{"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\/no\/calcul-metabolisme-de-base\/","title":{"rendered":"Beregning av basalmetabolisme: den mest presise formelen (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\/no\/\"><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\/no\/\">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\/no\/\">Hjem<\/a> &nbsp;\/&nbsp; Beregning av basalmetabolisme<\/div>\n  <div class=\"eyebrow\">Kalkulator &middot; Metabolismens vitenskap<\/div>\n  <h1 id=\"title\">Beregning av basalmetabolisme.\n    <span class=\"alt\">Den mest presise formelen: Harris-Benedict 1919, Mifflin-St Jeor 1990, eller Lean med fettprosent?<\/span>\n  <\/h1>\n  <p class=\"dek\">BMR-en din er grunnmuren i kalorim\u00e5let ditt. Uten den reelle fettprosenten kan den v\u00e6re 200 til 500&nbsp;kcal\/dag feil. Sammenlign de 3 formlene, se sannheten.<\/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; Lesetid 11&nbsp;min &middot; Oppdatert 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\">Gratis nedlasting<\/span>\n  <\/div>\n\n  <div class=\"hero-bottom\">\n    <div class=\"hero-lead\">\n      BMR (basalmetabolismen) er energien kroppen din forbrenner i hvile. Harris-Benedict-formelen er fra 1919, Mifflin-St Jeor fra 1990: ingen av dem bruker fettprosenten din. Lean st\u00f8tter seg p\u00e5 den reelle fettfrie massen din m\u00e5lt med AI BodyScan, fordi det er den som bestemmer forbruket ditt.\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>D\u00e9mo interactive<\/small>Touchez l&rsquo;\u00e9cran pour explorer l&rsquo;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>D\u00e9mo interactive<\/small>Touchez l&rsquo;\u00e9cran<br>for \u00e5 utforske 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=\"Aper\u00e7u de l'application Lean avec drilldown du TDEE\">\n          <div class=\"notch\"><\/div>\n          <div class=\"phone-screen\">\n            <button class=\"phone-back\" id=\"phoneBack\" aria-label=\"Tilbake\">&#8249;<\/button>\n            <div id=\"phoneImg\" class=\"phone-bg tab-depense\" role=\"img\" aria-label=\"Aper\u00e7u Lean, onglet D\u00e9pense\"><\/div>\n            <div class=\"phone-zones\" id=\"phoneZones\">\n              <div class=\"z\" data-sub=\"BMR\"  style=\"top:11%;height:21%\" role=\"button\" tabindex=\"0\" aria-label=\"D\u00e9tail BMR\"><\/div>\n              <div class=\"z\" data-sub=\"NEAT\" style=\"top:33%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"D\u00e9tail NEAT\"><\/div>\n              <div class=\"z\" data-sub=\"EAT\"  style=\"top:50%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"D\u00e9tail EAT\"><\/div>\n              <div class=\"z\" data-sub=\"TEF\"  style=\"top:67%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"D\u00e9tail TEF\"><\/div>\n            <\/div>\n            <div class=\"phone-navbar\" id=\"phoneNav\" aria-hidden=\"false\">\n              <button data-tab=\"bilan\"     type=\"button\" aria-label=\"Onglet Bilan\"><\/button>\n              <button data-tab=\"kcal\"      type=\"button\" aria-label=\"Onglet Calories\"><\/button>\n              <button data-tab=\"depense\"   type=\"button\" aria-label=\"Forbruk-fanen\"><\/button>\n              <button data-tab=\"strategie\" type=\"button\" aria-label=\"Onglet Strat\u00e9gie\"><\/button>\n            <\/div>\n          <\/div>\n        <\/div>\n        <div class=\"phone-tabs\" role=\"tablist\" aria-label=\"Naviguer dans l'app Lean\">\n          <button data-tab=\"bilan\"     type=\"button\">Oversikt<\/button>\n          <button data-tab=\"kcal\"      type=\"button\">Kalorier<\/button>\n          <button data-tab=\"depense\"   type=\"button\" class=\"on\">D\u00e9pense<\/button>\n          <button data-tab=\"strategie\" type=\"button\">Strat\u00e9gie<\/button>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"snippet rev\">\n    <div class=\"lbl\">Raskt svar<\/div>\n    <p>Den mest presise formelen for \u00e5 beregne basalmetabolismen din er den som st\u00f8tter seg p\u00e5 din <b>masse maigre r\u00e9elle<\/b>, ikke p\u00e5 statistiske gjennomsnitt. Harris-Benedict 1919 og Mifflin-St Jeor 1990 ansl\u00e5r BMR-en din ut fra vekt, h\u00f8yde, alder og kj\u00f8nn: feilmargin p\u00e5 200 til 500&nbsp;kcal\/dag p\u00e5 muskul\u00f8se eller stillesittende profiler. Lean m\u00e5ler fettprosenten din via AI BodyScan, og bruker deretter en <b>patentert propriet\u00e6r modell<\/b> som beregner BMR-en din p\u00e5 den reelle fettfrie massen, og som rekalibrerer seg n\u00e5r kroppssammensetningen din endres.<\/p>\n  <\/div>\n<\/section>\n\n<h2 class=\"sect\"><span class=\"num\">02 &middot; Kalkulator<\/span>Sammenlign de 3 formlene p\u00e5 dine egne tall<\/h2>\n<p>Legg inn dataene dine nedenfor. De tre beregningene oppdateres direkte. Deltaen mellom Mifflin-St Jeor og Lean-tiln\u00e6rmingen (BMR p\u00e5 fettfri masse) viser feilen du akkumulerer hver dag hvis du bruker en klassisk kalkulator.<\/p>\n\n<div class=\"calc-board\" id=\"calcBoard\">\n  <div class=\"calc-inputs\">\n    <h3>Parametrene dine<\/h3>\n    <div class=\"calc-row\">\n      <label>Kj\u00f8nn<\/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>Kvinne<\/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\">Vekt (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\u00f8yde (cm)<\/label><input id=\"cHeight\" type=\"number\" min=\"130\" max=\"220\" value=\"180\"><\/div>\n    <div class=\"calc-row\">\n      <label for=\"cBf\">Fettprosent <span class=\"bf-val\" id=\"bfVal\">15&thinsp;%<\/span><\/label>\n      <div class=\"calc-bf\"><input id=\"cBf\" type=\"range\" min=\"5\" max=\"40\" step=\"1\" value=\"15\"><\/div>\n    <\/div>\n    <div class=\"calc-note\">Tu ne connais pas ton bodyfat ? Lean le calcule depuis une photo (BodyScan IA, 5 secondes) avec une pr\u00e9cision DEXA-grade.<\/div>\n  <\/div>\n\n  <div class=\"calc-results\">\n    <div class=\"calc-card\">\n      <div class=\"label\">Harris-Benedict<\/div>\n      <div class=\"formula\">Formel fra 1919, uten fettprosent<\/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, uten fettprosent<\/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-tiln\u00e6rmingen<\/div>\n      <div class=\"formula\">BMR p\u00e5 den reelle fettfrie massen din<\/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      Avvik 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  Kalkulatoren ovenfor bruker en offentlig tiln\u00e6rming for \u00e5 ansl\u00e5 BMR p\u00e5 fettfri masse. <b>Leans patenterte propriet\u00e6re modell g\u00e5r lenger:<\/b> den integrerer den metabolske tilpasningen i underskudd, den fine sammensetningen fettfri masse \/ vann \/ glykogen, og rekalibrerer seg uke for uke. <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 profilen din 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; Svakheten<\/span>Uten fettprosent hviler BMR-en din p\u00e5 35 \u00e5r gamle gjennomsnitt<\/h2>\n\n<div class=\"statement\"><p>Harris-Benedict samler alle menn p\u00e5 <b>80&nbsp;kg \/ 180&nbsp;cm \/ 32&nbsp;\u00e5r<\/b> i samme boks. En definert mann med 10&nbsp;% fettprosent og en stillesittende med 28&nbsp;% f\u00e5r <span class=\"accent\">samme tall<\/span>.<\/p><\/div>\n\n<div class=\"body\">\n<p>BMR m\u00e5ler energien kroppen din forbrenner i hvile for \u00e5 drive hjertet, hjernen, nyrene dine og opprettholde temperaturen din. Mengden avhenger nesten helt av din <b>masse maigre<\/b> (organer + muskler). Fettmassen er derimot metabolsk nesten inert: 1 kg fett forbrenner omtrent 4 kcal\/dag, mot 13 kcal\/dag for 1 kg muskel.<\/p>\n<p>Harris-Benedict (1919) og Mifflin-St Jeor (1990) vet ikke hvor den fettfrie massen din slutter og fettet ditt begynner. De ansl\u00e5r ut fra totalvekt, h\u00f8yde, alder og kj\u00f8nn, p\u00e5 en referansepopulasjon fra for et \u00e5rhundre siden for den f\u00f8rste, fra for 35 \u00e5r siden for den andre. Resultat: en muskul\u00f8s profil med 12&nbsp;% fettprosent tildeles samme BMR som en stillesittende profil med 28&nbsp;%, mens den fettfrie massen hans forbrenner 200 til 400&nbsp;kcal mer hver dag.<\/p>\n<p>P\u00e5 et vekttapsm\u00e5l akkumuleres dette avviket. \u00abKaloriunderskuddet\u00bb ditt vist til 500&nbsp;kcal\/dag av MyFitnessPal kan bli et reelt underskudd p\u00e5 200&nbsp;kcal\/dag (stagnasjon) eller et underskudd p\u00e5 800&nbsp;kcal\/dag (muskeltap). Du vet ikke hvilket tilfelle du er i, fordi start-BMR-en din var feil.<\/p>\n<\/div>\n\n<div class=\"bodyscan-illust\" style=\"margin:40px auto 8px;display:flex;flex-direction:column;align-items:center;gap:14px;max-width:200px\">\n  <div class=\"mini-phone\" style=\"max-width:200px\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-bodyscan-result.webp\" alt=\"R\u00e9sultat BodyScan IA : pourcentage de masse grasse mesur\u00e9\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\"><\/div><\/div>\n  <div class=\"bodyscan-cap\" style=\"max-width:220px;font-size:13px;line-height:1.5;text-align:center\"><b>Bodyfat r\u00e9el<\/b>Foto, 5 sekunder. Lean beregner BMR-en din p\u00e5 nytt p\u00e5 den fettfrie massen din, ikke p\u00e5 gjennomsnitt.<\/div>\n<\/div>\n\n<div class=\"body\">\n<p>Den vitenskapelige tiln\u00e6rmingen for \u00e5 beregne en mer presis BMR n\u00e5r man har fettprosenten, st\u00f8tter seg p\u00e5 <b>fettfri masse (FFM)<\/b>. Den offentlige formen av denne ligningen, sitert siden 1980-tallet i den fysiologiske litteraturen, gir omtrent 370 + 21,6 &times; fettfri masse (kg). Det er det kalkulatoren v\u00e5r ovenfor gj\u00f8r. <b>Leans patenterte propriet\u00e6re modell<\/b> g\u00e5r lenger: den integrerer en funksjon for metabolsk tilpasning, kroppsvann, glykogen, og rekalibrerer seg via AI BodyScan ved hver veiing.<\/p>\n<\/div>\n\n<div class=\"micro-cta\">\n  Vil du ha din ekte BMR p\u00e5 den reelle fettprosenten din, uten 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 gj\u00f8r din f\u00f8rste BodyScan p\u00e5 5 sekunder.\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">04 &middot; Tre profiler, tre sannheter<\/span>Avviket Mifflin mot Lean vokser med sammensetningen din<\/h2>\n<p>Tre menn med ulike kroppstyper, sammenlignede beregninger. Tallene kommer fra de tre formlene p\u00e5 80&nbsp;kg \/ 180&nbsp;cm \/ 32&nbsp;\u00e5r, ved bare \u00e5 justere fettprosenten. Du ser umiddelbart hvor Harris-Benedict og Mifflin-St Jeor tar feil.<\/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;% fettprosent &middot; fettfri 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-tiln\u00e6rming (fettfri masse)<\/span><span class=\"v\">1&thinsp;873 kcal<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Avvik Lean vs Mifflin: <b style=\"color:var(--pink)\">+93 kcal\/dag<\/b>. Over 90 dager er det nesten 10&thinsp;000 kcal \u00abglemt\u00bb av de klassiske formlene.<\/div>\n  <\/div>\n\n  <div class=\"profile-card\">\n    <h4>Gjennomsnittsprofil<\/h4>\n    <div class=\"meta\">32 \u00e5r &middot; 80&nbsp;kg &middot; 180&nbsp;cm &middot; 20&nbsp;% fettprosent &middot; fettfri 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-tiln\u00e6rming (fettfri masse)<\/span><span class=\"v\">1&thinsp;735 kcal<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Avvik Lean vs Mifflin: <b style=\"color:var(--pink)\">&minus;45 kcal\/dag<\/b>. P\u00e5 denne gjennomsnittsprofilen passer Mifflin godt (det er profilen formelen ble kalibrert p\u00e5 i 1990). Ethvert avvik fra denne profilen \u00f8ker feilen.<\/div>\n  <\/div>\n\n  <div class=\"profile-card\">\n    <h4>Stillesittende profil<\/h4>\n    <div class=\"meta\">32 \u00e5r &middot; 80&nbsp;kg &middot; 180&nbsp;cm &middot; 28&nbsp;% fettprosent &middot; fettfri 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-tiln\u00e6rming (fettfri masse)<\/span><span class=\"v\">1&thinsp;597 kcal<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Avvik Lean vs Mifflin: <b style=\"color:var(--pink)\">&minus;183 kcal\/dag<\/b>. Mifflin overvurderer BMR-en hans med 166 kcal. Det er n\u00f8yaktig derfor s\u00e5 mange overvektige profiler \u00abikke g\u00e5r ned i vekt til tross for det beregnede underskuddet\u00bb.<\/div>\n  <\/div>\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">05 &middot; \u00c6rlig sammenligning<\/span>Styrker og begrensninger ved hver formel<\/h2>\n<p>Ingen formel er ubrukelig. Hver svarer til et bruksomr\u00e5de. Det reelle sp\u00f8rsm\u00e5let: kan du m\u00e5le fettprosenten din? Hvis ja, trenger du verken Mifflin eller Harris-Benedict lenger.<\/p>\n\n<div class=\"compar-grid\">\n  <div class=\"compar-card\">\n    <h4>Harris-Benedict<\/h4>\n    <div class=\"year\">Revidert 1919 &middot; basert p\u00e5 136 fors\u00f8kspersoner<\/div>\n    <p class=\"desc\">Den store stamforelderen. Fortsatt brukt som standard av mange nettkalkulatorer, inkludert forbrukerapper. Overvurderer systematisk BMR med 5 til 10&nbsp;% p\u00e5 moderne populasjoner.<\/p>\n    <p class=\"pros\"><b>+<\/b> Sitert overalt, sammenlignbar fra \u00e9n kalkulator til en annen.<\/p>\n    <p class=\"cons\"><b>&minus;<\/b> Referansepopulasjon fra for et \u00e5rhundre 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; basert p\u00e5 498 fors\u00f8kspersoner<\/div>\n    <p class=\"desc\">Rekalibrert p\u00e5 en amerikansk populasjon p\u00e5 slutten av 80-tallet. Regnes som den \u00abmoderne referansen uten fettprosent\u00bb av kliniske ern\u00e6ringsfysiologer. Presis til <b>&plusmn;10&nbsp;%<\/b> p\u00e5 gjennomsnittsprofilen, mye mindre p\u00e5 ytterpunktene.<\/p>\n    <p class=\"pros\"><b>+<\/b> Mer presis enn Harris-Benedict p\u00e5 70&nbsp;% av profilene.<\/p>\n    <p class=\"cons\"><b>&minus;<\/b> Ingen hensyn til fettprosent. Feilmargin p\u00e5 200 til 400 kcal p\u00e5 muskul\u00f8se eller stillesittende profiler.<\/p>\n  <\/div>\n\n  <div class=\"compar-card lean\">\n    <h4>Mod\u00e8le propri\u00e9taire brevet\u00e9 Lean<\/h4>\n    <div class=\"year\">2024 &middot; kalibrert p\u00e5 10&thinsp;000+ brukere med AI BodyScan<\/div>\n    <p class=\"desc\">St\u00f8tter seg p\u00e5 <b>masse maigre r\u00e9elle<\/b> m\u00e5lt med AI BodyScan, integrerer den metabolske tilpasningen i underskudd (Lean-konvensjon 100&rarr;0&nbsp;%), rekalibrert uke for uke via veiingen og sammensetningsvariasjonen din. Ikke en papirformel: en modell som l\u00e6rer av dataene dine.<\/p>\n    <p class=\"pros\"><b>+<\/b> Presisjon &plusmn;3&nbsp;% p\u00e5 muskul\u00f8se, stillesittende, overgangsalder- og post-graviditetsprofiler. Kontinuerlig rekalibrering.<\/p>\n    <p class=\"cons\"><b>&minus;<\/b> Krever en innledende AI BodyScan (5 sekunder, gratis i Lean) og regelmessige vektdata.<\/p>\n  <\/div>\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">06 &middot; Grunnmuren<\/span>Hvorfor en presis BMR er grunnlaget for alt det andre<\/h2>\n\n<div class=\"body\">\n<p>BMR er ikke et isolert tall. Det er den <b>f\u00f8rste byggesteinen<\/b> i metabolismens kanoniske ligning: <b>TDEE = BMR + NEAT + EAT + TEF<\/b>. Den metabolske tilpasningen kommer deretter som multiplikasjonskoeffisient for BMR i underskudd (Lean-konvensjon: 100&nbsp;% = optimalt, 90&nbsp;% = 10&nbsp;% akkumulert tilpasning).<\/p>\n<p>Hvis start-BMR-en din er 150&nbsp;kcal feil, er TDEE-en din 150&nbsp;kcal feil. Vekttapsm\u00e5let ditt er 150&nbsp;kcal feil. Inntaksplanen din er 150&nbsp;kcal feil. Derfor nekter Lean \u00e5 gi deg et m\u00e5l f\u00f8r BodyScan-en din er gjort. Ikke av lune: av 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; Basalmetabolisme<\/b>Beregnet p\u00e5 den fettfrie massen din via AI BodyScan. Rekalibrert ved hver veiing.<\/div>\n<\/div>\n\n<div class=\"micro-cta\">\n  Forst\u00e5 de 4 byggesteinene i TDEE i detalj: <a href=\"https:\/\/lean-app.com\/no\/calculateur-tdee\/\">calculateur TDEE complet<\/a> &middot; <a href=\"https:\/\/lean-app.com\/no\/eat\/\">EAT (trening)<\/a> &middot; <a href=\"https:\/\/lean-app.com\/no\/neat-depense-non-sportive\/\">NEAT (skritt)<\/a> &middot; <a href=\"https:\/\/lean-app.com\/no\/effet-thermique-des-aliments\/\">TEF (ford\u00f8yelse)<\/a>.\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">07 &middot; FAQ<\/span>Alt du lurer p\u00e5 om beregning av basalmetabolisme<\/h2>\n<details class=\"faq\"><summary>Hva er den mest presise formelen for \u00e5 beregne basalmetabolismen?<\/summary><div class=\"faq-body\"><p>Den mest presise formelen er den som st\u00f8tter seg p\u00e5 den reelle fettfrie massen, ikke p\u00e5 anslag ut fra vekt, h\u00f8yde, alder og kj\u00f8nn. Uten fettprosent forblir Mifflin-St Jeor 1990 den beste tiln\u00e6rmingen (\u00b110 % p\u00e5 70 % av profilene). Med fettprosent er en ligning p\u00e5 fettfri masse av typen 370 + 21,6 \u00d7 FFM mer presis. Leans patenterte propriet\u00e6re modell forfiner ytterligere ved \u00e5 integrere den metabolske tilpasningen og kontinuerlig rekalibrering.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Hvorfor er Harris-Benedict utdatert?<\/summary><div class=\"faq-body\"><p>Den opprinnelige formelen er fra 1919, revidert i 1984. Den ble kalibrert p\u00e5 136 fors\u00f8kspersoner, i et ern\u00e6ringsmilj\u00f8 og en livsstil sv\u00e6rt ulike v\u00e5re. P\u00e5 moderne populasjoner overvurderer den BMR med 5 til 10 %. Kliniske ern\u00e6ringsfysiologer anser den som foreldet siden Mifflin-St Jeor kom i 1990.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Mifflin-St Jeor vs Harris-Benedict: hvilken konkret forskjell?<\/summary><div class=\"faq-body\"><p>For en mann p\u00e5 80 kg, 180 cm, 32 \u00e5r gir Harris-Benedict omtrent 1 855 kcal, Mifflin-St Jeor omtrent 1 780 kcal. Mifflin ligger 75 kcal under Harris-Benedict. Mifflin er globalt mer riktig, men ingen av dem skiller en muskul\u00f8s profil fra en stillesittende profil.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Hvorfor endrer fettprosenten alt ved BMR-beregningen?<\/summary><div class=\"faq-body\"><p>Fordi det er den fettfrie massen, ikke den totale massen, som bestemmer hvileforbruket. 1 kg muskel forbrenner omtrent 13 kcal\/dag, 1 kg fett omtrent 4 kcal\/dag. To personer med samme vekt, men 10 poeng fettprosent i forskjell, har BMR-er som kan avvike med 200 til 400 kcal\/dag. Ingen formel uten fettprosent kan fange det.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Hvordan beregner Lean basalmetabolismen min?<\/summary><div class=\"faq-body\"><p>Lean bruker en patentert propriet\u00e6r modell. Hovedinndataen er fettprosenten din m\u00e5lt med AI BodyScan (foto, 5 sekunder, presisjon p\u00e5 DEXA-niv\u00e5). Lean utleder den reelle fettfrie massen din fra det, beregner en BMR p\u00e5 denne fettfrie massen, og integrerer deretter en funksjon for metabolsk tilpasning som rekalibrerer seg hver uke etter variasjonen din i vekt og sammensetning. Den fettfrie massen er den dominerende faktoren; alderen modulerer resultatet fint (hvileforbruket synker litt ved konstant fettfri masse gjennom \u00e5rene).<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Hvor ofte m\u00e5 man beregne BMR-en sin p\u00e5 nytt?<\/summary><div class=\"faq-body\"><p>S\u00e5 lenge kroppssammensetningen din ikke endres (stabil vekt, stabil fettprosent), endres ikke BMR-en din heller. S\u00e5 snart du mister eller legger p\u00e5 deg 2 kg, eller fettprosenten din varierer med 2 poeng, m\u00e5 du beregne p\u00e5 nytt. Lean gj\u00f8r det automatisk ved hver BodyScan og hver veiing.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Synker BMR-en min n\u00e5r jeg g\u00e5r ned i vekt?<\/summary><div class=\"faq-body\"><p>Ja, av to grunner. F\u00f8rste, fysiske grunn: du veier mindre, alts\u00e5 har du mindre fettfri masse \u00e5 vedlikeholde, alts\u00e5 synker den mekaniske BMR-en. Andre, fysiologiske grunn: kroppen din aktiverer en metabolsk tilpasning ved langvarig kaloriunderskudd, som bremser BMR-en din 5 til 20 % under forventet verdi. Lean modellerer begge fenomenene.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Beregning av basalmetabolisme mann vs kvinne: hvilken forskjell?<\/summary><div class=\"faq-body\"><p>Ved tilsvarende vekt, h\u00f8yde og alder har kvinner i gjennomsnitt 8 til 12 % mindre fettfri masse enn menn (hormonell og morfologisk forskjell). BMR-en deres er derfor strukturelt lavere, i st\u00f8rrelsesorden 150 til 250 kcal\/dag. De to klassiske formlene bruker en ulik kj\u00f8nnskonstant. I Lean er det den m\u00e5lte fettfrie massen som taler, uavhengig av kj\u00f8nn.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Basalmetabolisme i hvile vs under innsats: hva er forskjellen?<\/summary><div class=\"faq-body\"><p>BMR er strengt tatt forbruket i hvile (liggende, fastende, termisk n\u00f8ytralitet). N\u00e5r du g\u00e5r, legger du til NEAT (Non-Exercise Activity Thermogenesis). N\u00e5r du trener, legger du til EAT (Exercise Activity Thermogenesis). N\u00e5r du spiser, legger du til TEF (Thermic Effect of Food). Summen er TDEE-en din.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Hvilken formel bruker kalkulatoren ovenfor for &lsquo;Lean-tiln\u00e6rmingen&rsquo;?<\/summary><div class=\"faq-body\"><p>En offentlig ligning p\u00e5 fettfri masse, sitert i den fysiologiske litteraturen: BMR \u2248 370 + 21,6 \u00d7 fettfri masse (kg). Den fettfrie massen avledes av vekten og fettprosenten din. Det er en nyttig tiln\u00e6rming for \u00e5 forst\u00e5 effekten av fettprosenten. Leans patenterte propriet\u00e6re modell i appen g\u00e5r lenger (metabolsk tilpasning, vann, glykogen, kontinuerlig rekalibrering).<\/p><\/div><\/details>\n\n<div class=\"sources\">\n  <h4>Vitenskapelige 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 BMR-en din p\u00e5 den reelle fettprosenten din<\/h3>\n  <p>AI BodyScan p\u00e5 5 sekunder. Kontinuerlig rekalibrering. Uten formel fra 1919 eller 1990. Gratis nedlasting, 7 dagers 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. 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De andre appene gj\u00f8r det ikke.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/no\/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 forbrenner mer enn treningen <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Hvorfor skrittene og de ikke-sportslige aktivitetene dine utgj\u00f8r 15 til 30 % av det totale forbruket ditt.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/no\/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;\">Kalkulator for kaloriunderskudd: riktig tiln\u00e6rming for en deff <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Beregn underskuddet ditt p\u00e5 din reelle fettprosentbevisste TDEE. 3 tempoer langsomt\/moderat\/aggressivt.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/no\/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;\">Komplett TDEE-kalkulator: den kanoniske formelen BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Fettprosentbevisst TDEE-kalkulator med oppdeling av de 4 metabolske byggesteinene.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/no\/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 apper for \u00e5 telle kalorier i 2026: 8 apper 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 av basalmetabolisme: den mest presise formelen (2026)<\/title>\n<meta name=\"description\" content=\"Sammenlign Harris-Benedict, Mifflin-St Jeor og Lean-tiln\u00e6rmingen p\u00e5 fettfri masse via AI BodyScan. 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