Nutrition education programme changes food intake and baseball performance in high-school students

Abstract

Objective:

The aim of this study was to examine the effects of nutrition education programme using the Convenient, Attractive, Normative (CAN) framework to facilitate changes in mindset, attitudes and behaviours towards food among high-school male baseball players.

Design:

Quasi-experimental design.

Setting:

Two public high schools in Osaka, Japan.

Methods:

Students in two high schools (mean age ± SD, 16.6 ± .5 years) participated in the study. One school served as an intervention group (n = 28) and received the CAN nutrition education programme. The other school served as a control group (n = 22), and students within it did not receive the intervention. Students in the intervention group received three nutrition lecture sessions and face-to-face individual nutritional guidance over a 4 month intervention period. Before and after the intervention, all students were asked to record their food and beverage intake by taking food pictures, recording portion weights and sending these to the project dietitian. They were also asked to develop a dietary behaviour plan for meeting their goals. At the end of the intervention, they were asked about their experiences.

Results:

Students in the intervention improved their food intake, dietary balance and athletic performance. Bat swing speed was significantly faster following the intervention. Body weight increased without changing lean body mass in both groups.

Conclusion:

Results suggest that a CAN nutrition education programme may be effective in increasing motivation and promote dietary behaviour change among male adolescent athletes. Future interventions should examine these motivational processes and investigate the factors contributing to well-balanced meals.

Keywords

CAN framework dietary changes high-school baseball players nutrition education programme performance

Introduction

A well-balanced meal is considered essential for students’ physical and mental development (Alghadir et al., 2019) and improving athletes’ performance outcomes (Jenner et al., 2018). In high schools in Japan, students bring their lunch from home in the form of a home-made bento-box or purchase lunch at a cafeteria. Schools offer an important social environment for adolescents, and many actions have been taken to promote healthful behaviours, including the eating behaviours of adolescents (French and Stables, 2003; Sharma, 2006). School-based nutrition education programmes play an important role in promoting healthy eating (Zhou et al., 2016). Systematic reviews and meta-analyses show that school nutrition education programmes, particularly theory-based, multicomponent interventions, can have a significant impact on the nutrition of high school students (Langford et al., 2017; Murimi et al., 2017).

Other research studies have reported the effects of nutrition education on body growth, body composition and food selection among high school baseball (Ebi et al., 2006; Kojima et al., 2004) and soccer players (Patton-Lopez et al., 2018). Findings from these studies suggest that weight and lean body mass greatly impact strength and performance, which in turn are correlated with a team’s wins and losses. Patton-Lopez et al. (2018) reported that high school soccer players learned ‘eating for performance’ and significantly improved their dietary behaviours in a 2 year team-based nutrition education and life-skills intervention study. To achieve eating for performance, athletes must have appropriate nutrition in the form of a balanced diet and focus on not only athletic training but also life-skills such as daily healthy eating behaviours (Fujita, 2017; Patton-Lopez et al., 2018). In other words, having a well-balanced meal helps athletes develop a strong body that may exhibit maximum performance during matches and competitions, in addition to during regular daily training and time off from training.

The Knowledge–Attitude–Behaviour (KAB) model suggests that knowledge lays the foundations for subsequent attitudinal and behavioural change (Heshmat et al., 2015). Although a correlation between knowledge about nutrition and eating behaviour has been reported (Devlin et al., 2016; Heaney et al., 2011), athletes may have difficulty securing the calories and nutrients needed to match their training and sports needs (Bilsborough et al., 2016; Taguchi et al., 2020). In addition, it is not clear what kind of nutrition education programme leads to changes in awareness and attitudes towards daily diet among high school athletes. To investigate these issues, this study used the CAN framework to examine factors contributing to healthy food selection and consumption (Hanks et al., 2013; Wansink, 2013). The acronym CAN stands for Convenient (physically and cognitively), Attractive (comparatively and absolutely) and Normative (actual and perceived), and signals food types and volumes that are convenient and appealing to high school baseball players. The CAN framework for changing eating behaviour provides ‘a broad, action-based way’ to guide participants to select the healthier foods that are more convenient, more attractive or more normal (Wansink, 2015).

Among high school athletes, concepts of what is ‘convenient’, ‘attractive’ and ‘normal’ relate to the way foods are offered in school and at home. In this study, we developed a series of nutrition education tools (e.g. a baseball board scoring sheet, a goal-setting sheet, and a bento-box hands-on workshop) that could help guide students not only make healthier food choices, but also make their food more ‘convenient’, ‘attractive’ and ‘normal’ to eat. The goal was to reveal whether a nutrition education programme using the CAN framework improves the food intake and the performance of high school baseball players.

Methods

Participants

Participants were high school baseball players. Inclusion criteria were men, 15–16 years old, engaged (⩾ 5 h/week) in baseball practice and training and belonging to a high school baseball club. Exclusion criteria were participation in a high school sports club other than baseball, any acute infection or medications before inclusion or the presence of an injury (before inclusion) that might have affected participation in high school baseball practice and training.

The intervention group comprised 28 baseball players from Osaka Prefectural High School-I (Year 10 = 12 students and Year 11 = 16 students; mean ± SD, age, 16.6 ± .5 years; height, 171.0 ± 6.4 cm; weight, 60.9 ± 6.7 kg; body mass index [BMI], 20.8 ± 1.8). The control group consisted of 22 baseball players from Osaka Prefectural High School-II (Year 10 = 8 students and Year 11 = 14 students; mean ± SD, age, 16.6 ± .5 years; height, 169.0 ± 5.3 cm; weight, 60.5 ± 7.2 kg; BMI, 21.1 ± 2.2) (See Table 1). To calculate the sample size of this study, proxy data (Institute of Medicine, 2012; Ortega et al., 2008; Smith et al., 2014) and data from our previous unpublished studies were used. The calculation was based on a univariate repeated measures analysis of covariance using a 5% increase in muscular fitness and/or food intake. A final sample size of approximately 42 baseball players (with half participating in an intervention and half in control conditions) would yield 80% power to detect a significant difference (p ⩽ .05: one-tailed test in the expected direction). In order to increase statistical power, more baseball players (22 players in control, 28 players in intervention) were included. This sample size proved feasible and realistic based on our previous experience.

Table 1.

Change in body composition before and after intervention.

	Before intervention		After intervention
	IG	CG	IG	CG
Height (cm)	171.0 ± 6.4	169.0 ± 5.3	171.0 ± 6.0	169.7 ± 5.1
Weight (kg)	60.9 ± 6.7	60.5 ± 7.2	64.4 ± 7.4***	62.3 ± 7.1***
BMI (kg/m²)	20.8 ± 1.8	21.1 ± 2.2	21.8 ± 1.7***	21.2 ± 2.8
Body fat (%)	11.8 ± 4.1	13.5 ± 4.4	16.9 ± 3.5***	15.9 ± 4.6***
LBM (kg)	53.5 ± 5.1	51.9 ± 4.7	53.4 ± 5.5	52.1 ± 4.1

Mean ± standard deviation. IG: intervention group; n = 28. CG: control group; n = 22. LBM: Lean body mass. BMI: Body mass index. Independent t-test compares IG and CG in the same time period, no significant difference. Paired t-test compares values before and after the intervention within the same group.

***

p < .001.

Both the control and intervention schools conduct practice programmes to improve baseball skills (e.g. batting and fielding practices) during the competition season (March–November) and engage mainly in weight training during the off season (December–February). This study was conducted between August and December 2018. It was approved by the Osaka City University Ethics Review Committee (IRB#18–25). All participants provided written and oral informed consent to participate.

Study design and CAN nutrition education programme

Figure 1 details the educational programme based on a quasi-experimental design. Before the intervention programme started, the baseball players in two high schools were allocated to one of the following groups: intervention or control. Both schools are public high schools in different cities, but in the same prefecture, Osaka. In the intervention group, three nutrition education sessions (1 hour/session) and one individual face-to-face guidance session (15–20 minutes/student) were provided once a month for a 4 month period. The nutrition education sessions were designed by a team of health professionals. Each education session was delivered in a high school classroom by a team of registered dietitians. The 1 hour education sessions included lectures (Sessions 1 and 2) and a hands-on workshop (Session 3). Baseball players in the intervention group also received 15–20 minutes of individual nutritional guidance/counselling. None of the students had previously received athletes’ nutrition education classes nor talked to a dietitian about their meals and dietary habits. The students were not marked absent from a nutrition education session. However, the head coach, team managers and the presenting dietitians regularly monitored student attendance and communicated the importance of regular attendance to understand their daily healthy eating. Students in the intervention group were also asked to fill out the follow-up survey questionnaire at the end of the CAN nutrition programme. Body composition measurements, performance measurements and dietary assessments were made for all students in both intervention and control groups before and after the intervention. The control group did not receive any group or individual nutrition education sessions (See Figure 1).

Figure 1.

Nutrition education programme – study design.

To ensure compliance to the study among students in the intervention group, a registered dietitian provided them an individualised meal guideline sheet based on the Japanese nutrition balance guidelines (Hayabuchi et al., 2016) during the first session. The sheet contained information about their total energy and various nutrient needs together with a menu plan for improving performance outcomes. The sheet also included a list of food groups to ensure meals were balanced and described foods that should be avoided in their meals. In session 2, students in the intervention group had to report to dietitians their personal dietary goals and plans based on their individualised meal guideline sheet. To reinforce students’ efforts over a 4 month period, key self-management strategies (e.g. goal setting, peer support networks with teammates, self-monitoring and self-reinforcement) were used (Hongu et al., 2011).

We developed a nutrition education tool in the form of a baseball board scoring sheet (Figure 2) using the Japanese Food Guide Spinning Top (Ministry of Agriculture, Forestry and Fisheries, 2010). Using this, students could track the numbers of servings of each food group eaten during their daily meals. The baseball board scoring sheet helped not only make healthier choices cognitively more ‘convenient’ to make, but also more ‘convenient’ to consider or see when choosing a healthful diet (Wansink, 2015). In addition, students were asked to formulate their own rules regarding eating habits by setting personal goals for a 2 month period based on their current physical and performance and set behavioural goals in terms of dietary aspects. All students in the intervention group were asked to choose a healthful diet and to think of it as ‘normal to eat’ during the group and individual nutrition education sessions. By the end of the project, when healthier foods were placed on their plate, these same foods had become their norms and ‘normal to eat’ in terms of normative behaviour (Chandon and Wansink, 2002).

Figure 2.

Baseball board.

The third nutritional education session was designed so that each student would know the food volume (weight and calories) and contents (variety of foods) they should consume (Desbrow et al., 2014). In this session, participants worked together as a team (four students/team) in a hands-on learning setting. As displayed in Figure 3, students learned how to balance foods using a bento-box, which is a lunch box that is familiar and convenient to Japanese students (Nagasawa et al., 2016). Students were asked to create one bento-box per team (Figure 3).

Figure 3.

Bento box.

Anthropometric, energy expenditure and performance measurements

All baseline assessments and questionnaires were completed at the participating schools. Height (cm) was measured by using the stretch stature technique with a free-standing stadiometer (SECA 217, SECA Corp., Singapore), where students stood upright in bare feet with heels together, looking straight ahead (Marfell-Jones et al., 2006). A Dual Frequency Total Body Composition Analyzer DC-430A (TANITA Corp, Itabashi-Ku, Tokyo, Japan) was used to measure body composition. Performance measurement items were bat swing speed and base running speed (i.e. running time around all bases), which have been previously indicated to have a correlation with body composition (Herrmann et al., 2019). For the measurement of bat swing speed, a BSG-1 Basic (YUPITERU) speed gun was used. For the measurement of running time around all bases and base running speed (timing a player from home plate to first base), each school’s own stopwatches were used. A GPS Sports Monitor (Wristable GPS SF-810, EPSON) was used to measure energy expenditure. Measurements were taken over 2 days, one practice day and one rest (time off from training) day.

Dietary assessment

Dietary energy and nutrients were assessed over 3 days (two practice days and one day off from practice). Before and after the intervention, the students in both intervention and control groups were asked to choose 3 days (two practice days and one off-practice day) on which to record their food and beverage intake. All students were given instructions on how to record their typical days’ diet. Two practice days were or were not consecutive days, but these 2 days had to be within the same week. The students selected one off-practice day to do a food record, which was either on Saturday, Sunday or holiday, when they do not have baseball practice/training. After the intervention ended, again, all students were asked to record their food over 3 days. For the dietary assessment, the photography method was used (Mita and Tsudzuki, 2015; Sharp and Allman-Farinelli, 2014). Before the intervention started, the students received instructions on how to create 3 days of food records using a digital kitchen scale that each student can use and their smartphone to take meal pictures. Figure 4 shows the two steps of this dietary assessment photography method: (1) taking a picture and (2) sending pictures by email). The students also received the worksheet on which they could write the names of each meal, including the weight of ingredients, if the ingredients of the meal can be determined. The worksheet helped researchers to match/identify foods in food pictures that students took and analyse the nutrients. Students were asked to take photos of their meals placed on top of a place mat from overhead (Figure 4, (1) meal picture) and send them to the corresponding e-mail address for breakfast, lunch, dinner, and snacks. (Figure 4, (2) Moreover, they were asked to write down the weight of each food item before eating it and measure the weight of leftovers if there were any. (Figure 4, (1) – (2) before eating and (1) – (3) after eating) Thus, the researchers received photos and the worksheet from each student. Based on such information, the weight of food items was estimated by registered dietitians. EIYO-KUN (the Yoshimura, Shikoku University Nutrition Database, v.6.0) was used for the analysis on nutrient intake weight by each food group and daily dietary balance (calories, macronutrients and micronutrients).

Figure 4.

Dietary assessment photography method.

Questionnaire: follow-up survey

A brief questionnaire was used to evaluate students’ satisfaction with and perceptions of the CAN nutrition education. Students were asked what they liked or disliked about the programme. Here are the questions and answer key choices: (1) Numbers of sessions, (i) too many, (ii) good and (iii) too few; (2) Timing of the programme, that is, September to December, (i) good and (ii) better to start earlier (write a preferable timing of the programme); (3) Duration of the programme, that is, 60 minutes per session; (i) too long, (ii) good and (iii) too short; (4) Usefulness of advice, that is, impact of the programme – increased awareness or changing dietary behaviours, (i) it helped, (ii) I think it helped, (iii) I don’t think it helped and (iv) it did not help; and (5) Satisfaction with the programme – whether they would like to have another session in a future, (i) I would, (ii) I think I would, (iii) I don’t think I would and (iv) I wouldn’t. Finally, in an open-ended response, students were invited to write down what they remembered during the intervention, their feelings about the nutrition education sessions and any requests to the project team that they may have.

Statistical analysis

Athletes from both intervention and control groups were expected to increase body development and show the effects of training. Thus, an independent t-test was used to examine the effects on the body composition, performance and nutrient intake as well as the energy intake between the two groups in the same time period. The Wilcoxon signed rank test was used to compare nutrient intakes by energy-adjusted vitamin A, vitamin B₁, vitamin B₂, vitamin C and dietary fibre consumed before and after the intervention in the intervention group. Comparisons between the intervention and control groups were made using the Mann–Whitney U test to identify changes before and after the intervention in energy and nutrient intakes. SPSS 23.0 J for Windows was used for the analysis, setting the significance level at p < .05.

Results

Food intake and dietary balance

During practice days after the intervention, the intervention group significantly increased its intake of carbohydrates (395 vs 459 g, respectively), potassium (2579 vs 2997 mg) and vitamin C (74 vs 96 mg), and the lipid energy ratio (29 vs 26%E) significantly decreased (all P < .05, Table 2). There were no significant differences on time-off days (Table 3). In the comparison between the two groups, the intervention group had a significantly higher intake of potassium than the control group (2997 vs 2760 mg) on practice days. During time-off days, energy-adjusted potassium (942 vs 760 mg), calcium (177 vs 149 mg), vitamin A (197 vs 152 μg) and dietary fibre (6 vs 4 g) were significantly different between the groups. During practice days and time-off days after the intervention period, the control group significantly increased (P < .05) its total energy (practice days: 3217 vs 3624kcal, time-off days: 2736 vs 3849kcal) and carbohydrate intake (practice days: 459 vs 527 g, time-off days: 379 vs 560 g) compared to the intervention group.

Table 2.

Change in energy and nutrient intake before and after intervention (practice day).

	Before intervention		After intervention
	IG	CG	IG	CG
Energy (kcal)	2860 ± 816	2878 ± 554	3217 ± 598	3624 ± 723***,^†
Protein (g)	100.9 ± 30.7	99.3 ± 24.5	115.2 ± 26.4	120.1 ± 24.9***
Protein energy ratio (%E)	14.2 ± 1.8	13.9 ± 2.5	14.4 ± 1.8	13.4 ± 2.0
Lipid (g)	92.1 ± 35.3	84.3 ± 22.3	94.5 ± 22.1	105.2 ± 27.5***
Lipid energy ratio (%E)	28.6 ± 5.7	26.3 ± 5.8	26.3 ± 4.4*	26.1 ± 3.9
Carbohydrate (g)	395.0 ± 116.7	413.0 ± 99.2	458.5 ± 100.2*	526.6 ± 116.6***,^†
Carbohydrate energy ratio (%E)	55.6 ± 7.8	57.4 ± 7.8	57.1 ± 5.1	58.1 ± 4.9
Potassium (mg)	2579 ± 807	2334 ± 583	2997 ± 775*	2760 ± 779*,^††
Calcium (mg)	509 ± 195	437 ± 202	563 ± 182	541 ± 261*
Ferrum (mg)	8.2 ± 2.2	7.7 ± 1.7	9.0 ± 2.0	9.9 ± 2.1***
Vitamin A (μg)	500 ± 215	450 ± 182	602 ± 256	555 ± 285
Vitamin B1 (mg)	1.40 ± .50	1.34 ± .50	1.64 ± .54	1.68 ± .73
Vitamin B2 (mg)	1.42 ± .48	1.28 ± .35	1.54 ± .37	1.67 ± .59**
Vitamin C (mg)	74 ± 40	65 ± 27	96 ± 43*	84 ± 56
Dietary fibre (g)	12.4 ± 4.4	12.0 ± 3.0	14.4 ± 3.6	14.5 ± 4.9***

Mean ± standard deviation. IG: intervention group; n = 28. CG: control group; n = 22. Independent t-test compares IG and CG in the same time period. ^†p < .05, ^††p < .01.

Paired t-test compares values before and after the intervention within the same group.

p < .05, **p < .01, ***p < .001.

Table 3.

Change in energy and nutrient intake before and after intervention (time-off day).

	Before intervention		After intervention
	IG	CG	IG	CG
Energy (kcal)	2653 ± 728	2638 ± 491	2736 ± 796	3849 ± 892***,^†††
Protein (g)	87.8 ± 25.8	97.4 ± 23.5	98.9 ± 31.6	130.2 ± 32.2**,^††
Protein energy ratio (%E)	13.4 ± 2.4	15.0 ± 3.2	14.6 ± 2.8	13.8 ± 2.7***
Lipid (g)	83.4 ± 28.8	78.3 ± 22.1	85.0 ± 37.6	110.4 ± 32.9***,^†
Lipid energy ratio (%E)	28.2 ± 5.3	27.0 ± 6.9	27.5 ± 7.0	25.7 ± 5.1
Carbohydrate (g)	371.9 ± 110.8	368.5 ± 103.1	379.3 ± 112.9	559.7 ± 156.8***,^†††
Carbohydrate energy ratio (%E)	56.0 ± 5.7	55.4 ± 8.2	55.8 ± 7.4	58.0 ± 6.7***
Potassium (mg)	2240 ± 762	2285 ± 644	2773 ± 1159	2941 ± 685*
Calcium (mg)	392 ± 198	421 ± 205	543 ± 252	550 ± 331
Ferrum (mg)	7.4 ± 2.4	7.7 ± 2.1	8.1 ± 3.3	10.2 ± 2.6**,^†
Vitamin A (μg)	418 ± 154	458 ± 293	556 ± 329	582 ± 304
VitaminB1 (mg)	1.27 ± .60	1.26 ± .48	1.57 ± 1.00	1.97 ± .69**
VitaminB2 (mg)	1.42 ± .48	1.28 ± .35	1.54 ± .37	1.67 ± .59**,^†
VitaminC (mg)	79 ± 39	67 ± 36	78 ± 43	75 ± 32
Dietary fibre (g)	12.2 ± 4.8	11.4 ± 4.1	15.0 ± 5.3	15.5 ± 4.0**

Mean ± standard deviation. IG: intervention group; n = 28. CG: control group; n = 22. Independent t-test compares IG and CG in the same time period. ^†p < .05, ^††p < .01. ^†††p < .001.

Paired t-test compares values before and after the intervention within the same group.

p < .05, **p < .01, ***p < .001.

Table 2 shows total energy (kcal) and nutrient intakes on practice days, and Table 3 shows them on time-off days. Dietary intake by food groups showed that students in the intervention group increased the intake of grains (806 vs 935 g), green and yellow vegetables (87 vs 94 g) and fruits (42 vs 59 g) only on practice days. Milk and dairy intakes (161 vs 92 g; practice days; 176 vs 96 g; off-practice day) increased more in the intervention than the control group on both practice and time off from practice days.

Performance and body composition

One of the performance tests, bat swing speed (125 vs 127km/h, P < .05) improved significantly among Year 11 members of the intervention group (Table 4). However, no significant change in other performance tests was found before and after the intervention in any of the groups or years. There was a significant increase (P < .001) in body weight (intervention: 61 vs 64 kg, control: 61 vs 62 kg) after the intervention without significant changes in lean body mass in both the intervention and control groups (Table 1).

Table 4.

Change in performance of Year 10 and Year 11 before and after intervention.

	Year 10
	Before		After
	IG	CG	IG	CG
Base running speed (s)	4.15 ± .21	3.91 ± .26	4.34 ± .24*	4.04 ± .32
Running time around all bases (s)	15.77 ± 3.01	16.50 ± 01.22	16.80 ± .47	16.61 ± .89
Bat swing speed (km/h)	115.5 ± 6.9	125.3 ± 8.4^†	117.5 ± 8.2	117.3 ± 9.4
	Year 11
	Before		After
	IG	CG	IG	CG
Base running speed (s)	4.08 ± .21	3.84 ± .19^†	4.14 ± .37	3.94 ± .13**
Running time around all bases (s)	16.48 ± .47	16.25 ± .74	16.56 ± .40	16.61 ± .62
Bat swing speed (km/h)	124.7 ± 9.5	130.0 ± 7.6	127.4 ± 9.5*	122.1 ± 6.5**

Mean ± standard deviation. IG: intervention group; n = 16(11th) and 12(10th). CG: control group; n = 14(11^th) and n = 8(10^th).

Independent t-test compares IG and CG in the same time period. ^†p < .05.

Paired t-test compares values before and after the intervention within the same group. *p < .05 and **p < .01.

Follow-up survey

The survey completed following the nutrition education programme showed that 46% of the students in the intervention group said that their ‘mindset toward meals has changed’ and that they ‘learned that meals were related to body composition and performance’. Student comments on the experience-based learning session using the bento-box included the following: ‘I felt that my usual lunch has a large amount of meat’, ‘I felt that the amount I have to eat (grain) is large’, ‘I like a bento-box – it is easy to see the ratio of 2:1:1 (grain: meat: vegetables)’, ‘I eat a lot of meat’ and ‘I eat vegetables, but not enough’. One of students surprisingly said ‘(there are) many examples of vegetables (suitable) for a lunch box!’

Discussion

This study examined whether a nutrition education programme using the CAN framework given to high school baseball players was effective at changing the food intake and athletic performance of high school baseball players. The effects of nutrition education could be seen in the increase of the intake of vitamins and minerals after the intervention and greater understanding towards meal balance and intake that are necessary for baseball players.

An ideal/healthy weight gain is important for an athlete (Tarnopolsky et al., 1992). An ideal/healthy weight gain needs to be achieved gradually over several weeks to months. Young male athletes may gain up to .5 kg of lean mass per week. Rapid weight gain more than 1 kg per week results in increased body fat. Excess body fat can have a negative effect on health and athletic performance (Carl et al., 2017). According to a report by the Japan Sports Association, consuming sufficient carbohydrates, which is a source of energy, and having a high stock volume of muscle glycogens inhibits the breakdown of protein cells during exercise. Increasing energy intake has been reported to be significantly more important for increasing lean body mass than increasing protein intake (Mountjoy et al., 2014). In this study, students’ energy intake increased, with the total protein intake per day being an appropriate amount of 1.4–1.7 g/kg of body weight. Other previous work has suggested that in terms of performance, strike force improves as BMI increases (Hull et al., 2017). In this study, the body weight of the intervention group significantly increased and showed a significant improvement in the bat swing speed of the Year 11 students. Although the weight of the control group also increased (+ 1.8 kg), because the increment of the intervention group was larger (+ 3.5 kg), it is believed that increased weight above a certain level impacted the striking force improvement.

This study’s nutrition education programme based on the CAN framework enabled difficult behaviour changes (e.g. an increased intake of fruits and vegetables), thus increasing the intake of vitamins and minerals. The intervention group on practice days improved their vitamin and mineral intakes (i.e. potassium and vitamin C). The survey taken by the students in the intervention group indicated that a nutrition education programme comprising individual activities and group hands-on experiences could be effective in changing students’ dietary behaviour and motivations after 4 month intervention. In this study, over half of the athletes worked towards achieving the goals of ‘drinking milk every day’ and ‘eating fruits’ as part of their behaviour goals.

Study limitations and future prospects

Asking intervention participants to record and report food intake prior to, or after, an intervention may have both positive and negative effects on dietary behaviour change, biasing intervention outcomes. In this study, students in both groups were asked to make food records prior to and after an intervention period. There were significant dietary behaviour changes in students in both groups. The reason for the dietary behaviour change in the control group cannot be explained. However, participating in a nutrition education intervention for the first time in their life may have influenced participants’ dietary behaviour.

This study employed a 4 month, short-term intervention with no follow-up to see if behavioural changes were maintained after the programme finished. In addition, despite the use of the CAN framework, it cannot definitely be concluded that it was the use of this framework that resulted in the observed changes. The results of the follow-up survey, however, suggested that the CAN approach for nutrition education was well accepted by the young male athletes. Future work should seek to (1) identify influences and characteristics of young male athletes that may be helpful in advancing the CAN approach, 2) engage student athletes to better understand the factors influencing young baseball players’ nutrition perspectives, 3) develop appropriate assessment tools, 4) pilot an intervention to improve strength and improved performance levels and 5) evaluate lasting behaviour change.

Conclusion

A nutrition education programme emphasising taking action to accomplish goals as a normative rule was administered to high school baseball players. Post-intervention changes were observed in energy and nutrient assessment and questionnaire results, indicating the nutrition education programme promoted positive behaviour changes among high school athletes.

Footnotes

Acknowledgements

We thank high school students for their participation and Takeshi Yoshimura and Daisuke Tatsu for their assistance with this project. We would like to thank Craig Farnham, Benjamin Pope, and Trudy Morrow for reading and providing feedback on the manuscript.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Yukiko Ueda

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