scholarly journals Evaluating of the Axivity accelerometers algorithm in measurement of physical activity intensity in boys and girls

2019 ◽  
Author(s):  
Maedeh Mansoubi ◽  
Patrick Esser ◽  
Andy Meaney ◽  
Renske Metz ◽  
Kyle Beunder ◽  
...  
Keyword(s):  
Physical Activity ◽  
Activity Level ◽  
Physical Activity Intensity ◽  
Metabolic Equivalent ◽  
Activity Intensity ◽  
Accelerometer Signal ◽  
Run Test ◽  
Signal Vector ◽  
Shuttle Run ◽  
Vector Magnitude

Abstract Background: Accelerometers are new but popular tools in measurement of physical activity level but most of them use the algorithms which are more suitable for adults rather than adolescents. Also accelerometers accuracy in assessing physical activity intensity in boys and girls is widely unknown. Therefore, purpose the current study was to evaluate the validity of the Axivity accelerometers in relation to establish algorithm in the measurement of physical activity intensity in boys and girls. Methods: A total of 143 participants recruited from a local school in Oxfordshire and 119 of them (84 boys and 35 girls, age (12.71 ± 0.46)) completed the shuttle run test while wearing an AX3 accelerometer. Signal Vector Magnitude (gravity-subtracted) (SVMgs) and Metabolic equivalent (MET) values were calculated for both of boys and girls. Results: The study result showed that girls had significantly higher SVMgs value (P< 0.05) while according to the standard equations, girls have lower VO2max and MET in each shuttle run lap. Conclusion: This study result suggest that different algorithms might be necessary to measure physical activity in different genders.

scholarly journals Relationship between Physical Activity and Blood Lipid Profile in Residents of Yazd City (YaHS Study)

2020 ◽  
Author(s):  
Masoud Mirzaei ◽  
Farnaz Nekahi
Keyword(s):  
Physical Activity ◽  
Blood Lipid ◽  
Activity Level ◽  
Health Study ◽  
General Level ◽  
Statistical Relationship ◽  
Physical Activity Intensity ◽  
Blood Lipid Profile ◽  
Cross Sectional ◽  
Activity Intensity

Introduction: Inadequate physical activity is one of the causes of fat disorders and regular physical activity is one of the important factors in correcting fat disorders. The aim of this study was to determine the relationship between physical activity levels and blood lipids as a risk factor for cardiovascular disease. Methods: This analytical cross sectional study was conducted using the information of the registration phase of the Yazd People's Health Study on 9962 residents of Yazd in the age group of 20 to 70 years between 2014 and 2015. Study data were obtained using standard questionnaires and participants' blood samples. SPSS software, version 21, t-test, linear regression, and OR comparison of fat disorders were used in the physical activity intensity classes. Results: In the study sample, 49.4% are men. No statistical significant physical activity level was found in the study of the ratio of chance of fat disorder. Moreover, no significant relationship was observed in the study of the linear relationship between the general level of physical activity and fat profile components (p> 0.05). It should be noted that a significant statistical relationship was observed between the level of TC or blood total cholesterol and blood triglycerides with sex, body mass index and family history and some age groups. (p <0.05). Conclusion: In the analysis of the data of this study, no significant statistical relationship was found between blood lipid levels and physical activity.

Physical Activity, Aerobic Fitness, and Seven-Year Changes in Adiposity in the Canadian Population

2002 ◽  
Vol 27 (5) ◽  
pp. 449-462 ◽  
Author(s):  
Michelle D. Fortier ◽  
Peter T. Katzmarzyk ◽  
Claude Bouchard
Keyword(s):  
Physical Activity ◽  
Aerobic Fitness ◽  
Physical Activity Level ◽  
Activity Level ◽  
Activity Levels ◽  
Physical Activity Intensity ◽  
Physical Activity Change ◽  
Activity Intensity ◽  
Baseline Physical Activity ◽  
Fitness Levels

Associations among baseline physical activity, aerobic fitness, changes in physical activity, and 7-y changes in adiposity were determined. The sample consisted of 602 males and 644 females, aged 20-69 y, from the 1981 Canada Fitness Survey and the 1988 Campbell's Survey. Questionnaire-derived measures of physical activity level consisted of activity energy expenditure (AEE) and time spent on physical activity. Participants were grouped into physical activity level categories by AEE and physical activity intensity (based on MET values), and physical activity level changes were determined from movement between tertiles of AEE from baseline to follow-up. Aerobic fitness levels at baseline were determined using the Canadian Aerobic Fitness Test. Changes in body mass, the sum of five skinfolds (SF5), and waist circumference (WC) were used as indicators of adiposity change. ANCOVA and multiple regression analyses indicated that neither baseline physical activity levels, intensity, physical activity change categories, nor aerobic fitness levels were significant predictors of changes in adiposity. In conclusion, physical activity was not predictive of 7-y changes in indicators of adiposity in this sample. Key words: weight gain, longitudinal study, obesity, lifestyle

Influence of Movement Intensity and Physical Activity on Adiposity in Youth

2011 ◽  
Vol 8 (2) ◽  
pp. 164-173 ◽  
Author(s):  
Amy E. Mark ◽  
Ian Janssen
Keyword(s):  
Physical Activity ◽  
Activity Level ◽  
Physical Activity Intensity ◽  
Physically Active ◽  
Activity Intensity ◽  
Intensity Physical Activity ◽  
Vigorous Intensity ◽  
Total Fat ◽  
Total Body ◽  
Percentile Scores

Background:Despite the plethora of research examining the physical activity-adiposity relation in youth, questions remain regarding the ideal intensity. Therefore, the purpose of this study was to explore the independent effects of physical activity intensity and incidental movement on total and trunk adiposity.Methods:The sample consisted of 1165 youth aged 8 to 17 years from the 2003−04 U.S. National Health and Nutrition Examination Survey. Physical activity (low, moderate, vigorous intensity) and incidental movement (activity level when not physically active) were measured using Actigraph accelerometers over 7 days. Total body and trunk fat were measured using dual-energy X-ray absorptiometry; age- and sex-specific percentile scores were calculated.Results:Bivariate analyses revealed an inverse relation between total, low, moderate and vigorous intensity physical activity with total body and trunk fat. After consideration of the total volume of physical activity in the multivariate analyses, moderate-to-vigorous intensity physical activity remained significantly related to total and trunk fat. Participants with the highest (top 12.5%) moderate-to-vigorous intensity activity values had total fat percentile scores that were 34 points lower than participants with the lowest (bottom 25%) values.Conclusion:These results are consistent with public health guidelines which recommend that children and youth participate in moderate-to-vigorous intensity physical activity.

Level of Physical Activity at Lebanese Universities’ Students of Both Genders: A Comparative Study

2021 ◽  
Vol 9 (3) ◽  
pp. 8
Author(s):  
Fadi Fayyad ◽  
Milivoj Dopsaj
Keyword(s):  
Physical Activity ◽  
Extracurricular Activities ◽  
Activity Level ◽  
Moderate Activity ◽  
Vigorous Activity ◽  
Metabolic Equivalent ◽  
Activity Intensity ◽  
University Curriculum ◽  
The University ◽  
Physical Activity Classes

Background: Examining students’ levels of physical activity is important because these students will be the future leaders of their communities. Objectives: The aim of this study was to generate primary information and describe the lifestyle behavior patterns considering physical activity prevalence among gender-related Lebanese college students. Methods: The study involved 600 students (346 Men, 254 Women with mean age 23.5 ± 3.96). The participants’ levels of physical activity was examined by utilizing the International Physical Activity Questionnaire (IPAQ). The over-all level of physical activity including the four-lifestyle fields: work, transportation, home and gardening, and leisure-time, was presented as metabolic equivalent-min per week (MET-min/week). Results: Findings indicated 22% of students with high physical activity level, 61% and 17 % with moderate and low levels respectively. Based on activity Intensity, 47% (n= 282) of students were engaged in vigorous activity, while 45.2% (n= 271) were engaged in moderate activity, and 68.3% (n=410) were engaged in walking activities. Average time spent sitting for the whole sample was 6.23 daily hours. The level of weekly total physical activity expressed in metabolic equivalent represented 2970.5 MET/min/week in males and 2719.5 MET/min/week in females. Conclusion: In general, Lebanese universities students were equally active, with trivial supremacy for males. Lebanese university students met the (WHO) recommendations for physical activity (>150 min/week of moderate activity or > 75 min/week of vigorous activity or an equivalent combination of both activities). Physical Activity must be developed by the provision of physical activity classes in the university curriculum and extracurricular activities.

scholarly journals Metabolic equivalent of task (METs) thresholds as an indicator of physical activity intensity

PLoS ONE ◽  
2018 ◽  
Vol 13 (7) ◽  
pp. e0200701 ◽  
Author(s):  
Márcio de Almeida Mendes ◽  
Inácio da Silva ◽  
Virgílio Ramires ◽  
Felipe Reichert ◽  
Rafaela Martins ◽  
...  
Keyword(s):  
Physical Activity ◽  
Physical Activity Intensity ◽  
Metabolic Equivalent ◽  
Activity Intensity ◽  
Metabolic Equivalent Of Task

Step-Rate Thresholds for Physical Activity Intensity in Persons With Multiple Sclerosis

2014 ◽  
Vol 31 (1) ◽  
pp. 4-18 ◽  
Author(s):  
Stamatis Agiovlasitis ◽  
Robert W. Motl
Keyword(s):  
Physical Activity ◽  
Multiple Sclerosis ◽  
Group Interaction ◽  
Physical Activity Intensity ◽  
Metabolic Equivalent ◽  
Step Rate ◽  
Activity Intensity ◽  
The Relationship ◽  
Healthy Persons

This study examined whether the relationship between metabolic equivalent units (METs) and step-rate is altered in persons with multiple sclerosis (MS) and developed step-rate thresholds for activity intensity for these persons. Participants were 24 persons with MS (20 women; age = 44 ± 12) and 24 healthy persons without MS (20 women; age = 41 ± 11). The MS group was divided using the 12-item MS Walking Scale (MSWS-12) into two walking impairment subgroups: (a) minimal (n = 13, MSWS-12 ≤ 12.5) and (b) mild-moderate (n = 11, MSWS-12 > 12.5). METs were measured with spirometry and step-rate with hand-tally. Steprate, height, group, the step-rate by group interaction, and the square of step-rate significantly predicted METs. At a given height, the step-rate thresholds at 3 and 6 METs were lower for persons with minimal impairment than persons without MS and even lower for persons with mild-moderate impairment. The relationship between METs and step-rate is altered in persons with MS, lowering their step-rate thresholds for activity intensity, especially for persons with MS who have higher levels of walking impairment.

Validation and Comparison of 3 Accelerometers for Measuring Physical Activity Intensity During Nonlocomotive Activities and Locomotive Movements

2012 ◽  
Vol 9 (7) ◽  
pp. 935-943 ◽  
Author(s):  
Yuki Hikihara ◽  
Shigeho Tanaka ◽  
Kazunori Ohkawara ◽  
Kazuko Ishikawa-Takata ◽  
Izumi Tabata
Keyword(s):  
Physical Activity ◽  
The Other ◽  
Physical Activity Intensity ◽  
Metabolic Equivalent ◽  
Activity Intensity ◽  
Douglas Bag ◽  
Douglas Bag Method ◽  
Expired Air

Background:The current study evaluated the validity of 3 commercially-available accelerometers to assess metabolic equivalent values (METs) during 12 activities.Methods:Thirty-three men and thirty-two women were enrolled in this study. The subjects performed 5 nonlocomotive activities and 7 locomotive movements. The Douglas bag method was used to gather expired air. The subjects also wore 3 hip accelerometers, a Lifecorder uniaxial accelerometer (LC), and 2 triaxial accelerometers (ActivTracer, AT; Actimarker, AM).Results:For nonlocomotive activities, the LC largely underestimated METs for all activities (20.3%–55.6%) except for desk work. The AT overestimated METs for desk work (11.3%) and hanging clothes (11.7%), but underestimated for vacuuming (2.3%). The AM underestimated METs for all nonlocomotive activities (8.0%–19.4%) except for hanging clothes (overestimated by 16.7%). The AT and AM errors were significant, but much smaller than the LC errors (23.2% for desk work and –22.3 to –55.6% for the other activities). For locomotive movements, the 3 accelerometers significantly underestimated METs for all activities except for climbing down stairs.Conclusions:We conclude that there were significant differences for most activities in 3 accelerometers. However, the AT, which uses separate equations for nonlocomotive and locomotive activities, was more accurate for nonlocomotive activities than the LC.

Self-reported Physical Activity Intensity and Sleep Apnea Risk

2014 ◽  
Vol 46 ◽  
pp. 374
Author(s):  
Christopher E. Kline ◽  
Matthew P. Buman ◽  
Shawn D. Youngstedt ◽  
Barbara Phillips ◽  
Marco Tulio de Mello ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sleep Apnea ◽  
Physical Activity Intensity ◽  
Activity Intensity

scholarly journals Associations between objectively measured physical activity, sedentary behaviour and time in bed among 75+ community-dwelling Danish older adults

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Li-Tang Tsai ◽  
Eleanor Boyle ◽  
Jan C. Brønd ◽  
Gry Kock ◽  
Mathias Skjødt ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Sedentary Behavior ◽  
Sedentary Behaviour ◽  
Sleep Duration ◽  
Activity Level ◽  
Time In Bed ◽  
Objectively Measured ◽  
Objectively Measured Physical Activity ◽  
Vector Magnitude

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.

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