Factors associated with chronotype in individuals with bipolar disorder in remission
Background: Chronotype is trait-like construct reflecting long-term morningness–eveningness preferences. Higher eveningness scores are linked to sleep disturbances, night-eating, and addictive behaviors but remain understudied in subjects with bipolar disorder (BD). Aim: This study aimed to explore...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wolters Kluwer Medknow Publications
2025-04-01
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| Series: | Indian Journal of Psychiatry |
| Subjects: | |
| Online Access: | https://journals.lww.com/10.4103/indianjpsychiatry.indianjpsychiatry_980_24 |
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| Summary: | Background:
Chronotype is trait-like construct reflecting long-term morningness–eveningness preferences. Higher eveningness scores are linked to sleep disturbances, night-eating, and addictive behaviors but remain understudied in subjects with bipolar disorder (BD).
Aim:
This study aimed to explore the clinical and behavioral factors associated with chronotype in a euthymic cohort with BD.
Methods:
Adult individuals (18–45 years) with DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, 5th Edition) diagnosis of BD in clinical remission (≥3 months) were enrolled, if they did not have current psychiatric or substance use disorder as per Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST score < 27). Participants were assessed using the validated Hindi version of Composite Scale of Morningness-Eveningness (CSM), the National Institute of Mental Health (NIMH)-Life Chart Method, IGLSI (International Group for Study of Lithium) Scale for typical/atypical features, Pittsburgh Sleep Quality Index, Cognitive complaints in BD Rating Assessment, Seasonal Pattern Assessment Questionnaire, Bipolar Eating Disorder Scale, Internet Disorder Scale, and Functioning Assessment Short Test. After data normalization, exploratory factor analysis was conducted using principal component analysis with varimax rotation on the study variables excluding the CSM. Subsequently, regression analysis was performed with CSM as the dependent variable.
Results:
The mean age of the sample was 32.43 ± 7.68 years (n = 100; 35% females). Factor analysis revealed a latent structure with three factors: Factor 1 (global functioning), Factor 2 (disordered biological functions and rhythms), and Factor 3 (dysfunction due to sleep and internet use). The regression model was found to be statistically significant [F (3,96) = 5.520, P = 0.002; R2 = 0.147, adjusted R2 = 0.120). Factor-2 was a significant predictor of CSM score (B = -2.201, SE: 0.606, P < 0.001). For every unit increase in Factor 2 score, the CSM total score reduced on average by 2.2 units.
Conclusion:
This study highlights the role of disrupted sleep, eating behaviors, and seasonality in influencing the chronotype and their interconnectedness in individuals with BD. |
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| ISSN: | 0019-5545 1998-3794 |