Application of a Limit-Cycle Oscillator Model for Prediction of Circadian Phase in Rotating Night Shift Workers

• Published in: Scientific reports 2019-07, Vol.9 (1), p.11032-12, Article 11032
• Main Authors: Stone, Julia E., Aubert, Xavier L., Maass, Henning, Phillips, Andrew J. K., Magee, Michelle, Howard, Mark E., Lockley, Steven W., Rajaratnam, Shantha M. W., Sletten, Tracey L.
• Format: Article
• Language: English
• Subjects: 631/114/2397; 631/378/1385; 631/553/2693; Activity Cycles; Adult; Circadian Rhythm; Circadian rhythms; Diurnal; Female; Health Personnel; Humanities and Social Sciences; Humans; Jet lag; Male; Melatonin - analogs & derivatives; Melatonin - urine; Middle Aged; Models, Theoretical; multidisciplinary; Nighttime; Nursing; Phase shift; Science; Science (multidisciplinary); Shift Work Schedule - adverse effects; Workers; Wrist
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-019-47290-6

Practical alternatives to gold-standard measures of circadian timing in shift workers are needed. We assessed the feasibility of applying a limit-cycle oscillator model of the human circadian pacemaker to estimate circadian phase in 25 nursing and medical staff in a field setting during a transition from day/evening shifts (diurnal schedule) to 3–5 consecutive night shifts (night schedule). Ambulatory measurements of light and activity recorded with wrist actigraphs were used as inputs into the model. Model estimations were compared to urinary 6-sulphatoxymelatonin (aMT6s) acrophase measured on the diurnal schedule and last consecutive night shift. The model predicted aMT6s acrophase with an absolute mean error of 0.69 h on the diurnal schedule (SD = 0.94 h, 80% within ±1 hour), and 0.95 h on the night schedule (SD = 1.24 h, 68% within ±1 hour). The aMT6s phase shift from diurnal to night schedule was predicted to within ±1 hour in 56% of individuals. Our findings indicate the model can be generalized to a shift work setting, although prediction of inter-individual variability in circadian phase shift during night shifts was limited. This study provides the basis for further adaptation and validation of models for predicting circadian phase in rotating shift workers.