Diagnostic dashboard

The Numbers That Predict How Long You’ll Live

A practical scorecard for fitness, function, waist, pressure, and labs. The strongest free measures come before expensive biological-age panels.

Quick reference · signature tool

Biomarker Scorecard

Enter a value to save it locally. The colored gauges are orientation aids, not validated risk calculators; use the target text and measurement protocol, especially for age/sex-specific fitness and strength norms.

Metric
Evidence
Screening target / how to read it
Your value
VO2 max
mL/kg/min
STRONG
At or above the 50th percentile for age/sex on the same test; a lab test is not interchangeable with every watch estimate.
Trend first
Grip strength
best hand, kg
STRONG
Compare to an age/sex/handedness table; same dynamometer and position every time.
Trend first
Usual gait speed
m/s over 4–10 m
STRONG 65+
≥1.0 m/s is a useful older-adult functional benchmark; record the distance and whether the start was rolling.
Measure twice
Resting heart rate
bpm, morning trend
MODERATE
Personal baseline matters; a persistent rise is more actionable than chasing a universal athlete number.
Trend first
Waist ÷ height
same units
STRONG
Below 0.50 is a simple adult screening rule; measure waist consistently, not after a large meal.
<0.50 screen
Home systolic BP
mm Hg, averaged
STRONG
Use repeated validated-cuff readings; clinic targets and treatment decisions are individualized.
Average, don’t panic
HbA1c
percent
STRONG
<5.7% is the U.S. diagnostic normal range; anemia and some conditions can distort it.
Lab context
ApoB / non-HDL
mg/dL
STRONG
Risk-based, not one universal target. ApoB counts atherogenic particles; use the lab reference and risk discussion.
Risk-based
hs-CRP
mg/L
CONTEXT
<1 mg/L is a common low-CV-risk category; infection, injury and training can temporarily raise it.
Repeat if ill
5× sit-to-stand
seconds
FUNCTION
Use the same chair and no hands. Faster is generally better; age-specific interpretation is essential.
Protocol matters
Push-up capacity
standard reps
LIMITED
A functional proxy, not a lifespan test. Protocol, age and training history dominate a raw count.
Protocol matters
Epigenetic pace
consumer test
EMERGING
No actionable universal cutoff. A clock can be informative research, but do not turn a single paid result into a verdict.
Do not score

How to read a mortality claim

Predictive ≠ causal

Low grip can predict mortality because illness reduces strength. Improving grip is useful, but a dynamometer is not proof that the number itself causes lifespan.

Hazard ratio is relative

“HR 1.16 per 5 kg lower grip” compares rates within a study model. It does not predict your probability of dying next year.

Use trends and protocols

A cuff, watch, lab, chair height, time of day and training fatigue can move a reading. Standardize before interpreting change.

Start free

VO2 proxy, grip, gait, waist and home BP reveal more actionable information than many expensive multi-omics panels.

Working knowledge

What each metric predicts—and what it cannot tell you

VO2 max / cardiorespiratory fitness — strongest functional predictor

In 122,007 adults referred for treadmill testing, low versus elite fitness had adjusted all-cause mortality HR 5.04. This is a clinical referral cohort and association, not a promise that adding one MET multiplies lifespan. Measure with a lab test, a validated field protocol, or a wearable trend; compare only like with like. Example: a 45-year-old whose watch estimate rises from 28 to 33 mL/kg/min after months of training has a useful fitness trend even if the absolute estimate is biased. Move it with progressive aerobic work; see running and cycling.

Grip strength — cheap, global, and strongly prognostic

PURE followed 139,691 adults in 17 countries: each 5 kg lower grip was associated with 16% higher all-cause mortality (HR 1.16). Measure 2–3 maximal trials per hand with the same dynamometer and protocol; record the best or average consistently. Example: 38 kg today is not “good” without age/sex norms; it is a repeatable baseline. Improve whole-body strength, not forearm squeezing alone, via resistance training.

Gait speed — an older-adult vital sign

In 34,485 community-dwelling adults aged 65+, each 0.1 m/s faster usual gait speed was associated with HR 0.88 for mortality. Mark a 4- or 10-meter course, use a rolling start, time the middle distance, and calculate meters ÷ seconds. Example: 4 m in 4 seconds = 1.0 m/s. Slowdown, new asymmetry, pain, dizziness, or falls merits clinical context—not a self-rehabilitation protocol.

Resting HR and HRV — useful trends, weak universal targets

Higher resting HR is associated with higher mortality in cohort meta-analyses, but illness, medication, heat, sleep, alcohol, dehydration and measurement all matter. HRV is even more device- and algorithm-dependent. Example: a stable 52 bpm baseline that becomes 68 for several mornings may signal recovery, infection, load or medication change; it is not an aging score.

Waist-to-height — simple adiposity screen

Divide waist circumference by height in the same units. Example: 86 cm ÷ 178 cm = 0.48. The commonly used under-0.50 screen is useful because it scales waist to body size, but pregnancy, body composition and ethnicity complicate interpretation. Pair it with BP, glucose and function rather than treating it as a body-worth grade.

Blood pressure — causal risk, measurement-sensitive

Use an appropriately sized validated upper-arm cuff, sit quietly, and average multiple readings on multiple days. Example: an isolated 142/88 after coffee is not equivalent to a home average of 142/88. Repeated elevation deserves a clinician-led plan; do not “biohack” pressure with supplements.

ApoB / non-HDL — atherogenic particle burden

ApoB is a count proxy for particles that can enter arterial walls. It is often useful when LDL-C and triglycerides/insulin resistance disagree, but the correct target depends on absolute cardiovascular risk. Example: an ApoB of 82 mg/dL means little without age, BP, smoking, diabetes, LDL/non-HDL and clinical history. Use the lab decoder for context.

HbA1c / glucose — metabolic exposure, not a one-number diet grade

HbA1c estimates recent glycemic exposure; U.S. diagnostic categories use <5.7% normal, 5.7–6.4% prediabetes, and ≥6.5% diabetes when confirmed appropriately. Example: 5.8% should lead to context, repeat testing and risk discussion, not an internet diagnosis. Conditions affecting red cells can make A1c misleading.

hs-CRP — nonspecific inflammation signal

hs-CRP is commonly categorized <1, 1–3, and >3 mg/L for cardiovascular risk context, but an infection, injury, dental issue, or hard workout can transiently elevate it. Example: a 5 mg/L result during a cold should not become a “chronic inflammation” identity; repeat under stable conditions if clinically appropriate.

Sit-to-stand and push-ups — practical function proxies

Five-times sit-to-stand captures lower-body function; push-up capacity has a notable firefighter cohort association with cardiovascular events but is not general-population mortality proof. Example: record “five rises from a 45-cm chair, arms crossed, 9.4 seconds” rather than just “felt strong.” The protocol is the data.

Biological-age clocks — research signal, poor steering wheel

Epigenetic clocks and pace-of-aging measures may predict outcomes at population level, but consumer offerings differ in assay, algorithm, repeatability and interpretation. Example: a $300 result that says “+4 years” gives no validated instruction more important than fitness, smoking, BP, waist and clinically indicated labs. Pay only if the uncertainty itself is worth it to you.

Prioritize the five you will remeasure

If you can track only five: choose a fitness proxy, grip or sit-to-stand, waist-to-height, home BP average, and risk-appropriate lipids/ApoB. That mixes function, exposure and clinical risk. A bad functional result can reflect unrecognized disease—do not assume it is merely motivation.

Common mistakes

Buying a $500 panel first.

Measure the free functional giants and a validated home BP trend before upgrading measurement complexity.

Trusting one wearable reading.

Optical sensors, algorithms and context change. A trend on the same device is more useful than a cross-brand comparison.

Optimizing a marker in isolation.

A predictive biomarker may reflect disease, medication, training status, or reverse causation. Interpret the person, not a traffic-light row.

Sources and cluster links

Primary/authoritative sources accessed 2026-07-13: Mandsager et al. 2018 (fitness); Leong et al. 2015 PURE (grip); Studenski et al. 2011 (gait); Celis-Morales et al. 2018 (grip replication); CDC A1c categories. Norms must be matched to the protocol and reference population; this page intentionally avoids fabricating universal VO2/grip cutoffs.