Why does your body age differ between WHOOP, Garmin and Apple Health?

What each device actually calculates

Before comparing numbers, it's worth knowing that "biological age" isn't one metric with three implementations — it's three genuinely different models that happen to share a name.

Two things fall out of that table immediately: WHOOP is the only one of the three built on an explicit mortality-risk framework rather than a population percentile, and "Apple Watch biological age" is a category error — the watch measures inputs, it doesn't compute an age.

Apple Watch doesn't have a biological age feature — you're comparing a third-party app

This is worth being precise about, because it's the most common source of confusion in "why don't my numbers match" questions. Open the Health app on an Apple Watch and you'll find Cardio Fitness (VO2max), resting heart rate, HRV, sleep stages and steps — real, useful signals. What you won't find anywhere in Apple's own software is a single number that converts those into an age. Every "biological age on Apple Watch" result you've seen — whether it came from Vita, or any other app that reads Apple Health data — is a third-party calculation running on top of Apple's raw metrics, not an Apple product.

That matters for the comparison question, because it means an "Apple-based" estimate isn't really one thing at all. Two different apps reading the identical Apple Health export can and do produce different ages, for the same reason WHOOP and Garmin differ from each other: different weighting, different reference population, different update cadence. If you've compared your WHOOP Age to a biological-age app running on your iPhone and found a gap, you're not seeing "WHOOP vs. Apple" — you're seeing WHOOP's model vs. one specific third party's model, both reading overlapping but not identical raw data.

The two underlying math models, and why they don't reconcile

Strip away the branding and there are really only two approaches at work here, and they answer different questions.

• Hazard-ratio / mortality-risk models (WHOOP Age's approach). For each input metric, this method consults published research estimating that metric's association with all-cause mortality, then asks: what age would someone need to be, on average, to carry the same mortality risk as your current numbers? The output is framed as an "effective age" tied to a health-outcomes literature base — which is a meaningfully different question from "how fit are you for your age."
• Age-and-sex percentile models (Garmin's approach, and the model most Apple Health-based apps use for VO2max in particular). This method compares your metric to a reference distribution of people your age and sex, and reports where you land as an equivalent age. It's a fitness-percentile question, not a mortality-risk question, even though both get reported as "X years old."

Those are not two implementations of the same calculation — they're two different questions wearing the same label. A hazard-ratio model and a percentile model can legitimately disagree even when they're looking at identical raw VO2max and resting-heart-rate numbers, because they're not trying to answer the same thing. That's before you even get to the fact that each model also chooses different additional inputs (lean body mass and strength-training time for WHOOP; body composition for newer Garmin devices; lab-report markers for cross-source apps like Vita), which shifts the number independently of the underlying math.

What to actually do with three disagreeing numbers

None of this means the numbers are useless — it means you're using them for the wrong comparison. Here's the practical protocol:

1. Pick one estimate and track its own trend. Whichever device or app you use most consistently, judge it against its own history — is this month's number lower than last month's — not against a different tool's output for the same week.
2. Expect a reset when you switch devices or apps. A new model with a short data history behaves differently than one with six months of your data behind it. Give any new estimate 3-4 weeks of consistent data before drawing conclusions from it.
3. Use the underlying metrics as the tie-breaker, not the headline age. If WHOOP Age says one thing and your Apple-based estimate says another, look at what actually moved — VO2max, resting heart rate, HRV, sleep. If those individual numbers agree on direction, both age estimates are reading the same underlying reality correctly; they just convert it to years differently. See biological age vs. chronological age for how these wearable estimates stack up against blood and epigenetic tests on cost and precision.
4. Don't compare your number to anyone else's, on any device. Different starting fitness, different device, different model — a gap between two people's ages tells you almost nothing about who's actually healthier.
5. If you use both WHOOP and Apple Health, look for an estimate that reconciles them instead of picking one. Vita's Body Age is built specifically to blend WHOOP data (when you have a band) with Apple Health and lab-report markers into one continuous number, so switching or adding a device doesn't reset your baseline the way jumping between two single-source apps does — see Vita vs. WHOOP for how that fits alongside WHOOP's own Healthspan feature rather than replacing it.

The bottom line

WHOOP Age, Garmin Fitness Age and any Apple Health-based estimate disagree by design, not by error — they run different math (mortality hazard-ratio vs. age-percentile) on different combinations of inputs, and in Apple's case, the "device" isn't even the one doing the calculating. Comparing the three headline numbers to each other is close to meaningless; comparing each number to its own history over weeks and months is exactly what it's built for. If you're on more than one platform, an estimate that actually merges the data — rather than forcing you to average two disagreeing ages in your head — is the more useful tool going forward.