Aging, Science

Who’s Really Winning at Longevity?

Last updated: April 9, 2026

Crissman LoomisSeptember 4, 2025

The longevity space has become a spectator sport. Bryan Johnson spends $2 million annually and takes 100+ supplements daily, regularly posting detailed biomarker updates. Siim Land combines biohacking with athletic performance and recently responded to Bryan’s posts with his own comprehensive biomarker comparison.¹ Meanwhile, I’ve been testing whether minimal interventions can match their results.

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Inspired by their biomarker transparency, I compiled data from all three of us. The results challenge common assumptions about what optimization requires.

What Is Longevity

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The Investment Gap

When Siim published his superior biomarkers compared to Bryan, critics dismissed them: “Yeah, but you’re 18 years younger.” Here’s what makes this comparison interesting: I’m 6 years older than Bryan.

Consider the inputs by age:

Siim Land (29 years old):

• 6 regular supplements
• $100 monthly cost (supplements cost)*
• 4 hours weekly exercise
• 11,000 daily steps

Bryan Johnson (47 years old):

• 100 daily supplements
• $170,000 monthly cost (???)
• 6 hours weekly exercise
• 4,000 daily steps*

My approach (53 years old):

• 1 daily supplement (potassium)
• $60 monthly cost (gym membership)
• 1.5 hours weekly exercise
• 20,000 daily steps

*guesstimated

So we have a 53-year-old spending 3,000x less money and a quarter of the time in the gym compared to a 47-year-old, but walking 5x more. How do you think the biomarkers will compare?

Methodology: Creating Comparisons

Comparing biomarkers requires normalization since optimal ranges vary. For the charts, I scored each marker on a 0-100 scale where:

• 70-95: Within optimal range
• 30-70: Within normal but not optimal
• Below 30: Outside normal range

I reversed the direction for biomarkers where lower is considered better, such as cholesterol measures.

Category Winners: Where Each Approach Excels

Metabolic Health

The metabolic markers are remarkably similar across all three of us:

• HbA1c: Bryan 5.1%, Siim 4.9%, Me 5.0% (all within optimal range)
• Fasting glucose: Bryan 97, Siim 80, Me 86 mg/dL (all normal)
• Uric acid: Bryan 4.2, Siim 5.1, Me 5.2 mg/dL (all normal)

Siim edges ahead with perfect homocysteine at 5.6 μmol/L. Mine runs high at 11.5 μmol/L—something I haven’t addressed yet. Despite Bryan’s extensive methylation support supplements, we’re achieving essentially identical metabolic health.

Cardiovascular Fitness

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Siim’s combination of heavy training and younger age shows:

• VO2max: 66 ml/kg/min (99th percentile)
• Resting heart rate: 39 bpm
• HRV: 100ms

Bryan achieves solid fitness (VO2max 54.2) with his protocol. My current VO2max of 48 reflects lower cardio training. I do a mix of aerobic exercise and high-intensity interval training for less than an hour weekly. When I was training for my marathon, my VO2max reached 61.5, demonstrating how quickly this marker responds to dedicated training.

My blood pressure is higher than I would like it, at 121/78. That’s down from 126/83, thanks to taking potassium citrate supplements, my single longevity supplement.

Inflammation Markers

Here’s where minimal intervention shines:

• hsCRP: 0.05 mg/L (Bryan: 0.3, Siim: 0.1)
• Optimal inflammation despite no anti-inflammatory supplements

This ultra-low inflammation likely comes from 20,000 daily steps. Walking reduces inflammatory cytokines through multiple pathways including improved insulin sensitivity and reduced visceral fat.²

Lipid Panel

The lipid story is complex:

• ApoB (cardiovascular risk): Siim wins at 58 mg/dL
• HDL-C: I lead at 113 mg/dL 
• Triglycerides: Siim optimal at 39 mg/dL

My HDL of 113 mg/dL exceeds even the “optimal” range—a direct result of 20,000 daily steps. HDL increases somewhat linearly with step count,² and with 20,000 steps daily , the elevation is dramatic. High HDL levels can be caused by heavy alcohol consumption or overtraining. Given my moderate alcohol consumption and normal level of aerobic exercise, my HDL levels are likely protective.

Aging Biomarkers

Bryan’s Dunedin PACE shows 0.67 (aging at 67% normal speed), though he takes this test frequently and may be optimizing for it. The test creators acknowledge that only supplementation moves this metric, not diet or exercise, which raises questions about its validity as a comprehensive aging marker.

My Dunedin PACE varied from 0.8 to 0.98 across two tests, showing significant variability. Siim’s 0.62 is impressive but again, without supplementation, this metric may not capture the full picture of biological aging.

Bryan’s other aging markers:

• Telomere length: 11.4kb
• PhenoAge: 8.7 years younger

These metrics suggest his supplementation protocol impacts aging biomarkers, though whether this translates to actual longevity remains unknown.

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The Surprising Standouts

Liver Function

• AST: 32 IU/L (Bryan: 24, Siim: 23)
• ALT: 30 IU/L (Bryan: 21, Siim: 23)
• GGT: 23 U/L (Bryan: 8, Siim: 11)
• ALP: 47 IU/L (optimal range, all three similar)
• Albumin: 4.8 g/dL (Bryan: 4.5, Siim: 4.6)

While Bryan and Siim have lower transaminases, all values are well within healthy ranges. My slightly higher but still normal AST/ALT likely reflects moderate alcohol consumption rather than liver stress.

Kidney Function

Despite Siim’s concerns about Bryan’s kidney health from extensive supplementation, the data shows mixed results:

• eGFR: Siim 112, Me 82, Bryan 74 mL/min
• Cystatin-C (creatinine-neutral metric): Bryan 0.87, Me 0.82, Siim 0.67 mg/L

Bryan’s cystatin-C is still slightly below median for his age, suggesting his lower eGFR might reflect high muscle mass or creatine supplementation affecting creatinine levels rather than true kidney dysfunction. Siim shows the best overall kidney markers.

Strength Performance

Siim dominates:

• Bench press: 136kg
• Squat: 160kg (tied with me)
• Grip strength: 68.1kg

Bryan’s numbers (bench 109kg, squat 115kg,³ grip 59.9kg) reflect his unconventional training approach. He avoids traditional compound lifts like squats and deadlifts in favor of trendy exercises like backward sled pulls. While this may reduce injury risk, it appears to compromise traditional strength metrics like grip strength.

This demonstrates that targeted strength training with basic compound movements outweighs any supplement protocol for building functional strength.

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Body Composition & Bone Density

Bone mineral density (BMD) tells an interesting story:

• BMD T-scores: Siim 1.54, Bryan 1.47, Me 1.156

Both Siim and Bryan have excellent bone density. Siim lifted from a young age, while Bryan was previously overweight—both factors that boost BMD. As someone who’s always been thin, my first BMD check at 44 showed borderline osteopenia, over 1 standard deviation below expected for age. Since then, I’ve been hitting the gym hard and have improved to the 40th percentile—proof that bone density can be improved even in your 40s with dedicated strength training.

Visceral fat shows all three of us in healthy ranges:

• Siim: 0.25L (exceptional)
• Me: 0.51L
• Bryan: 0.56L

Cost-Benefit Analysis (A Tongue-in-Cheek Calculation)

Let’s have some fun with the numbers. Calculating biomarker improvement per dollar spent monthly:

Bryan Johnson:

• Normalized biomarker score: 65
• Cost: $170,000/month
• Efficiency: 0.00038 points per dollar

Siim Land:

• Normalized biomarker score: 78
• Cost: $300/month
• Efficiency: 0.26 points per dollar

My approach:

• Normalized biomarker score: 67
• Cost: $60/month
• Efficiency: 1.12 points per dollar

By this admittedly arbitrary metric, I achieve 3,000x better efficiency than Bryan and 4.3x better than Siim in biomarker optimization per dollar spent. Of course, this assumes all biomarkers are equally weighted and that normalized scores translate directly to health outcomes—both questionable assumptions. But it illustrates the diminishing returns of extreme optimization.

The Longevity Tiers

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The Unaging Challenge

References ▼References ▲

1. Siim’s biomarker post
2. Dose‐response association between step count and cardiovascular disease risk markers in middle‐aged adults
3. Siim’s estimate