Parameterizing and validating existing algorithms for identifying out-of-bed time using hip-worn accelerometer data from older women.
ABSTRACT: OBJECTIVE:To parameterize and validate two existing algorithms for identifying out-of-bed time using 24?h hip-worn accelerometer data from older women. APPROACH:Overall, 628 women (80??±??6 years old) wore ActiGraph GT3X+??accelerometers 24?h d-1 for up to 7 d and concurrently completed sleep-logs. Trained staff used a validated visual analysis protocol to measure in-bed periods on accelerometer tracings (criterion). The Tracy and McVeigh algorithms were adapted for optimal use in older adults. A training set of 314 women was used to choose two key thresholds by maximizing the sum of sensitivity and specificity for each algorithm and data (vertical axis, VA, and vector magnitude [VM]) combination. Data from the remaining 314 women were then used to test agreement in waking wear time (i.e. out-of-bed time while wearing the accelerometer) by computing sensitivity, specificity, and kappa comparing the algorithm output with the criterion. Waking wear time-adjusted means of sedentary time, light-intensity physical activity (light PA) and moderate-to-vigorous-intensity physical activity (MVPA) were then estimated and compared. MAIN RESULTS:Waking wear time agreement with the criterion was high for Tracy_VA, Tracy_VM, McVeigh_VA, and highest for McVeigh_VM. Compared to the criterion, McVeigh_VM had mean sensitivity??=??0.92, specificity??=??0.87, kappa??=??0.80, and overall mean difference (±SD) of??-0.04??±??2.5?h d-1. Minutes of sedentary time, light PA, and MVPA adjusted for waking wear time using the criterion measure and McVeigh_VM were not statistically different (p???>??0.43|all). SIGNIFICANCE:The McVeigh algorithm with optimal parameters using VM performed best compared to criterion sleep-log assisted visual analysis and is suitable for automated identification of waking wear time in older women when visual analysis is not feasible.
Project description:Accelerometers objectively assess physical activity (PA) and are currently used in several large-scale epidemiological studies, but there is no consensus for processing the data. This study compared the impact of wear-time assessment methods and using either vertical (V)-axis or vector magnitude (VM) cut-points on accelerometer output.Participants (7,650 women, mean age 71.4 y) were mailed an accelerometer (ActiGraph GT3X+), instructed to wear it for 7 days, record dates and times the monitor was worn on a log, and return the monitor and log via mail. Data were processed using three wear-time methods (logs, Troiano or Choi algorithms) and V-axis or VM cut-points.Using algorithms alone resulted in "mail-days" incorrectly identified as "wear-days" (27-79% of subjects had >7-days of valid data). Using only dates from the log and the Choi algorithm yielded: 1) larger samples with valid data than using log dates and times, 2) similar wear-times as using log dates and times, 3) more wear-time (V, 48.1 min more; VM, 29.5 min more) than only log dates and Troiano algorithm. Wear-time algorithm impacted sedentary time (~30-60 min lower for Troiano vs. Choi) but not moderate-to-vigorous (MV) PA time. Using V-axis cut-points yielded ~60 min more sedentary time and ~10 min less MVPA time than using VM cut-points.Combining log-dates and the Choi algorithm was optimal, minimizing missing data and researcher burden. Estimates of time in physical activity and sedentary behavior are not directly comparable between V-axis and VM cut-points. These findings will inform consensus development for accelerometer data processing in ongoing epidemiologic studies.
Project description:In adults, a minimum of 3-5 days of accelerometer monitoring is usually considered appropriate to obtain reliable estimates of physical activity (PA). However, a longer period of measurement might be needed to obtain reliable estimates of sedentary behavior (SED). The aim of this study was to determine the reliability of objectively assessed SED and PA in adults.Eighty-seven adult subjects (28 men; mean (standard deviation) age 31.3 (12.2) years; body mass index 23.7 (3.1) kg/m2) wore the GT3X+ accelerometer for 21 subsequent days, for which the reliability of different wear time criteria (8 to 12 h/day and 3 to 5 d/week) was explored. Variance partitioning along with the Spearman-Brown prophecy formula was used as the basis for determining intraclass-correlation coefficients (ICC) and the number of monitoring days needed (N) to achieve an ICC = 0.80. Week-by-week reliability was reported using ICC, Bland-Altman plots and absolute measures of agreement.Seven-10 days of monitoring was needed to reliably assess overall- (axis 1 and vector magnitude (VM) counts per minute (CPM)) and moderate-to-vigorous PA (MVPA), 3-4 days was needed for light PA (LPA), whereas the number of days needed for SED depended on whether adjustments were made for wear time (6-8 days) or not (13-15 days). The week-by-week ICC was ?0.70 for all variables, with limits of agreement being ±267.8 cpm for CPM, ±352.3 cpm for VM CPM, ±76.8 min/day for SED, ±57.8 min/day for LPA and ±43.8 min/day for MVPA, equal to 1.0-1.6 standard deviations, when adjustment was made for wear time.For most variables, more than one week of measurement was needed to achieve an ICC = 0.80. Correcting for wear time was crucial to reliably determine SED. Considerable week-by-week variability was found for all variables. Researchers need to be aware of substantial intra-individual variability in accelerometer-measurements.
Project description:We compared 24-hour waist-worn accelerometer wear time characteristics of 9-11 year old children in the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE) to similarly aged U.S. children providing waking-hours waist-worn accelerometer data in the 2003-2006 National Health and Nutrition Examination Survey (NHANES).Valid cases were defined as having ?4 days with ?10 hours of waking wear time in a 24-hour period, including one weekend day. Previously published algorithms for extracting total sleep episode time from 24-hour accelerometer data and for identifying wear time (in both the 24-hour and waking-hours protocols) were applied. The number of valid days obtained and a ratio (percent) of valid cases to the number of participants originally wearing an accelerometer were computed for both ISCOLE and NHANES. Given the two surveys' discrepant sampling designs, wear time (minutes/day, hours/day) from U.S. ISCOLE was compared to NHANES using a meta-analytic approach. Wear time for the 11 additional countries participating in ISCOLE were graphically compared with NHANES.491 U.S. ISCOLE children (9.92±0.03 years of age [M±SE]) and 586 NHANES children (10.43?±?0.04 years of age) were deemed valid cases. The ratio of valid cases to the number of participants originally wearing an accelerometer was 76.7% in U.S. ISCOLE and 62.6% in NHANES. Wear time averaged 1357.0?±?4.2 minutes per 24-hour day in ISCOLE. Waking wear time was 884.4?±?2.2 minutes/day for U.S. ISCOLE children and 822.6?±?4.3 minutes/day in NHANES children (difference = 61.8 minutes/day, p <?0.001). Wear time characteristics were consistently higher in all ISCOLE study sites compared to the NHANES protocol.A 24-hour waist-worn accelerometry protocol implemented in U.S. children produced 22.6 out of 24 hours of possible wear time, and 61.8 more minutes/day of waking wear time than a similarly implemented and processed waking wear time waist-worn accelerometry protocol. Consistent results were obtained internationally. The 24-hour protocol may produce an important increase in wear time compliance that also provides an opportunity to study the total sleep episode time separate and distinct from physical activity and sedentary time detected during waking-hours.ClinicalTrials.gov NCT01722500 .
Project description:Self-reported physical activity measures continue to be validated against accelerometers; however, the absence of standardized, accelerometer moderate-to-vigorous physical activity (MVPA) definitions has made comparisons across studies difficult. Furthermore, recent accelerometer models assess accelerations in three axes, instead of only the vertical axis, but validation studies have yet to take incorporate triaxial data.Participants (n = 10 115) from the Women's Health Study wore a hip-worn accelerometer (ActiGraph GT3X+) for seven days during waking hours (2011-2014). Women then completed a physical activity questionnaire. We compared self-reported with accelerometer-assessed MVPA, using four established cutpoints for MVPA: three using only vertical axis data (760, 1041 and 1952 counts per minute (cpm)) and one using triaxial data (2690 cpm).According to self-reported physical activity, 66.6% of women met the US federal physical activity guidelines, engaging in ?150 minutes per week of MVPA. The percent of women who met guidelines varied widely depending on the accelerometer MVPA definition (760 cpm: 50.0%, 1041 cpm: 33.0%, 1952 cpm: 13.4%, and 2690 cpm: 19.3%).Triaxial count data do not substantially reduce the difference between self-reported and accelerometer-assessed MVPA.
Project description:BACKGROUND:Accelerometers are widely used to assess child physical activity (PA) levels. Using the accelerometer data, several PA metrics can be estimated. Knowledge about the relationships between these different metrics can improve our understanding of children's PA behavioral patterns. It also has significant implications for comparing PA metrics across studies and fitting a statistical model to examine their health effects. The aim of this study was to examine the relationships among the metrics derived from accelerometers in children. METHODS:Accelerometer data from 24,316 children aged 5 to 18 years were extracted from the International Children's Accelerometer Database (ICAD) 2.0. Correlation coefficients between wear time, sedentary behavior (SB), light-intensity PA (LPA), moderate-intensity PA (MPA), vigorous-intensity PA (VPA), moderate- and vigorous-intensity PA (MVPA), and total activity counts (TAC) were calculated. RESULTS:TAC was approximately 22X103 counts higher (p < 0.01) with longer wear time (13 to 18 h/day) as compared to shorter wear time (8 to < 13 h/day), while MVPA was similar across the wear time categories. MVPA was very highly correlated with TAC (r = .91; 99% CI = .91 to .91). Wear time-adjusted correlation between SB and LPA was also very high (r = -.96; 99% CI = -.96, - 95). VPA was moderately correlated with MPA (r = .58; 99% CI = .57, .59). CONCLUSIONS:TAC is mostly explained by MVPA, while it could be more dependent on wear time, compared to MVPA. MVPA appears to be comparable across different wear durations and studies when wear time is ≥8 h/day. Due to the moderate to high correlation between some PA metrics, potential collinearity should be addressed when including multiple PA metrics together in statistical modeling.
Project description:In Iceland, there is a large variation in daylight between summer and winter. The aim of the study was to identify how this large variation influences physical activity (PA) and sedentary behavior (SB). Free living PA was measured by a waist-worn accelerometer for one week during waking hours in 138 community-dwelling older adults (61.1% women, 80.3 ± 4.9 years) during summer and winter months. In general, SB occupied about 75% of the registered wear-time and was highly correlated with age (? = 0.36). Although the differences were small, more time was spent during the summer in all PA categories, except for the moderate-to-vigorous PA (MVPA), and SB was reduced. More lifestyle PA (LSPA) was accumulated in ?5-min bouts during summer than winter, especially among highly active participants. This information could be important for policy makers and health professionals working with older adults. Accounting for seasonal difference is necessary in analyzing SB and PA data.
Project description:OBJECTIVE:We conducted a laboratory-based calibration study to determine relevant cutpoints for a hip-worn accelerometer among women ?60 years, considering both type and filtering of counts. METHODS:Two hundred women wore an ActiGraph GT3X+ accelerometer on their hip while performing eight laboratory-based activities. Oxygen uptake was measured using an Oxycon portable calorimeter. Accelerometer data were analyzed in 15-second epochs for both normal and low frequency extension (LFE) filters. Receiver operating characteristic (ROC) curve analyses were used to calculate cutpoints for sedentary, light (low and high), and moderate to vigorous physical activity (MVPA) using the vertical axis and vector magnitude (VM) counts. RESULTS:Mean age was 75.5 years (standard deviation 7.7). The Spearman correlation between oxygen uptake and accelerometry ranged from 0.77 to 0.85 for the normal and LFE filters and for both the vertical axis and VM. The area under the ROC curve was generally higher for VM compared to the vertical axis, and higher for cutpoints distinguishing MVPA compared to sedentary and light low activities. The VM better discriminated sedentary from light low activities compared to the vertical axis. The area under the ROC curves were better for the LFE filter compared to the normal filter for the vertical axis counts, but no meaningful differences were found by filter type for VM counts. CONCLUSION:The cutpoints derived for this study among women ?60 years can be applied to ongoing epidemiologic studies to define a range of physical activity intensities.
Project description:PURPOSE:This study aimed to determine whether physical activity patterns are associated with sleep later at night and if nighttime sleep is associated with physical activity patterns the next day among adult women. METHODS:Women (N = 353) living throughout the United States wore a wrist and a hip accelerometer for 7 d. Total sleep time (TST, hours per night) and sleep efficiency (SE, %) were estimated from the wrist accelerometer, and moderate to vigorous physical activity (MVPA, >1040 counts per minute, h·d) and sedentary behavior (SB, <100 counts per minute, h·d) were estimated from the hip accelerometer. Mixed-effects models adjusted for age, race, body mass index, education, employment, marital status, health status, and hip accelerometer wear time were used to analyze the data. Follow-up analyses using quantile regression were used to investigate associations among women with below average TST and MVPA and above average SB. RESULTS:The average age of our sample was 55.5 yr (SD = 10.2 yr). The majority of participants were White (79%) and married (72%), and half were employed full time (49%). The participants spent on average 8.9 and 1.1 h·d in SB and MVPA, respectively, and 6.8 h per night asleep. No associations were observed between MVPA and SB with nighttime TST or SE. There were no associations between nighttime TST and SE with MVPA or SB the next day. The findings were the same in the quantile regression analyses. CONCLUSION:In free-living adult women, accelerometry-estimated nighttime sleep and physical activity patterns were not associated with one another. On the basis of our observational study involving a sample of adult women, higher physical activity will not necessarily improve sleep at night on a day-to-day basis (and vice versa).
Project description:The aims of this report were 1) to describe the duration of moderate to vigorous physical activity (MVPA) and the proportion of participants meeting the recommended criterion of at least 150 min of MVPA per week as measured by the 7 Day Physical Activity Recall Questionnaire (7D-PAR) and accelerometer among women who were enrolled in the mPED trial; 2) to assess the level of agreement of the two measures using a Bland-Altman plot; and 3) to describe the positive and negative predictive values (PPV and NPV, respectively) of meeting the guidelines by calculating the percentage of women meeting the physical activity recommendation by the 7D-PAR who also met this recommendation based on data from the accelerometer.Baseline data on duration of MVPA from the mPED trial were analyzed for 215 women. Among the women who met the recommended criterion by the 7D-PAR (self-report), we calculated the proportion of individuals who also met it by the accelerometer (objective measure). A Bland Altman Plot was used to assess concordance between the two measures.The mean age was 52.4 (±11.2) years; 54.4 % were white; and 48.8 % were single or divorced. While median MVPA was 160 min/week by the 7D-PAR, it was only 24 min/week in the accelerometer. A total of 117 women met the 150-min criterion by the 7D-PAR. Of these, only 18 also met the criterion by the objective measure (PPV 15.4 %, 95 % CI 9.4-23.2 %). Among the 98 women who did not meet the criterion by the 7D-PAR, none met it by the accelerometer (NPV 100 %). A Bland Altman plot showed the mean difference of +145 min between the two measures with a 95 % limit of agreement at + 471 to -181 min.The large discrepancy between the self-reported and objective measures of MVPA meeting the 150-min criterion suggests that self-reported physical activity measures should be used with caution in intervention studies. While our data suggest that self-report could be used to identify a physically inactive sample, it would be likely to over-estimate the proportions of women who become active in one or both arms of trials of interventions promoting MVPA.ClinicalTrials.gov NCT01280812.
Project description:In this study, we investigate the associations of objectively measured waking (sedentary, light physical activity [LPA] and moderate-to-vigorous physical activity [MVPA]) and sleep duration and quality characteristics with cardiometabolic risk among older women. Participants from the Healthy Women Study 2010-11 follow-up visit (n = 136, age = 73 ± 2 years, white = 91.9%) concurrently wore an ActiGraph GT1M accelerometer and Actiwatch-2 for seven days. A composite cardiometabolic risk score was calculated by transforming metabolic syndrome (MetS) components and summing z-scores. Multivariable regression models were fitted to relate waking and sleep estimates with the MetS z-score after adjustment for covariates. Compositional data analysis was used to predict the MetS z-score when fixed durations of time were reallocated from one characteristic to another. MVPA (per 10 min/day increase; ? = -7.80, P < 0.01), LPA (per 30 min/day increase; ? = -0.29, P = 0.04), and sleep efficiency (? = -0.10, P = 0.04) were inversely associated with MetS z-score, while sedentary time (per 30 min/day increase; ? = 0.34, P = 0.01) was positively associated with MetS z-score. Reallocation of 5 min from MVPA to sleep, sedentary, or LPA resulted in the greatest predicted change in MetS z-score. On average, the reallocation of 5 min from MVPA to other characteristics predicted an 11% increase in triglycerides, 6% decrease in HDL-C, and 5% increase in waist circumference. Lastly, reallocating 30 min of sedentary time to LPA was associated with a modestly lower predicted MetS z-score. This study suggests that MVPA is the most important contributor of MetS and that maintaining MVPA and increasing LPA may be beneficial for reducing cardiometabolic risk among older women.