scholarly journals Stronger Association between High Intensity Physical Activity and Cardiometabolic Health with Improved Assessment of the Full Intensity Range Using Accelerometry

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1118
Author(s):  
Jonatan Fridolfsson ◽  
Mats Börjesson ◽  
Elin Ekblom-Bak ◽  
Örjan Ekblom ◽  
Daniel Arvidsson
Keyword(s):  
Physical Activity ◽  
High Intensity ◽  
Cardiometabolic Health ◽  
Accelerometer Data ◽  
Improved Method ◽  
Physical Activity Intensity ◽  
Activity Intensity ◽  
Intensity Physical Activity ◽  
Low Pass ◽  
The Relationship

An improved method of physical activity accelerometer data processing, involving a wider frequency filter than the most commonly used ActiGraph filter, has been shown to better capture variations in physical activity intensity in a lab setting. The aim of the study was to investigate how this improved measure of physical activity affected the relationship with markers of cardiometabolic health. Accelerometer data and markers of cardiometabolic health from 725 adults from two samples, LIV 2013 and SCAPIS pilot, were analyzed. The accelerometer data was processed using both the original ActiGraph method with a low-pass cut-off at 1.6 Hz and the improved method with a low-pass cut-off at 10 Hz. The relationship between the physical activity intensity spectrum and a cardiometabolic health composite score was investigated using partial least squares regression. The strongest association between physical activity and cardiometabolic health was shifted towards higher intensities with the 10 Hz output compared to the ActiGraph method. In addition, the total explained variance was higher with the improved method. The 10 Hz output enables correctly measuring and interpreting high intensity physical activity and shows that physical activity at this intensity is stronger related to cardiometabolic health compared to the most commonly used ActiGraph method.

Examining the Relationship Between Physical Activity Intensity and Adiposity in Young Women

2015 ◽  
Vol 12 (6) ◽  
pp. 764-769 ◽  
Author(s):  
Bruce W. Bailey ◽  
Pamela Borup ◽  
James D. LeCheminant ◽  
Larry A. Tucker ◽  
Jacob Bromley
Keyword(s):  
Physical Activity ◽  
Body Composition ◽  
Body Fat ◽  
Young Women ◽  
Physical Activity Intensity ◽  
Fat Percentage ◽  
Bod Pod ◽  
Activity Intensity ◽  
Objectively Measured ◽  
The Relationship

Background:The purpose of this study was to assess the relationship between intensity of physical activity (PA) and body composition in 343 young women.Methods:Physical activity was objectively measured using accelerometers worn for 7 days in women 17 to 25 years. Body composition was assessed using the BOD POD.Results:Young women who spent less than 30 minutes a week performing vigorous PA had significantly higher body fat percentages than women who performed more than 30 minutes of vigorous PA per week (F = 4.54, P = .0113). Young women who spent less than 30 minutes per day in moderate to vigorous PA (MVPA) had significantly higher body fat percentages than those who obtained more than 30 minutes per day of MVPA (F = 7.47, P = .0066). Accumulating more than 90 minutes of MVPA per day was associated with the lowest percent body fat. For every 10 minutes spent in MVPA per day, the odds of having a body fat percentage above 32% decreased by 29% (P = .0002).Conclusion:Vigorous PA and MVPA are associated with lower adiposity. Young women should be encouraged to accumulate at least 30 minutes of MVPA per day, however getting more than 90 minutes a day is predictive of even lower levels of adiposity.

scholarly journals Reexamination of Accelerometer Calibration with Energy Expenditure as Criterion: VO2net Instead of MET for Age-Equivalent Physical Activity Intensity

Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3377 ◽  
Author(s):  
Daniel Arvidsson ◽  
Jonatan Fridolfsson ◽  
Christoph Buck ◽  
Örjan Ekblom ◽  
Elin Ekblom-Bak ◽  
...  
Keyword(s):  
Physical Activity ◽  
Age Groups ◽  
Accelerometer Data ◽  
Physical Activity Intensity ◽  
Free Living ◽  
Activity Intensity ◽  
Age Related ◽  
Younger Age ◽  
Metabolic Equivalent Of Task ◽  
Adolescents And Adults

Accelerometer calibration for physical activity (PA) intensity is commonly performed using Metabolic Equivalent of Task (MET) as criterion. However, MET is not an age-equivalent measure of PA intensity, which limits the use of MET-calibrated accelerometers for age-related PA investigations. We investigated calibration using VO2net (VO2gross − VO2stand; mL⋅min−1⋅kg−1) as criterion compared to MET (VO2gross/VO2rest) and the effect on assessment of free-living PA in children, adolescents and adults. Oxygen consumption and hip/thigh accelerometer data were collected during rest, stand and treadmill walk and run. Equivalent speed (Speedeq) was used as indicator of the absolute speed (Speedabs) performed with the same effort in individuals of different body size/age. The results showed that VO2net was higher in younger age-groups for Speedabs, but was similar in the three age-groups for Speedeq. MET was lower in younger age-groups for both Speedabs and Speedeq. The same VO2net-values respective MET-values were applied to all age-groups to develop accelerometer PA intensity cut-points. Free-living moderate-and-vigorous PA was 216, 115, 74 and 71 min/d in children, adolescents, younger and older adults with VO2net-calibration, but 140, 83, 74 and 41 min/d with MET-calibration, respectively. In conclusion, VO2net calibration of accelerometers may provide age-equivalent measures of PA intensity/effort for more accurate age-related investigations of PA in epidemiological research.

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.

scholarly journals Ability of RT3 Accelerometer Cut Points to Detect Physical Activity Intensity in Ambulatory Children With Cerebral Palsy

2014 ◽  
Vol 31 (4) ◽  
pp. 310-324 ◽  
Author(s):  
Jennifer Ryan ◽  
Michael Walsh ◽  
John Gormley
Keyword(s):  
Physical Activity ◽  
Cerebral Palsy ◽  
Vigorous Physical Activity ◽  
Accelerometer Data ◽  
Physical Activity Intensity ◽  
Cut Points ◽  
Cut Point ◽  
Activity Intensity ◽  
Metabolic Equivalents ◽  
Children With Cerebral Palsy

This study investigated the ability of published cut points for the RT3 accelerometer to differentiate between levels of physical activity intensity in children with cerebral palsy (CP). Oxygen consumption (metabolic equivalents; METs) and RT3 data (counts/min) were measured during rest and 5 walking trials. METs and corresponding counts/min were classified as sedentary, light physical activity (LPA), and moderate to vigorous physical activity (MVPA) according to MET thresholds. Counts were also classified according to published cut points. A published cut point exhibited an excellent ability to classify sedentary activity (sensitivity = 89.5%, specificity = 100.0%). Classification accuracy decreased when published cut points were used to classify LPA (sensitivity = 88.9%, specificity = 79.6%) and MVPA (sensitivity = 70%, specificity = 95–97%). Derivation of a new cut point improved classification of both LPA and MVPA. Applying published cut points to RT3 accelerometer data collected in children with CP may result in misclassification of LPA and MVPA.

scholarly journals A Comparison of Preschoolers’ Physical Activity Indoors versus Outdoors at Child Care

2018 ◽  
Vol 15 (11) ◽  
pp. 2463 ◽  
Author(s):  
Pooja Tandon ◽  
Brian Saelens ◽  
Chuan Zhou ◽  
Dimitri Christakis
Keyword(s):  
Physical Activity ◽  
Child Care ◽  
Preschool Age ◽  
Accelerometer Data ◽  
Physical Activity Intensity ◽  
Activity Intensity ◽  
Preschool Age Children ◽  
Gps Devices ◽  
Outdoor Location ◽  
Indoor And Outdoor

The aims of this study were to quantify and examine differences in preschoolers’ indoor and outdoor sedentary time and physical activity intensity at child care using GPS devices and accelerometers. We conducted an observational study of 46 children (mean age 4.5 years, 30 boys, 16 girls) from five child care centers who wore accelerometers and GPS devices around their waists for five days during regular child care hours. GPS signal-to-noise ratios were used to determine indoor vs. outdoor location. Accelerometer data were categorized by activity intensity. Children spent, on average, 24% of child care time outdoors (range 12–37% by site), averaging 74 min daily outdoors (range 30–119 min), with 54% of children spending ≥60 min/day outdoors. Mean accelerometer activity counts were more than twice as high outdoors compared to indoors (345 (95) vs. 159 (38), (p < 0.001)), for girls and boys. Children were significantly less sedentary (51% of time vs. 75%) and engaging in more light (18% vs. 13%) and moderate-to-vigorous (MVPA) (31% vs. 12%) activity when outdoors compared to indoors (p < 0.001). To achieve a minute of MVPA, a preschooler needed to spend 9.1 min indoors vs. 3.8 min outdoors. Every additional 10 min outdoors each day was associated with a 2.9 min increase in MVPA (2.7 min for girls, 3.0 min for boys). Preschool-age children are twice as active and less sedentary when outdoors compared to indoors in child care settings. To help preschoolers achieve MVPA recommendations and likely attain other benefits, one strategy is to increase the amount of time they spend outdoors and further study how best to structure it.

scholarly journals Employing Machine Learning to Estimate Hallmark Measures of Physical Activities from Wrist-worn Devices Across Age Groups

2021 ◽  
Author(s):  
Mamoun T. Mardini ◽  
Chen Bai ◽  
Amal A. Wanigatunga ◽  
Santiago Saldana ◽  
Ramon Casanova ◽  
...  
Keyword(s):  
Physical Activity ◽  
Machine Learning ◽  
Energy Expenditure ◽  
Age Groups ◽  
Physical Activities ◽  
Accelerometer Data ◽  
Activity Type ◽  
Physical Activity Intensity ◽  
Activity Intensity ◽  
Score Range

Wrist-worn fitness trackers and smartwatches are proliferating with an incessant attention towards health tracking. Given the growing popularity of wrist-worn devices across all age groups, a rigorous evaluation for recognizing hallmark measures of physical activities and estimating energy expenditure is needed to compare their accuracy across the lifespan. The goal of the study was to build machine learning models to recognize physical activity type (sedentary, locomotion, and lifestyle) and intensity (low, light, and moderate), identify individual physical activities, and estimate energy expenditure. The primary aim of this study was to build and compare models for different age groups: young [20-50 years], middle (50-70 years], and old (70-89 years]. Participants (n = 253, 62% women, aged 20-89 years old) performed a battery of 33 daily activities in a standardized laboratory setting while wearing a portable metabolic unit to measure energy expenditure that was used to gauge metabolic intensity. Tri-axial accelerometer collected data at 80-100 Hz from the right wrist that was processed for 49 features. Results from random forests algorithm were quite accurate in recognizing physical activity type, the F1-Score range across age groups was: sedentary [0.955 – 0.973], locomotion [0.942 – 0.964], and lifestyle [0.913 – 0.949]. Recognizing physical activity intensity resulted in lower performance, the F1-Score range across age groups was: sedentary [0.919 – 0.947], light [0.813 – 0.828], and moderate [0.846 – 0.875]. The root mean square error range was [0.835 – 1.009] for the estimation of energy expenditure. The F1-Score range for recognizing individual physical activities was [0.263 – 0.784]. Performances were relatively similar and the accelerometer data features were ranked similarly between age groups. In conclusion, data features derived from wrist worn accelerometers lead to high-moderate accuracy estimating physical activity type, intensity and energy expenditure and are robust to potential age-differences.

scholarly journals Hubungan Perilaku Konsumsi dan Aktivitas Fisik dengan Diabetes Mellitus di Indonesia

2019 ◽  
Vol 47 (2) ◽  
pp. 97-106
Author(s):  
Made Agus Nurjana ◽  
Ni Nyoman Veridiana
Keyword(s):  
Physical Activity ◽  
Diabetes Mellitus ◽  
Physical Activity Intensity ◽  
Keywords Diabetes ◽  
Cross Sectional ◽  
Middle Income ◽  
Activity Intensity ◽  
Light Activity ◽  
Cross Sectional Design ◽  
The Relationship

Abstrak   Prevalensi Diabetes mellitus (DM) mengalami peningkatan secara global baik di negara berpenghasilan tinggi maupun negara berpenghasilan rendah dan menengah termasuk di Indonesia. Indonesia menduduki urutan ke empat dengan prevalensi diabetes tertinggi di dunia setelah India, China, dan Amerika Serikat. Tujuan dari tulisan ini adalah untuk mengkaji hubungan pola konsumsi dan aktivitas fisik dengan kejadian DM di Indonesia berdasarkan data Riskesdas tahun 2013.  Pengumpulan data dilakukan pada bulan Mei - Juni 2013 di 33 provinsi dan 497 kabupaten/kota di Indonesia. Desain penelitian ini adalah cross sectional. Jumlah sampel sebanyak 722.329 responden yang berusia 15 tahun ke atas. Hasil penelitian menunjukkan bahwa aktivitas fisik merupakan faktor risiko dominan terhadap kejadian DM di Indonesia. Masyarakat yang memiliki kebiasaan hanya melakukan aktifitas ringan mempunyai peluang untuk terkena DM 2,9 kali dibandingkan dengan masyarakat yang memiliki kebiasaan melakukan aktifitas berat, sedangkan masyarakat yang memiliki kebiasaan melakukan aktivitas sedang mempunyai peluang lebih rendah terkena DM yaitu 1,8 kali dibandingkan dengan aktivitas berat. Semakin berat aktivitas fisik yang dilakukan maka semakin sedikit kemungkinan terkena DM. Dalam mencegah semakin tingginya prevalensi DM di Indonesia maka diperlukan peningkatkan kesadaran masyarakat untuk meningkatkan intensitas aktivitas fisik terutama bagi masyarakat yang aktivitas fisiknya rendah.   Kata kunci : Diabetes mellitus, perilaku konsumsi, aktivitas fisik   Abstract   Prevalency Diabetes Mellitus (DM) experience increasing globally either in high income states or in the low and middle income states including Indonesia. Indonesia is the fourth prevalency Diabetes Mellitus in the world after India, China, and United States. The aim of this study is to analyze the relationship between consumsion pattern and physical activity on DM in Indonesia based on Riskesdas data in 2013. Data are gathered from may up to June 2013 in 33 provinces and 497 regencies/cities in Indonesia. The research is cross sectional design. The samples are 722.329 respondents aging among 15 years and over. The results show that the physical activity is the risk factor dominantly on the DM in Indonesia. Society having only light activity have a tendency to get DM 2.9 times compared to those who have the strongest activity, while those who are stronger activity have lower tendency to get DM that is 1.8 times compared to those who have the strongest activity. To prevent higher prevalency DM in Indonesia, it is expected to rise the societal care to increase physical activity intensity primarily for those who has the low physical activities.   Keywords : Diabetes mellitus, consumtive behavior, physical activity

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