Patients increasingly bring a stream of numbers from consumer health devices — smart scales, glucose sensors and body-composition apps — into clinical encounters. Reviewed as a flat dashboard of equals, these metrics generate anxiety and drive inappropriate changes to medication, diet and training, particularly during GLP-1–assisted weight loss. This white paper proposes a four-tier feedback model that ranks measurements by signal strength rather than treating them as competing verdicts: visceral adiposity and waist circumference (Tier 1) define therapeutic success; functional muscle strength (Tier 2) protects metabolic health; continuous glucose monitoring (Tier 3) supports behaviour change; and anthropometry and bioimpedance (Tier 4) support engagement only. Drawing on the primary literature, it argues that metabolic health and longevity are more tightly linked to muscle strength than to muscle mass. It then sets out a widely misunderstood statistical principle underpinning the hierarchy: a high correlation between a consumer bioimpedance device and DEXA is not the same as agreement. Using the Bland–Altman framework, it demonstrates how a flattering correlation coefficient can conceal limits of agreement too wide for clinical use in the individual, especially when tracking change over time. A downloadable HTML version is included alongside the PDF: its references are hyperlinked with superscript citations and return-links, making it easier to cite, search and link to specific sources.