Previous research has linked sedentary behaviour (SB) to adverse physical health outcomes in adults and youth. Although evidence for the relationship between SB and mental health outcomes (e.g., depression) is emerging, little is known regarding risk of anxiety. A systematic search for original research investigating the association between SB and risk of anxiety was performed using numerous electronic databases. A total of nine observational studies (seven cross-sectional and two longitudinal) were identified. Methodological quality of studies was assessed and a best-evidence synthesis was conducted. One cross-sectional study demonstrated a strong methodological quality, five cross-sectional studies demonstrated a moderate methodological quality and three studies (two cross-sectional one longitudinal) received a weak methodological quality rating. Overall, there was moderate evidence for a positive relationship between total SB and anxiety risk as well as for a positive relationship between sitting time and anxiety risk. There was inconsistent evidence for the relationship between screen time, television viewing time, computer use, and anxiety risk. Limited evidence is available on the association between SB and risk of anxiety. However, our findings suggest a positive association (i.e. anxiety risk increases as SB time increases) may exist (particularly between sitting time and risk of anxiety). Further high-quality longitudinal/interventional research is needed to confirm findings and determine the direction of these relationships.

Background: Government responses to managing the COVID-19 pandemic may have impacted the way individuals were able to engage in physical activity. Digital platforms are a promising way to support physical activity levels and may have provided an alternative for people to maintain their activity while at home. Objective: This study aimed to examine associations between the use of digital platforms and adherence to the physical activity guidelines among Australian adults and adolescents during the COVID-19 stay-at-home restrictions in April and May 2020. Methods: A national online survey was distributed in May 2020. Participants included 1188 adults (mean age 37.4 years, SD 15.1; 980/1188, 82.5% female) and 963 adolescents (mean age 16.2 years, SD 1.2; 685/963, 71.1% female). Participants reported demographic characteristics, use of digital platforms for physical activity over the previous month, and adherence to moderate- to vigorous-intensity physical activity (MVPA) and muscle-strengthening exercise (MSE) guidelines. Multilevel logistic regression models examined differences in guideline adherence between those who used digital platforms (ie, users) to support their physical activity compared to those who did not (ie, nonusers). Results: Digital platforms include streaming services for exercise (eg, YouTube, Instagram, and Facebook); subscriber fitness programs, via an app or online (eg, Centr and MyFitnessPal); facilitated online live or recorded classes, via platforms such as Zoom (eg, dance, sport training, and fitness class); sport- or activity-specific apps designed by sporting organizations for participants to keep up their skills (eg, TeamBuildr); active electronic games (eg, Xbox Kinect); and/or online or digital training or racing platforms (eg, Zwift, FullGaz, and Rouvy). Overall, 39.5% (469/1188) of adults and 26.5% (255/963) of adolescents reported using digital platforms for physical activity. Among adults, MVPA (odds ratio [OR] 2.0, 95% CI 1.5-2.7), MSE (OR 3.3, 95% CI 2.5-4.5), and combined (OR 2.7, 95% CI 2.0-3.8) guideline adherence were higher among digital platform users relative to nonusers. Adolescents’ MVPA (OR 2.4, 95% CI 1.3-4.3), MSE (OR 3.1, 95% CI 2.1-4.4), and combined (OR 4.3, 95% CI 2.1-9.0) guideline adherence were also higher among users of digital platforms relative to nonusers. Conclusions: Digital platform users were more likely than nonusers to meet MVPA and MSE guidelines during the COVID-19 stay-at-home restrictions in April and May 2020. Digital platforms may play a critical role in helping to support physical activity engagement when access to facilities or opportunities for physical activity outside the home are restricted.

Background: Stroke has been linked to a lack of physical activity; however, the extent of the association between inactive lifestyles and stroke risk has yet to be characterized across large populations.Purpose: This study aimed to explore the association between activity‐related behaviors and stroke incidence.Methods: Data from 1999 to 2018 waves of the concurrent cross‐sectional National Health and Nutrition Examination Survey (NHANES) were extracted. We analyzed participants characteristics and outcomes for all participants with data on whether they had a stroke or not and assessed how different forms of physical activity affect the incidence of disease.Results: Of the 102,578 individuals included, 3851 had a history of stroke. A range of activity‐related behaviors was protective against stroke, including engaging in moderate‐intensity work over the last 30 days (OR = 0.8, 95% CI = 0.7–0.9; P = 0.001) and vigorous‐intensity work activities over the last 30 days (OR = 0.6, 95% CI = 0.5–0.8; P < 0.001), and muscle‐strengthening exercises (OR = 0.6, 95% CI = 0.5–0.8; P < 0.001). Conversely, more than 4 h of daily TV, video, or computer use was positively associated with the likelihood of stroke (OR = 11.7, 95% CI = 2.1–219.2; P = 0.022).Conclusion: Different types, frequencies, and intensities of physical activity were associated with reduced stroke incidence, implying that there is an option for everyone. Daily or every other day activities are more critical in reducing stroke than reducing sedentary behavior duration.

Clusters of adolescents differentiated by patterns of physical activity and sedentary behavior (activity-related typologies) are common. Understanding both the characteristics of adolescents and modifiable correlates of these typologies, can help to develop interventions for those most at risk. This systematic review aimed to synthesize the socio-demographic characteristics and modifiable correlates of activity-related behavioral typologies among adolescents. A systematic search of seven electronic databases was conducted to identify quantitative studies using person-oriented statistical approaches to identify activity-related behavioral typologies among 12–18 year-olds. This systematic review was registered in Prospero (registration number: CRD42016046879). Thirty-six studies met the inclusion criteria and were classified according to three sub-themes based on behaviors included in the typologies (1. physical activity and sedentary behavior only; 2. physical activity, sedentary behavior and risk-related behaviors; 3. physical activity, sedentary behavior and diet). Studies were mostly cross-sectional and relied on self-report measures. Methods were considerably heterogeneous, however results revealed some consistency in typologies within specific groups. For example, typologies characterized by unhealthy behavior patterns (e.g., characterized by physical inactivity, high sedentary behavior and poor diet or high risk-related behaviors) comprised more older adolescents. With the exception of socio-demographics (age, sex, body mass index and socio-economic status), very few correlates have been studied to date (mostly school-related behavioral factors and intrapersonal influences), with evidence largely from typologies comprised of physical activity, sedentary behavior and diet. More research is needed to assess a range of modifiable correlates associated with activity-related behavior typologies among adolescents. This will allow for more targeted interventions, to achieve long-lasting, positive behavior change in adolescent populations.

Objectives: To examine i) the use of mobile apps and fitness trackers in adults during the COVID-19 pandemic to support health behaviors; ii) the use of COVID-19 apps; iii) associations between using mobile apps and fitness trackers, and health behaviors; iv) differences in usage amongst population subgroups. Methods: An online cross-sectional survey was conducted during June–September 2020. The survey was developed and reviewed independently by co-authors to establish face validity. Associations between using mobile apps and fitness trackers and health behaviors were examined using multivariate logistic regression models. Subgroup analyses were conducted using Chi-square and Fisher’s exact tests. Three open-ended questions were included to elicit participants’ views; thematic analysis was conducted. Results: Participants included 552 adults (76.7% women; mean age: 38±13.6 years); 59.9% used mobile apps for health, 38.2% used fitness trackers, and 46.3% used COVID-19 apps. Users of mobile apps or fitness trackers had almost two times the odds of meeting aerobic physical activity guidelines compared to non-users (odds ratio = 1.91, 95% confidence interval 1.07 to 3.46, P = .03). More women used health apps than men (64.0% vs 46.8%, P = .004). Compared to people aged 18–44 (46.1%), more people aged 60+ (74.5%) and more people aged 45–60 (57.6%) used a COVID-19 related app (P < .001). Qualitative data suggest people viewed technologies (especially social media) as a ‘double-edged sword’: helping with maintaining a sense of normalcy and staying active and socially connected, but also having a negative emotional effect stemming from seeing COVID-related news. People also found that mobile apps did not adapt quickly enough to the circumstances caused by COVID-19. Conclusions: Use of mobile apps and fitness trackers during the pandemic was associated with higher levels of physical activity, in a sample of educated and likely health-conscious individuals. Future research is needed to understand whether the association between using mobile devices and physical activity is maintained in the long-term.