Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter.
Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 141
Body Composition and Physical Performance 1992.
Pp. 141-173. Washington, D.C.
National Academy Press
9
Associations Among Body
Composition, Physical Fitness,
and Injury in Men and Women
Army Trainees
Bruce H. [ones, Matthew W. Bovee, and Joseph ]. Knapik
INTRODUCTION
Policies regulating the body composition of men and women in the
military service are a matter of ongoing interest to the U.S. Army. Body
composition is considered to be a component of a soldier's physical fitness,
and in the Army's view, obesity is associated with being unfit and "unsol-
dierly." This association is important because physical fitness is an essen-
tial component of military readiness for combat. To be prepared for its
combat mission, the Army attempts to select individuals with the fitness
and stamina to endure the rigors of Army training and combat. Simply
selecting fit men and women is not adequate, however, because physical
training is necessary to both develop and maintain the fitness of soldiers.
For physical training to be effective, however, it must overload cardiovas-
cular and musculoskeletal systems. This overloading entails a risk of mus-
culoskeletal injury. Thus an understanding of the interactions among body
composition, physical fitness, training, and injuries is an essential founda-
tion for policies governing both body composition and physical fitness.
In the following background material, the links between body composi-
tion and physical fitness made in Army regulations and policy will be re-
viewed, and components of physical fitness deemed to be essential to the
Army's mission will be enumerated. The assumption that body composition
reflects an individual's physical fitness will be explored. Also, the interac
141
OCR for page 142
42
BRUCE H. JONES, MATTHEW W. BOVEE, AND JOSEPH J. KNAPIK
lions between fitness, training, and injuries will be examined. Following this
background material, the results of two recent Army studies will be presented.
Individuals with a wide range in body fat (BF) volunteer to join the
Army annually, but not all are accepted for service. Because the Army is
concerned about the fitness of enlisters, some volunteers are medically dis-
qualified solely on the basis of their height and weight before entering the
service, the presumption being that they are not physically fit enough to be
enlisted (Fried!, chapter 3~. Army standards for medical fitness are set forth
in Army Regulation (AR) 40-501 (1987), which contains tables of accept-
able heights and weights for enlistment in the Army. On the basis of these
height-weight standards, only about 5 percent of eligible men in the United
States would be excluded from service in the Army. In contrast, over 30
percent of otherwise eligible women would be excluded (Friedl et al. 1989~.
In addition to height-weight standards, the Army also has a weight
control program that defines acceptable percentages of BE for individuals
who fail to meet the height-weight standards after enlistment (Army Regu-
lation 600-9; U.S. Army, 1986~. The two primary stated purposes of the
Army weight control program are to ensure that soldiers are adequately
physically fit to accomplish their combat mission and that they present "a
trim military appearance."
Because of its demand for physically fit soldiers, the Army has a pro-
gram of physical fitness, which is defined in Army Regulation 350-15 (AR
350-15; U.S. Army, 1989~. The objectives of this program are to enhance
combat readiness by developing and maintaining high levels of physical
fitness in all soldiers as measured by cardiorespiratory and muscular endur-
ance, muscle strength, flexibility, anaerobic performance, competitive spir-
it, self-discipline, and BF composition. The emphasis on physical fitness in
both the selection and retention process seems appropriate because soldiers
must have enough stamina and strength to perform a wide variety of physi-
cally demanding tasks such as marching with loads, digging fox holes,
scaling walls, and loading artillery shells.
Physical fitness and appropriate body composition are achieved and
maintained through physical training. The Army's program of physical
fitness training is described in Army Field Manual 21-20 (FM 21-20; U.S.
Department of the Army, 1985~. The manual lists five components of
fitness the program strives to develop:
· cardiorespiratory endurance;
· strength;
· muscle endurance;
· flexibility; and
· body composition, which includes lean body mass and fat mass and
which is affected by the other components of fitness.
OCR for page 143
BODY COMPOSITION, PHYSICAL FITNESS, AND INJURY
143
Army doctrine links physical fitness, weight control, body composition,
and physical training. Regulations regarding physical fitness and training in-
dicate that body composition is simply a subcomponent of fitness (U.S. De-
partment of the Army, 1985, 1989~. Even the weight control regulation (AR
600-9) states that its primary objective is physical fitness. For this reason,
before policies on the issue are decided, it is important to assess the degree to
which body composition influences the other components of physical fitness.
Injuries are another important consideration. Soldiers disabled by inju-
ry are less able to perform their regular duties even if they are otherwise
highly physically fit. In a sense, injury-prone soldiers are less physically fit
than those who are able to continuously perform their duties. Training- and
activity-related injuries are a matter of concern to the military not only
because they limit the function of individual soldiers, but because they
impinge on the combat readiness of entire units when their incidence is
even moderately high.
Existing data indicate that the incidence of training-related injuries is
high especially during basic training (Bensel and Kish, 1983; Cowan et al.,
1988; Jones et al., 1988; Kowal, 19801. One report (Tomlinson et al., 1987)
indicates that training-related injury rates are high among active duty sol-
diers as well. The majority of these injuries are overuse conditions of the
lower extremities, which arise directly from Army training or sports activi-
ties that the Army encourages (Jones, 1983; Tomlinson et al., 19871. His-
torical data also indicate that musculoskeletal injuries similar to those
seen in training are a common cause of morbidity even during wartime
(Reister, 1975~.
In exploring body composition as an indicator of fitness, it is important
to examine the relationship of body composition not only to components of
fitness listed in the Army fitness and training documents but also to injury.
Scientific literature on the interrelationships among body composition, physical
fitness, training, and injury will be explored next. In these studies body
composition is measured by either percent BF or body mass index (BMI).
It is well accepted by both military (Jette et al., 1990; Vogel and Friedl,
chapter 6) and civilian (Buskirk and Taylor, 1957; Cureton et al., 1979;
Miller and Blyth, 1955) authorities that increased BF is associated with
decreased weight-bearing endurance performance. Also, performance of
other physical activities and exercises are negatively affected by higher
levels of BF (Cureton et al., 1979; Jette et al., 1990; Vogel and Friedl,
chapter 61. Despite their significance, the correlations between percent BF
or BMI and other measures of physical fitness are low. Body composition
explains only 5 to 30 percent of the variance in endurance performance
measured by maximum oxygen uptake or timed run distance and even less
of other factors, such as sit-ups, push-ups, or vertical jumps (Cureton et al.,
1979; Jette et al., 1990; Vogel and Friedl, in press).
OCR for page 144
144
BRUCE H. JONES, MATTHEW W. BOVEE, AND JOSEPH J. KNAPIK
It is also well established that there is a dose response relationship
between increased training volume and increased risk of injury (Koplan et
al., 1985; Powell et al., 19861. Several studies have documented that higher
amounts of training-especially higher running mileage are associated with
higher injury rates (Blair et al., 1987; Koplan et al., 1982; Macera et al.,
1989a,b; Marti et al., 1988; Pollock et al., 1977~. With the exception of
volume of training, other risk factors for injury associated with physical
training have not been clearly established.
Physical fitness and body composition are suspected to affect the risks
of injury during physical activity for civilians and military personnel (Bensel,
1976; Cowan et al., 1988; Jones, 1983; Koplan et al., 1985; Macera et al.,
1989a), but the exact nature of that relationship has not been clearly estab-
lished. Another possible risk factor of importance to the military that may
be associated with both fitness and body composition is gender. During
basic training the incidence of injury for women has consistently been high-
er than that for men (Bensel and Kish, 1983; Kowal, 1980), but civilian
studies have not identified gender as a risk factor (Koplan et al., 1982;
Macera et al., 1989a,b).
TWO ARMY STUDIES OF
BODY COMPOSITION, FITNESS, AND INJURY
Rational decisions regarding Army policy on fitness, fatness, and training
are best made when based on data from military populations. As a founda-
tion for decision making, this paper will examine data from two epidemio-
logic studies of male and female Army trainees that were conducted by the
U.S. Army Research Institute of Environmental Medicine and that provide
further insight into the following areas:
· the relationship of percent OF and BMI with physical fitness and
their relative importance as predictors of physical fitness in male and fe-
male Army trainees;
· the degree of association of percent BE and BMI with risks of training
related injuries in men and women;
· the degree of association between physical fitness and risks of injury
in men and women;
· the degree of association between past physical activity or training
and current risks of injury;
· the relative importance of different parameters of body composition,
physical fitness, and physical training (activity) on risks of injury using a
multivariate model; and
· the implications of the above determinations for screening, selecting,
and training military personnel.
OCR for page 145
BODY COMPOSITION, PHYSICAL FITNESS, AND INJURY
Methods
145
The two studies described below were prospective follow-up studies of
initial entry trainees. Both were conducted at Fort Jackson, South Carolina.
One was completed in 1984 and the other in 1988, and both followed train-
ees through the full course of the 8-week basic training cycle.
Subjects
In 1984 potential volunteers were all trainees coming to the Fort Jack-
son reception station on one weekend. Ninety-nine percent volunteered to
participate. In 1988 volunteers were solicited from all women being pro-
cessed at the Fort Jackson reception station during 1 month. Male volun-
teers were recruited from men destined to be assigned to companies in the
same battalions as the female volunteers during the same 1-month period.
The volunteer rate from the second group in 1988 was 92 percent in this
group.
The 1984 data are from a population of 310 trainees (124 men and 186
women). The 1988 data are from three training battalions, a total of 2,245
trainees (1,349 men and 896 women). Because not all trainees in either
study were able to take all portions of the testing due to scheduling con-
flicts or assignment to other duties, the number of subjects Was not identical
in all portions of the analysis. Also, roughly 5 percent of men and 7 percent
of women trainees were lost from follow-up due to discharge from the
Army or transfer to another unit. Both studies were conducted in two
phases: a prescreening phase, which consisted of a series of body composi-
tion and physical fitness measures along with a questionnaire, and a follow-
up phase, which included a medical records review.
Both studies used a similar series of prescreening measures including
height, weight, percent body fat (BF), body mass index (BMI), a health and
fitness questionnaire, and Army physical fitness test results. Prescreening
measures were made on all individuals over a period of 1 or 2 days, with
the exception of physical fitness tests. Prior to screening, trainees were
informed of the nature of the study. Those who volunteered signed a con-
sent form, immediately after which they were screened and given the ques-
tionnaire. Follow-up consisted of medical records review and documenta-
tion of training.
Prescreening Measures
At Fort Jackson in 1984, BE was estimated from four skinfold measure-
ments using the equations of Durnin and Womersley (1974~.~ For the 1988
OCR for page 146
46
BRUCE H. JONES, MATTHEW W. BOVEE, AND JOSEPH J. KNAPIK
study, circumference measures were used to estimate percent BE (separate
sites and equations for men and women as specified in Army Regulation
600-9; U.S. Army, 19861. BMI for both men and women was calculated as
weight divided by height squared.
Physical fitness was assessed with the Army physical fitness test, which
was taken within the first 3 days of the onset of basic training. Measures
taken were 1-mile run or 2-mile run times and the number of sit-ups and
push-ups performed in a 2-minute time period. Entire units (companies) ran
either a 1- or a 2-mile "diagnostic fitness" test.
At Fort Jackson in 1984, past physical activity and sports participation
were assessed by a questionnaire delivered to groups of 50 or more recruits.
Each question was read aloud by trained personnel. The primary question
to assess physical activity level prior to entering the Army was: How active
are you compared to others of your age and sex? Subjects were asked to
rate their activity on a 4-point scale from inactive to very active. A similar
question was validated by Washburn et al. (1987~.
Total kcals of energy expended in leisure time recreational and sports
activities per week were estimated from questionnaire data. Study partici-
pants were asked to check activities they had done in the last year on a list
of common activities. For each activity checked they were asked to list
how many days per week on average they performed the activity and how
many minutes per performance. The average number of performances per
week was multiplied by the average number of minutes per performance a
subject reported doing an activity in the last 6 months. The number of kcals
per week was attained by multiplying minutes per week by an estimate of
the average number of kcals expended in a specified activity per minute.
All estimates were then summed for each individual. The question was
modeled after the Minnesota Leisure Time Physical Activity questionnaire
(Taylor, 1978~.
The 1984 questionnaire also queried trainees about their prior athletic
status (nonathlete = 1, recreational athlete = 2, nonschool team or intramu-
ral athlete = 3, and varsity athlete = 4~. The usual energy intensity (kcals
expended per minute) of the trainees' leisure time and sports activity was
also estimated by the investigators and rated on a four point scale (1 =
sedentary, 2 = low, 3 = moderate, and 4 = high). A more extensive ques-
tionnaire was delivered at Fort Jackson in 1988; the analyzed results are
not yet available.
Medical Follow-up
Medical follow-up was achieved by a periodic 100 percent medical
record review of every chart of every study participant. In 1984 a single
records review was conducted during the last week of training. In 1988
OCR for page 147
BODY COMPOSITION, PHYSICAL FITNESS, AND INJURY
147
records were reviewed every 2 to 3 weeks. An injury was defined as a sick-
call visit to a troop medical clinic for a musculoskeletal complaint that
received an injury diagnosis by a medical caretaker, usually a physician's
assistant or a physician.
Physical Training
Physical training was assessed by scrutinizing company training sched-
ules and verbal reports from company cadre in 1984. In 1988 daily training
logs were also used to document training.
Physical training for companies of men or women trainees for a specific
year was similar. In 1984 trainees ran and performed calisthenics 4 to 6
days per week. Men generally started running 1 mile and progressively
increased the distance of runs by about 0.5 mile per run each week up to 3
miles per run. On occasion they may have run 4 or 5 miles at a time near
the end of the training cycle. Women began running distances of 0.5 mile
per run and progressed in distance 0.5 mile per week up to 3 miles per run.
At Fort Jackson in 1988, trainees ran only 3 times per week; otherwise
routine physical training was fairly similar to that in 1984. Both years,
each company of trainees was required to complete a 5- to 10-mile road
march while carrying a light load (20 to 25 pounds [lbsi) in the middle of
the training cycle and another 8- to 12-mile march at the end of the cycle
with a heavier load (40 to 45 lbs). Every company also conducted training
and ran a time trial on an obstacle course and a confidence course.
Analysis
Pearson product-moment correlation coefficients were calculated to de-
scribe the relationship between continuous variables such as percent BF,
BMI, and physical fitness measurements (that is, run times and numbers of
sit-ups and push-ups). Also, to determine whether endurance performance
(run times) of trainees at different points along the spectrum of percent BF
and BMI was different, trainees were divided into quintiles (five roughly
equal-sized groups) on the basis of BF measures and weight-height ratios
(BMI). The mean run times of men and women in successive groups by
percent BF or BMI were compared to each other for significance using a
one-way analysis of variance (ANOVA). For significant ANOVAs, signif-
icant between-group differences were identified using a least significant
difference post hoc test.
A stepwise multiple regression model was developed to predict mile
run times for men and women from other physical measurements and ques-
tionnaire data at Fort Jackson in 1984. Changes in R2 values from the
stepwise regression output were interpreted as indicators of the amount of
OCR for page 148
148
BRUCE H. JONES, MATTHEW W. BOVEE, AND JOSEPH J. KNAPIK
variance in endurance performance explained by successive predictors step-
ping into the equations. The point estimate of the significance of B coeffi-
cients for each successive predictor variable are reported as p values in the
text. The significance of F scores are also reported for the successive steps
in the models for both men and women.
Risks of injury were calculated as the cumulative incidence (percent) of
trainees incurring one or more training-related injuries during the 8-week
basic training cycle. Relative risks (percent injured in contrast group divid-
ed by percent injured in referent group) were used to compare the incidence
of injury in groups possessing different supposed risk factors or exposed to
different levels of a risk factor. Significance of contrasted risks was tested
with simple chi-square tests or partitioned chi-squares. Mantel-Haenszel
chi-squares for linear trends were used when a trend was suspected on
inspection of the data.
To compare the risks of individuals exhibiting different levels of a
continuous risk factor such as percent BE or mile run time, subjects were
divided into successive quartiles (four roughly equal-sized groups) or quin-
tiles (five nearly equal-sized groups) of risk based on their measured value
of the variable of interest. For the 1984 data, trainees were placed into
quartiles of risk based on continuous measured variables because the sam-
ple size lacked power to demonstrate differences between smaller-sized groups.
Trainees in the 1988 study were divided into quintiles to obtain a clearer
picture of trends and because the sample size was large enough to support
more divisions without sacrificing power.
In both studies for all potential risk factors examined, a referent level
of risk was chosen, and each other level was compared to it. Referent
levels were usually the lowest level of risk observed or the level believed to
have the lowest risk based on other knowledge. Relative risks were calcu-
lated for each contrast. For the 1984 data, 90 percent confidence intervals
are reported in the tables below because this was a hypothesis-generating
study, and we did not want to fail to recognize a possible significant associ-
ation due to lack of power secondary to a small sample size. For 1988 data,
both 90 and 95 percent confidence intervals are reported in the tables be-
low. Point estimates of significance (p values) are reported in the text when
appropriate.
To control for the influence of body composition and physical fitness
on the risks of injury for women compared to men, Mantel-Haenszel chi-
squares stratified on percent BF and mile run times, respectively, were
performed. Finally, a stepwise logistic regression was also performed to
determine the most important factors contributing to the risk of injury in a
model where the effects of multiple factors were controlled for simulta
neously.
OCR for page 149
BODY COMPOSITION, PHYSICAL FITNESS, AND INJURY
Results
149
The mean physical characteristics and physical fitness test results for
men and women trainees in 1984 and 1988 are listed in Table 9-1. Compar-
isons of the descriptive characteristics and fitness of men in 1984 and 1988
indicate that they were very similar in age, height, weight, percent BE, and
BMI, but in 1988 they appeared to be slightly less fit; the same was true for
women. Comparing men and women, the men were taller, heavier, and had
higher BMIs than women in both 1984 and 1988, while women had higher
percentages of BF. In both years, men ran faster and performed more push
TABLE 9-1 Mean Descriptive Characteristics and Physical Fitness Test
Results of Men and Women Army Trainees at Fort Jackson, South
Carolina, in 1984 and 1988
Men
Women
Variable n Mean (SD) n Mean (SD)
1984
Age (years) 124 20.2 (2.7) 186 21.2 (3.6)*
Height (cm) 123 175.2 (6.6) 186 163.3 (6.6)
Weight (kg) 124 73.6 (10.9) 186 58.7 (5.8)
Body mass index
(weight/height2) 123 24.3 (3.1 ) 186 22.4 (2.0)*
Body fat (%) 124 16.9 (4~9) 186 25.2 (9.4)*
1-Mile run
(minutes) 79 7.2 (1.0) 140 9.7 (1.4)*
Sit-ups (no.) 98 54.5 (13.8) 163 39.7 (11.9)*
Push-ups (no.) 97 31.0 (9.3) 138 12.4 (9~9)*
1988
Age (years) 1,056 20.1 (3.3) 921 20.2 (3.5)*
Height (cm) 1,053 175.2 (7.1) 895 162.0 (6.5)
Weight (kg) 1,053 75.7 (12.2) 895 58.3 (6.5)
Body mass index
(weight~eight2) 1,053 24.6 (3.6) 895 22.2 (2.0)
Body fat (%) 1,053 16.1 (5.8) 895 26.8 (3.0)
1-Mile run
(minutes) 756 7.6 (0~9) 541 10.3 (1.8)*
2-Mile run
(minutes) 593 16.4 (2.2) 355 20.3 (2.3)*
Sit-ups (no.) 1,357 44.3 (12.2) 902 33.9 (13.8)*
Push-ups (no.) 1,357 30.5 (12.9) 792 10.3 (7~3)
*Difference between men and women significant at p < .05.
OCR for page 150
150
BRUCE H. JONES, MATTHEW W. BOVEE, AND JOSEPH J. KNAPIK
ups and sit-ups than women. Cutoff points for quartiles and quintiles of
percent BF, BMI, and run times are listed in Table 9-2 for 1984 and Table
9-3 for 1988.
Correlation of percent BF and Body Mass Index
The correlation between percent BF by skinfolds and BMI among men
trainees in 1984 was .81 (p < .000), and the correlation between BF by
circumferences and BMI in 1988 was .84 (p < .000~. For women trainees in
1984, the correlation between body fat by skinfolds and BMI was .64, while
in 1988 the correlation of body fat by circumferences and BMI was .86.
TABLE 9-2 Body Composition and Fitness Variable Medians, Quartile
Cutoff Points, and Ranges for Men and Women Army Trainees at Fort
Jackson, South Carolina, 1984
*
Variable Median Quartile Cutoff Point Range
Men
Percent body fat 16.6 Q1 13.1 7-29
Q3 20.6
Body mass index (kg/m2) 23.7 Q1 22.1 19-31
Q3 26.5
1-Mile run (minutes) 7.0 Q1 6.4 5.9-11.5
Q3 7.7
Sit-ups 52 Q 1 46.8 16-99
Q3 64.0
Push-ups 31 Q 1 26.5 4-53
Q3 36.0
Women
Percent body fat 25.1 Q122.4 14-37
Q3.4
Body mass index (kg/m2) 22.5 Q121.1 18-27
Q323.6
1-Mile run (minutes) 9.8 Q19.0 6.0-16.3
Q310.4
Sit-ups 51 Q 130.0 6-66
Q346.0
Push-ups 11 Q15.0
Q317.0
Median = Q2.
OCR for page 151
151
TABLE 9-3 Body Composition and Fitness Variable Medians, Quintile
Cutoff Points, and Ranges for Men and Women Army Trainees at Fort
Jackson, South Carolina, 1988
Variable Median Quintile Cutoff Point Range
Men
Percent body fat 15.4 Q 1 10.98 2.13-36.12
Q2 14.00
Q3 17.38
Q4 21.50
Body mass index (kg/m2) 24.3 Q1 21.38 17.22-34.32
Q2 23.34
Q3 25.14
Q4 28.07
1-Mile run (minutes) 7.5 Q1 6.83 5.5-10.9
Q2 7.27
Q3 7.73
Q4 8.38
2-Mile run (minutes) 16.4 Q1 14.60 11.4-26.0
Q2 15.67
Q3 16.56
Q4 17.83
Sit-ups 45 Q 1 34 2-85
Q2 41
Q3 47
Q4 54
Push-ups 29 Q 1 19 1-87
Q2 26
Q3 32
Q4 40
Women
Percent body fat 27.00 Q1 23.50 15.8~2.6
Q2 25.86
Q3 27.90
Q4 30.10
Body mass index (kg/m2) 22.4 Q1 20.27 16.36-27.20
Q2 21.79
Q3 22.97
Q4 24.11
1-Mile run (minutes) 10.0 Q1 8.94 5.6-19.3
Q2 9.72
Q3 10.41
Q4 11.50
continued on next page
OCR for page 164
64
BRUCE H. JONES, MAITHEW W. BOVEE, AND JOSEPH J. KNAPIK
TABLE 9-13 Risk of Injury for Women Versus Men Army Trainees by
Tertiles* of Mile Run Time, Fort Jackson, South Carolina, 1984
Risk of Injury (%)t
Run Time Confidence Interval
Fertile Women Men Risk Ratio (95%)
2
3
20.0% 17.5% 1.1 (~3~5)
(2tlO) (1 1/63)
37.3% 46.7% 0.8 (.4-1.5)
(22/59) (7/15)
57.7% 0.0%
(47/71) (0/1)
NOTE: Mantel-Haenszel summary risk ratio = .98 (.4 - 2.3); Mantel-Haenszel chi-square =
0.00, p = 1.00.)
*Tertiles were: T1 = S.9 - 7.9 minutes; T2 = 7.9 - 9.7 minutes; T3 = > 9.7 minutes.
"Percent risk = injured/(injured + not injured).
endurance as measured by run times was the best predictor of training-
related injuries.
Discussion
These two studies at Fort Jackson provided a unique opportunity to
prospectively examine the relationships among body composition, physical
fitness, and injury in men and women. The assemblage of basic trainees at
an Army reception station for several days prior to the onset of basic train-
ing permitted the collection of baseline data from direct physical measure-
ments and questionnaires. Access to medical records of this young, healthy
population provided an opportunity that would be rare outside the military.
Also, the records represent all health care received, because basic trainees
do not have access to any other health care system. A final unique aspect of
this study was that, unlike most epidemiologic studies of this nature on
civilian sports and exercise populations, all individuals in the study were
engaged in similar types and amounts of physical training and other daily
. . .
activities.
Many of the results of this study, such as the correlation between in-
creasing percent BE and decreasing endurance performance, were similar to
those reported by previous investigators. Other findings, such as the associ-
ation between lower levels of physical fitness and higher risks of injury,
were unique. These singular findings may be explained by characteristics
of this study design that were different from previous studies of this nature.
OCR for page 165
BODY COMPOSITION, PHYSICAL FITNESS, AND INJURY
165
Results of this study have important implications for the military and phys-
ically active civilian populations.
Correlation Between Body Composition and Physical Fitness
Because an underlying assumption of Army policy is that fatter soldiers
are less fit, it was deemed important to examine that premise. Others have
found significant correlations between measures of BF and fitness. Vogel
and Friedl (chapter 6) found a significant correlation (r = -.48) between
percent BF and maximum oxygen uptake for men. In another recent study,
Jette et al. (1990) reported correlations between BMI and estimated maxi-
mum oxygen uptake of -.41 for men and -.54 for women. Cureton et al.
(1979) found negative correlations between percent BF and run times of
men and women of-.30 and-.22, respectively. The findings presented here
were parallel to those; significant positive correlations were observed between
percent BF and 1- or 2-mile run times of .27 to .53 for men, but only .12 to .16
for women, which indicates that fatter men and women run slower.
In this study, correlations between BMI and run times were also signif-
icant and positive but of lower magnitude than for percent BF. This lower
correlation probably occurred because BMI is only a surrogate measure of
percent BF, and it is the inert fat tissue that detracts from weight-bearing
endurance performance. BMI accounted for only 65 to 70 percent of the
variance in percent BF among men trainees and between 40 and 70 percent
of the variance for women trainees.
Negative correlations between BMI and number of sit-ups performed in
1-minute intervals have been reported by Jette et al. (1990~: r = -.24 and r
= -.15 for men and women, respectively. In this study, negative correla-
tions were found between percent BF and number of sit-ups in 2 minutes of
-.17 to -.29 for men and -.12 to -.14 for women. Jette et al. (1990) also
observed negative correlations between BMI and push-ups with r = -.22 for
both men and women. Correlations in this study between percent BF and
push-ups for men ranged from -.17 to -.29, and those for women ranged
from -.02 to-.18. Correlations between BMI and sit-ups and push-ups
were lower than for percent BF and these calisthenics.
In general, the correlations between measures of BF and either push-
ups or sit-ups were lower than for those with weight-bearing endurance
performance such as running. These lower correlations with BF are attrib-
uted to the fact that individuals must lift only a portion of their body weight
against gravity to perform push-ups and sit-ups, but they must lift their
entire body weight, including the fat, to run.
To further understand the degree and significance of changes in run
times as level of BF increases, these changes were analyzed for successive
quintiles of BF in 1988. Significant differences in run times were found
OCR for page 166
66
BRUCE H. JONES, MATTHEW W. BOVEE, AND JOSEPH J. KNAPlK
between successive quintiles of percent BF among men, but only between
the extreme quintiles of BF, the fattest and the lower ones, among women.
This finding suggests that in this study, percent BF is not as good a discrim-
inator of fitness for women as for men. Vogel and Friedl (chapter 6) found
significant decreases in run time between quartiles of active-duty men and
women soldiers with successively higher percentages of BF.
As an aside, the relative run times of women may not be as strongly
affected by increases in percent BF because the relative range of fatness for
women is less than for men. The range of fatness for women is from 16 to
34 percent, a relative difference of 2.3 between extremes, while for men the
range is 2 to 30 percent, a 15-fold difference (Friedl et al., 1989~. For this
reason, percent BF provides less discriminating power for women.
The consistency and significance of the correlation between measures
of BF and endurance performance are important to the military because
current regulations and policy assume such a relationship. Also, the stron-
ger correlations between measures of percent BF and physical fitness (that
is, run times, sit-ups, and push-ups) than between BMI and fitness have
important implications for the military. Stronger correlations with percent
BF suggest that using BF standards rather than BMI or height-weight tables
as criteria for enlistment and retention would provide a better indicator
of recruit and soldier fitness not to mention a better measure of body
composition.
Predicting Endurance
Because of the universal requirement for soldiers to march and carry
loads, models were developed to predict the endurance performance of men
and women. A multiple regression model was used to determine the rela-
tive importance of multiple factors suspected of contributing to weight-
bearing endurance as measured by 1-mile run times. For both men and
women, the same 10 potential predictors of physical performance were can-
didate variables for the models: age, height, weight, percent BF, sit-ups,
push-ups, total leisure-time, kcals per week, self-assessed activity level,
level of sports participation, and aerobic intensity of usual leisure-time ac-
tivities. Four variables contributed to the final model for men, and five
variables contributed to the final model for women.
In the men's endurance prediction model, percent BF stepped into the
equation second-explaining 11 percent of the variance in run times-be-
hind sit-ups, which explained 19 percent of the variance. For the women's
model, percent BF stepped into the equation fourth behind self-assessed
activity, height, and sit-ups-explaining only 3 percent of the variance in
the run times of women trainees. Activity level was important in both
OCR for page 167
BODY COMPOSITION, PHYSICAL FITNESS, AND INJURY
167
models and explained more of the variance in endurance (15 percent) among
women than any other variable.
Results of this modeling suggest several things. First the regression
models coupled with the lower correlations between percent BF and run
times for women reported above suggest that percent BF is not as good an
indicator of fitness for women as it is for men. Second, the models for
predicting endurance performance suggest that in addition to percent BF,
other simple measures such as sit-ups-during the selection process might
contribute significantly to the Army's ability to recruit fit soldiers. Al-
though it might be difficult to use questions on self-assessed activity like
those in this study in the context of recruiting soldiers, it is clear that past
activity is an important factor in the prediction of fitness.
Risks of Injury
Previous studies have reported the incidence of musculoskeletal com-
plaints ranging from 42 to 54 percent for women Army trainees and 23 to
26 percent for men (Bensel and Kish, 1983; Jones, 1983; Kowal, 19804.
The cumulative incidence of injuries among trainees in this study was 51
percent for women and 27 percent for men, and the data here suggest that
risks of injury have been relatively stable over almost a decade.
Association Between Body Composition and Risk of Injury
hew studies have examined the association of percent BF and BMI with
the risk of training-related injuries, and no studies have systematically looked
at the relationship of BF and weight-bearing training injuries. A few stud-
ies of runners have examined the relationship of BMI to injuries (Blair et
al., 1987; Macera et al., 1989b; Marti et al., 19881. No association between
BMI and injury was reported for men or women runners in a study by
Macera et al. (1989b), while Blair et al. (1987) reported a slight but signifi-
cant positive correlation (r = .1) between BMI and risk of injury among
runners. More consistent with the findings here is Marti et al.'s (1988)
report of a bimodal distribution of injuries among men runners, in which the
groups with the highest and lowest BMIs in a population of distance runners
suffered the highest incidence of injuries. Macera et al. (1989a) in a pro-
spective study of exercising adults reported that a high BMI at baseline was
a risk factor for men but not for women.
During this study in 1984 it was felt that the relationships between
percent BF or BMI and risk of injury both might be bimodal. The hypothe-
sis was that men and women of more "average" BF, those in the middle
groups, would be at lower risk of injury than those at the high and low
OCR for page 168
68
BRUCE H. JONES, MATTHEW W. BOVEE, AND JOSEPH J. KNAPIK
extremes. For this reason, the middle quartiles and quintiles of body fat and
BMI were chosen as the referent level for contrasting risks.
It now appears, at least among this sample of men and women Army
trainees that the patterns of risk are different for men and women. The
univariate analysis suggests that the men trainees with the highest percent-
ages of BF are at greatest risk of injury. Certainly this was true in 1988
when the men trainees in the highest quintile of BF were at 1.5 times
greater risk than the lower ones. In contrast, it appears that women with the
lowest percentages of BF are at greater risk than those of average percent
BF as seen in 1988, when the women with the lowest body fats were at 1.3
times greater risk than those women in the middle.
With BMI, the distribution of risk of injury appears to be bimodal.
However, the only significant association for men occurred in 1984 when
the trainees with the highest BMI were at 2.1 times greater risk of injury
than those of average BMI. For women, the only significant associations
occurred in 1988. At that time, women with both the highest and lowest
BMI were at 1.5 and 1.6 times greater risk, respectively, than the more
"average" referent group.
Assuming that this observation is correct-that the fattest and highest
BMI men and the leanest and lowest BMI women represent the tails of the
distribution of BF at greatest risk of injury then a plausible explanation
for these findings is necessary. It may be that the men trainees with the
highest BF were at greater risk than their peers because they were carrying
so much extra weight as fat fat that would not only contribute to greater
fatigue at any given level of weight-bearing performance, but also would
impose an additional stress on the musculoskeletal system. Paradoxically, it
may be that the least fat women trainees were at greater risk for the converse
reason: too little lean body mass. Perhaps women with low percentages of
BP who are still relatively fat compared to men may not have enough lean
body mass to support their total body weight without undue stress.
In any case, distinct and consistent patterns of relationship between
percent BF or BMI and risk of injury are not evident. Some of this lack of
correspondence at least for percent BF may be attributable to different tech-
niques of measurement used in 1984 and 1988: skinfolds versus circumfer-
ences, respectively. Also, the apparently different pattern of association
between BF and injury for men and women in this study may hypothetically
be due to the fact that the Army height-weight selection standards artificial-
ly truncate the distribution of percent BF among women trainees. The
height-weight standards effectively exclude 30 percent of eligible women
but only 5 percent of men (Friedlet al., 1989~. Regardless of what accounts
for the differences between men and women, the current upper limits of
height-weight are not effectively excluding the women at greatest risk of
. .
1nJury.
OCR for page 169
BODY COMPOSITION, PlIYS1CAL FITNESS, AND INJURY
Association of Physical Fitness with Risk of injury
169
The association between physical fitness and risk of injury in this study
is more consistent for both men and women than the association with BE.
In fact, as the stratified and logistic regression analyses suggest, endurance
or weight-bearing fitness was the factor most strongly associated with risk
of injury. Men and women in this study with the least endurance that is,
the slowest run times-were at greatest risk of injury. The slowest men
were at 1.4 to 2.8 times greater risk than their slower counterparts, and the
slower women were at 1.3 to 1.8 times greater risk.
Other authors have not reported such a relationship between fitness and
injury. In fact, most report an increase in risk of training injuries for the
most fit individuals (Blair et al., 1987; Macera et al., 1989b; Marti et al.,
1988~. Blair et al. (1987) and Marti et al. (1988) both reported a positive
association between high levels of fitness and high risks of injury on univariate
analysis that disappeared when the amount of training (miles run) was ac-
counted for in a multivariate analysis. This result suggests that in these
studies the relationship between fitness and injury was confounded by the
association of fitness with greater amounts of training.
Studies by others on the relationship of physical fitness to injury pri-
marily investigated runners of different fitness levels who ran for different
numbers of miles at various intensities (Blair et al., 1987; Koplan et al.,
1982; Macera et al., 1989b; Marti et al., 19884. In this study, men and
women within companies (150 to 250 trainees) and to some extent across
companies-ran, marched, and exercised similar amounts and at similar
intensities, intensities that were dictated by the group and Army policy
rather than individual predilections. Thus this study provided controls for
confounding due to varied volume and intensity of training, which other
studies have not.
It is not surprising that a measure of weight-bearing fitness is associat-
ed with injury among Army trainees. The single most common physical
stress during basic training results from weight-bearing physical training, a
stress that is secondary to running, drill and ceremony, marching to and
from training sites, and road marching with loads. Even when not training,
weight-bearing musculoskeletal stress is unavoidable. Walking is usually
the only mode of transportation to and from the mess hall and other sites
during available leisure time. The more aerobically fit trainees are under
less physiological stress at any given activity level and may also have more
prior exposure to musculoskeletal stress. thus decreasing their risk of injury.
Whatever the underlying reason, the data here suggest that a measure of
endurance fitness might provide additional information to assist in identify-
ing injury-prone Army volunteers.
OCR for page 170
170
BRUCE H. JONES, MATTHEW W. BOVEE, AND JOSEPH J. KNAPIK
Association of Physical Activity and Risk of Injury
It is well known that higher volumes (amounts) of training are associat-
ed with higher risks of injuries among runners (Koplan et al., 1985; Powell
et al., 19861. But data from this study demonstrate that risks of injuries
among men trainees at Fort Jackson in 1984 decreased in a stepwise fashion
as self-reported levels of prior physical activity increased, and sedentary
men trainees were more than twice as likely to suffer training injuries. This
finding is similar to that from a study of marine recruits (Gardner et al.,
1988) in which a highly significant trend was observed of decreasing inci-
dence of stress fractures with increasing self-reported activity levels. These
data suggest that for men recruits higher prior physical activity levels may
protect against current injury when they are engaged in a uniform training
program, and are performing the same amounts of exercise as individuals
with less prior exposure to the stress of vigorous physical activity. Other
studies have looked at runners all of whom ran different distances, in which
case the "dose" or volume of running was the primary risk factor (Blair et
al., 1987; Koplan et al., 1982; Macera et al., 1989b; Marti et al., 1988~.
Gender, Physical Fitness, and Risk of injury
In the studies reported here, women were injured significantly more
often than men, between 1.6 and 1.8 times more often. This finding is in
agreement with those of previous Army studies of basic trainees (Bensel
and Kish, 1983; Kowal, 1980) but is not consistent with civilian studies
(Koplan et al., 1982; Macera et al., 1989a,b). The primary risks during
Army basic training are lower extremity injuries associated with weight-
bearing activities such as running and marching. Also, the pattern and
distribution of these injuries is similar to that for civilian runners and jog-
gers (Jones, 1983~. Despite these apparent similarities of trainee activity
and injuries to those of civilian runners and joggers, civilian studies have
not found women to be at higher risk (Koplan et al., 1982; Macera et al.,
1989b, Powell et al., 1986~.
Powell et al. (1986) concluded that "gender per se does not appear to
be an important risk factor for injuries." Macera and her colleagues (1989a,b)
have shown in both civilian runners and in exercising adults that gender is
not a risk factor for injury. Also, Koplan et al. (1982) found no differences
in risk of running injuries between men and women.
Selection bias could account for these contradictory findings between
military and civilian studies. Koplan et al. (1985) indicated that civilian
studies of physical activity, fitness, and related injury suffer from selection
bias. These studies (Koplan et al., 1982; Macera et al., 1989b; Powell et al.,
1986) are biased in that the populations studied include only individuals
OCR for page 171
BODY COMPOSITION, PHYSICAL FITNESS, AND INJURY
171
who were fit enough to tolerate routine vigorous training and had not quit
due to injury or for other reasons. If women were actually at greater risk of
injury, what would be expected is that fewer women would be represented
in the populations studied since women on average are less physically fit
than men (Table 9-1, Vogel et al., 1986~. In fact this is what is found. In
all the cited studies of runners (Koplan et al., 1982; Macera et al., 1989b)
and exercise participants (Macera et al., 1989a), the number of women in
the population examined were only 16 to 23 percent that of men.
If the hypothesis that only men and women who are fit enough to
survive training remain in the population of routine exercisers is true, then
we might expect that the injury rates among men and women of the same
high fitness levels would be similar.
The results of the study of Army
trainees in 1984 support such a conclusion. Although the crude risks of
injury were higher for women, when risks of injury were stratified on run
times (physical fitness), differences in risk between women and men disap-
peared, and the risk ratio approached 1. Also, with the logistic regression
model, gender remained the predominant and only significant risk factor for
injury with an odds ratio of 2.5 (p < .0005) until mile run time was entered
as a potential predictor, whereupon gender ceased to even approach signifi-
cance as a risk factor. Run time (aerobic fitness) replaced gender as the
sole and best Dredictor of injury (odds ratio = 3.5, p ~ .0001~.
., , , - O
~ ~ ~ . .
The possible implications of this finding are important for the Army,
the other military services, and possibly civilian exercise enthusiasts and
medical practitioners for two reasons. First, it suggests that low levels of
aerobic fitness or some related factor are a primary risk factor for muscu-
loskeletal injuries associated with military and possibly other vigorous weight-
bearing training activities such as running. Second, it indicates that gender
per se is not the major risk factor that a crude analysis of military training
injury data might imply, and that low physical fitness may be the underly-
ing predisposing factor.
Conclusion
In general, men enter the Army with lower percentages of BF than
women and are able to perform more sit-ups and push-ups and run faster
than women. They also suffer fewer injuries than women because of their
relatively higher levels of endurance and possibly other associated factors.
Data from this study suggest that measures of percent BF are not as
good at predicting physical fitness for women as they are for men. For both
men and women, physical fitness as measured by even simple techniques
such as sit-ups in combination with BF is a better predictor of other types of
fitness such as mile run times or other forms of weight-bearing endurance
than percent BF alone. Furthermore, higher percentages of BF for men are
OCR for page 172
72
BRUCE H. JONES, MATTHEW W. BOVEE, AND JOSEPH J. KNAPIK
associated with increased risk of injury, but for women they are not. Phys-
ical fitness is a better predictor of injury than BE or gender. Therefore, if
physical fitness and freedom from injury are important to the Army, it
would make sense to at least include some simple measure of fitness in the
screening process for prospective enlisters.
Several important conclusions can be made from this study and also the
process of analysis. A few multivariate analyses can be much more infor-
mative than numerous univariate analyses. Although univariate analyses
are the foundation of multivariate approaches such as those used here, they
are not a substitute for more complex models. More information generated
from larger populations and yielding more powerful multivariate models is
needed. With these models, the Army should be able to predict injuries and
also such factors as career success or discharge. This information could
provide the Army with a rational foundation from which to select and retain
men and women who are most likely to possess the combination of fitness,
fatness, and freedom from injury that is desired for military readiness.
REFERENCES
AR 600-9. 1986. See U.S. Department of the Army. 1986.
AR 40-501. 1987. See U.S. Department of the Army. 1987.
AR 350-15. 1989. See U.S. Department of the Army. 1989
Bensel, C. K. 1976. The effects of tropical and leather combat boots on lower extremity
disorders among Marine recruits. Technical Report No. 76t49/CEMEL. U.S. Army Natick
Research and Development Command, Natick, Mass.
Bensel, C. K., and R. N. Kish. 1983. Lower extremity disorders among men and women in
Army basic training and the effects of two types of boots. Technical Report No. TR-83/
026. U.S. Army Natick Research and Development Laboratories, Natick, Mass.
Blair, S. N., W. K. Harold, and N. N. Goodyear. 1987. Rates and risks for running and exercise
injuries: Studies in three populations. Res. Q. 58:221-228.
Buskirk, E., and H. L. Taylor. 1957. Maximal oxygen intake and its relation to body composi-
tion, with special reference to chronic physical activity and obesity. J. Appl. Physiol.
11 :72-78.
Cowan, D., B. Jones, P. Tomlinson, J. Robinson, D. Polly, P. Frykman, and K. Reynolds.
1988. The epidemiology of physical training injuries in U.S. Army infantry
trainees: Methodology, population and risk factors. Technical Report No. T4-89. U.S.
Army Research Institute of Environmental Medicine, Natick, Mass.
Cureton, K. J., L. D. Hensley, and A. Tiburzi. 1979. Body fatness and performance differences
between men and women. Res. Q. 50:333-340.
Durnin, J.V.G.A. and J. Wormersley. 1974. Body fat assessed from total body density and its
estimation from skinfold thickness: measurements on 481 men and women aged 16 to 72
years. Br. J. Nutr. 32:77-79.
Friedl, K. E., J. A. Vogel, M. W. Bovee, and B. H. Jones. 1989. Assessment of body weight
standards in male and female Army recruits. Technical Report No. 1 15-90. U.S. Army
Research Institute of Environmental Medicine, Natick, Mass.
Gardner, L. I., J. E. Dziados, B. H. Jones, J. R. Brundage, J. M. Harris, R. Sullivan, P. Gill.
OCR for page 173
BODY COMPOSlTlON, PHYSICAL FITNESS, AND INJURY
173
1988. Prevention of lower extremity stress fractures: A controlled trial of a shock absor-
bent insole. Am. J. Public Health 78(12):1563-1567.
Jette, M., W. Lewis, and K. Sidney. 1990. Fitness, performance and anthropometric character-
istics of 19,185 Canadian Forces personnel classified according to body mass index.
Milit. Med. 155:120-126.
Jones, B. H. 1983. Overuse injuries of the lower extremities associated with marching, jog-
ging, and running: A review. Milit. Med. 148:783-787.
Jones, B. H., R. Manikowski, J. A. Harris, J. E. Dziados, S. Norton, T. Ewart, J. A. Vogel.
1988. Incidence of and risk factors for injury and illness among male and female Army
basic trainees. Report number: T 19/88. U.S. Army Research Institute of Environmental
Medicine, Natick, Mass.
Koplan, J. P., K. E. Powell, R. K. Sikes, and R. W. Shirley. 1982. An epidemiologic study of
the benefits and risks of running. J. Am. Med. Assoc. 248:3118-3121.
Koplan, J. P., D. S. Siscovick, and G. M. Goldbaum. 1985. The risks of exercise: A public
health view of injuries and hazards. Public Health Rep. 100(2):189-195.
Kowal, D. M. 1980. Nature and causes of injuries to women resulting from an endurance
training program. Am. J. Sports Med. 8(4):265-269.
Macera, C. A., K. L. Jackson, G. W. Hagenmaier, J. J. Kronenfeld, H. W. Kohl, and S. N.
Blair. 1989a. Age, physical activity, physical fitness, body composition, and incidence
of orthopedic problems. Res. Q. 60:225-233.
Macera, C. A, R. R. Pate, K. E. Powell, K. L. Jackson, G. W. Hagenmaier, J. J. Krmenfeld, H.
W. Kohl, and S. N. Blair. 1989b. Predicting lower-extremity injuries among habitual
runners. Arch. Intern. Med. 149:2565-2568.
Marti, B., J. P. Vader, C. E. Minder, and T. Abelin. 1988. On the epidemiology of running in-
juries. The 1984 Bern Grand-Prix study. Am. J. Sports Med. 16:285-294.
Miller, A. T., Jr., and C. S. Blyth. 1955. Influence of body type and body fat content on the
metabolic cost of work. J. Appl. Physiol. 8:139-141.
Pollock, M. L., L. R. Gettman, C. A. Milesis, M. D. Bah, L. Durstine, and R. B. Johnson.
1977. Effects of frequency and duration of training on attrition and incidence of injury.
Med. and Sci. Sports 9:31-36.
Powell, K. E., H. W. Kohl, C. J. Caspersen, and S. N. Blair. 1986. An epidemiological per-
spective on the causes of running injuries. Phys. Sports Med. 14:100-114.
Reister, F. A. 1975. Medical Statistics in World War II. Office of the Surgeon General, Depart-
ment of the Army, Washington, D.C.
Taylor, H. L., D. R. Jacobs, B. Schucker, J. Knudsen, and A. S. Leon. 1978. A questionnaire
for the assessment of leisure time physical activities. J. Chronic Dis. 31:741-755.
Tomlinson, J. P. W. M. Lednar, and J. D. Jackson. 1987. Risk of injury in soldiers. Milit.
Med. 152:60-64.
U.S. Department of the Army. 1985. Army Field Manual 21-20: Physical Fitness Training.
Headquarters, Washington, D.C.
U.S. Department of the Army. 1986. Army Regulation 600-9. "The Army Weight Control
Program." September 1. Washington, D.C.
U.S. Department of the Army. 1987. Army Regulation 40-501. "Standards of Medical Fitness."
December 1. Washington, D.C.
U.S. Department of the Army. 1989. Army Regulation 350-15. "The Army Physical Fitness
Program." Washington, D.C.
Vogel, J. A., J. F. Patton, R. P. Mello, W. L. Daniels. 1986. An analysis of aerobic capacity in
a large United States population. J. Appl. Physiol. 60:494-500.
Washburn, R. A., L. L. Adams, and G. T. Haile. 1987. Physical activity assessment for epide-
miologic research: The utility of two simplified approaches. Prev. Med. 16:636-646.
OCR for page 174
Representative terms from entire chapter:
body composition
