Abstract:Decreases in individuals’ physical activity and increases in sedentary behavior and bodyweight have been reported during the COVID-19 pandemic. The present study assessed the ability of physical activity monitoring, which may promote physical activity and discourage sedentary behavior, to mitigate these negative outcomes. An evaluation of university samples (N = 404, 40.5 ± 15.4 years) of self-reported physical activity, sedentary behavior, and bodyweight prior to the closure of campus due to the pandemic in M… Show more
“…Previous studies have been conducted which investigate the influence of COVID-19 lockdowns on physical activity and behavioral changes using both subjective and objective means. Study findings among published work largely agree that COVID-19 lockdown restrictions posed a health risk due to behavioral changes resulting from altered routines (particularly for nonessential workers), reduced amount or intensity of physical activity, and increased bouts of sedentary behavior (Barkley et al, 2021;Kingsnorth et al, 2021). However, due to the nature of lockdown restrictions, such studies possess limitations associated with one or a combination of the following: reliance on self-reported measures, memory recall and candor (Buoite Stella et al, 2021); compliance (Fernández-García et al, 2021); representative demographics among participants (Kingsnorth et al, 2021;Stockwell et al, 2021); and population size; use of multiple device types and settings used to monitor activity levels (which introduced an array of measurement error due to heterogeneity; Buoite Stella et al, 2021;Germini et al, 2022).…”
Introduction: The COVID-19 lockdown introduced restrictions to free-living activities. Changes to these activities can be accurately quantified using combined measurement. Using activPAL3 and self-reports to collect activity data, the study aimed to quantify changes that occurred in physical activity and sedentary behavior between prelockdown and lockdown. The study also sought to determine changes in indoor and outdoor stepping. Methods: Using activPAL3, four participants recorded physical activity data prelockdown and during lockdown restrictions (February–June 2020). Single events (sitting, standing, stepping, lying) were recorded and analyzed by the CREA algorithm using an event-based approach. The analysis focused on step count, sedentary time, and lying (in bed) time; median and interquartile range were calculated. Daily steps classified as taking place indoors and outdoors were calculated separately. Results: 33 prelockdown and 92 in-lockdown days of valid data were captured. Median daily step count across all participants reduced by 14.8% (from 5,828 prelockdown to 4,963 in-lockdown), while sedentary and lying time increased by 4% and 8%, respectively (sedentary: 9.98–10.30 hr; lying: 9.33–10.05 hr). Individual variations were observed in hours spent sedentary (001: 8.44–8.66, 002: 7.41–8.66, 003: 11.97–10.59, 004: 6.29–7.94, and lying (001: 9.69–9.49, 002: 11.46–11.66, 003: 7.63–9.34, 004: 9.7–11.12) pre- and in-lockdown. Discrepancies in self-report versus algorithm classification of indoor/outdoor stepping were observed for three participants. Conclusion: The study quantitively showed lockdown restrictions negatively impacted physical activity and sedentary behavior; two variables closely linked to health outcomes. This has important implications for public health policies to help develop targeted interventions and mandates that encourage additional physical activity and lower sedentary behavior.
“…Previous studies have been conducted which investigate the influence of COVID-19 lockdowns on physical activity and behavioral changes using both subjective and objective means. Study findings among published work largely agree that COVID-19 lockdown restrictions posed a health risk due to behavioral changes resulting from altered routines (particularly for nonessential workers), reduced amount or intensity of physical activity, and increased bouts of sedentary behavior (Barkley et al, 2021;Kingsnorth et al, 2021). However, due to the nature of lockdown restrictions, such studies possess limitations associated with one or a combination of the following: reliance on self-reported measures, memory recall and candor (Buoite Stella et al, 2021); compliance (Fernández-García et al, 2021); representative demographics among participants (Kingsnorth et al, 2021;Stockwell et al, 2021); and population size; use of multiple device types and settings used to monitor activity levels (which introduced an array of measurement error due to heterogeneity; Buoite Stella et al, 2021;Germini et al, 2022).…”
Introduction: The COVID-19 lockdown introduced restrictions to free-living activities. Changes to these activities can be accurately quantified using combined measurement. Using activPAL3 and self-reports to collect activity data, the study aimed to quantify changes that occurred in physical activity and sedentary behavior between prelockdown and lockdown. The study also sought to determine changes in indoor and outdoor stepping. Methods: Using activPAL3, four participants recorded physical activity data prelockdown and during lockdown restrictions (February–June 2020). Single events (sitting, standing, stepping, lying) were recorded and analyzed by the CREA algorithm using an event-based approach. The analysis focused on step count, sedentary time, and lying (in bed) time; median and interquartile range were calculated. Daily steps classified as taking place indoors and outdoors were calculated separately. Results: 33 prelockdown and 92 in-lockdown days of valid data were captured. Median daily step count across all participants reduced by 14.8% (from 5,828 prelockdown to 4,963 in-lockdown), while sedentary and lying time increased by 4% and 8%, respectively (sedentary: 9.98–10.30 hr; lying: 9.33–10.05 hr). Individual variations were observed in hours spent sedentary (001: 8.44–8.66, 002: 7.41–8.66, 003: 11.97–10.59, 004: 6.29–7.94, and lying (001: 9.69–9.49, 002: 11.46–11.66, 003: 7.63–9.34, 004: 9.7–11.12) pre- and in-lockdown. Discrepancies in self-report versus algorithm classification of indoor/outdoor stepping were observed for three participants. Conclusion: The study quantitively showed lockdown restrictions negatively impacted physical activity and sedentary behavior; two variables closely linked to health outcomes. This has important implications for public health policies to help develop targeted interventions and mandates that encourage additional physical activity and lower sedentary behavior.
“…Literature has shown changes associated with pandemic-related restrictions may have resulted in decreased physical activity, increased sedentary behavior, and increased bodyweight 6,26,27 . Our results support previous literature suggesting the pandemic-related restrictions may have had a negative impact on sedentary behavior and bodyweight 6,26,27 .…”
Section: Discussionmentioning
confidence: 99%
“…Literature has shown changes associated with pandemic-related restrictions may have resulted in decreased physical activity, increased sedentary behavior, and increased bodyweight 6,26,27 . Our results support previous literature suggesting the pandemic-related restrictions may have had a negative impact on sedentary behavior and bodyweight 6,26,27 . Presently, we report that regardless of cell phone use individuals experienced an overall increase in weekly reported sitting as well as an increase in reported bodyweight during the pandemic.…”
Introduction: Cell phone use is associated with physical activity and sedentary behavior. These relationships have not been assessed in the context of the COVID-19 pandemic. This study assessed the potential effects of pandemic-related restrictions on cell phone use and the possible relationship of altered cell phone use to physical activity, sedentary behavior, and bodyweight.
Methods: Participants (N = 307) completed a survey assessing cell phone use, physical activity, sedentary behavior, and bodyweight before and after pandemic restrictions were implemented.
Results: Most participants reported increased cell phone use (χ2 = 61.50, p < 0.001). Participants increased sitting by 10 hours/week (F = 25.63, p < 0.001). Those that increased cell phone use reported greater increases in daily sitting (11.65 hours/week, F = 4.14, p = 0.04) than those that did not increase cell use (5.0 hours/week). There was also an increase (F = 10.08, p = 0.002, η2 = 0.04) in reported bodyweight regardless of cell phone use. Physical activity did not change (F ≤ 1.58, p ≥ 0.21).
Conclusions: During the pandemic individuals reported increased cell use, sedentary behavior, and bodyweight. Those that reported increased cell use reported greater increases in sitting than those not increasing cell use.
“…First, a larger sample of college-aged adults is needed to better identify if other factors can account for variations in physical activity behavior. Factors, such as age, weight status, athlete, non-athlete, exercise experience, and various levels of self-efficacy for physical activity and peer influence physical activity behavior 16,17,30 .…”
Section: Discussionmentioning
confidence: 99%
“…Interestingly, research also shows that college-aged adults tend to be extremely active or sedentary 15 . Not only are males more involved in physical activity but they tend to spend more time on electronics such as watching television and excessive seated cell phone activities as well 5,16,17 . It has been found that college-aged adults seem to be the most active for activities such as sports or other leisure physical activities 18 .…”
Introduction: Consumer grade, wrist-worn wearable fitness trackers (WFT) are commonly worn on a daily basis by college-aged adults. Objectively assessing college-aged adults physical activity throughout a 30-day period has not been well documented to accurately assess physical activity behavior.
Methods: Fifteen college-aged participants (male n=7 and female n=9), completed the 30-day tracking assessment while wearing a wrist-worn WFT. The WFT was worn on the non-dominant hand, per manufacture guidelines and was to only be removed to charge the battery, at night during sleeping hours.
Results: Throughout the 30 days, males accumulated more steps, expended more calories, and traveled a greater distance than their female counterparts, p < 0.005 for all. There were no main effects for step counts, daily caloric expenditure and daily total distance for days of the week (p ≥ 0.128 for all). However, there was a significant sex by day of the week interaction for daily steps (p = 0.005), but not total calories or total distance (p ≥ 0.096).
Conclusions: Males were more active and expended more calories than females throughout 30 days of monitoring. However, the day of the week did not significantly alter physical activity and caloric expenditure.
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