br General sociodemographic questionnaire br
2.4. General sociodemographic questionnaire
A sociodemographic questionnaire was also completed by partici-pants. Variables included age (in years), parity, education level (low, middle and high), marital status (single, divorced or widowed), em-ployment status (working, unemployed, housewife or unable to work), type of cancer, last menstrual period, depressed mood, diagnosis of osteoporosis, tobacco and alcohol intake, presence of climacteric symptoms and their treatment (soya isoflavones, cimicifuga racemosa, purified pollen extract or hormone replacement therapy). One unit of Maturitas 120 (2019) 35–39
Sample characteristics according to the history of cancer. Data 3X FLAG Peptide given as frequencies (%) or medians [interquartile range; p25-p75].
Cancer survivors Non cancer
BMI = body mass index.
alcohol was considered to be a standard glass of beer (285 ml), a single measure of spirit liquor (30 ml), a medium-sized glass of wine (120 ml), or one measure of an aperitif (60 ml) or equivalent. A cut-oﬀ of 3 units/ day was considered to diﬀerentiate between heavy and moderate drinkers .
Menopause-related quality of life among resilience subgroups in menopausal cancer survivors.
n = 80 LOW RESILIENCE HIGH RESILIENCE
Correlation between WYRS-14 and Cervantes-SF-16 total scores among cancer survivors.
Spearman rho coeﬃcient WYRS-14 TOTAL SCORE
Correlation between WYRS-14 and Cervantes-SF-16 total scores among all participants.
Rho de Spearman WYRS-14 TOTAL SCORE
Fig. 2. Correlation between WYRS-14 and Cervantes-SF-16 total scores among all participants.
Fig. 1. Correlation between WYRS-14 and Cervantes-SF-16 total scores among cancer survivors.
2.5. Statistical methods
Qualitative variables were summarized by their frequency dis-tribution and quantitative variables by their mean and standard de-viation ( ± SD). Continuous non-normally distributed variables were summarized by the median and interquartile range. Cronbach’s alpha coeﬃcient was used to measure internal consistency. The Student’s t-test or ANOVA was used to compare continuous variables. Non-para-metric variables were compared using the Mann-Whitney test or Kruskal-Wallis test, while categorical variables were compared using the chi-squared test. Spearman’s rank correlation coeﬃcient was cal-culated to determine the correlation between the scores on the WYRS-14 and the Cervantes-SF-16. For all tests, a significance value of 5% was used.
Sample size was set so as to achieve 80% power and a 5% alpha error.
The statistical analysis was performed using IBM SPSS Statistics 23 for Windows.
A total of 300 patients were invited to participate in this in-vestigation, 7 of whom provided incorrect or non-valid data (2.33%) and were excluded. Baseline characteristics of the remaining 293 women, 213 without a history of cancer and 80 cancer survivors, are shown in Table 1. Among the cancer survivors, 49 had breast cancer, 5 ovarian, 19 endometrial, 3 vulva and 4 cervical cancer. There were no statistically significant diﬀerences between cancer survivors and non-cancer participants in age, BMI, tobacco and alcohol intake, education level, employment status, time since last menstrual period, depressed mood or diagnosis of osteoporosis. Resilience level, measured by the WYRS-14, was significantly higher among cancer survivors (median total score 86.00 [75.25–93.00]) than in the non-cancer group (median total score 80 [69.50–88.00]) (p < 0.001).