Racial/Ethnic Disparities in Sleep Health and Potential Interventions Among Women in the United States

Abstract

While essential for health and wellness, the various dimensions of sleep health are generally not equitably distributed across the population, and reasons for racial/ethnic sleep disparities are not fully understood. In this review, we describe racial/ethnic sleep disparities and subsequent implications for health from prior and recently conducted epidemiological and clinical studies as well as the potential sleep interventions presented at the 2018 Research Conference on Sleep and the Health of Women at the National Institutes of Health. Given the clear connection between sleep and poor health outcomes such as cardiovascular disease, we concluded that future studies are needed to focus on sleep health in general, sleep disorders such as insomnia and obstructive sleep apnea in particular, and disparities in both sleep health and sleep disorders among women using an intersectional framework. Future research should also integrate sleep into interventional research focused on women's health as these results could address health disparities by informing, for example, future mobile health (mHealth) interventions prioritizing women beyond the clinical setting.

Introduction

Although essential for health and wellness, the various dimensions of sleep health such as duration, efficiency, regularity, timing, alertness, and quality all on a consistent basis are generally not equitably distributed across the population.^1,2 There are racial/ethnic disparities in sleep health that are not fully understood and addressed. Hence, the objective of this review is to describe racial/ethnic sleep disparities and subsequent medical and health implications, as well as the potential sleep interventions presented at the 2018 Research Conference on Sleep and the Health of Women at the National Institutes of Health. In addition to the epidemiological and clinical studies presented at the conference, we describe some more recently published studies that add to the epidemiological literature related to sleep disparities.

Sleep Health Disparities and Sex Differences in the U.S. Population

Useful for distinguishing a disparity from a difference, a health disparity is considered “a health difference that adversely affects populations designated as disadvantaged, based on one or more of the following health outcomes higher incidence or prevalence of disease, including earlier onset or more aggressive progression; premature or excessive mortality from specific conditions; greater global burden of disease, such as disability adjusted life years, as measured by population health metrics; poorer health behaviors and clinical outcomes related to the aforementioned information; and worse outcomes on validated self-reported measures that reflect daily functioning or symptoms from specific a health difference conditions.”³

There are racial/ethnic disparities in multiple sleep health dimensions. Across racial/ethnic groups and various sleep dimensions more generally, racial/ethnic minorities have been shown to, on average, be less likely to get the recommended amount of 7 hours of sleep; an exception to these findings is the proportion of Hispanics/Latinos who were not born in the United States getting the recommended amount of sleep compared to Whites.² There are also reports of lower sleep efficiency across racial/ethnic minority groups in general.² Among the groups where data exist, racial/ethnic minorities tend to spend less time in slow wave sleep, which is considered physiologically restorative.^4–6 There has been consistently observed greater variability in sleep timing, a higher likelihood of circadian misalignment, and greater daytime sleepiness.^2,7,8 Despite poorer sleep characteristics, racial/ethnic minorities are less likely to complain about their sleep, which has important implications for the use of self-reported data as objectively measured data demonstrate poorer sleep among racial/ethnic minorities. Blacks/African Americans and Asians are more likely to consider themselves of a morningness chronotype—or preferred early bed and wake times, preferred times for peak cognitive and physical performance, and psychological characteristics like affect—which can be influenced by social and environmental factors (e.g., systemic occupational demands).^9,10 Although a matter of debate with mixed/inconsistent data, racial/ethnic minorities appear to be more likely to experience insomnia (acknowledging that there are existing methodological and sampling limitations).¹¹

Of importance is obstructive sleep apnea (OSA)—a chronic disorder characterized by transient closure of the upper airway during sleep, causing lower oxygen levels and multiple awakenings—in Blacks/African Americans, Hispanics/Latinos, and Asians—who appear particularly susceptible and more likely to have OSA. Furthermore, data have shown that Black children have a four to six times higher prevalence of OSA compared with White children,^5,12 and Black compared with White women generally have a higher prevalence and severity of OSA.^12–14 Meetze et al. found that Black females with OSA were significantly younger than White females at the time of diagnosis, which could result in greater heath sequelae and severity over time.¹³ The first study published on OSA among Hispanics/Latinos by Redline et al. showed a high prevalence of sleep apnea in the United States. Among Latinos, almost one-third of men and 18% of women are affected by OSA, after accounting for obesity and age.¹⁵ There was also significant variation in the prevalence of OSA and associated symptoms, such as snoring and daytime sleepiness, across the different Hispanic/Latino heritage groups. Specifically, women of Puerto Rican background and men from Cuban background had the highest prevalence of OSA.

Along with sex/gender differences or disparities and despite few studies investigating intersectionality (or overlapping and interdependent systems of disadvantage that can compound health risks), a recent review has reported on sleep disparities by racial/ethnic and additional social identities stratified by sex/gender.² For instance, among the two most prevalent sleep disorders, men are more likely to be diagnosed with OSA and women are more likely to be diagnosed with or report insomnia, which is characterized as difficulty falling and staying asleep.^16–19 Sex/gender differences could exist, at least in part, due to differences in hormones (e.g., estrogen) and/or fat distribution that likely contributes to differences in pathophysiological manifestations. Further, disparities emanating from socialization could lead to higher levels of rumination among women.

Sleep Health Disparities in Cardiometabolic Disorders and Other Health Consequences

Recent studies have investigated the impact of various sleep dimensions on health outcomes such as obesity, type 2 diabetes, and cardiovascular disease among a racially/ethnically diverse group of women. Regarding obesity, racial/ethnic minorities (especially Black women) experience a disproportionate risk of both suboptimal sleep and obesity.²⁰ Previous epidemiological studies with racial/ethnic diversity generally included women and found insufficient sleep/sleep disturbances to be positively associated with obesity.²⁰ For instance, The Hispanic Community Health Study/Study of Latinos, which included women, showed that OSA was associated with a 90% increase in diabetes mellitus prevalence and 50% increase in hypertension prevalence, independent of obesity.¹⁵ These initial findings suggest a large burden of cardiometabolic diseases possibly caused by untreated OSA in Hispanic/Latinos. Racial/ethnic disparities have been observed across a wide range of outcomes related to cardiometabolic health that are considered negatively impacted by poor sleep.⁸ Sleep difficulty has been associated with type 2 diabetes in the overall population,²¹ and racial/ethnic minorities disproportionately experience both unfavorable sleep and type 2 diabetes.²² Using prospective data among 39,071 racially/ethnically diverse women from across the United States, self-reported sleep duration, sleep latency, night awakenings (NAs), and frequent napping were positively associated with higher type 2 diabetes risk over a mean follow-up period of 8.5 ± 2.1 years. Racial/ethnic minority women with poor sleep had a higher type 2 diabetes risk than Whites with recommended sleep.²³ Furthermore, associations between certain unfavorable sleep dimensions and the prevalence of metabolic syndrome (MetS) were stronger among premenopausal than postmenopausal women (i.e., short sleep [prevalence ratio [PR]_{premenopausal} = 1.23, confidence interval [95% CI]: 1.06–1.42], PR_{postmenopausal} = 1.09, 95% CI: 1.02–1.16, and insomnia symptoms [PR_{premenopausal} = 1.21, 95% CI: 1.05–1.41], [PR_{postmenopausal} = 1.11, 95% CI: 1.05–1.18]). These associations generally did not vary by race/ethnicity, but concurrent insomnia symptoms plus short sleep and MetS were more common among White and Hispanic/Latina postmenopausal women compared with their Black counterparts.²⁴ Importantly, two separate sex-specific mechanisms linking sleep restriction and food intake have been proposed as processes for increased obesity (a risk factor for MetS) in minorities.²⁵

Furthermore, the relationship between sleep and obesity may differ by race/ethnicity for modifiable and nonmodifiable reasons.²⁰ Regarding potential modifiable reasons, racial/ethnic minorities have lived in under-resourced physical and social environments that may also negatively affect sleep health and ultimately contribute to chronic physiological dysregulation that leads to poor health outcomes, such as obesity. A study of the physical environment that included a racially/ethnically diverse group of women found that, after adjusting for confounders, artificial light at night (ALAN) exposure while sleeping was positively associated with a higher prevalence of obesity at the start of the study, as measured using body mass index (PR = 1.03; 95% CI: 1.02–1.03), waist circumference (PR = 1.12; 95% CI: 1.09–1.16), waist-to-hip ratio (PR = 1.04; 95% CI: 1.00–1.08), and waist-to-height ratio (PR = 1.07; 95% CI: 1.04–1.09).²⁶ ALAN exposure while sleeping was also positively associated with obesity risk (relative risk [RR] = 1.19; 95% CI: 1.06–1.34). Sleeping with a television or a light on in the room compared with no ALAN was associated with ≥5 kg of weight gain (RR = 1.17, 95% CI: 1.08–1.27), a ≥10% body mass index increase (RR = 1.13, 95% CI: 1.02–1.26), overweight risk (RR = 1.22, 95% CI: 1.06–1.40), and obesity risk (RR = 1.33, 95% CI: 1.13–1.57) among women. Black women were the most likely to sleep with the television on during sleep. Ultimately, ALAN exposure while sleeping may increase risk of weight gain, overweight, and obesity among women. Future prospective studies in women may help elucidate this association, and interventional studies could clarify whether lowering exposure to ALAN while sleeping can assist in obesity prevention.

Sleep health may also impact racial/ethnic disparities in dementia. Improving sleep could also mitigate dementia disparities in Latinos, who are projected to account for nearly one-third of the 2040 U.S. population. Within a cross-sectional analysis of 9,714 Hispanic/Latino men and women between the ages of 45 and 74 from The Hispanic Community Health Study/Study of Latinos,²⁷ participants had multiple neurocognitive tests, assessing learning, memory, executive function, and processing speed. The severity of OSA defined with the apnea hypopnea index (AHI) was 8.9 for whole group and higher in men (11.5 compared with 6.8 for women). In addition, older participants had increase in AHI from 7.4 among those 45–54 years, to 11.5 in those aged 65–74 years. Sleep apnea was associated with neurocognitive dysfunction in all cognitive domains. In particular, the association was worse in women, compared with men; moreover, the group affected the most were women 45–55 years of age compared with older women. In the same sample of another study, participants who reported 7 hours of sleep on average had better cognitive scores (i.e., memory) than participants with shorter or longer hours of sleep.²⁸

Sleep Disparities and Environment Along with Psychosocial Determinants of Health

Racial/ethnic differences in exposure to environmental factors that impact sleep health may contribute to observed health disparities. Interestingly, while there is widespread residential and labor market segregation by race,^29,30 in a large nationally representative study that included women, disparities in short sleep duration were not observed, and cardiometabolic health disparities were generally reduced when non-Hispanic (NH)-Black and NH-White adults resided in government-assisted rental housing, which likely results in similar living conditions.³¹ Similarly, in a nationally representative study that included women, short sleep duration and cardiovascular health disparities were not observed among Puerto Rican and NH-White residents of government-assisted housing, but Puerto Rican homeowners were more likely to report short sleep duration (<7 hours) compared with NH-White homeowners. Further, this study revealed that Hispanic/Latino versus NH-White disparities in the sleep–cardiovascular health relationship may vary by Hispanic/Latino heritage group and housing tenure.³² Among both men and women using a nationally representative sample of the United States, Johnson et al.² identified racial/ethnic disparities in sleep duration and sleep difficulties by housing type (i.e., house/apartment, mobile home/trailer) overall as well as by race within housing type. Women residing in mobile homes/trailers were more likely (PR = 1.07, 95% CI: 1.04–1.09) to report short sleep duration (<7 hours) compared with participants living in houses/apartments, and Black women living in a house or apartment had a 24% higher prevalence (PR = 1.24, 95% CI: 1.20–1.27) of short sleep than White participants also living in a house or apartment. Differences in place rather than race may be the drivers and disparities; more research in this area is warranted.

Regarding an example of factors in the social environment that may contribute to sleep health disparities and its health sequelae in women, differences in early-life exposures to adversity or traumas appear to independently contribute to sleep health disparities in adulthood.^23,33 For instance, traumatic childhood experiences (TCEs) occurring before the age of 18 years were investigated in a recent study; these TCEs included sexual, physical, and psychological/emotional trauma; natural disasters; major accidents; and household dysfunction.²³ Women in this study also self-reported average sleep duration (short: <7 hours vs. recommended: 7–9 hours), sleep onset latency (SOL) of ∼30 versus <30 minutes, ∼3-NAs once asleep ∼3 times/week, and napping ≥3 versus <3 times/week. Fifty-five percent reported a TCE. Women with versus without any TCE had a higher prevalence of short sleep (PR = 1.08, 95% CI: 1.04–1.11), longer SOL (PR = 1.11, 95% CI: 1.06–1.16), frequent NAs (PR = 1.06, 95% CI: 1.00–1.11), and frequent napping (PR = 1.05, 95% CI: 0.99–1.12). TCEs by a perpetrator considered socially close versus not close were more strongly associated with short sleep (PR = 1.12, 95% CI: 1.09–1.16), SOL (PR = 1.27, 95% CI: 1.22–1.33), NA (PR = 1.20, 95% CI: 1.14–1.27), and napping (PR = 1.24, 95% CI: 1.17–1.32). This research underscores the importance of conducting sleep research from a life-course perspective as racial/ethnic disparities in sleep begin as early as infancy. For instance, Taveras et al. found that Black infants were 3.70 times and Hispanic/Latino infants 2.53 times more likely than NH-White children to get insufficient sleep despite ≥12 hours being recommended.³⁴

Another example of factors in the social environment that may contribute to racial/ethnic disparities in sleep among women are social stressors. For instance, Hispanic/Latinos are one of the most diverse ethnicities, with differences in environment, cultures, and behaviors providing an opportunity to evaluate the culturally relevant factors for health and disease. A study published by Alcantara et al. explored the unique stressors of Hispanic/Latinos in the United States.³⁵ In this study, acculturation stress and ethnic discrimination were associated with daytime sleepiness, chronic psychosocial stress was associated with insomnia symptoms, and ethnic discrimination was associated with short and long sleep durations. Furthermore, studies have suggested that nativity status may contribute to disparities in multiple sleep dimensions.^36–38

Limitations and Gaps in the Existing Literature

Regarding the current literature across racial/ethnic groups and various sleep dimensions, there is a lot of variability in the quality of the data. Most studies were observational and used a cross-sectional study design with only a few studies being experimental. Some studies had small sample sizes (especially for racial/ethnic minorities), which has implications regarding the disparities-related inferences made from the data. Demographic characteristics varied in terms of the participants' mean age and the proportion of women included in a study. Certain racial/ethnic minority populations (e.g., Native Hawaiian/Pacific Islanders) were seldom included, within-group populations were rarely studied, and most studies did not use objective sleep measures although systematic biases exist.³⁹ Addressing these current limitations represents opportunities for future research. For instance, future research should investigate multiple sleep dimensions that are objectively measured using a prospective study design. Within-group differences, intersectionality between race and sex (e.g., Black women having two social identities that influence risk) using an intersectionality framework, as well as the root, fundamental causes of sleep health disparities like modifiable social (e.g., adverse early-life events) and physical (e.g., ALAN) environmental factors should all be studied. In addition, future studies should be conducted from a life-course perspective as disparities in sleep begin in infancy.³⁴ Sleep needs to be investigated as a protective or risk factor in women's health, including reproduction as racial/ethnic minority women (especially Black women) have worse maternal and perinatal health outcomes than White women for which discrimination has been hypothesized as an important contributor or determinant.⁴⁰

Future Directions and Potential Interventions

To address sleep health disparities, transdisciplinary approaches are required,^41,42 especially when developing interventions to improve sleep health in populations most vulnerable to disordered or inadequate sleep, including those with chronic diseases, racial/ethnic minorities, and women.⁴³ Transdisciplinary research convenes expert investigators to tackle complex public health challenges, such as sex disparities in sleep health, by combining methodological approaches from different disciplines in research study design and implementation.⁴⁴ As described by Sampson et al., successful transdisciplinary research initiatives should have (1) collaborators and stakeholders working in concert for exemplary transformative studies, such as research efforts to improve access and usage of health care or address multiple chronic diseases; (2) use of new data sources, platforms, and natural experiments in studies; (3) unique transdisciplinary training programs to increase research capacity; (4) broad and inclusive research themes that incorporate multilevel factors; and (5) platforms for innovative transdisciplinary research that promote systems science approaches.⁴⁵ If implemented correctly, these interconnected steps should impact one another and could yield new approaches to address disparities in sleep health.

A socioecological model can serve as the theoretical framework for transdisciplinary research evaluating the causes and consequences of sleep health disparities and to design interventions to address disparities in sleep health. Socioecological models examine the complex interactions between individuals and their environment, and suggest that an individual's health is influenced through a series of interconnected domains.^46,47 Societal-level factors (i.e., public policy, neighborhood environment) impact social-level factors (i.e., family, friends, social groups), which, in turn, impact individual-level factors (i.e., biological factors, health behaviors). With regard to sleep health, insomnia, or “the presence of an individual's report of difficulty with sleep,” is illustrative of a sleep-related outcome that can be framed by the socioecological model.⁴⁸ Insomnia is particularly pertinent to women's health, given that insomnia is ∼1.5 times more common in women than in men, and prior data suggest that U.S. women ages ≥65 years are the most likely to have insomnia prompting clinical care to manage sleep problems.⁴⁹ Sex differences in circadian rhythm may contribute to higher rates of insomnia as females have a shorter circadian period caused by differences in endogenous temperature and melatonin rhythms as compared with males.^50–53 These sex differences could be related to circulating estrogen, which can impact the hypothalamic circadian pacemaker.^54–56 Changes in sex hormone production also increase risk of insomnia for females during puberty, women during pregnancy, and women during menopause, as progesterone metabolites can alter sleep patterns.^57–59

Ultimately, a woman's biologically determined sleep duration and her practices around sleep are influenced by her social environment, including social support, marital conflict, and socioeconomic status, which is influenced by her overall societal environment, including neighborhood geography, discrimination policies and practices, and the natural environment.^5,10 The interplay of these domains of influence can impact sleep duration and insomnia risk, leading to adverse health outcomes related to cardiovascular and immunologic health.^12–14 Sleep disturbances among pregnant women are increasingly linked to suboptimal maternal/birth outcomes, and despite worsening disparities in adverse birth outcomes, few U.S. studies investigating sleep by pregnancy status have included racially/ethnically diverse populations. Using a nationally representative sample of 71,644 (2,349 pregnant) women from the National Health Interview Survey (2004–2017), Feinstein et al. found that pregnant Black women compared with pregnant White women had a higher prevalence of short sleep (PR_Black = 1.35, 95% CI: 1.08–1.67), which may contribute to health disparities related to maternal and neonatal health outcomes.⁶⁰

Leveraging the socioecological model as a framework, it is important to consider the intersection between biological and psychosocial factors in sleep outcomes for women. For instance, the relationship between the gut microbiome and sleep health demonstrates this interaction between biology and psychology in sleep disparities. Researchers have found that psychological conditions, including anxiety and depression, are both related to sleep behavior and the gut microbiome; however, many of these crosscutting relationships have not been as robustly researched in women.^8,21,22,24 Gut microbiota communicate with the central nervous system—through neural, endocrine, and immune pathways—and thereby influence brain function, depression and anxiety symptoms, and sleep. The bidirectional relationship between the gut microbiome and the brain also means that the central nervous system may influence and regulate gut function and overall homeostasis through neurotransmitters.²⁸ Norepinephrine, epinephrine, dopamine, and serotonin are increasingly being studied specifically around their role in both gastrointestinal and central nervous system functioning.²⁹ Since serotonin plays a vital role in the modulation of sleep, a deregulation of serotonin related to the gut microbiome could lead to dysfunction around sleep behavior and mood.²⁹

Overall, employing a transdisciplinary team is also vital for developing effective health behavior interventions to address sex disparities for sleep disorders such as insomnia.³⁰ For instance, cognitive behavioral therapy has been shown to be particularly effective in treating insomnia; but, only recently have studies examined how it might be delivered electronically to populations of women with limited access to health care.^31,32

In recent years, researchers have conducted interventions designed to target sleep health from a socioecological framework.⁴⁷ For example, Jean-Louis et al. investigated a culturally tailored phone-based intervention that provided physician-recommended assessment and treatment for OSA among 380 African Americans (mean age = 58 years, 71% female) in a two-arm randomized controlled trial (RCT).⁶¹ The treatment arm of the intervention was designed to provide tailored health messages about OSA from trained health educators based on readiness to change and culturally relevant barriers for health behavior change.⁶¹ This study demonstrated that those in the treatment group had a 3.2 times greater likelihood of attending an initial sleep consultation than those in the control group, suggesting that the intervention aided in overcoming specific barriers related to seeking out care for OSA.⁶¹ Jean-Louis and colleagues are currently conducting another culturally tailored, sleep health education and social support intervention to improve OSA assessment and treatment adherence among African Americans.⁶² They will recruit 398 men and women with low-to-high risk for OSA for this two-arm RCT. The 12-month intervention will deliver culturally tailored, peer-led sleep health education, specifically designed using motivational enhancement principles. The findings from this RCT may identify methods for the evaluation and treatment of OSA among African Americans at the population level.⁶² Another RCT performed by Bertisch and colleagues investigated the effectiveness of yoga and physical therapy for improving sleep quality among 320 individuals who have chronic lower back pain (mean age = 46 years; 64% female, 82% non-White).⁶³ Participants were randomized to either (1) yoga classes, (2) one-on-one physical therapy, or (3) education only for >12 weeks. They demonstrated that at baseline almost all (92%) reported poor sleep quality. By the 12th week, those who received yoga classes and physical therapy reported modest but statistically significant increases in sleep quality as compared with those receiving only education.⁶³ Taken together, future sleep health interventions such as those addressing OSA and sleep quality should be designed to elucidate racial/ethnic and/or sex differences in treatment response.

Telehealth is a promising approach that could improve access to sleep health for minorities and other underserved populations. Importantly, the American Academy of Sleep Medicine has endorsed telemedicine as an approach to improve and optimize sleep health access and delivery. In addition, mobile health (mHealth) technology, as defined by wearable technology or mobile applications (apps) related to health, may reach at-risk populations outside of the clinical setting when most needed to improve sleep health.³³ Prior studies suggest that mHealth technology may improve behavioral intervention effectiveness by promoting self-monitoring and self-efficacy.⁶⁴ In recent years, there has been an increase in research conducted on mHealth interventions for sleep health. A systematic review highlighted the benefits of mHealth interventions on sleep health citing their impact on sleep quality, duration, and sleep disorders by highlighting different technological tools that help measure these sleep constructs.³⁵ However, much less is understood about incorporating mHealth technology, especially wearable technology, into community-based interventions focusing on sleep health. Although studies are scarce in the literature, researchers from the University of Pittsburgh are investigating adaptive mHealth interventions for insomnia.³⁶ Their Just-in-Time Adaptive Intervention platform called “iRest” (interactive Resilience Enhancing Sleep Tactics) included a smartphone app, clinician portal, and a secure communications portal between the smartphone app and the clinician portal. Pilot testing was conducted with 19 active duty military service members (aged 18–60 years); this pilot study revealed that study participants viewed the app as highly usable. In addition, their preliminary results indicate the potential usefulness of integrating wearable technologies (i.e., Fitbits) in mHealth research to improve sleep health; however, more robust research is needed on the utility of wearable technology in sleep interventions. Although women consisted of 18% of the pilot sample, the methodologies could be employed for future studies to isolate the impact of this intervention for women.

It is also important to acknowledge the potential barriers that may limit use of mHealth technologies in sleep health interventions. For example, participants may have limited trust of the use of technology for collecting their health information, thus illuminating concerns about privacy and the security of mHealth technologies. When developing community-based interventions using mHealth technology, one must consider the potential resource limitations in using technology, whether it be limited Wi-Fi access or limited technology exposure and literacy.³⁷ These disparities are even more stark when looking at rural communities that continue to lag behind urban areas in broadband access and smartphone ownership.³⁸ Collectively, these are some of the factors that may limit the use of mHealth technologies among women most impacted by health disparities. However, initial studies showing the use of mHealth technology in sleep interventions highlight the potential successes and challenges related to mHealth interventions for sleep health.

In short, sleep health is essential for women's health (including and beyond reproduction). Across the life course, poor sleep health disproportionately impacts racial/ethnic minority women; early-life exposures such as trauma appear to independently contribute to sleep in adulthood. Moreover, early-life exposures (including sleep insufficiency and disturbances) may contribute to recalcitrant and poorly understood health disparities, and racial/ethnic differences in the physical and social environments may serve as effective intervention targets to help eliminate health disparities among women. Based on the existing literature and current gaps in our understanding, there are several important (although nonexhaustive) research opportunities and future research directions regarding sleep health disparities and their health sequelae, specifically among women. Future research to address sex/gender disparities in sleep health should continue to elucidate mechanisms through which a woman's physical and social environments impact biological factors, and ultimately sleep health. For example, researchers could investigate the impact of sleep on maternal and child health during pregnancy as both sleep and maternal as well as child health are generally worse among racial/ethnic minority women. It is also important to study sleep from an intersectionality perspective where sleep across groups based on sex, race, and sexual orientation (e.g., lesbian Black women) should be investigated as unique stressors that may contribute to disparities requiring tailored interventions in these particularly disadvantaged groups. The impact on sleep of social stressors, such as acculturation stress, that are uniquely experienced by certain groups of women also needs further investigation. Furthermore, future studies are imperative to reduce sex/gender differences in the prevalence of sleep disorders such as insomnia and OSA, given the clear connection between sleep health and poor health outcomes such as cardiovascular disease.³⁹ The results of these studies will allow for, as an example, the development of tailored mHealth interventions prioritizing women outside of the clinical setting to reduce these health disparities. Specific methods for reducing barriers to participation in mHealth interventions for sleep health (e.g., privacy concerns, smartphone ownership, internet access) must be examined, so that women most vulnerable to sleep disorders may be reached. Ultimately, emerging data demonstrating sleep disparities among women underscore the importance continuing to strengthen the evidence base for public health professionals to integrate sleep into interventional research focused on women's health in hopes of improving population health and addressing health disparities.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This work was funded, in part, by the Intramural Program at the National Institutes of Health (NIH), National Institute of Environmental Health Sciences (NIEHS, Z1AES103325-01). T.M.P.-W., K.T., and M.R.A. are funded by the Division of Intramural Research of the National Heart, Lung, and Blood Institute (NHLBI: ZIA HL006148; ZIA HL006168; ZIA HL006225) and the Intramural Research Program of the National Institute on Minority Health and Health Disparities at the NIH.