Association of menopausal status and symptoms with depressive symptoms in middle-aged Chinese women

Construction and validation of a nomogram for predicting fatigue in climacteric women

OBJECTIVE

The aim was to develop and validate a nomogram for evaluating the risk of fatigue in climacteric women and to assess its clinical application value.

METHODS

Clinical information was collected from 402 climacteric women who visited a tertiary hospital in Shanghai between November 2023 and April 2024. Network analysis methods were utilized to analyze the core symptom (fatigue). The study participants were then randomly divided into training and validation cohorts in a 7:3 ratio. Univariate and multivariate logistic regression analyses were conducted to identify independent risk factors for fatigue in climacteric women. A nomogram prediction model was established based on these independent risk factors. The predictive performance of the model was evaluated using the concordance index, area under the curve, receiver operating characteristic curve, Hosmer-Lemeshow test, and calibration curve analysis. Additionally, decision curve analysis was performed to assess the model's performance in clinical applications.

RESULTS

Fatigue is identified as the core symptom in climacteric women. Educational level, chronic diseases, and depression status are independent influencing factors for fatigue in menopausal women. The area under the curve for the training cohort and validation cohort are 0.813 (95% CI, 0.743-0.884) and 0.759 (95% CI, 0.637-0.879), respectively, indicating that the model possesses good discriminative ability. The calibration curve shows good consistency between the predicted probabilities and actual probabilities in both the training and validation cohorts. Additionally, the P values for the Hosmer-Lemeshow test in the training and validation sets are 0.233 and 0.197, respectively, indicating good model calibration. Finally, the decision curve analysis curve demonstrates that the model has good clinical utility.

CONCLUSIONS

A simple nomogram based on three independent factors (educational level, chronic diseases, and depression status) can aid in clinically predicting the risk of fatigue in climacteric women.

Global, regional, and national burden of anxiety disorders during the perimenopause (1990-2021) and projections to 2035

PURPOSE

Perimenopause is associated with an increased risk of anxiety disorders, largely due to hormonal changes affecting the body's regulatory feedback mechanisms. This study aims to provide a comprehensive analysis of the global burden of anxiety disorders among perimenopausal women.

METHODS

Data from the 2021 Global Burden of Disease (GBD) database were utilized to assess disability-adjusted life years associated with anxiety disorders linked to perimenopause. We calculated trends using the estimated average percent change, and future projections were made using the Bayesian age-period-cohort model to estimate disability-adjusted life year trends for anxiety disorders from 2022 to 2035.

RESULTS

Between 1990 and 2021, the global age-standardized disability-adjusted life year rate for anxiety disorders among perimenopausal women increased from 625.51 (95% uncertainty interval: 429.1-891.09) to 677.15 (95% uncertainty interval: 469.45-952.72), indicating a rising trend with an estimated average percent change of 0.081 (95% confidence interval: 0.0043-0.143). Regional differences were noted, with anxiety disorder burdens varying across areas with different sociodemographic index levels. Projections suggest that by 2035, the global burden of anxiety disorders in perimenopausal women will rise to 1,180.43 per 100,000, a 40.67% increase compared with 2021 levels.

CONCLUSION

The burden of anxiety disorders during perimenopause is a growing global concern, with a significant increase anticipated in the coming years. Targeted prevention and intervention strategies are urgently needed to mitigate this rising burden and improve mental health outcomes during perimenopause.

Unraveling the core and bridge menopausal symptoms of perimenopausal women: a network analysis

OBJECTIVE

Perimenopause is the period from the early menopausal transition to 12 months after the final menstrual period. The clustering of menopausal symptoms poses a challenge for perimenopausal management. Core symptoms are targets for interventions that can alleviate other related symptoms. Bridge symptoms are connectors that link related symptom clusters and can improve the effectiveness of interventions. This study aims to construct a network structure of menopausal symptoms and to identify core and bridge symptoms as a reference for future management.

METHODS

Two hundred forty-two Chinese perimenopausal women were included in the survey. The structure and associations of the menopausal symptoms assessed by the Greene Climacteric Scale were analyzed using a network analysis. We generated the network structure graph using R software and checked its accuracy and stability.

RESULTS

In the menopausal transition, the most prevalent symptoms were feeling tired or lacking in energy, excitability, and irritability. Sexual dysfunction was common among early postmenopausal women. Irritability (S = 7.16, C = 0.0167, B = 8) was a core symptom of the network. The depressive symptom cluster was a core symptom cluster, most of which have high centrality indices. Excitability (B = 6) was a bridge symptom connecting the anxiety and depressive symptom clusters.

CONCLUSIONS

Our study has highlighted the crucial significance of irritability and excitability in perimenopausal management. Overcoming the challenges of perimenopausal management requires the public to ameliorate the prejudice and stigma associated with emotional symptoms.

Associations between menopausal symptoms and cardiovascular disease in middle-aged Chinese women

OBJECTIVE

This study aimed to examine the association between severity of menopausal symptoms and cardiovascular disease (CVD) risk among middle-aged Chinese women.

METHODS

A cross-sectional study recruited 9679 women aged 40-70 years from three socioeconomic regions of China in 2018. Menopausal symptoms were assessed by the modified Kupperman Menopausal Index (KMI). The severity of individual symptoms was classified as none (0 points), mild (1 points) and moderate-to-severe symptoms (2-3 points), and overall menopausal symptoms were classified as none (<15 points), mild (15-24 points) or moderate-to-severe (≥25 points) according to the sum score of the KMI. Logistic regression models were used to examine associations of the severity of menopausal symptoms with CVD risk.

RESULTS

A total of 5.6% of participants reported being diagnosed with CVD. Overall menopausal symptoms were more common in women aged 60-70 years than in women aged 40-59 years. After multiple adjustment, mild (odds ratio [OR] = 2.07, 95% confidence interval [CI]: 1.64-2.61) and moderate-to-severe (OR = 2.64, 95% CI: 1.92-3.63) overall menopausal symptoms were associated with increased risk of CVD compared with no symptoms. Significant positive associations between the severity of individual menopausal symptoms and CVD risk were observed for all 13 items.

CONCLUSION

The severity of menopausal symptoms was positively associated with CVD risk in middle-aged Chinese women.

Global prevalence of depression in menopausal women: A systematic review and meta-analysis

BACKGROUND

An association between the menopause and depression is widely reported. This review aims to determine the global prevalence of depression in menopausal women (this includes women in perimenopause and postmenopause).

METHODS

PubMed, Web of Science, Embase, and PsycINFO databases were systematically searched from database inception until March 1, 2024. Studies with validated methods for assessing the prevalence of depression in perimenopausal and postmenopausal women were included. Two authors independently extracted relevant data. Random effects meta-analysis and Meta-regression analysis were performed using Stata software.

RESULTS

Total of 55 studies (76,817 participants) were included in the review. A random effects model was used to calculate pooled prevalence. The pooled depression prevalence in menopausal women was 35.6 % (95 % CI: 32.0-39.2 %), with 33.9 % (95 % CI: 27.8-40.0 %) in perimenopausal women, and 34.9 % (95 % CI: 30.7-39.1 %) in postmenopausal women. Subgroup analyses indicated that region, screening tool, study design, and setting moderated the prevalence of depression. Meta-regression indicated that smaller sample sizes and poorer study quality were significantly associated with a higher prevalence.

LIMITATIONS

There was a high degree of heterogeneity across the included studies. Only articles published in English were included. There was significant publication bias in this meta-analysis. There is insufficient information about many risk factors of menopausal depression in current meta-analysis.

CONCLUSIONS

Depression is common among menopausal women worldwide. To reduce the negative impact of depression on health outcomes in menopausal women, regular screening and the availability of effective prevention and treatment measures should be made available for this population.

Prevalence and associated factors of depression in postmenopausal women: a systematic review and meta-analysis

BACKGROUND

Depression is a prevalent mental health problem in postmenopausal women. Given its significant impact on the quality of life and overall well-being of postmenopausal women, there is need for a comprehensive review and meta-analysis of the existing research globally. This systematic review and meta-analysis evaluated the global prevalence of depression and potential associated factors in postmenopausal women.

METHODS

The Cochrane Library, PubMed, EMBASE, Web of Science, MEDLINE, and PsycINFO databases were systematically searched from inception to March 22, 2023. The meta-analysis used the random-effects model to calculate the prevalence of depression rates and associated factors. In addition, subgroup analysis and sensitivity analysis were performed. Publication bias was assessed using funnel plots, Egger's test, and nonparametric trim-and-fill tests.

RESULTS

The meta-analysis included 50 studies that involved 385,092 postmenopausal women. The prevalence of depression in postmenopausal women was 28.00% (95% CI, 25.80-30.10). Among the factors relevant to depression among postmenopausal women, marital status (OR: 2.03, 95%CI: 1.33-3.11), history of mental illness (OR: 2.31, 95%CI: 1.50-3.57), chronic disease (OR: 3.13, 95%CI: 2.20-4.44), menstrual cycle (OR: 1.42, 95%CI: 1.17-1.72), abortion numbers (OR: 1.59, 95%CI: 1.40-1.80), menopausal symptoms (OR: 2.10, 95%CI: 1.52-2.90), and hormone replacement therapy (OR: 1.76, 95%CI: 1.31-2.35) were risk factors, while physical activity (OR: 0.56, 95%CI: 0.53-0.59), number of breastfed infants (OR: 0.43, 95%CI: 0.19-0.97), menopause age (OR: 0.44, 95%CI: 0.37-0.51) were preventive factors.

CONCLUSIONS

This study demonstrated that the prevalence of postmenopausal depression is high, and some risk factors and protective factors associated with it have been identified. It is necessary to improve screening and management and optimize prevention and intervention strategies to reduce the harmful effects of postmenopausal depression.

Association between sleep duration and depression in menopausal women: a population-based study

Aims

This research investigated menopausal women older than 50 years to find whether there were any independent relationships between the duration of sleep they got and their prevalence of depression.

Methods

National Health and Nutrition Examination Survey (NHANES) datasets from 2011-2020 were utilized in a cross-sectional study. Using multivariate linear regression models, the linear relationship between sleep duration and depression in menopausal women was investigated. Fitted smoothing curves and thresholds impact evaluation were used to investigate the nonlinear relationship. Then, subgroup analyses were performed according to smoking, drinking alcohol, diabetes, hypertension, heart disease, and moderate activities.

Results

This population-based study included a total of 3,897 menopausal women (mean age 65.47 ± 9.06 years) aged≥50 years; 3,159 had a depression score <10, and 738 had a depression score≥10. After controlling for all covariates, the prevalence of depression was 17% higher among participants with short sleep duration [OR=1.17, 95%CI=(0.65, 1.70), P<0.0001] and 86% [OR=1.86, 95%CI=(1.05, 2.66), P<0.0001] compared to participants with normal sleep duration. In subgroup analyses stratified by smoking and diabetes, the sleep duration and depression scores of non-smokers [β=-0.18, 95%CI= (-0.33, -0.02), P=0.0241] and diabetics were independently negatively correlated [β=-0.32, 95%CI= (-0.63, -0.01), P=0.0416]. Using a two-segment linear regression model, we discovered a U-shaped relationship between sleep duration and depression scores with an inflection point of 7.5 hours. Less than 7.5 hours of sleep was associated with an increased risk of developing depression [β=-0.81, 95%CI= (-1.05, -0.57), P<0.001]. However, sleeping more than 7.5 hours per night increased the risk of depression considerably [β=0.80, 95%CI= (0.51, 1.08), P<0.001].

Conclusions

Depression is associated with sleep duration in menopausal women. Insufficient or excessive sleep may increase the risk of depression in menopausal women.

High levels of physical activity are associated with a reduced likelihood of depressive symptoms in postmenopausal women

Depressive symptoms in postmenopausal women are a significant concern, but studies evaluated their relationship with menopausal symptoms and physical activity are limited. This cross-sectional study used the scale of the 9-item Patient Health Questionnaire (PHQ-9) and the modified Kupperman Index (KMI) to investigate the relationship between depressive symptoms, menopausal symptoms, and physical activity in postmenopausal women in Hunan Province, using cluster random sampling, and face-to-face interviews with women aged 50-64 years. The moderate (aOR = 2.242, 95 percent CI [1.646-3.052], P < .001) and severe menopausal symptoms (aOR = 3.654, 95 percent CI [1.754-7.611], P = .001), and low-level physical activity (aOR = 1.380, 95 percentCI [1.023-1.826], P = .035) may increase the risk of depressive symptoms. High levels of physical activity were associated with a decreased likelihood of depressive symptoms, but only when participants had no complaints of menopausal symptoms (aOR = 0.375, 95 percent CI [0.161-0.877], P = .024). This study provides a new result for the mental health of postmenopausal women and provides a reference for further related research.