Jordan R. Moon, PhD, CSCS*D, HFS€¦ · • Wang Z, Deurenberg P, Wang W et al. (1 999) Hydration...

Jordan R. Moon, PhD, CSCS*D, HFSResearch Institute Director

MusclePharm Corporation Sports Science CenterFaculty: United States Sports Academy

“A typical example or pattern of something; a pattern ormodel“ The Oxford English Dictionary

In science we typically see a “single reigning paradigm”over an idea. Heliocentrism vs. Geocentrism vs. The planets and sun orbit around the earth

vs. all planets orbit around the sun. First Copernicus in the 16 century and then Galileo in the 17 century, took decades

to be accepted mostly due to religious resistance… Now accepted, at least by most

In the late 1940s a man walked into a laboratory of a major photographicmanufacturer in America to demonstrate a new photographic process, buthe didn't bring along a camera or film. He brought along a red box with ashiny steel plate, a charging device, a light bulb and a container of blackpowder. The picture he created was faint but discernible.

"But where's the film?" they asked. "Where's the developer? Where's thedarkroom? Why, that's not really photography!" And so the companypassed up an opportunity to acquire the process for electrostaticphotography, or xerography...a process that has grown into a multi-billiondollar industry.

Why did they pass up such a great opportunity? Because the people whosaw the process were suffering from PARADIGM PARALYSIS.

John C. Harrison, Program Director, National Stuttering Project

Chester Carlson in 1938, U.S. Patent 2,297,691 on October 6, 1942 Xerography/Electrophotography is used by most printers and copy machines today.

When the paradigm effect is so strong that we are preventedfrom actually seeing what is under our very noses, we are said to

be suffering from:paradigm paralysis.

• Image from Thomas S.Kuhn In The Structure ofScientific Revolutions

As Eastern philosophers will tell you, one can arrive at major truths simply byobserving. I'm reminded of something that Margaret Mead, the anthropologist,wrote some years ago...and I'm paraphrasing now. She said--there's a tendencyamong people in her field to be too quick to relate what they see to what theyalready know. But to really make the creative breakthroughs, you can't work thisway. You need to observe with a blank mind. Without expectations. John C. Harrison,Program Director, National Stuttering Project

Consider what you may (or think you) KNOW about Percent Body Fat. What and how we use it (research, sports, clinics, home, etc.) The “normal” or “Healthy” ranges How it can impact health How it can be measured The most valid measurement tools and techniques The most reliable measurement tools and techniques

Now consider what you are ASSUMING about Percent Body Fat. That it CAN be measured validly and reliably not only in groups, but in individuals! Cadavers are equal to living humans and all are the same.

• Identify health risks associated with excessively lowor high body fat values

• Educate clients and athletes about the risks of lowor high body fat values

• Monitor changes is body composition

• Estimate healthy body weight goals

• Formulate dietary and exercise recommendations

• Monitor growth, development, and age-relatedchanges

Fat

Water

Proteinand

Mineral

Fat

Ca++Na+,K+,Cl-

Water

N

Fat

FFM

Fat

Bone-FreeLean

Tissue

BoneMineralProtein

Water(ICW/ECW)

Mineral

Fat

These models are not dependent on age, sex,ethnicity, fitness level, or fatness level and areconsidered the BEST reference methods!

6C 4/5C 3C 2CDXA

• Wang Z, Deurenberg P, Wang W et al. (1999) Hydration of fat-free body mass: new physiological modeling approach. Am J Physiol 276, E995-E1003. Obesity Research Center, St. Luke’s-Roosevelt Hospital, Columbia University.

• Wang Z, Deurenberg P, Wang W et al. (1999) Hydration of fat-free body mass: review and critique of a classic body-composition constant. Am JClin Nutr 69, 833-841. Obesity Research Center, St. Luke’s-Roosevelt Hospital, Columbia University

Where is the Fat?

FFM is EVERYTHING!!! Except (ALL) the fat! 100% Fat Free

FAT

FFM

2C

• Wang, Z., Deurenberg, P., Wang, W., Pietrobelli, A., Baumgartner, R. N., & Heymsfield, S. B. (1999). Hydration of fat-free body mass: review and critique ofa classic body-composition constant. Am J Clin Nutr, 69(5), 833-841.

• Provyn S, Clarys JP, Wallace J et al. (2008) Quality control, accuracy, and prediction capacity of dual energy X-ray absorptiometry variables and dataacquisition. J Physiol Anthropol 27, 317-323.

“Adipose tissue, being the morphological dimension, can be defined anatomically as thepaniculus adiposus (e.g. subcutaneous, intramuscular, and visceral) including connective tissue

and microscopic blood supply and nerves.” (Provyn, 2008)

AdiposeTissue (AT)

≈80%

OtherLipids/Fats

≈20%

Total Body Fat (%Fat)

Water16.2%

Lipids/Fat,ConnectiveTissue, etc.

83.8%

Adipose Tissue (BIG Fat Cells)

Water83.2%

Lipids/Fat,ConnectiveTissue, etc.

16.8%

Adipose Tissue (SMALL Fat Cells)

• Ask yourself if you think the %Fat scale you purchased for $80 is considering how much water is in youradipose tissue. What about your DXA and/or BODPOD

• Do you think this is constant even from day-to-day?

*NOT Fat-Free Mass (FFM)*FFSMM = Fat-Free Skeletal Muscle Mass

• Wang, Z., Deurenberg, P., Wang, W., Pietrobelli, A., Baumgartner, R. N., & Heymsfield, S. B. (1999). Hydration of fat-free body mass: review and critique of aclassic body-composition constant. Am J Clin Nutr, 69(5), 833-841.


• Sheng, H. P., and R. A. Huggins. A review of body composition studies with emphasis on total body water and fat. Am. J. Clin. Nutr. 32: 630–647, 1979.

Lipids/Fat2.21%

Non-Lipids(FFSMM)

97.79%

Skeletal Muscle

Water80.40%

Protein19.60%

FFM of Skeletal MuscleEndurance/More Slow Twitch

Water67.50%

Protein32.50%

FFM of Skeletal Muscle (FFSMM)Strength/More Fast Twitch

• Ask yourself if you think the scale you use that gives you a muscle mass and FFM readout that you purchased for $80 isconsidering how much water is in your muscle tissue. What about DXA and/or BODPOD?

• Do you think this is constant even from day-to-day? What about with training? What About age?

PureFat/Lipids

(%Fat)10.0%

Fat-Free (NoLipids/Fat)

86.0%

Bone4.0%

Total Body Mass(Lean: 10%Fat)

PureFat/Lipids

(%Fat)35.0%

Fat-Free (NoLipids/Fat)

61.0%

Bone4.0%

Total Body Mass(Overweight: 35%Fat)

Adipose Tissue(AT)5.7%

Skeletal Muscle54.0%

Blood10.9%

Other29.4%

Total Body Water is Contained in...

*Muscle Mass contains nearly 5 timesmore water than any other organ ortissue.

16.8 to83.8%

(17-84% )

67.5 to79.5%

(68-80%)

TBW:FFM ranges from 68 to 81%

Wang Z, Deurenberg P, Wang W et al. (1999) Hydration of fat-free body mass: review and critique of a classic body-composition constant. Am J Clin Nutr69, 833-841.Wang Z, Deurenberg P, Wang W et al. (1999) Hydration of fat-free body mass: new physiological modeling approach. Am J Physiol 276, E995-E1003.Obesity Research Center, St. Luke’s-Roosevelt Hospital, Columbia University

Wang Z, Deurenberg P, Wang W et al. (1999) Hydration of fat-free body mass: review and critique of a classicbody-composition constant. Am J Clin Nutr 69, 833-841.Obesity Research Center, St. Luke’s-Roosevelt Hospital, Columbia University

Fat

Water

Proteinand

Mineral

Fat

Ca++Na+,K+,Cl-

Water

N

FAT

FFM

Fat

Bone-FreeLean

Tissue

BoneMineralProtein

Water(ICW/ECW)

Mineral

Fat

These models are not dependent on age, sex,ethnicity, fitness level, or fatness level and areconsidered the BEST reference methods!

6C 4/5C 3C 2CDXA

All indirect measures of %Fat based on a 2C orgreater model. Body water and body fat – Bioimpedance spectroscopy (BIS),

Bioelectrical impedence analysis (BIA) Body fat, body density or fat-free mass Near-infrared interactance (NIR) Anthropometric assessments (height, weight, circumferences, etc.) Skinfold thickness assessment (Skinfolds)

Where can you get field method devices?

Only devices that have been researched (compared toreference methods) and proven accurate can be consideredvalid.What has been researched?

Valid body composition methods all have largerindividual errors compared to groups errors. NIR, BIA, Skinfolds, BOD POD®, underwater weighing, and DXA Group Total Error – 1.8 to 10.4%fat Individual errors ranging from around ±2%fat to ±12%fat

Let’s see what these errors look like•Moon, J. R., H. R. Hull, S. E. Tobkin, M. Teramoto, M. Karabulut, M. D. Roberts, E. D. Ryan, S. J. Kim, V. J. Dalbo, A. A. Walter, A. E. Smith, J. T. Cramer, and J. R.

Stout. Percent body fat estimations in college women using field and laboratory methods: a three-compartment model approach. J Int Soc Sports Nutr. 4:16, 2007.•Moon, J.R., et al., Anthropometric Estimations of Percent Body Fat in NCAA Division I Female Athletes: A 4-Compartment Model Validation. J Strength Cond Res, 2009. 23(4): p. 1068-

1076.•Moon, J.R., Body composition in athletes and sports nutrition: an examination of the bioimpedance analysis technique. European journal of clinical nutrition, 2013. 67 Suppl 1: p. S54-

9.•Moon, J.R., et al., Tracking fat-free mass changes in elderly men and women using single-frequency bioimpedance and dual-energy X-ray absorptiometry: a four-compartment model

comparison. European journal of clinical nutrition, 2013. 67 Suppl 1: p. S40-6.•Moon, J.R., et al., Percent body fat estimations in college men using field and laboratory methods: A three-compartment model approach. Dyn Med, 2008. 7(1): p. 7.•Moon, J. R., S. E. Tobkin, P. B. Costa, M. Smalls, W. K. Mieding, J. A. O’Kroy, R. F. Zoeller, and J. R. Stout. Validity of the BODPOD for assessing body composition

in athletic high school boys. J Strength Cond Res. 22:263-268, 2008.•Moon,, J.R., et al., Estimating body fat in NCAA Division I female athletes: a five-compartment model validation of laboratory methods. Eur J Appl Physiol, 2009. 105(1): p. 119-30.

Laboratory Methods•BOD POD – 16.2%•Underwater weighing – 15.8%•DXA – 20.1%

Male26yr6ft 1in228lbBMI = 30.1

Male26yr6ft 1in228lbBMI = 30.1

Reference5C model16.0%


Field Methods•Futrex 6100 – 19.5%•SFB7 (BIS) – 19.9%•DF50 (BIA) – 27.6%•Skinfold (3-site) – 10.6%•Skinfold (7-site) – 14.5%

Laboratory Methods•BOD POD – 29.5% (1.4%)•Underwater weighing - 27.3% (0.8%)•DXA – 31.2% (3.1%)

Female24yr5ft 7.5in149lbBMI = 22.9

Female24yr5ft 7.5in149lbBMI = 22.9



Field Methods•Futrex 6100 – 27.1% (1.0%)•SFB7 (BIS) – 31.8% (3.7%)•DF50 (BIA) – 34.1% (6.0%)•Skinfold (3-site) – 23.2% (4.9%)•Skinfold (7-site) – 23.3% (4.8%)

For example, a 22 year-old female who is 5ft 6in and 116lbs with a 3-site skinfold of 21.5%. There is a 95% chance that her ACTUAL %fat is

between 17.2% to 25.8%. That’s a range of 8.6%fat.WHICH IS GOOD!!!!

Keep this in mind when categorizing, prescribing, or evaluatingindividual exercise programs and nutrition interventions.

HOWEVER, this depends the skinfold equation, the subjects/client, thetester, the environment, the equipment, etc.

Unless you are in a lab testing a group of 8 or more subjects and usingthe mean values, ALL %Fat methods that do not consider TBW will resultin similar large errors. Plan on a range of AT LEAST +/- 6-10%Fat with your techniques regardless of a single

measurment or tracking changes.

Tracking body composition can be more importantthan ANY single assessment. To monitor weight goals, nutrition and health status, and

evaluate diet and exercise interventions both in clinical andcommercial settings HOWEVER, tracking body composition changes can be more

difficult than getting a single accurate estimate. Why? Because you introduce error when you take multiple measurements. Test re-test reliability

When performed correctly, with the exception of skinfolds, allmethods should have less than a 1%fat test re-test error … FOR ONLY ONE MEASUREMENT.

•Moon, J.R., et al., Tracking fat-free mass changes in elderly men and women using single-frequency bioimpedance and dual-energy X-ray absorptiometry: a four-compartment model comparison. European journal of clinical nutrition, 2013. 67 Suppl 1: p. S40-6.

•Moon, J.R., et al., Tracking fat-free mass changes in elderly men and women using single-frequency bioimpedance and dual-energy X-ray absorptiometry: a four-compartment model comparison. European journal of clinical nutrition, 2013. 67 Suppl 1: p. S40-6.

“The current data in combination with the reliability errors for both BIA and DXA FFM estimations suggest thatresults should be interpreted with caution if individual FFM changes are <5 kg; however, the magnitude of thechange in FFM estimated by BIA and DXA may not be accurate. Nevertheless, DXA and BIA can be usedinterchangeably for tracking changes in FFM in small groups (15–22) of healthy older adults.”

“A longitudinal study comparing several BIA equations and methodsneeds to be conducted in a wide range of athletes before BIA can berecommended for use in athletes to track changes. In addition, rawimpedance values can potentially be used to track body compositionchanges without the errors associated with prediction equations, yetmore research is needed in this area as well.”

“Currently, owing to variations in FFM density and FFM hydration inathletes, multiple-compartment models containing a valid TBWestimation are needed for the accurate estimation of FM or FFM inindividual athletes. In addition, the same multiple-compartmentmodels are needed to track small changes in body composition inathletes. However, if large changes exceeding 4–5 kg in either FM orFFM occur, the BIA estimation may have improved accuracy.”

•Moon, J.R., Body composition in athletes and sports nutrition: an examination of the bioimpedance analysis technique. European journal ofclinical nutrition, 2013. 67 Suppl 1: p. S54-9.

Consider good device error at +/-3.31 %fat Any changes need be greater than 3.31 %fat to be 100% sure

What about tester error? Our recent study produced reliability errors for the 5 BIA devices of

0.183 - 0.608%fat. Assuming that you take two measurements, the “minimum difference

needed to be considered real” is MD = √2(1.414214) * single measurement error MD = 0.507 to 1.684%fat

So what does the change need to be? At best 0.507%fat + 3.31%fat = 3.82%fat

If the device, under the same measurement conditions doesnot show a change >3.82% fat, then the change in body fat“cannot be considered real”!

BUT WAIT: The best scale was only accurate 75% of the time So if you had four people use the same scale, at best, three of the four

people would have a body fat that was a true loss or a true gain. How do you know which of the four will be false?

What does a 3.82%fat change require? A 160lb woman with 30%fat Lean mass = 112 lbs Fat mass = 48 lbs

After a 3.82%fat loss Lean mass = 112 lbs Fat mass = 41.9 lbs Body weight = 151.1 lbs

A difference of 6.1 lbs of fat At 1-2 lbs loss per week, this will take 3.1 – 6.1 weeks

Many methods, both laboratory and field, measure variables otherthan %fat. Skinfold thickness Circumferences Resistance Reactance Body volume Body weight

These are measurements, not estimates, so they are notdependent on age, sex, ethnicity, fitness level. (Like multiple-compartment models) However, fatness level can influence skinfold thickness measurements and it’s

not recommended for obese individuals.

These measurements can be tracked at lower cost and can helpdetermine the effectiveness of individual training programs andnutrition interventions.

MORE SENSITIVE TO CHANGE!

Is there a criterion thickness/circumference measurement?

Measuring skinfold thickness and circumference canbe more beneficial than body fat estimations! ≈ 75% of muscle is in the arms and legs Use skinfold calipers to measure the skinfold thickness of the

biceps, triceps, forearm, thigh, and calf. Use a measuring tape to measure the circumference of the

biceps, triceps, forearm, thigh, and calf. If the circumference measurements get bigger while the skinfold

measurements get smaller than they are most likely gainingmuscle and losing fat

If the circumference measurements get bigger and the skinfoldsstay the same, than they are most likely gaining muscle and notlosing fat

You get the idea!

Muscle Circumference (MC) Limb circumference (LC) Skinfold Thickness (ST)

MC = LC – π x ST Because the ST is a double thickness measurement you don’t

need to multiple ST by 2 in order to get the full diameter of fatand skin.

Example Arm circumference of 44 cm (440 mm) skinfold thickness 15 mm MC = 440 - 3.14 x 15 MC = 393 mm (39.3 cm)

NUMBER ONE If the changes (in a group or individual) are too small, every body

composition variable (fat mass, %fat, lean mass, etc.) may result ininaccurate estimations. Small changes can ONLY be evaluated ACCURATELY with a multiple-

compartment models.

If less accurate methods are used, there will need to bea much greater change in body composition todetermine actual change, both at the group andindividual level.

However, in the end, the accuracy of many methods isdetermined by the protocol and technique.

When using anthropometric methods the largest errors canbe attributed to the investigator/trainer/coach. Practice Practice Practice! 3 - 9% variability can be attributed to differences between

investigators/trainers (Lohman et al. 1984, Morrow et al. 1986) Jackson and Pollock (1978) suggest practicing on at least 50-

100 subjects/clients and take minimum of 2 measurements persite.. Wet and skin with lotion can alter skinfold values

Use estimation equations to calculate body composition valuesthat were developed using the same population you are testing. The Jackson and Pollock sum of 3 and 7 skinfold equations

have been validated in both athletic and nonathleticpopulations with success.

Skinfold Equations Men BD = 1.10938 - 0.0008267(SUM3) + 0.0000016(SUM3)2 - 0.0002574(AGE) BD = 1.112 - 0.00043499(SUM7) + 0.00000055(SUM7)2 - 0.00028826(AGE) SUM3 = Chest, abdomen, thigh SUM7 = Chest, subscapular, axilla, anterior suprailiac, abdomen, thigh, triceps

Women BD = 1.099421 - 0.0009929(SUM3) + 0.0000023(SUM3)2 - 0.0001392(AGE) BD = 1.097 - 0.00046971(SUM7) + 0.00000056(SUM7)2 - 0.00012828(AGE) SUM3 = anterior suprailiac, thigh, triceps SUM7 = Chest, subscapular, axilla, anterior suprailiac, abdomen, thigh, triceps

BD = Body Density %fat from BD = [(4.57 / BD) - 4.142] x 100

THESE EQUATIONS ONLY USE AGE AND SKINFOLD THICKNESS WILL SHOW THE SAME CHANGE IN %FAT AS THE RAW

SKINFOLD MEASUREMENTS IN mm.

Consistency is KEY Measure at the same time, each time 12hr prior, fast and no exercise is ideal

For women, measure at the same point in the menstrualcycle. Preferably when they are not in peak body mass periods, which can

occur at different times for all women (Bunt et al. 1989).

Use the same device for all measurements used to trackchanges; do not assume all devices can be used interchangeably. The most used skinfold calipers are the Lange and Harpenden,

which both apply consistent pressure (7-8g/mm2) throughoutthe range of measurement (0-60mm).

To be sure your clients’ skinfold thicknesses andcircumferences are reducing/increasing, you need tocalculate your “minimal difference” statistic.

WHY USE SKINFOLD THICKNESS AND CIRCUMFERENCES? They are simple measurements, like height and weight and are

not dependent on age, sex, ethnicity, or fitness level.

What you need Preferably 10 people per sex Measure each site around 24 hours apart A way to calculate your MD Statistic

It is a Colloquial Term, as well as Scientific, why? %Fat = Attractiveness, NOT REALLY WHAT IT IS! Or is it?

NOT SEXY

FEMALES

18.5%fat

19.75%fat

16.56%fat

16.66%fat

MALES

15.72%fat 15.14%fat

9.16%fat 8.82%fat

Our findings resolve a long-standing dispute in the attractivenessliterature by confirming that although WHR appears to be an importantpredictor of attractiveness, this is largely explained by the direct effect oftotal body fat on WHR, thus reinforcing the conclusion that total body fatis the primary determinant of female body shape attractiveness.Cornelissen, P.L., M.J. Tovee, and M. Bateson, Patterns of subcutaneous fat deposition and the relationship between bodymass index and waist-to-hip ratio: implications for models of physical attractiveness. J Theor Biol, 2009. 256(3): p. 343-50.

Quantifying ACTUAL %Fat (Every fat/lipid cell in a living human) is far morecomplex and more difficult than most people will ever realize.

Consider what %Fat is scientifically compared to socially! Just because something appears to be easy to measure and is easily

understood by most, doesn’t mean it is simple or that “everyone” is anexpert.

Anyone can use a stethoscope to listen to a heart, but it takes years ofpractice and education to hear a heart murmur.

Anyone can sing, but it takes talent and training to sing well and on pitch.

Male Recommendations (%Fat)Age (yr) NR Low Mid Upper Obese

6 - 17 < 5 5 - 10 11 - 25 26 - 31 > 31

18 - 34 < 8 8 13 22 > 22

35 - 55 < 10 10 18 25 > 25

55 + < 10 10 16 23 > 23

Female Recommendations (%Fat)Age (yr) NR Low Mid Upper Obese

6 - 17 < 12 12 - 15 16 - 30 31 - 36 > 36

18 - 34 < 20 20 28 35 > 35

35 - 55 < 25 25 32 38 > 38

55 + < 25 25 30 35 > 35

Body fat standards for the non-active

Male Recommendations (%Fat)Age (yr) Low Mid Upper

18 - 34 5 10 15

35 - 55 7 11 18

55 + 9 12 18

Female Recommendations (%Fat)Age (yr) Low Mid Upper

18 - 34 16 23 28

35 - 55 20 27 33

55 + 20 27 33

Body fat standards for the active

Sport Females MalesBallet dancing 13 - 20 8 - 14

Baseball 12 - 15

Basketball 20 - 27 7 - 11

Bodybuilding 9 - 13 6 - 9

Cycling 15 8 - 10

Football - Backs 9 - 12

Football - Linebackers 13 - 14

Football - Linemen 16 - 19

Football – QB/Kickers 14

Gymnastics 10 - 17 5 - 10

Ice Hockey 8 - 15

Racquetball 14 8 - 9

Rock climbing 10 - 15 5 - 10

Rowing 14 - 18 8 - 15

Skiing - Alpine 21 7 - 14

Skiing – Cross country 16 - 22 7 - 12

Skiing - Jumping 14

Soccer 10

Softball 22

Sport Females MalesSpeed Skating 15 - 24 11

Swimming 14 - 24 9 - 12

Tennis 20 15 - 16

Track - Discus 25 16

Track - Jumpers 8 - 14 7 - 8

Track – Distance runners 10 - 19 6 - 13

Track – Middle distance 10 - 14 7 - 12

Track – Shot putters 20 - 28 16 - 20

Track - Sprinters 11 - 19 8 - 16

Track - Decathletes 8 - 9

Track - Pentathletes 11

Track - Triathletes 7 - 17 5 - 11

Volleyball 16 - 25 11 - 12

Power lifters 9 - 16

Olympic Lifters 10 - 12

Wrestling 5 - 12

http://jordanmoon.com/uploads/Reliability_Calculator.xls

Please feel free to contact me with any questions

[email protected]

Jordan R. Moon, PhD, CSCS*D, HFS€¦ · • Wang Z, Deurenberg P, Wang W et al. (1 999) Hydration...

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