Eric T Hyde, Steve Nguyen, Fatima Tuz-Zahra, Christopher C Moore, Mikael Anne Greenwood-Hickman, Rod L Walker, Loki Natarajan, Dori Rosenberg, John Bellettiere
{"title":"同时佩戴 ActiGraph 和 ActivPAL 加速计的老年人步数指标的一致性。","authors":"Eric T Hyde, Steve Nguyen, Fatima Tuz-Zahra, Christopher C Moore, Mikael Anne Greenwood-Hickman, Rod L Walker, Loki Natarajan, Dori Rosenberg, John Bellettiere","doi":"10.1123/jmpb.2022-0001","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>Our study evaluated the agreement of mean daily step counts, peak 1-min cadence, and peak 30-min cadence between the hip-worn ActiGraph GT3X+ accelerometer, using the normal filter (AG<sub>N</sub>) and the low frequency extension (AG<sub>LFE</sub>), and the thigh-worn activPAL3 micro (AP) accelerometer among older adults.</p><p><strong>Methods: </strong>Nine-hundred and fifty-three older adults (≥65 years) were recruited to wear the ActiGraph device concurrently with the AP for 4-7 days beginning in 2016. Using the AP as the reference measure, device agreement for each step-based metric was assessed using mean differences (AG<sub>N</sub> - AP and AG<sub>LFE</sub> - AP), mean absolute percentage error (MAPE), and Pearson and concordance correlation coefficients.</p><p><strong>Results: </strong>For AG<sub>N</sub> - AP, the mean differences and MAPE were: daily steps -1,851 steps/day and 27.2%, peak 1-min cadence -16.2 steps/min and 16.3%, and peak 30-min cadence -17.7 steps/min and 24.0%. Pearson coefficients were .94, .85, and .91 and concordance coefficients were .81, .65, and .73, respectively. For AG<sub>LFE</sub> - AP, the mean differences and MAPE were: daily steps 4,968 steps/day and 72.7%, peak 1-min cadence -1.4 steps/min and 4.7%, and peak 30-min cadence 1.4 steps/min and 7.0%. Pearson coefficients were .91, .91, and .95 and concordance coefficients were .49, .91, and .94, respectively.</p><p><strong>Conclusions: </strong>Compared with estimates from the AP, the AG<sub>N</sub> underestimated daily step counts by approximately 1,800 steps/day, while the AG<sub>LFE</sub> overestimated by approximately 5,000 steps/day. However, peak step cadence estimates generated from the AG<sub>LFE</sub> and AP had high agreement (MAPE ≤ 7.0%). Additional convergent validation studies of step-based metrics from concurrently worn accelerometers are needed for improved understanding of between-device agreement.</p>","PeriodicalId":73572,"journal":{"name":"Journal for the measurement of physical behaviour","volume":"5 4","pages":"242-251"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9934009/pdf/nihms-1870840.pdf","citationCount":"0","resultStr":"{\"title\":\"Agreement of Step-Based Metrics From ActiGraph and ActivPAL Accelerometers Worn Concurrently Among Older Adults.\",\"authors\":\"Eric T Hyde, Steve Nguyen, Fatima Tuz-Zahra, Christopher C Moore, Mikael Anne Greenwood-Hickman, Rod L Walker, Loki Natarajan, Dori Rosenberg, John Bellettiere\",\"doi\":\"10.1123/jmpb.2022-0001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>Our study evaluated the agreement of mean daily step counts, peak 1-min cadence, and peak 30-min cadence between the hip-worn ActiGraph GT3X+ accelerometer, using the normal filter (AG<sub>N</sub>) and the low frequency extension (AG<sub>LFE</sub>), and the thigh-worn activPAL3 micro (AP) accelerometer among older adults.</p><p><strong>Methods: </strong>Nine-hundred and fifty-three older adults (≥65 years) were recruited to wear the ActiGraph device concurrently with the AP for 4-7 days beginning in 2016. Using the AP as the reference measure, device agreement for each step-based metric was assessed using mean differences (AG<sub>N</sub> - AP and AG<sub>LFE</sub> - AP), mean absolute percentage error (MAPE), and Pearson and concordance correlation coefficients.</p><p><strong>Results: </strong>For AG<sub>N</sub> - AP, the mean differences and MAPE were: daily steps -1,851 steps/day and 27.2%, peak 1-min cadence -16.2 steps/min and 16.3%, and peak 30-min cadence -17.7 steps/min and 24.0%. Pearson coefficients were .94, .85, and .91 and concordance coefficients were .81, .65, and .73, respectively. For AG<sub>LFE</sub> - AP, the mean differences and MAPE were: daily steps 4,968 steps/day and 72.7%, peak 1-min cadence -1.4 steps/min and 4.7%, and peak 30-min cadence 1.4 steps/min and 7.0%. Pearson coefficients were .91, .91, and .95 and concordance coefficients were .49, .91, and .94, respectively.</p><p><strong>Conclusions: </strong>Compared with estimates from the AP, the AG<sub>N</sub> underestimated daily step counts by approximately 1,800 steps/day, while the AG<sub>LFE</sub> overestimated by approximately 5,000 steps/day. However, peak step cadence estimates generated from the AG<sub>LFE</sub> and AP had high agreement (MAPE ≤ 7.0%). Additional convergent validation studies of step-based metrics from concurrently worn accelerometers are needed for improved understanding of between-device agreement.</p>\",\"PeriodicalId\":73572,\"journal\":{\"name\":\"Journal for the measurement of physical behaviour\",\"volume\":\"5 4\",\"pages\":\"242-251\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9934009/pdf/nihms-1870840.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal for the measurement of physical behaviour\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1123/jmpb.2022-0001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/10/11 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal for the measurement of physical behaviour","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1123/jmpb.2022-0001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/10/11 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
Agreement of Step-Based Metrics From ActiGraph and ActivPAL Accelerometers Worn Concurrently Among Older Adults.
Purpose: Our study evaluated the agreement of mean daily step counts, peak 1-min cadence, and peak 30-min cadence between the hip-worn ActiGraph GT3X+ accelerometer, using the normal filter (AGN) and the low frequency extension (AGLFE), and the thigh-worn activPAL3 micro (AP) accelerometer among older adults.
Methods: Nine-hundred and fifty-three older adults (≥65 years) were recruited to wear the ActiGraph device concurrently with the AP for 4-7 days beginning in 2016. Using the AP as the reference measure, device agreement for each step-based metric was assessed using mean differences (AGN - AP and AGLFE - AP), mean absolute percentage error (MAPE), and Pearson and concordance correlation coefficients.
Results: For AGN - AP, the mean differences and MAPE were: daily steps -1,851 steps/day and 27.2%, peak 1-min cadence -16.2 steps/min and 16.3%, and peak 30-min cadence -17.7 steps/min and 24.0%. Pearson coefficients were .94, .85, and .91 and concordance coefficients were .81, .65, and .73, respectively. For AGLFE - AP, the mean differences and MAPE were: daily steps 4,968 steps/day and 72.7%, peak 1-min cadence -1.4 steps/min and 4.7%, and peak 30-min cadence 1.4 steps/min and 7.0%. Pearson coefficients were .91, .91, and .95 and concordance coefficients were .49, .91, and .94, respectively.
Conclusions: Compared with estimates from the AP, the AGN underestimated daily step counts by approximately 1,800 steps/day, while the AGLFE overestimated by approximately 5,000 steps/day. However, peak step cadence estimates generated from the AGLFE and AP had high agreement (MAPE ≤ 7.0%). Additional convergent validation studies of step-based metrics from concurrently worn accelerometers are needed for improved understanding of between-device agreement.