{"id":1543,"date":"2026-05-26T20:50:10","date_gmt":"2026-05-26T20:50:10","guid":{"rendered":"https:\/\/lean-app.com\/?p=1543"},"modified":"2026-09-05T10:39:35","modified_gmt":"2026-09-05T10:39:35","slug":"calcul-metabolisme-de-base","status":"publish","type":"post","link":"https:\/\/lean-app.com\/de\/calcul-metabolisme-de-base\/","title":{"rendered":"Grundumsatz-Berechnung: die genaueste Formel (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\/de\/\"><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\/de\/\">Startseite<\/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\/de\/\">Startseite<\/a> &nbsp;\/&nbsp; Grundumsatz-Berechnung<\/div>\n  <div class=\"eyebrow\">Rechner &middot; Stoffwechsel-Wissenschaft<\/div>\n  <h1 id=\"title\">Grundumsatz-Berechnung.\n    <span class=\"alt\">Die pr\u00e4ziseste Formel: Harris-Benedict 1919, Mifflin-St Jeor 1990, oder Lean mit K\u00f6rperfett?<\/span>\n  <\/h1>\n  <p class=\"dek\">Dein BMR ist das Fundament deines Kalorienziels. Ohne echtes K\u00f6rperfett kann er um 200 bis 500&nbsp;kcal\/Tag falsch sein. Vergleiche die 3 Formeln, sieh die Wahrheit.<\/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>Das Lean-Team<\/strong> &middot; 11&nbsp;Min. Lesezeit &middot; Aktualisiert am 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\">Kostenloser Download<\/span>\n  <\/div>\n\n  <div class=\"hero-bottom\">\n    <div class=\"hero-lead\">\n      Der BMR (Grundumsatz) ist die Energie, die dein K\u00f6rper in Ruhe verbrennt. Die Harris-Benedict-Formel stammt von 1919, die von Mifflin-St Jeor von 1990: Keine nutzt dein K\u00f6rperfett. Lean st\u00fctzt sich auf deine echte, per KI-BodyScan gemessene Magermasse, weil sie deinen Verbrauch bestimmt.\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>Interaktive Demo<\/small>Tippe auf den Bildschirm und erkunde die 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>Interaktive Demo<\/small>Tippe auf den Bildschirm<br>und erkunde die 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=\"Vorschau der Lean-App mit TDEE-Drilldown\">\n          <div class=\"notch\"><\/div>\n          <div class=\"phone-screen\">\n            <button class=\"phone-back\" id=\"phoneBack\" aria-label=\"Zur&uuml;ck\">&#8249;<\/button>\n            <div id=\"phoneImg\" class=\"phone-bg tab-depense\" role=\"img\" aria-label=\"Lean-Vorschau, Tab Verbrauch\"><\/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=\"Tab Bilanz\"><\/button>\n              <button data-tab=\"kcal\"      type=\"button\" aria-label=\"Tab Kalorien\"><\/button>\n              <button data-tab=\"depense\"   type=\"button\" aria-label=\"Tab Verbrauch\"><\/button>\n              <button data-tab=\"strategie\" type=\"button\" aria-label=\"Tab Strategie\"><\/button>\n            <\/div>\n          <\/div>\n        <\/div>\n        <div class=\"phone-tabs\" role=\"tablist\" aria-label=\"Durch die Lean-App navigieren\">\n          <button data-tab=\"bilan\"     type=\"button\">Bilanz<\/button>\n          <button data-tab=\"kcal\"      type=\"button\">Kalorien<\/button>\n          <button data-tab=\"depense\"   type=\"button\" class=\"on\">Verbrauch<\/button>\n          <button data-tab=\"strategie\" type=\"button\">Strategie<\/button>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"snippet rev\">\n    <div class=\"lbl\">Schnelle Antwort<\/div>\n    <p>Die pr\u00e4ziseste Formel zur Berechnung deines Grundumsatzes ist die, die sich auf deine <b>echte Magermasse<\/b>st\u00fctzt, nicht auf statistische Mittelwerte. Harris-Benedict 1919 und Mifflin-St Jeor 1990 sch\u00e4tzen deinen BMR aus Gewicht, Gr\u00f6\u00dfe, Alter und Geschlecht: Fehlermarge 200 bis 500&nbsp;kcal\/Tag bei muskul\u00f6sen oder sitzenden Profilen. Lean misst dein K\u00f6rperfett per KI-BodyScan und wendet dann ein <b>patentiertes propriet\u00e4res Modell<\/b> an, das deinen BMR auf der echten Magermasse berechnet und sich neu kalibriert, wenn sich deine K\u00f6rperkomposition \u00e4ndert.<\/p>\n  <\/div>\n<\/section>\n\n<h2 class=\"sect\"><span class=\"num\">02 &middot; Rechner<\/span>Vergleiche die 3 Formeln auf deinen eigenen Zahlen<\/h2>\n<p>Gib unten deine Daten ein. Die drei Berechnungen aktualisieren sich live. Das Delta zwischen Mifflin-St Jeor und dem Lean-Ansatz (BMR auf Magermasse) zeigt den Fehler, den du jeden Tag ansammelst, wenn du einen klassischen Rechner nutzt.<\/p>\n\n<div class=\"calc-board\" id=\"calcBoard\">\n  <div class=\"calc-inputs\">\n    <h3>Deine Parameter<\/h3>\n    <div class=\"calc-row\">\n      <label>Geschlecht<\/label>\n      <div class=\"calc-sex\">\n        <label><input type=\"radio\" name=\"sex\" value=\"M\" checked><span>Mann<\/span><\/label>\n        <label><input type=\"radio\" name=\"sex\" value=\"F\"><span>Frau<\/span><\/label>\n      <\/div>\n    <\/div>\n    <div class=\"calc-row\"><label for=\"cAge\">Alter (Jahre)<\/label><input id=\"cAge\" type=\"number\" min=\"14\" max=\"90\" value=\"32\"><\/div>\n    <div class=\"calc-row\"><label for=\"cWeight\">Gewicht (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\">Gr\u00f6\u00dfe (cm)<\/label><input id=\"cHeight\" type=\"number\" min=\"130\" max=\"220\" value=\"180\"><\/div>\n    <div class=\"calc-row\">\n      <label for=\"cBf\">K\u00f6rperfettanteil <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\">Du kennst dein K\u00f6rperfett nicht? Lean berechnet es aus einem Foto (KI-BodyScan, 5 Sekunden) mit DEXA-grade Pr\u00e4zision.<\/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\">Formel von 1919, ohne K\u00f6rperfett<\/div>\n      <div class=\"result\"><span id=\"rHB\">0<\/span><span class=\"unit\">kcal\/Tag<\/span><\/div>\n    <\/div>\n    <div class=\"calc-card\">\n      <div class=\"label\">Mifflin-St Jeor<\/div>\n      <div class=\"formula\">Formel von 1990, ohne K\u00f6rperfett<\/div>\n      <div class=\"result\"><span id=\"rMSJ\">0<\/span><span class=\"unit\">kcal\/Tag<\/span><\/div>\n    <\/div>\n    <div class=\"calc-card lean\">\n      <div class=\"label\">Lean-Ansatz<\/div>\n      <div class=\"formula\">BMR auf deiner echten Magermasse<\/div>\n      <div class=\"result\"><span id=\"rLEAN\">0<\/span><span class=\"unit\">kcal\/Tag<\/span><\/div>\n    <\/div>\n    <div class=\"calc-delta\" id=\"calcDelta\">\n      Abstand Lean vs. Mifflin-St Jeor: <b id=\"deltaVal\">0 kcal\/Tag<\/b>\n    <\/div>\n  <\/div>\n<\/div>\n\n<div class=\"micro-cta\">\n  Der Rechner oben nutzt einen \u00f6ffentlichen Ansatz, um den BMR auf Magermasse zu sch\u00e4tzen. <b>Das patentierte propriet\u00e4re Lean-Modell geht weiter:<\/b> Es integriert die metabolische Anpassung im Defizit, die feine Zusammensetzung Magermasse \/ Wasser \/ Glykogen, und kalibriert sich Woche f\u00fcr Woche neu. <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\">Teste es auf deinem Profil in 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; Die Schwachstelle<\/span>Ohne K\u00f6rperfett beruht dein BMR auf 35 Jahre alten Mittelwerten<\/h2>\n\n<div class=\"statement\"><p>Harris-Benedict steckt alle M\u00e4nner mit <b>80&nbsp;kg \/ 180&nbsp;cm \/ 32&nbsp;Jahren<\/b> in dieselbe Schublade. Ein Definierter mit 10&nbsp;% K\u00f6rperfett und ein Sitzender mit 28&nbsp;% bekommen <span class=\"accent\">dieselbe Zahl<\/span>.<\/p><\/div>\n\n<div class=\"body\">\n<p>Der BMR misst die Energie, die dein K\u00f6rper in Ruhe verbrennt, um Herz, Gehirn und Nieren zu betreiben und deine Temperatur zu halten. Die Menge h\u00e4ngt fast vollst\u00e4ndig von deiner <b>Magermasse<\/b> ab (Organe + Muskeln). Die Fettmasse ist dagegen metabolisch fast tr\u00e4ge: 1 kg Fett verbrennt etwa 4 kcal\/Tag, gegen\u00fcber 13 kcal\/Tag f\u00fcr 1 kg Muskel.<\/p>\n<p>Harris-Benedict (1919) und Mifflin-St Jeor (1990) wissen nicht, wo deine Magermasse endet und dein Fett beginnt. Sie sch\u00e4tzen aus Gesamtgewicht, Gr\u00f6\u00dfe, Alter und Geschlecht, auf einer Referenzpopulation von vor einem Jahrhundert bei der ersten, von vor 35 Jahren bei der zweiten. Ergebnis: Ein muskul\u00f6ses Profil mit 12&nbsp;% K\u00f6rperfett bekommt denselben BMR wie ein sitzendes Profil mit 28&nbsp;%, obwohl seine Magermasse jeden Tag 200 bis 400&nbsp;kcal mehr verbrennt.<\/p>\n<p>Bei einem Abnehmziel summiert sich dieser Abstand. Dein von MyFitnessPal angezeigtes &bdquo;Kaloriendefizit&ldquo; von 500&nbsp;kcal\/Tag kann ein reales Defizit von 200&nbsp;kcal\/Tag werden (Stillstand) oder eines von 800&nbsp;kcal\/Tag (Muskelabbau). Du wei\u00dft nicht, in welchem Fall du bist, weil dein Ausgangs-BMR falsch war.<\/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>Echtes K\u00f6rperfett<\/b>Foto, 5 Sekunden. Lean berechnet deinen BMR auf deiner Magermasse neu, nicht auf Mittelwerten.<\/div>\n<\/div>\n\n<div class=\"body\">\n<p>Der wissenschaftliche Ansatz f\u00fcr einen pr\u00e4ziseren BMR, wenn man das K\u00f6rperfett kennt, st\u00fctzt sich auf die <b>Magermasse (FFM)<\/b>. Die \u00f6ffentliche Form dieser Gleichung, seit den 1980ern in der physiologischen Literatur zitiert, ergibt etwa 370 + 21,6 &times; Magermasse (kg). Genau das macht unser Rechner oben. <b>Das patentierte propriet\u00e4re Lean-Modell<\/b> geht weiter: Es integriert eine Funktion f\u00fcr metabolische Anpassung, das K\u00f6rperwasser, das Glykogen, und kalibriert sich via KI-BodyScan bei jeder W\u00e4gung neu.<\/p>\n<\/div>\n\n<div class=\"micro-cta\">\n  Du willst deinen echten BMR auf deinem echten K\u00f6rperfett, ohne Papierformel? <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\">Installiere Lean<\/a> und mach deinen ersten BodyScan in 5 Sekunden.\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">04 &middot; Drei Profile, drei Wahrheiten<\/span>Der Abstand Mifflin gegen Lean w\u00e4chst mit deiner Komposition<\/h2>\n<p>Drei M\u00e4nner verschiedener Morphotypen, Berechnungen im Vergleich. Die Zahlen kommen aus den drei Formeln bei 80&nbsp;kg \/ 180&nbsp;cm \/ 32&nbsp;Jahren, nur das K\u00f6rperfett wird angepasst. Du siehst sofort, wo Harris-Benedict und Mifflin-St Jeor danebenliegen.<\/p>\n\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>Sportliches Profil<\/h4>\n    <div class=\"meta\">32 Jahre &middot; 80&nbsp;kg &middot; 180&nbsp;cm &middot; 12&nbsp;% K\u00f6rperfett &middot; Magermasse 70,4&nbsp;kg<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Harris-Benedict 1919<\/span><span class=\"v\">1.855 kcal<\/span><\/div>\n      <div class=\"rw\"><span>Mifflin-St Jeor 1990<\/span><span class=\"v\">1.780 kcal<\/span><\/div>\n      <div class=\"rw lean\"><span>Lean-Ansatz (Magermasse)<\/span><span class=\"v\">1.873 kcal<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Abstand Lean vs. Mifflin: <b style=\"color:var(--pink)\">+93 kcal\/Tag<\/b>. \u00dcber 90 Tage sind das fast 10&thinsp;000 kcal, die die klassischen Formeln &bdquo;vergessen&ldquo;.<\/div>\n  <\/div>\n\n  <div class=\"profile-card\">\n    <h4>Durchschnittsprofil<\/h4>\n    <div class=\"meta\">32 Jahre &middot; 80&nbsp;kg &middot; 180&nbsp;cm &middot; 20&nbsp;% K\u00f6rperfett &middot; Magermasse 64&nbsp;kg<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Harris-Benedict 1919<\/span><span class=\"v\">1.855 kcal<\/span><\/div>\n      <div class=\"rw\"><span>Mifflin-St Jeor 1990<\/span><span class=\"v\">1.780 kcal<\/span><\/div>\n      <div class=\"rw lean\"><span>Lean-Ansatz (Magermasse)<\/span><span class=\"v\">1.735 kcal<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Abstand Lean vs. Mifflin: <b style=\"color:var(--pink)\">&minus;45 kcal\/Tag<\/b>. Auf diesem Durchschnittsprofil passt Mifflin gut (auf diesem Profil wurde die Formel 1990 kalibriert). Jede Abweichung von diesem Profil erh\u00f6ht den Fehler.<\/div>\n  <\/div>\n\n  <div class=\"profile-card\">\n    <h4>Sitzendes Profil<\/h4>\n    <div class=\"meta\">32 Jahre &middot; 80&nbsp;kg &middot; 180&nbsp;cm &middot; 28&nbsp;% K\u00f6rperfett &middot; Magermasse 57,6&nbsp;kg<\/div>\n    <div class=\"rows\">\n      <div class=\"rw\"><span>Harris-Benedict 1919<\/span><span class=\"v\">1.855 kcal<\/span><\/div>\n      <div class=\"rw\"><span>Mifflin-St Jeor 1990<\/span><span class=\"v\">1.780 kcal<\/span><\/div>\n      <div class=\"rw lean\"><span>Lean-Ansatz (Magermasse)<\/span><span class=\"v\">1.597 kcal<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Abstand Lean vs. Mifflin: <b style=\"color:var(--pink)\">&minus;183 kcal\/Tag<\/b>. Mifflin \u00fcbersch\u00e4tzt seinen BMR um 166 kcal. Genau deshalb &bdquo;nehmen so viele \u00fcbergewichtige Profile trotz berechnetem Defizit nicht ab&ldquo;.<\/div>\n  <\/div>\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">05 &middot; Ehrlicher Vergleich<\/span>St\u00e4rken und Grenzen jeder Formel<\/h2>\n<p>Keine Formel ist nutzlos. Jede beantwortet einen Anwendungsfall. Die echte Frage: Kannst du dein K\u00f6rperfett messen? Wenn ja, brauchst du weder Mifflin noch Harris-Benedict mehr.<\/p>\n\n<div class=\"compar-grid\">\n  <div class=\"compar-card\">\n    <h4>Harris-Benedict<\/h4>\n    <div class=\"year\">Revidiert 1919 &middot; basiert auf 136 Probanden<\/div>\n    <p class=\"desc\">Die gro\u00dfe Ahnin. Von vielen Online-Rechnern noch standardm\u00e4\u00dfig genutzt, auch von Mainstream-Apps. \u00dcbersch\u00e4tzt den BMR auf modernen Populationen systematisch um 5 bis 10&nbsp;%.<\/p>\n    <p class=\"pros\"><b>+<\/b> \u00dcberall zitiert, von Rechner zu Rechner vergleichbar.<\/p>\n    <p class=\"cons\"><b>&minus;<\/b> Referenzpopulation von vor einem Jahrhundert. \u00dcbersch\u00e4tzt die meisten Profile um 100 bis 200 kcal\/Tag.<\/p>\n  <\/div>\n\n  <div class=\"compar-card\">\n    <h4>Mifflin-St Jeor<\/h4>\n    <div class=\"year\">1990 &middot; basiert auf 498 Probanden<\/div>\n    <p class=\"desc\">Ende der 80er auf einer amerikanischen Population rekalibriert. Gilt bei klinischen Ern\u00e4hrungsberatern als die Referenz &bdquo;modern ohne K\u00f6rperfett&ldquo;. Pr\u00e4zise auf <b>&plusmn;10&nbsp;%<\/b> beim Durchschnittsprofil, deutlich weniger an den Extremen.<\/p>\n    <p class=\"pros\"><b>+<\/b> Pr\u00e4ziser als Harris-Benedict bei 70&nbsp;% der Profile.<\/p>\n    <p class=\"cons\"><b>&minus;<\/b> Keine Ber\u00fccksichtigung des K\u00f6rperfetts. Fehlermarge 200 bis 400 kcal bei muskul\u00f6sen oder sitzenden Profilen.<\/p>\n  <\/div>\n\n  <div class=\"compar-card lean\">\n    <h4>Patentiertes propriet\u00e4res Lean-Modell<\/h4>\n    <div class=\"year\">2024 &middot; kalibriert auf 10&thinsp;000+ Nutzern mit KI-BodyScan<\/div>\n    <p class=\"desc\">St\u00fctzt sich auf die <b>echte Magermasse<\/b> per KI-BodyScan gemessene Magermasse, integriert die metabolische Anpassung im Defizit (Lean-Konvention 100&rarr;0&nbsp;%), rekalibriert Woche f\u00fcr Woche \u00fcber deine W\u00e4gung und deine Kompositionsver\u00e4nderung. Keine Papierformel: ein Modell, das aus deinen Daten lernt.<\/p>\n    <p class=\"pros\"><b>+<\/b> Pr\u00e4zision &plusmn;3&nbsp;% bei muskul\u00f6sen und sitzenden Profilen, Menopause, nach Schwangerschaft. Kontinuierliche Rekalibrierung.<\/p>\n    <p class=\"cons\"><b>&minus;<\/b> Erfordert einen ersten KI-BodyScan (5 Sekunden, kostenlos in Lean) und regelm\u00e4\u00dfige Gewichtsdaten.<\/p>\n  <\/div>\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">06 &middot; Das Fundament<\/span>Warum ein pr\u00e4ziser BMR der Sockel von allem anderen ist<\/h2>\n\n<div class=\"body\">\n<p>Der BMR ist keine isolierte Zahl. Er ist der <b>erste Baustein<\/b> der kanonischen Gleichung des Stoffwechsels: <b>TDEE = BMR + NEAT + EAT + TEF<\/b>. Die metabolische Anpassung kommt danach als multiplikativer Koeffizient des BMR im Defizit (Lean-Konvention: 100&nbsp;% = optimal, 90&nbsp;% = 10&nbsp;% akkumulierte Anpassung).<\/p>\n<p>Ist dein Ausgangs-BMR um 150&nbsp;kcal falsch, ist dein TDEE um 150&nbsp;kcal falsch. Dein Abnehmziel ist um 150&nbsp;kcal falsch. Dein Ern\u00e4hrungsplan ist um 150&nbsp;kcal falsch. Deshalb weigert sich Lean, dir ein Ziel zu geben, solange dein BodyScan nicht gemacht ist. Keine Laune: Konsequenz.<\/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; Grundumsatz<\/b>Berechnet auf deiner Magermasse via KI-BodyScan. Bei jeder W\u00e4gung rekalibriert.<\/div>\n<\/div>\n\n<div class=\"micro-cta\">\n  Die 4 Bausteine des TDEE im Detail verstehen: <a href=\"https:\/\/lean-app.com\/de\/calculateur-tdee\/\">kompletter TDEE-Rechner<\/a> &middot; <a href=\"https:\/\/lean-app.com\/de\/eat\/\">EAT (Sport)<\/a> &middot; <a href=\"https:\/\/lean-app.com\/de\/neat-depense-non-sportive\/\">NEAT (Schritte)<\/a> &middot; <a href=\"https:\/\/lean-app.com\/de\/effet-thermique-des-aliments\/\">TEF (Verdauung)<\/a>.\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">07 &middot; FAQ<\/span>Alles, was du dich \u00fcber die Grundumsatz-Berechnung fragst<\/h2>\n<details class=\"faq\"><summary>Was ist die pr\u00e4ziseste Formel zur Berechnung des Grundumsatzes?<\/summary><div class=\"faq-body\"><p>Die pr\u00e4ziseste Formel ist die, die sich auf die echte Magermasse st\u00fctzt, nicht auf Sch\u00e4tzungen aus Gewicht, Gr\u00f6\u00dfe, Alter und Geschlecht. Ohne K\u00f6rperfett bleibt Mifflin-St Jeor 1990 die beste N\u00e4herung (\u00b110 % bei 70 % der Profile). Mit K\u00f6rperfett ist eine Magermasse-Gleichung wie 370 + 21,6 \u00d7 FFM pr\u00e4ziser. Das patentierte propriet\u00e4re Lean-Modell verfeinert weiter mit metabolischer Anpassung und kontinuierlicher Rekalibrierung.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Warum ist Harris-Benedict \u00fcberholt?<\/summary><div class=\"faq-body\"><p>Die Original-Formel stammt von 1919, revidiert 1984. Sie wurde auf 136 Probanden kalibriert, in einem Ern\u00e4hrungsumfeld und Lebensstil, die sich stark von unseren unterscheiden. Auf modernen Populationen \u00fcbersch\u00e4tzt sie den BMR um 5 bis 10 %. Klinische Ern\u00e4hrungsberater halten sie seit der Ankunft von Mifflin-St Jeor 1990 f\u00fcr obsolet.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Mifflin-St Jeor vs. Harris-Benedict: Was ist der konkrete Unterschied?<\/summary><div class=\"faq-body\"><p>Bei einem Mann mit 80 kg, 180 cm, 32 Jahren ergibt Harris-Benedict etwa 1 855 kcal, Mifflin-St Jeor etwa 1 780 kcal. Mifflin liegt rund 75 kcal unter Harris-Benedict. Mifflin ist insgesamt genauer, aber keine der beiden unterscheidet ein muskul\u00f6ses von einem sitzenden Profil.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Warum \u00e4ndert das K\u00f6rperfett alles an der BMR-Berechnung?<\/summary><div class=\"faq-body\"><p>Weil die Magermasse, nicht die Gesamtmasse, den Verbrauch in Ruhe bestimmt. 1 kg Muskel verbrennt etwa 13 kcal\/Tag, 1 kg Fett etwa 4 kcal\/Tag. Zwei Personen mit demselben Gewicht, aber 10 Punkten K\u00f6rperfett-Unterschied, k\u00f6nnen BMRs haben, die um 200 bis 400 kcal\/Tag auseinanderliegen. Keine Formel ohne K\u00f6rperfett kann das erfassen.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Wie berechnet Lean meinen Grundumsatz?<\/summary><div class=\"faq-body\"><p>Lean nutzt ein patentiertes propriet\u00e4res Modell. Die Haupteingabe ist dein per KI-BodyScan gemessenes K\u00f6rperfett (Foto, 5 Sekunden, DEXA-grade Pr\u00e4zision). Lean leitet daraus deine echte Magermasse ab, berechnet einen BMR auf dieser Magermasse und integriert dann eine Funktion f\u00fcr metabolische Anpassung, die sich jede Woche nach deiner Gewichts- und Kompositionsver\u00e4nderung rekalibriert. Die Magermasse ist der dominante Faktor; das Alter moduliert das Ergebnis fein (der Ruheverbrauch sinkt bei konstanter Magermasse leicht \u00fcber die Jahre).<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Wie oft sollte man seinen BMR neu berechnen?<\/summary><div class=\"faq-body\"><p>Solange sich deine K\u00f6rperkomposition nicht bewegt (Gewicht stabil, K\u00f6rperfett stabil), bewegt sich auch dein BMR nicht. Sobald du 2 kg verlierst oder zunimmst, oder dein K\u00f6rperfett um 2 Punkte variiert, musst du neu rechnen. Lean macht das automatisch bei jedem BodyScan und jeder W\u00e4gung.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Sinkt mein BMR, wenn ich abnehme?<\/summary><div class=\"faq-body\"><p>Ja, aus zwei Gr\u00fcnden. Erster, physischer Grund: Du wiegst weniger, hast also weniger Magermasse zu versorgen, also sinkt der mechanische BMR. Zweiter, physiologischer Grund: Dein K\u00f6rper aktiviert im anhaltenden Kaloriendefizit eine metabolische Anpassung, die deinen BMR um 5 bis 20 % unter seinen erwarteten Wert bremst. Lean modelliert beide Ph\u00e4nomene.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Grundumsatz-Berechnung Mann vs. Frau: Was ist der Unterschied?<\/summary><div class=\"faq-body\"><p>Bei gleichem Gewicht, Gr\u00f6\u00dfe und Alter haben Frauen im Schnitt 8 bis 12 % weniger Magermasse als M\u00e4nner (hormoneller und morphologischer Unterschied). Ihr BMR ist daher strukturell niedriger, in der Gr\u00f6\u00dfenordnung von 150 bis 250 kcal\/Tag. Die beiden klassischen Formeln nutzen eine unterschiedliche Geschlechtskonstante. Bei Lean spricht die gemessene Magermasse, unabh\u00e4ngig vom Geschlecht.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Grundumsatz in Ruhe vs. bei Belastung: Was ist der Unterschied?<\/summary><div class=\"faq-body\"><p>Der BMR ist strikt der Verbrauch in Ruhe (liegend, n\u00fcchtern, thermische Neutralit\u00e4t). Wenn du gehst, kommt das NEAT dazu (Non-Exercise Activity Thermogenesis). Beim Sport kommt das EAT dazu (Exercise Activity Thermogenesis). Beim Essen kommt das TEF dazu (Thermic Effect of Food). Die Summe ist dein TDEE.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Welche Formel nutzt der Rechner oben f\u00fcr den &sbquo;Lean-Ansatz&lsquo;?<\/summary><div class=\"faq-body\"><p>Eine \u00f6ffentliche Magermasse-Gleichung, in der physiologischen Literatur zitiert: BMR \u2248 370 + 21,6 \u00d7 Magermasse (kg). Die Magermasse wird aus deinem Gewicht und deinem K\u00f6rperfett abgeleitet. Eine n\u00fctzliche N\u00e4herung, um den Effekt des K\u00f6rperfetts zu verstehen. Das patentierte propriet\u00e4re Lean-Modell in der App geht weiter (metabolische Anpassung, Wasser, Glykogen, kontinuierliche Rekalibrierung).<\/p><\/div><\/details>\n\n<div class=\"sources\">\n  <h4>Wissenschaftliche Quellen<\/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>Hol dir deinen BMR auf deinem echten K\u00f6rperfett<\/h3>\n  <p>KI-BodyScan in 5 Sekunden. Kontinuierliche Rekalibrierung. Ohne Formel von 1919 oder 1990. Kostenloser Download, 7 Tage Testphase im Jahresabo.<\/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{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebApplication\",\"@id\":\"https:\/\/lean-app.com\/calcul-metabolisme-de-base\/#calculator\",\"name\":\"Calculateur du m\u00e9tabolisme de base (BMR)\",\"applicationCategory\":\"HealthApplication\",\"operatingSystem\":\"Web\",\"url\":\"https:\/\/lean-app.com\/calcul-metabolisme-de-base\/\",\"description\":\"Calculateur du BMR comparant Harris-Benedict 1919, Mifflin-St Jeor 1990 et approche sur masse maigre (avec bodyfat).\",\"inLanguage\":\"fr-FR\",\"offers\":{\"@type\":\"Offer\",\"price\":\"0\",\"priceCurrency\":\"EUR\"}},{\"@type\":\"FAQPage\",\"@id\":\"https:\/\/lean-app.com\/calcul-metabolisme-de-base\/#faq\",\"mainEntity\":[{\"@type\":\"Question\",\"name\":\"Quelle est la formule la plus pr\u00e9cise pour calculer le m\u00e9tabolisme de base ?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"La formule la plus pr\u00e9cise est celle qui s'appuie sur la masse maigre r\u00e9elle, pas sur des estimations depuis poids, taille, \u00e2ge et sexe. 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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.\"}},{\"@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. 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Andere Apps tun das nicht.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/de\/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: Wie der Alltag mehr verbrennt als der Sport <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Warum deine Schritte und Nicht-Sport-Aktivit\u00e4ten 15 bis 30 % deines Gesamtverbrauchs ausmachen.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/de\/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;\">Kaloriendefizit-Rechner: der richtige Ansatz f\u00fcr die Di\u00e4t <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Berechne dein Defizit auf deinem echten bodyfat-aware TDEE. 3 Tempi: langsam\/moderat\/aggressiv.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/de\/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;\">Kompletter TDEE-Rechner: die kanonische Formel BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Bodyfat-aware TDEE-Rechner mit Breakdown der 4 metabolischen Bausteine.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/de\/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;\">Beste Kalorienz\u00e4hler-Apps 2026: 8 Apps getestet <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Ehrlicher Vergleich: 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>Berechnung des Grundumsatzes: Harris-Benedict und BMR - Lean<\/title>\n<meta name=\"description\" content=\"Vergleiche Harris-Benedict, Mifflin-St Jeor und den Lean-Ansatz auf Magermasse via KI-BodyScan. 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