Saiyue Deng,1 Quan Wang,2 Jingjing Fan,3 Xiaoyun Yang,3 Junhua Mei,4 Jiajia Lu,5 Guohua Chen,4 Yuan Yang,1 Wenhua Liu,6 Runsen Wang,7 Yujia Han,7 Rong Sheng,7 Wei Wang,1 Li Ba,1 Fengfei Ding1,8 1Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People’s Republic of China; 2School of Nursing, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430000, People’s Republic of China; 3Cardiac Unit, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People’s Republic of China; 4Department of Neurology, Wuhan No.1 Hospital, Wuhan, 430022, People’s Republic of China; 5Cardiac Unit, Wuhan No.1 Hospital, Wuhan, 430022, People’s Republic of China; 6Department of Clinical Research Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430000, People’s Republic of China; 7Huawei Technologies Co, Shenzhen, People’s Republic of China; 8Department of Pharmacology, Shanghai Medical College, Fudan University, Shanghai, 200032, People’s Republic of ChinaCorrespondence: Fengfei Ding, Department of Pharmacology, Shanghai Medical College, Fudan University, Shanghai, 200032, People’s Republic of China, Tel +86 134 7625 5813, Email fengfei_ding@fudan.edu.cn Li Ba, Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People’s Republic of China, Tel +86 136 0764 1809, Email bali2015@126.comPurpose: Heart rate variability (HRV) indices have been used as stress indicators. Rare studies investigated the associations of circadian rhythms of the HRV indices with the stress, mood, and sleep conditions in populations under stress.Methods: In total 257 female participants (203 shift workers and 54 non-shift workers) were included. All the participants completed a structured questionnaire to assess the stress, mood, and sleep conditions and performed 24-hour Holter electrocardiogram monitoring on the day away from shifts. Using epochs of 1-min or 5-min beat-to-beat intervals, the HRV indices (SDNN, RMSSD, LF, HF, LF/HF, and LFnu, SD1, SD2, SD1/SD2) were plotted as a function of time and fitted into cosine periodic curves, respectively. Three mathematical parameters based on the cosine periodic curves were extracted, MESOR (M, overall averages of the cosine curve), amplitude (A, amplitude of the peak of the cosine curve), and acrophase (θ, latency to the peak) to quantify the circadian rhythms of the HRV indices. Multivariable linear regression models were used to reveal the associations of these parameters with the clinical assessments of stress, mood, or sleep conditions, as well as with the 24-h averages of the HRV indices.Results: The parameters M and A of SDNN, RMSSD, LF, and HF, and θ of LF/HF and LFnu significantly differ between shift and non-shift workers. The parameter θ of LF/HF positively correlates with the severity of stress and anxiety. The parameter A of LF/HF and LFnu also positively correlates with daytime sleepiness and sleep fragmentation. In addition, the parameters M and A instead of θ of SDNN, RMSSD, LF, LF/HF, and LFnu significantly correlate with the 24-h averages of HRV indices.Conclusion: The circadian rhythms of the HRV indices over 24 hours can, to some extent, predict the severity of stress, emotion and sleep conditions in female populations under stress.Keywords: circadian rhythms, HRV indices, mental health, stress, sleepiness, fatigue, sleep fragmentation