Impact of Shift Work on Cardiometabolic Health in a 24/7 Healthcare System

Thesis Abstract

This study investigates the impact of shift work on cardiometabolic health within a 24/7 hospital system, addressing the rising concern that irregular work hours contribute to adverse health outcomes among healthcare professionals. The aim is to quantify associations between shift patterns and cardiometabolic risk, and to identify mediating factors such as sleep quality, dietary habits, and physical activity. Specific objectives are (i) to compare cardiometabolic biomarkers across shift types (day, rotating, night) over a 12-month period; (ii) to examine the prospective relationship between shift-related circadian disruption and incident metabolic syndrome; (iii) to assess the mediating roles of sleep duration, sleep quality, and lifestyle behaviors; and (iv) to explore organizational factors that modulate these associations. The study adopts a prospective cohort design anchored in the WHO-ICNIRP framework for occupational health, enrolling 1,200 hospital staff members across four tertiary hospitals recruited through stratified random sampling to ensure representation by role (nurses, physicians, support staff) and shift pattern. Data collection comprises (a) objective cardiometabolic measures (blood pressure, fasting glucose, HbA1c, lipid profile, waist circumference, BMI) captured at baseline, 6 months, and 12 months; (b) objective activity and sleep metrics by wrist-actigraphy for 14 days every 6 months; (c) validated questionnaires for sleep quality (Pittsburgh Sleep Quality Index), circadian disruption (Shift Work Disorder Scale), diet (Food Frequency Questionnaire), and physical activity (Global Physical Activity Questionnaire); (d) organizational variables via management surveys on shift scheduling practices and psychosocial work environment. Blood samples are analyzed using standardized clinical chemistry methods, and data on medications are extracted from occupational health records to adjust for confounders. Statistical analysis proceeds in a multilevel framework to account for clustering within hospitals and repeated measures over time. Descriptive statistics summarize baseline characteristics. Linear mixed-effects models will assess associations between shift type and continuous cardiometabolic outcomes (e.g., fasting glucose, HbA1c, lipid levels, blood pressure), with time, shift pattern, and interaction terms as fixed effects and participant-level random intercepts. Cox proportional hazards models will estimate incident metabolic syndrome over the follow-up period. Mediation analyses employing structural equation modeling will test the indirect effects of sleep quality and lifestyle behaviors on the shift–cardiometabolic health relationship. Sensitivity analyses will adjust for age, sex, socioeconomic status, smoking, alcohol use, and comorbidities. Theoretical grounding draws on the Circadian Disruption–Metabolic Syndrome framework and the Demand–Control–Support model to interpret how work schedules and psychosocial factors influence health through behavioral and physiological pathways. Expected findings include higher cardiometabolic risk (elevated fasting glucose, HbA1c, triglycerides, blood pressure, increased waist circumference) among night and rotating shift workers compared with day workers, with attenuated associations after accounting for sleep quality and lifestyle behaviors. Sleep fragmentation and reduced duration are anticipated to mediate a substantial portion of the shift-related risk, while organizational factors such as forward-rotating schedules and predictable shift patterns may mitigate adverse outcomes. The study expects to contribute robust longitudinal evidence on how shift work interfaces with cardiometabolic health in a high-stakes clinical setting and to quantify the relative weights of behavioral versus physiological pathways. The contribution to knowledge includes (i) delineating the temporal dynamics of shift work–related cardiometabolic risk in a 24/7 healthcare system using objective biomarkers and longitudinal design; (ii) clarifying mediating mechanisms via rigorous mediation analysis; and (iii) informing evidence-based scheduling policies and targeted wellness interventions. The study will provide practical recommendations for hospital administrators, such as implementing forward-rotating schedules with adequate recovery periods, optimizing sleep health programs, and designing nutrition and physical activity support tailored to shift workers. A key conclusion anticipated is that addressing sleep quality and lifestyle mediators can substantially reduce cardiometabolic risk associated with non-day schedules, complementing pharmacological and clinical management strategies.