The relationships of multiple factors to menopausal symptoms in different racial/ethnic groups of midlife women: The structural equation modeling

ABSTRACT

The purpose of the present study was to examine the relationships of multiple factors to menopausal symptoms in different racial/ethnic groups of midlife women. This secondary analysis was conducted with the data from 980 midlife women that were collected from 2005 to 2013 using the Midlife Women’s Symptom Index. Structural equation modeling was used to analyze the data. The model had the highest fit indices for non-Hispanic (NH) White midlife women, and prominent racial/ethnic differences were observed in the relationships of multiple factors to menopausal symptoms. In all racial/ethnic groups (except in Hispanic women), perceived health status was significantly positively associated with menopausal symptoms (β = −0.149 for NH African-American; β = −0.207 for NH Asians; β = −0.162 for NH Whites). Body mass index was significantly positively associated with menopausal symptoms only in NH Asians (β = 0.118) and Hispanics (β = 0.210). The racial/ethnic differences in the relationships of multiple factors to menopausal symptoms could have resulted from the different cultural contexts in which women undergo during their menopausal transitions. Further cultural studies on the associations of racial/ethnic-specific factors with menopausal symptoms would help in understanding possible causes for racial/ethnic differences in the factors significantly associated with menopausal symptoms.

KEYWORDS:

• Covariates
• menopausal symptoms
• midlife women
• race/ethnicity
• structural equation modeling

Acknowledgments

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Declaration of interest

The authors have no conflict of interest/financial disclosure.

Additional information

Funding

The data for this study came from two larger studies funded by the National Institutes of Health: [Grant Numbers NIH/NINR/NIA; R01NR008926 and NIH/NINR/NHLBI; R01NR010568].