# @mackinprof on Instagram

- **Type:** Image
- **Original URL:** https://www.instagram.com/p/DIqwP_-Micn
- **Gondola URL:** https://gondola.cc/posts/59739858-mackinprof-instagram
- **Thumbnail:** https://img.gondola.cc/tr:w-,h-,fo-auto/postThumbnails/4ef07f9d9b.jpg
- **Posted:** 2025-04-20T12:15:34.000+00:00
- **Account Owner:** Stuart Phillips (@mackinprof) — https://gondola.cc/mackinprof

## Caption

WHAT’S THE BEST WAY TO TRAIN?

What combination of resistance training variables (load, sets, frequency) works best for gaining muscle strength and size? We've got answers backed by science! 💪

We performed the largest-ever network meta-analysis on resistance training (178 studies, 5097 participants  for strength, 119 studies, 3364 participants for hypertrophy)

🎯 Main takeaway:
ALL resistance training prescriptions improved strength and hypertrophy compared to no exercise, and there was actually NO statistically significant difference between them!

👉 Train smarter, not just harder! Choose what you prefer, stay consistent, and keep lifting!

If you care about maximizing results:

✅ Strength Gains (5097 people studied 45% women):
🥇 Heavier Loads, Multiple Sets, 3x/week — Ranked ‘best’ (Effect size: 1.60)
🥈 Heavier Loads, Multiple Sets, 2x/week (Effect size: 1.59)
🥉 Heavier Loads, Multiple Sets, 1x/week (Effect size: 1.54)

HEAVIER loads win because that’s what you’re practicing doing – want your 1RM to go up? Practice lifting your 1RM 12

✅ Muscle Hypertrophy (3364 people studied 47% women):
🥇 Heavy Loads, Multiple Sets, 2x/week — Ranked ‘best’ (Effect size: 0.66)
🥈 Lower Loads, Multiple Sets, 2x/week (Effect size: 0.56)
🥉Heavy Loads, Multiple Sets, 3x/week (Effect size: 0.51)

Reference: Currier et al. (2023), British Journal of Sports Medicine (link in bio, PMID  37414459)

#StrengthTraining #MuscleGrowth #ResistanceTraining #FitnessScience #TrainSmart #LiftingWeights #ExercisePrescription #MetaAnalysis

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## Tags

musclegrowth, exerciseprescription, liftingweights, resistancetraining, strengthtraining, trainsmart, fitnessscience, metaanalysis

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