Objective: The perimenopause is associated with increased hormone fluctuations and an elevated risk of depression. A number of predictors of depressive symptoms in the menopausal transition have previously been suggested. The purpose of this study was to investigate a set of biopsychosocial predictors of depressive symptoms in perimenopausal women. Methods: This cross-sectional study, investigating 114 perimenopausal women (according to the STRAW criteria) aged 40-56 years, was conducted within the scope of the Swiss Perimenopause Study. Multiple regression analyses were performed to identify the most accurate model predicting perimenopausal depressive symptoms. Depressive symptoms were assessed with the German version of the Center of Epidemiologic Studies Depression Scale (CES-D). Validated questionnaires were used to examine psychophysiological complaints, stress, self-esteem, self-compassion, body image, and social support. Estradiol (E2) and progesterone (P4) were assessed through saliva samples, and follicle-stimulating hormone and luteinizing hormone were determined through dried blood spot samples. Seven saliva samples per participant were used to investigate absolute levels and fluctuations of sex steroids. All other variables were measured once. Results: Multiple regression analyses revealed that E2 fluctuations (β=0.15, P = 0.015), history of depression (β=0.14, P = 0.033), menopausal symptoms (β=0.47, P < 0.0001), perceived stress (β=0.17, P = 0.014), body image (β= −0.25, P = 0.014) and self-esteem (β=−0.35, P < 0.0001) were predictive of perimenopausal depressive symptoms (R 2 = 0.60). P4 fluctuations and absolute levels of hypothalamic-pituitary-gonadal hormone were not statistically significant. Conclusions: E2 fluctuations were shown to be predictive of depressive symptoms in the perimenopause. Moreover, the presence of burdensome complaints and chronic stress as well as a poor self-evaluation seem to promote depressive symptoms in perimenopausal women.

A B S T R A C TThe menopausal transition is a critical phase for psychological disorders such as depression and anxiety, with prevalence rates of depression ranging up to 20% during the menopause. Nevertheless, the majority of women cope adequately with this reproductive transition phase and thus appear to be resilient. We assert that a variety of psychological factors influence the menopausal transition and result in an individual state on a continuum from successful adjustment to maladjustment. The purpose of this review is to offer a conceptual framework of resilience factors during the menopausal transition and to reveal which dimensions of resilience have already been verified for a healthy menopausal transition.We searched the databases PubMed and PsycINFO for studies investigating resilience factors during the menopausal transition which influence psychological and physical adjustment or maladjustment. A total of 23 articles were included.Altogether, we identified 15 different resilience factors, assessed with 23 different questionnaires. These factors can be grouped into six categories: core resilience, spirituality, control, optimism, emotion and selfrelated resilience. They are associated with a better adjustment to menopausal symptoms, milder physical symptoms, a better quality of and satisfaction with life, better well-being, less perceived stress and fewer depressive symptoms compared with women with lower levels of the respective resilience factors.Our conceptual framework includes resilience factors which have already been verified by empirical data. Further research is needed to determine whether these resilience factors can be assigned to a common factor and to incorporate biological resilience markers. already accompanied by various family, social and professional changes

Background: The perimenopause is associated with considerable biopsychosocial changes. The majority of women manage to adjust to these changes and cope well with the shift from reproductive to non-reproductive life. However, some women develop burdensome physical and psychological symptoms during the perimenopause. A strong link between menopausal complaints and depressed mood has been shown in this regard. To date, the decisive factors determining whether a woman will successfully achieve a healthy transition remain unclear. Thus, the purpose of this study is to investigate a range of theory-based markers related to health in perimenopausal women. Methods: The Swiss Perimenopause Study comprises a sample of 135 healthy perimenopausal women aged 40-56. A variety of health-related genetic, epigenetic, endocrinological, physiological, and psychosocial markers associated with the menopausal transition are investigated over a period of 13 months. Discussion: The Swiss Perimenopause Study will contribute to a better understanding of the biopsychosocial processes associated with the perimenopause, which should help to improve the clinical care of women undergoing the menopausal transition.

Despite significant biological, psychological, and social challenges in the perimenopause, most women report an overall positive well-being and appear to be resilient to potentially negative effects of this life phase. The objective of this study was to detect psychosocial variables which contribute to resilience in a sample of perimenopausal women. A total of 135 healthy perimenopausal women aged 40–56 years completed a battery of validated psychosocial questionnaires including variables related to resilience, well-being, and mental health. First, using exploratory factor analysis, we examined which of the assessed variables related to resilience can be assigned to a common factor. Second, linear regression analyses were performed to investigate whether a common resilience factor predicts well-being and mental health in the examined sample of women. Optimism (LOT-R-O), emotional stability (BFI-K-N), emotion regulation (ERQ), self-compassion (SCS-D), and self-esteem (RSES) in perimenopausal women can be allocated to a single resilience-associated factor. Regression analyses revealed that this factor is related to higher life satisfaction (SWLS; β = .39, p < .001, adj. R2 = .20), lower perceived stress (PSS-10; β = − .55, p < .001, adj. R2 = .30), lower psychological distress (BSI-18; β = − .49, p < .001, adj. R2 = .22), better general psychological health (GHQ-12; β = − .49, p < .001, adj. R2 = .22), milder menopausal complaints (MRS II; β = − .41, p < .001, adj. R2 = .18), and lower depressive symptoms (ADS-L; β = − .32, p < .001, adj. R2 = .26). The α levels were adjusted for multiple testing. Our findings confirm that several psychosocial variables (optimism, emotional stability, emotion regulation, self-compassion, and self-esteem) can be allocated to one common resilience-associated factor. This resilience factor is strongly related to women’s well-being as well as mental health in perimenopause.

Background: Perimenopause is characterized by a decline in the steroid hormones, estradiol, and progesterone. By contrast, the steroid hormone cortisol, a marker of the hypothalamic–pituitary–adrenal (HPA) axis, increases. Recent longitudinal studies reported fluctuations in steroid hormone levels during perimenopause, and even increases in estradiol levels. To understand these confounding results, it is necessary to conduct a longitudinal, highly standardized assessment of steroid hormone secretion patterns in perimenopausal women.Methods: This longitudinal study investigated 127 perimenopausal women aged 40–56 years for 13 months. Estradiol, progesterone, and cortisol were assessed using saliva samples, which were collected for two (during months 2 and 12 for estradiol and progesterone) or three (during months 2, 7, and 12 for cortisol) non-consecutive months over the course of the study. A total of 14 saliva samples per participant were analyzed to investigate the courses of estradiol and progesterone. Cortisol awakening response and fluctuations of cortisol throughout the day were measured using a total of 11 saliva samples per participant (on awakening, +30 min, +60 min, at 12:00 p.m., and before going to bed) for months 2, 7, and 12.Results: Multilevel analyses revealed variance in intercept and slope across participants for estradiol [intercept: SD = 5.16 (95% CI: 4.28, 6.21), slope: SD = 0.50 (95% CI: 0.39, 0.64)], progesterone [intercept: SD = 34.77 (95% CI: 25.55, 47.31), slope: SD = 4.17 (95% CI: 2.91, 5.99)], and cortisol (intercept: SD = 0.18 (95% CI: 0.14, 0.23), slope: SD = 0.02 (95% CI: 0.01, 0.02)]. Time predicted cortisol levels [b = −0.02, t(979) = −6.63, p &lt; 0.0001]. Perimenopausal status (early vs. late) did not predict estradiol [b = −0.36, t(1608) = −0.84, p = 0.400], progesterone [b = −4.55, t(1723) = −0.87, p = 0.385], or cortisol [b = 0.01, t(1124) = 0.61, p = 0.542] scores over time.Discussion: Our results are consistent with previous findings emphasizing highly individual fluctuations of estradiol and progesterone levels during perimenopause. However, our findings do not suggest a continuous decline during the observed transition phase, implying relatively stable periods of fluctuating hormone levels. Furthermore, given the lack of significant group differences, it may not be necessary to differentiate between early and late perimenopause from the standpoint of hormonal progression.