International Journal of Sport Nutrition and Exercise Metabolism, 2014, 24, 516  -523 http://dx.doi.org/10.1123/ijsnem.2013-0186 © 2014 Human Kinetics, Inc.

www.IJSNEM-Journal.com ORIGINAL RESEARCH

Adequacy of Nutrient Intakes in Elite Junior Basketball Players Marina Nikic´ and Saša Jakovljevic´ University of Belgrade

Željko Pedišic´ and Danielle Venus Karl-Franzens University of Graz

Zvonimir Šatalic´ University of Zagreb Purpose: The aim of this study was to assess the nutrient intakes of elite junior basketball players in comparison with nonathletes. Methods: A previously designed food frequency questionnaire was undertaken by 57 male elite junior basketball players 15 to 16 years of age and 53 nonathlete peers. Results: Mean estimated energy intake was more than 700 kcal higher in basketball players than in the nonathletes (p = .002). In both groups estimated energy intake was ~14% from protein, 38% from fat, and ~48% from carbohydrates. For the basketball players, estimated protein intake was below 1.4 g/kg in 32% of the group and above 1.7 g/ kg in 51%, while carbohydrate intake was below 6 g/kg in 56%. Percentages of participants who apparently failed to meet the estimated average requirement for micronutrients were higher in the nonathlete group. The nutrients most likely to fail to meet the recommendations for nutrient density were vitamin A (~70%), zinc (49% in basketball players and 30% in nonathletes), niacin and calcium (~30% for both micronutrients in both groups). Conclusion: Within the limitations of the survey methodology, elite junior basketball players appear to consume higher absolute energy, macronutrient and micronutrient intakes than nonathletes, but the contribution of macronutrients to daily energy intake and the nutrient density of food choices was similar for both groups. Elite junior basketball players might benefit from nutrition education targeting carbohydrate and protein intake. Dietary modifications that increase intakes of vitamin A, zinc, calcium and niacin in the diets of both groups might also be of value. Keywords: adolescent, sports, FFQ, diet, nutrition assessment Previous studies of the dietary practices of male basketball players have found self-reported daily energy intakes in the range of 3560 to 5570 kcal (Holway & Spriet, 2011). Meanwhile, the daily energy needs of tall (> 195 cm) male basketball players have been estimated at > 5000 kcal (Martinchik et al., 2003), with a recently conducted study of elite male junior basketball players (16 to 17 years) using a doubly labeled water method reporting a mean daily energy expenditure of 4626 kcal (Silva et al., 2013). Nikić and Jakovljević are with the Faculty of Sports Education, University of Belgrade, Belgrade, Serbia. Pedišić is with the Faculty of Kinesiology, University of Zagreb, Zagreb, Croatia. Venus is with the Institute of Sport Science, Karl-Franzens University of Graz, Graz, Austria. Šatalić is with the Faculty of Food Technology and Biotechnology, University of Zagreb, Zagreb, Croatia. Address author correspondence to Zvonimir Šatalić at [email protected]. 516

Although it can be assumed that increased energy needs are accompanied by increased food and nutrient intake, athletes can inadvertently fail to compensate for increased energy expenditure, compromising overall diet quality (Loucks et al., 2011). Many of the simplified energy and nutrient intake recommendations for athletes do not take into account their variability in training loads and growth patterns. The ability of young team sport players to achieve good nutritional practices is poorly addressed from several angles. First, the literature on dietary habits of team sport athletes is less developed than that of individual sport athletes (Mujika & Burke, 2010). In addition, there is a lack of specific inquiry into the nutrient requirements of young elite athletes, with recommendations typically being based on adult values (Petrie et al., 2004). Adolescents often follow dietary practices based on foods that are energy dense but low in essential nutrients (Diethelm et al., 2012). Poor food choices leading to inadequate micronutrient intake can also be observed

Nutrient Intakes in Junior Basketball Players   517

among young athletes (Hassapidou et al., 2002; Heaney et al., 2010; Gacek, 2007). Conversely, some studies show better dietary habits and nutrient intakes among adolescent athletes than their nonathlete peers (Cavadini et al., 2000; Croll et al., 2006; Cupisti et al., 2002). To address the lack of information on this topic, the aim of this study was to assess diet quality and nutrient adequacy in elite junior basketball players in comparison with that of their nonathlete peers.

Methods Participants The present cohort consisted of 57 male elite junior basketball players (15.6 ± 0.9 years) and 53 nonathlete peers (15.7 ± 0.5 years; mean ± standard deviation). An estimation of statistical power was undertaken based on an alpha error of < 0.05 and an expected medium effect size according to Cohen (1988; Cohen’s d = 0.60). The sample was calculated to be large enough to achieve a statistical power greater than 0.85 when analyzing differences between the basketball players and nonathletes using t test. The basketball players were members of top Serbian teams, including 10 players from the national team. Nonathlete peers with no history of participation in competitive sports were recruited from a public school. The basketball player participants were active in training for at least 5 years, and undertook an average of 8 ± 2 training sessions/week with an average duration of 111 ± 14 minutes per session. The study procedure was approved by the Institutional Review Board at the Faculty of Sport and Physical Education, University of Belgrade and since, all participants were underage, prior formal consent was given by their parents/guardians.

Dietary Assessment Nutrient intakes were estimated using a previously developed self-administered food frequency questionnaire (FFQ) designed for its use among young athletes (Pedišić et al., 2008; Sorić et al., 2008). Participants were asked to report their estimated intake of a variety of foods and drinks according to daily, weekly or monthly consumption frequency with a reference period of the previous month. Beverage intake was estimated by 11 questions; cereals and cereal products by 8; nuts, fruit, vegetables and related products by 10; milk and dairy products by 6; eggs and related products by 2; meat, fish and related products by 12; confectionery by 4 and sweeteners by 3 questions. Data were converted to estimated average daily nutrient intakes using the Croatian food composition tables (Kaić-Rak & Antonić, 1990). The FFQ also asks about the use of dietary supplements (products providing macronutrients, micronutrients, plant extracts, etc.) by two questions and creatine by one question, but these data were not included in the calculation, since the aim of the study was only to evaluate self-reported intakes from food only. Moreover, participants often provided vague

descriptions of used dietary supplements (for example, no product name or serving size), which impeded estimation of associated energy and nutrient intakes. Estimating selfreported nutrient intakes solely based on food consumption has been practiced in previous studies (Croll et al., 2006; de Lauzon et al., 2004). Exclusion of supplement use is considered a limitation (Lukaski, 2004) and must be taken into account when interpreting our results, as it potentially lowered total energy and nutrient intakes. Reliability and validity of FFQs are only low to moderate (Cade et al., 2004). Due to FFQs’ inability to measure true or accurate energy and nutrient intakes of our subjects (Pedišić et al., 2008), for the remainder of this paper they are referred to as estimated, apparent, or self-reported intakes. Estimated nutrient intakes were not compared with national reference intakes, but with widely used Dietary Reference Intakes, (DRI) which are broader in scope and application (Food and Nutrition Board, Institute of Medicine, 1997, 1998, 2000a, 2001). The Estimated Average Requirement (EAR) cut-point method was used to assess adequacy of micronutrient intake by counting the number of participants that had an estimated intake below the EAR (Food and Nutrition Board, Institute of Medicine, 2000b). The recently published and revised DRI, unlike the DRI from 1997, defined the EAR for calcium and enabled the use of EAR cut-point method for calcium (Food and Nutrition Board, Institute of Medicine, 2011). Adequacy of micronutrient intake was also assessed based on the principle of nutrient density. For this purpose, estimated micronutrient intakes were expressed per energy unit (1000 kcal) and evaluated against cut-off values derived from the DRI (Lee & Nieman, 2003).

Data Analysis Data analysis was performed using STATISTICA, version 8.0 (StatSoft, Inc., Tulsa, OK, USA). Quantitative data were presented as mean ± standard deviation and categorical data as percentages. To allow for generalization the 95% confidence intervals were calculated for means and percentages. Differences between basketball players and nonathletes in estimated nutrient intakes were analyzed using t test (for continuous variables) and the two proportion z-test (for categorical data). Cohen’s d values were calculated to determine relative effect size of the differences between groups in continuous variables. For all analyses the level of statistical significance was set at p < .05.

Results In total, 57 elite junior basketball players and 53 nonathlete peers participated in the study. There was no significant difference between the groups according to age (p = .633) or body mass index (p = .939; Table 1). Estimated energy intake was >700 kcal/d higher in the basketball players than in the nonathletes (p = .002, medium effect size; Table 2). In addition, a significant difference was found between the groups regarding

518  Nikic et al.

Table 1  Subjects’ Characteristics x– ± s / %a

Variable/Category

Basketball players

Nonathletes

Age (yr)

15.6 ± 0.9

15.7 ± 0.5

Body height (cm)

190.8 ± 7.9

184.1 ± 7.5

Body weight (kg)

78.0 ± 10.7

72.4 ± 12.2

Body mass index (kg/m2)b

21.3 ± 1.8

21.4 ± 3.5

< 18.5

4

6

18.5–25

93

89

25–30

4

2

> 30

0

4

aMean

± standard deviation are presented for quantitative variables and percentages for body mass index categories bBody mass index calculated according to self-reported height and weight

Table 2  Estimated Energy, Macronutrient and Water Intake in Elite Junior Basketball Players and Their Nonathlete Peers x– ± sa (95% CI)b Variable

Basketball players

Nonathletes

Cohen’s d

pc

Ed (kcal)

3962 ± 1376 (3597–4327)

3229 ± 1053 (2939–3520)

0.60

.002

E (kcal/kg)

51.1 ± 16.5 (46.7–55.5)

45.2 ± 14.8 (41.1–49.3)

0.38

.052

Protein (g)

140.0 ± 58.2 (124.6–155.4)

117.9 ± 39.3 (107.0–128.7)

0.45

.022

Protein (g/kg)

1.8 ± 0.7 (1.6–2.0)

1.7 ± 0.6 (1.5–1.8)

0.24

.207

Fat (g)

165.6 ± 64.4 (148.5–182.7)

140.7 ± 60.2 (124.1–157.3)

0.40

.039

Carbohydrate (g)

487.8 ± 171.8 (442.2–533.3)

375.9 ± 123.1 (342.0–409.9)

0.75

< .001

6.3 ± 2.1 (5.7–6.8)

5.3 ± 1.7 (4.8–5.7)

0.54

.006

38.3 ± 13.6 (34.7–41.9)

29.9 ± 12.0 (26.6–33.2)

0.66

< .001

Alcohol (g)

(0.4–0.8)

(0.6–1.7)

n/a

.002

Alcohol (% E)

(0.1–0.2)

(0.2–0.5)

n/a

< .001

4479.8 ± 1513.7 (4078.2–4881.5)

3462.9 ± 1102.8 (3158.9–3766.9)

0.77

< .001

1.2 ± 0.3 (1.1–1.3)

1.1 ± 0.4 (1.0–1.2)

0.12

.533

Carbohydrate (g/kg) Dietary fiber (g)

Water (g) Water (g/kcal) aMean

± standard deviation confidence interval for mean cp-value according to t test dTotal energy intake b95%

apparent carbohydrate intake relative to body weight (on average 1 g/kg/d higher intake for the basketball players, p = .006, standard effect size), but not for apparent energy and protein intake. Estimates of daily protein and carbohydrate intakes indicated that a significant number of basketball players in the cohort failed to meet dietary recommendations (American Dietetic Association et al., 2009). Specifically, the estimated protein intake was below 1.4 g/kg/d in 32% (95% CI, 20 to 44%), between 1.4 and 1.7 g/kg/d (recommended values) in 18% (95%

CI, 8 to 27%) and above 1.7 g/kg/d in 51% (95% CI, 38 to 64%) of the basketball players. Estimated carbohydrate intake was < 6 g/kg/d in 56% (95% CI, 43 to 69%) of the basketball players. In both cohorts apparent food practices provided ~14% energy from protein, ~38% from fat, and ~48% from carbohydrates. Over two thirds of the basketball players and their nonathletic peers apparently consumed > 35% of energy from fat (67% of basketball players and 68% of nonathletes, p = .888). The daily water intake was estimated at about 1 L/d higher in the basket-

Nutrient Intakes in Junior Basketball Players   519

ball players than among the nonathletes. However, it was almost equal when expressed relatively to the estimated energy intake (1.2 g/kcal/d in the basketball players vs. 1.1 g/kcal/d in the nonathletes, p = .533). The self-reported intakes of all assessed vitamins and minerals, excluding zinc, were significantly increased for basketball players (Table 3). The apparent dietary practices followed by basketball players provided nutrient intakes that are above EAR, for most of the vitamins and minerals. Estimated intakes of niacin, calcium and magnesium fell below EAR in only 2% and estimated vitamin A intake fell below EAR in 5% of the basketball players. Overall, percentages of participants with self-reported intakes below the EAR were higher for the nonathlete group. Among nonathletes, the highest percentages of participants with estimated intakes lower than EAR were found for vitamin A (25%), calcium and magnesium (15% for both minerals). No significant differences were

found between groups concerning the estimated nutrient density (Table 4). The estimated nutrient density below the recommended values was found for vitamin A (~70% of participants in both groups), zinc (49% in basketball players and 30% in nonathletes), niacin and calcium (~30% for both micronutrients in both groups).

Discussion Estimated absolute energy intake was on average 20% higher in basketball players than in nonathletes. The difference between groups was not significant when the estimated energy intake was expressed relative to body weight (51 vs. 45 kcal/kg/d, p = .052). Similar relative energy intakes were observed in US football players (15 to 18 years) and elite Spanish basketball players (mean age 25.1 years; 48 and 47 kcal/kg/d, respectively; Petrie et al., 2004, Schroder et al., 2004).

Table 3  Adequacy of Estimated Vitamin and Mineral Intake in Elite Junior Basketball Players and Their Nonathlete Peers x– ± sa (95% CI)b

% below EAR (95% CI)d

EAR

Basketball players

Nonathletes

Cohen’s d

pc

Basketball players

Nonathletes

pe

630 μg

1278.3 ± 506.1 (1144.0–1412.6)

1024.0 ± 447.3 (900.7– 1147.3)

0.54

.006

5 (0–11)

25 (13–36)

.004

Thiamine (mg)

1 mg

2.5 ± 0.9 (2.3–2.8)

2.1 ± 0.7 (1.9–2.2)

0.60

.002

0 (0–0)

4 (0–9)

.139

Riboflavin (mg)

1.1 mg

3.6 ± 1.5 (3.2–4.0)

3.0 ± 1.1 (2.7–3.3)

0.49

.012

0 (0–0)

0 (0–0)

1.000

Nutrient Vitamin A (µg)

Niacin (mg)

12 mg

0.45

.022

2 (0–5)

11 (3–20)

.040

Vitamin B6 (mg)

1.1 mg

7.3 ± 2.8 (6.5–8.0)

6.2 ± 2.5 (5.5–6.9)

0.40

.041

0 (0–0)

0 (0–0)

1.000

Vitamin C (mg)

63 mg

343.8 ± 173.2 (297.8–389.7)

251.2 ± 132.8 (214.6– 287.8)

0.60

.002

0 (0–0)

4 (0–9)

.139

Calcium (mg)

1100 mg

2160.7 ± 936.9 (1912.1–2409.3)

1824.0 ± 765.1 (1613.1–2034.9)

0.40

.042

2 (0–5)

15 (6–25)

.011

Magnesium (mg)

340 mg

643.2 ± 205.4 (588.7–697.7)

509.0 ± 149.7 (467.7– 550.3)

0.75

< .001

2 (0–5)

15 (6–25)

.011

Phosphorus (mg)

1055 mg

2700.3 ± 1078.5 (2414.1–2986.4)

2291.1 ± 748.7 (2084.8–2497.5)

0.44

.024

0 (0–0)

2 (0–6)

.298

Iron (mg)

7.7 mg

24.4 ± 9.0 (22.0–26.8)

19.7 ± 6.7 (17.8–21.5)

0.60

.002

0 (0–0)

0 (0–0)

1.000

Zinc (mg)

8.5 mg

20.6 ± 9.5 (18.0–23.1)

18.0 ± 7.7 (15.9–20.1)

0.30

.122

0 (0–0)

4 (0–9)

.139

Copper (µg)

685 µg

3112.0 ± 1336.1 (2757.4–3466.5)

2625.2 ± 1169.6 (2302.8–2947.6)

0.39

.045

0 (0–0)

0 (0–0)

1.000

Sodium (mg)

n/a

6512.1 ± 2025.6 (5974.7–7049.6)

5213.8 ± 1899.6 (4690.2–5737.4)

0.67

< .001

n/a

n/a

n/a

Potassium (mg)

n/a

6893.3 ± 2681.2 (6181.9–7604.7)

5259.7 ± 1768.3 (4772.3–5747.1)

0.72

< .001

n/a

n/a

n/a

aMean

25.1 ± 10.9 (22.2–28.0) 20.7 ± 9.0 (18.2–23.1)

± standard deviation confidence interval for mean cp-value according to t test dPercent of participants not meeting the Estimated Average Requirement (EAR) and its 95% confidence interval ep-value according to the two-proportion z-test b95%

520  Nikic et al.

Table 4  Estimated Nutrient Density of the Diet of Elite Junior Basketball Players and Their Nonathlete Peers

Nutrient

Nutrient recommendation per 1000 kcal

% below recommendation (95% CI)d

x– ± sa (95% CI)b Basketball players

Nonathletes

328.3 ± 89.8 (304.5–352.2)

319.0 ± 90.2 (294.1–343.9)

Cohen’s d

pc

Basketball players

Nonathletes

pe

0.10

.588

70 (58–82)

70 (58–82)

.967

Vitamin A (μg/1000 kcal)

360 μg/1000 kcal

Thiamine (mg/1000 kcal)

0.4 mg/1000 kcal

0.6 ± 0.1 (0.6–0.7) 0.6 ± 0.1 (0.6–0.7)

0.07

.724

0 (0–0)

0 (0–0)

1.000

Riboflavin (mg/1000 kcal)

0.5 mg/1000 kcal

0.9 ± 0.2 (0.9–1.0) 0.9 ± 0.2 (0.9–1.0)

0.07

.699

0 (0–0)

0 (0–0)

1.000

Niacin (mg/1000 kcal)

5.7 mg/1000 kcal

6.3 ± 1.2 (6.0–6.6) 6.4 ± 1.9 (5.9–6.9)

0.09

.657

28 (16–40)

34 (21–47)

.504

Vitamin B6 (mg/1000 kcal)

0.5 mg/1000 kcal

1.9 ± 0.4 (1.7–2.0) 1.9 ± 0.5 (1.8–2.1)

0.17

.379

0 (0–0)

0 (0–0)

1.000

Vitamin C (mg/1000 kcal)

27 mg/1000 kcal

86.7 ± 31.2 (78.4–94.9)

78.8 ± 36.3 (68.8–88.8)

0.24

.223

2 (0–5)

8 (0–15)

.145

Calcium (mg/1000 kcal)

460 mg/1000 kcal

551.7 ± 156.1 (510.2–593.1)

582.2 ± 203.7 (526.0–638.3)

0.17

.378

30 (18–42)

30 (18–43)

.967

Magnesium (mg/1000 kcal)

n/a

165.2 ± 25.3 (158.5–171.9)

162.2 ± 29.6 (154.0–170.3)

0.11

.564

n/a

n/a

n/a

Phosphorus (mg/1000 kcal)

450 mg/1000 kcal

681.2 ± 102.4 (654.0–708.4)

719.6 ± 128.5 (684.2–755.0)

0.33

.085

0 (0–0)

0 (0–0)

1.000

Iron (mg/1000 kcal)

4.5 mg/1000 kcal

6.2 ± 0.8 (6.0–6.4) 6.1 ± 1.0 (5.9–6.4)

0.02

.918

4 (0–8)

9 (2–17)

.203

Zinc (mg/1000 kcal)

5 mg/1000 kcal

5.2 ± 1.0 (4.9–5.4) 5.7 ± 1.9 (5.1–6.2)

0.35

.072

49 (36–62)

30 (18–43)

.043

Copper (μg/1000 kcal)

n/a

0.16

.418

n/a

n/a

n/a

787.1 ± 159.1 (744.9–829.3)

821.2 ± 271.0 (746.5–895.9)

aMean

± standard deviation confidence interval for mean cp-value according to t test dPercent of participants not meeting recommended nutrient density and its 95% confidence interval ep-value according to the two-proportion z-test b95%

The recommended protein intake for basketball players is approximately 1.4 to 1.7 g/kg/d (American Dietetic Association et al., 2009). Studies have shown that there is no rationale for protein intakes of above 2 g/kg/d (Tipton, 2011). Despite that, in the current study estimated protein intakes for the majority (60%) of basketball players were either below 1.4 or above 2 g/kg/d. Among nonathletes, the estimated protein intake was below the recommended value of 0.8 g/kg/d (Food and Nutrition Board, Institute of Medicine, 2002) in only two nonathletes, while it was above 2 g/kg in 25% of them. The difference in estimated protein intake (g/kg) between basketball players and nonathletes was not statistically significant. Our results indicate that more attention should be placed on planning and awareness of dietary protein consumption among basketball players.

Recommended protein intakes of 0.8 (Food and Nutrition Board, Institute of Medicine, 2002) and 1.4 to 1.7 g/kg (American Dietetic Association et al., 2009) for nonathletes and basketball players, respectively, represent thresholds for adults, which may not be suitable for adolescents. It was shown that positive nitrogen balance in male adolescents (both nonathletes and athletes) is achieved with protein intake of about 1.6 g/kg/d (Boisseau et al., 2002). Greater protein needs in adolescence are relative to growth and development. In addition, it has been suggested that the recommended protein intake for adults should be increased from 0.8 to 1.2 g/kg/d (Elango et al., 2010). Therefore, it might be that the estimated protein intakes of 1.8 and 1.7 g/kg/d among basketball players and nonathletes, respectively, were adequate. Previous studies have shown that the timing of protein

Nutrient Intakes in Junior Basketball Players   521

consumption also plays an important role in athletes’ diet (Phillips & van Loon, 2011). Unfortunately, the measure used in the current study does not allow for examination of this aspect of dietary habits for basketball players. Dietary guidelines for carbohydrate intake for athletes should be expressed relative to body weight instead of as a percentage of daily energy intake, since the latter approach may create impractical diets or insufficient carbohydrate intake. However, percentage of daily energy intake is a widely used guideline for the general population, with the aim of reducing the risk of chronic diseases (Burke et al., 2001; Food and Nutrition Board, Institute of Medicine, 2002). Basketball players should have a goal carbohydrate intake of >6 g/kg/d, ie, 8 to 12 g/kg/d during heavy training and competition (Burke et al., 2011). Teammates have varying carbohydrate needs depending on game time and eating strategies should be taken into account regarding each individual’s different nutritional goals (Maughan & Shirreffs, 2012). Estimated carbohydrate intake was below 6 g/kg/d for more than half of the basketball players in our sample, while nonathletes on average reported carbohydrate consumption within the recommended range of 45 to 65% of energy intake. It might be beneficial for basketball players to increase carbohydrate consumption through diet or alternatively with sport drinks, gels or bars, specifically during an intense basketball season, since maintaining energy input and output between games and during travels can be challenging (Ziv & Lidor, 2009). Increasing dietary fiber intake may be of value in both groups. 60% of basketball players and 76% of nonathletes, respectively, did not reach the recommended 38 g/d (Food and Nutrition Board, Institute of Medicine, 2002). Additional servings of fruit and vegetables would be beneficial for dietary fiber consumption and the overall diet quality. Micronutrient intakes below EAR do not necessarily indicate deficiency, however, since athletes may have nutrient requirements that are higher than for the general population, intakes below the EAR standards would theoretically be inadequate for approximately 50% of the athletes (Heaney et al., 2010). Only a small number of participants, specifically basketball players, had estimated micronutrient intakes below EAR. Nevertheless, estimates of nutrient density indicate that increased vitamin A, zinc, calcium and niacin intake might be beneficial among both groups. In previous studies, adolescent athletes consistently reported intakes of vitamin A and zinc that were lower than recommended (Lukaski, 2004).

Limitations This study was subject to several limitations. Firstly, the FFQ was used as a dietary assessment method. FFQs are often used to estimate absolute intakes however results should be cautiously evaluated since this method is primarily used for categorising intake, whereas 7-days food records is a preferred method for more precise estimates (Burke et al., 2003; Cade et al., 2004; Masson

et al., 2003). FFQs are subject to recall errors that can lead to overestimation at low and underestimation at high energy intakes (Burke et al., 2001; Magkos & Yannakoulia, 2003). It is possible that the FFQ in the current study underestimated energy and nutrient intakes, since the expected energy intake of both basketball players and nonathlete adolescents can be characterized as relatively high. Nevertheless, male team sports athletes are likely to be confident of their eating habits and body image and therefore an increased accuracy with the use of dietary assessment methods is expected (Burke et al., 2001; Sundgot-Borgen & Torstveit, 2004). Furthermore, our calculations did not include dietary supplement use, which may have also resulted in lower estimates of total energy and nutrient intakes. Taking the latter limitations into account, the reader should see the results of our study as estimated rather than true energy and nutrient intakes. In addition, there are several shortcomings associated with use of EAR method. Since EAR can underestimate nutrient requirements it is not always useful to identify individuals whose intakes are inadequate (Barr et al., 2002). However, it has been shown that EAR method is a valid standard for assessing nutrient inadequacy, less subject to overestimation and underestimation than other cut-points (de Lauzon et al., 2004). Limitations additionally include the assessment of the adequacy of estimated carbohydrate and protein intakes based on daily recommendations. A recent study emphasized the importance of meal-based protein quantities (Areta et al., 2013). Unfortunately, the protein intake throughout the day and in relation to training or games was not assessed. The current study also lacks data regarding the periodization of carbohydrate intake according to fuel requirements and goals of each of the specific days or phase of athletes’ program (Burke et al., 2011).

Conclusion Elite junior basketball players appear to have higher absolute energy, macronutrient and micronutrient intakes than nonathlete peers, but the contribution of macronutrients to daily energy intake and the nutrient density of food choices seems to be similar for both groups. Elite junior basketball players might benefit from nutrition education targeting carbohydrate and protein intake. Dietary modifications that increase intakes of vitamin A, zinc, calcium and niacin in the diets of both groups might also be of value.. Basketball is a team sport, but an individual approach is needed to adequately plan each athlete’s diet (Holway & Spriet, 2011). Acknowledgments The study was funded by the Faculty of Sport and Physical Education, University of Belgrade. The authors are very grateful to basketball clubs Crvena zvezda, FMP, Partizan, and Hemofarm, and to non-athlete participants. The authors declare no conflict of interest.

522  Nikic et al.

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