{"id":1424,"date":"2026-05-24T15:29:25","date_gmt":"2026-05-24T15:29:25","guid":{"rendered":"https:\/\/lean-app.com\/?p=1424"},"modified":"2026-08-22T18:01:49","modified_gmt":"2026-08-22T18:01:49","slug":"lean-vs-fatsecret","status":"publish","type":"post","link":"https:\/\/lean-app.com\/en\/lean-vs-fatsecret\/","title":{"rendered":"Lean face \u00e0 FatSecret : pr\u00e9cision premium face au tracker gratuit"},"content":{"rendered":"<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp\" 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18px;border-radius:14px;color:#fff;font-family:var(--font-display);font-weight:500;font-size:15px;letter-spacing:-.01em;display:flex;justify-content:space-between;align-items:center;box-shadow:0 6px 18px rgba(0,0,0,.06)}\n#lvm-shell .pyramid .level .k{font-family:var(--font-mono);font-size:10px;text-transform:uppercase;letter-spacing:.08em;opacity:.75}\n#lvm-shell .pyramid .l1{background:#0E0E10;width:100%}\n#lvm-shell .pyramid .l2{background:#1D1D1F;width:84%}\n#lvm-shell .pyramid .l3{background:#3a3a3c;width:68%}\n#lvm-shell .pyramid .l4{background:var(--pink);width:52%}\n#lvm-shell .pyramid-cap{text-align:center;font-size:13px;color:var(--muted);margin-top:14px}\n\n\/* Section 7 honnetete : scorecard horizontal bars *\/\n#lvm-shell .scorecard{margin:30px 0 10px;border:1px solid var(--rule);border-radius:20px;padding:28px 26px;background:#fff}\n#lvm-shell .scorecard-head{display:grid;grid-template-columns:1.4fr 1fr 1fr;column-gap:28px;align-items:center;padding-bottom:18px;margin-bottom:8px;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell .scorecard-head .h-crit{font-family:var(--font-mono);font-size:11px;font-weight:500;text-transform:uppercase;letter-spacing:.08em;color:var(--muted)}\n#lvm-shell .scorecard-head .h-brand{display:flex;align-items:center;gap:8px;font-family:var(--font-display);font-size:14px;font-weight:600;color:var(--ink)}\n#lvm-shell .scorecard-head .h-brand img{width:22px;height:22px;border-radius:5px;object-fit:cover}\n#lvm-shell .scorecard-row{display:grid;grid-template-columns:1.4fr 1fr 1fr;column-gap:28px;align-items:center;padding:14px 0;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell .scorecard-row:last-child{border-bottom:0}\n#lvm-shell .scorecard-row .crit{font-size:14px;color:var(--ink);font-weight:500;padding-right:14px}\n#lvm-shell .scorecard-row .bar{display:flex;flex-direction:row-reverse;align-items:center;gap:10px}\n#lvm-shell .scorecard-row .bar .b{flex:1;height:8px;border-radius:99px;background:var(--rule-soft);overflow:hidden;position:relative}\n#lvm-shell .scorecard-row .bar .b > i{display:block;height:100%;border-radius:99px;transition:width 1s cubic-bezier(.22,.61,.36,1)}\n#lvm-shell .scorecard-row .bar.lean .b > i{background:var(--pink)}\n#lvm-shell .scorecard-row .bar.mfp .b > i{background:var(--mfp)}\n#lvm-shell .scorecard-row .bar .v{font-family:var(--font-mono);font-size:12px;font-weight:600;color:var(--ink);min-width:32px;text-align:left}\n\n\/* Section 8 pour qui : persona checklist *\/\n#lvm-shell .persona{margin:28px 0 10px;display:grid;grid-template-columns:1fr;gap:14px}\n#lvm-shell .persona-it{display:grid;grid-template-columns:54px 1fr;gap:16px;padding:22px 24px;background:#fff;border:1px solid var(--rule);border-radius:18px;align-items:center}\n#lvm-shell .persona-it.match{background:var(--pink-soft);border-color:rgba(255,45,110,.25)}\n#lvm-shell .persona-it .pic{width:54px;height:54px;border-radius:50%;display:flex;align-items:center;justify-content:center;background:var(--rule-soft);position:relative;font-family:var(--font-mono);font-size:13px;font-weight:600;color:var(--ink)}\n#lvm-shell .persona-it.match .pic{background:var(--pink);color:#fff}\n#lvm-shell .persona-it .pic svg{width:24px;height:24px}\n#lvm-shell .persona-it h4{margin:0 0 4px;font-size:17px;letter-spacing:-.01em}\n#lvm-shell .persona-it p{margin:0;font-size:14px;color:var(--muted);line-height:1.55}\n#lvm-shell .persona-it.match h4{color:var(--ink)}\n\n\/* Section 9 migration : timeline steps *\/\n#lvm-shell .steps{display:grid;grid-template-columns:repeat(5,1fr);gap:14px;margin:28px 0;position:relative}\n#lvm-shell .steps::before{content:\"\";position:absolute;top:14px;left:7px;right:calc(20% - 18px);height:1px;background:linear-gradient(90deg,var(--pink) 0%,var(--rule-soft) 100%);z-index:0}\n#lvm-shell .step{position:relative;padding-top:24px;z-index:1}\n#lvm-shell .step::before{content:\"\";position:absolute;top:8px;left:0;width:14px;height:14px;border-radius:50%;background:var(--pink);border:3px solid #fff;box-shadow:0 0 0 1px var(--rule)}\n#lvm-shell .step .sn{font-family:var(--font-mono);font-size:11px;color:var(--pink);font-weight:600;letter-spacing:.08em}\n#lvm-shell .step h4{margin:6px 0 6px;font-size:15px;letter-spacing:-.01em}\n#lvm-shell .step p{font-size:13px;color:var(--muted);line-height:1.5;margin:0}\n\n\/* Section 10 debloque : feature stack numbered XL *\/\n#lvm-shell .feat-stack{margin:30px 0 10px;border-top:1px solid var(--rule)}\n#lvm-shell .feat-it{display:grid;grid-template-columns:auto 1fr auto;gap:24px;padding:26px 0;border-bottom:1px solid var(--rule);align-items:center}\n#lvm-shell .feat-it .fn{font-family:var(--font-display);font-size:48px;font-weight:600;color:var(--pink);line-height:1;letter-spacing:-.04em;width:74px}\n#lvm-shell .feat-it .ft{font-family:var(--font-display);font-size:22px;font-weight:600;color:var(--ink);letter-spacing:-.015em;line-height:1.25;margin-bottom:6px}\n#lvm-shell .feat-it .fd{font-size:15px;color:var(--muted);line-height:1.55;margin:0}\n#lvm-shell .feat-it .fc{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.08em;color:var(--muted);font-weight:500}\n#lvm-shell .feat-it:last-child{border-bottom:0}\n\n#lvm-shell .faq{margin:22px 0}\n#lvm-shell .faq details{border-bottom:1px solid var(--rule);padding:20px 0}\n#lvm-shell .faq details:first-of-type{border-top:1px solid var(--rule)}\n#lvm-shell .faq summary{cursor:pointer;list-style:none;display:flex;justify-content:space-between;align-items:center;gap:18px;font-family:var(--font-display);font-size:20px;font-weight:500;letter-spacing:-.015em;color:var(--ink)}\n#lvm-shell .faq summary::-webkit-details-marker{display:none}\n#lvm-shell .faq summary::after{content:\"+\";font-size:24px;color:var(--muted);font-weight:300;line-height:1;transition:transform .25s, color .25s}\n#lvm-shell .faq details[open] summary::after{transform:rotate(45deg);color:var(--pink)}\n#lvm-shell .faq details[open] summary{color:var(--pink)}\n#lvm-shell .faq .ans{margin-top:14px;font-size:16px;color:var(--muted);line-height:1.65}\n\n#lvm-shell .get-band{background:var(--paper-2);border-radius:24px;padding:48px 36px;margin:60px 0 40px;text-align:center}\n#lvm-shell .get-band .kicker{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;color:var(--pink);font-weight:600;letter-spacing:.1em;margin-bottom:14px}\n#lvm-shell .get-band h3{font-size:36px;margin:0 0 14px;letter-spacing:-.025em}\n#lvm-shell .get-band p{font-size:16px;color:var(--muted);max-width:480px;margin:0 auto 26px}\n#lvm-shell .get-band .stores{display:flex;justify-content:center;gap:14px;flex-wrap:wrap}\n#lvm-shell .get-band .stores a{line-height:0;transition:transform .15s}\n#lvm-shell .get-band .stores a:hover{transform:translateY(-3px)}\n#lvm-shell .get-band .stores img{height:60px;width:auto;border-radius:11px}\n\n#lvm-shell .sources{font-size:14px;color:var(--muted);line-height:1.7}\n#lvm-shell .sources ol{padding-left:22px}\n#lvm-shell .sources li{margin-bottom:8px}\n\n#lvm-shell footer{padding:50px 0 60px;border-top:1px solid var(--rule);margin-top:40px}\n#lvm-shell footer .row{display:flex;justify-content:space-between;align-items:center;gap:18px;flex-wrap:wrap}\n#lvm-shell footer .kicker{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.08em;color:var(--pink);font-weight:600}\n#lvm-shell footer p{font-size:13px;color:var(--muted);margin:8px 0 0}\n#lvm-shell footer .stores{display:flex;gap:8px}\n#lvm-shell footer .stores img{height:34px;width:auto;border-radius:6px}\n\n#lvm-shell .rev{opacity:0;transform:translateY(12px);transition:opacity .8s cubic-bezier(.22,.61,.36,1),transform .8s cubic-bezier(.22,.61,.36,1)}\n#lvm-shell .rev.on{opacity:1;transform:translateY(0)}\n@media (prefers-reduced-motion:reduce){#lvm-shell .rev{transition:none;opacity:1;transform:none}}\n\n@media (max-width:760px){\n  #lvm-shell .nav-row{padding:8px 18px;gap:8px}\n  #lvm-shell .nav-link{display:none}\n  #lvm-shell .nav-stores img{height:24px}\n  #lvm-shell .wrap{padding:0 22px}\n  #lvm-shell .hero{padding:34px 0 0}\n  #lvm-shell h1{font-size:46px;letter-spacing:-.035em}\n  #lvm-shell h1 .alt{font-size:.55em;margin-top:10px}\n  #lvm-shell .dek{font-size:20px}\n  #lvm-shell .hero-stores img{height:42px}\n  #lvm-shell .hero-bottom{grid-template-columns:1fr;gap:28px;margin:30px 0 40px;padding-top:24px;align-items:stretch}\n  #lvm-shell .phone-wrap{order:-1}\n  #lvm-shell .phone{width:240px}\n  #lvm-shell .tap-hint.desktop{display:none}\n  #lvm-shell .tap-hint.mobile{display:block;position:relative;left:auto;top:auto;text-align:center;margin:0 auto 10px;width:100%}\n  #lvm-shell .tap-hint.mobile .th-arrow{position:relative;display:block;margin:6px auto 0;width:34px;height:34px;transform:none;color:var(--pink)}\n  #lvm-shell .snippet{padding:24px 22px}\n  #lvm-shell .snippet p{font-size:18px}\n  #lvm-shell section{padding:48px 0}\n  #lvm-shell h2{font-size:34px;letter-spacing:-.03em}\n  #lvm-shell h3{font-size:24px}\n  #lvm-shell .section-label{margin-bottom:22px}\n  #lvm-shell .statement{padding:24px 0;margin:32px 0}\n  #lvm-shell .statement .num{font-size:44px}\n  #lvm-shell .statement .lbl{font-size:19px}\n  #lvm-shell .fig{padding:20px 14px 14px;border-radius:16px}\n  #lvm-shell .cv-wrap{height:310px}\n  #lvm-shell .method{grid-template-columns:1fr;gap:20px}\n  #lvm-shell .method.flip{grid-template-columns:1fr}\n  #lvm-shell .method.flip .m-phone{order:0}\n  #lvm-shell .mini-row{grid-template-columns:repeat(3,1fr);gap:10px}\n  #lvm-shell .mini-phone{padding:3px;border-radius:18px;border-width:1px;max-width:110px}\n  #lvm-shell .mini-phone .notch{width:42px;height:11px;border-radius:0 0 8px 8px}\n  #lvm-shell .mini-phone .scr{border-radius:15px}\n  #lvm-shell .mini-cap{font-size:10px}\n  #lvm-shell .mini-cap strong{font-size:13px}\n  #lvm-shell .duo-row{grid-template-columns:repeat(2,1fr);gap:12px}\n  #lvm-shell .duo-row .mini-phone{max-width:130px}\n  #lvm-shell .steps{grid-template-columns:1fr;gap:18px}\n  #lvm-shell .steps::before{display:none}\n  #lvm-shell .step{padding-top:0;padding-left:24px}\n  #lvm-shell .step::before{top:6px;left:0}\n  #lvm-shell .table-row{grid-template-columns:1.4fr .9fr .9fr}\n  #lvm-shell .table-row > .crit{padding:13px 12px;font-size:13px}\n  #lvm-shell .table-row > .cell{padding:13px 10px;font-size:12px;gap:8px}\n  #lvm-shell .table-row.head > div{padding:14px 12px;font-size:10px;gap:7px}\n  #lvm-shell .table-row.head .brand-cell img{width:20px;height:20px}\n  #lvm-shell .get-band{padding:36px 22px;border-radius:18px;margin:40px 0 30px}\n  #lvm-shell .get-band h3{font-size:28px}\n  #lvm-shell .get-band .stores img{height:50px}\n  #lvm-shell .cta-band{padding:22px;gap:14px}\n  #lvm-shell .cta-band .l{font-size:16px;min-width:0}\n  #lvm-shell .cta-band .stores img{height:38px}\n  #lvm-shell .faq summary{font-size:18px;gap:14px}\n  #lvm-shell .pyramid{max-width:100%}\n  #lvm-shell .pyramid .level{padding:11px 14px;font-size:14px}\n  #lvm-shell .scorecard{padding:20px 16px;border-radius:16px}\n  #lvm-shell .scorecard-head{grid-template-columns:1.2fr 1fr 1fr;column-gap:14px}\n  #lvm-shell .scorecard-head .h-brand{font-size:12px;gap:5px}\n  #lvm-shell .scorecard-head .h-brand img{width:18px;height:18px}\n  #lvm-shell .scorecard-row{grid-template-columns:1.2fr 1fr 1fr;column-gap:14px;padding:12px 0}\n  #lvm-shell .scorecard-row .crit{font-size:13px;padding-right:8px}\n  #lvm-shell .scorecard-row .bar{gap:6px}\n  #lvm-shell .scorecard-row .bar .v{font-size:11px;min-width:26px}\n  #lvm-shell .persona-it{grid-template-columns:44px 1fr;gap:12px;padding:16px 16px;border-radius:14px}\n  #lvm-shell .persona-it .pic{width:44px;height:44px;font-size:12px}\n  #lvm-shell .persona-it h4{font-size:15px}\n  #lvm-shell .persona-it p{font-size:13px}\n  #lvm-shell .feat-it{grid-template-columns:auto 1fr;gap:14px;padding:20px 0}\n  #lvm-shell .feat-it .fn{font-size:36px;width:54px}\n  #lvm-shell .feat-it .ft{font-size:18px}\n  #lvm-shell .feat-it .fd{font-size:13px}\n  #lvm-shell .feat-it .fc{display:none}\n}\n@media (max-width:480px){\n  #lvm-shell .phone-tabs{gap:5px}\n  #lvm-shell .phone-tabs button{padding:5px 8px;font-size:10px}\n  #lvm-shell .nav-stores{gap:4px}\n  #lvm-shell .nav-stores img{height:22px}\n  #lvm-shell .hero-stores img{height:40px}\n  #lvm-shell .crumb{font-size:12px}\n  #lvm-shell .table-row{grid-template-columns:1.3fr .85fr .85fr}\n  #lvm-shell .table-row > .crit{padding:11px 9px;font-size:12px}\n  #lvm-shell .table-row > .cell{padding:11px 8px;font-size:11px;gap:6px}\n  #lvm-shell .table-row.head > div{padding:11px 9px;font-size:9px;gap:5px}\n}<\/style>\n\n<style id=\"lvm-collision-reset\">\n\/* Hard reset for global theme styles that collide with our content *\/\nbody.postid-1424 #lvm-shell .hero{display:block!important;align-items:initial!important;justify-content:initial!important;text-align:left!important;flex-direction:initial!important;padding:54px 0 0!important}\nbody.postid-1424 #lvm-shell .wrap,\nbody.postid-1424 #lvm-shell main.wrap{display:block!important;max-width:760px!important;margin-left:auto!important;margin-right:auto!important;padding-left:28px!important;padding-right:28px!important}\n@media (max-width:820px){\n  body.postid-1424 #lvm-shell .wrap,\n  body.postid-1424 #lvm-shell main.wrap{padding-left:18px!important;padding-right:18px!important}\n}\nhtml, body{overflow-x:hidden!important}\nbody.postid-1424 #lvm-shell{overflow-x:hidden;max-width:100vw}\nbody.postid-1424 #lvm-shell *{max-width:100%}\nbody.postid-1424 #lvm-shell .nav-row{max-width:100vw;box-sizing:border-box}\nbody.postid-1424 #lvm-shell.force-show .rev{opacity:1!important;transform:none!important}\n\n\/* === A.1 PHONE BACKGROUND CLASSES === *\/\nbody.postid-1424 #lvm-shell .phone-bg{position:absolute;inset:0;width:100%;height:100%;background-size:cover;background-position:center top;background-repeat:no-repeat;transition:opacity .28s ease;background-color:#FAF0E6}\nbody.postid-1424 #lvm-shell .phone-bg.tab-depense{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp)}\nbody.postid-1424 #lvm-shell .phone-bg.tab-bilan{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp)}\nbody.postid-1424 #lvm-shell .phone-bg.tab-kcal{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp)}\nbody.postid-1424 #lvm-shell .phone-bg.tab-strategie{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp)}\nbody.postid-1424 #lvm-shell .phone-bg.sub-BMR{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp)}\nbody.postid-1424 #lvm-shell .phone-bg.sub-NEAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp)}\nbody.postid-1424 #lvm-shell .phone-bg.sub-EAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp)}\nbody.postid-1424 #lvm-shell .phone-bg.sub-TEF{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp)}\n\n\/* === v11.3 CTA BANDS MOBILE (badges plus gros + centrage) === *\/\n@media (max-width:760px){\n  body.postid-1424 #lvm-shell .cta-band{flex-direction:column!important;align-items:center!important;text-align:center!important;padding:26px 22px!important;gap:20px!important}\n  body.postid-1424 #lvm-shell .cta-band .l{min-width:0!important;width:100%!important;font-size:16px!important;line-height:1.5!important;text-align:center!important}\n  body.postid-1424 #lvm-shell .cta-band .stores{width:100%!important;justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1424 #lvm-shell .cta-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1424 #lvm-shell .cta-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1424 #lvm-shell .cta-band .stores img{height:56px!important;width:100%!important;max-width:170px!important;object-fit:contain!important;object-position:center!important;border-radius:10px!important}\n  body.postid-1424 #lvm-shell .get-band{padding:38px 22px!important}\n  body.postid-1424 #lvm-shell .get-band .stores{justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1424 #lvm-shell .get-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1424 #lvm-shell .get-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1424 #lvm-shell .get-band .stores img{height:56px!important;width:100%!important;max-width:170px!important;object-fit:contain!important;object-position:center!important;border-radius:10px!important}\n  body.postid-1424 #lvm-shell .get-band h3{font-size:26px!important;line-height:1.2!important}\n  body.postid-1424 #lvm-shell .get-band p{font-size:15px!important}\n}\n\n\/* === v11.2 BRAND BANNER above table responsive === *\/\n@media (max-width:760px){\n  body.postid-1424 #lvm-shell .brand-banner img{width:54px!important;height:54px!important}\n  body.postid-1424 #lvm-shell .brand-banner > div{padding:16px 12px!important;gap:8px!important}\n  body.postid-1424 #lvm-shell .brand-banner > div > div{font-size:15px!important}\n}\n\n\/* === v11.4 SCORECARD partie 7: redesign mobile === *\/\n@media (max-width:760px){\n  body.postid-1424 #lvm-shell .scorecard{padding:18px 16px!important;border-radius:16px!important}\n  body.postid-1424 #lvm-shell .scorecard-head{display:none!important}\n  body.postid-1424 #lvm-shell .scorecard-row{\n    display:block!important;\n    padding:14px 0!important;\n    border-bottom:1px solid #E8E2D6!important;\n  }\n  body.postid-1424 #lvm-shell .scorecard-row .crit{\n    display:block!important;\n    font-size:13px!important;\n    font-weight:600!important;\n    color:#0E0E10!important;\n    margin-bottom:10px!important;\n    padding-right:0!important;\n  }\n  body.postid-1424 #lvm-shell .scorecard-row .bar{\n    display:grid!important;\n    grid-template-columns:54px 1fr 32px!important;\n    column-gap:8px!important;\n    align-items:center!important;\n    padding:5px 0!important;\n    flex-direction:initial!important;\n    position:relative!important;\n  }\n  body.postid-1424 #lvm-shell .scorecard-row .bar::before{\n    content:attr(data-brand)!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:11px!important;\n    font-weight:600!important;\n    text-transform:uppercase!important;\n    letter-spacing:.05em!important;\n    color:#0E0E10!important;\n  }\n  body.postid-1424 #lvm-shell .scorecard-row .bar.lean::before{color:#FF2D6E!important}\n  body.postid-1424 #lvm-shell .scorecard-row .bar.mfp::before{color:#5B7FFF!important}\n  body.postid-1424 #lvm-shell .scorecard-row .bar .b{\n    height:10px!important;\n    width:100%!important;\n    border-radius:99px!important;\n    position:relative!important;\n    background:#EFEAE0!important;\n    overflow:hidden!important;\n  }\n  body.postid-1424 #lvm-shell .scorecard-row .bar .b > i{\n    display:block!important;\n    height:100%!important;\n    border-radius:99px!important;\n  }\n  body.postid-1424 #lvm-shell .scorecard-row .bar .v{\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:12px!important;\n    font-weight:700!important;\n    color:#0E0E10!important;\n    min-width:0!important;\n    text-align:right!important;\n  }\n}\n\n\/* === A.2 CHARTS MOBILE === *\/\n@media (max-width:760px){\n  \/* v13: charts FULL WIDTH (less card padding) + plus hauts pour vraie respiration *\/\n  body.postid-1424 #lvm-shell .cv-wrap{height:380px!important;min-height:360px!important;max-height:420px!important;width:100%!important}\n  body.postid-1424 #lvm-shell .cv-wrap canvas{width:100%!important;height:100%!important;display:block!important}\n  body.postid-1424 #lvm-shell .fig{padding:16px 4px 14px!important;margin:24px -4px 14px!important;overflow:visible!important}\n  body.postid-1424 #lvm-shell .fig-head{padding:0 12px!important;flex-wrap:wrap!important;gap:6px!important;margin-bottom:10px!important}\n  body.postid-1424 #lvm-shell .fig-body{padding:0 2px!important}\n  body.postid-1424 #lvm-shell .fig-cap{padding:0 12px!important;font-size:13px!important;margin-top:10px!important}\n}\n@media (max-width:480px){\n  body.postid-1424 #lvm-shell .cv-wrap{height:360px!important;min-height:340px!important;max-height:380px!important}\n  body.postid-1424 #lvm-shell .fig{padding:14px 2px 12px!important;margin:20px -6px 12px!important;border-radius:14px!important}\n  body.postid-1424 #lvm-shell .fig-body{padding:0!important}\n}\n\n\/* === v11.2 TABLEAU MOBILE STACKED CARDS avec mini-tags Lean\/MFP === *\/\n@media (max-width:760px){\n  body.postid-1424 #lvm-shell .table{border-radius:14px!important}\n  body.postid-1424 #lvm-shell .table-row.head{display:none!important}\n  body.postid-1424 #lvm-shell .table-row{\n    display:grid!important;\n    grid-template-columns:1fr 1fr!important;\n    grid-template-areas:\"crit crit\" \"lean mfp\"!important;\n    gap:0!important;\n    min-height:0!important;\n  }\n  body.postid-1424 #lvm-shell .table-row > .crit{\n    grid-area:crit!important;background:#0E0E10!important;color:#fff!important;\n    padding:11px 14px!important;font-size:13px!important;font-weight:600!important;\n    letter-spacing:-0.1px!important;border-right:0!important;line-height:1.35!important;\n    font-family:-apple-system,BlinkMacSystemFont,'SF Pro Display',sans-serif!important;text-transform:none!important;\n  }\n  body.postid-1424 #lvm-shell .table-row > .cell.lean{\n    grid-area:lean!important;border-right:1px solid #E8E2D6!important;\n    position:relative!important;background:#FFF1F5!important;padding-top:30px!important;\n  }\n  body.postid-1424 #lvm-shell .table-row > .cell:not(.lean):not(.crit){\n    grid-area:mfp!important;background:#F5F5F7!important;padding-top:30px!important;\n    position:relative!important;\n  }\n  body.postid-1424 #lvm-shell .table-row > .cell.lean::before{\n    content:\"LEAN\"!important;position:absolute!important;top:8px!important;left:12px!important;\n    right:auto!important;bottom:auto!important;width:auto!important;height:auto!important;\n    background:transparent!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:10px!important;font-weight:700!important;letter-spacing:.07em!important;\n    color:#FF2D6E!important;\n  }\n  body.postid-1424 #lvm-shell .table-row > .cell:not(.lean):not(.crit)::before{\n    content:\"FATSECRET\"!important;position:absolute!important;top:8px!important;left:12px!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:10px!important;font-weight:700!important;letter-spacing:.07em!important;\n    color:#2E7BE5!important;\n  }\n  body.postid-1424 #lvm-shell .table-row > .cell{\n    padding:12px 12px!important;font-size:13px!important;line-height:1.4!important;\n    align-items:flex-start!important;gap:7px!important;\n  }\n  body.postid-1424 #lvm-shell .icn{flex-shrink:0!important;margin-top:1px!important}\n}\n\n\/* === A.5 MINI-LOGOS partie 7 (triplet NEAT\/EAT\/TEF) === *\/\n@media (max-width:760px){\n  body.postid-1424 #lvm-shell .mini-row{gap:6px!important;margin:24px 0!important;grid-template-columns:repeat(3,1fr)!important}\n  body.postid-1424 #lvm-shell .mini-phone{max-width:100px!important;padding:2px!important;border-radius:14px!important;border-width:1px!important}\n  body.postid-1424 #lvm-shell .mini-phone.tiny{max-width:96px!important;padding:2px!important;border-radius:13px!important}\n  body.postid-1424 #lvm-shell .mini-phone .notch{width:30px!important;height:8px!important;border-radius:0 0 5px 5px!important}\n  body.postid-1424 #lvm-shell .mini-phone .scr{border-radius:11px!important}\n  body.postid-1424 #lvm-shell .mini-cap{font-size:10px!important;margin-top:8px!important}\n  body.postid-1424 #lvm-shell .mini-cap strong{font-size:12px!important;margin-top:2px!important}\n}\n\n\/* === MOCKUP TAP HINT MOBILE === *\/\n@media (max-width:760px){\n  body.postid-1424 #lvm-shell .tap-hint.mobile{position:relative!important;width:100%!important;left:auto!important;top:auto!important;text-align:center!important;margin:0 auto 14px!important;display:block!important}\n  body.postid-1424 #lvm-shell .tap-hint.desktop{display:none!important}\n  body.postid-1424 #lvm-shell .tap-hint.hidden{display:none!important;height:0!important;margin:0!important;padding:0!important}\n}\n\n\/* === A.6 BODYSCAN ILLUST partie BMR (override mobile mini-phone) === *\/\nbody.postid-1424 #lvm-shell .bodyscan-illust{margin:40px auto 8px!important;display:flex!important;flex-direction:column!important;align-items:center!important;gap:14px!important;max-width:220px!important}\nbody.postid-1424 #lvm-shell .bodyscan-illust .mini-phone{max-width:200px!important;padding:3px!important;border-radius:22px!important;border-width:1px!important}\nbody.postid-1424 #lvm-shell .bodyscan-illust .mini-phone .notch{width:40px!important;height:11px!important;border-radius:0 0 7px 7px!important}\nbody.postid-1424 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:18px!important}\n@media (max-width:760px){\n  body.postid-1424 #lvm-shell .bodyscan-illust{max-width:180px!important}\n  body.postid-1424 #lvm-shell .bodyscan-illust .mini-phone{max-width:160px!important;padding:3px!important;border-radius:20px!important}\n  body.postid-1424 #lvm-shell .bodyscan-illust .mini-phone .notch{width:34px!important;height:9px!important;border-radius:0 0 6px 6px!important}\n  body.postid-1424 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:16px!important}\n}\n<\/style>\n\n\n<div id=\"lvm-shell\"><div class=\"progress\" aria-hidden=\"true\"><i id=\"progBar\"><\/i><\/div>\n\n<header class=\"nav\">\n  <div class=\"nav-row\">\n    <a class=\"nav-brand\" href=\"https:\/\/lean-app.com\/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\" 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\" \/>\n      <\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\" aria-label=\"Available 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\" \/>\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 FatSecret<\/div>\n  <div class=\"eyebrow\">Comparison &middot; Nutrition &amp; TDEE<\/div>\n  <h1 id=\"title\">Lean versus FatSecret.\n    <span class=\"alt\">Premium precision versus the free community database.<\/span>\n  <\/h1>\n  <p class=\"dek\">FatSecret is free and has a big community. Lean sees your real expenditure on an official database. Two promises that don&rsquo;t play on the same field.<\/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 24, 2026<\/span>\n  <\/div>\n  <div class=\"hero-stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"T\u00e9l\u00e9charger sur l'App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Disponible sur Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <span class=\"or\">Free download<\/span>\n  <\/div>\n\n  <div class=\"hero-bottom\">\n    <div class=\"hero-lead\">\n      FatSecret is known for its 100% free, ad-supported model, its very large active community, and its multi-country coverage. It&rsquo;s a massive food log, present in more than 50 countries. But its TDEE formula remains Mifflin-St Jeor 1990, plus a static activity factor you tick once at sign-up (sedentary, lightly active, active, very active, extremely active). No real bodyfat measured inside the app, no metabolic adaptation. Its food database is crowdsourced, with documented accuracy gaps.\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=\"Balance 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\">Balance<\/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>FatSecret calculates your TDEE with Mifflin-St Jeor 1990 (no bodyfat measured inside the app) and a static activity factor chosen at sign-up from 5 boxes (sedentary, lightly active, active, very active, extremely active). The real strength of FatSecret is elsewhere: a 100% free, ad-supported model, a large active community, meal and recipe sharing, presence in more than 50 countries. Lean takes a different stance: recalculate every component of TDEE (<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> by macros) and modulate the BMR through metabolic adaptation continuously, with a food database backed by USDA and OpenFoodFacts.<\/p>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"constat\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">00 &middot; The reality<\/span><\/div>\n  <h2 id=\"constat\">FatSecret gives you free access, not the accuracy of your expenditure<\/h2>\n  <p>Tu es probablement d\u00e9j\u00e0 utilisateur de FatSecret, et tu l&rsquo;as choisi pour ce qu&rsquo;il fait de mieux&nbsp;: un journal alimentaire complet, sans abonnement, avec le lecteur de code-barres inclus.<\/p>\n  <p>Tu as scann\u00e9 des produits, cherch\u00e9 des aliments dans la base, repris des recettes partag\u00e9es par la communaut\u00e9. Le suivi des apports fonctionne.<\/p>\n\n  <div class=\"statement\">\n    <div class=\"num\">&minus;10 to &minus;15&nbsp;%<\/div>\n    <div class=\"lbl\">of measured TDEE decline after 4 to 6 weeks of a &minus;500&nbsp;kcal\/day deficit. FatSecret doesn&rsquo;t detect it. Your calorie target stays frozen on your activity factor from 100&nbsp;days ago.<\/div>\n  <\/div>\n\n  <p>Prenons un cas concret. FatSecret annonce un TDEE de 2&nbsp;500&nbsp;kcal, tu manges 2&nbsp;250, tu crois \u00eatre \u00e0 250&nbsp;kcal de d\u00e9ficit. Si ta d\u00e9pense r\u00e9elle est de 2&nbsp;280, ton d\u00e9ficit effectif tombe \u00e0 30&nbsp;kcal&nbsp;: la balance ne bougera pas.<\/p>\n  <p>La promesse de FatSecret est claire et tenue&nbsp;: un journal gratuit, une communaut\u00e9, une base couvrant de nombreux march\u00e9s. Elle ne porte simplement pas sur la pr\u00e9cision de la d\u00e9pense.<\/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, with no bodyfat measured in the app<\/h2>\n  <p>FatSecret doit lui aussi estimer ton m\u00e9tabolisme de base pour te donner un objectif. Il utilise Mifflin-St Jeor, standard de fait du secteur depuis trois d\u00e9cennies.<\/p>\n  <p>L&rsquo;\u00e9quation date de 1990&nbsp;: 498 sujets, calorim\u00e9trie indirecte, calibrage sur une population plus moderne que les travaux de 1919. C&rsquo;est un socle honn\u00eate, et gratuit \u00e0 impl\u00e9menter, ce qui explique sa pr\u00e9sence quasi universelle.<\/p>\n  <p>L\u00e0 o\u00f9 d&rsquo;autres apps proposent en option l&rsquo;\u00e9quation Katch-McArdle, calcul\u00e9e sur la masse maigre, FatSecret s&rsquo;en tient \u00e0 la formule de base. Aucun champ pour saisir ton taux de masse grasse, aucun calcul alternatif&nbsp;: c&rsquo;est la contrepartie assum\u00e9e d&rsquo;un produit sans abonnement.<\/p>\n  <p>Le gain de 1990 sur 1919 reste faible, parce que le probl\u00e8me conceptuel est intact&nbsp;: la formule ne regarde que ton poids. Pas ta composition corporelle.<\/p>\n  <p>La masse grasse ne consomme presque rien au repos. Les vrais postes de d\u00e9pense sont les organes et les muscles&nbsp;: foie, cerveau, c\u0153ur, reins. \u00c0 poids \u00e9gal, deux corps diff\u00e9rents br\u00fblent diff\u00e9remment.<\/p>\n  <p>Frankenfield 2013 (PubMed 23631843) a mesur\u00e9 l&rsquo;\u00e9cart face \u00e0 la calorim\u00e9trie indirecte&nbsp;: 87&nbsp;% de pr\u00e9cision chez les non-ob\u00e8ses, 68&nbsp;% chez les ob\u00e8ses, avec des d\u00e9rives jusqu&rsquo;\u00e0 330&nbsp;kcal par jour.<\/p>\n\n  <p style=\"margin-bottom:8px\"><strong>Worked example.<\/strong> Man of 1.80&nbsp;m, 120&nbsp;kg, 30&nbsp;% bodyfat&nbsp;:<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figure 1<\/span><span class=\"r\">kcal<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\"><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> for a man at 1.80m, 120&nbsp;kg, 30&nbsp;% bodyfat. The patented proprietary Lean model accounts for lean mass. Mifflin-St Jeor (FatSecret by default, with no lean-mass option), doesn&rsquo;t. A 500&nbsp;kcal gap, the equivalent of a full lunch.<\/p>\n  <\/div>\n\n  <p>Une erreur de 330&nbsp;kcal transforme un d\u00e9ficit th\u00e9orique en maintenance r\u00e9elle. Le tracking est gratuit, l&rsquo;erreur aussi, mais elle se paie en semaines de progression perdues.<\/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 body fat<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 at 80&nbsp;kg, one at 10&nbsp;% bodyfat (BMR 1,900), the other at 30&nbsp;% (BMR 1,500). FatSecret gives them the same number, with no lean-mass option.<\/div>\n  <\/div>\n\n  <p>Math\u00e9matiquement, une \u00e9quation nourrie du seul poids ne peut pas produire un r\u00e9sultat individualis\u00e9. Gratuite ou payante, elle est aveugle \u00e0 ce qui fait la diff\u00e9rence.<\/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 factor, picked once and for all, and the crowdsourced database<\/h2>\n  <p>C&rsquo;est l\u00e0 que la gratuit\u00e9 montre sa limite technique.<\/p>\n  <p>Apr\u00e8s avoir estim\u00e9 ton m\u00e9tabolisme de base, FatSecret doit calculer ta d\u00e9pense totale&nbsp;: le BMR plus les pas, les gestes du quotidien, le sport et la digestion.<\/p>\n  <p>La solution retenue est la plus \u00e9conomique \u00e0 impl\u00e9menter&nbsp;: un choix unique de niveau d&rsquo;activit\u00e9 au moment de l&rsquo;inscription. C&rsquo;est le coefficient PAL.<\/p>\n  <ul>\n    <li>Sedentary (PAL 1.2): desk job, little walking<\/li>\n    <li>Lightly Active (PAL 1.375): occasional walking, little sport<\/li>\n    <li>Active (PAL 1.55): regular walking, sport 3 to 5 times per week<\/li>\n    <li>Very Active (PAL 1.725): intense sport almost daily<\/li>\n    <li>Extremely Active (PAL 1.9): very intense sport or heavy physical work<\/li>\n  <\/ul>\n  <p>Ton m\u00e9tabolisme est multipli\u00e9 par ce coefficient, et le r\u00e9sultat devient ton objectif quotidien. Une seule saisie, valable ind\u00e9finiment.<\/p>\n  <p>L&rsquo;\u00e9cart avec la r\u00e9alit\u00e9 est consid\u00e9rable. Une journ\u00e9e immobile et une journ\u00e9e \u00e0 15&nbsp;000 pas ne se distinguent en rien dans ce calcul.<\/p>\n  <p>FatSecret sait importer tes pas depuis Apple Health ou Google Fit, et peut cr\u00e9diter une s\u00e9ance d\u00e9tect\u00e9e. Mais la base du calcul reste le coefficient d\u00e9clar\u00e9 au d\u00e9part.<\/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\"><canvas id=\"chartNEAT\" aria-label=\"Daily variability of caloric expenditure over 7 days, vs 2400 kcal fixed per FatSecret\"><\/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 FatSecret was showing (2,400&nbsp;kcal flat, PAL Active \u00d7 BMR). The pink annotations show why each day moves.<\/p>\n  <\/div>\n\n  <p>Un niveau d&rsquo;activit\u00e9 n&rsquo;est pas une constante. Il varie d&rsquo;une semaine \u00e0 l&rsquo;autre, selon ton travail, la m\u00e9t\u00e9o, ta forme du moment.<\/p>\n  <p>Aucune des cases propos\u00e9es ne correspond donc durablement \u00e0 ta r\u00e9alit\u00e9, et l&rsquo;objectif calorique s&rsquo;en trouve d\u00e9cal\u00e9 en permanence.<\/p>\n  <p>C&rsquo;est le vrai verrou&nbsp;: m\u00eame avec une meilleure \u00e9quation de m\u00e9tabolisme, un PAL fig\u00e9 suffirait \u00e0 fausser le r\u00e9sultat. Le NEAT, l&rsquo;EAT et le TEF ne se d\u00e9duisent pas d&rsquo;un multiplicateur unique.<\/p>\n  <p><strong>On top of this problem comes the quality of the food database.<\/strong> FatSecret displays a massive database thanks to its community, but that database is crowdsourced: users add foods, brands, recipes. Several studies on user-generated food databases have documented gaps of plus or minus 20 percent on the calories of popular entries, due to duplicates, mis-entered portions, and approximate calorie copies. You can type &ldquo;roast chicken&rdquo; and get 30 different entries with kcal values ranging from single to double. Lean settles it: a database backed by <strong>USDA and OpenFoodFacts<\/strong>, verified official sources, and AI photo scan of a dish for foods outside the database.<\/p>\n  <p>Un m\u00e9tabolisme sans mesure de composition corporelle, plus une activit\u00e9 r\u00e9sum\u00e9e \u00e0 une case coch\u00e9e une fois&nbsp;: l&rsquo;objectif final a peu de chances de tomber juste.<\/p>\n\n  <div class=\"cta-band rev\">\n    <div class=\"l\">See your real TDEE, broken down into BMR + NEAT + EAT + TEF. Free download.<\/div>\n    <div class=\"stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"p3\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">03 &middot; Problem 3<\/span><\/div>\n  <h2 id=\"p3\">Metabolic adaptation, never modeled<\/h2>\n  <p>C&rsquo;est la variable dont aucune app gratuite ne parle, et pour cause&nbsp;: la mod\u00e9liser demande de l&rsquo;ing\u00e9nierie continue.<\/p>\n  <p>Quand tu manges moins pendant des semaines, ton organisme r\u00e9duit sa d\u00e9pense pour se prot\u00e9ger. Le principe est celui du mode \u00e9conomie d&rsquo;un t\u00e9l\u00e9phone&nbsp;: rien ne s&rsquo;arr\u00eate, tout ralentit.<\/p>\n  <p>Ce m\u00e9canisme porte un nom, l&rsquo;adaptation m\u00e9tabolique, et il est document\u00e9&nbsp;: M\u00fcller 2015 (PubMed 26399868, r\u00e9analyse du Minnesota), Doucet 2001, Nunes 2020 (PMC7484122). L&rsquo;ampleur publi\u00e9e va de 5 \u00e0 25&nbsp;% du m\u00e9tabolisme de base.<\/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>Convention Lean&nbsp;: 100&nbsp;% correspond \u00e0 un m\u00e9tabolisme intact, 90&nbsp;% \u00e0 une adaptation de 10&nbsp;%. Comme le NEAT, l&rsquo;EAT et le TEF d\u00e9coulent du BMR, l&rsquo;ensemble du TDEE se d\u00e9cale.<\/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\"><canvas id=\"chartAdapt\" aria-label=\"TDEE dropping from 2500 to 2150 kcal over 8 weeks, vs 2500 fixed per FatSecret\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>real TDEE<\/strong> over 8 weeks of deficit at &minus;500&nbsp;kcal\/day. The pink curve drops. The FatSecret line stays flat. By week 6, you&rsquo;re already at maintenance. Without having changed anything.<\/p>\n  <\/div>\n\n  <p>Concr\u00e8tement&nbsp;: d\u00e9ficit de 25&nbsp;% vis\u00e9 sur un TDEE de 2&nbsp;000&nbsp;kcal, soit 1&nbsp;500&nbsp;kcal par jour. Apr\u00e8s une adaptation de 14&nbsp;%, le TDEE r\u00e9el n&rsquo;est plus que de 1&nbsp;720&nbsp;kcal. Le d\u00e9ficit effectif tombe \u00e0 220&nbsp;kcal, et la perte s&rsquo;arr\u00eate.<\/p>\n  <p>Le pi\u00e8ge tient \u00e0 la progressivit\u00e9. Les premi\u00e8res semaines donnent des r\u00e9sultats, ce qui valide la m\u00e9thode \u00e0 tes yeux. L&rsquo;\u00e9cart se creuse ensuite sans signal visible, jusqu&rsquo;au blocage.<\/p>\n  <p>La majorit\u00e9 des gens attribuent alors ce plateau \u00e0 leur volont\u00e9 ou \u00e0 un \u00ab&nbsp;m\u00e9tabolisme cass\u00e9&nbsp;\u00bb. Une app gratuite ne peut pas les d\u00e9tromper&nbsp;: elle n&rsquo;a jamais mesur\u00e9 la variable en cause.<\/p>\n  <p>FatSecret ne calcule pas l&rsquo;adaptation m\u00e9tabolique. Ton objectif reste le m\u00eame en semaine 8 qu&rsquo;au premier jour, sauf mise \u00e0 jour manuelle de ton poids. La gratuit\u00e9 n&rsquo;est pas le probl\u00e8me&nbsp;: l&rsquo;absence de mesure l&rsquo;est.<\/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 n&rsquo;a pas \u00e9t\u00e9 pens\u00e9 comme un FatSecret payant. La gratuit\u00e9 int\u00e9grale de FatSecret est un vrai choix, assum\u00e9, et personne ne le lui enl\u00e8ve. Mais un mod\u00e8le 100&nbsp;% gratuit impose ses contraintes&nbsp;: une base alimentaire aliment\u00e9e par les utilisateurs eux-m\u00eames, et un moteur de calcul fig\u00e9 depuis une d\u00e9cennie parce que le faire \u00e9voluer co\u00fbte de l&rsquo;ing\u00e9nierie. Lean fait le pari inverse&nbsp;: mesurer chaque composant du TDEE (BMR&nbsp;+&nbsp;NEAT&nbsp;+&nbsp;EAT&nbsp;+&nbsp;TEF), avec l&rsquo;adaptation m\u00e9tabolique qui module le BMR semaine apr\u00e8s semaine. Voici comment, brique par brique.<\/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>AI BodyScan<\/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>L\u00e0 o\u00f9 FatSecret te demande ton poids et en d\u00e9duit ton m\u00e9tabolisme, Lean part de ta <strong>lean mass<\/strong>. La nuance est d\u00e9cisive&nbsp;: le muscle consomme de l&rsquo;\u00e9nergie au repos, la graisse presque pas. Reste le probl\u00e8me historique&nbsp;: comment conna\u00eetre son taux de masse grasse sans payer un DEXA en clinique chaque semaine&nbsp;?<\/p>\n      <p>La r\u00e9ponse de Lean tient dans une photo. Le <strong>AI BodyScan<\/strong> analyse ton clich\u00e9 via un mod\u00e8le entra\u00een\u00e9 sur une banque de scans DEXA et renvoie ton bodyfat en quelques secondes. Tu le refais chaque semaine, ton m\u00e9tabolisme se recalcule seul. C&rsquo;est pr\u00e9cis\u00e9ment le type de fonctionnalit\u00e9 qu&rsquo;un mod\u00e8le gratuit ne peut pas financer.<\/p>\n      <p>Fini la pince \u00e0 pli cutan\u00e9 et sa marge d&rsquo;erreur, la balance \u00e0 imp\u00e9dance et ses variations selon ton hydratation, le DEXA et son co\u00fbt. Une photo, cinq secondes, chaque semaine.<\/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> Tes pas r\u00e9els remontent depuis HealthKit (iOS) ou Google Fit (Android). Rien \u00e0 d\u00e9clarer, rien \u00e0 estimer&nbsp;: ce sont les acc\u00e9l\u00e9rom\u00e8tres de ton t\u00e9l\u00e9phone qui comptent. Lean croise ensuite ces pas avec ton m\u00e9tabolisme pour convertir ton activit\u00e9 quotidienne en calories, alors qu&rsquo;une case \u00ab&nbsp;mod\u00e9r\u00e9ment actif&nbsp;\u00bb applique le m\u00eame multiplicateur \u00e0 un livreur et \u00e0 un t\u00e9l\u00e9travailleur.<\/p>\n      <p><strong>EAT.<\/strong> Tu choisis ton sport dans une liste (musculation, course, tennis, natation) et Lean applique le MET correspondant \u00e0 ton temps r\u00e9el d&rsquo;effort. Une s\u00e9ance de musculation d&rsquo;une heure avec des temps de repos ne vaut pas une heure de course continue&nbsp;: compter les deux \u00e0 l&rsquo;identique, c&rsquo;est se tromper de plusieurs centaines de kcal sur la semaine.<\/p>\n      <p><strong>TEF.<\/strong> Dig\u00e9rer co\u00fbte de l&rsquo;\u00e9nergie, et ce co\u00fbt d\u00e9pend de ce que tu manges&nbsp;: 20 \u00e0 30&nbsp;% des calories pour les prot\u00e9ines, 5 \u00e0 10&nbsp;% pour les glucides, 1 \u00e0 3&nbsp;% pour les lipides. Lean calcule ce poste sur tes macros r\u00e9els au lieu d&rsquo;appliquer un forfait de 10&nbsp;% identique pour tout le monde.<\/p>\n    <\/div>\n    <div class=\"m-phone\">\n      <div class=\"mini-row\" style=\"margin:0;gap:10px\">\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp\" alt=\"\u00c9cran NEAT Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">NEAT<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp\" alt=\"\u00c9cran EAT Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">EAT<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp\" alt=\"\u00c9cran TEF Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">TEF<\/strong><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"method\">\n    <div class=\"m-phone\">\n      <div class=\"mini-phone\" style=\"max-width:170px\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp\" alt=\"\u00c9cran d\u00e9pense totale Lean avec adaptation m\u00e9tabolique\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">Method<strong>Auto adaptation<\/strong><\/div>\n    <\/div>\n    <div>\n      <div class=\"m-tag\">Automatic metabolic adaptation<\/div>\n      <h3>A world first on a consumer app<\/h3>\n      <p><strong>L&rsquo;adaptation m\u00e9tabolique.<\/strong> C&rsquo;est la brique qu&rsquo;aucune app grand public ne mod\u00e9lise, gratuite ou payante. Semaine apr\u00e8s semaine en d\u00e9ficit, ton m\u00e9tabolisme ralentit&nbsp;: Lean ajuste ton TDEE \u00e0 la baisse selon les fourchettes publi\u00e9es (M\u00fcller 2015, Doucet 2001), au lieu de t&rsquo;afficher le m\u00eame objectif calorique en semaine 8 qu&rsquo;au premier jour.<\/p>\n      <p>Pass\u00e9 10 \u00e0 15&nbsp;% d&rsquo;adaptation, l&rsquo;app peut te recommander un retour \u00e0 la maintenance pour relancer ton m\u00e9tabolisme avant de repartir en d\u00e9ficit. C&rsquo;est le protocole que suivent les pr\u00e9parateurs, rendu automatique.<\/p>\n      <p>Aucun coefficient d&rsquo;activit\u00e9 \u00e0 cocher, aucune case fig\u00e9e \u00e0 l&rsquo;inscription. Chaque composant est mesur\u00e9, semaine apr\u00e8s semaine.<\/p>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"tab\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">05 &middot; Side-by-side<\/span><\/div>\n  <h2 id=\"tab\">Lean versus FatSecret, 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=\"table\" role=\"table\" aria-label=\"Lean vs FatSecret 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-fatsecret-real.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> <span>FatSecret<\/span><\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">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 lean-mass option<\/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, measured in the app<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No, no bodyfat input possible<\/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 mid\">&minus;<\/span> HealthKit sync, exercise calorie add-on, but outside any TDEE recomputation<\/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> Simple sport selection, standard exercise database<\/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> Calculated from macros, integrated into the TDEE<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> No, macros displayed without TEF computation<\/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, 5 static boxes (sedentary to extremely active, PAL 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 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, manual entry, barcode, or manual photo of the label<\/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, verified official sources<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Crowdsourced, documented duplicates and calorie gaps<\/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 target, manual recompute required<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Community sharing (meals, 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, focus on TDEE computation<\/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> Active community, shared recipes<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Multi-country coverage<\/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> Present in 50+ countries, multi-language<\/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> 4.5\/5, 100M+ cumulative downloads, broad audience<\/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> Free, ad-supported, optional Premium<\/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>Une app gratuite n&rsquo;a d&rsquo;int\u00e9r\u00eat que si tu t&rsquo;en sers encore dans six mois. Lean propose donc trois fa\u00e7ons d&rsquo;enregistrer un repas, pour que la friction ne soit jamais la raison de l&rsquo;abandon.<\/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>Food 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>Le scan photo IA change surtout les repas pris \u00e0 l&rsquo;ext\u00e9rieur. L\u00e0 o\u00f9 la base communautaire de FatSecret te fait choisir entre quinze versions du m\u00eame plat saisies par quinze utilisateurs, une photo suffit et tu passes \u00e0 la suite.<\/p>\n  <p>Au-del\u00e0 du repas, Lean affiche un TDEE qui se met \u00e0 jour dans la journ\u00e9e&nbsp;: chaque millier de pas rel\u00e8ve ton objectif calorique. Un total fig\u00e9 le matin ne peut pas refl\u00e9ter \u00e7a.<\/p>\n  <p>Et au-dessus, la Pyramide de Progression hi\u00e9rarchise ce qui compte&nbsp;:<\/p>\n\n  <div class=\"pyramid\" aria-label=\"Lean Progression Pyramid\">\n    <div class=\"level l1\"><span>Adherence<\/span><span class=\"k\">Base<\/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\">Top<\/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=\"fatsecret-better\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">07 &middot; Honesty<\/span><\/div>\n  <h2 id=\"fatsecret-better\">What FatSecret does better<\/h2>\n  <p>Lean is not perfect, and FatSecret has several real strengths worth acknowledging. Honest read, criterion by criterion, on the axes where FatSecret stays ahead. None of these axes is secondary: they are real pillars of the FatSecret promise, and they explain its massive adoption among the cost-conscious mainstream audience.<\/p>\n\n  <div class=\"scorecard rev\" aria-label=\"FatSecret vs Lean scorecard across 4 axes: free access and community\">\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-fatsecret-real.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> FatSecret<\/div>\n      <div class=\"h-brand\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> Lean<\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">100% free model (ad-supported)<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:95%\"><\/i><\/div><div class=\"v\">9,5<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:25%\"><\/i><\/div><div class=\"v\">2,5<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Multi-country coverage<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:92%\"><\/i><\/div><div class=\"v\">9,2<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:65%\"><\/i><\/div><div class=\"v\">6,5<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Community (meal and recipe sharing)<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:88%\"><\/i><\/div><div class=\"v\">8,8<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:20%\"><\/i><\/div><div class=\"v\">2,0<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Raw size of the food catalog<\/div>\n      <div class=\"bar mfp\"><div class=\"b\"><i style=\"width:90%\"><\/i><\/div><div class=\"v\">9,0<\/div><\/div>\n      <div class=\"bar lean\"><div class=\"b\"><i style=\"width:72%\"><\/i><\/div><div class=\"v\">7,2<\/div><\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>Honest read.<\/strong> On the free model, FatSecret is the market reference: everything is accessible without a paywall, funded by ads displayed in the app. No critical calorie-tracking feature is gated behind a Premium. It&rsquo;s a real differentiator, especially for users who are starting out or want a log without commitment. On multi-country coverage, FatSecret is present in more than 50 countries with localized versions and adapted food databases (local brands, regional dishes). No other mainstream app has invested as much in geographic expansion. On the community, FatSecret has built over 15 years an active network of users who share meals, recipes, tips, and successes. It&rsquo;s an adherence mechanism few apps reproduce. On catalog size, FatSecret shows several million entries, which covers very specific foods that smaller databases would miss.<\/p>\n  <p>If your main angle is paying nothing to track your calories, getting access in a country where few apps are localized, or if the community dimension helps you stick with it, FatSecret is more relevant than Lean. If your angle is the precision of <a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/tdee-calculator\/\">TDEE calculation<\/a>, bodyfat measured every week through BodyScan AI, automatic metabolic adaptation, and a food database backed by USDA and OpenFoodFacts rather than crowdsourced, that&rsquo;s exactly what was demonstrated in the 3 previous sections. Many users run Lean for measurement and FatSecret in parallel for rare-food coverage, which is entirely defensible.<\/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>Quatre profils. Si l&rsquo;un d&rsquo;eux te correspond, Lean a des chances de te convenir.<\/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&rsquo;ve been using FatSecret for a long time and haven&rsquo;t lost<\/h4>\n        <p>Tu utilises FatSecret depuis longtemps, tu appr\u00e9cies sa gratuit\u00e9, mais tu doutes du chiffre affich\u00e9 en face de tes efforts.<\/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>Le plateau s&rsquo;installe apr\u00e8s quatre \u00e0 huit semaines sans que rien n&rsquo;ait chang\u00e9 dans ton suivi. C&rsquo;est l&rsquo;adaptation m\u00e9tabolique, que Lean calcule et int\u00e8gre \u00e0 ton objectif.<\/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>Tu veux comprendre d&rsquo;o\u00f9 vient ton objectif&nbsp;: chaque composant affich\u00e9 s\u00e9par\u00e9ment, plut\u00f4t qu&rsquo;un total issu d&rsquo;une formule et d&rsquo;une case coch\u00e9e.<\/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>Tu veux enregistrer vite sans naviguer entre quinze versions du m\u00eame plat&nbsp;: photo, base cur\u00e9e ou code-barres.<\/p>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>FatSecret stays more relevant for<\/strong>&nbsp;: paying nothing for your calorie log, enjoying an active community that shares meals and recipes, or accessing a very large multi-country catalog. Precision of TDEE calculation and metabolic adaptation just aren&rsquo;t part of its main 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\">Switching from FatSecret to Lean (or using both) 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 ou Play Store. Inscription en trente secondes.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">02<\/div><h4>AI BodyScan<\/h4><p>Une photo, cinq secondes&nbsp;: ton taux de masse grasse s&rsquo;affiche, sans mat\u00e9riel.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">03<\/div><h4>Weight &amp; height<\/h4><p>Tu saisis ton poids et ta taille. C&rsquo;est tout ce qu&rsquo;il faut pour d\u00e9marrer.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">04<\/div><h4>Lean calculates<\/h4><p>BMR sur masse maigre r\u00e9elle, NEAT depuis tes pas via HealthKit ou Google Fit, EAT par MET, TEF sur tes macros, plus l&rsquo;adaptation m\u00e9tabolique appliqu\u00e9e au fil des semaines.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">05<\/div><h4>Log a meal<\/h4><p>Photo, code-barres ou base cur\u00e9e&nbsp;: trois fa\u00e7ons d&rsquo;enregistrer, sans doublons \u00e0 trier.<\/p><\/div>\n  <\/div>\n\n  <p style=\"margin-top:24px\"><strong>Important note.<\/strong> Lean doesn&rsquo;t import your FatSecret history automatically, nor your custom recipes. If you still use the FatSecret community to discover recipes or find a rare local food in its very large catalog, many users keep checking FatSecret as a complement, while using Lean daily for the TDEE calculation and precise tracking. The HealthKit \/ Google Health Connect sync, on the other hand, takes over immediately for your steps and activity history.<\/p>\n\n  <div class=\"cta-band rev\">\n    <div class=\"l\">Download Lean and start the BodyScan AI right now. Free sign-up.<\/div>\n    <div class=\"stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"deblock-h\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">10 &middot; What Lean unlocks<\/span><\/div>\n  <h2 id=\"deblock-h\">What Lean does, that FatSecret doesn&rsquo;t (on TDEE)<\/h2>\n  <p>Six fonctionnalit\u00e9s qu&rsquo;aucun tracker gratuit ne propose, pour une raison simple&nbsp;: elles demandent une mesure continue, pas seulement une base de donn\u00e9es.<\/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\">Ton taux de masse grasse mesur\u00e9 depuis une photo, chaque semaine. C&rsquo;est la donn\u00e9e qui individualise le m\u00e9tabolisme, et elle ne s&rsquo;obtient pas par saisie manuelle.<\/p><\/div><div class=\"fc\">Body fat<\/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\">Un repas enregistr\u00e9 en deux secondes par photo, sans chercher la bonne entr\u00e9e parmi quinze versions saisies par la communaut\u00e9.<\/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\">Ton TDEE se r\u00e9ajuste semaine apr\u00e8s semaine selon les valeurs publi\u00e9es. Le plateau du deuxi\u00e8me mois cesse d&rsquo;\u00eatre un myst\u00e8re.<\/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 et TEF affich\u00e9s distinctement et actualis\u00e9s dans la journ\u00e9e, au lieu d&rsquo;un total fig\u00e9 calcul\u00e9 une fois pour toutes.<\/p><\/div><div class=\"fc\">Live<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">05<\/div><div><div class=\"ft\">Official food database<\/div><p class=\"fd\">Tes tendances de poids, de masse grasse et de masse maigre sur plusieurs mois, pour distinguer une vraie stagnation d&rsquo;une fluctuation d&rsquo;eau.<\/p><\/div><div class=\"fc\">Base<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">06<\/div><div><div class=\"ft\">3 unified tracking methods<\/div><p class=\"fd\">Une hi\u00e9rarchie de priorit\u00e9s&nbsp;: adh\u00e9rence, puis objectif calorique, puis pas. Tu sais quoi corriger en premier.<\/p><\/div><div class=\"fc\">Tracking<\/div><\/div>\n  <\/div>\n\n  <p style=\"margin-top:26px\">You install the app for free, you test without commitment, then you decide whether 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>FatSecret is free with a big community, why compare it to Lean on TDEE&nbsp;?<\/summary><div class=\"ans\">FatSecret is known for its 100% free, ad-supported model, its very large active community, and its massive food database (more than 50 countries, meal and recipe sharing by users). That&rsquo;s its strength. But its calorie promise rests on Mifflin-St Jeor 1990 without bodyfat, plus a static activity factor picked from 5 boxes at sign-up (sedentary, lightly active, active, very active, extremely active). And its food database is crowdsourced, with documented accuracy gaps (duplicate entries, incorrect calories, mislabeled brands). Lean recalculates your BMR every day on your real bodyfat measured by BodyScan AI, and grounds its database in USDA + OpenFoodFacts. The two apps don&rsquo;t play on the same field: free community access versus Premium precision.<\/div><\/details>\n    <details><summary>Why doesn&rsquo;t FatSecret calculate the BMR on real bodyfat&nbsp;?<\/summary><div class=\"ans\">FatSecret applies Mifflin-St Jeor 1990 by default without a lean-mass option. No bodyfat measurement is built into the app, and no Katch-McArdle-type equation is offered even in advanced settings. The consequence is mechanical: two users of the same weight but with 10 and 30 percent bodyfat get the same FatSecret BMR, while their real expenditure can differ by 400 to 500 kcal per day. Lean integrates BodyScan AI to measure your bodyfat from a simple photo, to redo every week.<\/div><\/details>\n    <details><summary>Is FatSecret&rsquo;s crowdsourced food database reliable&nbsp;?<\/summary><div class=\"ans\">FatSecret displays a massive food database thanks to its community, which adds foods, brands, and recipes. That&rsquo;s its strength in terms of coverage. The flip side: duplicate entries are numerous, calorie values vary from one entry to another for the same food, and rigorous verification is not systematic. Several studies on user-generated food databases have documented gaps of plus or minus 20 percent on the calories of popular entries. Lean backs its database with USDA and OpenFoodFacts, verified official sources, and adds AI photo scan of a dish for foods outside the database.<\/div><\/details>\n    <details><summary>FatSecret imports steps via HealthKit, is that enough for NEAT&nbsp;?<\/summary><div class=\"ans\">FatSecret syncs Apple Health and Google Fit for steps and some sessions, and can add a calorie add-on for detected exercises. But the underlying TDEE calculation still rests on the activity factor picked at sign-up from 5 boxes (sedentary, lightly active, active, very active, extremely active). The NEAT measured day by day doesn&rsquo;t recompose total expenditure. Lean calculates NEAT directly from real steps measured every day, with no coefficient to pick.<\/div><\/details>\n    <details><summary>Is Lean free or paid&nbsp;?<\/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    <details><summary>Can you use Lean and FatSecret in parallel&nbsp;?<\/summary><div class=\"ans\">Yes, it&rsquo;s defensible if you appreciate the FatSecret community for sharing meals and recipes, or if you want to keep a free fallback to enter a food found in its database. Lean handles the metabolic engine (BMR on real bodyfat, NEAT, EAT, TEF, adaptation), FatSecret brings you a community log and broad multi-country coverage. It&rsquo;s a trade-off between precision and community coverage.<\/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>Ce n&rsquo;est pas un duel marketing. C&rsquo;est la gratuit\u00e9 communautaire face \u00e0 la pr\u00e9cision de la d\u00e9pense&nbsp;: deux promesses distinctes.<\/p>\n  <p>FatSecret reste le meilleur choix pour suivre ses calories sans rien payer, avec une communaut\u00e9 active et une couverture large.<\/p>\n  <p>Lean r\u00e9pond \u00e0 l&rsquo;autre besoin&nbsp;: un m\u00e9tabolisme calcul\u00e9 sur la masse maigre mesur\u00e9e par BodyScan IA via un mod\u00e8le propri\u00e9taire brevet\u00e9, un NEAT tir\u00e9 de tes pas r\u00e9els, un EAT par MET, un TEF sur tes macros, et l&rsquo;adaptation m\u00e9tabolique suivie semaine apr\u00e8s semaine.<\/p>\n  <p>La gratuit\u00e9, la communaut\u00e9 et la couverture internationale restent des points forts de FatSecret. Si tu l&rsquo;as utilis\u00e9 s\u00e9rieusement et que ta progression s&rsquo;est arr\u00eat\u00e9e sans explication, le probl\u00e8me se situe probablement du c\u00f4t\u00e9 de la d\u00e9pense.<\/p>\n<\/section>\n\n<div class=\"get-band rev\">\n  <div class=\"kicker\">Download<\/div>\n  <h3>Lean is available as a free download<\/h3>\n  <p>iOS et Android. Le BodyScan IA fonctionne avec une simple photo&nbsp;: ni pince \u00e0 pli cutan\u00e9, ni balance \u00e0 imp\u00e9dance, ni DEXA.<\/p>\n  <div class=\"stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\" aria-label=\"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\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" 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\" \/>\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\/depense-energetique-totale-v2\/\">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-depense-non-sportive\/\">NEAT: expenditure from steps and non-exercise activity<\/a>.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/en\/effet-thermique-des-aliments\/\">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)\">References<\/h3>\n  <ol>\n    <li>Harris J.A., Benedict F.G. (1919). A Biometric Study of Basal Metabolism in Man. Carnegie Institution of Washington.<\/li>\n    <li>Mifflin M.D. et al. (1990). A new predictive equation for resting energy expenditure in healthy individuals. American Journal of Clinical Nutrition.<\/li>\n    <li>Frankenfield D.C. et al. (2013). Validation of Mifflin-St Jeor equation in obese and non-obese populations. PubMed 23631843.<\/li>\n    <li>M&uuml;ller M.J., Bosy-Westphal A. (2013). Adaptive thermogenesis with weight loss in humans. Obesity. PubMed 26399868.<\/li>\n    <li>Doucet E. et al. (2001). Evidence for the existence of adaptive thermogenesis during weight loss. British Journal of Nutrition. PubMed 11319656.<\/li>\n    <li>Nunes C.L. et al. (2020). Metabolic adaptation and energy compensation following weight loss. PMC7484122.<\/li>\n    <li>Westerterp K.R. (2004). Diet induced thermogenesis. Nutrition and Metabolism.<\/li>\n    <li>USDA FoodData Central. National Nutrient Database for Standard Reference. fdc.nal.usda.gov.<\/li>\n    <li>OpenFoodFacts. Open and verified collaborative food database. openfoodfacts.org.<\/li>\n    <li>Studies on the accuracy of crowdsourced food databases (documented variability of plus or minus 20 percent on popular entries).<\/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 publi\u00e9 le 24 mai 2026, mis \u00e0 jour r\u00e9guli\u00e8rement avec les retours d&rsquo;utilisateurs et les nouvelles \u00e9tudes pertinentes. Lean est disponible sur iOS et Android.<\/p>\n      <\/div>\n      <div class=\"stores\">\n        <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n        <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/><\/a>\n      <\/div>\n    <\/div>\n  <\/div>\n<\/footer>\n\n<script>\n(function(){\n  var bar = document.getElementById('progBar');\n  function up(){\n    var h = document.documentElement;\n    var sc = (h.scrollTop)\/Math.max(1,(h.scrollHeight - h.clientHeight));\n    bar.style.transform = 'scaleX(' + Math.max(0,Math.min(1,sc)) + ')';\n  }\n  document.addEventListener('scroll', up, {passive:true});\n  up();\n})();\n\n(function(){\n  if (!('IntersectionObserver' in window)) {\n    document.querySelectorAll('.rev').forEach(function(n){n.classList.add('on')});\n    return;\n  }\n  var obs = new IntersectionObserver(function(entries){\n    entries.forEach(function(e){\n      if (e.isIntersecting) { e.target.classList.add('on'); obs.unobserve(e.target); }\n    });\n  }, {threshold:0.12});\n  document.querySelectorAll('.rev').forEach(function(n){ obs.observe(n); });\n})();\n\n(function(){\n  var phoneImg = document.getElementById('phoneImg');\n  var phoneBack = document.getElementById('phoneBack');\n  var zones = document.getElementById('phoneZones');\n  var topTabs = document.querySelectorAll('.phone-tabs button');\n  var navTaps = document.querySelectorAll('.phone-navbar button');\n\n  var tabMap = {\n    bilan:    {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp',     drill:false},\n    kcal:     {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp',      drill:false},\n    depense:  {src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp',   drill:true},\n    strategie:{src:'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp', drill:false}\n  };\n  var subMap = {\n    BMR:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp',\n    NEAT: 'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp',\n    EAT:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp',\n    TEF:  'https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp'\n  };\n  var currentTab = 'depense';\n\n  function setActive(tab){\n    topTabs.forEach(function(b){ b.classList.toggle('on', b.dataset.tab===tab); });\n  }\n  function showTab(tab){\n    var t = tabMap[tab]; if(!t) return;\n    currentTab = tab;\n    phoneImg.style.opacity = 0;\n    setTimeout(function(){\n      phoneImg.className = 'phone-bg tab-' + tab;\n      phoneImg.style.opacity = 1;\n      zones.style.display = t.drill ? 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16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Basal Metabolic Rate (BMR): everything you need to know to calculate it accurately <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Definition, TDEE equation, 4 historical formulas, why bodyfat changes everything.<\/span><\/a><\/li><li><a href=\"\/en\/depense-energetique-totale-v2\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Total Daily Energy Expenditure (TDEE): the canonical formula BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Understand the 4 components + metabolic adaptation, scientific sources 2025.<\/span><\/a><\/li><li><a href=\"\/en\/eat\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">EAT: your real workout expenditure, session by session <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Correct MET values, the double-counting trap, what Garmin and MyFitnessPal miss.<\/span><\/a><\/li><li><a href=\"\/en\/meilleures-applications-calories-2026\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Best calorie counting apps in 2026: 8 apps tested <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Lean, MFP, Cronometer, Yazio, Lifesum, FatSecret, Noom, Foodvisor.<\/span><\/a><\/li><li><a href=\"\/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;\">Which MyFitnessPal alternative in 2026? 5 apps tested <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Honest comparison, TDEE accuracy, usability.<\/span><\/a><\/li><li><a href=\"\/en\/comparatifs\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">All Lean comparisons against major calorie apps <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Hub: MyFitnessPal, Yazio, Cronometer, Lifesum, FatSecret, Noom.<\/span><\/a><\/li><li><a href=\"\/en\/lean-vs-myfitnesspal\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean vs MyFitnessPal: the TDEE formula that changes everything <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Why MFP gets your real calorie expenditure wrong.<\/span><\/a><\/li><li><a href=\"\/en\/calculateur-tdee\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">TDEE Calculator: the canonical formula BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Bodyfat-aware calculator with breakdown of the 4 metabolic components.<\/span><\/a><\/li><\/ul><\/aside>","protected":false},"excerpt":{"rendered":"<p>Lean TDEE Calculator Home &nbsp;\/&nbsp; Lean vs FatSecret Comparison &middot; Nutrition &amp; TDEE Lean vs FatSecret. Premium precision vs the free community database. FatSecret is free and has a large community. Lean sees your real expenditure on an official database. Two promises that do not play on the same field. The Lean team &middot; Read 12&nbsp;min &middot; Updated [&hellip;]<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-lvm-blank","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1424","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Lean face \u00e0 FatSecret : pr\u00e9cision premium face au tracker gratuit - Lean<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/lean-app.com\/en\/lean-vs-fatsecret\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Lean face \u00e0 FatSecret : pr\u00e9cision premium face au tracker gratuit - Lean\" \/>\n<meta property=\"og:description\" content=\"Lean TDEE Calculator Home &nbsp;\/&nbsp; Lean vs FatSecret Comparison &middot; Nutrition &amp; TDEE Lean vs FatSecret. 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