scholarly journals Physical activity patterns in a nationally representative sample of adults in Ireland

2001 ◽  
Vol 4 (5a) ◽  
pp. 1107-1116 ◽  
Author(s):  
MBE Livingstone ◽  
PJ Robson ◽  
S McCarthy ◽  
M Kiely ◽  
K Harrington ◽  
...  
Keyword(s):  
Physical Activity ◽  
Representative Sample ◽  
Vigorous Physical Activity ◽  
Activity Patterns ◽  
Leisure Activity ◽  
Work Activity ◽  
Men And Women ◽  
Metabolic Equivalents ◽  
Household Activities ◽  
Nationally Representative

AbstractObjectiveTo evaluate habitual levels of physical activity in a nationally representative sample of adults in Ireland.DesignCross-sectional survey using a self-administered questionnaire. Usual levels of work, recreational and household activities were evaluated in relation to anthropometric, demographic and socio-economic characteristics. The amount and intensity of all activities were quantified by assigning metabolic equivalents (METS) to each activity.SettingRepublic of Ireland and Northern Ireland, 1997–1999.SubjectsRandom sample of 1379 adults aged 18–64 years.ResultsMen were approximately twice as active in work and recreational activity (139.7 ± 83.9 METS) as women (68.5 ± 49.8 METS; P < 0.001), but women were three times more active in household tasks (65.9 ± 58.7 METS vs. 22.6 ± 24.6 METS; P < 0.001). Overall levels of physical activity declined with increasing age, particularly leisure activity in men. In women the decline in work activity was offset by spending more time in household pursuits. Twenty-five per cent of the subjects were extremely overweight (body mass index (BMI) > 28kg m−2) or obese (BMI > 30kg m−2). Fewer obese subjects reported higher levels of work and leisure activities. However, a higher percentage of obese women reported participation in the higher levels of household activities. Participation rates in recreational activities were low. Walking was the most important leisure activity of both men (41%) and women (60%). In terms of hours per week spent in vigorous physical activity, men were more active than women, professional and skilled non-manual women were more active than women in other social classes, and younger subjects (aged 18–35 years) were more active than older subjects.ConclusionsThe holistic approach used in the assessment of physical activity in this study has revealed important and subtle differences in the activity patterns of men and women. Failure to fully characterise the respective activity patterns of men and women could lead to ill-informed public health policy aimed at promoting and sustaining lifetime habits of physical activity. The results suggest that simple population-focused programmes to promote physical activity are unlikely to offer the same chance of long-term success as more sensitive and individualised strategies.

scholarly journals Habitual physical activity patterns in a nationally representative sample of U.S. adults

2020 ◽  
Author(s):  
Susan K Malone ◽  
Freda Patterson ◽  
Laura Grunin ◽  
Gail D Melkus ◽  
Barbara Riegel ◽  
...  
Keyword(s):  
Physical Activity ◽  
Health Behaviors ◽  
Representative Sample ◽  
Clinical Characteristics ◽  
Activity Patterns ◽  
Low Frequency ◽  
Multiple Dimensions ◽  
Long Duration ◽  
Daily Frequency ◽  
Nationally Representative

Abstract Physical inactivity is a leading determinant of noncommunicable diseases. Yet, many adults remain physically inactive. Physical activity guidelines do not account for the multidimensionality of physical activity, such as the type or variety of physical activity behaviors. This study identified patterns of physical activity across multiple dimensions (e.g., frequency, duration, and variety) using a nationally representative sample of adults. Sociodemographic characteristics, health behaviors, and clinical characteristics associated with each physical activity pattern were defined. Multivariate finite mixture modeling was used to identify patterns of physical activity among 2003–2004 and 2005–2006 adult National Health and Nutrition Examination Survey participants. Chi-square tests were used to identify sociodemographic differences within each physical activity cluster and test associations between the physical activity clusters with health behaviors and clinical characteristics. Five clusters of physical activity patterns were identified: (a) low frequency, short duration (n = 730, 13%); (b) low frequency, long duration (n = 392, 7%); (c) daily frequency, short duration (n = 3,011, 55%); (d) daily frequency, long duration (n = 373, 7%); and (e) high frequency, average duration (n = 964, 18%). Walking was the most common form of activity; highly active adults engaged in more varied types of activity. High-activity clusters were comprised of a greater proportion of younger, White, nonsmoking adult men reporting moderate alcohol use without mobility problems or chronic health conditions. Active females engaged in frequent short bouts of activity. Data-driven approaches are useful for identifying clusters of physical activity that encompass multiple dimensions of activity. These activity clusters vary across sociodemographic and clinical subgroups.

scholarly journals Annual rhythms in adults’ lifestyle and health (ARIA): protocol for a 12-month longitudinal study examining temporal patterns in weight, activity, diet, and wellbeing in Australian adults

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Rachel G. Curtis ◽  
Timothy Olds ◽  
François Fraysse ◽  
Dorothea Dumuid ◽  
Gilly A. Hendrie ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Weight ◽  
Weight Gain ◽  
Repeated Measures ◽  
Vigorous Physical Activity ◽  
Activity Patterns ◽  
Intervention Strategy ◽  
Temporal Patterns ◽  
Trial Registration ◽  
Multi Level

Abstract Background Almost one in three Australian adults are now obese, and the rate continues to rise. The causes of obesity are multifaceted and include environmental, cultural and lifestyle factors. Emerging evidence suggests there may be temporal patterns in weight gain related, for example, to season and major festivals such as Christmas, potentially due to changes in diet, daily activity patterns or both. The aim of this study is to track the annual rhythm in body weight, 24 h activity patterns, dietary patterns, and wellbeing in a cohort of Australian adults. In addition, through data linkage with a concurrent children’s cohort study, we aim to examine whether changes in children’s body mass index, activity and diet are related to those of their parents. Methods A community-based sample of 375 parents aged 18 to 65 years old, residing in or near Adelaide, Australia, and who have access to a Bluetooth-enabled mobile device or a computer and home internet, will be recruited. Across a full year, daily activities (minutes of moderate to vigorous physical activity, light physical activity, sedentary behaviour and sleep) will be measured using wrist-worn accelerometry (Fitbit Charge 3). Body weight will be measured daily using Fitbit wifi scales. Self-reported dietary intake (Dietary Questionnaire for Epidemiological Studies V3.2), and psychological wellbeing (WHOQOL-BREF and DASS-21) will be assessed eight times throughout the 12-month period. Annual patterns in weight will be examined using Lowess curves. Associations between changes in weight and changes in activity and diet compositions will be examined using repeated measures multi-level models. The associations between parent’s and children’s weight, activity and diet will be investigated using multi-level models. Discussion Temporal factors, such as day type (weekday or weekend day), cultural celebrations and season, may play a key role in weight gain. The aim is to identify critical opportunities for intervention to assist the prevention of weight gain. Family-based interventions may be an important intervention strategy. Trial registration Australia New Zealand Clinical Trials Registry, identifier ACTRN12619001430123. Prospectively registered on 16 October 2019.

scholarly journals Cannabis use, sedentary behavior, and physical activity in a nationally representative sample of US adults

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Lydia Q. Ong ◽  
John Bellettiere ◽  
Citlali Alvarado ◽  
Paul Chavez ◽  
Vincent Berardi
Keyword(s):  
Physical Activity ◽  
Sedentary Behavior ◽  
Vigorous Physical Activity ◽  
Health Impact ◽  
Cannabis Use ◽  
Objective Measures ◽  
Health And Nutrition ◽  
Nationally Representative ◽  
The Relationship ◽  
Potential Public Health

Abstract Background Prior research examining the relationship between cannabis use, sedentary behavior, and physical activity has generated conflicting findings, potentially due to biases in the self-reported measures used to assess physical activity. This study aimed to more precisely explore the relationship between cannabis use and sedentary behavior/physical activity using objective measures. Methods Data were obtained from the 2005–2006 National Health and Nutrition Examination Survey. A total of 2,092 participants (ages 20–59; 48.8% female) had accelerometer-measured sedentary behavior, light physical activity, and moderate-to-vigorous physical activity. Participants were classified as light, moderate, frequent, or non-current cannabis users depending on how often they used cannabis in the previous 30 days. Multivariable linear regression estimated minutes in sedentary behavior/physical activity by cannabis use status. Logistic regression modeled self-reported moderate-to-vigorous physical activity in relation to current cannabis use. Results Fully adjusted regression models indicated that current cannabis users’ accelerometer-measured sedentary behavior did not significantly differ from non-current users. Frequent cannabis users engaged in more physical activity than non-current users. Light cannabis users had greater odds of self-reporting physical activity compared to non-current users. Conclusions This study is the first to evaluate the relationship between cannabis use and accelerometer-measured sedentary behavior and physical activity. Such objective measures should be used in other cohorts to replicate our findings that cannabis use is associated with greater physical activity and not associated with sedentary behavior in order to fully assess the potential public health impact of increases in cannabis use.

scholarly journals Longitudinal Changes in Sitting Patterns, Physical Activity, and Health Outcomes in Adolescents

Children ◽  
2018 ◽  
Vol 6 (1) ◽  
pp. 2 ◽  
Author(s):  
Ana Contardo Ayala ◽  
Jo Salmon ◽  
David Dunstan ◽  
Lauren Arundell ◽  
Kate Parker ◽  
...  
Keyword(s):  
Physical Activity ◽  
Vigorous Physical Activity ◽  
Activity Patterns ◽  
Sitting Time ◽  
Linear Regression Models ◽  
Anthropometric Measures ◽  
Prolonged Sitting ◽  
Intensity Physical Activity ◽  
Changes Over Time

This study examined two-year changes in patterns of activity and associations with body mass index (BMI) and waist circumference (WC) among adolescents. Inclinometers (activPAL) assessed sitting, sitting bouts, standing, stepping, and breaks from sitting. ActiGraph-accelerometers assessed sedentary time (SED), light-intensity physical activity (LIPA, stratified as low- and high-LIPA), and moderate-to-vigorous physical activity (MVPA). Anthropometric measures were objectively assessed at baseline and self-reported at follow-up. Data from 324 and 67 participants were obtained at baseline and follow-up, respectively. Multilevel mixed-effects linear regression models examined changes over time, and associations between baseline values and BMI and WC at follow-up. There were significant increases in BMI (0.6 kg/m2) and durations of prolonged sitting (26.4 min/day) and SED (52 min/day), and significant decreases in stepping (−19 min/day), LIPA (−33 min/day), low-LIPA (−26 min/day), high-LIPA (−6.3 min/day), MVPA (−19 min/day), and the number of breaks/day (−8). High baseline sitting time was associated (p = 0.086) with higher BMI at follow-up. There were no significant associations between baseline sitting, prolonged sitting, LIPA, or MVPA with WC. Although changes in daily activity patterns were not in a favourable direction, there were no clear associations with BMI or WC. Research with larger sample sizes and more time points is needed.

scholarly journals Youth Physical Activity Patterns During School and Out-of-School Time

Children ◽  
2018 ◽  
Vol 5 (9) ◽  
pp. 118 ◽  
Author(s):  
Pedro Saint-Maurice ◽  
Yang Bai ◽  
Spyridoula Vazou ◽  
Gregory Welk
Keyword(s):  
Physical Activity ◽  
High School Students ◽  
Discrete Time ◽  
Vigorous Physical Activity ◽  
Activity Patterns ◽  
After School ◽  
Activity Levels ◽  
School Students ◽  
Time Periods ◽  
Out Of School

This study describes age, sex, and season patterns in children’s physical activity behaviors during discrete time periods, both in school and at home. Participants were 135 elementary, 67 middle, and 89 high-school students (128 boys and 163 girls) involved in a larger school activity monitoring project. We examined time spent in moderate-to-vigorous physical activity (MVPA) at recess, physical education (PE), lunch, commuting to/from school, before-school, after-school, evening, and weekend segments. Differences in MVPA by age, sex, and season were examined using a three-way analysis of variance and separately for each individual segment. Moderate-to-vigorous physical activity levels varied by context and were higher during recess (15.4 ± 8.5 min) while at school, and on Saturdays (97.4 ± 89.5 min) when youth were out-of-school. Elementary children were more active than their older counterparts only during lunch time, after-school, and Sunday (p < 0.05). Boys were consistently more active than girls at all segments. Participants were only more active during non-winter than winter months during PE (p = 0.006), after-school (p < 0.001), and Sunday (p = 0.008) segments. These findings showed that activity levels in youth vary during the day and season. The segments reflect discrete time periods that can potentially be targeted and evaluated to promote physical activity in this population.

1. The Effects of an Aerobic Exercise Intervention on Daily Activity Patterns

2016 ◽  
Author(s):  
James Bouma
Keyword(s):  
Physical Activity ◽  
Aerobic Exercise ◽  
Daily Activity ◽  
Exercise Intervention ◽  
Vigorous Physical Activity ◽  
Activity Patterns ◽  
Low Intensity ◽  
Low Volume ◽  
Low Intensity Exercise ◽  
Daily Activity Patterns

The purpose of this study was to examine the effects of participation in an aerobic exercise intervention on daily activity occurring outside of the structured exercise sessions. Participants were randomized into one of the following 4 conditions: 1) No-exercise, 2) Low volume, low intensity exercise (LVLI), 3) High volume, low intensity exercise (HVLI), 4) Low volume, high intensity (LVHI). Physical activity was measured over 7 days with an accelerometer at baseline and during week 8 of the intervention. Activity was defined as: sedentary behaviour (SED; < 100 counts/minute), light physical activity (LPA; 100 to 1951 counts/minute), moderate-to-vigorous physical activity (MVPA; ≥1952 counts/minute), and total physical activity (TPA; LPA + MVPA). Activity was quantified as average total minutes per day of each SED, LPA, MVPA, and TPA. A one-way ANOVA was used to determine if time spent in SED, LPA, MVPA, and TPA changed from baseline to week 8. Seventy-one participants (No-exercise; n=12, LVLI n=17, HVLI n=24, LVHI; n=18,) with a mean age of 54 y and waist circumference of 110 cm completed 8 weeks of the intervention. There were no significant differences in SED, LPA, MVPA, or TPA between groups at baseline. There was no significant change in SED, LPA, MVPA, or TPA at week 8 compared to baseline (p>0.05). Similarly, there were no significant differences in activity variables between exercise conditions. Our observations suggest that daily activity patterns do not change with the implementation of an exercise intervention in men and women.

scholarly journals SELF-REPORTED PHYSICAL ACTIVITY IN SPECIALIZED AND UNSPECIALIZED YOUTH

2020 ◽  
Vol 8 (4_suppl3) ◽  
pp. 2325967120S0021
Author(s):  
Julie A. Young ◽  
Amy E Valasek ◽  
James Onate
Keyword(s):  
Physical Activity ◽  
Sports Medicine ◽  
Vigorous Physical Activity ◽  
Activity Patterns ◽  
Daily Basis ◽  
Recreational Activities ◽  
Physical Activity Patterns ◽  
Medicine Clinic ◽  
Risk Of Injury

The benefits of physical activity cross all domains of health. Unfortunately, many children are not meeting the current American College of Sports Medicine recommendations of 60 minutes of moderate to vigorous physical activity (MVPA) 7 days a week. This is especially deleterious since physical activity patterns during childhood may carryover to adulthood. Research has also shown that participating in one sport may increase the risk of injury. The purpose of this study was to examine self-reported exercise levels in children reporting to a tertiary sports medicine clinic over a three year period. Subjects were asked “How many minutes of moderate to vigorous physical activity per day?” and “How many days per week do you participate in moderate to vigorous physical activity”. Minutes per week of MVPA was calculated. Age, sex, and current sports and recreational activities were recorded. There were 7427 unique patients (53% female) with an average age of 13.8±2.6. The average minutes per day of exercise was reported as 85.6±44.4, average days per week was 4.4±1.6 and minutes per week was 410.8±266.9. Females reported less minutes per day (83.5 vs. 87.8, p<.001), less days per week (4.2 vs 4.7, p<.001) and less minutes per week (384.1 vs 440.2, p<.001) than males. On average, females reported 56 minutes less activity per week than their male counterparts. There were 3618 participants who only reported one activity and were categorized as specialized in a single physical activity. Those that specialized in a single activity were significantly older (14.1 vs 13.4, p<.001). There were no significant differences between reported minutes per day between specialized and unspecialized athletes (85.8 vs 85.2, p=.57). Those who specialized in one activity reported more days per week (4.6 vs 4.2. p<.001) and more minutes per week (423.8 vs 397.0, p=.001) than unspecialized athletes. Research has consistently shown that females are less active than males. Those who specialized in one activity participated in more minutes per week of activity, mainly through participating in more days of physical activity. Children should be encouraged to participate in a variety of activities on a daily basis to ensure they receive the benefits of physical activity.

scholarly journals Social media captures demographic and regional physical activity

2019 ◽  
Vol 5 (1) ◽  
pp. e000567 ◽  
Author(s):  
Nina Cesare ◽  
Quynh C Nguyen ◽  
Christan Grant ◽  
Elaine O Nsoesie
Keyword(s):  
Physical Activity ◽  
Social Media ◽  
Physical Inactivity ◽  
Specific Activity ◽  
Activity Patterns ◽  
Health Behaviours ◽  
Population Level ◽  
Statistical Modelling ◽  
Men And Women ◽  
The Usa

ObjectivesWe examined the use of data from social media for surveillance of physical activity prevalence in the USA.MethodsWe obtained data from the social media site Twitter from April 2015 to March 2016. The data consisted of 1 382 284 geotagged physical activity tweets from 481 146 users (55.7% men and 44.3% women) in more than 2900 counties. We applied machine learning and statistical modelling to demonstrate sex and regional variations in preferred exercises, and assessed the association between reports of physical activity on Twitter and population-level inactivity prevalence from the US Centers for Disease Control and Prevention.ResultsThe association between physical inactivity tweet patterns and physical activity prevalence varied by sex and region. Walking was the most popular physical activity for both men and women across all regions (15.94% (95% CI 15.85% to 16.02%) and 18.74% (95% CI 18.64% to 18.88%) of tweets, respectively). Men and women mentioned performing gym-based activities at approximately the same rates (4.68% (95% CI 4.63% to 4.72%) and 4.13% (95% CI 4.08% to 4.18%) of tweets, respectively). CrossFit was most popular among men (14.91% (95% CI 14.52% to 15.31%)) among gym-based tweets, whereas yoga was most popular among women (26.66% (95% CI 26.03% to 27.19%)). Men mentioned engaging in higher intensity activities than women. Overall, counties with higher physical activity tweets also had lower leisure-time physical inactivity prevalence for both sexes.ConclusionsThe regional-specific and sex-specific activity patterns captured on Twitter may allow public health officials to identify changes in health behaviours at small geographical scales and to design interventions best suited for specific populations.

Physical activity volume in relation to risk of atrial fibrillation. A non-linear meta-regression analysis

2018 ◽  
Vol 25 (8) ◽  
pp. 857-866 ◽  
Author(s):  
Cristian Ricci ◽  
Federico Gervasi ◽  
Maddalena Gaeta ◽  
Cornelius M Smuts ◽  
Aletta E Schutte ◽  
...  
Keyword(s):  
Physical Activity ◽  
Atrial Fibrillation ◽  
Relative Risk ◽  
Vigorous Physical Activity ◽  
Response Analysis ◽  
Metabolic Equivalents ◽  
Increased Risk ◽  
Non Linear ◽  
Meta Regression ◽  
Physical Activity Volume

Background Light physical activity is known to reduce atrial fibrillation risk, whereas moderate to vigorous physical activity may result in an increased risk. However, the question of what volume of physical activity can be considered beneficial remains poorly understood. The scope of the present work was to examine the relation between physical activity volume and atrial fibrillation risk. Design A comprehensive systematic review was performed following the PRISMA guidelines. Methods A non-linear meta-regression considering the amount of energy spent in physical activity was carried out. The first derivative of the non-linear relation between physical activity and atrial fibrillation risk was evaluated to determine the volume of physical activity that carried the minimum atrial fibrillation risk. Results The dose–response analysis of the relation between physical activity and atrial fibrillation risk showed that physical activity at volumes of 5–20 metabolic equivalents per week (MET-h/week) was associated with significant reduction in atrial fibrillation risk (relative risk for 19 MET-h/week = 0.92 (0.87, 0.98). By comparison, physical activity volumes exceeding 20 MET-h/week were unrelated to atrial fibrillation risk (relative risk for 21 MET-h/week = 0.95 (0.88, 1.02). Conclusion These data show a J-shaped relation between physical activity volume and atrial fibrillation risk. Physical activity at volumes of up to 20 MET-h/week is associated with reduced atrial fibrillation risk, whereas volumes exceeding 20 MET-h/week show no relation with risk.

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