Sleeping patterns and cardiometabolic health among self employed and employed workers in the UK: A biosocial analysis

Background: Self-employment is presented as a route to autonomy and flexibility, yet evidence on its health consequences remains mixed. While some self-employed workers benefit from greater control and satisfaction, others – in solo or precarious forms – face high job demands, financial insecurity and blurred work–life boundaries that may undermine well-being. Sleep is an underexplored mechanism linking work conditions to health. Short and poor-quality sleep are associated with increased psychological distress and cardiometabolic risk. Entrepreneurship research also suggests that sleep plays an important role in self-regulation, decision-making and performance, although much of this evidence relies on small or selective samples. Yet, biosocial studies have rarely examined how sleep might connect to entrepreneurship or self-employment to processes of biological ageing.
Methods: This study uses Understanding Society, the UK Household Longitudinal Study, integrating longitudinal survey data with biomarker measures. We construct sleep-work-wellbeing profiles across self-employed and wage-employees using information on sleep duration, quality and insomnia-like symptoms, work hours and wellbeing. Latent profile analysis is being used to identify distinct configurations of work conditions, sleep and wellbeing, which are then examined in relation to cardiometabolic biomarkers as indicators of biological ageing.
Findings: Analyses are ongoing. We anticipate identifying distinct sleep-work well-being profiles between wage-employees and self-employed, including more favourable profiles characterised by a lifestyle with adequate sleep that supports well-being, in contrast to adverse profiles marked by poor sleep, long or irregular working hours and declining well-being. We will test whether these profiles show differences in cardiometabolic risk, and whether high-risk profiles are concentrated in more precarious forms of self-employment relative to other work arrangements.
Conclusion: By combining social and biological data, this study will show how patterns of work and sleep shape health inequalities, informing prevention efforts and the design of sleep-supportive interventions for self-employed and employed workers in the UK.