Research project IM/RT/23/LATTITUDE (Research action IM)
Why this scientific question ?
One of the major problems faced by crews on mission in Antarctica is sleep disorders. More specifically, there is a poor quality of subjective sleep, increased fragmentation, a reduction in slow-wave sleep and a disruption of our circadian cycle. The main reason identified for these problems is the absence of normal photoperiodicity (24-hour day/night alternation) in this part of the world. Our team has published an important contribution to this state of the question.
A number of confounding inter-individual and cross-cultural variables have yet to be clarified Firstly, an Antarctic expedition crew has no (intergenerational) experience of life in isolation and in this fairly hostile environment. In contrast, the inhabitants of the higher latitude regions of the Arctic do have such experience. This raises the whole question of expedition adaptation versus intergenerational adaptation. In addition, gender effects have been documented in the physiological adaptation at Antarctic bases. Crews of Antarctic missions are known for their unequal gender distribution, with a very large minority of women, which affects their experience and the data collected.
We therefore want to understand which factors play a major role in adaptation by including in our study variables such as the degree of isolation, age and psychosocial context, origin, and lifestyle habits. In the framework of this project, we will collect data in Arctic population, inhabitants of high latitudes, to compare to our Antarctic data set. This will allow us to investigate whether, at the same latitudes, we find similar effects on sleep architecture and circadian rhythms.
Scientific aims of the project :
1. Understand whether sleep disturbance in Antarctica should be attributed to latitude or lived experience, or an interaction between the two?
2. Further explore a gender effect in sleep and circadian rhythms in Antarctica/Arctic regions
3. Integration: A Bayesian network analysis (BNA) to understand how certain underlying mechanisms may link aspects of seasonality.
