|GainZ - Are they all about T and we just didn't do the right statistical tests in previous studies to realize that?|
In the conclusion of their study, Mangine et al. point out that the previously used "[t]raditional statistical measures do not adequately assess the relationships between multiple variables that exist across time" (Mangine. 2016).
In order to overcome this problem, their study used what the scientists call a "unique method for analyzing these types of relationships without the need for transforming data"; and - first things first - their the PLS-SEM analysis (details below) shows: "baseline muscle size and the hormonal response to resistance exercise are related to muscle hypertrophy following 8 wks of training (Mangine. 2016).
|Figure 2: Sign. associations between PWO hormone levels and lean mass, as well as fiber size increases (West. 2012).|
|Free testosterone (upper line) and cortisol (lower line) levels before and after exhaustive endurance exercise in trained young men (Anderson. 2016).|
That's obviously significantly different from what we see in the Magine study, at hand, where the likewise previously trained subjects completed at least 28 resistance training sessions (~90%) of an 8-wk resistance-training program (4 sessions/wk) that included six upper- and lower-body exercises during each session, under supervision of certified strength & conditioning specialists.
"significant amount of information [that] is lost when using either of these statistical procedures for assessing the relationships between concepts that exist across time (i.e. hypertrophy, multiple endocrine responses) because the statistics can only assess the relationship between two sets of values" (Mangine. 2016).With their approach, on the other hand, Mangine et al. (2016) transformed the correlation between hypertrophy and the endocrine response from baseline and post-testing into a single value (i.e. change score, average score). The method to do this is called "partial least squares structural equation modeling" (PLS-SEM) and it allows estimating complex cause-effect relationship models with latent variables. Since it is a component-based estimation approach, it differs from the covariance-based structural equation modeling you'd usually expect to be used and constitutes, as the scientists summarize
"[...] a variance based procedure that utilizes bootstrapping to statistically assess the relationships between multiple latent variables that are developed from several collected indicator variables [which has] been used to assess relationships within the biomedical sciences [already... even though] it has not yet been used to assess the relationships between the post-exercise endocrine response and muscle hypertrophy" (Mangine. 2016).For it to work, the authors obviously have to assume that "the related variables were collected without systematic or random error" in their experiment that included pre-tests (PRE) of measures of muscle size (thickness and cross-sectional area) of the vastus lateralis and rectus femoris in 26 resistance-trained men who were randomly selected to complete a high-volume (VOL, n=13, 10–12RM, 1-min rest) or high-intensity (INT, n = 13, 3–5RM, 3-min rest) resistance training program while following a food-log controlled diet that was supplemented with a standardized supplement containing ~235 mL of chocolate milk (170 calories; 2.5g Fat; 29g Carbohydrate; 9g protein) or Lactaid® (150 calories; 2.5g Fat; 24g Carbohydrate; 8g protein) to each participant immediately following each workout.
|A pre- vs post-workout salivary testosterone test could hold the clue to the perfect workout | more|
|Figure 3: Actually significant was only the link between the effect of the muscle mass before the study and the testosterone response and the testosterone response on the muscle mass after the 8-wk study (Mangine. 2016).|
|Table 1: In contrast to what you may have expected, there was no sign difference in the way the hormones effected the outcomes of the 8-wk resistance training study between the high intensity and volume arm (Magine. 2016).|
- Ahtiainen, Juha P., et al. "Muscle hypertrophy, hormonal adaptations and strength development during strength training in strength-trained and untrained men." European journal of applied physiology 89.6 (2003): 555-563.
- Beaven CM, Cook CJ, Gill ND. Significant strength gains observed in rugby players after specific resistance exercise protocols based on individual salivary testosterone responses. J Strength Cond Res. 2008 Mar;22(2):419-25.
- Mangine, Gerald T., et al. "Exercise-Induced Hormone Elevations Are Related To Muscle Growth." The Journal of Strength & Conditioning Research (2016).
- McCall, Gary E., et al. "Acute and chronic hormonal responses to resistance training designed to promote muscle hypertrophy." Canadian Journal of Applied Physiology 24.1 (1999): 96-107.
- Walker, Simon, et al. "Effects of prolonged hypertrophic resistance training on acute endocrine responses in young and older men." Journal of Aging & Physical Activity 23.2 (2015).
- West, Daniel WD, and Stuart M. Phillips. "Associations of exercise-induced hormone profiles and gains in strength and hypertrophy in a large cohort after weight training." European journal of applied physiology 112.7 (2012): 2693-2702.