Sammito Stefan, Thielmann Beatrice, Böckelmann Irina
German Air Force Centre of Aerospace Medicine, Cologne, Germany.
Occupational Medicine, Faculty of Medicine, Otto von Guericke University, Magdeburg, Germany.
Front Physiol. 2024 Aug 6;15:1430458. doi: 10.3389/fphys.2024.1430458. eCollection 2024.
Heart rate variability (HRV) is an important non-invasive marker for the assessment of an organism's autonomic physiological regulatory pathways. Lower HRV has been shown to correlate with increased mortality. HRV is influenced by various factors or diseases. The aim of this narrative review is to describe the current state of knowledge on factors influencing HRV and their significance for interpretation.
The narrative review only included reviews, meta-analyses, and cohort studies which were published until 2021. HRV confounders were grouped into four categories (non-influenceable physiological factors, diseases, influenceable lifestyle factors and external factors).
The review found that HRV was decreased not only in non-influenceable physiological factors (e.g., age, gender, ethnicity) but also in connection with various number of acute and chronic diseases (e.g., psychiatric diseases, myocardial infarction, heart failure), influenceable lifestyle factors (e.g., alcohol abuse, overweight, physical activity), and external factors (e.g., heat, noise, shift work, harmful- and hazardous substances).
In order to improve the quality of HRV studies and to ensure accurate interpretation, it is recommended that confounders be taken into account in future diagnostic measurements or measurements in the workplace (e.g., as part of health promotion measures) in order to counteract data bias.
心率变异性(HRV)是评估机体自主神经生理调节途径的重要非侵入性指标。较低的HRV已被证明与死亡率增加相关。HRV受多种因素或疾病影响。本叙述性综述的目的是描述影响HRV的因素的当前知识状态及其对解读的意义。
本叙述性综述仅纳入截至2021年发表的综述、荟萃分析和队列研究。HRV混杂因素分为四类(不可影响的生理因素、疾病、可影响的生活方式因素和外部因素)。
该综述发现,HRV不仅在不可影响的生理因素(如年龄、性别、种族)中降低,而且与多种急性和慢性疾病(如精神疾病、心肌梗死、心力衰竭)、可影响的生活方式因素(如酗酒、超重、体育活动)以及外部因素(如热、噪音、轮班工作、有害和危险物质)有关。
为了提高HRV研究的质量并确保准确解读,建议在未来的诊断测量或工作场所测量(如作为健康促进措施的一部分)中考虑混杂因素,以抵消数据偏差。