What 29 Daily Health Metrics Taught Me About Recovery at 52

I’ve been tracking health data obsessively for months now. Apple Watch, MyFitnessPal, InBody scans, Strava. Every morning I wake up to a brief that pulls 29 different metrics into one report. Not because I enjoy spreadsheets (I do, but that’s beside the point). Because at 52, training for Hyrox and a half-marathon, I can’t afford to guess.

Here’s what I’ve learned so far. Some of it confirmed what I expected. Some of it surprised me.

The metrics I actually track

Every day, my Apple Watch and MyFitnessPal push data to a system I built. It captures:

Vitals: resting heart rate, HRV, respiratory rate, blood oxygen saturation, VO2 max, cardio recovery, wrist temperature

Sleep: total hours, core sleep, deep sleep, REM, time awake

Activity: steps, distance, active calories, basal calories, exercise minutes, walking speed, daylight exposure

Running mechanics: speed, power, stride length, ground contact time, vertical oscillation

Nutrition: calories, protein, carbs, fat, fiber, sugar, cholesterol, potassium

That’s a lot of numbers. Most of them are useless in isolation. The value is in what they tell you when you look at them together.

Deep sleep is the metric I was ignoring

Everyone talks about total sleep hours. Seven to eight hours, you’re fine, right? Not exactly.

My total sleep has been averaging 5.4 hours this week. Not great, but I’ve trained through worse. What actually flagged something was my deep sleep. Some nights I’m getting 31 minutes. Others 43 minutes. The research says adults need 1 to 2 hours of deep sleep for adequate growth hormone release, which is when your body does the bulk of its muscle repair.

At 52, with a training load that includes 6am sessions six days a week, deep sleep isn’t a nice-to-have. It’s where the adaptation happens. I can eat 160g of protein and train perfectly, but if my deep sleep is consistently under 45 minutes, I’m not recovering. The protein just gets oxidised.

The connection I didn’t expect: fiber intake. On days where my fiber drops below 20g, my deep sleep tanks within 24 hours. The mechanism makes sense when you read the research. Fiber feeds gut microbes that produce short-chain fatty acids, particularly butyrate, which acts as a sleep-promoting signal. One study showed a 50% increase in non-REM sleep in subjects with higher SCFA production. But I never would have connected “didn’t eat enough vegetables yesterday” to “slept terribly” without seeing both numbers side by side.

My running form tells me more than my pace

I’ve been watching my pace improve over the past few weeks. March 3: 6:56/km. March 19: 6:23/km. That’s 33 seconds faster per kilometre in two and a half weeks. Feels good.

But the running mechanics data tells a more complete story.

Ground contact time: 257ms. That’s the time each foot spends on the ground per stride. Lower is generally better for efficiency. Elite runners are typically under 200ms. At 257ms, I’m in recreational territory, which is fine, but it tells me I can gain free speed by improving my turnover rather than pushing harder.

Vertical oscillation: 8.7cm. This is how much I bounce up and down with each stride. Energy spent going up is energy not spent going forward. Below 8.5cm is considered efficient. I’m close but leaking a bit.

Stride length: 1.01m. Combined with my ground contact time, this gives me a cadence picture. Shorter strides with faster turnover would reduce my GCT and oscillation simultaneously.

Running power: 217W. This is the total energy output per stride. As my form improves, I should see the same pace at lower wattage, which means better economy.

None of these numbers mean much alone. A pace of 6:23/km could be achieved with terrible form and high effort, or efficient form at moderate effort. The mechanics tell me which one I’m doing. And right now, I’m improving pace while my form metrics are staying stable, which means the gains are coming from fitness, not form. That’s fine for now, but it means there’s a form efficiency reserve I haven’t tapped yet.

HRV is a lagging indicator, not a score

My HRV this week has been bouncing between 26 and 33ms. My baseline from February was around 45ms. That looks alarming on paper.

But HRV doesn’t exist in a vacuum. It’s a lagging indicator of autonomic nervous system load. Mine dropped during a two-week holiday in Tasmania where I changed time zones, ate differently, disrupted my sleep routine, and then came back to full training volume immediately. That’s exactly when you’d expect HRV to dip.

What matters more is whether it’s trending back toward baseline. And it is. Slowly. The coaching insight here isn’t “your HRV is bad, take a rest day.” It’s “your nervous system is still recalibrating after a disruption, expect it to take another week, and don’t stack high-intensity sessions back to back until it recovers.”

The resting heart rate tells the same story from a different angle. Mine is sitting at 53-54 bpm. That’s actually solid. If my HRV was low AND my resting HR was elevated, I’d be worried about overreaching. But low HRV with normal resting HR usually means lifestyle stress, sleep disruption, or recovery lag rather than overtraining.

What I eat shows up in what I track 24 hours later

This is the one that keeps hitting me. Nutrition isn’t just about fuelling the day’s workout. It’s about setting up tomorrow’s recovery.

My protein target is 159g daily (2.0g/kg at 79.6kg). On days I hit it, my recovery scores the next morning are consistently higher. On days I fall short, particularly below 120g, my HRV and deep sleep both take a hit.

The fiber connection I mentioned earlier is part of this too. My daily target is 25g+. Most days I’m hitting 22-23g. Not terrible, but the research suggests the gut microbiome benefits accelerate above 25g. I’m close enough that a single extra serving of vegetables or oats would push me over.

The calorie picture is trickier. My MyFitnessPal data shows 585 kcal for yesterday. That’s clearly not all I ate. It’s what I logged. The actual target based on my BMR (1,854 kcal) plus active calories (974) is closer to 2,828 kcal. The gap between tracked and actual intake is something every food logger deals with. But at least having the target visible keeps me honest about the direction.

Body composition is the scoreboard

All these daily metrics are inputs. The scoreboard is the InBody scan.

My latest (24 February):

• Weight: 79.6kg (at goal)
• Skeletal muscle mass: 39.1kg
• Body fat: 13.7%
• InBody score: 91/100
• Visceral fat: 4/9

The trend from November to February was concerning. My SMM dropped from 40.8kg to 38.0kg, then recovered to 39.1kg. That’s a 1.7kg lean mass dip over three months, partly due to inconsistent training over the holidays and partly due to insufficient protein on too many days.

The daily metrics exist to prevent that from happening again. If I can see my protein, sleep, and training load every single morning, I can catch a bad trend before it shows up on the scan eight weeks later.

The 5am brief

Every morning at 5am, before I head to the gym, I get a report that pulls all of this together. Recovery score. Sleep breakdown. Vitals. Yesterday’s training. Running mechanics. Nutrition. And coaching insights that connect the dots.

Not “your sleep was 6.7 hours.” That’s a number. Instead: “Your fiber was 22g and your deep sleep was 43 minutes. Push for 25g+ today. Also your HRV is 7ms below baseline, consider Zone 2 instead of intervals.”

That’s the difference between tracking data and using data. The tracking is easy. Every wearable does it. The synthesis is what’s been missing. Connecting sleep quality to fiber intake to training readiness to body composition trends is where the actual value lives.

I’m 117 days out from Hyrox and 156 from a half-marathon. At 52, the margin for error is smaller than it was at 30. I can’t recover from stupid training decisions the way I used to. So I let the data catch the stupid decisions before I make them.

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Suggested X Thread

Tweet 1: I track 29 health metrics daily. Apple Watch, MyFitnessPal, InBody scans, Strava. Most of them are useless alone. The value is in what they say together. Thread on what I’ve learned at 52.

Tweet 2: Deep sleep is the metric I was ignoring. Total hours? Fine. But 31 minutes of deep sleep means growth hormone isn’t peaking. At 52, that’s where muscle repair happens. You can eat 160g protein but if deep sleep is under 45min, you’re not recovering.

Tweet 3: The connection I didn’t expect: fiber intake. Below 20g, my deep sleep tanks within 24 hours. Fiber feeds gut microbes that produce sleep-promoting SCFAs. Never would’ve connected “ate fewer vegetables” to “slept terribly” without seeing both numbers.

Tweet 4: Running pace improved 33s/km in 2.5 weeks. But ground contact time, vertical oscillation, and stride length tell me the gains are from fitness, not form. There’s a form efficiency reserve I haven’t tapped yet. Free speed sitting on the table.

Tweet 5: HRV dipped from 45 to 26ms. Looks alarming. But resting HR is still 53bpm. That pattern = lifestyle/sleep disruption, not overtraining. Context matters more than the number. Every morning brief I get now connects these dots before I train. That’s the difference.