Search Results

You are looking at 21 - 30 of 175 items for :

  • "physical activity assessment" x
Clear All
Restricted access

Alex Griffiths, Calum Mattocks, Andy Robert Ness, Kate Tilling, Chris Riddoch and Sam Leary

Background:

A study deriving a threshold for moderate- to vigorous-intensity physical activity (MVPA) in terms of accelerometer counts in 12-year-old children was repeated with a subset of the same children at 16 years.

Methods:

Fifteen girls and thirty boys took part in 6 activities (lying, sitting, slow walking, walking, hopscotch and jogging) while wearing an Actigraph 7164 accelerometer and a Cosmed K4b2 portable metabolic unit. Random intercepts modeling was used to estimate cut points for MVPA (defined as 4 METs).

Results:

Using a single model, the sex-specific thresholds derived for MVPA at 16 years were some way below the 3600 counts/minute used for both sexes at age 12, particularly for girls. However graphical examination suggested that a single model might be inadequate to describe both higher- and lower-intensity activities. Models using only lower-intensity activities close to the 4 METs threshold supported retention of the 3600 counts/minute cut point for both sexes.

Conclusions:

When restricting to lower-intensity activities only, these data do not provide sufficient evidence to change the previously established cut point of 3600 counts/minute to represent MVPA. However, further data and more sophisticated modeling techniques are required to confirm this decision.

Restricted access

Leon Straker, Amity Campbell, Svend Erik Mathiassen, Rebecca Anne Abbott, Sharon Parry and Paul Davey

Background:

Capturing the complex time pattern of physical activity (PA) and sedentary behavior (SB) using accelerometry remains a challenge. Research from occupational health suggests exposure variation analysis (EVA) could provide a meaningful tool. This paper (1) explains the application of EVA to accelerometer data, (2) demonstrates how EVA thresholds and derivatives could be chosen and used to examine adherence to PA and SB guidelines, and (3) explores the validity of EVA outputs.

Methods:

EVA outputs are compared with accelerometer data from 4 individuals (Study 1a and1b) and 3 occupational groups (Study 2): seated workstation office workers (n = 8), standing workstation office workers (n = 8), and teachers (n = 8).

Results:

Line graphs and related EVA graphs highlight the use of EVA derivatives for examining compliance with guidelines. EVA derivatives of occupational groups confirm no difference in bouts of activity but clear differences as expected in extended bouts of SB and brief bursts of activity, thus providing evidence of construct validity.

Conclusions:

EVA offers a unique and comprehensive generic method that is able, for the first time, to capture the time pattern (both frequency and intensity) of PA and SB, which can be tailored for both occupational and public health research.

Restricted access

Melissa Raymond, Adele Winter and Anne E. Holland

Background:

Older adults undergoing rehabilitation may have limited mobility, slow gait speeds and low levels of physical activity. Devices used to quantify activity levels in older adults must be able to detect these characteristics.

Objective:

To investigate the validity of the Positional Activity Logger (PAL2) for monitoring position and measuring physical activity in older inpatients (slow stream rehabilitation).

Methods:

Twelve older inpatients (≥65 years) underwent a 1-hour protocol (set times in supine, sitting, standing; stationary and moving). Participants were video-recorded while wearing the PAL2. Time spent in positions and walking (comfortable and fast speeds) were ascertained through video-recording analysis and compared with PAL2 data.

Results:

There was no difference between the PAL2 and video recording for time spent in any position (P-values 0.055 to 0.646). Walking speed and PAL2 count were strongly correlated (Pearson’s r = .913, P < .01). The PAL2 was responsive to within-person changes in gait speed: activity count increased by an average of 52.47 units (95% CI 3.31, 101.63). There was 100% agreement for transitions between lying to sitting and < 1 transition difference between siting to standing.

Conclusion:

The PAL2 is a valid tool for quantifying activity levels, position transitions, and within-person changes in gait speed in older inpatients.

Restricted access

Daniel P. Hatfield, Virginia R. Chomitz, Kenneth Chui, Jennifer M. Sacheck and Christina D. Economo

Background:

Associations between physical activity (PA) intensity and volume and adolescents’ cardiometabolic health have research, policy, and practice implications. This study compares associations between cardiometabolic risk factors and 1) moderate-to-vigorous PA (MVPA) minutes versus total PA volume (accelerometer-derived total activity counts, TAC) and 2) light PA volume (counts at light intensity, L-TAC) versus moderate-to-vigorous PA volume (counts at moderate-to-vigorous intensity, MV-TAC).

Methods:

2105 adolescents from 2003– 2006 NHANES were included. Independent variables were MVPA minutes, TAC, L-TAC, and MV-TAC. Regression models tested associations between PA variables and continuous metabolic risk index (CMRI), waist circumference, systolic and diastolic blood pressure, HDL, insulin, and triglycerides.

Results:

TAC demonstrated a slightly stronger inverse association with CMRI (P = .004) than did MVPA (P = .013). TAC and MVPA were both associated with systolic and diastolic pressure, HDL, and insulin; associations were similar or slightly stronger for TAC. L-TAC and MV-TAC were both associated with CMRI and HDL. Only L-TAC was associated with diastolic pressure. Only MV-TAC was associated with waist circumference, systolic pressure, and insulin.

Conclusions:

Compared with MVPA minutes, TAC demonstrates similar or slightly stronger associations with cardiometabolic risk factors. L-TAC and MV-TAC appear similarly associated with adolescents’ clustered risk but differently associated with individual risk factors.

Restricted access

Jeanette Gustat, Christopher E. Anderson and Sandy J. Slater

Background: Spaces that promote play are important for the physical, social, and psychological growth of children. Public spaces, including playgrounds, provide an important venue for children to engage in play. A simple tool is needed to evaluate playground features and conditions. Methods: A simple play space audit instrument to assess the presence and condition of playground features was tested on a sample of 70 playgrounds during the summer of 2017, in Chicago, IL. Duplicate observations were collected on 17 playgrounds. Frequencies of features were tabulated, and reliability of variables was assessed using percent agreement and kappa statistic. Scores were created to summarize playground “playability,” overall and within domains of general overview, surface, path, and play equipment/structure features. Results: The tool demonstrated acceptable reliability with high kappa values between .79 and .90 for all items in domains. The overall score, general overview score, and play equipment/structure scores were correlated with mean playground usage. Conclusions: This brief instrument allows reliable assessment of playground features and their conditions. The scoring method generates a summary of playground conditions and features, which facilitates comparison of playgrounds. This tool has the potential to assist communities in evaluating their play spaces and identifying where to focus resources for improvements.

Restricted access

Natalie Jayne Taylor, Scott E. Crouter, Rebecca J. Lawton, Mark T. Conner and Andy Prestwich

Background:

Precise measurement of physical activity (PA) is required to identify current levels and changes in PA within a population, and to gauge effectiveness of interventions.

Methods:

The Online Self-reported Walking and Exercise Questionnaire (OSWEQ) was developed for monitoring PA via the Web. Forty-nine participants (mean ± SD; age = 27 ± 11.9yrs) completed the OSWEQ and International PA Questionnaire (IPAQ) short form 3 times [T1/T2/T3 (separated by 7-days)] and wore an Actigraph-GT3X-accelerometer for 7-days between T2-T3. For each measure, estimates of average MET·min·day−1 and time spent in moderate PA (MPA), vigorous PA (VPA) and moderate and vigorous PA (MVPA) were obtained.

Results:

The OSWEQ and IPAQ demonstrated test-retest reliability for MPA, VPA, and MVPA minutes and average MET·min·day−1 between T1-T2 (OSWEQ range, r = .71–.77; IPAQ range, r = .59–.79; all, P < .01). The OSWEQ and IPAQ, compared with the GT3X, had lower estimates (mean error ± 95% PI) of MVPA MET·min·day−1 by 150.4 ± 477.6 and 247.5 ± 477.5, respectively.

Conclusions:

The OSWEQ demonstrates good test-retest reliability over 7-days and better group level estimates of MET·min·day−1 than the IPAQ, compared with the GT3X. These results suggest that the OSWEQ is a reliable and valid measure among young/working age adults and could be useful for monitoring PA trends over time.

Restricted access

Sarah M. Camhi, Susan B. Sisson, William D. Johnson, Peter T. Katzmarzyk and Catrine Tudor-Locke

Background:

Objective physical activity data analyses focus on moderate-to-vigorous physical activity (MVPA) without considering lower intensity lifestyle-type activities (LA). We describe 1) quantity of LA (minutes and steps per day) across demographic groups, 2) proportion of LA to total physical activity, and 3) relationships between LA and MVPA using NHANES 2005−2006 accelerometer adult data (n = 3744).

Methods:

LA was defined as 760 to 2019 counts per minute (cpm) and MVPA as ≥2020 cpm. LA was compared within gender, ethnicity, age, and BMI groups. Regression analyses examined independent effects. Correlations were evaluated between LA and MVPA. All analyses incorporated sampling weights to represent national estimates.

Results:

Adults spent 110.4 ± 1.6 minutes and took 3476 ± 54 steps per day in LA. Similar to MVPA, LA was highest in men, Mexican Americans, and lowest in adults ≥60 years or obese. When LA was held constant, ethnic differences no longer predicted MVPA minutes, and age no longer predicted MVPA steps. LA and MVPA minutes (r = .84) and steps per day (r = .72) were significantly correlated, but attenuated with MVPA modified bouts (≥10 minutes sustained activity).

Conclusions:

LA accumulation differs between demographic subgroups and is related to MVPA: adults who spend more minutes and steps in MVPA also spend them in LA.

Restricted access

Bethany Forseth and Stacy D. Hunter

Background: There is limited research examining the intensity of yoga and intensity variations between different styles. The purpose of this review is to examine the intensity of yoga based on different physiologic responses both between different yoga styles and within styles of yoga. Methods: Articles were searched for on the PubMed database in early 2019. Inclusion criteria were as follows: (1) written in English, (2) cite a specific style of yoga and include whole yoga session, and (3) measure metabolic or heart rate response. Results: Ten articles were reviewed; articles reported oxygen consumption (n = 1), heart rate (n = 4), or both variables (n = 5). Yoga styles assessed included ashtanga (n = 2), Bikram (n = 3), gentle (n = 1), hatha (n = 3), Iyengar (n = 1), power (n = 1), and vinyasa (n = 1). Oxygen consumption commonly categorized yoga as a light-intensity activity, while heart rate responses classified different yoga into multiple intensities. Conclusion: This review demonstrates that large differences in intensity classifications are observed between different styles of yoga. Furthermore, metabolic and heart rate responses can be variable, leading to inconsistent intensity classifications. This is likely due to their nonlinear relationship during yoga. Thus, it is imperative that the field of yoga research works together to create a standard for reporting yoga.

Restricted access

Ryan McGrath, Chantal A. Vella, Philip W. Scruggs, Mark D. Peterson, Christopher J. Williams and David R. Paul

Background: This investigation sought to determine how accelerometer wear (1) biased estimates of sedentary behavior (SB) and physical activity (PA), (2) affected misclassifications for meeting the Physical Activity Guidelines for Americans, and (3) impacted the results of regression models examining the association between moderate to vigorous physical activity (MVPA) and a clinically relevant health outcome. Methods: A total of 100 participants [age: 20.6 (7.9) y] wore an ActiGraph GT3X+ accelerometer for 15.9 (1.6) hours per day (reference dataset) on the hip. The BOD POD was used to determine body fat percentage. A data removal technique was applied to the reference dataset to create individual datasets with wear time ranging from 15 to 10 hours per day for SB and each intensity of PA. Results: Underestimations of SB and each intensity of PA increased as accelerometer wear time decreased by up to 167.2 minutes per day. These underestimations resulted in Physical Activity Guidelines for Americans misclassification rates of up to 42.9%. The regression models for the association between MVPA and body fat percentage demonstrated changes in the estimates for each wear-time adherence level when compared to the model using the reference MVPA data. Conclusions: Increasing accelerometer wear improves daily estimates of SB and PA, thereby also improving the precision of statistical inferences that are made from accelerometer data.

Restricted access

Karyn Tappe, Ellen Tarves, Jayme Oltarzewski and Deirdra Frum

Background:

Predictive modeling for physical activity behavior has included many different psychological components, including planning, motivation, personality, and self-efficacy. However, habit formation in exercise maintenance has not been well explored and lacks reliable measurement tools. The current study explores novel survey questions that examine behavioral components of exercise habit, including frequency, environmental cuing, and temporal constancy of behavior. We then relate these concepts to an established psychological measure of habit, the Self-Report Habit Inventory (SRHI).

Methods:

One hundred and seventy-four exercisers were surveyed at 2 private fitness clubs. A single questionnaire was administered that included the SRHI and the novel behavioral questions developed from habit formation concepts.

Results:

Habit formation was reported by many of the exercisers. Participants scoring higher on the SRHI also reported higher frequency of physical activity and a higher probability of environmental cuing. Exercise frequency did not correlate well with environmental cuing.

Conclusions:

Habit formation appears relevant to the physical activity patterns of many regular exercisers. However, wide variation in response styles was evident suggesting further development and exploration of the novel questionnaire is warranted. The ultimate goals are to include habit in predictive models of physical activity, and then to inform interventions to increase exercise adherence.