Abstract
Study Objectives:
The goals of this study were to estimate rates of undiagnosed, diagnosed, and treated sleep apnea in women veterans and to identify factors associated with diagnosis and treatment of sleep apnea in this population.
Methods:
A large nationwide postal survey was sent to a random sample of 4,000 women veterans who had received health care at a Veterans Health Administration (VA) facility in the previous 6 months. A total of 1,498 surveys were completed. Survey items used for the current analyses included: demographics; sleep apnea risk, diagnostic status, and treatment; symptoms of other sleep disorders (eg, insomnia); mental health symptoms; and comorbidities.
Results:
Among responders, 13% of women reported a prior sleep apnea diagnosis. Among women who reported a diagnosis of sleep apnea, 65% reported using positive airway pressure therapy. A sleep apnea diagnosis was associated with older age, higher BMI, non-Hispanic African American/Black racial/ethnic identity, being unemployed, other sleep disorder symptoms (eg, insomnia), depression and post-traumatic stress disorder symptoms, and multimorbidity. Among women without a sleep apnea diagnosis, 43% scored as “high risk” on the STOP (snoring, tiredness, observed apneas, blood pressure) questionnaire. High risk scores were associated with older age, higher BMI, African American/Black identity, other sleep disorder symptoms (eg, insomnia), mental health symptoms, and multimorbidity. Only BMI differed between women using vs not using positive airway pressure therapy.
Conclusions:
Women veterans with diagnosed sleep apnea were commonly treated with positive airway pressure therapy, which is standard first-line treatment; however, many undiagnosed women were at high risk. Efforts to increase screening, diagnosis, and treatment of sleep apnea in women with comorbid mental and physical health conditions are needed.
Citation:
Martin JL, Carlson G, Kelly M, et al. Sleep apnea in women veterans: results of a national survey of VA health care users. J Clin Sleep Med. 2021;17(3):555–565.
Keywords: sleep apnea, sleep disordered breathing, women, veterans, positive airway pressure therapy
BRIEF SUMMARY
Current Knowledge/Study Rationale: Sleep apnea is a common sleep disorder and a known risk factor for cardiovascular disease; however, it is not well studied in women. Veterans are at high risk for sleep apnea; however, studies to date have included a large proportion of male veterans, and there are no studies specifically of women who are veterans.
Study Impact: This study demonstrates that a large number of women veterans are at high risk for sleep apnea, but most are undiagnosed. Variables associated with high sleep apnea risk were identified to guide diagnosis and treatment of sleep apnea in women who receive VA health care. Only BMI was related to use of positive airway pressure treatment among those diagnosed, suggesting differences with studies in the veteran population of mostly male participants.
INTRODUCTION
The proportion of veterans who are women is increasing steadily due to changes in the composition of the active duty military. Understanding the health care needs of this growing segment of the patients served by the Veterans Health Administration (VA) is of utmost importance, as their health care needs are different from those of their male counterparts.1 Sleep disorders, including sleep apnea, are common among veterans overall,2,3 and there is growing evidence that sleep disorders contribute to poor outcomes in veteran patients in terms of quality of life,4 cardiovascular and metabolic health,5,6 and mortality.7 The VA and Department of Defense recently developed clinical practice guidelines related to the diagnosis and treatment of sleep disorders, including sleep apnea.8 The guidelines recommend screening for sleep apnea in symptomatic patients, diagnostic testing for those who are high risk, and treatment with positive airway pressure (PAP) therapy as a first-line approach; however, the guidelines do not address sex-specific differences in screening, diagnosis, or treatment.
Sleep apnea is the most commonly diagnosed sleep disorder among veterans who receive VA health care,2 and rates of diagnosed sleep apnea have been steadily increasing for active duty and veteran men and women alike.2,9 This increase is likely attributable to increasing awareness, in combination with rising rates of obesity nationwide,10 and among VA users, obesity prevalence in women is 44%, which is greater than in men.11 Despite this increasing awareness, there is less information on sleep apnea among women compared to men, perhaps owing to lower prevalence in women in the population at large. For example, the Wisconsin Sleep Cohort Study found that 34% of men and 17% of women studied between 2007 and 2010 met the minimum criteria for sleep apnea (apnea-hypopnea index ≥ 5 events/h).5 While the underlying disease is similar in men and women, there are known sex differences in the underlying pathophysiologic factors underpinning disordered breathing during sleep overall. Specifically, 2 key features distinguish breathing during sleep in men vs women: higher pharyngeal compliance and increased propensity to hypocapnic central apnea in men relative to women.12,13 The former increases the risk of pharyngeal collapse and the latter increases not only the risk of pharyngeal collapse but also breathing instability and recurrent apnea.
While research on differences in the presentation of sleep apnea between men and women is limited, there is some evidence that men and women with sleep apnea describe different symptoms related to their disease.14,15 The classic symptoms of sleep apnea are largely derived from studies that included mostly men, and few studies have included a sufficiently large number of women to explore risk factors and associated symptoms specifically among women, especially women veterans.16 This absence of data may reduce clinical suspicion for sleep apnea and create barriers to diagnostic testing in women, increasing the likelihood that women with sleep apnea remain undiagnosed and hence untreated.7–9 Another factor that may contribute to underdiagnosis is the overall low rate of sleep apnea in premenopausal women, which may lead to lower suspicion that sleep-related symptoms are due to sleep apnea, but rather, that they are due to insomnia, which is more common among women compared to men.17
In the current study, we used data that focused on sleep-related symptoms from a nationwide survey of women veterans who use VA health care.18,19 Our first objective was to identify rates of diagnosed sleep apnea among women veterans who use VA health care, and the proportion of diagnosed women who used PAP therapy. Our second objective was to identify women at high risk for sleep apnea who were not previously diagnosed and to explore differences between women with and without reported diagnosed sleep apnea in terms of demographic factors, symptoms of other sleep disorders, mental health symptoms, and comorbid conditions. Our third objective was to explore differences between women who reportedly used PAP therapy to those who did not in terms of the same patient characteristics.
METHODS
Study survey sample
The national study sample was identified using simple random sampling of all women veterans (n > 300,000) who had received health care services at a VA facility (1 or more VA visits) in the 6-month period from May to November, 2012. A dataset was obtained from the VA Health Eligibility Center, which included contact information (name, address, telephone number) and other data elements available through administrative records (eg, age, sex, period of military service). The 6-month time frame was chosen based on our prior experience conducting a postal survey in one VA Healthcare System20: Women who had interacted with the VA Healthcare System within the past 6 months were more likely to have valid addresses and phone numbers compared to women who had not been seen in the prior 6 months. Additional details related to survey methodology and insomnia-related findings have been published previously.18,19
A random sample of 4,000 women was selected from the cohort of approximately 300,000 women veterans described above. Using standard postal survey methodology, including steps to reduce risk of nonresponse bias,21 surveys were sent by mail in batches of 1,000 surveys per mailing between February and October, 2013. If no response was received within 3 weeks, a second survey was sent. After the final set of surveys were mailed, all nonresponders from the first 1,000-person cohort were contacted by phone and offered the opportunity to complete the survey verbally as an additional strategy for reducing response bias.21 For the purpose of this analysis, a “responder” was defined as an individual who returned a survey and provided answers to the sleep apnea–related items [ie, responded about diagnosis and treatment of sleep apnea, plus the 4 items necessary for computing the STOP (snoring, tiredness, observed apneas, blood pressure) questionnaire].22 Out of the 1,562 surveys returned by mail or completed by phone, 1,498 surveys were complete and available for the current analysis (total response rate = 37%). Using available administrative data from VA Health Eligibility Center, we found minimal differences between responders and nonresponders, (eg, the unweighted percentage who reported a diagnosis of sleep apnea was 13.4% while the weighted percentage was 12.0%, a difference of only 1.3%), thus weighting for nonresponse was not employed as weighting had minimal impact on the key variable of interest.
This study was approved by the Institutional Review Board of the VA Greater Los Angeles Healthcare System. A waiver of documentation of consent was obtained for the survey.
Survey
The original survey study was conducted for the purpose of estimating the prevalence of insomnia and other sleep disorders and identifying insomnia treatment preferences among women veterans.19 The survey included cover material describing the survey as research and 4 pages of questionnaire items. The specific items used in the current analyses are described below. Variable selection was based on a demonstrated or theoretical relationship with sleep disorders. The survey elements reported here included demographics, sleep apnea-related items, insomnia severity, mental health symptoms, and physical health–related factors. Core survey items were developed and tested in a previous study.20
Demographics
Demographic characteristics evaluated in the survey included self-identified race/ethnicity, marital status, employment status, and military service history. Age (computed as date of survey completion minus date of birth, in years) was obtained from administrative databases. Self-reported height and weight were also collected and used to calculate body mass index [BMI; height (meters) divided by weight (in kilograms) squared]
Sleep apnea
The survey included the 4 items used to evaluate sleep apnea risk from the STOP questionnaire.22 This scale includes 4 dichotomous yes/no items: snoring, tiredness, observed apneas, and high blood pressure, with 1 point given per “yes” response. Scores of 2 or higher suggest high risk for sleep apnea. Items were developed and formatted for use in the postal survey to cover each of these domains. “Yes” responses to the following questions were scored as “1” on the STOP questionnaire for a total possible score of 0–4.
Do you snore loudly? (yes/no)
During the past month, did you feel tired, fatigued, or sleepy during the day? (yes/no)
Has anyone told you that you stop breathing during your sleep? (yes/no)
Do you have or have you ever been treated for: high blood pressure? (yes/no, asked as part of a comorbidity checklist)
In addition, the survey asked women if they had been diagnosed with sleep apnea or had previously received treatment (new items developed for this survey). Each question was asked in a yes/no format.
Have you ever been diagnosed with sleep apnea? (yes/no)
Do you use a CPAP, BPAP, or APAP machine to treat sleep apnea? (yes/no)
Symptoms related to other sleep disorders
The 7-item Insomnia Severity Index was used to evaluate the severity of insomnia symptoms.23 Restless legs syndrome symptoms and nightmares were assessed via the following questions (developed for this survey):
When you try to relax in the evening or sleep at night, do you have unpleasant, restless feelings in your legs that can be relieved by walking or movement? (yes/no)
During the past month, how often did you have disturbing dreams and/or nightmares? (4-item scale assessing frequency that was dichotomized to “not during the past month” = 0 and any response indicating nightmares in the past month = 1)
Mental health measures
We evaluated 3 domains of mental health using brief screening measures. The Patient Health Questionnaire (PHQ-4)24 was used to assess symptoms of depression (2 items) and anxiety (2 items) over the past 2 weeks, and a total score was computed for depression (0–6) and anxiety (0–6). The primary care–post-traumatic stress disorder (PC-PTSD)-4 item25 was also included to evaluate risk for PTSD.
Self-reported comorbidities
A list of self-reported medical and psychiatric conditions was developed for the survey using 3 sources: (1) the most common International Classification of Diseases, Ninth Revision26 diagnostic codes for women veterans who use VA health care, (2) the Comorbidity Index,27 and (3) history of medical conditions assessed in the Study of Women’s Health Across the Nation (SWAN).28 A total of 15 comorbid conditions were included in the survey, including 9 medical and 6 psychiatric conditions/symptoms. Respondents were asked “Do you have, or have you ever been treated for … (yes/no):
High blood pressure (included in the STOP questionnaire, above)
Heart disease
High cholesterol
Diabetes
Gastroesophageal reflux disease (GERD)
Chronic pain (including back pain or headaches)
Breathing problems (such as asthma, emphysema, or COPD)
Thyroid disorders
Traumatic brain injury (TBI)
Depression
Anxiety or panic disorder
Post-traumatic stress disorder (PTSD)
Problem drinking or alcoholism
Drug use (other than alcohol)
Bipolar disorder or manic-depressive disorder
Data analysis
We first estimated rates of diagnosed sleep apnea by computing the percent of respondents who answered “yes” to having received a diagnosis. Among those women, we then computed the percent of respondents who reported using a continuous positive airway pressure (CPAP), bilevel positive airway pressure (BPAP), or automatic or autotitrating positive airway pressure machine to treat sleep apnea. Of the respondents who did not report a diagnosis of sleep apnea, none reported using PAP therapy.
Among the women who answered “no” to having diagnosed sleep apnea, we computed their risk score on the STOP questionnaire, and categorized them as “high risk” (ie, STOP score ≥ 2) vs “low risk” (ie, STOP score of 0 or 1). Among women who were not diagnosed with sleep apnea, we compared those who were at high vs low risk according to their score on the STOP using t tests (continuous variables) and chi-square tests (categorical variables). Again, we compared the 2 groups in terms of demographic factors, evidence of other sleep disorders (ie, insomnia, restless legs syndrome, nightmares), mental health symptoms, and comorbid conditions.
Among women with diagnosed sleep apnea, we compared women who were using PAP therapy to those who were not via t tests (continuous variables) and chi square tests (categorical variables). We compared the 2 groups in terms of demographic factors, evidence of other sleep disorders, mental health symptoms, and comorbid conditions.
For all statistical tests, P < .05 was used to establish statistical significance. Since there is limited data on sleep in women veterans, we considered multiple factors in balancing the risk of type I and type II errors in this study. Rather than employ a stringent type I error correction (eg, Bonferroni correction), we elected to use P < .05 for each individual statistical test, and to interpret the totality of the results, with the understanding that a small number of findings may not be replicated in future research. This means that up to 5% of tests conducted may, in fact, represent type I errors. Based on the number of tests carried out within this study, we expected 4–5 tests to be significant by chance alone. This decision was made based on a desire to avoid increasing risk of type II errors in a relatively under-studied area, as this could limit future investigation of potentially important findings in this early cross-sectional study. Data were analyzed using STATA 15.1. (StataCorp LLC, College Station, TX).29
RESULTS
Survey sample characteristics
Characteristics of respondents (n = 1,498) with sufficient data for inclusion in this analysis are shown in Table 1. The average age was 52 years, ranging from 18 to > 100 years. Forty-one percent identified racial/ethnic minority group status. As expected in VA patient populations, most women reported medical and psychiatric comorbidities. The most commonly reported medical comorbidity was chronic pain, which was reported by 65% of respondents. The most common mental health condition reported was depression (54%). Less than half (41%) were currently employed for wages.
Table 1.
Demographics and descriptive characteristics for survey respondents (n = 1,498).
| Mean (SD) or Frequency (%) | 95% CI | |
|---|---|---|
| Sociodemographic characteristics | ||
| Age | 51.6 (14.6) | 50.9, 52.4 |
| Race/ethnicity | ||
| Non-Hispanic White | 921 (61.5%) | 59.0%, 63.9% |
| Hispanic | 362 (24.2%) | 22.1%, 26.4% |
| Non-Hispanic African American/Black | 69 (4.6%) | 3.7%, 5.8% |
| All other groups (including > 1 race/ethnicity) | 146 (9.7%) | 8.3%, 11.3% |
| Employed for wages | 614 (41.1%) | 38.6%, 43.6% |
| Married/living as married | 662 (41.7%) | 39.3%, 44.3% |
| BMI (m/kg2) | 28.8 (6.4) | 28.5%, 29.2% |
| Sleep apnea | ||
| Diagnosed with sleep apnea | 200 (13.4%) | 11.7%, 15.2% |
| Treatment with CPAP (yes) | 130 (65%) | 58.1%, 71.3% |
| Not diagnosed with sleep apnea | 1298 (86.7%) | 84.8%, 88.3% |
| High risk for sleep apnea (STOP ≥ 2) | 564 (43.5%) | 40.1%, 46.2% |
| Symptoms of other sleep disorders | ||
| ISI total score (0–28) | 12.8 (7.1) | 12.5%, 13.2% |
| RLS symptoms (yes) | 590 (39.5%) | 37.0%, 42.0% |
| Nightmares (past month, yes) | 472 (31.6%) | 29.3%, 34.0% |
| Mental health symptoms | ||
| PHQ-4 Depression (0–8) | 1.9 (2.0) | 2.0%, 2.3% |
| PHQ-4 Anxiety (0–8) | 2.2 (2.0) | 1.8%, 2.0% |
| PC-PTSD (0–4) | 1.5 (1.6) | 1.4%, 1.5% |
| Medical comorbidities (yes/no) | ||
| High blood pressure | 585 (39.1%) | 36.7%, 41.6% |
| Heart disease | 161 (10.8%) | 9.3%, 12.5% |
| High cholesterol | 608 (40.8%) | 38.3%, 43.3% |
| Diabetes | 232 (15.6%) | 13.8%, 17.5% |
| GERD | 491 (33.0%) | 30.6%, 35.4% |
| Chronic pain (including back pain or headaches) | 965 (64.5%) | 62.1%, 66.9% |
| Breathing problems (such as asthma, emphysema or COPD) | 351 (23.5%) | 21.4%, 25.7% |
| Thyroid disorders | 312 (20.9%) | 18.9%, 23.0% |
| TBI | 77 (5.2%) | 4.2%, 6.4% |
| Mental health comorbidities (yes/no) | ||
| Depression | 808 (54.2%) | 51.7%, 56.7% |
| Anxiety or panic disorder | 626 (42.0%) | 39.5%, 44.5% |
| PTSD | 453 (30.5%) | 28.2%, 32.9% |
| Problem drinking or alcoholism | 103 (6.9%) | 5.7%, 8.3% |
| Drug use (other than alcohol) | 46 (3.1%) | 2.3%, 4.1% |
| Bipolar/manic-depressive disorder | 153 (10.3%) | 8.8%, 11.9% |
BMI = body mass index, COPD = chronic obstructive pulmonary disease, CPAP = continuous positive airway pressure, GERD = gastroesophageal reflux disease, ISI = Insomnia Severity Index, PC-PTSD = primary care–post-traumatic stress disorder, PHQ = patient health questionnaire, PTSD = post-traumatic stress disorder, RLS = restless legs syndrome, SD = standard deviation, TBI = traumatic brain injury.
Sleep apnea diagnosis
Two hundred respondents [13.4%; 95% confidence interval (CI) 11.7% to 15.1%] reported being diagnosed with sleep apnea (Figure 1). Women who reported a diagnosis of sleep apnea were significantly older, were less likely to be employed, and had higher BMI. Women who identified as non-Hispanic African American/Black were more likely to report a diagnosis of sleep apnea. There were no differences between groups regarding marital status. In terms of other sleep-related symptoms, women with diagnosed sleep apnea had higher Insomnia Severity Index scores and were more likely to have restless legs syndrome symptoms and nightmares. Women with diagnosed sleep apnea also had more symptoms of depression and PTSD but not anxiety/panic, and had higher rates of diagnosed medical and mental health comorbidities (see Table 2).
Figure 1. Flow diagram showing number of women diagnosed with and treated for sleep apnea, and risk (based on the STOP screening questionnaire) among those who are undiagnosed.
PAP = positive airway pressure.
Table 2.
Differences between women who reported a diagnosis of sleep apnea vs women who did not report a previous diagnosis of sleep apnea (total n = 1,498).
| Have you been diagnosed with sleep apnea? | P-Value | ||
|---|---|---|---|
| Yes | No | ||
| Number of women | 200 (13.4%) | 1,298 (86.7%) | — |
| Sociodemographic characteristics | |||
| Age | 55.3 (11.9) | 51.1 (14.9) | < .001 |
| Race/ethnicity | |||
| Non-Hispanic White | 114 (57%) | 807 (62.2%) | 0.162 |
| Hispanic | 60 (30%) | 302 (23.3%) | 0.039 |
| Non-Hispanic African American/Black | 12 (6.0%) | 57 (4.4%) | 0.314 |
| All other groups (including > 1 race/ethnicity) | 14 (7.0%) | 132 (10.2%) | 0.162 |
| Employed for wages | 66 (33.0%) | 548 (42.3%) | 0.013 |
| Married/living as married | 77 (38.5%) | 545 (42.3%) | 0.318 |
| BMI (m/kg2) | 32.6 (7.6) | 28.3 (6.0) | < .001 |
| Symptoms of other sleep disorders | |||
| ISI total score (0–28) | 15.0 (6.9) | 12.5 (7.1) | < .001 |
| RLS symptoms (yes/no) | 103 (51.8%) | 487 (37.6%) | < .001 |
| Nightmares (past month, yes/no) | 77 (38.5%) | 395 (30.5%) | 0.024 |
| Mental health symptoms | |||
| PHQ-4 Depression (0–8) | 2.6 (2.0) | 1.8 (2.0) | < .001 |
| PHQ-4 Anxiety (0–8) | 2.4 (2.0) | 2.1 (2.0) | 0.059 |
| PC-PTSD (0–4) | 1.9 (1.7) | 1.4 (1.6) | < .001 |
| Medical comorbidities (yes/no) | |||
| High blood pressure | 115 (57.5%) | 470 (36.2%) | < .001 |
| Heart disease | 40 (20.1%) | 121 (9.4%) | < .001 |
| High cholesterol | 113 (57.1%) | 495 (38.3%) | < .001 |
| Diabetes | 69 (34.9%) | 163 (12.6%) | < .001 |
| GERD | 103 (51.5%) | 388 (30.1%) | < .001 |
| Chronic pain (including back pain or headaches) | 158 (79.8%) | 807 (62.2%) | < .001 |
| Breathing problems (such as asthma, emphysema or COPD) | 83 (41.7%) | 268 (20.71%) | < .001 |
| Thyroid disorders | 61 (30.7%) | 251 (19.4%) | < .001 |
| TBI | 17 (8.6%) | 60 (4.7%) | 0.019 |
| Mental health comorbidities (yes/no) | |||
| Depression | 140 (70.7%) | 668 (51.7%) | < .001 |
| Anxiety or panic disorder | 108 (54.3%) | 518 (40.1%) | < .001 |
| PTSD | 90 (45.5%) | 363 (28.2%) | < .001 |
| Problem drinking or alcoholism | 13 (6.6%) | 90 (7.0%) | 0.836 |
| Drug use (other than alcohol) | 3 (1.5%) | 43 (3.3%) | 0.178 |
| Bipolar/manic-depressive disorder | 30 (15.0%) | 123 (9.5%) | 0.019 |
BMI = body mass index, COPD = chronic obstructive pulmonary disease, GERD = gastroesophageal reflux disease, ISI = Insomnia Severity Index, PC-PTSD = primary care–post-traumatic stress disorder, PHQ = patient health questionnaire, PTSD = post-traumatic stress disorder, RLS = restless legs syndrome, TBI = traumatic brain injury.
Risk of sleep apnea among undiagnosed women veterans
Among those who did not report a diagnosis of sleep apnea (n = 1,298), 43.4% (95% CI 40.1% to 46.2%) scored as high risk on the STOP screening questionnaire (Figure 1). Differences between undiagnosed women at high and low risk of sleep apnea are shown in Table 3. Undiagnosed women who were high risk for sleep apnea were significantly older, were more likely to identify as non-Hispanic White, and had higher BMI but did not differ in terms of employment or marital status. Women who identified as non-Hispanic White were less likely to be high risk and women who identified as non-Hispanic African American/Black were more likely to be high risk. Undiagnosed women who were high risk also had more symptoms of other sleep disorders, more mental health symptoms (depression, anxiety/panic, and PTSD), and more comorbid conditions.
Table 3.
Differences between undiagnosed women at high risk vs low risk for sleep apnea on the STOP screening questionnaire (total n = 1,298).
| Risk for Sleep Apnea on STOP | P-Value | ||
|---|---|---|---|
| Low Risk (STOP < 2) | High Risk (STOP ≥ 2) | ||
| Number of women | 734 (56.5%) | 564 (43.5%) | |
| Sociodemographic characteristics | |||
| Age | 49.5 (15.8) | 53.1 (13.3) | < .001 |
| Race/ethnicity | |||
| Non-Hispanic White | 486 (66.2%) | 321 (56.9%) | 0.001 |
| Hispanic | 33 (4.5%) | 24 (4.3%) | 0.834 |
| Non-Hispanic African American/Black | 136 (18.5%) | 166 (29.4%) | < .001 |
| All other groups (including > 1 race/ethnicity) | 79 (10.8%) | 53 (9.4%) | 0.420 |
| Employed for wages | 318 (43.4%) | 230 (40.9%) | 0.364 |
| Married/living as married | 322 (44.1%) | 223 (6.4%) | 0.122 |
| BMI (m/kg2) | 26.8 (5.) | 30.2 (6.6) | < .001 |
| Symptoms of other sleep disorders | |||
| ISI total score (0–28) | 11.1 (7.2) | 14.4 (6.4) | < .001 |
| RLS symptoms (yes/no) | 236 (32.3%) | 251 (44.5%) | < .001 |
| Had nightmare (yes/no) | 195 (26.6%) | 200 (35.5%) | 0.001 |
| Mental health symptoms | |||
| PHQ-4 Depression (0–8) | 1.6 (1.9) | 2.2 (2.0) | < .001 |
| PHQ-4 Anxiety (0–8) | 1.9 (1.9) | 2.4 (2.1) | < .001 |
| PC-PTSD (0–4) | 1.2 (1.6) | 1.6 (1.7) | < .001 |
| Medical comorbidities (yes/no) | |||
| Heart disease | 44 (6.0%) | 77 (13.8%) | < .001 |
| High cholesterol | 211 (28.8%) | 284 (50.5%) | < .001 |
| Diabetes | 46 (6.3%) | 117 (20.9%) | < .001 |
| GERD | 188 (25.6%) | 200 (36.0%) | < .001 |
| Chronic pain (including back pain or headaches) | 411 (56.0%) | 396 (70.3%) | < .001 |
| Breathing problems (such as asthma, emphysema, or COPD) | 118 (16.1%) | 150 (26.6%) | < .001 |
| Thyroid disorders | 131 (17.9%) | 120 (21.3%) | 0.126 |
| TBI | 35 (4.8%) | 25 (4.5%) | 0.784 |
| Mental health comorbidities (yes/no) | |||
| Depression | 344 (47.1%) | 324 (57.5%) | < .001 |
| Anxiety or panic disorder | 272 (37.2%) | 246 (43.8%) | 0.017 |
| PTSD | 190 (26.1%) | 173 (30.9%) | 0.054 |
| Problem drinking or alcoholism | 50 (6.8%) | 40 (7.1%) | 0.839 |
| Drug use (other than alcohol) | 20 (2.7%) | 23 (4.1%) | 0.180 |
| Bipolar/manic-depressive disorder | 63 (8.6%) | 60 (10.7%) | 0.207 |
BMI = body mass index, COPD = chronic obstructive pulmonary disease, GERD = gastroesophageal reflux disease, ISI = Insomnia Severity Index, PC-PTSD = primary care–post-traumatic stress disorder, PHQ = patient health questionnaire, PTSD = post-traumatic stress disorder, RLS = restless legs syndrome, TBI = traumatic brain injury.
Treatment of sleep apnea with PAP therapy
Among those reporting a diagnosis of sleep apnea (n = 200), 130 women (65%) reported using PAP therapy (Figure 1). Women using PAP therapy had significantly higher BMI than women not using PAP therapy. There were no other significant differences on survey variables between women who used or did not use PAP therapy (see Table 4).
Table 4.
Differences between women who used positive airway pressure (PAP) therapy to treat sleep apnea vs those who did not use PAP therapy (total N = 200).
| Treatment with PAP Therapy | P-Value | ||
|---|---|---|---|
| Using PAP | Not Using PAP | ||
| Number of women | 130 (65%) | 70 (35%) | |
| Sociodemographic characteristics | |||
| Age | 55.5 (11.4) | 55.0 (12.9) | 0.753 |
| Race/ethnicity | |||
| Non-Hispanic White | 76 (58.5%) | 38 (54.3%) | 0.570 |
| Hispanic | 7 (5.4%) | 5 (7.1%) | 0.619 |
| Non-Hispanic African American/Black | 41 (31.5%) | 19 (27.1%) | 0.518 |
| All other groups (including > 1 race/ethnicity) | 6 (4.6%) | 8 (11.4%) | 0.072 |
| Employed for wages | 45 (34.6%) | 21 (30.0%) | 0.508 |
| Married/living as married | 44 (33.8%) | 33 (47.1%) | 0.066 |
| BMI (m/kg2) | 34.4 (8.0) | 29.3 (5.7) | < .001 |
| Other sleep disorders | |||
| ISI total score (0–28) | 14.6 (6.7) | 15.7 (7.2) | 0.271 |
| RLS symptoms (yes/no) | 68 (52.7%) | 35 (50.0%) | 0.715 |
| Had nightmare (yes/no) | 47 (36.2%) | 30 (42.9%) | 0.353 |
| Mental health symptoms | |||
| PHQ-4 Depression (0–8) | 2.5 (2.0) | 2.8 (2.1) | 0.348 |
| PHQ-4 Anxiety (0–8) | 2.3 (2.0) | 2.6 (2.1) | 0.385 |
| PC-PTSD (0–4) | 1.7 (1.6) | 2.1 (1.7) | 0.094 |
| Medical comorbidities (yes/no) | |||
| High blood pressure | 76 (58.5%) | 39 (55.7%) | 0.708 |
| Heart disease | 27 (20.8%) | 13 (18.8%) | 0.747 |
| High cholesterol | 75 (58.1%) | 38 (55.1%) | 0.678 |
| Diabetes | 46 (35.9%) | 23 (32.9%) | 0.664 |
| GERD | 69 (53.1%) | 34 (48.6%) | 0.543 |
| Chronic pain (incl. back pain, headaches) | 102 (79.1%) | 56 (81.2%) | 0.727 |
| Breathing problems (such as asthma, emphysema, or COPD) | 57 (44.2%) | 26 (37.1%) | 0.337 |
| Thyroid disorders | 38 (29.5%) | 23 (32.9%) | 0.620 |
| TBI | 9 (7.0%) | 8 (11.6%) | 0.281 |
| Mental health comorbidities (yes/no) | |||
| Depression | 94 (72.3%) | 46 (67.6%) | 0.494 |
| Anxiety or panic disorder | 69 (53.5%) | 39 (55.7%) | 0.763 |
| PTSD | 57 (44.5%) | 33 (47.1%) | 0.724 |
| Problem drinking or alcoholism | 8 (6.3%) | 5 (7.1%) | 0.809 |
| Drug use (other than alcohol) | 2 (1.6%) | 1 (1.4%) | 0.946 |
| Bipolar/manic-depressive disorder | 21 (16.2%) | 9 (12.9%) | 0.534 |
BMI = body mass index, COPD = chronic obstructive pulmonary disease, GERD = gastroesophageal reflux disease, ISI = Insomnia Severity Index, PC-PTSD = primary care–post-traumatic stress disorder, PHQ = patient health questionnaire, PTSD = post-traumatic stress disorder, RLS = restlesss legs syndrome, TBI = traumatic brain injury.
DISCUSSION
This study is among the first to report on rates of sleep apnea among a large sample of women. Within this sample of women veterans who use VA health care, we found that 13.4% reported a prior diagnosis of sleep apnea, which is higher than the reported rates among women in the Wisconsin Sleep Cohort Study (3% among women 30–49, and 9% among women age 50–70).30 This difference may be related to the inclusion of women over age 70, high rates of obesity, and the high comorbidity burden of women who use VA health care. Veterans have more diagnosed health conditions than their non-veteran counterparts, and women using VA health care have greater medical and mental health comorbidity than women veterans who do not receive VA care.31 Women veterans also experience high rates of military sexual trauma,32–35 which is associated with increased risk of a variety of negative physical and mental health consequences.36 In our study we do not have information on trauma specifically, but over 30% of respondents reported PTSD, which is a known risk factor for low PAP adherence in male veterans.37
This study also provides information about potential predictors of sleep apnea diagnosis among women veterans. Similar to non-veteran women, sleep apnea diagnosis was more common in older women, women with higher BMI, non-Hispanic African American/Black women, and unemployed women. This is consistent with previous studies indicating that older patients and non-Hispanic African American/Black patients are at an increased risk for developing sleep apnea.14,38,39 Additionally, a number of sleep disorder symptoms (insomnia, restless legs syndrome, and nightmares) and mental health symptoms (PTSD and depression) were more commonly reported by women with a sleep apnea diagnosis in the current study. Results revealed that all medical comorbidities analyzed (high blood pressure, heart disease, high cholesterol, diabetes, gastroesophageal reflux disease, chronic pain, breathing problems, thyroid disorders, and traumatic brain injury) were more common in women with diagnosed sleep apnea compared to undiagnosed women, and most mental health comorbidities (all except problematic drinking and drug use) were more common in women diagnosed with sleep apnea compared to those without a diagnosis. These findings are not surprising as comorbidities among sleep disorders are well documented,40,41 and there is a growing body of literature demonstrating the relationship between psychiatric disorders and sleep apnea as well.42,43 Greater health care use by women with multiple comorbidities may also increase likelihood of detection of disorders such as sleep apnea and lead to referrals for diagnostic testing. Due to the cross-sectional nature of the current study, we cannot comment on the directional nature of these relationships; however, it appears that women veterans with a sleep apnea diagnosis are likely to present with multiple symptoms. It is important that providers evaluate potential sleep apnea symptoms and not simply attribute symptoms to other sleep, medical, or psychiatric disorders.
Another important finding from the current study was that, among women without a prior sleep apnea diagnosis, 43% were at high risk for sleep apnea based on the symptoms they endorsed. Not surprisingly, many of the same variables associated with sleep apnea diagnosis were also associated with elevated sleep apnea risk in undiagnosed women, including: older age, higher BMI, non-Hispanic African American/Black racial/ethnic identity, sleep disorder symptoms, mental health symptoms, and medical and mental health comorbidities. These findings are largely consistent with prior research; however, it is notable that factors associated with diagnosis of sleep apnea are similar to factors associated with being high risk but not yet diagnosed. This suggests a need for assessing risk of sleep apnea in all patients with sleep complaints. In fact, the recent VA/DOD Clinical Practice Guidelines suggest use of the STOP questionnaire to identify patients with sleep complaints who may need further evaluation.8
Our study also shows that, among women veterans who have been diagnosed with sleep apnea, only two-thirds reportedly used PAP therapy, which is considered first-line treatment. It is not clear from the information collected within the survey why one-third of women were not using this treatment, whether alternative approaches (eg, oral appliance therapy) were used, or whether no treatment was being used. Women who were treated with PAP and women who were diagnosed with sleep apnea but did not use PAP differed only in terms of BMI. Women using PAP treatment did not differ in terms of other demographic variables, sleep-related symptoms, mental health symptoms/comorbidities, or medical comorbidities. It is not clear why women using PAP treatment had higher BMI; however, one possible explanation is that they had more severe sleep apnea and clinicians more actively encourage women with obesity to use PAP. Also, women with higher BMI may experience greater benefit from PAP and therefore were more likely to report use of this treatment at the time of the survey. There is 1 study showing PTSD and nightmares are associated with lower PAP use (using objective monitoring data) among veterans; however, that study did not include any women.44 A more recent study of veterans who received treatment in a VA sleep disorders center found that Black race was associated with less PAP use (compared to White race) over the first 30 days of treatment, but again, the study sample was 95% male veterans.45 We did not find differences in PAP use among women veterans based on racial/ethnic identity. Another study found worse PAP adherence in younger women (ages 18–30) compared to women in other age ranges and compared to men in a national sample,46 but age was not different in users and nonusers of PAP in our study.
This study had multiple strengths and some limitations. Importantly, this was the first study to examine rates of sleep apnea diagnosis, presence of high-risk symptoms, and PAP use in a nationwide sample of women veterans. This study also involved widely cited and empirically validated self-reported measures plus new items developed through systematic survey development methods; however, a key limitation is the absence of objective data on diagnosis of sleep apnea or use of PAP therapy. Another potential limitation is the possibility of survey response bias because participants self-selected to return the postal survey. It is possible that individuals who completed the survey may differ from those who did not in terms of their sleep apnea symptoms or other important characteristics. Additionally, women veterans are a unique population and results from the current study may not generalize to women more broadly. For example, the fact that there were no differences between women with sleep apnea who do or do not use PAP is in contrast with recent research and should be replicated. Given the exploratory nature of the current study, we selected a limited number of variables to examine based on the larger sleep apnea literature, and unmeasured variables may play an important role. Lastly, we acknowledge that there is a risk of type I error in a study with multiple comparisons. In this study, there may have been 4–5 significant differences due to type I errors; however, there were 41 statistically significant findings, and the pattern of findings is highly consistent. We have focused on the overall patterns of differences observed rather than emphasizing 1 specific statistical test finding. Nevertheless, we caution the reader about drawing conclusions regarding any particular significant result, as any particular test may be a type I error. Instead, attention should focus on the overall pattern of results, which demonstrates that a sleep apnea diagnosis and high-risk symptoms are associated with poorer physical and mental health in women veterans, but use of PAP therapy in those who were already diagnosed was not.
This study provides novel information regarding sleep apnea prevalence as well as its treatment among women veterans. Sleep apnea is understudied in women compared to men. Research should continue to explore risk factors for sleep apnea and treatment barriers to PAP that may be unique to women. Future studies should also identify potential sex differences in terms of both sleep apnea presentation and PAP treatment response. This study shows that many women veterans with high risk symptoms are not diagnosed with sleep apnea and demonstrates the importance of assessing for sleep apnea in women, particularly in the context of multiple medical and mental health comorbidities. Finally, this study should inform work to implement the new VA/DOD Clinical Practice Guidelines,8 with particular attention to the needs of women veterans at high risk for sleep apnea.
DISCLOSURE STATEMENT
All authors have seen and approved the manuscript. All authors have agreed to be accountable for all aspects of the work. Work for this study was performed at the authors’ respective institutions. Primary Source of Funding: VA Quality Enhancement Research Initiative (QUERI) RRP 12-189. This research was supported by the VA Quality Enhancement Research Initiative (QUERI; RRP 12-189; PI: Martin); Research Services of the VA Greater Los Angeles Healthcare System (VAGLAHS); and VAGLAHS Geriatric Research, Education and Clinical Center. Dr. Yano’s time was funded by a VA HSR&D Service Senior Research Career Scientist Award (Project #RCS 05-195). Dr. Martin was supported by a VA HSR&D Service Research Career Scientist Award (#RCS 20-191), and the NIH/NHLBI with a research mentoring award (K24 HL143055). Dr. Kelly and Dr. Carlson were supported by the VA Office of Academic Affiliations through the Advanced Fellowship Programs in HSR&D and Advanced Geriatrics and the Advanced Fellowship Programs in HSR&D and Women’s Health. Dr. Song was supported by the NIH/NIA (K23AG045937). The authors report no conflicts of interest.
ACKNOWLEDGMENTS
The authors thank the VA Health Eligibility Center, Stella Jouldjian, MSW, MPH, Julia Yosef, MA, RN, Simone Vukelich, and Sergio Martinez for their assistance with the study. The authors also thank Terry Vandenberg, MA, posthumously, for her many contributions to this project.
Author contributions: Martin: conception and design; acquisition, analysis and interpretation of data; drafting the work or revising it critically; final approval of the version submitted for publication. Carlson: conception; interpretation of data; drafting the work and revising it critically; final approval of the version submitted for publication. Kelly: conception and design; acquisition, analysis, and interpretation of data; drafting the work or revising it critically; final approval of the version submitted for publication. Fung: conception and design; interpretation of data; critically revising the work; final approval of the version submitted for publication. Song: interpretation of data; drafting the work and revising it critically; final approval of the version submitted for publication. Mitchell: conception and design; acquisition, analysis, and interpretation of data; drafting the work and revising it critically; final approval of the version submitted for publication. Zeidler: conception and design; interpretation of data; critically revising the work; final approval of the version submitted for publication. Josephson: conception and design; acquisition, analysis, and interpretation of data; drafting the work or revising it critically; final approval of the version submitted for publication. Badr: interpretation of data; drafting the work and revising it critically; final approval of the version submitted for publication. Zhu: analysis of data, drafting the work and revising it critically, final approval of the version submitted for publication. Alessi: conception and design; analysis and interpretation of data; drafting the work or revising it critically; final approval of the version submitted for publication. Washington: conception and design; acquisition, analysis, and interpretation of data; drafting the work or revising it critically; final approval of the version submitted for publication. Yano: conception and design; analysis and interpretation of data; drafting the work or revising it critically; final approval of the version submitted for publication.
ABBREVIATIONS
- PTSD
post-traumatic stress disorder
- STOP
snoring, tiredness, observed apneas, blood pressure
- VA
Veterans Health Administration
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