1. Introduction
The COVID-19 pandemic, caused by the SARS-CoV-2 coronavirus, has been declared an international public health emergency. The World Health Organization (WHO) has expressed concern about the mental health, psychosocial and socio-economic consequences of the COVID-19 pandemic [
1].
Already, at the beginning of the pandemic, it was observed that isolation or quarantine significantly affected the usual activities or livelihood of many people, which could result in an increase in the level of anxiety, depression, insomnia, alcohol or drug abuse, self-mutilation or even suicide [
2]. The outburst of the COVID-19 pandemic and the following strict restrictions implemented by governments resulted in many dire consequences for the whole society. The most common symptoms were loneliness, increased anxiety and financial hardships caused by rapid halt of the economy. The global pandemic was a shock for many, and there was a lack of effective methods of coping with stress on such a scale.
This led to a further emotional burden, and thus to an increase in anxiety, sorrow or depressive symptoms. In most cases, people instinctively adapted to new conditions, but there were still many who needed help from a professional psychologist because long exposure to lockdown restrictions could lead to serious mental problems [
3,
4].
According to the WHO definition, mental health is a state of well-being in which an individual realizes his/her abilities, is able to cope with various life situations, and is able to participate in social life and work productively. Effective functioning in society and the foundation of well-being is a pillar of mental health, which means more than the absence of mental disorders [
5]. Furthermore, mental health is considered as the most important condition for a good life quality. Stressful events, on the other hand, are strong adverse environmental factors may predispose to mental disorders [
6].
Due to experiencing negative emotions during the COVID-19 pandemic, the National Health Commission has issued guidelines promoting psychological interventions aimed at civilians, medical staff and patients during the COVID-19 pandemic [
7].
Social support (SS) is a necessary buffer of stressful life events, which is defined as resources provided by other people [
8], which may be emotional, tangible, informative or evaluative [
9]. In addition, it is verbal and non-verbal communication between recipients and service providers that reduces uncertainty about the situation, in relation to each other and relationships to strengthen the perception of personal control over one’s life [
10]. The right amount of social support significantly improves mental health and relieves symptoms of depression, lowers the level of anxiety, improves self-efficacy and prevents loneliness [
11]. Support networks develop throughout life and exist even when activation is not required. The most important sources of support are those natural, such as family, friends, relatives or social groups to which an individual functioning in a social environment belongs [
12]. In addition, many scientists report that perceived support, which refers to the subjective sense of the potential availability of support, is a better predictor of well-being, coping with stress and health compared to the support received [
13]. The availability of social support is a particularly important variable in the context of social and cultural determinants of the quality of life of women in the perimenopausal period [
14].
A special period in the life of every woman is menopause, defined as: “The permanent cessation of menstruation due to the loss of ovarian follicle function. Biologically, menopause means a loss of fertility for a woman and is a natural physiological process that usually occurs between the ages of 45 and 55” [
15]. Menopause is an important event in a woman’s life and is associated with symptoms such as hot flashes, night sweats, palpitations, mood swings, insomnia, anxiety, depression, attention deficit disorder, nervousness, headaches, mood swings, dysphoria, tension and tearfulness [
16]. Hormonal changes taking place in a woman’s body significantly affect everyday functioning; moreover, there are many controversies regarding the role of menopause in the development of depression and anxiety [
4]. It is worth noting that although there is an increased risk of clinical and subclinical depression during the period of reduced estrogen levels, its occurrence should not be directly attributed to menopause, but to various factors, including neurotransmitters, sociodemographic variables [
17], psychosocial variables [
18], personality traits [
19] or genome [
20,
21].
Women in the perimenopausal period are particularly vulnerable to well-being disorders, especially during the COVID-19 pandemic. Both changes occurring in connection with menopause, as well as psychological or socio-economic consequences resulting from the duration of the COVID-19 pandemic, may negatively affect women’s mental health [
5].
The aim of our study was to assess the mental state and social support of peri- and postmenopausal women during the SARS-CoV-2 pandemic. Moreover, the aim of this study was to assess whether sociodemographic variables (age, education, place of residence, marital status) and psychological distress of women (depression and anxiety) have an impact on the support received during the SARS-CoV-2 pandemic.
2. Materials and Methods
2.1. Settings and Design
The research was conducted from August to October 2021 among peri- and post-menopausal women in Zachodniopomorskie voivodeships (Poland). The inclusion criteria were female sex, the age of 41–75 years, no clinically confirmed mental disease and informed written consent to participate in the study. The exclusion criteria were: history of psychiatric treatment, no consent to participate in the study, age <41.
The size of the study sample was established on the basis of statistical data concerning the size of the 41–75 years old female population in the West Pomeranian Voivodeship in 2021. The confidence level was set at 95%, the maximum error at 7%, and the estimated fraction size at 0.5. The total number of women qualified for the study was 295.
A total of 295 peri- and post-menopausal women were invited to participate in the survey. Only 218 women correctly completed the surveys (completion rate: 74%). The majority of the respondents were postmenopausal women (55%).
The respondents were divided into two groups with regard to their menopausal status defined as [
22]:
Perimenopause―the time immediately before menopause with the symptoms of the coming menopause (when endocrine, biological and clinical features of the coming menopause begin);
Postmenopause―the last menstruation at least 12 months before the study.
Recruitment of participants was carried out by means of information posters hung in public places and advertisements in local newspapers.
Respondents who met the inclusion criteria received general information regarding the course and purpose of the study, as well as instructions on completing the questionnaires. After giving consent to participate in the study, women received a questionnaire form. The respondents were informed that the study is entirely voluntary and anonymous as well as that the results obtained will be used for scientific purposes.
2.2. Ethical Considerations
The Bioethics Committee of the Pomeranian Medical University in Szczecin Approved this study ((KB-0012/46/01/2013). Approval number 6). This study was conducted as per the Declaration of Helsinki agreement. All participants were verbally informed about the study, and their consent was obtained.
2.3. Research Instruments
The factors influencing peri- and postmenopausal women’s mental health during the COVID-19 pandemic were determined using the following standardized survey instruments:
Beck Depression Inventory (BDI) is a 21-question research instrument for measuring the severity of depression. There are four possible answers to each question, with the intensity of each response ranging from 0 (the least severe symptom) to 3 (the most severe symptom). The total score reflects the degree of depressive symptoms. No depression (0–11 points), mild depression (12–19 points), moderate depression (20–25 points), and severe depression (26–plus points) were the four score ranges used in the study [
23]. Additionally, we divided patients into those who had depression (12 points or more) and those who did not have it (less than 12 points). The BDI’s Cronbach’s alpha was 0.89 [
24].
The Spielberg State-Trait Anxiety Scale (STAI) is a tool used in research to assess both trait and state anxiety. No anxiety (≤20), mild anxiety (21–39), moderate anxiety (40–59), and severe anxiety (60–80) are the four categories that make up the STAI questionnaire score, which ranges from 20 to 80 points. The range of Cronbach’s alphas for trait anxiety and state anxiety respectively was 0.86 to 0.92 and 0.83 to 0.92 [
25].
The Blatt–Kupperman Index (BKMI) evaluates climacteric symptoms using an 11-item questionnaire. The questionnaire asks about both physical and psychological symptoms, such as fatigue, anxiety, and melancholy. The physical symptoms listed include sweating/hot flushes, palpitations, vertigo, headaches, paresthesia, and arthralgia and myalgia. These complaints are rated from 0 to 3 in terms of their seriousness. The sum of all the items determines the final score. The study adopted the following score ranges: 0–16 = no symptoms, 17–25 = mild symptoms, 26–30 = moderate symptoms, and ≥31 = severe symptoms [
26].
The Inventory of Social Supportive Behaviors (ISSB) is a 40-item self-report questionnaire that was created to gauge how frequently people received different types of assistance in the month prior. The tool conceptualizes social support as including both concrete forms of assistance, like the provision of goods and services, and intangible forms of assistance, like advice and expressions of respect. On 5-point Likert scales (1 = not at all, 2 = once or twice, 3 = roughly once a week, 4 = several times a week, and 5 = roughly every day), subjects are asked to rate the frequency of each item. The ISSB divides support into four categories: instrumental support, information support, emotional support, and appraisal support. The ISSB’s Cronbach’s alpha was 0.90 [
27,
28].
The demographic information (age, marital status, place of residence, education, and employment status), the medical information (menstruation, menopausal syndromes), the history of exposure to COVID-19, and any other pertinent information regarding COVID-19 were all gathered using the author’s questionnaire.
2.4. Statistical Analysis
The analysis of quantitative variables (expressed numerically) was performed by calculating the mean, standard deviation, median, quartiles, and minimum and maximum values. Comparison of quantitative variables in the two groups was performed using the Mann-Whitney U test. Correlations between quantitative variables were analyzed using Spearman’s correlation coefficient. The Kruskal-Wallis test and the Dunn test were used in the study.
All calculations were performed using R version 4.1.2. (RStudio, Boston, MA, USA). The level of statistical significance was set at
p < 0.05 [
29].
3. Results
3.1. Characteristics of the Respondents
The study sample consisted of 218 women who correctly completed the questionnaires. The mean age was 53 years (SD = 6.7). The majority of the respondents were female in a formal relationship (57.8%), achieved higher education (54.13%), living in a city of more than 100 thousand residents (59.17%) and professionally active (83.94%). Of the 218 surveyed women, 55.1% were respondents who had their last menstrual period at least 12 months before the study. The age of the last menstruation in postmenopausal women averaged 49.39 years (SD = 3.71).
A total of 41.3% of the respondents get over COVID-19 but 92.7% were not hospitalized for COVID-19. 58.26% felt fear of COVID-19 and 58.3% of the subjects were in quarantine due to COVID-19.
Among the surveyed women, 62.4% had a person in their immediate family who was ill with COVID-19. In addition, 22.94% of respondents lost a loved one during the SARS-CoV-2 pandemic. The vast majority of respondents (78%) had limited contact with their loved ones and were vaccinated against COVID-19 (76%).
3.2. The Severity of Depression, Anxiety, Climacteric Symptoms and Social Support among the Peri- and Postmenopausal Women during the SARS-CoV-2 Pandemic
Analysis was performed on depressive symptoms (according to the BDI), climacteric symptoms (according to the BKMI), anxiety (according to the STAI), and social support (according to the MSPSS) among peri- and postmenopausal women of the West Pomeranian Voivodeship during the SARS-CoV-2 pandemic.
A total of 75.2% of the subjects had no depressive symptoms, while 13.8% showed mild, 7.3% moderate, 3.7% severe symptoms of depression according to the BDI.
The majority of the respondents had moderate level of anxiety as a state (40.8%) and low level of anxiety as a trait (51.4%).
The BKMI diagnosed severe climacteric symptoms in only 14.2 % of the women analyzed, moderate symptoms in 7.8 % of the women and minor symptoms in 25.7% of the women, and 52.3 % of the women had no symptoms at all.
The analysis of the results obtained from the ISSB showed that the average score for the emotional support subscale was 32.14 points, for information support 46.77 points, for instrumental support 58.83 points, and for appraisal support 17.44 points. This means that the respondents receive emotional, information and instrumental support several times a week. In turn, they receive appraisal support once a week (
Table 1).
3.3. Analysis of the Relationship between Sociodemographic Variables (Age, Education, Place of Residence, Marital Status) and Medical Variables (Menopausal Status, Get over COVID-19) on the Severity of Depression, Anxiety, Climacteric Symptoms and Social Support among the Peri- and Postmenopausal Women during the SARS-CoV-2 Pandemic
This study analyzed the influence of selected sociodemographic variables (age, education, place of residence, marital status) severity of depression, anxiety, climacteric symptoms and social support among the peri- and postmenopausal women during the SARS-CoV-2 pandemic.
It was found that age significantly correlates with anxiety as a state (
p = 0.036 r = −0.142). There were no statistically significant correlations between age and anxiety as a trait and no statistically significant correlations between age and severity of depression (
Table 2). The analysis of the impact of other sociodemographic variables (marital status, place of residence, education and professional activity) on the severity of depression among peri- and postmenopausal women during the SARS-CoV-2 pandemic showed no statistically significant correlations (
Table S1).
The anxiety as state was significantly stronger in people with higher education than in people with secondary education.
Analysis of the data did not demonstrate the difference in education on anxiety as a trait. Analysis of the influence of other sociodemographic variables (marital status, place of residence, professionally active) on the severity of anxiety among the peri- and postmenopausal women during the SARS-CoV-2 pandemic did not reveal any statistically significant difference (
p > 0.05) (
Table 3).
The analysis demonstrated no statistically significant relationships between climacteric syndrome according to the BKMI and sociodemographic variables (age, marital status, place of residence, education, professionally active) among the peri- and postmenopausal women during the SARS-CoV-2 pandemic (
Table S1).
There were no statistically significant correlations between age and social support according to ISSB (
Table 2). Data analysis showed statistically significant differences in emotional and value support according to the ISSB, taking into account the professional activity of the respondents. Professionally inactive women showed higher levels of emotional support (
p = 0.05) and evaluative support (
p = 0.014). An analysis of the influence of other sociodemographic variables (marital status, place of residence, education) on the social support among the peri- and postmenopausal women during the SARS-CoV-2 pandemic did not reveal any statistically significant difference (
p > 0.05) (
Table S2).
The anxiety as state was significantly stronger in perimenopausal women than in postmenopausal women (
p = 0.028). The analysis demonstrated no statistically significant influence of menstruation on anxiety as a trait. The anxiety as state (
p = 0.016) and a trait (
p = 0.011) were significantly stronger in women who get over COVID-19 (
Table 4). Menopausal status and get over of COVID-19 were not a statistically significant contributors to depressive symptoms in women during the SARS-CoV-2 pandemic (
Table 3).
The analysis demonstrated no statistically significant difference between climacteric syndrome according to the BKMI, depression according of the BDI or social support according ISSB and medical variables (menopausal status, get over COVID-19) among the peri- and postmenopausal women during the SARS-CoV-2 pandemic (
p > 0.05) (
Table S3).
The climacteric symptoms according of BKMI was found to significantly correlate with anxiety as a state (
p < 0.001, r = 0.34) and anxiety as a trait (
p < 0.001, r = 0.315) (
Table 5). This means that the stronger the accident symptoms, the greater the severity of anxiety.
The analysis demonstrated statistically positive significant correlation between climacteric syndrome according to the BKMI and depression according of the BDI among the peri- and postmenopausal women during the SARS-CoV-2 pandemic. It was shown that the greater the accident symptoms, the stronger the intensity of depressiveness (
Table 5).
3.4. Analysis of the Correlations between Social Support and Severity of Depression, Anxiety, Climacteric Symptoms among the Peri- and Postmenopausal women during the SARS-CoV-2 Pandemic
The analysis demonstrated no statistically significant correlation between social support according to the ISSB and depression according of the BDI among the peri- and postmenopausal women during the SARS-CoV-2 pandemic. There were no statistically significant correlations between social support according to ISSB and anxiety according of STAI. The social support was not found to significantly correlate with climacteric symptoms according of BKMI (
Table 6).
5. Limitations
The digressions presented in this research have defined certain limitations and implications for professional practice. There is a rich literature covering the impact of the COVID-19 pandemic on the mental health of the population (in which the incidence of depression, anxiety, the level of stress or the need for social support was assessed). However, studies rarely concern women in the perimenopausal period, who, due to hormonal changes, are particularly susceptible to mood changes, depression, anxiety or stress.
Unfortunately, our study has some limitations. First, the study used a self-report questionnaire. Respondents could respond to it in a socially acceptable way. However, the research assumption was based on trust and understanding of the questions by the respondents. In addition, the selection of respondents was random.
In addition, we consider the small group of women surveyed as a limitation of the study, in which the menopausal status was determined on the basis of a questionnaire, and not sex hormone level tests.
Despite the limitations of our study, it is worth mentioning that its advantage was the individual approach to the study group. Activities that recognize women’s needs and aid in adjustment to the new reality must be included. Allowing for the potential use of psychological assistance seems crucial. Institutional preventive measures must also be taken to avoid psychological issues during and after the COVID-19 pandemic. Therefore, it is advisable to conduct further research and take preventive measures to protect the mental health of women in the perimenopausal period.