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Table 3 Characteristics and results of studies that examined reliability of ActiGraph models for measuring sedentary behaviour in older adults (mean age ≥ 60 years), ordered from largest to smallest sample size

From: Validity of objective methods for measuring sedentary behaviour in older adults: a systematic review

Study Participants and data source Monitor and epochs analysed Methods Results for Sedentary Behaviour
Kocherginsky, et al., 2016 [36] n = 2208
57% female (weighted)
Mean age = 74.2 y (95% CI 73.7–74.7)
USA: Data collected for National Health and Nutrition Examination Survey (NHANES)
ActiGraph 7164
Worn on right hip
60-s epochs
Free-living
Activities: VA < 100 cpm
Observation period: 7 consecutive days during waking hours
Valid hours and days: ≥10 h; ≥1 day
Non-wear algorithm: 60 min of consecutive zeros, no allowance for interruptions
Analysis: used linear regression to examine variations across days of the week; computed Lin’s concordance coefficients to compare 2-day and then 3-day averages to 7-day average among participants with 7 valid days of data
Average daily percent of time spent in SB
Monday to Friday: 65.3–65.9%
Saturday: 66.3%
Sunday: 69.6%
Difference between Sunday and Monday to Saturday was significant (p < 0.001).
Difference between Saturday and Monday to Friday was significant (p = 0.045).
Comparison of % time spent in SB between 2 & 3 day averages with 7-day average
Lin’s concordance r:
For 2-day vs 7-day: 0.91
For 3-day vs 7-day: 0.94
Keadle et al. (2017) [27] n: 209
Only females
Mean age: 70.6 ± 5.7 y
USA: Data collected for an observational ancillary study of participants from the Women’s Health Study, a randomized trial of aspirin and vitamin E to reduce risk of cardiovascular disease and cancer. Data collected after completion of the trial.
ActiGraph GT3X+
Worn on hip
60-s epochs
Free-living
Activities: VM < 200 cpm
Observation period: two to three 7-day periods over 2–3 y during waking hours
Valid hours and days: ≥10 h; ≥4 day
Non-wear algorithm: Choi algorithm [61] and ≥ 600 min/day
Analysis: computed reproducibility of sitting time across time periods ICCs; used linear mixed models; assessed utility of one 7-day assessment for classifying 2–3 year behaviour by cross-classifying participants using the baseline quartile distribution for SB and the quartile distribution of the average of two follow up assessments
ICCs (95% CI) over 2–3 years
All participants: 0.75 (0.69, 0.80)
Younger: 0.74 (0.66, 0.81)
Older: 0.74 (0.65, 0.81)
Normal weight: 0.73 (0.65, 0.80)
Overweight: 0.76 (0.68, 0.83)
Less active: 0.75 (0.67, 0.82)
More active: 0.64 (0.54, 0.73)
Percent agreement in classification of SB into same quartile at baseline and average of follow-up assessments: 50 and 7% misclassified by ≥2 quartiles
Wanner et al., 2013 [32] n = 65
32 males, 33 females (50.8%)
Mean age = 60.8 ± 9.9 y
Switzerland: Data collected for ancillary study of the Swiss Cohort Study on Air Pollution and Long and Heart Disease in Adults, after completion of the main study.
ActiGraph GT3X Two worn on right hip
60-s epochs
Free-living
Activities: VA < 150 cpm, <  100 cpm and < 200 cpm
Observation period: 8 consecutive days
Valid hours and days: not reported
Non-wear algorithm: 60 min of consecutive zeros, no allowance for interruptions
Analysis: compared normal filter to low-frequency extension (LTE) filter using Spearman correlations, Wilcoxon rank sum tests, scatter plots, and Bland–Altman plots; used linear regression to compute correction factors in half the sample and re-analyse results using correction factor
NORMAL VS LTE FILTER FOR VA < 150 CPM
Non-wear time
Spearman r: 0.97
Mean difference: 8.9 ± 13.3; 1.5% ± 2.2%, p < 0.001
Sedentary time (min/day)
Spearman r: 0.96
Mean difference: 25.7 ± 17.6; 4.5% ± 3.1%, p < 0.001
Other findings
Results for mean differences did not change if cut-point changed to < 100 or < 200 cpm for SB.
Plots showed non-wear time and SB time were systematically lower for low-frequency extension vs normal filter.
CORRECTION FACTOR FOR LFE FILTER FOR VA < 150 CPM
Nonwear min/day: 2.996 + (1.01 x nonwear time from LFE)
Sedentary min/day: 62.74 + (0.93 x sedentary time from LFE)
COMPARE NORMAL VS LTE USING CORRECTION FACTORS FOR VA < 150 CPM
Non-wear time:
Mean difference: − 0.8 ± 9.1;
− 0.2% ± 1.5, p = 0.30
Sedentary time (min/day):
Mean difference: 0.1 ± 15.6;
− 0.1% ± 2.7%, p = 0.72
Hart et al., 2011 [35] n = 52
13 males; 39 females
Mean age: 69.3 ± 7.4 y
USA: Data collected from participants of larger ongoing study of physical activity patterns.
ActiGraph 7164
Worn on right waist
60-s epochs
Free-living
Activities: VA ≤50 cpm
Observation period: 21 consecutive days during all waking hours
Valid hours and days: not reported
Non-wear algorithm: 60 min of consecutive zeros, no allowance for interruptions
Analysis: computed reproducibility of sitting time using Spearman-Brown Prophecy Formulas based on ICC; computed RMANOVA to examine differences between days of the week
Number of days of measurement required for:
ICC = 0.80: 5 days
ICC = 0.85: 7 days
ICC = 0.90: 11 days
ICC = 0.95: 21 days
No significant differences between days of week in time spent in SB (p = 0.48)
  1. Abbreviations: cpm Counts per minute, IQR Inter-quartile range, ICC Intraclass correlation coefficient; valid hours and days: for free-living studies lasting at least 7 days, number of hours per day and days during observation period that were required for data to be included in analysis; VA Vertical axis, VM Vector magnitude, m Minutes, s Seconds, h Hours, y Years