Clustering Iranian women according to their Menopausal Severity Symptoms (MSSI-۳۸)

Introduction: Clustering analysis can help in identification of at-risk groups. The study aimed to identify clusters of midlife women by their similarity of menopausal severity symptoms.Method: In this cross-sectional study, ۶۶۴ women living in Mashhad, Iran were collected. The Menopause Severity Symptoms Inventory was used to collect information about menopausal symptoms. A clustering algorithm was applied to classify women with different menopausal symptoms.Result: k-means clustering algorithm, extracted three major clusters based on different menopausal symptoms. The first cluster involved ۳۰۱ (۴۵%) women with mild symptoms, the second was a cluster of moderate symptoms women with size ۱۳۱ (۲۰%). The remaining ۲۳۲ (۳۵%) of women were placed in the third cluster.Conclusion: Three major clusters of women were identified. The study revealed a high prevalence of pain in muscles and joints, anxiety, and vasomotor symptoms among Iranian women, so promoting women's self-care and some interventions could alleviate these issues.

کلیدواژه ها:

Menopausal Severity Symptoms ، MSSI-۳۸ ، K-Means Clustering ، Classification