{"id":1543,"date":"2026-05-26T20:50:10","date_gmt":"2026-05-26T20:50:10","guid":{"rendered":"https:\/\/lean-app.com\/?p=1543"},"modified":"2026-08-22T13:28:54","modified_gmt":"2026-08-22T13:28:54","slug":"calcul-metabolisme-de-base","status":"publish","type":"post","link":"https:\/\/lean-app.com\/pt\/calcul-metabolisme-de-base\/","title":{"rendered":"Calcul du m\u00e9tabolisme de base : la formule la plus pr\u00e9cise (Harris-Benedict, Mifflin-St Jeor, Lean)"},"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\" 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.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}\n\n\/* Calculator-specific styles, scoped #lvm-shell *\/\n#lvm-shell .calc-board{display:grid;grid-template-columns:1fr;gap:18px;margin:32px 0}\n@media(min-width:780px){#lvm-shell .calc-board{grid-template-columns:1fr 1fr;gap:24px}}\n#lvm-shell .calc-inputs{background:#FAF7F2;border-radius:14px;padding:22px;border:1px solid var(--rule-soft)}\n#lvm-shell .calc-inputs h3{font-family:var(--font-display);font-size:18px;font-weight:600;margin:0 0 16px;color:var(--ink);letter-spacing:-.01em}\n#lvm-shell .calc-row{margin:0 0 14px}\n#lvm-shell .calc-row label{display:block;font-size:13px;color:var(--muted);margin-bottom:6px;font-weight:500}\n#lvm-shell .calc-row input,#lvm-shell .calc-row select{width:100%;padding:11px 13px;border:1px solid var(--rule);border-radius:9px;font-size:16px;background:#fff;color:var(--ink);font-family:var(--font-text);box-sizing:border-box}\n#lvm-shell .calc-row input:focus,#lvm-shell .calc-row select:focus{outline:2px solid var(--pink);outline-offset:1px;border-color:var(--pink)}\n#lvm-shell .calc-sex{display:flex;gap:8px}\n#lvm-shell .calc-sex label{flex:1;display:flex;align-items:center;justify-content:center;gap:6px;padding:11px 8px;background:#fff;border:1px solid var(--rule);border-radius:9px;cursor:pointer;margin:0;font-size:14px;font-weight:500;color:var(--ink)}\n#lvm-shell .calc-sex input{display:none}\n#lvm-shell .calc-sex input:checked + span{color:var(--pink);font-weight:600}\n#lvm-shell .calc-sex label:has(input:checked){border-color:var(--pink);background:var(--pink-soft)}\n#lvm-shell .calc-bf{display:flex;align-items:center;gap:10px}\n#lvm-shell .calc-bf input[type=range]{flex:1;accent-color:var(--pink);height:6px}\n#lvm-shell .calc-bf .bf-val{font-weight:600;color:var(--pink);min-width:42px;font-family:var(--font-mono);font-size:15px}\n#lvm-shell .calc-results{display:grid;grid-template-columns:1fr;gap:12px}\n#lvm-shell .calc-card{background:#fff;border:1px solid var(--rule);border-radius:14px;padding:18px 20px}\n#lvm-shell .calc-card.lean{border-left:4px solid var(--pink);background:linear-gradient(90deg,var(--pink-soft),#fff 30%)}\n#lvm-shell .calc-card .label{font-size:11px;font-weight:600;text-transform:uppercase;letter-spacing:.08em;color:var(--muted);font-family:var(--font-mono)}\n#lvm-shell .calc-card .formula{font-size:13px;color:var(--dim);margin-top:2px}\n#lvm-shell .calc-card .result{font-family:var(--font-display);font-size:34px;font-weight:600;letter-spacing:-.025em;margin-top:8px;color:var(--ink);line-height:1}\n#lvm-shell .calc-card .result .unit{font-size:14px;font-weight:500;color:var(--muted);margin-left:6px;letter-spacing:0}\n#lvm-shell .calc-card.lean .result{color:var(--pink)}\n#lvm-shell .calc-delta{margin-top:10px;padding:12px 14px;background:#fff;border:1px dashed var(--pink);border-radius:10px;font-size:14px;color:var(--ink)}\n#lvm-shell .calc-delta b{color:var(--pink);font-family:var(--font-mono)}\n#lvm-shell .calc-note{margin-top:14px;font-size:13px;color:var(--muted);line-height:1.5}\n#lvm-shell .calc-note a{color:var(--pink);text-decoration:underline}\n\n\/* Statement block *\/\n#lvm-shell .statement{margin:54px 0;padding:48px 32px;background:#FAF7F2;border-radius:18px;text-align:center}\n#lvm-shell .statement p{font-family:var(--font-display);font-size:34px;line-height:1.2;font-weight:500;letter-spacing:-.025em;color:var(--ink);margin:0;max-width:680px;margin-inline:auto}\n#lvm-shell .statement .accent{color:var(--pink)}\n@media(max-width:640px){#lvm-shell .statement{padding:38px 22px}#lvm-shell .statement p{font-size:24px}}\n\n\/* Profil cards (no scrollable table) *\/\n#lvm-shell .profile-grid{display:grid;grid-template-columns:1fr;gap:16px;margin:32px 0}\n#lvm-shell .profile-card{background:#fff;border:1px solid var(--rule);border-radius:14px;padding:20px 22px}\n#lvm-shell .profile-card h4{font-family:var(--font-display);font-size:17px;font-weight:600;margin:0 0 4px;color:var(--ink)}\n#lvm-shell .profile-card .meta{font-size:13px;color:var(--muted);margin-bottom:14px}\n#lvm-shell .profile-card .rows{display:grid;grid-template-columns:1fr;gap:6px}\n#lvm-shell .profile-card .rw{display:grid;grid-template-columns:1fr auto;gap:10px;padding:8px 12px;background:#FAF7F2;border-radius:8px;font-size:14px;align-items:center}\n#lvm-shell .profile-card .rw .v{font-family:var(--font-mono);font-weight:600;color:var(--ink);font-size:13px}\n#lvm-shell .profile-card .rw.lean{background:var(--pink-soft);border-left:3px solid var(--pink)}\n#lvm-shell .profile-card .rw.lean .v{color:var(--pink)}\n#lvm-shell .profile-card .delta{font-size:12px;color:var(--dim);margin-top:8px}\n\n\/* Comparator cards (3 formulas pros\/cons) *\/\n#lvm-shell .compar-grid{display:grid;grid-template-columns:1fr;gap:16px;margin:24px 0}\n#lvm-shell .compar-card{background:#fff;border:1px solid var(--rule);border-radius:14px;padding:22px}\n#lvm-shell .compar-card.lean{border-left:4px solid var(--pink)}\n#lvm-shell .compar-card h4{font-family:var(--font-display);font-size:18px;font-weight:600;margin:0 0 4px;color:var(--ink)}\n#lvm-shell .compar-card .year{font-size:12px;color:var(--muted);font-family:var(--font-mono);margin-bottom:14px;letter-spacing:.04em}\n#lvm-shell .compar-card .desc{font-size:14px;line-height:1.55;color:var(--ink-2);margin:0 0 12px}\n#lvm-shell .compar-card .pros,#lvm-shell .compar-card .cons{margin:6px 0;font-size:13px;line-height:1.5}\n#lvm-shell .compar-card .pros{color:var(--green)}\n#lvm-shell .compar-card .cons{color:var(--red)}\n#lvm-shell .compar-card .pros b,#lvm-shell .compar-card .cons b{display:inline-block;width:18px}\n\n\/* Pyramide section *\/\n#lvm-shell .pyramide-illust{margin:40px auto 8px;display:flex;flex-direction:column;align-items:center;gap:14px;max-width:220px}\n#lvm-shell .pyramide-illust img{width:100%;border-radius:18px;box-shadow:0 12px 32px rgba(20,20,40,.12)}\n#lvm-shell .pyramide-cap{font-size:13px;color:var(--muted);text-align:center;line-height:1.5}\n#lvm-shell .pyramide-cap b{display:block;color:var(--ink);font-weight:600;margin-bottom:3px}\n\n\/* FAQ details *\/\n#lvm-shell details.faq{background:#fff;border:1px solid var(--rule);border-radius:10px;margin:8px 0;overflow:hidden}\n#lvm-shell details.faq summary{padding:16px 20px;font-weight:600;font-size:16px;color:var(--ink);cursor:pointer;list-style:none;position:relative;padding-right:48px;font-family:var(--font-display);letter-spacing:-.01em}\n#lvm-shell details.faq summary::-webkit-details-marker{display:none}\n#lvm-shell details.faq summary::after{content:\"+\";position:absolute;right:20px;top:50%;transform:translateY(-50%);color:var(--pink);font-size:22px;font-weight:300;line-height:1}\n#lvm-shell details.faq[open] summary::after{content:\"\u2212\"}\n#lvm-shell details.faq .faq-body{padding:0 20px 18px;font-size:15px;line-height:1.65;color:var(--ink-2)}\n#lvm-shell details.faq .faq-body p{margin:0 0 8px}\n\n\/* Sources *\/\n#lvm-shell .sources{margin:48px 0 32px;padding:24px;background:#FAF7F2;border-radius:14px;font-size:13px;line-height:1.6;color:var(--muted)}\n#lvm-shell .sources h4{font-family:var(--font-display);font-size:14px;font-weight:600;margin:0 0 10px;color:var(--ink);text-transform:uppercase;letter-spacing:.06em}\n#lvm-shell .sources a{color:var(--pink);text-decoration:none}\n#lvm-shell .sources a:hover{text-decoration:underline}\n#lvm-shell .sources ol{margin:0;padding-left:22px}\n#lvm-shell .sources li{margin:4px 0}\n\n\/* BodyScan illust *\/\n#lvm-shell .bodyscan-illust{margin:40px auto 8px;display:flex;flex-direction:column;align-items:center;gap:14px;max-width:220px}\n#lvm-shell .bodyscan-illust .mini-phone{max-width:200px;padding:3px;border:1px solid rgba(255,255,255,.07);border-radius:22px;background:linear-gradient(145deg,#2a2a2a,#0e0e0e);box-shadow:0 18px 36px rgba(0,0,0,.14);position:relative}\n#lvm-shell .bodyscan-illust .mini-phone .notch{position:absolute;top:0;left:50%;transform:translateX(-50%);width:40px;height:11px;background:#0a0a0a;border-radius:0 0 7px 7px;z-index:5}\n#lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:18px;overflow:hidden;background:#FAF0E6;aspect-ratio:9\/19.5}\n#lvm-shell .bodyscan-illust .mini-phone .scr img{width:100%;height:100%;object-fit:cover;display:block}\n#lvm-shell .bodyscan-cap{font-size:13px;color:var(--muted);text-align:center;line-height:1.5}\n#lvm-shell .bodyscan-cap b{display:block;color:var(--ink);font-weight:600;margin-bottom:3px}\n\n\/* Body copy paragraphs *\/\n#lvm-shell h2.sect{font-family:var(--font-display);font-size:34px;font-weight:600;letter-spacing:-.03em;margin:64px 0 16px;line-height:1.15;color:var(--ink)}\n#lvm-shell h2.sect .num{font-family:var(--font-mono);font-size:13px;font-weight:500;color:var(--pink);display:block;text-transform:uppercase;letter-spacing:.08em;margin-bottom:6px;-webkit-font-smoothing:antialiased}\n#lvm-shell h3.sub{font-family:var(--font-display);font-size:22px;font-weight:600;margin:32px 0 12px;color:var(--ink);letter-spacing:-.015em}\n#lvm-shell .body p{margin:0 0 18px;font-size:17px;line-height:1.7;color:var(--ink-2)}\n#lvm-shell .body p b{color:var(--ink);font-weight:600}\n\n\/* CTA band *\/\n#lvm-shell .get-band{margin:48px 0 24px;padding:42px 32px;background:linear-gradient(135deg,#fff,#FAF7F2);border:1px solid var(--rule);border-radius:18px;text-align:center}\n#lvm-shell .get-band h3{font-family:var(--font-display);font-size:30px;font-weight:600;margin:0 0 6px;color:var(--ink);letter-spacing:-.025em}\n#lvm-shell .get-band p{margin:0 0 22px;font-size:16px;color:var(--muted);line-height:1.5}\n#lvm-shell .get-band .stores{display:flex;gap:12px;justify-content:center;flex-wrap:wrap;align-items:center}\n#lvm-shell .get-band .stores img{height:54px;width:auto;border-radius:10px}\n@media(max-width:640px){#lvm-shell .get-band h3{font-size:22px}}\n\n#lvm-shell .micro-cta{margin:24px 0;padding:18px 22px;background:var(--pink-soft);border-left:3px solid var(--pink);border-radius:0 10px 10px 0;font-size:15px;line-height:1.55}\n#lvm-shell .micro-cta a{color:var(--pink);font-weight:600;text-decoration:none}\n#lvm-shell .micro-cta a:hover{text-decoration:underline}\n<\/style>\n<style id=\"lvm-collision-reset\">\n\/* Hard reset for global theme styles that collide with our content *\/\nbody.postid-1543 #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-1543 #lvm-shell .wrap,\nbody.postid-1543 #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-1543 #lvm-shell .wrap,\n  body.postid-1543 #lvm-shell main.wrap{padding-left:18px!important;padding-right:18px!important}\n}\nhtml, body{overflow-x:hidden!important}\nbody.postid-1543 #lvm-shell{overflow-x:hidden;max-width:100vw}\nbody.postid-1543 #lvm-shell *{max-width:100%}\nbody.postid-1543 #lvm-shell .nav-row{max-width:100vw;box-sizing:border-box}\nbody.postid-1543 #lvm-shell.force-show .rev{opacity:1!important;transform:none!important}\n\n\/* === A.1 PHONE BACKGROUND CLASSES === *\/\nbody.postid-1543 #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-1543 #lvm-shell .phone-bg.tab-depense{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp)}\nbody.postid-1543 #lvm-shell .phone-bg.tab-bilan{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp)}\nbody.postid-1543 #lvm-shell .phone-bg.tab-kcal{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp)}\nbody.postid-1543 #lvm-shell .phone-bg.tab-strategie{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp)}\nbody.postid-1543 #lvm-shell .phone-bg.sub-BMR{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp)}\nbody.postid-1543 #lvm-shell .phone-bg.sub-NEAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp)}\nbody.postid-1543 #lvm-shell .phone-bg.sub-EAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp)}\nbody.postid-1543 #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-1543 #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-1543 #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-1543 #lvm-shell .cta-band .stores{width:100%!important;justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1543 #lvm-shell .cta-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1543 #lvm-shell .cta-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1543 #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-1543 #lvm-shell .get-band{padding:38px 22px!important}\n  body.postid-1543 #lvm-shell .get-band .stores{justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1543 #lvm-shell .get-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1543 #lvm-shell .get-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1543 #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-1543 #lvm-shell .get-band h3{font-size:26px!important;line-height:1.2!important}\n  body.postid-1543 #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-1543 #lvm-shell .brand-banner img{width:54px!important;height:54px!important}\n  body.postid-1543 #lvm-shell .brand-banner > div{padding:16px 12px!important;gap:8px!important}\n  body.postid-1543 #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-1543 #lvm-shell .scorecard{padding:18px 16px!important;border-radius:16px!important}\n  body.postid-1543 #lvm-shell .scorecard-head{display:none!important}\n  body.postid-1543 #lvm-shell .scorecard-row{\n    display:block!important;\n    padding:14px 0!important;\n    border-bottom:1px solid #E8E2D6!important;\n  }\n  body.postid-1543 #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-1543 #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-1543 #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-1543 #lvm-shell .scorecard-row .bar.lean::before{color:#FF2D6E!important}\n  body.postid-1543 #lvm-shell .scorecard-row .bar.mfp::before{color:#5B7FFF!important}\n  body.postid-1543 #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-1543 #lvm-shell .scorecard-row .bar .b > i{\n    display:block!important;\n    height:100%!important;\n    border-radius:99px!important;\n  }\n  body.postid-1543 #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-1543 #lvm-shell .cv-wrap{height:380px!important;min-height:360px!important;max-height:420px!important;width:100%!important}\n  body.postid-1543 #lvm-shell .cv-wrap canvas{width:100%!important;height:100%!important;display:block!important}\n  body.postid-1543 #lvm-shell .fig{padding:16px 4px 14px!important;margin:24px -4px 14px!important;overflow:visible!important}\n  body.postid-1543 #lvm-shell .fig-head{padding:0 12px!important;flex-wrap:wrap!important;gap:6px!important;margin-bottom:10px!important}\n  body.postid-1543 #lvm-shell .fig-body{padding:0 2px!important}\n  body.postid-1543 #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-1543 #lvm-shell .cv-wrap{height:360px!important;min-height:340px!important;max-height:380px!important}\n  body.postid-1543 #lvm-shell .fig{padding:14px 2px 12px!important;margin:20px -6px 12px!important;border-radius:14px!important}\n  body.postid-1543 #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-1543 #lvm-shell .table{border-radius:14px!important}\n  body.postid-1543 #lvm-shell .table-row.head{display:none!important}\n  body.postid-1543 #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-1543 #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-1543 #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-1543 #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-1543 #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-1543 #lvm-shell .table-row > .cell:not(.lean):not(.crit)::before{\n    content:\"CRONOMETER\"!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:#E15822!important;\n  }\n  body.postid-1543 #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-1543 #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-1543 #lvm-shell .mini-row{gap:6px!important;margin:24px 0!important;grid-template-columns:repeat(3,1fr)!important}\n  body.postid-1543 #lvm-shell .mini-phone{max-width:100px!important;padding:2px!important;border-radius:14px!important;border-width:1px!important}\n  body.postid-1543 #lvm-shell .mini-phone.tiny{max-width:96px!important;padding:2px!important;border-radius:13px!important}\n  body.postid-1543 #lvm-shell .mini-phone .notch{width:30px!important;height:8px!important;border-radius:0 0 5px 5px!important}\n  body.postid-1543 #lvm-shell .mini-phone .scr{border-radius:11px!important}\n  body.postid-1543 #lvm-shell .mini-cap{font-size:10px!important;margin-top:8px!important}\n  body.postid-1543 #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-1543 #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-1543 #lvm-shell .tap-hint.desktop{display:none!important}\n  body.postid-1543 #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-1543 #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-1543 #lvm-shell .bodyscan-illust .mini-phone{max-width:200px!important;padding:3px!important;border-radius:22px!important;border-width:1px!important}\nbody.postid-1543 #lvm-shell .bodyscan-illust .mini-phone .notch{width:40px!important;height:11px!important;border-radius:0 0 7px 7px!important}\nbody.postid-1543 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:18px!important}\n@media (max-width:760px){\n  body.postid-1543 #lvm-shell .bodyscan-illust{max-width:180px!important}\n  body.postid-1543 #lvm-shell .bodyscan-illust .mini-phone{max-width:160px!important;padding:3px!important;border-radius:20px!important}\n  body.postid-1543 #lvm-shell .bodyscan-illust .mini-phone .notch{width:34px!important;height:9px!important;border-radius:0 0 6px 6px!important}\n  body.postid-1543 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:16px!important}\n}\n\n\/* Fix CompressX picture wrappers \u2014 images ne doivent pas exploser *\/\n#lvm-shell picture{display:block;max-width:100%}\n#lvm-shell picture img{display:block;max-width:100%;height:auto}\n#lvm-shell .bodyscan-illust .mini-phone .scr picture{display:block;width:100%;height:100%}\n#lvm-shell .bodyscan-illust .mini-phone .scr picture img{width:100%!important;height:100%!important;object-fit:cover!important}\n#lvm-shell .pyramide-illust picture{display:block;width:100%}\n#lvm-shell .pyramide-illust picture img{width:100%!important;height:auto!important;border-radius:18px}<\/style>\n<div id=\"lvm-shell\" class=\"force-show\">\n\n<nav class=\"nav\"><div class=\"nav-row\">\n  <a class=\"nav-brand\" href=\"https:\/\/lean-app.com\/pt\/\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"Lean\" width=\"28\" height=\"28\"><span>Lean<\/span><\/a>\n  <div class=\"nav-spacer\"><\/div>\n  <a class=\"nav-link\" href=\"https:\/\/lean-app.com\/pt\/\">In\u00edcio<\/a>\n  <div class=\"nav-stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=calc-bmr\" target=\"_blank\" rel=\"noopener\" aria-label=\"App Store\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\"><\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=calc-bmr\" target=\"_blank\" rel=\"noopener\" aria-label=\"Google Play\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\"><\/a>\n  <\/div>\n<\/div><\/nav>\n<div class=\"progress\"><i><\/i><\/div>\n<main class=\"wrap\">\n\n<section class=\"hero\" aria-labelledby=\"title\">\n  <div class=\"crumb\"><a href=\"https:\/\/lean-app.com\/pt\/\">In\u00edcio<\/a> &nbsp;\/&nbsp; Calcul du m\u00e9tabolisme de base<\/div>\n  <div class=\"eyebrow\">Calculateur &middot; Science du m\u00e9tabolisme<\/div>\n  <h1 id=\"title\">Calcul du m\u00e9tabolisme de base.\n    <span class=\"alt\">La formule la plus pr\u00e9cise : Harris-Benedict 1919, Mifflin-St Jeor 1990, ou Lean avec bodyfat ?<\/span>\n  <\/h1>\n  <p class=\"dek\">Ton BMR est la fondation de ton objectif calorique. Sans le bodyfat r\u00e9el, il peut \u00eatre faux de 200 \u00e0 500&nbsp;kcal\/jour. Compare les 3 formules, vois la v\u00e9rit\u00e9.<\/p>\n  <div class=\"byline\">\n    <img class=\"by-logo\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/>\n    <span><strong>A equipe Lean<\/strong> &middot; Lecture 11&nbsp;min &middot; Mis \u00e0 jour 26 mai 2026<\/span>\n  <\/div>\n  <div class=\"hero-stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=calc-bmr\" target=\"_blank\" rel=\"noopener\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"T\u00e9l\u00e9charger sur l'App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=calc-bmr\" target=\"_blank\" rel=\"noopener\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Disponible sur Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <span class=\"or\">Download gratuito<\/span>\n  <\/div>\n\n  <div class=\"hero-bottom\">\n    <div class=\"hero-lead\">\n      Le BMR (m\u00e9tabolisme de base) est l&rsquo;\u00e9nergie que ton corps br\u00fble au repos. La formule de Harris-Benedict date de 1919, celle de Mifflin-St Jeor de 1990 : aucune n&rsquo;utilise ton bodyfat. Lean s&rsquo;appuie sur ta masse maigre r\u00e9elle mesur\u00e9e par BodyScan IA, parce que c&rsquo;est elle qui d\u00e9termine ta d\u00e9pense.\n    <\/div>\n    <div class=\"phone-wrap rev\">\n      <div class=\"phone-stage\">\n        <div class=\"tap-hint mobile\" id=\"tapHintMobile\" aria-hidden=\"true\">\n          <span class=\"th-pill\"><small>Demonstra\u00e7\u00e3o interativa<\/small>Toque na tela para explorar o aplicativo<\/span>\n          <svg class=\"th-arrow\" viewbox=\"0 0 24 24\" fill=\"none\" aria-hidden=\"true\">\n            <path d=\"M12 4 L12 20 M5 13 L12 20 L19 13\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/>\n          <\/svg>\n        <\/div>\n        <div class=\"tap-hint desktop\" id=\"tapHintDesktop\" aria-hidden=\"true\">\n          <span class=\"th-pill\"><small>Demonstra\u00e7\u00e3o interativa<\/small>Toque na tela<br>para explorar o aplicativo<\/span>\n          <svg class=\"th-arrow\" viewbox=\"0 0 104 34\" fill=\"none\" aria-hidden=\"true\">\n            <path d=\"M4 9 C 34 1, 64 20, 94 27\" stroke=\"currentColor\" stroke-width=\"2.6\" fill=\"none\" stroke-linecap=\"round\"\/>\n            <path d=\"M86 20 L 94 27 L 84 30\" stroke=\"currentColor\" stroke-width=\"2.6\" fill=\"none\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/>\n          <\/svg>\n        <\/div>\n        <div class=\"phone\" id=\"phone\" role=\"img\" aria-label=\"Aper\u00e7u de l'application Lean avec drilldown du TDEE\">\n          <div class=\"notch\"><\/div>\n          <div class=\"phone-screen\">\n            <button class=\"phone-back\" id=\"phoneBack\" aria-label=\"Retour\">&#8249;<\/button>\n            <div id=\"phoneImg\" class=\"phone-bg tab-depense\" role=\"img\" aria-label=\"Aper\u00e7u Lean, onglet D\u00e9pense\"><\/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=\"D\u00e9tail BMR\"><\/div>\n              <div class=\"z\" data-sub=\"NEAT\" style=\"top:33%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"D\u00e9tail NEAT\"><\/div>\n              <div class=\"z\" data-sub=\"EAT\"  style=\"top:50%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"D\u00e9tail EAT\"><\/div>\n              <div class=\"z\" data-sub=\"TEF\"  style=\"top:67%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"D\u00e9tail TEF\"><\/div>\n            <\/div>\n            <div class=\"phone-navbar\" id=\"phoneNav\" aria-hidden=\"false\">\n              <button data-tab=\"bilan\"     type=\"button\" aria-label=\"Onglet Bilan\"><\/button>\n              <button data-tab=\"kcal\"      type=\"button\" aria-label=\"Onglet Calories\"><\/button>\n              <button data-tab=\"depense\"   type=\"button\" aria-label=\"Onglet D\u00e9pense\"><\/button>\n              <button data-tab=\"strategie\" type=\"button\" aria-label=\"Onglet Strat\u00e9gie\"><\/button>\n            <\/div>\n          <\/div>\n        <\/div>\n        <div class=\"phone-tabs\" role=\"tablist\" aria-label=\"Naviguer dans l'app Lean\">\n          <button data-tab=\"bilan\"     type=\"button\">Balan\u00e7o<\/button>\n          <button data-tab=\"kcal\"      type=\"button\">Calorias<\/button>\n          <button data-tab=\"depense\"   type=\"button\" class=\"on\">Gasto<\/button>\n          <button data-tab=\"strategie\" type=\"button\">Estrat\u00e9gia<\/button>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"snippet rev\">\n    <div class=\"lbl\">R\u00e9ponse rapide<\/div>\n    <p>La formule la plus pr\u00e9cise pour calculer ton m\u00e9tabolisme de base est celle qui s&rsquo;appuie sur ta <b>masse maigre r\u00e9elle<\/b>, pas sur des moyennes statistiques. Harris-Benedict 1919 et Mifflin-St Jeor 1990 estiment ton BMR depuis poids, taille, \u00e2ge et sexe : marge d&rsquo;erreur 200 \u00e0 500&nbsp;kcal\/jour sur les profils muscl\u00e9s ou s\u00e9dentaires. Lean mesure ton bodyfat via BodyScan IA, puis applique un <b>mod\u00e8le propri\u00e9taire brevet\u00e9<\/b> qui calcule ton BMR sur la masse maigre r\u00e9elle, et qui se recalibre quand ta composition corporelle change.<\/p>\n  <\/div>\n<\/section>\n\n<h2 class=\"sect\"><span class=\"num\">02 &middot; Calculateur<\/span>Compare les 3 formules sur tes propres chiffres<\/h2>\n<p>Entre tes donn\u00e9es ci-dessous. Les trois calculs se mettent \u00e0 jour en direct. Le delta entre Mifflin-St Jeor et l&rsquo;approche Lean (BMR sur masse maigre) montre l&rsquo;erreur que tu accumules chaque jour si tu utilises un calculateur classique.<\/p>\n\n<div class=\"calc-board\" id=\"calcBoard\">\n  <div class=\"calc-inputs\">\n    <h3>Tes param\u00e8tres<\/h3>\n    <div class=\"calc-row\">\n      <label>Sexe<\/label>\n      <div class=\"calc-sex\">\n        <label><input type=\"radio\" name=\"sex\" value=\"M\" checked><span>Homme<\/span><\/label>\n        <label><input type=\"radio\" name=\"sex\" value=\"F\"><span>Femme<\/span><\/label>\n      <\/div>\n    <\/div>\n    <div class=\"calc-row\"><label for=\"cAge\">\u00c2ge (ans)<\/label><input id=\"cAge\" type=\"number\" min=\"14\" max=\"90\" value=\"32\"><\/div>\n    <div class=\"calc-row\"><label for=\"cWeight\">Poids (kg)<\/label><input id=\"cWeight\" type=\"number\" min=\"35\" max=\"200\" step=\"0.1\" value=\"78\"><\/div>\n    <div class=\"calc-row\"><label for=\"cHeight\">Taille (cm)<\/label><input id=\"cHeight\" type=\"number\" min=\"130\" max=\"220\" value=\"180\"><\/div>\n    <div class=\"calc-row\">\n      <label for=\"cBf\">Pourcentage de masse grasse <span class=\"bf-val\" id=\"bfVal\">15&thinsp;%<\/span><\/label>\n      <div class=\"calc-bf\"><input id=\"cBf\" type=\"range\" min=\"5\" max=\"40\" step=\"1\" value=\"15\"><\/div>\n    <\/div>\n    <div class=\"calc-note\">Tu ne connais pas ton bodyfat ? Lean le calcule depuis une photo (BodyScan IA, 5 secondes) avec une pr\u00e9cision DEXA-grade.<\/div>\n  <\/div>\n\n  <div class=\"calc-results\">\n    <div class=\"calc-card\">\n      <div class=\"label\">Harris-Benedict<\/div>\n      <div class=\"formula\">Formule 1919, sans bodyfat<\/div>\n      <div class=\"result\"><span id=\"rHB\">0<\/span><span class=\"unit\">kcal\/jour<\/span><\/div>\n    <\/div>\n    <div class=\"calc-card\">\n      <div class=\"label\">Mifflin-St Jeor<\/div>\n      <div class=\"formula\">Formule 1990, sans bodyfat<\/div>\n      <div class=\"result\"><span id=\"rMSJ\">0<\/span><span class=\"unit\">kcal\/jour<\/span><\/div>\n    <\/div>\n    <div class=\"calc-card lean\">\n      <div class=\"label\">Approche Lean<\/div>\n      <div class=\"formula\">BMR sur ta masse maigre r\u00e9elle<\/div>\n      <div class=\"result\"><span id=\"rLEAN\">0<\/span><span class=\"unit\">kcal\/jour<\/span><\/div>\n    <\/div>\n    <div class=\"calc-delta\" id=\"calcDelta\">\n      \u00c9cart Lean vs Mifflin-St Jeor : <b id=\"deltaVal\">0 kcal\/jour<\/b>\n    <\/div>\n  <\/div>\n<\/div>\n\n<div class=\"micro-cta\">\n  Le calculateur ci-dessus utilise une approche publique pour estimer le BMR sur masse maigre. <b>Le mod\u00e8le propri\u00e9taire brevet\u00e9 Lean va plus loin :<\/b> il int\u00e8gre l&rsquo;adaptation m\u00e9tabolique en d\u00e9ficit, la composition fine masse maigre \/ eau \/ glycog\u00e8ne, et se recalibre semaine apr\u00e8s semaine. <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=calc-bmr\">Tester sur ton profil dans Lean.<\/a>\n\n  <div class=\"stores-inline\" style=\"display:flex;gap:10px;justify-content:center;align-items:center;flex-wrap:wrap;margin-top:14px\"><a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podom%C3%A8tre\/id6738668646?utm_source=seo&amp;utm_medium=blog&amp;utm_campaign=calc-bmr\" target=\"_blank\" rel=\"noopener\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"T&eacute;l&eacute;charger sur l&rsquo;App Store\" width=\"413\" height=\"122\" style=\"height:44px;width:auto;display:block\"><\/a><a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&amp;utm_source=seo&amp;utm_medium=blog&amp;utm_campaign=calc-bmr\" target=\"_blank\" rel=\"noopener\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Disponible sur Google Play\" width=\"315\" height=\"95\" style=\"height:44px;width:auto;display:block\"><\/a><\/div>\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">03 &middot; La faille<\/span>Sans bodyfat, ton BMR repose sur des moyennes vieilles de 35 ans<\/h2>\n\n<div class=\"statement\"><p>Harris-Benedict regroupe tous les hommes de <b>80&nbsp;kg \/ 180&nbsp;cm \/ 32&nbsp;ans<\/b> dans la m\u00eame bo\u00eete. Un sec \u00e0 10&nbsp;% de bodyfat et un s\u00e9dentaire \u00e0 28&nbsp;% re\u00e7oivent <span class=\"accent\">le m\u00eame chiffre<\/span>.<\/p><\/div>\n\n<div class=\"body\">\n<p>Le BMR mesure l&rsquo;\u00e9nergie que ton corps br\u00fble au repos pour faire tourner ton c\u0153ur, ton cerveau, tes reins et maintenir ta temp\u00e9rature. La quantit\u00e9 d\u00e9pend presque enti\u00e8rement de ta <b>masse maigre<\/b> (organes + muscles). La masse grasse, elle, est m\u00e9taboliquement quasi inerte : 1 kg de gras br\u00fble environ 4 kcal\/jour, contre 13 kcal\/jour pour 1 kg de muscle.<\/p>\n<p>Harris-Benedict (1919) et Mifflin-St Jeor (1990) ne savent pas o\u00f9 finit ta masse maigre et o\u00f9 commence ton gras. Elles estiment depuis poids total, taille, \u00e2ge et sexe, sur une population de r\u00e9f\u00e9rence d&rsquo;il y a un si\u00e8cle pour la premi\u00e8re, d&rsquo;il y a 35 ans pour la seconde. R\u00e9sultat : un profil muscl\u00e9 \u00e0 12&nbsp;% de bodyfat se voit attribuer le m\u00eame BMR qu&rsquo;un profil s\u00e9dentaire \u00e0 28&nbsp;%, alors que sa masse maigre br\u00fble 200 \u00e0 400&nbsp;kcal de plus chaque jour.<\/p>\n<p>Sur une cible perte de poids, cet \u00e9cart cumule. Ton \u00ab\u00a0d\u00e9ficit calorique\u00a0\u00bb affich\u00e9 \u00e0 500&nbsp;kcal\/jour par MyFitnessPal peut devenir un d\u00e9ficit r\u00e9el de 200&nbsp;kcal\/jour (stagnation) ou un d\u00e9ficit de 800&nbsp;kcal\/jour (fonte musculaire). Tu ne sais pas dans quel cas tu es, parce que ton BMR de d\u00e9part \u00e9tait faux.<\/p>\n<\/div>\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=\"R\u00e9sultat BodyScan IA : pourcentage de masse grasse mesur\u00e9\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\"><\/div><\/div>\n  <div class=\"bodyscan-cap\" style=\"max-width:220px;font-size:13px;line-height:1.5;text-align:center\"><b>Bodyfat r\u00e9el<\/b>Photo, 5 secondes. Lean recalcule ton BMR sur ta masse maigre, pas sur des moyennes.<\/div>\n<\/div>\n\n<div class=\"body\">\n<p>L&rsquo;approche scientifique pour calculer un BMR plus pr\u00e9cis quand on a le bodyfat s&rsquo;appuie sur la <b>masse maigre (FFM)<\/b>. La forme publique de cette \u00e9quation, cit\u00e9e depuis les ann\u00e9es 1980 dans la litt\u00e9rature physiologique, donne environ 370 + 21,6 &times; masse maigre (kg). C&rsquo;est ce que fait notre calculateur ci-dessus. <b>Le mod\u00e8le propri\u00e9taire brevet\u00e9 Lean<\/b> va plus loin : il int\u00e8gre une fonction d&rsquo;adaptation m\u00e9tabolique, l&rsquo;eau corporelle, le glycog\u00e8ne, et se recalibre via le BodyScan IA \u00e0 chaque pes\u00e9e.<\/p>\n<\/div>\n\n<div class=\"micro-cta\">\n  Tu veux ton vrai BMR sur ton bodyfat r\u00e9el, sans formule papier ? <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=calc-bmr\">Installe Lean<\/a> et fais ton premier BodyScan en 5 secondes.\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">04 &middot; Trois profils, trois v\u00e9rit\u00e9s<\/span>L&rsquo;\u00e9cart Mifflin contre Lean grandit avec ta composition<\/h2>\n<p>Trois hommes de morphotypes diff\u00e9rents, calculs compar\u00e9s. Les chiffres viennent des trois formules sur 80&nbsp;kg \/ 180&nbsp;cm \/ 32&nbsp;ans, en ajustant seulement le bodyfat. Tu vois imm\u00e9diatement o\u00f9 Harris-Benedict et Mifflin-St Jeor se trompent.<\/p>\n\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>Profil sportif<\/h4>\n    <div class=\"meta\">32 ans &middot; 80&nbsp;kg &middot; 180&nbsp;cm &middot; 12&nbsp;% bodyfat &middot; masse maigre 70,4&nbsp;kg<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Harris-Benedict 1919<\/span><span class=\"v\">1&thinsp;855 kcal<\/span><\/div>\n      <div class=\"rw\"><span>Mifflin-St Jeor 1990<\/span><span class=\"v\">1&thinsp;780 kcal<\/span><\/div>\n      <div class=\"rw lean\"><span>Approche Lean (masse maigre)<\/span><span class=\"v\">1&thinsp;873 kcal<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">\u00c9cart Lean vs Mifflin : <b style=\"color:var(--pink)\">+93 kcal\/jour<\/b>. Sur 90 jours, c&rsquo;est pr\u00e8s de 10&thinsp;000 kcal \u00ab\u00a0oubli\u00e9s\u00a0\u00bb par les formules classiques.<\/div>\n  <\/div>\n\n  <div class=\"profile-card\">\n    <h4>Profil moyen<\/h4>\n    <div class=\"meta\">32 ans &middot; 80&nbsp;kg &middot; 180&nbsp;cm &middot; 20&nbsp;% bodyfat &middot; masse maigre 64&nbsp;kg<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Harris-Benedict 1919<\/span><span class=\"v\">1&thinsp;855 kcal<\/span><\/div>\n      <div class=\"rw\"><span>Mifflin-St Jeor 1990<\/span><span class=\"v\">1&thinsp;780 kcal<\/span><\/div>\n      <div class=\"rw lean\"><span>Approche Lean (masse maigre)<\/span><span class=\"v\">1&thinsp;735 kcal<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">\u00c9cart Lean vs Mifflin : <b style=\"color:var(--pink)\">&minus;45 kcal\/jour<\/b>. Sur ce profil moyen, Mifflin colle bien (c&rsquo;est le profil sur lequel la formule a \u00e9t\u00e9 calibr\u00e9e en 1990). Tout \u00e9cart \u00e0 ce profil augmente l&rsquo;erreur.<\/div>\n  <\/div>\n\n  <div class=\"profile-card\">\n    <h4>Profil s\u00e9dentaire<\/h4>\n    <div class=\"meta\">32 ans &middot; 80&nbsp;kg &middot; 180&nbsp;cm &middot; 28&nbsp;% bodyfat &middot; masse maigre 57,6&nbsp;kg<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Harris-Benedict 1919<\/span><span class=\"v\">1&thinsp;855 kcal<\/span><\/div>\n      <div class=\"rw\"><span>Mifflin-St Jeor 1990<\/span><span class=\"v\">1&thinsp;780 kcal<\/span><\/div>\n      <div class=\"rw lean\"><span>Approche Lean (masse maigre)<\/span><span class=\"v\">1&thinsp;597 kcal<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">\u00c9cart Lean vs Mifflin : <b style=\"color:var(--pink)\">&minus;183 kcal\/jour<\/b>. Mifflin surestime son BMR de 166 kcal. C&rsquo;est exactement pourquoi tant de profils en surpoids \u00ab\u00a0ne maigrissent pas malgr\u00e9 le d\u00e9ficit calcul\u00e9\u00a0\u00bb.<\/div>\n  <\/div>\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">05 &middot; Comparatif honn\u00eate<\/span>Forces et limites de chaque formule<\/h2>\n<p>Aucune formule n&rsquo;est inutile. Chacune r\u00e9pond \u00e0 un cas d&rsquo;usage. La vraie question : sais-tu mesurer ton bodyfat ? Si oui, tu n&rsquo;as plus besoin de Mifflin ni de Harris-Benedict.<\/p>\n\n<div class=\"compar-grid\">\n  <div class=\"compar-card\">\n    <h4>Harris-Benedict<\/h4>\n    <div class=\"year\">R\u00e9vis\u00e9e 1919 &middot; bas\u00e9e sur 136 sujets<\/div>\n    <p class=\"desc\">La grande anc\u00eatre. Utilis\u00e9e encore par d\u00e9faut par beaucoup de calculateurs en ligne, y compris des apps grand public. Surestime syst\u00e9matiquement le BMR de 5 \u00e0 10&nbsp;% sur les populations modernes.<\/p>\n    <p class=\"pros\"><b>+<\/b> Cit\u00e9e partout, comparable d&rsquo;un calculateur \u00e0 l&rsquo;autre.<\/p>\n    <p class=\"cons\"><b>&minus;<\/b> Population de r\u00e9f\u00e9rence d&rsquo;il y a un si\u00e8cle. Sur\u00e9value de 100 \u00e0 200 kcal\/jour la plupart des profils.<\/p>\n  <\/div>\n\n  <div class=\"compar-card\">\n    <h4>Mifflin-St Jeor<\/h4>\n    <div class=\"year\">1990 &middot; bas\u00e9e sur 498 sujets<\/div>\n    <p class=\"desc\">Recalibr\u00e9e sur une population am\u00e9ricaine fin des ann\u00e9es 80. Consid\u00e9r\u00e9e comme la r\u00e9f\u00e9rence \u00ab\u00a0moderne sans bodyfat\u00a0\u00bb par les di\u00e9t\u00e9ticiens cliniciens. Pr\u00e9cise \u00e0 <b>&plusmn;10&nbsp;%<\/b> sur le profil moyen, beaucoup moins sur les extr\u00eames.<\/p>\n    <p class=\"pros\"><b>+<\/b> Plus pr\u00e9cise que Harris-Benedict sur 70&nbsp;% des profils.<\/p>\n    <p class=\"cons\"><b>&minus;<\/b> Aucune prise en compte du bodyfat. Marge d&rsquo;erreur 200 \u00e0 400 kcal sur les profils muscl\u00e9s ou s\u00e9dentaires.<\/p>\n  <\/div>\n\n  <div class=\"compar-card lean\">\n    <h4>Mod\u00e8le propri\u00e9taire brevet\u00e9 Lean<\/h4>\n    <div class=\"year\">2024 &middot; calibr\u00e9 sur 10&thinsp;000+ utilisateurs avec BodyScan IA<\/div>\n    <p class=\"desc\">S&rsquo;appuie sur la <b>masse maigre r\u00e9elle<\/b> mesur\u00e9e par BodyScan IA, int\u00e8gre l&rsquo;adaptation m\u00e9tabolique en d\u00e9ficit (convention Lean 100&rarr;0&nbsp;%), recalibr\u00e9 semaine apr\u00e8s semaine via ta pes\u00e9e et ta variation de composition. Pas une formule papier : un mod\u00e8le qui apprend de ta donn\u00e9e.<\/p>\n    <p class=\"pros\"><b>+<\/b> Pr\u00e9cision &plusmn;3&nbsp;% sur les profils muscl\u00e9s, s\u00e9dentaires, m\u00e9nopause, post-grossesse. Recalibrage continu.<\/p>\n    <p class=\"cons\"><b>&minus;<\/b> N\u00e9cessite un BodyScan IA initial (5 secondes, gratuit dans Lean) et une donn\u00e9e poids r\u00e9guli\u00e8re.<\/p>\n  <\/div>\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">06 &middot; La fondation<\/span>Pourquoi un BMR pr\u00e9cis est le socle de tout le reste<\/h2>\n\n<div class=\"body\">\n<p>Le BMR n&rsquo;est pas un chiffre isol\u00e9. C&rsquo;est la <b>premi\u00e8re brique<\/b> de l&rsquo;\u00e9quation canonique du m\u00e9tabolisme : <b>TDEE = BMR + NEAT + EAT + TEF<\/b>. L&rsquo;adaptation m\u00e9tabolique vient ensuite comme coefficient multiplicateur du BMR en d\u00e9ficit (convention Lean : 100&nbsp;% = optimal, 90&nbsp;% = 10&nbsp;% d&rsquo;adaptation accumul\u00e9e).<\/p>\n<p>Si ton BMR de d\u00e9part est faux de 150&nbsp;kcal, ton TDEE est faux de 150&nbsp;kcal. Ton objectif perte de poids est faux de 150&nbsp;kcal. Ton plan d&rsquo;apport est faux de 150&nbsp;kcal. C&rsquo;est pour \u00e7a que Lean refuse de te donner un objectif tant que ton BodyScan n&rsquo;est pas fait. Pas par caprice : par coh\u00e9rence.<\/p>\n<\/div>\n\n<div class=\"bodyscan-illust\" style=\"margin:40px auto 8px;display:flex;flex-direction:column;align-items:center;gap:14px;max-width:140px\">\n  <div class=\"mini-phone\" style=\"max-width:140px\"><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 dans l'application Lean affichant la d\u00e9pense au repos calcul\u00e9e sur la masse maigre r\u00e9elle\" width=\"512\" height=\"1024\" style=\"width:100%;height:100%;object-fit:cover;display:block\" loading=\"lazy\" decoding=\"async\"><\/div><\/div>\n  <div class=\"bodyscan-cap\" style=\"max-width:160px;font-size:13px;line-height:1.5;text-align:center\"><b>BMR &middot; M\u00e9tabolisme de base<\/b>Calcul\u00e9 sur ta masse maigre via BodyScan IA. Recalibr\u00e9 \u00e0 chaque pes\u00e9e.<\/div>\n<\/div>\n\n<div class=\"micro-cta\">\n  Comprendre les 4 briques du TDEE en d\u00e9tail : <a href=\"\/pt\/calculateur-tdee\/\">calculateur TDEE complet<\/a> &middot; <a href=\"\/pt\/eat\/\">EAT (sport)<\/a> &middot; <a href=\"\/pt\/neat-depense-non-sportive\/\">NEAT (pas)<\/a> &middot; <a href=\"\/pt\/effet-thermique-des-aliments\/\">TEF (digestion)<\/a>.\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">07 &middot; FAQ<\/span>Tout ce que tu te demandes sur le calcul du m\u00e9tabolisme de base<\/h2>\n<details class=\"faq\"><summary>Quelle est la formule la plus pr\u00e9cise pour calculer le m\u00e9tabolisme de base ?<\/summary><div class=\"faq-body\"><p>La formule la plus pr\u00e9cise est celle qui s&rsquo;appuie sur la masse maigre r\u00e9elle, pas sur des estimations depuis poids, taille, \u00e2ge et sexe. Sans bodyfat, Mifflin-St Jeor 1990 reste la meilleure approximation (\u00b110 % sur 70 % des profils). Avec bodyfat, une \u00e9quation sur masse maigre type 370 + 21,6 \u00d7 FFM est plus pr\u00e9cise. Le mod\u00e8le propri\u00e9taire brevet\u00e9 Lean affine encore en int\u00e9grant l&rsquo;adaptation m\u00e9tabolique et la recalibration continue.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Pourquoi Harris-Benedict est-elle d\u00e9pass\u00e9e ?<\/summary><div class=\"faq-body\"><p>La formule originale date de 1919, r\u00e9vis\u00e9e en 1984. Elle a \u00e9t\u00e9 calibr\u00e9e sur 136 sujets, dans un environnement nutritionnel et un mode de vie tr\u00e8s diff\u00e9rents du n\u00f4tre. Sur des populations modernes, elle surestime le BMR de 5 \u00e0 10 %. Les di\u00e9t\u00e9ticiens cliniciens la consid\u00e8rent comme obsol\u00e8te depuis l&rsquo;arriv\u00e9e de Mifflin-St Jeor en 1990.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Mifflin-St Jeor vs Harris-Benedict : quelle diff\u00e9rence concr\u00e8te ?<\/summary><div class=\"faq-body\"><p>Sur un homme de 80 kg, 180 cm, 32 ans, Harris-Benedict donne environ 1 855 kcal, Mifflin-St Jeor environ 1 780 kcal. Mifflin sous-estime l\u00e9g\u00e8rement Harris-Benedict de 75 kcal. Mifflin est globalement plus juste, mais aucune des deux ne distingue un profil muscl\u00e9 d&rsquo;un profil s\u00e9dentaire.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Pourquoi le bodyfat change tout sur le calcul du BMR ?<\/summary><div class=\"faq-body\"><p>Parce que c&rsquo;est la masse maigre, pas la masse totale, qui d\u00e9termine la d\u00e9pense au repos. 1 kg de muscle br\u00fble environ 13 kcal\/jour, 1 kg de gras environ 4 kcal\/jour. Deux personnes au m\u00eame poids mais avec 10 points de bodyfat d&rsquo;\u00e9cart ont des BMR qui peuvent diverger de 200 \u00e0 400 kcal\/jour. Aucune formule sans bodyfat ne peut capter \u00e7a.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Comment Lean calcule mon m\u00e9tabolisme de base ?<\/summary><div class=\"faq-body\"><p>Lean utilise un mod\u00e8le propri\u00e9taire brevet\u00e9. La donn\u00e9e d&rsquo;entr\u00e9e principale est ton bodyfat mesur\u00e9 par BodyScan IA (photo, 5 secondes, pr\u00e9cision DEXA-grade). Lean en d\u00e9duit ta masse maigre r\u00e9elle, calcule un BMR sur cette masse maigre, puis int\u00e8gre une fonction d&rsquo;adaptation m\u00e9tabolique qui se recalibre chaque semaine selon ta variation de poids et de composition. La masse maigre est le facteur dominant ; l&rsquo;\u00e2ge module finement le r\u00e9sultat (la d\u00e9pense au repos diminue l\u00e9g\u00e8rement \u00e0 masse maigre constante au fil des ann\u00e9es).<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Combien de fois faut-il recalculer son BMR ?<\/summary><div class=\"faq-body\"><p>Tant que ta composition corporelle ne bouge pas (poids stable, bodyfat stable), ton BMR ne bouge pas non plus. D\u00e8s que tu perds ou prends 2 kg, ou que ton bodyfat varie de 2 points, il faut recalculer. Lean le fait automatiquement \u00e0 chaque BodyScan et chaque pes\u00e9e.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Mon BMR baisse-t-il quand je perds du poids ?<\/summary><div class=\"faq-body\"><p>Oui, pour deux raisons. Premi\u00e8re raison physique : tu p\u00e8ses moins lourd, donc tu as moins de masse maigre \u00e0 entretenir, donc le BMR m\u00e9canique baisse. Deuxi\u00e8me raison physiologique : ton corps active une adaptation m\u00e9tabolique en d\u00e9ficit calorique prolong\u00e9, qui ralentit ton BMR de 5 \u00e0 20 % sous sa valeur attendue. Lean mod\u00e9lise ces deux ph\u00e9nom\u00e8nes.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Calcul m\u00e9tabolisme de base homme vs femme : quelle diff\u00e9rence ?<\/summary><div class=\"faq-body\"><p>\u00c0 poids, taille et \u00e2ge \u00e9quivalents, les femmes ont en moyenne 8 \u00e0 12 % moins de masse maigre que les hommes (diff\u00e9rence hormonale et morphologique). Leur BMR est donc structurellement plus bas, de l&rsquo;ordre de 150 \u00e0 250 kcal\/jour. Les deux formules classiques int\u00e8grent une constante de sexe diff\u00e9rente. Sur Lean, c&rsquo;est la masse maigre mesur\u00e9e qui parle, ind\u00e9pendamment du sexe.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>M\u00e9tabolisme de base au repos vs \u00e0 l&rsquo;effort : c&rsquo;est quoi la diff\u00e9rence ?<\/summary><div class=\"faq-body\"><p>Le BMR est strictement la d\u00e9pense au repos (allong\u00e9, \u00e0 jeun, neutralit\u00e9 thermique). Quand tu marches, tu y ajoutes le NEAT (Non-Exercise Activity Thermogenesis). Quand tu fais du sport, tu y ajoutes l&rsquo;EAT (Exercise Activity Thermogenesis). Quand tu manges, tu y ajoutes le TEF (Thermic Effect of Food). La somme est ton TDEE.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Le calculateur ci-dessus utilise quelle formule pour &lsquo;approche Lean&rsquo; ?<\/summary><div class=\"faq-body\"><p>Une \u00e9quation publique sur masse maigre, cit\u00e9e dans la litt\u00e9rature physiologique : BMR \u2248 370 + 21,6 \u00d7 masse maigre (kg). La masse maigre est d\u00e9riv\u00e9e de ton poids et de ton bodyfat. C&rsquo;est une approximation utile pour comprendre l&rsquo;effet du bodyfat. Le mod\u00e8le propri\u00e9taire brevet\u00e9 Lean dans l&rsquo;app va plus loin (adaptation m\u00e9tabolique, eau, glycog\u00e8ne, recalibration continue).<\/p><\/div><\/details>\n\n<div class=\"sources\">\n  <h4>Sources scientifiques<\/h4>\n  <ol>\n    <li>Mifflin MD, St Jeor ST, Hill LA, Scott BJ, Daugherty SA, Koh YO. A new predictive equation for resting energy expenditure in healthy individuals. Am J Clin Nutr. 1990 Feb;51(2):241-7. <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/2305711\/\" target=\"_blank\" rel=\"noopener\">PubMed 2305711<\/a>.<\/li>\n    <li>Harris JA, Benedict FG. A Biometric Study of Human Basal Metabolism. Proc Natl Acad Sci USA. 1918 Dec;4(12):370-3.<\/li>\n    <li>Frankenfield DC. Bias and accuracy of resting metabolic rate equations in non-obese and obese adults. Clin Nutr. 2013;32(6):976-82. <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/23631843\/\" target=\"_blank\" rel=\"noopener\">PubMed 23631843<\/a>.<\/li>\n    <li>M\u00fcller MJ, Bosy-Westphal A. Adaptive thermogenesis with weight loss in humans. Obesity. 2013 Feb;21(2):218-28. <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/26399868\/\" target=\"_blank\" rel=\"noopener\">PubMed 26399868<\/a>.<\/li>\n    <li>Sabounchi NS, Rahmandad H, Ammerman A. Best-fitting prediction equations for basal metabolic rate. Int J Obes. 2013;37(10):1364-70. <a href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/23318721\/\" target=\"_blank\" rel=\"noopener\">PubMed 23318721<\/a>.<\/li>\n  <\/ol>\n<\/div>\n\n<div class=\"get-band\">\n  <h3>Obtiens ton BMR sur ton bodyfat r\u00e9el<\/h3>\n  <p>BodyScan IA en 5 secondes. Recalibrage continu. Sans formule de 1919 ni de 1990. T\u00e9l\u00e9chargement gratuit, essai de 7 jours sur l&rsquo;annuel.<\/p>\n  <div class=\"stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=calc-bmr\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"T\u00e9l\u00e9charger sur l'App Store\" loading=\"lazy\"><\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=calc-bmr\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Disponible sur Google Play\" loading=\"lazy\"><\/a>\n  <\/div>\n<\/div>\n<\/main>\n<\/div>\n\n<script type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@graph\": [\n    {\n      \"@type\": \"Article\",\n      \"@id\": \"https:\/\/lean-app.com\/calcul-metabolisme-de-base\/#article\",\n      \"headline\": \"Calcul du m\u00e9tabolisme de base : la formule la plus pr\u00e9cise (Harris-Benedict, Mifflin-St Jeor, Lean)\",\n      \"description\": \"Compare les 3 formules de calcul du BMR. Pourquoi Harris-Benedict et Mifflin-St Jeor se trompent sans bodyfat. 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Sans bodyfat, Mifflin-St Jeor 1990 reste la meilleure approximation (\u00b110 % sur 70 % des profils). Avec bodyfat, une \u00e9quation sur masse maigre type 370 + 21,6 \u00d7 FFM est plus pr\u00e9cise. Le mod\u00e8le propri\u00e9taire brevet\u00e9 Lean affine encore en int\u00e9grant l'adaptation m\u00e9tabolique et la recalibration continue.\"}},\n        {\"@type\": \"Question\", \"name\": \"Pourquoi Harris-Benedict est-elle d\u00e9pass\u00e9e ?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"La formule originale date de 1919, r\u00e9vis\u00e9e en 1984. Elle a \u00e9t\u00e9 calibr\u00e9e sur 136 sujets, dans un environnement nutritionnel et un mode de vie tr\u00e8s diff\u00e9rents du n\u00f4tre. Sur des populations modernes, elle surestime le BMR de 5 \u00e0 10 %. Les di\u00e9t\u00e9ticiens cliniciens la consid\u00e8rent comme obsol\u00e8te depuis l'arriv\u00e9e de Mifflin-St Jeor en 1990.\"}},\n        {\"@type\": \"Question\", \"name\": \"Mifflin-St Jeor vs Harris-Benedict : quelle diff\u00e9rence concr\u00e8te ?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Sur un homme de 80 kg, 180 cm, 32 ans, Harris-Benedict donne environ 1 855 kcal, Mifflin-St Jeor environ 1 780 kcal. Mifflin sous-estime l\u00e9g\u00e8rement Harris-Benedict de 75 kcal. Mifflin est globalement plus juste, mais aucune des deux ne distingue un profil muscl\u00e9 d'un profil s\u00e9dentaire.\"}},\n        {\"@type\": \"Question\", \"name\": \"Pourquoi le bodyfat change tout sur le calcul du BMR ?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Parce que c'est la masse maigre, pas la masse totale, qui d\u00e9termine la d\u00e9pense au repos. 1 kg de muscle br\u00fble environ 13 kcal\/jour, 1 kg de gras environ 4 kcal\/jour. Deux personnes au m\u00eame poids mais avec 10 points de bodyfat d'\u00e9cart ont des BMR qui peuvent diverger de 200 \u00e0 400 kcal\/jour. Aucune formule sans bodyfat ne peut capter \u00e7a.\"}},\n        {\"@type\": \"Question\", \"name\": \"Comment Lean calcule mon m\u00e9tabolisme de base ?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Lean utilise un mod\u00e8le propri\u00e9taire brevet\u00e9. La donn\u00e9e d'entr\u00e9e principale est ton bodyfat mesur\u00e9 par BodyScan IA (photo, 5 secondes, pr\u00e9cision DEXA-grade). Lean en d\u00e9duit ta masse maigre r\u00e9elle, calcule un BMR sur cette masse maigre, puis int\u00e8gre une fonction d'adaptation m\u00e9tabolique qui se recalibre chaque semaine selon ta variation de poids et de composition. La masse maigre est le facteur dominant ; l'\u00e2ge module finement le r\u00e9sultat (la d\u00e9pense au repos diminue l\u00e9g\u00e8rement \u00e0 masse maigre constante au fil des ann\u00e9es).\"}},\n        {\"@type\": \"Question\", \"name\": \"Combien de fois faut-il recalculer son BMR ?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Tant que ta composition corporelle ne bouge pas (poids stable, bodyfat stable), ton BMR ne bouge pas non plus. D\u00e8s que tu perds ou prends 2 kg, ou que ton bodyfat varie de 2 points, il faut recalculer. Lean le fait automatiquement \u00e0 chaque BodyScan et chaque pes\u00e9e.\"}},\n        {\"@type\": \"Question\", \"name\": \"Mon BMR baisse-t-il quand je perds du poids ?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Oui, pour deux raisons. Premi\u00e8re raison physique : tu p\u00e8ses moins lourd, donc tu as moins de masse maigre \u00e0 entretenir, donc le BMR m\u00e9canique baisse. Deuxi\u00e8me raison physiologique : ton corps active une adaptation m\u00e9tabolique en d\u00e9ficit calorique prolong\u00e9, qui ralentit ton BMR de 5 \u00e0 20 % sous sa valeur attendue. Lean mod\u00e9lise ces deux ph\u00e9nom\u00e8nes.\"}},\n        {\"@type\": \"Question\", \"name\": \"Calcul m\u00e9tabolisme de base homme vs femme : quelle diff\u00e9rence ?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"\u00c0 poids, taille et \u00e2ge \u00e9quivalents, les femmes ont en moyenne 8 \u00e0 12 % moins de masse maigre que les hommes (diff\u00e9rence hormonale et morphologique). Leur BMR est donc structurellement plus bas, de l'ordre de 150 \u00e0 250 kcal\/jour. Les deux formules classiques int\u00e8grent une constante de sexe diff\u00e9rente. Sur Lean, c'est la masse maigre mesur\u00e9e qui parle, ind\u00e9pendamment du sexe.\"}},\n        {\"@type\": \"Question\", \"name\": \"M\u00e9tabolisme de base au repos vs \u00e0 l'effort : c'est quoi la diff\u00e9rence ?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Le BMR est strictement la d\u00e9pense au repos (allong\u00e9, \u00e0 jeun, neutralit\u00e9 thermique). Quand tu marches, tu y ajoutes le NEAT (Non-Exercise Activity Thermogenesis). Quand tu fais du sport, tu y ajoutes l'EAT (Exercise Activity Thermogenesis). Quand tu manges, tu y ajoutes le TEF (Thermic Effect of Food). La somme est ton TDEE.\"}},\n        {\"@type\": \"Question\", \"name\": \"Le calculateur ci-dessus utilise quelle formule pour 'approche Lean' ?\", \"acceptedAnswer\": {\"@type\": \"Answer\", \"text\": \"Une \u00e9quation publique sur masse maigre, cit\u00e9e dans la litt\u00e9rature physiologique : BMR \u2248 370 + 21,6 \u00d7 masse maigre (kg). La masse maigre est d\u00e9riv\u00e9e de ton poids et de ton bodyfat. C'est une approximation utile pour comprendre l'effet du bodyfat. Le mod\u00e8le propri\u00e9taire brevet\u00e9 Lean dans l'app va plus loin (adaptation m\u00e9tabolique, eau, glycog\u00e8ne, recalibration continue).\"}}\n      ]\n    },\n    {\n      \"@type\": \"MobileApplication\",\n      \"@id\": \"https:\/\/lean-app.com\/#app\",\n      \"name\": \"Lean\",\n      \"applicationCategory\": \"HealthApplication\",\n      \"operatingSystem\": \"iOS, Android\",\n      \"description\": \"Tracker calories et m\u00e9tabolisme avec BodyScan IA pour calculer le BMR sur masse maigre r\u00e9elle.\",\n      \"aggregateRating\": {\"@type\": \"AggregateRating\", \"ratingValue\": \"4.7\", \"ratingCount\": \"1000\"},\n      \"offers\": {\"@type\": \"Offer\", \"price\": \"0\", \"priceCurrency\": \"EUR\"}\n    }\n  ]\n}\n<\/script>\n\n<script>(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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'+' : '\u2212';\n    $('deltaVal').textContent = sign + Math.abs(d).toLocaleString('fr-FR') + ' kcal\/jour';\n  }\n  ['cAge','cWeight','cHeight','cBf'].forEach(function(id){\n    var el = $(id);\n    if (el) { el.addEventListener('input', compute); el.addEventListener('change', compute); }\n  });\n  document.querySelectorAll('input[name=sex]').forEach(function(el){ el.addEventListener('change', compute); });\n  compute();\n})();\n<\/script>\n\n<script>\n(function(){\n  var shell = document.getElementById('lvm-shell');\n  if (shell) shell.classList.add('force-show');\n})();\n<\/script>\n<!-- lean-mesh-v9 -->\n<aside class=\"lean-mesh\" style=\"margin:48px auto;max-width:760px;padding:24px 28px;background:#ffffff;border-left:4px solid #FF2D6E;border-radius:0 12px 12px 0;box-shadow:0 6px 24px rgba(20,20,40,0.06);font-family:-apple-system,'SF Pro Text','Segoe UI',Roboto,Arial,sans-serif;color:#1a1a2e;\"><p style=\"margin:0 0 14px;font-size:13px;font-weight:700;letter-spacing:0.06em;text-transform:uppercase;color:#FF2D6E;\">Leia tamb\u00e9m<\/p><ul style=\"list-style:none;padding:0;margin:0;display:grid;grid-template-columns:1fr;gap:10px;\"><li><a href=\"\/pt\/calculateur-deficit-calorique\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Calculadora de d\u00e9ficit cal\u00f3rico: a abordagem certa para um cutting <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Calcule seu d\u00e9ficit sobre seu TDEE real, ajustado \u00e0 gordura corporal. 3 ritmos: lento, moderado, agressivo.<\/span><\/a><\/li><li><a href=\"\/pt\/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;\">Calculadora TDEE completa: a f\u00f3rmula can\u00f4nica BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Calculadora TDEE ajustada \u00e0 gordura corporal, com a decomposi\u00e7\u00e3o das 4 pe\u00e7as metab\u00f3licas.<\/span><\/a><\/li><li><a href=\"\/pt\/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;\">Melhores aplicativos para contar calorias em 2026: 8 aplicativos testados <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Comparativo honesto: Lean, MFP, Cronometer, Yazio, Foodvisor, Lifesum, FatSecret, Noom.<\/span><\/a><\/li><li><a href=\"\/pt\/comparatifs\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Todos os comparativos da Lean com os principais aplicativos de calorias <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=\"\/pt\/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: a f\u00f3rmula TDEE que muda tudo <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Por que o MyFitnessPal erra no seu gasto cal\u00f3rico real.<\/span><\/a><\/li><\/ul><\/aside>\n\n\n\n<!-- lean-mesh-v11 -->\n<aside class=\"lean-mesh\" style=\"margin:48px auto;max-width:760px;padding:24px 28px;background:#ffffff;border-left:4px solid #FF2D6E;border-radius:0 12px 12px 0;box-shadow:0 6px 24px rgba(20,20,40,0.06);font-family:-apple-system,'SF Pro Text','Segoe UI',Roboto,Arial,sans-serif;color:#1a1a2e;\"><p style=\"margin:0 0 14px;font-size:13px;font-weight:700;letter-spacing:0.06em;text-transform:uppercase;color:#FF2D6E;\">Leia tamb\u00e9m<\/p><ul style=\"list-style:none;padding:0;margin:0;display:grid;grid-template-columns:1fr;gap:10px;\"><li><a href=\"\/pt\/effet-thermique-des-aliments\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Efeito t\u00e9rmico dos alimentos (TEF): as 69 kcal que os outros aplicativos ignoram <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">A Lean calcula o TEF em tempo real sobre seus macros. Os outros aplicativos n\u00e3o fazem isso.<\/span><\/a><\/li><li><a href=\"\/pt\/neat-depense-non-sportive\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">NEAT: como o dia a dia queima mais que o esporte <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Por que seus passos e atividades fora do esporte representam de 15 a 30% do seu gasto total.<\/span><\/a><\/li><li><a href=\"\/pt\/calculateur-deficit-calorique\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Calculadora de d\u00e9ficit cal\u00f3rico: a abordagem certa para um cutting <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Calcule seu d\u00e9ficit sobre seu TDEE real, ajustado \u00e0 gordura corporal. 3 ritmos: lento, moderado, agressivo.<\/span><\/a><\/li><li><a href=\"\/pt\/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;\">Calculadora TDEE completa: a f\u00f3rmula can\u00f4nica BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Calculadora TDEE ajustada \u00e0 gordura corporal, com a decomposi\u00e7\u00e3o das 4 pe\u00e7as metab\u00f3licas.<\/span><\/a><\/li><li><a href=\"\/pt\/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;\">Melhores aplicativos para contar calorias em 2026: 8 aplicativos testados <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Comparativo honesto: Lean, MFP, Cronometer, Yazio, Foodvisor, Lifesum, FatSecret, Noom.<\/span><\/a><\/li><\/ul><\/aside>","protected":false},"excerpt":{"rendered":"<p>Compare les 3 formules de calcul du BMR. Pourquoi Harris-Benedict 1919 et Mifflin-St Jeor 1990 se trompent sans bodyfat. L&rsquo;approche Lean sur masse maigre via BodyScan IA.<\/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":[13],"tags":[],"class_list":["post-1543","post","type-post","status-publish","format-standard","hentry","category-comparateurs"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Calcul m\u00e9tabolisme de base : la formule la plus pr\u00e9cise (2026)<\/title>\n<meta name=\"description\" content=\"Compare Harris-Benedict, Mifflin-St Jeor et l&#039;approche Lean sur masse maigre via BodyScan IA. 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