Which is better for adolescents’ health: "regular exercise" or "weekend warriors"? --A cross-sectional study based on a sample from Tibet

Which is better for adolescents’ health: "regular exercise" or "weekend warriors"? --A cross-sectional study based on a sample from Tibet | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Which is better for adolescents’ health: "regular exercise" or "weekend warriors"? --A cross-sectional study based on a sample from Tibet Feng Peng, Meng Yuan, Bowen Song, Chenyu Liu, Xiaotong Zhang, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7354192/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract OBJECTIVE: The study aims to analyze the distributional characteristics of one-week activity patterns among Tibetan adolescents and to explore the relationship between physical activity patterns and physical health. METHODS: This study employed a stratified cluster sampling method (with a Han-Tibetan ratio of 3:1), recruiting a total of 1275 students from two middle schools in Lhasa. Eventually, 1070 participants who met the criteria were retained. Chi-square test was used to compare the differences in ethnicity in terms of gender, educational stage, and activity patterns. Independent sample t-test was used to compare the differences in social economic status among ethnic groups, while the Mann-Whitney U test was used to analyze the differences in sleep and diet scores . Binary logistic regression was used to analyze the association between the three activity patterns and physical health. RESULTS: “Regular” ( OR =2.103, 95% CI :1.304~3.393, P =0.002) and “bouted” ( OR =3.343, 95% CI :1.628~6.866, P =0.001) were superior to the under-activity mode in enhancing physical health. There is no difference between the two in terms of improving physical health.( P =0.277). In the insufficient pattern group, the probability of reaching a physical health score of 80 gradually increased with the increase in intensity [vigorous physical activity percentage(VPA) and MET]( P trend <0.001; P trend =0.011). CONCLUSIONS: Both “regular” and “bouted” activity patterns have similar effects on improving the health of Tibetan teenagers. For those who lack exercise, it is recommended to adopt a "time + intensity" dual compensation strategy: while ensuring the duration of moderate to high-intensity exercise, the intensity of each session can be moderately increased. children and adolescents physical activity patterns physical health Tibetan 1. Introduction In adolescence period, being actively involved in physical activity (PA) not only strengthens bones [ 1 ] , muscle and cardio-pneumonia function, but also relieves academic stress and lifts mood. Regular physical activity is associated with lower morbidity rates of cardiovascular disease [ 2 ] , type 2 diabetes [ 3 ] , hypertension [ 4 ] , cancer [ 5 ] , obesity [ 6 ] and depression [ 7 ] . The World Health Organization recommends that school-age children should get at least 60 minutes of moderate-intensity physical activity every day of the week [ 8 ] . However, reports show that about 80% of children and adolescents globally do not meet the recommended minimum weekly level of physical activity [ 9 ] . In today's society, people have to cope with fast-paced lives and ever-increasing tasks, which makes regular physical activity become a challenge. As a result, most people choose to do physical activity on weekends, commonly known as "weekend warriors" [ 10 ] , which means completing at least 150 minutes of moderate to vigorous physical activity on 1–2 days of the week. Min et al. [ 11 ] have found that bouted MVPA during 1–2 days per week is associated with a reduced risk of brain disease.White’s et al. [ 12 ] study on children and adolescents found that no significant influence difference in cardiovascular health between regular physical activity and bouted physical activity on weekends when total MVPA was achieved. The health benefits of physical activity derive from a skillful balance of frequency, duration, and intensity. In addition to the frequency and duration of exercise, intensity is also an important indicator to consider. The health benefits of high-intensity exercise outweigh those of moderate-intensity exercise [ 13 ] , in which relationship between physical activity and obesity is particularly strong in adolescents. Studies have found that low body fat percentage is strongly associated with high intensity physical activity, but not with moderate intensity [ 14 ] . Robert Ross' team further revealed a positive correlation between increased exercise intensity and improved cardio-pneumonia function at a fixed amount of exercise [ 15 ] . Currently, factors such as excessive academic burden and extracurricular [ 16 ] tutoring prevent children and adolescents from engaging in regular physical activity, leading to health problems with a high efficiency. In this context, how to flexibly adjust exercise programs and cultivate good exercise habits has become an important issue in the field of physical activity promotion for children and adolescents. Taking adolescents in Tibet as the research object, this study aims to deeply analyze the distribution characteristics of their one-week activity patterns and explore the intrinsic connection between physical activity patterns and physical health, with a wish to provide reference for improving the physical health of adolescents in Tibet. 2. Methods 2.1 Participants This cross-sectional study was conducted in Lhasa from June to December 2020. Two middle schools (Lhasa No. 8 Middle School and Lhasa Middle School) were selected through convenience sampling as research sites. Using random cluster sampling, we recruited Tibetan and Han Chinese student classes across all grade levels. To address the 3:1 ethnic ratio imbalance between Tibetan and Han students in these schools, we randomly selected 3 Tibetan classes and 2 Han classes per grade (with fewer Han students per class). The inclusion criteria were: (1) current enrollment in junior or senior high school; (2) aged 12–18 years; (3) physically healthy without disabilities; and (4) voluntary participation with parental/guardian written informed consent. Enrolled participants received accelerometers and questionnaires to assess daily physical activity (PA), socioeconomic status (SES), and anthropometric measurements. From an initial recruitment of 1,275 students, 19 were excluded due to invalid accelerometer data and 186 for incomplete questionnaires, yielding a final sample of 1,070 eligible participants. The study protocol was approved by the Human Research Ethics Committee of East China Normal University (Approval No. HR 0077-2020), with written informed consent obtained from all participants' parents/guardians. 2.2 Physical Activity The ActiGraph GT3X + accelerometer was used to collect physical activity in this study. During the test, the accelerometer was worn on the right hip for 7 days (including 5 weekdays and 2 rest days), and the device was only allowed to be removed during water activities such as swimming, bathing and showering. The sampling interval was set to 1-second epoch ,which defined 1 day of accelerometer wear time ≥ 600 min as 1 valid day, and at least 4 valid days (3 weekdays + 1 rest day) as the accelerometer wear criteria for analysis.This standard configuration aligns with established research protocols in the field [ 17 ] . Physical activity intensities were classified using research-established cut-points: sedentary (0-100 counts/min), light (101-2,295 counts/min), moderate (2,296-4,011 counts/min), and vigorous (≥ 4,012 counts/min) [ 18 ] .Energy expenditure was calculated using the energy expenditure formula:METs = 2.757+(0.0015×counts/minute)-(0.08957×age)-(0.000038×counts/minute×age )[ 19 ] . 2.3 Physical Health Score In this study, nine indicators were used to evaluate six aspects of adolescent physical health, and the weights of the indicators were differentiated in the evaluation. Specifically, BMI and waist circumference were used to evaluate body composition, with weighting coefficients of 14% and 6%. The grip strength, 30s sit-ups and standing long jump were used to evaluate strength, with weighting coefficients of 5%, 9%, and 10%. The 20-meter shuttle run test was used to evaluate cardiorespiratory endurance, with a 28% weighting coefficient. The 20-second side-step Test was used to evaluate agility and coordination, with an 8% weighting coefficient. The 50m dash was used to evaluate speed, with an 8% weighting coefficient; seated body bends were used to evaluate flexibility, with an 12% weighting coefficient. Each single index was scored out of 100 points, and the scoring was based on the evaluation standards given by existing studies. The total score of physical health was the weighted sum of the scores of each single index: ≥90 points was excellent, 80.0-89.9 points was good, 60.0-79.9 points was passing, and < 60.0 points was failing. Finally, 80 points were used as the line to divide the study subjects into two groups with high and low physical health levels. The study showed that the evaluation standard is systematic, scientific and feasible, and could accurately reflect the physical health level of children and adolescents in China [ 20 ] . 2.4 Delineation of Activity Patterns Activity patterns are categorized based on a weekly MVPA length of 420 minutes. The weekly MVPA duration < 420 min is defined as the insufficient activity pattern; the weekly MVPA duration ≧ 420 min is defined as the "regular" activity pattern and the bouted activity pattern. Regular activity pattern is defined as MVPA of 60 min or more on most days of the week; and bouted activity pattern is defined as MVPA of 60 min or more on only a few days of the week. For days with less than seven (4–6) active days of wear, the median of the active days of wear is used as the cut-off point [ 21 ] . The regularity mode of activity is defined as the number of days with a regular activity pattern of 60 min MVPA > median valid Days. Bouted activity pattern with 60 min MVPA ≤ median effective day. The classification criteria is shown in Table 1 . Table 1 Dividing the length of the activity model Valid day/day Insufficient Activity Pattern Regular Activity Pattern Bouted Activity Pattern 4 - 3–4 1–2 5 - 4–5 1–3 6 - 4–6 1–3 7 - 5–7 1–4 Note: The median effective days are 2.5, 3, 3.5, and 4 days for median values of 4, 5, 6, and 7 days, in that order. 2.5 Socioeconomic Status (SES) The study assessed SES through parental questionnaires evaluating three key dimensions: education, occupation, and income(Details of the questionnaire can be found in the attachment.).Procedures for measuring the three dimensions of SES and their validation have been described elsewhere [ 22 ] . The scoring system was implemented as follows: Parental education was quantified by years of schooling ; Parental occupation was coded using the International Standard Classification of Occupations (ISCO) scale; Monthly household income was categorized into four tiers with corresponding points: ≤2,000 CNY (2 points), 2,001–5,000 CNY (5 points), 5,001–8,000 CNY (8 points), and > 8,000 CNY (10 points). The data processing protocol involved: variable screening/transformation, missing value treatment, standardization of all variables into z-scores, and principal component analysis (PCA) to derive the composite SES index. 2.6 Dietary Habits The study evaluated the dietary habits of the study participants through questionnaires(Details of the questionnaire can be found in the attachment.) on the number of times they ate breakfast in a week, the number of days a week they ate at least one egg, the number of days a week they drank at least one glass of milk, yogurt, or soymilk, and the number of times they usually drank sugary beverages per day in a month, which were calculated using the same methodology as the SES: (1) categorically assign scores to the number of times they ate breakfast, the number of times they ate eggs, and the number of times they drank milk, yogurt, and soymilk (≤ 2 times 1 point; 3–4 times, 2 points; 5–7 times, 3 points); and categorize and assign scores to sugary beverages (1 time or no drink, 3 points; 2–4 times, 2 points; 5 times and above, 1 point); (2) filtering or transforming; (3) deal with the missing values; and (4) convert all the variables into a standardized score and perform a principal component analysis to calculate and get the dietary habits score. 2.7 Sleep Quality In this study, sleep quality was evaluated by the Pittsburgh Sleep Quality Index scale(PSQI) [ 23 ] . The PSQI consists of 19 items that can be categorized into 7 components: subjective sleep quality, time to sleep, sleep duration, sleep efficiency, sleep disorders, hypnotic medication application, and daytime functioning. Each component is scored on a scale of 0–3, and the cumulative score for each component is the total PAQI score, with higher scores indicating poorer sleep quality. The PSQI scores were categorized as 0–5, very good; 6–10 okay; 11–15, fair; and 16–21, very poor. 2.8 Statistical analysis The chi-square test was used to compare the ethnic differences in gender, study stage and activity patterns. Independent samples t-test was used to compare ethnic differences in socioeconomic status, while Mann-Whitney U test was employed to analyze differences in sleep quality scores and dietary habit scores as they violated the normality assumption.The dichotomous classification of physical fitness scores with a cut-off score of 80 is used as the dependent variable. And binary logistic regression is used to analyze the relationship between the insufficient activity pattern, the regular activity pattern, and the bouted activity. 3. Results Table 2 shows the activity distribution model of the participants. Han Chinese adolescents had higher SES (1.42 ± 2.41) and sleep quality scores[4.00(2.00,6.00)] than Tibetan (-1.48 ± 4.04; 3.00(2.00,5.00)), with statistically significant differences (all p < 0.001), and lower eating habit scores (-0.51(-0.82,0.43)) than Tibetan ( 0.43(-0.51,1.38)), and the difference was statistically significant ( p < 0.001). The proportion of insufficient activity patterns (90.2%) was higher in Han Chinese than in Tibetan (83.5%), while the proportion of regular (7.0%) and bouted(2.8%) activity patterns was lower than in Tibetan (11.8%, 4.7%), and the difference was statistically significant (P = 0.006). Table 2 Distributional Characteristics of participants' Activity Patterns Han Chinese Tibetan χ 2 /t/Z P Number Percentage Number Percentage Gender 1.363 0.243 Male 226 48.1% 267 44.5% Women 244 51.9% 333 55.5% Segments 7.734 0.005 Junior High School 156 33.2% 249 41.5% High School 314 66.8% 351 58.5% Socio-Economic Status 1.42 ± 2.41 −1.48 ± 4.04 14.456 < 0.001 Sleep Quality Score 4.00 (2.00,6.00) 3.00 (2.00,5.00) −3.793 < 0.001 Dietary Habits Score −0.51(−0.82,0.43) 0.43(−0.51,1.38) −7.903 < 0.001 Mode of activity 10.137 0.006 Insufficient Activity Patterns 424 90.2% 501 83.5% Regular Activity Patterns 33 7.0% 71 11.8% Bouted Activity Model 13 2.8% 28 4.7% Table 3 shows the relationship between participants' activity patterns and physical health. Adolescents with regular and bouted activity patterns were 2.1 times ( OR = 2.103, 95% CI : 1.304–3.393, P = 0.002) and 3.3 times ( OR = 3.343, 95% CI : 1.628–6.866, P = 0.001) more likely to achieve a fitness level of 80 or higher than those with "insufficient" activity patterns. 1.628–6.866, P = 0.001). There is no significant association between "regular" ( OR = 0.629, 95% CI : 0.273–1.450, P = 0.277) activity and achieving a physical fitness score of 80 compared to "centralized" mode. Table 3 Relationship between Activity Patterns and Physical Health among Adolescents in Tibet Mode of activity Model 1 Model 2 OR (95% CI ) P-value OR (95% CI ) P-value Using the "insufficient" activity model as a reference "Insufficient" Ref - Ref - "Regularity." 1.899 (1.263, 2.855) 0.002 2.103 (1.304, 3.393) 0.002 "Centralized" 3.139 (1.624, 6.068) 0.001 3.343 (1.628, 6.866) 0.001 Using the "Centralized" activity model as a reference "Centralized" Ref - Ref - "Insufficient" 0.319 (0.165, 0.616) 0.001 0.299 (0.146, 0.614) 0.001 "Regularity." 0.605 (0.285, 1.283) 0.190 0.629 (0.273, 1.450) 0.277 Table 4 shows the relationship between MVPA duration and physical health in different activity patterns. In the "insufficient" activity mode group, the probability of reaching a physical health score of 80 increased gradually with the increase in MVPA duration. In the "regular" and "centralized" activity modes, there was no significant change in the probability of reaching a physical fitness score of 80 as the length of MVPA increased. Table 4 Relationship between MVPA and Physical Health in Different Activity Patterns Activity Model Physical Fitness Score Model 1 Model 2 (80 points) OR (95% CI ) P-value OR (95% CI ) P-value "Insufficient" Activity Pattern Q1(≤ 36.9min/day) 25.0% Ref - Ref - Q2(36.9–46.1 min/day) 24.4% 2.688 (1.773,4.074) < 0.001 1.840 (1.157, 2.926) 0.010 Q3(46.1–53.9 min/day) 26.1% 2.683 (1.779,4.046) < 0.001 1.874 (1.183, 2.968) 0.007 Q4 ( ≧ 53.9min/day) 24.5% 4.020 (2.661,6.073) < 0.001 2.128 (1.334, 3.395) 0.002 Trend test P trend < 0.001 0.003 "Regularity" Activity Pattern Q1 (≤ 72.7min/day) 26.0% Ref - Ref - Q2(72.7–78.7 min/day) 19.2% 3.394 (0.996, 11.569) 0.051 3.826 (0.797, 18.362) 0.094 Q3(78.7–87.1 min/day) 29.8% 1.766 (0.622, 5.016) 0.285 1.190 (0.340, 4.157) 0.786 Q4 ( ≧ 87.1min/day) 25.0% 1.697 (0.572, 5.037) 0.341 1.379 (0.330, 5.758) 0.660 Trend test P trend 0.502 0.952 "Centralized" Activity Pattern Q1 (≤ 61.74min/day) 26.8% Ref - Ref - Q2(61.74–64.11 min/day) 22.0% 0.714 (0.118, 4.319) 0.714 - - Q3(64.11–70.9 min/day) 29.3% 1.714 (0.285, 10.303) 0.556 - - Q4 ( ≧ 70.9min/day) 22.0% 1.143 (0.179, 7.283) 0.888 Trend test P trend 0.626 0.490 Note: Quartiles of MVPA hours for the "insufficient" activity pattern, "regular" activity pattern, and "centralized" activity pattern were obtained for each pattern as Q1, Q3, and Q4, Q2, Q3 and Q4 for each mode. Table 5 shows the relationship between activity patterns of different intensity (VPA percentage) and physical health. In the "insufficient" activity pattern group, the probability of reaching a physical health score of 80 gradually increased with increasing intensity (VPA percentage) ( P trend <0.001), and the probability of reaching a physical health score of 80 gradually increased with increasing intensity (VPA percentage) ( P trend <0.001). In the "Regular" ( P trend =0.894) and the "centralized" ( P trend =0.573) activity patterns, there was no significant change in the probability of reaching a physical fitness score of 80 with increasing intensity (VPA percentage). Table 5 Relationship between Activity Patterns and Physical Health in Different Activity Patterns in terms of Intensity (VPA percentage) Activity Model Physical Health Score Model 1 Model 2 (80 points) OR (95% CI ) P-value OR (95% CI ) P-value "Insufficient" Activity Pattern Q1 (≤ 29.9%) 25.0% Ref - Ref - Q2 (29.9%−35.8%) 24.4% 1.114 (0.760, 1.632) 0.581 1.558 (1.004, 2.420) 0.048 Q3 (35.8%−41.9%) 26.1% 1.202 (0.820, 1.760) 0.346 1.869 (1.191, 2.933) 0.007 Q4 ( ≧ 41.9%) 24.5% 1.775 (1.217, 2.589) 0.003 2.205 (1.428, 3.403) < 0.001 Trend test P trend 0.003 < 0.001 "Regularity" Activity Pattern Q1 (≤ 39.7%) 21.2% Ref - Ref - Q2 (39.7%−45.8%) 28.8% 1.143 (0.380, 3.438) 0.812 1.455 (0.383, 5.535) 0.582 Q3 (45.8%−51.2%) 25.0% 1.600 (0.507, 5.054) 0.423 1.329 (0.336, 5.259) 0.685 Q4 ( ≧ 51.2%) 25.0% 1.000 (0.321, 3.113) - 0.927 (0.220, 3.903) 0.918 Trend test P trend 0.878 0.894 "Centralized" Activity Pattern Q1 (≤ 39.2%) 24.4% Ref - Ref - Q2 (39.2%−42.3%) 19.5% 1.400 (0.232, 8.464) 0.714 2.227 (0.238, 21.793) 0.475 Q3 (42.3%−49.2%) 31.4% 1.867 (0.283, 12.310) 0.517 1.243 (0.139, 11.090) 0.846 Q4 ( ≧ 49.2%) 24.4% 1.867 (0.283, 12.310) 0.517 2.547 (0.220, 9.497) 0.454 Trend test P trend 0.479 0.573 Note: Quartiles of the intensity (VPA share) of the "insufficient" activity pattern, the "regular" activity pattern, and the "centralized" activity pattern were obtained for each pattern, Q1, Q2, Q3, and Q4. Q1, Q2, Q3 and Q4. Table 6 shows the relationship between activity patterns and physical health for different activity pattern intensities (MET). In the "insufficient" activity pattern group, the probability of reaching a physical health score of 80 increased gradually with increasing MET( P trend =0.011). There is no significant association between different intensities in "regular" ( P trend =0.636) and "centralized" ( P trend =0.070) activity patterns and physical health. Table 6 Relationship between the Intensity of Different Activity Patterns (MET) and Physical Fitness activity model Physical Fitness Score Model 1 Model 2 (80 points) OR (95% CI ) P-value OR (95% CI) P-value "Insufficient" Activity Pattern Q1 (≤ 1.17) 25.0% Ref - Ref - Q2 (1.17–1.20) 25.3% 0.980 (0.673, 1.426) 0.914 1.000 (0.646, 1.549) 0.998 Q3 (1.20–1.24) 25.0% 1.263 (0.871, 1.833) 0.218 1.590 (1.019, 2.483) 0.041 Q4 ( ≧ 1.24) 24.8% 0.855 (0.584, 1.254) 0.421 1.625 (1.010, 2.614) 0.045 Trend Test Ptend 0.748 0.011 "Regularity" Activity Pattern Q1 (≤ 1.31) 25.0% Ref - Ref - Q2 (1.31–1.34) 26.0% 1.067 (0.358, 3.182) 0.908 0.944 (0.237, 3.770) 0.935 Q3 (1.34–1.40) 24.0% 0.489 (0.160, 1.492) 0.209 1.577 (0.291, 8.551) 0.598 Q4 ( ≧ 1.40) 25.0% 1.000 (0.333, 3.005) - 1.441 (0.267, 7.778) 0.671 Trend Test Ptend 0.927 0.636 "Centralized" Activity Model Q1 (≤ 1.26) 24.4% Ref - Ref - Q2 (1.26–1.30) 22.0% 0.643 (0.101, 4.097) 0.640 3.500 (0.132, 92.514) 0.453 Q3 (1.30–1.32) 26.8% 3.429 (0.287, 40.946) 0.330 - 0.998 Q4 ( ≧ 1.32) 26.8% 0.357 (0.059, 2.159) 0.262 - 0.998 Trend Test Ptend 0.847 0.070 Note: Quartiles of the intensity (Mettle value) of the "insufficient" activity pattern, the "regular" activity pattern, and the "centralized" activity pattern were obtained as Q1, Q3, and Q4 for each pattern, Q2, Q3 and Q4 for each pattern. 4. Discussion The study found that regular and bouted activity patterns were superior to insufficient patterns in enhancing adolescents' physical health and that there was no significant difference between the two in enhancing physical health. For adolescents in insufficient patterns, in addition to increasing MVPA time, increasing the intensity of each exercise properly could compensate for the lack of activity time. The study showed that no significant difference was revealed in improving physical health, either by adopting a regular weekly routine of physical activity or by opting for a bouted approach to physical activity. This finding emphasizes the important role of total physical activity, rather than frequency, in improving physical health. A prospective cohort study conducted by researchers at MIT and Harvard University in the United States showed that both regular physical activity and weekend bursts of physical activity, as long as they met health guideline recommendations, were associated with a reduced risk of 264 diseases, with the strongest correlation being cardiometabolic diseases [ 24 ] . This is consistent with White et al. [ 12 ] .Lee et al. 's study of mortality risk in adults showed that a weekly energy expenditure of 1,000 kcal through PA was effective in reducing mortality in an otherwise low-risk population, regardless of the frequency of PA 10 .Research by Shiroma et al. [ 25 ] supports this idea. They found that even "weekend warriors" who were active only 1–2 days per week had a significantly lower risk of death, comparable to those who were consistently exercise.O'Donovan et al. [ 26 ] further examined cause mortality, cardiovascular disease mortality, and cancer mortality by analyzing data from a large-scale health survey of over 63,000 adults in England and Scotland. The results showed that "weekend warriors" had a lower risk of all types of mortality compared to under-active populations, and that this reduction in risk was similar to that of frequently active populations. Specifically, this type of focused physical activity was comparable to regular daily physical activity in preventing cardiovascular disease and reducing mortality. This finding challenges the conventional wisdom that physical activity must be evenly distributed throughout each day or week. In response to traditional policy requirements, timely updates should be made to ensure that students achieve an adequate total amount of physical activity each week. By giving children and youths more flexibility in planning their physical activities through this adjustment, schools should take proactive measures to further enhance the intensity of students' physical activities and encourage them to rationalize their exercise schedules according to their own circumstances [ 27 ] . On this basis, the required amount of MVPA can be effectively accumulated, whether through physical education classes at school, after-school interest groups, or natural integration in daily activities at home . The study also found that for adolescents who have difficulty in achieving a cumulative 420 minutes of moderate to high intensity physical activity per week, elevating the intensity of exercise can compensate to some extent for the lack of time spent due to exercise. This finding is consistent with Robert et al.'s findings in adults [ 15 ] . The study showed that increasing exercise intensity significantly eliminated cardiorespiratory non-responsiveness within 24 weeks, improving abdominal obesity and reducing cardiovascular disease risk in a sedentary population, while following current physical activity guidelines. In addition, Hansen et al. [ 28 ] showed that sustained moderate to high intensity physical activity reduced blood glycated hemoglobin and increased skeletal muscle oxidative capacity. The results of the study further confirm the positive effects of a shift from moderate to high intensity exercise on children's physical health. Of particular note, the study found that the probability of achieving a physical fitness score of 80 increased with increasing Mettle values in the "insufficient" activity group. This result emphasizes the importance of "making a move" [ 29 ] , even if a transition from a sedentary state to any form of physical activity can have a positive effect on the physical health of children and adolescents. This suggests that all children and adolescents should be encouraged to do exercise, by fully use the most of recess time [ 30 ] , to get up out of their seats, and to engage in any form of physical activity,getting up and out of their seats for any possible physical activity. Currently, compulsory education schools in Beijing [ 32 ] , China, have optimized recess activities to ensure that students enjoy a 15-minute recess, encouraging teachers and students to get out of the classroom and into the sunshine, thus enjoying a healthier and more energetic school life and effectively promoting students' physical and mental health development. In addition, many provinces and cities in China [ 31 ] are actively exploring and practicing the optimization of recess activities, striving to create a more active and healthy recess environment for students. In terms of the content of recess activities, primary and secondary schools around the world are actively enriching the form of recess activities, not only retaining the traditional radio broadcast exercises, but also introducing a variety of sports games, dances, musical activities, and team-building games, with the aim of stimulating students' interest in learning, enhancing the spirit of teamwork, and at the same time achieving the purpose of exercising the body [ 33 ] . This study is that it adopts a more comprehensive perspective that considers the combined effects of physical activity duration, frequency and intensity on physical fitness. This multidimensional and multilevel study design helps to reveal the complex link between physical activity and physical health more precisely. However, this study has certain limitations—since the research participants were limited to adolescent groups in the specific region of Tibet, the generalizability of the findings may be affected to some extent. 5. Conclusions Both "regular" and "bouted" activity patterns can significantly improve the physical health level of Tibetan adolescents, but there is no significant difference in their health benefits. For adolescents with insufficient activity patterns, in addition to increasing MVPA time, also can consider increasing the intensity of each exercise to compensate for the lack of activity time. Declarations Clinical trial number: not applicable. Ethics approval and consent to participate This research adhered to the relevant requirements of the "Helsinki Declaration".The study protocol was approved by the Human Research Ethics Committee of East China Normal University (Approval No. HR 0077-2020), with written informed consent obtained from all participants' parents/guardians. Consent for publication This study has obtained the permission of the guardians of the participants for the publication of the content. Competing interests The authors declared no conflict of interest. Author details 1 School of Physical Education, Ludong University, Yantai 264000, Shandong, China 2 School of Physical Education, Xizang Minzu University, Xianyang 712000, Shaanxi, China 3 Xiguan Primary School, Fushan District, Yantai City, Shandong Province, China 264000 4 School of Physical Education, Jinan University, Jinan 250000, Shandong, China Funding This research was funded by the 2023 annual key project of the "14th Five-Year Plan" for educational science in Shandong Province, titled "Research on Establishing a Supervision System for Promoting Students' Meeting of Physical Health Standards (2023ZD027)". Author Contribution Peng Feng is mainly responsible for handling the data and the overall writing of the thesis. Sun Yi is responsible for the overall control and revision of the thesis. Yuan Meng is responsible for data testing. Song Bowen is responsible for data testing. Zhang Xiaotong is responsible for data testing. Liu Chenyu is responsible for data testing. Sun Shuangshuang is responsible for data testing. Li Desheng is responsible for data testing. Li Ming is also responsible for data testing. Acknowledgement We acknowledge the support from Shanghai University of Sport, especially Prof. Wang Lijuan and Dr. Zheng Nan for their expertise in data validation. Data availability The dataset generated and/or analyzed during the current research period is not publicly available, but can be obtained upon reasonable request. Availability of data and materials The data and analysis materials of this study are not yet made publicly available, but access can be provided upon reasonable request. References Janz KF, Letuchy EM, Eichenberger Gilmore JM, Burns TL, Torner JC, Willing MC, Levy SM. Early physical activity provides sustained bone health benefits later in childhood. Med Sci Sports Exerc. 2010;42(6):1072–8. Wernhart S, Dinic M, Pressler A, Halle M. 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Volume 14. Nutrients; 2022. p. 1773. Lee IM, Sesso HD, Oguma Y, Paffenbarger RS Jr.. The weekend warrior and risk of mortality. Am J Epidemiol. 2004;160(7):636 – 41. 10.1093/aje/kwh274 . PMID: 15383407. Min J, Cao Z, Duan T, Wang Y, Xu C. Accelerometer-derived 'weekend warrior' physical activity pattern and brain health. Nat Aging. 2024;4(10):1394–402. 10.1038/s43587-024-00688-y . Epub 2024 Aug 21. PMID: 39169268. White DA, Willis EA, Ptomey LT, Gorczyca AM, Donnelly JE. Weekly Frequency of Meeting the Physical Activity Guidelines and Cardiometabolic Health in Children and Adolescents. Med Sci Sports Exerc. 2022;54(1):106–12. PMID: 34334716; PMCID: PMC8678143. Zhou X, Li J, Jiang X. Effects of different types of exercise intensity on improving health-related physical fitness in children and adolescents: a systematic review. Sci Rep. 2024;14(1):14301. 10.1038/s41598-024-64830-x . PMID: 38906965; PMCID: PMC11192957. Gutin B, Yin Z, Humphries MC, Barbeau P. Relations of moderate and vigorous physical activity to fitness and fatness in adolescents. Am J Clin Nutr. 2005;81(4):746 – 50. 10.1093/ajcn/81.4.746 . PMID: 15817847. Ross R, Hudson R, Stotz PJ, Lam M. Effects of exercise amount and intensity on abdominal obesity and glucose tolerance in obese adults: a randomized trial. Ann Intern Med. 2015;162(5):325 – 34. 10.7326/M14-1189 . PMID: 25732273. Brown SL, Nobiling BD, Teufel J, Birch DA. Are kids too busy? early adolescents' perceptions of discretionary activities, overscheduling, and stress. J Sch Health. 2011;81(9):574 – 80. 10.1111/j.1746-1561.2011.00629.x . PMID: 21831071. Marques A, Santos R, Ekelund U, Sardinha LB. Association between physical activity, sedentary time, and healthy fitness in youth. Med Sci Sports Exerc. 2015;47(3):575 – 80. 10.1249/MSS.0000000000000426 . PMID: 24977696. Evenson KR, Catellier DJ, Gill K, Ondrak KS, McMurray RG. Calibration of two objective measures of physical activity for children. J Sports Sci. 2008;26(14):1557-65. 10.1080/02640410802334196 . PMID: 18949660. Freedson P, Pober D, Janz KF. Calibration of accelerometer output for children. Med Sci Sports Exerc. 2005;37(11 Suppl):S523-30. 10.1249/01.mss.0000185658.28284.ba . PMID: 16294115. Liu JI, Xiaojian YIN, Huipan WU, et al. An exploratory study of physical fitness evaluation standards for children and adolescents in China under the background of integration of physical education[J]. Sports Sci. 2021;41(03):42–54. Janssen I, Wong SL, Colley R, Tremblay MS. The fractionalization of physical activity throughout the week is associated with the cardiometabolic health of children and youth. BMC Public Health. 2013;13:554. Guo Y, Yin X, Sun Y, Zhang T, Li M, Zhang F, Liu Y, Xu J, Pei D, Huang T. Research on Environmental Influencing Factors of Overweight and Obesity in Children and Adolescents in China. Nutrients. 2021;14(1):35. Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193–213. Kany S, Al-Alusi MA, Rämö JT, Pirruccello JP, Churchill TW, Lubitz SA, Maddah M, Guseh JS, Ellinor PT, Khurshid S. Associations of Weekend Warrior Physical Activity With Incident Disease and Cardiometabolic Health. Circulation. 2024;150(16):1236–47. Shiroma EJ, Lee IM, Schepps MA, Kamada M, Harris TB. Physical Activity Patterns and Mortality: The Weekend Warrior and Activity Bouts. Med Sci Sports Exerc. 2019;51(1):35–40. O'Donovan G, Lee IM, Hamer M, Stamatakis E. Association of Weekend Warrior and Other Leisure Time Physical Activity Patterns With Risks for All-Cause, Cardiovascular Disease, and Cancer Mortality. JAMA Intern Med. 2017;177(3):335–342. 10.1001/jamainternmed.2016.8014 . Erratum in: JAMA Intern Med. 2022;182(5):579. Jianzhen S, Liu J. An Exploration of the Concept of Exercise Density Based on the Chinese Healthy Physical Education Curriculum Model [J]. J Capital Univ Phys Educ Sports. 2019;31(05):406–16. Hansen D, Dendale P, Jonkers RA, Beelen M, Manders RJ, Corluy L, Mullens A, Berger J, Meeusen R, van Loon LJ. Continuous low- to moderate-intensity exercise training is as effective as moderate- to high-intensity exercise training at lowering blood HbA(1c) in obese type 2 diabetes patients. Diabetologia. 2009;52(9):1789–97. Bevington F, Piercy KL, Olscamp K, Hilfiker SW, Fisher DG, Barnett EY. The Move Your Way Campaign: Encouraging Contemplators and Families to Meet the Recommendations From the Physical Activity Guidelines for Americans. J Phys Act Health. 2020;17(4):397–403. Zhao Youjun. Construction of a Long-term Mechanism for Primary School Physical Education's Big Recess Activities [J]. Contemp Sports Sci Technol. 2022;12(27):70–3. General Office of the State Council. Outline of the Planning for Building an Education Power (2024–2035) (2025-1-19) [2025-02-27] http://www.moe.gov.cn/jyb_xxgk/moe_1777/moe_1778/202501/t20250119_1176193.html Beijing Municipal Education Commission. Notice on Optimizing Recess Activities in Compulsory Education Schools. Jing Jiao Ji [2024] No. 9. (2024-8-30) [2025-02-18]. [ https://jw.beijing.gov.cn/xxgk/2024zcwj/2024qtwj/202408/t20240829_3784438.html] Ministry of Education. Establishing a Long-term Mechanism for Regular Supervision and Inspection [R], 2023. Additional Declarations No competing interests reported. Supplementary Files questionnaire.doc Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 30 Sep, 2025 Reviewers agreed at journal 25 Sep, 2025 Reviewers invited by journal 25 Sep, 2025 Editor assigned by journal 05 Sep, 2025 Editor invited by journal 26 Aug, 2025 Submission checks completed at journal 26 Aug, 2025 First submitted to journal 26 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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Introduction","content":"\u003cp\u003eIn adolescence period, being actively involved in physical activity (PA) not only strengthens bones\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e, muscle and cardio-pneumonia function, but also relieves academic stress and lifts mood. Regular physical activity is associated with lower morbidity rates of cardiovascular disease\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e, type 2 diabetes\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e, hypertension\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e, cancer\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e, obesity\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e and depression\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. The World Health Organization recommends that school-age children should get at least 60 minutes of moderate-intensity physical activity every day of the week\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. However, reports show that about 80% of children and adolescents globally do not meet the recommended minimum weekly level of physical activity\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn today's society, people have to cope with fast-paced lives and ever-increasing tasks, which makes regular physical activity become a challenge. As a result, most people choose to do physical activity on weekends, commonly known as \"weekend warriors\"\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e, which means completing at least 150 minutes of moderate to vigorous physical activity on 1\u0026ndash;2 days of the week. Min et al.\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e have found that bouted MVPA during 1\u0026ndash;2 days per week is associated with a reduced risk of brain disease.White\u0026rsquo;s et al.\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e study on children and adolescents found that no significant influence difference in cardiovascular health between regular physical activity and bouted physical activity on weekends when total MVPA was achieved. The health benefits of physical activity derive from a skillful balance of frequency, duration, and intensity. In addition to the frequency and duration of exercise, intensity is also an important indicator to consider. The health benefits of high-intensity exercise outweigh those of moderate-intensity exercise\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e, in which relationship between physical activity and obesity is particularly strong in adolescents. Studies have found that low body fat percentage is strongly associated with high intensity physical activity, but not with moderate intensity\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Robert Ross' team further revealed a positive correlation between increased exercise intensity and improved cardio-pneumonia function at a fixed amount of exercise\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eCurrently, factors such as excessive academic burden and extracurricular\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e tutoring prevent children and adolescents from engaging in regular physical activity, leading to health problems with a high efficiency. In this context, how to flexibly adjust exercise programs and cultivate good exercise habits has become an important issue in the field of physical activity promotion for children and adolescents. Taking adolescents in Tibet as the research object, this study aims to deeply analyze the distribution characteristics of their one-week activity patterns and explore the intrinsic connection between physical activity patterns and physical health, with a wish to provide reference for improving the physical health of adolescents in Tibet.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Participants\u003c/h2\u003e\u003cp\u003eThis cross-sectional study was conducted in Lhasa from June to December 2020. Two middle schools (Lhasa No. 8 Middle School and Lhasa Middle School) were selected through convenience sampling as research sites. Using random cluster sampling, we recruited Tibetan and Han Chinese student classes across all grade levels. To address the 3:1 ethnic ratio imbalance between Tibetan and Han students in these schools, we randomly selected 3 Tibetan classes and 2 Han classes per grade (with fewer Han students per class).\u003c/p\u003e\u003cp\u003eThe inclusion criteria were: (1) current enrollment in junior or senior high school; (2) aged 12\u0026ndash;18 years; (3) physically healthy without disabilities; and (4) voluntary participation with parental/guardian written informed consent. Enrolled participants received accelerometers and questionnaires to assess daily physical activity (PA), socioeconomic status (SES), and anthropometric measurements.\u003c/p\u003e\u003cp\u003eFrom an initial recruitment of 1,275 students, 19 were excluded due to invalid accelerometer data and 186 for incomplete questionnaires, yielding a final sample of 1,070 eligible participants. The study protocol was approved by the Human Research Ethics Committee of East China Normal University (Approval No. HR 0077-2020), with written informed consent obtained from all participants' parents/guardians.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Physical Activity\u003c/h2\u003e\u003cp\u003eThe ActiGraph GT3X\u0026thinsp;+\u0026thinsp;accelerometer was used to collect physical activity in this study. During the test, the accelerometer was worn on the right hip for 7 days (including 5 weekdays and 2 rest days), and the device was only allowed to be removed during water activities such as swimming, bathing and showering. The sampling interval was set to 1-second epoch ,which defined 1 day of accelerometer wear time\u0026thinsp;\u0026ge;\u0026thinsp;600 min as 1 valid day, and at least 4 valid days (3 weekdays\u0026thinsp;+\u0026thinsp;1 rest day) as the accelerometer wear criteria for analysis.This standard configuration aligns with established research protocols in the field\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Physical activity intensities were classified using research-established cut-points: sedentary (0-100 counts/min), light (101-2,295 counts/min), moderate (2,296-4,011 counts/min), and vigorous (\u0026ge;\u0026thinsp;4,012 counts/min)\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e.Energy expenditure was calculated using the energy expenditure formula:METs\u0026thinsp;=\u0026thinsp;2.757+(0.0015\u0026times;counts/minute)-(0.08957\u0026times;age)-(0.000038\u0026times;counts/minute\u0026times;age\u003csup\u003e)[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Physical Health Score\u003c/h2\u003e\u003cp\u003eIn this study, nine indicators were used to evaluate six aspects of adolescent physical health, and the weights of the indicators were differentiated in the evaluation. Specifically, BMI and waist circumference were used to evaluate body composition, with weighting coefficients of 14% and 6%. The grip strength, 30s sit-ups and standing long jump were used to evaluate strength, with weighting coefficients of 5%, 9%, and 10%. The 20-meter shuttle run test was used to evaluate cardiorespiratory endurance, with a 28% weighting coefficient. The 20-second side-step Test\u003c/p\u003e\u003cp\u003ewas used to evaluate agility and coordination, with an 8% weighting coefficient. The 50m dash was used to evaluate speed, with an 8% weighting coefficient; seated body bends were used to evaluate flexibility, with an 12% weighting coefficient. Each single index was scored out of 100 points, and the scoring was based on the evaluation standards given by existing studies. The total score of physical health was the weighted sum of the scores of each single index: \u0026ge;90 points was excellent, 80.0-89.9 points was good, 60.0-79.9 points was passing, and \u0026lt;\u0026thinsp;60.0 points was failing. Finally, 80 points were used as the line to divide the study subjects into two groups with high and low physical health levels. The study showed that the evaluation standard is systematic, scientific and feasible, and could accurately reflect the physical health level of children and adolescents in China\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Delineation of Activity Patterns\u003c/h2\u003e\u003cp\u003eActivity patterns are categorized based on a weekly MVPA length of 420 minutes. The weekly MVPA duration\u0026thinsp;\u0026lt;\u0026thinsp;420 min is defined as the insufficient activity pattern; the weekly MVPA duration\u0026thinsp;≧\u0026thinsp;420 min is defined as the \"regular\" activity pattern and the bouted activity pattern. Regular activity pattern is defined as MVPA of 60 min or more on most days of the week; and bouted activity pattern is defined as MVPA of 60 min or more on only a few days of the week. For days with less than seven (4\u0026ndash;6) active days of wear, the median of the active days of wear is used as the cut-off point\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. The regularity mode of activity is defined as the number of days with a regular activity pattern of 60 min MVPA\u0026thinsp;\u0026gt;\u0026thinsp;median valid Days. Bouted activity pattern with 60 min MVPA\u0026thinsp;\u0026le;\u0026thinsp;median effective day. The classification criteria is shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDividing the length of the activity model\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eValid day/day\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInsufficient Activity Pattern\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRegular Activity Pattern\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBouted Activity Pattern\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u0026ndash;4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u0026ndash;2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u0026ndash;5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u0026ndash;3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u0026ndash;6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u0026ndash;3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u0026ndash;7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u0026ndash;4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: The median effective days are 2.5, 3, 3.5, and 4 days for median values of 4, 5, 6, and 7 days, in that order.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Socioeconomic Status (SES)\u003c/h2\u003e\u003cp\u003eThe study assessed SES through parental questionnaires evaluating three key dimensions: education, occupation, and income(Details of the questionnaire can be found in the attachment.).Procedures for measuring the three dimensions of SES and their validation have been described elsewhere\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. The scoring system was implemented as follows: Parental education was quantified by years of schooling ; Parental occupation was coded using the International Standard Classification of Occupations (ISCO) scale; Monthly household income was categorized into four tiers with corresponding points: \u0026le;2,000 CNY (2 points), 2,001\u0026ndash;5,000 CNY (5 points), 5,001\u0026ndash;8,000 CNY (8 points), and \u0026gt;\u0026thinsp;8,000 CNY (10 points). The data processing protocol involved: variable screening/transformation, missing value treatment, standardization of all variables into z-scores, and principal component analysis (PCA) to derive the composite SES index.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6 Dietary Habits\u003c/h2\u003e\u003cp\u003eThe study evaluated the dietary habits of the study participants through questionnaires(Details of the questionnaire can be found in the attachment.) on the number of times they ate breakfast in a week, the number of days a week they ate at least one egg, the number of days a week they drank at least one glass of milk, yogurt, or soymilk, and the number of times they usually drank sugary beverages per day in a month, which were calculated using the same methodology as the SES: (1) categorically assign scores to the number of times they ate breakfast, the number of times they ate eggs, and the number of times they drank milk, yogurt, and soymilk (\u0026le;\u0026thinsp;2 times 1 point; 3\u0026ndash;4 times, 2 points; 5\u0026ndash;7 times, 3 points); and categorize and assign scores to sugary beverages (1 time or no drink, 3 points; 2\u0026ndash;4 times, 2 points; 5 times and above, 1 point); (2) filtering or transforming; (3) deal with the missing values; and (4) convert all the variables into a standardized score and perform a principal component analysis to calculate and get the dietary habits score.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.7 Sleep Quality\u003c/h2\u003e\u003cp\u003eIn this study, sleep quality was evaluated by the Pittsburgh Sleep Quality Index scale(PSQI)\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. The PSQI consists of 19 items that can be categorized into 7 components: subjective sleep quality, time to sleep, sleep duration, sleep efficiency, sleep disorders, hypnotic medication application, and daytime functioning. Each component is scored on a scale of 0\u0026ndash;3, and the cumulative score for each component is the total PAQI score, with higher scores indicating poorer sleep quality. The PSQI scores were categorized as 0\u0026ndash;5, very good; 6\u0026ndash;10 okay; 11\u0026ndash;15, fair; and 16\u0026ndash;21, very poor.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.8 Statistical analysis\u003c/h2\u003e\u003cp\u003eThe chi-square test was used to compare the ethnic differences in gender, study stage and activity patterns. Independent samples t-test was used to compare ethnic differences in socioeconomic status, while Mann-Whitney U test was employed to analyze differences in sleep quality scores and dietary habit scores as they violated the normality assumption.The dichotomous classification of physical fitness scores with a cut-off score of 80 is used as the dependent variable. And binary logistic regression is used to analyze the relationship between the insufficient activity pattern, the regular activity pattern, and the bouted activity.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the activity distribution model of the participants. Han Chinese adolescents had higher SES (1.42\u0026thinsp;\u0026plusmn;\u0026thinsp;2.41) and sleep quality scores[4.00(2.00,6.00)] than Tibetan (-1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;4.04; 3.00(2.00,5.00)), with statistically significant differences (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and lower eating habit scores (-0.51(-0.82,0.43)) than Tibetan ( 0.43(-0.51,1.38)), and the difference was statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The proportion of insufficient activity patterns (90.2%) was higher in Han Chinese than in Tibetan (83.5%), while the proportion of regular (7.0%) and bouted(2.8%) activity patterns was lower than in Tibetan (11.8%, 4.7%), and the difference was statistically significant \u003cem\u003e(P\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDistributional Characteristics of participants' Activity Patterns\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eHan Chinese\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eTibetan\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e /t/Z\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePercentage\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumber\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePercentage\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.363\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.243\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e226\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e267\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e44.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWomen\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e244\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e51.9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e333\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e55.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSegments\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e7.734\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJunior High School\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e156\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33.2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e249\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e41.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh School\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e314\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e66.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e351\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e58.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSocio-Economic Status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e1.42\u0026thinsp;\u0026plusmn;\u0026thinsp;2.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u0026minus;1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;4.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e14.456\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSleep Quality Score\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e4.00 (2.00,6.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e3.00 (2.00,5.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;3.793\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDietary Habits Score\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u0026minus;0.51(\u0026minus;0.82,0.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0.43(\u0026minus;0.51,1.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026minus;7.903\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMode of activity\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10.137\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInsufficient Activity Patterns\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e424\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e90.2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e501\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e83.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegular Activity Patterns\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBouted Activity Model\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.7%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the relationship between participants' activity patterns and physical health. Adolescents with regular and bouted activity patterns were 2.1 times (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.103, 95% \u003cem\u003eCI\u003c/em\u003e: 1.304\u0026ndash;3.393, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002) and 3.3 times (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.343, 95% \u003cem\u003eCI\u003c/em\u003e: 1.628\u0026ndash;6.866, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) more likely to achieve a fitness level of 80 or higher than those with \"insufficient\" activity patterns. 1.628\u0026ndash;6.866,\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). There is no significant association between \"regular\" (\u003cem\u003eOR\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.629, 95% \u003cem\u003eCI\u003c/em\u003e: 0.273\u0026ndash;1.450, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.277) activity and achieving a physical fitness score of 80 compared to \"centralized\" mode.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRelationship between Activity Patterns and Physical Health among Adolescents in Tibet\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eMode of activity\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eModel 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eModel 2\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eOR\u003c/em\u003e (95% \u003cem\u003eCI\u003c/em\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eOR\u003c/em\u003e (95% \u003cem\u003eCI\u003c/em\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eUsing the \"insufficient\" activity model as a reference\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\"Insufficient\"\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\"Regularity.\"\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.899 (1.263, 2.855)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.103 (1.304, 3.393)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\"Centralized\"\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.139 (1.624, 6.068)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.343 (1.628, 6.866)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eUsing the \"Centralized\" activity model as a reference\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\"Centralized\"\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\"Insufficient\"\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.319 (0.165, 0.616)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.299 (0.146, 0.614)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\"Regularity.\"\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.605 (0.285, 1.283)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.190\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.629 (0.273, 1.450)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.277\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the relationship between MVPA duration and physical health in different activity patterns. In the \"insufficient\" activity mode group, the probability of reaching a physical health score of 80 increased gradually with the increase in MVPA duration. In the \"regular\" and \"centralized\" activity modes, there was no significant change in the probability of reaching a physical fitness score of 80 as the length of MVPA increased.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRelationship between MVPA and Physical Health in Different Activity Patterns\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eActivity Model\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhysical Fitness Score\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eModel 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eModel 2\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(80 points)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eOR\u003c/em\u003e (95% \u003cem\u003eCI\u003c/em\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eOR\u003c/em\u003e (95% \u003cem\u003eCI\u003c/em\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003e\"Insufficient\" Activity Pattern\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ1(\u0026le;\u0026thinsp;36.9min/day)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ2(36.9\u0026ndash;46.1 min/day)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.688 (1.773,4.074)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.840 (1.157, 2.926)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ3(46.1\u0026ndash;53.9 min/day)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.683 (1.779,4.046)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.874 (1.183, 2.968)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ4 (\u0026thinsp;≧\u0026thinsp;53.9min/day)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.020 (2.661,6.073)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.128 (1.334, 3.395)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrend test P\u003csub\u003etrend\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003e\"Regularity\" Activity Pattern\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ1 (\u0026le;\u0026thinsp;72.7min/day)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ2(72.7\u0026ndash;78.7 min/day)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19.2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.394 (0.996, 11.569)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.051\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.826 (0.797, 18.362)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.094\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ3(78.7\u0026ndash;87.1 min/day)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.766 (0.622, 5.016)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.285\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.190 (0.340, 4.157)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.786\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ4 (\u0026thinsp;≧\u0026thinsp;87.1min/day)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.697 (0.572, 5.037)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.341\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.379 (0.330, 5.758)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.660\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrend test P\u003csub\u003etrend\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.502\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.952\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003e\"Centralized\" Activity Pattern\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ1 (\u0026le;\u0026thinsp;61.74min/day)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ2(61.74\u0026ndash;64.11 min/day)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.714 (0.118, 4.319)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.714\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ3(64.11\u0026ndash;70.9 min/day)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.714 (0.285, 10.303)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.556\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ4 (\u0026thinsp;≧\u0026thinsp;70.9min/day)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.143 (0.179, 7.283)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.888\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrend test P\u003csub\u003etrend\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.626\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.490\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: Quartiles of MVPA hours for the \"insufficient\" activity pattern, \"regular\" activity pattern, and \"centralized\" activity pattern were obtained for each pattern as Q1, Q3, and Q4, Q2, Q3 and Q4 for each mode.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the relationship between activity patterns of different intensity (VPA percentage) and physical health. In the \"insufficient\" activity pattern group, the probability of reaching a physical health score of 80 gradually increased with increasing intensity (VPA percentage) (\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e\u0026lt;0.001), and the probability of reaching a physical health score of 80 gradually increased with increasing intensity (VPA percentage) (\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e\u0026lt;0.001). In the \"Regular\" (\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e=0.894) and the \"centralized\" (\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e=0.573) activity patterns, there was no significant change in the probability of reaching a physical fitness score of 80 with increasing intensity (VPA percentage).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRelationship between Activity Patterns and Physical Health in Different Activity Patterns in terms of Intensity (VPA percentage)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eActivity Model\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhysical Health Score\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eModel 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eModel 2\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(80 points)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eOR\u003c/em\u003e (95% \u003cem\u003eCI\u003c/em\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eOR\u003c/em\u003e (95% \u003cem\u003eCI\u003c/em\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003e\"Insufficient\" Activity Pattern\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ1 (\u0026le;\u0026thinsp;29.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ2 (29.9%\u0026minus;35.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.114 (0.760, 1.632)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.581\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.558 (1.004, 2.420)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.048\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ3 (35.8%\u0026minus;41.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.1%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.202 (0.820, 1.760)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.346\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.869 (1.191, 2.933)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ4 (\u0026thinsp;≧\u0026thinsp;41.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.775 (1.217, 2.589)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.205 (1.428, 3.403)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrend test P\u003csub\u003etrend\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003e\"Regularity\" Activity Pattern\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ1 (\u0026le;\u0026thinsp;39.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21.2%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ2 (39.7%\u0026minus;45.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.143 (0.380, 3.438)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.812\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.455 (0.383, 5.535)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.582\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ3 (45.8%\u0026minus;51.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.600 (0.507, 5.054)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.423\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.329 (0.336, 5.259)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.685\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ4 (\u0026thinsp;≧\u0026thinsp;51.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.000 (0.321, 3.113)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.927 (0.220, 3.903)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.918\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrend test P\u003csub\u003etrend\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.878\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.894\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003e\"Centralized\" Activity Pattern\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ1 (\u0026le;\u0026thinsp;39.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ2 (39.2%\u0026minus;42.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19.5%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.400 (0.232, 8.464)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.714\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.227 (0.238, 21.793)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.475\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ3 (42.3%\u0026minus;49.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e31.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.867 (0.283, 12.310)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.517\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.243 (0.139, 11.090)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.846\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ4 (\u0026thinsp;≧\u0026thinsp;49.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.867 (0.283, 12.310)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.517\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.547 (0.220, 9.497)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.454\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrend test P\u003csub\u003etrend\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.479\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.573\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: Quartiles of the intensity (VPA share) of the \"insufficient\" activity pattern, the \"regular\" activity pattern, and the \"centralized\" activity pattern were obtained for each pattern, Q1, Q2, Q3, and Q4. Q1, Q2, Q3 and Q4.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows the relationship between activity patterns and physical health for different activity pattern intensities (MET). In the \"insufficient\" activity pattern group, the probability of reaching a physical health score of 80 increased gradually with increasing MET(\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e=0.011). There is no significant association between different intensities in \"regular\" (\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e=0.636) and \"centralized\" (\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003etrend\u003c/em\u003e\u003c/sub\u003e=0.070) activity patterns and physical health.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRelationship between the Intensity of Different Activity Patterns (MET) and Physical Fitness\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eactivity model\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhysical Fitness Score\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eModel 1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eModel 2\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(80 points)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eOR\u003c/em\u003e (95% \u003cem\u003eCI\u003c/em\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eOR\u003c/em\u003e (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003e\"Insufficient\" Activity Pattern\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ1 (\u0026le;\u0026thinsp;1.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ2 (1.17\u0026ndash;1.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.3%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.980 (0.673, 1.426)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.914\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.000 (0.646, 1.549)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.998\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ3 (1.20\u0026ndash;1.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.263 (0.871, 1.833)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.218\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.590 (1.019, 2.483)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.041\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ4 (\u0026thinsp;≧\u0026thinsp;1.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.855 (0.584, 1.254)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.421\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.625 (1.010, 2.614)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.045\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrend Test Ptend\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.748\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003e\"Regularity\" Activity Pattern\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ1 (\u0026le;\u0026thinsp;1.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ2 (1.31\u0026ndash;1.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.067 (0.358, 3.182)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.908\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.944 (0.237, 3.770)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.935\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ3 (1.34\u0026ndash;1.40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.489 (0.160, 1.492)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.209\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.577 (0.291, 8.551)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.598\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ4 (\u0026thinsp;≧\u0026thinsp;1.40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.000 (0.333, 3.005)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.441 (0.267, 7.778)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.671\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrend Test Ptend\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.636\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003e\"Centralized\" Activity Model\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ1 (\u0026le;\u0026thinsp;1.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRef\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ2 (1.26\u0026ndash;1.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22.0%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.643 (0.101, 4.097)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.640\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.500 (0.132, 92.514)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.453\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ3 (1.30\u0026ndash;1.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.429 (0.287, 40.946)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.330\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.998\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ4 (\u0026thinsp;≧\u0026thinsp;1.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.357 (0.059, 2.159)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.262\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.998\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrend Test Ptend\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.847\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.070\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: Quartiles of the intensity (Mettle value) of the \"insufficient\" activity pattern, the \"regular\" activity pattern, and the \"centralized\" activity pattern were obtained as Q1, Q3, and Q4 for each pattern, Q2, Q3 and Q4 for each pattern.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe study found that regular and bouted activity patterns were superior to insufficient patterns in enhancing adolescents' physical health and that there was no significant difference between the two in enhancing physical health. For adolescents in insufficient patterns, in addition to increasing MVPA time, increasing the intensity of each exercise properly could compensate for the lack of activity time.\u003c/p\u003e\u003cp\u003eThe study showed that no significant difference was revealed in improving physical health, either by adopting a regular weekly routine of physical activity or by opting for a bouted approach to physical activity. This finding emphasizes the important role of total physical activity, rather than frequency, in improving physical health. A prospective cohort study conducted by researchers at MIT and Harvard University in the United States showed that both regular physical activity and weekend bursts of physical activity, as long as they met health guideline recommendations, were associated with a reduced risk of 264 diseases, with the strongest correlation being cardiometabolic diseases\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. This is consistent with White et al.\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e.Lee et al. 's study of mortality risk in adults showed that a weekly energy expenditure of 1,000 kcal through PA was effective in reducing mortality in an otherwise low-risk population, regardless of the frequency of PA\u003csup\u003e10\u003c/sup\u003e.Research by Shiroma et al. \u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003esupports this idea. They found that even \"weekend warriors\" who were active only 1\u0026ndash;2 days per week had a significantly lower risk of death, comparable to those who were consistently exercise.O'Donovan et al.\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003efurther examined cause mortality, cardiovascular disease mortality, and cancer mortality by analyzing data from a large-scale health survey of over 63,000 adults in England and Scotland. The results showed that \"weekend warriors\" had a lower risk of all types of mortality compared to under-active populations, and that this reduction in risk was similar to that of frequently active populations. Specifically, this type of focused physical activity was comparable to regular daily physical activity in preventing cardiovascular disease and reducing mortality. This finding challenges the conventional wisdom that physical activity must be evenly distributed throughout each day or week. In response to traditional policy requirements, timely updates should be made to ensure that students achieve an adequate total amount of physical activity each week. By giving children and youths more flexibility in planning their physical activities through this adjustment, schools should take proactive measures to further enhance the intensity of students' physical activities and encourage them to rationalize their exercise schedules according to their own circumstances\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. On this basis, the required amount of MVPA can be effectively accumulated, whether through physical education classes at school, after-school interest groups, or natural integration in daily activities at home .\u003c/p\u003e\u003cp\u003eThe study also found that for adolescents who have difficulty in achieving a cumulative 420 minutes of moderate to high intensity physical activity per week, elevating the intensity of exercise can compensate to some extent for the lack of time spent due to exercise. This finding is consistent with Robert et al.'s findings in adults\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. The study showed that increasing exercise intensity significantly eliminated cardiorespiratory non-responsiveness within 24 weeks, improving abdominal obesity and reducing cardiovascular disease risk in a sedentary population, while following current physical activity guidelines. In addition, Hansen et al.\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e showed that sustained moderate to high intensity physical activity reduced blood glycated hemoglobin and increased skeletal muscle oxidative capacity. The results of the study further confirm the positive effects of a shift from moderate to high intensity exercise on children's physical health. Of particular note, the study found that the probability of achieving a physical fitness score of 80 increased with increasing Mettle values in the \"insufficient\" activity group. This result emphasizes the importance of \"making a move\"\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e, even if a transition from a sedentary state to any form of physical activity can have a positive effect on the physical health of children and adolescents. This suggests that all children and adolescents should be encouraged to do exercise, by fully use the most of recess time\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e, to get up out of their seats, and to engage in any form of physical activity,getting up and out of their seats for any possible physical activity. Currently, compulsory education schools in Beijing\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e, China, have optimized recess activities to ensure that students enjoy a 15-minute recess, encouraging teachers and students to get out of the classroom and into the sunshine, thus enjoying a healthier and more energetic school life and effectively promoting students' physical and mental health development. In addition, many provinces and cities in China\u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e are actively exploring and practicing the optimization of recess activities, striving to create a more active and healthy recess environment for students. In terms of the content of recess activities, primary and secondary schools around the world are actively enriching the form of recess activities, not only retaining the traditional radio broadcast exercises, but also introducing a variety of sports games, dances, musical activities, and team-building games, with the aim of stimulating students' interest in learning, enhancing the spirit of teamwork, and at the same time achieving the purpose of exercising the body\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThis study is that it adopts a more comprehensive perspective that considers the combined effects of physical activity duration, frequency and intensity on physical fitness. This multidimensional and multilevel study design helps to reveal the complex link between physical activity and physical health more precisely. However, this study has certain limitations\u0026mdash;since the research participants were limited to adolescent groups in the specific region of Tibet, the generalizability of the findings may be affected to some extent.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eBoth \"regular\" and \"bouted\" activity patterns can significantly improve the physical health level of Tibetan adolescents, but there is no significant difference in their health benefits. For adolescents with insufficient activity patterns, in addition to increasing MVPA time, also can consider increasing the intensity of each exercise to compensate for the lack of activity time.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eClinical trial number: not applicable.\u003c/strong\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cp\u003e This research adhered to the relevant requirements of the \"Helsinki Declaration\".The study protocol was approved by the Human Research Ethics Committee of East China Normal University (Approval No. HR 0077-2020), with written informed consent obtained from all participants' parents/guardians.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eConsent for publication\u003c/h2\u003e\u003cp\u003e This study has obtained the permission of the guardians of the participants for the publication of the content.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eThe authors declared no conflict of interest.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eAuthor details\u003c/h2\u003e\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eSchool of Physical Education, Ludong University, Yantai 264000, Shandong, China\u003c/p\u003e\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eSchool of Physical Education, Xizang Minzu University, Xianyang 712000, Shaanxi, China\u003c/p\u003e\u003cp\u003e\u003csup\u003e3\u003c/sup\u003eXiguan Primary School, Fushan District, Yantai City, Shandong Province, China 264000\u003c/p\u003e\u003cp\u003e\u003csup\u003e4\u003c/sup\u003eSchool of Physical Education, Jinan University, Jinan 250000, Shandong, China\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis research was funded by the 2023 annual key project of the \"14th Five-Year Plan\" for educational science in Shandong Province, titled \"Research on Establishing a Supervision System for Promoting Students' Meeting of Physical Health Standards (2023ZD027)\".\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003ePeng Feng is mainly responsible for handling the data and the overall writing of the thesis. Sun Yi is responsible for the overall control and revision of the thesis. Yuan Meng is responsible for data testing. Song Bowen is responsible for data testing. Zhang Xiaotong is responsible for data testing. Liu Chenyu is responsible for data testing. Sun Shuangshuang is responsible for data testing. Li Desheng is responsible for data testing. Li Ming is also responsible for data testing.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe acknowledge the support from Shanghai University of Sport, especially Prof. Wang Lijuan and Dr. Zheng Nan for their expertise in data validation.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e\u003cp\u003eThe dataset generated and/or analyzed during the current research period is not publicly available, but can be obtained upon reasonable request.\u003c/p\u003e\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\u003cp\u003eThe data and analysis materials of this study are not yet made publicly available, but access can be provided upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eJanz KF, Letuchy EM, Eichenberger Gilmore JM, Burns TL, Torner JC, Willing MC, Levy SM. Early physical activity provides sustained bone health benefits later in childhood. 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Outline of the Planning for Building an Education Power (2024\u0026ndash;2035) (2025-1-19) [2025-02-27] \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.moe.gov.cn/jyb_xxgk/moe_1777/moe_1778/202501/t20250119_1176193.html\u003c/span\u003e\u003cspan address=\"http://www.moe.gov.cn/jyb_xxgk/moe_1777/moe_1778/202501/t20250119_1176193.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBeijing Municipal Education Commission. Notice on Optimizing Recess Activities in Compulsory Education Schools. Jing Jiao Ji [2024] No. 9. (2024-8-30) [2025-02-18]. [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://jw.beijing.gov.cn/xxgk/2024zcwj/2024qtwj/202408/t20240829_3784438.html]\u003c/span\u003e\u003cspan address=\"https://jw.beijing.gov.cn/xxgk/2024zcwj/2024qtwj/202408/t20240829_3784438.html]\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMinistry of Education. Establishing a Long-term Mechanism for Regular Supervision and Inspection [R], 2023.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"children and adolescents, physical activity patterns, physical health, Tibetan","lastPublishedDoi":"10.21203/rs.3.rs-7354192/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7354192/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOBJECTIVE: The study aims to analyze the distributional characteristics of one-week activity patterns among Tibetan adolescents and to explore the relationship between physical activity patterns and physical health.\u003c/p\u003e\n\u003cp\u003eMETHODS: This study employed a stratified cluster sampling method (with a Han-Tibetan ratio of 3:1), recruiting a total of 1275 students from two middle schools in Lhasa. Eventually, 1070 participants who met the criteria were retained. Chi-square test was used to compare the differences in ethnicity in terms of gender, educational stage, and activity patterns. Independent sample t-test was used to compare the differences in social economic status among ethnic groups, while the Mann-Whitney U test was used to analyze the differences in sleep and diet scores . Binary logistic regression was used to analyze the association between the three activity patterns and physical health.\u003c/p\u003e\n\u003cp\u003eRESULTS: “Regular” (\u003cem\u003eOR\u003c/em\u003e=2.103, 95%\u003cem\u003eCI\u003c/em\u003e:1.304~3.393, \u003cem\u003eP\u003c/em\u003e=0.002) and “bouted” (\u003cem\u003eOR\u003c/em\u003e=3.343, 95%\u003cem\u003eCI\u003c/em\u003e:1.628~6.866,\u003cem\u003e P\u003c/em\u003e=0.001) were superior to the under-activity mode in enhancing physical health. There is no difference between the two in terms of improving physical health.(\u003cem\u003eP\u003c/em\u003e=0.277). In the insufficient pattern group, the probability of reaching a physical health score of 80 gradually increased with the increase in intensity [vigorous physical activity percentage(VPA) and MET](\u003cem\u003eP\u003c/em\u003e\u003csub\u003etrend\u003c/sub\u003e \u0026lt;0.001;\u003cem\u003e P\u003c/em\u003e\u003csub\u003etrend\u003c/sub\u003e =0.011).\u003c/p\u003e\n\u003cp\u003eCONCLUSIONS: Both “regular” and “bouted” activity patterns have similar effects on improving the health of Tibetan teenagers. 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