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Sleep apnea in postmenopausal women is associated with joint pain severity and fatigability: a cross-sectional study

Odai, Tamami MD, PhD1; Terauchi, Masakazu MD, PhD, NCMP1; Umeki, Hidenori MD2; Miyasaka, Naoyuki MD, PhD3; Somekawa, Yoshiaki MD, PhD2

Author Information
doi: 10.1097/GME.0000000000001974
  • Open

Abstract

Sleep-disordered breathing (SDB) is categorized into central sleep apnea and obstructive sleep apnea syndrome (OSAS); the latter accounts for the majority of SDB cases. Central sleep apnea is caused by heart failure and stroke, whereas OSAS can be a risk factor for lifestyle-related diseases, such as hypertension and diabetes, contributing to the progression of cardiovascular diseases (CVDs), the leading cause of death worldwide,1 through hypoxia and increased sympathetic nervous system activity. The gold standard for diagnosis of OSAS is polysomnography to calculate the apnea-hypopnea index (AHI), which is the number of times apnea-hypopnea occurs in an hour. In the diagnostic algorithm for SDB in Japan,2 home sleep apnea testing can also be used for the screening of SDB. AHI assessed by a portable monitoring device is called the respiratory disturbance index (RDI). Poly-somnography is recommended for patients with an RDI ≥ 15, as assessed with a portable monitoring device.2 Patients with an AHI ≥ 20 or RDI ≥ 40 should be treated with continuous positive airway pressure.

It is well known that the prevalence of OSAS increases in postmenopausal women, and this could be associated with a decrease in the levels of sex steroids. It has been reported that AHI has an inverse association with serum levels of progesterone and estradiol.3 Another study found that the prevalence of sleep apnea was 4.5 times higher in postmenopausal women than in premenopausal women, whereas hormone therapy contributed to a reduction in the prevalence of OSAS.4 Peri- and postmenopausal women have a variety of physical and psychological symptoms, including vasomotor symptoms, palpitations, various types of pain (eg, head, back, muscle, and joint pain), urogenital disorders, sleep disorders, fatigue, and depression. There is an overlap of symptoms between OSAS and menopause. Therefore, it is worthwhile to clarify the association between OSAS and menopausal symptoms, as it could contribute to the diagnosis of OSAS at an early stage and prevent the progression of CVDs in later life. Recently, the severity of vasomotor symptoms was shown to be associated with the risk of obstructive sleep apnea in middle-aged women.5 However, the relationship between sleep apnea and other symptoms in middle-aged and older women is still not fully understood. The aim of the present study was to investigate the associations between various physical and psychological symptoms and RDI or nadir transcutaneous oxygen saturation (SpO2), as assessed by a portable monitoring device, in Japanese postmenopausal women who had treatment-resistant sleep disorders.

METHODS

Study participants

In this cross-sectional study, we retrospectively analyzed the medical records of 51 postmenopausal Japanese women who visited the Menopause Clinic in the JA Toride Medical Center, Ibaraki, Japan. We started examining sleep apnea using a portable monitoring device in June 2016. Between June 2016 and December 2018, the participants whose subjective sleep quality did not improve after a month-long pharmacotherapy regimen underwent a sleep test at home. The participants also responded to questionnaires on sleep disorders and physical, psychological, and menopausal symptoms. We investigated the association between sleep apnea parameters and the severity of various symptoms.

The research procedures were approved by the JA Toride Medical Center Review Board, and written informed consent was obtained from all participants. The study was conducted in accordance with the principles of the Declaration of Helsinki.

Measurements

Sleep apnea

The severity of objective sleep disorders was investigated using a portable monitoring device (SAS-2100, Teijin, Osaka, Japan) at home. The accuracy ofportable monitoring has been verified by studies that showed that a home-based diagnosis of OSAS was comparable to that using polysomnography in a laboratory.6,7 The supplier provided the device to the participant, who wore a saturated oxygen sensor at the fingertip and a nasal cannula with an airflow sensor overnight. After the test, the supplier retrieved the device and analyzed it to obtain the RDI, nadir SpO2 (%), and snoring frequency (times/hour) data. For participants with an RDI of ≥ 15, polysomnography was recommended, according to the diagnostic algorithm for SDB published by the Ministry of Health, Labour and Welfare in Japan.2

Questionnaire

Subjective sleep disorder was evaluated using the Epworth Sleepiness Scale (ESS) and the Pittsburgh Sleep Quality Index (PSQI). We also investigated psychological symptoms using the Zung Self-Rating Depression Scale (SDS), Hospital Anxiety and Depression Scale (HADS), and the Cornell Medical Index (CMI). Additionally, physical symptoms were assessed using the CMI and the Questionnaire for Assessment of Climacteric Syndrome in Japanese Women (ACS).

The ESS consists of eight items for evaluating drowsiness in common daily life situations using a four-point grade scale.8 Participants who received more than ten points were considered to be experiencing severe drowsiness. The PSQI, a tool used to assess the quantity and quality of subjective sleep over the preceding month, is composed of seven subcategories (Table 2).9 More than five points on the PSQI global score indicates severe sleep disturbance. The SDS was developed by Zung in 1965 as a screening tool for depression using a four-point Likert scale.10 The SDS consists of two items for feelings, eight items for physical status, and ten items for psychological status (Table 2). Item responses are based on how often the women believe the emotion in question: hardly, rarely, sometimes, and always. Points of 50-59, 60-69, or 70 or more indicate a mild, moderate, or severe depressive status, respectively. The HADS, a reliable instrument for screening anxiety and depression, was developed to evaluate the psychological health of patients with physical symptoms.11 The HADS is composed of seven items each for anxiety and depression. Participants responded to these items using a four-point Likert scale, and those who received a score of 8-10 points or 11-21 points were considered likely to be or definitely experiencing anxiety or depression, respectively. The CMI was developed as a self-administered physical and psychological health questionnaire.12 The CMI for women comprises 213 items, which are composed of 12 sections for somatic symptoms (A to L) and six sections (M to R) for mental health symptoms (Table 2). Assessments ofsubjective physical and psychological symptoms were conducted based on yes (one point) or no (zero points) answers; women with a higher score have various health problems. Additionally, neurotic disorders were evaluated by calculating the sum of the scores of three sections for physical symptoms (CIJ score) and six sections for mental health symptoms (M to R score). The ACS was developed to assess menopausal symptoms in Japanese women using a four-point Likert scale based on the severity of symptoms (none, mild, moderate, and severe).13 This shows that women with higher scores experience more severe symptoms. It assesses 21 items, including vasomotor function, insomnia, psychological symptoms, fatigue, pain, chest symptoms, memory decline, and paresthesia (Table 2).

TABLE 1 - Background characteristics of the participants
RDI Nadir SpO2
Study participants (n = 51) <15 (n = 29) ≥15 (n = 22) P value ≥90% (n = 16) <90% (n = 35) P value
Age, y 62.2 (9.1) 60.2 (9.3) 64.9 (8.3) 0.088 a 57.6 (9.2) 64.3 (8.4) 0.004 a
Hight, cm 154.9 (4.0) 155.7 (3.9) 153.7 (3.9) 0.103 a 155.9 (3.7) 154.4 (4.0) 0.257 a
Weight, kg 57.7 (11.2) 57.2 (10.7) 58.4 (12.3) 0.669 a 59.2 (8.9) 57.0 (12.3) 0.277 a
Body mass index, kg/m2 23.9 (4.3) 23.2 (4.4) 25.1 (4.8) 0.183 a 24.4 (3.8) 23.8 (4.6) 0.482 a
Cardiovascular parameters
 Systolic blood pressure, mmHg 133.0 (16.9) 131.9 (19.3) 134.4 (13.9) 0.650 a 133.5 (21.9) 132.9 (15.3) 0.888 a
 Diastolic blood pressure, mmHg 79.0 (10.3) 78.0 (12.4) 80.4 (6.8) 0.487 a 77.8 (12.3) 79.5 (9.7) 0.669 a
 Heart rate, min–1 78.3 (13.3) 77.7 (17.2) 79.1 (6.8) 0.773 a 78.4 (15.6) 78.2 (12.7) 0.760 a
 High-density lipoprotein cholesterol, mg/dL 61.3 (16.5) 63.6 (16.3) 58.1 (16.6) 0.249 a 64.5 (16.8) 59.8 (16.4) 0.281 a
 Low-density lipoprotein cholesterol, mg/dL 113.9 (23.6) 117.4 (26.5) 108.9 (18.0) 0.219 a 112.7 (27.7) 114.5 (21.8) 0.400 a
 Triglyceride, mg/dL 123.4 (56.7) 119.2 (55.1) 129.6 (59.9) 0.533 a 111.7 (47.8) 129.1 (60.4) 0.327 a
 Total cholesterol, mg/dL 202.5 (31.3) 209.0 (33.4) 192.1 (25.5) 0.074 a 202.9 (33.1) 202.4 (31.0) 0.935 a
 Hemoglobin A1c, % 6.0 (0.8) 5.8 (0.6) 6.3 (0.9) 0.049 a 5.9 (0.7) 6.1 (0.8) 0.141 a
 Carotid artery intima-media thickness, mm 1.5 (0.7) 1.2 (0.5) 1.8 (0.9) 0.019 a 1.2 (0.7) 1.6 (0.7) 0.047 a
Medical history
 Hypertension, n 21 10 11 0.389 b 8 13 0.541 b
 Dyslipidemia, n 25 15 10 0.779 b 7 18 0.765 b
 Diabetes, n 6 2 4 0.383 b 2 4 1.000 b
RDI, respiratory disturbance index; SpO2, percutaneous oxygen saturation.Values are mean (standard deviation) or the number of appropriate patients. Statistical analyses were performed using the aMann-Whitney U-test and bchi-square test.

TABLE 2 - Sleep parameters of the participants
RDI Nadir SpO2
Study participants (n = 51) <15 (n = 29) >15 (n = 22) P value ≥90% (n = 16) <90% (n = 35) P value
Objective sleep apnea parameters
 Respiratory disturbance index 15.9 (12.9) 6.5 (4.2) 28.2 (9.8) <0.001 a 5.4 (5.1) 20.7 (12.6) <0.001 a
 Minimum SpO2, % 85.3 (6.5) 88.8 (4.6) 80.7 (5.9) <0.001 a 91.9 (2.1) 82.3 (5.6) <0.001 a
 Snoring frequency, times/h 62.1 (93.7) 38.4 (96.9) 92.6 (81.7) 0.001 a 25.9 (34.9) 78.5 (107.0) 0.093 a
Subjective sleep parameters
 ESS 7.2 (4.0) 6.5 (3.6) 8.2 (4.5) 0.287 a 7.0 (3.4) 7.3 (4.3) 0.920 a
 PSQI grobal score 9.7 (3.9) 9.3 (4.1) 10.3 (3.6) 0.380 a 9.0 (3.0) 10.1 (4.2) 0.369 a
  PSQI-1, Sleep quality 1.5 (0.8) 1.4 (0.7) 1.5 (0.9) 0.861 a 1.4 (0.5) 1.5 (0.9) 0.630 a
  PSQI-2, Sleep latency 1.4 (0.9) 1.4 (1.0) 1.3 (0.9) 0.866 a 1.2 (0.8) 1.4 (1.0) 0.459 a
  PSQI-3, Sleep duration 2.0 (1.0) 1.8 (1.0) 2.3 (0.9) 0.093 a 2.1 (0.7) 1.9 (1.1) 0.758 a
  PSQI-4, Sleep efficiency 1.3 (1.2) 1.2 (1.2) 1.3 (1.1) 0.751 a 1.6 (1.2) 1.1 (1.1) 0.278 a
  PSQI-5, Sleep disturbance 1.2 (0.6) 1.2 (0.6) 1.3 (0.5) 0.239 a 0.9 (0.3) 1.4 (0.6) 0.012 a
  PSQI-6, Use of sleep medication 1.1 (1.3) 1.1 (1.3) 1.1 (1.4) 0.925 a 0.7 (1.1) 1.3 (1.4) 0.215 a
  PSQI-7, Daytime dysfunction 1.3 (0.8) 1.1 (0.8) 1.4 (0.9) 0.217 a 1.1 (0.9) 1.3 (0.8) 0.300 a
ESS, Epworth Sleepiness Scale; PSQI, Pittsburgh Sleep Quality Index; RDI, respiratory disturbance index; SpO2, percutaneous oxygen saturation.Values are presented as the mean (standard deviation). Statistical analyses were performed using the aMann-Whitney U test.

Background characteristics

We asked the participants if they had been diagnosed with noninfectious diseases, such as hypertension, dyslipidemia, and diabetes, and if they were being treated with medication. The participants’ body mass index was calculated by measuring their height and weight. Furthermore, cardiovascular parameters, such as blood pressure, heart rate, serum lipid profile (high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglyceride, and total cholesterol levels), and glucose tolerance (hemoglobin A1c level) were evaluated. We measured maximum carotid artery intima-media thickness (CIMT), defined as the maximum value among the bilateral common carotid artery, carotid bulb, and internal CIMT.

Statistical analyses

Continuous variables are presented as mean ± standard deviation. The required sample size in each group was estimated as 29, as calculated from the level of effect size, two-sided alpha, and powers of 0.5, 0.05, and 0.80, respectively. The differences between the two groups were examined using the Mann-Whitney U test and chi-squared test. Using cut-off points for a variance inflation factor of >10, multicollinearity between variables was identified. Multivar-iate linear regression analysis to determine the independent relationships between RDI/nadir SpO2 and the associated symptoms was conducted. Statistical analysis was performed using GraphPad Prism version 5.02 (GraphPad Software, San Diego, CA) and JMP version 12 (SAS Institute Inc., Cary, NC).

RESULTS

The mean age of the participants was 62.2 ± 9.1 years, and they were not current hormone users. The mean RDI and nadir SpO2 were 15.9 ± 12.9 and 85.2% ± 6.5%, respectively. Among the 51 study participants, 22 participants had an RDI ≥ 15 and six participants had an RDI ≥ 40. Twenty-two participants (43.1%) underwent polysomnography and seven (13.7%) were diagnosed with OSAS. The study participants were divided into two groups basedontheir RDI(RDI < 15 and ≥ 15) and SpO2 (SpO2 ≥ 90 and < 90). The differences in the background characteristics and sleep parameters of 51 participants in each group were evaluated. Significant differences were observed in hemoglobin A1c (P = 0.049) and CIMT (P = 0.019) between the two groups of RDI, as well as in age (P = 0.004) and CIMT (P = 0.047) between the two groups of nadir SpO2 (Table 1). These background factors were later used as independent variables in the multivariate analysis. Concerning the sleep parameters, the mean snoring frequency was significantly higher in the higher RDI and lower nadir SpO2 groups (Table 2). The mean ESS and PSQI scores also tended to be higher in the higher RDI and lower nadir SpO2 groups, although there were no significant differences except for the PSQI-5 score between the two nadir SpO2 groups. We next investigated the associations between RDI/SpO2 and each global score of three questionnaires (SDS, ACS, and HADS) and 63 individual symptom scores (Table 3). There were no significant differences in the global scores of the three questionnaires between the two groups of both RDI and SpO2.A significant difference in joint pain (ACS-18) was found between the two groups of RDI (P = 0.007), and there were significant differences in tiredness (SDS-10), mood (SDS-11), difficulty falling asleep (ACS-3), joint pain (ACS-18), fatigability (CMI-I), frequency of illness (CMI-J), and physical symptoms (CMI-CIJ) between the two groups of nadir SpO2 (tiredness, P= 0.047; mood, P= 0.018; difficulty falling asleep, P= 0.017; joint pain, P= 0.029; fatigability, P= 0.003; frequency of illness, P= 0.002; and physical symptoms, P= 0.013) (Table 3). The mean scores of these symptoms were higher in the groups with a higher RDI and a lower nadir SpO2. There was no multicollinearity among these independent variables. Finally, we performed multivariate linear regression analysis to determine the independent relationships between the above-mentioned symptoms and RDI/nadir SpO2. After adjusting for age, body mass index (Model 2), and selected background factors (Model 3), the severity of joint pain remained significantly correlated with RDI (Model 2, standardized partial regression coefficient [β] = 0.394, P= 0.005; Model 3, β = 0.423, P= 0.016), as well as nadir SpO2 and fatigability (Model 2, β = – 0.484, P β 0.002; Model 3, β = – 0.472, P= 0.007) (Table 4).

TABLE 3 - Differences in various symptoms between the groups of RDI/nadir SpO2 in the study participants
RDI (n = 51) Nadir SpO2
<15 (n = 29) ≥15 (n = 22) P value ≥90%(n = 16) <90%(n = 35) P value
SDS global score 44.6 (9.5) 44.7 (14.4) 0.806 42.3 (9.9) 45.8 (12.3) 0.159
 SDS-1 I believe down-hearted and blue. 2.0 (0.9) 2.3 (1.0) 0.489 1.9 (0.9) 2.3 (0.9) 0.199
 SDS-2 Morning is when I believe the best. 2.8 (1.1) 2.4 (1.2) 0.266 2.3 (1.0) 2.8 (1.2) 0.177
 SDS-3 I have crying spells or believe like it. 2.0 (0.9) 2.1 (0.8) 0.868 2.0 (0.9) 2.0 (0.9) 0.921
 SDS-4 I have trouble sleeping at night. 2.3 (1.3) 1.2 (0.3) 0.402 2.0 (1.1) 2.7 (1.2) 0.067
 SDS-5 I eat as much as I used to. 1.9 (1.0) 1.6 (0.9) 0.232 1.9 (1.1) 1.7 (0.9) 0.833
 SDS-6 I still enjoy sex. 2.3 (0.9) 2.6 (1.2) 0.391 2.3 (1.0) 2.5 (1.1) 0.680
 SDS-7 I notice that I am losing weight. 1.7 (1.1) 1.6 (0.9) 0.832 1.5 (1.1) 1.7 (1.0) 0.359
 SDS-8 I have trouble with constipation. 2.0 (1.1) 1.9 (1.0) 0.971 2.0 (1.0) 1.9 (1.1) 0.758
 SDS-9 My heart beats faster than usual. 2.9 (1.0) 2.7 (0.8) 0.515 2.7 (1.1) 2.8 (0.8) 0.783
 SDS-10 I get tired for no reason. 3.1 (0.8) 2.8 (1.1) 0.472 2.7 (0.8) 3.2 (0.9) 0.047
 SDS-11 My mind is as clear as it used to be. 2.8 (1.0) 2.9 (0.9) 0.720 2.3 (1.0) 3.1 (0.8) 0.018
 SDS-12 I find it easy to do the things I used to. 2.2 (0.9) 2.1 (1.1) 0.630 1.9 (1.0) 2.3 (1.0) 0.278
 SDS-13 I am restless and can’t keep still. 2.1 (1.1) 2.0 (0.9) 0.885 1.9 (1.0) 2.1 (1.0) 0.631
 SDS-14 I believe hopeful about the future. 2.7 (0.8) 2.6 (1.1) 0.692 2.6 (0.8) 2.7 (1.0) 0.660
 SDS-15 I am more irritable than usual. 2.7 (1.1) 2.3 (1.1) 0.260 2.7 (1.2) 2.5 (1.0) 0.535
 SDS-16 I find it easy to make decisions. 2.4 (1.1) 2.4 (1.2) 0.859 2.2 (1.1) 2.5 (1.1) 0.393
 SDS-17 I believe that I am useful and needed. 2.2 (0.9) 2.1 (1.0) 0.630 2.1 (1.0) 2.1 (0.9) 0.820
 SDS-18 My life is pretty full. 2.2 (1.0) 2.7 (1.1) 0.140 2.1 (1.0) 2.6 (1.1) 0.166
 SDS-19 I believe that others would be better off if I were dead. 1.5 (0.8) 1.4 (0.7) 0.509 1.5 (0.8) 1.5 (0.7) 0.825
 SDS-20 I still enjoy the things I used to be. 2.3 (0.7) 2.2 (1.1) 0.408 2.1 (0.7) 2.3 (1.0) 0.447
ACS global score 25.7 (9.0) 25.6 (9.8) 0.749 24.2 (8.9) 26.4 (9.5) 0.638
 ACS-1 Hot flashes 1.0 (0.) 1.3 (0.8) 0.401 1.1 (0.8) 1.2 (0.8) 0.675
 ACS-2 Sweats 1.2 (0.9) 1.1 (1.0) 0.913 1.3 (0.9) 1.1 (1.0) 0.568
 ACS-3 Difficulty falling asleep 1.0 (0.9) 1.2 (0.8) 0.479 0.6 (0.7) 1.3 (0.8) 0.017
 ACS-4 Difficulty staying asleep 1.3 (0.9) 1.3 (0.8) 0.952 1.5 (0.8) 1.2 (0.8) 0.387
 ACS-5 Easy excitability or irritability 1.3 (0.7) 1.1 (0.7) 0.442 1.3 (0.7) 1.2 (0.8) 0.736
 ACS-6 Anxiety 1.2 (0.9) 1.3 (0.9) 0.728 1.2 (0.9) 1.3 (0.9) 0.744
 ACS-7 Worry about something trivial 1.4 (0.8) 1.3 (0.8) 0.649 1.3 (0.8) 1.4 (0.8) 0.774
 ACS-8 Worry about self depression 1.2 (0.8) 1.4 (0.8) 0.529 1.2 (0.9) 1.3 (0.7) 0.860
 ACS-9 Easy fatigability 1.2 (0.9) 1.2 (0.8) 0.981 1.1 (0.9) 1.3 (0.8) 0.479
 ACS-10 Eye strain 1.6 (0.7) 1.4 (0.8) 0.568 1.5 (0.7) 1.6 (0.8) 0.628
 ACS-11 Forgetfulness 1.5 (0.7) 1.4 (0.7) 0.597 1.4 (0.8) 1.5 (0.6) 0.831
 ACS-12 Dizziness 1.0 (0.8) 0.9 (0.9) 0.740 1.0 (0.8) 1.0 (0.9) 0.990
 ACS-13 Palpitation 1.2 (0.8) 1.3 (0.7) 0.864 1.1 (0.8) 1.3 (0.8) 0.346
 ACS-14 Tightness 0.6 (0.7) 0.6 (0.6) 0.781 0.4 (0.5) 0.7 (0.7) 0.306
 ACS-15 Headache 1.6 (0.7) 1.6 (0.8) 0.840 1.7 (0.6) 1.5 (0.8) 0.719
 ACS-16 Shoulder stiffness 1.7 (0.5) 1.7 (0.7) 0.731 1.7 (0.5) 1.7 (0.6) 0.729
 ACS-17 Lumbago 1.3 (0.7) 1.7 (0.7) 0.104 1.5 (0.6) 1.5 (0.8) 0.736
 ACS-18 Joint pain 0.8 (0.9) 1.5 (0.7) 0.007 0.7 (0.8) 1.3 (0.8) 0.029
 ACS-19 Cold constitution 1.2 (0.9) 1.0 (0.8) 0.536 1.3 (0.9) 1.0 (0.8) 0.208
 ACS-20 Numbness in the limbs 0.7 (0.8) 0.8 (0.9) 0.789 0.7 (0.8) 0.8 (0.9) 0.669
 ACS-21 Auditory hyperesthesia 0.9 (0.8) 0.9 (0.9) 0.960 0.9 (0.9) 0.9 (0.9) 0.772
 CMI-A Eyes and ears 3.2 (2.2) 2.8 (2.0) 0.590 3.1 (2.0) 3.0 (2.2) 0.660
 CMI-B Respiratory system 3.5 (3.5) 4.8 (2.6) 0.066 2.9 (3.2) 4.6 (3.2) 0.052
 CMI-C Cardiovascular system 3.3 (2.4) 3.3 (1.9) 0.752 2.8 (2.2) 3.6 (2.2) 0.186
 CMI-D Digestive tract 4.8 (3.1) 4.0 (2.9) 0.465 3.4 (2.4) 5.1 (3.3) 0.104
 CMI-E Musculoskeletal system 2.1 (1.2) 3.1 (2.2) 0.209 1.9 (1.1) 2.8 (1.9) 0.126
 CMI-F Skin 2.0 (2.0) 1.8 (2.0) 0.560 1.5 (1.4) 2.2 (2.2) 0.468
 CMI-G Nervous system 2.6 (2.2) 3.1 (2.1) 0.386 2.3 (2.0) 3.1 (2.2) 0.241
 CMI-H Genito-urinary system 3.1 (2.8) 3.3 (2.5) 0.804 3.4 (2.7) 3.0 (2.7) 0.569
 CMI-I Fatigability 2.0 (1.7) 2.6 (1.4) 0.246 1.2 (1.4) 2.7 (1.5) 0.003
 CMI-J Frequency of illness 2.0 (2.0) 2.1 (2.2) 0.698 0.9 (1.2) 2.6 (2.1) 0.002
 CMI-K Miscellanellus diseases 1.8 (1.7) 1.4 (1.1) 0.566 1.8 (1.8) 1.6 (1.3) 0.989
 CMI-L Habits 2.1 (1.3) 1.9 (0.9) 0.715 2.1 (1.5) 2.0 (1.0) 0.773
 CMI-M Maladaptation 2.0 (2.8) 3.4 (2.2) 0.424 2.9 (2.6) 3.3 (2.5) 0.550
 CMI-N Depression 0.9 (1.4) 1.0 (1.2) 0.476 0.7 (1.3) 1.0 (1.3) 0.333
 CMI-O Anxiety 2.0 (1.8) 1.5 (1.4) 0.371 1.4 (1.3) 2.0 (1.9) 0.398
 CMI-P Sensitivity 1.9 (1.9) 1.4 (1.7) 0.439 1.4 (1.7) 1.9 (1.9) 0.387
 CMI-Q Irritation 2.4 (2.6) 2.1 (2.5) 0.652 2.5 (2.5) 2.2 (2.6) 0.609
 CMI-R Tension 1.7 (1.7) 1.5 (1.5) 0.836 1.4 (1.9) 1.7 (1.5) 0.335
 CMI-CIJ Physical symptoms 7.2 (4.5) 6.7 (4.4) 1.000 4.6 (3.0) 8.0 (4.7) 0.013
 CMI-M to R Mental symptoms 11.9 (10.2) 9.2 (7.8) 0.504 9.8 (9.5) 10.9 (9.3) 0.603
HADS 12.8 (5.7) 10.7 (4.8) 0.333 13.1 (6.0) 11.3 (5.1) 0.401
HADS-anxiety 6.9 (3.5) 5.5 (2.5) 0.299 6.8 (3.7) 6.1 (2.9) 0.719
HADS-depression 5.9 (3.4) 5.1 (3.1) 0.632 6.3 (3.9) 5.2 (2.9) 0.472
ACS, Questionnaire for Assessment of Climacteric Syndrome in Japanese Women; CMI, Cornell Medical Index; ESS, Epworth Sleepiness Scale; HADS, Hospital Anxiety and Depression Scale; PSQI, Pittsburgh Sleep Quality Index; R, Pearson correlation coefficients; RDI, respiratory disturbance index; SDS, Zung Self-Rating Depression Scale; SpO2, percutaneous oxygen saturation.

TABLE 4 - Relationships between selected symptoms and RDI/nadir SpO2
Relationship between RDI and joint pains (ACS-18)
β SE P R2
Model 1 0.328 2.063 0.029 0.086
Model 2 0.394 1.787 0.005 0.287
Model 3 0.423 2.567 0.016 0.362
Relationship with nadir SpO2
Symptoms Questionnaire β SE P R2
Model 1
 tiredness SDS10 –0.195 1.044 0.206 0.015
 mood SDS11 –0.217 1.032 0.157 0.025
 difficulty falling asleep ACS-3 –0.297 1.137 0.053 0.066
 joint pains ACS-18 –0.352 1.086 0.021 0.103
 fatigability CMI-I –0.411 0.549 0.008 0.148
 frequency of illness CMI-J –0.331 0.455 0.035 0.086
 physical symptoms CMI-CIJ –0.149 0.221 0.330 <0.001
Model 2
 joint pains ACS-18 –0.440 0.914 0.002 0.313
 fatigability CMI-I –0.48 0.509 0.002 0.236
 frequency of illness CMI-J –0.36 0.428 0.027 0.138
Model 3
 joint pains ACS-18 –0.28 1.004 0.066 0.341
 fatigability CMI-I –0.47 0.495 0.007 0.321
 frequency of illness CMI-J –0.25 0.425 0.148 0.179
β, standardized partial regression coefficient; ACS, Questionnaire for Assessment of Climacteric Syndrome in Japanese Women; CMI, Cornell Medical Index; R2, adjusted coefficient of determination; RDI, respiratory disturbance index; SDS, Zung Self-Rating Depression Scale; SE, standard error; SpO2, percutaneous oxygen saturation.Model 1: Unadjusted model.Model 2: Multivariate linear regression analysis adjusted for age and body mass index.Model 3: Multivariate linear regression analysis adjusted for age, body mass index, and selected background factors (RDI, hemoglobin A1c, and carotid intima-media thickness [CIMT]; SpO2, CIMT).

DISCUSSION

In this cross-sectional study, we found that a higher RDI was significantly associated with an increased severity injoint pain and a lower nadir SpO2 was associated with the severity of fatigability in Japanese postmenopausal women who had treatment-refractory insomnia.

Apnea, hypoxia, and hypercapnia in OSAS result in dys-autonomia, vascular endothelial dysfunction, and increased reactive oxygen species (ROS) production, leading to the development of various conditions, such as arrhythmia, heart failure, hypertension, insulin resistance, atherosclerosis, and CVDs.14 The prevalence of OSAS increases after menopause,4 whereas more than half of women in the menopausal transition and postmenopausal women also experience mus-culoskeletal joint pain,18 implying a link between these pains and estrogen depletion. Several reports have shown that joint tissues have estrogen receptors,19-23 and estrogen plays a role in maintaining the homeostasis of articular tissues, such as cartilage, the subchondral bone, the synovium, ligaments, and muscles.24 In addition, there have been several animal studies on the beneficial effects of estrogen or selective estrogen receptor modulator administration on joint cartilage, such as decreased incidence of osteoarthritis, control of cartilage erosion, and increased proteoglycan synthesis by articular chondrocytes, although the evidence remains inconclusive.25 Enhanced ROS production through chronic intermittent hypoxia and rapid reoxygenation in OSAS induces the activity of nuclear factor κB(NF-κB) pathways, a central mediator of the inflammatory process.15 Additionally, ROS are involved in chondrocyte cell death and articular cartilage degeneration through matrix component degradation, activation of catabolic cytokines, and decline in cartilage repair ability.16 The ROS-induced inflammatory response through NF-κB activation and cartilage degeneration may be responsible for joint pain in the participants of this study with a higher RDI. The response to hypoxia may lead to the development of cartilage destruction and joint pain. Moreover, it is well known that estrogen deficiency contributes to increased ROS levels.26 Rising oxidative stress by hypoxia and estrogen decline, and loss of the beneficial effects of estrogen on joints might contribute to severe joint pain in postmenopausal women with a higher RDI. In contrast, a recent study involving 360 men with OSAS showed that OSAS was not associated with multiple musculoskeletal join pain.17 This finding may be attributed to differences in sex.

Fatigue is commonly observed in patients with OSAS. The prevalence of fatigue in a high-risk OSAS group has been found to be 63%.27 A Japanese study showed that 6.5% of patients with persistent fatigue had OSAS.28 It is widely known that fatigue is associated with low sleep quality and continuous short sleep deprivation. Autonomic nervous system disorders, immune dysfunction, and excess oxidative stress caused by sleep disorders also contribute to fatigue.29 Mills et al30 reported an association between fatigue in OSAS and activated inflammatory pathways. Repeated SpO2 decline could lead to sympathetic nerve hyperactivity, hypoxia-induced oxidative stress, and increased levels of inflammatory mediators, resulting in fatigue. Greatly decreased SpO2 levels could exaggerate these reactions.

The present study has several limitations. The study population was small in size and narrow, consisting of only Japanese middle-aged and older women in our menopause clinic; therefore, generalizing our results to a wider population is difficult. Furthermore, any causal relationship between RDI and the severity of joint pain or between nadir SpO2 and fatigue, remains unclear, owing to the cross-sectional design of this study. Although we assessed the prevalence of joint pain, we did not evaluate pain intensity or pain site, or perform objective assessments. Additionally, we did not investigate several influential factors on RDI/SpO2 decline and physical and mental status, such as bone-tissue and soft-tissue morphology in the upper respiratory tract and lifestyle factors. We also did not investigate the history of hormone use in the study participants. Despite these limitations, our study had several strengths. Physical and psychological statuses were extensively evaluated using several questionnaires. Our study is the first in the literature to find an association between RDI and the severity of join pain. Moreover, there was a gap between subjective and objective sleep disorders, which could suggest that some women with SDB experienced severe physical symptoms and poor subjective sleep complaints. This could provide a new opportunity for the early detection and treatment of OSAS in middle-aged and older women with intractable sleep disturbance and severe joint pain. Larger-scale epidemiological studies are necessary to verify our findings.

CONCLUSIONS

In conclusion, a higher RDI was significantly associated with an increased severity of joint pain, and a lower nadir SpO2 was associated with increased fatigue in Japanese middle-aged and older women who had treatment-resistant sleep impediment. Women with severe sleep disorders combined with joint pain and/or fatigue should have the opportunity of checking whether they have developed OSAS.

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Keywords:

Fatigue; Joint pain; Menopause; Obstructive sleep apnea syndrome; Sleep apnea

Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of The North American Menopause Society.