Women experience distinct reproductive life stages, including infancy, childhood, adolescence/menarche, adulthood, pre-menopause, menopause, and post-menopause. The World Health Organization (WHO) defines menopause as “a natural phenomenon that is deemed to have occurred after 12 consecutive months without menstruation for which there is no other obvious physiological or pathological cause and in the absence of clinical intervention” (1). During menopause, hormonal changes occur due to decreased ovarian endocrine activity, impacting the production of estrogen and progesterone, potentially affecting quality of life. Menopausal symptoms may encompass vasomotor issues like hot flashes and night sweats, psycho-social challenges including increased anxiety and reduced sleep, physical discomfort like joint and knee pain, backache, and vaginal dryness, as well as reduced interest in sexual activity. These and the related changes occurring in cardiovascular risk profile and osteoporosis are well-elucidated in the SWAN study (2). Numerous global studies have explored the quality of life in menopausal women, employing various assessment tools, with the Menopause-Specific Quality of Life Questionnaire-Intervention (MENQOL-I) (3) being a commonly used instrument. Studies have shown that women at early peri, late peri or post menopause exhibited significant reduction in functioning than premenopausal women (4). National level studies have shown prevalence of post-menopausal women experiencing menopausal symptoms and poor quality of life to range between 70.2 and 73.8% (5, 6).

The concept of QoL encompasses various dimensions, including physical, psychological, and social wellbeing, as well as functional status. Osteoporosis can profoundly impact each of these dimensions, compromising an individual's ability to engage in daily activities, maintain independence, and enjoy a fulfilling life. Postmenopausal osteoporosis (PMO) is a generalized skeletal disorder in which decreased bone density contributes to increased risk of fracture (7). A hospital-based study from North India, estimated the prevalence of osteoporosis to be 37.5% among postmenopausal women (8).

Standard equipment used to measure osteoporosis is the use of Dual Energy Xray Absorptiometry (DEXA) scan which is expensive, inaccessible and makes use of high energy X-Ray radiation. One low cost, easy, no radiation tool for screening osteoporosis in older people is Osteoporosis Self-Assessment Tool for Asians (OSTA) (9).

One of the causes of fracture is minor trauma that occurs following falls. Older people with past history of falls have been found to have increased risk of falls. A tool that is used to assess the fear of fall in older people is the Fall Efficacy Scale International (FES-I) questionnaire FES-I.¹

This study aims to assess the quality of life and its determinants of post-menopausal women in Ernakulam district using the menopause specific Quality of Life Intervention (MENQOL-I) scale. This study also tries to look at risk of osteoporosis among menopausal women, and fear of fall as they are factors that contribute to fragility fractures and increased morbidity among older people. These measures are now in focus since Kerala is experiencing demographic transition in which there is an increase in the number of people in older age groups, especially women.

The average age of the 379 post-menopausal women in this study was 60 years, with a standard deviation of 6.83 years. The mean age at menopause was determined to be 50.58 years, with a standard deviation of 4.28 years. Post-menopausal women in the study had an average BMI of 24.56 kg/m².

The majority of study participants identified with the Hindu religion (59.1%), while 34% had attained a high school level of education. Homemakers constituted 89.2% of the participants, and 55.4% resided in nuclear families. Majority, 89.4%, were married. Urban residents accounted for 50.4% of the participants, and 83.6% lived in self-owned houses. Notably, 95% reported Out-Of-Pocket expenses in healthcare, and 63.8% belonged to Above Poverty Line (APL) families based on their ration/public distribution system cards.

Among the post-menopausal women, 55.4% were classified as overweight, and 15.3% were categorized as obese. Additionally, 12.9% had a history of bone fractures, 22.4% were on calcium supplementation, and 35.4% reported a history of consuming calcium-rich foods such as milk and green leafy vegetables (Table 1).

According to responses from the MENQOL-I questionnaire, 27% of women (103) reported experiencing hot flashes in the vasomotor domain. In the psychosocial domain, 26.6% (101) mentioned accomplishing less than they used to. For the physical domain, 64.6% (245) of post-menopausal women reported aching muscles and joints (Table 2).

The psychosocial domain exhibited the highest impact on postmenopausal women, affecting 47.8% (181) of them, suggesting that this domain had the most significant influence. In close succession, the physical domain impacted 45.1% (171) of postmenopausal women, whereas the vasomotor domain had the lowest proportion, with 26.4% (100) of postmenopausal women affected (Figure 1).

Participants in the study perceived psychosocial symptoms such as anxiety or nervousness (36.4%) and impatience with others (22.7%) as highly impactful on their quality of life. Additionally, they identified physical symptoms like muscle and joint aches (64.6%), discomfort in the back of the neck and head (37.5%), and feelings of tiredness and fatigue (36.7%) as affecting their quality of life. Notably, a smaller proportion of women perceived vasomotor symptoms such as hot flashes (27.2%), sweating (26.1%), and night sweats (16.4%) as impacting their quality of life.

The various socio-demographic factors, risk of osteoporosis based on OSTA score, fear of fall based on Fall Efficacy Scale International questionnaire were checked for association with impact score in quality of life (high and low) in the vasomotor, physical and psychosocial domains. This analysis is represented in the Tables 3–5. All factors with a p-value in chi-square test < 0.2 were further used in the logistic regression modeling, backward conditional model was used.

Logistic regression analysis was conducted to identify determinants affecting quality of life domains. In the vasomotor domain, occupation (employed) showed a significant association [adjusted odds ratio (aOR): 2.07, 95% confidence interval (C.I.): 1.05, 4.09]. In the psychosocial domain, factors such as age of attaining menopause (>50 years, aOR: 1.54, 95% C.I.: 1.00, 2.37), payment of health expenses (insurance, aOR: 3.24, 95% C.I.: 1.16, 9.00), history of bone fracture (yes, aOR: 2.34, 95% C.I.: 1.21, 4.52), and concern of falling (high concern, aOR: 2.74, 95% C.I.: 1.78, 4.23) were statistically significant. In the physical domain, factors such as house ownership (rent, aOR: 1.84, 95% C.I.: 1.42, 6.69), marital status (single, aOR: 3.09, 95% C.I: 1.42, 6.69), and concern of falling (high concern, aOR: 5.49, 95% C.I.: 3.48, 8.66) were found to be statistically significant (Table 6).

The evaluation of osteoporosis risk among post-menopausal women revealed that more than half (53%) of the post-menopausal women had moderate risk while 10.6% (40) were at high risk and 36.4% (138) at mild risk, respectively.

In this cross-sectional community-based study involving 379 post-menopausal women from Ernakulam district, Kerala, the quality of life was assessed using the MENQOL-I questionnaire in the Vasomotor, Psychosocial, and Physical domains.

Studies from other parts of the country showed that the symptoms based on domains in MENQOL that affected the quality of life were different from the current study. However, pattern that was prominent were the symptoms in physical domain which affects the quality of life in post-menopausal women. Gaikwad et al. in a study looking at menopausal symptoms among teachers in Raipur, Chhattisgarh, found that 87.5% of the study participants had symptoms in the psychosocial domain, followed by 68.05% participants having symptoms in the physical domain and 51.85% suggesting vasomotor symptoms as affecting the quality of life (13).

Logistic regression analysis indicated that the determinant associated with symptoms in the vasomotor domain was occupation (employed participants). Women with high symptom scores in the psychosocial domain, were those who attained menopause above 50 years, participants with insurance, having a history of fracture and a high concern of falling. In the physical domain, high symptom scores were associated with women living in rented house, single women and those with high concern of falling.

In a study by Karmakar et al. on the quality of life of post-menopausal women in West Bengal, it was found that vasomotor symptoms were associated with type of family; psychological symptoms were associated with age; physical symptoms with caste, education and marital status (14). In a study from Nepal, significant factors that were associated with quality of life were marital status, number of children, education, occupation and health seeking behavior (15). Studies have found women with occupation and higher educational status to have lower scores (16, 17).

In the current study, participants who were employed had higher odds of suffering from vasomotor symptoms. The stress of managing household work and occupation simultaneously may have a bearing on the condition. Many employed women pass through midlife crisis typically at this age. Having a supportive environment both at home and workplace can ease the stress.

Insured participants in this study had higher score in the psychosocial domain, reflecting the fact that better economic circumstances may influence health seeking behavior. Women with history of fracture and concerned about falling also had higher psychosocial domain scores. In another study conducted among menopausal women in urban part of Hyderabad, India characteristics like education and socioeconomic status were significant determinants of quality of life (6). In this study, among postmenopausal women, risk of osteoporosis was high in 40 (10.6%), moderate in 201 (53%) and mild risk seen in 138 (36.4%) of post-menopausal women.

In a study assessing the OSTA tool's efficacy in evaluating the risk of non-vertebral fractures in post-menopausal Chinese women, findings revealed that 46.1% exhibited high-risk osteoporosis, 34.3% showed moderate risk, and 19.6% had low risk (18). Another study by Ha and Baek found an association between BMI and lower bone mineral density, indicating a potential link with osteoporosis (19). Moreover, research by Kung and Huang emphasized genetic and environmental factors as contributors to osteoporosis, with environmental determinants including smoking, alcohol consumption, low calcium intake, low body weight, and physical inactivity (20).

In this community-based study of postmenopausal quality of life among women, it was found that quality of life was affected by multiple determinants. In depth analysis of the real scenario regarding these determinants calls for a mixed methodology approach. Only three domains namely, vasomotor, psychosocial and physical were addressed. The cultural scenario prevalent in the study area made it hard to explore the quality of life in sexual domain. Conversations about menopause are frequently avoided in families, communities, and workplaces. Providing a supportive environment at home and workplace and having a fall safe environment can improve the quality of life of postmenopausal women. Prevention of fractures should also be given importance, since women with a history of fracture had lesser quality of life. In view of the fact that being single aggravates the physical symptoms of menopause; having good friends and family support may contribute to improved quality of life during menopausal transition.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving humans were approved by Amrita School of Medicine Ethical Committee. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

RN: Methodology, Software, Conceptualization, Data curation, Formal analysis, Investigation, Project administration, Resources, Writing – original draft. TJ: Methodology, Software, Supervision, Validation, Visualization, Writing – review & editing. LG: Conceptualization, Methodology, Writing – review & editing. AA: Writing – review & editing, Project administration. MM: Data curation, Formal analysis, Writing – review & editing, Software. GR: Data curation, Formal analysis, Writing – review & editing.