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 |
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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) |