How to Read a BOD POD
Updated: Jun 5, 2019
Body composition can be measured in multiple ways. So if you had the chance to wear a swimsuit and swim cap and sit in a hollowed-out egg with a sound mimicking a dog whimpering in your ear, why wouldn’t you want to use the BOD POD?
But post-BOD POD, how do you explain the results to an athlete? If asked, or for your own peace of mind, do you know how the numbers are derived?
Below, I’ll explain:
How the BOD POD works.
How fat mass, fat-free mass, and their percentages are derived.
Areas of potential error.
If a woman’s menstrual cycle impacts the results.
Part 2 of my BOD POD series reviews the impact that hydration and food intake have on the test’s results (stay tuned!).
As a heads up, throughout this post I’ll refer to:
The “BOD POD report”: Click here to view an example printout.
COSMED: They are the manufacturers of the BOD POD.
Also, this post wasn’t sponsored by COSMED. My curiosity behind not knowing how the numbers that I report to athletes are derived is what drove me to write this post. I did meet COSMED at the CPSDA 2019 Annual Conference and had the chance to ask questions. They were gracious in teaching me and following up with their research.
How Does the BOD POD Work?
The fancy term is air displacement plethysmography.
Prior to having someone sit in the BOD POD, the machine is first calibrated with a cylinder of a known volume. When the person sits in the machine they displace air. The difference between the calibrated volume and the person’s displaced air volume is the person’s body volume. Using this known volume, simple math calculates the person’s density and body fat percentage.
Note that the person being measured needs to be wearing minimal, tight clothing (e.g., sports bra, shorts) and a swim cap. Otherwise, baggy clothes and flowing hair would increase the person’s displacement and volume, which would skew the BOD POD results (i.e., a larger volume = smaller density = higher % Fat reading).
Ultimately, the BOD POD is a two-compartment model: The body is measured as fat and non-fat (a.k.a., fat-free mass). You can neither determine bone mineral density nor total body water.
Results: What Does it All Mean?
Fat Mass (FM) and % Fat:
FM is fat—or everything in the body that isn’t muscle, bone, organs, ligaments, etc.
The % Fat is the percentage of total body weight attributed to fat. For instance:
(X lbs. fat / X lbs. total mass) x 100 = X % Fat
On the BOD POD report, FM is listed as both a percentage and in pounds body weight. In practice, I find athletes are more interested in the % Fat.
How is Body Fat Calculated?
In the “Test Profile” section of the BOD POD report, you’ll see the density model used is “Siri”.
Using the Siri predictive equation, body fat is calculated once the athlete’s body volume and density are determined:
Density = Mass (kg) / Volume (L)
Siri equation = [495 / density (kg/L)] – 450 = % Fat
Using my own BOD POD report as an example, for equation #1 I calculated density to be 1.0415 kg/L whereas the BOD POD report listed 1.0393 kg/L. A higher density inserted into equation #2 would result in a lower % Fat (my own BOD POD would then have been 1.0% lower).
So why is the density different? Our lungs contain air to which the BOD POD software aims to account for, without having subjects forcibly expel all of the air in their lungs during the test. Plus, equation #2 assumes equal density of tissues throughout the body. For instance, fat is assumed to have a density of 0.90 kilograms/liter and lean muscle (here the fat-free mass) of 1.10 kg/L. Depending on levels of hydration, the densities would differ.
Hence, there’s a lot of wiggle room that the BOD POD software aims to account for.
Body Fat Isn't Equal: Storage & Essential Fat
The BOD POD doesn’t differentiate between storage and essential fat, so the FM number that's generated includes both types of fat (i.e., total fat mass). It’s up to you to interpret these numbers to the athlete.
Storage fat is beyond what the body requires for optimal functioning and is available for when energy intake is lacking, as an insulator to keep the body warm, and acts as padding against trauma.
Essential fat is needed for the production of sex-specific hormones, is a component of the muscles and vital organs (e.g., heart, lungs, intestines), and is necessary to promote optimal, overall health. The BOD POD report notes that “the minimum amount of ‘essential fat’ is approximately 3-5% for men, and 12-15% for women.” Depending on where you read, I’ve seen lower numbers like 2-5% for men and 10-13% for women. A woman’s essential fat is higher due to additional bodily tasks like childbearing (and having adequate body fat to even become pregnant) and menstruation.
Having too little essential fat is a sign of poor health, and increases a:
Person’s risk of becoming sick, impaired bone development, and weakened muscles.
Woman’s risk of menstrual irregularities, infertility, and reduced estrogen production.
Man’s risk of reduced testosterone production and hypogonadotropic or secondary hypogonadism (i.e., sperm count drops, reproduction takes a backseat to survival).
Keep in mind that these numbers are average ranges, meaning healthful and unhealthful outliers will exist. In practice, I’ve counseled:
A female with 9% Fat experiencing regular menstruation (not using oral contraceptives), normal mood and energy levels, and no history of stress fractures or reactions.
A male with 3% Fat experiencing a normal sex drive, mood, and energy levels.
A female with 17% Fat having lost their period due to increased stress via too strenuous of combined training, traveling, and academic schedules—all in the presence of adequate energy intake.
Acknowledging Error: Using % Fat as an Example
What isn’t printed on the report is the error. Athletes see 15% Fat in January and 16% in March. Note that every measurement taken will have an error—there are no absolutes. For the BOD POD, research proposes the error to be 1-3%. Biological variables—like fluid and meal ingestion, recent exercise, and dehydration—are some of the largest contributors to measurement error.
Using the average error of 2%, the body fat reading for the above example would be:
15% (13-17%)
16% (14-18%)
Both measurements overlap, meaning that both could be the same number (e.g., 15%), extremely different numbers (13% and 18%), the precise numbers as listed (15% and 16%), or any other combination within those ranges.
I spoke with COSMED and as of right now, the software option to include the error ranges in the BOD POD report does not exist.
Fat-free Mass (FFM) and Percent Fat-free Mass (% FFM):
FFM is everything that isn’t fat. The assumption for an adult is that bone, ligament, organs, etc. have reached their adulthood levels—meaning that if FFM changes then the change is assumed to be muscle.
The two equations for this group of measurements can be found once FM and % Fat are known:
FFM (lbs.) = Body weight - FM
% FFM = 100 - % Fat
In practice, I find athletes are more interested in the FFM number in pounds vs. the percentage.
Energy Expenditure Results:
Energy Expenditure Calculation
Sports dietitians learn that the recommended predictive energy equation to use in an athletic population is the Cunningham equation due to its use of FFM—to which the BOD POD measures. In speaking with reps from COSMED, the BOD POD software considers both FM and FFM when calculating the resting metabolic rate (RMR), as referenced by a 1992 paper published in the American Journal of Clinical Nutrition (AJCN).
The equation used for the COSMED BOD POD is as follows:
RMR = (25.8 x FFM in kg) + (4.04 x FM in kg)
As a reference, I plugged my own BOD POD report results into this calculation and applied the activity factors (see next section). The numbers were accurate to 3-6 calories.
From the AJCN paper’s method’s section, deriving the equation:
“…consisted of 86 males and 127 adult females, 81 of whom were nonobese and 132 of whom were obese. Subjects were considered obese if their body fat was > 20% (males) or > 30% females.”
Research has shown that the BOD POD may overestimate fat percentage in some (i.e., female college athletes*) and underestimate it in others (i.e., college football players**).
Out of curiosity, using the Cunningham, Harris-Benedict, and Mifflin-St. Jeor equations as references, all estimated the RMR to be ~200-300 calories greater than the BOD POD report’s predictions. Granted, it's very difficult to precisely measure energy expenditure and intake. Whether it's a predictive equation or the BOD POD report, be consistent with what value you use when counseling athletes on their diet.
Energy Expenditure Results Table: Daily Activity Level
The RMR reflects an athlete lying in bed all day, only infrequently getting up to use the bathroom or walk to the kitchen. But this isn’t what athletes are doing most of the week.
The calculated RMR is then multiplied by activity factors to estimate how many calories an athlete will burn once active.
Per the BOD POD report’s referenced 2002 Institute of Medicine’s “Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, And Amino Acids”, the activity factors are:
However, there are a few differences when comparing to the BOD POD’s “Estimated Resting Metabolic Rate” report:
In practice, I don’t use the specific PAL numbers from the BOD POD’s report, since the exertion equivalents and descriptions don’t always resonate with the athlete. Rather, during a debrief meeting I explain that as activity duration and intensity increase, as does their body’s need for energy. Plus, calories needed won’t be stagnant from day-to-day, since training programs will differ.
Does Menstruation Impact the Results?
Possibly.
Research has shown that menstruating women experience variable changes in body mass, with increases of 1-3% Fat and total body water by 1.5 kg (3.3 lbs.) when body composition was measured using the underwater weighing technique. Varying hormones throughout the menstrual cycle are thought to impact hydration as the fluctuating hormones estradiol and progesterone coincide with sodium and water retention. Hormonal changes are also thought to (possibly) shift appetite and caloric intake.
Per the research, not all menstruating women experience significant differences in their BOD POD or body composition results, or even their subjective feelings (e.g., “I feel heavier during my period” or “my appetite spikes and I eat nonstop and anything in sight”). So we cannot make a broad assumption for all women.
Granted, the BOD POD protocol doesn’t ask a woman if they’re having their period at the time of the test, or what part of their cycle they’re currently in. Ideally, and with multiple body composition measurements, a woman would be measured on the same day within her cycle as she had in prior appointments—keeping in mind that a woman may vary from the average 28-day menstrual timeline.
In reality, a collegiate sports dietitian would schedule a team BOD POD session. For a women’s swim team of ~20-30 athletes, scheduling out individual meetings to match each athlete’s menstrual cycle is unlikely. Rather, speak with your female athlete about the potential impact their menstrual cycle may have on their BOD POD results and ask if they subjectively feel any differences in their body dependent on the time of month.
Take-home Messages:
As always, counsel the athlete sitting in front of you.
First ever BOD POD: Like a cross-sectional study, you only have one data point that you assume to be accurate. Explain to the athlete the BOD POD’s potential error. If any numbers are of concern, further ask the athlete about their stress levels, sleep pattern, mood, nutritional habits, and, if applicable, menstrual pattern or any changes to it.
Multiple BOD PODs: Like a long-term study, you now have multiple data points to review. A pattern should present itself and any outliers (or error) will be obvious. Keep in mind the time of year and athlete’s training pattern (i.e., is there a cyclical pattern to changes in % Fat, FFM, and/or body mass during the offseason, preseason, and once in season?). Remember: Body composition need not be steady throughout the year.
Further Reading:
Dempster, P., & Aitkens, S. (1995). Med Sci Sports Exerc,(27)12:1692-1697.
COSMED Example BOD POD Report:
Page 1: Current measurement results
*The female college athlete study compared BOD POD to underwater weighing (UWW) and skinfolds. The BOD POD was shown to overestimate % Fat. Granted, converting skinfolds into % BF equations can under- or overestimate % BF and UWW requires a person to be submerged underwater and blow out all of the air in their lungs (i.e., very difficult for subjects to fully do), so UWW also has its limitations.
Study: Vescovi, J.D., Hildebrandt, L., Miller, W., Hammer, R., & Spiller, A. (2002). Evaluation of the BOD POD for Estimating Percent Fat in Female College Athletes. J Strength Cond Res,16(4):599-605.
**The male college football athlete study compared BOD POD to UWW, with 20 of the 69 athletes also completing a DXA. BOD POD significantly underestimated % Fat compared to both UWW and DXA, mainly because the BOD POD overestimated body density.
Study: Collins, M.A., Millard-Stafford, M.L., Sparling, P.B., Snow, T.K., Rosskopf, L.B., . . . & Omer, J. (1999). Evaluation of the BOD POD for assessing body fat in collegiate football players. Med Sci Sports Exerc,31(9):1350-1356.
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