scholarly journals Sedentary Behavior and Physical Activity are associated with Sleep Duration and Sleep Quality in Postmenopausal Women

2018 ◽  
Vol 50 (5S) ◽  
pp. 133
Author(s):  
Seth A. Creasy ◽  
Cynthia A. Thomson ◽  
David O. Garcia ◽  
Tracy E. Crane ◽  
Betsy C. Wertheim ◽  
...  
2021 ◽  
Vol 141 (2) ◽  
pp. 89-96
Author(s):  
Hsin-Yen Yen ◽  
Hao-Yun Huang

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.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Li-Tang Tsai ◽  
Eleanor Boyle ◽  
Jan C. Brønd ◽  
Gry Kock ◽  
Mathias Skjødt ◽  
...  

Abstract Background Older adults are recommended to sleep 7–8 h/day. Time in bed (TIB) differs from sleep duration and includes also the time of lying in bed without sleeping. Long TIB (≥9 h) are associated with self-reported sedentary behavior, but the association between objectively measured physical activity, sedentary behavior and TIB is unknown. Methods This study was based on cross-sectional analysis of the Healthy Ageing Network of Competence (HANC Study). Physical activity and sedentary behaviour were measured by a tri-axial accelerometer (ActiGraph) placed on the dominant wrist for 7 days. Sedentary behavior was classified as < 2303 counts per minute (cpm) in vector magnitude and physical activity intensities were categorized, as 2303–4999 and ≥ 5000 cpm in vector magnitude. TIB was recorded in self-reported diaries. Participants were categorized as UTIB (usually having TIB 7–9 h/night: ≥80% of measurement days), STIB (sometimes having TIB 7–9 h/night: 20–79% of measurement days), and RTIB (rarely having TIB 7–9 h/night: < 20% of measurement days). Multinominal regression models were used to calculate the relative risk ratios (RRR) of being RTIB and STIB by daily levels of physical activity and SB, with UTIB as the reference group. The models were adjusted for age, sex, average daily nap length and physical function. Results Three hundred and fourty-one older adults (median age 81 (IQR 5), 62% women) were included with median TIB of 8 h 21 min (1 h 10 min)/day, physical activity level of 2054 (864) CPM with 64 (15) % of waking hours in sedentary behavior. Those with average CPM within the highest tertile had a lower RRR (0.33 (0.15–0.71), p = 0.005) for being RTIB compared to those within the lowest tertile of average CPM. Accumulating physical activity in intensities 2303–4999 and ≥ 5000 cpm/day did not affect the RRR of being RTIB. RRR of being RTIB among highly sedentary participants (≥10 h/day of sedentary behavior) more than tripled compared to those who were less sedentary (3.21 (1.50–6.88), p = 0.003). Conclusions For older adults, being physically active and less sedentary was associated with being in bed for 7–9 h/night for most nights (≥80%). Future longitudinal studies are warranted to explore the causal relationship sbetween physical activity and sleep duration.


2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1017.2-1018
Author(s):  
N. Kelly ◽  
E. Hawkins ◽  
H. O’leary ◽  
K. Quinn ◽  
G. Murphy ◽  
...  

Background:Rheumatoid arthritis (RA) is a chronic, autoimmune inflammatory condition that affects 0.5% of the adult population worldwide (1). Sedentary behavior (SB) is any waking behavior characterized by an energy expenditure of ≤1.5 METs (metabolic equivalent) and a sitting or reclining posture, e.g. computer use (2) and has a negative impact on health in the RA population (3). Sleep is an important health behavior, but sleep quality is an issue for people living with RA (4, 5). Poor sleep quality is associated with low levels of physical activity in RA (4) however the association between SB and sleep in people who have RA has not been examined previously.Objectives:The aim of this study was to investigate the relationship between SB and sleep in people who have RA.Methods:A cross-sectional study was conducted. Patients were recruited from rheumatology clinics in a large acute public hospital serving a mix of urban and rural populations. Inclusion criteria were diagnosis of RA by a rheumatologist according to the American College of Rheumatology criteria age ≥ 18 and ≤ 80 years; ability to mobilize independently or aided by a stick; and to understand written and spoken English. Demographic data on age, gender, disease duration and medication were recorded. Pain and fatigue were measured by the Visual Analogue Scale (VAS), anxiety and depression were assessed using the Hospital Anxiety and Depression Scale (HADS), and sleep quality was assessed using the Pittsburgh Sleep Quality Index. SB was measured using the ActivPAL4™ activity monitor, over a 7-day wear period. Descriptive statistics were calculated to describe participant characteristics. Relationships between clinical characteristics and SB were examined using Pearson’s correlation coefficients and regression analyses.Results:N=76 participants enrolled in the study with valid data provided by N=72 participants. Mean age of participants was 61.5years (SD10.6) and the majority 63% (n = 47) were female. Participant mean disease duration was 17.8years (SD10.9). Mean SB time was 533.7 (SD100.1) minutes (8.9 hours per day/59.9% of waking hours). Mean sleep quality score was 7.2 (SD5.0) (Table 1). Correlation analysis and regression analysis found no significant correlation between sleep quality and SB variables. Regression analysis demonstrated positive statistical associations for SB time and body mass index (p-value=0.03846, R2 = 0.05143), SB time and pain VAS (p-value=0.009261, R2 = 0.07987), SB time and HADS (p-value = 0.009721, R2 = 0.08097) and SB time and HADSD (p-value = 0.01932, R2 = 0.0643).Conclusion:We found high levels of sedentary behavior and poor sleep quality in people who have RA, however no statistically significant relationship was found in this study. Future research should further explore the complex associations between sedentary behavior and sleep quality in people who have RA.References:[1]Carmona L, et al. Rheumatoid arthritis. Best Pract Res Clin Rheumatol 2010;24:733–745.[2]Anon. Letter to the editor: standardized use of the terms “sedentary” and “sedentary behaviours”. Appl Physiol Nutr Metab = Physiol Appl Nutr Metab 2012;37:540–542.[3]Fenton, S.A.M. et al. Sedentary behaviour is associated with increased long-term cardiovascular risk in patients with rheumatoid arthritis independently of moderate-to-vigorous physical activity. BMC Musculoskelet Disord 18, 131 (2017).[4]McKenna S, et al. Sleep and physical activity: a cross-sectional objective profile of people with rheumatoid arthritis. Rheumatol Int. 2018 May;38(5):845-853.[5]Grabovac, I., et al. 2018. Sleep quality in patients with rheumatoid arthritis and associations with pain, disability, disease duration, and activity. Journal of clinical medicine, 7(10)336.Table 1.Sleep quality in people who have RASleep variableBed Time N(%) before 10pm13(18%) 10pm-12pm43 (60%) after 12pm16 (22%)Hours Sleep mean(SD)6.56 (1.54)Fall Asleep minutes mean(SD)33.3(27.7)Night Waking N(%)45(63%)Self-Rate Sleep mean(SD)2.74 (0.90)Hours Sleep mean(SD)6.56 (1.54)Disclosure of Interests:None declared


Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 848
Author(s):  
Jin-Suk Ra ◽  
Hyesun Kim

This study aimed to identify the combined effects of unhealthy lifestyle behaviors, including diet, sedentary behavior, and physical activity on metabolic syndrome (MS) and components of MS among postmenopausal women. Secondary data analysis was conducted using the Korean National Health and Nutrition Examination Survey (2014–2018) with a cross-sectional study design. Logistic regression analysis was conducted with data from 6114 Korean postmenopausal women. While no significant effects of unhealthy lifestyle behaviors, either individually or as a combination, were found for MS, prolonged sedentary behavior without poor dietary behavior and insufficient physical activity was associated with increased likelihood of abdominal obesity (adjusted odds ratio [AOR]: 1.59, 95% confidence interval [CI]: 1.10–2.29) and impaired fasting glucose (AOR: 1.54, 95% CI: 1.13–2.10). The combination of poor dietary behavior and prolonged sedentary behaviors was also associated with increased likelihood of abdominal obesity (AOR: 1.48, 95% CI: 1.10–2.00) and impaired fasting glucose (AOR: 1.49, 95% CI: 1.14–1.96). In addition, prolonged sedentary behavior and insufficient physical activity together were associated with increased likelihood of abdominal obesity (AOR: 2.81, 95% CI: 1.90–4.20) and impaired fasting glucose (AOR: 1.59, 95% CI: 1.13–2.24). Finally, combining poor dietary behavior, prolonged sedentary behavior, and insufficient physical activity was also associated with increased likelihood of abdominal obesity (AOR: 2.05, 95% CI: 1.50–2.80) and impaired fasting glucose (AOR: 1.71, 95% CI: 1.32–2.23). Strategies for replacing sedentary behavior of postmenopausal women with activities are warranted for prevention of abdominal obesity and impaired fasting glucose.


2014 ◽  
Vol 46 ◽  
pp. 684
Author(s):  
Christie L. Ward-Ritacco ◽  
Amanda L. Adrian ◽  
Patrick J. O’Connor ◽  
Mary Ann Johnson ◽  
Laura Q. Rogers ◽  
...  

Circulation ◽  
2018 ◽  
Vol 137 (suppl_1) ◽  
Author(s):  
Jessica A Parascando ◽  
Fan He ◽  
Steriani Elavsky ◽  
Edward O Bixler ◽  
Julio Fernandez-Mendoza ◽  
...  

Introduction: A decrease in sleep quantity and quality is a growing concern in the adolescent population. Concurrently, an increase in physical inactivity has been shown to be related to numerous health consequences. There is a lack of literature on the relationship between sleep, physical activity (PA) and sedentary behavior (SB) in the adolescent population, particularly looking at night-to-night sleep irregularity. Hypothesis: We hypothesized that increased PA and decreased SB in both objective and subject modalities would be associated with greater habitual sleep duration (HSD) and lesser habitual sleep variability (HSV) in this adolescent population. Methods: Objective and subjective sleep and activity measurements were collected from 295 adolescents in the Penn State Child Cohort follow-up examination. Objectively-measured variables were obtained through 7 consecutive days of actigraphy collection. HSD was calculated as the average sleep duration across 7 nights, and HSV was calculated as the standard deviation (SD) of intra-individual sleep duration. Subjects with <5 nights of sleep data were excluded from analysis. Self-administered questionnaires were used to collect subjectively-measured sleep, PA, and SB data. The relationships between sleep and behavior measures were assessed using linear regressions. All models were adjusted for age, sex, race and BMI percentile. Results: On average, our sample was 16.8 years, 52% male, and 79% white. We found that higher SB was associated with shorter HSD. With one SD change in objectively-measured SB (1014 minutes), HSD is reduced by 16 (3.6) minutes (p<0.05). Although not statistically significant, subjective SB showed a similar pattern. Unexpectedly, both objective and subjective measures of increased PA were associated with shorter HSD. In terms of HSV, we found that higher subjective SB was associated with greater HSV; specifically, with one SD change in subjectively-measured SB (8.64 points), HSV increased by 0.011 (0.004) minutes. None of the PA measures were significantly associated with HSV. Conclusions: In conclusion, objectively-measured sleep patterns are related to physical activity/inactivity. Our results emphasize the need of future studies to systematically assess the inter-relationship of sleep and physical activity in this population.


Author(s):  
Lovro Štefan ◽  
Goran Vrgoč ◽  
Tomislav Rupčić ◽  
Goran Sporiš ◽  
Damir Sekulić

The main purpose of the study was to explore the associations of sleep duration and sleep quality with physical activity (PA). In this cross-sectional study, participants were 894 elderly individuals (mean age 80 ± 3 years; 56.0% women) living in nursing homes. PA, sleep duration, and sleep quality (based on the Pittsburgh Sleep Quality Index (PSQI)) were self-reported. The associations of sleep duration and sleep quality with PA at the nursing home level were analyzed using generalized estimating equations with clustering. Participants reporting short sleep duration (<6 h; OR = 0.45; 95% CI 0.25–0.80) were less likely to report sufficient PA, yet those reporting long sleep duration (>9 h; OR = 2.61; 95% CI 1.35–5.02) and good sleep quality (<5 points; OR = 1.59; 95% CI 1.19–2.12) were more likely to report sufficient PA. When sleep duration and sleep quality were entered into the same model, the same associations remained. This study shows that elderly individuals who report short sleep duration are less likely to meet PA guidelines, while those who report long sleep duration and good sleep quality are more likely to meet PA guidelines. Strategies aiming to improve sleep duration and sleep quality are warranted.


2018 ◽  
Vol 1 (5) ◽  
Author(s):  
Guangyu Wang ◽  
Mei Zhen Zhang

Objective The majority studies focused on obesity prevention on physical activity and eating behavior. However, epidemiological studies have shown that sleep duration and sleep quality could be an adjustable risk factor for obesity. The aim of this study was to examine the associations of sleep quality with different measurement of obesity in Chinese university students. Methods A total of 481 college students aged 18-25 years volunteered to participate in this study. Sleep quality was assessed by Pittsburgh Sleep Quality Index (PSQI)questionnaire. International Physical Activity Questionnaire (IPAQ)was used to determine the physical activity, Psychological status was assessed by Self-Rating Depression Scale (SDS) and Self-Rating Anxiety Scale (SAS). Body height, weight and waist circumference are measured by a trained researcher. Body composition was evaluated by a bio-impedance device (InBody 230, South Korea). Independent sample t test was applied to compare the sleep characteristics, physical activity, obesity, depression and anxiety in different gender students. The associations among the dependent variables BMI, body fat percentage, and the independent variables age, sleep quality and sleep durations was examined using Multiple linear regression models. SPSS 22.0 (IMB SPSS Inc) was used for all statistical. Results The BMI (22.9±3.4 vs 21.6±3.2, p<0.001) of male students were significantly higher than that of female, but the percentage of body fat (18.7±6.9 vs 29.7±7.0, p<0.001) was lower than that of female. We observed a positive association between sleep quality and body fat percentage (β = 0.166, P = 0.037), and a negative association with age (β = -0.166, P = 0.008) in female students. Sleep quality was associated positively with BMI (β = 0.360, P<0.001), body fat percentage (β = 0.260, P<0.001), and age (β = 0.215, P<0.001) in male students; An inverse correlation between sleep duration and BMI (β = -0.141, P = 0.015), body fat percentage (β = -0.134, P = 0.022) was found, and a positive relationship with  anxiety scores (β = 0.331, P<0.001) in male students. while an inverse relationship was found with WHR (β = -0.236, P = 0.001), waist circumference (β = -0.169, P = 0.007), and a positive association between sleep duration with anxiety scores (β = 0.331, P<0.001) and depression scores (β = 0.415, P<0.001) in female students. Conclusions The obesity of male and female students goes up with the increase of total score of sleep quality, anxiety and depression, and goes down with the increase of sleep duration, physical activity time and energy consumption. Male obesity increases with age, but female obesity decreases with age. Among the importance of males' sleep duration and sleep quality in the obesity risk assessment, BMI and body fat percentages are more accurate, while for females, BMI and waist circumference is of no statistical significance.  


2019 ◽  
Vol 23 ◽  
pp. 1-26
Author(s):  
Andrea Wendt ◽  
Thaynã Ramos Flores ◽  
Inácio Crochemore Mohnsam Silva ◽  
Fernando César Wehrmeister

The aim of this study was to systematically examine the literature on physical activity and sleep in non-clinical and population-based settings. The inclusion criteria were original studies testing the association between physical activity (as exposure) and sleep (as outcome) in representative samples of the general population, workers, or undergraduate students. Sleep health included sleep duration, sleep quality and insomnia. Studies evaluating samples including only individuals with some disease or a health condition were excluded. A search was performed in the PubMed, Scopus, Lilacs, CINAHL, and SPORTdiscus databases in March 2018. Data extraction was performed using the following items: year, author, country, population, age group, sample size, study design, sleep measurement/definition, physical activity measurement/definition, adjustment and main results. A total of 57 studies were selected, which markedly used heterogeneous instruments to measure physical activity and sleep. The majority were conducted in high-income countries and with cross-sectional design. Physical activity was associated with lower odds of insomnia (observed in 10 of 17 studies), poor sleep quality (observed in 12 of 19 studies) and long sleep duration (observed in 7 of 11 studies). The results about short sleep or continuous sleep duration remain unclear. Physical activity seems to be associated with sleep quality and insomnia, especially among adult and elderly populations in which these outcomes are more usually measured. The short- and long-term effects of physical activity intensities and dose-response on sleep should be better evaluated.


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