Preamble

Investigative Study on the Physical Fitness Testing Status of First and Second Year High School Students in Urban and Rural Areas in China

JING Tao¹, DAI Yongmei², LUO Jianying³, CAO Yanjun⁴, LUO Wei¹, PENG Chi⁵, JI Yelinfan⁶, ZHANG Cuijun⁷, HUANG Yu⁸, ZHENG Qing⁹, SHEN Hejun¹⁰*

¹Department of Rehabilitation Therapy, School of Exercise and Health, Nanjing Sport Institute, Nanjing 210014, China
²Nutrition Department, Nanjing Women and Children's Healthcare Hospital/Women's Hospital of Nanjing Medical University, Nanjing 210004, China
³Clinical Nutrition Department, Northern Jiangsu People's Hospital of Jiangsu Province/Clinical Medical School, Yangzhou University, Yangzhou 225001, China
⁴Department of Traditional Chinese Medicine, Shanghai University of TCM Shanghai TCM-Integrated Hospital, Shanghai 200082, China
⁵Nutrition Department, Baoying County Maternal and Child Health Hospital, Yangzhou 225800, China
⁶School of Sports Medicine and Rehabilitation, Beijing Sport University, Beijing 100084, China
⁷Nutrition Department, Yangzhou Maternal and Child Care Service Centre, Yangzhou 225002, China
⁸Department of Physical Education Teaching and Research, Liyang High School of Jiangsu Province, Liyang 213300, China
⁹Department of Physical Education Teaching and Research, Hanjiang High School of Jiangsu Province, Yangzhou 225009, China
¹⁰School of Physical Education and Humanities, Nanjing Sport Institute, Nanjing 210014, China

Corresponding author: SHEN Hejun, Professor; E-mail: 2282315862@qq.com

Abstract

Background Current research on physical fitness test scores among high school students remains largely confined to localized areas within individual provinces and cities, with few large-scale, multicenter studies covering entire regions. The widespread adoption of blended online and offline teaching models across schools has inevitably extended the already lengthy sedentary time for high school students. Whether this trend impacts student physical health requires urgent investigation at a national level.

Objective To investigate and analyze physical fitness test performance and related influencing factors among first- and second-year high school students in urban and rural areas across China's seven major geographic regions, and to identify pathways for balanced improvement in physical fitness levels.

Methods Using stratified random cluster sampling, we conducted a survey from January to March 2019 in high schools across 31 provinces (municipalities and autonomous regions) in seven geographic regions (East China, South China, North China, Central China, Northwest China, Southwest China, and Northeast China). Sampling was stratified by urban districts/counties and townships/villages, with one urban district/county high school and one township/village high school randomly selected from each region, totaling 62 schools. We collected physical fitness test data from 42,523 first- and second-year high school students. Test indicators included: BMI (physical development), lung capacity (physiological function), sit-and-reach (flexibility), pull-ups and 50-meter run and standing long jump (explosive strength of upper and lower limbs), 1-minute sit-ups (core strength), and 800-meter/1000-meter runs (cardiorespiratory endurance). Non-parametric tests and multiple linear regression analysis were used to explore influencing factors.

Results The median age of the 42,523 students was 16.00 (16.00, 17.00) years; 20,074 (47.2%) were male and 22,449 (52.8%) female; 21,725 (51.1%) were from urban districts/counties and 20,798 (48.9%) from townships/villages. Significant differences existed in gender and urban-rural distribution across the seven regions (P<0.05). For male students, all physical fitness test scores differed significantly across regions (P<0.05), with the top three regions for each indicator being: height (North China > Northeast China > Central China), body mass (Northeast China > North China > Central China), BMI (Central China > Northeast China > North China), lung capacity (Northeast China > Central China > South China), 50-meter run (South China > Central China > East China), standing long jump (South China > North China > Northwest China), sit-and-reach (South China > Southwest China > Central China), pull-ups (South China > Southwest China > Northwest China), and 1000-meter run (South China > Central China > Southwest China). Urban male students showed higher lung capacity but lower scores in 50-meter run, standing long jump, sit-and-reach, pull-ups, and 1000-meter run compared to their rural counterparts (P<0.001). For female students, all test scores also differed significantly across regions (P<0.05), with top three regions being: height (North China > Northeast China > Northwest China), body mass (Northeast China > North China > Northwest China), BMI (Northeast China > North China > Northwest China), lung capacity (Northeast China > South China > Central China), 50-meter run (South China > Central China > East China), standing long jump (South China > North China > Central China), sit-and-reach (Northeast China > Central China > South China), 1-minute sit-ups (North China > Central China = Southwest China > East China), and 800-meter run (Northeast China > Central China > South China). Urban female students had higher height, body mass, and BMI scores, but lower lung capacity, 50-meter run, standing long jump, sit-and-reach, 1-minute sit-ups, and 800-meter run scores than rural females (P<0.001). Multiple linear regression showed that for males, pull-up scores were negatively correlated with BMI and 1000-meter run scores, and positively correlated with 50-meter run, standing long jump, and sit-and-reach scores (P<0.05), with sit-and-reach being the strongest predictor, followed by 1000-meter run. Male 1000-meter run scores were negatively correlated with BMI and pull-up scores, and positively correlated with 50-meter run, standing long jump, and sit-and-reach scores (P<0.05), with pull-ups being the strongest predictor, followed by sit-and-reach. For females, 1-minute sit-up scores were positively correlated with BMI, lung capacity, standing long jump, and 800-meter run scores, and negatively correlated with 50-meter run and sit-and-reach scores (P<0.05), with BMI being the strongest predictor, followed by sit-and-reach. Female 800-meter run scores were negatively correlated with BMI, 50-meter run, and sit-and-reach scores, and positively correlated with standing long jump and 1-minute sit-up scores (P<0.05), with sit-and-reach being the strongest predictor, followed by BMI.

Conclusion Urban male students showed comparable physical development levels to rural males, while urban female students demonstrated higher physical development than their rural counterparts. However, urban students of both genders exhibited significantly lower explosive strength of upper and lower limbs, core strength, and cardiorespiratory endurance compared to rural students. Apart from physical development indicators, male students in South China showed clear advantages across multiple physical fitness tests. BMI emerged as a primary factor influencing cardiorespiratory endurance and strength levels in both genders.

Keywords High school student; Physical fitness testing; Urban and rural areas; Cardiopulmonary endurance; Explosive power; Core strength

Main Text

The importance of physical fitness among high school students cannot be overstated. For college-bound students, physical fitness represents a crucial indicator of quality education, and consciously cultivating their interest and health awareness in sports activities will contribute significantly to their physical and mental well-being. However, current pass and excellence rates in physical fitness testing among Chinese high school students remain unsatisfactory. Given China's vast territory and significant population distribution differences, physical fitness levels vary across regions and genders. Existing research primarily reflects the status of high school students within smaller provincial or municipal areas, with few multicenter, large-scale studies. Notably, a single national retrospective study on physical fitness pass and excellence rates among Han Chinese adolescents aged 13-18 did not report individual test item scores, and its timeliness cannot represent recent trends.

Concurrently, Chinese high school students face widespread physical inactivity, declining muscular strength and cardiorespiratory endurance, and persistently increasing myopia rates—factors that have become primary concerns affecting adolescent health. Physical fitness levels also correlate with sleep disorders and depression. Importantly, while older adolescents maintain positive attitudes toward exercise, the proliferation of online video instruction has exacerbated sedentary behavior, posing long-term health consequences.

Currently, a gap exists between the physical fitness pass and excellence rates of Chinese middle school students and the targets set forth in the "Healthy China 2030" planning outline. The 14th Five-Year Plan period represents a critical time for achieving these targets, making comprehensive investigation of high school students' physical fitness levels an essential prerequisite. This large-scale study of first- and second-year high school students across urban and rural areas in seven geographic regions provides valuable empirical evidence for improving adolescent physical fitness.

1.1 Study Population

Using stratified random cluster sampling, we selected 62 schools from 31 provinces (municipalities and autonomous regions) across seven geographic regions from January to March 2019. Sampling was stratified by urban districts/counties and townships/villages, with one urban and one rural high school randomly selected from each region, yielding a total of 62 schools. We surveyed 42,523 first- and second-year high school students (aged 14-18, healthy and able to complete physical fitness tests) and collected their test scores. The geographic distribution included 6 schools in Northeast China, 10 in Northwest China, 10 in Southwest China, 14 in East China, 6 in South China, 10 in North China, and 6 in Central China. This study complied with the Human Subjects Ethics Committee charter of Nanjing Sport Institute (approval number: RT-2021-05), and all participating students provided informed consent for anonymous data collection.

1.2.1 Physical Fitness Testing and Measurement Standards

The 62 participating schools conducted tests according to the Ministry of Education's "National Student Physical Fitness Standards (2014 Revision)" and the 2020 National Physical Exercise Standards Work Guidance Manual.

1.2.2 Physical Fitness Measurement Items

Measurements included: (1) height and weight for BMI calculation (kg/cm²); (2) lung capacity (mL); (3) 50-meter run (s); (4) standing long jump (cm); (5) sit-and-reach (times/min); (6) 1-minute sit-ups for females (times); (7) 800-meter run for females (min); (8) pull-ups for males (times); and (9) 1000-meter run for males (min). These indicators reflect physical development (BMI), physiological function (lung capacity), flexibility (sit-and-reach), explosive strength of upper and lower limbs (pull-ups, 50-meter run, standing long jump), core strength (1-minute sit-ups), and cardiorespiratory endurance (800m/1000m runs). Note that shorter times indicate better performance for running events.

1.2 Quality Control

Physical education teachers from the 62 participating schools, all rigorously trained, served as test administrators and were responsible for data collection and database establishment. Strict double-entry verification procedures were implemented, and data with obvious outliers were excluded according to predefined criteria.

1.3 Statistical Methods

Original data were imported into SPSS 25.0. The Kolmogorov-Smirnov test assessed normality of continuous variables. Non-normally distributed continuous variables were expressed as median (P25, P75) and analyzed using non-parametric tests: Mann-Whitney U test for two-group comparisons and Kruskal-Wallis H test for multi-group comparisons. Gender and urban-rural composition ratios across regions were expressed as percentages and compared using chi-square tests. Multiple linear regression analysis, controlling for confounding variables and calculating variance inflation factors (VIF) to assess multicollinearity, was used to identify influencing factors. Statistical significance was set at P<0.05.

2.1 Demographic Characteristics

Among the 42,523 students, the median age was 16.00 (16.00, 17.00) years; 20,074 (47.2%) were male and 22,449 (52.8%) female; 21,725 (51.1%) were from urban districts/counties and 20,798 (48.9%) from townships/villages. Regional distribution was: East China (8,015; 18.8%), South China (3,939; 9.3%), North China (4,083; 9.6%), Central China (4,309; 10.1%), Northwest China (3,856; 9.1%), Southwest China (12,659; 29.8%), and Northeast China (5,662; 13.3%). Significant differences existed in gender and urban-rural distribution across regions (P<0.05) (Table 1).

2.2.1 Regional Comparisons for Male Students

Significant differences existed across all physical fitness test scores among male students from the seven regions (P<0.05). Rankings from highest to lowest were: height (North China > Northeast China > Central China > Northwest China > East China > South China > Southwest China); body mass (Northeast China > North China > Central China > Northwest China > East China > South China > Southwest China); BMI (Central China > Northeast China > North China > South China > East China > Northwest China > Southwest China); lung capacity (Northeast China > Central China > South China > North China > Northwest China > East China > Southwest China); 50-meter run (South China > Central China > East China > North China > Northwest China > Southwest China > Northeast China); standing long jump (South China > North China > Northwest China > East China = Central China > Southwest China > Northeast China); sit-and-reach (South China > Southwest China > Central China > Northwest China > East China > North China > Northeast China); pull-ups (South China > Southwest China > Northwest China > Central China > Northeast China > North China > East China); and 1000-meter run (South China > Central China > Southwest China > North China > Northwest China > East China > Northeast China) (Table 2).

2.2.2 Urban-Rural Comparisons for Male Students

No significant differences existed in height, body mass, or BMI between urban and rural male students (P>0.05). However, urban males showed higher lung capacity but lower scores in 50-meter run, standing long jump, sit-and-reach, pull-ups, and 1000-meter run compared to rural males (P<0.001) (Table 3).

2.2.3 Regional Comparisons for Female Students

Significant differences existed across all physical fitness test scores among female students from the seven regions (P<0.05). Rankings were: height (North China > Northeast China > Northwest China > Central China > East China > Southwest China > South China); body mass (Northeast China > North China > Northwest China > Central China > East China > Southwest China > South China); BMI (Northeast China > North China > Northwest China > Southwest China > East China > Central China > South China); lung capacity (Northeast China > South China > Central China > East China > Northwest China > North China > Southwest China); 50-meter run (South China > Central China > East China > Southwest China > Northwest China > North China > Northeast China); standing long jump (South China > North China > Central China > East China > Southwest China > Northwest China > Northeast China); sit-and-reach (Northeast China > Central China > South China > East China > Southwest China > Northwest China > North China); 1-minute sit-ups (North China > Central China > East China = Southwest China > South China > Northwest China > Northeast China); and 800-meter run (Northeast China > Central China > South China > Southwest China > Northwest China > East China > North China) (Table 4).

2.2.4 Urban-Rural Comparisons for Female Students

Urban female students showed higher height, body mass, and BMI scores but lower lung capacity, 50-meter run, standing long jump, sit-and-reach, 1-minute sit-ups, and 800-meter run scores compared to rural females (P<0.001) (Table 5).

2.3.1 Influencing Factors for Male Pull-ups and 1000-meter Run

Based on the two bonus-point indicators, multiple linear regression analysis was conducted with pull-ups and 1000-meter run scores as dependent variables and BMI, lung capacity, 50-meter run, standing long jump, and sit-and-reach scores as independent variables, controlling for region and urban-rural distribution. Results showed pull-up scores were negatively correlated with BMI and 1000-meter run scores, and positively correlated with 50-meter run, standing long jump, and sit-and-reach scores (P<0.05). Sit-and-reach showed the highest standardized regression coefficient (β), representing the strongest influence, followed by 1000-meter run. The 1000-meter run scores were negatively correlated with BMI and pull-up scores, and positively correlated with 50-meter run, standing long jump, and sit-and-reach scores (P<0.05). Pull-ups showed the highest β value, representing the strongest influence, followed by sit-and-reach (Table 6).

2.3.2 Influencing Factors for Female Sit-ups and 800-meter Run

Multiple linear regression analysis with 1-minute sit-ups and 800-meter run scores as dependent variables showed sit-up scores were positively correlated with BMI, lung capacity, standing long jump, and 800-meter run scores, and negatively correlated with 50-meter run and sit-and-reach scores (P<0.05). BMI showed the highest β value, representing the strongest influence, followed by sit-and-reach. The 800-meter run scores were negatively correlated with BMI, 50-meter run, and sit-and-reach scores, and positively correlated with standing long jump and 1-minute sit-up scores (P<0.05). Sit-and-reach showed the highest β value, representing the strongest influence, followed by BMI (Table 7).

These findings indicate that urban male students' physical development (height, body mass, BMI) is comparable to rural males, while urban female students' physical development exceeds that of rural females. However, urban students of both genders demonstrate significantly lower explosive strength of upper and lower limbs, core strength, and cardiorespiratory endurance than rural students. Notably, male students in South China show distinct advantages across multiple physical fitness domains beyond basic physical development.

Discussion

3.1 Differences in Urban-Rural Education and Community Environments

Our results reveal complex relationships between urban-rural settings and physical fitness. Urban male students exhibited higher lung capacity but inferior performance in speed, power, flexibility, and endurance compared to rural males. Urban female students showed greater physical development but lower functional fitness across most domains. These patterns align with previous research indicating that urban youth are less likely to meet physical fitness standards than their rural peers.

Multiple factors contribute to these disparities. Community environments and sports facilities correlate with residents' physical activity levels, though research on community impacts on adolescent activity requires further investigation. Beyond community factors, schools and families represent primary venues for student physical activity. The availability and accessibility of school sports equipment and facilities significantly influence participation levels and effectiveness.

Urban students face unique challenges: lower overall activity levels, limited after-school activity time, and restricted autonomous movement due to urban infrastructure. Conversely, rural students often have more accessible spaces for activity. Within limited school physical education hours, increasing exercise intensity merits consideration. Research from Shanghai suggests that adjusting traditional PE programs to include higher-intensity activities could effectively improve student fitness.

3.2 Regional Geographic and Family Environment Differences

Regional variations in physical fitness are substantial. Male students in Northeast, North, and Central China showed greater physical development than those in Northwest, Southwest, East, and South China, yet demonstrated lower explosive power, flexibility, and endurance. South China males excelled in power, flexibility, and endurance. For females, Northeast, North, and Northwest regions showed higher physical development, while South China females demonstrated superior lower limb explosive power and Northeast females showed greater flexibility and cardiorespiratory endurance but lower core strength.

These regional differences likely stem from diverse natural and built environments. South China's varied topography (mountains, hills, plateaus, plains, karst landscapes, and water bodies) may enhance aerobic capacity adaptation. Family environments also play crucial roles, with parental support significantly influencing student participation. Research involving 2,452 middle school students found that higher maternal occupational status, longer maternal education, and increased parental exercise companionship correlated with healthier BMI and lower myopia rates.

3.3 Policy Support and Physical Fitness

According to Ministry of Education requirements, the 1000-meter run (male), 800-meter run (female), pull-ups (male), and 1-minute sit-ups (female) carry bonus points (10 points each, with 20 points maximum per item, representing 20% weighting each). This underscores the importance of cardiorespiratory endurance and fundamental strength. Our regression analysis reveals that male pull-up and 1000-meter run scores are mutually influential, with BMI negatively affecting both. For females, BMI is the primary factor influencing sit-up and 800-meter run performance, negatively impacting cardiorespiratory endurance but positively correlating with core strength.

These findings suggest that lower BMI correlates with better cardiorespiratory endurance, while higher BMI in males reduces upper body strength but increases core strength in females. The interplay among fitness components highlights the need for comprehensive intervention strategies. Achieving Healthy China 2030 targets requires transforming educational approaches—from focusing on testing to emphasizing exercise, from results to process, and from academic achievement to holistic health promotion.

3.4 Limitations

This study has several limitations. First, the anonymous survey of minors prevented collection of complete parental education and income data due to time constraints and privacy protections, limiting demographic correlation analyses. Second, the study focused on first- and second-year students aged 18 and under, excluding third-year students who often exceed 19-20 years of age. Age was calculated by birth year rather than exact date. Finally, logistical constraints prevented simultaneous data collection across all regions, which should be considered when interpreting results.

Conclusion

This large-scale investigation of physical fitness test performance among urban and rural first- and second-year high school students reveals critical patterns. Urban males show comparable physical development to rural males, while urban females exceed rural females in physical development. However, urban students of both genders demonstrate significantly lower explosive strength, core strength, and cardiorespiratory endurance than their rural counterparts. Male students exhibit clear north-south geographic differences, while females show broader regional variations. South China males demonstrate distinct advantages across multiple fitness domains. BMI emerges as a primary factor influencing cardiorespiratory endurance and strength in both genders.

These findings provide empirical support for achieving Healthy China 2030 objectives during the 14th Five-Year Plan period. Despite widespread fitness testing, declining student physical fitness trends persist, necessitating enhanced attention from schools and families. For minors who represent China's future, establishing proper health perspectives and recognizing the importance of physical activity for long-term health is a societal responsibility. Schools and parents must help students develop healthy lifestyles and habits, shifting focus from testing to genuine physical engagement.

Funding: National Social Science Fund "13th Five-Year Plan" 2019 Education Science Project (BLA190212)

Author Contributions: JING Tao conceptualized and designed the study, created figures, performed statistical analysis, and wrote the manuscript. DAI Yongmei, LUO Jianying, CAO Yanjun, LUO Wei, JI Yelinfan, and PENG Chi contributed to feasibility analysis and literature collection. ZHANG Cuijun participated in data interpretation. HUANG Yu and ZHENG Qing supervised training, implementation, and data collection across regions. SHEN Hejun oversaw study implementation, quality control, and manuscript review, assuming overall responsibility.

Conflict of Interest: The authors declare no conflicts of interest.

ORCID: JING Tao: https://orcid.org/0009-0001-5169-0115

References

[1] SONG Yi, LUO Dongmei, HU Peijin, et al. Trend analysis of physical fitness standard excellence rates among 13-18-year-old Han Chinese middle school students from 1985 to 2014[J]. Journal of Peking University (Health Sciences), 2020, 52(2): 317-322.

[2] WANG Qiongqiong. Research on high school students' physical fitness in physical education[J]. Teaching Management and Education Research, 2020(3): 13-15.

[3] CHEN S T, LIU Y, TREMBLAY M S, et al. Meeting 24-h relationships with overweight and obesity among Chinese children and adolescents[J]. Journal of Sport and Health Science, 2021, 10(3): 349-359.

[4] CHU-KO F, CHONG M L, CHUNG C J, et al. Exploring the factors related to adolescent health literacy, health-promoting lifestyle profile, and health status[J]. BMC Public Health, 2021, 21(1): 2196.

[5] ZHANG Peiyu, XU Jie, ZHANG Wanting, et al. Analysis of health literacy, screen time, and influencing factors among middle school students in Yinchuan[J]. Chinese Journal of School Health, 2021, 42(4): 551-555.

[6] LAN Min, YANG Xubo, LIU Longqian. Comparative study on visual fatigue induced by projection and LCD television[J]. Chinese Journal of Ophthalmology, 2019, 55(8): 595-600.

[7] XU Y T, MEI M R, WANG H, et al. Association between weight status and physical fitness in Chinese mainland children and adolescents: a cross-sectional study[J]. International Journal of Environmental Research and Public Health, 2020, 17(7): 2468.

[8] ZENG Zhuping, WU Huipan, BI Cunjian, et al. Correlation between physical exercise screen time and psychological sub-health among Chinese adolescents[J]. Chinese Journal of School Health, 2021, 42(1): 23-27.

[9] JIANG Y, XU G J. Research on the cultivation path of teenagers' sports health literacy under the background of healthy China[J]. Journal of Healthcare Engineering, 2022, 2022: 3031475.

[10] PAN S H. Research on physical health status and exercise intervention of primary and middle school students in the background of core literacy[J]. International Journal of Frontiers in Medicine, 2020, 2(2): 39-48.

[11] ZHU X H, HAEGELE J A, SUN H C. Health-related fitness knowledge growth in middle school years: individual- and school-level correlates[J]. Journal of Sport and Health Science, 2020, 9(6): 664-669.

[12] TAO Fangbiao. Building a health promotion system for adolescents towards Healthy China 2030[J]. Chinese Journal of School Health, 2023, 44(1): 1-5.

[13] CHAI Hua, JIANG Xiaozhen. Opportunities and challenges for primary and secondary school physical education teachers' professional development under the "Healthy China 2030" planning outline[J]. Journal of Inner Mongolia Normal University (Educational Science Edition), 2018, 31(8): 64-67.

[14] LIANG Fengbo, MAO Zhenming, CHENG Tianyou, et al. "Healthy China 2030" planning outline and school physical education reform policies (3): ensuring at least one hour of daily physical activity at school[J]. Journal of Wuhan Institute of Physical Education, 2018, 52(7): 82-87.

[15] MAO Zhenming, YANG Duoduo, LI Haiyan. "Healthy China 2030" planning outline and school physical education reform policies (2): achieving over 25% excellence rate in the National Student Physical Fitness Standard[J]. Journal of Wuhan Institute of Physical Education, 2018, 52(4): 75-80.

[16] CAI Zhibing, ZHANG Keyun. Research on China's standard regional system division[J]. Academics, 2014(12): 63-83.

[17] WANG Dianli, YU Qi. Structural adjustment of national space: 70 years of changes and functional transformation in China's administrative divisions[J]. Administrative Tribune, 2019, 26(4): 5-12.

[18] YANG Qinjie, ZHUANG Rulong. Knowledge mapping of administrative division research in the past two decades: CiteSpace III analysis based on CSSCI database[J]. World Regional Studies, 2018, 27(1): 141-150.

[19] LIANG Jinshe, LIU Yang. On the classification of Chinese city sizes[J]. Urban Development Studies, 2020, 27(3): 13-18.

[20] YANG Zhen, LEI Jun. Spatiotemporal patterns and influencing factors of urbanization development in Chinese prefecture-level and above cities[J]. Journal of University of Chinese Academy of Sciences, 2019, 36(1): 82-92.

[21] ZENG Lin, TAO Liyuan, ZHAO Yingshuai. Sample size estimation in health management research[J]. Chinese Journal of Health Management, 2021, 15(2): 205-208.

[22] LI Kang, HE Jia. Medical Statistics[M]. 7th ed. Beijing: People's Medical Publishing House, 2018: 168.

[23] Ministry of Education of the People's Republic of China. Notice on issuing the "National Student Physical Fitness Standards (2014 Revision)" (Jiaotiyu [2014] No. 5)[EB/OL]. (2014-07-07)[2022-04-06].

[24] National Sports Bureau Group Department. National Physical Exercise Standards Work Guidance Manual[M]. Beijing: People's Sports Publishing House, 2020.

[25] GE Junbo, XU Yongjian, WANG Chen. Internal Medicine[M]. 9th ed. Beijing: People's Medical Publishing House, 2018: 764.

[26] KE Youzhi. Research on the correlation between socioeconomic level and physical activity among children and adolescents: taking parts of the Yangtze River Delta as an example[D]. Shanghai: Shanghai University of Sport, 2020.

[27] DENG Yanan. Research on shared development of school and community sports facilities in Jinan based on SWOT-PEST model[D]. Jinan: Shandong Sport University, 2019.

[28] CAI Ruijin, XUE Xiaoan, JI Liu, et al. Effects of replacing 10-minute LPA with MPA or VPA on high school students' physical fitness[J]. Journal of Wuhan Institute of Physical Education, 2021, 55(3): 82-91.

[29] CHENG Gang, LU Jiaqi, CHEN Zheng. Research on the influence of family capital on middle school students' physical fitness[J]. Educational Science Research, 2020(11): 44-50, 64.

[30] CHEN Lingling. Investigation on physical fitness status of middle school students in Zhidan County, Yan'an, Shaanxi[J]. Sports Fashion, 2019(6): 282.

[31] LIU Xiaohu. Investigation and analysis of middle school students' physical fitness: taking Wuwei No. 6 Middle School as an example[J]. Science and Education Guide, 2021(3): 191-192.

[32] DA Tingting. Investigation and analysis of physical fitness and sleep quality among junior high school students[J]. Gansu Education, 2019(24): 125.

[33] YANG Tingrui. Reflections on middle school students' physical fitness testing[J]. Contemporary Sports Technology, 2021, 11(12): 253-256.

[34] DU Jianjun. Analysis of intervention effects of cross-theoretical "trinity" physical fitness education model on middle school students' physical fitness[J]. Chinese Health Service Management, 2021, 38(9): 697-700.

[35] LI Junde. Exploration of middle school physical education under the background of physical fitness testing[J]. Education Observation, 2022, 11(17): 109-112.

[36] LIN Zhiping. Reflections on problems existing in middle school students' physical fitness testing[J]. Contemporary Sports Technology, 2020, 10(16): 90-91.

Received: January 6, 2024; Revised: February 4, 2024
Edited by: KANG Yanhui