{"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\/es\/calcul-metabolisme-de-base\/","title":{"rendered":"C\u00e1lculo del metabolismo basal: la f\u00f3rmula m\u00e1s precisa (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\/es\/\"><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\/es\/\">Inicio<\/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\/es\/\">Inicio<\/a> &nbsp;\/&nbsp; C\u00e1lculo del metabolismo basal<\/div>\n  <div class=\"eyebrow\">Calculadora &middot; Ciencia del metabolismo<\/div>\n  <h1 id=\"title\">C\u00e1lculo del metabolismo basal.\n    <span class=\"alt\">La f\u00f3rmula m\u00e1s precisa: \u00bfHarris-Benedict 1919, Mifflin-St Jeor 1990, o Lean con grasa corporal?<\/span>\n  <\/h1>\n  <p class=\"dek\">Tu BMR es la base de tu objetivo cal\u00f3rico. Sin la grasa corporal real, puede estar equivocado en 200 a 500&nbsp;kcal\/d\u00eda. Compara las 3 f\u00f3rmulas, mira la verdad.<\/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>El equipo Lean<\/strong> &middot; 11&nbsp;min de lectura &middot; Actualizado el 26 de mayo de 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\">Descarga gratuita<\/span>\n  <\/div>\n\n  <div class=\"hero-bottom\">\n    <div class=\"hero-lead\">\n      El BMR (metabolismo basal) es la energ\u00eda que tu cuerpo quema en reposo. La f\u00f3rmula de Harris-Benedict data de 1919, la de Mifflin-St Jeor de 1990: ninguna usa tu grasa corporal. Lean se apoya en tu masa magra real medida por BodyScan IA, porque es ella la que determina tu gasto.\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>Demostraci\u00f3n interactiva<\/small>Toca la pantalla para explorar la aplicaci\u00f3n<\/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>Demostraci\u00f3n interactiva<\/small>Toca la pantalla<br>para explorar la aplicaci\u00f3n<\/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=\"Vista general de la aplicaci\u00f3n Lean con desglose del TDEE\">\n          <div class=\"notch\"><\/div>\n          <div class=\"phone-screen\">\n            <button class=\"phone-back\" id=\"phoneBack\" aria-label=\"Volver\">&#8249;<\/button>\n            <div id=\"phoneImg\" class=\"phone-bg tab-depense\" role=\"img\" aria-label=\"Vista Lean, pesta\u00f1a Gasto\"><\/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=\"Detalle BMR\"><\/div>\n              <div class=\"z\" data-sub=\"NEAT\" style=\"top:33%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"Detalle NEAT\"><\/div>\n              <div class=\"z\" data-sub=\"EAT\"  style=\"top:50%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"Detalle EAT\"><\/div>\n              <div class=\"z\" data-sub=\"TEF\"  style=\"top:67%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"Detalle TEF\"><\/div>\n            <\/div>\n            <div class=\"phone-navbar\" id=\"phoneNav\" aria-hidden=\"false\">\n              <button data-tab=\"bilan\"     type=\"button\" aria-label=\"Pesta\u00f1a Balance\"><\/button>\n              <button data-tab=\"kcal\"      type=\"button\" aria-label=\"Pesta\u00f1a Calor\u00edas\"><\/button>\n              <button data-tab=\"depense\"   type=\"button\" aria-label=\"Pesta\u00f1a Gasto\"><\/button>\n              <button data-tab=\"strategie\" type=\"button\" aria-label=\"Pesta\u00f1a Estrategia\"><\/button>\n            <\/div>\n          <\/div>\n        <\/div>\n        <div class=\"phone-tabs\" role=\"tablist\" aria-label=\"Navegar por la aplicaci\u00f3n Lean\">\n          <button data-tab=\"bilan\"     type=\"button\">Balance<\/button>\n          <button data-tab=\"kcal\"      type=\"button\">Calor\u00edas<\/button>\n          <button data-tab=\"depense\"   type=\"button\" class=\"on\">Gasto<\/button>\n          <button data-tab=\"strategie\" type=\"button\">Estrategia<\/button>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"snippet rev\">\n    <div class=\"lbl\">Respuesta r\u00e1pida<\/div>\n    <p>La f\u00f3rmula m\u00e1s precisa para calcular tu metabolismo basal es la que se apoya en tu <b>masa magra real<\/b>, no en medias estad\u00edsticas. Harris-Benedict 1919 y Mifflin-St Jeor 1990 estiman tu BMR desde peso, altura, edad y sexo: margen de error de 200 a 500&nbsp;kcal\/d\u00eda en perfiles musculosos o sedentarios. Lean mide tu grasa corporal v\u00eda BodyScan IA, y aplica despu\u00e9s un <b>modelo propietario patentado<\/b> que calcula tu BMR sobre la masa magra real, y que se recalibra cuando tu composici\u00f3n corporal cambia.<\/p>\n  <\/div>\n<\/section>\n\n<h2 class=\"sect\"><span class=\"num\">02 &middot; Calculadora<\/span>Compara las 3 f\u00f3rmulas con tus propias cifras<\/h2>\n<p>Introduce tus datos abajo. Los tres c\u00e1lculos se actualizan en directo. El delta entre Mifflin-St Jeor y el enfoque Lean (BMR sobre masa magra) muestra el error que acumulas cada d\u00eda si usas una calculadora cl\u00e1sica.<\/p>\n\n<div class=\"calc-board\" id=\"calcBoard\">\n  <div class=\"calc-inputs\">\n    <h3>Tus par\u00e1metros<\/h3>\n    <div class=\"calc-row\">\n      <label>Sexo<\/label>\n      <div class=\"calc-sex\">\n        <label><input type=\"radio\" name=\"sex\" value=\"M\" checked><span>Hombre<\/span><\/label>\n        <label><input type=\"radio\" name=\"sex\" value=\"F\"><span>Mujer<\/span><\/label>\n      <\/div>\n    <\/div>\n    <div class=\"calc-row\"><label for=\"cAge\">Edad (a\u00f1os)<\/label><input id=\"cAge\" type=\"number\" min=\"14\" max=\"90\" value=\"32\"><\/div>\n    <div class=\"calc-row\"><label for=\"cWeight\">Peso (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\">Altura (cm)<\/label><input id=\"cHeight\" type=\"number\" min=\"130\" max=\"220\" value=\"180\"><\/div>\n    <div class=\"calc-row\">\n      <label for=\"cBf\">Porcentaje de grasa corporal <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\">\u00bfNo conoces tu grasa corporal? Lean la calcula desde una foto (BodyScan IA, 5 segundos) con precisi\u00f3n grado DEXA.<\/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\">F\u00f3rmula de 1919, sin grasa corporal<\/div>\n      <div class=\"result\"><span id=\"rHB\">0<\/span><span class=\"unit\">kcal\/d\u00eda<\/span><\/div>\n    <\/div>\n    <div class=\"calc-card\">\n      <div class=\"label\">Mifflin-St Jeor<\/div>\n      <div class=\"formula\">F\u00f3rmula de 1990, sin grasa corporal<\/div>\n      <div class=\"result\"><span id=\"rMSJ\">0<\/span><span class=\"unit\">kcal\/d\u00eda<\/span><\/div>\n    <\/div>\n    <div class=\"calc-card lean\">\n      <div class=\"label\">Enfoque Lean<\/div>\n      <div class=\"formula\">BMR sobre tu masa magra real<\/div>\n      <div class=\"result\"><span id=\"rLEAN\">0<\/span><span class=\"unit\">kcal\/d\u00eda<\/span><\/div>\n    <\/div>\n    <div class=\"calc-delta\" id=\"calcDelta\">\n      Diferencia Lean vs Mifflin-St Jeor: <b id=\"deltaVal\">0 kcal\/d\u00eda<\/b>\n    <\/div>\n  <\/div>\n<\/div>\n\n<div class=\"micro-cta\">\n  La calculadora de arriba usa un enfoque p\u00fablico para estimar el BMR sobre masa magra. <b>El modelo propietario patentado de Lean va m\u00e1s lejos:<\/b> integra la adaptaci\u00f3n metab\u00f3lica en d\u00e9ficit, la composici\u00f3n fina masa magra \/ agua \/ gluc\u00f3geno, y se recalibra semana tras semana. <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\">Pru\u00e9balo con tu perfil en 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; El fallo<\/span>Sin grasa corporal, tu BMR se apoya en medias de hace 35 a\u00f1os<\/h2>\n\n<div class=\"statement\"><p>Harris-Benedict mete a todos los hombres de <b>80&nbsp;kg \/ 180&nbsp;cm \/ 32&nbsp;a\u00f1os<\/b> en la misma caja. Un definido al 10&nbsp;% de grasa y un sedentario al 28&nbsp;% reciben <span class=\"accent\">la misma cifra<\/span>.<\/p><\/div>\n\n<div class=\"body\">\n<p>El BMR mide la energ\u00eda que tu cuerpo quema en reposo para hacer funcionar tu coraz\u00f3n, tu cerebro, tus ri\u00f1ones y mantener tu temperatura. La cantidad depende casi por completo de tu <b>masa magra<\/b> (\u00f3rganos + m\u00fasculos). La masa grasa, en cambio, es metab\u00f3licamente casi inerte: 1 kg de grasa quema unas 4 kcal\/d\u00eda, frente a 13 kcal\/d\u00eda por 1 kg de m\u00fasculo.<\/p>\n<p>Harris-Benedict (1919) y Mifflin-St Jeor (1990) no saben d\u00f3nde acaba tu masa magra y d\u00f3nde empieza tu grasa. Estiman desde peso total, altura, edad y sexo, sobre una poblaci\u00f3n de referencia de hace un siglo la primera, de hace 35 a\u00f1os la segunda. Resultado: un perfil musculoso al 12&nbsp;% de grasa recibe el mismo BMR que un perfil sedentario al 28&nbsp;%, cuando su masa magra quema 200 a 400&nbsp;kcal m\u00e1s cada d\u00eda.<\/p>\n<p>Con un objetivo de p\u00e9rdida de peso, esta diferencia se acumula. Tu &laquo;d\u00e9ficit cal\u00f3rico&raquo; mostrado a 500&nbsp;kcal\/d\u00eda por MyFitnessPal puede volverse un d\u00e9ficit real de 200&nbsp;kcal\/d\u00eda (estancamiento) o un d\u00e9ficit de 800&nbsp;kcal\/d\u00eda (p\u00e9rdida de m\u00fasculo). No sabes en qu\u00e9 caso est\u00e1s, porque tu BMR de partida era falso.<\/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>Grasa corporal real<\/b>Foto, 5 segundos. Lean recalcula tu BMR sobre tu masa magra, no sobre medias.<\/div>\n<\/div>\n\n<div class=\"body\">\n<p>El enfoque cient\u00edfico para calcular un BMR m\u00e1s preciso cuando se conoce la grasa corporal se apoya en la <b>masa magra (FFM)<\/b>. La forma p\u00fablica de esta ecuaci\u00f3n, citada desde los a\u00f1os 80 en la literatura fisiol\u00f3gica, da alrededor de 370 + 21,6 &times; masa magra (kg). Es lo que hace nuestra calculadora de arriba. <b>El modelo propietario patentado de Lean<\/b> va m\u00e1s lejos: integra una funci\u00f3n de adaptaci\u00f3n metab\u00f3lica, el agua corporal, el gluc\u00f3geno, y se recalibra v\u00eda BodyScan IA en cada pesada.<\/p>\n<\/div>\n\n<div class=\"micro-cta\">\n  \u00bfQuieres tu BMR real sobre tu grasa corporal real, sin f\u00f3rmula de papel? <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\">Instala Lean<\/a> y haz tu primer BodyScan en 5 segundos.\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">04 &middot; Tres perfiles, tres verdades<\/span>La diferencia Mifflin contra Lean crece con tu composici\u00f3n<\/h2>\n<p>Tres hombres de morfotipos distintos, c\u00e1lculos comparados. Las cifras salen de las tres f\u00f3rmulas con 80&nbsp;kg \/ 180&nbsp;cm \/ 32&nbsp;a\u00f1os, ajustando solo la grasa corporal. Ves de inmediato d\u00f3nde se equivocan Harris-Benedict y Mifflin-St Jeor.<\/p>\n\n<div class=\"profile-grid\">\n  <div class=\"profile-card\">\n    <h4>Perfil deportivo<\/h4>\n    <div class=\"meta\">32 a\u00f1os &middot; 80&nbsp;kg &middot; 180&nbsp;cm &middot; 12&nbsp;% de grasa &middot; masa magra 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>Enfoque Lean (masa magra)<\/span><span class=\"v\">1&thinsp;873 kcal<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Diferencia Lean vs Mifflin: <b style=\"color:var(--pink)\">+93 kcal\/d\u00eda<\/b>. En 90 d\u00edas, son casi 10&thinsp;000 kcal &laquo;olvidadas&raquo; por las f\u00f3rmulas cl\u00e1sicas.<\/div>\n  <\/div>\n\n  <div class=\"profile-card\">\n    <h4>Perfil medio<\/h4>\n    <div class=\"meta\">32 a\u00f1os &middot; 80&nbsp;kg &middot; 180&nbsp;cm &middot; 20&nbsp;% de grasa &middot; masa magra 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>Enfoque Lean (masa magra)<\/span><span class=\"v\">1&thinsp;735 kcal<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Diferencia Lean vs Mifflin: <b style=\"color:var(--pink)\">&minus;45 kcal\/d\u00eda<\/b>. En este perfil medio, Mifflin encaja bien (es el perfil sobre el que la f\u00f3rmula se calibr\u00f3 en 1990). Toda desviaci\u00f3n de este perfil aumenta el error.<\/div>\n  <\/div>\n\n  <div class=\"profile-card\">\n    <h4>Perfil sedentario<\/h4>\n    <div class=\"meta\">32 a\u00f1os &middot; 80&nbsp;kg &middot; 180&nbsp;cm &middot; 28&nbsp;% de grasa &middot; masa magra 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>Enfoque Lean (masa magra)<\/span><span class=\"v\">1&thinsp;597 kcal<\/span><\/div>\n    <\/div>\n    <div class=\"delta\">Diferencia Lean vs Mifflin: <b style=\"color:var(--pink)\">&minus;183 kcal\/d\u00eda<\/b>. Mifflin sobreestima su BMR en 166 kcal. Exactamente por eso tantos perfiles con sobrepeso &laquo;no adelgazan pese al d\u00e9ficit calculado&raquo;.<\/div>\n  <\/div>\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">05 &middot; Comparativa honesta<\/span>Fuerzas y l\u00edmites de cada f\u00f3rmula<\/h2>\n<p>Ninguna f\u00f3rmula es in\u00fatil. Cada una responde a un caso de uso. La verdadera pregunta: \u00bfsabes medir tu grasa corporal? Si s\u00ed, ya no necesitas ni Mifflin ni Harris-Benedict.<\/p>\n\n<div class=\"compar-grid\">\n  <div class=\"compar-card\">\n    <h4>Harris-Benedict<\/h4>\n    <div class=\"year\">Revisada en 1919 &middot; basada en 136 sujetos<\/div>\n    <p class=\"desc\">La gran antecesora. A\u00fan usada por defecto por muchas calculadoras online, incluidas apps de gran p\u00fablico. Sobreestima sistem\u00e1ticamente el BMR del 5 al 10&nbsp;% en poblaciones modernas.<\/p>\n    <p class=\"pros\"><b>+<\/b> Citada en todas partes, comparable de una calculadora a otra.<\/p>\n    <p class=\"cons\"><b>&minus;<\/b> Poblaci\u00f3n de referencia de hace un siglo. Sobrevalora en 100 a 200 kcal\/d\u00eda la mayor\u00eda de los perfiles.<\/p>\n  <\/div>\n\n  <div class=\"compar-card\">\n    <h4>Mifflin-St Jeor<\/h4>\n    <div class=\"year\">1990 &middot; basada en 498 sujetos<\/div>\n    <p class=\"desc\">Recalibrada sobre una poblaci\u00f3n americana a finales de los 80. Considerada la referencia &laquo;moderna sin grasa corporal&raquo; por los dietistas cl\u00ednicos. Precisa a <b>&plusmn;10&nbsp;%<\/b> en el perfil medio, mucho menos en los extremos.<\/p>\n    <p class=\"pros\"><b>+<\/b> M\u00e1s precisa que Harris-Benedict en el 70&nbsp;% de los perfiles.<\/p>\n    <p class=\"cons\"><b>&minus;<\/b> Ninguna consideraci\u00f3n de la grasa corporal. Margen de error de 200 a 400 kcal en perfiles musculosos o sedentarios.<\/p>\n  <\/div>\n\n  <div class=\"compar-card lean\">\n    <h4>Modelo propietario patentado de Lean<\/h4>\n    <div class=\"year\">2024 &middot; calibrado en 10&thinsp;000+ usuarios con BodyScan IA<\/div>\n    <p class=\"desc\">Se apoya en la <b>masa magra real<\/b> masa magra medida por BodyScan IA, integra la adaptaci\u00f3n metab\u00f3lica en d\u00e9ficit (convenci\u00f3n Lean 100&rarr;0&nbsp;%), recalibrado semana tras semana v\u00eda tu pesada y tu variaci\u00f3n de composici\u00f3n. No es una f\u00f3rmula de papel: un modelo que aprende de tus datos.<\/p>\n    <p class=\"pros\"><b>+<\/b> Precisi\u00f3n &plusmn;3&nbsp;% en perfiles musculosos, sedentarios, menopausia, posparto. Recalibraci\u00f3n continua.<\/p>\n    <p class=\"cons\"><b>&minus;<\/b> Requiere un BodyScan IA inicial (5 segundos, gratis en Lean) y un dato de peso regular.<\/p>\n  <\/div>\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">06 &middot; La base<\/span>Por qu\u00e9 un BMR preciso es el z\u00f3calo de todo lo dem\u00e1s<\/h2>\n\n<div class=\"body\">\n<p>El BMR no es una cifra aislada. Es el <b>primer bloque<\/b> de la ecuaci\u00f3n can\u00f3nica del metabolismo: <b>TDEE = BMR + NEAT + EAT + TEF<\/b>. La adaptaci\u00f3n metab\u00f3lica viene despu\u00e9s como coeficiente multiplicador del BMR en d\u00e9ficit (convenci\u00f3n Lean: 100&nbsp;% = \u00f3ptimo, 90&nbsp;% = 10&nbsp;% de adaptaci\u00f3n acumulada).<\/p>\n<p>Si tu BMR de partida est\u00e1 equivocado en 150&nbsp;kcal, tu TDEE est\u00e1 equivocado en 150&nbsp;kcal. Tu objetivo de p\u00e9rdida de peso est\u00e1 equivocado en 150&nbsp;kcal. Tu plan de ingesta est\u00e1 equivocado en 150&nbsp;kcal. Por eso Lean se niega a darte un objetivo mientras tu BodyScan no est\u00e9 hecho. No por capricho: por coherencia.<\/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; Metabolismo basal<\/b>Calculado sobre tu masa magra v\u00eda BodyScan IA. Recalibrado en cada pesada.<\/div>\n<\/div>\n\n<div class=\"micro-cta\">\n  Entender los 4 bloques del TDEE en detalle: <a href=\"https:\/\/lean-app.com\/es\/calculateur-tdee\/\">calculadora TDEE completa<\/a> u00b7 <a href=\"https:\/\/lean-app.com\/es\/eat\/\">EAT (deporte)<\/a> u00b7 <a href=\"https:\/\/lean-app.com\/es\/neat-depense-non-sportive\/\">NEAT (pasos)<\/a> u00b7 <a href=\"https:\/\/lean-app.com\/es\/effet-thermique-des-aliments\/\">TEF (digesti\u00f3n)<\/a>.\n<\/div>\n\n<h2 class=\"sect\"><span class=\"num\">07 &middot; FAQ<\/span>Todo lo que te preguntas sobre el c\u00e1lculo del metabolismo basal<\/h2>\n<details class=\"faq\"><summary>\u00bfCu\u00e1l es la f\u00f3rmula m\u00e1s precisa para calcular el metabolismo basal?<\/summary><div class=\"faq-body\"><p>La f\u00f3rmula m\u00e1s precisa es la que se apoya en la masa magra real, no en estimaciones desde peso, altura, edad y sexo. Sin grasa corporal, Mifflin-St Jeor 1990 sigue siendo la mejor aproximaci\u00f3n (\u00b110 % en el 70 % de los perfiles). Con grasa corporal, una ecuaci\u00f3n sobre masa magra tipo 370 + 21,6 \u00d7 FFM es m\u00e1s precisa. El modelo propietario patentado de Lean afina m\u00e1s integrando la adaptaci\u00f3n metab\u00f3lica y la recalibraci\u00f3n continua.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>\u00bfPor qu\u00e9 Harris-Benedict est\u00e1 superada?<\/summary><div class=\"faq-body\"><p>La f\u00f3rmula original data de 1919, revisada en 1984. Se calibr\u00f3 en 136 sujetos, en un entorno nutricional y un estilo de vida muy distintos de los nuestros. En poblaciones modernas, sobreestima el BMR del 5 al 10 %. Los dietistas cl\u00ednicos la consideran obsoleta desde la llegada de Mifflin-St Jeor en 1990.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Mifflin-St Jeor vs Harris-Benedict: \u00bfqu\u00e9 diferencia concreta?<\/summary><div class=\"faq-body\"><p>En un hombre de 80 kg, 180 cm, 32 a\u00f1os, Harris-Benedict da unas 1 855 kcal, Mifflin-St Jeor unas 1 780 kcal. Mifflin queda unas 75 kcal por debajo de Harris-Benedict. Mifflin es globalmente m\u00e1s justa, pero ninguna de las dos distingue un perfil musculoso de uno sedentario.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>\u00bfPor qu\u00e9 la grasa corporal lo cambia todo en el c\u00e1lculo del BMR?<\/summary><div class=\"faq-body\"><p>Porque es la masa magra, no la masa total, la que determina el gasto en reposo. 1 kg de m\u00fasculo quema unas 13 kcal\/d\u00eda, 1 kg de grasa unas 4 kcal\/d\u00eda. Dos personas con el mismo peso pero 10 puntos de grasa de diferencia pueden tener BMR que divergen 200 a 400 kcal\/d\u00eda. Ninguna f\u00f3rmula sin grasa corporal puede captarlo.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>\u00bfC\u00f3mo calcula Lean mi metabolismo basal?<\/summary><div class=\"faq-body\"><p>Lean usa un modelo propietario patentado. El dato de entrada principal es tu grasa corporal medida por BodyScan IA (foto, 5 segundos, precisi\u00f3n grado DEXA). Lean deduce tu masa magra real, calcula un BMR sobre esa masa magra, e integra despu\u00e9s una funci\u00f3n de adaptaci\u00f3n metab\u00f3lica que se recalibra cada semana seg\u00fan tu variaci\u00f3n de peso y composici\u00f3n. La masa magra es el factor dominante; la edad modula finamente el resultado (el gasto en reposo baja ligeramente a masa magra constante con los a\u00f1os).<\/p><\/div><\/details>\n<details class=\"faq\"><summary>\u00bfCada cu\u00e1nto hay que recalcular el BMR?<\/summary><div class=\"faq-body\"><p>Mientras tu composici\u00f3n corporal no se mueva (peso estable, grasa estable), tu BMR tampoco se mueve. En cuanto pierdes o ganas 2 kg, o tu grasa var\u00eda 2 puntos, hay que recalcular. Lean lo hace autom\u00e1ticamente en cada BodyScan y cada pesada.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>\u00bfMi BMR baja cuando pierdo peso?<\/summary><div class=\"faq-body\"><p>S\u00ed, por dos razones. Primera raz\u00f3n f\u00edsica: pesas menos, as\u00ed que tienes menos masa magra que mantener, as\u00ed que el BMR mec\u00e1nico baja. Segunda raz\u00f3n fisiol\u00f3gica: tu cuerpo activa una adaptaci\u00f3n metab\u00f3lica en d\u00e9ficit cal\u00f3rico prolongado, que frena tu BMR del 5 al 20 % bajo su valor esperado. Lean modela ambos fen\u00f3menos.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>C\u00e1lculo del metabolismo basal hombre vs mujer: \u00bfqu\u00e9 diferencia?<\/summary><div class=\"faq-body\"><p>A peso, altura y edad equivalentes, las mujeres tienen de media un 8 a 12 % menos de masa magra que los hombres (diferencia hormonal y morfol\u00f3gica). Su BMR es por tanto estructuralmente m\u00e1s bajo, del orden de 150 a 250 kcal\/d\u00eda. Las dos f\u00f3rmulas cl\u00e1sicas integran una constante de sexo distinta. En Lean, habla la masa magra medida, independientemente del sexo.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>Metabolismo basal en reposo vs en esfuerzo: \u00bfcu\u00e1l es la diferencia?<\/summary><div class=\"faq-body\"><p>El BMR es estrictamente el gasto en reposo (tumbado, en ayunas, neutralidad t\u00e9rmica). Cuando caminas, le a\u00f1ades el NEAT (Non-Exercise Activity Thermogenesis). Cuando haces deporte, le a\u00f1ades el EAT (Exercise Activity Thermogenesis). Cuando comes, le a\u00f1ades el TEF (Thermic Effect of Food). La suma es tu TDEE.<\/p><\/div><\/details>\n<details class=\"faq\"><summary>\u00bfQu\u00e9 f\u00f3rmula usa la calculadora de arriba para el &lsquo;enfoque Lean&rsquo;?<\/summary><div class=\"faq-body\"><p>Una ecuaci\u00f3n p\u00fablica sobre masa magra, citada en la literatura fisiol\u00f3gica: BMR \u2248 370 + 21,6 \u00d7 masa magra (kg). La masa magra se deriva de tu peso y tu grasa corporal. Es una aproximaci\u00f3n \u00fatil para entender el efecto de la grasa corporal. El modelo propietario patentado de Lean en la app va m\u00e1s lejos (adaptaci\u00f3n metab\u00f3lica, agua, gluc\u00f3geno, recalibraci\u00f3n continua).<\/p><\/div><\/details>\n\n<div class=\"sources\">\n  <h4>Fuentes cient\u00edficas<\/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>Obt\u00e9n tu BMR sobre tu grasa corporal real<\/h3>\n  <p>BodyScan IA en 5 segundos. Recalibraci\u00f3n continua. Sin f\u00f3rmula de 1919 ni de 1990. Descarga gratis, 7 d\u00edas de prueba en el plan anual.<\/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 %. 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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. 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Deuxi\u00e8me raison physiologique : ton corps active une adaptation m\u00e9tabolique en d\u00e9ficit calorique prolong\u00e9, qui ralentit ton BMR de 5 \u00e0 20 % sous sa valeur attendue. Lean mod\u00e9lise ces deux ph\u00e9nom\u00e8nes.\"}},{\"@type\":\"Question\",\"name\":\"Calcul m\u00e9tabolisme de base homme vs femme : quelle diff\u00e9rence ?\",\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"\u00c0 poids, taille et \u00e2ge \u00e9quivalents, les femmes ont en moyenne 8 \u00e0 12 % moins de masse maigre que les hommes (diff\u00e9rence hormonale et morphologique). Leur BMR est donc structurellement plus bas, de l'ordre de 150 \u00e0 250 kcal\/jour. Les deux formules classiques int\u00e8grent une constante de sexe diff\u00e9rente. 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Las dem\u00e1s apps no lo hacen.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/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: c\u00f3mo lo cotidiano quema m\u00e1s que el deporte <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Por qu\u00e9 tus pasos y actividades no deportivas representan del 15 al 30 % de tu gasto total.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/calculateur-deficit-calorique\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Calculadora de d\u00e9ficit cal\u00f3rico: el enfoque correcto para una definici\u00f3n <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Calcula tu d\u00e9ficit sobre tu TDEE real bodyfat-aware. 3 ritmos: lento\/moderado\/agresivo.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/calculateur-tdee\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Calculadora TDEE completa: la f\u00f3rmula can\u00f3nica BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Calculadora TDEE bodyfat-aware con desglose de los 4 bloques metab\u00f3licos.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/es\/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;\">Mejores aplicaciones para contar calor\u00edas en 2026: 8 apps probadas <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Comparativa honesta: 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>C\u00e1lculo del metabolismo basal: Harris-Benedict y BMR - Lean<\/title>\n<meta name=\"description\" content=\"Compara Harris-Benedict, Mifflin-St Jeor y el enfoque Lean sobre masa magra v\u00eda BodyScan IA. 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