The evidence

Built on the evidence, not on a hunch.

Before we built MetaScore, we asked one question and refused to answer it with an opinion: what actually measures a person's metabolic health?

Answering it meant working through hundreds of peer-reviewed studies, clinical guidelines and validated risk models — from insulin resistance and cardiovascular risk to fitness, strength and biological age. We kept only the markers with independent evidence behind them — at least two studies for each, drew every threshold from recognised clinical guidance, and combined them into one system a practitioner can run and a member can understand.

27
peer-reviewed studies cited
7
recognised clinical guidelines
5M+
people across the research

How the system was composed.

Every marker in MetaScore earns its place. We did not invent thresholds — we took them from clinical guidance and the strongest available research, then combined them into two indices and one score.

1

Review

Work through the published evidence for each candidate marker — blood pressure, glucose, lipids, uric acid, strength, fitness and more.

2

Select

Keep only markers with independent evidence and a recognised clinical threshold. Discard anything that could not be defended.

3

Combine

Weight and combine the markers into two indices, then a single, colour-coded score.

The result
Metabolic Health Index + Functional Age Index = your MetaScore, out of 48
Blood and body markers, and physical function — one number, four clear zones.

The research behind the markers.

At least two independent, peer-reviewed studies stand behind every marker. Wherever a study is open access, it links straight to the full paper — not an abstract, not a paywall.

Insulin resistance & metabolic markers
Cardiovascular Diabetology, 2025 — TyG index and cardiovascular mortality. Read →
Large prospective cohort: the triglyceride–glucose index independently predicts cardiovascular death.
Frontiers in Endocrinology, 2025 — METS-IR and TyG validation. Read →
Confirms both indices predict metabolic-syndrome onset and CVD without an insulin assay.
Peronnet et al., 2021 — Regulation of glucose metabolism. Read →
Integrative model of insulin-dependent and independent glucose control.
Galgani, Moro & Ravussin, 2008 — Metabolic flexibility and insulin resistance.
Established metabolic flexibility as a measurable marker of fuel switching.
Glucose & pre-diabetes risk
Frontiers in Endocrinology, 2026 — Impaired fasting glucose and cardio-kidney-metabolic risk. Read →
Tracks how rising fasting glucose compounds cardiometabolic risk over time.
BMJ, 2016 — Pre-diabetes and cardiovascular disease.
53 cohorts, 1,611,339 people — the largest meta-analysis on pre-diabetes and CVD.
J. Am. Coll. Cardiology, 2010 — Impaired fasting glucose and CVD.
Meta-analysis of 18 prospective studies; the risk gradient across glucose bands.
Combined cardiovascular risk
Hashemi Madani et al., 2020 — Golestan Cohort. BMC Cardiovascular Disorders. Read →
Directly relevant to the combined-signal logic behind the score.
Suzuki, Kaneko et al., 2023 — J. Am. Heart Association. Read →
Reinforces the multiplicative risk of combined metabolic signals.
Wilson et al. / Framingham Heart Study — Circulation, 2008.
The foundational validated model behind QRISK3, the UK gold standard.
Waist-to-height ratio
Frontiers in Nutrition, 2025 — Waist-to-height ratio and mortality. Read →
Prospective cohort: waist-to-height ratio predicts all-cause and obesity-related mortality.
PLOS ONE, 2024 — Waist-to-height ratio vs BMI and waist circumference. Read →
Large US cohort: waist-to-height ratio is the stronger predictor of cause-specific mortality.
Cholesterol — LDL
PLOS Medicine, 2020 — Lipoprotein lipids and coronary heart disease (Mendelian randomization). Read →
Genetic evidence that LDL causally raises coronary heart-disease risk.
Frontiers in Cardiovascular Medicine, 2023 — Hypercholesterolaemia and ischaemic heart disease (Mendelian randomization). Read →
Independent causal confirmation using genetic instruments.
Cholesterol Treatment Trialists' Collaboration — Lancet, 2010. 170,000 participants.
Each 1.0 mmol/L reduction in LDL cut major vascular events by 21%.
Resting heart rate
Zhang et al., 2016 — Resting heart rate and mortality. CMAJ meta-analysis. Read →
Higher resting heart rate is associated with higher all-cause and cardiovascular mortality.
Avram et al., 2019 — Real-world resting heart-rate norms, Health eHeart Study. n = 66,788. Read →
The population reference range behind the resting-heart-rate threshold.
Uric acid
Frontiers in Endocrinology, 2026 — Serum uric acid and coronary heart disease. Read →
Updated dose-response meta-analysis linking uric acid to coronary risk.
PLOS ONE, 2023 — Uric acid and 20-year all-cause mortality in older adults. Read →
Sex-specific uric acid levels predict ischaemic ECG changes and long-term mortality.
Fitness & longevity — the Functional Age Index
Scientific Reports, 2021 — Cardiorespiratory fitness and disease outcomes. Read →
Dose-response: higher measured fitness, lower risk across outcomes.
Kokkinos et al., 2022 — Fitness and mortality. JACC. n = 750,000 veterans.
One of the largest fitness-mortality cohorts ever assembled.
Kodama et al., 2009 — Cardiorespiratory fitness and mortality. JAMA meta-analysis.
Fitness as an independent predictor of all-cause mortality.
Strength & sarcopenia — grip strength
BMC Medicine, 2022 — Handgrip strength, morbidity and mortality. Read →
Grip strength predicts mortality across cardiometabolic multimorbidity.
Frontiers in Public Health, 2023 — Grip strength and all-cause mortality. Read →
Independent association between grip strength and survival in older adults.
Biological age
Liu et al., 2018 — PhenoAge: a new aging measure (NHANES). PLOS Medicine. Read →
The open-access validation of phenotypic age against morbidity and mortality.
eLife, 2020 — The challenges of estimating biological age. Read →
Independent methodological validation of biological-age estimation.
Belsky et al., 2020 — Quantifying biological ageing (KDM). PNAS.
The method behind the biological-age estimate.

The clinical guidelines we drew from.

Thresholds are not ours to invent. Each range is drawn from recognised clinical guidance.

NICE NG136Hypertension and home blood-pressure monitoring thresholds.
NHS lipid guidance (general population)LDL cholesterol reference ranges.
WHO diabetes classificationFasting glucose diagnostic thresholds.
ADA Standards of CareGlucose and pre-diabetes bands.
EWGSOP2 (2019)European consensus on sarcopenia and grip strength.
Asian Working Group for Sarcopenia (2019)Strength and function cut-points.
QRISK3 / NHS Health CheckUK cardiovascular risk-assessment standard.

MetaScore supports wellness assessment, education and lifestyle coaching. It does not diagnose medical conditions or replace advice from a doctor or qualified healthcare professional. Thresholds and their sources are recorded and referenced within the platform.

See the evidence in action.

Book a free demonstration and a complimentary metabolic assessment — and see your own results, built on this same research.

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