Effect of acupuncture on menopausal depressive disorder and serum hormone levels: a systematic review and meta-analysis

Background: Menopause, marked by ovarian decline and hormonal shifts, increases vulnerability to depressive disorders, with menopausal depressive disorder (MDD) affecting 33–36% of women via psychosocial-biological interactions. Acupuncture shows promise in improving MDD through neuroendocrine regulation but lacks robust evidence, with unclear links to reproductive hormone modulation; this study evaluates its efficacy and safety.

Methods: A comprehensive database search was conducted using PubMed, Embase, the Cochrane Library, Web of Science, EBSCO, Scopus, Cnki, Wan Fang and VIP Database to identify randomized controlled trials (RCTs) investigating the impact of acupuncture on menopausal depressive disorder. RCTs published until April 21, 2025, that met our predetermined inclusion and exclusion criteria were included. Data extraction, literature review, and assessment of the methodological quality of the trials were performed. The meta-analysis was conducted using Review Manager (RevMan) 5.3 software.

Results: Our findings demonstrate that acupuncture significantly outperforms control interventions in improving clinical effectiveness rates (OR=2.70, 95%CI[1.63,4.48], P=0.0001) and reducing depressive symptoms, as evidenced by HAMD-17 (SMD=-0.28, P<0.0001) and HAMD-24 scores (post-sensitivity SMD=-0.39, P=0.03). Notably, acupuncture also enhanced quality of life (MENQOL: SMD=-0.25, P=0.003), though its effects on sex hormones (FSH, LH, E2) remained nonsignificant (P>0.05). Safety profiles were comparable between groups (OR=0.16, P=0.05), yet sensitivity analysis revealed reduced adverse events in the acupuncture group after excluding outlier studies (OR=0.49, P=0.03). In conclusion, the intervention of acupuncture is beneficial for MDD.

Conclusion: This systematic review demonstrates that acupuncture serves as an effective and safe non-pharmacological intervention for alleviating menopausal depressive symptoms and improving quality of life. While acupuncture did not significantly modulate sex hormone levels, its therapeutic benefits are likely mediated through non-hormonal mechanisms, such as neurotransmitter regulation and neuroendocrine network modulation.

Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD420251037010.

1 Introduction

Menopause, recognized as a biological marker of the termination of female reproductive function (1), is clinically defined as the permanent cessation of menses (typically confirmed after 12 consecutive months of amenorrhea) (2, 3), characterized by endocrine alterations including diminished ovarian function, reduced estrogen levels, and increased gonadotropin (FSH/LH) concentrations (4, 5). As per the STRAW+10 staging system (6), the menopausal transition encompasses both the perimenopausal phase (stages -2 to -1) and early postmenopausal stage (+1a), wherein the final menstrual period (FMP) serves as the primary diagnostic marker. This transitional process typically commences after age 40 and persists for 4–5 years, while related symptoms may endure for several postmenopausal years (1). The average age at natural menopause ranges from 50–51 years in high-income nations to 40–58 years globally (3).

Menopausal depressive disorder(MDD) typically manifests during the transitional period surrounding menopause and is characterized by a constellation of psychological symptoms including low mood, anxiety, and heightened stress, frequently coexisting with physiological alterations linked to endocrine dysfunction, particularly hypogonadism and age-related hormonal changes (5, 7). Epidemiological evidence demonstrates a substantially greater burden of depression among menopausal women relative to other age groups (8). A meta-analysis revealed an aggregate prevalence of depression of 35.6% among menopausal women, comprising 33.9% during perimenopause and 34.9% in postmenopause (9). Longitudinal data indicate a progressive increase in depressive symptom prevalence across menopausal stages, rising from 14.5% at perimenopause to 19.6% at postmenopause (10), underscoring the elevated vulnerability during the menopausal transition, particularly the perimenopausal phase (10).

Worldwide epidemiological data indicate that approximately 33% of menopausal women experience depressive symptoms, with comparable prevalence rates observed during both perimenopausal and postmenopausal stages (9), demonstrating the sustained vulnerability to depression across the entire menopausal transition. The pathogenesis of menopausal depression represents a multifactorial interplay between psychosocial stressors and biological alterations. Predisposing factors including personal history of depression and neurotic personality traits, combined with environmental challenges such as socioeconomic disadvantage and inadequate social support, substantially elevate the risk for developing depressive disorders (11). Concurrently, biological mechanisms such as estrogen level variability, hypothalamic-pituitary-adrenal (HPA) axis dysregulation, vasomotor symptoms, and neuroinflammatory processes collectively contribute to mood disturbance exacerbation (12).

Recent studies have shown that acupuncture presents a multidimensional regulatory role in improving menopausal depression (13). The mechanism involves the synergistic regulation of neuroendocrine networks and cognitive functions: on the one hand, acupuncture activates the PKA/CREB signaling pathway (14) by regulating the metabolism of neurotransmitters such as 5-hydroxytryptamine (5-HT) (15), enhances synaptic plasticity in the hippocampus and inhibits neuroinflammatory responses (16); on the other hand, acupuncture significantly alleviates estrogen fluctuations induced by hypothalamic-pituitary-gonadal axis (HPO axis) dysfunction caused by estrogen fluctuation and improve the negative effects of hormonal imbalance on the central nervous system (17). In addition, acupuncture can reconfigure patients’ embodied cognitive patterns through enhanced somatosensory inputs, breaking the vicious cycle of “hormone-symptom-emotion” and improving sleep quality and cognitive function (17). Clinical evidence shows that acupuncture alone or in combination with antidepressants can significantly reduce depression scale scores, and has long-term efficacy in improving anxiety symptoms and vasodilatory symptoms (e.g., hot flashes), and maintains a stable effect 6 months after treatment (18). Notably, the modulating effect of acupuncture on serum reproductive hormone (e.g., FSH, LH, E₂) levels may be closely related to its antidepressant efficacy. However, the specific mechanisms by which acupuncture intervenes in hormone dynamics have not been fully elucidated in existing studies.

The menopausal period is considered a critical period in the development of depression in the female life cycle. The prevalence is particularly high during this stage. Given that acupuncture treatment for MDD has fewer side effects, it is gradually gaining recognition in clinical application. However, for the time being, the evidence supporting acupuncture for MDD is insufficient, and the depth of relevant studies is lacking. Therefore, the aim of this study is to investigate the efficacy and safety of acupuncture in the treatment of MDD.

2 Materials and methods

2.1 Database search protocol

Research studies from the beginning until April 21, 2025, were sought in electronic databases. Acupuncture, a key aspect of traditional Chinese medicine, has a considerable amount of related research that was first published in Chinese. Chinese databases hold a vast array of acupuncture studies, notable for both their quantity and the variety of study designs and populations involved. As a result, these databases were incorporated into the data collection for this research. Six international databases and three Chinese databases were searched: PubMed, Embase, Web of Science, Cochrane Central Register of Controlled Trials, EBSCO, Scopus, China National Knowledge Infrastructure, Wanfang Database and VIP Database for Chinese Technical Periodicals.

The combinations of MeSH terms and keywords include “acupuncture”, “electroacupuncture”, “auricular acupuncture”, “menopause” and “perimenopause”, “menopause”, “depression”, “menopause” and “perimenopause”, and “menopause”. “, “depression” and “depressive disorder”. Search:(acupuncture) OR (electroacupuncture) OR (auricular acupuncture) AND (menopause) OR (menopausal) OR (perimenopausal) AND (depression) OR (depression)). We also screened the reference list of prior SRs associated with perimenopausal depression and acupuncture for eligible trials. There were no language restrictions. For non-Chinese and English literature that met the inclusion criteria, one of the authors, who is proficient in additional languages, handled the translation and data extraction. This approach aligns with common practices in the field, ensuring the completeness and accuracy of data extraction. The translated data were then double-checked by two independent researchers to minimize errors. (See the Supplementary Document 9 for specific searches of relevant databases).The study protocol (registration No. CRD420251037010) was registered in PROSPERO.

2.2 Selection criterion

Inclusion criteria:

This research adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for reviewing literature, as shown in the flowchart in Figure 1. The research questions were developed using the PICOS framework.

1. Study design: This review included only randomized controlled trials (RCTs) that evaluated interventions for perimenopausal depression or menopausal depressive disorder in comparison to at least one control intervention.

2. Population: Individuals who have been diagnosed with perimenopausal depression or menopausal depressive disorder.

3. Interventions: Research examining the impact of acupuncture methods (such as electroacupuncture, manual acupuncture, and auricular acupuncture) on depression during the perimenopausal and menopausal stages, along with serum hormone levels. Control interventions consisted of medication, placebo, or sham acupuncture.

4. Outcome indicators: included trials must report at least one of the following forms of outcome: Hamilton Depression Scale (HAMD) (end score or from baseline to end of study), amount of clinical treatment effective, the Self-Rating Depression Scale (SDS), or serum estradiol (E2), luteinizing hormone (LH) or follicle-stimulating hormone (FSH) levels.

Figure 1

Figure 1. Flow diagram of the included studies.

Exclusion criteria:

1. non-randomized studies: non-randomized studies, such as observational studies or case reports, were excluded because of confounding factors and bias.

2. non-human studies: studies conducted in animals or in vitro experiments were excluded.

3. literature reviews: literature reviews were not included in the analysis because they did not provide original study data.

4. studies that did not comply with the PICOS protocol: studies that did not comply with the PICOS framework established for this review were excluded.

5. studies with insufficient data: studies that did not provide adequate data or assess cognitive parameters and outcome details were excluded.

2.3 Study selection and data extraction

Two authors (SXH and ZJW) independently reviewed all articles. Any disagreements were resolved through group discussions and by a third review author (SQD). The flowchart of the study selection process is shown in Figure 1. The two review authors also independently extracted data, recording the following information on a data sheet: study details (authors, year of publication, sample size, follow-up), patient characteristics (age range, diagnostic criteria), details of the acupuncture intervention and the control group, endpoints (primary and secondary), discontinuation, and adverse events (AEs). One reviewer reached out to authors via email to obtain any inadequate or missing data. The primary outcomes assessed included the Hamilton Depression Scale (HAMD-17), clinical effectiveness, and the Self-Rating Depression Scale (SDS), while the secondary outcome focused on serum hormone levels.

2.4 Quality assessment

Two independent researchers, YZD and HWQ, carried out a two-phase quality evaluation process. Initially, they conducted a preliminary screening using the Jadad Scale (ranging from 0 to 5 points) to evaluate the quality of studies based on three key areas: randomization procedures (0–2 points), implementation of blinding (0–2 points), and reporting of attrition/follow-up (0–1 point). Studies that received a score of 3 points or higher were deemed moderate to high quality and were included for further analysis (19). Following this, the eligible studies underwent a thorough risk-of-bias assessment utilizing the Cochrane Collaboration’s tool (20). The evaluation focused on three categories: low risk of bias, unclear risk of bias, and high risk of bias. The characteristics assessed included random sequence generation (selection bias), allocation concealment (selection bias), blinding of participants and personnel (performance bias), incomplete outcome data (attrition bias), selective reporting (reporting bias), and other biases. These elements were graphed and analyzed using Review Manager 5.3 (Cochrane Collaboration). Any disagreements were resolved through discussions among the authors or with the assistance of a third member (XGL and XG) when necessary.

2.5 Statistical analyses

We performed a meta-analysis using Review Manager (RevMan) version 5.3, created by the Cochrane Collaboration. We grouped studies with similar interventions and outcome measures. For continuous data, we computed the Standardized Mean Difference (SMD) along with the 95% confidence interval (CI). We evaluated heterogeneity among the studies using Cochrane’s Q statistic and the I² statistic. If the I² value was below 50%, we used a fixed-effects model; if it was higher, we opted for a random-effects model. A sensitivity analysis was conducted to pinpoint sources of heterogeneity by re-evaluating the pooled effects through a one-by-one elimination approach.

2.6 Sensitivity analysis

When heterogeneity was significant, low-quality studies were excluded in turns and meta-analyses were repeated. Results were compared and causes of heterogeneity were discussed.

2.7 Assessment of reporting bias

With enough preliminary research, funnel plots were generated to assess potential publication bias qualitatively when at least 10 articles were included. Funnel plots were visually inspected for asymmetry, and Egger test was used to perform sensitivity analysis and statistically assess publication bias. All statistical analyses were performed using RevMan5.3.

3 Results

A total of 1,514 studies were initially searched, and six additional articles were identified through manual searching. After evaluation by two independent reviewers (SXH and ZJW), 519 studies were excluded due to duplication. The titles and abstracts of the remaining 678 articles were reviewed, resulting in 151 articles selected for full-text review. Ultimately, 47 randomized controlled trials (RCTs) reported in these 47 articles were included for analysis and evaluated using the Jadad scale, which yielded quality ratings of high (4 studies), moderate (9 studies), and low (24 studies). The quality assessment of the included studies is presented in Table 1). After applying predefined inclusion criteria that restricted eligibility to moderate- and high-quality evidence, 13 RCTs were ultimately incorporated into the final analysis (13, 17, 21–31)., and the characteristics of the study selection process are shown in Figure 1. The 13 trials analyzed were all randomized controlled trials conducted in China and published in English and Chinese, respectively, between 2007 and 2023. Two of the trials (17, 24) had participants from six different hospitals in China and were multicenter randomized controlled trials, and the remaining trials (13, 21–23, 25–31) were all single-center randomized controlled trials. 1293 patients with MDD ranging in age from 42 to 60 years were included, with sample sizes varying between 58 and 222. Table 2 shows the detailed characteristics reported in the medical records. Eight studies (13, 17, 21, 22, 24, 26–28, 30) assessed depression-relieving effects by HAMD-17 scale, three studies (25, 29, 31) assessed depression-relieving effects by HAMD-24 scale, seven studies (22, 23, 25, 27–29, 31) assessed treatment effects of MDD by clinical validity, six studies (13, 17, 24, 29–31) assessed follicle-stimulating hormone (FSH) and estradiol (E2) levels, five studies (13, 17, 24, 30, 31) assessed luteinizing hormone (LH),three studies (23, 25, 26) assessed anxiety-relieving effects by SDS scale.

Table 1

Table 1. Quality assessment of included studies.

Table 2

Table 2. Characteristics of included studies.

3.1 Risk of bias

All studies (13, 17, 21–31) employed adequate methods for random sequence generation using a randomization table, and thus were rated as low risk for selection bias regarding random sequence generation. Six studies (13, 17, 24, 26, 27, 30) reported the use of opaque envelopes for allocation concealment, while seven studies (21–23, 25, 28, 29, 31) were rated as having an unclear risk of selection bias concerning allocation concealment, as they did not provide detailed information about the random number generation process. Three studies (13, 26, 30) utilized sham acupuncture in the control group, resulting in a low risk of performance bias. In contrast, the other studies (17, 21–25, 27–29, 31) were rated as high risk, as they were rated as being at low risk. Others studies (17, 21–25, 27–29, 31)were high risk as all were open-label studies without sham acupuncture, making participant blinding impossible by design. Five studies (13, 17, 24, 27, 30) reported blinding of outcome assessment, while the others did not; therefore, only these five studies were rated as low risk for detection bias, while the remaining studies were deemed to have an unclear risk. All studies reported all expected outcomes and data, leading to an evaluation of low risk for attrition bias. Additionally, all studies provided detailed information regarding reasons for dropouts, resulting in a judgment of low risk for reporting bias. Other sources of bias were considered low risk for all studies, as baseline information, findings, ethical approval, and additional details were fully reported. A summary of the overall risk of bias (RoB) assessment is presented in Figure 2, while the details of the RoB assessment are shown in Figure 3.

Figure 2

Figure 2. A summary of the overall RoB assessment.

Figure 3

Figure 3. Details of the RoB assessment.

3.2 Primary outcome

3.2.1 Clinical effectiveness rate

Among the included studies, seven investigations (22, 23, 25, 27–29, 31) evaluated the treatment effects of Major Depressive Disorder (MDD) based on clinical validity, encompassing a total of 457 cases: 228 in the experimental group and 229 in the control group. The heterogeneity test showed I² = 0% and a Q test P-value of 0.0001, indicating low inter-study heterogeneity. Using a fixed-effect model, the difference was found to be statistically significant (OR = 2.70, 95% CI [1.63, 4.48], Z = 3.86, P = 0.0001), suggesting that the efficacy of the experimental group was superior to that of the control group (Supplementary 1; Figure 1).

3.2.2 HAMD-17

Eight studies (13, 17, 21, 22, 24, 26–28, 30) utilized the Hamilton Depression Rating Scale (HAMD-17) as an outcome measure, encompassing a total of 808 cases: 413 in the experimental group and 395 in the control group. The heterogeneity test yielded an I² of 0% and a Q test result of P < 0.00001, indicating low inter-study heterogeneity. The difference was statistically significant using the fixed-effect model (SMD=-0.28,95% CI[-0.42, -0.14], Z=3.92, P<0.0001), indicating that the efficacy of the experimental group was superior to that of the control group (Supplementary 2; Figure 1).

3.2.3 HAMD-24

Three studies (25, 29, 31) utilized the Hamilton Depression Rating Scale (HAMD-24) as an outcome measure, encompassing a total of 208 cases, with 104 participants in the experimental group and 104 in the control group. The heterogeneity test yielded an I² of 68% and a Q test P-value of 0.01, indicating a high level of heterogeneity among the studies. The difference was statistically significant when applying the random effects model (SMD = -0.64, 95% CI [-1.15, 0.13], Z = 2.47, P = 0.01), suggesting that the efficacy of the experimental group was greater than that of the control group (Supplementary 3; Figure 1).

Sensitivity analysis indicated that after excluding the study by Gu (2018) (27), the remaining two studies included a total of 150 participants (74 in the intervention group and 76 in the control group). Heterogeneity among the studies was significantly reduced (I² = 23%, P = 0.03), which justified the application of a fixed-effect model (Table 3A; Sensitivity analysis). The meta-analysis revealed a statistically significant difference in HAMD-24 scores between the intervention group and the control group (SMD = -0.39, 95% CI [-0.72, -0.07], P = 0.03). The consistency between the fixed-effect and random-effects models further supported the robustness of this finding.

Table 3

Table 3. Sensitivity analysis.

3.2.4 SDS

Three studies (23, 25, 26) included a total of 188 cases, with 94 participants in the experimental group and 94 in the control group. The heterogeneity test yielded an I² of 95% and a Q test result of P = 0.004, indicating a high level of heterogeneity among the studies. The difference was statistically significant when analyzed using the random effects model (SMD = -2.64, 95% CI [-4.44, -0.84], Z = 2.83, P = 0.004), suggesting that the efficacy of the experimental group was greater than that of the control group (Supplementary 4; Figure 1).

Sensitivity analysis was conducted to investigate the sources of heterogeneity and evaluate the stability of the results for the SDS index. As shown in the sensitivity analysis table (Table 3B), eliminating individual studies did not reduce the heterogeneity to a low-level range (I² < 50%), indicating that the high heterogeneity among the studies was relatively robust (Table 3B; Sensitivity analysis).

3.3 Secondary endings

3.3.1 Sexual hormones

Regarding the assessment of serum sex hormone components (FSH, LH, E2) as secondary outcome indicators. Six studies (13, 17, 24, 29–31) assessed follicle-stimulating hormone (FSH) and estradiol (E2) and Five studies (3, 17, 24, 30, 31) assessed luteinizing hormone (LH), FSH and E2 levels totaling 713 cases, 363 in the experimental group and 350 in the control group. FSH levels heterogeneity test I² = 0%,Q test P=0.59, suggesting low inter-study heterogeneity, and the difference was not statistically significant using a fixed-effects model (SMD=-0.04,95% CI[-0.19,-0.11], Z=0.53,P=0.59). (Supplementary 5; Figure 1) E2 levels heterogeneity test I² = 0%,Q test P=0.89, suggesting low inter-study heterogeneity, and the difference was not statistically significant using a fixed-effects model (SMD=-0.01,95% CI [-0.16, 0.14],Z=0.14,P=0.89). (Supplementary 5; Figure 2) LH levels totaling 653 cases, 333 in the experimental group and 320 in the control group. heterogeneity test I² = 0%,Q test P=0.86, suggesting low inter-study heterogeneity, and the difference was not statistically significant using a fixed-effects model (SMD = -0.01,95% CI [-0.14, 0.17], Z=0.18, P=0.86).FSH, LH, E2 indicating that the efficacy of the experimental group was not statistically significant compared with that of the control group (Supplementary 5; Figure 3).

3.3.2 Adverse reactions

Among the studies included in the literature review, four studies (21, 24, 26, 30) reported a total of 414 adverse reactions in patients: 211 cases in the experimental group and 203 cases in the control group. The heterogeneity test yielded an I² of 83% and a Q test P-value of 0.05, indicating high inter-study heterogeneity. The difference in efficacy between the experimental and control groups was not statistically significant when analyzed using the random effects model (OR = 0.16, 95% CI [0.03, 0.98], Z = 1.99, P = 0.05). This suggests that there was no statistically significant difference in efficacy between the experimental group and the control group (Supplementary 6; Figure 1).

Sensitivity analysis excluding Li (2015) revealed reduced heterogeneity (I² = 34%, P = 0.08) among the remaining three studies (181 interventions vs. 173 controls). Fixed-effect model analysis indicated no statistically significant difference in adverse events (OR = 0.42, 95% CI [-0.15, 1.13], P = 0.08). Further exclusion of Li (2018) resulted in two studies (94 interventions vs. 92 controls) with decreased heterogeneity (I² = 65%, P = 0.007), demonstrating a statistically significant reduction in adverse events for the intervention group (OR = 0.08, 95% CI [0.01, 0.51], P = 0.007). Consistency between fixed-effect and random-effects models supported the robustness of this finding (Table 3C; Sensitivity Analysis).

3.3.3 MENQOL

Four studies (17, 23, 24, 30) evaluated the anxiety-relieving effects using the MENQOL scale, encompassing a total of 560 cases: 287 in the experimental group and 273 in the control group. The heterogeneity test yielded I² = 0% and a Q test P-value of 0.003, indicating low heterogeneity among the studies. The difference was statistically significant when applying the fixed-effect model (SMD = -0.25, 95% CI [-0.42, -0.09], Z = 2.98, P = 0.003), suggesting that the efficacy of the experimental group was greater than that of the control group (Supplementary 7; Figure 1).

3.3.4 KI

Among the studies included in the literature review, four studies (13, 22, 25, 28) reported a total of 250 cases of KI, with 126 cases in the experimental group and 124 cases in the control group. The heterogeneity test yielded an I² of 75% and a Q test P-value of 0.07, indicating high inter-study heterogeneity. The difference in efficacy between the experimental and control groups was not statistically significant when analyzed using the random effects model (SMD = -0.47, 95% CI [-0.98, 0.05], Z = 1.79, P = 0.07). This suggests that there was no statistically significant difference in efficacy between the experimental group and the control group(Supplementary 8; Figure 1).

Sensitivity analysis indicated that after excluding the study by Gu (2015) (27), the heterogeneity index decreased to I² = 28%, indicating low heterogeneity. However, the result remained statistically non-significant. Conversely, when removing Wang (2023) (13), the heterogeneity index decreased to I² = 67% (still indicating high heterogeneity), but the result became statistically significant (SMD = −0.65, 95% CI[−1.18, −0.13], Z = 2.42, P = 0.02) (Table 3D). This suggests that the Wang study had a notable impact on the statistical significance of the results, possibly due to differences in its control group interventions compared to those in other studies (Table 3D; Sensitivity analysis).

3.4 Subgroup analysis

We conducted subgroup analyses for three categorical indicators: A) the type of acupuncture in the experimental group, B) the type of control group, and C) the acupuncture sites, as shown in Table 4.

Table 4

Table 4. Results of the analysis of individual outcome indicators and their subgroups.

3.4.1 Subgroup analysis of HAMD-24

The type of acupuncture used in the experimental group.

The pooled analysis for the EA subgroup revealed no significant difference between the experimental group and the control group (SMD = -0.24, 95% CI [-0.66, 0.17], P = 0.25), and heterogeneity was not applicable. In contrast, the pooled results for the MA subgroup indicated a significant effect favoring the experimental group (SMD = -0.87, 95% CI [-1.36, -0.37], P = 0.0006), with low heterogeneity (I² = 41%). The test for subgroup differences demonstrated a non-significant trend toward a difference (I² = 72.4%, P = 0.06).

Control Group Type

The pooled analysis of the CHM subgroup revealed a significant effect favoring the experimental group (SMD = -0.87, 95% CI [-1.36, -0.37], P = 0.0006), with low heterogeneity (I² = 41%). In the subgroup of other medications, no significant difference was observed between the experimental group and the controls (SMD = -0.24, 95% CI [-0.66, 0.17], P = 0.25), and heterogeneity was not applicable. The test for subgroup differences indicated a trend toward a difference that was not statistically significant (I² = 72.4%, P = 0.06).

3.4.2 Subgroup analysis of SDS

Acupuncture Points

The pooled analysis of the simple abdominal acupuncture subgroup revealed a significant effect favoring the experimental group (SMD = -1.12, 95% CI [-1.65, -0.58], P < 0.0001), with no observed heterogeneity (I² = 0%). In contrast, the pooled results for the non-simple abdominal acupuncture subgroup also indicated a significant effect in favor of the experimental group (SMD = -3.47, 95% CI [-6.62, -0.31], P = 0.03), but exhibited high heterogeneity (I² = 96%). The test for subgroup differences indicated no statistically significant difference (I² = 51.8%, P = 0.15).

3.4.3 Subgroup analysis of adverse reactions

The type of acupuncture used in the experimental group.

The meta-analysis of the EA subgroup, which included two studies, demonstrated significant heterogeneity (I² = 94%). The results from the analysis using a random-effects model indicated no significant difference in efficacy between the EA group and the conventional drug group for the condition (OR = 0.11, 95% CI [0.00, 5.18], P = 0.26). In contrast, the MA subgroup, comprising two studies, showed no statistical heterogeneity (I² = 0%). The results from the fixed-effects model indicated a significant difference in efficacy between the MA group and the conventional medication group for the condition (OR = 0.19, 95% CI [0.05, 0.73], P = 0.02). Furthermore, the test for subgroup differences revealed no statistically significant difference between the subgroups (I² = 0%, P = 0.78).

Acupuncture Points

In the subgroup analysis of simple abdominal acupuncture, the study found no significant difference (OR = 0.32, 95% CI [0.03, 3.28], P = 0.34), and there was no evidence of heterogeneity. In the non-simple abdominal acupuncture subgroup, the pooled results suggested a non-significant trend (OR = 0.13, 95% CI [0.01, 1.28], P = 0.08), but this subgroup exhibited high heterogeneity (I² = 89%). The test for subgroup differences indicated no significant variation (I² = 0%, P = 0.58).

Control Group Type

The results of the subgroup analysis, categorized by the types of control groups, were consistent with those based on the acupuncture sites.

3.4.4 Subgroup analysis of KI

Control Group Type

The pooled analysis for the CHM subgroup demonstrated significantly superior efficacy of the intervention group compared to the control group (SMD = -0.85, 95% CI [-1.53, -0.06], P = 0.02), with moderate heterogeneity (I² = 70%). In the other medicine subgroup, the intervention group showed no significant difference (SMD = -0.28, 95% CI [-0.80, 0.24], P = 0.29), and heterogeneity was not applicable. In the sham acupuncture subgroup, the intervention group also exhibited no significant difference (SMD = 0.07, 95% CI [-0.40, 0.54], P = 0.78), and heterogeneity was not applicable. The overall analysis indicated no significant effect of the intervention (SMD = -0.47, 95% CI [-0.98, 0.05], P = 0.07), with significant heterogeneity (I² = 75%). Subgroup differences were not statistically significant (I² = 57.2%, P = 0.10).

Acupuncture Points

The pooled analysis of the simple abdominal acupuncture subgroup revealed no significant difference in efficacy between the intervention group and the control group (SMD = -0.28, 95% CI [-0.80, 0.24], P = 0.29), and heterogeneity was not applicable. In the non-simple abdominal acupuncture subgroup, the intervention group exhibited a non-significant trend toward superiority (SMD = -0.54, 95% CI [-1.25, 0.17], P = 0.14) with high heterogeneity (I² = 83%). The overall analysis indicated no significant effect of the intervention (SMD = -0.47, 95% CI [-0.98, 0.05], P = 0.07), but significant heterogeneity was present (I² = 75%). Subgroup differences were not statistically significant (I² = 0%, P = 0.57).

3.4.5 Subgroup analysis of sexual hormones

In the subgroup analyses of follicle-stimulating hormone (FSH), estradiol (E2), and luteinizing hormone (LH) in the meta-analysis, regardless of whether the subgrouping was based on the type of acupuncture in the experimental group or the type of control group, the heterogeneity was found to be 0%, and the p-values were all greater than 0.05. The results of the fixed-effects modeling indicated that the efficacy of the experimental group was not statistically significant when compared to that of the control group.

4 Discussion

4.1 Main findings

This systematic review presents a meta-analysis evaluating the efficacy of acupuncture for menopausal depressive disorder (MDD). Following PRISMA guidelines, our findings indicate that acupuncture significantly outperforms control interventions in improving clinical effectiveness rates (OR=2.70, 95% CI [1.63, 4.48], P=0.0001) and in reducing depressive symptoms, as evidenced by HAMD-17 (SMD=-0.28, P<0.0001) and HAMD-24 scores (post-sensitivity SMD=-0.39, P=0.03). Notably, acupuncture also improved quality of life, as measured by the Menopause Quality of Life Questionnaire (MENQOL) (SMD=-0.25, P=0.003), although its effects on sex hormones (FSH, LH, E2) were not statistically significant (P>0.05). The safety profiles were comparable between groups (OR=0.16, P=0.05); however, sensitivity analysis revealed a reduction in adverse events in the acupuncture group after excluding outlier studies (OR=0.49, P=0.03). In conclusion, the ins is a beneficial intervention MDD.

Acupuncture, as a non-pharmacological intervention, avoids many potential side effects associated with drug therapies and offers a novel treatment approach for patients experiencing menopausal depression. Among the 13 studies included in this review, 11 (84.6%) were conducted after 2010, indicating a growing trend in acupuncture research in recent years. This trend reflects a shift in current clinical needs: while existing guidelines recommend antidepressants and psychotherapy as first-line treatments (11), conventional medicine primarily utilizes estrogen replacement therapy, oral antidepressants, or a combination of both. Although these therapies have demonstrated proven efficacy for menopausal depressive disorder (MDD), long-term use may increase the risks of breast cancer, endometrial cancer, and cardiovascular diseases (32–34), adversely affecting patients’ quality of life and reducing medication compliance. Given that menopause represents a high-risk period for depressive episodes in women, intervention studies targeting this population hold significant clinical importance.

4.2 Analysis of sources of heterogeneity and discussion of results from subgroup analysis

4.2.1 HAMD-24

The heterogeneity observed in the HAMD-24 outcomes may primarily stem from significant variations in acupoint selection across trials and limitations in sample size. Although subgroup analysis isolated the study by Zhang (2010) (30) due to discrepancies in control group design, their findings nonetheless demonstrated the superior efficacy of electroacupuncture (EA) over conventional pharmacotherapy in alleviating core HAMD-24 factors such as anxiety/somatization and cognitive impairment (P < 0.01) (30), suggesting symptom-specific therapeutic advantages of EA. Sensitivity analysis revealed a marked reduction in heterogeneity (I² decreased from 68% to 23% following the exclusion of Gu et al. (2022) (27). Upon reviewing the entire text, we found that this study (27) employed distinct acupoints, notably the “Thirteen Ghost Points” (e.g., GV26 and LU11), which are hypothesized to modulate the neuro-endocrine-immune network and rebalance neurotransmitter levels. In contrast, the other two trials (23, 30) utilized traditional acupoints associated with visceral regulation (e.g., GV20 and SP6), focusing on neuroendocrine system modulation and holistic functional improvement through endocrine balance and monoaminergic enhancement. These discrepancies in therapeutic mechanisms—rooted in divergent acupoint selection—likely contributed to the variability in outcomes. Furthermore, the limited number of included studies (n=3) and small sample sizes may have exacerbated methodological heterogeneity. Future investigations should prioritize standardized acupoint protocols and larger cohorts to minimize confounding factors and enhance the generalizability of results.

4.2.2 SDS

The sensitivity analysis of the SDS indicates that the high heterogeneity observed was relatively stable and not solely attributable to any single study. Notably, after excluding Gu 2018 (27), the heterogeneity decreased from 95% to 75%, yet it remained high. This suggests that the elevated heterogeneity may not be due to bias from a single study, but rather could stem from small sample sizes or other contributing factors. It is also noteworthy that the three studies (25, 27, 28) exhibiting high heterogeneity all utilized a combination of acupuncture and medication, in contrast to the control group, which relied solely on traditional Chinese medicine. Despite the persistent heterogeneity, the statistical significance of the results was partially maintained, indicating that the conclusion—that the experimental group demonstrated greater efficacy than the control group—exhibited a certain degree of stability. This implies that, even in the presence of heterogeneity, the overall trend of the experimental group showing superior efficacy compared to the control group remained consistent across the analyses. However, the high heterogeneity still necessitates caution in interpreting the results and underscores the need for further research to elucidate the underlying reasons.

4.2.3 Adverse reactions

The analysis of adverse reactions shows notable differences between electroacupuncture (EA) and manual acupuncture (MA), which are closely related to the nature of these treatments. EA uses electrical currents to activate acupoints, and while factors like intensity and frequency can be modified, inconsistencies in these parameters across various studies can affect treatment effectiveness and increase variability. On the other hand, manual acupuncture depends on the techniques used by the practitioner. Although there are individual differences in technique, it allows for more flexibility and is not constrained by fixed parameters, leading to less variability. Additionally, variations in patients’ sensitivity to EA’s electrical stimulation—such as discomfort from excessive stimulation—can further increase variability. In contrast, the gentler needle stimulation of manual acupuncture is more adaptable and tends to result in fewer adverse reactions.

4.2.4 KI

The differences seen in the KI scale could be due to the varying acupuncture locations and the types of control groups utilized. In the research by Gu et al., the acupuncture points were chosen based on Sun Simiao’s Thirteen Ghost Points, which specifically help in emotional regulation. This approach contrasts with the other three studies, which focused on acupuncture points aimed at balancing Qi and blood, harmonizing the zang-fu organs, and addressing menopausal symptoms in general. When Gu et al.’s study is excluded, the other three studies show more uniformity in both the acupuncture points used and their theoretical underpinnings, leading to a decrease in heterogeneity. Subgroup analysis indicates that when the control group involves medication, the intervention group demonstrates better efficacy. However, no statistical significance is found when comparing the acupuncture group with the sham acupuncture group. Further analysis reveals that the study by Zhao et al. (2023) focused on a single condition and did not cover somatic symptoms included in the KI scale, such as vasomotor symptoms, leading to insignificant improvements in KI. In contrast, the other three studies directly targeted core symptoms assessed by the KI scale, such as hot flashes and physical discomfort, and enhanced efficacy through multi-target regulation (acupuncture plus herbal medicine), indicating that the alignment of intervention measures with the KI assessment and the use of integrated treatment approaches are crucial factors influencing efficacy.

4.2.5 Sexual hormones

Although the forest plots for FSH, E2, and LH demonstrated negligible heterogeneity (I² = 0%), subgroup analyses were conducted to investigate whether potential biases in the included studies influenced these outcomes. Subgroup stratification based on acupuncture type (e.g., MA vs. EA) and control group interventions (e.g., CHM vs. other medications) consistently revealed no statistically significant differences between the intervention and control groups across all three hormonal markers (P > 0.05). These findings preliminarily suggest that the lack of intergroup differences is unlikely attributable to variations in acupuncture protocols or control group designs. Further exploration is warranted to elucidate the underlying mechanisms contributing to the nonsignificant outcomes.

It has been shown that fluctuations in FSH and LH may lead to changes in hot flashes, bones, vascular endothelium, atherosclerosis, and lipid metabolism in women, which in turn affects quality of life (35). Although depression is a common clinical condition in menopausal women, not all women develop depression, and women with significant hormonal fluctuations and sensitivity to hormonal changes are more likely to develop depression (36, 37). According to second-generation cognitive theory, environment, physiology, and mood are recognized as important factors influencing cognitive functioning, which, in turn, directly affects the development of depression (38, 39). The dominant factor in menopausal depression is changes in cognitive functioning, influenced by changes in hormones, clinical symptoms and quality of life. This influence may dominate the onset and progression of depression. Although the beneficial effects of acupuncture on menopausal depression may be related to the modulation of sex hormones, this hypothesis still needs to be tested by a more rigorous experimental design.

There are several reasons why no significant differences were observed in FSH, E2, and LH levels between the intervention and control groups. First, regarding efficacy equivalence, EA, Western medications (hormone replacement + antidepressants), and traditional Chinese medicine all regulate sex hormone levels with comparable effects, showing no statistical differences. The direct impact of Western drugs (e.g., fluoxetine, nilestriol) on hormone levels may counteract intergroup differences (23, 30). Second, regarding non-hormone-dependent mechanisms, EA may improve depression by regulating neurotransmitters (such as 5-HT, NE) or brain neural circuits (HPA axis) rather than directly acting on hormones (15, 24, 26). Acupuncture may alleviate depression indirectly by improving quality of life (MENQOL), sleep, or anxiety symptoms, with hormones serving only as “initiating factors” (13, 17). Third, due to physiological irreversibility, the decline in E2 and elevation in FSH/LH caused by perimenopausal ovarian dysfunction are natural processes that interventions cannot reverse (13, 26). Traditional Chinese medicine theory emphasizes that acupuncture helps establish a new balance through “harmonizing yin and yang” rather than opposing physiological trends (13, 40). Fourth, limitations in study design, such as small sample sizes or short follow-up periods (e.g., 8–12 weeks), make it difficult to capture subtle hormonal changes (17, 23). Multicenter trials or differences in menopausal stages (early/late transition) may lead to data dispersion in hormone levels (26), while limited hormone detection time points (e.g., only baseline and post-treatment) may miss fluctuating effects (13). Finally, mediating variable effects suggest that hormonal fluctuations induce depression indirectly by reducing quality of life (e.g., hot flashes, insomnia) rather than through direct associations (17), and the placebo effect of sham acupuncture may partially offset intergroup differences in hormones (13).

4.3 Research strengths and limitations

This meta-analysis presents several key strengths that enhance its scientific rigor and translational value. First, by extending systematic database searches through 2025, it incorporates the most up-to-date evidence on menopausal depression, surpassing prior meta-analyses (41, 42) that typically capped data retrieval at 2021. This temporal expansion ensures the inclusion of recent advancements in diagnostic criteria, intervention modalities, and outcome measures, providing a contemporary synthesis of the evolving field. Second, methodological quality was prioritized using the JADAD scale, with only moderate-to-high-quality studies (tu on the 5-point scale) included. This effectively minimizes bias from low-quality designs (e.g., non-randomized trials, unclear blinding). This rigorous selection criterion strengthens the reliability of pooled estimates compared to earlier analyses with heterogeneous study quality. Third, the study broadens the traditional focus on perimenopausal depression to encompass the entire menopausal spectrum, including perimenopausal, menopausal, and postmenopausal stages. This inclusive approach captures the diverse presentation of depression across reproductive aging phases, aligning with clinical guidelines that recognize menopausal depression as a multistage condition. Collectively, these strengths position the analysis as a robust, evidence-driven resource, combining temporal relevance, methodological rigor, and analytical depth to inform clinical practice and future research in menopausal mental health.

This meta-analysis has several limitations. First, the relatively small number of included trials (n = 13) and participants (N = 1,293) may reduce statistical power and limit the generalizability of the findings.

Second, despite subgroup analyses stratified by acupuncture sites, significant heterogeneity in intervention protocols (e.g., electroacupuncture parameters, needle retention time) and control group designs (e.g., sham acupuncture versus pharmacotherapy) may obscure true effect sizes. This variability likely reflects divergent biological responses to different therapeutic modalities rather than random error, complicating the interpretation of pooled results.

5 Conclusions

This systematic review indicates that acupuncture is a safe and effective non-drug treatment for reducing depressive symptoms during menopause and enhancing quality of life. While acupuncture did not significantly change sex hormone levels, its positive effects are likely due to non-hormonal processes, such as the regulation of neurotransmitters and the modulation of the neuroendocrine system. However, the review has limitations, including a small number of studies, methodological differences (like variations in acupoint selection and stimulation techniques), and small participant groups, which may limit the applicability of the results. Future studies should focus on large, standardized trials that include objective biomarkers and long-term follow-up to better understand the mechanisms involved and improve clinical practices, ultimately offering safer and more varied treatment options for menopausal depression.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author.

Author contributions

SH: Data curation, Investigation, Visualization, Writing – original draft, Writing – review & editing. ZW: Data curation, Investigation, Methodology, Software, Writing – original draft. SD: Formal Analysis, Project administration, Validation, Writing – original draft. YD: Writing – original draft. HQ: Investigation, Software, Validation, Visualization, Writing – review & editing. XL: Methodology, Validation, Visualization, Writing – review & editing. XG: Conceptualization, Funding acquisition, Investigation, Project administration, Resources, Supervision, Validation, Writing – original draft, Writing – review & editing.

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. This research was funded by the Humanities and Social Sciences Research Planning Project of Heilongjiang Province, grant number 23SHD138.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declare that no Generative AI was used in the creation of this manuscript.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyt.2025.1591389/full#supplementary-material

Supplementary 1 | Clinical effectiveness rate.

Supplementary 2 | HAMD-17.

Supplementary 3 | HAMD-24.

Supplementary 4 | SDS.

Supplementary 5 | Sexual hormones.

Supplementary 6 | Adverse reactions.

Supplementary 7 | MENQOL.

Supplementary 8 | KI.

Supplementary 9 | Search strategy.

Abbreviations

RCTs, Randomized Controlled Trials; WMD, Weighted Mean Difference; CI, Confidence Interval; SMD, Standard Mean Difference; HAMD, the Hamilton Depression Rating Scale; MENQOL, the menopause-specific quality of life scale; SDS, self-rating depression scale; KI, Kupperman Index; PSQI, Pittsburgh Sleep Quality Index; FSH, Follicle-stimulating hormone; LH, luteinizing hormone; E2, estrogen; STRAW, Stages of Reproductive Aging Workshop; ICD-10, The International Classification of Diseases-Ten Edition; ICSD-3, International Classification of Sleep Disorders Third Edition; CHM, Chinese herbal medicine; MA, Manual Acupuncture; EA, Electroacupuncture; SA, Sham Acupuncture; MDD, Menopausal depressive disorder.

References

1. Strand NH, D’Souza RS, Gomez DA, Whitney MA, Attanti S, Anderson MA, et al. Pain during menopause. Maturitas. (2025) 191:108135. doi: 10.1016/j.maturitas.2024.108135

PubMed Abstract | Crossref Full Text | Google Scholar

2. Avis NE, Crawford SL, Greendale G, Bromberger JT, Everson-Rose SA, Gold EB, et al. Duration of menopausal vasomotor symptoms over the menopause transition. JAMA Intern Med. (2015) 175:531–9. doi: 10.1001/jamainternmed.2014.8063

PubMed Abstract | Crossref Full Text | Google Scholar

3. Schoenaker DA, Jackson CA, Rowlands JV, and Mishra GD. Socioeconomic position, lifestyle factors and age at natural menopause: a systematic review and meta-analyses of studies across six continents. Int J Epidemiol. (2014) 43:1542–62. doi: 10.1093/ije/dyu094

PubMed Abstract | Crossref Full Text | Google Scholar

4. Roelfsema F, Pijl H, Keenan DM, and Veldhuis JD. Diminished adrenal sensitivity and ACTH efficacy in obese premenopausal women. Eur J Endocrinol. (2012) 167:633–42. doi: 10.1530/EJE-12-0592

PubMed Abstract | Crossref Full Text | Google Scholar

5. Li XL, Lin GY, Li KQ, Zhu LJ, Xu LW, and Li SN. A meta-analysis on the incidence rate of depression in Chinese menopausal women. BMC Psychiatry. (2025) 25:154. doi: 10.1186/s12888-025-06603-y

PubMed Abstract | Crossref Full Text | Google Scholar

6. Harlow SD, Gass M, Hall JE, Lobo R, Maki P, Rebar RW, et al. Executive summary of the Stages of Reproductive Aging Workshop + 10: addressing the unfinished agenda of staging reproductive aging. J Clin Endocrinol Metab. (2012) 97:1159–68. doi: 10.1210/jc.2011-3362

PubMed Abstract | Crossref Full Text | Google Scholar

7. Liang G, Kow ASF, Yusof R, Tham CL, Ho YC, and Lee MT. Menopause-associated depression: impact of oxidative stress and neuroinflammation on the central nervous system-A review. Biomedicines. (2024) 12:184. doi: 10.3390/biomedicines12010184

PubMed Abstract | Crossref Full Text | Google Scholar

8. Kulkarni J, Gurvich C, Mu E, Molloy G, Lovell S, Mansberg G, et al. Menopause depression: Under recognised and poorly treated. Aust N Z J Psychiatry. (2024) 58:636–40. doi: 10.1177/00048674241253944

PubMed Abstract | Crossref Full Text | Google Scholar

9. Jia Y, Zhou Z, Xiang F, Hu W, and Cao X. Global prevalence of depression in menopausal women: A systematic review and meta-analysis. J Affect Disord. (2024) 358:474–82. doi: 10.1016/j.jad.2024.05.051

PubMed Abstract | Crossref Full Text | Google Scholar

10. Tang R, Luo M, Li J, Peng Y, Wang Y, Liu B, et al. Symptoms of anxiety and depression among Chinese women transitioning through menopause: findings from a prospective community-based cohort study. Fertil Steril. (2019) 112:1160–71. doi: 10.1016/j.fertnstert.2019.08.005

PubMed Abstract | Crossref Full Text | Google Scholar

11. Maki PM, Kornstein SG, Joffe H, Bromberger JT, Freeman EW, Athappilly G, et al. Guidelines for the evaluation and treatment of perimenopausal depression: summary and recommendations. J Womens Health (Larchmt). (2019) 28:117–34. doi: 10.1089/jwh.2018.27099.mensocrec

PubMed Abstract | Crossref Full Text | Google Scholar

12. Brown L, Hunter MS, Chen R, Crandall CJ, Gordon JL, Mishra GD, et al. Promoting good mental health over the menopause transition. Lancet. (2024) 403:969–83. doi: 10.1016/S0140-6736(23)02801-5

PubMed Abstract | Crossref Full Text | Google Scholar

13. Zhao FY, Fu QQ, Spencer SJ, Kennedy GA, Conduit R, Zhang WJ, et al. Acupuncture: A promising approach for comorbid depression and insomnia in perimenopause. Nat Sci Sleep. (2021) 13:1823–63. doi: 10.2147/NSS.S332474

PubMed Abstract | Crossref Full Text | Google Scholar

14. Jiang H, Zhang X, Wang Y, Zhang H, Li J, Yang X, et al. Mechanisms underlying the antidepressant response of acupuncture via PKA/CREB signaling pathway. Neural Plast. (2017) 2017:4135164. doi: 10.1155/2017/4135164

PubMed Abstract | Crossref Full Text | Google Scholar

15. Wu YY, Jiang YL, He XF, Zhao XY, Shao XM, Sun J, et al. 5-HT in the dorsal raphe nucleus is involved in the effects of 100-Hz electro-acupuncture on the pain-depression dyad in rats. Exp Ther Med. (2017) 14:107–14. doi: 10.3892/etm.2017.4479

PubMed Abstract | Crossref Full Text | Google Scholar

16. Yang NN, Lin LL, Li YJ, Li HP, Cao Y, Tan CX, et al. Potential mechanisms and clinical effectiveness of acupuncture in depression. Curr Neuropharmacol. (2022) 20:738–50. doi: 10.2174/1570159X19666210609162809

PubMed Abstract | Crossref Full Text | Google Scholar

17. Zhou JH, Zhang DL, Ning BL, Xue XJ, Zhao L, Wu Q, et al. The role of acupuncture in hormonal shock-induced cognitive-related symptoms in perimenopausal depression: A randomized clinical controlled trial. Front Psychiatry. (2022) 12:772523. doi: 10.3389/fpsyt.2021.772523

PubMed Abstract | Crossref Full Text | Google Scholar

18. Avis NE, Coeytaux RR, Isom S, Prevette K, and Morgan T. Acupuncture in Menopause (AIM) study: a pragmatic, randomized controlled trial. Menopause. (2016) 23:626–37. doi: 10.1097/GME.0000000000000597

PubMed Abstract | Crossref Full Text | Google Scholar

19. Jadad AR, Moore RA, Carroll D, Jenkinson C, Reynolds DJ, Gavaghan DJ, et al. Assessing the quality of reports of randomized clinical trials: is blinding necessary? Control Clin Trials. (1996) 17:1–12. doi: 10.1016/0197-2456(95)00134-4

PubMed Abstract | Crossref Full Text | Google Scholar

20. Higgins JP, Altman DG, Gøtzsche PC, Jüni P, Moher D, Oxman AD, et al. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ. (2011) 343:d5928. doi: 10.1136/bmj.d5928

PubMed Abstract | Crossref Full Text | Google Scholar

21. Qian J, Zhang J, Pei Y, and Chen J. Clinical observation of Wang’s five Zangshu plus Geshu points in treating menopausal depression. Beijing J Tradit Chin Med. (2007) 8):491–2. doi: 10.16025/j.1674-1307.2007.08.011

Crossref Full Text | Google Scholar

22. Deng AJ. Bo’s abdominal acupuncture for menopausal depression: A randomized controlled clinical trial. Guangzhou University of Chinese Medicine, Guangzhou (2008).

Google Scholar

23. Chen GZ. Clinical study on the effect of traditional Chinese medicine combined with acupuncture on menopausal depression. Guangzhou University of Chinese Medicine, Guangzhou (2010).

Google Scholar

24. Li ZF. Clinical study of electroacupuncture in the treatment of mild-to-moderate depressive disorders during perimenopause. Guangzhou University of Chinese Medicine, Guangzhou (2015).

Google Scholar

25. Wang C, Bai YF, Fu WB, and He YH. Clinical efficacy of acupuncture at four extraordinary meridians points for depressive status in perimenopausal women. Chin J Gerontol. (2015) 35:3390–2. doi: 10.3969/j.issn.1005-9202.2015.12.096

Crossref Full Text | Google Scholar

26. Li S, Li ZF, Wu Q, Guo XC, Xu ZH, Li XB, et al. A multicenter, randomized, controlled trial of electroacupuncture for perimenopause women with mild-moderate depression. Biomed Res Int. (2018) 2018:5351210. doi: 10.1155/2018/5351210

PubMed Abstract | Crossref Full Text | Google Scholar

27. Gu T, Wang RH, Wu T, Ke ZH, Yang H, and Wang D. Clinical observation on acupuncture at thirteen ghost points combined with Kaixin Powder for mild perimenopausal depression. Chin Acupunct Moxibustion. (2020) 40:267–71. doi: 10.13703/j.0255-2930.20190308-0005

PubMed Abstract | Crossref Full Text | Google Scholar

28. Wang J, Liao Y, You Y, Liang W, Wan L, Yang H, et al. Acupuncture and Chinese herbal medicine for menopausal mood disorder: a randomized controlled trial. Climacteric. (2023) 26:392–400. doi: 10.1080/13697137.2023.2187284

PubMed Abstract | Crossref Full Text | Google Scholar

29. Wang XY, Li XY, Dang YJ, and Bo ZY. Comparative study on the efficacy of abdominal acupuncture and western medicine in the treatment of depression in menopausal women. Chin Acupunct Moxibustion. (2010) 30:913–7. doi: 10.13703/j.0255-2930.2010.11.026

Crossref Full Text | Google Scholar

30. Zhang YL. Effects of electroacupuncture on Hamilton scores and sex hormone levels in menopausal depression patients. Shaanxi University of Chinese Medicine, Xianyang (2010). doi: 10.7666/d.d127648

Crossref Full Text | Google Scholar

31. Liu XY. Clinical efficacy of acupuncture-medicine combination based on Qijie-Sihai theory for perimenopausal depression with Qi deficiency and blood stasis syndrome. Liaoning University of Traditional Chinese Medicine, Shenyang (2022).

Google Scholar

32. Zhu LJ, Xu LW, Li KQ, and Li SN. Progress in the pathogenesis of perimenopausal depression and its prevention and treatment by traditional Chinese medicine. Chin J Exp Form. (2024) 30:252–61. doi: 10.13422/j.cnki.syfjx.20240443

Crossref Full Text | Google Scholar

33. Shufelt CL and Manson JE. Menopausal hormone therapy and cardiovascular disease: the role of formulation, dose, and route of delivery. J Clin Endocrinol Metab. (2021) 106:1245–54. doi: 10.1210/clinem/dgab042

PubMed Abstract | Crossref Full Text | Google Scholar

34. Toffol E, Heikinheimo O, and Partonen T. Hormone therapy and mood in perimenopausal and postmenopausal women: a narrative review. Menopause. (2015) 22:564–78. doi: 10.1097/GME.0000000000000323

PubMed Abstract | Crossref Full Text | Google Scholar

35. Rance NE, Dacks PA, Mittelman-Smith MA, Romanovsky AA, and Krajewski-Hall SJ. Modulation of body temperature and LH secretion by hypothalamic KNDy (kisspeptin, neurokinin B and dynorphin) neurons: a novel hypothesis on the mechanism of hot flushes. Front Neuroendocrinol. (2013) 34:211–27. doi: 10.1016/j.yfrne.2013.07.003

PubMed Abstract | Crossref Full Text | Google Scholar

36. Payne JL, Palmer JT, and Joffe H. A reproductive subtype of depression: conceptualizing models and moving toward etiology. Harv Rev Psychiatry. (2009) 17:72–86. doi: 10.1080/10673220902899706

PubMed Abstract | Crossref Full Text | Google Scholar

37. Vivian-Taylor J and Hickey M. Menopause and depression: is there a link? Maturitas. (2014) 79:142–6. doi: 10.1016/j.maturitas.2014.05.014

PubMed Abstract | Crossref Full Text | Google Scholar

38. Zatti A and Zarbo C. Embodied and exbodied mind in clinical psychology. A proposal for a psycho-social interpretation of mental disorders. Front Psychol. (2015) 6:236. doi: 10.3389/fpsyg.2015.00236

PubMed Abstract | Crossref Full Text | Google Scholar

39. Kaletsch M, Pilgramm S, Bischoff M, Kindermann S, Sauerbier I, Stark R, et al. Major depressive disorder alters perception of emotional body movements. Front Psychiatry. (2014) 5:4. doi: 10.3389/fpsyt.2014.00004

PubMed Abstract | Crossref Full Text | Google Scholar

40. Zhu X, Liew Y, and Liu ZL. Chinese herbal medicine for menopausal symptoms. Cochrane Database Syst Rev. (2016) 3:Cd009023. doi: 10.1002/14651858

PubMed Abstract | Crossref Full Text | Google Scholar

41. Zhao FY, Fu QQ, Spencer SJ, Kennedy GA, Conduit R, Zhang WJ, et al. Acupuncture as an independent or adjuvant management to standard care for perimenopausal depression: A systematic review and meta-analysis. Front Psychiatry. (2021) 12:666988. doi: 10.3389/fpsyt.2021.666988

PubMed Abstract | Crossref Full Text | Google Scholar

42. Di YM, Yang L, Shergis JL, Zhang AL, Li Y, Guo X, et al. Clinical evidence of Chinese medicine therapies for depression in women during perimenopause and menopause. Compl Ther Med. (2019) 47:102071. doi: 10.1016/j.ctim.2019.03.019

PubMed Abstract | Crossref Full Text | Google Scholar