Long-term night shift work and cardiometabolic health in healthcare workers: a review of mechanisms and precision intervention strategies

Long-term night shift work has become one of the major risk factors for the cardiometabolic health of healthcare workers. Traditional perspectives have largely attributed this to sleep deprivation. However, recent studies have revealed that circadian misalignment itself constitutes an independent pathogenic factor. This article provides a systematic review of the epidemiological evidence, pathophysiological mechanisms, and precision intervention strategies in this field. Existing studies indicate a clear dose-response relationship between night shift exposure and cardiometabolic risk, with this association being modified by sex and age and capable of causing long-term or even irreversible health damage. Mechanistically, the desynchronization of central and peripheral circadian clocks serves as the core initiating event, which can induce neuroendocrine and autonomic imbalance. Emerging mechanisms include chronic low-grade inflammation, gut microbiota dysbiosis, and epigenetic modifications (e.g., DNA methylation changes of clock genes and human endogenous retrovirus elements). Together, they constitute a complex molecular network that underlies the pathogenic effects of night shift work. Based on these mechanisms, current intervention strategies are transitioning from one-size-fits-all recommendations to individualized approaches. These include circadian phenotype-based risk stratification, chrononutrition, timed light therapy, and precision scheduling at the organizational level. However, existing research still faces challenges including poor adherence, lack of long-term follow-up data, and insufficient multidisciplinary integration. To enable precise prevention of night-shift-related health damage in healthcare workers, future efforts should integrate digital health technologies and multidisciplinary collaboration. Full-career longitudinal cohorts should be established, incorporating multidimensional data, including chronotype, gene expression, metabolic phenotypes, and lifestyle, to build individualized risk assessment systems. This will support personalized health management and minimize the cumulative cardiometabolic damage caused by long-term night shifts.