According to an investigation by the World Health Organization (WHO), the population of women at least 50 years of age will reach 1.2 billion by 2030 [1]. Around this age, women will experience an important transition in their life - menopause. Most will experience perimenopausal symptoms, some of which will last for a short time, some for decades, and some will have a passive effect on their life to some extent. A recent survey showed that perimenopausal symptoms, hormone replacement treatment, marital status, educational status, and osteoporosis are associated with the quality of life (QOL) in perimenopausal and postmenopausal women [2]. During this period, many women will be disturbed by lower urinary tract symptoms, which may also have a negative effect on their life to some extent [3]. Another recent survey showed that overactive bladder (OAB), stress urinary incontinence (SUI), and mixed urinary incontinence (MUI) have a passive effect on the QOL in perimenopausal and postmenopausal women [4].

The Sixth National Census of China showed the total population of China to be 1,370,536,875 in 2015 [5]; thus, the number of women in China over 50 years of age is quite large. Past research has demonstrated that many factors affect the QOL of women during this special period; however, there has been lack of such research in Chinese women thus far. The current survey aims to explore the factors related to the QOL in Chinese perimenopausal and postmenopausal.

The study initially included 403 women aged 36-76 years who visited the menopause clinic of Peking University First Hospital between September 2012 and December 2013. The Peking University First Hospital is a famous Third Class A hospital in China, with an average of 7,000 consultations per day in all of its outpatient clinics. About half of the patients were from other provinces in China. The menopause clinic is an outpatient clinic of this hospital. The study was approved by the Clinical Ethics Committee of Peking University First Hospital (Grant No. 2013 [681]) and all of the women provided informed consent to participate.

Participants with menopausal symptoms and menopause-related irregular rhythm (menstruation less than 12 times/year) or amenorrhea for 12 consecutive months were included. A total of 320 women met the criteria and were included in the final sample of the study. Participants were classified as having either (1) natural menopause or (2) menopausal symptoms. WHO defines natural menopause as the permanent cessation of menstruation resulting from the loss of ovarian follicular activity. Natural menopause is recognized to have occurred after 12 consecutive months of amenorrhea for which there is no other obvious pathological or physiological cause [1]. Menopausal symptoms refer to a wide variety of physical and emotional experiences that may or may not be related to hormonal or menstrual changes including: hot flashes, vaginal dryness, loss of libido, depression, anxiety, irritability, poor memory, loss of concentration, mood swings, insomnia, tiredness, aching limbs, loss of energy, and dry skin [6].

A cross-sectional questionnaire survey was administered to the women enrolled in the study. Figure 1 presents the study flow diagram. A self-administered questionnaire comprising 260 items over five pages was given to the participants who completed it in approximately 20 minutes. The questionnaire recorded general information such as age, profession, body weight, body mass index (BMI), marital status, educational level, menstrual history, childbearing history, and previous or current diseases based on diagnoses from the patient’s doctor or during annual physical examinations. The questionnaire also included the modified Kup-perman index (mKMI), overactive bladder symptom score (OABSS), and the short form health survey (SF-36). The mKMI is widely used to evaluate menopausal symptoms. The OABSS is widely used to diagnose OAB, drug use, and lifestyle. The SF-36 is widely used to evaluate the QOL. Additional details for the OABSS, mKMI, and SF-36 are provided below. The patient’s attitude towards the occurrence of menopause was also assessed through the questionnaire.

Most of the independent variables, such as menopausal status, marital status, profession, educational background, exercise times, monthly income, complications (according to medical records), as well as the mKMI, OABSS, and SF-36 were investigated using closed-ended questions. Other variables, including age at menarche, last menstrual period, duration of menopausal symptoms, height, and weight were assessed using open-ended questions. All women completed the questionnaire under the guidance of doctors who were trained and certified in the use of the questionnaire. Trained doctors completed the items in the questionnaire that needed to be calculated such as BMI and the total scores for the mKMI, OABSS, and SF-36. Trained doctors also interpreted medical terms in the questionnaire. All doctors were from the Department of Obstetrics and Gynecology. The time to fill out the questionnaire was restricted to 20 minutes.

OABSS: OAB was diagnosed using the OABSS, which is a symptom assessment tool designed to quantify OAB symptoms using a single score. It includes questions about the following four symptoms of OAB: daytime frequency, night time frequency, urgency, and urge incontinence. The Chinese version of the OABSS scale has been validated for the Chinese population [7]. The subjects were asked to rate their symptom severity using a Likert scale, with maximum (most severe) scores of 2, 3, 4, and 5 for daytime frequency, night time frequency, urgency, and urge incontinence, respectively. The total score ranged from 0 to 15, with a higher score indicating more severe OAB. According to clinical guidelines, a minimum OABSS score of 3 and a minimum urgency score of 2 are required to diagnose OAB, and the severity of OAB is classified as mild (OABSS, 3-5), moderate (OABSS, 6-11), or severe (OABSS, 12-15) [8].

mKMI: The mKMI is more sensitive than the menopause rating scale for the evaluation of menopausal symptoms in Chinese populations [9], and it considers 13 symptoms divided into the following four grades (0-3 points) according to the severity: 0=no symptoms, 1=mild symptoms, 2=moderate symptoms, and 3=severe symptoms. The weighted score for hot flashes or sweating is 4 points: paresthesia, insomnia, mood swings, sexual problems, and urinary infection are scored 2 points each, and other symptoms are scored 1 point each. The authors calculated the morbidity of menopausal symptoms using an mKMI cutoff score of ≥ 15, which was the diagnostic criterion. Menopausal symptoms were classified according to the mKMI score as mild (mKMI, 15-24), moderate (mKMI, 25-34), or severe (mKMI, ≥ 35). All of the above criteria were based on definitions cited in the Journal of Chinese Gynecology and Obstetrics, 2007 [10].

SF-36: The SF-36 questionnaire is widely used throughout the world to evaluate the QOL. The SF-36 questionnaire includes nine dimensions: physical functioning (PF; range 10-30), physical role (PR; range, 4-8), bodily pain (BP; range, 2-11), general health (GH; range 5-25), vitality (VT; range, 4-24), social functioning (SF; range, 2-10), emotional role (ER; range, 3-6), mental health (MH; range, 5-30), and health transition (HT). The dimensions of PF to GH represent the physical component and VT to MH represent the mental component of the QOL. The derived score for each dimension = (origin score-lowest possible score)/possible score range*100, and the total QOL is the sum of the derived score for PF to MH. The International Quality Of Life Assessment (IQOLA) determined SF-36 to be an important evaluation tool [11]. The Chinese version has been validated [12-14].

The initial sample of the current study was 403 patients and 320 patients were included in the final sample.

Statistical analyses were performed using the Statistical Analysis System (v.9.4). Data are presented as mean ± standard deviation (SD) for continuous variables. The median, mean, maximum, and minimum, Q1, and Q3 values were calculated for the final menstrual period and duration of menopausal symptoms. Categorical variables were expressed as frequencies and percentages. The t-test was used to evaluate differences for continuous variables. Cronbach’s α was used to test for questionnaire intramural consistency. Spearman correlation was performed prior to binary logistic regression to eliminate the possibility of collinearity among variables. Single factor logistic regression analysis was performed to determine the possible factors related to the QOL. Binary multivariate logistic regression analysis (method=ENTER) was performed to identify the factors associated with the QOL. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to evaluate the risk factors. A linear-regression analysis was performed to explore the linear association between continuous variables. A p-value of < 0.05 was considered statistically significant.

Of the 403 questionnaires received, 83 were excluded according to the exclusion criteria. Therefore, 320 patients included the final study sample. The average age was 52.55±5.960 years and the participants were diverse in educational background and profession (Table 1). The average age of menarche was 13.75±1.712 years and the average number of pregnancies was 2.44±1.469. The average mKMI, total OABSS, and total QOL scores were 21.72±9.790, 2.13±2.313, and 492.51±145.348, respectively. Additional details are provided in Table 1.

The analysis of intramural consistency for the SF-36 demonstrated that the intramural consistency was acceptable as each consistency score was less than the Cronbach’s α (Table 2).

Single factor logistic regression of the total QOL score was not statistically significant for: age, profession (compared to the state organizations), monthly income, complications (including hypertension, diabetes, osteoporosis, hyperlipidemia, stroke, cervical spondylosis, uterine (myoma) fibroid, benign ovarian tumor, benign breast tumor, cervical cancer, breast cancer), family life situation (including living with husband, children, parents, father-in-law and mother-in-law, grandchildren, solitude), age of menarche, marital status, number of pregnancies, term birth number, natural delivery number, cesarean section number, height, weight, waistline, hipline, duration of perimenopausal symptoms, methods of relieving perimenopausal symptoms [including regular exercise, chatting with family, traditional Chinese medicine (TCM), developing new interests, ‘letting it be’, and other ways], diet guidance during the perimenopause period, medicine to relieve perimenopausal symptoms, routine exercise ways (including walking, jogging, brisk walking, swimming, sitting-up exercise, ball games, cycling, other ways), exercise frequency (>3 times/week), pelvic floor muscle function, and pelvic organ prolapse (Table 3). However, educational background [OR=0.759, 95%CI (0.617, 0.934), p = 0.009], current smoking [OR=9.477, 95%CI (1.186, 75.702), p=0.034], passive smoking [OR=1.635, 95%CI (1.044, 2.560), p = 0.032], coronary heart disease [OR=5.267, 95%CI (1.135, 24.433), p = 0.034], low frequency of sexual intercourse in the last six months [OR=2.336, 95%CI (1.065, 5.124), p = 0.034], BMI [OR=1.697, 95%CI (1.090, 2.640), p = 0.019], the duration of menopausal symptoms [OR=2.631, 95%CI (1.214, 5.704), p = 0.014], mKMI [OR=1.119, 95%CI (1.085, 1.153), p < 0.001], passive attitude towards menopause [OR=3.142, 95%CI (1.972, 5.007), p < 0.001], dancing [OR=0.563, 95%CI (0.334, 0.951), p = 0.032], OABSS [OR=1.268, 95%CI (1.125, 1.429), p < 0.001], and degree of urine leakage [OR=1.205, 95%CI (1.008, 1.440), p = 0.041] were significantly associated with total QOL. While educational background and dancing were protective factors for total QOL, the remaining were risk factors (Table3).

Multiple binary logistic regression analysis demonstrated that current smoking [OR=10.13, 95%CI (1.14, 89.88), p = 0.038], mKMI [OR=9.151, 95%CI (1.996, 41.96), p = 0.004], and a passive attitude towards menopause [OR=3.465, 95%CI (1.878, 6.392), p < 0.001] were related risk factors for low total QOL. However, educational background, frequency of sexual intercourse in the last six months, passive smoking, coronary heart disease, BMI, the duration of menopausal symptoms, dancing, and the degree of urine leakage were not statistically significant (Table 4).

Multiple binary logistic regression analysis was also performed for each dimension of QOL using the potential factors determined from single factor logistic regression analyses performed for each dimension (results of the individual single factor analyses are not shown). Factors significantly associated with PF were: age [OR=1.062, 95%CI (1.010, 1.117), p = 0.019], current smoking [OR=7.464, 95%CI (1.394, 39.983), p = 0.019], mKMI [OR=3.741, 95%CI (1.436, 9.743), p = 0.007], and OABSS [OR=1.825, 95%CI (1.035, 3.220), p = 0.038]. However, osteoporosis, coronary heart disease, cervical spondylosis, frequency of sexual intercourse in the last six months, the duration of menopausal symptoms, regular exercises relieving menopausal symptoms, jogging, brisk walking, dancing, swimming, and ball games were not statistically significant (Tables 5 and 6).

Factors significantly associated with PR included: frequency of sexual intercourse in the last six months [OR=2.489, 95%CI (1.056, 5.867), p = 0.037], mKMI [OR=4.499, 95%CI (1.432, 14.136), p = 0.010], passive attitude [OR=1.989, 95%CI (1.148, 3.445), p = 0.014], dancing [OR=0.495, 95%CI (0.270, 0.909), p = 0.023], and OABSS [OR=2.933, 95%CI (1.591, 5.407), p = 0.001). However, age, BMI, the duration of menopausal symptoms, and jogging were not statistically significant (Tables 5 and 9).

Factors significantly associated with BP included: height [OR=0.955, 95%CI (0.912, 0.999), p = 0.047] and TCM to relieve perimenopausal symptoms [OR=1.787, 95%CI (1.075, 2.971), p = 0.025]. However, hypertension, hyperlipidemia, coronary heart disease, BMI, waistline, mKMI, passive attitude towards menopause, jogging, and OABSS were not statistically significant (Tables 7 and 8).

Factors significantly associated with GH included: height [OR=0.932, 95%CI (0.891, 0.974), p = 0.002], TCM to relieve menopausal symptoms [OR=1.836, 95%CI (1.042, 3.225), p = 0.036], mKMI [OR=2.879, 95%CI (1.047, 7.918), p = 0.041], passive attitude towards menopause [OR=2.526, 95%CI (1.503, 4.245), p < 0.001]. However, ‘let it be’ was not statistically significant (Tables 7 and 8).

Factors significantly associated with VT included: living with husband [OR=0.483, 95%CI (0.238, 0.978), p = 0.043], mKMI [OR=3.403, 95%CI (1.213, 9.543), p = 0.020], and a passive attitude towards menopause [OR=3.261, 95%CI (1.969, 5.401), p < 0.001]. However, passive smoking, coronary heart disease, and OABSS were not statistically significant (Tables 9 and 10).

Factors significantly associated with SF included: mKMI [OR=3.779, 95%CI (1.240, 11.513), p = 0.019], passive attitude towards menopause [OR=3.308, 95%CI (1.949, 5.614), p < 0.001], and OABSS [OR=2.067, 95%CI (1.163, 3.675), p = 0.013]. However, pregnancies and swimming were not statistically significant (Tables 9 and 10).

Factors significantly associated with RE included: passive smoking [OR=1.765, 95%CI (1.018, 3.060), p = 0.043), low frequency of sexual intercourse in the last six months [OR=2.638, 95%CI (1.056, 6.593), p = 0.038], mKMI [OR=4.073, 95%CI (1.272, 13.045), p = 0.018], passive attitude towards menopause [OR=3.455, 95%CI (1.921, 6.214), p < 0.001], and OABSS [OR=2.502, 95%CI (1.343, 4.661), p = 0.004]. However, education background, coronary heart disease, and jogging were not statistically significant (Tables 11 and 12).

Factors significantly associated with MH included: mKMI [OR=8.329, 95%CI (2.144, 32.364), p = 0.002], passive attitude towards menopause [OR=2.224, 95%CI (1.136, 4.354), p = 0.020], and OABSS [OR=2.304, 95%CI (1.066, 4.981), p = 0.034]. However, monthly income, passive smoking, chatting with family to relieve perimenopausal symptoms, swimming, and sitting-up exercise were not statistically significant (Tables 11 and 12).

Results for t-tests and linear regression analyses regarding information about the relatives living with the participants and association with QOL dimensions were as follows: the number of relatives showed no linear regression association with any dimension of QOL, living with husband + parents was better than living with only with husband in terms of GH and MH, living with husband + parents was better than living with husband + children in terms of VT, SF, RE, MH, and total QOL. Results from similar analyses regarding complications were as follows: the number of complications was associated with PF, GH, and total QOL; gynecological disease was better than hypertension in terms of PF and BP, and better than cervical spondylosis in terms of PF. Results regarding methods to relieve perimenopausal symptoms were as follows: the number of complications was associated with PF, regular exercise to relieve perimenopausal symptoms was better than using TCM in terms of VT, culturing hobbies to relieve perimenopausal symptoms was better than regular exercise in terms of SF, and the number of routine sports showed association with PF, RP, VT, MH, and total QOL.

The present survey creatively used the mKMI, OABSS, and SF-36 QOL questionnaires to simultaneously investigate many factors that potentially impact the QOL in perimenopausal and postmenopausal Chinese women. The results showed that current smoking, mKMI score, a passive attitude towards menopause, and high OABSS are risk factors for a low total QOL score. In addition, the results showed that each QOL dimension is associated with specific risk and protective factors. Below, the authors discuss the findings in the context of previous reports.

In general, women during the perimenopausal and postmenopausal periods will be affected by a variety of factors. Current smoking, perimenopausal symptoms, a passive attitude towards menopause, and high OABSS are risk factors for low QOL, while dancing, height, and living with a husband may be protective factors for some QOL dimensions. Each QOL dimension is associated with specific risk factors, and hot flashes may not be the most important factor to the QOL. Paresthesia, depression, fatigue, muscle/ joint pain, and palpitations may also be risk factors to both the physical and mental components of the QOL. Individualized treatment of women during this special period may improve the QOL to a large extent. Fully exploring the factors affecting women during this special period can help make more precise and effective treatments that may improve the QOL.