Importance of a balanced diet on the physical fitness level of schoolchildren aged 6–12

Importance of a balanced dieton the physical fitness level ofschoolchildren aged 6–12

Louisa Chung and Thomas WongHong Kong Polytechnic University, Hong Kong

Joanne Wai Yee ChungInstitute of Education, Hong Kong

AbstractPrevious studies have focused on a single nutrient’s relationship with disease and thus are unable tostrongly support the health claims of a balanced diet. This article explores the integrated effect ofnine nutrients on an individual’s physical fitness level. Two-day dietary records and physical fitnessassessments were collected in three primary schools. Cluster analysis allowed compliance withnutrient recommendations to be compared among groups of primary school students with differ-ent characteristics. Two clusters were identified statistically. Cluster B, which comprised moreschoolchildren at the ‘Good’ and ‘Pass’ levels and fewer at the ‘Excellent’ level, had significantlymore participants who met the guidelines for total fat, saturated fat, sodium and cholesterol, com-pared with Cluster A. This finding reveals the benefits of a balanced diet, with physical fitness levelas the outcome measure. The results also have implications for approaching health problems fromthe diet–fitness perspective rather than the obesity–disease perspective.

Keywordsassessment, child health, clinical guidelines, nutrition

Introduction

A balanced diet is a diet that meets all of an individual’s nutritional needs (with all nutrients in

the correct amounts and in proportion to one another) for bodily maintenance and the repair of

physiological processes, growth and development (U.S. National Library of Medicine and U.S.

Corresponding author:

Louisa Chung, Centre for Integrative Digital Health, School of Nursing, Hong Kong Polytechnic University, Hunghom,

Kowloon, Hong Kong

Email: [email protected]

Journal of Child Health Care000(00) 1–16

ª The Author(s) 2010Reprints and permission:

sagepub.co.uk/journalsPermissions.navDOI: 10.1177/1367493510374065

chc.sagepub.com

National Institutes of Health, 2006). The traditional approach is to concentrate on how individual

macro and micro-nutrients affect health (Anderson et al., 1994; Brown et al., 1999; Food and

Environmental Hygiene Department, 2007; Mahan and Escott-Stump, 2000; Packer and Fuchs,

1997; Wolk et al., 1999). Although an association between individual nutrients and health has

been reported, the importance of a balanced diet has rarely been investigated. The World Health

Organization and many dietetic associations advocate the importance of a balanced diet

(American Dietetic Association, see www.Eatright.org; see also Stein and Moritz, 2009;

U.S. Department of Agriculture, 2009), but no research has been published to prove the benefits

of such a diet.

In addition to eating habits, physical activity habits have been frequently used to explain the

emergence of childhood obesity. Key factors in overweight children and childhood obesity are

reported to include little physical activity and large amounts of television viewing, internet brows-

ing and multimedia entertainment (Lissner and Heitmann, 1995). Etelson et al. (2003) found that

many parents did not consider childhood obesity to be a serious problem, as they perceived their

children’s excess weight to be a temporary problem and unlikely to lead to adult obesity. This

reflects the inability of contemporary nutrition education to show the association between a

balanced diet and good health. Once children have grown up with health problems, it may be too

late for dietary modification. Based on an assessment of body size, cardiovascular and respiratory

function and muscle strength and flexibility, physical fitness level is one of the predictors of chil-

dren’s health problems, but has been seldom studied with nutrient profiles and the duration of

physical activity. There is well-documented evidence to demonstrate the relationship of certain

nutrients with disease, but little published work addresses the relationship between nutrients and

physical fitness (Levitsky, 2001; Lissner and Heitmann, 1995). A possible reason for this gap in

the research, as well as for the limitations of previous research, may be that diet and exercise are

not the only factors affecting an individual’s physical fitness level. Healthcare systems worldwide

are changing from a proactive to a preventive approach, which means that we need to take the

diet–fitness approach rather than the obesity–disease approach to health problems. The aim of the

study reported herein, which was motivated by the urge to support the promotion of a balanced

diet through an integrated approach, was to investigate the relationship between nine nutrients and

fitness characteristics in primary schoolchildren.

Conceptual framework

This study explores the interrelationships among nine common nutrients with duration of physical

activity and physical fitness level:

1. carbohydrate;

2. protein;

3. total fat;

4. saturated fat;

5. calcium;

6. dietary fiber;

7. vitamin C;

8. sodium; and

9. cholesterol.

2 Journal of Child Health Care 00(000)

Cluster analysis allowed the characteristics of primary schoolchildren in different clusters to be

explored. The findings of this study will provide an alternative perspective to the common

characteristics of nutrients and physical activity among primary schoolchildren with different

physical fitness levels.

The research set out to answer the following research question:

What are the demographic characteristics and nutrient profiles of primary schoolchildren with different

levels of physical fitness?

The hypothesis was that primary schoolchildren with both a balanced diet and a longer daily dura-

tion of physical activity will demonstrate higher levels of physical fitness than their counterparts

without them.

Method

Sample

All students from three primary schools in Hong Kong were invited to participate in the study. To

ensure their safety, any children with a history of cardiovascular or cardio-respiratory disease, or

who had had an operation or suffered trauma or injury, were excluded from taking part. Physical

fitness assessments were conducted in the primary schools between October 2005 and December

2006 by the study’s professionally qualified researchers. Demographic data, including two-day

food diaries and records of the daily amount of time spent on various activities, were collected

from the participating children’s parents or guardians.

Dietary intake assessment

Two-day dietary records, a commonly used instrument for dietary intake, were employed. Because

the primary schoolchildren recruited were not competent to self-report their daily dietary intake,

their caregivers – that is, their parents or carers – were the preferred proxy. A dietary record sheet

was given to all of the parents and carers with self-explanatory instructions on how to complete a

two-day food diary to record their children’s food consumption. They were asked to use the record

sheet provided to record their children’s food intake based on time, and were instructed to docu-

ment such details as all of the ingredients in each dish, either the weight of each ingredient in grams

(or if in a liquid state, the volume in milliliters) or the ingredient portion size, cooking method,

amount of oil used and the type of sauce added, if any. The food diaries were then collected and

the recorded food items were input into Nutritionist Pro version 2.5 (a nutrient analysis software

package). The Nutritionist Pro food database contains more than 12,000 brand-name foods and

8000 generic foods for nutrient analysis (Axxya Systems, 2009).

As mentioned previously, the nine nutrients were selected for data analysis. These were selected

because they are major nutrients of concern and they are always included in the nutrition labels on

packaged food. The average value of each of the nine nutrients for each student over the two days

was calculated using the aforementioned software. The average values of the nutrients were then

input into the Statistical Package for the Social Sciences (SPSS) version 13.0 for descriptive

statistical analysis. The consumption value of the nine nutrients for each child was then compared

to see whether their nutrient intake met the recommendations as set out in the 2005 Dietary Guide-

lines for Americans (U.S. Department of Health and Human Services and U.S. Department of

Chung et al 3

Agriculture, 2009), which are widely accepted globally. The intended nutrients for study were

blinded to the parents, carers and students so as to avoid bias in habitual dietary recording.

Physical fitness assessment

The physical fitness assessments for all of the participating students were scheduled for consecu-

tive Saturdays. The protocol of the China Education Bureau (China Education Bureau and China

Sports Bureau, 2004) was adopted in conducting the assessment of each participating student

(Table 1).

The measurements were:

� body height;

� body weight;

� sit-and-reach;

� 50-meter running;

� standing long-jump;

� lung capacity; and

� a step test (Table 2).

These parameters then allowed an assessment of body mass index (BMI; kg/m2), flexibility,

muscle strength and cardiovascular and respiratory endurance. All physical fitness parameters

were measured using electronic equipment specially designed to the meet the protocols (see

Shenzhen Goodfamily Enterprise Ltd, www.goodfamily.cc). This equipment was used to eliminate

subjective judgements and reduce errors during data collection. The physical fitness items tested

depended on the student’s level and year of study (Table 1). These items were assigned specific

weightings in advance and were subscored by matching age group and gender (China Education

Bureau and China Sports Bureau, 2004). Adding together the subscores, the total score for each

child was ranked in four categories: a total score equal to or below 59 was awarded a ‘Fail’ grade;

a total score in the range of 60–75 was a ‘Pass’; a total score between 76 and 85 was ‘Good’; and a

total score equal to or more than 86 was ‘Excellent’ (China Education Bureau and China Sports

Table 1. Physical fitness test items and corresponding weightings for students of different levels of study atprimary school

Primary 1 and 2(Age 6–7)



QuestionnaireDemographic

p p p

Test item WeightingBody height 60 40 15Body weightSit-and-reach 40 20Standing long-jump 30 3050-meter run 30Step test 20Lung capacity 15

Total Score 100 100 100


Table 2. Measurements of physical fitness parameters

Testing item Description Measurement Unit

Body height � A researcher pressed the ‘Start’ button on

the panel to measure body height.

� The student took off their shoes and

stepped on the platform.

� The student stood in front of the standing

scale and faced forward with their eye

level kept in the horizontal plane.

� A bar from the top of the scale was pushed

down until it reached the top of the stu-

dent’s head. A ‘Beep’ sound indicated that

the body height recording had taken place.

� A researcher pressed the ‘Confirm’ button

and keyed in the student’s identification

number (ID).

� Body height Meters

Body weight � A researcher pressed the ‘Start’ button on

the panel to measure body weight.

� The student took off their shoes and

stepped on the platform.

� A ‘Beep’ sound indicated that the equip-

ment had recorded the student’s body

weight.


and keyed in the student’s ID.

� Body weight Kilograms

Sit-and-reach � A researcher pressed the ‘Start’ button on

the panel to measure sit-and-reach.

� The student sat on the floor with legs

straight and feet touching the side of the

scale.

� The student held their fingers straight and

placed one hand on top of the other.

� By bending the body trunk with no bend-

ing of the knees, the student pushed the

sliding scale forward as far as possible.

� A ‘Beep’ sound indicated that the sliding

scale had stopped, and the equipment

recorded the distance from the starting

point to the stopping point.

� The student performed the assessment

twice, and the equipment recorded the

longest distance.


and input the student’s ID.

� Distance between the

starting point and

stopping point of the

sliding scale

Centimeters

(continued)

Chung et al 5

Table 2 (continued)


50-meterrunning

� At least two students ran along a 50-meter

straight and smooth running track.

� After a ‘Beep’ sound, the students started

running, and the researcher timed them

with a stopwatch.

� A researcher recorded the students’ IDs

and the corresponding time required to

complete the 50-meter run.

� Time spent running for

50-meter in a

straight direction

Seconds

Standinglong-jump

� A researcher pressed the ‘Start’ button of

the panel to measure the standing long

jump.

� The student stepped on Region 1 of the

electronic mat, which was the nearest

starting distance to the testing distance.

� The student jumped forward with two legs

leaving the electronic mat and reaching it

with them together.

� When the student reached the electronic

mat at the final region, a ‘Beep’ sound

indicated the equipment had recorded the

distance between Region 1 and the final

region.

� If the student reached beyond the elec-

tronic mat, they were asked to take the test

again by starting with Region 2 which was

the second longest starting point. If they

reached beyond the mat again, they were

asked to repeat the test by starting from

Region 3, which was the longest starting

point.

� The student repeated the assessment two

times, and the equipment recorded the

longest distance.



� Distance between the start-

ing point and final point of

the electronic mat

Centimeters

(continued)


Bureau, 2004). If a student failed to complete one or more of the assigned test items, then their total

score was categorized as ‘missing data’.

Statistical methods

Cluster analysis is a statistical classification method that groups a set of observations into mean-

ingful subsets. Observations in the same cluster share certain characteristics (Aldenderfer and

Blashfield, 1984). Segmentation of the study sample was performed via cluster analysis to reveal

distinct characteristics of the schoolchildren under study. Sixteen variables were used for analysis:

gender (male/female), level of study at primary school (Primary 1 and Primary 2; Primary 3 and

Primary 4; Primary 5 and Primary 6), average daily duration of physical activity (30 minutes or

Table 2 (continued)


Lungcapacity

� A researcher pressed the ‘Start’ button on

the panel to measure lung capacity.

� The student inhaled as deeply as possible

through the mouthpiece of the equipment,

and then exhaled slowly and continuously

until all of the inhaled air had been

exhaled.

� The mouthpiece sensor received the signal

and gave a ‘Beep’ sound.

� The student repeated the test, and the

equipment recorded the higher volume

from the two records.



� Exhaled air volume milliliters

Step test � A maximum of eight students took the

assessment at the same time, standing in

front of a 25 cm-high wooden block.

� A three minute-long piece of music was

played, and students followed the rhythm

of the music to step on the block with their

left leg first and then their right leg, fol-

lowed by the left leg down and the right

leg down.

� After 3minutes of stepping on and off the

block, each student’s 30-minute pulse was

counted in the intervals of ‘1minute to 1.5

minutes,’ ‘2 minutes to 2.5 minutes’ and ‘3

minutes to 3.5 minutes.’

� The step text index was calculated by

[180/(Sum of 3 counted pulse rates) � 2]

� 100.

� Pulse rate of three

30-minute intervals

Number ofpulses

Chung et al 7

below; between 30 minutes and two hours; two hours or above); average daily duration of multi-

media entertainment play (30 minutes or below; between 30 minutes and two hours; two hours or

above); average daily duration of reading (30 minutes or below; between 30 minutes and two

hours; two hours or above); average daily duration of homework (30 minutes or below; between

30 minutes and two hours; two hours or above); physical fitness level (‘Excellent’, ‘Good’, ‘Pass’

or ‘Fail’); and the schoolchildren’s compliance with the intake recommendations for each of the

nine nutrients (dichotomous variables: yes/no). Two-step cluster analysis was employed based

on these variables. A chi-square test was used to test differences in various characteristics between

the clusters.

Ethical considerations

A research proposal, information sheet and consent form for the parents or carers were submitted to

and approved by the university ethics committee before the project began.

Results

Of the diaries, 177 were found to be complete and suitable for further nutrient analysis. Five cases

were excluded subsequently because the children were more than 12 years old, which is atypical

for primary school education. Therefore the data of 172 students were used for statistical analysis.

The chi-square test results showed that the children’s physical fitness levels decreased signifi-

cantly with age (p ¼ 0.006). Students in Primary 1 (P1) and Primary 2 (P2) were more physically

fit than those in other years (Figure 1).

Many of the P1 students received ‘Excellent’ or ‘Good’ rankings, whereas the P2 students were

more likely to receive ‘Excellent’ or ‘Pass’ rankings, and one-third received a ‘Fail’. Most of the

Figure 1. Overall ranking of physical fitness level of students at different levels of education


Primary 3 (P3), Primary 4 (P4), Primary 5 (P5) and Primary 6 (P6) students received ‘Good’ or

‘Pass’ rankings.

The socioeconomic status of the families of the participating children is described in Table 3.

The education level of their fathers and mothers was mainly secondary, with 38.8 percent of the

fathers and 19.4 percent of the mothers having no formal education. Most of the parents chose not

to disclose their level of education. Around one-tenth of the fathers worked as managers, profes-

sionals or associated professionals, and 16.2 percent were employed in unskilled jobs; 15.6 percent

were employed in other categories. One-tenth of the mothers worked in unskilled jobs, 6.1 percent

had clerical positions and 5.1 percent worked in managerial or other professional careers; 8.3 per-

cent were employed in other categories. Half of the fathers and 70 percent of the mothers chose not

to disclose their occupation. Household income was not requested in the demographic section of

the questionnaire, as this is considered to be sensitive information in Hong Kong and most of the

parents would probably have refused to answer. However, the economic status of the participating

school districts is revealed from government statistics. Two of the schools were located in Shatin

and one in Kowloon City. The difference in the median monthly domestic household income

between these two districts is only 5.7 percent (Census and Statistics Department, 2001).

Cluster analysis

Two-step cluster analysis yielded two clusters, based on Schwarz’s BIC ¼ 3702.267 and ratio of

distance measures ¼ 1.464, with 77.3 percent of the children falling into Cluster A (N ¼ 133) and

22.7 percent (N¼ 39) into Cluster B. The two clusters were formed on the basis of the similarity of

their responses to the 16 variables. The demographic data are presented in Table 4.

The mean age of Cluster A was 8.78 years (SD¼ 1.71), whereas that of Cluster B was 8.59 years

(SD¼ 1.71). There were no significant differences between the two in terms of gender and level of

study, and their mean ages were similar. Cluster A had an equal number of males and females,

whereas Cluster B had more males (64%) than females (36%). Nearly half of the children in Clus-

ter A were studying in Primary 3 and Primary 4, whereas nearly half of those in Cluster B were in

Primary 5 and 6. The average total energy input and average consumption of the nine nutrients

were also analyzed by cluster (Figure 2).

Table 3. Socioeconomic status of primary schoolchildren’s parents

Father MotherN ¼ 1537 N (%) N (%)

EducationNo formal education 597 (38.8) 298 (19.4)Primary education 0 (0) 261 (17.0)Secondary education 84 (54.9) 905 (58.9)Tertiary education or above 96 (6.2) 73 (4.7)

OccupationManager, professional, associated professional 172 (11.2) 79 (5.1)Clerical work 35 (2.3) 94 (6.1)Unskilled labor 249 (16.2) 161 (10.5)Other 240 (15.6) 127 (8.3)Not disclosed 841 (54.7) 1076 (70.0)

Chung et al 9

Relationship between duration of physical activity and physical fitness level

In Cluster A, about one-third of the children (36%) had an average daily duration of physical activ-

ity of 30 minutes or below, and two-thirds (60%) had an average daily duration of physical activity

between 30 minutes and two hours respectively (Table 4). More than half (59%) of those in this

cluster spent 30 minutes to two hours daily on multimedia entertainment play, with 35 percent

of them spending two hours or more. The majority of the children in Cluster A spent 30 minutes

to two hours (60%) daily on homework, with just over one-third (37%) spending two hours or

more. A small proportion (3%) of those in this cluster reported spending 30 minutes or less on

homework each day.

In Cluster B, 46 percent and 49 percent of the children were found to spend 30 minutes or below

and 30 minutes to two hours daily on physical activity, respectively. Only 5 percent of them spend

two hours or more per day on such activity. More than half (56%) of these children reported spend-

ing 30 minutes to two hours daily on multimedia entertainment play, with 38 percent spending two

Table 4. Demographic data and duration of physical activity by cluster

VariableCluster

Chi-square testA (N ¼ 133) B (N ¼ 39)

p valueMean SD Mean SD

age 8.78 1.71 8.59 1.71N % N %

GenderMale 68 73.1 25 26.9 0.153Female 65 82.3 14 17.7

Level of study*P1 and P2 (age 6–7) 26 78.8 7 21.2 0.510P3 and P4 (age 8–9) 59 80.8 14 19.2P5 and P6 (age 10–12) 48 72.7 18 27.3

Daily physical activity30 mins or below 48 72.7 18 27.3 0.44530 mins to 2 hours 80 80.8 19 19.22 hours or more 5 71.4 2 28.6

Daily multimedia playing30 mins or below 8 80.0 2 20.0 0.92930 mins to 2 hours 78 78.0 22 22.02 hours or more 47 75.8 15 24.2

Daily reading30 mins or below 63 79.7 16 20.3 0.17030 mins to 2 hours 62 72.9 23 27.12 hours or more 8 100.0 0 0

Daily homework30 mins or below 4 80.0 1 20.0 0.26230 mins to 2 hours 80 73.4 29 26.62 hours or more 49 84.5 9 15.5

*P1 ¼ Primary 1; P2 ¼ Primary 2; P3 ¼ Primary 3; P4 ¼ Primary 4; P5 ¼ Primary 5; P6 ¼ Primary 6


Chung et al 11

hours or more. Only 5 percent of the children in Cluster B spent 30 minutes or less engaged in

multimedia entertainment play each day. None of the students in Cluster B reads for two hours

or more each day. Few (3%) spend 30 minutes or less on homework per day. The majority of the

children (75%) in Cluster B spend 30 minutes to two hours daily on homework, although 23 per-

cent spend more than two hours.

Relative to the children in Cluster B, those in Cluster A spend more time each day engaged in a

physical activity (p ¼ 0.445) and a similar amount of time on multimedia entertainment play

(0.929), reading (0.170) and homework (0.262).

Relationship between nutrients and physical fitness level

Using the 2005 Dietary Guidelines for Americans as a reference, 14 percent of the children in Clus-

ter A and 13 percent of those in Cluster B were found to meet the recommended guidelines for

carbohydrate consumption (p ¼ 0.908) (Table 5).

Thus, most of the children in both clusters eat fewer carbohydrates than the amount recommended.

With regard to protein intake, 63 percent of the children in Cluster A and 64 percent of those in Cluster

Figure 2. Students’ nutrient profiles by cluster and level of education


B were found to meet the recommended guidelines (p¼ 0.914). Only one (0.8%) child in Cluster A,

but nearly all (95%) in Cluster B, were found to meet the recommended guidelines for total fat

consumption ( p < 0.001). Around one-third (29%) of those in Cluster A and nearly all (92%) in Clus-

ter B met the recommendations for saturated fat intake (p < 0.001). Around one-fifth (23%) of the

children in Cluster A and nearly two-thirds (64%) of those in Cluster B were found to meet the

guidelines for sodium consumption (p < 0.001). Around half (51%) of the children in Cluster A and

most (82%) of those in Cluster B had the recommended cholesterol intake (p < 0.001). Two-thirds

(67%) of the Cluster A children and around half (46%) of the Cluster B met the guidelines for vitamin

C consumption (p¼ 0.019), whereas only four (3%) children in Cluster A and none in Cluster B had

the recommended dietary fiber intake (p¼ 0.273). Finally, 14 (11%) children in Cluster A and none in

Cluster B had sufficient calcium intake (p ¼ 0.035), according to the guidelines.

Table 5. Comparison of nutrients and physical fitness level

NutrientsCluster A Cluster B

Chi-square testN % N % p value

1. Meet carbohydrate guidelines?Yes 18 78.3 5 21.7 0.908No 115 77.2 34 22.8

2. Meet protein guidelines?Yes 84 77.1 25 22.9 0.914No 49 77.8 14 22.2

3. Meet total fat guidelines?Yes 1 2.6 37 97.4 <0.001No 132 98.5 2 1.5

4. Meet saturated fat guidelines?Yes 38 51.4 36 48.6 <0.001No 95 96.9 3 3.1

5. Meet sodium guidelines?Yes 30 54.5 25 45.5 <0.001No 103 88.0 14 12.0

6. Meet cholesterol guidelines?Yes 68 68.0 32 32.0 <0.001No 65 90.3 7 9.7

7. Meet vitamin C guidelines?Yes 89 83.2 18 16.8 0.019No 44 67.7 21 32.3

8. Meet dietary fiber guidelines?Yes 4 100.0 0 0 0.273No 129 76.8 39 23.2

9.Meet calcium guidelines?Yes 14 100.0 0 0 0.035No 119 75.3 39 24.7

Physical fitness levelExcellent 15 83.3 3 16.7 0.352Good 36 69.2 16 30.8Pass 74 79.6 19 20.4Fail 8 88.9 1 11.1

Chung et al 13

In Cluster A, 11 percent were given ‘Excellent’, 27 percent were given ‘Good’, 56 percent were

given ‘Pass’ and 6 percent of the children were given ‘Fair’ ratings for their levels of physical fit-

ness. Among those in Cluster B, 8 percent achieved rankings of ‘Excellent’, 41 percent achieved

rankings of ‘Good’, 49 percent achieved rankings of ‘Pass’ and 3 percent achieved rankings of

‘Fair’ (p ¼ 0.352) (Table 5).

As can be seen in Figure 3, the physical fitness level in Cluster A was distributed with a peak at

the ‘Pass’ level, whereas Cluster B physical fitness was distributed equally between ‘Good’ and

‘Pass’. In total, 38 percent of the children in Cluster A and 49 percent of those in Cluster B were

rated at the ‘Excellent’ and ‘Good’ levels (Figure 3). Therefore, the latter were deemed to have

better levels of physical fitness than the former.

Discussion

Cluster analysis was adopted in this study because this approach is best able to categorize a group

of subjects into subgroups and allow similar characteristics among the defined variables to be iden-

tified and calculated. Here, the schoolchildren in each subgroup bore similar characteristics in

terms of nutrient compliance, various activity levels and physical fitness level. The results show

that significantly more primary schoolchildren in Cluster B had diets that met contemporary US

intake guidelines for total fat (p<0.001), saturated fat (p<0.001), sodium (p<0.001) and cholesterol

(p<0.001) than those in Cluster A. However, the diets of significantly more of the children in Clus-

ter A met the consumption guidelines for vitamin C (p¼ 0.019) and calcium (p¼ 0.035) relative to

those in Cluster B. Thus, it may be deduced that low intake levels of total fat, saturated fat, sodium

and cholesterol may be factors contributing to better physical fitness. Hence, the results of this

study provide strong support for the US consumption guidelines for these four nutrients in terms

of their integrated effect on health.

Few of the children in Cluster A had good eating habits, which include low intake levels of total

fat, saturated fat, sodium and cholesterol, although most met the vitamin C and calcium consump-

tion guidelines. This finding raises the question of whether vitamin C and calcium are essential

Figure 3. Distribution of physical fitness of the two clusters


nutrients for physical fitness in children. In terms of their documented benefits, vitamin C is a good

antioxidant and calcium is good for building bone mass. Thus, it is possible that these two nutrients

are not associated with the physiological functions tested in the physical fitness assessment in this

study. Although the children in Cluster A were less physically fit in general, more of them achieved

an ‘Excellent’ level compared with those in Cluster B, which may be due to the greater number that

met the calcium consumption guidelines.

Cluster B comprised more children whose diets were balanced in nutrients, and their higher per-

centage of ‘Good’ and ‘Pass’ physical fitness levels confirms the benefits of a balanced diet, espe-

cially in terms of total fat, saturated fat, sodium and cholesterol intake. Nutrition education in

school is of critical importance, as it helps to establish good eating habits that will continue into

adulthood (Demory-Luce et al., 2004). In the USA, the new food guide pyramid already incorpo-

rates an element of exercise (www.eatright.org; U.S. Department of Agriculture, 2009). The impli-

cation is that diet and exercise must be combined in an integrated health education program. As

there is a lack of research into such a combined approach, the findings of this study provide

research data to support the benefits of adopting physical fitness level as an outcome indicator.

The different characteristics found in the two groups under study here provide strong evidence

of the importance of raising awareness among parents that a healthy diet must begin in childhood.

Conclusion

Limitations of the study

Since the primary schoolchildren were young and thus not competent to complete the question-

naire on their own, the assumption of the present study was that the data collected by their proxies

was reliable. Also, because the physical activity patterns of the students were collected in the form

of a questionnaire, the data analysis could only be the frequency of every activity, lacking the

intensity data and hence energy expenditure data, thus the comparison of energy requirement.

In addition, different physical activity intensity levels may confer different benefits. A more accu-

rate level could be determined if such activity were quantified in terms of total energy with com-

ponents of duration and intensity. In addition, although food diaries are a commonly used

instrument as a survey method, they were time-consuming to fill out, resulting in a difficulty in

collecting good quality data.

Areas for further research

Further research is needed to explore the ability to reproduce the results of this study. Suggestions

include using food photos as dietary intake records for more accurate food intake analysis, and

using digital pedometers to record the intensity of physical activity and the time spent on each type

of activity.

The results of this study support the recommended daily intake levels set out in the most recent

US dietary guidelines for four nutrients—total fat, saturated fat, sodium and cholesterol—out of

the nine examined in terms of good physical fitness among primary schoolchildren. They also con-

firm the integrated effect of a balanced diet.

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Importance of a balanced diet on the physical fitness level of schoolchildren aged 6–12

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