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Behavioral Sleep Medicine, 8:260273, 2010

ISSN: 1540-2002 print/1540-2010 online

DOI: 10.1080/15402002.2010.509255

Ethnic Differences in Continuous PositiveAirway Pressure (CPAP) Adherence in Veterans

With and Without Psychiatric Disorders

Melanie K. Means, Christi S. Ulmer, and Jack D. EdingerDepartment of Veterans Affairs Medical Center and

Duke University Medical Center, Durham, NC

Continuous positive airway pressure (CPAP) is a safe, effective treatment for sleep apnea, yet

adherence is notoriously problematic. Vulnerable populations that may be at increased risk of sleep

apnea include African Americans (AAs) and individuals with psychiatric disorders, yet little is

known about whether such individuals are at increased risk of CPAP non-adherence. This study

examined rates of CPAP adherence in a large sample of AA and Caucasian American (CA) military

veterans with and without comorbid mental health disorders. AAs used CPAP less than CAsthroughout the first 3 months of treatment. AAs with mental health diagnoses showed the lowest

CPAP adherence; additional research is needed to identify factors that may be increasing the risk

for CPAP non-adherence in these individuals.

Obstructive sleep apnea (OSA) is a common medical disorder associated with many adverse

outcomes such as cardio- and cerebro-vascular disease, diabetes, impaired neurocognitive

performance, and increased motor vehicle accidents (Punjabi, 2008; Sanders & Givelber, 2006).

Prevalence estimates range from 2% to 7% in adults; risk factors include obesity, male gender,

age, craniofacial anatomy, and family history (Punjabi, 2008; Sanders & Givelber, 2006).

Military veterans may be at increased risk of OSA because they are predominantly maleand have a high prevalence of cardiovascular disease and obesity (Das et al., 2005; Johnson,

Pietz, Battleman, & Beyth, 2004). In a large sample of over four million Veterans Health

Administration beneficiaries, the prevalence of OSA was found to be 2.91% (Sharafkhaneh,

Giray, Richardson, Young, & Hirshkowitz, 2005; Sharafkhaneh, Richardson, & Hirshkowitz,

2004), and rates exceeding 8% have been reported in Persian Gulf War veterans (Peacock,

Morris, Houghland, Anders, & Blanton, 1997).

Correspondence should be addressed to Melanie K. Means, Psychology Service (116B), Department of Veterans

Affairs Medical Center, 508 Fulton St., Durham, NC 27705. E-mail: [email protected]

This article is not subject to U.S. copyright law.

260

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CPAP ADHERENCE IN VETERANS 261

African Americans (AAs) also may be particularly vulnerable to OSA because they have high

rates of comorbid cardiovascular risk factors such as obesity (Centers for Disease Control and

Prevention, 2009; Ogden et al., 2006; Wang & Beydoun, 2007), hypertension (Hajjar, Kotchen,& Kotchen, 2006; LaRosa & Brown, 2005), and diabetes (Cowie et al., 2006; LaRosa & Brown,

2005; Maskarinec et al., 2009). Over the past decade, there has been increasing recognition

of ethnic differences in normal sleep patterns between AAs and Caucasian Americans (CAs),

with AAs demonstrating lighter sleep patterns and poorer sleep quality (Durrence & Lichstein,

2006; Redline et al., 2004). Thus, AA individuals may be predisposed to developing sleep

problems. Other factors that have been implicated in increasing the risk of OSA in AAs include

craniofacial anatomy, genetics, culture, environment, health care disparity, and socioeconomic

status (SES; Buxbaum, Elston, Tishler, & Redline, 2002; Cakirer et al., 2001; See, Mensah, &

Olopade, 2006; Villaneuva, Buchanan, Yee, & Grunstein, 2005).

Studies investigating ethnic differences in OSA have yielded mixed findings (for a review,

see Durrence & Lichstein, 2006). In general, prevalence rates of OSA in AAs are comparable

or higher than CAs (Durrence & Lichstein, 2006; Kripke et al., 1997; Young et al., 2002).

In young adults, sleep-disordered breathing may be more common in AAs compared to CAs

(Redline et al., 1997). In a community sample of elderly individuals, the overall prevalence of

sleep-disordered breathing in AAs and CAs was similar, but the risk of having severe OSA

was twice as high in AAs (Ancoli-Israel et al., 1995). In a retrospective review of university

clinic patients with OSA, AA males were found to be more obese and to have lower oxygen

saturation levels on their sleep study compared to CA males (Meetze, Gillespie, & Lee, 2002).

The primary treatment for OSA is continuous positive airway pressure (CPAP) therapy due

to its effectiveness in eliminating sleep-related upper airway obstruction, reducing excessive

daytime somnolence, and improving cardiopulmonary function (Hirshkowitz & Lee-Chiong,2006). Unfortunately, many patients treated with CPAP eventually discontinue its use against

medical advice for reasons such as physical discomfort related to the CPAP mask, dryness in

the nose and throat, chronic rhinitis, nighttime awakenings, panic or claustrophobic reactions

to the nasal mask, and the noise and inconvenience of the CPAP apparatus (Engleman & Wild,

2003; Hirshkowitz & Lee-Chiong, 2006). What little is known about ethnic differences in

CPAP adherence has been gleaned from a few retrospective studies. In one analysis of patients

treated in a university sleep clinic, there was no difference in long-term ( 3 months) CPAP

adherence between AA and CA patients (Scharf, Seiden, DeMore, & Carter-Pokras, 2004).

A major weakness of this study, however, was reliance upon self-reported estimates of CPAP

adherence, which is known to underestimate objective adherence (Engleman et al., 1996; Lajos

et al., 2004). Two other studies investigated CPAP adherence at 1 month posttreatment, with

objective usage data obtained directly from the CPAP machines; both of these studies reported

significantly lower CPAP adherence in AA versus CA patients (Budhiraja et al., 2007; Joo &

Herdegen, 2007). Joo and Herdegen found that, in an urban public hospital, AA patients were

5.5 times more likely to be non-adherent with CPAP as CA patients, controlling for gender

and body mass index (BMI). Budhiraja et al. reported a difference in CPAP adherence of 1 hr

per night in AA (4.4 hr) versus CA (5.5 hr) patients.

Mental health symptoms may further complicate a patients ability to use CPAP successfully.

The relationship between OSA and psychiatric symptoms such as depression and anxiety is

well-documented. Psychiatric disorders are more prevalent in individuals with OSA compared

to those without (Saunamaki & Jehkonen, 2007; Schroder & OHara, 2005), a finding that

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262 MEANS, ULMER, EDINGER

has been replicated in a veteran population (Sharafkhaneh et al., 2005). However, little is

known about the role psychiatric factors play in adherence to CPAP. It seems reasonable to

infer that symptoms such as anxiety or depression may impede adherence. For example, aperson suffering from an anxiety disorder may be prone to develop anxiety or panic reactions

to the CPAP mask, or a person with depression may lack the energy or motivation to engage

successfully in CPAP treatment. Recent investigations have lent some support to the interplay

between CPAP adherence and psychiatric factors. Kjelsberg, Ruud, and Stavem (2005) found

that high levels of depression or anxiety in their OSA sample were associated with CPAP

non-adherence. In a sample of Alzheimers patients with OSA, Ayalon et al. (2006) similarly

found higher depression scores to be related to lower CPAP adherence. Lajos et al., (2004)

reported that veterans with posttraumatic stress disorder (PTSD) and OSA had higher levels of

CPAP-related anxiety compared to those without PTSD, and anxiety was predictive of poorer

CPAP adherence.

This study was designed to explore the relationship between CPAP adherence and ethnicity

in a large data set of veterans with OSA and to further determine whether psychiatric status

imposes additional challenges in tolerating CPAP therapy. We investigated differences in CPAP

adherence amongst AA and CA patients with and without psychiatric diagnoses. Our first

research question was, Is there a difference in objective CPAP use between AA and CA

veterans? Specifically, we hypothesized that AA veterans would show poorer CPAP adherence

1 and 3 months after initiation of CPAP therapy (Hypothesis 1). Our second research question

asked, Is CPAP adherence impacted by psychiatric status? We hypothesized that AA and

CA veterans with a psychiatric diagnosis would demonstrate lower rates of CPAP adherence

compared to AA and CA veterans with no mental health diagnosis.

METHOD

Design

The design of this study is a cross-sectional retrospective review of CPAP adherence records

maintained in a clinical database (Encore Pro, Version 1.8i; Respironics Inc., Murrysville, PA)

at the Durham Veterans Affairs (VA) Medical Center Neurodiagnostic Clinic between the years

2000 and 2008. The study was approved by the institutional review board at the Durham (North

Carolina) VA Medical Center.

Participants

To be considered for this study, veterans had to be obtaining their primary medical care through

the VA. They had received a diagnosis of OSA or upper airway resistance syndrome, along

with a prescription for CPAP therapy. All veterans included in the study were enrolled in the

Sleep Apnea Clinic at the Durham VA Medical Center, were nave to CPAP, and had 90

days of continuous CPAP adherence data from the initial implementation of CPAP therapy.

They were excluded if any of the following conditions were met: (a) diagnosis of central

sleep apnea or a comorbid sleep disorder (e.g., narcolepsy, restless legs syndrome, or periodic

limb movement disorder), (b) past history of CPAP use, (c) inpatient status during the CPAP

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TABLE 1

Selection of Study Sample From Continuous Positive

Airway Pressure Database

Variable n %

Reason for exclusion

Missing data 1,088 61.4

Adherence intervention 75 4.2

Inpatient 47 2.7

Central apnea/comorbid sleep disorder 23 1.3

No Veterans Affairs primary care provider 21 1.2

Eligible records 518 29.2

Total records reviewed 1,772 100.0

adherence time period, or (d) participation in a psychological or behavioral treatment to promote

CPAP adherence during the study time period.

In sum, 1,772 patient records were reviewed from the Encore Pro database. Table 1 presents

the percentage of patients that were excluded for various reasons. By far, the most common

reason for exclusion was missing data; this category included veterans who had been on

CPAP prior to the implementation of the adherence database or who had transferred their

medical care to the VA after starting CPAP. Complete 90-day adherence data were available

on 518 veterans. Ethnicity distribution was as follows: AA (40.0%), CA (56.8%), Hispanic

(1.4%), other (1.0%), and unknown (1.0%). Because of the small incidence of Hispanic,

other, and unknown ethnicities, these individuals were excluded from analyses.Of the 501 veterans (95.4% male) in the final sample, 294 (58.7%) were CA, and 207

(41.3%) were AA. One or more mental health diagnoses were present in 60.9% of the sample

.n D 305/, whereas 39.1% of veterans .n D 196/ did not have a mental health diagnosis.

Of the 305 veterans with a mental health diagnosis, virtually all (96.4%) were diagnosed with

either PTSD, a mood disorder, or both (see Table 2). The most common diagnostic category

TABLE 2

Type of Mental Health Diagnoses

Sample

African

Americansa

Caucasiansb

Psychiatric

Diagnostic Categories N n % n %

PTSD only 18 8 44.4 10 55.6

PTSD C mood only 115 58 50.4 57 49.6

PTSD C mood C 1 other 30 11 36.7 19 63.3

PTSD C 1 other 4 1 25.0 3 75.0

Mood only 93 33 35.5 60 64.5

Mood C 1 other 34 10 29.4 24 70.6

Other 11 1 9.1 10 90.9

Note. N D 305. PTSD D posttraumatic stress disorder.a

n D 122.b

n D 183.

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(37.7%) was comorbid PTSD and mood disorder. The other category included diagnoses such

as other anxiety disorders, personality disorders, psychotic disorders, substance use disorders,

bereavement, and adjustment disorders.All veterans were prescribed REMstar (Respironics, Inc., Murrysville, PA) brand devices.

Most veterans (81.6%) were using the standard CPAP model (average pressure was 8.6 cm/H2O),

16.2% had an automatic pressure delivery device (auto-PAP), and 2.2% were prescribed a

bilevel pressure device (BiPAP).

Procedures

The Encore Pro database was reviewed, and records containing 90 days of CPAP usage

data were considered for inclusion. The VA electronic medical record was examined for each

veteran with eligible CPAP adherence data. Demographic variables (age, gender, ethnicity, andBMI) were procured from this medical record. The Respiratory Disturbance Index (RDI) was

obtained from the medical record report of the diagnostic polysomnogram. Presence or absence

of a mental health disorder was determined based on a chart review of each veterans electronic

medical record by the first author (a licensed clinical psychologist). Psychiatric disorders had

to be present or active at the time of CPAP initiation in order to be rated.

Dependent Measures

Measures of CPAP adherence were derived from the Encore Pro database. This database

stores information uploaded from a removable SmartCard (Respironics, Inc., Murrysville, PA)data card inserted into each CPAP unit. Sleep clinic staff routinely extract information from

the SmartCard at the time of veterans clinic visits to provide objective evidence of CPAP

adherence.

For this investigation, CPAP adherence was measured at two time points: the first 30 days

and the first 90 days of use. The 1-month time point was selected because a patients initial

use of CPAP is highly predictive of long-term use (Herdegen et al., 2000; Kribbs et al., 1993).

The 3-month time point provides a more stable and longer-term measure of CPAP adherence.

The dependent measures included the percentage of nights CPAP was used and the average

hours per night of CPAP use (on nights used) at the 1- and 3-month time points.

Analyses

AAs were compared to CAs on age, BMI, RDI, and type of CPAP machine prescribed using

the F-distribution and chi-square statistics as appropriate. Controlling for relevant covariates as

described below, a one-way (factor D ethnicity) univariate analysis of covariance (ANCOVA)

was used to compare groups to test Hypothesis 1, and a two-way (factors D mental health

diagnosis and ethnicity) univariate ANCOVA was used to test Hypothesis 2. Post hoc testing

for Hypothesis 2 was conducted with a Tukey HSD test. The assumptions for use of parametric

inferential statistics were met for all variables. SPSS v. 16 (SPSS, Inc., Chicago, IL) was used

to conduct all statistical analyses.

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TABLE 3

Demographic and Apnea Severity Characteristics of Sample

Sample

African

Americansa Caucasiansb

Characteristic M SD M SD M SD F

Age 55.85 10.28 53.15 10.06 57.75 10.02 25.50**

Body mass index 34.54 6.07 35.25 6.14 34.04 5.98 4.85*

Respiratory Disturbance Index 41.73 30.21 43.10 30.73 40.75 29.85 0.73

Note. N D 501.an D 207. bn D 294.

*p < :05. **p < :001.

RESULTS

The demographic and RDI characteristics of study participants are summarized in Table 3. CAs

were significantly older and had lower BMI than AAs (see Table 3). RDI did not differ by

ethnicity. RDI was, however, significantly lower in those with a mental health diagnosis ( M D

38:22, SD D 29:24) relative to those without (M D 47:22, SD D 30:94), F .1; 498/D 10:77,

p D :001.

Hypothesis 1

The two CPAP adherence measures, percentage of nights used and average hours per night,

were highly correlated at both 1-month (r D :59, p < :001) and 3-month (r D :67, p < :001)

assessments. Adherence means for the entire sample and by ethnic group are summarized

in Table 4. Controlling for age and BMI, the percentage of nights that CPAP was used was

significantly higher in CAs than AAs at both the 1-month and 3-month follow ups. Similarly,

TABLE 4

Continuous Positive Airway Pressure Adherence Differences Between Ethnic Groups

Sample

African


Adherence Measure M SD M SD M SD F

Nights used at 1 month (%) 68.02 32.29 61.54 32.58 72.57 31.35 12.39*

Average hours use at 1 month 4.55 2.12 3.93 1.95 4.98 2.13 23.36*

Nights used at 3 months (%) 61.80 34.07 53.68 33.70 67.51 33.20 15.99*

Average hours use at 3 months 4.49 2.07 3.90 1.94 4.91 2.07 20.52*

Note. N D 499.an D 206. bn D 293.

*p < :0001.

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the average number of hours of CPAP use per night was significantly higher in CAs than AAs

at both time points.

Hypothesis 2

Table 5 summarizes differences in adherence as a function of both ethnicity and mental health

status controlling for age, BMI, and RDI. We found a main effect for mental health diagnosis on

the percentage of nights CPAP was used at the 3-month follow up; veterans with a psychiatric

TABLE 5

Analysis of Covariance of Adherence as a Function of Ethnicity

and Mental Health Diagnosis

Variable df Mean Square F

Percentage of CPAP use at 1 month

Age 1 1,480.02 1.50

BMI 1 132.25 0.13

RDI 1 8,043.95 8.14**

Mental health diagnosis 1 2,373.52 2.40

Ethnicity 1 8,393.65 8.50**

Ethnicity Mental Health Diagnosis 1 6,044.11 6.12*

Error 491 987.70

Average CPAP use at 1 month

Age 1 139,354.95 9.42**

BMI 1 17,723.25 1.20

RDI 1 67,964.04 4.60*


Ethnicity 1 264,846.28 17.91***


Error 491 14,789.29

Percentage of CPAP use at 3 months

Age 1 4,578.15 4.33*

BMI 1 1,459.92 1.38

RDI 1 15,615.97 14.78***

Mental health diagnosis 1 5,293.88 5.01*

Ethnicity 1 12,463.23 11.80**

Ethnicity

Mental Health Diagnosis 1 7,362.72 6.97**Error 491 1,056.56

Average CPAP use at 3 months

Age 1 209,308.00 15.16***

BMI 1 31,338.90 2.27

RDI 1 121,720.69 8.82**


Ethnicity 1 212,796.36 15.42***


Error 491 13,804.38

Note. CPAP D continuous positive airway pressure; BMI D body mass index;

RDI D Respiratory Disturbance Index.

*p < :05. **p < :01. ***p < :001.

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FIGURE 1 Percentage of nights of continuous positive airway pressure used at 1-month follow-up.

disorder had fewer nights of CPAP use. However, we also found a significant interaction

between ethnicity and mental health status for both adherence measures at both time points,

indicating that the relationship between adherence and mental health status depends upon

ethnicity (Figures 14). Post hoc testing revealed that adherence was not associated with mental

health status in CAs. However, AAs with a mental health diagnosis had a significantly lowerpercentage of nights CPAP use at both the 1-month and 3-month time points, and fewer

average hours of use at the 3-month time point relative to all other groups (AAs without a

FIGURE 2 Average hours of continuous positive airway pressure used at 1-month follow-up.

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FIGURE 3 Percentage of nights of continuous positive airway pressure used at 3-month follow-up.

mental health diagnosis and CAs with or without a mental health diagnosis). For average CPAP

use at 1 month, AAs with a mental health diagnosis used CPAP less than CAs (regardless of

mental health status).

Additional analyses were conducted to determine if the type of mental health diagnosis

in AAs was associated with CPAP adherence. Analyses were conducted on three diagnostic

categories: PTSD group (AAs with a diagnosis of PTSD and with or without additional

FIGURE 4 Average hours of continuous positive airway pressure used at 3-month follow-up.

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mental health diagnoses), mood group (AAs with a mood disorder and with or without

additional mental health diagnoses), and PTSD/mood group (AAs with diagnoses of PTSD and

a mood disorder and with or without additional mental health diagnoses). One-way univariateANCOVAs were used to compare CPAP adherence between each diagnostic group (PTSD,

mood, and PTSD C mood) and AAs who had no psychiatric diagnosis, controlling for age,

BMI, and RDI.

Compared to AA veterans with no psychiatric diagnosis, AAs with PTSD used CPAP a

significantly lower percentage of nights at both 1 month, F .5; 201/D 5:65, p D :02; and 3

months, F .5; 201/D 7:85, p D :006. They also had lower average hours of use at 3 months,

F .5; 201/ D 5:27, p D :02. AAs with a mood disorder used CPAP on a lower percentage

of nights at both 1 month, F .5; 201/ D 9:13, p D :003, and 3 months, F .5; 201/ D 10:93,

p D :001; and fewer average nightly use at both 1 month, F .5; 201/ D 5:11, p D :03,

and 3 months, F .5; 201/ D 7:64, p D :006. Similarly, AAs with both PTSD and a mood

disorder used CPAP on a lower percentage of nights at both 1 month, F .5; 201/ D 7:24,

p D :008, and 3 months, F .5; 201/ D 8:00, p D :005; with lower average use at both 1

month, F .5; 201/D 4:82, p D :03, and 3 months, F .5; 201/D 6:74, p D :01.

Exploratory Analyses

Additional analyses were conducted to explore possible ethnic differences in number of mental

health diagnoses, receipt of mental health services, and type of CPAP device.

Number of psychiatric diagnoses. The number of mental health diagnoses by ethnic

category is presented in Table 6. Although there were as many as five psychiatric diagnosesassigned, most veterans had either one or two diagnoses. The Mann-Whitney U test was used

to investigate differences in number of psychiatric diagnoses by ethnic group and was not

significant.

Receipt of mental health services. A post hoc qualitative analysis was undertaken toinvestigate the possibility that our findings among veterans with a mental health diagnosis might

TABLE 6

Number of Mental Health Diagnoses

Sample

African


No. of Psychiatric

Diagnoses N n % n %

1 122 42 34.4 80 65.6

2 140 67 47.9 73 52.1

3 33 9 27.3 24 72.7

4 8 3 37.5 5 62.5

5 2 1 50.0 1 50.0

Note. N D 305.a

n D 122.b

n D 183.

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be explained by an ethnic bias in the utilization or receipt of mental health services. Twenty

patient records (10 AAs and 10 CAs) were randomly selected from our sample of veterans with

a mental health diagnosis. The electronic medical records for these veterans were scrutinizedfor information about psychiatric treatment. Eighty percent of veterans in each ethnic group had

an active prescription for a psychoactive medication at the time of CPAP therapy initiation. One

half of the veterans in each ethnic group were under the care of a VA psychiatrist. Similarly,

30% of veterans in each group were receiving group or individual psychotherapy in addition to

psychiatric services. Two veterans (20%) in each group were not receiving any mental health

care. Based on this subset, there were no identifiable differences in the amount or type of

mental health care received between AA and CA veterans.

Type of CPAP device. Chi-square tests were conducted to investigate the potentialinfluence of CPAP machine type (standard CPAP vs. auto-PAP vs. BiPAP) on ethnicity and

presence or absence of a mental health diagnosis. The type of machine prescribed did not differ

by ethnic category or mental health diagnosis.

DISCUSSION

This retrospective study was conducted to determine whether ethnicity and mental health status

were associated with CPAP adherence in a large sample of military veterans. Previous studies

suggest that AAs tend to be less adherent to CPAP than CAs, and that patients with symptoms

of anxiety and depression show less CPAP adherence than do those without such symptoms. In

regard to our first research question, Is there a difference in objective CPAP use between AAand CA veterans?, we found that AAs demonstrated significantly lower adherence on both

adherence measures at both time points. AAs used CPAP approximately 1 less night per week

and 1 less hour per night compared to CAs, findings that supported our first hypothesis and

are consistent with those reported by Budhiraja et al. (2007).

For our second research question, Is CPAP adherence impacted by psychiatric status?,

we predicted that patients with psychiatric diagnoses would show lower adherence than those

without such disorders. Our examination of the combined factors of ethnicity and mental health

status suggests that the influence of mental health status on adherence is only relevant to AAs

since adherence was not associated with mental health status in CAs. We found that AAs with

a mental health diagnosis tended to use CPAP fewer nights per week and for less time per

night at 1 month, and for less time each night at the 3-month assessment than AAs without

such a diagnosis. Additional analyses did not reveal substantial differences between specific

disorders in AAs in terms of their relationship to adherence in that PTSD, mood disorders, and

the combined conditions were all significantly related to CPAP non-adherence.

It seems noteworthy to mention that AAs with mental health diagnoses used CPAP only

47% of the nights and for 3.6 hr per night, on average, at 3 months. This average usage pattern

falls below the standard of using CPAP for at least 4 hr per night on 70% of the nights that

has been used in previous research to connote minimally acceptable CPAP use (Kribbs et al.,

1993). Thus, the AA patients with mental health diagnoses in our sample seem least likely

to derive clinical benefit from CPAP therapy, despite their having relatively similar disease

severity as the other three subgroups.

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Reasons for the poor CPAP adherence among AAs with mental health diagnoses in our

sample are difficult to ascertain, although it is possible to provide speculations about such

findings. As our analyses statistically controlled for the effects of age, BMI, and RDI, itappears that none of these factors played a significant role in our findings. There was no

evidence that the type of CPAP device prescribed differed between ethnic groups. It is possible

that the AA patients with mental disorders had more serious or more poorly controlled mental

conditions than did the CA patients with mental disorders, which thereby resulted in poorer

adherence to CPAP. However, our qualitative review did not yield any appreciable differences

in amount or type of mental health treatment between CAs and AAs, nor were there differences

in number of psychiatric diagnoses by ethnic group. It is also possible that AAs with mental

disorders have unique treatment needs that are not met satisfactorily by the standard methods

of CPAP introduction and education that was used with our patient cohort. Unfortunately, the

retrospective nature of this study prevents us from ascertaining if these explanations are tenable.

Future studies that consider these speculations would be useful.

Our study findings add to the growing body of literature that suggest a patients ethnicity

and mental health status are factors that need to be considered at the time of CPAP therapy

initiation (Ayalon et al., 2006; Budhiraja et al., 2007; Joo & Herdegen, 2007; Kjelsberg et al.,

2005; Lajos et al., 2004). In addition, our findings suggest the importance of factors other

than ethnicity and psychiatric status that may influence CPAP adherence. As shown in Table 5,

both age and RDI were significantly related to our CPAP adherence measures. Generally,

older patients and those with more severe OSA disease were more prone to adhere to CPAP

than were younger patients or those with less severe OSA. These findings reiterate those of

previous studies (Budhiraja et al., 2007; Collen, Lettieri, Kelly, & Roop, 2009; Engleman

& Wild, 2003; Rolfe, Olson & Saunders, 1991), and suggest that such factors should beconsidered when introducing CPAP therapy in addition to the ethnicity and mental health of

the patient. Specifically, these findings imply more directed efforts toward CPAP adherence

should be devoted to younger patients and those with milder disease to boost chances for

adequate adherence to this treatment.

It is important to consider several limitations of our study design and dataset. As noted, this

was a retrospective study and, thus, lacked some of the controls inherent in studies that are

conducted on a prospective basis. We did not have information available concerning veterans

educational levels, current income levels, or other measures of socioeconomic status (SES);

thus, we could not control for the influence of SES on outcomes. Although one previous

study found no association between a proxy socioeconomic indicator of income and CPAP

adherence (Scharf et al., 2004), emerging research suggests a relationship between SES and

both acceptance and adherence to CPAP (Platt et al., 2009; Simon-Tuval et al., 2009). Also,

although we could identify the presence of psychiatric disorders at the time of CPAP therapy,

information regarding the severity or treatment outcome of these conditions was unavailable.

Finally, our sample included only AA and CA military veterans composed mostly of male

patients followed at a single VA medical center. Thus, our findings may not generalize to

other VA or non-VA patient samples, to women, or to other ethnic minority groups. Despite

these limitations, our findings do seem noteworthy in regard to the influence of ethnicity

and mental health status on CPAP adherence. Future studies are needed to provide a better

understanding for the causes of the differences we noted and methods for ameliorating these

differences.

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ACKNOWLEDGMENTS

This material is the result of work supported with resources and the use of facilities of theDurham North Carolina Veterans Affairs Medical Center. The contents herein do not represent

the views of the Department of Veterans Affairs or the United States Government.

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