Comparison of Symptoms Between Midlife Women in Peri-menopause and Post-menopause Using Network Comparison Test

doi:10.21203/rs.3.rs-1616757/v1

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Comparison of Symptoms Between Midlife Women in Peri-menopause and Post-menopause Using Network Comparison Test

https://doi.org/10.21203/rs.3.rs-1616757/v1

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Introduction.

Midlife women in peri-menopause and post-menopause experience a complex array of symptoms. However, there are conflicting results on how their symptom experience differs by menopausal stage. Current studies have not examined the interconnected relationship among menopausal symptoms and understood how this relationship may differ based on the menopausal stage.

Purpose.

This study aims to examine and compare the symptom network structure and key symptoms between midlife women in peri-menopause and post-menopause.

Method.

This is a secondary data analysis using cross-sectional data (visit 5) from the Study of Women’s Health Across the Nation. Network analysis was used to visualize the network structure and to identify key symptoms. Then, network comparison test was conducted to compare the symptom network properties. Propensity score matching was used to match participants in terms of their covariates.

Result.

In midlife women in peri-menopause, frequent mood change was the key symptom with the highest strength (1.59) and closeness (1.28). In midlife women in post-menopause, night sweat was the key symptom with the highest strength (1.35) and betweenness (1.82). The symptom networks were not significantly different between the two groups in terms of global strength (S = 0.01, p = 0.974), network structure (M = 0.10, p = 0.461), and specific centrality measure (C=-0.10, p = 0.083).

Conclusion.

While the symptom networks were not invariant, the key symptoms were different between the two groups. This indicates a potential need for different symptom management approach in midlife women in peri-menopause and post-menopause. With this new knowledge, clinicians should offer targeted key symptom assessment and management in clinical settings.

Menopause

Midlife

Symptoms

Women's Health

With natural aging, midlife women enter into peri-menopause and post-menopause (Taechakraichana et al., 2002). Herein, the female reproductive life course is broadly classified into three main stages that include pre-menopause, peri-menopause, and post-menopause. Pre-menopause refers to a period of regular menstrual cycle with no change in cycle regularity or length (Butler & Santoro, 2011). However, hormonal changes such as an increase in follicle-stimulating hormone (FSH) and drop in estrogen and progesterone, begin with peri-menopause and continue through post-menopause (El Khoudary et al., 2019). Peri-menopause is a period of time when a woman has irregular menstrual cycles or skips a menstrual cycle (Butler & Santoro, 2011; El Khoudary et al., 2019). Post-menopause is a period of time when a woman has not had a menstrual cycle for more than 12 months in a row (Butler & Santoro, 2011; El Khoudary et al., 2019). Midlife peri-menopausal and post-menopausal women experience more prevalent and severe symptoms than pre-menopausal women as they experience decline in their ovarian and function, with varying degrees of severity (Greenblum et al., 2013; Taechakraichana et al., 2002). These symptoms include vasomotor symptoms, psychological symptoms, somatic symptoms, and sexual symptoms, all of which adversely affect the health-related quality of life in many midlife women (Greenblum et al., 2013; Kaunitz & Manson, 2015).

To date, research studies support the complex symptoms experienced by midlife women in peri-menopause and post-menopause (Augoulea et al., 2019; Greenblum et al., 2013; Mulhall et al., 2018). However, there are conflicting results on how their symptom experience differs by menopausal stage (peri-menopause, post-menopause). For example, a recent study found that peri-menopause was associated with an increased risk of greater symptoms of depression and post-menopause with greater symptoms of anxiety (Mulhall et al., 2018). In contrast, an epidemiological study reported a higher severity in anxiety symptoms and lower severity in depressive symptoms during peri-menopause (Tangen & Mykletun, 2008). Such mixed findings are evident in other types of symptoms such as sexual symptoms. A cross-sectional study found that post-menopausal women experienced more severe sexual symptoms than peri-menopausal women (Vanwesenbeeck et al., 2001). On the other hand, a multi-ethnic study yielded different finding that peri-menopausal women experienced more sexual symptoms (i.e. loss of sexual interest) among Australian and Japanese women (Anderson et al., 2004). As a result, there is still a lack of understanding on the different symptom experience related to their menopausal stage in midlife women.

Traditional statistical methodologies such as regression models have been widely used to examine the relationship between symptoms and menopausal stage in midlife women (Hevey, 2018; Mulhall et al., 2018). While they offer important findings, these methodologies are not suitable for examining the interconnected relationship among symptoms and understanding how this interconnected relationship may differ based on the menopausal stage (Hevey, 2018). To fulfill this gap, network analysis may address the shortcomings of more simplistic methods by using the following several aspects. First, network analysis provides a strong methodological approach to investigate and understand the interconnected relationship among various menopausal symptoms (Papachristou et al., 2019). Second, it provides a graphic visualization of the network structure which conveys information about the direction and strength of the relationship among symptoms (Hevey, 2018). Third, it provides centrality measures (i.e. strength, closeness, and betweenness) that identifies key symptoms within each symptom network (Hevey, 2018; Papachristou et al., 2019). Fourth, some properties of network models can be further compared between the two menopausal stages through the use of network comparison test, which allows us to better understand the potential differences in the symptom experience between midlife women in peri-menopause and post-menopause. Currently, there is only one study that used network analysis to compare the number and types of key symptoms and symptom clusters experienced by midlife peri-menopausal and post-menopausal women with and without metabolic syndrome (Min et al., 2022). However, this study examined midlife women in peri-menopause and post-menopause together and assumed their symptom experience to be similar for both groups (Min et al., 2022).

The purpose of this current exploratory study was to examine and compare the symptom network structure and key symptoms between midlife women in peri-menopause and post-menopause through the use of network analysis. Then, network comparison test was conducted to compare the network properties of peri-menopause and post-menopause symptom networks. As the symptom network between these two menopausal stages may be different due to the influence of covariates, we matched participants from each menopausal stage using propensity score matching (PSM) and created a comparable group.

Design and Data Collection. This is a secondary data analysis using cross-sectional visit 5 data from the Study of Women’s Health Across the Nation (SWAN). Among all available annual visits, visit 5 was selected to obtain a greater number of midlife women in peri-menopause and post-menopause.

Description of the Data Set. SWAN is a community-based study that examines the overall health of midlife women in multiple racial/ethnic groups across seven different community sites (MI, MA, IL, CA, NJ, PA) in the United States. The aim of SWAN is to understand how the physical, biological, psychological, and social changes during midlife and menopausal transition affect the health and health outcomes in midlife women. At baseline, a total of 3,302 participants met the SWAN study eligibility criteria and were enrolled to the study. These participants were followed up annually with the most recent visit in 2016. More details can be find elsewhere (Torréns et al., 2009).

Participants. A total of 2,617 participants met the inclusion criteria for the current study with 1,719 participants in peri-menopause group and 898 participants in post-menopause group. The inclusion criteria for the peri-menopause group was: (1) midlife women aged 40–65 years, and (2) in early or late peri-menopause. The inclusion criteria for the post-menopause group was: (1) midlife women aged 40–65 years, and (2) in natural or surgical post-menopause.

Demographic and Clinical Characteristics. Demographic and clinical characteristics were obtained mostly from self-report using SWAN-designed questionnaire. One of the clinical characteristics, body mass index (BMI), was calculated using the height and weight that were measured during each visit using standardized study protocols (Hall et al., 2012). Demographic characteristics included age, race/ethnicity, marital status, level of education, annual household income, employment status, and social support. Clinical characteristics included overall perception of health and BMI.

Menopausal Stage. Menopausal stage was collected based on the self-reported menstrual bleeding patterns. Peri-menopause was defined as having menstrual period in the past 3 months with change in menstrual cycle regularity in the past 12 months or no menstrual period in the past 3 months with intermittent menstrual bleeding within the past 12 months. Post-menopause refers to having no menstrual period in the past 12 consecutive months (Bromberger et al., 2011; Min et al., 2022).

Symptoms. A total of fourteen symptoms were selected based on the literature and symptoms studied in the SWAN study (Greenblum et al., 2013; Min et al., 2021). Symptoms with prevalence less than 20% were excluded to increase the clinical significance of our study findings as recommended by previous researchers (Albusoul et al., 2017). The final set of included symptoms were frequent mood change, anxiety, depression, headache, forgetfulness, trouble sleeping, night sweat, hot flash, decreased sexual desire, decreased sexual arousal, decreased sexual satisfaction, vaginal dryness, get up from sleep to urinate, and stiffness.

The Center for Epidemiological Studies of Depression (CES-D) scale was used to measure depression which has shown to be a reliable and valid tool among midlife U.S adults with Cronbach’s alpha of .90 (Cosco et al., 2017; Jones et al., 2020). A composite score of four anxiety symptoms (irritability, nervousness, feeling fearful, and heart pounding) was derived to measure anxiety as recommended in previous literature, which has shown a good convergent validity with the Generalized Anxiety Disorder (GAD-7) scale (Bromberger et al., 2013; Kravitz et al., 2014). Other symptoms were measured from self-report using SWAN-designed questionnaire that asked about the frequency of each symptom experienced in the past two weeks. A composite score was derived to measure the severity of each symptom that ranged from 0 (mild) to 3 (severe) (Min et al., 2021, 2022).

Data Analysis.

Propensity Score Matching. Midlife peri-menopausal women (n = 1,719) were statistically matched with midlife post-menopausal women (n = 898) using propensity score matching with ration of 1:1, which resulted in (peri-menopause = 898; post-menopause = 898). The covariates used for propensity score matching were the demographic and clinical characteristics: age, race/ethnicity, marital status, level of education, annual household income, employment status, social support, overall perception of health, and BMI. Using the R-package MatchIt, the propensity scores were calculated with logistic regression and matching was performed using the nearest neighbor matching algorithm. Then, the covariate balance was assessed before and after propensity score matching using χ² tests for categorical variables and independent t-tests for continuous variables to ensure that the propensity score matching has worked.

Network Analysis. The symptom networks were constructed using the propensity-score matched midlife peri-menopausal and post-menopausal women. The following steps for network analysis were followed: (1) network assessment, (2) network accuracy and stability, and (3) network comparison. R statistical software version 3.6.2 was used to conduct network analysis.

(1) Network Assessment. A Pairwise Markov Random Field (PMRF), which is an undirected network model, was used construct the network structure (Hevey, 2018; Papachristou et al., 2019). The q-graph in R-package was used to create partial correlations for both groups. To estimate the network, the “graphical least absolute shrinkage and selection operator (LASSO) algorithm with extended Bayesian Information Criteria (EBIC)” was used with a recommended gamma (γ) value of 0.25. This method was selected to minimize the number of spurious edges and potential issues of over-fitting and unstable estimates (Hevey, 2018). LASSO has been recommended for its flexibility in terms of non-continuous data and low likelihood of false positive edges and the selected EBIC helps enhance the accuracy and interpretability of the constructed networks (Hevey, 2018).

Within the constructed network, nodes represent symptoms and edges represent the relationship between the symptoms independent of other nodes (Papachristou et al., 2019). A blue edge represents a positive relationship and a red edge represents a negative relationship between the two nodes. In addition, the strength of the relationship is indicated by the width of each edge, where a thick edge indicates a strong relationship and a thin edge indicates a weak relationship between the two nodes. To estimate the importance of each node within the network, three centralities measures of strength, betweenness, and closeness were estimated. Strength measures how strongly a node is connected to other nodes based on the sum of weighted number and strength of all connections of this specific node in relation to other nodes (Hevey, 2018). Betweenness indicates the number of times that a node is in the shortest pathway between other nodes (Hevey, 2018). Closeness measures the average distance of a specific node to other nodes in the network (Hevey, 2018). Nodes with high centrality values were considered to be key symptoms within each network.

(2) Network Accuracy and Stability. After the network assessment, network accuracy and stability were examined using the R-package bootnet. We calculated a 95% confidence interval to estimate the accuracy of edge weights. As confidence interval requires prior knowledge on the sampling estimation which is often difficult to have, we conducted the non-parametric bootstrapping method (1,500 bootstrap iterations) to repeatedly estimate the model to obtain the required statistics. Then, we conducted a case-drop bootstrapping method to estimate the correlation stability coefficient (Cs-coefficient) to quantify the stability of centrality indices. While there is no specific cut-off value for Cs-coefficient, researchers recommend a minimum value of .25 and preferably over 0.50 (Epskamp et al., 2018). Finally, we conducted bootstrapped difference test with α = .05 based on 1,500 bootstrap iterations to test for statistical significance between two node strengths or edge weights.

(3) Network Comparison. The R-package NetworkComparisonTest (NCT) was used to compare the symptom network properties between midlife women in peri-menopause and post-menopause. The NCT is a permutation-based hypothesis test that allows for a direct comparison of two symptom networks through testing for differences in their network structure 1000 times repeatedly. It tests on four invariance hypotheses that include (1) global strength, (2) network structure, (3) one-to-one edge strength, and (4) specific centrality measure. The global strength invariance hypothesis assumes the overall connectivity to be identical across subpopulations. The network structure invariance hypothesis assumes the structure to be completely identical across subpopulations. The one-to-one edge strength invariance hypothesis assumes a specific edge to be identical across subpopulations. Last, the specific centrality measure assumes that the two networks are not significantly different in strength centrality measure (van Borkulo, 2018).

Sample Characteristics

Before Propensity Score Matching. The mean age of midlife women in post-menopause (52.66 ± 2.54 years) was higher than that of midlife women in peri-menopause (50.14 ± 2.35 years), which was statistically significant (p < 0.001). A higher percentage of midlife women in post-menopause were single/never married, separated, widowed, and divorced and the difference was statistically significant (p = 0.032). In addition, midlife women in post-menopause had a higher percentage of annual household income less than $19,999 and lower percentage of annual household income more than $19,999 (p < 0.001) and current employment status (p = 0.043) when compared to midlife women in peri-menopause. In regards to their overall health perception, midlife women in post-menopause perceived their health to be poor or fair while midlife women in peri-menopause perceived their health to be good, very good, or excellent (p = 0.002).

After Propensity Score Matching. The difference between the mean age between midlife women in peri-menopause and post-menopause remained statistically significant (p < 0.001). However, other demographic and clinical characteristics were not statistically significant or lost statistical significance after propensity score matching.

Table 1

Demographic characteristics before and after PSM
Covariates	Before PSM		p-value	After PSM		p-value
	Mean ± SD or (%)			Mean ± SD or %
	Peri-menopause (n = 1719)	Post-menopause (n = 898)		Peri-menopause (n = 898)	Post-menopause (n = 898)
Age	50.14 ± 2.35	52.66 ± 2.54	< 0.001**	51.70 ± 2.06	52.66 ± 2.54	< 0.001**
Race/ethnicity			0.433			0.998
African American	511 (29.7)	248 (27.6)		243 (27.1)	248 (27.6)
Chinese	70 (4.1)	42 (4.7)		41 (4.6)	42 (4.7)
Japanese	106 (6.2)	44 (4.9)		44 (4.9)	44 (4.9)
White	846 (49.2)	462 (51.4)		468 (52.1)	462 (51.4)
Hispanic	186 (10.8)	102 (11.4)		102 (11.4)	102 (11.4)
Marital status			0.032*			0.889
Single/never married	219 (12.7)	120 (13.4)		126 (14.0)	120 (13.4)
Currently married	1154 (67.1)	560 (62.4)		559 (62.2)	560 (62.4)
Separated	56 (3.3)	37 (4.1)		31 (3.5)	37 (4.1)
Widowed	46 (2.7)	41 (4.6)		36 (4.0)	41 (4.6)
Divorced	244 (14.2)	140 (15.6)		146 (16.3)	140 (15.6)
Education			0.133			0.876
Less than high school	161 (9.4)	90 (10.0)		85 (9.5)	90 (10.0)
High school graduate	469 (27.3)	216 (24.1)		234 (26.1)	216 (24.1)
Some college	564 (32.8)	281 (31.3)		281 (31.3)	281 (31.3)
College graduate	271 (15.8)	150 (16.7)		147 (16.4)	150 (16.7)
Post graduate	254 (14.8)	161 (17.9)		151 (16.8)	161 (17.9)
Annual Income			< 0.001**			0.698
Less than $19,999	145 (8.4)	100 (11.1)		87 (9.7)	100 (11.1)
$20,000 to $49,999	366 (21.3)	248 (27.6)		240 (26.7)	248 (27.6)
$50,000 to $99,999	827 (48.1)	362 (40.3)		375 (41.8)	362 (40.3)
$100,000 or more	381 (22.2)	188 (20.9)		196 (21.8)	188 (20.9)
Currently employed	1397 (81.3)	700 (78.0)	0.043*	711 (79.2)	700 (78.0)	0.527
Social support			0.252			0.853
None of the time	10 (0.6)	7 (0.8)		6 (0.7)	7 (0.8)
A little-some of the time	207 (12.0)	127 (14.1)		120 (13.4)	127 (14.1)
Most-all of the time	1502 (87.4)	764 (85.1)		772 (86.0)	764 (85.1)
Overall health			0.002*			0.271
Poor-fair	212 (12.3)	155 (17.3)		136 (15.1)	155 (17.3)
Good-very good	530 (30.8)	275 (30.6)		262 (29.2)	275 (30.6)
Excellent	977 (56.8)	468 (52.1)		500 (55.7)	468 (52.1)
Body mass index, kg/m²	28.63 ± 6.83	28.94 ± 6.88	0.27	28.90 ± 6.90	28.94 ± 6.88	0.89
* significant at p < 0.05
** significant at p < 0.01

Network Assessment.

Figure 2 visualizes the symptom network structure for midlife women in peri-menopause and post-menopause, respectively. In both networks, a strong relationship between anxiety-frequent mood change, night sweat-hot flash, depression-anxiety, decreased sexual satisfaction-decreased sexual arousal, and decreased sexual desire-decreased sexual arousal. In addition, a negative relationship was noted in both groups between vaginal dryness-forgetfulness and stiffness-night sweat. The strength of the relationship was stronger for most of the symptoms for midlife women in peri-menopause. In the symptom network for midlife women in peri-menopause, a negative relationship was found between stiffness-night sweat, vaginal dryness-forgetfulness, and hot flash-forgetfulness. On the other hand, for midlife women in post-menopause, a negative relationship was found between vaginal dryness-decreased sexual desire, frequent mood change-decreased sexual arousal, and decreased sexual desire-forgetfulness.

Table 2 shows the values for three centrality indices (strength, betweenness, and closeness). In midlife women in peri-menopause, frequent mood change had the highest strength value (1.59) and closeness value (1.28), and depression had the highest betweenness value (1.71). In midlife women in post-menopause, night sweat had the highest strength value (1.35) and betweenness value (1.82), and anxiety had the highest closeness value (0.96). Refer to Fig. 3 for the plotting of centrality indices.

Table 2

Symptom centrality indices
Symptom	Peri-menopause			Symptom	Post-menopause
	Strength	Betweenness	Closeness		Strength	Betweenness	Closeness
Frequent mood change	1.5906338	1.10942752	1.27870539	Night sweat	1.34599838	1.82449661	0.646734
Anxiety	1.30223592	-0.4034282	1.1138894	Anxiety	1.30087455	1.54380482	0.95690286
Night sweat	1.10120459	1.51285571	0.88086226	Decreased sexual arousal	1.28311822	0.28069179	0.386336
Hot flash	1.02001489	-0.4034282	0.62578437	Frequent mood change	0.92438132	0.56138357	0.81873571
Depression	0.51039623	1.7145698	0.96264874	Depression	0.72933508	0.14034589	0.855285
Decreased sexual arousal	0.44180381	0.30257114	-0.8355279	Hot flash	0.31854259	-1.1227671	0.14258477
Trouble sleeping	0.12259358	0.10085705	0.94305275	Decreased sexual desire	-0.093409	-0.8420754	0.1774242
Headache	-0.446191	-1.0085705	0.31708061	Decreased sexual satisfaction	-0.1437964	-0.5613836	0.05096409
Decreased sexual satisfaction	-0.4631572	1.00857047	-0.6477004	Trouble sleeping	-0.2226306	0.42103768	0.59998789
Vaginal dryness	-0.5801728	-1.0085705	-0.0594484	Vaginal dryness	-0.5548253	1.12276714	0.8151575
Get up to urinate	-1.0921919	-1.0085705	-0.4835326	Headache	-1.1983032	-1.1227671	-0.6576593
Decreased sexual desire	-1.1051924	-1.0085705	-1.1749164	Get up to urinate	-1.1984766	-1.1227671	-0.8028034
Forgetfulness	-1.1788892	-1.0085705	-1.5998155	Stiff	-1.2280564	-0.5613836	-1.9799671
Stiff	-1.2230883	0.10085705	-1.3210824	Forgetfulness	-1.2627526	-0.5613836	-2.0096823

Network Accuracy and Stability.

For both symptom networks for midlife women in peri-menopause and post-menopause, strength showed a higher stability than betweenness and closeness with a Cs-coefficient of 0.751. For midlife women in peri-menopause, the Cs-coefficient for betweenness was 0 and closeness was 0.283. For midlife women in post-menopause, the Cs-coefficient for betweenness was 0.128 and closeness was 0.439.

Network Comparison.

When comparing two networks, we failed to reject the four invariance hypotheses of global strength, network structure, one-to-one edge, and specific centrality measure. The global strength (S = 0.01, p = 0.974) for midlife women in peri-menopause was 3.73 and midlife women in post-menopause was 3.75, which was not statistically significant. The network structure was insignificant between the two networks (M = 0.10, p = 0.461). Last, the specific centrality measure was also not significant between the two groups (C=-0.10, p = 0.083). As the global strength, network structure invariance, and specific centrality measure were not significant, the edge invariance test was not further conducted.

To the best of our knowledge, this is the first study to use network analysis to understand the interconnected relationship among symptoms and to identify key symptoms in midlife women in peri-menopause and post-menopause. In addition, we further compared the symptom networks between the two groups through network comparison test. While the symptom networks between the two groups were not invariant, the network assessment, network accuracy and stability, and key symptoms within each network were different.

Our study found that there was a strong relationship between certain symptoms (i.e. anxiety-frequent mood change, night sweat-hot flash, depression-anxiety, decreased sexual satisfaction-decreased sexual arousal, and decreased sexual desire-decreased sexual arousal) in both groups, though the strength of the relationship was stronger in midlife women in peri-menopause. This further supports the current literature where midlife women in peri-menopause and post-menopause experience a significant decline in their sexual activity due to decreased sexual desire, arousal, and satisfaction (Thornton et al., 2015). The etiology of these sexual symptoms is often multifactorial that include physiological, pathophysiological, and hormonal changes in midlife women and requires careful evaluation and management (Thornton et al., 2015). In addition, previous research supports the presence of vasomotor symptoms such as hot flash, night sweats, and cold sweats that often occur together in midlife women during their transition from peri-menopause to post-menopause, which indicates their strong relationship with each other (Augoulea et al., 2019). We also found a negative relationship between vaginal dryness-forgetfulness and stiffness-night sweat in both groups. While there is a strong evidence that midlife women in peri-menopause and post-menopause experience vaginal dryness, forgetfulness, stiffness, and night sweat, our findings add to current body of evidence about the potential negative relationship among these symptoms (Augoulea et al., 2019; Avis et al., 2018; Kim & Jung, 2015; Ruan et al., 2017).

Through examining three centrality indices (strength, betweenness, closeness), frequent mood change was the key symptom in midlife women in peri-menopause with its highest strength and closeness value, and night sweat was the key symptom in midlife women in post-menopause with its highest strength and betweenness value. To date, there is only one study that identified the key symptoms within each type of symptom cluster based on symptom occurrence and severity dimension in midlife peri-menopausal and post-menopausal women with and without metabolic syndrome (Min et al., 2022). This study looked at the midlife women in peri-menopause and post-menopause together based on the presence and absence of metabolic syndrome. Among those without metabolic syndrome, it identified anxiety, sleep disturbance, night sweat, and vaginal dryness based on symptom severity (Min et al., 2022). Similarly, our study also identified night sweat as one of the key symptoms but also found the potential importance of frequent mood change. However, Min et al., 2022 found frequent mood change to have the lowest centrality values in the psychological/somatic cluster which contradicts our study findings. Key symptoms are critical study findings that may serve as targets for future symptom management interventions (Min et al., 2022; Papachristou et al., 2019). Therefore, it is important to further examine the importance of frequent mood change in midlife women in post-menopause through clinical assessment and research.

With the use of network comparison test, we further compared the two symptom networks between midlife women in peri-menopause and post-menopause and tested for four invariance hypotheses of global strength, network structure, centrality strength, and one-to-one edge. While the two symptom networks were not invariant, the global strength was higher in midlife women in post-menopause. Van Borkulo et al., 2015 reported that a more strongly connected and dense network of symptoms may indicate a poorer prognosis as these individuals may experience more prevalent and severe symptoms than those in a less connected and dense network (van Borkulo et al., 2015). This may potentially indicate that midlife in post-menopause may experience a more complex array of symptoms, leading to poor prognosis. The network structure invariance was also not significant between the two groups, all of which did not lead us to further conduct the edge invariance test. The one-to-one edge invariance test may help identify the relationship between symptoms that are significantly stronger in one group than the other, as well as the central edges within each network. These findings may explain the potential differences in symptoms experienced by midlife women in peri-menopause and post-menopause.

Our study has several limitations to consider. First, network comparison test has been used mainly for gaussian and binary data (van Borkulo, 2018). All the ordinal symptom variables used for current data analysis was treated as gaussian, which has been used by previous researchers. However, the results should be interpreted with caution as it may include some bias. Second, this is an exploratory study that focuses on the network structure based on symptom severity. As symptom is conceptualized as multidimensional, future studies should identify and compare the symptom networks using other symptom dimensions such as occurrence and frequency. Third, all the symptoms were obtained via self-report using the SWAN-designed questionnaire, which may impact the validity of our study findings. Fourth, a significant number of sample size was lost for midlife women in peri-menopause during propensity score matching. While a comparable group was created through the use of propensity score matching, the validity of our study findings may be affected. Last, the covariates selected for propensity score matching were based on data availability. As a result, important covariates that can influence menopausal symptoms in midlife women may not have been considered.

The current study used network analysis to find that there were some similar overlapping positive and negative relationships between symptoms in midlife women in peri-menopause and post-menopause with difference in strength. The key symptoms were different for both groups, which indicates a potential need for different symptom management approach. However, the symptom networks were not invariant in terms of global strength, network structure, specific centrality measure, and one-to-one edge invariance.

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Declaration of Conflicting Interests: The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.

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Comparison of Symptoms Between Midlife Women in Peri-menopause and Post-menopause Using Network Comparison Test

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