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Exploring Causal Pathways to Sleep Quality in Young Adults Using a Multimodal Data-Driven Causal Discovery Analysis.

Xiong Xiao1,2, Yulin Wang3, Debo Dong3

  • 1School of Life Health Information Science and Engineering, Chongqing University of Posts and Telecommunications, Chongqing, People's Republic of China.

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Summary

This study used causal discovery analysis to identify key factors influencing poor sleep quality. Negative affect, somaticism, and delay discounting were found to directly impact sleep.

Keywords:
causal discovery analysisdelay discountingnegative affectresting-state fMRIsleep qualitysomaticism

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Area of Science:

  • Neuroscience
  • Psychology
  • Data Science

Background:

  • Poor sleep quality is a widespread issue affecting physical and mental health.
  • The intricate mechanisms and contributing factors to poor sleep quality remain incompletely understood.

Purpose of the Study:

  • To investigate the causal pathways influencing sleep quality using a data-driven causal discovery analysis (CDA) approach.
  • To explore the complex interactions between phenotypic factors, brain network connectivity, and sleep quality.

Main Methods:

  • Utilized data from the Human Connectome Project (HCP) with 1206 healthy young adults.
  • Employed exploratory factor analysis to group 122 phenotypic variables into 21 factors.
  • Applied Greedy Fast Causal Inference (GFCI) to construct a causal model integrating phenotypic factors, brain network connectivity, and sleep quality.

Main Results:

  • A hierarchical causal model was developed, demonstrating complex inter-domain interactions affecting sleep quality.
  • Identified negative affect, somaticism, and delay discounting as direct phenotypic contributors to poor sleep quality.
  • Discovered demographic-specific causal pathways for sleep quality related to gender and relationship status.

Conclusions:

  • The data-driven model elucidates multifaceted mechanisms influencing sleep quality.
  • Highlights critical factors impacting sleep, offering insights for sleep theory development and interventions.
  • Suggests potential for targeted strategies to improve sleep quality based on identified causal pathways.