Interest in cardiac vagal activity (CVA; e.g., parasympathetically-mediated heart rate variability) as a biomarker of physical and mental health has increased exponentially in recent years. However, the understanding of sources of within-person change (i.e., intra-individual variance) in CVA is lagging behind. This systematic review and meta-analysis summarizes and quantifies current empirical evidence of within-person changes in measures of CVA across the menstrual cycle in naturally-cycling premenopausal females. We conducted an extensive literature search following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement in five databases to identify observational studies with repeated measures of CVA in at least two menstrual cycle phases. A broad meta-analysis (nstudies = 37; nindividuals = 1,004) revealed a significant CVA decrease from the follicular to luteal phase (d = −0.39, 95% CI (−0.67, −0.11)). Furthermore, 21 studies allowed for finer-grained comparisons between each of two cycle phases (menstrual, mid-to-late follicular, ovulatory, early-to-mid luteal, and premenstrual). Significant decreases in CVA were observed from the menstrual to premenstrual (nstudies = 5; nindividuals = 200; d = −1.17, 95% CI (−2.18, −0.17)) and from the mid-to-late follicular to premenstrual phases (nstudies = 8; nindividuals = 280; d = −1.32, 95% CI (−2.35, −0.29)). In conclusion, meta-analyses indicate the presence of CVA fluctuations across the menstrual cycle. Future studies involving CVA should control for cycle phase. Recommendations for covarying or selecting cycle phase are provided.

A recent meta-analysis revealed that cardiac vagal activity (mostly indicated by vagally-mediated heart rate variability; HRV) decreases significantly from the follicular to luteal menstrual cycle phase in naturally-cycling participants. However, the question remains as to whether cyclical changes in estradiol (E2), progesterone (P4), or both are responsible for HRV fluctuations. We present the first studies to use repeated measures of E2, P4, and HRV across the cycle to model both the unique and interactive effects of person-centered E2 and P4 on HRV in multilevel models. In study one, 40 naturally-cycling participants were assessed weekly across four weeks, and were blind to the cycle focus of the study. In study two, 50 naturally-cycling participants were examined in three precisely defined cycle phases via ovulation testing. Both studies revealed that only P4 was correlated with HRV, such that higher-than-usual P4 significantly predicted lower-than-usual HRV within a given participant. In line with this, cycle phase comparisons revealed lower HRV in the mid-luteal phase (characterized by elevated P4) than in other phases. No significant main or interactive effects of E2 on HRV were found. Future female health studies should investigate individual differences in these effects and potential consequences of cyclical HRV changes on daily functioning.

Oxytocin, an evolutionarily conserved neuropeptide, plays a crucial role in various physiological and behavioural processes, offering potential therapeutic benefits for several psychiatric and neurodevelopmental conditions. Despite its promise, oxytocin research has been marked by inconsistent results concerning its therapeutic applications and underlying mechanisms. Performing a systematic review and meta-analysis is a popular approach to shed light on mixed findings in a body of literature; however, they can become quickly outdated as new evidence becomes available. Given these challenges, research on the links between oxytocin and biobehavioural outcomes is ideally positioned for the adoption of 'living' meta-analyses, which allow for the continuous integration of new data and updated conclusions. Here we introduce the Active Monitoring of Oxytocin Research Evidence (AMORE) platform (https://amore-project.org), which is a hub that aggregates articles and materials associated with living meta-analyses for biobehavioural oxytocin research in humans. Developed through consensus among 24 expert researchers, a standardized framework was established that either requires or recommends practices ensuring transparency and rigor in living meta-analyses featured on the AMORE platform. Overall, AMORE has been designed to advance human oxytocin biobehavioural research by the timely integration of emerging evidence through transparent living meta-analyses. To date, two living meta-analysis projects at different stages of publication are hosted on AMORE, demonstrating the platform's practical application.