PhD Student, Faculty Produce Article on Midlife Menopausal Women

PhD Student, Faculty Produce Article on Midlife Menopausal Women

Se Hee Min, PhD student, produced a manuscript publication entitled "Identification of Symptom Clusters Among Midlife Menopausal Women with Metabolic Syndrome" with faculty.

qing yangeun-ok imsharron dochertyse hee minSe Hee Min, PhD student, produced a manuscript publication entitled "Identification of Symptom Clusters Among Midlife Menopausal Women with Metabolic Syndrome" in Western Journal of Nursing Research with Sharron L. Docherty, assistant dean, PhD in Nursing Program, Eun-Ok Im, former associate dean for Research Development and Regulatory Affairs, and Qing Yang, associate professor.

Abstract

The aim of this study was to identify and compare symptom clusters in midlife menopausal women with and without metabolic syndrome based on symptom occurrence and severity dimension through secondary data analysis of the Study of Women’s Health Across the Nation. Exploratory factor analysis was used to group symptoms that are highly correlated with each other and verified by confirmatory factor analysis. Midlife menopausal women with metabolic syndrome (n = 424) experienced mental health, vasomotor, and somatic cluster across both symptom dimensions. In contrast, midlife menopausal women without metabolic syndrome (n = 1022) experienced mental health/sleep/urinary, vasomotor, and somatic cluster for symptom occurrence dimension and mental health/sleep, vasomotor/genital, and somatic cluster for symptom severity dimension. This is the first study to identify symptom clusters in midlife menopausal women with metabolic syndrome, who are at risk for experiencing complex symptoms associated with menopause transition and metabolic syndrome, and to compare symptom clusters to those without metabolic syndrome.

Citation

 Min, S. H., Docherty, S. L., Im, E.-O., & Yang, Q. (2021). Identification of Symptom Clusters Among Midlife Menopausal Women with Metabolic Syndrome. Western Journal of Nursing Research. https://doi.org/10.1177/01939459211018824
 

 

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