Introduction: Many studies reported that the factors associated with the intensity of menopausal symptoms vary according to race, culture, and ethnicity. Different instruments, measure severe menopausal symptoms. The present study aims to classify Iranian women between 42 and 60 years according to the similarity of menopausal severity symptoms and then find the risk factors related to allocating in severe symptoms groups.
Method: In this cross-sectional study, 664 women aged 42-60, living in Mashhad, Iran were collected. The Menopause Severity Symptoms Inventory (MSSI-38) was used to collect information about menopausal symptoms. K-Means clustering algorithm was applied to classify women with different menopausal symptoms in separate groups. The baseline category logit model and ANOVA were used to find the associated factors and covariates with clusters.
Result: K-Means clustering algorithm, extracted three major clusters based on different menopausal symptoms. The first cluster involved 301 (45%) women with mild symptoms, the second was a cluster of moderate symptoms women with size 131 (20%). The remaining 232 (35%) of women were placed in the third cluster. The baseline category logit model showed that Compared to Cluster 1, Cluster 2 is associated with a higher underlying diseases (OR = 1.51, P-value = 0.03), lack of physical activity (OR = 1.79, P-value = 0.003), having more than five pregnancies (OR = 2.11, P-value = 0.017), and being peri menopause (OR = 1.71, P-value = 0.03). In contrast, Cluster 3 shows an even stronger association with underlying diseases (OR = 3.71, P-value < 0.001), physical activity (OR = 2.46, P-value = 0.001), insufficient income (OR = 3.43, P-value < 0.001, and being peri menopause (OR = 2.09, P-value = 0.029) or post menopause (OR = 2.02, P-value = 0.044) when compared to Cluster 1.
Conclusion: Based on these findings, women with underlying diseases, varying levels of physical activity, different income levels, different number of pregnancies, and menopause status in the moderate (Cluster 2) and severe symptomatic groups (Cluster 3) exhibited significant differences compared to those in the mild symptomatic group (Cluster 1). These results underscore the necessity for targeted interventions, such as promoting physical activity and providing mental health support, to alleviate menopausal symptoms. Additionally, further research is essential to identify the causal factors contributing to these symptoms, which could lead to improved care and health policies for women experiencing menopause.
Keywords: Baseline category logit model; Cluster analysis; K-Means algorithm; Menopausal Severity Symptoms (MSSI-38).
© 2024. The Author(s).