fitness: add kcal estimation based on Lytle et al. (2019) regression model
Estimate strength workout energy expenditure using the Lytle et al. multiple linear regression model. Maps all 77 exercises to 7 studied categories with confidence levels. Shows kcal on stats page (cumulative), session cards, workout detail, and workout completion screen. Supports sex/height demographics via profile section on measure page. Includes info tooltip with DOI reference.
This commit is contained in:
@@ -1,7 +1,8 @@
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<script>
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import { page } from '$app/stores';
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import { getExerciseById, getExerciseMetrics } from '$lib/data/exercises';
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import { Clock, Weight, Trophy, Route, Gauge } from 'lucide-svelte';
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import { estimateWorkoutKcal } from '$lib/data/kcalEstimate';
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import { Clock, Weight, Trophy, Route, Gauge, Flame } from 'lucide-svelte';
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import { detectFitnessLang, fitnessSlugs } from '$lib/js/fitnessI18n';
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const lang = $derived(detectFitnessLang($page.url.pathname));
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@@ -115,6 +116,27 @@
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return { points, viewBox: `0 0 ${vbW} ${vbH}` };
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});
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/** Estimate kcal for this session */
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const kcalResult = $derived.by(() => {
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/** @type {import('$lib/data/kcalEstimate').ExerciseData[]} */
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const exercises = [];
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for (const ex of session.exercises) {
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const exercise = getExerciseById(ex.exerciseId, lang);
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const metrics = getExerciseMetrics(exercise);
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if (metrics.includes('distance')) continue; // skip cardio
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const weightMultiplier = exercise?.bilateral ? 2 : 1;
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const sets = ex.sets
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.filter((/** @type {any} */ s) => s.reps > 0)
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.map((/** @type {any} */ s) => ({
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weight: (s.weight ?? 0) * weightMultiplier,
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reps: s.reps ?? 0
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}));
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if (sets.length > 0) exercises.push({ exerciseId: ex.exerciseId, sets });
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}
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if (exercises.length === 0) return null;
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return estimateWorkoutKcal(exercises);
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});
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/** Check if this session has any cardio exercise with GPS data */
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const hasGpsCardio = $derived(session.exercises.some(ex => {
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const exercise = getExerciseById(ex.exerciseId, lang);
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@@ -190,6 +212,9 @@
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{:else if session.totalVolume}
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<span class="stat"><Weight size={14} /> {session.totalVolume >= 1000 ? `${(session.totalVolume / 1000).toFixed(1)}t` : `${Math.round(session.totalVolume).toLocaleString()} kg`}</span>
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{/if}
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{#if kcalResult}
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<span class="stat kcal"><Flame size={14} /> {kcalResult.kcal} ± {kcalResult.kcal - kcalResult.lower} kcal</span>
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{/if}
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{#if session.prs && session.prs.length > 0}
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<span class="stat pr"><Trophy size={14} /> {session.prs.length} PR{session.prs.length > 1 ? 's' : ''}</span>
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{/if}
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@@ -272,6 +297,9 @@
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color: var(--color-primary);
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font-weight: 700;
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}
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.stat.kcal {
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color: var(--nord12);
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}
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.stat.pr {
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color: var(--nord13);
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}
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@@ -0,0 +1,410 @@
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/**
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* Kilocalorie estimation for strength training based on:
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*
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* Lytle, J.R. et al. (2019) "Predicting Energy Expenditure of an Acute
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* Resistance Exercise Bout in Men and Women."
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* Med. Sci. Sports Exerc., 51(7), pp.1532–1537.
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* DOI: 10.1249/MSS.0000000000001925
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*
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* The paper provides a multiple-linear-regression model trained on indirect
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* calorimetry (VO₂) from 52 subjects performing 7 resistance exercises at
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* 60–70 % 1RM. The model predicts **net** kilocalories (total minus resting
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* metabolic cost) from demographic and training-volume variables.
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*
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* ─── Total bout equation (R² = 0.773, SEE = 28.5 kcal) ───────────────────
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*
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* Net kcal = 0.874·height_cm − 0.596·age_yr − 1.016·fat_mass_kg
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* + 1.638·lean_mass_kg + 2.461·(TV / 1000) − 110.742
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*
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* where TV = Σ(sets × reps × weight_kg) across the workout.
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*
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* NOTE: The published abstract prints the TV scaling factor as "×10⁻²" but
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* verification against the paper's own reported means (male = 161.2 kcal)
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* shows the correct factor is **×10⁻³** (i.e. TV / 1000). The Table 2
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* column header "Volume m³ (kg)" confirms this.
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*
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* ─── Individual exercise equations (Table 2) ─────────────────────────────
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*
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* Seven exercise-specific equations are also provided. In these, the
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* "Weight (kg)" coefficient applies to the exercise weight / 100 and the
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* "Volume" coefficient applies to exercise TV / 1000. (Verified by
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* back-calculating against the study's reported demographics and means.)
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*
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* ─── Limitations & uncertainty ────────────────────────────────────────────
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*
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* • Calibrated on Keiser pneumatic machines, 60–70 % 1RM, 2–3 sets of
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* 8–12 reps. Accuracy degrades for very different protocols.
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* • Demographics limited to ages 20–58.
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* • We map all 77 app exercises to the 7 studied exercises. Exercises that
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* are close analogues (e.g. incline bench → chest press) inherit the
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* equation directly; distant mappings (e.g. hip thrust → leg press)
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* carry additional uncertainty.
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* • Bodyweight exercises (pull-ups, dips, push-ups) add a fraction of
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* body mass to the logged weight before computing TV.
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* • When height, age, or body composition are unknown, defaults are used
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* (175 cm, 30 yr, 22 % body fat) which adds ~±10 kcal per workout
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* to the uncertainty.
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*/
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// ── Individual exercise regression coefficients (Table 2) ──────────────
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interface ExerciseCoeffs {
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h: number; // height (cm)
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age: number; // age (yr)
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g: number; // gender (male=1, female=0)
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fm: number; // DEXA fat mass (kg)
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lm: number; // DEXA lean mass (kg)
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w: number; // exercise weight / 100
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v: number; // exercise TV / 1000
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c: number; // constant
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see: number; // standard error of estimate (kcal)
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}
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const LYTLE_EXERCISES: Record<string, ExerciseCoeffs> = {
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'leg-press': {
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h: 0.120, age: -0.093, g: 0, fm: 0, lm: 0.297,
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w: 1.169, v: 0, c: -13.837, see: 4.4
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},
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'chest-press': {
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h: 0.186, age: -0.317, g: -0.198, fm: 0, lm: 0.271,
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w: 4.211, v: 0, c: -28.468, see: 4.7
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},
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'leg-curl': {
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h: 0, age: -0.129, g: 0, fm: 0, lm: 0.245,
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w: 5.189, v: -0.100, c: 6.633, see: 5.36
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},
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'lat-pulldown': {
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h: 0, age: -0.165, g: 0, fm: -0.128, lm: 0.187,
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w: 4.725, v: 0, c: 8.483, see: 4.96
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},
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'leg-extension': {
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h: 0, age: -0.08, g: -1.635, fm: -0.185, lm: 0.394,
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w: 4.252, v: 0, c: 1.444, see: 5.31
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},
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'triceps-pushdown': {
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h: 0.255, age: 0, g: -5.124, fm: -0.239, lm: 0.390,
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w: 1.919, v: 0, c: -44.891, see: 4.99
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},
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'biceps-curl': {
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h: 0.292, age: -0.091, g: -7.068, fm: 0, lm: 0.351,
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w: 1.510, v: -0.156, c: -44.262, see: 5.60
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},
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};
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// ── Total bout equation coefficients ───────────────────────────────────
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const TOTAL_BOUT = {
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h: 0.874,
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age: -0.596,
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fm: -1.016,
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lm: 1.638,
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tv: 2.461, // applied to TV / 1000
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c: -110.742,
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see: 28.465,
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r2: 0.773,
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};
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// ── Exercise → Lytle category mapping ──────────────────────────────────
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//
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// confidence: 'direct' = very close analogue of the studied exercise
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// 'close' = same movement pattern / muscle group
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// 'distant' = best available but mechanically different
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type MappingConfidence = 'direct' | 'close' | 'distant';
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interface ExerciseMapping {
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lytleKey: string;
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confidence: MappingConfidence;
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bwFraction?: number; // fraction of bodyweight to add (for bodyweight exercises)
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}
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export const EXERCISE_MAP: Record<string, ExerciseMapping> = {
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// === CHEST → chest-press ===
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'bench-press-barbell': { lytleKey: 'chest-press', confidence: 'direct' },
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'incline-bench-press-barbell': { lytleKey: 'chest-press', confidence: 'close' },
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'decline-bench-press-barbell': { lytleKey: 'chest-press', confidence: 'close' },
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'bench-press-close-grip-barbell': { lytleKey: 'chest-press', confidence: 'close' },
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'bench-press-dumbbell': { lytleKey: 'chest-press', confidence: 'close' },
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'incline-bench-press-dumbbell': { lytleKey: 'chest-press', confidence: 'close' },
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'chest-fly-dumbbell': { lytleKey: 'chest-press', confidence: 'distant' },
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'chest-dip': { lytleKey: 'chest-press', confidence: 'close', bwFraction: 0.90 },
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'push-up': { lytleKey: 'chest-press', confidence: 'close', bwFraction: 0.64 },
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'cable-crossover': { lytleKey: 'chest-press', confidence: 'distant' },
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// === BACK → lat-pulldown ===
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'bent-over-row-barbell': { lytleKey: 'lat-pulldown', confidence: 'close' },
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'deadlift-barbell': { lytleKey: 'leg-press', confidence: 'distant' }, // full-body → leg-press as largest compound
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'pull-up': { lytleKey: 'lat-pulldown', confidence: 'direct', bwFraction: 1.0 },
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'chin-up': { lytleKey: 'lat-pulldown', confidence: 'direct', bwFraction: 1.0 },
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'lat-pulldown-cable': { lytleKey: 'lat-pulldown', confidence: 'direct' },
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'seated-row-cable': { lytleKey: 'lat-pulldown', confidence: 'close' },
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'dumbbell-row': { lytleKey: 'lat-pulldown', confidence: 'close' },
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't-bar-row': { lytleKey: 'lat-pulldown', confidence: 'close' },
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'incline-row-dumbbell': { lytleKey: 'lat-pulldown', confidence: 'close' },
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'face-pull-cable': { lytleKey: 'lat-pulldown', confidence: 'distant' },
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// === SHOULDERS → chest-press (pressing) or lat-pulldown (pulling) ===
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'overhead-press-barbell': { lytleKey: 'chest-press', confidence: 'close' },
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'overhead-press-dumbbell': { lytleKey: 'chest-press', confidence: 'close' },
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'lateral-raise-dumbbell': { lytleKey: 'biceps-curl', confidence: 'distant' }, // isolation, similar load range
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'lateral-raise-cable': { lytleKey: 'biceps-curl', confidence: 'distant' },
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'front-raise-dumbbell': { lytleKey: 'biceps-curl', confidence: 'distant' },
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'reverse-fly-dumbbell': { lytleKey: 'biceps-curl', confidence: 'distant' },
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'upright-row-barbell': { lytleKey: 'lat-pulldown', confidence: 'distant' },
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'shrug-barbell': { lytleKey: 'lat-pulldown', confidence: 'distant' },
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'shrug-dumbbell': { lytleKey: 'lat-pulldown', confidence: 'distant' },
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// === ARMS (biceps) → biceps-curl ===
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'bicep-curl-barbell': { lytleKey: 'biceps-curl', confidence: 'direct' },
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'bicep-curl-dumbbell': { lytleKey: 'biceps-curl', confidence: 'direct' },
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'hammer-curl-dumbbell': { lytleKey: 'biceps-curl', confidence: 'close' },
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'preacher-curl-barbell': { lytleKey: 'biceps-curl', confidence: 'close' },
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'concentration-curl-dumbbell': { lytleKey: 'biceps-curl', confidence: 'close' },
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'cable-curl': { lytleKey: 'biceps-curl', confidence: 'close' },
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// === ARMS (triceps) → triceps-pushdown ===
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'tricep-pushdown-cable': { lytleKey: 'triceps-pushdown', confidence: 'direct' },
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'skullcrusher-dumbbell': { lytleKey: 'triceps-pushdown', confidence: 'close' },
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'skullcrusher-barbell': { lytleKey: 'triceps-pushdown', confidence: 'close' },
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'overhead-tricep-extension-dumbbell': { lytleKey: 'triceps-pushdown', confidence: 'close' },
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'tricep-dip': { lytleKey: 'triceps-pushdown', confidence: 'close', bwFraction: 0.90 },
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'kickback-dumbbell': { lytleKey: 'triceps-pushdown', confidence: 'close' },
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// === LEGS (quad-dominant) → leg-press or leg-extension ===
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'squat-barbell': { lytleKey: 'leg-press', confidence: 'close' },
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'front-squat-barbell': { lytleKey: 'leg-press', confidence: 'close' },
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'leg-press-machine': { lytleKey: 'leg-press', confidence: 'direct' },
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'lunge-dumbbell': { lytleKey: 'leg-press', confidence: 'close' },
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'bulgarian-split-squat-dumbbell': { lytleKey: 'leg-press', confidence: 'close' },
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'leg-extension-machine': { lytleKey: 'leg-extension', confidence: 'direct' },
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'goblet-squat-dumbbell': { lytleKey: 'leg-press', confidence: 'close' },
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'hack-squat-machine': { lytleKey: 'leg-press', confidence: 'close' },
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// === LEGS (hamstring/posterior) → leg-curl ===
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'leg-curl-machine': { lytleKey: 'leg-curl', confidence: 'direct' },
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'romanian-deadlift-barbell': { lytleKey: 'leg-curl', confidence: 'close' },
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'romanian-deadlift-dumbbell': { lytleKey: 'leg-curl', confidence: 'close' },
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'hip-thrust-barbell': { lytleKey: 'leg-press', confidence: 'distant' },
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'nordic-hamstring-curl': { lytleKey: 'leg-curl', confidence: 'close', bwFraction: 0.70 },
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// === LEGS (calves) → leg-extension (closest isolation) ===
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'calf-raise-machine': { lytleKey: 'leg-extension', confidence: 'distant' },
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'calf-raise-standing': { lytleKey: 'leg-extension', confidence: 'distant' },
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// === CORE → biceps-curl (similar isolation load range) ===
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'plank': { lytleKey: 'biceps-curl', confidence: 'distant' },
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'decline-crunch': { lytleKey: 'biceps-curl', confidence: 'distant' },
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'flat-leg-raise': { lytleKey: 'biceps-curl', confidence: 'distant' },
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'crunch': { lytleKey: 'biceps-curl', confidence: 'distant' },
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'hanging-leg-raise': { lytleKey: 'biceps-curl', confidence: 'distant' },
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'cable-crunch': { lytleKey: 'biceps-curl', confidence: 'distant' },
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'russian-twist': { lytleKey: 'biceps-curl', confidence: 'distant' },
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'ab-wheel-rollout': { lytleKey: 'biceps-curl', confidence: 'distant', bwFraction: 0.50 },
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// === OTHER ===
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'clean-and-press-barbell': { lytleKey: 'leg-press', confidence: 'distant' },
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'farmers-walk': { lytleKey: 'leg-press', confidence: 'distant' },
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};
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// ── Confidence penalty for uncertainty ──────────────────────────────────
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// Additional SEE (kcal) added per exercise based on mapping confidence.
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// 'direct' = same exercise, no additional error.
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// 'close' = same pattern, small extrapolation error.
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// 'distant' = different pattern, larger extrapolation.
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const CONFIDENCE_SEE: Record<MappingConfidence, number> = {
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direct: 0,
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close: 2,
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distant: 5,
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};
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// ── Demographics type ──────────────────────────────────────────────────
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export interface Demographics {
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heightCm?: number; // default: 175
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ageYr?: number; // default: 30
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isMale?: boolean; // default: true (gender=1)
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bodyWeightKg?: number; // default: 80
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bodyFatPct?: number; // default: 22
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}
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const DEFAULTS: Required<Demographics> = {
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heightCm: 175,
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ageYr: 30,
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isMale: true,
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bodyWeightKg: 80,
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bodyFatPct: 22,
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};
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function resolveDemographics(d?: Demographics) {
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const heightCm = d?.heightCm ?? DEFAULTS.heightCm;
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const ageYr = d?.ageYr ?? DEFAULTS.ageYr;
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const isMale = d?.isMale ?? DEFAULTS.isMale;
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const bodyWeightKg = d?.bodyWeightKg ?? DEFAULTS.bodyWeightKg;
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const bodyFatPct = d?.bodyFatPct ?? DEFAULTS.bodyFatPct;
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const fatMassKg = bodyWeightKg * bodyFatPct / 100;
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const leanMassKg = bodyWeightKg - fatMassKg;
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const gender = isMale ? 1 : 0;
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// Track how many fields used defaults (for uncertainty)
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let defaultCount = 0;
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if (d?.heightCm == null) defaultCount++;
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if (d?.ageYr == null) defaultCount++;
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if (d?.bodyWeightKg == null) defaultCount++;
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if (d?.bodyFatPct == null) defaultCount++;
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return { heightCm, ageYr, gender, fatMassKg, leanMassKg, bodyWeightKg, defaultCount };
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}
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// ── Per-exercise set data ──────────────────────────────────────────────
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export interface SetData {
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weight: number; // external load in kg (already ×2 for bilateral)
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reps: number;
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}
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export interface ExerciseData {
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exerciseId: string;
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sets: SetData[];
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}
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// ── Core estimation functions ──────────────────────────────────────────
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/**
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* Compute effective weight for a set, adding bodyweight fraction where applicable.
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*/
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function effectiveWeight(exerciseId: string, externalWeight: number, bodyMassKg: number): number {
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const mapping = EXERCISE_MAP[exerciseId];
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if (mapping?.bwFraction) {
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return externalWeight + bodyMassKg * mapping.bwFraction;
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}
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return externalWeight;
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}
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/**
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* Estimate kcal for a single exercise using the individual Lytle equation.
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*/
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function estimateExerciseKcal(
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exerciseId: string,
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sets: SetData[],
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demo: ReturnType<typeof resolveDemographics>
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): { kcal: number; see: number } {
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const mapping = EXERCISE_MAP[exerciseId];
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if (!mapping) return { kcal: 0, see: 0 };
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const coeffs = LYTLE_EXERCISES[mapping.lytleKey];
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if (!coeffs) return { kcal: 0, see: 0 };
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// Compute average exercise weight and total TV for this exercise
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let totalTV = 0;
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let totalWeightedWeight = 0;
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||||
let totalReps = 0;
|
||||
for (const s of sets) {
|
||||
if (s.reps <= 0) continue;
|
||||
const w = effectiveWeight(exerciseId, s.weight, demo.bodyWeightKg);
|
||||
totalTV += w * s.reps;
|
||||
totalWeightedWeight += w * s.reps;
|
||||
totalReps += s.reps;
|
||||
}
|
||||
if (totalReps === 0) return { kcal: 0, see: 0 };
|
||||
|
||||
const avgWeight = totalWeightedWeight / totalReps;
|
||||
|
||||
const kcal = coeffs.h * demo.heightCm
|
||||
+ coeffs.age * demo.ageYr
|
||||
+ coeffs.g * demo.gender
|
||||
+ coeffs.fm * demo.fatMassKg
|
||||
+ coeffs.lm * demo.leanMassKg
|
||||
+ coeffs.w * (avgWeight / 100)
|
||||
+ coeffs.v * (totalTV / 1000)
|
||||
+ coeffs.c;
|
||||
|
||||
const see = Math.sqrt(coeffs.see ** 2 + CONFIDENCE_SEE[mapping.confidence] ** 2);
|
||||
|
||||
return { kcal: Math.max(0, kcal), see };
|
||||
}
|
||||
|
||||
/**
|
||||
* Estimate kcal for an entire workout using the total bout equation.
|
||||
*
|
||||
* Returns point estimate and 95% confidence interval.
|
||||
*/
|
||||
export function estimateWorkoutKcal(
|
||||
exercises: ExerciseData[],
|
||||
demographics?: Demographics
|
||||
): { kcal: number; lower: number; upper: number; see: number } {
|
||||
const demo = resolveDemographics(demographics);
|
||||
|
||||
// Compute total TV across all exercises
|
||||
let totalTV = 0;
|
||||
for (const ex of exercises) {
|
||||
for (const s of ex.sets) {
|
||||
if (s.reps <= 0) continue;
|
||||
const w = effectiveWeight(ex.exerciseId, s.weight, demo.bodyWeightKg);
|
||||
totalTV += w * s.reps;
|
||||
}
|
||||
}
|
||||
|
||||
const kcal = TOTAL_BOUT.h * demo.heightCm
|
||||
+ TOTAL_BOUT.age * demo.ageYr
|
||||
+ TOTAL_BOUT.fm * demo.fatMassKg
|
||||
+ TOTAL_BOUT.lm * demo.leanMassKg
|
||||
+ TOTAL_BOUT.tv * (totalTV / 1000)
|
||||
+ TOTAL_BOUT.c;
|
||||
|
||||
// Uncertainty: model SEE + demographic default uncertainty
|
||||
// Each defaulted demographic adds ~3-4 kcal of uncertainty (height ±10cm = ±8.7,
|
||||
// age ±10yr = ±6.0, body comp ±5% = ±5-8 kcal; halved for ±1σ)
|
||||
const demoUncertainty = demo.defaultCount * 4;
|
||||
const see = Math.sqrt(TOTAL_BOUT.see ** 2 + demoUncertainty ** 2);
|
||||
|
||||
const point = Math.max(0, kcal);
|
||||
return {
|
||||
kcal: Math.round(point),
|
||||
lower: Math.max(0, Math.round(point - 1.96 * see)),
|
||||
upper: Math.round(point + 1.96 * see),
|
||||
see: Math.round(see * 10) / 10,
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Estimate kcal per exercise within a workout (using individual equations).
|
||||
* Useful for showing which exercises contributed most.
|
||||
*/
|
||||
export function estimatePerExerciseKcal(
|
||||
exercises: ExerciseData[],
|
||||
demographics?: Demographics
|
||||
): { exerciseId: string; kcal: number; see: number; confidence: MappingConfidence }[] {
|
||||
const demo = resolveDemographics(demographics);
|
||||
|
||||
return exercises.map((ex) => {
|
||||
const { kcal, see } = estimateExerciseKcal(ex.exerciseId, ex.sets, demo);
|
||||
const confidence = EXERCISE_MAP[ex.exerciseId]?.confidence ?? 'distant';
|
||||
return { exerciseId: ex.exerciseId, kcal: Math.round(kcal * 10) / 10, see: Math.round(see * 10) / 10, confidence };
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Estimate cumulative kcal across multiple workouts.
|
||||
* Uncertainty decreases relative to the total as errors partially cancel.
|
||||
*/
|
||||
export function estimateCumulativeKcal(
|
||||
workoutResults: { kcal: number; see: number }[]
|
||||
): { kcal: number; lower: number; upper: number } {
|
||||
let totalKcal = 0;
|
||||
let sumSeeSquared = 0;
|
||||
|
||||
for (const w of workoutResults) {
|
||||
totalKcal += w.kcal;
|
||||
sumSeeSquared += w.see ** 2;
|
||||
}
|
||||
|
||||
// Cumulative SEE = sqrt(sum of individual SEE²)
|
||||
// This assumes errors are independent across workouts
|
||||
const cumulativeSee = Math.sqrt(sumSeeSquared);
|
||||
|
||||
return {
|
||||
kcal: Math.round(totalKcal),
|
||||
lower: Math.max(0, Math.round(totalKcal - 1.96 * cumulativeSee)),
|
||||
upper: Math.round(totalKcal + 1.96 * cumulativeSee),
|
||||
};
|
||||
}
|
||||
@@ -71,8 +71,14 @@ const translations: Translations = {
|
||||
workout_singular: { en: 'Workout', de: 'Training' },
|
||||
workouts_plural: { en: 'Workouts', de: 'Trainings' },
|
||||
lifted: { en: 'Lifted', de: 'Gehoben' },
|
||||
est_kcal: { en: 'Est. kcal', de: 'Gesch. kcal' },
|
||||
kcal_set_profile: { en: 'Set sex & height in', de: 'Geschlecht & Grösse unter' },
|
||||
distance_covered: { en: 'Distance Covered', de: 'Zurückgelegt' },
|
||||
workouts_per_week: { en: 'Workouts per week', de: 'Trainings pro Woche' },
|
||||
sex: { en: 'Sex', de: 'Geschlecht' },
|
||||
male: { en: 'Male', de: 'Männlich' },
|
||||
female: { en: 'Female', de: 'Weiblich' },
|
||||
height: { en: 'Height (cm)', de: 'Grösse (cm)' },
|
||||
no_workout_data: { en: 'No workout data to display yet.', de: 'Noch keine Trainingsdaten vorhanden.' },
|
||||
weight: { en: 'Weight', de: 'Gewicht' },
|
||||
|
||||
@@ -167,6 +173,7 @@ const translations: Translations = {
|
||||
|
||||
// Measure page
|
||||
measure_title: { en: 'Measure', de: 'Messen' },
|
||||
profile: { en: 'Profile', de: 'Profil' },
|
||||
new_measurement: { en: 'New Measurement', de: 'Neue Messung' },
|
||||
edit_measurement: { en: 'Edit Measurement', de: 'Messung bearbeiten' },
|
||||
weight_kg: { en: 'Weight (kg)', de: 'Gewicht (kg)' },
|
||||
|
||||
Reference in New Issue
Block a user