Abstract
Abstract Introduction The accurate estimation of sleep is critical for understanding who is most at risk for sleep disorders and associated disease outcomes. Individuals who overestimate sleep disturbances may be at increased risk for insomnia. A few studies have shown demographic differences in the accuracy of sleep estimation when comparing subjective and objective measures; however, the previous literature is inconsistent and focuses primarily on older adults. We sought to replicate these studies in a large sample of nurses using 14 days of sleep diary and actigraphy measures. Methods Participants were 392 nurses (91.8% female; 77.8% white, mean age = 39.54) recruited for a larger study. Participants completed 14 days of actigraphy and sleep diaries to prospectively assess total sleep time (TST) and sleep efficiency (SE). Discrepancy between diary and actigraphy measures was calculated by subtracting actigraphy measures from diary measures. Linear regression was used to examine how age, race (0 = race other than white, 1 = white), gender (1 = male, 2 = female), ethnicity (1= non-Hispanic/Latinx, 2 = Hispanic/Latinx) predicted degree of sleep discrepancy. Results The average discrepancy between diary and actigraphy TST was 30.29 minutes (SD = 29.28), and the average discrepancy between diary and actigraphy SE was 4.16% (SD = 5.66). Race and ethnicity did not predict amount of TST or SE discrepancy. However, younger individuals had more discrepancy in both TST (b = -0.48, p < .001) and SE (b = -0.09, p < .001). Men also had a greater discrepancy in both TST (b = -10.90, p < .05) and SE (b = -2.56, p < .05). Conclusion Men and younger individuals had greater discrepancies between diary and actigraphy measures of sleep. This is in contrast to some previous research showing that elderly women tend to display greater discrepancies between subjective and objective measures of sleep. It is essential that future research explore the discrepancies between subjective and objective measures of sleep in larger and more demographically diverse samples. Establishing a better understanding of this relationship is crucial, as it may have significant implications for the diagnosis and treatment of insomnia. Support NIH/NIAID R01AI128359-01
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