|Year : 2014 | Volume
| Issue : 2 | Page : 144-150
Relationship of body mass index with 1,600 m running, 50 m swimming, and pull-ups performance in army cadets
Pantelis Theo Nikolaidis, Dionisis Zisimatos
Laboratory of Human Performance and Rehabilitation, Department of Physical and Cultural Education, Hellenic Army Academy, Greece
|Date of Web Publication||9-Oct-2014|
Pantelis Theo Nikolaidis
Thermopylon 7, Nikaia -18450
Context: While the importance of physical fitness for cadets is well-documented, no study has ever been conducted to investigate if there is an optimal body mass index (BMI) for physical fitness in army cadets. Aims: The aim of this study was to examine the association between BMI and physical fitness in cadets. Settings and Design: Cross-sectional study. Materials and Methods: Male army cadets (n = 196, aged 18-19 years) were examined for weight and height, their BMI was calculated, and they performed three tests: 1,600 m running, 50 m swimming, and pull-ups. Statistical analysis used: Student's t-test was used to examine differences between normal weight and overweight cadets, while a one-way analysis of variance (ANOVA) examined differences between BMI quartiles with regard to physical fitness. Results: BMI was directly related to running (r = 0.30, P < 0.001) and inversely related to pull-ups (r = −0.22, P = 0.002), while there was no significant correlation between BMI and swimming time (r = −0.05, P = 0.517). The comparison between normal weight and overweight (n = 54, 27.6%) participants revealed differences with regard to running (t192= −2.86, P = 0.005) and pull-ups (t194 = 2.41, P = 0.017), but not in swimming (t193 = 0.52, P = 0.605). One-way ANOVA revealed also differences between BMI quartiles with regard to running (F3,190 = 3.91, P = 0.010) and pull-ups (F3,192 = 5.73, P = 0.001), but not for swimming (F3,191 = 0.74, P = 0.528). Conclusions: In summary, the correlation analysis revealed that the higher the BMI, the lower the performance in running and pull-ups. Normal weight performed better in these tests than overweight participants, but BMI did not influence performance in swimming. Our findings confirmed previous observations about the negative effect of overweight on physical fitness. However, since the best performances in running and in pull-ups were achieved by different BMI quartiles, we concluded that the optimal BMI depends on the physical fitness parameter that one is interested in.
العلاقة بين مؤشر كتلة الجسم مع الجرى لمسافة 1600، السباحة 50 مترا، ورياضة سحب وامتداد الاطراف العليا للجسم لدى الطلاب المنخرطون في الجيش
خلفية البحث: على الرغم من أن اللياقة البدنية لدي للطلاب الجيش هي موثقة جيدا، ولكن لم تجري أي دراسة للتحقق إذا كان مؤشر كتلة الجسم المثالية (BMI) له اى اثر غلى اللياقة البدنية لهؤلاء الطلاب.
الأهداف: كان الهدف من هذه الدراسة هو فحص العلاقة بين مؤشر كتلة الجسم واللياقة البدنية لطلاب الجيش.
الإعدادات والتصميم: دراسة مستعرضة.
المواد والطرق: تم فحص طلاب الجيش ذكر فى 196 فردا تتراوح أعمارهم بين 18-19 عاما وتم تسجيل الوزن والطول، ومن ثم حساب مؤشر كتلة الجسم، وأجريت لهم ثلاثة اختبارات: الجرى 1600 م على التوالي، 50 متر سباحة، ورياضة سحب وامتداد الاطراف العليا للجسم.
التحليل الإحصائي المستخدمة: تم استخدام اختبار t الطالب لدراسة الاختلافات بين الوزن الطبيعي والوزن الزائد ، في حين فحص وتحليل التباين الأحادي (ANOVA) الفرق بين مؤشر كتلة الجسم واللياقة البدنية.
النتائج: اتضح ان مؤشر كنلة الجسم له علاقة مباشرة مع رياضة الجرى (r = 0.30، P <0.001) وعلاقة عكسية مع رياضة سحب وامتداد الاطراف العليا للجسم (r = -0.22، P = 0.002)، في حين لم يك هناك ارتباطا كبيرا بين مؤشر كتلة الجسم والسباحة (r = -0.05، P = 0.517). وكشف اختار ANOVA فوارق بين الرياضات المختلفة.
الاستنتاجات: كشف تحليل الارتباطات أنه كلما ارتفع مؤشر كتلة الجسم، انخفض الأداء في رياضة الجرى ورياضة سحب وامتداد الاطراف العليا للجسم. وأن الوزن الطبيعي يصاحبه أداءا أفضل في هذه الاختبارات بالمقارنة مع زيادة الوزن، ولكن لم يؤثر على الأداء في السباحة. وأكدت النتائج التي توصلنا إليها الملاحظات السابقة حول الأثر السلبي لزيادة الوزن على اللياقة البدنية. وبما انه قد تحقق أفضل أداء في رياضة الجرى ورياضة سحب وامتداد الاطراف العليا للجسم فى مختلف مؤشرات كتلة الجسم ، استنتجنا أن مؤشر كتلة الجسم المثلى تعتمد على اللياقة.
Keywords: army cadets, body mass index, cardiorespiratory fitness, muscle endurance, pull-ups, running, swimming
|How to cite this article:|
Nikolaidis PT, Zisimatos D. Relationship of body mass index with 1,600 m running, 50 m swimming, and pull-ups performance in army cadets
. Saudi J Sports Med 2014;14:144-50
|How to cite this URL:|
Nikolaidis PT, Zisimatos D. Relationship of body mass index with 1,600 m running, 50 m swimming, and pull-ups performance in army cadets
. Saudi J Sports Med [serial online] 2014 [cited 2019 Dec 10];14:144-50. Available from: http://www.sjosm.org/text.asp?2014/14/2/144/142372
| Introduction|| |
The research on the determinants of army cadets' performance from a physiological perspective has focused on profiling physical fitness characteristics ,, and evaluating the effect of training programs on physical fitness. ,,, It is now well-established that cadets should possess certain physical and physiological characteristics in order to successfully function in a variety of conditions and environments. ,, To evaluate these characteristics in army academies, candidates are examined for physical fitness as a part of the procedure to enter to the academies and cadets undertake such tests as a part of the regular examination system (e.g. twice per year).
Hellenic Army Academy, like the other academies of the Greek military, has specific physical fitness tests with standards that must be met or exceeded to advance further one's studies. An issue specific to the military is not having enough physically capable personnel who are able to complete the demands of training. To evaluate their performance, cadets are regularly being tested for weight, swimming capacity, cardiorespiratory (1,600 m running), and muscular endurance (pull-ups). Maintaining an optimal level of physical fitness is important for performance and injury prevention. For instance, cardiorespiratory endurance and pull-ups have been shown to differentiate Canadian Special Operations Regiment applicants according to their performance,  while low cardiorespiratory and muscle endurance performance in male recruits  and low cardiorespiratory endurance in marine corps were injury risk factors. 
In addition to possess certain physical characteristics (a minimum of height is a prerequisite to enter to the army academies), cadets should also maintain their weight in a particular range. Thus, the achievement of an optimal weight is a main concern in cadets' daily life. Body mass index (BMI) is an easily-administered and inexpensive method to monitor weight status. Although it is commonly used in a health setting to classify humans as underweight, normal weight, overweight, and obese;  its application in physically active populations has been questioned, because it is associated with fat mass, as well as with fat free mass.  On the other hand, recent findings revealed nearly perfect correlation of BMI with fat mass, very large with body fat percentage, and low to moderate with lean mass in conscripts  and similar trends were observed in various sport populations (e.g. adolescent and adult male team handball players,  adolescent,  and adult male soccer players  and female volleyball players  ). Independently from the degree of its association with fat or fat-free mass, it still can evaluate athlete's body weight for a given stature, and thus, contribute to weight control. However, BMI is often overlooked in studies on military populations and there are many studies on these populations, which present data on stature and body weight, but not on BMI. ,,,,,,
While the importance of physical fitness for cadets is well-documented, no study has ever been conducted to investigate if there is an optimal BMI for physical fitness in army cadets. There is evidence from research conducted chiefly on young general populations that BMI is associated with reduced physical fitness ,,,, and the same has recently been shown on sport populations. ,,, The comparison between groups with different BMI in the abovementioned studies has revealed that the groups with lower or normal BMI perform better in physical fitness tests than overweight or obese. While such findings would be attributed to the association of BMI with fat mass, in the case of physically active populations, in which there is an increased fat-free mass, we would not expect the same association between BMI and physical fitness.
Investigating the correlations between BMI and physical fitness, and examining differences in physical fitness between groups varying for BMI in army cadets may contribute to better identify an optimal weight for each cadet, and thus, to tailor individualized training program to achieve this weight. Since physical fitness has many components (e.g. cardiorespiratory endurance, muscular endurance) it would be also interesting and have many practical implications to know whether BMI correlates with overall physical fitness or only with some components and the magnitude of these correlations. Therefore, the aim of this study was to examine the relationship of BMI with three measures of physical fitness (1600 m running, 50 m swimming and pull-ups) in army cadets.
| Materials and methods|| |
In this cross-sectional study, we used four approaches; first, we examined the correlation between BMI and physical fitness components; second, we compared physical fitness between two groups with different BMI (namely between those classified as normal weight and those as overweight); third, we compared physical fitness between quartiles of BMI; and fourth, we examined intraindividual differences in participants with similar BMI or physical fitness level. Testing procedures were performed during the academic year 2011-2012, in the end of the first semester, as part of the regular physical fitness examination of cadets, in four separate days within 2 weeks. The study protocol was performed in accordance with the ethical standards from the Declaration of Helsinki in 1975, and approved by the local Institutional Review Board. Male army cadets (n = 196, aged 18-19 year) [Table 1] were examined for weight and height, their BMI was calculated (day 1), and they performed three tests: 1,600 m running (day 2), 50 m swimming (day 3), and pull-ups (day 4). The exercise tests were conducted on weekdays between 4 and 6 pm for all participants on similar environmental conditions (temperature 16-20°C and humidity 60-76%). Each testing session was preceded by a standardized warm-up including 10 min running (swimming in day 3) and 10 min stretching exercises, which was not well-controlled in this study due to the high ratio between participants and test administrators.
|Table 1: Anthropometric characteristics and physical fitness of normal weight and overweight participants|
Click here to view
The 1,600 m running test was conducted on track-and-field court with plastic floor. Participants competed in groups of 20 and ran nonstop. They were permitted to walk if they were unable to run the entire distance. Time was recorded in the nearest 0.01 s. In pull-ups, each repetition was completed with strict form. Two test administrators participated in this examination; one administrator counted the maximal number of repetitions they completed and the other evaluated whether the technique was correct (up until chin being completely over the bar and down to full extension of elbows). Best score was 18 repetitions. The 50 m swimming was performed in an indoor pool in groups of ten. Time was recorded in the nearest 0.01 s.
Statistical analyses were performed using IBM Statistical Package for Social Sciences (SPSS) v. 20.0 (SPSS, Chicago, USA). Data were expressed as mean and standard deviations of the mean (SD). International cut-off points of BMI were employed to classify adult participants as normal weight (≤ 25 kg/m 2 ), overweight (25-30 kg/m 2 ), or obese (>30 kg/m 2 ).  Association between physical fitness, and BMI was examined using Pearson's product moment correlation coefficient (r). Magnitude of correlation coefficients were considered as trivial (r < 0.1), small (0.1 < r < 0.3), moderate (0.3 < r < 0.5), large (0.5 < r < 0.7), very large (0.7 < r < 0.9), and nearly perfect (r > 0.9) and perfect (r = 1).  Student independent t-test was employed to test differences in physical fitness between normal weight and overweight participants for each age group. A one-way analysis of variance (ANOVA) was used to compare BMI quartiles. Effect sizes (ES) for statistical differences were determined using the following criteria: ES ≤ 0.2, trivial; 0.2 < ES ≤ 0.6, small; 0.6 < ES ≤ 1.2, moderate; 1.2 < ES ≤ 2.0, large; and ES > 2.0, very large.  The level of significance was set at α =0.05. Z-scores were calculated for 1,600 m running, 50 m swimming, and pull-ups; and a physical fitness index (PFI) was calculated as the sum of the three physical fitness components' z-scores.
| Results|| |
BMI was directly related to running (r = 0.30, P < 0.001) and inversely related to pull-ups (r = −0.22, P = 0.002), while there was no significant correlation of BMI with swimming time (r = −0.05, P = 0.517) and PFI (r = 0.04, P = 0.630). The small to moderate correlation between BMI and running time indicated that the higher the BMI, the higher the time needed to cover the 1,600 m distance, and consequently the worst the performance in running, while the small and negative correlation between BMI and pull-ups suggested that the higher the BMI, the worst the performance in pull-ups.
The comparison between normal weight and overweight (n = 54, 27.6%) participants revealed differences with regard to running (t192= −2.86, P = 0.005; −10 (−17;−3) s, mean difference (95% confidence intervals); ES = −0.46) and pull-ups (t194 = 2.41, P = 0.017; +2.0 (0.4;3.7) repetitions; ES = 0.39), but not in swimming (t193 = 0.52, P = 0.605) and in PFI (t191= −0.08, P = 0.933). The effect size in both running and pull-ups was small. These findings suggested that normal weight participants had better performance in running and pull-ups than their overweight counterparts.
The first BMI quartile ranged from 17.59-21.94 kg/m 2 , the second 21.96-23.38 kg/m 2 , the third 23.48-25.39 kg/m 2 , and the fourth 25.40-29.93 kg/m 2 [Table 2]. One-way ANOVA revealed differences between BMI quartiles with regard to running (F3, 190 = 3.91, P = 0.010, η2 = 0.058) and pull-ups (F3,192 = 5.73, P = 0.001, η2 = 0.082), but not for swimming (F3,191 = 0.74, P = 0.528) and PFI (F3,189 = 0.61, P = 0.608). Considering the values of eta square, a small effect size was suggested in both the cases of running and pull-ups; 5.8% of running and 8.2% of pull-ups performance was explained by BMI quartiles. Bonferroni post-hoc test revealed better running performance in the first quartile than the forth quartile, and better pull-ups performance in the second quartile than in the third and fourth quartiles. While in the case of running the best performance was that of the first quartile (i.e., the quartile with the smaller BMI), in the case of pull-ups the second quartile had the best performance.
|Table 2: Anthropometric characteristics and physical fitness of participants according to BMI quartiles|
Click here to view
In addition, we examined intraindividual variability in physical fitness in six pairs of participants: Two participants with − 1, 0 and 1 z-score in BMI [Figure 1], and two with − 1, 0 and 1 z-score in PFI [Figure 2]. Compared with those with 0 and 1 z-scores of BMI, we observed higher values in the participants with − 1 z-score. In all cases, there was large interindividual and intraindividual variability of the scores, that is, one participant scored higher than the other in one test and lower in another, and each participant scored high in one test and low in another, respectively. Examining the three pairs with equal z-scores in PFI, we noticed that, first, there was large interindividual and intraindividual variability; and second, participants with equal PFI differed with regard to their BMI.
|Figure 1: Z-scores of 1,600 m running, pull-ups, 50 m swimming, and physical fi tness index (PFI) in two participants with −1 (a), 0 (b), and 1 z-score (c) of body mass index (BMI)|
Click here to view
|Figure 2: Z-scores of 1,600 m running, pull-ups, 50 m swimming, and body mass index (BMI) in two participants with -1 (a), 0 (b), and 1 z-score (c) of physical fi tness index (PFI)|
Click here to view
| Discussion|| |
In this study we investigated the relationship between BMI and physical fitness in army cadets, and particularly, whether there is an optimal BMI for physical fitness. The most important finding was that the best performance in different physical fitness components was related with different levels of BMI; the lowest BMI quartile achieved the best performance in cardiorespiratory endurance, while the second quartile scored the highest values in muscular endurance. In contrast, considering that there was neither a correlation between BMI and overall physical fitness nor difference between normal weight and overweight participants, and BMI quartiles; we did not find overall physical fitness to be associated with a particular level of BMI. These findings may have practical implications on cadets' physical preparation for the regular official assessment of their physical fitness level. For instance, a cadet that wants to improve the time in the 1,600 m running should be aware of the finding that success in this test correlates with smaller values of BMI. The low to moderate correlations of BMI with running and pull-ups, that is, the higher the BMI, the lower the performance in these tests, implied a negative relationship of BMI with cardiorespiratory and muscular endurance, respectively.
Our findings with regard to the comparison between normal weight and overweight participants came to terms with previous studies on general populations. ,,,, It should be highlighted that most of these studies were conducted in children and adolescents, and therefore, attention should be paid when comparing their findings with those of the present study due to the age-related differences with regard to body composition and physical fitness. Chen and colleagues  showed that normal weight male children and adolescents 6-18 years had superior performance in cardiorespiratory endurance and in muscle strength and muscle endurance than their overweight counterparts. In line with the aforementioned study, Mak and colleagues  also revealed higher values in cardiorespiratory endurance, muscle strength, and muscle endurance in normal weight than in overweight male adolescents 12-18 year. In a corresponding age group of male adolescents (13-18.5 year),  overweight participants achieved lower performances in most of the test that they were examined. The results of this study were also in agreement with those of Bovet and colleagues  in male adolescents 12-15 year and with those of Duvigneaud and colleagues.  Thus, the higher values of physical fitness, which had been previously noticed in normal weight compared to overweight children and adolescents, were also observed in our study.
The trend observed in this comparison between quartiles was in agreement with a study on four BMI groups (underweight, normal weight, overweight, and obese) of 7-11 year boys, in which the best performance in 1 mile running was achieved by the lighter group and in pull-ups by the second group, and the worst scores in both tests were recorded in the third and fourth (heaviest) group.  From a physiological point of view, this trend should be attributed to that, although 1,600 m running and pull-ups are both weight-bearing physical fitness tests, they tax different energy transfer systems (aerobic and anaerobic, respectively). In addition, since pull-ups test is a measure of muscular endurance, performance in this test relies more on fat-free mass more than 1,600 m running does, and thus, a minimum of mass is necessary to achieve high scores, which in turn might explain that the second BMI quartile had the best score in pull-ups. In contrast with the significant correlations of BMI with 1,600 m running and pull-ups performance, and the significant differences in these tests between groups with different BMI values, we did not find respective correlations and differences in the case of swimming performance. An explanation for this discrepancy might be that in swimming the body is supported by the water making it easier to move an extra load through the water and that, considering the variability of scores in 50 m swimming, there are different levels of expertise.
The mechanisms behind the abovementioned associations between BMI and physical fitness have not been yet clarified. Considering the nearly perfect correlation between BMI and fat mass,  an excess fat mass in overweight participants could explain these differences between groups with different BMI, because this fat mass is an extra load to be moved while performing 1,600 m running and pull-ups. Although the application of BMI in sport populations has been questioned,  it might have performance- and health-related implications in army cadets. In contrast with other military populations' BMI (e.g. Canadian Special Operations Regiment applicants 26.5 kg/m 2 ,  Finish conscripts 24.6 ± 4.7 kg/m 2  , Finish conscripts 23.9 ± 4.0 kg/m -2 ,  US Special Weapons and Tactics team 27.1 kg/m 2 ,  US soldiers 26.4 kg/m 2 ,  US Army Reserved Officers cadets 25.2 kg/m 2 ,  and Greek conscripts 24.7 ± 4.2 kg/m 2 ,  participants in this study had lower mean score; and considering the SD value, were more homogenous. Based on this value, the profile of Army cadets may be classified as normal weight, while a minority is overweight, but not obese. The smaller prevalence of overweigh/obesity in our sample with regard to conscripts of Greek army (38.9%)  or the general population of three Balkan countries (43.8%)  should be attributed to the absence of obese participants. Hence, we interpret the current findings to indicate that overweight/obesity affects army cadets in smaller extent compared to other military and general population.
In addition to examining correlations and differences between BMI groups, we also investigated intraindividual differences with regard to physical fitness. Finding the best performance in cardiorespiratory and muscular endurance in different BMI quartiles was an indication that large intraindividual variability in cadets exists, that is, there were cadets with above-average 1,600 m score and below-average pull-ups score, but overall similar scores. These results were confirmed by the analysis of intraindividual differences. These observations came to terms with findings of a recent study on intraindividual variability in female volleyball players. 
These findings addressed the need for individualized approach in physical fitness. Knowledge about the strength and weakness of each cadet can help develop optimal training programs. BMI, cardiorespiratory, and muscular endurance are subjected to changes depending on the applied program. For instance, a 4-month basic training program has been reported to decrease weight by 1.2% and BMI 1.3%, and improve maximal oxygen uptake by 10.2% and push-ups 58.4%.  Another study of 12-week basic training revealed amelioration in maximal oxygen uptake by 14.2, but increased weight and BMI by 1.3%. 
The cross-sectional design of this study constitutes a main limitation of its findings. Another choice of design would be to monitor participants for a long period and to examine the effect of a possible fluctuation of body mass on physical fitness. However, we chose the present study design because we considered that there would not be large changes in body mass sufficient to examine their effect on physical fitness. ,,, Another limitation of this study was the sample size, which did not allow comparing many BMI groups. Previous studies that compared more than two BMI groups , have mentioned that the relationship between BMI and most of physical fitness parameters follows an inverse "U" pattern rather than being linear. This can explain partially the small differences between normal weight and overweight groups, as well as the relatively small to moderate correlations between BMI and 1,600 m running and pull-ups. Since performance may vary according to the year of studies,  this should be taken into account when applying our findings to older classes of cadets.
In summary, we found that there was not a unique optimal BMI for overall physical fitness, but since the best performances in running and in pull-ups were achieved by different BMI quartiles, we concluded that the optimal BMI depends on the physical fitness parameter that one is interested in. The correlation analysis revealed that the higher the BMI, the lower the performance in running and pull-ups. Normal weight performed better in these tests than overweight participants, but BMI did not influence performance in swimming. Our findings confirmed previous observations about the negative effect of overweight on physical fitness.
| Acknowledgement|| |
We gratefully thank all cadets who participated in this study.
| References|| |
Carlson MJ, Jaenen SP. The development of a preselection physical fitness training program for Canadian Special Operations Regiment applicants. J Strength Cond Res 2012;Suppl 2:S2-14.
Cuddy JS, Slivka DR, Hailes WS, Ruby BC. Factors of trainability and predictability associated with military physical fitness test success. J Strength Cond Res 2011;25:3486-94.
Warr BJ, Alvar BA, Dodd DJ, Heumann KJ, Mitros MR, Keating CJ, et al
. How do they compare?: An assessment of predeployment fitness in the Arizona National Guard. J Strength Cond Res 2011;25:2955-62.
Hofstetter MC, Mader U, Wyss T. Effects of a 7-week outdoor circuit training program on Swiss Army recruits. J Strength Cond Res 2012;26:3418-25.
Yanovich R, Evans R, Israeli E, Constantini N, Sharvit N, Merkel D, et al
. Differences in physical fitness of male and female recruits in gender-integrated army basic training. Med Sci Sports Exerc 2008;40 (Suppl 11):S654-9.
Williams AG. Effects of basic training in the British Army on regular and reserve army personnel. J Strength Cond Res 2005;19:254-9.
Knapik J, Darakjy S, Scott SJ, Hauret KG, Canada S, Marin R, et al
. Evaluation of a standardized physical training program for basic combat training. J Strength Cond Res 2005;19:246-53.
Knapik JJ, Rieger W, Palkoska F, Van Camp S, Darakjy S. United States Army physical readiness training: Rationale and evaluation of the physical training doctrine. J Strength Cond Res 2009;23:1353-62.
Knapik JJ, Sharp MA, Canham-Chervak M, Hauret K, Patton JF, Jones BH. Risk factors for training-related injuries among men and women in basic combat training. Med Sci Sports Exerc 2001;33:946-54.
Lisman P, O'Connor FG, Deuster PA, Knapik JJ. Functional movement screen and aerobic fitness predict injuries in military training. Med Sci Sports Exerc 2013;45:636-43.
WHO. Physical status: The use and interpretation of anthropometry. Report of a WHO Expert Committee. World Health Organ Techn Rep Ser 1995;854:1-452.
Ode JJ, Pivarnik JM, Reeves MJ, Knous JL. Body mass index as a predictor of percent fat in college athletes and nonathletes. Med Sci Sports Exerc 2007;39:403-9.
Mattila VM, Tallroth K, Marttinen M, Pihlajamaki H. Physical fitness and performance. Body composition by DEXA and its association with physical fitness in 140 conscripts. Med Sci Sports Exerc 2007;39:2242-7.
Nikolaidis PT, Ingebrigtsen J. The effect of excess body mass on physical fitness in adolescent and adult male handball players. Indian J Physiol Pharmacol 2013;57:369-79.
Nikolaidis PT. Prevalence of overweight and association between body mass index, body fat percent and physical fitness in male soccer players aged 14-16 years. Sci Sports 2013;28:125-32.
Nikolaidis PT. Body mass index and body fat per cent are associated with decreased power output in soccer players. Cent Eur J Med 2012;7:783-9.
Nikolaidis PT. Body mass index and body fat percentage are associated with decreased physical fitness in adolescent and adult female volleyball players. J Res Med Sci 2013;18:22-6.
Harman EA, Gutekunst DJ, Frykman PN, Nindl BC, Alemany JA, Mello RP, et al
. Effects of two different eight-week training programs on military physical performance. J Strength Cond Res 2008;22:524-34.
Trank TV, Ryman DH, Minagawa RY, Trone DW, Shaffer RA. Running mileage, movement mileage, and fitness in male U.S. Navy recruits. Med Sci Sports Exerc 2001;33:1033-8.
Thomas DQ, Lumpp SA, Schreiber JA, Keith JA. Physical fitness profile of Army ROTC cadets. J Strength Cond Res 2004;18:904-7.
Piirainen JM, Salmi JA, Avela J, Linnamo V. Effect of body composition on the neuromuscular function of Finnish conscripts during an 8-week basic training period. J Strength Cond Res 2008;22:1916-25.
Maric L, Krsmanovic B, Mraovic T, Gogic A, Sente J, Smajic M. The effectiveness of physical education of the Military Academy cadets during a 4-year study. Vojnosanit Pregl 2013;70:16-20.
Artero EG, Espana-Romero V, Ortega FB, Jimenez-Pavon D, Ruiz JR, Vicente-Rodriguez G, et al
. Health-related fitness in adolescents: Underweight, and not only overweight, as an influencing factor. The AVENA study. Scand J Med Sci Sports 2010;20:418-27.
Bovet P, Auguste R, Burdette H. Strong inverse association between physical fitness and overweight in adolescents: A large school-based survey. Int J Behav Nutr Phys Activ 2007;4:24.
Chen LJ, Fox KR, Haase A, Wang JM. Obesity, fitness and health in Taiwanese children and adolescents. Eur J Clin Nutr 2006;60:1367-75.
Duvigneaud N, Matton L, Wijndaele K, Deriemaeker P, Lefevre J, Philippaerts R, et al
. Relationship of obesity with physical activity, aerobic fitness and muscle strength in Flemish adults. J Sports Med Phys Fitness 2008;48:201-10.
Mak KK, Ho SY, Lo WS, Thomas GN, McManus AM, Day JR, et al
. Health-related physical fitness and weight status in Hong Kong adolescents. BMC Public Health 2010;10:88.
Hopkins WG, Marshall SW, Batterham AM, Hanin J. Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc 2009;41:3-13.
Batterham AM, Hopkins WG. Making meaningful inferences about magnitudes. Int J Sports Physiol Perform 2006;1:50-7.
Esmaeilzadeh S, Ebadollahzadeh K. Physical fitness, physical activity and sedentary activities of 7 to 11 year old boys with different body mass indexes. Asian J Sports Med 2012;3:105-12.
Mikkola I, Jokelainen JJ, Timonen MJ, Harkonen PK, Saastamoinen E, Laakso MA, et al
. Physical activity and body composition changes during military service. Med Sci Sports Exerc 2009;41:1735-42.
Pryor RR, Colburn D, Crill MT, Hostler DP, Suyama J. Fitness characteristics of a suburban special weapons and tactics team. J Strength Cond Res 2012;26:752-7.
Sharp MA, Knapik JJ, Walker LA, Burrell L, Frykman PN, Darakjy SS, et al
. Physical fitness and body composition after a 9-month deployment to Afghanistan. Med Sci Sports Exerc 2008;40:1687-92.
Papadimitriou A, Fytanidis G, Papadimitriou DT, Priftis KN, Nicolaidou P, Fretzayas A. Prevalence of overweight and obesity in young Greek men. Obes Rev 2008;9:100-3.
Krassas GE, Kelestimur F, Micic D, Tzotzas T, Konstandinidis T, Bougoulia M, et al
. Self-reported prevalence of obesity among 20,329 adults from large territories of Greece, Serbia and Turkey. Hormones (Athens) 2003;2:49-54.
Nikolaidis PT, Ziv G, Arnon M, Lidor R. Physical characteristics and physiological attributes of female volleyball players: The need for individual data. J Strength Cond Res 2012;26:2547-57.
Santtila M, Hakkinen K, Nindl BC, Kyrolainen H. Cardiovascular and neuromuscular performance responses induced by 8 weeks of basic training followed by 8 weeks of specialized military training. J Strength Cond Res 2012;26:745-51.
[Figure 1], [Figure 2]
[Table 1], [Table 2]