How Sedentary Are University Students? A Systematic Review and Meta-Analysis

Abstract

Accumulating high volumes of sedentary behaviour is a risk factor for multiple negative health-related outcomes. The objective of this review was to synthesise the evidence on the levels of sedentary behaviour in university students. Screened records from 13 databases were included if (i) published after 2007 and (ii) reported on university students' amount of total or domain-specific sedentary behaviour. Sub-group and meta-regression analyses were conducted to investigate potential sources of heterogeneity (moderators). A total of 125 studies met the inclusion criteria. Most studies were cross-sectional (84%) and reported screen time (61%) or total sedentary time (39%). Self-reported data indicated that university students spend 7.29 h per day being sedentary. The levels of total sedentary behaviour were significantly higher when measured with accelerometers (M = 9.82 h per day). Computer use presented significantly higher prevalence over other modalities of screen time. Among the explored factors (i.e. countries' income, age, gender, and study's publication date), only publication date significantly moderated sedentary behaviour. Results suggest that a considerable proportion of university students (i) engage in higher levels of sedentary time compared to the general young adult population and (ii) accumulate levels of sedentary time that have been associated with an increased risk for detrimental health outcomes. In addition, meta-regression analyses suggest that sedentary time has increased over the last 10-year period among university students. These findings may inform future initiatives and policies targeting university students' sedentary behaviour. Further research is needed to identify the factors moderating sedentary behaviour in the university setting.

Associations of Objectively-Assessed Smartphone Use with Physical Activity, Sedentary Behavior, Mood, and Sleep Quality in Young Adults: A Cross-Sectional Study

“…The use of the smartphone is most prevalent in adolescents and young adults [12][13][14][15][16][17][18]. In the United States, more than 90% of the population above 13 years of age have access to a smartphone, and over 92% of adolescents and 88% of adults use social media platforms [12,13,19].…”

“…Research on college-aged individuals has shown that this population uses these devices four to eight hours per day, with the highest users interacting with the device almost non-stop [14,20]. Because interacting with smartphones has become an ever-present activity [15] it is important to understand the health effects of smartphone-based screen time accumulation [16], especially since screen-based sedentary behaviors are directly associated with health harms for young people [17] with evidence for cardiovascular risk factors [18], including higher blood pressure during exercise in youth [21] and low cardiorespiratory fitness [22]. Moreover, screen time ≥2 h per day was reported to be an important risk factor for overweight/obesity in those aged 21-30 years [23,24].…”

Using the Behavior Change Wheel to Understand University Students’ Prolonged Sitting Time and Identify Potential Intervention Strategies

“…University students are a population sub-group at risk of accumulating high levels of sitting time, as activities such as attending lectures and studying likely involve sitting for long periods [8]. Evidence from a recent meta-analysis indicates that university students report spending seven to eight hours sitting per day, with accelerometer-based estimates commonly two to three hours higher [9,10]. Research thus suggests that university students are highly sedentary [11], and that their daily sitting time is comparable to those of desk-based office workers [12].…”

Objective Measures to Assess Active Commuting Physical Activity to School in Young People: A Systematic Review Protocol and Practical Considerations

“…As recommended by a previous systematic review [ 38 ], the risk of bias will be evaluated according to the “The Cochrane Risk of Bias Tool 2” for randomised studies [ 45 ], “ROBINS-I” for non-randomised studies [ 46 ], and an adaptation of “The Cochrane Collaboration’s Tool for Assessing Risk of Bias” for observational studies [ 47 ]. Cochrane Risk of Bias Tool 2 [ 45 ] includes 5 items: (1) bias arising from the randomisation process; (2) bias due to deviations from intended interventions; (3) bias due to missing data; (4) bias in measurement outcomes; and (5) bias in the selection of the reported result.…”