Anthropometrics and Body Composition Effects on SFAS Performance

Introduction

We know that in powerlifting and weightlifting, high levels of lean muscle mass are strongly associated with competition success. And in swimming, low levels of body fat and taller stature are strongly associated with competition success.

What if we had the same kind of data on performance at selection courses like BUD/S, SFAS, or RASP? The extent of our previous analyses has been on physical performance predictors of success. For information on how APFT scores, running, and rucking affect selection rates, check out out this article.

At that time, we did not have research on how anthropometrics and body composition impacted selection rates. However, new research has been released by the U.S. Army Special Operations Command and the U.S. Army Research Institute of Environmental Medicine on the effect of anthropometrics and body composition on physical performance and selection rate at Special Forces Assessment and Selection.

In this article, we’ll start by diving into the methods and statistical analysis of the study, but if you wish to skip to practical applications, please skip to the conclusion.

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Materials and Methods to the Study

Soldiers attending SFAS between May 2015 and March 2017 were enrolled in a longitudinal, observational study. Prior to the course, 795 candidates had their height, body mass, and body mass index (BMI) measured. Body composition metrics were measured for 117 candidates with a dual-energy X-ray absorptiometry (DEXA) scan which measures body fat percentage, fat mass, lean mass, bone mineral content (BMC), and bone mineral density (BMD).

The researchers performed statistical analyses to determine the associations and effect sizes of anthropometrics (height, body mass, and body mass index) and body composition (body fat percentage, lean mass, BMC, and BMD) on physical performance and selection rate at Special Forces Assessment and Selection.

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Effects on Physical Performance

^{Correlation (r) between Anthropometrics and Body Composition and Physical Performance Measures among Soldiers Enrolled in U.S. Army Special Forces Assessment and Selection a}

	Height (cm)	Body mass (kg)	BMI (kg/m2)	Body fat (%)	Fat mass (kg)	Lean mass (kg)	BMC (kg)	BMD (g/cm2)
	r	r	r	r	r	r	r	r
APFT total score	0.01	−0.14	−0.13	−0.40	−0.47	−0.12	−0.09	0.03
	P = .826	P < .001	P < .001	P < .001	P < .001	P = .185	P = .322	P = .712
APFT push-up score	−0.22	−0.10	0.05	−0.30	−0.34	−0.08	−0.17	−0.01
	P < .001	P = .007	P = .132	P = .001	P < .001	P = .362	P = .059	P = .919
APFT sit-up score	−0.03	−0.11	−0.11	−0.22	−0.30	−0.19	−0.06	−0.05
	P = .382	P = .002	P = .003	P = .016	P = .001	P = .039	P = .506	P = .583
APFT 2-mile run score	0.06	−0.15	−0.24	−0.44	−0.46	0.00	0.03	0.16
	P = .072	P < .001	P < .001	P < .001	P < .001	P = .991	P = .721	P = .090
Pull-ups	−0.12	−0.18	−0.15	−0.38	−0.41	−0.13	−0.04	0.10
	P = .001	P < .001	P < .001	P < .001	P < .001	P = .153	P = .631	P = .264
Run time	−0.12	0.19	0.19	0.40	0.43	0.01	0.00	−0.07
	P = .002	P < .001	P < .001	P < .001	P < .001	P = .946	P = .998	P = .449
Road march time	−0.12	−0.15	−0.11	0.36	0.23	−0.34	−0.17	−0.15
	P = .001	P < .001	P = .003	P < .001	P = .021	P < .001	P = .080	P = .129
Obstacle course score	0.04	−0.07	−0.08	−0.25	−0.32	−0.10	0.00	0.01
	P = .283	P = .057	P = .045	P = .013	P = .001	P = .338	P = .987	P = .956
Land navigation points	0.06	0.05	0.03	−0.46	−0.43	0.00	0.04	0.04
	P = .165	P = .306	P = .561	P < .001	P < .001	P = .972	P = .737	P = .758

Lower body fat percentage and fat mass were significantly associated with better performance on all physical performance measures:

• APFT
• Pull-ups
• Run
• Loaded road march
• Obstacle course
• Land navigation

Higher lean mass was significantly associated with better performance on the loaded road march, but also lower APFT sit-up scores

Lower body mass and BMI was associated with better performance on

• APFT
• Pull-ups
• Run
• Obstacle course

Higher body mass and BMI was associated with better performance on the loaded road march

Shorter stature was associated with better performance on push-ups (APFT) and pull-ups

Taller stature was associated with better performance on SFAS run and loaded road march

The BMC and BMD measures were not significantly associated with physical performance measures.

The strength of correlations for physical performance from highest to lowest are as follows

1. Fat mass (|r| = 0.23−0.47),
2. Body Fat Percentage (|r| = 0.22−0.46)
3. Lean mass (|r| = 0.19–0.34)
4. BMI (|r| = 0.08–0.24)
5. Height (|r| = 0.12–0.22)
6. Body Mass (|r| = 0.10–0.15).
   

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Effects on Selection Rate

On average, the selected soldiers were taller (5’10.4 ± 2.6 vs. 5’9.6 ± 2.6 in)

On average, the selected soldiers had higher

• Body mass (189 ± 19.4 vs. 181 ± 21.2 lbs), BMI (26.8 ± 2.2 vs. 26.3 ± 2.6 kg/m²)
• lean mass (67.2 ± 7.3 vs. 61.9 ± 7.6 kg)
• BMC (3.47 ± 0.40 vs. 3.29 ± 0.56 kg)
• BMD (1.34 ± 0.10 vs. 1.28 ± 0.10 g/cm²)

On average, the selected soldiers had lower

• Body fat percentage (17.3 ± 3.4 vs. 20.1 ± 4.5%)
• Fat mass (14.2 ± 3.7 vs. 15.8 ± 4.4 kg)

The associations ranked from highest to lowest effect sizes are as follows

1. Lean mass (Cohen’s d = 0.71)
2. Body fat percentage (d = 0.70)
3. BMD (d = 0.60)
4. Body mass (d = 0.40)
5. Fat mass (d = 0.39)
6. BMC (d = 0.37)
7. Height (d = 0.35)
8. BMI (d = 0.21).

Note that once body mass was adjusted for height, the associations between height and selection rate were attenuated.

The reasons for non-selection were previously reported;¹⁵ the majority failed to meet SFAS standards (>50%), and other reasons for non-selection include failing the APFT at the course start, voluntary and involuntary withdrawal due to medical conditions, voluntary withdrawal due to lack of motivation, and involuntary withdrawal due to integrity violations, losing equipment, safety violations, and other reasons.

https://academic.oup.com/milmed/advance-article/doi/10.1093/milmed/usab315/6327577?login=false

where d = 0.8 was considered a large effect size, d = 0.5 was considered medium, and d = 0.2 was considered small.²² Differences in predicted probability (%) and likelihood (odds ratio [OR] and 95% confidence interval [CI]) of selection between quartiles of anthropometric and body composition measures were determined with Wald chi-square and logistic regression. Logits (coefficients) derived from logistic regression models were converted to probabilities with the following formula²³:

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Practical Recommendations

Likelihood of selection
	Mean ± SD	Predicted probability of selection	P	Δb	OR	95% CI	Model R2
Height (cm)							0.03
Q1	169.1 ± 2.6	19.1%	REF	–	1.00	–
Q2	174.9 ± 1.3	32.3%	.003	13.2%	2.03	1.28–3.21
Q3	179.4 ± 1.2	34.0%	.001	14.9%	2.18	1.38–3.46
Q4	186.3 ± 3.7	37.9%	<.001	18.8%	2.58	1.64–4.07
Height (cm)—adjusted for body mass (kg)c							0.06
Q1	169.1 ± 2.6	22.7%	REF	–	1.00	–
Q2	174.9 ± 1.3	33.6%	.024	10.9%	1.72	1.08–2.76
Q3	179.4 ± 1.2	31.7%	.070	9.0%	1.58	0.96–2.60
Q4	186.3 ± 3.7	32.3%	.071	9.6%	1.62	0.96–2.75
Body mass (kg)							0.06
Q1	71.7 ± 3.6	16.5%	REF	–	1.00	–
Q2	79.5 ± 1.8	30.3%	.001	13.8%	2.20	1.36–3.56
Q3	86.0 ± 1.9	37.5%	<.001	21.0%	3.04	1.90–4.86
Q4	95.9 ± 5.5	39.1%	<.001	22.6%	3.25	2.03–5.20
Body mass (kg)—adjusted for height (cm)c							0.06
Q1	71.7 ± 3.6	18.2%	REF	–	1.00	–
Q2	79.5 ± 1.8	30.9%	.006	12.7%	2.01	1.23–3.28
Q3	86.0 ± 1.9	36.4%	<.001	18.2%	2.57	1.56–4.24
Q4	95.9 ± 5.5	35.9%	.001	17.7%	2.52	1.47–4.32
BMI (kg/m2)							0.04
Q1	23.4 ± 1.0	17.6%	REF	–	1.00	–
Q2	25.5 ± 0.5	37.6%	<.001	20.0%	2.82	1.77–4.49
Q3	27.1 ± 0.5	36.0%	<.001	18.4%	2.64	1.66–4.20
Q4	29.7 ± 1.5	32.2%	.001	14.6%	2.22	1.39–3.56
Body fat (%)							0.13
Q1	14.2 ± 1.6	51.6%	REF	–	1.00	–
Q2	17.3 ± 0.7	41.4%	.428	−10.2%	0.66	0.24–1.84
Q3	20.1 ± 0.9	28.6%	.075	−23.0%	0.38	0.13–1.11
Q4	25.2 ± 2.2	13.8%	.003	−37.8%	0.15	0.04–0.53
Fat mass (kg)							0.07
Q1	10.7 ± 1.4	43.3%	REF	–	1.00	–
Q2	13.3 ± 0.6	41.4%	.879	−1.9%	0.92	0.33–2.59
Q3	15.9 ± 0.8	34.5%	.487	−8.8%	0.69	0.24–1.97
Q4	21.2 ± 2.8	17.2%	.034	−26.1%	0.27	0.08–0.91
Lean mass (kg)							0.12
Q1	54.1 ± 5.9	20.0%	REF	–	1.00	–
Q2	61.9 ± 1.5	27.6%	.495	7.6%	1.52	0.46–5.11
Q3	66.1 ± 1.4	31.0%	.334	11.0%	1.80	0.55–5.92
Q4	73.2 ± 3.8	58.6%	.003	38.6%	5.67	1.78–18.1
BMC (kg)							0.07
Q1	2.84 ± 0.19	26.7%	REF	–	1.00	–
Q2	3.19 ± 0.07	24.1%	.824	−2.6%	0.88	0.27–2.83
Q3	3.43 ± 0.07	34.5%	.515	7.8%	1.45	0.48–4.41
Q4	3.96 ± 0.59	51.7%	.052	25.0%	2.95	0.99–8.75
BMD (g/cm2)							0.19
Q1	1.18 ± 0.05	20.0%	REF	–	1.00	–
Q2	1.27 ± 0.02	13.8%	.527	−6.2%	0.64	0.16–2.55
Q3	1.33 ± 0.02	46.7%	.032	26.7%	3.50	1.11–11.0
Q4	1.44 ± 0.05	57.1%	.005	37.1%	5.33	1.66–17.1

Increase Muscle Mass (while maintaining competitive run times)

Higher levels of lean muscle mass was the predictor most strongly correlated with getting selected. To those who have not reviewed our previous article which outlined that rucking is the greatest predictor of SFAS success and that muscle mass and strength are most associated with low ruck march times, this may comes as a surprise.

But it makes perfect sense. Candidates are required to perform heavy load carriage with ruck marches, grip heavy jerry cans, and move heavy apparatuses. All of these activities are biased towards strength, and MASS MOVES MASS. A candidate who weighs 150lbs will have a lot harder time rucking with his 65lb rucksack than a candidate who weighs 200lbs, and the selection stats prove this. Candidates who weigh less than 166lbs have an abysmally low selection rate of 16%, while those who weigh 199lbs or more have a 39% selection rate.

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Muscle Mass Results in Slow Run Times?

One rebuttal we have received when suggesting candidates follow a regimented weight lifting program to build muscle mass and gain strength is that run times will suffer. The data does show that increased levels of lean muscle mass was associated with slower run times.

But overall, candidates in the top 25% of lean mass had three times the odds of being selected than those in the bottom 25%. What does this mean?

Well, candidates should strive to pack on as much lean muscle mass and strength as possible while maintaining a competitive 2 mile and 5 mile time. To give some context, the average selected SFAS candidate was 5’10.5 and 189lbs. The average candidate who was not selected was 5’9.5 and 181lbs.

And when we look at the predicted selection rate based on body mass adjusted for the average 5’10 guy, the optimal weight is between 185lbs and 222lbs. Candidates should strive to build muscle mass and strength while maintaining competitive run times (2 mile < 13min, 5 mile < 36min).

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Lower Body Fat Percentage

While muscle mass is the greatest predictor of SFAS success, low body fat percentage was associated with improvement on all physical performance metrics, and the second greatest predictor of SFAS success.

Candidates in the lowest quartile of body fat percentage had a 51% selection rate, while those in the top quartile had a 13% selection rate. Additional fat mass is likely detrimental to performance because it does not contribute to generating force, while lean muscle mass does. Candidates with low body fat percentages had faster 2 mile run times, obstacle course performances, and performed more sit up, push up, and pull ups.

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Get Shredded for Selection?

Candidate with 15.8% body fat (plus or minus 1.6%) had a 51.6% selection rate.

Candidates with 17.3% body fat (plus or minus 0.7%) had a 41.4% selection rate.

Candidates with 20.1% body fat (plus or minus 0.9%) had a 28.6% selection rate.

Candidates with 25.2% body fat (plus or minus 2.2%) had a 13.8% selection rate.

Remember, these body fat percentages were performed with a DEXA scan. Here are two examples of physiques and body fat percentages from DEXA scans.

The man on the left is 16.9% body fat, and the man on the right is 21.2% body fat.

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Conclusion

On average, selected candidates were taller, had more muscle mass, and were heavier. They also had lower body fat percentages and less fat mass. Candidates should maintain a lean physique to facilitate performance on improvements in running and calisthenics, while simultaneously focusing on build muscle and strength to improve rucking times.

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Read More

How to Join Special Forces as a Civilian
Resources to Train for Special Forces
Weight Lifting Program for Special Forces