A novel method to separate circadian from non-circadian masking effects to enhance estimation of circadian timing and amplitude from core body temperature

Study objectives: Circadian disruption contributes to adverse effects on sleep, performance, and health. One accepted method to track continuous daily changes in central circadian timing is to measure core body temperature (CBT), and establish daily, circadian-related CBT minimum time (Tmin). This method typically applies cosine-model fits to measured CBT data, which may not adequately account for substantial masking of circadian effects, and thus estimates of the circadian-related Tmin. This study introduced a novel physiology-grounded analytic approach to separate circadian from non-circadian effects on CBT, which we compared against traditional cosine-based methods. Methods: The dataset comprised 33 healthy participants (mean ± SD 32 ± 13 years) attending a 39-h in-laboratory study with an initial overnight sleep followed by an extended wake period. CBT data were collected at 30-s intervals via ingestible capsules. Our design captured CBT during both the baseline sleep period and during extended wake period (without sleep) and allowed us to model the influence of circadian and non-circadian effects of sleep, wake, and activity on CBT using physiology-guided generalized additive models. Results: Compared to the traditional cosine model, the new model exhibited superior fits to CBT (Pearson R 0.90 [95 %CI; [0.83–0.96] versus 0.81 [0.55–0.93]). The difference between estimated vs measured circadian Tmin, derived from the day without sleep, was better fit with our method (0.2 [−0.5,0.3] hours) versus previous methods (1.4 [1.1 to 1.7] hours). Conclusions: This new method provides improved demasking of non-circadian influences compared to traditional cosine methods, including the removal of a sleep-related bias towards an earlier estimate of circadian Tmin.