Neurophysiological and Sociocultural Burden of Night Shift Work: A Multidimensional Analysis

Document Type : Original Article

Authors

1 Behbahan Faculty of Medical Sciences, Behbahan, Iran

2 Department of Health Safety and Environment, Persian Gulf Bidboland Gas Treating Company, Behbahan, Iran

3 Department of Occupational Health Engineering and Safety, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran

10.30491/hpr.2026.582500.1539
Abstract
Background: Gender differences in sleep disturbances among night shift workers, especially mothers, are influenced by biological and cultural factors, with insomnia and cardiovascular strain heightened during night shifts.
Objectives: The main goals are to evaluate gender-specific differences in sleep disruption and blood pressure, assess correlations between demographic variables (age, education, parenthood) and circadian preferences, and identify the mechanisms linking shift work to autonomic dysfunction.
Methods: A cross-sectional analysis was conducted in 2023 using standardized questionnaires (DRS-15, CTI) and calibrated blood pressure measurements. Non-parametric Spearman correlations were performed using SPSS version 27 for non-normally distributed data, as indicated by the Kolmogorov-Smirnov test (P < 0.05).
Results: Women exhibited a stronger preference for routine stability (r = -0.102, P = 0.037), while higher education was associated with greater openness to change (r = -0.095, P = 0.043). In terms of cardiovascular effects, blood pressure had weak but significant correlations with wake time (r = 0.114, P = 0.014), indicating a circadian-autonomic relationship. Parenthood reduced sleep efficiency by 13%, while marital status and education had minimal effects (R² < 1.3%).
Conclusion: This study highlights the importance of multidimensional interventions addressing the physiological (blood pressure management) and sociocultural (childcare support) aspects of shift-work-related health problems. Future research should combine actigraphy with metabolomic profiling to further understand chronic disease pathways.

Keywords


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