Beta-Glucan for Common Cold
Yeast beta-glucan may modestly lower how often or how severely healthy adults catch colds, but the evidence is weak: it comes mostly from small, manufacturer-funded trials, and the single largest study found no reduction in cold incidence at all. It is not a reliable way to prevent the common cold.
Why this grade7-layer evidence engine
This claim earns a Weak (C) grade because the favorable signal is real but fragile. A 2021 meta-analysis of 13 randomized trials (PMID 33900466) reported that yeast beta-glucan lowered upper-respiratory-infection incidence (OR 0.345), cut the number of episodes, and shortened their duration, but the authors themselves flagged high heterogeneity and a small number of low-to-moderate quality trials.
Crucially, the best single studies disagree with that optimistic pooled result. The largest and methodologically strongest RCT (PMID 30198828, n=299) found NO reduction in cold incidence or overall severity, with only a modest dip in early physical symptoms during days 1-7. A 2017 trial in older adults (PMID 28606567, n=100) showed only a non-significant trend, while a smaller 2013 trial (PMID 23340963, n=162) reported about 25% fewer symptomatic colds. The picture is genuinely mixed, not a clean win.
Two further problems hold the grade down. Almost every trial was funded by a beta-glucan manufacturer (Leiber GmbH, Wellmune/Kerry) or run by contract research firms, a pervasive conflict of interest that tends to inflate apparent benefit. And no health authority endorses it for colds: the FDA's authorized claim covers only cereal (oat/barley) soluble fiber for heart disease, EFSA twice rejected the yeast immune and common-cold claims, and major clinics (Mayo, Cleveland, Harvard) and the NIH Office of Dietary Supplements do not address it. Note that cereal beta-glucan and yeast beta-glucan are different molecules; the cholesterol claim is not evidence for cold prevention.
Scoring transparency
All scores computed by a 7-layer evidence engine — fully auditable▸View the full decision path (audit trail)
- compute_raw_score — 加權公式: L2×0.30 + L3×0.25 + L5×0.25 + L11×0.10 + L1×0.10 = 0.449
- tier_from_score — 依分數區間映射至 tier letter
- apply_hec_rules — 高品質 SR/MA 顯示 positive (1 篇 > 0 negative)
- tier_strict_requirement_check — Tier 條件達標，未降階
- detect_disputes — 偵測到 0 個 hard + 1 個 soft dispute
- decide_status — 依 tier + dispute 結果決定 status