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. 2017 Oct 23;7:13854. doi: 10.1038/s41598-017-13395-z

Association between pulse wave velocity and hot flashes/sweats in middle-aged women

Ruwei Yang 1,#, Yang Zhou 1,#, Changbin Li 1, Minfang Tao 1,
PMCID: PMC5653868  PMID: 29062032

Abstract

As women age and go through menopause, they suffer a higher incidence of cardiovascular morbidity and mortality. Previous studies have shown that a relationship exists between hot flashes/sweats and an increased risk of cardiovascular disease. However, the association between hot flashes/sweats and arterial stiffness is unclear. We aim to explore the relationship between hot flashes/sweats and arterial stiffness using the modified Kupperman index (KMI) questionnaire and measure the brachial-ankle pulse wave velocity (baPWV). The prevalence of hot flashes in our research was reported to be 41.77%. There was a statistically significant difference between the mean baPWV among groups that experienced different severities of hot flashes/sweats according to one-way ANOVA test (p < 0.001). The baPWV values were positively associated with the severity of hot flashes/sweats based on linear regression after adjusting for established cardiovascular confounders (95% CI: (5.86, 43.23), p = 0.01). To the best of our knowledge, this study is the first investigation to propose that baPWV may serve both as an objective index for evaluating the severity of hot flashes/sweats and as a predictor of arterial stiffness beyond Cardiac Vascular Disease (CVD) risk factors in middle-aged women.

Introduction

Vasomotor symptoms (63.5%), fatigue (50.7%) and palpitations (35.1%) are common symptoms in peri- and postmenopausal Chinese women1. Hot flashes or night sweats, which are vasomotor symptoms, are regarded as thermoregulatory events that might be associated with estrogen deprivation or fluctuation2 and may exert a negative impact on the quality of life of menopausal women3. In addition, a growing body of evidence suggests a link between vasomotor symptoms and cardiovascular risks46; however, not all studies in the field agree79, possibly due to the use of different biomarkers, sample selection bias, and use of observational versus interventional studies.

The pulse wave velocity is the wave velocity between two points of an arterial system; it is positively correlated with arteriosclerosis and is useful in clinical applications to evaluate arterial stiffness10. The ability to measure brachial-ankle pulse wave velocity (baPWV) is commonly available in clinical practice; it is precise, not time-consuming, simple and non-invasive11.

Women’s risk of cardiovascular disease may increase as they progress through menopause12,13. Studies of the association between hot flashes/sweats and cardiovascular disease incidence reported conflicting results. It is not clear whether an association exists between hot flashes/sweats and baPWV in middle-aged women. Therefore, we aim to evaluate the impact of hot flashes/sweats on arterial stiffness by studying the correlation between hot flashes/sweats and baPWV in an effort to guide protocols for handling hot flashes/sweats and to aid in monitoring arterial stiffness in peri- and postmenopausal women.

Results

Participants

A total of 589 subjects were enrolled in this study; the characteristics of the study population are listed in Table 1. The mean age (SD) of participants was 50.5(5.7). The mean height, weight, BMI, systolic pressure, diastolic pressure and heart rate all followed normal distributions, the incidence of hot flashes/sweats was 41.77%.

Table 1.

Characteristics of the study population.

Characteristic Menopausal Status
Total Pre-menopause Peri-menopause Early Post-menopause Late Post-menopause
n = 589 n = 194 n = 114 n = 140 n = 141
Age(year) 50.50 ± 5.70 45.07 ± 3.28 49.14 ± 3.60 52.95 ± 3.41 56.62 ± 3.66
Height (cm) 159.60 ± 5.03 160.44 ± 4.35 159.11 ± 4.85 159.67 ± 4.75 158.78 ± 6.07
Weight(kg) 59.56 ± 7.99 59.21 ± 7.64 59.46 ± 7.60 60.72 ± 8.11 58.97 ± 8.59
BMI(kg/m2) 23.38 ± 3.01 23.00 ± 2.83 23.50 ± 3.01 23.81 ± 3.02 23.38 ± 3.20
SBP(mmHg) 125.27 ± 17.87 119.93 ± 16.18 124.19 ± 19.11 127.05 ± 18.05 131.72 ± 16.65
DBP(mmHg) 76.38 ± 11.54 73.06 ± 10.07 75.64 ± 12.41 78.26 ± 10.04 79.69 ± 10.90
Heart rate(bpm) 69.81 ± 10.28 70.29 ± 9.77 68.33 ± 9.69 69.54 ± 10.07 70.60 ± 11.51
Age groups, n(%)
 40–44 131(22.2) 107(55.2) 19(16.7) 3(2.1) 2(1.4)
 45–49 131(22.2) 71(36.6) 37(32.5) 18(12.9) 5(3.5)
 50–54 181(30.7) 16(8.2) 56(49.1) 80(57.1) 29(20.6)
 55–60 146(24.8) 0(0.0) 2(1.8) 39(27.9) 105(74.5)
Marital status, n(%)
 Married 555(94.2) 181(93.3) 110(96.5) 133(95.0) 131(92.9)
 Divorced 20(3.4) 8(4.1) 2(1.8) 6(4.3) 4(2.8)
 Separated, Widowed 10(1.7) 2(1.0) 2(1.8) 1(0.7) 5(3.5)
 Unmarried 4(0.7) 3(1.5) 0(0.0) 0(0.0) 1(0.7)
Employment status, n(%)
 Yes 248(42.1) 125(64.4) 62(54.4) 44(31.4) 17(12.1)
 No 341(57.9) 69(35.6) 52(45.6) 96(68.6) 124(87.9)
Education, n(%)
 None 52(8.8) 12(6.2) 9(7.9) 11(7.9) 20(14.2)
 Primary 75(12.7) 24(12.4) 15(13.2) 21(15.0) 15(10.6)
 Junior high 148(25.1) 45(23.2) 40(35.1) 30(21.4) 33(23.4)
 Senior high 172(29.3) 51(26.3) 28(24.6) 46(32.9) 47(33.3)
 College 130(22.1) 58(29.9) 20(17.5) 29(20.7) 23(16.3)
 Postgraduate 12(2.0) 4(2.1) 2(1.8) 3(2.1) 3(2.1)
Gynecological diseases, n(%)
 Uterine fibroid 212(36.0) 56(28.9) 46(40.4) 60(42.9) 50(35.5)
 Endometriosis 9(1.5) 3(1.5) 1(0.9) 4(2.9) 1(0.7)
Chronic disease, n(%)
 Hypertension 105(17.8) 23(11.9) 14(12.3) 30(21.4) 38(27.0)
 Diabetes 42(7.1) 9(4.6) 4(3.5) 17(12.1) 12(8.5)
 Hotflashes/sweats(yes), n(%) 41(21.1) 57(50) 61(56.4) 4(48.9) 246(41.4)

BaPWV data

According to one-way ANOVA, there was a statistically significant difference in baPWV values across age groups (p < 0.001), menopausal status (p < 0.001), and severity of hot flashes/sweats (p < 0.001). The baPWV of each group was significantly different. (p < 0.001) (Table 2).

Table 2.

Comparison of baPWV among different groups by age, menopausal status and degree of severity of hot flashes/sweats.

characteristics n mean ± SD 95% CI
lower upper
Age 40–44 113 1193.32 ± 169.72* 1161.69 1224.96
Age 45–49 141 1241.54 ± 167.50* 1213.69 1269.43
Age 50–54 183 1381.92 ± 236.69* 1347.40 1416.44
Age 55–60 152 1462.64 ± 272.34* 1419.00 1506.29
Premenopause 194 1226.89 ± 185.55* 1200.61 1253.16
Perimenopause 114 1292.51 ± 188.83* 1257.23 1327.91
Early Postmenopause 140 1389.36 ± 233.12* 1350.40 1428.31
Late Postmenopause 141 1455.62 ± 289.89* 1407.35 1503.89
Hot flashes/sweats 0 points 343 1287.09 ± 227.30* 1262.95 1311.23
Hot flashes/sweats 1 point 178 1376.07 ± 229.59* 1342.11 1410.03
Hot flashes/sweats 2 points 55 1433.86 ± 289.78* 1355.53 1512.20
Hot flashes/sweats 3 points 13 1526.27 ± 243.72* 1327.84 1724.70

*Means p <0.001 CI: Confidence Interval.

Pearson’s correlation analyses revealed that systolic blood pressure, diastolic blood pressure, age, heart rate, triglyceride (TG), body mass index (BMI), and low density lipoprotein (LDL) levels were positively correlated with baPWV (p < 0.05). Height and HDL levels were significantly negatively correlated with baPWV (Table 3). Spearman’s correlation analyses revealed that hot flashes/sweats (r = 0.243, p < 0.001), menopausal status (r = 0.367, p < 0.001), and the KMI total score (r = 0.237, p < 0.001) were significantly positively correlated with baPWV menopausal status and hot flashes/sweats (Table 3).

Table 3.

Correlation analysis of baPWV with some characteristics.

Items r p value
Age(year) 0.439** <0.001
HDL(mmol/L) −0.093* 0.024
LDL(mmol/L) 0.136** 0.001
TG(mmol/L) 0.200** <0.001
TC(mmol/L) 0.139** 0.001
Height(cm) −0.114** 0.006
Weight(kg) 0.081 0.050
BMI(kg/m2) 0.140** 0.001
Systolic pressure(mmHg) 0.594** <0.001
Diastolic pressure(mmHg) 0.548** <0.001
Heart rate(bpm) 0.302** <0.001
Menopausal status 0.367** <0.001
Flashes/sweats(points) 0.243** <0.001
KMI total score(points) 0.237** <0.001

**Means p <0.001; *Means p <0.05. HDL, high-density lipoprotein; LDL, Low density lipoprotein; TC, total cholesterol; TG, Triglyceride; BMI, body mass index. Hot flash and KMI total score were analyzed by Spearman’s correlation, others were computed by Pearson’s correlation.

As shown in Table 4, we observed a significant positive association between baPWV and hot flashes/sweats (p = 0.010). BaPWV was also significantly associated with SBP, age, hypertension, heart rate, and diabetes mellitus in the full multiple linear regression model following corrections for age, BMI, HDL, LDL, TC, TG, DBP, height, and menopausal status.

Table 4.

Linear regression analysis of baPWV with hot flashes/sweats in an adjusted model.

Traits Unstandardized coefficients 95% CI p value Corrected R²
B Std Error
SBP(mmHg) 3.76 0.64 (2.5, 5.025) <0.001 0.54
Age(year) 10.67 1.31 (8.11, 12.24) <0.001
Hypertension(yes) −147.53 20.21 (187.21, 107.84) <0.001
Heart rate (bpm) 3.68 0.70 (2.31, 5.05) <0.001
Diabetes mellitus(yes) −98.58 27.04 (−151.69, −45.46) <0.001
Flashes/sweats 24.54 9.52 (5.86, 43.23) 0.010

Covariates: BMI, HDL, LDL, TC, TG, DBP, height, menopausal status.

Discussions

Based on 589 women’s modified KMI scores, the prevalence of hot flashes/sweats was found to be 41.77%, which is similar to previous findings from other Asian countries, such as Japan, Hong Kong, Singapore14 and South Korea15, and was significantly lower than that found in white populations16,17. The discrepancy may be explained by the racial and cultural context18, demographic and socioeconomic characteristics19, and methods of symptom identification20.

This study revealed that the pulse wave velocity is significantly associated with aging, menopausal status and duration of menopause; this finding parallels the relationship between the decrease in estrogen levels in menopausal women and vascular aging. As a result, baPWV is considered to be a possibly effective measure to evaluate arterial stiffness in middle-aged women.

Our study found that the pulse wave velocity was positively correlated with the frequency of hot flashes/sweats and the severity of symptoms (r = 0.243, p < 0.001). After adjusting for established cardiovascular risk factors, such as systolic blood pressure, diastolic blood pressure, age, menopause, heart rate, TG, BMI, TC, LDL, HDL, and hot flashes/sweats (95% CI: 5.86–43.23, p = 0.01), the results remain significant using a linear regression analysis. Therefore, we can safely infer that the assessment of baPWV is a valuable tool to evaluate symptoms of hot flashes/sweats, the method provides an objective standard by which to assess symptoms of hot flashes in menopausal women.

It is known that SBP, DBP, age, menopause, BMI, TG, TC and LDL are risk factors for cardiovascular diseases21. Our analyses have shown that SBP, DBP, age, heart rate, TG, BMI, TC, LDL were significantly positively correlated with baPWV, which is consistent with previous studies22. After adjusting for these items in addition to a history of hypertension and diabetes mellitus, the independent risk factors for higher arterial stiffness were found to be age, systolic blood pressure, history of hypertension and diabetes mellitus, heart rate and hot flashes/sweats. We can therefore extrapolate self-reporting hot flashes/sweats has clinical implications for predicting arterial stiffness in menopause beyond other CVD risk factors.

Additionally, we should pay more attention to hot flashes/sweats. We suggest that people who experience severe hot flashes/sweats should focus on atherosclerosis and baPWV, and health staff should prioritize the treatment of people with hot flashes/sweats by, for example, providing menopausal hormone therapy.

To the best of our knowledge, this may be the first study to suggest that hot flashes/sweats and their severity are associated with higher baPWV. We suggest that baPWV may serve as a metric to monitor arterial stiffness for middle-aged women. Additionally, baPWV can likely be regarded as an objective index for evaluating the severity of hot flashes/sweats; furthermore, self-reporting hot flashes/sweats is of prominent value to assess arterial stiffness independent of CVD risk factors in middle-aged women. however, it is worthy of further exploration and research. Because of the limited survey samples, more community-based studies on large groups of people are important. Our team will continue to conduct future relevant research to confirm the validity of these results. We are now conducting a cohort study of measuring baPWV before and after MHT to explore changes in pulse wave velocity after MHT in middle-aged women.

Limitations

Several limitations need to be mentioned. First, the inherent drawback of an observational survey may attenuate the causal relationship. Secondly, systemic errors due to the baPWV tool may be produced, for its calculation of path length comes from a height-based formula for Japanese population. However, the height of Chinese is similar to that of Japanese. Finally, hot flashes/sweat ascertained by questionnaire would produce memory bias. Therefore, further longitudinal study is needed to confirm these relationships. Our team is now working on the following-up investigation.

Conclusions

  1. BaPWV may serve as a metric to monitor arterial stiffness in middle-aged women

  2. BaPWV may provide an objective standard to evaluate the severity of vasomotor symptoms.

  3. Self-reporting hot flashes/sweats may be regarded as an easy and quick predictor of arterial stiffness independent of CVD risk factors in middle-aged women.

Methods

Study Subjects

Women who received a physical examination at the Center of Health Examination of Shanghai Jiao Tong University Affiliated Sixth People’s Hospital from the 28st of November 2016 to the 28th of September 2017 were enrolled in this study. The inclusion criteria included the following: 1) aged between 40 and 60 years; 2) normal cognition, has the ability to complete the questionnaire by herself; and 3) volunteered to participate in this research. The exclusion criteria included the following: 1) female who received menopausal hormone treatment (MHT) or any traditional Chinese medicine indicated for menopause in the past 6 months; 2) history of mental disorder; and 3) history of serious organic diseases (e.g., coronary heart disease, stroke, systemic autoimmune disease).

A total of 589 women met to the criteria. The reproductive medicine center of the Shanghai Sixth People’s Hospital institutional review board approved this study, This analytic cross-sectional study enrolled 1904 participants aged 40–60 years who visited the physical examination center in the Shanghai Sixth people’s Hospital, Shanghai Jiao Tong University School of Medicine, China, from January 2016 to November 2016. The study protocol was approved by the Ethics Committee of Shanghai Sixth People’s Hospital, and the study was performed in accordance with the approved guidelines. All the participants provided written informed consents after full explanation of the study.

Questionnaire

The women’s health demographic questionnaire included basic information, such as age, education, marital status, occupation, history of MHT and traditional Chinese medicine, menopausal states, menstrual states, gynecological history, and past history. This questionnaire has been applied previously23,24.

Menopausal status group

According to the stages of reproductive aging workshop (STRAW + 10)25, we divided subjects into the following groups: premenopausal (with regular menstrual cycle), perimenopausal (consecutive irregularities >7 days from their normal cycle), early postmenopausal (absence of menstrual periods for at least 12 months and less than 5 years) and late postmenopausal (absence of menstrual periods for more than 5 years).

Menopausal symptoms and hot flashes/sweats group

We used a valid modified KMI scale in Chinese to evaluate the severity of menopausal symptoms26. The modified KMI scale consists of three aspects: 1) somatic symptoms, such as hot flashes/sweats, palpitation, vertigo, headache, paresthesia, formication, arthralgia and myalgia; 2) mental symptoms, such as fatigue, nervousness and melancholia; and 3) genitourinary tract symptoms, such as urinary infections and sexual complaints. The sum of the scores from 0 to 63 points were categorized into four grades:

  1. score ≤6, asymptomatic (148 subjects)

  2. 6< score ≤15, mildly symptomatic (259 subjects)

  3. 15< score ≤30, moderately symptomatic (159 subjects)

  4. score >30, severely symptomatic (23 subjects)

According to the modified KMI subproject, we divided the hot flashes/sweats group into four groups:

  1. 10 point, no hot flashes/sweats (342 subjects)

  2. 1 point, hot flashes and sweats ≤3 times/day (178 subjects)

  3. 2 points, 3< hot flashes and sweats ≤9 times/day (55 subjects)

  4. 3 points, hot flashes and sweats >9 times/day (14 subjects).

Measurement of PWV

We used an automatic waveform analyzer (BP-203RPE III, OMRON, Japan) to measure baPWV. Participants were asked to remain supine and at rest for 5 minutes before the PWV examination27. We record the heart rate concurrently.

Laboratory examination

All participants underwent a fasting lipid profile consisting of total cholesterol (TC), triglycerides triglyceride (TG), high-density lipoprotein (HDL)and low density lipoprotein (LDL). Height, weight and systolic blood pressure (SBP), diastolic blood pressure (DBP) were determined on the same day. Body mass index (BMI) was computed by dividing weight in kilograms by the square of their height in meters.

Statistical analysis

SPSS Statistics 23.0 (IBM Corporation, Armonk, NY, USA) was used for all analyses. All variables were presented as the mean ± standard deviation (SD) or number (%). One-way ANOVAs were used to analyze the variation in PWV by menopausal status and degree of hot flashes/sweats. Pearson correlation analysis was performed to evaluate the relationship between age, HDL, LDL, TC, TG, height, weight, BMI, SBP, DBP, heart rate and baPWV. Spearman correlation analysis was performed to evaluate the relationship between menopausal status, hot flashes/sweats and baPWV. Associations with the pulse wave velocity and hot flashes/sweats were computed with a linear regression analysis. R² values were derived from linear regression models. Residuals analysis was performed and diagnostic plots were made to verify model assumptions. A two-sided P-value < 0.05 was considered statistically significant.

Acknowledgements

The authors work the study participants and the research associates who made it possible to complete this research project. This study was supported by grants from the Shanghai Science and Technology Committee (154119050202) and Shanghai Health Development Planning Commission (GWIV15).

Author Contributions

Minfang Tao conceived and designed the study. Ruwei Yang wrote the first draft. Yang Zhou revised the manuscripts. Changbin Li input and managed the data. All of the authors read and approved the final manuscript.

Competing Interests

The authors declare that they have no competing interests.

Footnotes

Ruwei Yang and Yang Zhou contributed equally to this work.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  • 1.Huseth-Zosel A, Strand M, Perry J. Socioeconomic differences in the menopausal experience of Chinese women. J. Post Reprod Health. 2014;20:98–103. doi: 10.1177/2053369114544729. [DOI] [PubMed] [Google Scholar]
  • 2.Freedman RR. Pathophysiology and treatment of menopausal hot flashes. J. Semin Reprod Med. 2005;23:117–25. doi: 10.1055/s-2005-869479. [DOI] [PubMed] [Google Scholar]
  • 3.Avis NE, et al. Health-related quality of life in a multiethnic sample of middle-aged women: Study of Women’s Health Across the Nation (SWAN) J. Med Care. 2003;41:1262–76. doi: 10.1097/01.MLR.0000093479.39115.AF. [DOI] [PubMed] [Google Scholar]
  • 4.Thurston RC, et al. Hot flashes and subclinical cardiovascular disease: findings from the Study of Women’s Health Across the Nation Heart Study. J. Circulation. 2008;118:1234–40. doi: 10.1161/CIRCULATIONAHA.108.776823. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Herber-Gast G, Brown WJ, Mishra GD. Hot flushes and night sweats are associated with coronary heart disease risk in midlife: a longitudinal study. J. BJOG. 2015;122:1560–7. doi: 10.1111/1471-0528.13163. [DOI] [PubMed] [Google Scholar]
  • 6.Silveira JS, et al. Hot flashes: emerging cardiovascular risk factors in recent and late postmenopause and their association with higher blood pressure. J. Menopause. 2016;23:846–55. doi: 10.1097/GME.0000000000000641. [DOI] [PubMed] [Google Scholar]
  • 7.Tuomikoski P, et al. Biochemical markers for cardiovascular disease in recently postmenopausal women with or without hot flashes. J. Menopause. 2010;17:145–51. doi: 10.1097/GME.0b013e3181acefd5. [DOI] [PubMed] [Google Scholar]
  • 8.Svartberg J, et al. Vasomotor symptoms and mortality: the Rancho Bernardo Study. J. Menopause. 2009;16:888–91. doi: 10.1097/gme.0b013e3181a4866b. [DOI] [PubMed] [Google Scholar]
  • 9.Hautamaki H, et al. Menopausal hot flushes do not associate with changes in heart rate variability in controlled testing: a randomized trial on hormone therapy. J. Acta Obstet Gynecol Scand. 2013;92:902–8. doi: 10.1111/aogs.12164. [DOI] [PubMed] [Google Scholar]
  • 10.Yamaji Y, Mitsushima T, Koike K. Pulse-wave velocity, the ankle-brachial index, and the visceral fat area are highly associated with colorectal adenoma. J. Dig Liver Dis. 2014;46:943–9. doi: 10.1016/j.dld.2014.05.012. [DOI] [PubMed] [Google Scholar]
  • 11.Miyano I, et al. Association between brachial-ankle pulse wave velocity and 3-year mortality in community-dwelling older adults. J. Hypertens Res. 2010;33:678–82. doi: 10.1038/hr.2010.56. [DOI] [PubMed] [Google Scholar]
  • 12.Wu L, et al. Effects of lifestyle intervention improve cardiovascular disease risk factors in community-based menopausal transition and early postmenopausal women in China. J. Menopause. 2014;21:1263–8. doi: 10.1097/GME.0000000000000248. [DOI] [PubMed] [Google Scholar]
  • 13.Rahman I, Akesson A, Wolk A. Relationship between age at natural menopause and risk of heart failure. J. Menopause. 2015;22:12–6. doi: 10.1097/GME.0000000000000261. [DOI] [PubMed] [Google Scholar]
  • 14.Yang D, et al. Menopausal symptoms in mid-life women in southern China. J. Climacteric. 2008;11:329–36. doi: 10.1080/13697130802239075. [DOI] [PubMed] [Google Scholar]
  • 15.Yim G, et al. Prevalence and severity of menopause symptoms and associated factors across menopause status in Korean women. J. Menopause. 2015;22:1108–16. doi: 10.1097/GME.0000000000000438. [DOI] [PubMed] [Google Scholar]
  • 16.Williams RE, et al. Menopause-specific questionnaire assessment in US population-based study shows negative impact on health-related quality of life. J. Maturitas. 2009;62:153–9. doi: 10.1016/j.maturitas.2008.12.006. [DOI] [PubMed] [Google Scholar]
  • 17.Gast GC, et al. Menopausal complaints are associated with cardiovascular risk factors. J. Hypertension. 2008;51:1492–8. doi: 10.1161/HYPERTENSIONAHA.107.106526. [DOI] [PubMed] [Google Scholar]
  • 18.El Shafie K, et al. Menopausal symptoms among healthy, middle-aged Omani women as assessed with the Menopause Rating Scale. J. Menopause. 2011;18:1113–9. doi: 10.1097/gme.0b013e31821b82ee. [DOI] [PubMed] [Google Scholar]
  • 19.Perez JA, et al. Epidemiology of risk factors and symptoms associated with menopause in Spanish women. J. Maturitas. 2009;62:30–6. doi: 10.1016/j.maturitas.2008.10.003. [DOI] [PubMed] [Google Scholar]
  • 20.Chedraui P, et al. Menopausal symptoms and associated risk factors among postmenopausal women screened for the metabolic syndrome. J. Arch Gynecol Obstet. 2007;275:161–8. doi: 10.1007/s00404-006-0239-7. [DOI] [PubMed] [Google Scholar]
  • 21.Zhou F, et al. Relationship between brachial-ankle pulse wave velocity and metabolic syndrome components in a Chinese population. J. J Biomed Res. 2014;28:262–8. doi: 10.7555/JBR.28.20130160. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Park JS, et al. Relationships between serum uric acid, adiponectin and arterial stiffness in postmenopausal women. J. Maturitas. 2012;73:344–8. doi: 10.1016/j.maturitas.2012.09.009. [DOI] [PubMed] [Google Scholar]
  • 23.Tao MF, et al. Poor sleep in middle-aged women is not associated with menopause per se.J.Braz. J Med Biol Res. 2016;49:e4718. doi: 10.1590/1414-431X20154718. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Sun D, et al. Sleep disturbance and correlates in menopausal women in Shanghai. J. J Psychosom Res. 2014;76:237–41. doi: 10.1016/j.jpsychores.2013.12.002. [DOI] [PubMed] [Google Scholar]
  • 25.Harlow SD, et al. Executive summary of the Stages of Reproductive Aging Workshop + 10: addressing the unfinished agenda of staging reproductive aging. J.J Clin Endocrinol Metab. 2012;97:1159–68. doi: 10.1210/jc.2011-3362. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Tao M, et al. Correlation between the modified Kupperman Index and the Menopause Rating Scale in Chinese women. J. Patient Prefer Adherence. 2013;7:223–9. doi: 10.2147/PPA.S42852. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Lin YH, et al. Adrenalectomy improves increased carotid intima-media thickness and arterial stiffness in patients with aldosterone producing adenoma. J. Atherosclerosis. 2012;221:154–9. doi: 10.1016/j.atherosclerosis.2011.12.003. [DOI] [PubMed] [Google Scholar]

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