clustering iranian women according to their menopausal severity symptoms (mssi-38)

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, 664 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 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. 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.