Impact of Sleep Extension on Metabolic Biomarkers in Shift Workers: Field Study

Thesis Abstract

Sleep disruption among shift workers is associated with adverse metabolic profiles, yet practical interventions to mitigate these effects in field settings remain underexplored. This study investigates whether structured sleep extension over eight weeks improves metabolic biomarkers and related physiological processes in shift workers, addressing the gap between laboratory findings and real-world work demands. The aim is to determine the extent to which increasing nightly sleep duration influences insulin sensitivity, lipid metabolism, inflammatory status, and autonomic function in a heterogeneous shift-working cohort. Specific objectives include (1) quantifying baseline and post-intervention sleep duration and quality using actigraphy and sleep diaries; (2) assessing changes in fasting glucose, insulin, HOMA-IR, lipid subfractions (HDL-C, LDL-C, triglycerides), high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), and 24-hour autonomic markers; (3) examining whether sleep extension moderates metabolic responses by occupation, chronotype, and caffeine intake; (4) evaluating adherence feasibility, perceived barriers, and worker-reported well-being. The study is guided by the Two-Process Model of Sleep Regulation and the allostatic load framework, allowing integration of circadian alignment with cumulative physiological strain. The research adopts a quasi-experimental, longitudinal field design with a mixed-methods component. A total of 240 shift workers, aged 22–60 years, recruited from healthcare, manufacturing, and public safety sectors, will be randomized at the unit level into an intervention group (n=120) receiving a structured sleep-extension protocol and a control group (n=120) maintaining habitual sleep patterns. Sleep extension will involve standardized sleep opportunity augmentation (target increase of 90 minutes per night) and sleep hygiene coaching delivered through weekly briefings and digital reminders. Objective sleep will be measured via wrist actigraphy (e.g., 7-day rolling averages) at baseline, week 4, week 8, and a follow-up at week 12. Primary metabolic outcomes will be assessed from fasting venous blood samples collected at baseline and week 8 plasma glucose, fasting insulin, HOMA-IR, total cholesterol, LDL-C, HDL-C, triglycerides, hs-CRP, and IL-6. Secondary data include 24-hour heart rate variability (HRV) metrics from ambulatory monitors, saliva cortisol as a stress biomarker, and accelerometer-derived physical activity. Instruments include validated questionnaires for sleep quality (Pittsburgh Sleep Quality Index), daytime sleepiness (Epworth Sleepiness Scale), chronotype (Munich Chronotype Questionnaire), and mood (Profile of Mood States). Data analysis comprises intention-to-treat and per-protocol approaches. Primary analyses will implement linear mixed-effects models to evaluate time-by-group interactions for metabolic biomarkers, adjusting for age, sex, baseline BMI, caffeine intake, physical activity, and occupation type. Mediation analyses will test whether changes in sleep duration and sleep efficiency mediate metabolic outcomes. Thematic analysis of semi-structured interviews (n=40 purposively sampled from the intervention group) will elucidate perceived facilitators and barriers to adherence and contextual factors affecting sleep behavior. Anticipated findings include statistically significant improvements in insulin sensitivity (lower HOMA-IR), favorable shifts in lipid profiles (increased HDL-C, reduced triglycerides), and reductions in systemic inflammatory markers (hs-CRP, IL-6) among the sleep-extended group relative to controls. Associated reductions in nocturnal sympathetic activity and enhancements in HRV, together with improved subjective well-being and daytime functioning, are expected. The study aims to demonstrate dose-response relationships between sleep extension and metabolic health, with effect modification by chronotype and occupational context. The study contributes to knowledge by translating laboratory-based sleep-health findings into a pragmatic field intervention applicable across diverse shift-work environments, integrating physiological, behavioral, and psychosocial data to delineate mechanisms linking sleep duration to metabolic regulation. Practical implications include informing workplace policies on shift scheduling, sleep-health promotion programs, and occupational health guidelines to mitigate cardiometabolic risk among shift workers. Limitations include potential non-adherence, residual confounding from unmeasured lifestyle factors, and generalizability constrained to the examined sectors. Recommendations emphasize scalable sleep-extension interventions, integration with circadian-aligned scheduling, and long-term follow-up to assess sustained metabolic benefits and health outcomes.