The Sleep Crisis Is Increasingly a Social Issue

Sleep health is not equal among US adults, with new research implicating education level, age, body mass index (BMI), and lack of nutritional security as contributing to the racial and ethnic disparities a group of researchers saw after examining data from 2 National Health and Nutrition Examination Surveys, 2005-2008 and 2015-2018.

Their findings were published in a recent issue of BMC Public Health.¹

The patient population for this analysis comprised 17,476 adults representing more than 109 million noninstitutionalized US adults overall and from 4 racial/ethnic groups: Hispanic (n = 4588), non-Hispanic Black (n = 3774), non-Hispanic White (n = 7293), and other races (n = 1821). Mean (SE) ages were 47.0 (0.3), 41.5 (0.4), 44.5 (0.3), 48.8 (0.4), and 44.4 (0.6) years, respectively (P < .001). Female individuals represented more than half of the persons included in every group except for Hispanic individuals; more than 85% had a high school degree or higher education, 57.6% were married, 54.7% were never-smokers, and 59.2% were former or light to moderate alcohol drinkers (all P < .001).

Measuring Healthy Sleep

Beyond public health experts long decrying their concerns regarding chronic sleep deprivation, research is increasingly highlighting racial and ethnic disparities in sleep health, with minoritized populations exhibiting higher rates of sleep disorders, the authors explained.^2-4 They wanted to quantify how much of the sleep gap between racial and ethnic groups could be explained by measurable social, behavioral, and economic factors.

Their healthy sleep score was based on 5 favorable factors, each assigned 1 point: sleeping 7 to 8 hours per night, no trouble sleeping, no snoring, no excessive daytime sleepiness, and no nocturia (≥ 1 episode/night). Hispanic adults had a mean (SE) score of 3.12 (0.03); non-Hispanic Black adults, 2.84 (0.02); non-Hispanic White adults, 3.03 (0.02); and adults of other races, 3.15 (0.04). These varying results were considered statistically significant (P < .001).

Non-Hispanic Black adults had the lowest overall sleep scores, with a −0.18 (0.03) (P < .001) difference compared with non-Hispanic White adults in unadjusted models. Hispanic adults had slightly higher scores than White adults in unadjusted analyses (β = 0.09; P = .005), and adults of other races had modestly higher scores (β = 0.12; P = .003).

Explaining the Gap

To understand what drives these differences, the authors examined 12 covariates. At baseline, levels of severe food insecurity were highest in the Hispanic cohort (28.7%) vs overall (14.5%) and the White cohort (10.4%) (all P < .001); private insurance was the most common health insurance type in more than 50% overall and each subgroup, but highest among the White cohort (84.5%) and lowest among the Hispanic cohort (50.2%) (all P < .001), and close to half of the Hispanic cohort (45.2%) did not have insurance (all P < .001); the Hispanic (55.1%) and the non-Hispanic Black (52.5%) had the highest rates of the lowest level of household income, $0 to $44,999 (P < .001); the White cohort (44.5%) had the highest rate of the highest level of household income, $75,000 or more (P < .001); BMI was similar overall, ranging from 27.5 to 30.8 kg/m² (P < .001); and the Hispanic cohort has the most amount of physical activity per week by far, at 5972 minutes, or 12.6% more than the non-Hispanic Black cohort, the next closest with 5124 minutes (P < .001).

They used Blinder-Oaxaca decomposition, an economic modeling technique typically used to explain wage disparities by gender and race,⁵ to drill down to individual-level factors that may have an adverse impact on healthy sleep scores. This method separated disparities into explained and unexplained components. Four factors emerged as dominant contributors to disparities: education level, age, food security, and BMI.

Among Hispanic adults compared with non-Hispanic White adults, these were the largest contributors to the explained portion of the gap (all P < .001):

• Education level: 0.11 (0.03) points
• Age: −0.08 (0.01) points
• Food security: 0.07 (0.01) points
• BMI: 0.04 (0.01) points

Among non-Hispanic Black adults, the same factors also played major roles, so that if they had the same distribution of these characteristics as non-Hispanic White adults, their healthy sleep scores would change by the following (all P < .001):

• Education level: 0.03 (0.01) points
• Age: –0.06 (0.01) points
• Food security: 0.06 (0.01) points
• BMI: 0.06 (0.01)

In fully adjusted regression models, non-Hispanic Black adults continued to have significantly lower sleep scores than non-Hispanic White adults (β = −0.186; P < .001), suggesting that measurable covariates did not completely account for disparities.

“It is critical to understand that these disparities are not attributable to inherent biological or genetic differences between racial groups. Rather, race is a social construct, and observed health inequities are fundamentally driven by social determinants of health and structural racism,” the authors wrote. “The ‘unexplained component’ is ascribed to disparities in intercepts and regression coefficients arising from unobserved factors, such as potential discrimination disparities.”

Conclusion

These findings suggest that narrowing racial and ethnic gaps in sleep health will require interventions targeting food insecurity, educational opportunity, and obesity to meaningfully improve sleep health, particularly among marginalized communities. At the same time, the persistence of unexplained disparities underscores the need to address broader structural factors—including discrimination, neighborhood conditions, and access to resources—that shape how social determinants translate into health outcomes.

References

1. Yuan X, Cai L, Huang H, et al. Decomposition of racial and ethnic disparities in sleep health among US adults, NHANES from 2005–2008 and 2015–2018. BMC Public Health. Published online February 11, 2026. doi:10.1186/s12889-026-26531-0
2. 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
3. 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
4. Sheehan CM, Frochen SE, Walsemann KM, Ailshire JA. Are U.S. 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
5. Rahimi E, Hashemi Nazari SS. A detailed explanation and graphical representation of the Blinder-Oaxaca decomposition method with its application in health inequalities. Emerg Themes Epidemiol. 2021;18(1):12. doi:10.1186/s12982-021-00100-9