Validation of Accelerometer Wear and Nonwear Time Classification Algorithm

Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN 37232-2260, USA.
Medicine and science in sports and exercise (Impact Factor: 3.98). 02/2011; 43(2):357-64. DOI: 10.1249/MSS.0b013e3181ed61a3
Source: PubMed


the use of movement monitors (accelerometers) for measuring physical activity (PA) in intervention and population-based studies is becoming a standard methodology for the objective measurement of sedentary and active behaviors and for the validation of subjective PA self-reports. A vital step in PA measurement is the classification of daily time into accelerometer wear and nonwear intervals using its recordings (counts) and an accelerometer-specific algorithm.
the purpose of this study was to validate and improve a commonly used algorithm for classifying accelerometer wear and nonwear time intervals using objective movement data obtained in the whole-room indirect calorimeter.
we conducted a validation study of a wear or nonwear automatic algorithm using data obtained from 49 adults and 76 youth wearing accelerometers during a strictly monitored 24-h stay in a room calorimeter. The accelerometer wear and nonwear time classified by the algorithm was compared with actual wearing time. Potential improvements to the algorithm were examined using the minimum classification error as an optimization target.
the recommended elements in the new algorithm are as follows: 1) zero-count threshold during a nonwear time interval, 2) 90-min time window for consecutive zero or nonzero counts, and 3) allowance of 2-min interval of nonzero counts with the upstream or downstream 30-min consecutive zero-count window for detection of artifactual movements. Compared with the true wearing status, improvements to the algorithm decreased nonwear time misclassification during the waking and the 24-h periods (all P values < 0.001).
the accelerometer wear or nonwear time algorithm improvements may lead to more accurate estimation of time spent in sedentary and active behaviors.

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    • "Wear time was defined as 24 h minus nonwear time. To define nonwear time, we adapted the recommendations of Choi et al [24] to the TracmorD accelerometer. R software version 3.1.2 "
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    ABSTRACT: Background: There is evidence that physical activity (PA) can attenuate the influence of the fat mass- and obesity-associated (FTO) genotype on the risk to develop obesity. However, whether providing personalized information on FTO genotype leads to changes in PA is unknown. Objective: The purpose of this study was to determine if disclosing FTO risk had an impact on change in PA following a 6-month intervention. Methods: The single nucleotide polymorphism (SNP) rs9939609 in the FTO gene was genotyped in 1279 participants of the Food4Me study, a four-arm, Web-based randomized controlled trial (RCT) in 7 European countries on the effects of personalized advice on nutrition and PA. PA was measured objectively using a TracmorD accelerometer and was self-reported using the Baecke questionnaire at baseline and 6 months. Differences in baseline PA variables between risk (AA and AT genotypes) and nonrisk (TT genotype) carriers were tested using multiple linear regression. Impact of FTO risk disclosure on PA change at 6 months was assessed among participants with inadequate PA, by including an interaction term in the model: disclosure (yes/no) × FTO risk (yes/no). Results: At baseline, data on PA were available for 874 and 405 participants with the risk and nonrisk FTO genotypes, respectively. There were no significant differences in objectively measured or self-reported baseline PA between risk and nonrisk carriers. A total of 807 (72.05%) of the participants out of 1120 in the personalized groups were encouraged to increase PA at baseline. Knowledge of FTO risk had no impact on PA in either risk or nonrisk carriers after the 6-month intervention. Attrition was higher in nonrisk participants for whom genotype was disclosed (P=.01) compared with their at-risk counterparts. Conclusions: No association between baseline PA and FTO risk genotype was observed. There was no added benefit of disclosing FTO risk on changes in PA in this personalized intervention. Further RCT studies are warranted to confirm whether disclosure of nonrisk genetic test results has adverse effects on engagement in behavior change. Trial registration: NCT01530139; (Archived by WebCite at:
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    • "Choi et al., modified to include use of triaxial data [15] [16]. Briefly, non-wear time was defined as 90 consecutive minutes of 0 vector magnitude (VM) counts, with allowance for up to 2 min of nonzero counts when upstream and downstream windows also contained 30 consecutive minutes of zero counts for detection of artifactual movements. "
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    ABSTRACT: It is unclear how physical activity estimates differ when assessed using hip- vs wrist-worn accelerometers. The objective of this study was to compare physical activity assessed by hip- and wrist-worn accelerometers in free-living older women.
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    • "Sedentary time was defined as the number of minutes/day spent at 0–99 counts per minute (Wong et al., 2011). Non-wear time was defined as at least 90 consecutive minutes of zero counts (Choi et al., 2011). During non-wear periods, up to 2 min of nonzero counts were allowed provided that they were not detected in a 30-minute window upstream or downstream of the non-wear period, and recommendations put forth by Colley and colleagues were used to identify spurious data (Colley and Gorber). "
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    ABSTRACT: Excessive sedentary behavior is associated with negative health outcomes independent of physical activity. Objective estimates of time spent in sedentary behaviors are lacking among adults from diverse Hispanic/Latino backgrounds. The objective of this study was to describe accelerometer-assessed sedentary time in a large, representative sample of Hispanic/Latino adults living in the United States, and compare sedentary estimates by Hispanic/Latino background, sociodemographic characteristics and weight categories. This study utilized baseline data from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) that included adults aged 18-74. years from four metropolitan areas (N. =. 16,415). Measured with the Actical accelerometer over 6. days, 76.9% (n. =. 12,631) of participants had >10. h/day and >3. days of data. Participants spent 11.9. h/day (SD 3.0), or 74% of their monitored time in sedentary behaviors. Adjusting for differences in wear time, adults of Mexican background were the least (11.6. h/day), whereas adults of Dominican background were the most (12.3. h/day), sedentary. Women were more sedentary than men, and older adults were more sedentary than younger adults. Household income was positively associated, whereas employment was negatively associated, with sedentary time. There were no differences in sedentary time by weight categories, marital status, or proxies of acculturation. To reduce sedentariness among these populations, future research should examine how the accumulation of various sedentary behaviors differs by background and region, and which sedentary behaviors are amenable to intervention.
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