Lauderdale, D.S., Schumm, L.P., (2015) Response. to Dr. kawada Journals, of Gerontology Series B: Psychological Sciences and Social Sciences, doi:10.1093/geronb/gbu221.
Editorial
Response to Dr. Kawada Diane S. Lauderdale, L. Philip Schumm Department of Public Health Sciences, University of Chicago
e appreciate the opportunity to respond to Dr. Kawada’s thoughtful comments on our paper, “Assessment of sleep in the national social life, health, and aging project.” This paper was published in a special issue of Journals of Gerontology: Social Sciences devoted to describing the data collected as a part of the National Social Life Health and Aging Project (NSHAP) in 2010–2011, with the goal of facilitating this dataset’s use by the broader research community (Lauderdale et al., 2014). The purpose of the paper was to describe the sleep data, which included both survey questions and actigraphy data. Dr. Kawada characterizes the paper as concluding that there is a discrepancy between sleep duration from actigraphy and survey questions, but that is inaccurate. The association between self-reported and actigraph-estimated sleep duration is a complicated research question, and we did not address it in this paper. The paper did include one descriptive figure that displays joint variation, with little comment. We agree with Dr. Kawada’s motivating concern that perceptions of sleep and objectively estimated sleep characteristics are both meaningful. Dr. Kawada’s first point is an important technical issue about how to analyze the actigraphy data. We can confirm that we used the manufacturer’s default cutoff for the “total activity count” of 40 to score each epoch as sleep versus wake. Philips Respironics used this cutoff in their own internal validation studies and therefore recommends it. Moreover, changing the cutoff can change the determination of sleep start and end (which are based on a period of contiguous epochs scored as sleep), which were also validated by the manufacturer
based on the default cutoff. We are happy to make the raw, epoch-level activity counts available to other researchers, if they wish to set other thresholds. In fact, we have reanalyzed our data with the more sensitive threshold of 20, and the correlations between sleep metrics determined using a threshold of 20 versus 40 were extremely high (e.g., >0.99 for total sleep time). For metrics such as sleep fragmentation that use the sleep/wake threshold only indirectly (via determination of sleep start and end), the correlation in the NSHAP sample was 1.0. Because these correlations are so high, associations between these sleep parameters and other variables will be essentially the same whichever threshold is used. What would differ is the actual minutes identified as sleep within the sleep interval. On average, 4% of the epochs in the sleep interval among NSHAP participants would be recategorized from sleep to wake with the more sensitive threshold, resulting in mean sleep duration 18 min shorter. However, the correlation with self-reported sleep would be essentially unchanged. Dr. Kawada’s other points about why self-reported and actigraphy data may differ among subgroups of individuals with comorbidities are interesting, and the NSHAP data provide the opportunity to investigate hypotheses such as these in a nationally-representative sample of the community-dwelling elderly. Reference Lauderdale, D. S., Schumm, L. P., Kurina, L. M., McClintock, M., Thisted, R. A., Chen, J. H., & Waite, L. (2014). Assessment of sleep in the national social life, health, and aging project. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 69, Suppl 2, S125–S133. doi:10.1093/geronb/gbu092
© The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: [email protected].
Page 1 of 1
Downloaded from http://psychsocgerontology.oxfordjournals.org/ at University of California, San Francisco on March 28, 2015
W
Editorial
Response to Dr. Kawada Diane S. Lauderdale, L. Philip Schumm Department of Public Health Sciences, University of Chicago
e appreciate the opportunity to respond to Dr. Kawada’s thoughtful comments on our paper, “Assessment of sleep in the national social life, health, and aging project.” This paper was published in a special issue of Journals of Gerontology: Social Sciences devoted to describing the data collected as a part of the National Social Life Health and Aging Project (NSHAP) in 2010–2011, with the goal of facilitating this dataset’s use by the broader research community (Lauderdale et al., 2014). The purpose of the paper was to describe the sleep data, which included both survey questions and actigraphy data. Dr. Kawada characterizes the paper as concluding that there is a discrepancy between sleep duration from actigraphy and survey questions, but that is inaccurate. The association between self-reported and actigraph-estimated sleep duration is a complicated research question, and we did not address it in this paper. The paper did include one descriptive figure that displays joint variation, with little comment. We agree with Dr. Kawada’s motivating concern that perceptions of sleep and objectively estimated sleep characteristics are both meaningful. Dr. Kawada’s first point is an important technical issue about how to analyze the actigraphy data. We can confirm that we used the manufacturer’s default cutoff for the “total activity count” of 40 to score each epoch as sleep versus wake. Philips Respironics used this cutoff in their own internal validation studies and therefore recommends it. Moreover, changing the cutoff can change the determination of sleep start and end (which are based on a period of contiguous epochs scored as sleep), which were also validated by the manufacturer
based on the default cutoff. We are happy to make the raw, epoch-level activity counts available to other researchers, if they wish to set other thresholds. In fact, we have reanalyzed our data with the more sensitive threshold of 20, and the correlations between sleep metrics determined using a threshold of 20 versus 40 were extremely high (e.g., >0.99 for total sleep time). For metrics such as sleep fragmentation that use the sleep/wake threshold only indirectly (via determination of sleep start and end), the correlation in the NSHAP sample was 1.0. Because these correlations are so high, associations between these sleep parameters and other variables will be essentially the same whichever threshold is used. What would differ is the actual minutes identified as sleep within the sleep interval. On average, 4% of the epochs in the sleep interval among NSHAP participants would be recategorized from sleep to wake with the more sensitive threshold, resulting in mean sleep duration 18 min shorter. However, the correlation with self-reported sleep would be essentially unchanged. Dr. Kawada’s other points about why self-reported and actigraphy data may differ among subgroups of individuals with comorbidities are interesting, and the NSHAP data provide the opportunity to investigate hypotheses such as these in a nationally-representative sample of the community-dwelling elderly. Reference Lauderdale, D. S., Schumm, L. P., Kurina, L. M., McClintock, M., Thisted, R. A., Chen, J. H., & Waite, L. (2014). Assessment of sleep in the national social life, health, and aging project. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 69, Suppl 2, S125–S133. doi:10.1093/geronb/gbu092
© The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: [email protected].
Page 1 of 1
Downloaded from http://psychsocgerontology.oxfordjournals.org/ at University of California, San Francisco on March 28, 2015
W
