Abstract
Purpose
This study aims to compare the physical fitness test results of Japanese children in 2008 and 2018 to narrow the gap between life expectancy and healthy life expectancy and extend healthy life expectancy. In addition, this paper sought to explore the potential of implementing health education programs as a new social context to promote race equality and human rights in health and social care.
Design/methodology/approach
This study was conducted in 2008 and 2018 in Nagano Prefecture, Japan. Physical fitness tests related to growth and development were administered to participants aged 6–17 years.
Findings
Physical fitness measurements in 2018, specifically those for walking ability and endurance, were significantly inferior to those in 2008. In a gender-specific analysis, boys outperformed girls in muscle strength, muscle endurance, walking ability and endurance tests, while girls outperformed boys in the balance test.
Research limitations/implications
Most of the junior and senior high school students who participated in the EO test exceeded the upper limit of 120 s, suggesting that the load of the measurement method is low and improvement is necessary. In 2018, a large variation in 6M results was observed among participants, possibly due to the differences in the level of seriousness during the 6M test. Therefore, to ensure that junior and senior high school students properly perform the EO and 6M tests, it is necessary to devise an effective method of implementation, such as changing the physical fitness test load.
Originality/value
Mere health education is ineffective to address health inequalities. Addressing structural factors is essential to avoid unintended consequences such as increasing the gap between groups of people. However, one way to extend healthy life expectancy is to improve overall health, including differences in the health status of groups due to differences in region and socioeconomic status.
Keywords
Citation
Fujimori, S., Ashida, K., Watanabe, N., Nishino, T., Sasamori, F., Okuhara, M., Tabuchi, H. and Terasawa, K. (2024), "Human rights health care measures reporting physical fitness test for ages 6 to 17 with 10-year follow-up", International Journal of Human Rights in Healthcare, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJHRH-12-2023-0092
Publisher
:Emerald Publishing Limited
Copyright © 2024, Satomi Fujimori, Kazuki Ashida, Noriaki Watanabe, Tomoyuki Nishino, Fumihito Sasamori, Masao Okuhara, Hisaaki Tabuchi and Koji Terasawa.
License
Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial & non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
Health education for children has been reported to have a significant effect on their growth (WHO: World Health Organization, 2022; UNICEF: United Nations Children’s Fund, 2022) (CDC) (Muennig et al., 2011). In addition, the World Health Organization (WHO) has reported that in a rapidly aging global society, extending healthy life expectancy (HLE) can lead to decreased medical expenses (WHO: World Health Organization, 2015b). Currently, in Japan, a gap of nearly 10 years exists between the average HLE and the life expectancy at birth, and this situation has continued for more than 20 years (WHO: World Health Organization, 2019). Therefore, the challenge for public health in Japan is to build a system to support a super-aging society that enables everything from disease prevention to medical care amid tight social security finances (Imai, 2016). The Japanese Ministry of Health, Labour and Welfare intends to extend the HLE and reduce medical and nursing expenses (Ministry of Health, Labor and Welfare health: MHLW, 2022). Specifically, enhancing people’s health can result in fewer lifestyle-related illnesses and dementia, thereby extending HLE and preventing early retirement from work because of disease (WHO: World Health Organization, 2015b; Ministry of Health, Labor and Welfare health, 2022). In addition, it has been shown that the impairment of workers’ health affects the gross domestic product (Rasmussen et al., 2016) and that the improvement of health levels through health education brings about benefits (Henke et al., 2011). Furthermore, a cost-benefit analysis of the Child Parent Center Early Education Program for 26 year olds revealed that attending a preschool program against unhealthy habits such as using alcohol, tobacco and illegal drugs provides a gross social benefit of $10.83 for every dollar invested; reported net income per participant of $83,708 (Reynolds et al., 2011). For instance, research indicates that people who join a comprehensive early stage health education program develop fewer unhealthy habits and are less likely to indulge in excessive alcohol, cigarette, and illegal drug consumption (UNICEF: United Nations Children's Fund, 2022). Therefore, the effectiveness of early health education from childhood is increasingly effective (Ramon et al., 2018) (Ekwaru et al., 2021). However, till date, no established health education method for children has been implemented.
Since 1998, a systematic health education program for older adults developed at the Shinshu University in Japan (HESU) has been implemented in Nagano Prefecture in Japan, the Saraya region in Thailand, the Bali region in Indonesia and the Cebu region in the Philippines (Fujimori et al., 2018; Fujimori et al., 2020; Maruo et al., 2015; Maruo et al., 2020; Murata et al., 2015; Nakade et al., 2017; Terasawa et al., 2022; Watanabe et al., 2015). HESU has been implementing ongoing comprehensive social capital-oriented and human rights-friendly health education aimed at fostering empathy and cooperation, with the regular goal of 7,000 steps per day. By leveraging the social capital of participants and staff and striving to ensure prosperity of people based on dignity and freedom, the goal of taking 7,000 steps per day to improve health may be achieved. Systematic HESU programs evaluate energy expenditure and test brain function, physical fitness, and blood parameters. In addition, HESU organizes educational seminars on exercise, nutrition, and recreational activities, such as hiking and cooking. It follows the plan-do-check-act cycle, which was developed and accredited as per the International Organization for Standardization (ISO) 9001 (2008) standard in 2014, and moved to self-declaration in 2021. Furthermore, HESU plans to develop and integrate a dementia improvement program into the existing health education program.
In the future, the development of effective health education programs for children will become imperative, as they play a significant role in supporting and driving a super-aging society. In addition, we sought to explore the potential for implementing health education programs as a new social context to promote race equality and human rights in health and social care. In addition, involving victims, perpetrators and local residents, we explored the possibility of using restorative justice to address cultural, social and political prejudices against specific individuals and groups in hate crimes targeting women and minorities (Gavrielides, 2012, 2022).
Previous research proposes that increased physical strength leads to good health (Monbushou [MEXT: Ministry of Education, Culture, Sports, Science and Technology, Japan], 2000) (Japan Sports Agency, 2023). This physical fitness survey was conducted in 2008 among participants aged 6–17 years, and a follow-up survey was conducted after 10 years in 2018. This early health education aimed to ensure that children’s health is maintained and promoted throughout their lives until old age. Therefore, the purpose of this study was to compare the results of the children’s physical fitness survey, understand the actual health status of children, identify areas of improvement and improve the health level of children, which will ultimately contribute to the extension of healthy life expectancy.
2. Method
The surveys were conducted in September to October 2008 and September to October 2018 in Nagano Prefecture, Japan, in the same elementary, junior high, and high schools where physical fitness tests related to growth and development were administered to participants aged 6–18 years. In 2008, first grade elementary school children in Japan were between six and seven years of age, born between April 1, 2002 and March 31, 2003; however, they were designated as six years old. Therefore, the notation for the second grade of elementary school was seven years old. The total number of participants in 2008 was 445, including 217 boys and 228 girls. In contrast, the number of participants in 2018 was 510, including 261 boys and 249 girls. For both the years, the total of participants was 955, including 478 boys and 477 girls (Table 1). A physical fitness survey was conducted among participants aged 6–17 year.
Since 1964, the Ministry of Education, Culture, Sports, Science, and Technology of Japan has conducted a “survey on the physical fitness and athletic ability” of the Japanese people to clarify the current state of physical fitness and athletic ability. In 1999, the test was revised to the “New Physical Fitness Test,” and data on 50,000–75,000 people aged 6–79 is published every year, aiming to lead a healthy and vibrant society in the 21st century. The physical fitness test events were divided into four age groups: for ages 6–11: grip strength for muscle strength (GS), sit-ups for muscle endurance (SU), sit-and-reach flexibility for muscle flexibility (SR), repeated side jumps, shuttle run, 50 m run, standing long jump and software throw; for ages 12–19 years: GS, SU, SR, repeated horizontal jumps, shuttle run, 50 m run, standing long jump and handball throw; for ages 20–64, GS, SU, SR, repetitive horizontal jumping, shuttle run and standing long jump; and for age 65–79: GS, SU, SR, eyes-open single-leg stance (EO), 10-m obstacle walk for walking ability (10M) and 6-min walk for endurance (6M). A total of 22,000 elementary schools, 12,000 junior high schools and 5,000 high schools are there in Japan, and data for each school participating in physical fitness tests are published annually (Japan Sports Agency, 2023, Japan in terms of statistics, 2023). In Nagano Prefecture, 360 elementary schools, 200 junior high schools and 100 high schools are present, and one school from each cooperated and participated in this study. Japan has 47 prefectures, including the Nagano Prefecture. A physical fitness test (target age: 65–79 years) was established by the Ministry of Education, Culture, Sports, Science, and Technology of Japan according to the implementation guidelines. The test consisted of the following six tasks: grip strength, sit-ups, sit-and-reach flexibility, eyes-open single-leg stance, 10-m obstacle walk and 6-min walk (Ministry of Education, Culture, Sports, Science and Technology, 2019). These tests have already been conducted in preschool children to ensure their safety, performance and reporting (Molenaar et al., 2008; Oja and Jürimäe, 1997; Koslow, 1987; Greenspan, 1990; Kasuga et al., 2012; Rikli et al., 1992), and our project is currently analyzing data from these tests on 3–79 years olds. Exercise is a planned, repetitive physical activity aimed at maintaining and increasing physical fitness (Caspersen et al., 1985). Physical fitness is defined as a set of health-related attributes that can be improved through regular exercise and has been shown to have a significant positive relationship with exercise outcomes (American College of Sports Medicine, 2018). Furthermore, the characteristics of physical fitness can be measured using physical fitness tests and are associated with disease prevention and health promotion; it is considered appropriate to measure physical fitness elements before a prevention program (Farley et al., 2020). Gender includes the social, psychological, cultural and behavioral aspects of being a man, woman or another gender identity. Depending on the context, this may include sex-based social structures and gender expressions (Becker et al., 2020).
However, the physical fitness tests among participants aged 6–11, 12–19, 20–64 and 65–79 years were different. Therefore, it was not possible to investigate physical fitness values in line with the continued growth and development of participants aged 6–17 years, although among individuals aged 6–79 years, GS, SU and SR were performed similarly. Therefore, the national average values for GS, SU and SR physical fitness tests in 2008 (Statistics of Japan “e-Stat”; Portal site for Japanese Government statistics, 2009) and 2018 (Statistics of Japan “e-Stat”; Portal site for Japanese Government statistics, 2019) were also overlaid with the survey values conducted in Nagano Prefecture (Table 2, Figures 1–3).
The ratio of boys to girls was approximately 50/50. Physical fitness was measured using the Ministry of Education, Culture, Sports, Science, and Technology physical fitness test for individuals aged 65–79 years was carried out in consideration of the safety of the participants. The fitness test includes: 1) grip strength for muscle strength (GS; kg), 2) sit-ups for muscle endurance (SU; times), 3) sit-and-reach flexibility for muscle flexibility (SR; cm), 4) eyes-open single-leg stance for balance (EO; s), 5) 10-m obstacle walk for walking ability (10M; s), and 6) 6-min walk for endurance (6M; m) (Monbushou [MEXT: Ministry of Education, Culture, Sports, Science and Technology, Japan], 2000).
Procedures of this study involving experiments on human participants are done in accord with the ethical standards of the Committee on Human Experimentation of the institution in which the experiments were done or in accord with the Declaration of Helsinki of 1964 and its later amendments or comparable ethical standards.
The participation in this study was voluntary and non-participation had no adverse effects. Even if the parents agreed to participate, they could withdraw at any time. After receiving a detailed explanation of the study, parents agreed that their children will participate. The parents of participants were informed about the potential experimental risks and informed consent was obtained according to the policies for human participants at Shinshu University.
They were assured that their data would be strictly managed to ensure privacy. Individuals who had neurological disorders, undergone orthopedic surgery within the last two years, or had a psychiatric disorder were excluded. The parents of each participant were given a detailed explanation of the study and were informed of the potential experimental risks. Written informed consent was obtained in accordance with the policies for human participants at Shinshu University. The Ethics Committee of Shinshu University approved the study protocol (control numbers: 003 and 180; dates of receipt: 7/14/2007 and 4/14/2017).
2.1 Statistical analyses
In this study, the physical fitness of elementary, junior high and high school students aged 6–17 years, who were followed up twice, in 2008 and 2018, in terms of GS, SU, SR, EO, 10M and 6M, were analyzed. The analysis method used a repeated three-way analysis of variance that took into account survey year, gender, and age factors; if a significant interaction was found, a simple main effect of each factor was calculated and investigated. If a significant effect was observed, the Bonferroni method was used for multiple comparisons. The level of significance was set at p < 0.05. Statistical analyses were performed using IBM SPSS Statistics for Windows version 29.
3. Results
3.1 Differences of physical fitness tests on each grade between 2008 and 2018
3.1.1 Relationship with age, gender and age factors based on GS.
The results of GS were good in the order of Nagano in 2008, national average in 2008, national average in 2018, and Nagano in 2018 (Figure 1, Table 3). In GS, a three-factor mixed analysis of variance (ANOVA) for each scale for survey, gender, and age, and the simple interaction effects between survey and gender and between survey and age were not found to be significantly different. However, the main effects of gender and age were significantly different, with multiple comparisons showing 2008 < 2018 (p < 0.001) and boys > girls (p < 0.001). “The main effect'' indicates a significant difference in the mean of the analyzed factor between the levels of the factor. The less-than-sign is a mathematical symbol that denotes the inequality between the two values.
Regarding simple interaction, gender and age were significantly different [F (11,919) = 28.011, p < 0.001, η2 = 0.251], and the main effect of gender was significantly different, with multiple comparisons showing 13–17: boys > girls (p < 0.001).
3.2 Relationship with age, gender and age factors based on SU
SU tended to be better in Nagano in 2008 and 2018 than in 2008 and 2018, the national average. (Figure 2, Table 4). In SU, a three-factor mixed ANOVA for each scale on survey, gender, and age, and the simple interaction effects between survey and gender and between survey and age were not significantly different. However, survey and gender were found to have significantly different main effects, with multiple comparisons showing that 2008 < 2018 (p < 0.001) and boys > girls (p < 0.001). For simple interaction effects, gender and age were significantly different [F (11,914) = 9.864, p < 0.001, η2 = 0.106], and the main effect of gender was significantly different, with multiple comparisons showing 13–17: boys > girls (p < 0.001) and 6: boys < girls (p < 0.001).
3.3 Relationship with age, gender and age factors based on SR
SR tended to be better in Nagano in 2008 and 2018 than in 2008 and 2018 the national average (Figure 3, Table 5). In the SR, a three-factor mixed ANOVA for each scale on survey, gender and age, and the simple interaction effect between survey and gender showed no significant difference. However, the main effect of the survey was significantly different, with multiple comparisons showing 2008 < 2018 (p < 0.001). A significant difference was found in the simple interaction effect between survey and age [F (1, 920) = 3.400, p < 0.001, η2 = 0.039], and between gender and age [F (1, 920) = 2.594, p < 0.003, η2 = 0.030], and the main effect of gender was significantly different, with multiple comparisons showing 17: boys > girls (p < 0.05) and 7–9: boys < girls (p < 0.05).
3.4 Relationship with age, gender and age factors based on EO
EO tended to perform better in 2018 than in 2008 (Figure 4, Table 6). In EO, a three-factor mixed ANOVA for each scale on survey, gender and age, and the simple interaction effects between survey and gender and between survey and age found no significant difference. However, survey and gender were found to have significantly different main effects, with multiple comparisons showing 2008 < 2018 (p < 0.001) and boys < girls (p < 0.001). In simple interaction effects, gender and age were significantly different [F (11,821) = 4.486, p < 0.001, η2 = 0.057], with the main effect of gender found to be significantly different, with multiple comparisons showing 6 and 8–10: boys < girls (p < 0.01).
3.5 Relationship with age, gender and age factors based on 10M
The 10M group was able to walk faster in 2008, except for those aged 10–13 years (Figure 5, Table 7). In the 10M group, a three-factor mixed ANOVA for each scale on survey, gender and age, and the simple interaction effect between survey and gender showed no significant differences. However, the main effect of survey was significantly different, with multiple comparisons showing 2008 < 2018 (p < 0.05) and boys < girls (p < 0.001). Significant differences were found in the simple interaction effect between survey and age [F (11, 820) = 3.274, p < 0.001, η2 = 0.042], and gender and age [F (1, 820) = 4.559, p < 0.001, η2 = 0.058], and the main effect of gender was significantly different, with multiple comparisons showing 12–17: boys < girls (p < 0.05).
3.6 Relationship with age, gender and age factors based on 6M
The 6M group was able to walk faster in 2008, except for those aged 11 and 13 years (Figure 6, Table 8). In the 6M group, a significant difference was found in the three-factor mixed ANOVA for each scale for survey, gender and age [F (11,796) = 3.457, p < 0.001]. Also, both the simple interaction effect between survey and age [F (11, 820) = 8.467, p < 0.001, η2 = 0.102] and gender and age [F (11,820) = 6.827, p < 0.001, η2 = 0.084] were significantly different. The main effects of survey and gender were found to be significantly different, with multiple comparisons showing 6–10, 12, 14–17: 2008 > 2018, and 7,10, 12–17: boys>girls (p < 0.05). However, there was no significant difference in the simple interaction effect between the survey and gender. The main effect of survey was significantly different, with multiple comparisons showing 2008 > 2018 (p < 0.05) and boys > girls (p < 0.001).
4. Discussion
The purpose of this study was to understand the growth process of children’s physical strength, identify areas for improvement, and contribute to high-quality health education for a super-aging society by conducting physical fitness measurements in children aged 6–17 years. The physical fitness tests revealed that 10M and 6M results in 2018 were significantly inferior to those in 2008. In addition, the study demonstrated that boys performed significantly better than girls 10M and 6M tests. Based on these findings, the study authors recommend focusing on training lower limb muscle strength, especially for girls, and acquiring the ability to walk quickly with balance in Japanese children aged 6–17 years. The study results may be related to the gradual decrease in the number of steps taken by Japanese children. In 1979, the number of steps per day taken by children aged 6–12 years was approximately 20,000 (Hatano, 1979), which reportedly decreased to 12,000–16,000 in around 2010 (Nakamura, 2004; Tokyo Metropolitan Board of Education, 2012). This decrease in the number of steps taken by children may be related to lack of exercise. Similar declines in leg muscle strength were also noted in Slovenia between 1983 and 2014 (Đurić et al., 2021). A decline in 20 m shuttle run test performance was reported in 11 countries from 1981 to 2000 (Tomkinson et al., 2003). Physical inactivity is also a global phenomenon, with the WHO citing a 15% decline by 2030, with 81% of children aged 11–17 years failing to meet the WHO-recommended 60 min of moderate to vigorous physical activity (WHO: World Health Organization, 2015a). When analyzed by walking ability and endurance, 10M, and 6M performances were better in 2008 than in 2018, whereas EO was performed longer in 2018 than in 2008. In the gender-specific analysis, boys outperformed girls in GS, SU, 10M and 6M tests, whereas girls outperformed boys in EO test. In 2008, boys exhibited well-developed characteristics necessary for muscle strength, muscle endurance, walking ability, and endurance. In contrast, girls demonstrated well-developed elements of balance ability and flexibility. This may be attributed to the significantly larger biceps and vastus lateralis muscles in men than in women (Miller et al., 1993). In Canada, boys were significantly better than girls in 10M and agility tests. In the USA, boys demonstrated significant superior muscle strength, including grip strength and pull-ups, than that of girls (Laurson et al., 2017). Moreover, in Turkey, girls exhibited significantly better flexibility than that of boys (Saygin et al., 2007), and in Europe, girls aged 6–11 years exhibited significantly better balance ability and flexibility than those of boys (De Miguel-Etayo et al., 2014), which is similar to the results of the present study. Physical fitness is closely related to health; therefore, maintenance and improvement of physical strength in a well-balanced manner is desirable. However, it is also necessary to recognize the characteristics of men and women, and make recommendations accordingly.
5. Limitations
Most of the junior and senior high school students who participated in the EO test exceeded the upper limit of 120 s, suggesting that the load of the measurement method is low and improvement is necessary. In 2018, a large variation in 6M results was observed among participants, possibly due to the differences in the level of seriousness during the 6M test. Therefore, to ensure that junior and senior high school students properly perform the EO and 6M tests, it is necessary to devise an effective method of implementation, such as changing the physical fitness test load.
6. Conclusion
This study suggests that, in addition to improving the health of the elderly, promoting early health education may be one way to cope with a super-aging society. Joint research between Shinshu University, Mahidol University, Southwestern University and Udayana University was utilized for HESU health education in Nagano Prefecture of Japan; the Saraya region, Thailand; the Cebu region, Philippines; and the Bali region, Indonesia. This study aimed to improve the health level and productivity of the community by providing equal health education across regions and races. Through this process, aiming for educational practices, including early HESU health education, we adopted a method that complied with ISO evaluation standards, compared the physical fitness survey which was conducted in 2008 for children aged 6–17 years and repeated 10 years later in 2018. This study aimed to promote early health education and anticipate the continued maintenance and promotion of children’s health until they reach old age. In addition, we sought to explore the potential for implementing health education programs as a new social context to promote race equality and human rights in health and social care. The purpose of this study was to compare the results of the children’s physical fitness survey, understand the actual situation, identify areas of improvement and improve the health level of children, which will ultimately lead to the extension of healthy life expectancy.
The results of the physical fitness tests revealed that 10M and 6M tests in 2018 were significantly inferior to those in 2008. In gender-specific analysis, boys outperformed girls in GS, SU, 10M and 6M tests, whereas girls outperformed boys in EO test. Boys exhibited more developed muscle strength, muscle endurance, walking ability and endurance, while girls exhibited more developed balance ability. Physical fitness is closely associated with health. To consider the social determinants of health equity and appropriately propose health education, it is desirable to consider the differences in characteristics between boys and girls and maintain and improve physical fitness in a well-balanced manner.
The physical fitness measurement of children aged 6–17 years conducted in this survey, provides valuable data that is unprecedented worldwide. The health-related fitness data in this manuscript focuses on medical and social care and proposes a new concept of early health education aimed at extending healthy life expectancy, promoting racial equality and respecting human rights. In addition, involving victims, perpetrators and local residents, we explored the possibility of using restorative justice to address cultural, social and political prejudices against specific individuals and groups in hate crimes targeting women and minorities. Furthermore, the physical fitness results described in this study can be internationally applied to comparative studies, systematic evaluation of interventions, analysis of qualitative data and study of health and social care institutions and the political process.
Figures
Figure 1
Hand grip strength
Figure 2
Sit-ups
Figure 3
Sit and reach flexibility
Figure 4
Eyes open single leg stance
Figure 5
10-m obstacle walk
Figure 6
A 6-min walk
Participants in 2008 and 2018
| Sex/age | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | Total |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Boys in 2008 | 16 | 18 | 17 | 14 | 17 | 13 | 19 | 18 | 19 | 23 | 21 | 22 | 266 |
| Girls in 2008 | 21 | 19 | 16 | 16 | 18 | 18 | 20 | 21 | 17 | 20 | 20 | 22 | 285 |
| Total in 2008 | 37 | 37 | 33 | 30 | 35 | 31 | 39 | 39 | 36 | 43 | 41 | 44 | 551 |
| Boys in 2018 | 19 | 13 | 12 | 14 | 8 | 11 | 18 | 20 | 18 | 42 | 41 | 45 | 295 |
| Girls in 2018 | 17 | 14 | 14 | 11 | 12 | 9 | 21 | 20 | 20 | 38 | 40 | 33 | 293 |
| Total in 2018 | 36 | 27 | 26 | 25 | 20 | 20 | 39 | 40 | 38 | 80 | 81 | 78 | 588 |
Source: Table by authors
In 2008 and 2018, the number of participants for each age group who performed GS, SU and SR, respectively
| Event/age | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | Total |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| In 2008 | |||||||||||||
| GS | 2,204 | 2,261 | 2,209 | 2,248 | 2,223 | 2,240 | 2,204 | 2,808 | 2,806 | 2,840 | 2,855 | 2,855 | 29,753 |
| SU | 2,200 | 2,223 | 2,219 | 2,252 | 2,228 | 2,252 | 2,807 | 2,814 | 2,814 | 2,852 | 2,850 | 2,864 | 30,375 |
| SR | 2,216 | 2,242 | 2,205 | 2,239 | 2,216 | 2,242 | 2,800 | 2,816 | 2,814 | 2,854 | 2,852 | 2,866 | 30,362 |
| In 2008 | |||||||||||||
| GS | 2,294 | 2,251 | 2,209 | 2,248 | 2, 223 | 2,240 | 2,763 | 2,771 | 2,778 | 2,832 | 2,859 | 2,842 | 28,087 |
| SU | 2,200 | 2,223 | 2,222 | 2,252 | 2,220 | 2,218 | 2,755 | 2,765 | 2,782 | 2,841 | 2,843 | 2854 | 30,175 |
| SR | 2,216 | 2,242 | 2,205 | 2,239 | 2,231 | 2,226 | 2,758 | 2,776 | 2,783 | 2,849 | 2,848 | 2,860 | 30,233 |
Source: Table by authors
Comparison of GS in 2008 and 2018
| ANOVA | ||||||
|---|---|---|---|---|---|---|
| Event | Source | df | F | P | ηp2 | Multiple comparison |
| GS. | Survey | 1 | 3.611 | 0.058 | 0.004 | |
| Gender | 1 | 80.031 | 0.001 | 0.078 | Boys>girls | |
| Survey×gender | 1 | 0.026 | 0.872 | 0.000 | ||
| Suvey | 1 | 19.531 | 0.001 | 0.021 | 2008 < 2018 | |
| Age | 11 | 176.734 | 0.001 | 0.679 | 6 < 9 - 17, 7 - 8 < 10 - 17, 9 < 11–17, 10 - 11 < 12 - 17, 12 < 13 - 17, 13 < 14 - 17, 14 < 16 - 17, 15 < 17 | |
| Survey×age | 11 | 0.825 | 0.615 | 0.010 | ||
| Gender | 1 | 163.615 | 0.001 | 0.151 | 13 - 17: boys>girls, | |
| Age | 11 | 288.079 | 0.001 | 0.775 | Boys: 6 - 7 < 9–17, 8 < 10 - 17, 9 < 11 - 17, 10 < 12 - 17, 11 - 12 < 13 - 17, 13 < 14 - 17, 14 - 15 < 16 - 17 | |
| Gender × age | 11 | 28.011 | 0.001 | 0.251 | Girls: 6 < 9 - 17, 7 < 11 - 17, 8 < 10 - 17, 9 - 11 < 12, 12 < 15 - 17 | |
| Survey × age × gender | 11 | 0.944 | 0.479 | 0.010 | ||
Source: Table by authors
Comparison of SU in 2008 and 2018
| ANOVA | ||||||
|---|---|---|---|---|---|---|
| Event | Source | df | F | p | ηp2 | Multiple comparison |
| SU | Survey | 1 | 17.173 | 0.001 | 0.018 | 2008 < 2018 |
| Gender | 1 | 55.138 | 0.001 | 0.056 | boys>girls | |
| Survey × gender | 1 | 1.211 | 0.217 | 0.001 | ||
| Suvey | 1 | 0.264 | 0.608 | 0.000 | ||
| Age | 11 | 104.696 | 0.001 | 0.558 | 6 < 8 - 17, 7 < 9 - 17, 8 < 10 - 17, 9 < 12 - 17, 10 - 12 < 13 - 17, 13 < 16 - 17, 14 < 17, 15 < 16 - 17 | |
| Survey × age | 11 | 1.449 | 0.146 | 0.017 | ||
| Gender | 1 | 77.046 | 0.001 | 0.078 | 13 - 17: boys>girls, 6: boys<girls | |
| Age | 11 | 137.729 | 0.001 | 0.615 | boys: 6 < 7 - 17, 7–8 < 10–17, 9 - 12 < 13 - 17, 13 < 17, 15 < 16 - 17 | |
| Gender × age | 11 | 9.864 | 0.001 | 0.106 | girls: 6 < 12 - 17, 7 < 9 - 17, 8 - 9 < 12 - 17, 10 < 13 - 17, 11 < 14 - 17, 12 - 13 < 16 - 17, 15 < 16 - 17 | |
| Survey × age × gender | 11 | 1.149 | 0.320 | 0.014 | ||
Source: Table by authors
Comparison of SR in 2008 and 2018
| Event | Source | ANOVA | ||||
|---|---|---|---|---|---|---|
| df | F | p | ηp2 | Multiple comparison | ||
| SR | Survey | 1 | 19.159 | 0.001 | 0.020 | 2008 < 2018 |
| Gender | 1 | 0.358 | 0.550 | 0.000 | ||
| Survey × gender | 1 | 1.449 | 0.146 | 0.017 | ||
| Suvey | 1 | 0.152 | 0.697 | 0.000 | ||
| Age | 11 | 100.035 | 0.001 | 0.545 | 2008: 6 < 10 - 17, 7 < 11–17, 8 - 11 < 12–17, 13 < 17 | |
| Survey × age | 11 | 3.400 | 0.001 | 0.039 | 2018: 6 - 11 < 12 - 17, 12 < 13–17, 13 < 17 | |
| Gender | 1 | 7.118 | 0.008 | 0.008 | 17: boys>girls | |
| Age | 11 | 103.684 | 0.001 | 0.554 | 7 - 9: boys<girls, | |
| Gender × age | 11 | 2.594 | 0.003 | 0.030 | boys: 6 < 8 - 17, 7 < 10, 12 - 17, 8 < 10 - 17, 9 - 11 < 12 - 17, 12 < 16–17, 13 - 15 < 17 | |
| Survey × age × gender | 11 | 0.808 | 0.632 | 0.010 | girls: 6 < 11 - 17, 7 - 10 < 12 - 17, 11 < 13–17, 12 < 16 - 17, 15 < 17 | |
Source: Table by authors
Comparison of EO in 2008 and 2018
| Event | Source | ANOVA | ||||
|---|---|---|---|---|---|---|
| df | F | p | ηp2 | Multiple comparison | ||
| EO | Survey | 1 | 27.756 | 0.001 | 0.032 | 2008 < 2018 |
| Gender | 1 | 18.390 | 0.001 | 0.021 | boys<girls | |
| Survey × gender | 1 | 0.493 | 0.483 | 0.001 | ||
| Suvey | 1 | 21.791 | 0.001 | 0.026 | 2008 < 2018 | |
| Age | 11 | 27.440 | 0.001 | 0.269 | 6 < 8, 10 - 17, 7 < 10 - 17, 8 < 12 - 17, 9 < 11 - 17, 10 < 15 - 17, 11 < 17 | |
| Survey × age | 11 | 1.293 | 0.223 | 0.017 | ||
| Gender | 1 | 33.782 | 0.001 | 0.040 | 6, 8 - 10: boys<girls, | |
| Age | 11 | 30.181 | 0.001 | 0.288 | boys: 6 < 8, 10 - 17, 7, 9 < 11 - 17, 8 < 12 - 17, 10 < 12 - 13, 15 - 17 | |
| Gender × age | 11 | 4.486 | 0.001 | 0.057 | girls: 6–7 < 10, 12–17, 9 < 17 | |
| Survey × age × gender | 11 | 0.890 | 0.550 | 0.012 | ||
Source: Table by authors
Comparison of 10M in 2008 and 2018
| ANOVA | ||||||
|---|---|---|---|---|---|---|
| Measurements | Source | df | F | P | ηp2 | Multiple comparison |
| 10M | Survey | 1 | 6.030 | 0.014 | 0.007 | 2008<2018 |
| Gender | 1 | 80.774 | 0.001 | 0.088 | boys<girls | |
| Survey × gender | 1 | 1.277 | 0.259 | 0.002 | ||
| Suvey | 1 | 11.077 | 0.001 | 0.013 | 8-9, 14: 2008<2018, 13: 2008>2018 | |
| Age | 11 | 21.865 | 0.001 | 0.227 | 2008: 6>9-17, 7>9-10, 12, 14-17, 8>9, 14, 16 | |
| Survey × age | 11 | 3.274 | 0.001 | 0.042 | 2018: 6, 8>9-17, 7>10-13, 15-17, 13>17 | |
| Gender | 1 | boys: 6-7>9-17, 8>10, 12-17, 9>16-17 | ||||
| Age | 11 | girls: 6>9-17, 7>9-10, 8>9-10, 12-14, 16, 10>17 | ||||
| Gender × age | 11 | 4.559 | 0.001 | 0.058 | 12-17: boys<girls, | |
| Survey × age × gender | 11 | 1.058 | 0.393 | 0.014 | ||
Source: Table by authors
Comparison 6M in 2008 and 2018
| ANOVA | ||||||
|---|---|---|---|---|---|---|
| Measurements | Source | df | F | p | ηp2 | Multiple comparison |
| 6M | Survey | 1 | 191.707 | 0.001 | 0.186 | 2008>2018 |
| Gender | 1 | 205.649 | 0.001 | 0.197 | boys>girls | |
| Survey × gender | 1 | 0.868 | 0.352 | 0.001 | ||
| Suvey | 1 | 158.107 | 0.001 | 0.162 | 6-10, 12, 14-17: 2008>2018 | |
| Age | 11 | 15.198 | 0.001 | 0.169 | 2008: 6<10, 7, 9, 10>15, 17, 9-10<15, 17 | |
| Survey × age | 11 | 8.467 | 0.001 | 0.102 | 2018: 6-8<10-11, 13, 9<11, 9>12, 14, 17, 10>12, 14-16, 11>12, 14-17, 12>13, 15-16, 13>14-17 | |
| Gender | 1 | 163.837 | 0.001 | 0.167 | ||
| Age | 11 | 16.859 | 0.001 | 0.184 | boys: 6<9-11, 13, 15-16, 7<13, 8<10, 13, 10-11>12, 17, 12<13, 13>14-17, 15>17, 16>17 | |
| Gender × age | 11 | 6.827 | 0.001 | 0.084 | girls: 6<10-11, 6>15, 7>15, 17, 8>15, 9>12, 14-17, 10-11>12, 14-17, 13>15, 17, 15<16 | |
| Survey × age × gender | 11 | 3.457 | 0.001 | 0.046 | 7, 10, 12-17: boys >girls | |
Source: Table by authors
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Further reading
CDC: Centers for Disease Control and Prevention (2024), “Early childhood education”, available at: www.cdc.gov/policy/hi5/earlychildhoodeducation/index.html 〈CDC Archive: archived for historical purposes (Last Reviewed: January 11, 2023)〉 (accessed 9 June 2024).
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Acknowledgements
Funding: Koji Terasawa was supported by a grant-in-aid for scientific research (Kiban A:16H02713) from the Ministry of Education, Culture, Sports, Science and Technology of Japan. The sponsor was not involved in the study design, collection, analysis and interpretation of data, report writing or the decision to submit the article for publication.
Conflict of interest: The authors declare that they have no conflict of interest.
Corresponding author
About the authors
Satomi Fujimori is based at the Faculty of Education, Graduate School of Education, Shinshu University, Nagano, Japan
Kazuki Ashida is based at the Informatics and Electronics, National Institute of Technology, Nagano College, Nagano, Japan
Noriaki Watanabe is based at the Graduate School of Medicine, Science and Technology, Shinshu University – Ueda Campus, Ueda, Japan
Tomoyuki Nishino is based at the Graduate School of Science and Technology, Shinshu University, Ueda, Japan
Fumihito Sasamori is based at the Department of Electrical and Computer Engineering, Graduate School of Engineering, Faculty of Engineering, Shinshu University, Nagano, Japan
Masao Okuhara is based at the Applied Information Engineering, Faculty of Engineering, Suwa University of Science, Chino, Japan
Hisaaki Tabuchi is based at the Department of Psychology, University of Innsbruck, Innsbruck, Austria
Koji Terasawa is based at the Graduate School of Medicine, Shinshu University, Matsumoto, Japan