Validation of accelerometer wear and nonwear time classification algorithm

Physical activity monitoring in extremely obese adolescents from the Teen-LABORATORIES study

BACKGROUND

The accuracy of physical activity (PA) monitors to discriminate between PA, sedentary behavior, and nonwear in extremely obese (EO) adolescents is unknown.

METHODS

Twenty-five subjects (9 male/16 female; age = 16.5 ± 2.0 y; BMI = 51 ± 8 kg/m2) wore 3 activity monitors (StepWatch [SAM], Actical [AC], Actiheart [AH]) during a 400-m walk test (400MWT), 2 standardized PA bouts of varying duration, and 1 sedentary bout.

RESULTS

For the 400MWT, percent error between observed and monitor-recorded steps was 5.5 ± 7.1% and 82.1 ± 38.6% for the SAM and AC steps, respectively (observed vs. SAM steps: -17.2 ± 22.2 steps; observed vs. AC steps: -264.5 ± 124.8 steps). All activity monitors were able to differentiate between PA and sedentary bouts, but only SAM steps and AH heart rate were significantly different between sedentary behavior and nonwear (P < .001). For all monitors, sedentary behavior was characterized by bouts of zero steps/counts punctuated by intermittent activity steps/counts; nonwear was represented almost exclusively by zero steps/counts.

CONCLUSION

Of all monitors tested, the SAM was most accurate in terms of counting steps and differentiating levels of PA and thus, most appropriate for EO adolescents. The ability to accurately characterize PA intensity in EO adolescents critically depends on activity monitor selection.

Sporadic and bouted physical activity and the metabolic syndrome in adults

PURPOSE

Physical activity guidelines recommend that adults accumulate at least 150 min of moderate-to-vigorous physical activity (MVPA) per week in bouts of at least 10 min. However, sporadic MVPA contributes significantly to total physical activity and may also affect health. The study objective was to determine, within adults age 18 to 64 yr, whether MVPA accumulated in bouts is more strongly associated with metabolic syndrome (MetS) than an equivalent volume of MVPA accumulated sporadically.

METHODS

The study sample included 1119 adults age 18 to 64 yr from the 2007-2009 Canadian Health Measures Survey, a nationally representative cross-sectional study. The energy expenditure from bouted (at least 10 consecutive minutes) and sporadic (<10 consecutive minutes) MVPA was measured for 7 d using Actical accelerometers. The presence of MetS was determined using established criteria. Associations were examined using logistic regression and controlled for covariates (age, sex, education, diet, and smoking).

RESULTS

After adjusting for the covariates and each other, bouted and sporadic MVPA were independently associated with the MetS. For each additional MET-hour per week of bouted MVPA, the relative odds of the MetS decreased by 9% (95% confidence interval, 3%-14%). For each additional MET-hour per week of sporadic MVPA, the relative odds of the MetS decreased by 11% (5%-16%). Overlapping confidence interval indicates no difference in the effect estimates for bouted and sporadic MVPA. Secondary analyses revealed that small bursts of sporadic MVPA (1-3 min) were meaningful when predicting the MetS.

CONCLUSION

Within this representative sample of Canadian adults, sporadic MVPA was associated with the MetS to a similar order of magnitude as an equivalent volume of bouted MVPA.

Associations of social and environmental supports with sedentary behavior, light and moderate-to-vigorous physical activity in obese underserved adolescents

Background

Evidence to support differential health impacts of sedentary behavior (SB), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) is building. However, few studies have examined individual, social, and environmental supports across the full range of sedentary and physical activities, including key influences such as self-efficacy, parenting factors, and home and neighborhood resources. This may be particularly important in underserved (low-income, minority), overweight/obese adolescents due to the social and environmental challenges (lack of resources, etc.) associated with increasing MVPA. This study evaluated a range of bioecological factors including individual (self-efficacy), parental (parental support, monitoring, limit-setting, and nurturance), and environmental (perceived home resources for PA and neighborhood support for PA) predictors of SB, LPA and MVPA in overweight/obese adolescents.

Methods

Overweight/obese and predominantly minority adolescents and caregivers (n = 181) completed measures in 2010 in the US including surveys assessing self-efficacy for PA, parenting variables related to PA and home and neighborhood supports for PA. Outcomes included 7-day accelerometer estimates of SB, LPA, and MVPA.

Results

Regression analyses showed parental social support and neighborhood support were significantly associated with LPA. No significant associations were found for SB or MVPA.

Conclusions

Results emphasized the importance of examining a range of sedentary and PA intensities and highlighted the role of parental and neighborhood social supports for LPA. These results have important implications that suggest that health promotion efforts should target social and environmental supports for increasing LPA in youth who are overweight/obese.

Calibration of self-report tools for physical activity research: the Physical Activity Questionnaire (PAQ)

Background

The utility of self-report measures of physical activity (PA) in youth can be greatly enhanced by calibrating self-report output against objectively measured PA data.

This study demonstrates the potential of calibrating self-report output against objectively measured physical activity (PA) in youth by using a commonly used self-report tool called the Physical Activity Questionnaire (PAQ).

Methods

A total of 148 participants (grades 4 through 12) from 9 schools (during the 2009–2010 school year) wore an Actigraph accelerometer for 7 days and then completed the PAQ. Multiple linear regression modeling was used on 70% of the available sample to develop a calibration equation and this was cross validated on an independent sample of participants (30% of sample).

Results

A calibration model with age, gender, and PAQ scores explained 40% of the variance in values for the percentage of time in moderate-to-vigorous PA (_%MVPA) measured from the accelerometers (_%MVPA = 14.56 - (sex*0.98) - (0.84*age) + (1.01*PAQ)). When tested on an independent, hold-out sample, the model estimated _%MVPA values that were highly correlated with the recorded accelerometer values (r = .63) and there was no significant difference between the estimated and recorded activity values (mean diff. = 25.3 ± 18.1 min; p = .17).

Conclusions

These results suggest that the calibrated PAQ may be a valid alternative tool to activity monitoring instruments for estimating _%MVPA in groups of youth.

Prevalence of physical activity and sedentary behavior among stroke survivors in the United States

BACKGROUND

The risk of stroke is greatest among adults who have experienced a previous stroke, transient ischemic attack, or myocardial infarction. Physical activity may reduce the secondary risk of stroke through mediating effects on blood pressure, vasoconstriction, and circulating lipid concentrations; however, little is known about the prevalence of physical activity and sedentary behavior among stroke survivors in the United States.

METHODS

Using data from the National Health and Nutrition Examination Survey (NHANES), we describe self-reported and objectively measured physical activity and sedentary behavior among adults with a self-reported history of stroke. We also contrast physical activity among stroke survivors with that of adults without stroke (unexposed) to illustrate expected behavior in the absence of disease.

RESULTS

Fewer participants with stroke met weekly physical activity guidelines as outlined in the 2008 Physical Activity Guidelines for Americans when compared with unexposed participants (17.9% vs 25.0%) according to self-reported data. In addition, participants with stroke reported less moderate (46.1% vs 54.7%) and vigorous (9.1% vs 19.6%) leisure activity compared with unexposed participants. As measured by accelerometer, time since diagnosis was inversely associated with physical activity engagement, and participants with stroke recorded more daily hours of sedentary behavior compared with unexposed participants (10.1 hours vs 8.9 hours).

CONCLUSION

Findings from this study provide a basis for future work seeking to measure the impact of physical activity on the secondary prevention of stroke by characterizing the prevalence of physical activity and sedentary behavior among stroke survivors in the United States.

Built environment and physical activity in New Zealand adolescents: a protocol for a cross-sectional study

INTRODUCTION

Built-environment interventions have the potential to provide population-wide effects and the means for a sustained effect on behaviour change. Population-wide effects for adult physical activity have been shown with selected built environment attributes; however, the association between the built environment and adolescent health behaviours is less clear. This New Zealand study is part of an international project across 10 countries (International Physical Activity and the Environment Network-adolescents) that aims to characterise the links between built environment and adolescent health outcomes.

METHODS AND ANALYSES

An observational, cross-sectional study of the associations between measures of the built environment with physical activity, sedentary behaviour, body size and social connectedness in 1600 New Zealand adolescents aged 12-18 years will be conducted in 2013-2014. Walkability and neighbourhood destination accessibility indices will be objectively measured using Geographic Information Systems (GIS). Physical activity and sedentary behaviours will be objectively measured using accelerometers over seven consecutive days. Body mass index will be calculated as weight divided by squared height. Demographics, socioeconomic status, active commuting behaviours and perceived neighbourhood walkability will be assessed using the Neighbourhood Environment Walkability Scale for Youth and psychosocial indicators. A web-based computer-assisted personal interview tool Visualisation and Evaluation of Route Itineraries, Travel Destinations, and Activity Spaces (VERITAS) and Global Positioning System (GPS) receivers will be used in a subsample of 300 participants. A qualitative research component will explore barriers and facilitators for physical activity in adolescents with respect to the built and social environment in a subsample of 80 participants.

ETHICS AND DISSEMINATION

The study received ethical approval from the Auckland University of Technology Ethics Committee (12/161). Data will be entered and stored into a secure (password protected) database. Only the named researchers will have access to the data. Data will be stored for 10 years and permanently destroyed thereafter. The results papers will be submitted for publication in peer-reviewed journals.

Separating bedtime rest from activity using waist or wrist-worn accelerometers in youth

Recent interest in sedentary behavior and technological advances expanded use of watch-size accelerometers for continuous monitoring of physical activity (PA) over extended periods (e.g., 24 h/day for 1 week) in studies conducted in natural living environment. This approach necessitates the development of new methods separating bedtime rest and activity periods from the accelerometer recordings. The goal of this study was to develop a decision tree with acceptable accuracy for separating bedtime rest from activity in youth using accelerometer placed on waist or wrist. Minute-by-minute accelerometry data were collected from 81 youth (10-18 years old, 47 females) during a monitored 24-h stay in a whole-room indirect calorimeter equipped with a force platform covering the floor to detect movement. Receiver Operating Characteristic (ROC) curve analysis was used to determine the accelerometer cut points for rest and activity. To examine the classification differences, the accelerometer bedtime rest and activity classified by the algorithm in the development group (n = 41) were compared with actual bedtime rest and activity classification obtained from the room calorimeter-measured metabolic rate and movement data. The selected optimal bedtime rest cut points were 20 and 250 counts/min for the waist- and the wrist-worn accelerometer, respectively. The selected optimal activity cut points were 500 and 3,000 counts/min for waist and wrist-worn accelerometers, respectively. Bedtime rest and activity were correctly classified by the algorithm in the validation group (n = 40) by both waist- (sensitivity: 0.983, specificity: 0.946, area under ROC curve: 0. 872) and wrist-worn (0.999, 0.980 and 0.943) accelerometers. The decision tree classified bedtime rest correctly with higher accuracy than commonly used automated algorithm for both waist- and wrist-warn accelerometer (all p<0.001). We concluded that cut points developed and validated for waist- and wrist-worn uniaxial accelerometer have a good power for accurate separation of time spent in bedtime rest from activity in youth.

Association of physical activity in the past year and immediately after in vitro fertilization on pregnancy

OBJECTIVE

To estimate the association of physical activity on in vitro fertilization (IVF).

DESIGN

Prospective cohort study.

SETTING

Academic infertility clinic.

PATIENT(S)

Women (n = 121) undergoing nondonor IVF embryo transfer (fresh or frozen).

INTERVENTION(S)

The women completed a questionnaire on past year physical activity and wore an accelerometer from embryo transfer to serum pregnancy testing.

MAIN OUTCOME MEASURE(S)

Implantation, intrauterine gestation, and live birth.

RESULT(S)

Based on self-reported past year physical activity, the adjusted odds of intrauterine gestation was higher among those that had higher continuous active living (odds ratio [OR] 1.96, 95% confidence interval [CI] 1.09-3.50), sports/exercise (OR 1.48, CI 1.02-2.15), and total activity (OR 1.52, 95%CI 1.15-2.01) indices. After embryo transfer, women did almost no vigorous activity (median 0 min/d) as measured by the accelerometer. More of their time was spent in light activity (median 3.0 h/d) and sedentary behaviors (median 9.3 h/d). Accelerometer-measured physical activity and sedentary behavior after embryo transfer were not associated with any IVF outcome.

CONCLUSION(S)

An active lifestyle in the preceding year favorably impacted the IVF outcome. After embryo transfer, women engaged in mostly light physical activity and sedentary behaviors; therefore, the impact of vigorous physical activity on implantation could not be determined.

Objectively measured physical activity in four-year-old British children: a cross-sectional analysis of activity patterns segmented across the day

BACKGROUND

Little is known about preschool-aged children's levels of physical activity (PA) over the course of the day. Using time-stamped data, we describe the levels and patterns of PA in a population-based sample of four-year-old British children.

METHODS

Within the Southampton Women's Survey the PA levels of 593 4-year-old children (51% female) were measured using (Actiheart) accelerometry for up to 7 days. Three outcome measures: minutes spent sedentary (<20 cpm); in light (LPA: ≥20-399 cpm) and in moderate-to-vigorous activity (MVPA: ≥400 cpm) were derived. Average daily activity levels were calculated and then segmented across the day (morning, afternoon and evening). MVPA was log-transformed. Two-level random intercept models were used to analyse associations between activity level and temporal and demographic factors.

RESULTS

Children were active for 67% (mean 568.5 SD 79.5 minutes) of their daily registered time on average, with 88% of active time spent in LPA. All children met current UK guidelines of 180 minutes of daily activity. There were no differences in children's average daily levels of sedentary activity and LPA by temporal and demographic factors: differences did emerge when activity was segmented across the day. Sex differences were largest in the morning, with girls being more sedentary, spending fewer minutes in LPA and 18% less time in MVPA than boys. Children were more sedentary and less active (LPA and MVPA) in the morning if they attended childcare full-time compared to part-time, and on weekend mornings compared to weekdays. The reverse was true for weekend afternoons and evenings. Children with more educated mothers were less active in the evenings. Children were less sedentary and did more MVPA on summer evenings compared to winter evenings.

CONCLUSIONS

Preschool-aged children meet current physical activity guidelines, but with the majority of their active time spent in LPA, investigation of the importance of activity intensity in younger children is needed. Activity levels over the day differed by demographic and temporal factors, highlighting the need to consider temporality in future interventions. Increasing girls' morning activity and providing opportunities for daytime activity in winter months may be worthwhile.

Innovation through Wearable Sensors to Collect Real-Life Data among Pediatric Patients with Cardiometabolic Risk Factors

Background. While increasing evidence links environments to health behavior, clinicians lack information about patients' physical activity levels and lifestyle environments. We present mobile health tools to collect and use spatio-behavioural lifestyle data for personalized physical activity plans in clinical settings. Methods. The Dyn@mo lifestyle intervention was developed at the Sainte-Justine University Hospital Center to promote physical activity and reduce sedentary time among children with cardiometabolic risk factors. Mobility, physical activity, and heart rate were measured in free-living environments during seven days. Algorithms processed data to generate spatio-behavioural indicators that fed a web-based interactive mapping application for personalised counseling. Proof of concept and tools are presented using data collected among the first 37 participants recruited in 2011. Results. Valid accelerometer data was available for 5.6 (SD = 1.62) days in average, heart rate data for 6.5 days, and GPS data was available for 6.1 (2.1) days. Spatio-behavioural indicators were shared between patients, parents, and practitioners to support counseling. Conclusion. Use of wearable sensors along with data treatment algorithms and visualisation tools allow to better measure and describe real-life environments, mobility, physical activity, and physiological responses. Increased specificity in lifestyle interventions opens new avenues for remote patient monitoring and intervention.

Objectively measured physical activity is related to cognitive function in older adults

OBJECTIVES

To explore the relationship between cognitive functioning and time spent at different intensities of physical activity (PA) in free-living older adults.

DESIGN

Cross sectional analyses.

SETTING

Continuing care retirement communities.

PARTICIPANTS

Older adults residing in seven continuing care retirement communities in San Diego County with an average age of 83; 70% were female, and 35% had a graduate-level education (N = 217).

MEASUREMENTS

PA was measured objectively using hip worn accelerometers with data aggregated to the minute level. Three cut points were used to assess low light-intensity PA (LLPA), high light-intensity PA (HLPA), and moderate- to vigorous-intensity PA (MVPA). The Trail Making Test (TMT) Parts A and B were completed, and time for each test (seconds) and time for Part B minus time for Part A (seconds) were used as measures of cognitive function. Variables were log-transformed and entered into linear regression models adjusting for demographic factors (age, education, sex) and other PA intensity variables.

RESULTS

LLPA was not related to any TMT test score. HLPA was significantly related to TMT A, B, and B minus A but only in unadjusted models. MVPA was related to TMT B and B minus A after adjusting for demographic variables.

CONCLUSION

There may be a dose response between PA intensity and cognitive functioning in older adults. The stronger findings supporting a relationship between MVPA and cognitive functioning are consistent with previous observational and intervention studies.

Cross-cultural validation of a simple self-report instrument of physical activity in immigrants from the Middle East and native Swedes

AIM

To investigate cross-cultural validity of a simple self-report instrument of physical activity intended to be used in Swedish health care.

METHODS

A validation study performed in 599 Iraqis (58% men) and 553 Swedes (53% men) aged 30-75 years living in the city of Malmö, Sweden. The self-report instrument by the Swedish National Board of Health and Welfare was compared to corresponding measures assessed from accelerometry as reference.

RESULTS

The agreement between the methods in assessing the participants as sufficiently/insufficiently physically active (cut-point 150 min/week) was 65% in the Iraqis and 52% in the Swedes (p<0.001). The proportion disagreement where the self-reported physical activity was sufficient but insufficient according to the accelerometry was 26% and 45% in Iraqis and Swedes, respectively. Physical activity time (min/week) was overestimated by self-report compared to accelerometry by 71% in the Iraqis and 115% in the Swedes (p<0.001). The smallest and largest overestimation was seen in Iraqi (57%) and Swedish (139%) women, respectively. The deviation of the self-report instrument compared to accelerometry was related to the physical activity level, as the overestimation mainly occurred at lower physical activity.

CONCLUSIONS

The self-report instrument proposed by the Swedish National Board of Health and Welfare may overestimate the proportion sufficiently physically active, but to an extent depending on cultural background and gender.

Using accelerometers to measure physical activity in large-scale epidemiological studies: issues and challenges

BACKGROUND

The current guidelines for aerobic activity require that adults carry out ≥150 min/week of moderate-intensity physical activity, with a large body of epidemiological evidence showing this level of activity to decrease the incidence of many chronic diseases. Less is known about whether light-intensity activities also have such benefits, and whether sedentary behaviour is an independent predictor of increased risks of these chronic diseases, as imprecise assessments of these behaviours and cross-sectional study designs have limited knowledge to date.

METHODS

Recent technological advances in assessment methods have made the use of movement sensors, such as the accelerometer, feasible for use in longitudinal, large-scale epidemiological studies. Several such studies are collecting sensor-assessed, objective measures of physical activity with the aim of relating these to the development of clinical endpoints. This is a relatively new area of research; thus, in this article, we use the Women's Health Study (WHS) as a case study to illustrate the challenges related to data collection, data processing and analyses of the vast amount of data collected.

RESULTS

The WHS plans to collect 7 days of accelerometer-assessed physical activity and sedentary behaviour in ~18 000 women aged ≥62 years. Several logistical challenges exist in collecting data; nonetheless, as of 31 August 2013, 11 590 women have already provided some data. In addition, the WHS experience on data reduction and data analyses can help inform other similar large-scale epidemiological studies.

CONCLUSIONS

Important data on the health effects of light-intensity activity and sedentary behaviour will emerge from large-scale epidemiological studies collecting objective assessments of these behaviours.

Neighborhood walkability, income, and hour-by-hour physical activity patterns

PURPOSE

This study aimed to investigate both the mean daily physical activity and the hour-by-hour physical activity patterns across the day using accelerometry and how they are associated with neighborhood walkability and individual income.

METHODS

Moderate physical activity (MPA) was assessed by accelerometry in 2252 adults in the city of Stockholm, Sweden. Neighborhood walkability (residential density, street connectivity, and land use mix) was objectively assessed within 1000m network buffers around the participants' residence and individual income was self-reported.

RESULTS

Living in a high walkability neighborhood was associated with more mean daily MPA compared with living in a low walkability neighborhood on weekdays and weekend days. Hour-by-hour analyses showed that this association appeared mainly in the afternoon/early evening during weekdays, whereas it appeared across the middle of the day during weekend days. Individual income was associated with mean daily MPA on weekend days. On weekdays, the hour-by-hour analyses showed that high income was associated with more MPA around noon and in late afternoon/early evening, whereas low income was associated with more MPA at the hours before noon and in the early afternoon. During the weekend, high income was more consistently associated with higher MPA.

CONCLUSIONS

Hour-by-hour accelerometry physical activity patterns provides a more comprehensive picture of the associations between neighborhood walkability and individual income and physical activity and the variability of these associations across the day.

Energy expenditure compared to physical activity measured by accelerometry and self-report in adolescents: a validation study

Background

Physical inactivity is responsible for 5.3 million deaths annually worldwide. To measure physical activity energy expenditure, the doubly labeled water (DLW) method is the gold standard. However, questionnaires and accelerometry are more widely used. We compared physical activity measured by accelerometer and questionnaire against total (TEE) and physical activity energy expenditure (PAEE) estimated by DLW.

Methods

TEE, PAEE (TEE minus resting energy expenditure) and body composition were measured using the DLW technique in 25 adolescents (16 girls) aged 13 years living in Pelotas, Brazil. Physical activity was assessed using the Actigraph accelerometer and by self-report. Physical activity data from accelerometry and self-report were tested against energy expenditure data derived from the DLW method. Further, tests were done to assess the ability of moderate-to-vigorous intensity physical activity (MVPA) to predict variability in TEE and to what extent adjustment for fat and fat-free mass predicted the variability in TEE.

Results

TEE varied from 1,265 to 4,143 kcal/day. It was positively correlated with physical activity (counts) estimated by accelerometry (rho  = 0.57; p = 0.003) and with minutes per week of physical activity by questionnaire (rho  = 0.41; p = 0.04). An increase of 10 minutes per day in moderate-to-vigorous intensity physical activity (MVPA) relates to an increase in TEE of 141 kcal/day. PAEE was positively correlated with accelerometry (rho  = 0.64; p = 0.007), but not with minutes per week of physical activity estimated by questionnaire (rho  = 0.30; p = 0.15). Physical activity by accelerometry explained 31% of the vssariability in TEE. By incorporating fat and fat-free mass in the model, we were able to explain 58% of the variability in TEE.

Conclusion

Objectively measured physical activity significantly contributes to the explained variance in both TEE and PAEE in Brazilian youth. Independently, body composition also explains variance in TEE, and should ideally be taken into account when using accelerometry to predict energy expenditure values.

A novel approach to characterize physical activity patterns in preschool-aged children

OBJECTIVE

Routine moderate-to-vigorous physical activity (MVPA) is associated with better health outcomes; the purpose of this work was to evaluate healthy preschooler physical activity patterns with objective measurement.

METHODS AND PROCEDURES

An objective prospective study of 50 normally developing children 3-5 years old who were ≥50th and <95th BMI percentile and enrolled in a family-based healthy lifestyle study in 2011-2012. Participants wore a tri-axial accelerometer for 7 continuous days. Outcome measures consisted of wear time examining four common MVPA patterns: isolated spurt (IS), isolated sustained activity (ISA), clustered spurt (CS), and clustered sustained activity (CSA).

RESULTS

Participants were 4.3 years, 56% female, 52% African-American, and 26% overweight. Forty-five children met wear time criteria. On average, children spent 14.5% of wake-wear time in MVPA, requiring 11.3 h to complete 90% of their daily MVPA. Children spent the majority of MVPA in CS (62.1%, followed by CSA (20.1%). Remaining MVPA was spent in IS (15.5%) and ISA (2.3%).

CONCLUSION

It takes most of the waking day for preschoolers to attain their PA. They engage in short spurts of small duration, in four common MVPA patterns. Utilizing this method could better characterize preschooler physical activity needs in practice and policy guidelines.

Accelerometer measured daily physical activity and sedentary pursuits--comparison between two models of the Actigraph and the importance of data reduction

BACKGROUND

Very few validation studies have been performed between different generations of the commonly used Actigraph accelerometers. We compared daily physical activity data generated from the old generation Actigraph model 7164 with the new generation Actigraph GT1M accelerometer in 15 young females for eight consecutive days. We also investigated if different wear time thresholds had any impact on the findings. Minutes per day of moderate and vigorous physical activity (MVPA), vigorous physical activity (VPA) and very vigorous physical activity (VVPA) were calculated. Moreover, minutes of sedentary pursuits per day were calculated.

FINDINGS

There were significant (P < 0.05) differences between the Actigraph 7164 and the GT1M concerning MVPA (61 ± 21vs. 56 ± 23 min/day), VPA (12 ± 8 vs. 9 ± 3 min/day) and VVPA (3.2 ± 3.0 vs. 0.3 ± 1.1 min/day). The different wear time thresholds had little impact on minutes per day in different intensities. Median minutes of sedentary pursuits per day ranged from 159 to 438 minutes depending on which wear time threshold was used (i.e. 10, 30 or 60 minutes), whereas very small differences were observed between the two different models.

CONCLUSIONS

Data from the old generation Actigraph 7164 and the new generation Actigraph GT1M accelerometers differ, where the Actigraph GT1M generates lower minutes spent in free living physical activity. Median minutes of sedentary pursuits per day are highly dependent on which wear time threshold that is used, and not by accelerometer model.

Identifying accelerometer nonwear and wear time in older adults

Background

Five accelerometer-derived methods of identifying nonwear and wear time were compared with a self-report criterion in adults ≥ 56 years of age.

Methods

Two hundred participants who reported wearing an Actical™ activity monitor for four to seven consecutive days and provided complete daily log sheet data (i.e., the criterion) were included. Four variables were obtained from log sheets: 1) dates the device was worn; 2) time(s) the participant put the device on each day; 3) time(s) the participant removed the device each day; and 4) duration of self-reported nonwear each day. Estimates of wear and nonwear time using 60, 90, 120, 150 and 180 minutes of consecutive zeroes were compared to estimates derived from log sheets.

Results

Compared with the log sheet, mean daily wear time varied from -84, -43, -24, -14 and -8 min/day for the 60-min, 90-min, 120-min, 150-min and 180-min algorithms, respectively. Daily log sheets indicated 8.5 nonwear bouts per week with 120-min, 150-min and 180-min algorithms estimating 8.2-8.9 nonwear bouts per week. The 60-min and 90-min methods substantially overestimated number of nonwear bouts per week and underestimated time spent in sedentary behavior. Sensitivity (number of compliant days correctly identified as compliant) improved with increasing minutes of consecutive zero counts and stabilized at the 120-min algorithm. The proportion of wear time being sedentary and absolute and proportion of time spent in physical activity of varying intensities were nearly identical for each method.

Conclusions

Utilization of at least 120 minutes of consecutive zero counts will provide dependable population-based estimates of wear and nonwear time, and time spent being sedentary and active in older adults wearing the Actical™ activity monitor.

Physical activity and sedentary behavior among adults 60 years and older: New York City residents compared with a national sample

This study describes moderate to vigorous physical activity (MVPA) and sedentary behavior among New York City (NYC) residents 60 years and older and compared with national United States' estimates. Adults aged 60 or older living in NYC (n = 760) were compared with similar aged adults from the National Health and Nutrition Examination Survey (NHANES; n = 2,451 adults). Both groups wore an ActiGraph accelerometer for one week. The NYC sample recorded 13.2, 23.8, and 37.8 mean min/day of MVPA and the NHANES sample recorded 10.6, 21.1, and 39.3, depending on the definition. Sedentary behavior averaged 9.6 hr/day for the NYC sample and 9.3 hr/day for the NHANES sample. The NYC sample spent a longer proportion of time in sedentary behavior and light activities, but more time in MVPA than the NHANES sample. Urbanicity may explain some of the differences between the two samples.

Maternal awareness of young children's physical activity: levels and cross-sectional correlates of overestimation

BACKGROUND

Factors associated with parental awareness of children's physical activity (PA) levels have not been explored in preschool-aged children. This paper investigates maternal awareness of preschool-aged children's PA levels and determined correlates associated with maternal overestimation of PA.

METHODS

Data from the Southampton Women's Survey, a UK population-based study, were collected March 2006 through June 2009. Daily minutes of moderate-to-vigorous PA (MVPA) were derived using accelerometry in 478 4-year-old children. Mothers who were realistic or overestimated their child's PA were identified. Log-binomial regression was used to analyse correlates of maternal overestimation of PA levels in children whose mothers perceived them to be active (n = 438).

RESULTS

40.8% of children were classified as inactive: 89.7% of these were perceived to be active by their mothers (over-estimators). These mothers were more likely to think their child sometimes lacked skills required to be physically active (RR (95% CI) = 1.29(1.03-1.63)) and their child was more likely to attend nursery full-time (RR = 1.53(1.14-2.04)). They were less likely to have older children at home (RR = 0.71(0.56-0.90)).

CONCLUSIONS

Almost 90% of mothers of inactive preschool-aged children perceive their child to be active. Nursery-school attendance and having older siblings at home may be important to consider when designing behavioural interventions to increase PA in preschool children.

Assessing the contribution of parks to physical activity using global positioning system and accelerometry

PURPOSE

Parks offer a free option for physical activity in many communities. How much time people spend using parks and the contribution that parks makes to their physical activity is not known. This study describes patterns of park use and physical activity among a diverse adult sample.

METHODS

From five US states, 248 adults enrolled in or near 31 study parks. Participants wore a global positioning system (GPS) monitor (Qstarz BT-Q1000X) and an ActiGraph accelerometer (GT1M) concurrently for 3 wk. Parks were mapped from local and national park shape files. Park visits and travel to and from the parks were derived from the objective data.

RESULTS

Participants visited parks a median of 2.3 times per week, and park visits lasted a median of 42.0 min. Overall, participants engaged in a median of 21.7 min·d-1 of moderate activity and 0.1 min·d-1 of vigorous activity, with an average of 8.2% of all moderate and 9.4% of all vigorous activity occurring within the parks. Among those with at least one park visit (n = 218), counts per minute, moderate, moderate-to-vigorous physical activity (MVPA), number and time in MVPA bouts per day, and sedentary behavior were all higher on days when a park was visited compared with days when a park was not visited. Considering several definitions of active travel, walking or bicycling to and from the park added an additional 3.7-6.6 mean minutes of MVPA per park visit.

CONCLUSIONS

Parks contributed as a place and destination for physical activity but were underused. One of the next steps in this line of inquiry is to understand characteristics of parks used more often as a place and destination for physical activity.

Correlates of light and moderate-to-vigorous objectively measured physical activity in four-year-old children

Background

Correlates of physical activity (PA) are hypothesized to be context and behaviour specific, but there is limited evidence of this in young children. The aim of the current study is to investigate associations between personal, social and environmental factors and objectively measured light and moderate-to-vigorous PA (LPA and MVPA, respectively) in four-year-old children.

Methods

Cross-sectional data were used from the Southampton Women’s Survey, a UK population-based longitudinal study. Four-year old children (n = 487, 47.0% male) had valid PA data assessed using accelerometry (Actiheart) and exposure data collected with a validated maternal questionnaire (including data on child personality, family demographics, maternal behaviour, rules and restrictions, and perceived local environment). Linear regression modelling was used to analyse associations with LPA and MVPA separately, interactions with sex were explored.

Results

LPA minutes were greater in children whose mothers reported more PA (vs. inactive: regression coefficient±standard error: 6.70±2.94 minutes), and without other children in the neighbourhood to play with (−6.33±2.44). MVPA minutes were greater in children with older siblings (vs. none: 5.81±2.80) and those whose mothers used active transport for short trips (vs. inactive: 6.24±2.95). Children accumulated more MVPA in spring (vs. winter: 9.50±4.03) and, in boys only, less MVPA with availability of other children in the neighbourhood (−3.98±1.70).

Discussion

Young children’s LPA and MVPA have differing associations with a number of social and environmental variables. Interventions targeting PA promotion in young children outside of formal care settings should consider including intensity specific factors.

Factors associated with participant compliance in studies using accelerometers

Participant compliance is an important issue in studies using accelerometers. Some participants wear the accelerometer for the duration specified by the researchers but many do not. We investigated a range of demographic factors associated with participant compliance in obtaining analyzable accelerometer data. A total of 3601 participants (aged 47.6±13.1 years, 44.6% male) were included. They were asked to wear an accelerometer (ActiGraph) for four consecutive days after completing a household survey during March 2009-January 2011 in Hong Kong. Participants wore the accelerometer on average for 13.9h in a 24-h day. No significant difference was found between males and females (p=0.38). Using log-linear regression, it was found that older participants (0.5% more wearing hours for each year of age, p<0.001), those with full-time job (p<0.01), with tertiary education (p<0.01), non-smokers (p<0.01) and with high self-reported health (p<0.05) wore the accelerometer for more hours. These results provide details for estimating compliance rates for samples with different characteristics and thus sample size calculation to account for participant compliance.

Normative steps/day values for older adults: NHANES 2005-2006

BACKGROUND

Pedometers are more likely than accelerometers to be used in walking interventions and other applications, including wide spread adoption by lay people. The purpose of this article is to provide older adults' sex-and-age-specific normative values for accelerometer-determined steps/day, adjusted to a pedometer-based scale.

METHODS

The data source was accelerometer data collected over multiple valid days (defined as ≥ 10 h/day; mean 5.8 ± SE 0.1 valid days) from 1,196 60+ year olds participating in the 2005-2006 National Health and Nutrition Examination Survey. Accelerometer data were adjusted to a pedometer scale using an established process of censoring steps counted during those minutes where activity counts totaled <500. Quintile-defined categories of adjusted steps/day (lowest, below average, average, above average, and highest) for six age groups (60-64, 65-69, 70-74, 75-79, 80-84, and 85+ years) were computed for the entire sample and separately for each sex. LMSChartmakerPro was used to create smoothed percentile curves corresponding to the 5th, 25th, 50th, 75th, and 95th percentiles.

RESULTS

Men aged 65-69 years defined the highest single category (>9,126 steps/day) and women aged 85+ years of age defined the lowest single category (<276 steps/day). In general, steps/day tended to decrease within each quintile-defined category as age increased. Similar patterns were apparent in the more detailed LMSChartmakerPro percentiles.

CONCLUSIONS

These data represent the first presentation of a detailed population distribution of normative accelerometer-determined steps/day adjusted to pedometer scaling, an instrument more likely to be used in clinical and public health applications.

Validation of a previous-day recall measure of active and sedentary behaviors

PURPOSE

A previous-day recall (PDR) may be a less error-prone alternative to traditional questionnaire-based estimates of physical activity and sedentary behavior (e.g., past year), but the validity of the method is not established. We evaluated the validity of an interviewer administered PDR in adolescents (12-17 yr) and adults (18-71 yr).

METHODS

In a 7-d study, participants completed three PDR, wore two activity monitors, and completed measures of social desirability and body mass index. PDR measures of active and sedentary time was contrasted against an accelerometer (ActiGraph) by comparing both to a valid reference measure (activPAL) using measurement error modeling and traditional validation approaches.

RESULTS

Age- and sex-specific mixed models comparing PDR to activPAL indicated the following: 1) there was a strong linear relationship between measures for sedentary (regression slope, β1 = 0.80-1.13) and active time (β1 = 0.64-1.09), 2) person-specific bias was lower than random error, and 3) correlations were high (sedentary: r = 0.60-0.81; active: r = 0.52-0.80). Reporting errors were not associated with body mass index or social desirability. Models comparing ActiGraph to activPAL indicated the following: 1) there was a weaker linear relationship between measures for sedentary (β1 = 0.63-0.73) and active time (β1 = 0.61-0.72), (2) person-specific bias was slightly larger than random error, and (3) correlations were high (sedentary: r = 0.68-0.77; active: r = 0.57-0.79).

CONCLUSIONS

Correlations between the PDR and the activPAL were high, systematic reporting errors were low, and the validity of the PDR was comparable with the ActiGraph. PDR may have value in studies of physical activity and health, particularly those interested in measuring the specific type, location, and purpose of activity-related behaviors.

Healthy families study: design of a childhood obesity prevention trial for Hispanic families

BACKGROUND

The childhood obesity epidemic disproportionately affects Hispanics. This paper reports on the design of the ongoing Healthy Families Study, a randomized controlled trial testing the efficacy of a community-based, behavioral family intervention to prevent excessive weight gain in Hispanic children using a community-based participatory research approach.

METHODS

The study will enroll 272 Hispanic families with children ages 5-7 residing in greater Nashville, Tennessee, United States. Families are randomized to the active weight gain prevention intervention or an alternative intervention focused on oral health. Lay community health promoters implement the interventions primarily in Spanish in a community center. The active intervention was adapted from the We Can! parent program to be culturally-targeted for Hispanic families and for younger children. This 12-month intervention promotes healthy eating behaviors, increased physical activity, and decreased sedentary behavior, with an emphasis on parental modeling and experiential learning for children. Families attend eight bi-monthly group sessions during four months then receive information and/or support by phone or mail each month for eight months. The primary outcome is change in children's body mass index. Secondary outcomes are changes in children's waist circumference, dietary behaviors, preferences for fruits and vegetables, physical activity, and screen time.

RESULTS

Enrollment and data collection are in progress.

CONCLUSION

This study will contribute valuable evidence on efficacy of a childhood obesity prevention intervention targeting Hispanic families with implications for reducing disparities.

Physical activity in German adolescents measured by accelerometry and activity diary: introducing a comprehensive approach for data management and preliminary results

INTRODUCTION

Surveillance of physical activity (PA) is increasingly based on accelerometry. However, data management guidelines are lacking. We propose an approach for combining accelerometry and diary based PA information for assessment of PA in adolescents and provide an example of this approach using data from German adolescents.

METHODS

The 15-year-old participants comprised a subsample the GINIplus birth cohort (n = 328, 42.4% male). Data on PA was obtained from hip-worn accelerometers (ActiGraph GT3X) for seven consecutive days, combined with a prospective activity diary. Major aspects of data management were validity of wear time, handling of non-wear time and diary comments. After data cleaning, PA and percentage of adolescents meeting the recommendations for moderate-to-vigorous activity (MVPA) per day were determined.

RESULTS

From the 2224 recorded days 493 days (25%) were invalid, mainly due to uncertainties relating to non-wear time (322 days). Ultimately, 269 of 328 subjects (82%) with valid data for at least three weekdays and one weekend day were included in the analysis. Mean MVPA per day was 39.1 minutes (SD ±25.0), with boys being more active than girls (41.8±21.5 minutes vs. 37.1±27.8 minutes, p<0.001). Accordingly, 24.7% of boys and 17.2% of girls (p<0.01) met the WHO recommendations for PA. School sport accounted for only 6% of weekly MVPA. In fact, most MVPA was performed during leisure time, with the majority of adolescents engaging in ball sports (25.4%) and endurance sports (19.7%). Girls also frequently reported dancing and gymnastics (23%).

CONCLUSION

For assessment of PA in adolescents, collecting both accelerometry and diary-based information is recommended. The diary is vital for the identification of invalid data and non-compliant participants. Preliminary results suggest that four out of five German adolescents do not meet WHO recommendations for PA and that school sport contributes only little to MVPA.

Influence of allowable interruption period on estimates of accelerometer wear time and sedentary time in older adults

The criteria one uses to reduce accelerometer data can profoundly influence the interpretation of research outcomes. The purpose of this study was to examine the influence of 3 different interruption periods (i.e., 20, 30, and 60 min) on the amount of data retained for analyses and estimates of sedentary time among older adults. Older adults (N = 311, M age = 71.1) wore an accelerometer for 7 d and reported wear time on an accelerometer log. Accelerometer data were downloaded and scored using 20-, 30-, and 60-min interruption periods. Estimates of wear time, derived using each interruption period, were compared with self-reported wear time, and descriptive statistics were used to compare estimates of sedentary time. Results showed a longer interruption period (i.e., 60 min) yields the largest sample size and the closest approximation of self-reported wear time. A short interruption period (i.e., 20 min) is likely to underestimate sedentary time among older adults.

Objectively measured physical activity in the 1993 Pelotas (Brazil) birth cohort

INTRODUCTION

Data on physical activity levels of adolescents are mostly derived from self-reported instruments, and the vast majority of studies using objective measures are from high-income countries. The aim of this study was to describe the patterns of objectively measured physical activity in Brazilian adolescents.

METHODS

In 2004-2005 (mean age of 13.3 yr), a subsample of the 1993 Pelotas (Brazil) Birth Cohort with data on all previous visits was approached. Physical activity was measured using the ActiGraph GT1M accelerometer (ActiGraph Corporation, Pensacola, FL). Demographic and other variables were assessed by self-report.

RESULTS

A total of 486 individuals (51% boys) provided valid data on objectively measured physical activity (response rate = 95.1%). The mean registered time of accelerometer data was 1191 min·d (SD = 112). The mean times (in minutes) spent in sedentary, light, moderate, and vigorous activities were 962 (SD = 114), 176 (SD = 46), 36 (SD = 16), and 17 (SD = 10) min·d, respectively. More than 30% of the adolescents accumulated ≥60 min·d of moderate-to-vigorous physical activity (MVPA). Physical activity intensity (counts per minute) and the prevalence of accumulation ≥60 min·d of MVPA were higher among boys and in those who walked or cycled to school. The prevalence of accumulation >60 min·d of MVPA was 125% higher in those from lower economic levels compared with higher economic levels (P < 0.001).

CONCLUSION

A large proportion of Brazilian adolescents of the 1993 Pelotas Birth Cohort do not achieve the current recommendation for health-related physical activity, and active commuting to school may be a target for interventions aimed at increasing physical activity. Physical activity levels are higher in lower socioeconomic groups than that in higher groups.

Comparison of older and newer generations of ActiGraph accelerometers with the normal filter and the low frequency extension

Background

Many studies used the older ActiGraph (7164) for physical activity measurement, but this model has been replaced with newer ones (e.g., GT3X+). The assumption that new generation models are more accurate has been questioned, especially for measuring lower intensity levels. The low-frequency extension (LFE) increases the low-intensity sensitivity of newer models, but its comparability with older models is unknown. This study compared step counts and physical activity collected with the 7164 and GT3X + using the Normal Filter and the LFE (GT3X+N and GT3X+LFE, respectively).

Findings

Twenty-five adults wore 2 accelerometer models simultaneously for 3Âdays and were instructed to engage in typical behaviors. Average daily step counts and minutes per day in nonwear, sedentary, light, moderate, and vigorous activity were calculated. Repeated measures ANOVAs with post-hoc pairwise comparisons were used to compare mean values. Means for the GT3X+N and 7164 were significantly different in 4 of the 6 categories (p < .05). The GT3X+N showed 2041 fewer steps per day and more sedentary, less light, and less moderate than the 7164 (+25.6, -31.2, -2.9 mins/day, respectively). The GT3X+LFE showed non-significant differences in 5 of 6 categories but recorded significantly more steps (+3597 steps/day; p < .001) than the 7164.

Conclusion

Studies using the newer ActiGraphs should employ the LFE for greater sensitivity to lower intensity activity and more comparable activity results with studies using the older models. Newer generation ActiGraphs do not produce comparable step counts to the older generation devices with the Normal filter or the LFE.

Using accelerometers in youth physical activity studies: a review of methods

BACKGROUND

In 2005, investigators convened by the National Cancer Institute recommended development of standardized protocols for accelerometer use and reporting decision rules in articles. A literature review was conducted to document accelerometer methods and decision rule reporting in youth physical activity articles from 2005-2010.

METHODS

Nine electronic databases identified 273 articles that measured physical activity and/or sedentary behavior using the most-used brand of accelerometer (ActiGraph). Six key methods were summarized by age group (preschool, children, and adolescents) and trends over time were examined.

RESULTS

Studies using accelerometers more than doubled from 2005-2010. Methods included 2 ActiGraph models, 6 epoch lengths, 6 nonwear definitions, 13 valid day definitions, 8 minimum wearing day thresholds, 12 moderate-intensity physical activity cut points, and 11 sedentary cut points. Child studies showed the most variation in methods and a trend toward more variability in cut points over time. Decision rule reporting improved, but only 54% of papers reported on all methods.

CONCLUSION

The increasing diversity of methods used to process and score accelerometer data for youth precludes comparison of results across studies. Decision rule reporting is inconsistent, and trends indicate declining standardization of methods. A methodological research agenda and consensus process are proposed.

Using the SenseCam to improve classifications of sedentary behavior in free-living settings

BACKGROUND

Studies have shown relationships between important health outcomes and sedentary behavior, independent of physical activity. There are known errors in tools employed to assess sedentary behavior. Studies of accelerometers have been limited to laboratory environments.

PURPOSE

To assess a broad range of sedentary behaviors in free-living adults using accelerometers and a Microsoft SenseCam that can provide an objective observation of sedentary behaviors through first person-view images.

METHODS

Participants were 40 university employees who wore a SenseCam and Actigraph accelerometer for 3-5 days. Images were coded for sitting and standing posture and 12 activity types. Data were merged and aggregated to a 60-second epoch. Accelerometer counts per minute (cpm) of <100 were compared with coded behaviors. Sensitivity and specificity analyses were performed. Data were collected in June and July 2011 and analyzed in April 2012.

RESULTS

TV viewing, other screen use, and administrative activities were correctly classified by the 100-cpm cutpoint. However, standing behaviors also fell under this threshold, and driving behaviors exceeded it. Multiple behaviors occurred simultaneously. A nearly 30-minute per day difference was found in sedentary behavior estimates based on the accelerometer versus the SenseCam.

CONCLUSIONS

Researchers should be aware of the strengths and weaknesses of the 100-cpm accelerometer cutpoint for identifying sedentary behavior. The SenseCam may be a useful tool in free-living conditions to better understand health behaviors such as sitting.

Assessment of wear/nonwear time classification algorithms for triaxial accelerometer

PURPOSE

The objective of this study is to assess the performance of existing wear/nonwear time classification algorithms for accelerometry data collected in the free-living environment using a wrist-worn triaxial accelerometer and a waist-worn uniaxial accelerometer in older adults.

METHODS

Twenty-nine adults age 76 to 96 yr wore wrist accelerometers for approximately 24 h per day and waist accelerometers during waking for approximately 7 d of free living. Wear and nonwear times were classified by existing algorithms (Alg([ActiLife]), Alg([Troiano]), and Alg([Choi])) and compared with wear and nonwear times identified by data plots and diary records. With the use of bias and probability of correct classification, the performance of the algorithms, two time windows (60 and 90 min), and vector magnitude (VM) versus vertical axis (V) counts from a triaxial accelerometer were compared.

RESULTS

Automated algorithms (Alg([Choi]) and Alg([Troiano])) classified wear/nonwear time intervals more accurately from VM than V counts. The use of the 90-min time window improved wear/nonwear classification accuracy when compared with the 60-min window. The Alg([Choi]) and Alg([Troiano]) performed better than the manufacturer-provided algorithm (Alg([ActiLife])), and the Alg([Choi]) performed better than the Alg([Troiano]) for wear/nonwear time classification using the data collected by both accelerometers.

CONCLUSIONS

Triaxial wrist-worn accelerometer can be used for an accurate wear/nonwear time classification in free-living older adults. The use of the 90-min window and the VM counts improves the performance of commonly used algorithms for wear/nonwear classification for both uniaxial and triaxial accelerometers.

Is the pain of activity log-books worth the gain in precision when distinguishing wear and non-wear time for tri-axial accelerometers?

OBJECTIVE

To compare three methods for assessing wear time from accelerometer data: automated, log-books and a combination of the two.

DESIGN

Cross-sectional study.

METHODS

Forty-five office workers wore an Actigraph GT3X accelerometer and kept a detailed activity log-book for 7 days. The automated method used six algorithms to determine non-wear time (20, 60, or 90 min of consecutive zero counts with and without 2-min interruptions); the log-book method used participant recorded on/off times; the combined method used the 60-min automated filter (with ≤2 min interruptions) plus detailed log-book data. Outcomes were number of participants with valid data, number of valid days, estimates of wear time and time spent in sedentary, light, moderate and vigorous activity. Percentage misclassification, sensitivity, specificity, and area under the receiver-operating curve were compared for each method, with the combined method as the reference.

RESULTS

Using the combined method, 34 participants met criteria for valid wear time (≥10 h/day, ≥4 days). Mean wear times ranged from 891 to 925 min/day and mean sedentary time s from 438 to 490 min/day. Percentage misclassification was higher and area under the receiver-operating curve was lower for the log-book method than for the automated methods. Percentage misclassification was lowest and area under the receiver-operating curve highest for the 20-min filter without interruptions, but this method had fewer valid days and participants than the 60 and 90-min filters without interruptions.

CONCLUSIONS

Automated filters are as accurate as a combination of automated filters and log-books for filtering wear time from accelerometer data. Automated filters based on 90-min of consecutive zero counts without interruptions are recommended for future studies.

The Alberta moving beyond breast cancer (AMBER) cohort study: a prospective study of physical activity and health-related fitness in breast cancer survivors

Background

Limited research has examined the association between physical activity, health-related fitness, and disease outcomes in breast cancer survivors. Here, we present the rationale and design of the Alberta Moving Beyond Breast Cancer (AMBER) Study, a prospective cohort study designed specifically to examine the role of physical activity and health-related fitness in breast cancer survivorship from the time of diagnosis and for the balance of life. The AMBER Study will examine the role of physical activity and health-related fitness in facilitating treatment completion, alleviating treatment side effects, hastening recovery after treatments, improving long term quality of life, and reducing the risks of disease recurrence, other chronic diseases, and premature death.

Methods/Design

The AMBER Study will enroll 1500 newly diagnosed, incident, stage I-IIIc breast cancer survivors in Alberta, Canada over a 5 year period. Assessments will be made at baseline (within 90 days of surgery), 1 year, and 3 years consisting of objective and self-reported measurements of physical activity, health-related fitness, blood collection, lymphedema, patient-reported outcomes, and determinants of physical activity. A final assessment at 5 years will measure patient-reported data only. The cohort members will be followed for an additional 5 years for disease outcomes.

Discussion

The AMBER cohort will answer key questions related to physical activity and health-related fitness in breast cancer survivors including: (1) the independent and interactive associations of physical activity and health-related fitness with disease outcomes (e.g., recurrence, breast cancer-specific mortality, overall survival), treatment completion rates, symptoms and side effects (e.g., pain, lymphedema, fatigue, neuropathy), quality of life, and psychosocial functioning (e.g., anxiety, depression, self-esteem, happiness), (2) the determinants of physical activity and health-related fitness including demographic, medical, social cognitive, and environmental variables, (3) the mediators of any observed associations between physical activity, health-related fitness, and health outcomes including biological, functional, and psychosocial, and (4) the moderators of any observed associations including demographic, medical, and biological/disease factors. Taken together, these data will provide a comprehensive inquiry into the outcomes, determinants, mechanisms, and moderators of physical activity and health-related fitness in breast cancer survivors.

Physical activity, sedentary time, and pericardial fat in healthy older adults

Pericardial fat is emerging as a unique risk factor for coronary disease. We examined the relationship between objectively measured physical activity during free-living and pericardial fat. Participants were 446 healthy men and women (mean age = 66 ± 6 years), without history or objective signs of cardiovascular disease (CVD), drawn from the Whitehall II epidemiological cohort. Physical activity was objectively measured using accelerometers (Actigraph GT3X) worn around the hip during waking hours for 7 consecutive days (average daily wear time = 889 ± 68 min/day), and was classified as sedentary (<200 counts/min (cpm)), light (200-1,998 cpm), or moderate-vigorous physical activity (MVPA; ≥1,999 cpm). Pericardial fat volume was measured in each participant using electron beam computed tomography. Average daily cpm in men was 338.0 ± 145.0 and in women 303.8 ± 130.2. There was an inverse association between average cpm and pericardial fat (B = -0.070, 95% confidence interval (CI), -0.101, -0.040, P < 0.001), and this remained significant after adjusting for age, sex, registered wear time, BMI, lipids, glycemic control, blood pressure, smoking, statins, and social status. Both sedentary time (B = 0.081, 95% CI, 0.022, 0.14) and MVPA (B = -0.362, 95% CI, -0.527, -0.197) were also associated with pericardial fat, although associations for sedentary time did not remain significant after adjustment for MVPA. The inverse association between physical activity and pericardial fat was stronger among overweight and obese adults than in normal weight. Objectively assessed daily activity levels are related to pericardial fat in healthy participants, independently of BMI. This might be an important mechanism in explaining the association between physical activity and CVD prevention.

Physical activity classification using the GENEA wrist-worn accelerometer

INTRODUCTION

Most accelerometer-based activity monitors are worn on the waist or lower back for assessment of habitual physical activity. Output is in arbitrary counts that can be classified by activity intensity according to published thresholds. The purpose of this study was to develop methods to classify physical activities into walking, running, household, or sedentary activities based on raw acceleration data from the GENEA (Gravity Estimator of Normal Everyday Activity) and compare classification accuracy from a wrist-worn GENEA with a waist-worn GENEA.

METHODS

Sixty participants (age = 49.4 ± 6.5 yr, body mass index = 24.6 ± 3.4 kg·m⁻²) completed an ordered series of 10-12 semistructured activities in the laboratory and outdoor environment. Throughout, three GENEA accelerometers were worn: one at the waist, one on the left wrist, and one on the right wrist. Acceleration data were collected at 80 Hz. Features obtained from both fast Fourier transform and wavelet decomposition were extracted, and machine learning algorithms were used to classify four types of daily activities including sedentary, household, walking, and running activities.

RESULTS

The computational results demonstrated that the algorithm we developed can accurately classify certain types of daily activities, with high overall classification accuracy for both waist-worn GENEA (0.99) and wrist-worn GENEA (right wrist = 0.97, left wrist = 0.96).

CONCLUSIONS

We have successfully developed algorithms suitable for use with wrist-worn accelerometers for detecting certain types of physical activities; the performance is comparable to waist-worn accelerometers for assessment of physical activity.

Longitudinal patterns in physical activity and sedentary behaviour from mid-life to early old age: a substudy of the Whitehall II cohort

Background

There are few longitudinal data on physical activity patterns from mid-life into older age. The authors examined associations of self-reported physical activity, adiposity and socio-demographic factors in mid-life with objectively assessed measures of activity in older age.

Methods

Participants were 394 healthy men and women drawn from the Whitehall II population-based cohort study. At the baseline assessment in 1997 (mean age 54 years), physical activity was assessed through self-report and quantified as metabolic equivalent of task hours/week. At the follow-up in 2010 (mean age 66 years), physical activity was objectively measured using accelerometers worn during waking hours for seven consecutive days (average daily wear time 891±68 min/day).

Results

Self-reported physical activity at baseline was associated with objectively assessed activity at follow-up in various activity categories, including light-, moderate- and vigorous-intensity activity (all ps<0.04). Participants in the highest compared with lowest quartile of self-reported activity level at baseline recorded on average 64.1 (95% CI 26.2 to 102.1) counts per minute more accelerometer-assessed activity at follow-up and 9.0 (2.0–16.0) min/day more moderate-to-vigorous daily activity, after adjusting for baseline covariates. Lower education, obesity and self-perceived health status were also related to physical activity at follow-up. Only age and education were associated with objectively measured sedentary time at follow-up.

Conclusion

Physical activity behaviour in middle age was associated with objectively measured physical activity in later life after 13 years of follow-up, suggesting that the habits in adulthood are partly tracked into older age.

A catalog of rules, variables, and definitions applied to accelerometer data in the National Health and Nutrition Examination Survey, 2003-2006

Introduction

The National Health and Nutrition Examination Survey (NHANES) included accelerometry in the 2003–2006 data collection cycles. Researchers have used these data since their release in 2007, but the data have not been consistently treated, examined, or reported. The objective of this study was to aggregate data from studies using NHANES accelerometry data and to catalogue study decision rules, derived variables, and cut point definitions to facilitate a more uniform approach to these data.

Methods

We conducted a PubMed search of English-language articles published (or indicated as forthcoming) from January 2007 through December 2011. Our initial search yielded 74 articles, plus 1 article that was not indexed in PubMed. After excluding 21 articles, we extracted and tabulated details on 54 studies to permit comparison among studies.

Results

The 54 articles represented various descriptive, methodological, and inferential analyses. Although some decision rules for treating data (eg, criteria for minimal wear-time) were consistently applied, cut point definitions used for accelerometer-derived variables (eg, time spent in various intensities of physical activity) were especially diverse.

Conclusion

Unique research questions may require equally unique analytical approaches; some inconsistency in approaches must be tolerated if scientific discovery is to be encouraged. This catalog provides a starting point for researchers to consider relevant and/or comparable accelerometer decision rules, derived variables, and cut point definitions for their own research questions.

Identifying sedentary time using automated estimates of accelerometer wear time

PURPOSE

The authors evaluated the accuracy of three automated accelerometer wear-time estimation algorithms against self-report. Direct effects on sedentary time (<100 cpm) and indirect effects on moderate-to-vigorous physical activity (MVPA, ≥1952 cpm) time were examined.

METHODS

A subsample from the 2004/2005 Australian Diabetes, Obesity and Lifestyle Study (n=148) completed activity logs and wore accelerometers for a total of 987 days. A published algorithm that allows movement within non-wear periods (Algorithm 1) was compared with one that allows less movement (Algorithm 2) or no movement (Algorithm 3). Implications for population estimates were examined using 2003/2004 US National Health and Nutrition Examination Survey data.

RESULTS

Mean difference per day between the criterion and estimated wear time was negligible for all three algorithms (≤11 min), but 95% limits of agreement (LOA) were wide (±≥2 h). Respectively, the algorithms (1, 2 and 3) misclassified sedentary time as non-wear on 31.9%, 19.4% and 18% of days and misclassified non-wear time as sedentary on 42.8%, 43.7% and 51.3% of days. Use of Algorithm 2 (compared with Algorithm 1) affected population estimates of sedentary time (higher by 20 min/day) but not MVPA time. Agreement between Algorithms 1 and 2 was good for MVPA time (mean difference -0.08, LOA: -2.08, 1.91 min), but not for wear time or sedentary time.

CONCLUSION

Accelerometer wear time can be estimated accurately on average; however, misclassification can be substantial for individuals. Algorithm choice affects estimates of sedentary time. Allowing very limited movement within non-wear periods can improve accuracy.

Objectively assessed physical activity, sedentary time, and coronary artery calcification in healthy older adults

OBJECTIVE

Physical activity is related to lower risk of cardiovascular disease, but data relating to coronary lesions have been conflicting. These inconsistencies may in part be due to unreliable assessment of physical activity and limitations imposed by self-reported data. The purpose of this study was to determine the relationship between objectively measured physical activity and coronary artery calcium (CAC).

METHODS AND RESULTS

Participants were 443 healthy men and women (mean age=66±6 years), without history or objective signs of coronary heart disease, drawn from the Whitehall II epidemiological cohort. Physical activity was objectively measured using accelerometers worn during waking hours for 7 consecutive days (average daily wear time=889±68 minutes/day). CAC was measured in each participant using electron beam computed tomography and was quantified according to the Agatston scoring system. On average, 54.4% of the sample recorded at least 30 minutes/day of moderate to vigorous physical activity (MVPA). There was no association between MVPA and presence of detectable CAC. For the participants with detectable CAC (n=283) a weak inverse relationship between MVPA (minutes/day) and log Agatston score was observed (B=-0.008, 95% CI: -0.16 to 0.00, P=0.05), although the association was no longer present after adjustments for age, sex, and conventional risk factors. No associations were seen for light activity or sedentary time.

CONCLUSIONS

Our results confirm no association between objectively assessed physical activity and CAC. Because CAC measures cannot identify more vulnerable lesions, additional studies are required to examine whether physical activity can promote plaque stability.