This cross-sectional study describes the temporal trends in racial and ethnic disparities in sleep duration during a 15-year period among US adults with sleep data available from the National Health Interview Survey.
Key Points
Question
How have racial and ethnic differences in self-reported sleep duration among US adults changed from 2004 to 2018?
Findings
In this cross-sectional study of 429 195 US adults, the prevalence of short and long sleep duration were persistently higher among Black individuals during the 15-year study period. The disparities in short sleep duration were highest for Black women, Black individuals with middle or high income, and young and middle-aged Black adults.
Meaning
These findings suggest that marked racial and ethnic differences in sleep duration persisted from 2004 to 2018 and may contribute to health disparities among Black individuals.
Abstract
Importance
Historically marginalized racial and ethnic groups are generally more likely to experience sleep deficiencies. It is unclear how these sleep duration disparities have changed during recent years.
Objective
To evaluate 15-year trends in racial and ethnic differences in self-reported sleep duration among adults in the US.
Design, Setting, and Participants
This serial cross-sectional study used US population-based National Health Interview Survey data collected from 2004 to 2018. A total of 429 195 noninstitutionalized adults were included in the analysis, which was performed from July 26, 2021, to February 10, 2022.
Exposures
Self-reported race, ethnicity, household income, and sex.
Main Outcomes and Measures
Temporal trends and racial and ethnic differences in short (<7 hours in 24 hours) and long (>9 hours in 24 hours) sleep duration and racial and ethnic differences in the association between sleep duration and age.
Results
The study sample consisted of 429 195 individuals (median [IQR] age, 46 [31-60] years; 51.7% women), of whom 5.1% identified as Asian, 11.8% identified as Black, 14.7% identified as Hispanic or Latino, and 68.5% identified as White. In 2004, the adjusted estimated prevalence of short and long sleep duration were 31.4% and 2.5%, respectively, among Asian individuals; 35.3% and 6.4%, respectively, among Black individuals; 27.0% and 4.6%, respectively, among Hispanic or Latino individuals; and 27.8% and 3.5%, respectively, among White individuals. During the study period, there was a significant increase in short sleep prevalence among Black (6.39 [95% CI, 3.32-9.46] percentage points), Hispanic or Latino (6.61 [95% CI, 4.03-9.20] percentage points), and White (3.22 [95% CI, 2.06-4.38] percentage points) individuals (P < .001 for each), whereas prevalence of long sleep changed significantly only among Hispanic or Latino individuals (−1.42 [95% CI, −2.52 to −0.32] percentage points; P = .01). In 2018, compared with White individuals, short sleep prevalence among Black and Hispanic or Latino individuals was higher by 10.68 (95% CI, 8.12-13.24; P < .001) and 2.44 (95% CI, 0.23-4.65; P = .03) percentage points, respectively, and long sleep prevalence was higher only among Black individuals (1.44 [95% CI, 0.39-2.48] percentage points; P = .007). The short sleep disparities were greatest among women and among those with middle or high household income. In addition, across age groups, Black individuals had a higher short and long sleep duration prevalence compared with White individuals of the same age.
Conclusions and Relevance
The findings of this cross-sectional study suggest that from 2004 to 2018, the prevalence of short and long sleep duration was persistently higher among Black individuals in the US. The disparities in short sleep duration appear to be highest among women, individuals who had middle or high income, and young or middle-aged adults, which may be associated with health disparities.
Introduction
In the US, historically marginalized racial and ethnic groups are generally more likely to report and experience sleep deficiencies that may be drivers of racial and ethnic disparities in physical health, mental health, and quality of life.1,2,3,4,5,6,7,8,9 Both short and long sleep duration are more prevalent among Black and Hispanic or Latino individuals compared with White individuals.10,11,12,13,14 The proportion of people reporting short sleep duration has increased across different racial and ethnic groups, widening the gap between Black and White individuals in recent years.12 This increase occurred while a national health objective to increase the proportion of people with sufficient sleep was in place.15,16
In 2020, the National Institute on Minority Health and Health Disparities; the National Heart, Lung, and Blood Institute; and the Office of Behavioral and Social Sciences Research proposed a framework for sleep health disparities research that focused on the need for greater understanding of health consequences and interventions that may eliminate them.8 Their report underscores the need for a more detailed evaluation of the population-level trends in sleep health disparities.
Several key gaps in knowledge persist. First, although information on short sleep is available, our understanding of trends in disparities in long sleep, which is also a risk factor for adverse health outcomes, remains poor. Moreover, little information is available on trends in the racial and ethnic disparities in sleep health stratified by age, sex, or household income.17,18,19 For instance, an understanding of how racial and ethnic differences in sleep duration vary with age may illuminate the periods during a lifetime in which these disparities emerge and peak. Furthermore, there are known differences in sleep duration by age and sex,20 and people with low income are more likely to report poorer sleep health.21 How these differences vary by race and ethnicity remains unknown, and a deeper understanding of these variations is important to identify at-risk groups and institute effective interventions. Finally, many studies have not included Asian individuals as a distinct albeit heterogeneous racial group.
Accordingly, we evaluated the temporal trends in racial and ethnic disparities in sleep duration during a 15-year period using representative data from the National Health Interview Survey (NHIS). We estimated differences in the reported short or long sleep duration between racial and ethnic groups overall and stratified by sex, household income, and health status. In addition, we evaluated the racial and ethnic differences in the association between sleep duration and age. The purpose of this study is to illuminate trends in racial and ethnic disparities in sleep duration and thereby inform policies and practices designed to address these disparities.
Methods
Data Source
We used data from the annual NHIS from 2004 to 2018. The NHIS has a complex multistage area probability design that accounts for nonresponse and oversampling of underrepresented groups, which allows for nationally representative estimates (details in eMethods in the Supplement).22 We used data from the Sample Adult Core file, which includes responses from 1 randomly selected adult from each family for a more in-depth questionnaire (mean conditional response rate from 2004 to 2018, 80.3%; mean final response rate from 2004 to 2018, 62.1%) (eMethods in the Supplement). We obtained the harmonized data from the Integrated Public Use Microdata Series Health Surveys,23 including the NHIS strata, primary sampling unit, and person weights. All NHIS respondents provided oral consent before participation. The institutional review board at Yale University exempted the study from review because NHIS data are publicly available. The study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.
Study Population
We included individuals 18 years or older from 2004 to 2018 of the NHIS. We excluded respondents with missing sleep data. Owing to small numbers, we also excluded those who identified as non-Hispanic Alaskan Native or American Indian and those who identified as non-Hispanic and did not select a primary race (details are given in the Results section).
Demographic Variables
Participants were classified into 4 mutually exclusive racial and ethnic subgroups—non-Hispanic Asian (hereinafter, Asian), non-Hispanic Black or African American (hereinafter, Black), Hispanic or Latino, and non-Hispanic White (hereinafter, White)—based on their responses to the following questions: “What race do you consider yourself to be?” and “Do you consider yourself Latino/Hispanic?” Other characteristics included were self-reported age, sex, household income level, health status, and geographic region. Based on the family income level relative to the respective year’s federal poverty level from the US Census Bureau, income level was categorized as low (<200% of the federal poverty level) or middle to high (≥200% of the federal poverty level).24,25,26 Other clinical and sociodemographic characteristics were used only to describe the study population (eMethods in the Supplement).
Sleep Duration
In the NHIS, participants were asked, “On average, how many hours of sleep do you get in a 24-hour period?” The responses were coded as integers, rounded to the nearest hour (eMethods in the Supplement). We defined recommended sleep duration as 7 to 9 hours of sleep in a 24-hour period, short sleep duration as fewer than 7 hours, and long sleep duration as more than 9 hours, consistent with expert consensus recommendations.27
Statistical Analysis
We first described the general characteristics of the study population. For each year, we estimated the short and long sleep duration prevalence for each racial and ethnic group using multivariable multinomial logistic regression models, adjusting for age and region (details are provided in the eMethods in the Supplement). To measure the racial and ethnic differences in short and long sleep duration, we subtracted the annual prevalence among White individuals from the annual prevalence among Asian, Black, and Hispanic or Latino individuals for that year. Using these annual estimates and differences between estimates, we determined trends during the study period by fitting weighted linear regression models. In a separate analysis, we tested for an absolute difference in each sleep duration prevalence within each racial and ethnic group and the differences between groups from 2004 to 2018 using a z test.
To evaluate the association between race and ethnicity and each of these sleep duration outcomes by age, we used multinomial logistic regression models with categorical sleep duration as the dependent variable and age group as the independent variable (eMethods in the Supplement). We then stratified the main analysis described above by sex and household income separately. Owing to the high amount of missing income information from nonresponse, the NHIS data include multiply imputed income variables for respondents who do not report income. Thus, our income-stratified analysis was performed based on the National Center for Health Statistics recommendations for multiply imputed data analysis (eMethods in the Supplement).28 For a supplementary analysis, we also stratified the main temporal trends analysis by health status to explore the extent to which the sleep disparities were explained by racial and ethnic differences in self-perceived health. Finally, we performed a sensitivity analysis to assess whether the observed disparities in short sleep duration between Black and White individuals may be explained solely by differences in self-report bias of sleep duration (eMethods in the Supplement).29
For all analyses, a 2-sided P < .05 was used to determine statistical significance. All analyses were performed between July 26, 2021, and February 10, 2022, using Stata SE, version 17.0 (StataCorp LLC), and incorporated the NHIS strata, primary sampling unit, and sample adult weights to produce nationally representative estimates using the svy family of commands for structured survey data. All results are reported with 95% CIs. The NHIS strata, primary sampling unit, and person weights were obtained from the Integrated Public Use Microdata Series. All person weights were pooled and divided by the number of years studied according to guidance from the NHIS.30
Results
Population Characteristics
Among the 444 743 adults interviewed from 2004 to 2018, we excluded 10 203 (2.3%) who had missing information on sleep duration. Because of small numbers, we also excluded 3440 individuals who identified as non-Hispanic Alaskan Native or American Indian and 1905 individuals who identified as non-Hispanic and did not select a primary race (eFigure 1 in the Supplement). Thus, the study sample consisted of 429 195 individuals (median [IQR] age, 46 [31-60] years; 51.7% [95% CI, 51.5%-51.9%] women and 48.3% [95% CI, 48.1%-48.5%] men), of whom 5.1% (95% CI, 4.9%-5.2%) identified as Asian, 11.8% (95% CI, 11.5%-12.2%) identified as Black, 14.7% (95% CI, 14.2%-15.1%) identified as Hispanic or Latino, and 68.5% (95% CI, 67.9%-69.0%) identified as White. Study population characteristics are shown in Table 1, and the unadjusted sleep duration distribution by race and ethnicity is shown in eFigure 2 in the Supplement.
Table 1. Study Population Characteristics.
| Characteristic | Participant race and ethnicitya | ||||
|---|---|---|---|---|---|
| Asian (n = 22 924) | Black (n = 61 226) | Hispanic or Latino (n = 71 567) | White (n = 273 478) | All (N = 429 195) | |
| Age, median (IQR), y | 42 (31-55) | 42 (29-56) | 38 (28-51) | 48 (33-62) | 46 (31-60) |
| Age group, y | |||||
| 18-39 | 44.6 (43.5-45.6) | 44.8 (44.1-45.5) | 53.7 (53.0-54.3) | 34.5 (34.0-34.9) | 39.0 (38.6-39.4) |
| 40-64 | 42.1 (41.2-43.0) | 42.2 (41.7-42.8) | 37.2 (36.7-37.7) | 44.7 (44.4-45.1) | 43.2 (42.9-43.5) |
| ≥65 | 13.4 (12.7-14.0) | 12.9 (12.5-13.3) | 9.1 (8.8-9.5) | 20.8 (20.5-21.1) | 17.8 (17.5-18.0) |
| Sex | |||||
| Women | 52.8 (52.0-53.6) | 55.0 (54.5-55.6) | 49.3 (48.8-49.8) | 51.6 (51.4-51.8) | 51.7 (51.5-51.9) |
| Men | 47.2 (46.4-48.0) | 45.0 (44.4-45.5) | 50.7 (50.2-51.2) | 48.4 (48.2-48.7) | 48.3 (48.1-48.5) |
| US citizenship (n = 428 343) | 69.7 (68.5-70.8) | 95.3 (94.9-95.6) | 65.2 (64.3-66.1) | 98.5 (98.4-98.5) | 91.8 (91.5-92.0) |
| Educational level attained (n = 426 934) | |||||
| Less than high school | 9.4 (8.8-10.1) | 16.8 (16.3-17.3) | 35.3 (34.5-36.0) | 9.5 (9.3-9.7) | 14.1 (13.8-14.4) |
| High school diploma/GED | 26.8 (26.5-27.1) | 30.3 (29.7-30.9) | 26.5 (26.0-27.0) | 26.8 (26.5-27.1) | 26.6 (26.4-26.9) |
| Some college | 22.3 (21.4-23.1) | 33.3 (32.7-34.0) | 25.0 (24.4-25.5) | 31.4 (31.1-31.7) | 30.2 (30.0-60.5) |
| Bachelor’s degree or higher | 32.3 (31.8-32.8) | 19.6 (19.0-20.2) | 13.3 (12.8-13.7) | 32.3 (31.8-32.8) | 29.1 (28.6-29.5) |
| Annual income <200% federal poverty levelb | 28.0 (24.9-31.3) | 46.4 (44.1-48.7) | 51.4 (49.4-48.7) | 24.0 (23.0-25.0) | 30.8 (29.9-31.7) |
| Uninsured at the time of interview (n = 427 762) | 12.0 (11.4-12.6) | 18.1 (17.6-18.6) | 33.4 (32.6-34.2) | 10.3 (10.1-10.6) | 14.7 (14.5-15.0) |
| US regionc | |||||
| Northeast | 19.7 (18.4-21.2) | 15.9 (15.1-16.8) | 13.7 (12.8-14.6) | 18.9 (18.4-19.5) | 17.8 (17.4-18.3) |
| Midwest | 13.1 (12.0-14.2) | 17.5 (16.6-18.5) | 9.2 (8.3-10.0) | 28.0 (27.3-28.7) | 23.2 (22.7-23.8) |
| South | 22.0 (20.6-23.5) | 58.2 (56.8-59.6) | 36.6 (35.1-38.1) | 33.8 (33.0-34.5) | 36.5 (35.8-37.1) |
| West | 45.2 (43.3-47.1) | 8.4 (7.9-8.9) | 40.6 (39.0-42.2) | 19.4 (18.8-20.0) | 22.5 (22.0-23.1) |
| Married or living with partner (n = 427 923) | 64.5 (63.5-65.5) | 34.5 (33.9-35.1) | 53.0 (52.4-53.6) | 57.8 (57.3-58.2) | 54.7 (54.3-55.0) |
| Employment status (n = 428 865) | |||||
| With a job/working | 65.1 (64.2-66.0) | 59.9 (59.2-60.5) | 65.3 (64.7-65.9) | 62.3 (61.9-62.7) | 62.6 (62.3-62.9) |
| Not in labor force | 30.8 (29.9-31.7) | 31.9 (31.2-32.5) | 29.1 (28.5-29.7) | 34.3 (33.9-34.6) | 33.0 (32.7-33.4) |
| Unemployed | 4.1 (3.8-4.4) | 8.3 (8.0-8.6) | 5.7 (5.4-5.9) | 3.5 (3.4-3.6) | 4.4 (4.3-4.5) |
| Poor or fair health | 8.9 (8.4-9.4) | 17.7 (17.3-18.2) | 13.8 (13.4-14.2) | 11.7 (11.5-12.0) | 12.6 (12.4-12.8) |
| Comorbidities | |||||
| Hypertension | 22.2 (21.4-23.0) | 36.2 (35.6-36.9) | 20.7 (20.3-21.2) | 30.4 (30.1-30.7) | 29.3 (29.0-29.5) |
| Diabetes | 7.7 (7.3-8.2) | 11.6 (11.2-11.9) | 9.1 (8.8-9.4) | 8.2 (8.1-8.4) | 8.7 (8.6-8.8) |
| Prior stroke/MI | 2.7 (2.4-3.3) | 5.4 (5.2-5.7) | 3.1 (2.9-3.3) | 6.0 (5.9-6.1) | 5.3 (5.2-5.4) |
| Cancer | 3.1 (2.9-3.4) | 4.2 (4.0-4.4) | 2.9 (2.8-3.1) | 10.6 (10.4-10.7) | 8.3 (8.2-8.4) |
| Emphysema/chronic bronchitis | 1.8 (1.6-2.0) | 4.6 (4.4-4.8) | 2.8 (2.6-2.9) | 5.8 (5.6-5.9) | 5.0 (4.9-5.1) |
| Current smoker | 9.6 (9.1-10.1) | 18.8 (18.3-19.3) | 12.5 (12.2-12.9) | 19.6 (19.3-19.9) | 18.0 (17.8-18.2) |
| Obesity (BMI ≥30) | 9.7 (9.2-10.3) | 37.5 (36.9-38.1) | 30.9 (30.3-31.4) | 27.0 (26.8-27.3) | 28.0 (27.7-28.2) |
Abbreviations: BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); GED, general equivalency diploma; MI, myocardial infarction.
Unless otherwise indicated, data are expressed as weighted percentage of participants (95% CI).
Annual household income was categorized relative to the respective year’s federal poverty level from the US Census Bureau into middle to high income (≥200%) and low income (<200%). The weighted proportion of individuals with annual income at less than 200% of the federal poverty level was estimated using multiple imputation.
Based on where the housing unit of the survey participant was located. The 4 regions correspond to the regions recognized by the US Census Bureau.
Temporal Trends From 2004 to 2018
Short Sleep Duration
In 2004, the age- and region-adjusted estimated prevalence of short sleep (<7 hours) was 31.4% (95% CI, 28.1%-34.8%) among Asian individuals, 35.3% (95% CI, 33.4%-37.2%) among Black individuals, 27.0% (95% CI, 25.4%-28.6%) among Hispanic or Latino individuals, and 27.8% (95% CI, 27.1%-28.6%) among White individuals (Figure 1). From 2004 to 2018, the prevalence of short sleep increased significantly among Black (6.39 [95% CI, 3.32-9.46] percentage points), Hispanic or Latino (6.61 [95% CI, 4.03-9.20] percentage points), and White (3.22 [95% CI, 2.06-4.38] percentage points) individuals regardless of sex or household income stratum (P < .001 for each; Table 2 and eTable 1 in the Supplement). In the same period, the difference between Hispanic or Latino and White individuals increased significantly (3.39 [95% CI, 0.56-6.23] percentage points; P = .02) but did not change significantly between the other subgroups. In 2018, compared with the estimated prevalence among White individuals (31.0% [95% CI, 30.1%-31.9%]), short sleep duration among Black and Hispanic or Latino individuals was higher by 10.68 percentage points (95% CI, 8.12-13.24 percentage points; P < .001) and 2.44 percentage points (95% CI, 0.23-4.65 percentage points; P = .03), respectively (Table 2). The observed disparities between Black and White individuals remained in our sensitivity analysis that accounted for differences in overestimation of sleep duration between the 2 groups (eFigure 3 in the Supplement).
Figure 1. Overall Annual Estimated Prevalence of Short Sleep Duration by Race and Ethnicity Among US Adults.
Short sleep duration was defined as self-reported sleep duration of fewer than 7 hours in a 24-hour period (data source: National Health Interview Survey, 2004-2018). Annual prevalence estimates were obtained using multinomial logistic regression adjusted by age and US region (details are found in the Methods section and the eMethods in the Supplement). Error bars represent 95% CIs.
Table 2. Change in Short and Long Sleep Duration Prevalence by Race and Ethnicity, 2004 to 2018a.
| Characteristic | Participant race and ethnicity | |||||||
|---|---|---|---|---|---|---|---|---|
| Asian | Black | Hispanic or Latino | White | |||||
| Change, percentage points (95% CI) | P value | Change, percentage points (95% CI) | P value | Change, percentage points (95% CI) | P value | Change, percentage points (95% CI) | P value | |
| Short sleep duration | ||||||||
| Absolute change in prevalence, 2004-2018 | ||||||||
| All | 1.58 (−2.95 to 6.10) | .50 | 6.39 (3.32 to 9.46) | <.001 | 6.61 (4.03 to 9.20) | <.001 | 3.22 (2.06 to 4.38) | <.001 |
| Women | 4.02 (−2.35 to 10.40) | .22 | 7.07 (3.07 to 11.07) | <.001 | 4.44 (1.10 to 7.77) | .009 | 3.69 (2.13 to 5.26) | <.001 |
| Men | −0.84 (−7.40 to 5.72) | .80 | 5.67 (1.20 to 10.14) | .01 | 8.75 (4.84 to 12.66) | <.001 | 2.72 (1.12 to 4.31) | .001 |
| Low household income | 3.24 (−6.94 to 13.41) | .53 | 8.14 (3.57 to 12.72) | <.001 | 6.57 (2.77 to 10.38) | <.001 | 5.02 (2.65 to 7.39) | <.001 |
| Middle to high household income | 0.98 (−4.24 to 6.20) | .71 | 4.97 (0.77 to 9.18) | .02 | 6.04 (2.33 to 9.75) | .001 | 2.96 (1.63 to 4.28) | <.001 |
| Difference compared with White individuals, 2004 | ||||||||
| All | 3.65 (0.20 to 7.09) | .04 | 7.51 (5.45 to 9.57) | <.001 | −0.95 (−2.73 to 0.82) | .29 | NA | NA |
| Women | 2.73 (−2.16 to 7.62) | .27 | 8.69 (5.97 to 11.41) | <.001 | 0.40 (−1.84 to 2.63) | .73 | NA | NA |
| Men | 4.40 (−0.59 to 9.39) | .08 | 6.18 (3.21 to 9.16) | <.001 | −2.36 (−4.87 to 0.15) | .07 | NA | NA |
| Low household income | 1.49 (−6.30 to 9.28) | .71 | 1.49 (−1.59 to 4.56) | .34 | −6.06 (−8.69 to −3.42) | <.001 | NA | NA |
| Middle to high household income | 4.24 (0.33 to 8.16) | .03 | 10.23 (7.31 to 13.16) | <.001 | 1.54 (−1.16 to 4.25) | .26 | NA | NA |
| Difference compared with White individuals, 2018 | ||||||||
| All | 2.00 (−1.15 to 5.16) | .21 | 10.68 (8.12 to 13.24) | <.001 | 2.44 (0.23 to 4.65) | .03 | NA | NA |
| Women | 3.06 (−1.31 to 7.43) | .17 | 12.07 (8.74 to 15.39) | <.001 | 1.14 (−1.79 to 4.06) | .45 | NA | NA |
| Men | 0.84 (−3.71 to 5.39) | .72 | 9.14 (5.44 to 12.84) | <.001 | 3.68 (0.28 to 7.07) | .03 | NA | NA |
| Low household income | −0.30 (−7.26 to 6.66) | .93 | 4.61 (0.47 to 8.74) | .03 | −4.51 (−8.14 to −0.88) | .02 | NA | NA |
| Middle to high household income | 2.27 (−1.52 to 5.89) | .23 | 12.25 (8.95 to 15.55) | <.001 | 4.62 (1.76 to 7.49) | .002 | NA | NA |
| Absolute change in difference compared with White individuals, 2004-2018 | ||||||||
| All | −1.64 (−6.32 to 3.03) | .49 | 3.17 (−0.11 to 6.46) | .06 | 3.39 (0.56 to 6.23) | .02 | NA | NA |
| Women | 0.33 (−6.23 to 6.89) | .92 | 3.38 (−0.91 to 7.68) | .12 | 0.74 (−2.94 to 4.43) | .69 | NA | NA |
| Men | −3.56 (−10.31 to 3.20) | .30 | 2.95 (−1.79 to 7.70) | .22 | 6.04 (1.81 to 10.26) | .005 | NA | NA |
| Low household income | −1.79 (−12.24 to 8.66) | .74 | 3.12 (−2.03 to 8.27) | .24 | 1.55 (−2.94 to 6.03) | .50 | NA | NA |
| Middle to high household income | −1.97 (−7.36 to 3.41) | .47 | 2.02 (−2.39 to 6.43) | .37 | 3.08 (−0.86 to 7.02) | .13 | NA | NA |
| Long sleep duration | ||||||||
| Absolute change in prevalence, 2004-2018 | ||||||||
| All | −0.12 (−1.84 to 1.60) | .89 | −1.24 (−2.68 to 0.20) | .09 | −1.42 (−2.52 to −0.32) | .01 | 0.17 (−0.34 to 0.68) | .51 |
| Women | −0.81 (−3.42 to 1.80) | .54 | −0.51 (−2.32 to 1.30) | .58 | −2.05 (−3.46 to −0.64) | .004 | 0.15 (−0.43 to 0.74) | .61 |
| Men | 0.44 (−1.61 to 2.48) | .68 | −2.13 (−4.24 to −0.02) | .05 | −0.78 (−2.41 to 0.89) | .36 | 0.28 (−0.42 to 0.97) | .44 |
| Low household income | −2.30 (−6.81 to 2.21) | .32 | −2.12 (−4.65 to 0.41) | .10 | −1.39 (−3.01 to 0.24) | .09 | 0.72 (−0.47 to 1.91) | .24 |
| Middle to high household income | 0.78 (−0.80 to 2.36) | .34 | −0.51 (−2.17 to 1.16) | .55 | −1.28 (−2.88 to 0.32) | .12 | 0.18 (−0.34 to 0.69) | .50 |
| Difference compared with White individuals, 2004 | ||||||||
| All | −0.92 (−2.41 to 0.56) | .22 | 2.90 (1.81 to 3.99) | <.001 | 1.09 (0.33 to 1.85) | .005 | NA | NA |
| Women | −0.11 (−2.35 to 2.13) | .92 | 2.49 (1.17 to 3.80) | <.001 | 1.54 (0.46 to 2.61) | .005 | NA | NA |
| Men | −1.72 (−3.48 to 0.04) | .06 | 3.41 (1.69 to 5.12) | <.001 | 0.66 (−0.46 to 1.79) | .25 | NA | NA |
| Low household income | −0.06 (−4.20 to 4.08) | .98 | 3.49 (1.52 to 5.45) | <.001 | −0.34 (−1.57 to 0.90) | .59 | NA | NA |
| Middle to high household income | −1.40 (−2.61 to −0.18) | .02 | 1.47 (0.26 to 2.68) | .02 | 1.03 (−0.14 to 2.21) | .09 | NA | NA |
| Difference compared with White individuals, 2018 | ||||||||
| All | −1.27 (−2.25 to −0.29) | .01 | 1.44 (0.39 to 2.48) | .007 | −0.55 (−1.47 to 0.36) | .24 | NA | NA |
| Women | −1.07 (−2.55 to 0.40) | .15 | 1.83 (0.45 to 3.20) | .009 | −0.67 (−1.74 to 0.41) | .23 | NA | NA |
| Men | −1.56 (−2.81 to −0.30) | .02 | 1.00 (−0.41 to 2.42) | .16 | −0.39 (−1.81 to 1.03) | .59 | NA | NA |
| Low household income | −3.08 (−5.23 to −0.94) | .005 | 0.65 (−1.34 to 2.64) | .52 | −2.45 (−4.04 to −0.85) | .003 | NA | NA |
| Middle to high household income | −0.79 (−1.93 to 0.35) | .17 | 0.79 (−0.46 to 2.05) | .22 | −0.42 (−1.62 to 0.78) | .49 | NA | NA |
| Absolute change in difference compared with White individuals, 2004-2018 | ||||||||
| All | −0.34 (−2.12 to 1.43) | .70 | −1.46 (−2.98 to 0.05) | .06 | −1.65 (−2.84 to −0.45) | .007 | NA | NA |
| Women | −0.96 (−3.64 to 1.71) | .48 | −0.66 (−2.56 to 1.24) | .50 | −2.20 (−3.72 to −0.68) | .005 | NA | NA |
| Men | 0.16 (−2.00 to 2.32) | .88 | −2.40 (−4.63 to −0.18) | .03 | −1.05 (−2.86 to 0.76) | .25 | NA | NA |
| Low household income | −3.02 (−7.68 to 1.64) | .20 | −2.84 (−5.64 to −0.04) | .05 | −2.11 (−4.12 to −0.10) | .04 | NA | NA |
| Middle to high household income | 0.61 (−1.06 to 2.27) | .47 | −0.68 (−2.42 to 1.07) | .47 | −1.45 (−3.13 to 0.23) | .09 | NA | NA |
Abbreviation: NA, not applicable.
Data source is the National Health Interview Survey from 2004 to 2018. Short sleep duration was defined as fewer than 7 hours of sleep in a 24-hour period; long sleep duration, as more than 9 hours of sleep in a 24-hour period. For change in prevalence and change in difference, positive percentage points indicate the prevalence (or its difference compared with White individuals) increased; negative percentage points, it decreased. Prevalence estimates were adjusted by age and region.
Similarly, the prevalence difference between Black women and White women persisted during the study period and was 12.07 percentage points (95% CI, 8.74-15.39 percentage points; P < .001) in 2018; among men in 2018, the difference was 9.14 percentage points (95% CI, 5.44-12.84 percentage points; P < .001). The prevalence difference between Hispanic or Latino men and White men, which was absent in 2004, increased and reached 3.68 percentage points (95% CI, 0.28-7.07 percentage points; P = .03) in 2018, whereas there was no significant change in the difference between women (1.14 [95% CI, −1.79 to 4.06] percentage points; P = .45) (Table 2 and eFigure 4 in the Supplement).
When stratified by income, there were no significant changes in the differences between groups during the study period. In 2018, the difference between Black individuals and White individuals was 12.25 percentage points (95% CI, 8.95-15.55 percentage points; P < .001) among those with middle to high income and 4.61 percentage points (95% CI, 0.47-8.74 percentage points; P = .03) among those with low income. In the same year, the difference between Hispanic or Latino individuals and White individuals was 4.62 percentage points (95% CI, 1.76-7.49 percentage points; P = .002) among those with middle to high income and −4.51 percentage points (95% CI, −8.14 to −0.88 percentage points; P = .02) among those with low income (Table 2). The differences in 2018 between Asian and White individuals were not significant for low (−0.30 [95% CI, −7.26 to 6.66] percentage points; P = .93) and middle to high (2.27 [95% CI, −1.52 to 5.89] percentage points; P = .23) income levels.
Long Sleep Duration
In 2004, the adjusted estimated prevalence of long sleep (>9 hours) was 2.5% (95% CI, 1.4%-4.3%) among Asian individuals, 6.4% (95% CI, 5.4%-7.5%) among Black individuals, 4.6% (95% CI, 3.9%-5.3%) among Hispanic or Latino individuals, and 3.5% (95% CI, 3.2%-3.8%) among White individuals (Figure 2). From 2004 to 2018, the prevalence of long sleep significantly changed only among Hispanic or Latino individuals (−1.42 [95% CI, −2.52 to −0.32] percentage points; P = .01) (Table 2). In 2018, compared with the estimated long sleep prevalence among White individuals (3.7% [95% CI, 3.4%-4.1%]), prevalence was higher by 1.44 percentage points among Black individuals (95% CI, 0.39-2.48 percentage points; P = .007). Compared with White women, Black women had higher prevalence of long sleep during the study period (1.83 [95% CI, 0.45-3.20] percentage points; P = .009) (Table 2 and eFigure 5 in the Supplement). When stratified by income, the 2018 difference between Black and White individuals was not significant (low income, 0.65 [95% CI, −1.34 to 2.64] percentage points [P = .52]; middle to high income, 0.79 [95% CI, −0.46 to 2.05] percentage points [P = .22]) (eFigure 5 in the Supplement). When stratified by health status, the observed racial and ethnic disparities in short and long sleep duration persisted within each health status stratum during the study period (eTables 2 and 3 and eFigures 6 and 7 in the Supplement).
Figure 2. Overall Annual Estimated Prevalence of Long Sleep Duration by Race and Ethnicity Among US Adults.
Long sleep duration was defined as self-reported sleep duration of more than 9 hours in a 24-hour period (data source: National Health Interview Survey, 2004-2018). Annual prevalence estimates were obtained using multinomial logistic regression adjusted by age and US region (details are found in the Methods section and eMethods in the Supplement). Error bars represent 95% CIs.
Differences in the Association Between Sleep Duration and Age
Short Sleep Duration
When compared with White individuals of the same age, short sleep duration was more prevalent among Black individuals, with a difference starting at 6.91 percentage points (95% CI, 5.35-8.46 percentage points) among those aged 18 to 24 years, peaking at 10.74 percentage points (95% CI, 8.92-12.55 percentage points) among those aged 50 to 59 years, and reaching 2.91 percentage points (95% CI, 0.76-5.10 percentage points) among those 80 years or older (Figure 3 and eFigure 8 in the Supplement). Among those older than 65 years, the prevalence of short sleep duration decreased for all subgroups as age increased. Similar patterns were observed by sex and among those with middle to high income (eFigure 9 in the Supplement).
Figure 3. Association Between Age and Short and Long Sleep Duration by Race and Ethnicity Among US Adults.
Short sleep duration was defined as self-reported sleep duration of fewer than 7 hours in a 24-hour period; long sleep duration, self-reported sleep duration of more than 9 hours in a 24-hour period (data source: National Health Interview Survey, 2004-2018). Prevalence estimates for each age group were obtained using multinomial logistic regression (details are found in the Methods section and the eMethods in the Supplement). Error bars represent 95% CIs.
Long Sleep Duration
Across all racial and ethnic groups, prevalence of long sleep was lower among those aged 30 to 60 years. Except for individuals aged 18 to 24 years, Black individuals had a higher prevalence than White individuals across all age groups, ranging from 1.69 percentage points (95% CI, 0.95-2.43 percentage points) among those aged 30 to 35 years to 3.78 percentage points (95% CI, 1.77-5.79 percentage points) among those 80 years or older (Figure 3). Similar patterns were observed by sex and income strata (eFigure 10 in the Supplement).
Discussion
In this nationally representative sample of US adults from 2004 to 2018, we found an increasing prevalence of short sleep duration with persistence of racial and ethnic differences. Black individuals consistently had the highest prevalence of short sleep duration, reaching a difference of 10.68 percentage points compared with White individuals in 2018. The disparities were greater for Black women and Black individuals with middle to high income. In addition, the proportion of Hispanic or Latino individuals who reported short sleep increased among men, widening their gap with White men to 3.68 percentage points in 2018. Furthermore, Black individuals also had the highest prevalence of long sleep duration during the study period, although this disparity was narrower than that of short sleep. Prevalence among Asian individuals did not change significantly during the 15-year period and was not significantly different from that of White individuals. Notably, when analyzed by age, the racial and ethnic disparities were greatest among young and middle-aged Black adults and slightly narrowed among older Black adults.
This study expands the literature in several ways. First, we used data from 2004 to 2018 to describe trends in racial and ethnic disparities in sleep duration. Our findings regarding increasing prevalence of short sleep duration are consistent with those of previous NHIS studies,11,12,31,32,33 expanding them by quantifying the magnitude and significance of change in these racial and ethnic differences in the past 15 years and by analyzing disparities in long sleep duration. Of note, another study34 used data from the American Time Use Survey and found a slight increase in sleep duration from 2003 to 2016. Such a discrepancy may arise, in part, from how sleep duration is ascertained in each survey. In contrast with the holistic assessment of mean sleep length in the NHIS, the American Time Use Survey is a telephone-based survey that asks individuals to describe how they spent their day, starting at 4 am the previous day and ending at 4 am on the interview day.35 In addition, in the American Time Use Survey, self-reported time lying in bed may be recorded as sleep even if awake.36 Further research is needed to better understand this discrepancy. Second, we assessed the racial and ethnic differences in the association between each of these sleep duration outcomes and age. To the best of our knowledge, this has not been described previously. Third, we stratified our findings by sex and income, providing further insight into the characterization of these disparities. Fourth, we stratified by health status and found persistence in the disparities. Finally, we included Asian individuals in our analyses, finding that their estimates remained stable, without substantial differences compared with White individuals in 2018.
To understand why short sleep duration may be more common among Black individuals, it is important to discuss the influence of psychosocial stressors, such as race-based discrimination, on sleep health. The stress from perceived race-based discrimination (and its anticipation or vigilance) has been reported to contribute to shorter sleep duration,37 and Black individuals in the US are more likely to experience this than individuals of other racial or ethnic groups. We showed that the disparity in short sleep duration remained stable for 15 years for Black individuals. Further, it has been reported that the effect of perceived discrimination on sleep duration is greater among Black women than among Black men,38 which could partially explain our finding that the racial gaps in short sleep were the widest among Black women. Additional studies are needed to understand how these stressors derived from racial discrimination have changed over the last decades. Future work should also explore the extent to which Hispanic or Latino men may be facing increasing race- and ethnicity-based discrimination or other social stressors that could explain their widening gap with White men during the study period.
Long sleep was also persistently more prevalent among Black individuals, particularly among Black women. This finding may be explained by persistent racial differences in prevalence and type of underlying health conditions and socioeconomic stressors that could potentially lead to long sleep duration, including multimorbidity profiles (an indicator of multiple concurrent chronic conditions) and unemployment.39,40,41 Disparities in multimorbidity prevalence and unemployment rates persisted during the study period for Black individuals,42,43 which could support this explanation. However, further research is needed to understand these patterns and their causes.
The fact that the disparities were the widest among young and middle-aged adults suggests that factors related to working or employment conditions might disproportionally prevent Black individuals from having adequate sleep.44 Notably, when analyzed over years and by age, the gap between Black and White individuals with low income was substantially narrower compared with the gap among those with middle or high income. This finding suggests that a higher income may prevent White individuals from experiencing sleep duration alterations but does not have such a protective association among Black individuals. This differential association of income with sleep health is consistent with observations that higher educational attainment and professional responsibility are associated with lower odds of short sleep among White adults and with greater odds among Black and Hispanic or Latino adults.45,46,47 The findings of the present study suggest that income may be an indicator of educational and professional attainment and that Black individuals with higher income may be more commonly exposed to stressors preventing adequate sleep, including higher levels of racial discrimination.48
Our findings have important public health implications. These persistent disparities may contribute to other persistent racial and ethnic disparities in health. One study26 indicated that from 1999 to 2018, Black individuals had the highest prevalence of poor or fair health. Although the cross-sectional nature of the previous study26 and our study prevents us from assessing causality, the combined findings suggest that short or long sleep duration may be associated with detriments in health. Although the underlying cause of each sleep duration alteration may differ, both short and long sleep duration put individuals at increased risk of depression, reduced quality of life, cardiovascular disease, diabetes, and death, among other conditions.7,49,50,51,52,53 Such a persistent disparity in sleep duration among Black individuals may thus be associated with other health disparities and may serve as an imperfect indicator of overall disparities in health and well-being. For the national objective of achieving health equity, understood as the assurance of the condition of optimal health for all individuals,54 it is thus instrumental to also strive for the elimination of socioeconomic and health conditions that prevent racial and ethnic minority individuals from achieving adequate sleep.
Our findings also have important implications for the design of public health interventions, suggesting that targeted efforts should be made to improve sleep health among Black and Hispanic or Latino individuals. The observed persistent—and growing—disparities in sleep duration serve as an additional indicator of the consequences of the artificial hierarchy in which racial and ethnic minority individuals encounter higher barriers to maintaining a healthy life, including income distribution inequality, racial segregation, restricted access to medical care, and exposure to social and environmental conditions that affect health and sleep (eg, light, noise, and air pollution). Thus, and as with other disparities, public policies may be ineffective at eliminating these racial and ethnic disparities in sleep duration without accounting for systemic racism as a fundamental cause.
Limitations
This study has several limitations. We relied on self-reported duration of sleep, which may be subject to recall and social desirability bias. Of note, across racial and ethnic groups, self-reported sleep has shown a low-to-moderate agreement with objective measurement of sleep duration.29,55,56,57 When compared with polysomnographic findings, White individuals overestimated their sleep duration by a mean of 73 minutes, whereas Black individuals overestimated it by 54 minutes.29 Such an overestimation may misclassify some participants’ sleep duration. Nonetheless, the potential 20-minute difference in self-reported sleep duration accuracy between White and Black individuals would only minimally explain the disparity between them, as suggested by our sensitivity analysis. Furthermore, self-reported sleep duration has important health implications, including consistent association with mortality across different populations49,58,59,60,61 and across racial and ethnic groups in the US.62 In addition, for the entire study period, we lacked other information that may have provided a more in-depth understanding of these disparities in sleep health, including subjective sleep quality, efficiency, and timing.63 Last, it is possible that the declining NHIS response rates may have influenced our findings. Nonetheless, the NHIS design has several strategies to mitigate nonresponse bias (eMethods in the Supplement).
Conclusions
In this cross-sectional study of NHIS data from 2004 to 2018, there were significant differences in sleep duration by race and ethnicity, and the prevalence of unrecommended sleep duration was persistently higher among Black individuals. The disparities were greatest for Black women, Black individuals who had middle or high income, and young and middle-aged Black adults. Given the importance of sleep to health, the prevalence of short and long sleep duration may be associated with health disparities.
eMethods. Data Collection and Statistical Analysis
eReferences
eTable 1. Annualized Rate of Change in Short and Long Sleep Duration by Race and Ethnicity, 2004 to 2018
eTable 2. Change in Short Sleep Duration Prevalence by Race and Ethnicity and Health Status, 2004 to 2018
eTable 3. Change in Long Sleep Duration Prevalence by Race and Ethnicity and Health Status, 2004 to 2018
eFigure 1. Study Population Flowchart
eFigure 2. Unadjusted Sleep Duration Distribution by Race and Ethnicity
eFigure 3. Short Sleep Sensitivity Analysis Accounting for Differences in Bias of Self-reported Sleep Duration Between Black Individuals and White Individuals
eFigure 4. Annual Estimated Prevalence of Short Sleep Duration by Race and Ethnicity Among US Adults Stratified by Sex and Income Level
eFigure 5. Annual Estimated Prevalence of Long Sleep Duration by Race and Ethnicity Among US Adults Stratified by Sex and Income Level
eFigure 6. Adjusted Annual Prevalence of Short Sleep Duration by Race and Ethnicity Among Those With Poor or Fair Health and With Good to Excellent Health, 2004 to 2018
eFigure 7. Adjusted Annual Prevalence of Long Sleep Duration by Race and Ethnicity Among Those With Poor or Fair Health and With Good to Excellent Health, 2004 to 2018
eFigure 8. Racial and Ethnic Differences in the Association Between Age and Sleep Duration
eFigure 9. Association Between Age and Short Sleep Prevalence by Race and Ethnicity Stratified by Sex and Income Level
eFigure 10. Association Between Age and Long Sleep Prevalence by Race and Ethnicity Stratified by Sex and Income Level
References
- 1.St-Onge MP, Grandner MA, Brown D, et al. ; American Heart Association Obesity, Behavior Change, Diabetes, and Nutrition Committees of the Council on Lifestyle and Cardiometabolic Health; Council on Cardiovascular Disease in the Young; Council on Clinical Cardiology; and Stroke Council . Sleep duration and quality: impact on lifestyle behaviors and cardiometabolic health: a scientific statement from the American Heart Association. Circulation. 2016;134(18):e367-e386. doi: 10.1161/CIR.0000000000000444 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Tobaldini E, Fiorelli EM, Solbiati M, Costantino G, Nobili L, Montano N. Short sleep duration and cardiometabolic risk: from pathophysiology to clinical evidence. Nat Rev Cardiol. 2019;16(4):213-224. doi: 10.1038/s41569-018-0109-6 [DOI] [PubMed] [Google Scholar]
- 3.Liu Y, Wheaton AG, Croft JB, Xu F, Cunningham TJ, Greenlund KJ. Relationship between sleep duration and self-reported health-related quality of life among US adults with or without major chronic diseases, 2014. Sleep Health. 2018;4(3):265-272. doi: 10.1016/j.sleh.2018.02.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Itani O, Jike M, Watanabe N, Kaneita Y. Short sleep duration and health outcomes: a systematic review, meta-analysis, and meta-regression. Sleep Med. 2017;32:246-256. doi: 10.1016/j.sleep.2016.08.006 [DOI] [PubMed] [Google Scholar]
- 5.Goldstein SJ, Gaston SA, McGrath JA, Jackson CL. Sleep health and serious psychological distress: a nationally representative study of the United States among White, Black, and Hispanic/Latinx adults. Nat Sci Sleep. 2020;12:1091-1104. doi: 10.2147/NSS.S268087 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Buxton OM, Marcelli E. Short and long sleep are positively associated with obesity, diabetes, hypertension, and cardiovascular disease among adults in the United States. Soc Sci Med. 2010;71(5):1027-1036. doi: 10.1016/j.socscimed.2010.05.041 [DOI] [PubMed] [Google Scholar]
- 7.Jike M, Itani O, Watanabe N, Buysse DJ, Kaneita Y. Long sleep duration and health outcomes: a systematic review, meta-analysis and meta-regression. Sleep Med Rev. 2018;39:25-36. doi: 10.1016/j.smrv.2017.06.011 [DOI] [PubMed] [Google Scholar]
- 8.Jackson CL, Walker JR, Brown MK, Das R, Jones NL. A workshop report on the causes and consequences of sleep health disparities. Sleep. 2020;43(8):zsaa037. doi: 10.1093/sleep/zsaa037 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Johnson DA, Jackson CL, Williams NJ, Alcántara C. Are sleep patterns influenced by race/ethnicity—a marker of relative advantage or disadvantage? evidence to date. Nat Sci Sleep. 2019;11:79-95. doi: 10.2147/NSS.S169312 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Chen X, Wang R, Zee P, et al. Racial/ethnic differences in sleep disturbances: the Multi-Ethnic Study of Atherosclerosis (MESA). Sleep. 2015;38(6):877-888. doi: 10.5665/sleep.4732 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Khubchandani J, Price JH. Short sleep duration in working American adults, 2010-2018. J Community Health. 2020;45(2):219-227. doi: 10.1007/s10900-019-00731-9 [DOI] [PubMed] [Google Scholar]
- 12.Sheehan CM, Frochen SE, Walsemann KM, Ailshire JA. Are US adults reporting less sleep? findings from sleep duration trends in the National Health Interview Survey, 2004-2017. Sleep. 2019;42(2):zsy221. doi: 10.1093/sleep/zsy221 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Krueger PM, Friedman EM. Sleep duration in the United States: a cross-sectional population-based study. Am J Epidemiol. 2009;169(9):1052-1063. doi: 10.1093/aje/kwp023 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Jean-Louis G, Grandner MA, Youngstedt SD, et al. Differential increase in prevalence estimates of inadequate sleep among Black and White Americans. BMC Public Health. 2015;15:1185. doi: 10.1186/s12889-015-2500-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Office of Disease Prevention and Health Promotion; US Department of Health and Human Services . Healthy People 2020. Sleep health. Updated February 6, 2022. Accessed February 11, 2022. https://www.healthypeople.gov/2020/topics-objectives/topic/sleep-health
- 16.Office of Disease Prevention and Health Promotion; US Department of Health and Human Services . Healthy People 2030. Sleep. Accessed February 11, 2022. https://health.gov/healthypeople/objectives-and-data/browse-objectives/sleep
- 17.Jackson CL, Powell-Wiley TM, Gaston SA, Andrews MR, Tamura K, Ramos A. Racial/ethnic disparities in sleep health and potential interventions among women in the United States. J Womens Health (Larchmt). 2020;29(3):435-442. doi: 10.1089/jwh.2020.8329 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Stamatakis KA, Kaplan GA, Roberts RE. Short sleep duration across income, education, and race/ethnic groups: population prevalence and growing disparities during 34 years of follow-up. Ann Epidemiol. 2007;17(12):948-955. doi: 10.1016/j.annepidem.2007.07.096 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Whinnery J, Jackson N, Rattanaumpawan P, Grandner MA. Short and long sleep duration associated with race/ethnicity, sociodemographics, and socioeconomic position. Sleep. 2014;37(3):601-611. doi: 10.5665/sleep.3508 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Kocevska D, Lysen TS, Dotinga A, et al. Sleep characteristics across the lifespan in 1.1 million people from the Netherlands, United Kingdom and United States: a systematic review and meta-analysis. Nat Hum Behav. 2021;5(1):113-122. doi: 10.1038/s41562-020-00965-x [DOI] [PubMed] [Google Scholar]
- 21.Carroll JE, Irwin MR, Stein Merkin S, Seeman TE. Sleep and multisystem biological risk: a population-based study. PLoS One. 2015;10(2):e0118467. doi: 10.1371/journal.pone.0118467 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Centers for Disease Control and Prevention . About the National Health Interview Survey. Reviewed September 16, 2020. Accessed February 11, 2022. https://www.cdc.gov/nchs/nhis/about_nhis.htm
- 23.Blewett LA, Rivera Drew JA, King ML, Williams KCW. IPUMS health surveys: National Health Interview Survey, version 6.4 [dataset]. 2019. Accessed March 16, 2021. 10.18128/D070.V6.4 [DOI]
- 24.Caraballo C, Valero-Elizondo J, Khera R, et al. Burden and consequences of financial hardship from medical bills among nonelderly adults with diabetes mellitus in the United States. Circ Cardiovasc Qual Outcomes. 2020;13(2):e006139. doi: 10.1161/CIRCOUTCOMES.119.006139 [DOI] [PubMed] [Google Scholar]
- 25.Dubay LC, Lebrun LA. Health, behavior, and health care disparities: disentangling the effects of income and race in the United States. Int J Health Serv. 2012;42(4):607-625. doi: 10.2190/HS.42.4.c [DOI] [PubMed] [Google Scholar]
- 26.Mahajan S, Caraballo C, Lu Y, et al. Trends in differences in health status and health care access and affordability by race and ethnicity in the United States, 1999-2018. JAMA. 2021;326(7):637-648. doi: 10.1001/jama.2021.9907 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Watson NF, Badr MS, Belenky G, et al. Recommended amount of sleep for a healthy adult: a joint consensus statement of the American Academy of Sleep Medicine and Sleep Research Society. Sleep. 2015;38(6):843-844. doi: 10.5665/sleep.4716 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Division of Health Interview Statistics National Center for Health Statistics . Multiple imputation of family income and personal earnings in the National Health Interview Survey: methods and examples. August 2019. Accessed February 11, 2022. https://nhis.ipums.org/nhis/resources/tecdoc18.pdf
- 29.Jackson CL, Patel SR, Jackson WB II, Lutsey PL, Redline S. Agreement between self-reported and objectively measured sleep duration among White, Black, Hispanic, and Chinese adults in the United States: Multi-Ethnic Study of Atherosclerosis. Sleep. 2018;41(6). doi: 10.1093/sleep/zsy057 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Centers for Disease Control and Prevention . National Health Interview Survey, 1997-2018. Survey description document. Reviewed July 7, 2021. Accessed February 11, 2022. https://www.cdc.gov/nchs/nhis/1997-2018.htm
- 31.Ford ES, Cunningham TJ, Croft JB. Trends in self-reported sleep duration among US adults from 1985 to 2012. Sleep. 2015;38(5):829-832. doi: 10.5665/sleep.4684 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Hisler GC, Muranovic D, Krizan Z. Changes in sleep difficulties among the US population from 2013 to 2017: results from the National Health Interview Survey. Sleep Health. 2019;5(6):615-620. doi: 10.1016/j.sleh.2019.08.008 [DOI] [PubMed] [Google Scholar]
- 33.Jokela M, García-Velázquez R, Gluschkoff K, Airaksinen J, Rosenström T. Health behaviors and psychological distress: changing associations between 1997 and 2016 in the United States. Soc Psychiatry Psychiatr Epidemiol. 2020;55(3):385-391. doi: 10.1007/s00127-019-01741-7 [DOI] [PubMed] [Google Scholar]
- 34.Basner M, Dinges DF. Sleep duration in the United States 2003-2016: first signs of success in the fight against sleep deficiency? Sleep. 2018;41(4):zsy012. doi: 10.1093/sleep/zsy012 [DOI] [PubMed] [Google Scholar]
- 35.US Bureau of Labor Statistics . American Time Use Survey. Survey documentation. November 2021. Accessed February 11, 2022. https://www.bls.gov/tus/documents.htm
- 36.Ogilvie RP, Patel SR. Changing national trends in sleep duration: did we make America sleep again? Sleep. 2018;41(4):zsy055. doi: 10.1093/sleep/zsy055 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Gaston SA, Feinstein L, Slopen N, Sandler DP, Williams DR, Jackson CL. Everyday and major experiences of racial/ethnic discrimination and sleep health in a multiethnic population of U.S. women: findings from the Sister Study. Sleep Med. 2020;71:97-105. doi: 10.1016/j.sleep.2020.03.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Sims M, Diez-Roux AV, Gebreab SY, et al. Perceived discrimination is associated with health behaviours among African-Americans in the Jackson Heart Study. J Epidemiol Community Health. 2016;70(2):187-194. doi: 10.1136/jech-2015-206390 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Blanchflower DG, Bryson A. Unemployment and sleep: evidence from the United States and Europe. Econ Hum Biol. 2021;43:101042. doi: 10.1016/j.ehb.2021.101042 [DOI] [PubMed] [Google Scholar]
- 40.Irwin MR, Olmstead R, Carroll JE. Sleep disturbance, sleep duration, and inflammation: a systematic review and meta-analysis of cohort studies and experimental sleep deprivation. Biol Psychiatry. 2016;80(1):40-52. doi: 10.1016/j.biopsych.2015.05.014 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Kalgotra P, Sharda R, Croff JM. Examining multimorbidity differences across racial groups: a network analysis of electronic medical records. Sci Rep. 2020;10(1):13538. doi: 10.1038/s41598-020-70470-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Caraballo C, Mahajan S, Massey D, et al. Temporal trends in racial and ethnic disparities in multimorbidity prevalence in the United States, 1999-2018. medRxiv. Preprint posted online December 8, 2021. doi: 10.1101/2021.08.25.21262641 [DOI] [PubMed]
- 43.US Bureau of Labor Statistics . Labor force characteristics by race and ethnicity, 2018. October 2019. Accessed January 27, 2022. https://www.bls.gov/opub/reports/race-and-ethnicity/2018/home.htm
- 44.Grandner MA, Williams NJ, Knutson KL, Roberts D, Jean-Louis G. Sleep disparity, race/ethnicity, and socioeconomic position. Sleep Med. 2016;18:7-18. doi: 10.1016/j.sleep.2015.01.020 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Luo L, Buxton OM, Gamaldo AA, Almeida DM, Xiao Q. Opposite educational gradients in sleep duration between Black and White adults, 2004-2018. Sleep Health. 2021;7(1):3-9. doi: 10.1016/j.sleh.2020.10.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Sheehan CM, Walsemann KM, Ailshire JA. Race/ethnic differences in educational gradients in sleep duration and quality among US adults. SSM Popul Health. 2020;12:100685. doi: 10.1016/j.ssmph.2020.100685 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Jackson CL, Redline S, Kawachi I, Williams MA, Hu FB. Racial disparities in short sleep duration by occupation and industry. Am J Epidemiol. 2013;178(9):1442-1451. doi: 10.1093/aje/kwt159 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Mouzon DM, Taylor RJ, Nguyen AW, Ifatunji MA, Chatters LM. Everyday discrimination typologies among older African Americans: gender and socioeconomic status. J Gerontol B Psychol Sci Soc Sci. 2020;75(9):1951-1960. doi: 10.1093/geronb/gbz088 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Svensson T, Saito E, Svensson AK, et al. Association of sleep duration with all- and major-cause mortality among adults in Japan, China, Singapore, and Korea. JAMA Netw Open. 2021;4(9):e2122837. doi: 10.1001/jamanetworkopen.2021.22837 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Liu TZ, Xu C, Rota M, et al. Sleep duration and risk of all-cause mortality: a flexible, non-linear, meta-regression of 40 prospective cohort studies. Sleep Med Rev. 2017;32:28-36. doi: 10.1016/j.smrv.2016.02.005 [DOI] [PubMed] [Google Scholar]
- 51.Gallicchio L, Kalesan B. Sleep duration and mortality: a systematic review and meta-analysis. J Sleep Res. 2009;18(2):148-158. doi: 10.1111/j.1365-2869.2008.00732.x [DOI] [PubMed] [Google Scholar]
- 52.Medic G, Wille M, Hemels ME. Short- and long-term health consequences of sleep disruption. Nat Sci Sleep. 2017;9:151-161. doi: 10.2147/NSS.S134864 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Cappuccio FP, D’Elia L, Strazzullo P, Miller MA. Sleep duration and all-cause mortality: a systematic review and meta-analysis of prospective studies. Sleep. 2010;33(5):585-592. doi: 10.1093/sleep/33.5.585 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Keenan W, Sanchez CE, Kellogg E, et al. Achieving Behavioral Health Equity for Children, Families, and Communities: Proceedings of a Workshop. 2, Introduction to Health Equity and Social Determinants of Health. February 13, 2019. Accessed September 20, 2021. https://www.ncbi.nlm.nih.gov/books/NBK540766/
- 55.Cespedes EM, Hu FB, Redline S, et al. Comparison of self-reported sleep duration with actigraphy: results from the Hispanic Community Health Study/Study of Latinos Sueño Ancillary Study. Am J Epidemiol. 2016;183(6):561-573. doi: 10.1093/aje/kwv251 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56.Lauderdale DS, Knutson KL, Yan LL, Liu K, Rathouz PJ. Self-reported and measured sleep duration: how similar are they? Epidemiology. 2008;19(6):838-845. doi: 10.1097/EDE.0b013e318187a7b0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.Jackson CL, Ward JB, Johnson DA, Sims M, Wilson J, Redline S. Concordance between self-reported and actigraphy-assessed sleep duration among African-American adults: findings from the Jackson Heart Sleep Study. Sleep. 2020;43(3):zsz246. doi: 10.1093/sleep/zsz246 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Tamakoshi A, Ohno Y; JACC Study Group . Self-reported sleep duration as a predictor of all-cause mortality: results from the JACC study, Japan. Sleep. 2004;27(1):51-54. [PubMed] [Google Scholar]
- 59.Kwok CS, Kontopantelis E, Kuligowski G, et al. Self-reported sleep duration and quality and cardiovascular disease and mortality: a dose-response meta-analysis. J Am Heart Assoc. 2018;7(15):e008552. doi: 10.1161/JAHA.118.008552 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60.Kronholm E, Laatikainen T, Peltonen M, Sippola R, Partonen T. Self-reported sleep duration, all-cause mortality, cardiovascular mortality and morbidity in Finland. Sleep Med. 2011;12(3):215-221. doi: 10.1016/j.sleep.2010.07.021 [DOI] [PubMed] [Google Scholar]
- 61.Gupta K, Nagalli S, Kalra R, et al. Sleep duration, baseline cardiovascular risk, inflammation and incident cardiovascular mortality in ambulatory US adults: National Health and Nutrition Examination Survey. Am J Prev Cardiol. 2021;8:100246. doi: 10.1016/j.ajpc.2021.100246 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Yang L, Xi B, Zhao M, Magnussen CG. Association of sleep duration with all-cause and disease-specific mortality in US adults. J Epidemiol Community Health. Published online January 13, 2021. doi: 10.1136/jech-2020-215314 [DOI] [PubMed] [Google Scholar]
- 63.Buysse DJ. Sleep health: can we define it? does it matter? Sleep. 2014;37(1):9-17. doi: 10.5665/sleep.3298 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
eMethods. Data Collection and Statistical Analysis
eReferences
eTable 1. Annualized Rate of Change in Short and Long Sleep Duration by Race and Ethnicity, 2004 to 2018
eTable 2. Change in Short Sleep Duration Prevalence by Race and Ethnicity and Health Status, 2004 to 2018
eTable 3. Change in Long Sleep Duration Prevalence by Race and Ethnicity and Health Status, 2004 to 2018
eFigure 1. Study Population Flowchart
eFigure 2. Unadjusted Sleep Duration Distribution by Race and Ethnicity
eFigure 3. Short Sleep Sensitivity Analysis Accounting for Differences in Bias of Self-reported Sleep Duration Between Black Individuals and White Individuals
eFigure 4. Annual Estimated Prevalence of Short Sleep Duration by Race and Ethnicity Among US Adults Stratified by Sex and Income Level
eFigure 5. Annual Estimated Prevalence of Long Sleep Duration by Race and Ethnicity Among US Adults Stratified by Sex and Income Level
eFigure 6. Adjusted Annual Prevalence of Short Sleep Duration by Race and Ethnicity Among Those With Poor or Fair Health and With Good to Excellent Health, 2004 to 2018
eFigure 7. Adjusted Annual Prevalence of Long Sleep Duration by Race and Ethnicity Among Those With Poor or Fair Health and With Good to Excellent Health, 2004 to 2018
eFigure 8. Racial and Ethnic Differences in the Association Between Age and Sleep Duration
eFigure 9. Association Between Age and Short Sleep Prevalence by Race and Ethnicity Stratified by Sex and Income Level
eFigure 10. Association Between Age and Long Sleep Prevalence by Race and Ethnicity Stratified by Sex and Income Level