Accessing physical activity among young adults attending a university: the role of sex, race/ethnicity, technology use, and sleep

Concordance Between Accelerometer-Measured and Self-Reported Physical Activity and Sedentary Time in Adults with Autism

This study examined the concordance between accelerometry-measured and self-reported physical activity (PA) and sedentary time in adults with autism. Twenty-four participants wore an ActiGraph GT3X + accelerometer for seven consecutive days and completed the International Physical Activity Questionnaire-Short Form (IPAQ-SF) on the last day of their study participation. Bland-Altman plots assessed the magnitude of agreement between the two measures. Nearly 80% of the participants accumulated the recommended ≥ 150 min of moderate to vigorous PA (MVPA)/week, but were also sedentary for over nine hours/day according to accelerometry data. Findings showed that adults with autism tended to overreport MVPA (b = 1.606, p < 0.01) and underreport sedentary time (b = 1.161, p = 0.03) via the IPAQ-SF, as compared to objective measurements.

Effect of physical exercise on sleep quality in college students: Mediating role of smartphone use

OBJECTIVE

To investigate the effect of physical exercise on sleep quality and the mediating effect of smartphone use behavior in college students.

METHODS

A cross-sectional study design was adopted. An online survey of 5,075 college students was conducted using the Physical Activity Rating Scale-3, the Pittsburgh Sleep Quality Index, and the Mobile Phone Addiction Tendency Scale.

RESULTS

The sleep quality of college students was poor, and the proportion of college students with good sleep quality was 23.567%. A significant correlation existed between sleep quality and physical exercise (r = -0.159, P < 0.001) and mobile phone addiction (r = 0.355, P < 0.001). Physical exercise can predict sleep quality in college students (β = -0.011, P < 0.001). Smartphone use plays a part in mediating the process by which physical exercise affects sleep quality.

CONCLUSION

Chinese college students have poor sleep quality. Physical exercise and smartphone use behavior are important factors affecting the sleep quality of college students. Physical exercise can directly predict the sleep quality of college students and can predict the sleep quality of college students through the mediating effect of smartphone use behavior.

The relationship of daily physical activity and sleep in adults: variations by age, sex, and race

Prior work suggests physical activity (PA) is related to quantity and quality of sleep. Questions remain regarding directionality, and whether relationships vary by age, sex, and race. We examined daily bidirectional associations between PA and sleep over one week. Participants were 427 adults from the MIDUS Biomarker study, with a mean age of 54.21 ± 11.67 (61% female, 30% non-white). PA (total activity) and sleep (total sleep time; TST and waking after sleep onset; WASO) were measured with an ActiWatch 64. Multilevel mixed-effects models showed differences in the relationships between PA and sleep by age, race, and sex. Following a day with increased PA, younger and nonwhite participants had significantly shorter TST. Days with higher PA were also associated with less WASO for younger participants. Bidirectional effects also emerged; following a night with shorter TST, men, not women, engaged in less next-day PA. Like other studies of daily PA and sleep, effect sizes were small. Future studies should assess potential mechanisms that could explain these demographic differences.

Institutional factors associated with college students' healthy physical activity and body composition: A first semester follow-up

Objective: The first aim of this study was to examine changes in freshman college students' health-enhancing physical activity (PA) and body composition across the first semester. Secondly, this study aimed to explore the role of socio-ecological variables on these processes. Methods: A sample of 166 participants (108 females, 58 males, M_age = 18.14[.96]) completed self-report pre-and posttest data on vigorous PA (VPA), moderate-to-vigorous PA (MVPA), and body mass index (BMI). Results: The results showed a statistically significant increase in BMI, but no statistically significant changes in VPA or MVPA. The findings revealed that our socio-ecological model predicted .71, .39, and .92 percent of the end of the year VPA, MVPA, and BMI, respectively. The findings highlighted the positive role of peer support, positive motivation, and university's Recreational Services on measured healthy behaviors. Conclusions: These findings suggest a need to increase college students' VPA.

How disability severity is associated with changes in physical activity and inactivity from adolescence to young adulthood

BACKGROUND

Disabilities may play a different role in determining people's physical activity (PA) and physical inactivity (PI) levels when they go through multiple lifetime transitions (e.g., graduation, marriage) between adolescence and young adulthood. This study investigates how disability severity is associated with changes in PA and PI engagement levels, focusing on adolescence and young adulthood, when the patterns of PA and PI are usually formed.

METHODS

The study employed data from Waves 1 (adolescence) and 4 (young adulthood) of the National Longitudinal Study of Adolescent Health, which covers a total of 15,701 subjects. We first categorized subjects into 4 disability groups: no, minimal, mild, or moderate/severe disability and/or limitation. We then calculated the differences in PA and PI engagement levels between Waves 1 and 4 at the individual level to measure how much the PA and PI levels of individuals changed between adolescence and young adulthood. Finally, we used two separate multinomial logistic regression models for PA and PI to investigate the relationships between disability severity and the changes in PA and PI engagement levels between the two periods after controlling for multiple demographic (age, race, sex) and socioeconomic (household income level, education level) variables.

RESULTS

We showed that individuals with minimal disabilities were more likely to decrease their PA levels during transitions from adolescence to young adulthood than those without disabilities. Our findings also revealed that individuals with moderate to severe disabilities tended to have higher PI levels than individuals without disabilities when they were young adults. Furthermore, we found that people above the poverty level were more likely to increase their PA levels to a certain degree compared to people in the group below or near the poverty level.

CONCLUSIONS

Our study partially indicates that individuals with disabilities are more vulnerable to unhealthy lifestyles due to a lack of PA engagement and increased PI time compared to people without disabilities. We recommend that health agencies at the state and federal levels allocate more resources for individuals with disabilities to mitigate health disparities between those with and without disabilities.

Physical Activity Patterns According to the Type of Physical Education Classes by Sex and Obesity among Korean Adolescents

This study aimed to compare physical activity patterns according to the type of physical education by sex and body mass index categories among Korean adolescents. We analyzed physical activity using an accelerator in a physical education class among Korean middle school students (1305 boys and 1328 girls). An independent t-test and regression analysis were conducted to compare differences between the obesity groups by sex. As game play time increased, light activity increased in boys in the normal group. Among the girls, sedentary time decreased in the normal, at-risk for obesity, and obese groups. Moderate activity increased in the underweight, normal, at-risk for obesity, and obese groups. Vigorous activity increased in the normal group. As free activity time increased, sedentary time also increased in the normal, at-risk for obesity, and obese groups. Vigorous activity decreased in the normal group. Among the girls, sedentary time increased in the underweight group. Light activity decreased in the underweight and normal groups. A strategy to increase physical activity during physical education class is to increase game play time for girls and decrease free activity time for boys.

Effect of Mobile Phone Addiction on Physical Exercise in University Students: Moderating Effect of Peer Relationships

OBJECTIVE

The influence of mobile phone addiction (MPA) on physical exercise in university students was explored, and peer relationships were introduced as a moderating variable.

METHODS

A cross-sectional study design was adopted, and an online survey questionnaire was conducted to investigate two universities in Nantong City, Jiangsu Province, and Chongzuo City, Guangxi Zhuang Autonomous Region. A total of 4959 university students completed the questionnaire. Measurement tools included the Mobile Phone Addiction Tendency Scale, the Physical Activity Rating Scale, and the Peer Rating Scale of university students.

RESULTS

University students scored 39.322 ± 15.139 for MPA and 44.022 ± 7.735 for peer relationships, with 87.8% of their physical exercise, in terms of exercise grade, being classified as medium or low intensity. The MPA of the university students was negatively correlated with peer relationships (r = -0.377, p < 0.001) and physical exercise behavior (r = -0.279, p < 0.001). The moderating effect of peer relationships on the MPA-physical exercise behavior relationship was significant (ΔR² = 0.03, p < 0.001).

CONCLUSIONS

The physical exercise of university students was at a medium or low intensity. The more serious the university students' addiction to mobile phones was, the lower the amount of physical exercise. The physical activity of males was higher than that of females. MPA and peer relationships were the limiting factors of the physical exercise behavior of university students. Under the lower effect of peer relationship regulation, MPA had a greater negative impact on physical exercise behavior. The data from this research can provide theoretical support to improve the participation of university students in physical activities.

Physical activity and mental health in sports university students during the COVID-19 school confinement in Shanghai

Background

In 2022, Shanghai was seriously affected by the coronavirus disease 2019 (COVID-19) pandemic. The government implemented citywide static management for 2 months, as well as all universities in Shanghai, which changed the normal learning and living style of sports students and led to a decline in physical activity level. As the physical activity has a strong correlation with mental health, this study aimed to investigate the current state of physical activity (PA) and mental health of the students in Shanghai University of Sport. It will try to reveal the correlation between PA and depressive symptoms, anxiety symptoms, fear of COVID-19 and smartphone addiction.

Methods

A cross-sectional survey was conducted on a random sample of 400 students who came from six different majors in May 2022 at the Shanghai University of Sport. Respondents completed the International Physical Activity Questionnaire Short Form (IPAQ-SF), the Chinese version of the 9-item Patient Health Questionnaire (PHQ-9), the Chinese version of the Generalized Anxiety Disorder Scale (GAD-7), the Chinese version of the COVID-19 Fear Scale (FCV- 19S), and the Smartphone Addiction Scale (SAS-SV). Demographics, PA, depressive symptoms, anxiety symptoms, fear of COVID-19, and smartphone addiction were compared. A binary logistic regression model was used for the further analysis.

Results

A total of 376 college students were included in the final analysis. Binary logistics analysis showed that moderate physical activity (MPA) was negatively correlated with depression (OR = 0.95, 95%CI = 0.93-0.98), anxiety (OR = 0.97, 95%CI = 0.95-0.99), fear of COVID 19(OR = 0.99, 95%CI = 0.98-0.99)and smartphone addiction (OR = 0.94, 95%CI = 0.9-0.98) (all P < 0.05). Sedentary behavior was positively correlated with smartphone addiction (OR = 1.01, P < 0.01, 95%CI = 1.001-1.004).

Conclusion

There was an association between the presence of MPA and depressive symptoms, anxiety symptoms, fear of COVID-19, smartphone addiction, and sedentary behavior associated with smartphone addiction levels. Clarifying the causal relationship between PA and mental health will require further research.

Physical Culture and Sports as an Educational Basis of Students' Healthy Physical Activities during and Post-Lockdown COVID-19 Restrictions

(1) Background: The SARS-CoV-2 virus manifests itself in many aspects of everyday life, among which one of the most frequently accentuated are changes in physical activity from the perspective of lockdown mobility limitations. The aim of this study was to assess the level of physical activity in groups of students with different levels of educational engagement in physical activity while taking into account the realities of remote and traditional education. (2) Methods: The study was conducted among 200 students of 3 majors with varying degrees of curriculum related to physical activity, including students of physical education (n-73), tourism and recreation (n-65) and students of a non-physical education major (n-62). The survey technique used was the short version of the International Physical Activity Questionnaire (IPAQ). (3) Results: PE students are the most engaged in physical activity compared to other study groups. This pattern is particularly true for high physical activity. An interesting observation is that, in the post-lockdown period, there was no statistically significant difference between the physical activity levels of PE students and TR students. Meanwhile, such a difference in favor of PE students was evident during the lockdown period. (4) Conclusions: Educational links to physical activity appear to be an important factor in stimulating this activity during times of epidemiological emergency.

Physical Activity and Sedentary Behavior in University Students–The Role of Gender, Age, Field of Study, Targeted Degree, and Study Semester

Background

Physical inactivity and sedentary behavior are modifiable risk factors for an unhealthy lifestyle in university students. The aim of this study was to identify subgroups among German university students with an increased risk for unhealthy behavior. For this purpose, differences in physical activity and sedentary behavior with respect to sociodemographic and study related factors were examined.

Methods

A total of 4,351 students participated in an online survey. The amount of physical activity (metabolic equivalent of task-min/week) and the sitting time (h/day) were assessed using the German short form of the International Physical Activity Questionnaire. Differences in gender and age as well as field of study, targeted degree and study semester were analyzed using a single factorial ANOVA with Tukey correction or a Welch-ANOVA with Games-Howell correction.

Results

For physical activity, significant differences were found for gender (F_{(2, 80.46)} = 17.79, p < 0.001, ηp2 = 0.009), for field of study (F_{(5, 1738.09)} = 7.41, p < 0.001, ηp2 = 0.01), and for study semester (F_{(1, 948.12)} = 5.53, p < 0.05, ηp2 =0.001), but not for age and targeted degree (p > 0.05). For sedentary behavior, significant differences were found for field of study (F_{(5, 3816)} = 5.69, p < 0.001, ηp2 = 0.01) and targeted degree (F_{(3, 3868)} = 3.94, p < 0.01, ηp2 = 0.003), but not for gender, age and study semester (p > 0.05).

Conclusion

Female students, students enrolled in “natural sciences, mathematics and informatics” and first year students appear to have an increased risk of an unhealthy lifestyle. Future research should identify barriers to and incentives of physical activity as well as reasons for high amounts of SB in sub-populations of university students. Suitable prevention and intervention programs are necessary.

Body weight perception and physical activity among young adults: Analysis from the national longitudinal study of adolescent to adult health

ObjectiveTo identify the young adults' perception of their weight and examine the associations between young adults' weight perception and physical activities. Participants: A total of 4,882 participants' responses were derived from the Add Health, Wave III. Method: Chi-square tests were used to examine the weight perception and multinomial logistic regression used to assess the association between weight perception and physical activities. Results: Perceived weight and weight management among male participants were significantly different from female participants (p<.001, p<.001, respectively). Young adults with self-perception of being "slightly overweight" and "very overweight" were more likely of participating in physical activities such as gymnastic/weight lift/strength (OR = 0.91, p <.001 and OR = 0.77, p<.001) and walking (OR = 1.08, p<.001 and OR = 1.13, p<.001). Conclusion: The study showed that physical activities significantly increased the probability of accurate perceived weight. Steps should be taken to implement interventions that increase accurate weight perception and promote physical activity among young adults.

Gender Differences in the Associations Between Physical Activity, Smartphone Use, and Weight Stigma

Background

Physical activity (PA) is important for health. However, there is little evidence on how weight stigma, time spent on sedentary activities (including smartphone, social media, online learning), time spent on outdoor activity, and nomophobia associate with PA among Chinese individuals with consideration of gender. The present study examined the aforementioned associations in the COVID-19 pandemic era.

Methods

University students (N = 3,135; 1,798 females, 1,337 males) with a mean age of 19.65 years (SD = 2.38) years completed an online survey from November to December, 2021. The online survey assessed weight stigma (using the Perceived Weight Stigma Scale and Weight Bias Internalization Scale), PA (using the International Physical Activity Questionnaire Short Form), time spent on different activities (using self-designed items for time on smartphone, outdoor activity, social media, and online learning), and nomophobia (using the Nomophobia Questionnaire). Parallel mediation models were constructed (dependent variable: PA; mediators: perceived weight stigma, weight-related self-stigma, time spent on smartphone, time spent on outdoor activity, time spent on social media, and time spent online learning; independent variable: nomophobia) and evaluated using Hayes' Process Macro Model 4 (IBM SPSS 20.0).

Results

Weight-related self-stigma (β = −0.06; p = 0.03), time spent on outdoor activity (β = 0.21; p < 0.001), time spent on social media (β = 0.07; p = 0.02), time spent on online learning (β = 0.06; p = 0.03), and nomophobia (β = −0.07; p = 0.01) were all significant factors explaining the PA among female participants. Perceived weight stigma (β = −0.07; p = 0.01), time spent on outdoor activity (β = 0.27; p < 0.001), and time spent on online learning (β = 0.10; p = 0.002) were all significant factors explaining PA among male participants.

Conclusion

Chinese healthcare providers should design programs on weight stigma reduction and outdoor activity improvement to enhance PA among university students.

Ecological Momentary Assessment of Physical Activity and Wellness Behaviors in College Students Throughout a School Year: Longitudinal Naturalistic Study

Background

The Wellness Environment app study is a longitudinal study focused on promoting health in college students.

Objective

The two aims of this study were (1) to assess physical activity (PA) variation across the days of the week and throughout the academic year and (2) to explore the correlates that were associated with PA, concurrently and longitudinally.

Methods

The participants were asked to report their wellness and risk behaviors on a 14-item daily survey through a smartphone app. Each student was provided an Apple Watch to track their real time PA. Data were collected from 805 college students from Sept 2017 to early May 2018. PA patterns across the days of the week and throughout the academic year were summarized. Concurrent associations of daily steps with wellness or risk behavior were tested in the general linear mixed-effects model. The longitudinal, reciprocal association between daily steps and health or risk behaviors were tested with cross-lagged analysis.

Results

Female college students were significantly more active than male ones. The students were significantly more active during the weekday than weekend. Temporal patterns also revealed that the students were less active during Thanksgiving, winter, and spring breaks. Strong concurrent positive correlations were found between higher PA and self-reported happy mood, 8+ hours of sleep, ≥1 fruit and vegetable consumption, ≥4 bottles of water intake, and ≤2 hours of screen time (P<.001). Similar longitudinal associations found that the previous day’s wellness behaviors independently predicted the following day’s higher PA except for mood. Conversely, the higher previous-day PA levels were associated with better mood, more fruit and vegetable consumption, and playing less music, but with higher liquor consumption the next day.

Conclusions

This study provides a comprehensive surveillance of longitudinal PA patterns and their independent association with a variety of wellness and risk behaviors in college students.

Health-related consequences of the type and utilization rates of electronic devices by college students

Background

College students are leading an evolution of device use both in the type of device and the frequency of use. They have transitioned from desktop stations to laptops, tablets, and especially smartphones and use them throughout the day and into the night.

Methods

Using a 35-min online survey, we sought to understand how technology daily usage patterns, device types, and postures affect pain and discomfort to understand how knowledge of that pain might help students avoid it. Data were analyzed from 515 students (69.5% male) who completed an internet-delivered survey (81.3% response rate).

Results

Participants ranked smartphones as their most frequently used technology (64.0%), followed by laptops and tablets (both 53.2%), and desktop computers (46.4%). Time spent using smartphones averaged over 4.4 h per day. When using their devices, students were more likely to adopt non-traditional workplace postures as they used these devices primarily on the couch or at a chair with no desk.

Conclusion

Recent trends in wireless academic access points along with the portability of small handheld devices, have made smartphones the most common link to educational materials despite having the least favorable control and display scenario from an ergonomic perspective. Further, the potential impact of transitions in work environments due to COVID-19 may further exacerbate ergonomic issues among millions highlighting the need for such work to be carried out.

Changes in Physical Activity and Sedentary Behavior in Chinese Young Adults during the COVID-19 Pandemic: A Repeated-Measure Study throughout One Year

Though we know physical activity (PA) decreased while sedentary behavior (SB) increased compared to that before the COVID-19 pandemic, little is known about subsequent changes in PA and SB throughout one year in the post-pandemic era. This study aimed to examine the changes in PA and SB in a sample of Chinese young adults using a four-wave repeated-measure design during the pandemic. A total of 411 participants provided self-reported data of sociodemographic characteristics (e.g., sex, age), PA, and SB. Nonparametric tests and generalized estimating equations were conducted. Results revealed significant changes in moderate to vigorous PA (MVPA), light PA (LPA), and SB. The MVPA of Wave 1, 2, and 3 was significantly less than that of Wave 4 (p < 0.001); the LPA of Wave 1 and 2 was significantly less than that of Wave 4; the SB of Wave 1 was significantly more than that of Wave 4 (p < 0.05). Being female was the only predictor of changes in MVPA (Beta = −0.311, p< 0.001). Being female (Beta = 0.115, p = 0.003) and perceived family affluence (Beta = −0.059, p< 0.001) were predictors of changes in SB. As such, PA was less, while SB was more during the early stages of the pandemic. With the progress of the pandemic stages, health behaviors in young adults have been gradually improved. Sex and perceived family affluence were two important factors in predicting health behaviors. Our results can inform efficient policies or interventions in the COVID-19 era and future similar public health events.

The effect of COVID-19 pandemic and quarantine period on physical activity and dietary habits of college-aged students

The coronavirus disease 2019 (COVID-19) pandemic led to sudden extreme changes in lifestyle, potentially causing adverse changes in physical activity, sedentary behavior, and dietary habits. The objective of the study was to investigate the effects of COVID-19 quarantine on physical activity, dietary habits, and food insecurity among college students who were impacted by the quarantine periods and campus closures. The findings of the study will provide preliminary evidence on dietary, physical activity, and sedentary behavior changes induced by the pandemic among college students.

Participants (n ​= ​403) completed a cross-sectional self-report online questionnaire, evaluating the physical activity, sedentary behavior, and dietary behaviors before- and during-COVID-19 campus closures (March–May 2020). Sociodemographic and descriptive information was also obtained from each participant. Wilcoxon signed-rank test was used to assess changes in physical activity, sedentary behavior, and dietary habits. McNemar's test was used to compare food insecurity changes. Data were presented as median and interquartile range.

A total of 291 participants who met the inclusion criteria were enrolled in the study (college-aged, 18–24 years). Physical activity decreased at vigorous (2 days/week to 1 day/week, p ​< ​0.001), moderate (4 days/week to 1 day/week, p ​< ​0.001), and light (4 days/week to 2 days/week, p ​< ​0.001) intensity levels, while sedentary behavior increased (4 ​h/day to 7 ​h/day, p ​< ​0.001) from pre-to during-COVID-19 quarantine period. Frequencies of meals at home and alcohol consumption increased (Z ​= ​−3.911 and Z ​= ​−4.022, p ​< ​0.001), while frequency of fruit consumption decreased (Z ​= ​−2.116, p ​< ​0.001) from pre-to during-COVID-19 quarantine period. Daily alcohol intake also increased during COVID-19 quarantine period (Z ​= ​−4.442, p ​< ​0.001). Lastly, the percentage of individuals reporting food insecurity significantly increased during COVID-19 quarantine (p ​< ​0.001).

College-aged students in quarantine significantly decreased physical activity participation and increased sedentary behavior. Changes in dietary habits were observed, including increased meals at home, alcohol consumption, and decreased fruit consumption. Food insecurity also doubled among college-aged students during quarantine. Public health strategies to attenuate these changes in lifestyle habits should be implemented during a global pandemic.

The Biological and Motivational Effects of Aerobic Exercise With Virtual Reality

Purpose: There is no significant evidence of both biological and motivational effects between virtual reality exercises to traditional/conventional exercise. The aim of this study is to assess the biological and motivational effects of aerobic exercises with virtual reality and traditional exercise methods. Methods: 20 students participated as control and 60 students were divided randomly and equally into two groups, virtual reality exercise group (VRE) and traditional exercise group (TE). Two groups completed the exercise training. Tests were applied to the three groups at the beginning and in the end of the study. An activity monitor and pulse oximeter were used to measure energy expenditure during exercises. Results: After eight weeks, the data from pulse oximeter showed no statistical significance between the exercise groups. The active energy expenditure, PAL and step counts were statistically significant in TE group. There was a statistically significant increase in the sleep quality of the TE group (p = .000). There was no statistical significance among the anxiety scores of all groups. In the spring semester, there was a statistically significant increase in both VRE and TE groups compared to the fall semester (p < .05). Conclusion: The virtual reality exercises produce greater motivational effects, whereas traditional exercises bring greater physical improvements.

Physical activity and sleep quality correlations with anthropometric measurements in young adults

OBJECTIVE

This cross-sectional study examined correlations between physical activity and anthropometrics as well as sleep quality and anthropometrics.

PARTICIPANTS

College students (n = 85) with average age 25.6 ± 5.4 years.

METHODS

Participants received full-body dual-energy x-ray absorptiometry scans and completed validated surveys: Habitual Physical Activity questionnaire, Pittsburgh Sleep Quality Index (PSQI), and Epworth Sleepiness Scale.

RESULTS

Males reported more sports-related physical activity than females (p = 0.041). Physical activity indices and percent body fat were inversely correlated (total ⍴ = -0.320, p < 0.001; sport β = -0.378, p = 0.003). Participants had poor overall sleep quality (PSQI = 6.19 ± 2.99). The PSQI sleep quality index: disturbance was directly correlated with body mass index (BMI) (β = 0.328, p = 0.007).

CONCLUSION

Health interventions on college campuses should promote more physical activity and better quality sleep as these factors were related to improved body anthropometrics and potentially reduced chronic disease risk.

Epidemiology of health risk behavior among university students

Introduction: Moderate and vigorous physical activity is essential to maintain proper body composition, to reduce the risk of ischemic heart disease, diabetes, and cancer. In addition, it reduces the risk of stroke, hypertension, and depression. Even so, it is an essential determinant of energy expenditure and, therefore, fundamental for energy balance and weight control. Objective: The objective of this epidemiological study is twofold: to quantify and qualify the physical activity of students at the Federal University of Mato Grosso (UFMT) and to compare the level of physical activity of incoming and graduating students. Methodology: The present study used the National College Health Behavior Survey (NCHRBS) questionnaire adapted and validated for use by Brazilian undergraduate students and addressed only aspects related to physical activity. Of the 18,986 students enrolled on UFMT's 5 campuses, 9,720 students accessed the questionnaire. Of these, 7,379 had their answers validated, corresponding to 75.92% of accesses or 38.87% of the universe studied. Results: This study found differences in the level of physical activity among university students, observing less physical activity on the Rondonópolis campus, less physical activity for students in the areas of Linguistics and Letters, when compared with students from other areas, less physical activity in students females when compared to males and less physical activity among freshmen compared to graduates. Conclusion: The study suggest the need for greater investment in policies to promote physical activity among university students in all areas.

Sleep and physical activity in university students: A systematic review and meta-analysis

University students have low levels of physical activity and report disturbances to sleep, which are independently associated with poor health outcomes. Some research suggests that there is a bi-directional relationship between sleep and physical activity in adults. However, the relationship between sleep and physical activity in university students has not yet been evaluated. Therefore, the aim of this systematic review and meta-analysis was to qualitatively synthesise and quantitatively evaluate the evidence for the association between sleep and physical activity in university students. Twenty-nine eligible studies were included, with a total of 141,035 participants (43% men and 57% women). Only four studies used device-based measures of sleep and/or physical activity, with the remainder including self-report measures. Qualitative synthesis found that the majority of studies did not find any association between sleep and physical activity in university students. However, random-effects meta-analysis showed that moderate-to-high intensity physical activity was associated with lower PSQI scores (e.g., better sleep quality) [r = -0.18, 95% CI (-0.37, 0.03), p = 0.100]. Further, a weak negative association between moderate-to-vigorous physical activity level and sleep duration was also found [r = -0.02, 95% CI (-0.16, 0.12), p = 0.760]. As the findings of this review are predominantly derived from cross-sectional investigations, with limited use of device-based measurement tools, further research is needed to investigate the relationship between sleep and physical activity in university students. Future studies should employ longitudinal designs, with self-report and device-based measures, and consider the intensity and time of physical activity as well as records of napping behaviour.

Association between the pattern of mobile phone use and sleep quality in Northeast China college students

OBJECTIVES

Currently, mobile penetration is high amongst college students. The aims of this study were to investigate the characteristics of mobile phone use and to explore the influence of mobile phone use characteristics on sleep quality amongst college students.

METHODS

From December 2016 to January 2017, we collected mobile phone use characteristics and sleep quality data using the Pittsburgh Sleep Quality Index (PSQI) and standardised questionnaires that were answered by 4500 medical university students in Liaoning Province (actual response rate of 94%, n = 4234 college students). This study used the SPSS 21.0 software to establish the database and perform the statistical analysis.

RESULTS

One hundred percent of the college students had mobile phones and used mobile phones for entertainment (91%), work (51%), obtaining information (61%), and other purposes (23%). Additionally, there was a statistically significant difference in the PSQI score between students who held the phone at a distance of more than 10 cm from their eyes and those who held it a distance of less than 10 cm (P = 0.002). Multiple logistic regression analysis showed that the risk of poor sleep quality was 1.21-1.53 times higher for those who spent more than 5 h a day using their phones and 1.41-1.59 times higher for those who used their phones for more than half an hour before going to bed when the lights were off.

CONCLUSIONS

Daily cumulative mobile phone use and use with the lights off before sleep are associated with poorer sleep quality.

Relationships of Sleep Duration, Midpoint, and Variability with Physical Activity in the HCHS/SOL Sueño Ancillary Study

OBJECTIVE/BACKGROUND

Short and long sleep duration, later sleep midpoint, and greater intra-individual sleep variability are associated with lower physical activity, but previous research lacks objective and concurrent assessment of sleep and physical activity. This cross-sectional study examined whether sleep duration, midpoint, and variability in duration and midpoint were related to wrist actigraphy-measured physical activity.

PARTICIPANTS

Participants were 2156 Hispanics/Latinos in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) Sueño Ancillary Study.

METHODS

Participants wore Actiwatch devices to measure sleep and physical activity via the wrist for ≥5 days. Physical activity was defined as minutes/day in the upper quartile of the sampling distribution's non-sleep activity, capturing light to vigorous physical activity.

RESULTS

An inverse linear relationship between sleep duration and physical activity was found such that each additional sleep hour related to 29 fewer minutes of physical activity (B = -28.7, SE = 3.8), p < .01). Variability in sleep midpoint was also associated with physical activity; with each 1-hr increase in variability there were 24 more minutes of physical activity (B = 24.2, SE = 5.6, p < .01). In contrast, sleep midpoint and variability in duration were not associated with physical activity. Sensitivity analyses identified an association of short sleep duration and greater variability in sleep duration with greater accelerometry-derived moderate-to-vigorous physical activity measured at the HCHS/SOL baseline (M = 2.1 years before the sleep assessment).

CONCLUSIONS

Findings help clarify inconsistent prior research associating short sleep duration and sleep variability with greater health risks but also contribute novel information with simultaneous objective assessments.

Profile and determinants of daily physical activity objectively assessed in university students

BACKGROUND

The aim of this study was to quantify and compare physical activity (PA) levels of university students from different fields of study, and to investigate its correlates.

METHODS

221 students (111 female, 20 [18-23] years), from different study fields were cross-sectionally assessed for daily PA (pedometer), cardiorespiratory fitness (20 m Shuttle Run Test-20mSRT), health-related quality of life (HRQoL), anxiety and depression symptoms.

RESULTS

In general, 60% of the students were physically active (>8000 steps/day), presented good HRQoL and cardiorespiratory fitness, minimal symptoms of depression and moderate of anxiety. The highest PA level was observed in students from physical education and sport sciences, and the lowest in those from social sciences (median [IQR]: 9882 [8435-13510] versus 7593 [6070-9753] steps/day, respectively; P<0.01). Male students were more active than female. Steps/day was moderately associated with VO<inf>2</inf>max (r=0.42), VO<inf>2</inf>%pred (r=0.41) and distance achieved in the 20mSRT (r=0.43) (P<0.0001 for all), and weakly associated with anxiety symptoms (r=-0.20; P=0.004) and HRQoL domains (0.15<r<0.21; P<0.05). Distance achieved in the 20mSRT was the only determinant of steps/day (adjusted R2=0.22; P<0.0001).

CONCLUSIONS

Most university students can be considered as physically active. In these young adults, lower PA level correlates moderately with worse cardiorespiratory fitness and weakly with worse HRQoL and anxiety symptoms.

Physical Activity among Spanish Undergraduate Students: A Descriptive Correlational Study

Achieving the recommended levels of physical activity (PA) is associated with better health. Despite this, most undergraduate students report low levels of PA. This study aimed to assess the achievement of recommended PA levels in a wide sample of undergraduate students from Madrid (N = 2960). Overall PA and leisure-time PA (LTPA) were measured with the Global Physical Activity Questionnaire (GPAQ). Descriptive analyses and logistic regression were performed. It was revealed that 22.4% and 55.6% of overall PA and LTPA, respectively, did not achieve World Health Organization (WHO) recommendations. When PA was measured as overall PA, the achievement of the recommended level was positively predicted by male sex; a Body Mass Index (BMI) indicative of normal weight or being overweight; spending less time sitting or reclining; work; and studying health science, social sciences, engineering, or architecture (all p < 0.001; r² = 0.075). Using LTPA, the positive predictors of achieving recommended PA levels were male sex, having a BMI indicative of normal weight or being overweight, work, studying at a public university, and studying health science (r² = 0.048). These findings suggest that universities should implement strategies to promote PA.

Smartphone Use Predicts Being an "Active Couch Potato" in Sufficiently Active Adults

Purpose: To investigate the relationship between smartphone use, television viewing, and the "active couch potato" in sufficiently active adults. Methods: A sample of 328 sufficiently active adults aged 18 to 80 years (mean ± SD = 38 ± 15 years) completed surveys assessing smartphone use, television viewing, physical activity, and sedentary behavior. Active couch potatoes were defined as individuals who met physical activity guidelines and engaged in 8 or more hours per day of sedentary behavior. Results: Mean smartphone use was 4.04 ± 3.74 hours per day. There were 128/328 (39%) participants coded as active couch potatoes. Active couch potato was significantly positively (Wald = 7.326, P = .007) associated with smartphone use. Being an active couch potato was not (Wald = 0.658, P = .417) associated with television viewing. Sedentary behavior and smartphone use were significantly greater (t ≥ 3.55, P < .001) among active couch potatoes (11.35 ± 3.25 hours sitting per day, 4.95 ± 4.5 hours smartphone use per day) than sufficiently active, nonsedentary individuals (5.06 ± 1.64 hours sitting per day, 3.45 ± 3.04 hours smartphone use per day). Conclusion: In sufficiently active adults, smartphone use predicted being an active couch potato and television viewing did not.

Gender Differences in Predictors of Physical Activity among Korean College Students Based on the Health Promotion Model

Aim: Despite the numerous physical and psychological benefits of physical activity (PA), the prevalence of achieving PA recommendations decreases in college students. Therefore, this study was conducted to identify factors influencing PA in male and female college students based on the Health Promotion Model.

Methods: A quantitative, cross-sectional research design was used to investigate factors influencing PA among male and female college students. A convenience sample of 264 Korean students was recruited from three colleges. Participants completed measures of physical activity, perceived benefits/barriers to PA, PA self-efficacy, activity-related affect, and peer support.

Results: A multiple regression analysis indicated that the factors affecting PA in male college students were PA self-efficacy and subjective economic status, while the factors affecting PA in female students were PA self-efficacy, subjective health status, activity-related affect, and peer support.

Conclusions: School health centers or wellness centers need to develop exercise self-efficacy enhancement programs to provide motivation for PA among college students. It might also be necessary to develop a customized PA program that considers gender differences.