Evaluation of the Menopause-Specific Quality of Life Questionnaire

In Brief Objective Despite being used in multiple studies, the Menopause-Specific Quality of Life Questionnaire (MENQOL) has not been assessed with factor analysis, a common method of item reduction in quality of life tools. Methods The Menopause Epidemiology Study is a cross-sectional population-based study of women 40 to 65 years old in the United States chosen from a source population selected by random digit dialing and probability sampling. We focused on 2,703 postmenopausal women for our analyses. Before analysis and to prevent model overfitting, we split our sample into two equal groups using a uniform random sample. Using parallel analysis for factor extraction, we performed confirmatory factor analysis on the MENQOL to examine the current factor structure and to evaluate the efficiency of the items in the existing tool. Reliability coefficients (Cronbach α) were calculated for each of the domains. Results With few exceptions, the items from the original MENQOL factored into the domains under which they were originally placed. Using this method, five items did not add significant statistical value to the scoring of the domains: difficulty sleeping; poor memory; accomplishing less than I used to; changes in appearance, texture, or tone of my skin; and feeling tired. Reliability coefficients for the four original domains were acceptable: vasomotor, 0.87; psychosocial, 0.85; physical, 0.88; and sexual, 0.77. Conclusions Results from factor analysis indicate that although the MENQOL was developed more than 15 years ago, the strength of the items is still highly valuable today in the assessment of women’s menopause-related quality of life. This is the first study to conduct factor analytic techniques on the Menopause-Specific Quality of Life instrument. Using confirmatory factor analysis and parallel analysis, the results show that the domain structure remains robust when used in a population-based setting, despite being created and largely used in clinical trials.