Weightology Research Review January 2020

The January 2020 issue of the Weightology Research Review is now online!⁠

If you want to get jacked, this is THE issue you'll want to read.⁠

Here's the table of contents for this issue:

  • Volume or training to failure: which is more important to building muscle?
  • Does plate size impact calorie intake?
  • Training to failure: the load matters!
  • Muscle confusion: more psychological than physiological
  • More volume = more muscle? It may depend on the training structure!
  • Highly palatable foods: we know them when we see them...or do we?
  • NEAT reduction: a matter of efficiency
  • Breakfast: metabolism booster or buster?

There's been a number of recent studies on training volume and training to failure, and I cover them all. In one of the reviews, I go over the recent Brigatto study, just what it means for you in terms of training volume, and how it fits in with all the other volume research. In two other reviews, I cover training to failure and just when you should and shouldn't. Finally, I cover a recent study on "muscle confusion" and whether there's any benefit or detriment to it.⁠

I round things out with reviews on plate size and calorie consumption, objective identification of hyperpalatable foods, NEAT and muscle efficiency, and breakfast and metabolism.⁠

Here's a visual snapshot of some of the content:

Whether you're trying to build muscle, lose fat, compete in physique shows, or help your clients lose weight and get fit, there's something in this issue for everyone.⁠

Subscribers get an interactive, mobile-friendly, color PDF each month, and access to an archive of nearly 300 video and written research reviews, evidence-based guides, and Q&As.⁠

Want to see more? Click here to subscribe!

Want to see some example content? Click here!

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Keeping up with the research is tough, so let us do the work for you. Consider signing up for Research Explained in Practical Summaries (REPS). We cover 5 studies per month and break everything down for you, so you don't need a PhD to interpret the data. You also get access to all back content. Click here to learn more.  
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