Monday, April 23, 2012

Meta Analysis Confirms: Strength Gains Depend on Training Status, Age, Workout Frequency, Rest Intervals & More

Image 1: Johanna Quas (86), "Germany's Fittest Granny"; check out this video of her on the high bar to see an extraordinary exception proving the rule - everybody who believes he/she could rival Johanna's gymnastic skills, could try that at the next world cup, where she probably will be competing again.
"Rodents are no little human beings", you will probably have heard or read this sentence at least a hundred times by now, but have you heard someone say "3 sets are not 1 set", "women are not men" or "8 weeks are not 16 weeks"? No, well in that case, a recently published meta-analysis of 45 primary strength training studies involving 1712 participants by Michael Fröhlich, Lutz Links and Andrea Pieter, is for you (Fröhlich. 2012).

Age, sex, training status, ... a hell lot of things to consider

The scientists from the University of Saarland and the Deutsche Hochschule für Prävention  und Gesundheitsmanagementin Saarbrücken conducted an extensive analysis of the respective training outcomes depending on individual preconditions of the subjects and study specific methodological variables like
  • training status, 
  • gender, 
  • age,
  • duration of the study,
  • total number of workouts,
  • training frequency,
  • periodization,
  • number of sets,
  • rest times between sets
and came up with a whole host of interesting results. And though the main utility of the effect sizes the researchers calculated based on data that was pre-coded according to an adapted scheme from Rustenbach (2003) probably is to enable other scientists to design trials that will yield significant results, the dependence of the "distinctness" of the study outcomes on one or more of the aforementioned parameters could also tell you something about how to interpret study data and maybe even about the efficiency of your own strength training routine.

The average training routine performed by an average trainee

If we take a look at the "average study" from Fröhlich et al. comprehensive dataset, we can identify the following characteristics:
  • average exercises: 5 exercises
  • average duration of the study: 12.5 weeks
  • average number of workouts: 36.25 workouts total
  • average number of workouts / week: 2.62 workouts/ week
The average subject was a 26.9 year old untrained (66% of the studies) male human being and had to perform leg extensions, leg presses or squats for the lower and bench presses, biceps curls and lat pulldowns for the upper body (exercises in order of frequency).

What if...? Personal, intervention and workout specifics influence the effect sizes

Even non-experts should not be surprised that Fröhlich et al. found significant effects (p < 0.001) for both the total study duration, as well as the total number of workouts:
Figure 1: Effect sizes according to training status, subject age, no. of workouts per week, no. of sets per exercise, and rest between sets (data adapted from Fröhlich. 2012)
As figure 1 goes to show, there were yet a number of other significant (*p < 0.05) or highly significant (**p < 0.01; ***p < 0.001) parameters which may be regarded as being predictive of the significance of the study outcomes, or - put more simply - whether or not the training intervention yielded a measurable effect.

A tale of trained and untrained subjects and different training regimen

Image 2: While sex doesn't matter for rookies, trained women are having a harder time gaining strength than men.
In addition to the data in figure one, Fröhlich et al. identified a couple of other interesting cross-dependences, such as:
  • a significant difference between the effect sizes in trained men (F=1.5) vs. women (F=1.19), despite no difference for all subjects
  • there was no significant difference between hypertrophy (F=1.01), strength-endurance (F=0.97) and coordinative strength training (1-4 reps a 70%-100%; F=1.23) as far as improvements in strength across all subject groups were concerned; despite their non-significance the data does thusly confirm conventional training wisdom about
  • contrary to the global analysis the sub-analysis of untrained subjects revealed a statistically significant  influence of periodization on the effect sizes, with F=1.00 for non-periodized and 1.37 for periodized protocols
Of particular importance in the context of the ongoing discussion about the value of studies involving previously untrained subjects is also the following translated statement from the discussion of the results: 
[...] the strength increase in untrained subjects is very high at the beginning of the study. In the course of the training intervention, it is more or less continuous, but the performance increase per time unit is [...] continuously decreasing. This means that the adaptation curve is flattening out as the level of performance increases.
Now, this is not a new result, yet still one, why you, someone with say 3 years of regular strength training under his/her belt cannot expect the exact same +10% increase in bench press performance after 1-week of supplementation with Supplement X as Mr Trainingsnoob from study A, the producer of supplement X is referring to in his write-up.

Don't compare apples and oranges

Even in the absence of supplementation untrained subjects can achieve an average increase in strength of 25%-30% within the first 6 months, before they hit their first plateau (ACSM. 2009). You better take this, as well as the influence of other confounding variables into account, whenever you compare your own results with other people from the gym, or the anonymous subjects of scientific studies, if you do want to do yourself justice... that this also implies that you must have done something wrong, if you are / once you were a male scrawny beginner in the prime of his life and your bench or squat did not go up from say 100lbs to 130lbs within the first 6 months of your training, should be self-evident, right?