Interaction between physical activity and outdoor time on allostatic load in Chinese college students

Zhang, Dan; Li, Tingting; Xie, Yang; Tao, Shuman; Yang, Young Il; Zou, Liwei; Qu, Yang; Zhai, Shuang; Tao, Fangbiao; Wu, Xiaoyan

doi:10.1186/s12889-022-12518-0

Cited by 10 publications

(9 citation statements)

References 28 publications

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“…College Student Behavior and Health Cohort Study ( 11 ) is a cohort study designed to investigate the longitudinal outcomes of health-related behaviors of college students who were in freshman through junior year between April 2019 and June 2021. The survey was conducted using a cluster of a random sampling of whole groups with the college as the primary sampling unit.…”

Section: Methodsmentioning

confidence: 99%

“…The threshold of BMI was defined using the screening for overweight and obesity among school-age children and adolescents (WS/T 586-2018) ( 15 ). The other parameters refer to the demarcation standard of university students in our previous study ( 11 ).…”

Section: Methodsmentioning

confidence: 99%

“…Metabolic scores were calculated using four metabolic parameters including BMI, WC, FBG, and insulin, which were mentioned in our previous study ( 11 ). Each parameter is defined as a value according to the threshold criteria; parameters above the threshold are defined as a score of 1.…”

Section: Methodsmentioning

confidence: 99%

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Poor sleep pattern is associated with metabolic disorder during transition from adolescence to adulthood

et al. 2023

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ObjectiveThe purpose of this study was to investigate whether sleep pattern is associated with metabolic disorders among young adults.MethodsWe measured sleep patterns using multiple sleep behaviors in an ongoing prospective cohort among college students (n = 1,151). At baseline, 729 college students provided fasting blood samples and human body morphological measurements for quantification of metabolic parameters. Then, 340 participants continued to take metabolic parameters measurements at a 2-year follow-up. Sleep patterns were defined by chronotype, sleep duration, insomnia, snoring, and daytime sleepiness. Metabolic scores were derived for four metabolic parameters including body mass index (BMI), waist circumference (WC), fasting blood sugar (FBG), and insulin. Multivariate linear regression model was applied to analyze the association between sleep pattern types and metabolic parameters and metabolic scores.ResultsIn the baseline survey, we found that a total of 41 (4.1%) participants had poor sleep patterns. Then, metabolic scores were significantly higher among college students with poor sleep patterns, compared with those who with healthy sleep patterns at baseline (1.00 ± 0.96 vs. 0.78 ± 0.72, p < 0.05) and 2-year follow-up (0.34 ± 0.65 vs. 1.50 ± 1.64, p < 0.05). After covariates were adjusted, poor sleep pattern (β = 0.22, 95% CI: 0.06~2.53, p = 0.001) was associated with elevated metabolic scores at the 2-year follow-up.ConclusionsThe elevated metabolic burden observed in college students with poor sleep patterns highlights the need to identify and address sleep problems in order to minimize the long-term impact on disease vulnerability.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Poor sleep pattern is associated with metabolic disorder during transition from adolescence to adulthood

et al. 2023

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“…In college, boys may have more time and resources than girls to exercise, especially playing football, basketball and outdoor sports. Exercise can effectively regulate negative emotions, relieve adolescents' study pressure, and effectively reduce the incidence of sleep disorders [12]. Exercise is one of the main regulators of people's physical and mental health.…”

Section: Gender Factors In Differences In Sleep Status Of Secondary S...mentioning

confidence: 99%

Analysis of Factors Influencing the Sleep Duration Insufficient of Secondary School Students in Kunshan

Wang

2023

SHS Web Conf.

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As growing sleep problems among secondary school students, this paper analyse the factors affecting the insufficient sleep time of secondary school students, with a view to providing clues for improving the insufficient sleep time of secondary school students. A total of 218 secondary school students in Kunshan were randomly selected to collect information on gender, school year, residence status, number of days of ≥60 min /d moderate-intensity exercise (d /w), and length of outdoor activities during the day (h /d); regression models were used to analyse the influencing factors of insufficient sleep time among the secondary school students. The rate of sleep deprivation among 218 secondary school students was 78.89%. It was found that female students had a higher risk of insufficient sleep than male students, high school students had a higher risk of insufficient sleep than junior high school students, and the number of days of moderate to high intensity and the amount of outdoor time during the daytime had a significant positive influence on the adequacy of sleep. Insufficient sleep is common among secondary school students in Kunshan, which should be taken seriously by families, schools and society, and relevant measures should be taken to improve the sleep time of secondary school students.

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“…Previous studies extensively analyzed teachers' stress, which directly affects teaching and learning activities [25,49,82]. It was observed that stress affects teachers' physical and mental health [83,84]. Excessive stressful conditions can also cause teachers' depression and reduce teaching performance, which interferes with sustainable education.…”

Section: Teachers' Stress Levelsmentioning

confidence: 99%

Key Factors Affecting Mathematics Teachers’ Well-Being and Stress Levels: An Extended Engagement Theory

Jian

Wijaya

2022

IJERPH

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The mathematics teachers’ profession often has many challenges. It also occupies important positions at the K-12 education level, in which mathematics knowledge is the basis of all scientific fields. This tends to cause high-stress levels and a negative effect on well-being. Mathematics teachers’ well-being has been less examined, and therefore this study aims to determine the factors affecting mathematics teachers’ well-being and stress levels. The 210 data points collected from Chinese mathematics teachers using a web-based questionnaire were analyzed for reliability and validity, then model fit and SEM were applied for model validation after removing 3 invalid data points and incomplete responses. The results showed that behavioral and cognitive engagements significantly affect teachers’ well-being, while the affective engagement was insignificant. The TPMK was the strongest significant predictor that had a positive impact on improving well-being and reducing stress levels. In addition, the stress level of mathematics teachers was influenced by gender and age. Finally, it was proven that teachers’ well-being significantly reduced stress levels. This study’s implication was to provide information on how to reduce stress levels.

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Interaction between physical activity and outdoor time on allostatic load in Chinese college students

Cited by 10 publications

References 28 publications

Poor sleep pattern is associated with metabolic disorder during transition from adolescence to adulthood

Poor sleep pattern is associated with metabolic disorder during transition from adolescence to adulthood

Analysis of Factors Influencing the Sleep Duration Insufficient of Secondary School Students in Kunshan

Key Factors Affecting Mathematics Teachers’ Well-Being and Stress Levels: An Extended Engagement Theory

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