Is Sitting Always Inactive and Standing Always Active? A Simultaneous Free-Living activPal and ActiGraph Analysis

Sedentary Behavior (SB), defined as sitting with minimal physical activity, is an emergent public health topic. However, the measurement of SB considers either posture (e.g., activPal) or physical activity (e.g., ActiGraph), and thus neglects either active sitting or inactive standing. The aim of this study was to determine the true amount of active sitting and inactive standing in daily life, and to analyze by how much these behaviors falsify the single sensors’ sedentary estimates. Sedentary time of 100 office workers estimated with activPal and ActiGraph was therefore compared with Bland-Altman statistics to a combined sensor analysis, the posture and physical activity index (POPAI). POPAI classified each activPal sitting and standing event into inactive or active using the ActiGraph counts. Participants spent 45.0% [32.2%–59.1%] of the waking hours inactive sitting (equal to SB), 13.7% [7.8%–21.6%] active sitting, and 12.0% [5.7%–24.1%] inactive standing (mean [5th–95th percentile]). The activPal overestimated sedentary time by 30.3% [12.3%–48.4%] and the ActiGraph by 22.5% [3.2%–41.8%] (bias [95% limit-of-agreement]). The results showed that sitting is not always inactive, and standing is not always active. Caution should therefore be paid when interpreting the activPal (ignoring active sitting) and ActiGraph (ignoring inactive standing) measured time as SB.

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Influence of the Perception of Barriers in Practice of PA in Adolescents: Explanatory Model

Healthcare ◽

10.3390/healthcare9040380 ◽

2021 ◽

Vol 9 (4) ◽

pp. 380

Author(s):

Iago Portela-Pino ◽

Myriam Alvariñas-Villaverde ◽

Javier Martínez-Torres ◽

Margarita Pino-Juste

Keyword(s):

Physical Activity ◽

Body Image ◽

Risk Factor ◽

Social Anxiety ◽

Activity Index ◽

School Year ◽

Factorial Model ◽

High Fatigue ◽

Physical Activity Index ◽

And Gender

Background: Sedentarism is an important risk factor for non-communicable diseases. To avoid it, it is necessary to establish the barriers which influence a low level of practice of Physical Activity. Methods: This study, conducted with 833 students, aims to describe a model to explain the barriers determining the level of practice of Physical Activity in adolescents according to age, school year, BMI and gender. The inclusion of the analyzed barriers followed the tetra-factorial model: Body image/physical and social anxiety; Tiredness/laziness; Responsibilities/lack of time and Environment/facilities. Results: The barriers to Physical Activity in adolescents are fatigue and sloth, and temporary obligations. The barrier that least influences the practice of Physical Activity is the environment and body image. It is determined that the subjects with the lowest Physical Activity index were those with a high fatigue and laziness score and higher age. The level of physical activity of this population is medium (95% CI, 2.8274–2.9418). Conclusions: It is necessary to overcome tiredness or apathy towards the practice of Physical Activity, especially in those under 16 years of age.

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Analyzing Free-Living Physical Activity of Older Adults in Different Environments Using Body-Worn Activity Monitors

Journal of Aging and Physical Activity ◽

10.1123/japa.18.2.171 ◽

2010 ◽

Vol 18 (2) ◽

pp. 171-184 ◽

Cited By ~ 35

Author(s):

P. Margaret Grant ◽

Malcolm H. Granat ◽

Morag K. Thow ◽

William M. Maclaren

Keyword(s):

Physical Activity ◽

Older Adults ◽

Sedentary Time ◽

Likelihood Estimation ◽

Day Hospital ◽

Free Living ◽

Activity Monitors ◽

The Third ◽

Patient Groups ◽

Restricted Maximum Likelihood Estimation

This study measured objectively the postural physical activity of 4 groups of older adults (≥65 yr). The participants (N= 70) comprised 3 patient groups—2 from rehabilitation wards (cityn= 20, 81.8 ± 6.7 yr; ruraln= 10, 79.4 ± 4.7 yr) and the third from a city day hospital (n= 20, 74.7 ± 7.9 yr)—and a healthy group to provide context (n= 20, 73.7 ± 5.5 yr). The participants wore an activity monitor (activPAL) for a week. A restricted maximum-likelihood-estimation analysis of hourly upright time (standing and walking) revealed significant differences between day, hour, and location and the interaction between location and hour (p< .001). Differences in the manner in which groups accumulated upright and sedentary time (sitting and lying) were found, with the ward-based groups sedentary for prolonged periods and upright for short episodes. This information may be used by clinicians to design appropriate rehabilitation interventions and monitor patient progress.

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Abstract 17026: Effects of Supervised Exercise Therapy on Free-Living Physical Activity Among Patients With Symptomatic Peripheral Artery Disease

Circulation ◽

10.1161/circ.138.suppl_1.17026 ◽

2018 ◽

Vol 138 (Suppl_1) ◽

Author(s):

Erica Schorr ◽

Mary Whipple ◽

Diane Treat-Jacobson

Keyword(s):

Physical Activity ◽

Peripheral Artery Disease ◽

Exercise Therapy ◽

Sedentary Time ◽

Peripheral Artery ◽

Activity Tracking ◽

Free Living ◽

Supervised Exercise ◽

Artery Disease ◽

Tracking Devices

Introduction: Evidence supporting the effects of supervised exercise therapy (SET) on alleviating symptoms and improving walking ability for patients with symptomatic peripheral artery disease (PAD) is robust and well recognized. However, little is known about the impact of SET on free-living physical activity (PA). The aim of this study was to examine the relationship between participation in SET and changes in free-living PA among individuals in the the EX ercise Training to Reduce Claudication: Arm ER gometry versus T readmill Walking ( EXERT ) trial. Methods: In this randomized, controlled trial, 104 participants (mean age 68±9; 29% female) were allocated to receive treadmill (TM) exercise (n=41), upper body ergometry (UBE) exercise (n=42), or usual-care (UC) (n=21) for 12 weeks. Exercise participants attended SET three times per week; UC participants met with study staff weekly. PA was measured over 7 days via waist-worn ActiGraph accelerometers at baseline, 6, and 12 weeks. Steps per day was the primary outcome. Secondary outcomes were proportion of time in light and moderate to vigorous physical activity (MVPA), and sedentary time. PA was controlled for in TM participants by using SET logs. Results were analyzed using descriptive statistics, two-sample t-tests, and analysis of variance. Results: Regardless of randomization, average daily steps were low at baseline and 6 weeks (4,013 steps, p =.72; and 3,911 steps, p =.84, respectively), and slightly higher at 12 weeks (4,307 steps; p =.93). Although not statistically significant but perhaps clinically relevant, UBE participants exhibited greater increases in MVPA over 12 weeks (0.9% to 1.3%; F =.48, p =.62) compared to TM (1.2% to 1.3%; F =.35, p =.71) and UC (1.3% to 1.5%, F =.03, p =.97); similarly all participants exhibited reductions in sedentary time and increases in free-living PA between baseline and 12 weeks. Conclusions: These data suggest individuals with PAD attending SET replace sedentary time with light or moderate intensity PA regardless of exercise modality. Despite study participants meeting the recommended daily steps for adults with chronic conditions (3,500-5,500 steps), it is suspected that they did not reach the daily goal of 30 minutes of enhanced PA to reduce health risks. Future research should incorporate activity tracking devices that can provide feedback on PA as an approach to meet daily PA goals. Activity tracking devices used in conjunction with SET may further improve walking distance, symptom management, and quality of life among patients with symptomatic PAD.

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Framingham Physical Activity Index

Medicine & Science in Sports & Exercise ◽

10.1097/00005768-199706001-00008 ◽

1997 ◽

Vol 29 (Supplement) ◽

pp. 33-35

Author(s):

&NA;

Keyword(s):

Physical Activity ◽

Activity Index ◽

Physical Activity Index

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PREDICTION OF LOW HDL-CHOLESTEROL USING ROUTINE PHYSICAL EXAM AND A SIMPLE PHYSICAL ACTIVITY INDEX

Journal of Cardiopulmonary Rehabilitation ◽

10.1097/00008483-199409000-00010 ◽

1994 ◽

Vol 14 (5) ◽

pp. 321

Author(s):

Mitchell H. Whaley ◽

Leonard A. Kaminsky ◽

Gregory B. Dwyer ◽

Leroy H. Getchell

Keyword(s):

Physical Activity ◽

Activity Index ◽

Hdl Cholesterol ◽

Physical Exam ◽

Low Hdl ◽

Physical Activity Index

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Educational training program to increase the moderate to vigorous physical activity index in physical education teachers

Retos ◽

10.47197/retos.v0i39.78014 ◽

2020 ◽

pp. 192-199

Author(s):

Javier Arturo Hall-López

Keyword(s):

Physical Activity ◽

Physical Education ◽

Training Program ◽

Activity Index ◽

Vigorous Physical Activity ◽

World Health ◽

Physical Education Teachers ◽

Educational Training ◽

Physical Activity Index ◽

Educational Training Program

Abstract. Objective: To design and evaluate a training program to increase the moderate to vigorous physical activity index in physical education teachers. Method: the volunteer subjects participated in the educational training program whose goal was to obtain competences on how to create a pedagogical climate in physical education class oriented to the participation of students in moderate to vigorous physical activity at least 50% of the class evaluated quantitatively using the system for observing fitness instruction time (SOFIT), during their university studies and when they have graduated as physical education teachers. Results: The physical activity index increased from 36.6% to 61.2%. Conclusions: The application of the program showed effectiveness with didactic strategies to involve the student in moderate to vigorous physical activity as established by the World Health Organization. Resumen. Objetivo: Diseñar y evaluar un programa de formación educativa para aumentar el índice de actividad física moderada a vigorosa en profesores de educación física. Método: los sujetos voluntarios participaron en el programa de formación que tuvo como meta obtener competencias sobre cómo crear un clima pedagógico en la clase de educación física orientado a la participación de los estudiantes en actividad física moderada a vigorosa por lo menos el 50% de la clase evaluado de manera cuantitativa mediante el sistema para observar el tiempo de instrucción de actividad física (SOFIT), durante sus estudios universitarios y al ser egresados como profesores de educación física. Resultados: el índice de actividad física se incrementó de 36.6% a 61.2%. Conclusiones: La aplicación del programa mostro efectividad con estrategias didácticas para involucrar al alumno en actividad física moderada a vigorosa como lo establece la Organización Mundial de la Salud.

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Physical Activity Intensity Cut-Points for Wrist-Worn GENEActiv in Older Adults

Frontiers in Sports and Active Living ◽

10.3389/fspor.2020.579278 ◽

2021 ◽

Vol 2 ◽

Author(s):

François Fraysse ◽

Dannielle Post ◽

Roger Eston ◽

Daiki Kasai ◽

Alex V. Rowlands ◽

...

Keyword(s):

Physical Activity ◽

Older Adults ◽

Classification Accuracy ◽

Operating Characteristic ◽

Sedentary Time ◽

Vigorous Physical Activity ◽

Physical Activity Intensity ◽

Characteristic Analysis ◽

Free Living ◽

Activity Intensity

Purpose: This study aims to (1) establish GENEActiv intensity cutpoints in older adults and (2) compare the classification accuracy between dominant (D) or non-dominant (ND) wrist, using both laboratory and free-living data.Methods: Thirty-one older adults participated in the study. They wore a GENEActiv Original on each wrist and performed nine activities of daily living. A portable gas analyzer was used to measure energy expenditure for each task. Testing was performed on two occasions separated by at least 8 days. Some of the same participants (n = 13) also wore one device on each wrist during 3 days of free-living. Receiver operating characteristic analysis was performed to establish the optimal cutpoints.Results: For sedentary time, both dominant and non-dominant wrist had excellent classification accuracy (sensitivity 0.99 and 0.97, respectively; specificity 0.91 and 0.86, respectively). For Moderate to Vigorous Physical Activity (MVPA), the non-dominant wrist device had better accuracy (ND sensitivity: 0.90, specificity 0.79; D sensitivity: 0.90, specificity 0.64). The corresponding cutpoints for sedentary-to-light were 255 and 375 g · min (epoch independent: 42.5 and 62.5 mg), and those for the light-to-moderate were 588 and 555 g · min (epoch-independent: 98.0 and 92.5 mg) for the non-dominant and dominant wrist, respectively. For free-living data, the dominant wrist device resulted in significantly more sedentary time and significantly less light and MVPA time compared to the non-dominant wrist.

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Sleep disturbance as a moderator of the association between physical activity and later pain onset among American adults aged 50 and over: evidence from the Health and Retirement Study

BMJ Open ◽

10.1136/bmjopen-2019-036219 ◽

2020 ◽

Vol 10 (6) ◽

pp. e036219

Author(s):

Daniel Whibley ◽

Heidi M Guyer ◽

Leslie M Swanson ◽

Tiffany J Braley ◽

Anna L Kratz ◽

...

Keyword(s):

Physical Activity ◽

Sleep Disturbance ◽

Activity Index ◽

Vigorous Physical Activity ◽

Index Score ◽

Health And Retirement Study ◽

Physical Activity Index ◽

Activity Index Score ◽

Incident Pain ◽

Retirement Study

ObjectiveTo examine whether sleep disturbance modifies the association between physical activity and incident pain.DesignProspective population-based study.SettingHealth and Retirement Study.ParticipantsAmerican adults aged ≥50 years who reported no troublesome pain in 2014 were re-assessed for pain in 2016. Of 9828 eligible baseline respondents, 8036 (82%) had complete follow-up data for adjusted analyses (weighted analysis population N=42 407 222).ExposuresPhysical activity was assessed via interview with questions about time spent in moderate and vigorous physical activity. Sleep disturbance, assessed using a modified form of the Jenkins Sleep Scale, was examined as a potential moderator.Main outcome measureTroublesome pain.ResultsIn weighted analyses, 37.9% of the 2014 baseline pain-free sample participated in moderate or vigorous physical activity once a week or less, with an overall mean Physical Activity Index Score of 9.0 (SE=0.12). 18.6% went on to report troublesome pain in 2016. Each one-point higher on the Physical Activity Index Score was associated with a reduced odds ratio (OR) of incident pain for those who endorsed sleep disturbance never/rarely (OR=0.97, 95% CI 0.94 to 0.99), but not for those who endorsed sleep disturbance sometimes (OR=0.99, 95% CI 0.97 to 1.01) or most of the time (OR=1.01, 95% CI 0.99 to 1.03). The analysis of possible interaction demonstrated that frequency of sleep disturbance moderated the physical activity and incident pain association (Wald test: p=0.02).ConclusionsThe beneficial association of physical activity on reduced likelihood of later pain was only observed in persons who endorsed low levels of sleep disturbance.

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