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Volume 14 No. 06
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Scientific Investigations

Insomnia Symptoms Among Female Veterans: Prevalence, Risk Factors, and the Impact on Psychosocial Functioning and Health Care Utilization

Kimberly A. Babson, PhD1; Ava C. Wong, MPH2; Danielle Morabito1; Rachel Kimerling, PhD1,2
1National Center for PTSD-Dissemination and Training Division, VA Palo Alto Health Care System, Menlo Park, California; 2Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, California

ABSTRACT

Study Objectives:

To examine the prevalence of self-reported insomnia symptoms, identify subgroups of female veterans with clinically significant insomnia symptoms, and examine the effect on psychosocial functioning and health care utilization.

Methods:

Cross-sectional analysis of insomnia symptoms and associated characteristics among a stratified random sample of female veterans using Department of Veterans Affairs primary care facilities between October 1, 2010 and September 30, 2011 (n = 6,261) throughout the United States. The primary outcome was reported presence of insomnia symptoms. Other variables included psychological disorders, chronic conditions, chronic pain, and demographic variables.

Results:

Overall, 47.39% of female veterans screened positively for insomnia symptoms. They differed demographically from those without insomnia symptoms and reported more substance use, chronic physical conditions, and psychological conditions. Receiver operating characteristic analysis indicated the primary factor that differentiated those with versus those without insomnia symptoms was depression. Individuals were further differentiated based on presence of pain and posttraumatic stress disorder. Results yielded eight homogenous subgroups of women at low and high risk of experiencing insomnia symptoms.

Conclusions:

Sleep problems are common among female veterans (47.39%) despite limited diagnosis of sleep disorders (0.90%). Eight unique subgroups of female veterans with both low and high insomnia symptoms were observed. These subgroups differed in terms of psychosocial functioning and health care utilization, with those with depression, posttraumatic stress disorder, and pain having the poorest outcomes. These results shed light on the prevalence of insomnia symptoms experienced among female veterans and the effect on psychosocial functioning and health care utilization. Results can inform targeted detection and customized treatment among female veterans.

Citation:

Babson KA, Wong AC, Morabito D, Kimerling R. Insomnia symptoms among female veterans: prevalence, risk factors, and the impact on psychosocial functioning and health care utilization. J Clin Sleep Med. 2018;14(6):931–939.


BRIEF SUMMARY

Current Knowledge/Study Rationale: Symptoms of insomnia have been shown to interfere with physical, psychological, and psychosocial well-being. As the proportion of female veterans and their rate of health care utilization is growing, it is important to understand the prevalence of insomnia symptoms in this population.

Study Impact: This study found insomnia was prevalent in nearly half of female veterans enrolled in primary care at the Veterans Health Administration. Targeted treatments for insomnia should be integrated in routine care for female veterans.

INTRODUCTION

Insomnia is a public health epidemic.1 Although common among the general population, there is increased prevalence among certain populations. Military personnel and women represent two groups at elevated risk. Disturbed sleep is one of the most common complaints among veterans from conflicts in Iraq and Afghanistan,2 affecting 30% of returning soldiers.3 Prevalence rates are even higher among certain subsets of military personnel. For example, 58.3% of soldiers returning with traumatic brain injury3 and 90% to 100% of Vietnam-era military veterans with posttraumatic stress disorder (PTSD) report symptoms of insomnia.4,5 Women represent another group with elevated risk for insomnia, with a 1.4 greater risk compared to men.6,7 Therefore, female veterans may represent a particularly high-risk group. Martin and colleagues estimated the prevalence of insomnia in female veterans to be 52.3% in women treated in the greater Los Angeles area.8 However, the national prevalence of insomnia among female veterans is currently unknown.

Insomnia is associated with physical and psychological conditions as well as impairments in psychosocial functioning and elevations in health care utilization.9 Among veterans, insomnia has been associated with PTSD, depression, suicidality, chronic pain, traumatic brain injury, and poorer treatment outcomes from mental health interventions,1014 making insomnia a heterogeneous disorder common among many subgroups of veterans. Psychosocial consequences are also pronounced. Among civilian samples, insomnia is associated with absenteeism, workplace complaints,1517 unemployment,18 alcohol-related problems,19 and significant impairment in social relationships that is particularly pronounced among women.20 However, the psychosocial sequelae associated with insomnia among female veterans have not been examined. Finally, insomnia is strongly associated with increased health care utilization.16 However, it is unclear how insomnia is associated with health care utilization among female veterans. It is not only necessary to understand the prevalence, and consequences, of insomnia symptoms among a changing population of veterans, but it is also critical to understand the unique combination of factors that are associated with subgroups of veterans who have clinically significant insomnia symptoms and how this affects functioning and health care. Such information is necessary to inform assessment and clinical decision making for veterans presenting with a clinical concern that cuts across diagnostic boundaries.21

The Veterans Health Administration (VHA) within the Department of Veterans Affairs (VA) is the largest integrated health care system in the United States making this an ideal setting to explore health care approaches to insomnia. Women now represent the largest proportion of veterans using VA health care services,22 with 57.4% of female veterans seeking services within VA and 89.8% of those women using services more than once,23 making female veterans more likely to initiate VA health care services than their male counterparts.24 Based on the changing population of veterans and increasing rates of VA health care utilization among women, it is important to understand how this heterogeneous symptom, insomnia, and the related comorbid conditions are affecting health care utilization including primary care and mental health appointments. In addition, as women are more likely to receive a prescription for psychotropic medication,25 it is important to examine the effect of insomnia on prescribing practices for female veterans.

This study sought to address these three gaps in the literature. First, we examined the prevalence of insomnia symptoms among a representative sample of female veterans. Second, as insomnia symptoms are present among heterogeneous groups (ie, psychological conditions, medical conditions) we aimed to identify homogenous subgroups of women with clinically significant insomnia symptoms. Third, secondary analyses were conducted to support the receiver operating characteristic (ROC) analysis by providing data on potential differential outcomes in terms of psychosocial functioning and medical and mental health care utilization among these specific subgroups of women. Such information would allow for targeted detection and customized treatment among female veterans.

METHODS

Sample and Procedures

Data were drawn from the Women's Overall Mental Health Assessment of Needs (WOMAN) Survey.26 The WOMAN Survey is a cross-sectional telephone-based survey conducted from June through September 2012 among a national, population-based stratified random sample of female veterans using VHA primary care.

Exclusion criteria included incomplete or international mailing address and current diagnosis of psychosis or dementia. Overall, 84% percent of eligible women with verified contact information participated in the study. The survey was linked to past-year VA administrative data sources to characterize health care utilization. Participants were then mailed a $20 check for their time. All procedures were approved by the Stanford University Institutional Review Board. The current study included 6,261 women who completed the insomnia screener.

Measures

Insomnia

Two items from the Insomnia Severity Index (ISI)27 were used to screen for current symptoms of insomnia consistent with the third edition of the International Classification for Sleep Disorders (ICSD-3) criteria for insomnia: trouble initiating or maintaining sleep, and daytime consequences. The first item combined items 1–3 from the original scale, assessing the severity of problems falling asleep, staying asleep, or waking up too early. Responses were organized on a scale from 1 (none) to 5 (very severe). The second item inquired about the extent to which sleep problems interfere with daily life, and responses were organized on a scale from 1 (not at all) to 5 (extremely). A score of 3 (moderate) or higher on both items indicated a positive screening.

Pain Severity

Severity of pain was obtained from the patients' most recent medical visit within the past year. Severity ratings were based on the 11-point numeric rating scale (0 = no pain, 10 = worst pain).

Psychological Conditions, Chronic Physical Conditions, Sleep Apnea, and Pain Disorders

VA administrative data was used to assess 23 mental health conditions, chronic physical conditions, sleep apnea, and pain disorders. Diagnoses were determined by examining all VA in-patient and outpatient visits in the year prior to the survey. Mental health diagnoses within the past 12 months were classified using International Classification of Diseases, Ninth Revision (ICD-9) codes for mental health conditions according to the Agency for Healthcare Research and Quality Clinical Classifications Software framework.28 Chronic conditions were quantified by grouping ICD-9 diagnostic codes for chronic conditions according to Centers for Medicare and Medicaid Services coding guidelines.29 Because of overlap with mental health conditions, the diagnostic group for depression was excluded from chronic condition categories. The total number of chronic conditions was calculated. Sleep apnea was classified using ICD-9 codes. Pain disorders were classified using ICD-9 codes for disorders characterized by noncancer chronic physical pain.

Hazardous Drinking

Past-year alcohol misuse was assessed using a modified three-item screening version of the Alcohol Use Disorders Identification test (AUDIT-C).30 Consistent with VA policy, a cutoff score of 5 was used to indicate a positive screening for alcohol misuse.

Demographic Characteristics and Psychosocial Functioning

Demographic characteristics, including employment status were assessed using the WOMAN Survey. Low social support was queried using an item, “How often do you get the social and emotional support you need?” Housing instability was assessed using two items and was indicated by women who responded late rent or without a home in the past year. Low income was defined as annual household income of less than $25,000.

Health Care Utilization

VA Medical Statistical Analysis System Outpatient Event files were used to assess: past-year outpatient mental health care and primary care visits, inpatient hospitalizations, and the medication fills for sleep medications (ramelteon, eszopiclone, zaleplon, zolpidem, trazodone), opioids (excluding buprenorphine and methadone), and benzodiazepines. Only outpatient medication fills in the past year (ie, same time frame as utilization) were examined.

Data Analytic Plan

Analyses were based on weighted data to account for design characteristics, nonresponse, and post-stratification to provide a representation of female veterans using primary care facilities throughout VA. Descriptive statistics were used to examine the prevalence of insomnia symptoms. Demographic and psychosocial factors were then examined between those with versus those without a positive screening for insomnia symptoms.

An ROC classification model31 was used to identify patient-level predictors of a positive screen for insomnia symptoms using publicly available ROC5 software (https://web.stanford.edu/∼yesavage/ROC.html). ROC analyses can function as recursive partitioning classification models to identify homogenous subgroups of individuals based on their probability for a binary outcome. These subgroups are defined by underlying higher order interactions among predictor variables. For continuous predictors, cutoff points are generated at all values observed in the variable. Categorical predictors are entered as dichotomous indicator variables. The procedure iteratively divides the sample based on the predictor and cutoff point that best discriminate on the binary outcome, repeating the process on each subsample until a stopping rule (P > .01) is reached, completing the analysis. For the current study, criteria for predictor selection were set to maximize efficiency, the balance between sensitivity and specificity. After three-way interactions were reached, we calculated the prevalence of insomnia symptoms for each subgroup and constructed a decision tree diagram (see Figure 1). The ROC included the following variables: presence/absence of psychological disorder diagnosis, as well as the number of chronic conditions, pain severity, age, race, marital status, education, low income, and geographic residence (see Table 1 and Table 2). The presence or absence of a positive insomnia screen was the primary outcome.

Graphical depiction of ROC analysis.

Graphical depiction of ROC analysis in identifying the percent (n) of women with insomnia within a specific subgroup.

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Figure 1

Graphical depiction of ROC analysis.

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Demographic factors included within the ROC model as a function of the presence versus absence of insomnia.

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Table 1

Demographic factors included within the ROC model as a function of the presence versus absence of insomnia.

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Psychological and physical conditions included as predictors in the ROC model as a function of the presence versus absence of insomnia symptoms.

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Table 2

Psychological and physical conditions included as predictors in the ROC model as a function of the presence versus absence of insomnia symptoms.

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Finally, we used logistic and negative binomial regressions to explore psychosocial functioning and health care utilization among women with insomnia symptoms within each of the subgroups identified by the ROC. For dichotomous outcomes, logistic regression was conducted. For continuous outcomes, negative binomial regressions were conducted.

RESULTS

Prevalence of Insomnia Symptoms Among Female Veterans

A positive screen for insomnia was observed for 47.39% (n = 2,967) of women. Of those with insomnia symptoms, 42.1% (n = 1,248) endorsed moderate severity whereas 57.9% (n = 1,719) reported severe to very severe insomnia symptoms. Meanwhile, 39.2% (n = 1,163) reported moderate, 38.2% (n = 1,133) endorsed severe, and 22.6% (n = 671) endorsed extreme functional impairment.

Women with insomnia symptoms tended to be younger in age, non-white, and have lower socioeconomic standing compared to those without insomnia symptoms (see Table 1). Women with insomnia symptoms also exhibited higher rates of alcohol use, higher pain severity, more chronic conditions, more outpatient mental health care visits, and higher rates of psychological conditions compared to women without insomnia symptoms (see Table 2 and Table 3).

Psychosocial functioning and health care utilization as a function of insomnia subgroup.

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Table 3

Psychosocial functioning and health care utilization as a function of insomnia subgroup.

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Patient-Level Predictors of Insomnia Symptoms Among Female Veterans

See Figure 1 for a graphical depiction of the results. The primary factor that differentiated those with versus those without insomnia symptoms was depression. Specifically, 65.5% of veterans with depression endorsed insomnia symptoms compared to 37.3% of those without depression (χ2 = 458.63, P < .01, k = .26). Those with depression were further differentiated by a pain severity ≥ 4 (on a 0–10 scale) during their most recent doctor appointment in the past year (χ2 = 200.25, P < .01, k = .22). Here, 75.3% of veterans with depression and a pain severity ≥ 4 endorsed insomnia symptoms compared to 58.4% of veterans with depression and a pain severity < 4. Among those with a pain severity ≥ 4, results were further differentiated by PTSD (χ2 = 38.71, P < .01, k = .15). Here, 84.3% of female veterans with depression, a pain severity ≥ 4, and PTSD endorsed insomnia symptoms, compared to 70.0% of women with depression, a pain severity ≥ 4, and without PTSD. A stopping rule was met at this point. However, among those with depression and a pain score < 4, and PTSD further differentiated this group such that 70.6% of veterans with depression, a pain severity < 4, and PTSD endorsed insomnia compared to 51.9% of women with depression, a pain severity < 4, and without PTSD (χ2 = 24.39, P < .01, k = .12). A stopping rule was met at this point, indicating no further differentiation.

Among those without depression, a pain severity ≥ 4 was the best predictor of insomnia symptoms (χ2 = 68.82, P < .01, k = .22). Here, 54.5% of those without depression and a pain severity ≥ 4 endorsed insomnia symptoms compared to 30.5% without depression and a pain severity < 4. Age further differentiated this group (χ2 = 21.68, P < .01, k = .11). Among those without depression, 57.7% of those with a pain severity ≥ 4 who were younger than 62 years endorsed insomnia (compared to 40.1% of those without depression, a pain severity ≥ 4 who were age 62 years or older). A stopping rule for this group was met at this point, indicating no further differentiation. Among those without depression and a pain severity < 4, PTSD further differentiated this group (χ2 = 123.63, P < .01, k = .16) such that 68.7% of those without depression and a low pain severity, but with PTSD endorsed insomnia symptoms (compared to 26.2% of those without depression or PTSD). A stopping rule was met for this group, indicating no further differentiation.

Subgroup Characteristics: Psychosocial Functioning and Health Care Utilization

ROC analyses identified 8 unique subgroups of female veterans with differential risk for insomnia symptoms. These groups were characterized by the following: (1) depression, pain and PTSD; (2) depression and pain; (3) depression and PTSD; (4) depression only; (5) pain and young; (6) pain and elderly; (7) PTSD only; (8) healthy insomnia. Analyses examined psychosocial functioning (housing stability, social support, and unemployment) and health care utilization (past-year inpatient hospitalizations, number of outpatient mental health and primary care visits, and pharmacotherapy use), within each of these groups compared to the healthy insomnia reference group (see Table 3).

Psychosocial Functioning

See Table 3 for model results. Overall, we observed that those with depression, pain and PTSD, depression and pain, depression and PTSD, and those with pain who were elderly were all at higher risk for having unstable housing compared to the healthy insomnia group. Those with depression, pain and PTSD, depression and pain, and depression and PTSD all had a higher risk of being unemployed and having poor social support compared to the healthy insomnia group.

Health Care Utilization

See Table 3 for an overview of all analyses. Logistic regression yielded no differences in past-year inpatient hospitalizations for any of the subgroups in comparison to the healthy insomnia group. However, negative binomial regression indicated that all subgroups, except those with pain only, had more past-year outpatient mental health appointments. In addition, all subgroups, except those with PTSD only and the elderly with pain, had an increased incidence of primary care appointments compared to the healthy insomnia group within the past year (Figure 2). Logistic regressions yielded a similar pattern of findings in terms of pharmacotherapy. In terms of sleep medication, those with depression, pain and PTSD, depression and pain, depression and PTSD, and depression only were more likely than the healthy insomnia group to receive sleep medication. In addition, all groups were more likely to receive a prescription for both opioids and benzodiazepines compared to the healthy insomnia group. Those with depression and pain had the highest risk of prescription opioids compared to the healthy insomnia group. In terms of benzodiazepines, those with depression, pain, and PTSD had a more than fivefold likelihood of using prescription benzodiazepines compared to the healthy insomnia group (Figure 2).

Forest plots.

Forest plots presenting odds ratios and confidence intervals for mental health visits (A), primary care visits (B), benzodiazepine prescriptions (C), and opioid prescriptions (D) by subgroups.

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Figure 2

Forest plots.

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DISCUSSION

Insomnia affects almost half of female veterans enrolled in VHA primary care, despite less than 1% of medical charts including an insomnia diagnosis. This discrepancy may be because of a lack of assessment, or the fact that insomnia is a heterogeneous symptom that is associated with a myriad of physical and psychological conditions. Although insomnia is not simply a symptom of underlying conditions, it is a comorbid condition that should be managed independently and concurrently with other associated conditions. In fact, we observed that risk for insomnia symptoms varied across 8 diagnostic subgroups of female veterans ranging from a low prevalence of 26.2% (healthy women) to a high of 84.3% (women with depression, pain, and PTSD). These subgroups were also associated with risk for poor psychosocial functioning and health care utilization in terms of primary care and mental health appointments and well as pharmacotherapy. These findings are consistent with those observed by Martin and colleagues.8

Demographic and clinical factors, easily obtained from medical charts by a provider, provided the ability to classify female veterans with insomnia symptoms into eight subgroups. Even among healthy women, more than one-fourth experienced insomnia symptoms, highlighting the wide prevalence of insomnia symptoms among female veterans. In contrast, nearly all women with depression, pain, and PTSD reported insomnia symptoms, demonstrating a clinical need to routinely evaluate insomnia among women with these diagnoses. These same groups also had the overall poorest psychosocial functioning across domains and the highest rates of health care utilization in terms of mental health and primary care appointments. Of particular note was the use of medications including sleep medication, opioids, and benzodiazepines across groups. Results demonstrated high rates of benzodiazepine prescriptions among women with PTSD. Clinical practice guidelines for the management of PTSD32 have provided evidence against the use of benzodiazepines. This caution was followed by a significant decrease in benzodiazepine prescribing practices among men with PTSD33; however, our results suggest that these changes in prescribing practices have not been consistently integrated for female veterans. Indeed, this is consistent with previous work that has demonstrated a consistent decrease in benzodiazepine prescriptions among male veterans with PTSD, whereas an increase has been steadily observed among female veterans.25 Similarly, all groups had higher rates of opioid prescriptions compared to the healthy group, including among individuals without pain. However, this is consistent with previous work suggesting that veterans with PTSD and other mental health conditions were more likely to receive a prescription for opioids compared to those without such conditions. This is particularly concerning as opioids have a negative effect on sleep architecture34 and have been associated with increased risk for poor clinical outcomes among veterans, particularly veterans with PTSD.35

Findings should be considered in light of the following limitations. First, the cross-sectional nature of the data does not allow for causal conclusions to be made. Future work would benefit from prospective evaluation. Second, although the use of the ISI is consistent with how insomnia is diagnosed in clinical practice, only a subset of questions from the ISI were used in the current study. This abbreviated version has not been validated. Future research would benefit from examining the validity of an abbreviated version of the ISI, or use of the full measure. Third, the potential contribution of additional factors should be considered. Although we sought to include factors that have been strongly tied to insomnia, future work would benefit from examining the influence of other potential factors such as underlying biological factors (eg, cortisol levels). Fourth, the rates of chronic conditions may appear lower than other estimates using similar methods, as depression was removed from chronic condition counts and examined separately. Given the high prevalence of depression among women, this likely reduces the proportions of women described as having multiple chronic conditions. Finally, the sample comprised veterans engaged in VA health care services. Future research is needed to determine if results generalize to veterans who are not engaged in the VA health care system.

Given the high prevalence of key comorbid conditions (depression, PTSD, pain), the high prevalence of insomnia, and the effect on psychosocial functioning among female veterans combined with the evidence for the treatment of insomnia (namely cognitive behavioral therapy for insomnia and brief behavioral therapy for insomnia), insomnia is a high-value condition for implementing a standard screening for women with key comorbidities, and a standard screening into routine care. The primary care mental health integration is a great opportunity to assess for and triage insomnia symptoms. The ISI is a relatively brief self-report measure that has been used to assess for insomnia in comorbid conditions. Such assessment could set the stage for brief behavioral interventions conducted in this setting by social workers and nurse practitioners or identify the need to refer to specialty clinics.

DISCLOSURE STATEMENT

This study was funded by the VA HSR&D SDR 12-196. Additional funding support was provided by a VA Clinical Science Research and Development Career Development Award (IK2 CX001023; Babson). The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the United States Government. The authors have no financial involvement with organizations whose financial interest may be affected by the material in the manuscript or which might potentially bias it. All authors have reviewed and approved the submission of this manuscript. Dr. Babson is now an employee of Jazz Pharmaceuticals, with stock and/or options in the company. The views expressed in this presentation do not reflect those of Jazz Pharmaceuticals and are solely the authors. Nothing in this paper represents official Jazz policy or procedures.

ABBREVIATIONS

AUDIT-C

Alcohol Use Disorder Identification Test

DSM

Diagnostic and Statistical Manual of Mental Disorders

ICD

International Classification of Diseases

ISI

Insomnia Severity Index

PTSD

posttraumatic stress disorder

ROC

receiver operating characteristic

VA

Department of Veterans Affairs

VHA

Veterans Health Administration

WOMAN Survey

Women's Overall Mental Health Assessment of Needs Survey

ACKNOWLEDGMENTS

The authors thank Julie Karpenko, MSW, Liberty Greene, MS, M.Ed, and Meghan Saweikis, MS, JD for their contributions to the WOMAN Study.

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