Accelerometer adherence and performance in a cohort study of US hispanic adults
2016-04-08T10:23:53Z (GMT) by
Purpose: This study described the adherence and performance of the accelerometer in a cohort study of adults. Methods: From 2008-2011, 16,415 Hispanic/Latino adults age 18-74 years enrolled in the Hispanic Community Health Study/Study of Latinos. Immediately following the baseline visit, participants wore an Actical accelerometer for one week. This study explored correlates of accelerometer participation and adherence, defined as wearing it for 3-6 days for >=10 hours each day. Accelerometer performance was assessed by exploring the number of different values of accelerometer counts/minute for each participant. Results: Overall, 92.3% (n=15,153) had at least one day with accelerometer data and 77.7% (n=12,750) were adherent. Both accelerometer participation and adherence were higher among participants who were married or partnered, reported a higher household income, were first generation immigrants, or reported lower sitting time. Accelerometer participation was higher among those with no stair limitations. Adherence was higher among participants who were male, older, employed or retired, not US born, preferred Spanish over English, reported higher work activity or lower recreational activity, and those with a lower body mass index. Among the sample that met the adherence definition, the maximum recorded count/minute was 12,000, and there were a total of 5,846 different counts/minute. On average, participants had 115 different counts/minute over 6 days (median 108, interquartile range 91-125). The number of different counts/minute were higher among men, younger ages, normal weight, and those with higher accelerometer assessed physical activity. Conclusion: Several correlates differed between accelerometer participation and adherence. These characteristics could be targeted in future studies to improve accelerometer wear. The performance of the accelerometer provides insight into creating a more accurate non-wear algorithm.