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Article

Autonomic Profile, Physical Activity, Body Mass Index and Academic Performance of School Students

by
Daniel Mendoza-Castejón
1 and
Vicente Javier Clemente-Suárez
1,2,*
1
Faculty of Sport Sciences, Universidad Europea de Madrid, Villaviciosa de Odón, 28670 Madrid, Spain
2
Grupo de Investigación en Cultura, Educación y Sociedad, Universidad de la Costa, Barranquilla 080002, Colombia
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(17), 6718; https://0-doi-org.brum.beds.ac.uk/10.3390/su12176718
Submission received: 17 July 2020 / Revised: 12 August 2020 / Accepted: 17 August 2020 / Published: 19 August 2020
(This article belongs to the Special Issue Advances in Physical Education, Exercise and Sport: Towards a Healthy and Sustainable Lifestyle)
Versions Notes

Abstract

:
The aim of this study was to analyze the autonomic modulation, physical activity, body mass index, and academic performance of preschool and school students by grade. Extracurricular physical activity, heart rate variability, body mass index, and objective and subjective academic performance were analyzed in 180 preschool and primary school students (7.91 ± 2.29 years). Significant lower heart rate and higher parasympathetic modulation were found in 10–12-year-old primary education students. The 8–9-year-old students obtained the worst results in English and in five of the subjective academic performance items. Students aged 10–12 years old presented the highest body composition values. No significant differences were found on the extracurricular physical activity by age. No correlation between autonomic profile, physical activity, and body composition with objective academic performance was found. Nerveless subjective academic performance perception of teachers presented a negative correlation with body composition and the parasympathetic modulation. School students presented an increased body mass index and parasympathetic modulation by age. Physical activity of all students, independently of the age, were lower than the official recommendations.

1. Introduction

Success in the educational process is usually related to aspects that reflect in individual qualification depending on the knowledge area, daily performance, and attitude. The assessment of these elements is usually based on solving tests, making specific works, or daily tasks to check the student’s continuous progress [1,2]. However, multiple complex variables, such as individual qualities, sociocultural-economic environment, and school reality, could directly or indirectly influence the student’s status and their academic performance. In this line, students’ quality of life plays a key role in their academic performance [3,4,5].
It is known that promoting healthy habits (including physical activity) during early school age seems to be quite noteworthy to improve academic achievement [6,7] and could be capital to keep a healthy lifestyle in the future, especially in western countries with an important increase in sedentarism and obesity [8,9,10]. In this line, an excessive fat percentage was related to increased morbidity and mortality. Body mass index (BMI) is a basic and simple indicator to compare individual body status with standard population, but is necessary to note that one’s BMI value could be associated to different body fat percentages affected by age, sex, ethnicity, or individual differences. In education, BMI has been usually associated with academic results in children and adolescents, showing a negative correlation [11,12]. High BMI values could be signs of an unhealthy lifestyle and increased internal stress in children that could affect their performance at school [13,14]. Physical education at school has structured programs aiming to reach this purpose [15]. This is important since the amount of physical activity, sport practice, kind of practice, and the intensity carried out by students in their free time are considered important factors for the students’ multidimensional growth [16,17].
Previous researches pointed out several physical and physiological benefits of moderate and regular physical practice in school children [18], including brain and cognitive functioning such as perception, decision, execution, concentration, and memory [19,20]. All these elements could help to deal with routine academic requirements and even with specific events such as tests or exams in different areas as mathematical calculation, linguistic reasoning, or creativity [21,22,23,24]. Despite the benefits found on health, fitness, and short-term academic improvements on students, there is still no evidence on the influence of physical activity practice on long-term academic performance, requiring more studies that explain these influences [25,26,27]. Currently, there is a widespread trend among students and their families regarding the reduction of physical practice when the academic demand increases, or when the educational stage changes [28,29]. On the contrary, a recent research found that maintaining the daily routine in terms of number of sessions per week, volume and intensity of physical activity does not negatively affects grades of students on evaluation periods. In fact, students with better academic profiles were those who played more sport [30].
Another remarkable aspect is that elementary students is a sensitive population to suffer increased anxiety levels because they present a lack of self-control or fewer tools to face this kind of stressful situations, such as evaluation periods, than other educational stages such as secondary or higher education [31,32,33]. Previous studies conducted in higher education stage showed how the psychological profile of students is an important variable to keep stress under control [34,35], which is essential to reach a correct learning process [36]. The academic environment generates stress that can be detected by the heart rate variability (HRV) measurements [37], being a useful tool to analyze autonomic nervous system dysregulation due to the stress in early educational stages [38]. The cathartic function of physical activity is an interesting utilitarian dimension for students [39,40], reducing their sympathetic activation and stabilizing their autonomic modulation. Therefore, it could help them cope with academic stress and anxiety, improving their academic performance.
In order to improve knowledge in this multifactorial stress area, we conducted the present research with the aim to analyze the autonomic modulation, physical activity, body mass index, and academic performance of preschool and school students by grade. The initial hypothesis was that students with higher physical activity and lower body mass index would present higher parasympathetic modulation and higher academic performance.

2. Materials and Methods

2.1. Participants

We analyzed 180 Spanish preschool and primary school students (7.91 ± 2.29 years, from 3 to 12 years). The division by age was made as follows: pre-school education (3–5 years), n = 27; first primary stage (6–7 years) corresponding to 1st and 2nd school year, n = 58; second primary stage (8–9 years), corresponding to 3rd and 4th school year, n = 51; third primary stage (10–12 years), corresponding to 5th and 6th school year, n = 44. All participants, parental or guardian figures, and their professors were informed about the experimental procedures, indicating the right to withdraw from the study at any time and providing a written informed consent before starting the study, following the Helsinki Declaration (as revised in Brazil, 2013). All the data were collected anonymously, and the procedure was approved by the European University of Madrid Ethical Committee (CIPI/18/074).

2.2. Procedure

The present descriptive and non-experimental research based in quantitative data analyzed physiological stress markers, extracurricular physical activity, body mass index, and academic performance in school students. The data collection took place in the last week of the first term evaluations and before the report cards were given. To reduce possible students’ anxiety at the time of measurement, the researchers visited the schools to introduce themselves to the children, presenting the devices used for the data collection. Physical education teachers helped with this propose. Furthermore, the students who participated in the study had filled out particularly a small booklet two weeks at home before the collection of HRV data at the school. Parents and teachers cooperated to help them, explaining the most difficult questions especially for the earliest ages. Previously, they were informed about the instructions and each item meaning. The document contained their basic data and the questionnaires specified below. Likewise, the center provided the students’ grades with their express authorization.
The HRV analysis was conducted using the Polar V800 heart rate monitor (Polar, Kempele, Finland). The RR waves interval of the heartbeat (temporal distance in milliseconds of the consecutive R waves of an electrogram) were recorded consistent with previous research [41]. Following previous procedures [42,43], we analyzed the HRV for five minutes prior to start a regular school day, with the students seated in a quiet room. The R-R series was analyzed using the Kubios HRV software, version 2.0 (Biosignal Analysis and Medical Imaging Group, University of Kuopio, Finland), developed in accordance with the recommendations of the existing scientific literature [44,45]. The next HRV variables were evaluated: heart rate mean (HRmean) and the sensitivity of the short-term variability (SD1) and long-term variability (SD2) of the non-linear spectra of the HRV; percentage of differences between normal adjacent R-R intervals greater than 50 ms (pNN50); the square root of the average of the sum of the differences squared between normal adjacent R-R intervals (RMSSD); the low-frequency band in normalized units (low-frequency LFn); the high-frequency band in normalized units (high-frequency, HFn); and LF/HF ratio. These variables provide information on the student’s autonomic nervous system.
To analyze Physical Activity profile, the validated self-report questionnaire in children and adolescents, (Physical Activity Questionnaire for Children and Adolescents) PAQ-C and PAQ-A, respectively [46,47], was employed. These questionnaires were selected due to their easy application and because they are two of the most employed questionnaires in these populations.
The Body Mass Index (BMI) was calculated using the classic formula: weight(kg)/height(m)2, because bioimpedance and other anthropometric measurements were not available, accepting the limitation of the result. Weight and height were measured in physical education class and BMI was calculated later. BMI was used because it is a widely used standard measure for weight categories that may lead to health problems [48].
To analyze subjective perception of students’ academic performance (SPAP), a questionnaire about the teachers’ subjective perception of students’ academic performance was filled, in which they answered the following five questions in a 1 (never) to 5 (always) rank: “Student shows interest and curiosity in learning new things?”, “Student works to finish the tasks you begin?”, “Student stays calm and in control when faced with a challenge?”, “Student cares about doing well in school?”, and “Student does all the work required?” Each teacher completed the questionnaire about their class group alone at the school.
The objective academic performance was analyzed by the academic qualification of each subject carried out by the students and the total average of all the subjects. This basic information was provided by the school direction with official data.

2.3. Statistical Analysis

The statistical analysis was carried out using the Statistical Package for the Social Sciences (SPSS) version 24.0 (SPSS Inc., Chicago, IL, USA). Descriptive statistics (mean and standard deviation) were calculated for each variable. The normality was tested by the Kolmogorov-Smirnov test. As all the variables presented a parametric distribution, a MANOVA with age group as fixed factor was conducted to explore differences in the variables analyzed. Finally, a bivariate correlation analysis was performed using the Pearson test. The significance level was p ≤ 0.05. The effect size was also calculated.

3. Results

The MANOVA presented significant differences between age groups (F: 6252; p: 0.000; η2: 0.894). This analysis found significantly lower HR mean values in primary 3rd stage than preschool students and the others primary groups. No significant differences have been found between groups in the other HRV variables measured (Table 1).
Regarding academic performance, significant differences were only found in English and Religion/Social Values grades, and five of the six items in the SPAP between groups. Primary 1st stage (Group 2) showed the best results in English among the groups, but primary 2nd stage (Group 3) obtained the worst results in English, as well as in five of the six SPAP items (Table 2).
Primary 3rd stage (Group 4) presented highest values in height, weight, and BMI than younger groups (Table 3). Age seems to have a strong relation with body growth. No significant differences were found on the extracurricular physical activity by groups, but a small increased tendency with age was observed as well.
In the correlational analysis we found a negative significant correlation between SPAP average and BMI (r: −0.181; p: 0.042), RMSSD (r: −0.191; p: 0.027), pNN50 (r: −0.283; p: 0.001) and SD1 (r: −0.191; p: 0.027).

4. Discussion

The aim of this study was to analyze the autonomic modulation, physical activity, body mass index, and academic performance of preschool and school students by grade. The initial hypothesis was partially confirmed since only lower body mass index correlated with better subjective academic performance.
The HRV analysis has been confirmed as a useful and non-invasive technique to measure autonomic modulation in children [49]. Students’ HR mean analysis revealed a tendency to decrease by grade whereas an incremental tendency in parasympathetic modulation (RMSSD, pNN50 and SD1) was found by grade and age, coinciding with previous researches [50,51]. These results might be in accordance with a normal maturation of autonomic nervous system where parasympathetic activation increases from birth to young adulthood [52,53]. These results were in line with a normalized growth, according with the significant increase in height, weight, and BMI [54]. Previous studies have positively related higher BMI with an increase in internal physiological stress of subjects [55]. A body composition imbalance might indicate unhealthy lifestyle habits contributing to acquire non-recommended stress status [56,57,58].
No correlation was found between physical activity and academic performance by grade, although the amount of weekly extracurricular physical activity showed an increased tendency by grade. Some studies from the beginning of the 21st century did not conclusively find that physical activity and physical education contribute to achieve better academic results, but none of them found that these results were worsened by the practice [59]. However, current evidences indicate a positive influence on cognitive development, executive functions, specific brain areas, and some improvements on curricular areas, such as language, foreign language, mathematics, or in academic skills, as reading or arithmetic [60,61,62,63]. Independently, the values of physical activity presented in the sample analyzed were lower than the recommendations from health promoting institutions for children [64]. This circumstance brings a serious problem in western societies: the sedentary lifestyle. This habit is increasingly established among the population and it might lead to overweight and obesity as a trigger to other more severe pathologies [65]. Currently identified as one of the main problems is the time spent in front of the screens, whether for study/work needs or for new leisure modalities. Spanish children and adolescents do not follow the recommendations regarding the maximum of screen viewing [66], which is two hours per day. Thus, global interventions in children and adolescents are crucial for acquiring the right knowledge, convictions, skills, and attitudes that help shape a pro-healthy lifestyle [67].
Regarding academic performance, there were no differences in the grade average between the groups analyzed, but a slight decreasing trend from the first to the last year was found. These results could be motivated by the progressive demand and complexity of the curriculum of each school year, which requires more effort from the students. However, it would also be necessary to keep in mind other factors such as the lack of motivation and boredom that students suffer in their course’s progression [68]. The lack of adaptation to the changes that the schools make each academic stage, limited emotional control [69], or low intrinsic motivation to engage might also be related to a poor enjoyment of their cognitive efforts [70]. Nevertheless, SPAP analysis revealed significant differences between groups in five of the six items evaluated. Daily academic performance and regular work in the classroom were better in preschool and primary 3rd stage (younger students obtained higher scores). Central ages obtained the lowest ratings, specifically in primary 2nd stage (8–9 years) with the worst score perceived. The concepts included in this evaluation are related to attitudinal aspects such as good behavior, self-control, responsibility or involvement, and proactivity in the classroom, which are frequently considered as a source of better subsequent results. Besides the specific conformation of each class group, it is not clear why these results appear in these age groups. Future research should explain this fact.
In the correlation analysis a negative correlation was found between BMI and the SPAP average, in line with previous studies where higher BMI correlated with worse academic achievements [71,72]. SPAP average also negatively correlated with RMSSD, pNN50, and SD1, variables related with a parasympathetic modulation. These results were opposite to the initial hypothesis, showing the influence of autonomous modulation in academic performance of students, but future studies with a larger sample must delve in this line for better knowledge of this complex relation. An appropriate autonomic nervous system regulation promotes a healthier general state, that, joining a higher emotional control, better self-efficacy conception and self-confidence, would prepare students for the incoming academic challenges [73,74]. These tools are basic to develop stress control abilities, reducing anxiety states in high academic demand moments, and strengthening student’s self-knowledge. In this line, active exercise, playful-sporting, respiratory or emotional control have shown their effectivity to reduce stress in children [75]. Some studies have indicated that active programs in two basic dimensions of action (curricular and extracurricular), could improve the basic conditions to face daily school demands. In this line, the authors suggest an increase in the physical activity (even prior to the school day) and physical education time with higher intensity of practice, standing the teachers as a promoters for instilling a love for being active within their leisure time because physical activity practice has been recognized as a good way to provide a global development in children and adolescents [76,77,78]. Educational institutions should follow global guidelines and consider all those advantages and virtues to maintain health and an appropriate fitness status in school ages [79]. The entire educational community (authorities, schools, educators, students, and families) should be involved to promote positive behaviors and decrease anxiety in the school environment.
The main limitation of the present study was the small sample size. It was difficult to recruit students to conduct the complete research requirements, especially in early ages. Another limitation was the use of BMI and no use of anthropometric measurements such as skin folds and circumferences or Bioimpedance, but material limitation precluded their use. A third limitation was the absence of analysis of maturation of students, and future research might seek to address these issues.
For future research it would be interesting to explain deeply the type of physical activity and intensity of students in their leisure time. Future studies involving other higher educational stages might provide more information about the evolution of autonomic modulation, academic performance, and physical activity in students.

5. Conclusions

School students presented an increased body mass index and parasympathetic modulation by age. Physical activity of all students, independently of the age, were lower than the official recommendations. No correlation between autonomic profile, physical activity, and body composition with objective academic performance was found. Nerveless subjective academic performance perception of teachers presented a negative correlation with body composition and parasympathetic modulation of students.

Author Contributions

Conceptualization, D.M.-C. and V.J.C.-S.; methodology and formal analysis, D.M.-C. and V.J.C.-S.; investigation, D.M.-C. and V.J.C.-S.; data curation, V.J.C.-S.; writing—Original draft preparation, D.M.-C.; writing—Review and editing, D.M.-C. and V.J.C.-S.; visualization, D.M.-C. and V.J.C.-S.; supervision and funding acquisition, V.J.C.-S. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the David A. Wilson Award for Excellence in Teaching and Learning Research Award 2017, project number XOTRIO1712.

Acknowledgments

We want to acknowledge the collaboration of students, families, and teachers.

Conflicts of Interest

The authors declare no conflict of interest.

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Table
Table 1. Heart rate variability of students.
Table 1. Heart rate variability of students.
VariableGroup 1 PreschoolGroup 2 Primary
1st Stage		Group 3 Primary
2nd Stage		Group 4 Primary
3rd Stage		Fpη2Group Comparison
HRmean (b/min)114.65 ± 12.62101.17 ± 10.24107.97 ± 17.7286.36 ± 12.897.950.0010.1684 < 2 < 3 < 1
SD1 (ms)47.01 ± 30.9439.34 ± 16.9047.81 ± 24.2046.46 ± 19.260.180.8340.005
SD2 (ms)127.80 ± 116.7499.30 ± 40.13125.51 ± 51.84115.94 ± 36.190.110.8920.003
pNN50 (%)23.11 ± 19.4921.95 ± 13.3026.68 ± 15.9632.04 ± 13.811.510.2270.037
RMSSD (ms)66.41 ± 43.6955.57 ± 23.8767.53 ± 34.1965.64 ± 27.200.180.8340.005
LF (n.u.)68.25 ± 20.3967.49 ± 18.6767.14 ± 14.1261.10 ± 14.290.650.5240.016
HF (n.u.)31.48 ± 20.1432.38 ± 18.6031.28 ± 13.3438.77 ± 14.291.350.2650.033
LF/HF ratio 5.15 ± 9.2811.35 ± 45.922.90 ± 2.122.02 ± 1.381.570.2140.005
HR mean, heart rate mean; RMSSD, root-mean square differences of successive heartbeat intervals; pNN50, percentage of successive RR-interval pairs differing in more than 50 milliseconds in the entire recording divided by the total number of RR waves intervals; LF: low-frequency band; HF: high-frequency band; LF/HF Ratio; SD1, transverse axis; SD2, longitudinal axis.
Table
Table 2. Grades and Subjective Perception of Academic Performance (SPAP) of students.
Table 2. Grades and Subjective Perception of Academic Performance (SPAP) of students.
Group 1 PreschoolGroup 2 Primary
1st Stage		Group 3 Primary 2nd StageGroup 4 Primary
3rd Stage		F pη2Group Comparison
Grade average (0–10) 7.28 ± 1.136.87 ± 1.296.95 ± 1.171.800.1710.044
Sciences grade (0–10) 7.13 ± 1.497.21 ± 1.526.90 ± 1.631.450.2390.036
Social sciences grade (0–10) 6.86 ± 1.726.27 ± 1.676.72 ± 1.681.920.1530.046
Language grade (0–10) 7.20 ± 1.807.07 ± 1.687.09 ± 1.490.350.7020.009
Math’s grade (0–10) 7.37 ± 1.586.78 ± 1.896.79 ± 1.672.200.1170.053
English grade (0–10) 6.93 ± 1.765.64 ± 1.986.18 ± 1.550.720.0020.1432 > 4 > 3
Arts grade (0–10) 7.36 ± 1.117.25 ± 1.247.13 ± 1.400.720.4890.018
Music grade (0–10) 7.29 ± 1.326.96 ± 1.446.86 ± 1.531.700.1880.041
Crafts grade (0–10) 7.27 ± 1.167.15 ± 1.317.06 ± 1.300.340.7060.009
Physical education grade (0–10) 7.06 ± 1.056.82 ± 0.897.29 ± 1.171.020.3630.025
Religion/S.Values grade (0–10) 8.29 ± 1.037.62 ± 1.397.53 ± 1.312.620.0790.062
Student shows interest and curiosity in learning new things? (1–5)4.29 ± 1.104.00 ± 1.433.31 ± 1.214.11 ± 1.214.130.0200.0951,2,4 > 3
Student works to finish the tasks you begin? (1–5)4.11 ± 1.393.96 ± 1.563.21 ± 1.454.02 ± 1.203.730.0280.0861,2,4 > 3
Student stays calm and in control when faced with a challenge? (1–5)4.00 ± 1.464.27 ± 1.222.90 ± 1.423.11 ± 1.4610.740.0000.2141,2,4 > 3
Student cares about doing well in school? (1–5)4.14 ± 1.323.91 ± 1.503.34 ± 1.444.11 ± 1.184.400.0150.1001,2,4 > 3
Student does all the work required? (1–5)4.22 ± 1.364.06 ± 1.463.43 ± 1.464.00 ± 1.212.640.0770.063
SPAP average (1–5)4.15 ± 1.074.04 ± 1.053.24 ± 0.913.87 ± 0.927.650.0010.1621,2,4 > 3
Table
Table 3. Body mass index and physical activity of students.
Table 3. Body mass index and physical activity of students.
Group 1 PreschoolGroup 2 Primary
1st stage		Group 3 Primary
2nd stage		Group 4 Primary
3rd stage		Fpη2Group Comparison
Height (cm)108 ± 10.20124.27 ± 7.84138.27 ± 8.67148.42 ± 8.1846.000.0000.5381 < 2 < 3 < 4
Weight (Kg)19.40 ± 3.4526.92 ± 6.1837.01 ± 9.2543.86 ± 10.0020.460.0000.3411 < 2 < 3 < 4
BMI (Kg/m2)16.82 ± 3.4117.41 ± 3.0819.20 ± 3.8919.78 ± 3.494.380.0160.1001 < 2 < 3 < 4
PAQC-A (1-5)1.48 ± 0.581.59 ± 0.671.61 ± 0.581.71 ± 0.610.1600.8520.004
BMI, Body Mass Index; PAQC-A: Physical Activity Questionnaire for Children and Adolescents.

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Mendoza-Castejón, D.; Clemente-Suárez, V.J. Autonomic Profile, Physical Activity, Body Mass Index and Academic Performance of School Students. Sustainability 2020, 12, 6718. https://0-doi-org.brum.beds.ac.uk/10.3390/su12176718

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Mendoza-Castejón D, Clemente-Suárez VJ. Autonomic Profile, Physical Activity, Body Mass Index and Academic Performance of School Students. Sustainability. 2020; 12(17):6718. https://0-doi-org.brum.beds.ac.uk/10.3390/su12176718

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Mendoza-Castejón, Daniel, and Vicente Javier Clemente-Suárez. 2020. "Autonomic Profile, Physical Activity, Body Mass Index and Academic Performance of School Students" Sustainability 12, no. 17: 6718. https://0-doi-org.brum.beds.ac.uk/10.3390/su12176718

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