In 2020, the average height of males aged between 18 and 44 years in China figured at ***** centimeters, up *** centimeters compared to that in 2015. On the other side, obesity and overweight conditions have seen a gradual increase across the country mainly related to an unhealthy diet and a less active urban lifestyle.

Descriptive statistics for height components by quintiles in men:Height (m): Quintile 1: mean = 1.62, range = 1.15–1.65, std = 0.03; Quintile 2: mean = 1.67, range = 1.65–1.69, std = 0.009; Quintile 3: mean = 1.70, range = 1.69–1.72, std = 0.008; Quintile 4: mean = 1.73, range = 1.72–1.75, std = 0.008; Quintile 5: mean = 1.78, range = 1.75–1.96, std = 0.03. Leg Length (cm): Quintile 1: mean = 74.1, range = 37–76, std = 2.02; Quintile 2: mean = 77.5, range = 76.1–78.9, std = 0.61; Quintile 3: mean = 79.5, range = 79–80, std = 0.47; Quintile 4: mean = 81.4, range = 80–82.5, std = 0.61; Quintile 5: mean = 84.9, range = 82.5–101, std = 2.06. Sitting height (cm): Quintile 1: mean = 85.6, range = 56.087.9, std = 1.84; Quintile 2: mean = 88.6, range = 88.0–90.0, std = 0.53; Quintile 3: mean = 90.5, range = 90.0–91.5, std = 0.53; Quintile 4: mean = 92.4, range = 91.6–93.1, std = 0.47; Quintile 5: mean = 95.2, range = 93.1–108.0, std = 1.51.*Expressed as per standard deviation change. Model 1: univariate analyses. Model 2 controlled for birth cohort, education, and income. Model 3 controlled for birth cohort, education, income, and BMI at baseline. Model 4 controlled for birth cohort, education, income, smoking before age 20, BMI at age 20, BMI at baseline, and participation in team sports during adolescence.

In 2023, South Korean high school students were among the tallest in Asia, with male students aged 16 years old averaging ***** cm and female students averaging ***** cm. Both South Korean men and women have seen drastic increases in height over the past century, and in the case of women, the change in average height is the largest increase for any population in the world. Height is linked to health The average height of a population can be a good indicator for the overall health of that country; aside from genetic factors, nutrition and childhood infections play an important role in how a child will develop in terms of growth. South Koreans can expect to live longer these days; the average life expectancy at birth has steadily increased and was at **** years as of 2022. Women are expected to live slightly longer than men by around five years. The average weight of South Korean high school students has also generally increased over the years, which may suggest nutrition has improved. However, as with many other OECD countries, the obesity rate has also increased among the population.

Descriptive statistics for the leg-length-to-sitting-height ratio by quintiles of the leg-length-to-sitting-height in women are as follows: Quintile 1: mean = 0.80, range = 0.43–0.82, std = 0.02; Quintile 2: mean = 0.84, range = 0.82–0.85, std = 0.008; Quintile 3: mean = 0.86, range = 0.85–0.88, std = 0.007; Quintile 4: mean = 0.89, range = 0.88–0.91, std = 0.009; Quintile 5: mean = 0.95, range = 0.91–2.02, std = 0.05. Descriptive statistics for the leg-length-to-sitting-height ratio by quintiles of the leg-length-to-sitting-height in men are as follows: Quintile 1: mean = 0.82, range = 0.43–0.84, std = 0.02; Quintile 2: mean = 0.85, range = 0.84–0.87, std = 0.007; Quintile 3: mean = 0.88, range = 0.87–0.89, std = 0.006; Quintile 4: mean = 0.90, range = 0.89–0.91, std = 0.008; Quintile 5: mean = 0.94, range = 0.91–1.46, std = 0.03.*Expressed as per standard deviation change.Model 1: univariate analyses. Model 2 controlled for birth cohort, education, and income. Model 3 controlled for birth cohort, education, income, and BMI at baseline. Model 4 controlled for birth cohort, education, income, smoking before age 20, BMI at age 20, BMI at baseline, and participation in team sports during adolescence.

IntroductionChinese are reported to have a higher percent body fat (%BF) and a higher percent trunk fat (%TF) than whites for a given body mass index (BMI). However, the associations of these ethnic differences in body composition with metabolic risks remain unknown. Methods and ProceduresA total of 1 029 Chinese from Hangzhou, China, and 207 whites from New York, NY, USA, were recruited in the present study. Body composition was measured using dual-energy X-ray absorptiometry (DXA). Analysis of covariance was used to assess the ethnic differences in fat, fat distribution, and metabolic risk factors. ResultsAfter adjusting for BMI, age, and height, Chinese men had an average of 3.9% more %BF and 12.1% more %TF than white men; Chinese women had an average of 2.3% more %BF and 11.8% more %TF than white women. Compared with whites, higher metabolic risks were detected in Chinese for a given BMI after adjusting for age and height. Further adjustment for %BF did not change these ethnic disparities. However, after adjusting for %TF, the ethnic differences decreased and become insignificant in triglyceride, high-density lipoprotein cholesterol, and blood pressure (except for systolic blood pressure in men). For fasting plasma glucose, the ethnic differences persisted after adjustment for %BF, but decreased significantly from 0.910 to 0.686 mmol/L among men, and from 0.629 to 0.355 mmol/L among women, when the analyses were further controlled for %TF. DiscussionChinese have both higher %BF and %TF than white people for a given BMI. However, only %TF could in part account for the higher metabolic risk observed in Chinese men and women.

IntroductionThis study primarily investigates the impact of a 6-week Sprint Interval Training (SIT) intervention on the physical fitness test results of male university students, as well as the dose-response relationship in adjusting the experimental protocol.MethodsA total of 26 male university students (aged 20 ± 2 years; height 174 ± 7 cm; weight 70 ± 14 kg; mean ± SD) with no systematic training in the past 3 months, no physiological diseases, and healthy physical condition voluntarily participated in the experiment. The SIT protocol was designed based on a classic Wingate sprint protocol (4-6 x 30 s sprints with 4 m of recovery), and adjustments were made based on the participants' actual adaptation. The final intervention consisted of 6 weeks of training, three times per week, with 2-3 repetitions of 30-s Wingate sprints (Cd = 0.075, resistance on the ergometer = weight/kg x Cd) and 4–5 m of recovery.ResultsThe results showed significant improvements in key anaerobic capacity indicators after the 6-week intervention: Average Power (AP) increased from 77.4 ± 10.1 to 132.6 ± 21.1 (p < 0.01, Adjusted p < 0.03 ment, with a maximum effect size of 3.344), Peak Power (PP) increased from 102.9 ± 14.5 to 189.5 ± 28.8 (p < 0.01, Adjusted p < 0.02, maximum effect 3.790), and Time to Peak Power (TTP) decreased from 12.3 ± 3.3 to 9.5 ± 2.6 (p < 0.01), confirming that the intervention enhanced the participants' anaerobic capacity. Additionally, The results of the physical fitness test showed significant improvements: standing long jump (SLJ) increased from 2.31 ± 0.15 m to 2.45 ± 0.18 m (significance level p < 0.01), 50 m sprint time decreased from 7.32 ± 0.42 s to 6.98 ± 0.38 s (significance level p < 0.01), and 1,000 m from 235.6 ± 18.4 s to 220.3 ± 16.8 s (significance level p < 0.01). Other metrics such as Body mass, BMI, Vital capacity, and Pull-ups also showed minor increases. Interestingly, Sit forward in a sitting position scores showed a noticeable improvement (from 12.9 ± 6.8 to 15.8 ± 6.2, p = 0.091).DiscussionFurthermore, The adjustment of the training programme has achieved good results, as evidenced by the fact that participants have achieved a training completion rate of over 95%, maintained a moderate subjective fatigue rating (RPE score of 13-15), and no one has withdrawn from the training due to discomfort.ConclusionThe modified SIT protocol proves to be an efficient and practical training method for improving college students' physical fitness.