{"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\/da\/calcul-metabolisme-de-base\/","title":{"rendered":"Beregning af basalstofskifte: den mest pr\u00e6cise 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\/da\/\"><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\/da\/\">Hjem<\/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\/da\/\">Hjem<\/a> &nbsp;\/&nbsp; Beregning af basalstofskifte<\/div>\n  <div class=\"eyebrow\">Beregner &middot; Stofskiftets videnskab<\/div>\n  <h1 id=\"title\">Beregning af basalstofskifte.\n    <span class=\"alt\">Den mest pr\u00e6cise formel: Harris-Benedict 1919, Mifflin-St Jeor 1990, eller Lean med fedtprocent?<\/span>\n  <\/h1>\n  <p class=\"dek\">Din BMR er fundamentet for dit kaloriem\u00e5l. Uden den reelle fedtprocent kan den v\u00e6re 200 til 500&nbsp;kcal\/dag forkert. Sammenlign de 3 formler, se sandheden.<\/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>Lean-teamet<\/strong> &middot; L\u00e6setid 11&nbsp;min &middot; Opdateret 26. maj 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\">Gratis download<\/span>\n  <\/div>\n\n  <div class=\"hero-bottom\">\n    <div class=\"hero-lead\">\n      BMR (basalstofskiftet) er den energi, din krop forbr\u00e6nder i hvile. Harris-Benedict-formlen er fra 1919, Mifflin-St Jeor fra 1990: ingen af dem bruger din fedtprocent. Lean bygger p\u00e5 din reelle fedtfri masse m\u00e5lt med AI BodyScan, fordi det er den, der bestemmer dit forbrug.\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>Interaktiv demo<\/small>Tryk p\u00e5 sk\u00e6rmen for at udforske appen<\/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>Interaktiv demo<\/small>Tryk p\u00e5 sk\u00e6rmen<br>for at udforske appen<\/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=\"Oversigt over Lean-appen med drilldown af TDEE\">\n          <div class=\"notch\"><\/div>\n          <div class=\"phone-screen\">\n            <button class=\"phone-back\" id=\"phoneBack\" aria-label=\"Tilbage\">&#8249;<\/button>\n            <div id=\"phoneImg\" class=\"phone-bg tab-depense\" role=\"img\" aria-label=\"Lean-oversigt, Forbrug-fanen\"><\/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-detaljer\"><\/div>\n              <div class=\"z\" data-sub=\"NEAT\" style=\"top:33%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"NEAT-detaljer\"><\/div>\n              <div class=\"z\" data-sub=\"EAT\"  style=\"top:50%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"EAT-detaljer\"><\/div>\n              <div class=\"z\" data-sub=\"TEF\"  style=\"top:67%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"TEF-detaljer\"><\/div>\n            <\/div>\n            <div class=\"phone-navbar\" id=\"phoneNav\" aria-hidden=\"false\">\n              <button data-tab=\"bilan\"     type=\"button\" aria-label=\"Oversigt-fanen\"><\/button>\n              <button data-tab=\"kcal\"      type=\"button\" aria-label=\"Kalorier-fanen\"><\/button>\n              <button data-tab=\"depense\"   type=\"button\" aria-label=\"Forbrug-fanen\"><\/button>\n              <button data-tab=\"strategie\" type=\"button\" aria-label=\"Strategi-fanen\"><\/button>\n            <\/div>\n          <\/div>\n        <\/div>\n        <div class=\"phone-tabs\" role=\"tablist\" aria-label=\"Naviger i Lean-appen\">\n          <button data-tab=\"bilan\"     type=\"button\">Oversigt<\/button>\n          <button data-tab=\"kcal\"      type=\"button\">Kalorier<\/button>\n          <button data-tab=\"depense\"   type=\"button\" class=\"on\">Forbrug<\/button>\n          <button data-tab=\"strategie\" type=\"button\">Strategi<\/button>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"snippet rev\">\n    <div class=\"lbl\">Hurtigt svar<\/div>\n    <p>Den mest pr\u00e6cise formel til at beregne dit basalstofskifte er den, der bygger p\u00e5 din <b>reel fedtfri masse<\/b>, ikke p\u00e5 statistiske gennemsnit. Harris-Benedict 1919 og Mifflin-St Jeor 1990 estimerer din BMR ud fra v\u00e6gt, h\u00f8jde, alder og k\u00f8n: fejlmargin p\u00e5 200 til 500&nbsp;kcal\/dag p\u00e5 muskul\u00f8se eller stillesiddende profiler. Lean m\u00e5ler din fedtprocent via AI BodyScan og anvender derefter en <b>patenteret egenudviklet model<\/b> som beregner din BMR p\u00e5 den reelle fedtfri masse, og som rekalibrerer sig, n\u00e5r din kropssammens\u00e6tning \u00e6ndrer sig.<\/p>\n  <\/div>\n<\/section>\n\n<h2 class=\"sect\"><span class=\"num\">02 &middot; Beregner<\/span>Sammenlign de 3 formler p\u00e5 dine egne tal<\/h2>\n<p>Indtast dine data nedenfor. De tre beregninger opdateres live. Deltaet mellem Mifflin-St Jeor og Lean-tilgangen (BMR p\u00e5 fedtfri masse) viser den fejl, du akkumulerer hver dag, hvis du bruger en klassisk beregner.<\/p>\n\n<div class=\"calc-board\" id=\"calcBoard\">\n  <div class=\"calc-inputs\">\n    <h3>Dine parametre<\/h3>\n    <div class=\"calc-row\">\n      <label>K\u00f8n<\/label>\n      <div class=\"calc-sex\">\n        <label><input type=\"radio\" name=\"sex\" value=\"M\" checked><span>Mand<\/span><\/label>\n        <label><input type=\"radio\" name=\"sex\" value=\"F\"><span>Kvinde<\/span><\/label>\n      <\/div>\n    <\/div>\n    <div class=\"calc-row\"><label for=\"cAge\">Alder (\u00e5r)<\/label><input id=\"cAge\" type=\"number\" min=\"14\" max=\"90\" value=\"32\"><\/div>\n    <div class=\"calc-row\"><label for=\"cWeight\">V\u00e6gt (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\">H\u00f8jde (cm)<\/label><input id=\"cHeight\" type=\"number\" min=\"130\" max=\"220\" value=\"180\"><\/div>\n    <div class=\"calc-row\">\n      <label for=\"cBf\">Fedtprocent <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\">Kender du ikke din fedtprocent? Lean beregner den fra et foto (AI BodyScan, 5 sekunder) med pr\u00e6cision p\u00e5 DEXA-niveau.<\/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 fra 1919, uden fedtprocent<\/div>\n      <div class=\"result\"><span id=\"rHB\">0<\/span><span class=\"unit\">kcal\/dag<\/span><\/div>\n    <\/div>\n    <div class=\"calc-card\">\n      <div class=\"label\">Mifflin-St Jeor<\/div>\n      <div class=\"formula\">Formel fra 1990, uden fedtprocent<\/div>\n      <div class=\"result\"><span id=\"rMSJ\">0<\/span><span class=\"unit\">kcal\/dag<\/span><\/div>\n    <\/div>\n    <div class=\"calc-card lean\">\n      <div class=\"label\">Lean-tilgangen<\/div>\n      <div class=\"formula\">BMR p\u00e5 din reelle fedtfri masse<\/div>\n      <div class=\"result\"><span id=\"rLEAN\">0<\/span><span class=\"unit\">kcal\/dag<\/span><\/div>\n    <\/div>\n    <div class=\"calc-delta\" id=\"calcDelta\">\n      Forskel Lean vs Mifflin-St Jeor: <b id=\"deltaVal\">0 kcal\/dag<\/b>\n    <\/div>\n  <\/div>\n<\/div>\n\n<div class=\"micro-cta\">\n  Beregneren ovenfor bruger en offentlig tilgang til at estimere BMR p\u00e5 fedtfri masse. <b>Leans patenterede egenudviklede model g\u00e5r l\u00e6ngere:<\/b> den integrerer den metaboliske tilpasning i underskud, den fine sammens\u00e6tning fedtfri masse \/ vand \/ glykogen, og rekalibrerer sig uge for uge. <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\">Test p\u00e5 din profil i 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; Svagheden<\/span>Uden fedtprocent hviler din BMR p\u00e5 35 \u00e5r gamle gennemsnit<\/h2>\n\n<div class=\"statement\"><p>Harris-Benedict samler alle m\u00e6nd p\u00e5 <b>80&nbsp;kg \/ 180&nbsp;cm \/ 32&nbsp;\u00e5r<\/b> i samme kasse. En defineret mand med 10&nbsp;% fedtprocent og en stillesiddende med 28&nbsp;% f\u00e5r <span class=\"accent\">samme tal<\/span>.<\/p><\/div>\n\n<div class=\"body\">\n<p>BMR m\u00e5ler den energi, din krop forbr\u00e6nder i hvile for at drive dit hjerte, din hjerne, dine nyrer og opretholde din temperatur. M\u00e6ngden afh\u00e6nger n\u00e6sten helt af din <b>fedtfri masse<\/b> (organer + muskler). Fedtmassen er derimod metabolisk n\u00e6sten inaktiv: 1 kg fedt forbr\u00e6nder cirka 4 kcal\/dag, mod 13 kcal\/dag for 1 kg muskel.<\/p>\n<p>Harris-Benedict (1919) og Mifflin-St Jeor (1990) ved ikke, hvor din fedtfri masse slutter, og dit fedt begynder. De estimerer ud fra totalv\u00e6gt, h\u00f8jde, alder og k\u00f8n, p\u00e5 en referencepopulation fra et \u00e5rhundrede siden for den f\u00f8rste, fra 35 \u00e5r siden for den anden. Resultat: en muskul\u00f8s profil med 12&nbsp;% fedtprocent tildeles samme BMR som en stillesiddende profil med 28&nbsp;%, selv om hans fedtfri masse forbr\u00e6nder 200 til 400&nbsp;kcal mere hver dag.<\/p>\n<p>P\u00e5 et v\u00e6gttabsm\u00e5l akkumuleres denne forskel. Dit \u00abkalorieunderskud\u00bb vist til 500&nbsp;kcal\/dag af MyFitnessPal kan blive et reelt underskud p\u00e5 200&nbsp;kcal\/dag (stagnation) eller et underskud p\u00e5 800&nbsp;kcal\/dag (muskeltab). Du ved ikke, hvilket tilf\u00e6lde du er i, fordi din start-BMR var forkert.<\/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>Reel fedtprocent<\/b>Foto, 5 sekunder. Lean genberegner din BMR p\u00e5 din fedtfri masse, ikke p\u00e5 gennemsnit.<\/div>\n<\/div>\n\n<div class=\"body\">\n<p>Den videnskabelige tilgang til at beregne en mere pr\u00e6cis BMR, n\u00e5r man har fedtprocenten, bygger p\u00e5 den <b>fedtfri masse (FFM)<\/b>. Den offentlige form af denne ligning, citeret siden 1980'erne i den fysiologiske litteratur, giver cirka 370 + 21,6 &times; fedtfri masse (kg). Det er det, vores beregner ovenfor g\u00f8r. <b>Leans patenterede egenudviklede model<\/b> g\u00e5r l\u00e6ngere: den integrerer en funktion for metabolisk tilpasning, kropsvand, glykogen, og rekalibrerer sig via AI BodyScan ved hver vejning.<\/p>\n<\/div>\n\n<div class=\"micro-cta\">\n  Vil du have din rigtige BMR p\u00e5 din reelle fedtprocent, uden papirformel? <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\">Installer Lean<\/a> og lav din f\u00f8rste BodyScan p\u00e5 5 sekunder.\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">04 &middot; Tre profiler, tre sandheder<\/span>Forskellen Mifflin mod Lean vokser med din sammens\u00e6tning<\/h2>\n<p>Tre m\u00e6nd med forskellige kropstyper, sammenlignede beregninger. Tallene kommer fra de tre formler p\u00e5 80&nbsp;kg \/ 180&nbsp;cm \/ 32&nbsp;\u00e5r, ved kun at justere fedtprocenten. Du ser straks, hvor Harris-Benedict og Mifflin-St Jeor tager fejl.<\/p>\n\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>Sportslig profil<\/h4>\n    <div class=\"meta\">32 \u00e5r &middot; 80&nbsp;kg &middot; 180&nbsp;cm &middot; 12&nbsp;% fedtprocent &middot; fedtfri masse 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>Lean-tilgang (fedtfri masse)<\/span><span class=\"v\">1&thinsp;873 kcal<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Forskel Lean vs Mifflin: <b style=\"color:var(--pink)\">+93 kcal\/dag<\/b>. Over 90 dage er det n\u00e6sten 10&thinsp;000 kcal \u00abglemt\u00bb af de klassiske formler.<\/div>\n  <\/div>\n\n  <div class=\"profile-card\">\n    <h4>Gennemsnitsprofil<\/h4>\n    <div class=\"meta\">32 \u00e5r &middot; 80&nbsp;kg &middot; 180&nbsp;cm &middot; 20&nbsp;% fedtprocent &middot; fedtfri masse 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>Lean-tilgang (fedtfri masse)<\/span><span class=\"v\">1&thinsp;735 kcal<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Forskel Lean vs Mifflin: <b style=\"color:var(--pink)\">&minus;45 kcal\/dag<\/b>. P\u00e5 denne gennemsnitsprofil passer Mifflin godt (det er den profil, formlen blev kalibreret p\u00e5 i 1990). Enhver afvigelse fra den profil \u00f8ger fejlen.<\/div>\n  <\/div>\n\n  <div class=\"profile-card\">\n    <h4>Stillesiddende profil<\/h4>\n    <div class=\"meta\">32 \u00e5r &middot; 80&nbsp;kg &middot; 180&nbsp;cm &middot; 28&nbsp;% fedtprocent &middot; fedtfri masse 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>Lean-tilgang (fedtfri masse)<\/span><span class=\"v\">1&thinsp;597 kcal<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Forskel Lean vs Mifflin: <b style=\"color:var(--pink)\">&minus;183 kcal\/dag<\/b>. Mifflin overvurderer hans BMR med 166 kcal. Det er pr\u00e6cis derfor, s\u00e5 mange overv\u00e6gtige profiler \u00abikke taber sig trods det beregnede underskud\u00bb.<\/div>\n  <\/div>\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">05 &middot; \u00c6rlig sammenligning<\/span>Styrker og begr\u00e6nsninger ved hver formel<\/h2>\n<p>Ingen formel er ubrugelig. Hver svarer til en brugssituation. Det reelle sp\u00f8rgsm\u00e5l: kan du m\u00e5le din fedtprocent? Hvis ja, har du hverken brug for Mifflin eller Harris-Benedict l\u00e6ngere.<\/p>\n\n<div class=\"compar-grid\">\n  <div class=\"compar-card\">\n    <h4>Harris-Benedict<\/h4>\n    <div class=\"year\">Revideret 1919 &middot; baseret p\u00e5 136 fors\u00f8gspersoner<\/div>\n    <p class=\"desc\">Den store stammoder. Bruges stadig som standard af mange online-beregnere, inklusive forbruger-apps. Overvurderer systematisk BMR med 5 til 10&nbsp;% p\u00e5 moderne populationer.<\/p>\n    <p class=\"pros\"><b>+<\/b> Citeret overalt, sammenlignelig fra den ene beregner til den anden.<\/p>\n    <p class=\"cons\"><b>&minus;<\/b> Referencepopulation fra et \u00e5rhundrede siden. Overvurderer de fleste profiler med 100 til 200 kcal\/dag.<\/p>\n  <\/div>\n\n  <div class=\"compar-card\">\n    <h4>Mifflin-St Jeor<\/h4>\n    <div class=\"year\">1990 &middot; baseret p\u00e5 498 fors\u00f8gspersoner<\/div>\n    <p class=\"desc\">Rekalibreret p\u00e5 en amerikansk population i slutningen af 80'erne. Betragtes som \u00abden moderne reference uden fedtprocent\u00bb af kliniske di\u00e6tister. Pr\u00e6cis til <b>&plusmn;10&nbsp;%<\/b> p\u00e5 gennemsnitsprofilen, meget mindre p\u00e5 yderpunkterne.<\/p>\n    <p class=\"pros\"><b>+<\/b> Mere pr\u00e6cis end Harris-Benedict p\u00e5 70&nbsp;% af profilerne.<\/p>\n    <p class=\"cons\"><b>&minus;<\/b> Ingen hensyn til fedtprocent. Fejlmargin p\u00e5 200 til 400 kcal p\u00e5 muskul\u00f8se eller stillesiddende profiler.<\/p>\n  <\/div>\n\n  <div class=\"compar-card lean\">\n    <h4>Leans patenterede egenudviklede model<\/h4>\n    <div class=\"year\">2024 &middot; kalibreret p\u00e5 10&thinsp;000+ brugere med AI BodyScan<\/div>\n    <p class=\"desc\">Bygger p\u00e5 den <b>reel fedtfri masse<\/b> m\u00e5lt med AI BodyScan, integrerer den metaboliske tilpasning i underskud (Lean-konvention 100&rarr;0&nbsp;%), rekalibreret uge for uge via din vejning og din sammens\u00e6tningsvariation. Ikke en papirformel: en model, der l\u00e6rer af dine data.<\/p>\n    <p class=\"pros\"><b>+<\/b> Pr\u00e6cision &plusmn;3&nbsp;% p\u00e5 muskul\u00f8se, stillesiddende, overgangsalder- og post-graviditetsprofiler. Kontinuerlig rekalibrering.<\/p>\n    <p class=\"cons\"><b>&minus;<\/b> Kr\u00e6ver en indledende AI BodyScan (5 sekunder, gratis i Lean) og regelm\u00e6ssige v\u00e6gtdata.<\/p>\n  <\/div>\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">06 &middot; Fundamentet<\/span>Hvorfor en pr\u00e6cis BMR er grundlaget for alt det andet<\/h2>\n\n<div class=\"body\">\n<p>BMR er ikke et isoleret tal. Det er den <b>f\u00f8rste byggesten<\/b> i stofskiftets kanoniske ligning: <b>TDEE = BMR + NEAT + EAT + TEF<\/b>. Den metaboliske tilpasning kommer derefter som multiplikationskoefficient for BMR i underskud (Lean-konvention: 100&nbsp;% = optimalt, 90&nbsp;% = 10&nbsp;% akkumuleret tilpasning).<\/p>\n<p>Er din start-BMR 150&nbsp;kcal forkert, er din TDEE 150&nbsp;kcal forkert. Dit v\u00e6gttabsm\u00e5l er 150&nbsp;kcal forkert. Din indtagsplan er 150&nbsp;kcal forkert. Derfor n\u00e6gter Lean at give dig et m\u00e5l, f\u00f8r din BodyScan er lavet. Ikke af lune: af konsekvens.<\/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; Basalstofskifte<\/b>Beregnet p\u00e5 din fedtfri masse via AI BodyScan. Rekalibreret ved hver vejning.<\/div>\n<\/div>\n\n<div class=\"micro-cta\">\n  Forst\u00e5 de 4 byggesten i TDEE i detaljer: <a href=\"https:\/\/lean-app.com\/da\/calculateur-tdee\/\">komplet TDEE-beregner<\/a> u00b7 <a href=\"https:\/\/lean-app.com\/da\/eat\/\">EAT (tr\u00e6ning)<\/a> u00b7 <a href=\"https:\/\/lean-app.com\/da\/neat-depense-non-sportive\/\">NEAT (skridt)<\/a> u00b7 <a href=\"https:\/\/lean-app.com\/da\/effet-thermique-des-aliments\/\">TEF (ford\u00f8jelse)<\/a>.\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">07 &middot; FAQ<\/span>Alt du sp\u00f8rger dig selv om beregning af basalstofskifte<\/h2>\n<details class=\"faq\"><summary>Hvilken er den mest pr\u00e6cise formel til at beregne basalstofskiftet?<\/summary><div class=\"faq-body\"><p>Den mest pr\u00e6cise formel er den, der bygger p\u00e5 den reelle fedtfri masse, ikke p\u00e5 estimater ud fra v\u00e6gt, h\u00f8jde, alder og k\u00f8n. Uden fedtprocent er Mifflin-St Jeor 1990 stadig den bedste tiln\u00e6rmelse (\u00b110 % p\u00e5 70 % af profilerne). Med fedtprocent er en ligning p\u00e5 fedtfri masse af typen 370 + 21,6 \u00d7 FFM mere pr\u00e6cis. Leans patenterede egenudviklede model forfiner yderligere ved at integrere den metaboliske tilpasning og kontinuerlig rekalibrering.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Hvorfor er Harris-Benedict for\u00e6ldet?<\/summary><div class=\"faq-body\"><p>Den oprindelige formel er fra 1919, revideret i 1984. Den blev kalibreret p\u00e5 136 fors\u00f8gspersoner, i et ern\u00e6ringsmilj\u00f8 og en livsstil meget forskellig fra vores. P\u00e5 moderne populationer overvurderer den BMR med 5 til 10 %. Kliniske di\u00e6tister anser den for for\u00e6ldet siden Mifflin-St Jeor kom i 1990.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Mifflin-St Jeor vs Harris-Benedict: hvilken konkret forskel?<\/summary><div class=\"faq-body\"><p>For en mand p\u00e5 80 kg, 180 cm, 32 \u00e5r giver Harris-Benedict cirka 1 855 kcal, Mifflin-St Jeor cirka 1 780 kcal. Mifflin ligger 75 kcal under Harris-Benedict. Mifflin er globalt mere rigtig, men ingen af dem skelner en muskul\u00f8s profil fra en stillesiddende profil.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Hvorfor \u00e6ndrer fedtprocenten alt for BMR-beregningen?<\/summary><div class=\"faq-body\"><p>Fordi det er den fedtfri masse, ikke den totale masse, der bestemmer forbruget i hvile. 1 kg muskel forbr\u00e6nder cirka 13 kcal\/dag, 1 kg fedt cirka 4 kcal\/dag. To personer med samme v\u00e6gt, men 10 point fedtprocent i forskel, har BMR'er, der kan afvige med 200 til 400 kcal\/dag. Ingen formel uden fedtprocent kan fange det.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Hvordan beregner Lean mit basalstofskifte?<\/summary><div class=\"faq-body\"><p>Lean bruger en patenteret egenudviklet model. Den vigtigste inputdata er din fedtprocent m\u00e5lt med AI BodyScan (foto, 5 sekunder, pr\u00e6cision p\u00e5 DEXA-niveau). Lean udleder din reelle fedtfri masse af det, beregner en BMR p\u00e5 denne fedtfri masse og integrerer derefter en funktion for metabolisk tilpasning, der rekalibrerer sig hver uge efter din variation i v\u00e6gt og sammens\u00e6tning. Den fedtfri masse er den dominerende faktor; alderen modulerer resultatet fint (forbruget i hvile falder let ved konstant fedtfri masse gennem \u00e5rene).<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Hvor ofte skal man genberegne sin BMR?<\/summary><div class=\"faq-body\"><p>S\u00e5 l\u00e6nge din kropssammens\u00e6tning ikke \u00e6ndrer sig (stabil v\u00e6gt, stabil fedtprocent), \u00e6ndrer din BMR sig heller ikke. S\u00e5 snart du taber eller tager 2 kg p\u00e5, eller din fedtprocent varierer med 2 point, skal du genberegne. Lean g\u00f8r det automatisk ved hver BodyScan og hver vejning.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Falder min BMR, n\u00e5r jeg taber mig?<\/summary><div class=\"faq-body\"><p>Ja, af to grunde. F\u00f8rste, fysiske grund: du vejer mindre, s\u00e5 du har mindre fedtfri masse at vedligeholde, s\u00e5 den mekaniske BMR falder. Anden, fysiologiske grund: din krop aktiverer en metabolisk tilpasning ved langvarigt kalorieunderskud, som bremser din BMR 5 til 20 % under den forventede v\u00e6rdi. Lean modellerer begge f\u00e6nomener.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Beregning af basalstofskifte mand vs kvinde: hvilken forskel?<\/summary><div class=\"faq-body\"><p>Ved tilsvarende v\u00e6gt, h\u00f8jde og alder har kvinder i gennemsnit 8 til 12 % mindre fedtfri masse end m\u00e6nd (hormonel og morfologisk forskel). Deres BMR er derfor strukturelt lavere, i st\u00f8rrelsesordenen 150 til 250 kcal\/dag. De to klassiske formler bruger en forskellig k\u00f8nskonstant. I Lean er det den m\u00e5lte fedtfri masse, der taler, uafh\u00e6ngigt af k\u00f8n.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Basalstofskifte i hvile vs under anstrengelse: hvad er forskellen?<\/summary><div class=\"faq-body\"><p>BMR er strengt forbruget i hvile (liggende, fastende, termisk neutralitet). N\u00e5r du g\u00e5r, l\u00e6gger du NEAT (Non-Exercise Activity Thermogenesis) til. N\u00e5r du dyrker sport, l\u00e6gger du EAT (Exercise Activity Thermogenesis) til. N\u00e5r du spiser, l\u00e6gger du TEF (Thermic Effect of Food) til. Summen er din TDEE.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Hvilken formel bruger beregneren ovenfor til &lsquo;Lean-tilgangen&rsquo;?<\/summary><div class=\"faq-body\"><p>En offentlig ligning p\u00e5 fedtfri masse, citeret i den fysiologiske litteratur: BMR \u2248 370 + 21,6 \u00d7 fedtfri masse (kg). Den fedtfri masse udledes af din v\u00e6gt og din fedtprocent. Det er en nyttig tiln\u00e6rmelse til at forst\u00e5 fedtprocentens effekt. Leans patenterede egenudviklede model i appen g\u00e5r l\u00e6ngere (metabolisk tilpasning, vand, glykogen, kontinuerlig rekalibrering).<\/p><\/div><\/details>\n\n<div class=\"sources\">\n  <h4>Videnskabelige kilder<\/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>F\u00e5 din BMR p\u00e5 din reelle fedtprocent<\/h3>\n  <p>AI BodyScan p\u00e5 5 sekunder. Kontinuerlig rekalibrering. Uden formel fra 1919 eller 1990. Gratis download, 7 dages pr\u00f8veperiode p\u00e5 \u00e5rsabonnementet.<\/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. 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.\"}},{\"@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.\"}},{\"@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.\"}},{\"@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.\"}},{\"@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).\"}},{\"@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.\"}},{\"@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.\"}},{\"@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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C'est une approximation utile pour comprendre l'effet du bodyfat. 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Det g\u00f8r de andre apps ikke.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/da\/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: hvordan hverdagen forbr\u00e6nder mere end sporten <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Hvorfor dine skridt og ikke-sportslige aktiviteter udg\u00f8r 15 til 30 % af dit samlede forbrug.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/da\/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;\">Beregner for kalorieunderskud: den rette tilgang til et cut <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Beregn dit underskud p\u00e5 din reelle fedtprocentbevidste TDEE. 3 tempi langsomt\/moderat\/aggressivt.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/da\/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;\">Komplet TDEE-beregner: den kanoniske formel BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Fedtprocentbevidst TDEE-beregner med opdeling af de 4 metaboliske byggesten.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/da\/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;\">De bedste apps til at t\u00e6lle kalorier i 2026: 8 apps testet <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">\u00c6rlig sammenligning: 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>Beregning af basalstofskifte: Harris-Benedict og BMR - Lean<\/title>\n<meta name=\"description\" content=\"Sammenlign Harris-Benedict, Mifflin-St Jeor og Lean-tilgangen p\u00e5 fedtfri masse via AI BodyScan. 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