Methods: The data used for this secondary analysis came from two national Internet surveys among 1,054 midlife women (316 Whites, 255 Hispanics, 250 African Americans, and 233 Asians). The instruments used to collect the data were: questions on background characteristics, questions on socioeconomic factors, and the Cognitive Symptom Index for Midlife Women (CMW). The CMW was developed based on the Midlife Women’s Symptom Index (MSI); the CMW included 21 questions on cognitive symptoms. The KR-20 of the CMW was 0.87 (the prevalence sub-scale) and the Cronbach’s alpha of the CMW was 0.91 (the severity sub-scale). The data were analyzed using Poisson regression analysis and multiple logistic regression analyses. Poisson regression analyses were conducted to determine the associations of socioeconomic factors to the total numbers of cognitive symptoms. Since the assumption of normal distribution (tested with Kolmogorov-Smirnov test) was violated (p<0.001), Poisson regression analyses were used. The likelihood ratio χ2 test was performed to examine the goodness of fit. Logistic regression analyses were conducted to decide the associations of socioeconomic factors to the total severity scores of cognitive symptoms with the Hosmer & Lemeshow goodness of fit test.
Results: In total participants, socioeconomic factors including low educational level, divorced/single and very low and somewhat low family income were positively associated with the total numbers of cognitive symptoms (p<0.05). In White women, socioeconomic factors including low educational level, divorced/single and very low and somewhat low family income were positively associated with the total numbers of cognitive symptoms. In Hispanic women, only employment was positively associated with the total numbers of cognitive symptoms. In African American women, only family income (very low and somewhat low family income) was positively associated with the total numbers of cognitive symptoms (p<0.05). In Asian women, socioeconomic factors including low educational level and very low and somewhat low family income were positively associated with the total numbers of cognitive symptoms (p<0.05).
After categorizing the participants into two groups by the mean total severity scores of total participants and individual racial/ethnic groups (low versus high cognitive symptoms), multiple logistic regression analyses were conducted. In total participants, only family income [very low (OR=0.19, 95% CI=0.11–0.35) and somewhat low family income (OR=1.84, 95% CI=1.14–2.97)] was significantly positively associated with the total severity scores of cognitive symptoms. In White women, socioeconomic factors including partial college (OR=0.39, 95% CI= 0.17–0.92) and very low (OR=0.04, 95% CI=0.01–0.14) and somewhat low family income (OR=0.28, 95% CI=0.10-0.73) were significantly positively associated with the total severity scores. In Hispanic women, only very low family income (OR=0.62, 95% CI=0.15-2.58) was significantly positively associated. In Asian women, only family come [very low (OR=0.18, 95%CI=0.04-0.85) and somewhat low family income (OR=0.26, 95% CI=0.09–0.73)] was significantly positively associated with the total severity scores for cognitive symptoms. In African American women, only somewhat low family income (OR=0.38, 95% CI=0.15-0.92) was significantly associated with the total severity scores of cognitive symptoms.
Conclusions: The findings supported significant associations of socioeconomic factors to cognitive symptoms experienced during menopausal transition. Because this was a secondary analysis, further studies on the associations of socioeconomic factors to cognitive symptoms of midlife women are needed among diverse groups of midlife women.