Characterizing light-dark cycles in the Neonatal Intensive Care Unit: a retrospective observational study

Front Physiol. 2023 Aug 16:14:1217660. doi: 10.3389/fphys.2023.1217660. eCollection 2023.


Objectives: To characterize bedside 24-h patterns in light exposure in the Neonatal Intensive Care Unit (NICU) and to explore the environmental and individual patient characteristics that influence these patterns in this clinical setting. Methods: We conducted a retrospective cohort study that included 79 very preterm infants who stayed in an incubator with a built-in light sensor. Bedside light exposure was measured continuously (one value per minute). Based on these data, various metrics (including relative amplitude, intradaily variability, and interdaily stability) were calculated to characterize the 24-h patterns of light exposure. Next, we determined the association between these metrics and various environmental and individual patient characteristics. Results: A 24-h light-dark cycle was apparent in the NICU with significant differences in light exposure between the three nurse shifts (p < 0.001), with the highest values in the morning and the lowest values at night. Light exposure was generally low, with illuminances rarely surpassing 75 lux, and highly variable between patients and across days within a single patient. Furthermore, the season of birth and phototherapy had a significant effect on 24-h light-dark cycles, whereas no effect of bed location and illness severity were observed. Conclusion: Even without an official lighting regime set, a 24-h light-dark cycle was observed in the NICU. Various rhythmicity metrics can be used to characterize 24-h light-dark cycles in a clinical setting and to study the relationship between light patterns and health outcomes.

Keywords: NICU; chronobiology; circadian rhythms; light; light-dark cycles; neonatology; phototherapy; preterm birth.

Grants and funding

This work was supported by a grant from the Velux Stiftung (project 1793 to JD and LK). During parts of this work, LK was supported by a VENI fellowship from the Netherlands Organisation for Health Research and Development ZonMw (grant number 2020–09150161910128).