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Sleep and Circadian Disruption as Contributors to Early Cardiometabolic Vulnerability Among Shift-Working Healthcare Professionals: A Systematic Review

Jul 2026 · Current Epidemiology Reports · Vol 13 · 0 citations · 47 references

TL;DR

Current evidence supports a relationship between sleep and circadian disruption and early cardiometabolic vulnerability among healthcare shift workers and integrating wearable-derived behavioral metrics with physiologic and biomarker-based phenotyping may improve the early identification of high-risk occupational profiles before irreversible cardiometabolic disease develops.

Abstract

Chronic circadian disruption, sleep impairment, and occupational stress in shift-working healthcare professionals can contribute to early cardiometabolic dysfunction before overt cardiovascular disease develops. This systematic review examines epidemiologic and physiologic evidence linking sleep and circadian disruption with autonomic, endocrine, metabolic, and vascular abnormalities in this population. All the included studies revealed associations with poor sleep quality, reduced sleep duration, circadian misalignment, autonomic imbalance and poor metabolic profiles with night-shift or rotational schedules. A number of studies have shown abnormalities in heart rate variability, cortisol modulation, melatonin rhythmicity, endothelial function, risk of obesity, hypertension, and glucose dysregulation among shift-working health care workers. The feasibility of diagnosing early subclinical cardiometabolic risk is supported by emerging wearable-based and ambulatory physiologic monitoring methods such as actigraphy, digital sleep phenotyping, and biomarker testing. Furthermore, evidence indicates heterogeneity in physiologic susceptibility according to sex, chronotype, shift schedule, and stress-related behavioral factors. However, longitudinal multimodal physiologic studies remain limited. Current evidence supports a relationship between sleep and circadian disruption and early cardiometabolic vulnerability among healthcare shift workers. Integrating wearable-derived behavioral metrics with physiologic and biomarker-based phenotyping may improve the early identification of high-risk occupational profiles before irreversible cardiometabolic disease develops.

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