Tonight's Research Interlude

Training Bodybuilding
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I started this up last Thursday, so we might as well roll with it. If you’re deconditioned, you’re more likely to get hurt. Go figure…

Gabbett TJ, Domrow N. Risk factors for injury in subelite rugby league players.Am J Sports Med. 2005 Mar;33(3):428-34.

BACKGROUND: Although player fatigue and playing intensity have been suggested to contribute to injuries in rugby league players, no study has confirmed if the level of physical fitness is a risk factor for injury in rugby league players. The aim of this study was to identify risk factors for injury in subelite rugby league players. HYPOTHESIS: Low physical fitness levels are risk factors for injury in subelite rugby league players. STUDY DESIGN: Cohort study; Level of evidence, 2. METHODS: One hundred fifty-three players from a subelite rugby league club underwent preseason measurements of muscular power (vertical jump), speed (10- and 40-m sprint), and maximal aerobic power (multistage fitness test) over 4 competitive seasons. All injuries sustained by players were prospectively recorded over the 4 competitive seasons. RESULTS: The risk of injury was greater in players with low 10- and 40-m speed. Players with a low maximal aerobic power had a greater risk of sustaining a contact injury. In addition, players who completed less than 18 weeks of training before sustaining their initial injuries were at greater risk of sustaining a subsequent injury. CONCLUSIONS: Subelite rugby league players with low speed and maximal aerobic power are at an increased risk of injury. In addition, players who complete less than 18 weeks of training before sustaining an initial injury are at greater risk of sustaining a subsequent injury. These findings highlight the importance of speed and endurance training to reduce the incidence of injury in subelite rugby league players.

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You know how Mike and I are always talking about grooving motor patterns? Here’s a great example; just imagine how good Michael Jordan got at shooting jump shots after playing 30+ years of competitive hoops. If you want to get good at something, practice it and become as efficient as possible.

Bennett S, Davids K. The manipulation of vision during the powerlift squat: exploring the boundaries of the specificity of learning hypothesis. Res Q Exerc Sport. 1995 Sep;66(3):210-8.

The available information for controlling a multidegree-of-freedom sport action was manipulated in 2 experiments. In the first, 10 intermediate lifters were participants; for the second, 8 skilled and 8 less skilled lifters were observed. Three single repetitions of a powerlift squat were performed under 3 vision conditions (i.e., full, ambient, no vision). The less skilled and intermediate lifters’ technical performance decreased significantly with the removal of visual information. There was no detrimental effect in the skilled group. Despite the differing information constraints, skilled lifters exhibited a high level of positioning accuracy and timing consistency across conditions. These data fail to support the theoretical predictions of the specificity of learning hypothesis. The differences between the task constraints in this study and those in manual aiming investigations may represent a boundary to the current propositions of the specificity of learning hypothesis.

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For all the aging PLs and OLs in the crowd:

[quote]Anton MM, Spirduso WW, Tanaka H. Age-related declines in anaerobic muscular performance: weightlifting and powerlifting. Med Sci Sports Exerc. 2004 Jan;36(1):143-7.

PURPOSE: One approach to studying the effects of aging on physiological functional capacity (PFC) in humans is to analyze the peak physical performance of trained athletes with increasing age. The primary aim of the present study was to determine weightlifting and powerlifting performance with increasing age in both men and women. METHODS: We performed a retrospective analysis of top age-group weightlifting and powerlifting records compiled from the U.S. Weightlifting and U.S. Powerlifting Organizations. RESULTS: Regression analyses showed that in both men and women weightlifting and powerlifting performance declined curvilinearly and linearly, respectively. The rate and the overall magnitude of declines in performance with age were markedly greater (P < 0.05) in weightlifting than in powerlifting. The rates of age-related decline in muscular power were not different between upper body (bench press) and lower body (squat). Similarly, the age-related declines were not different between snatch and clean and jerk in weightlifting events. The magnitude of the declines with age was greater (P < 0.05) in women than in men in weightlifting; no such sex-related differences were observed in powerlifting performance. CONCLUSIONS: The findings in this cross-sectional study indicate that 1) peak anaerobic muscular power, as assessed by peak lifting performance, decreases progressively even from earlier ages than previously thought; 2) the overall magnitude of decline in peak muscular power appears to be greater in tasks requiring more complex and powerful movements; 3) the age-related rates of decline are greater in women than in men only in the events that require more complex and explosive power; and 4) upper- and lower-body muscular power demonstrate similar rate of decline with age.[/quote]

To elaborate on the “from earlier ages than previously thought,” here’s an excerpt from the article:

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These researchers obviously know nothing about what most powerlifters typically eat!

[quote]
Hurley BF, Hagberg JM, Seals DR, Ehsani AA, Goldberg AP, Holloszy JO. Glucose tolerance and lipid-lipoprotein levels in middle-aged powerlifters. Clin Physiol. 1987 Feb;7(1):11-9.

The purpose of this study was to obtain information regarding the effects of a form of strength training (powerlifting) on certain coronary artery disease (CAD) risk factors in middle-aged men. The risk factors studied were the plasma lipid-lipoprotein profile, glucose tolerance and plasma insulin levels, all of which have been shown to be favourably influenced by endurance training in middle-aged and older men. Five elite powerlifters (52 +/- 9 years) were compared to distance runners and sedentary controls of similar age with whom they were matched in terms of body fatness as estimated from skin-fold thickness measurements. The powerlifters had a significantly (P less than 0.01) lower HDL cholesterol (HDL-C) level (34 +/- 4 mg/100 ml) than the sedentary controls (48 +/- 12 mg/100 ml) and runners (54 +/- 8 mg/100 ml). The total cholesterol to HDL-C ratio, a good indicator of CAD risk, was 41% higher in the powerlifters than in the controls, and 57% higher than in the runners (both P less than 0.01). The total area under the glucose tolerance curve during an oral glucose tolerance test (OGTT) for the powerlifters was 74% higher than for the sedentary controls (P less than 0.05) and 229% higher than for runners (P less than 0.01). Similarly, the total area under the OGTT insulin curve for the powerlifters was 68% higher than for sedentary controls and 332% higher than for the runners (P less than 0.001). These findings suggest that middle-aged powerlifters, in marked contrast to endurance athletes, have an increased risk of developing CAD.[/quote]

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Isn’t it amazing at how “elementary” some studies are?

Aside from the fact that it invovles tons of planning, calculus level stats, etc., couldn’t a lot of elementary PE teachers tell you what this study concluded?

Stay strong
MR

[quote]Eric Cressey wrote:
I started this up last Thursday, so we might as well roll with it. If you’re deconditioned, you’re more likely to get hurt. Go figure…
[/quote]

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very cool, Eric.

do you know at what age peak performance is believed to be; and what factors (or main factor) that we know of that are involved with the decrease in performance with age?

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[quote]wufwugy wrote:
very cool, Eric.

do you know at what age peak performance is believed to be; and what factors (or main factor) that we know of that are involved with the decrease in performance with age?[/quote]

From Tarpenning (2004):

“It has been reported that maximal strength peaks at ~30 yr of age, plateaus, and remains relatively stable for the next 20 yr, with an age-related decline in strength becoming significant after age 50.”

I think it’s fair to say that the main factor involved would be hormonal in nature: andropause. This has implications in terms of both sarcopenia and osteopenia.

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Here’s one that I believe was/will be presented at ACSM this week. It was forwarded to me ahead of time; how cool is it that they could predict this almost exactly?!?!

[quote]A Mathematical Model Of The 2004 Tour De France l?Alpe-d?Huez Time-trial Winning Performance

Daniel P. Heil, FACSM. Montana State University, Bozeman, MT.

PURPOSE: The purpose of this study was to design a mathematical model that accurately predicted Lance Armstrong?s winning performance for Stage 16 of the 2004 Tour de France. The stage was a 15.5 km time-trial (TT) up l?Alpe-d?Huez, a legendary uphill climb that included 13.8 km of uphill cycling with an average grade of +7.9%.

METHODS: The course profile was modeled as 16 combinations of road distance and average grade as published by the Tour de France organizers. The first and last course sections were relatively flat (0 to +1.3%) while the 14 middle uphill sections averaged +5 to +11.5% with an elevation change from 720 m to 1840 m. An iterative algorithm solved for a single unknown quantity (time to complete TT) as a balance between the ability to generate power for forward movement (power supply) and the net power required to overcome gravity, aerodynamic drag, and rolling resistance.

Based upon reports in the popular literature, power supply for Armstrong was assumed to average 500 W over the entire race. The model also assumed that Armstrong?s body mass, equipment (shoes and helmet) and bike masses to be 71 kg, 1.2 kg and 6.8 kg, respectively. The algorithm was designed to choose between an aerodynamic tuck or hill climbing body position based upon which position maximized ground speed for each of the 16 course sections. Estimates of frontal area were predicted (EJAP 87:520-528, 2002) while changes in WS with body position were estimated from previous work (EJAP 75:160-165, 1997).

Power supply was also adjusted downward for increased altitude using a previously published formula for acclimatized cyclists. The algorithm was assumed to be a valid representation of Armstrong?s performance if the predicted performance was within +/-1% of the actual performance.

RESULTS: On July 21, 2004, Armstrong won the l?Alpe-d?Huez TT in 39:41 mins. The proposed algorithm predicted Armstrong?s time would be 39:40 mins for a difference of -0:01 sec (or <0.05% difference) which meets the apriori criteria for validity.

CONCLUSIONS: This study represents the first composite mathematical cycling model to accurately predict TT performance that includes both flat and uphill course sections, the influence of body position on power supply and drag, as well as the influence of altitude on power supply.[/quote]

PS - An average of 500 watts is absolutely ridiculous!