorie goal stays based on the PAL box you picked at onboarding.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figure 2 &middot; 7 real days<\/span><span class=\"r\">kcal\/day<\/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=\"Daily variability of calorie expenditure over 7 days, vs 2400 kcal fixed according to Yazio\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>Real expenditure<\/strong> measured over 7&nbsp;days for a Lean user. The grey line is what Yazio showed (2,400&nbsp;kcal flat, moderate PAL \u00d7 BMR). The pink annotations show why each day moves.<\/p>\n  <\/div>\n\n  <p>You can&rsquo;t reduce your activity level to a static box. You might be active in weeks when you barely work from home, and sedentary in weeks when you never leave the office. You might be active in summer and sedentary in winter. You might be active from Tuesday to Friday and sedentary on weekends.<\/p>\n  <p>Which box are you going to pick this week? The truth is that none of the 5 will be correct. So Yazio will give you a TDEE that&rsquo;s systematically disconnected from reality.<\/p>\n  <p>Key point of this article: even if Yazio had a perfect BMR formula (which it doesn&rsquo;t), the static PAL alone would be enough to break everything. You cannot estimate a <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/neat-non-exercise-activity-thermogenesis\/\">NEAT<\/a>, EAT and <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/thermic-effect-of-food-tef\/\">TEF<\/a> with a single multiplier on top of BMR. Conceptually absurd.<\/p>\n  <p>You get the idea: <strong>a BMR formula without bodyfat, plus a static PAL approximation of all other expenditure components, gives you very low odds of hitting your goals over 3 to 6 months.<\/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\">See your real TDEE, broken down into BMR + NEAT + EAT + TEF. Free download.<\/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; Problem 3<\/span><\/div>\n  <h2 id=\"p3\">Metabolic adaptation, never modeled<\/h2>\n  <p>This is the final boss. The most subtle concept. And probably the most important.<\/p>\n  <p>When you&rsquo;re in a calorie deficit, your body realizes it&rsquo;s receiving less energy than before. To protect itself, it switches to power-saving mode. Exactly like your iPhone&rsquo;s low-power mode: everything keeps working, just using less energy. Your BMR drops. Your NEAT drops. Your EAT drops.<\/p>\n  <p>This is called metabolic adaptation. The scientific literature is clear and reproducible: M&uuml;ller 2015 (PubMed 26399868, Minnesota revisit), Doucet 2001 (PubMed 11430776), Nunes 2020 (PMC7484122) over 6 weeks of deficit. Here are the numbers:<\/p>\n  <ul>\n    <li>Deficit of &minus;250&nbsp;kcal per day, over 2 to 8 weeks: adaptation of <strong>5 to 10%<\/strong> (TDEE drops to 90-95&nbsp;% of the initial level)<\/li>\n    <li>Deficit of &minus;500&nbsp;kcal per day: <strong>10 to 15%<\/strong> adaptation (TDEE drops to 85-90&nbsp;%)<\/li>\n    <li>Deficit of &minus;750&nbsp;kcal per day: <strong>15 to 25%<\/strong> adaptation (TDEE drops to 75-85&nbsp;%)<\/li>\n  <\/ul>\n  <p>Lean convention: 100&nbsp;% = optimal, 90&nbsp;% = 10&nbsp;% adaptation. And since NEAT, EAT and TEF all depend directly on the BMR, almost the entire TDEE is impacted.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figure 3 &middot; 8 weeks in deficit<\/span><span class=\"r\">kcal\/day<\/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 dropping from 2500 to 2150 kcal over 8 weeks, vs 2500 fixed according to Yazio\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>real TDEE<\/strong> over 8 weeks of a &minus;500&nbsp;kcal\/day deficit. The pink curve drops. The Yazio line stays flat. By week 6, you&rsquo;re already at maintenance. Without having changed a thing.<\/p>\n  <\/div>\n\n  <p>Concretely: if you planned a 10&nbsp;% deficit on a TDEE of 2,500 (eating 2,250 per day), and your body adapts by 10&nbsp;%, your real TDEE has dropped to 2,250. You&rsquo;re at maintenance. You stop losing.<\/p>\n  <p>The trap is how insidious it is. At first, you lose weight. You&rsquo;re happy. You keep going. But week after week, the adaptation stacks. And at some point, without changing anything in your tracking, <strong>you stop losing<\/strong>.<\/p>\n  <p>95% of people go through this without understanding. They blame their willpower. They blame their \"broken metabolism\". They jump into harsher diets, which makes adaptation worse. Spiral.<\/p>\n  <p>Yazio never computes metabolic adaptation. It gives you a fixed, static goal. When you plateau after 6 weeks, the app has no idea why.<\/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; Lean's solution<\/span><\/div>\n  <h2 id=\"solution\">How Lean fixes each of the 3 problems<\/h2>\n  <p>Lean wasn&rsquo;t built as an improved clone of Yazio. Lean was built as the app we wished existed to track the full TDEE theory seriously: BMR + NEAT + EAT + TEF, plus metabolic adaptation as a 5th brick that modulates the BMR continuously. Here&rsquo;s how Lean handles each component, concretely.<\/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\">Step 1<strong>BodyScan AI<\/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\">Step 2<strong>BMR recalculated<\/strong><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n    <div>\n      <div class=\"m-tag\">BMR on real bodyfat<\/div>\n      <h3>Proprietary patented model, built on lean mass<\/h3>\n      <p>Lean uses a <strong>proprietary patented model<\/strong> which depends directly on lean mass, not raw bodyweight. To do that, the app needs your bodyfat. And here we hit the historically painful problem: how do you measure your bodyfat without paying for a clinic DEXA scan every week?<\/p>\n      <p>Lean&rsquo;s answer: the <strong>BodyScan AI<\/strong>. You take a photo, the app runs it through a model trained on a massive bank of DEXA scans, and you get your estimated bodyfat in seconds. You can redo it every week. The BMR recomputes automatically.<\/p>\n      <p>Goodbye skinfold calipers (imprecise), goodbye bioimpedance scales (unreliable), goodbye DEXA scan (perfect but not accessible weekly). One photo, 5 seconds.<\/p>\n    <\/div>\n  <\/div>\n\n  <div class=\"method flip\">\n    <div>\n      <div class=\"m-tag\">No activity coefficient<\/div>\n      <h3>NEAT, EAT, TEF calculated separately<\/h3>\n      <p><strong>NEAT.<\/strong> Lean pulls your real step count via HealthKit (iOS) or Google Fit (Android). No declaration. No &ldquo;I think I walk enough.&rdquo; Your steps, measured by your smartphone&rsquo;s very precise accelerometers. The <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/neat-non-exercise-activity-thermogenesis\/\">NEAT is computed by crossing those steps with your BMR<\/a>, every day, with no coefficient to pick.<\/p>\n      <p><strong>EAT.<\/strong> For each training session, you pick the sport from a list (strength training, running, tennis, swimming, etc.), and Lean uses the sport&rsquo;s MET (Metabolic Equivalent Task) to compute the real expenditure. You enter the actual time <strong>effective<\/strong> of sport (not the total time with rest periods: the mistake 100&nbsp;% of smartwatches make). A strength session at 1,050&nbsp;kcal according to your Apple Watch? Reality is closer to 200&nbsp;kcal. Lean refuses that drift.<\/p>\n      <p><strong>TEF.<\/strong> Digestion burns energy, and it isn't a flat 10% lump. <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/thermic-effect-of-food-tef\/\">Protein costs 20 to 30%<\/a> of their calories in digestion. Carbs 5 to 10&nbsp;%. Fats 1 to 3&nbsp;%. Lean computes your real TEF from your macros. At 3,000&nbsp;kcal\/day, that can be a 100&nbsp;kcal gap depending on your diet composition.<\/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\">Automatic metabolic adaptation<\/div>\n      <h3>A world first on a consumer app<\/h3>\n      <p>Lean is, to our knowledge, the first app to compute metabolic adaptation automatically. As your weeks in deficit add up, the app adjusts your TDEE downward based on the scientifically established figures (M&uuml;ller 2015, Doucet 2001, Nunes 2020). Convention 100 &rarr; 0&nbsp;%: 100&nbsp;% = optimal, 90&nbsp;% = 10&nbsp;% adaptation. You don&rsquo;t have to do anything. You see your calorie goal readjust gently, with no surprises.<\/p>\n      <p>When you hit 10 to 15&nbsp;% adaptation, the app can recommend a return to maintenance to reset your BMR before going back into deficit. Cycle, plateau, cycle. Just like in serious protocols.<\/p>\n      <p>No activity coefficient to pick. No static PAL box. Just every component computed precisely, week after week.<\/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\">Method<strong>Metabolic adaptation<\/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; Side-by-side<\/span><\/div>\n  <h2 id=\"tab\">Lean vs Yazio, criterion by criterion<\/h2>\n  <p>An honest read of each app's strengths and weaknesses. No criterion touches price.<\/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=\"Lean vs Yazio Comparison\">\n    <div class=\"table-row head\" role=\"row\">\n      <div role=\"columnheader\">Criterion<\/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\">BMR formula<\/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> Proprietary patented model (lean mass)<\/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, no bodyfat<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Uses bodyfat<\/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> Yes<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Bodyfat measured inside the 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 AI via photo<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">NEAT (steps, non-exercise activity)<\/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> Computed from real steps every day<\/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> Bundled into the static PAL<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">EAT (exercise expenditure)<\/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> Per sport via MET, effective time<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Mixed with NEAT under &ldquo;Activities\/Burned&rdquo;<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">TEF (digestion)<\/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> Computed from 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> Not computed<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Metabolic adaptation<\/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> Automatic, week by week<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Activity multiplier to pick<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> No, computed on real data<\/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> Yes, frozen activity level (5 boxes, 1.2 to 1.9)<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">AI photo scan of a meal<\/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> Yes, unlimited<\/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> Yes, available since June 2025<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Barcode scan<\/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> Yes<\/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> Yes<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Food database<\/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, curated<\/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> 4M+ items, strong EU\/DE coverage<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Calorie deficit recommendation<\/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> Adapted to real TDEE<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Fixed estimate<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Intermittent fasting<\/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> Out of scope<\/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 free, PRO programs<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Guided recipes<\/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> Out of scope<\/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> 3,000+ recipes<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">EU coverage and localization<\/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> EU leader, 20 languages, strong DE\/AT\/CH<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Reputation and audience size<\/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, 10,000+ users, young FR app<\/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 users, founded 2014<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Business model<\/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, 7-day free trial on the annual subscription<\/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 on trial<\/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 ways to track a meal<\/h2>\n  <p>Tracking calories is fine. <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/comment-compter-ses-calories\/\">Doing it for 12 months is another story<\/a>. Principle #1, <strong>before science, before macros, before everything<\/strong>is adherence. If the tracking method annoys you, you quit after 3 weeks. Lean offers 3 ways to log a meal:<\/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\">Method 1<strong>Database<\/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\">Method 2<strong>Barcode<\/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\">Method 3<strong>AI photo scan<\/strong><\/div>\n    <\/div>\n  <\/div>\n\n  <ol>\n    <li><strong>Database search.<\/strong> Curated base, USDA + OpenFoodFacts. No community noise, no \"Roast chicken\" entered 47 times by 47 different users with 47 different values.<\/li>\n    <li><strong>Barcode scan.<\/strong> Standard. You scan your pasta box, you get the macros.<\/li>\n    <li><strong>AI photo scan of a meal.<\/strong> You photograph your plate, the AI detects the foods, you get the calories and macros per food.<\/li>\n  <\/ol>\n  <p>The AI photo scan is the adherence game changer. When you eat out, at a restaurant, at friends&rsquo;, it&rsquo;s extremely practical. One photo, you close the app, you enjoy your evening. Yes, it&rsquo;s less accurate than weighing to the gram with a kitchen scale. But over 12 months, that&rsquo;s what makes the difference between sticking with it and giving up. And sticking with it is what counts.<\/p>\n  <p>Beyond meal-by-meal tracking, Lean shows a <strong>live TDEE that updates throughout the day<\/strong>. The more you walk, the more your expenditure rises, the more your daily calorie goal adjusts. You see your calorie balance live. It&rsquo;s more motivating than a number frozen at 8&nbsp;a.m.<\/p>\n  <p>And above all that sits the <strong>Progression Pyramid<\/strong>. It&rsquo;s an app screen that ranks what matters:<\/p>\n\n  <div class=\"pyramid\" aria-label=\"Lean Progression Pyramid\">\n    <div class=\"level l1\"><span>Adherence<\/span><span class=\"k\">Foundation<\/span><\/div>\n    <div class=\"level l2\"><span>Calorie target<\/span><span class=\"k\">Tier 2<\/span><\/div>\n    <div class=\"level l3\"><span>Steps \/ NEAT<\/span><span class=\"k\">Tier 3<\/span><\/div>\n    <div class=\"level l4\"><span>Macronutrients<\/span><span class=\"k\">Peak<\/span><\/div>\n  <\/div>\n  <div class=\"pyramid-cap\">Don&rsquo;t skip steps. If you&rsquo;re not consistent on tracking, optimizing macros to the percent is pointless.<\/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; Honesty<\/span><\/div>\n  <h2 id=\"yazio-better\">What Yazio does better<\/h2>\n  <p>Lean is not perfect, and Yazio has several real strengths worth acknowledging. Honest read, criterion by criterion, on the axes where Yazio still leads.<\/p>\n\n  <div class=\"scorecard rev\" aria-label=\"Scorecard Yazio vs Lean on 4 secondary axes\">\n    <div class=\"scorecard-head\">\n      <div class=\"h-crit\">Axis<\/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\">Built-in intermittent fasting<\/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\">Guided recipes<\/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\">EU coverage and localization<\/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\">Audience size and reviews<\/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>Honest read.<\/strong> On intermittent fasting, Yazio is the mainstream reference: 20 trackers, 16:8 free, guided programs in PRO. Lean does not stop you at all from running 16:8 or any other eating-window protocol, the app simply isn&rsquo;t built around it. On recipes, 3,000+ in-house entries with weekly meal planning, that&rsquo;s a standard where Yazio leads. On EU coverage and localization, Lean is solid too (French, English, Spanish, Portuguese, Italian, German, Polish, Hungarian), but Yazio is still stronger in DE\/AT\/CH and has a 12-year head start in European reputation.<\/p>\n  <p>If your main angle is structured fasting or learning about eating windows, Yazio is more relevant than Lean. If your angle is the precision of the <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/tdee-calculator\/\">TDEE calculation<\/a>, bodyfat measured every week, and automatic metabolic adaptation, that&rsquo;s exactly what was demonstrated in the 3 previous sections.<\/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; Who it's for<\/span><\/div>\n  <h2 id=\"forwho\">Who Lean is built for<\/h2>\n  <p>4 profiles. If you recognise yourself in at least one, Lean is probably built for you.<\/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>You used Yazio seriously and didn&rsquo;t lose weight<\/h4>\n        <p>You ran an honest deficit for weeks, with no result. The cause is very likely a distorted TDEE. Lean fixes it at the root via BMR on real bodyfat.<\/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>You plateau after several weeks of cutting<\/h4>\n        <p>Plateau that drags on after 4 to 8 weeks. That&rsquo;s metabolic adaptation. Lean computes it automatically and readjusts your goal every week.<\/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>You want to understand your metabolism<\/h4>\n        <p>Lean shows each component (BMR, NEAT, EAT, TEF) and explains adaptation separately, instead of hiding everything behind a single number. You see where every kcal of expenditure comes from.<\/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>You want tracking that lasts 12 months<\/h4>\n        <p>AI photo scan + curated database + barcode cover every use case, from raw ingredient to restaurant pizza. That's what makes the difference between sticking with it and giving up.<\/p>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>Yazio may be enough for<\/strong>&nbsp;: structured intermittent fasting, guided recipes, or simple tracking without diving into TDEE science. Precise calorie computation simply isn&rsquo;t part of its promise.<\/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; Migration<\/span><\/div>\n  <h2 id=\"migrate\">Migrate from Yazio to Lean in 3 minutes<\/h2>\n\n  <div class=\"steps\">\n    <div class=\"step\"><div class=\"sn\">01<\/div><h4>Download Lean<\/h4><p>App Store or Play Store. Sign-up in 30 seconds.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">02<\/div><h4>BodyScan AI<\/h4><p>One photo, 5 seconds. You get your bodyfat.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">03<\/div><h4>Weight &amp; height<\/h4><p>You enter your weight and height. That&rsquo;s it.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">04<\/div><h4>Lean computes<\/h4><p>BMR on real bodyfat, NEAT via HealthKit \/ Google Fit (real steps), EAT via MET, TEF via macros, plus metabolic adaptation that modulates the BMR. Automatic.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">05<\/div><h4>Log a meal<\/h4><p>Photo, barcode or database. You get the flow.<\/p><\/div>\n  <\/div>\n\n  <p style=\"margin-top:24px\"><strong>Important note.<\/strong> Lean doesn&rsquo;t auto-import your Yazio recipes. If you want to bring your favorite meals over, you can recreate them as Lean favorites manually. The HealthKit \/ Google Health Connect sync, on the other hand, takes over instantly for your steps and activity history.<\/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\">Download Lean and start the BodyScan AI right now. Free sign-up.<\/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; What Lean unlocks<\/span><\/div>\n  <h2 id=\"deblock-h\">What Lean does, that Yazio never will<\/h2>\n  <p>Six features that exist in no other consumer tracker. They all come from the same principle: compute every TDEE component precisely, not approximate it.<\/p>\n\n  <div class=\"feat-stack\">\n    <div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">Unlimited BodyScan AI<\/div><p class=\"fd\">Your real bodyfat, measured from a single photo, redone every week. The data point that flips the entire BMR calculation. No other consumer app offers this.<\/p><\/div><div class=\"fc\">Bodyfat<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">Unlimited AI photo scan of a meal<\/div><p class=\"fd\">Track your restaurant meal in 2 seconds. No scale, no manual entry. The adherence game-changer over 12 months.<\/p><\/div><div class=\"fc\">Adherence<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">Automatic metabolic adaptation<\/div><p class=\"fd\">Your TDEE re-adjusts week after week following the scientifically established numbers. You avoid the plateaus nobody can explain.<\/p><\/div><div class=\"fc\">Adaptation<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">04<\/div><div><div class=\"ft\">Live TDEE breakdown<\/div><p class=\"fd\">BMR + NEAT + EAT + TEF each shown, updated throughout the day. No more frozen 8am number. You see your calorie balance live.<\/p><\/div><div class=\"fc\">Live<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">05<\/div><div><div class=\"ft\">Full history and trends<\/div><p class=\"fd\">Track weight, bodyfat, lean mass trends over months. Understand your cycles. Spot the phases where you progress and the ones where you stall.<\/p><\/div><div class=\"fc\">History<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">06<\/div><div><div class=\"ft\">3 unified tracking methods<\/div><p class=\"fd\">Photo, barcode, curated database. No other app offers all three with this level of precision. You pick the method based on context.<\/p><\/div><div class=\"fc\">Tracking<\/div><\/div>\n  <\/div>\n\n  <p style=\"margin-top:26px\">You install the app for free, you try it without commitment, then you decide if the tool fits your goal.<\/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\">Frequently asked questions<\/h2>\n  <div class=\"faq\">\n    <details><summary>Yazio uses Mifflin-St Jeor, that&rsquo;s modern, why criticize?<\/summary><div class=\"ans\">Mifflin-St Jeor (1990) marginally fixes Harris-Benedict (1919) but inherits the same conceptual flaw: no bodyfat as input. Frankenfield 2013 (PubMed 23631843) measures 75&nbsp;% accuracy in obese subjects vs 87&nbsp;% in non-obese. If your bodyfat is high, the BMR error can exceed 250 to 315&nbsp;kcal per day.<\/div><\/details>\n    <details><summary>Yazio is highly rated (4.6) and has 100&nbsp;M users, how can it be bad?<\/summary><div class=\"ans\">Yazio is excellent on user experience, intermittent fasting and the guided recipe library. What we question here is only the precision of the TDEE calculation, which is the core of the &ldquo;calorie tracker&rdquo; promise. A massive audience validates mainstream product quality, it does not validate the scientific precision of the formula.<\/div><\/details>\n    <details><summary>What about intermittent fasting in Lean?<\/summary><div class=\"ans\">Not natively. Lean offers neither a 16:8 timer nor a guided fasting program. If that&rsquo;s your main angle, Yazio is more relevant. Lean is designed for TDEE computation and body recomposition, not for structuring eating windows.<\/div><\/details>\n    <details><summary>Yazio syncs with Apple Health and Google Fit, isn&rsquo;t that enough for NEAT?<\/summary><div class=\"ans\">Yazio captures steps and activity via HealthKit \/ Google Fit, but uses them for the &ldquo;Activities&rdquo; section and to estimate sport-burned calories, not to recompute your TDEE continuously. The PAL picked at signup (1.2 \/ 1.375 \/ 1.55 \/ 1.725 \/ 1.9) remains the basis of the calculation. Lean, conversely, recomposes your NEAT from real steps every day.<\/div><\/details>\n    <details><summary>Is Lean free or paid?<\/summary><div class=\"ans\">Lean is Premium, with a 7-day free trial on the annual subscription. You download, you test BodyScan AI, AI photo meal scan, TDEE recomposition, no commitment. If the tool fits your goal, you keep going. Otherwise, you cancel renewal before the trial ends.<\/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; Conclusion<\/span><\/div>\n  <h2 id=\"conclu\">1990 vs 2026<\/h2>\n  <p>This isn&rsquo;t Yazio vs Lean in marketing. This is 1990 vs 2026 in science.<\/p>\n  <p>Yazio uses Mifflin-St Jeor, published in 1990, plus a frozen activity level you tick once at signup (one of 5 PAL boxes: 1.2 \/ 1.375 \/ 1.55 \/ 1.725 \/ 1.9), and ignores metabolic adaptation. The combination of the three makes any precise tracking impossible beyond a few weeks. It&rsquo;s mathematical.<\/p>\n  <p>Lean was built to do the exact opposite: BMR based on <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/total-daily-energy-expenditure-tdee\/\">real bodyfat<\/a> (measured by BodyScan AI) via a proprietary patented model, <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/neat-non-exercise-activity-thermogenesis\/\">NEAT from real steps<\/a>, EAT per sport via MET, <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/thermic-effect-of-food-tef\/\">TEF from macros<\/a>, plus metabolic adaptation that modulates the BMR week after week. Every component computed precisely, with no magic coefficient.<\/p>\n  <p>Yazio is still very solid on intermittent fasting and the recipe library. If you tried Yazio seriously and didn&rsquo;t get the results you hoped for on your cut, the problem isn&rsquo;t you. The problem is under the hood. Switch apps.<\/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>Lean is available as a free download<\/h3>\n  <p>iOS and Android. The BodyScan AI works from a single photo. No skinfold calliper, no bioimpedance scale, no 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=\"Download Lean on the 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=\"Download Lean on 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\">Further reading<\/span><\/div>\n  <h3 id=\"links\" style=\"margin-top:0\">Internal links<\/h3>\n  <ul>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/tdee-calculator\/\">Free online TDEE calculator<\/a> &middot; web version, no sign-up, same logic as the app (BMR + NEAT + EAT + TEF).<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/total-daily-energy-expenditure-tdee\/\">Understand TDEE in depth (BMR, NEAT, EAT, TEF, adaptation)<\/a> &middot; deep-science article.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/comment-compter-ses-calories\/\">How to count your calories properly<\/a> &middot; practical guide for beginners.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/neat-non-exercise-activity-thermogenesis\/\">NEAT: expenditure from steps and non-exercise activity<\/a>.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/thermic-effect-of-food-tef\/\">TEF: digestion burns calories<\/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\">Sources<\/span><\/div>\n  <h3 id=\"src\" style=\"margin-top:0;color:var(--ink)\">Bibliography<\/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>Article published on May 23, 2026. Updated regularly with user feedback and relevant new studies. Lean is available on iOS and 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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Lean sees your real expenditure.<\/span><\/a><\/li><li><a href=\"\/en\/lean-vs-lifesum\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean vs Lifesum: premium diet coaching versus TDEE precision <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Lifesum sells dietary wrapping. Lean rebuilds your TDEE continuously.<\/span><\/a><\/li><li><a href=\"\/en\/lean-vs-fatsecret\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean vs FatSecret: Premium precision versus the free community-driven database <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">FatSecret is free. Lean is precise. The hidden cost of free, explained.<\/span><\/a><\/li><li><a href=\"\/en\/lean-vs-noom\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean vs Noom: psychological coaching versus metabolic precision <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Noom changes your habits. Lean measures your expenditure. Coaching doesn't replace measurement.<\/span><\/a><\/li><li><a href=\"\/en\/alternative-myfitnesspal\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Alternative to MyFitnessPal: the 5 real options in 2026 <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Honest comparison: Lean, Yazio, Cronometer, Lifesum, FatSecret.<\/span><\/a><\/li><\/ul><\/aside>","protected":false},"excerpt":{"rendered":"<p>Lean TDEE Calculator Home &nbsp;\/&nbsp; Lean vs Yazio Comparison &middot; Nutrition &amp; TDEE Lean vs Yazio. Europe's most loved calorie tracker vs the only one that recomputes your TDEE continuously. Yazio counts. Lean calculates. The difference shows after 6 weeks. The Lean team &middot; 12&nbsp;min read &middot; Updated May 21 [&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: why Yazio gets your TDEE wrong (2026)<\/title>\n<meta name=\"description\" content=\"Yazio uses Mifflin-St Jeor 1990 + 5 static PAL buckets. 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