0310 Multidimensional Sleep Health During Pregnancy: Associations with Rurality and Socioeconomic Status

Abstract Introduction Poor sleep health during pregnancy is associated with adverse pregnancy outcomes. Limited evidence suggests that rurality and low socioeconomic status (SES) are associated with poorer sleep health; however, these associations require more research in pregnant populations. This study aims to examine associations of rurality and SES with sleep health across pregnancy. Methods Data are from Pregnancy 24/7 Cohort Study (N=500). Most participants lived in urban areas (77.2%), had private insurance (83.5%), and were college educated (75.7%). Sleep was measured each trimester using device-based and self-reported methods (Actiwatch Spectrum Plus and Pittsburgh Sleep Quality Index [PSQI], respectively). Rurality was defined using Rural-Urban Commuting Area (RUCA) codes categorized as urban (1–3), micropolitan rural (4–6), and small town rural (7–10). SES was derived using latent class analysis of insurance, income, and education, with model fit statistics supporting three classes (low, mid, high). Sleep health outcomes were defined using the RU-SATED framework, including regularity, satisfaction, alertness, timing, efficiency, and duration and dichotomized using established cut-points. A composite RU-SATED score was created using dichotomized sleep health components, creating a scale of 0 to 6 (best). Generalized mixed-effects models assessed associations between SES and rurality with sleep health (RU-SATED and dichotomized components), adjusted for maternal age, pre-pregnancy BMI, and children in the home. Random effects accounted for repeated measures. Results After covariate adjustment, rurality was not significantly associated with individual sleep health components or the composite RU-SATED score, while SES showed multiple associations. For the composite RU-SATED score, a clear gradient emerged, with mid- and high-SES participants scoring 0.59 and 0.90 points higher than those in the lowest SES group (all p< 0.001). SES disparities were also evident across several individual components: mid- and high-SES groups had higher odds of ideal sleep regularity (OR: 2.60-5.66, 95% CI: 1.21-14.74) alertness (OR: 3.47-8.45, 95% CI: 1.28-39.42) timing (OR: 5.86-6.26, 95% CI: 2.09-25.16), and efficiency (OR: 4.39-12.39, 95% CI: 2.64-22.52). SES was not associated with sleep satisfaction or duration. Conclusion SES, not rurality, emerged as a determinant of sleep health, underscoring the need for additional research and strategies to support sleep health among low-SES pregnant individuals. Support (if any) R01HL153095-05S1

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Journal
SLEEP
Published
2026-05-01
DOI
https://doi.org/10.1093/sleep/zsag091.0310
Primary Topic
Sleep and related disorders
Type
article
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0.00
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article

0310 Multidimensional Sleep Health During Pregnancy: Associations with Rurality and Socioeconomic Status

Chooza Moon, Brianne Nichols, Alex Crisp, Bethany Gibbs et al.
SLEEP
Sleep and related disorders
article

0310 Multidimensional Sleep Health During Pregnancy: Associations with Rurality and Socioeconomic Status

Chooza Moon, Brianne Nichols, Alex Crisp, Bethany Gibbs, Christopher Kline, Kara Whitaker, Jacob Gallagher, Katrina Wilhite, Jaemyung Kim
article en

Abstract

Abstract Introduction Poor sleep health during pregnancy is associated with adverse pregnancy outcomes. Limited evidence suggests that rurality and low socioeconomic status (SES) are associated with poorer sleep health; however, these associations require more research in pregnant populations. This study aims to examine associations of rurality and SES with sleep health across pregnancy. Methods Data are from Pregnancy 24/7 Cohort Study (N=500). Most participants lived in urban areas (77.2%), had private insurance (83.5%), and were college educated (75.7%). Sleep was measured each trimester using device-based and self-reported methods (Actiwatch Spectrum Plus and Pittsburgh Sleep Quality Index [PSQI], respectively). Rurality was defined using Rural-Urban Commuting Area (RUCA) codes categorized as urban (1–3), micropolitan rural (4–6), and small town rural (7–10). SES was derived using latent class analysis of insurance, income, and education, with model fit statistics supporting three classes (low, mid, high). Sleep health outcomes were defined using the RU-SATED framework, including regularity, satisfaction, alertness, timing, efficiency, and duration and dichotomized using established cut-points. A composite RU-SATED score was created using dichotomized sleep health components, creating a scale of 0 to 6 (best). Generalized mixed-effects models assessed associations between SES and rurality with sleep health (RU-SATED and dichotomized components), adjusted for maternal age, pre-pregnancy BMI, and children in the home. Random effects accounted for repeated measures. Results After covariate adjustment, rurality was not significantly associated with individual sleep health components or the composite RU-SATED score, while SES showed multiple associations. For the composite RU-SATED score, a clear gradient emerged, with mid- and high-SES participants scoring 0.59 and 0.90 points higher than those in the lowest SES group (all p< 0.001). SES disparities were also evident across several individual components: mid- and high-SES groups had higher odds of ideal sleep regularity (OR: 2.60-5.66, 95% CI: 1.21-14.74) alertness (OR: 3.47-8.45, 95% CI: 1.28-39.42) timing (OR: 5.86-6.26, 95% CI: 2.09-25.16), and efficiency (OR: 4.39-12.39, 95% CI: 2.64-22.52). SES was not associated with sleep satisfaction or duration. Conclusion SES, not rurality, emerged as a determinant of sleep health, underscoring the need for additional research and strategies to support sleep health among low-SES pregnant individuals. Support (if any) R01HL153095-05S1

SLEEPVol. 49(Supplement_1)
West Virginia University (US), University of Iowa (US), University of Pittsburgh (US), Iowa State University (US)
No poverty
Openalex Percentile: Top 4%
Sleep and related disorders
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