Compositional insights on the association between physical activity and sedentary behavior on momentary mood in daily life

2021 ◽  
pp. 102102
Author(s):  
Marco Giurgiu ◽  
Ulrich W. Ebner-Priemer ◽  
Dorothea Dumuid
Keyword(s):  
Physical Activity ◽  
Sedentary Behavior ◽  
Daily Life

scholarly journals High sedentary behavior and compromised physical capabilities in adult smokers despite the suitable level of physical activity in daily life

2017 ◽  
Vol 19 (1) ◽  
pp. 62 ◽  
Author(s):  
Vinicius Tonon Lauria ◽  
Evandro Fornias Sperandio ◽  
Agatha Caveda Matheus ◽  
Rodrigo Pereira da Silva ◽  
Marcello Romiti ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Composition ◽  
Sedentary Behavior ◽  
Daily Life ◽  
Bioelectrical Impedance ◽  
Cardiopulmonary Exercise Test ◽  
Similar Amount ◽  
Physically Active ◽  
Minute Walk ◽  
Sedentary Activities

DOI: http://dx.doi.org/10.5007/1980-0037.2017v19n1p62 Sedentary behavior may play an important role for health outcomes, regardless of the amount of physical activity in daily life (PADL).We aimed to evaluate and compare sedentary behavior as well as physical capabilities in physically active smokers and non-smokers. Twenty-eight adult smokers and 38 non-smokers free of lung disease were matched for age, sex, body mass index, body composition, cardiovascular risk and moderate-to-vigorous PADL. Participants underwent spirometry, cardiopulmonary exercise test (CPET), six-minute walk test (6MWT), isokinetic dynamometry, and body composition (bioelectrical impedance).Despite the similar amount of moderate-to-vigorous PADL(median, 4.5h/week for smokers and 4.0h/week for non-smokers), smokers spent more time lying (median, 8.2h/week: 95% confidence interval, 5.4 to 19.1 vs. 6.1h/week: 3.7 to 11.2) and in sedentary activities (median, 100h/week: 66 to 129 vs. 78h/week: 55 to 122) compared to non-smokers. Smokers also presented worse spirometry, peak V’O2 and maximum heart rate in the CPET, 6MWT, and isokinetic indices (p<0.05). We observed a strong correlation between the time spent lying and spirometry (r = - 0.730) in smokers. Smoking is related to higher sedentary behavior, despite the suitable PADL. An appropriate PADL did not reduce the deleterious effects of smoking on physical capabilities. Interrupting sedentary behavior may be an appropriate intervention target in smokers for reducing the risk of diseases.

scholarly journals Off-Training Levels of Physical Activity and Sedentary Behavior in Young Athletes: Preliminary Results during a Typical Week

Sports ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 141 ◽  
Author(s):  
Juliana Exel ◽  
Nuno Mateus ◽  
Bruno Travassos ◽  
Bruno Gonçalves ◽  
Isabel Gomes ◽  
...  
Keyword(s):  
Physical Activity ◽  
Cluster Analysis ◽  
Sedentary Behavior ◽  
Daily Life ◽  
Young Athletes ◽  
Preliminary Results ◽  
Daily Life Activities ◽  
Quality Of Recovery ◽  
Health Related

The level of physical activity (PA) and sedentary behavior (SED) off-training of young athletes may reveal the quality of recovery from training and highlight health related issues. Thus, the aim was to identify and describe young athletes’ PA and SED off-training, according to daily life activities. Eight athletes (15.7 ± 2 years, 1.72 ± 0.6 m height, 62.9 ± 10.2 kg) of a sport talent program wore on their waist a tri-axial accelerometer (ActiGraph® wGT9X-link, Shalimar, FL, USA) at 30 Hz for 15 consecutive days, and reported their schedule. A two-step cluster analysis classified three groups according to sedentary PA and MVPA. The Sedentary (56.9%), presented the highest sedentary PA (mean [CI], 37.37 [36.45–38.29] min/hour); The Hazardous (19.4%) had the lowest values of sedentary and MVPA (10.07 [9.41–10.36] min/hour and 8.67 [7.64–9.70] min/hour, respectively). Balanced (23.7%) had the highest MVPA (28.61 [27.16–30.07] min/hour). Sedentary had the lowest count of home time associated (20%) and higher school (26%) time when compared to the Hazardous (13%). The Balanced showed the highest count of school (61%) and home time (47%). Different profiles for young athletes revealed alarming behavior in the associations with sedentary PA, sitting and SED breaks, which may influence performance and health.

Comparisons of physical activity and sedentary behavior between owners and non-owners of commercial wearable devices

2021 ◽  
Vol 141 (2) ◽  
pp. 89-96
Author(s):  
Hsin-Yen Yen ◽  
Hao-Yun Huang
Keyword(s):  
Physical Activity ◽  
Sleep Quality ◽  
Sedentary Behavior ◽  
Sedentary Time ◽  
Short Form ◽  
Wearable Devices ◽  
Wearable Device ◽  
World Health ◽  
World Health Organization Quality ◽  
Quality Of Life Scale

Aims: Wearable devices are a new strategy for promoting physical activity in a free-living condition that utilizes self-monitoring, self-awareness, and self-determination. The main purpose of this study was to explore health benefits of commercial wearable devices by comparing physical activity, sedentary time, sleep quality, and other health outcomes between individuals who used and those that did not use commercial wearable devices. Methods: The research design was a cross-sectional study using an Internet survey in Taiwan. Self-administered questionnaires included the International Physical Activity Questionnaire–Short Form, Pittsburgh Sleep Quality Index, Health-Promoting Lifestyle Profile, and World Health Organization Quality-of-Life Scale. Results: In total, 781 participants were recruited, including 50% who were users of wearable devices and 50% non-users in the most recent 3 months. Primary outcomes revealed that wearable device users had significantly higher self-reported walking, moderate physical activity, and total physical activity, and significantly lower sedentary time than non-users. Wearable device users had significantly better sleep quality than non-users. Conclusion: Wearable devices inspire users’ motivation, engagement, and interest in physical activity through habit formation. Wearable devices are recommended to increase physical activity and decrease sedentary behavior for promoting good health.

scholarly journals 2020 WHO guidelines on physical activity and sedentary behavior

2021 ◽  
Author(s):  
Anthony D. Okely ◽  
Anna Kontsevaya ◽  
Johan Ng ◽  
Chalchisa Abdeta
Keyword(s):  
Physical Activity ◽  
Sedentary Behavior ◽  
Who Guidelines

scholarly journals Associations of working from home with occupational physical activity and sedentary behavior under the COVID‐19 pandemic

2021 ◽  
Vol 63 (1) ◽  
Author(s):  
Noritoshi Fukushima ◽  
Masaki Machida ◽  
Hiroyuki Kikuchi ◽  
Shiho Amagasa ◽  
Toshio Hayashi ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sedentary Behavior ◽  
Occupational Physical Activity ◽  
Working From Home

scholarly journals Can Health-Promoting Schools Contribute to Better Health Behaviors? Physical Activity, Sedentary Behavior, and Dietary Habits among Israeli Adolescents

2021 ◽  
Vol 18 (3) ◽  
pp. 1183
Author(s):  
Hila Beck ◽  
Riki Tesler ◽  
Sharon Barak ◽  
Daniel Sender Moran ◽  
Adilson Marques ◽  
...  
Keyword(s):  
Physical Activity ◽  
Health Behavior ◽  
Confidence Interval ◽  
Health Behaviors ◽  
Sedentary Behavior ◽  
Dietary Habits ◽  
Group Differences ◽  
Time Behavior ◽  
Health Promoting ◽  
The Mean

Schools with health-promoting school (HPS) frameworks are actively committed to enhancing healthy lifestyles. This study explored the contribution of school participation in HPS on students’ health behaviors, namely, physical activity (PA), sedentary behavior, and dieting. Data from the 2018/2019 Health Behavior in School-aged Children study on Israeli adolescents aged 11–17 years were used. Schools were selected from a sample of HPSs and non-HPSs. Between-group differences and predictions of health behavior were analyzed. No between-group differences were observed in mean number of days/week with at least 60 min of PA (HPS: 3.84 ± 2.19 days/week, 95% confidence interval of the mean = 3.02–3.34; non-HPS: 3.93 ± 2.17 days/week, 95% confidence interval of the mean = 3.13–3.38). Most children engaged in screen time behavior for >2 h/day (HPS: 60.83%; non-HPS: 63.91%). The odds of being on a diet were higher among more active children (odds ratio [OR] = 1.20), higher socio-economic status (OR = 1.23), and female (OR = 2.29). HPS did not predict any health behavior. These findings suggest that HPSs did not contribute to health behaviors more than non-HPSs. Therefore, health-promoting activities in HPSs need to be improved in order to justify their recognition as members of the HPS network and to fulfill their mission.

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