The Burden of Sleep Problems

Abstract

Introduction: Sleep disorders affect up to 1 in 4 adults and can adversely affect a variety of health conditions. However, little is known about detection of sleep disorders in ethnically diverse urban primary care settings. Methods: Patients in urban primary care settings completed surveys to screen for sleep problems and identify comorbid conditions. Providers were given screening results, and provided feedback regarding their clinical utility. Results: Participants (n = 95) were predominantly women (76.8%) and black, non-Hispanic (46.3%), or Hispanic (38.9%). High proportion of participants screened positive for insomnia (31.6%) and screened high risk for sleep apnea (42.1%). Only one-third (32.6%) of participants reported sleeping the recommended 7 to 9 hours per night. The presence of chronic pain (χ² = 4.97, P = .03) was associated with clinically significant insomnia. Obesity was associated with fewer hours of sleep per night, t = 2.19(87), P = .03, and risk for sleep apnea (OR = 3.11, 95% CI = 1.28-7.50). Participants were interested in receiving help for sleep issues during their primary care visits (40%), and providers found the screening at least somewhat useful (74.4%). Discussion: Results highlight the potentially high unmet need for screening and treatment of sleep problems in ethnically diverse urban primary care settings.

Background

In the United States, 50 to 70 million adults have a sleep disorder.¹ Insomnia and sleep apnea affect 6% to 10% and 10% to 25% of adults, respectively.² Population³ and primary car⁴ studies report associations between disordered sleep and medical conditions such as obesity, diabetes, and chronic pain, and overall mortality. Primary care providers can play a critical role in identifying and reducing disordered sleep.² However, primary care settings typically do not routinely screen for sleep disorders, which may contribute to underidentification.^5-7

Ethnically diverse urban primary care settings may be particularly important targets for sleep disorder screening. Low socioeconomic status and urban living are risk factors for sleep disorders.^8-10 People who identify as black or Hispanic are less likely to report sleeping the 7 to 9 hours per night recommended by the National Sleep Foundation¹¹ compared to white, non-Hispanic in population-based studies.¹² Sleep disorders are underidentified in ethnically diverse populations; for example, only 1.3% of individuals in the Hispanic Community Health Study reported a diagnosis of sleep-disordered breathing, despite almost 40% meeting diagnostic criteria.¹³

Few studies have evaluated sleep problems in urban primary care settings; approximately half of participants in each study identified as white, and half as black.^4,10 These studies demonstrated high rates of poor sleep quality (78%) and elevated risk for sleep apnea (59%).⁴ Identifying as black (vs white) was significantly associated with poorer sleep quality.¹⁰

The current pilot observational study aimed to provide a preliminary evaluation of the prevalence of sleep problems, associations between sleep problems and relevant medical comorbidities, and primary care physician assessment of sleep screening utility in a predominantly black and Hispanic urban primary care setting.

Methods

Participants

Participants (N = 95) were recruited from waiting rooms at 2 primary care clinics affiliated with a major metropolitan hospital in the Bronx, New York. Inclusion criteria were the following: age ≥18 years, English or Spanish speaking, seeing a primary care provider, and capacity to consent.

Procedures

Graduate psychology students approached all patients presenting for primary care during collection periods in July-August, 2015 to screen for inclusion criteria and ascertain interest in participating. After giving oral consent, participants completed surveys in English or Spanish in clinic waiting rooms. Participants received $5 compensation. Providers received screening results prior to appointments, and rated screening utility after. The Albert Einstein College of Medicine Institutional Review Board (# 2014-3350) approved the study.

Measures

Demographics

Participants reported age, gender (male, female, other), Ethnicity (Hispanic, non-Hispanic), and race (white, black/African American, Native American, Asian, Pacific Islander, other).

Help With Sleep Problems

Participants responded “yes” or “no” to: “Have you ever tried to get help for your sleep problems?” and “Are you getting help for your sleep problems now?”; if yes, participants indicated treatment type. Participants responded “yes” or “no” to “Would you like to get help with your sleep?”

Comorbidities

Participants self-reported ever receiving a physician diagnosis of cardiovascular disease, diabetes, chronic pain, or migraine. Height and weight were obtained from the medical record to assess obesity.

Sleep Behavior

Items from the Pittsburgh Sleep Quality Index,¹⁴ a well-validated measure of sleep quality, evaluated bedtime, latency to sleep onset (in minutes), rise time, and estimated hours of sleep per night.

The Insomnia Severity Index

The Insomnia Severity Index¹⁵ (ISI) is a 7-item self-report insomnia screener. Responses range from 0 (“no problem”) to 4 (“very severe problem”). Total scores are classified as absence of insomnia (0-7), subthreshold insomnia (8-14), clinical insomnia (moderate) (15-21), or clinical insomnia (severe) (22-28). The ISI is a well-validated measure with excellent internal consistency (α = .90) and good sensitivity (0.86) and specificity (0.87) for identifying insomnia.¹⁵ The ISI has also been validated for use in primary care, and has demonstrated excellent internal consistency (α = .92) in this setting.¹⁶

The Berlin Questionnaire

The Berlin Questionnaire¹⁷ is a 10-item obstructive sleep apnea screener. The Berlin Questionnaire assesses 3 categories: snoring behavior, daytime sleepiness, and history of hypertension and obesity. Individuals are deemed “high risk” for sleep apnea if they meet a minimum threshold in 2 or more categories and “low risk” if one or zero categories are endorsed. The Berlin Questionnaire is well-validated in primary care, and has demonstrated excellent internal consistency (α = .86-.92) and good sensitivity (0.86) and specificity (0.77).¹⁷

Physician Assessment

Physicians were provided with screening results for each participant prior to the appointment. After the appointment, physicians ranked the perceived utility of the screening results, how the screening results informed patient care, and the extent to which sleep impacted the patient’s other health conditions.

Data Analysis Plan

Data were analyzed using SPSS Version 22. Descriptive statistics were presented for demographic and sleep variables. Chi-squares evaluated relationships between race/ethnicity and sleep problems. Bivariate correlations tested associations between descriptive variables and sleep problems. Odds ratios assessed associations between weight classifications (obesity vs nonobesity) and sleep problems.

Results

Participants (76.8% women, 46.3% black, non-Hispanic and 38.9% Hispanic, mean ± SD age = 44.6 ± 16.8 years) reported sleeping 6.2 hours/night (SD = 1.7) with 31.8 minutes to sleep onset (SD = 37.3) (Table 1). On the ISI, 30 participants (31.6%) screened positive for clinical insomnia (severe=7.4%; moderate= 24.2%). On the Berlin Questionnaire, 40 participants (42.1%) screened “high risk” for sleep apnea.

Table 1.

Demographic and Sleep Descriptive Statistics.

Characteristic	Participants (Mean + SD)	Participants, (n) %
Gender
Female		(73) 76.8
Male		(22) 23.2
Age, years	44.69 ± 16.82
Race/Ethnicity
Black, non-Hispanic		(44) 46.3
Hispanic		(37) 38.9
White		(6) 6.3
Native American		(6) 6.3
Asian		(2) 2.1
Sleep variables
Hours of sleep/night	6.2 ± 1.7
Clinical insomnia		(30) 31.6
High risk for sleep apnea		(40) 42.1

Approximately one-third (32.6%) of participants reported sleeping the recommended 7 to 9 hours per night (Figure 1).¹⁷ A large proportion of participants wanted help with sleep (39.4%); only 12.6% of participants reported currently receiving sleep health care, and 28.4% reported previously receiving sleep health care.

Figure 1.

Participants’ reported hours of sleep per night with National Sleep Foundation guidelines.

Self-reported medical diagnoses included high blood pressure (46.3%), cardiovascular disease (12.6%), diabetes (24.2%), chronic pain (14.7%), and migraine (12.6%). Chronic pain diagnoses were more common among persons with versus without clinically significant insomnia (57% vs 27%, χ² = 4.97, P = .03). No other self-reported diagnoses were associated with sleep.

Mean body mass index (BMI) was 31.80 kg/m² (SD = 7.20); 53.9% of participants met criteria for obesity. Weight status was not associated with overall insomnia severity; however, individuals with obesity reported fewer hours of sleep per night (mean = 5.79 hours, SD = 1.59) compared with individuals without obesity (mean = 6.57 hours, SD = 1.77), t = 2.19 (87), P = .03. Compared to non-obesity, obesity was significantly associated with high risk for sleep apnea (OR = 3.11, 95% CI 1.28-7.50). BMI was significantly higher among individuals who reported problems with snoring (mean = 34.16 kg/m², SD = 8.08) compared with those who did not (mean = 30.60 kg/m², SD = 6.46), t = −2.26 (87), P = .03.

Fewer than half of providers returned surveys (38.9%). Among providers who completed surveys (n = 37), the majority reported screening tools were at least somewhat useful (74.4%), and brought sleep problems to their attention (51.4%). Fewer questionnaires indicated that screeners informed patient counseling (17.1%), testing (5.7%), and referrals (5.7%).

Conclusion

This pilot observational study suggests insomnia and sleep apnea may represent an unmet need among urban, predominantly black and Hispanic primary care patients. Only one-third of participants reported sleeping the recommended 7 to 9 hours each night.¹¹ Approximately one-third of participants screened positive for clinical insomnia, and more than 40% were at high risk for sleep apnea; however, only 12% were currently receiving medical care for their sleep problems. In this sample, clinical insomnia was associated with chronic pain, while risk for sleep apnea was associated with obesity. These results extend previous research, where 59% of predominantly white and black primary care patients were at high risk for sleep apnea, and poor sleep quality was related with obesity.⁴

Results from provider surveys suggest logistic constraints may limit the utility of routine sleep screening in busy urban primary care settings. Fewer than half of providers returned surveys, highlighting the fast pace and high clinical load of urban primary cares. The majority of providers indicated the sleep screeners successfully brought sleep to their attention. However, primary care providers may need improved internal and referral resources to act on information gained from sleep screening. Home sleep testing represents a valid and accessible alternative to a facility-based sleep study to provide diagnostic information regarding sleep apnea.¹⁸ Integration of health psychology in primary care can improve access to evidence-based behavioral insomnia treatment¹⁹; mobile applications are an effective alternative when behavioral health access is limited.¹⁹

To address gaps in the literature, this study targeted urban primary care settings with predominantly black and Hispanic patients. This study addressed linguistic diversity with questionnaires in English and Spanish. Given the paucity of research in this population, these results provide new information about an understudied and important patient population; however, results may not generalize to other populations. This study evaluated sleep and medical comorbidities primarily through the self-report of patients who actively consented to participate in the study; future studies should utilize physician diagnosis or medical record to evaluate clinical diagnoses. Fewer than half of provider questionnaires were returned; provider results should be interpreted with caution. Future qualitative studies should evaluate barriers and facilitators to sleep disorder treatment in this population, and develop and implement individual- and system-level interventions to address identified gaps in sleep management in this population.

Author Biographies

Elizabeth K. Seng is an assistant professor of Psychology and Neurology. Her interests include assessment and management of behavioral factors which exacerbate migraine and other painful conditions.

Cynthia Cervoni is a 4th-year graduate student in the Clinical Psychology, Health Emphasis Ph.D. Program at Ferkauf Graduate School of Psychology. Her areas of interest include obesity and pain.

Jessica L. Lawson is a 4th-year graduate stduent in the Clinical Psychology, Health Emphasis Ph.D. Program at Ferkauf Gradaute School of Psychology. Her areas of interest include health disparities and obesity.

Tanya Oken is a 4th-year graduate student in the Clinical Psychology, Health Emphasis Ph.D. Program at Ferkauf Graduate School of Psychology. Her areas of interest include addressing social disparities in health, mental health, and childhood development.

Sloane Sheldon is a 4th-year graduate student in the Clinical Psychology, Health Emphasis Ph.D. Program at Ferkauf Graduate School of Psychology. Her areas of interest include health psychology and neurocognitive functioning.

M. Diane Mckee is an associate professor and Co-Director of the Division of Research in the Department of Family and Social Medicine. Her interests include women’s health issues in primary and preventive care.

Karen A. Bonuck is a professor in the Departments of Family and Social Medicine, Obstetrics & Gynecology and Women’s Health, and Pediatrics. Her interests include using social-ecological approaches to evaluate and intervene with disparities in pediatric health.