bluuebunny/crossref_metadata_2025 huggingface dataset:
0235 Technology Use Impacted Sleep Patterns in Older Adults During and After the COVID-19 Pandemic
Authors: Weiss Carleara , Lach Helen , Lorenz Rebecca
Published: April 2024

Introduction

Sleep, health status, and quality of life were highly impacted by the COVID-19 pandemic. Coping mechanisms such as using digital media and smartphones used to reduce social isolation, may have negatively impacted sleep. The purpose of this analysis was to examine the relationships between digital media use and sleep among older adults using data from the Experiences of Older Adults During COVID-19.

Methods

Community-dwelling older adults participated in an anonymous survey in 2020 during the initial months (N=509) of the COVID-19 pandemic, with a one-year follow-up in 2021 (N=118). A secondary cross-sectional analysis was conducted to examine the relationship between sleep and smartphone use. We used descriptive analysis, independent t-tests, and Pearson coefficients to measure linear correlation amongst age, gender, technology use, sleep variables, sleep duration, timing, onset latency, wake after sleep onset, and feeling refreshed upon awakening.

Results

Participants in both waves were predominantly female (75.2%; mean age 76.4 years), 49.5% married, and 40.7% living alone. Sleep satisfaction (<.001) and timing (<.001) significantly improved after COVID-19. Smartphone use was significantly lower post-COVID-19 (0.02). Smartphone use was negatively correlated with sleep duration, feeling refreshed upon awakening, and sleep satisfaction. Female sleep satisfaction correlated with sleep duration 6-8h/night (<.001) and timing (being asleep or trying to sleep between 2-4 am;<.001).

Conclusion

Sleep satisfaction and timing improved at the 2021 follow-up. Digital media and smartphones were used as tools for connection during social isolation; however, they impaired sleep duration, satisfaction, and feeling refreshed the next day. Female participants were more satisfied with longer sleep duration. Further studies with racially and gender diverse sample may provide insights on technology use and sleep in older adults post-COVID-19 pandemic.

Support (if any)

1K99AG079117-01 (Weiss); Saint Louis University COVID-19 Rapid Response Fund (Lach; OpenWater 1804)
0243 Untangling the Complexities of Sleep and Diet After Job Loss in Under-Represented Minority Groups
Authors: Haynes Patricia , White Lauryn
Published: April 2024

Introduction

Obesity is a public health crisis disproportionately affecting underrepresented racial and ethnic minority (URM) groups; it is also linked to risk factors, like poor diet and poor sleep quality. Little is known about how URM groups sleep and eat after involuntary job loss, a stressful life event that could impact food choices through financial strain. To this aim, we examined whether individuals identifying as an URM with worse sleep (multidimensional composite, sleep fragmentation) would demonstrate worse dietary patterns over the next 18 months, as compared to individuals identifying as non-Hispanic and white (NHW).

Methods

Data were derived from ADAPT, an 18-month cohort study with 188 participants who experienced recent involuntary job loss. Participants completed a multi-model sleep assessment (Actiwatch-Spectrum, daily sleep diaries, interview) for the calculation of a multidimensional composite score; sleep fragmentation was operationalized as the number of wake bouts during the in-bed period. Participants completed 24-hour dietary recall interviews to compute the Healthy Eating Index (HEI)-2015 index. Mixed effects linear modeling tested interactions between URM identity (33% Hispanic or 30% Not White Race) and sleep indices over time.

Results

The HEI did not change significantly over time with multidimensional sleep health, when controlling for body mass index, biological sex, education, and reemployment. More wake bouts were associated with higher HEI scores (healthier diet) in URM individuals and lower HEI scores (less healthy diet) in NHW individuals (Estimate = -0.36, SE = .14, p < .05). This interaction was driven by lower consumption of refined grains and saturated fats and an increased consumption of greens and beans over time in URMs and less consumption of whole grains in NHW.

Conclusion

In a population of individuals who recently experienced involuntary job loss, sleep fragmentation was associated with dietary quality but multidimensional sleep health was not. The association between sleep fragmentation was in an opposite direction than hypothesized in URM individuals. Future research may benefit from testing the daily relationships between sleep fragmentation, the cost of foods, and resiliency factors (e.g., cultural differences in dietary choices) when under financial strain.

Support (if any)

US National Institute of Health, National Heart, Lung, and Blood Institute (NHLBI,1R01HL117995)
0248 The Role of Neighborhood Deprivation in Sleep Health
Authors: Barber Lauren , McCullough Lauren E , Faw Kierstin , Zhong Charlie , Peoples Anita , Bodelon Clara , Teras Lauren R , Patel Alpa , Johnson Dayna
Published: April 2024

Introduction

Previous studies, mostly with small sample sizes, demonstrate inconsistent associations between the socioeconomic neighborhood environment and sleep among adults. Using data from a large cohort, we examined the association between neighborhood deprivation and sleep health.

Methods

The Cancer Prevention Study-3 is a large prospective cohort of American men and women enrolled at baseline between 2006 and 2013. The Neighborhood Deprivation Index (NDI) was derived for US census tracts using principal components analysis of 2008-2012 American Community Survey data on poverty, income, occupation, housing, employment, and education. Participant addresses at baseline were geocoded to the tract level and linked to the NDI. Participants (N=180,592) self-reported, in categories, their sleep duration in a 24-hour period on weekdays and weekends on the 2015 follow-up questionnaire and sleep quality in 2018. Weekly habitual sleep duration was calculated from a weighted average of weekday and weekend durations. Multivariable logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for the association between NDI in quintiles and each sleep outcome, overall and by race and ethnicity.

Results

Participants had an average age of 48.6 (standard deviation=9.6) years and were predominantly women (79.2%). Most participants identified as White (93.5%), while smaller proportions identified with racial and ethnic minoritized populations (e.g., Black: 2.6%, Hispanic: 5.6%). Compared to the least deprived neighborhoods, living in the most deprived neighborhoods was associated with a 25% (OR=1.25, 95% CI 1.18-1.33) higher odds of short (< 7 hours) versus recommended (7-8 hours) sleep duration. Neighborhood deprivation was also associated with an increased odds of long sleep duration (≥9 hours; OR=1.13, 95% CI 1.06-1.21) and poor sleep quality (OR=1.06, 95% CI 1.01-1.10). Race and ethnicity modified the relationship between neighborhood deprivation and long sleep duration, such that the association was only observed among White participants.

Conclusion

Results from this large well-powered study indicate neighborhood deprivation may adversely impact sleep health by increasing the odds of shorter and longer than recommended sleep duration and poor sleep quality. More research in large diverse samples is needed to confirm these findings.

Support (if any)

Support: Support was provided by the National Institutes of Health (R01CA259192).
0250 Impact of Air Quality on Nocturnal Awakenings Among Blacks
Authors: Elvariste Stessie , Blanc Judite , Gallop Erin-Leigh , Oliveira Bruno , Seixas Azizi , Jean-Louis Girardin
Published: April 2024

Introduction

The Air Quality Index (AQIUS) is a measure of how clean or polluted the ambient air of a given area may be, scored 0-500 (0-50 excellent; 300< hazardous) based on components measurable in the air. Air Quality-related risk factors that affect health outcomes include preexisting diseases and low-socioeconomic status, factors that are disproportionately present in Black communities. Sleep plays a vital role in health outcomes and awakenings after sleep onset has been associated with an increased risk of cardiovascular related diseases. Previous research has also suggested that mechanisms explaining long-term health outcomes include air quality exposure during sleep. To understand those mechanisms, this study explores the association between average awakenings at night and AQIUS score among Blacks.

Methods

Data were pulled from 2 NIH-funded studies (ESSENTIAL and MOSAIC). Analyses of correlation matrices were conducted, descriptive statistics were analyzed, and linear regression analysis of AQIUS and average awakenings in minutes was performed using SPSS 29. For a period of seven days, 108 Black participants ≥ 18 years, monitored their bedroom's air quality using the IQAir device, which provided the AQIUS score during their sleep. Participants wore Fitbits for a week to track their sleep and physical activity. The effect of AQIUS on sleep parameters: average awakenings at night, sleep efficiency, quality, and duration was explored.

Results

Of 108 participants, 75 were Female (69.4%) and 33 were male (n=30.6%), Mage 48.31 ±16.725 years. On average, study participants experience 15.57±7.316 awakenings per sleep period. Number of awakenings was moderately negatively correlated (r(106)=.465,p<.001) with AQIUS, showing that as air quality decreases, the number of night awakenings increases. Regression analyses revealed AQIUS as a strong predictor of average awakenings in minutes at night in Blacks [β=-.248; p< .006].)

Conclusion

Air Quality Index is a robust predictor of average nocturnal awakenings among Blacks. Further research should investigate the importance of air quality to prevent cardiovascular diseases and to promote better overall health and sleep.

Support (if any)

NIH R01AG067523, R01HL142066
0262 Awakening to Inequality: Exploring the Social Determinants of Sleep Health in Low-Income, Black Americans
Authors: Troxel Wendy , Haas Ann , Ghosh-Dastidar Bonnie , Rosso Andrea , Hale Lauren , Buysse Daniel , Dubowitz Tamara
Published: April 2024

Introduction

Sleep health is defined as a multidimensional pattern of sleep and wakefulness that is adapted to individual, societal, and environmental demands, and that fosters mental and physical well-being. Prior research demonstrates that social determinants, operating at the household, interpersonal, and community levels, associate with individual dimensions of sleep health (e.g., sleep duration), and may underlie racial disparities in such dimensions. However, scant research has investigated social determinants of multidimensional sleep health. The current study investigates cross-sectional associations between multi-level social determinants, including household food insecurity, interpersonal discrimination, and neighborhood social cohesion, safety and satisfaction, and multidimensional sleep health among a low-income, Black American community-based sample.

Methods

Participants included 530 Black American participants (82% female; mean age= 60.3) from two urban neighborhoods. Based on the Ru SATED construct, we constructed a composite Sleep Health (SH) score from the sum of scores representing “healthy” and “unhealthy” ranges of 6 sleep dimensions [i.e., regularity, satisfaction, alertness/ sleepiness, timing, efficiency and duration (Range = 0-6)]. Sleep dimensions were derived from actigraphy or self-reports. Food insecurity (range=0-3), interpersonal discrimination (range=0-21), and neighborhood cohesion, safety, and satisfaction (each with range=1-5) were measured via validated self-report surveys. Linear regression analyses examined the association between each social determinant and sleep health, after adjustment for age, sex, neighborhood, education, and body mass index.

Results

Greater food insecurity and greater interpersonal discrimination were associated with poorer sleep health scores (B=-.15; SE=.05 and B=-.03; SE=.01, respectively). In contrast, greater neighborhood safety and satisfaction were associated with better sleep health scores (B= .22; SE=.06 and B=.11; SE=.05, respectively). There was not a significant association between social cohesion and sleep health.

Conclusion

These findings demonstrate that determinants of sleep health go beyond the individual level, encompassing socio-environmental influences that may act as risk or protective factors. Our results suggest that both individual and policy-level interventions may be needed to mitigate pervasive and enduring sleep health disparities.

Support (if any)

AG R01AG072652
0264 Sleep Duration Among Samoan Children: A Descriptive Study of Behavioral and Sociodemographic Correlates
Authors: von Ash Tayla , Choy Courtney , Dunsiger Shira , Soti-Ulberg Christina , Wang Dongging , Reupena Muagututia , Duckham Rachel , Naseri Take , Hawley Nicola
Published: April 2024

Introduction

Sleep is important for child health and development and has been associated with obesity risk. Pacific Island nations have amongst the highest obesity prevalence globally, but little is known about child sleep in these settings. The study aimed to: 1) describe nighttime sleep duration and the proportion of children who met sleep recommendations between 2 and 9 years old, and 2) identify behavioral and sociodemographic correlates of sleep duration in Samoa.

Methods

This secondary analysis used three waves of data collected from the Ola Tuputupua’e (‘Growing Up’) cohort in Samoa between 2015 and 2020. Primary caregivers reported how many hours their child slept at night. Means and standard deviations were calculated for child sleep duration, while frequencies and proportions were calculated for meeting the World Health Organization age-based sleep recommendation (>11 hours for toddlers, >10 hours for preschool-age children, and >9 hours for school-age children. We ran multivariable regression models, stratified by age group to assess associations between child characteristics, sociodemographic characteristics, and zBMI, diet-, and activity-related factors with sleep duration across the waves. Mixed effects models were used to account for the fact that data was repeated within participants and allow for both time varying and time-invariant factors.

Results

Average nighttime sleep duration was 9.7 (1.1) for toddlers, 9.5 (1.0) for preschoolers, and 9.4 (1.3) for school-age children. Based on nighttime sleep duration, approximately 86% of toddlers did not meet their age-specific sleep recommendation, compared to 51% of preschoolers and 23% of school-age children. Living in a lower income household was associated with more sleep (β: 0.57 [95% CI: 0.29, 0.86]) compared to living in a higher income household, while having a primary caregiver who did not complete high school (β: -0.62 [95% CI: -0.88, -0.36]) was associated with less sleep. Increased total carbohydrate intake (β: -0.19 [95% CI: -0.33, 0.00]) and greater adherence to a neotraditional dietary pattern (β: -0.14 [95% CI: -0.24, -0.05]) were associated with shorter sleep.

Conclusion

Interventions focusing on early childhood sleep may be needed in Samoa. However, further investigations accounting for daytime sleep are needed and research to inform intervention components.

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0265 Disparities in Bed and Wake Times in the US Population Associated with Typical Work Hours
Authors: Garber Sofia , Kennedy Kathryn E R , Hartstein Lauren , Valencia Dora Y , Killgore William , Grandner Michael A
Published: April 2024

Introduction

Racial and ethnic minority populations are at an increased risk of having shorter sleep duration and poorer sleep quality. This nationally-representative study examines whether groups differ on their typical sleep opportunity window, and whether this depends on typical work hours.

Methods

Data were obtained from adults who participated in the National Health And Nutrition Examination Survey (NHANES), overseen by the CDC, for the 2017-2018 and 2019-2020 (March, pre-pandemic) waves. These data were combined and weighted using NHANES sample weights. Habitual sleep timing was assessed as self-reported typical bedtime and wake time, which was converted to minutes from midnight. Race/ethnicity was self-reported as non-Hispanic White, Black/African-American, Mexican-American, Other Latinx, Asian, or Multiracial/Other. Work time was categorized as None, 20 or fewer hours, 21-39 hours, 40 hours (reference), 41-59 hours, or 60 or more hours. Covariates included demographics (age, sex) and socioeconomics (education, income-poverty ratio).

Results

Overall, compared to Non-Hispanic Whites, Blacks/African-Americans went to bed 14 minutes later, Mexican Americans went to bed 18 minutes earlier and got out of bed 33 minutes earlier, and Asians went to bed 13 minutes later and woke up 16 minutes later. And compared to those who worked 40 hours, those who worked less than 40 hours went to bed later and woke up later, and those who worked 60+ hours went to bed later. There was a significant race/ethnicity by work hours interaction. The relationship between race/ethnicity and sleep timing differed depending on which work hours category respondents were in. Overall, Black-White differences in bedtime were seen in those who worked 41-59 hours. Mexican-White differences in bedtime were seen for non-working and 40 hours and for waketime were seen for all <=40 hours groups. Asian-White differences were seen for bedtime for 41-59 hours and for waketime in non-working, 40 hours, and 60+ hours. Multiracial-White differences were seen for bedtime in non-working 21-39 hours, and for waketime in 21-39 hours.

Conclusion

Even after accounting for other elements of sleep, Blacks/African-Americans, and Asians still exhibit delayed sleep. Future research is required to further explore disparities in circadian rhythm and culturally targeted interventions for sleep health.

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0268 Sleep Duration Associated with Cognitive Decline: Influence of Age and Race/Ethnicity
Authors: Ghani Sadia , Tubbs Andrew , Seixas Azizi , Killgore William , Grandner Michael
Published: April 2024

Introduction

Insufficient and excessive sleep are associated with cognitive dysfunction in older adults. Limited studies are available for adults < 50 years of age and the influence of race/ethnicity in a nationally representative population. We investigated the association between sleep duration and cognitive decline and the influence of age and race/ethnicity, in U.S adults >40 years of age.

Methods

Data from the 2022 Behavioral Risk Factor Surveillance System (BRFSS) was used. Twelve states collected data on cognitive decline, assessed with: “During the past 12 months, have you experienced confusion or memory loss that is happening more often or is getting worse?” among individuals aged 40 or older (N=63,948). Population-weighted logistic regression analyses examined this in relation to self-reported habitual sleep duration in models that also included age (by decade), sex, race/ethnicity, education, and depression history.

Results

In adjusted analyses, increased likelihood of perceived cognitive decline was seen for ≤4h (OR=2.50), 5h (OR=2.06), 6h (OR=1.51), 9h (OR=1.34), and 10+hr (OR=2.15), compared to 7h. A 3-way interaction was found (p=0.0001), as well as a 2-way interaction for sleep-by-age (p< 0.0001) but not sleep-by-race (p=0.16). There was an age gradient, such that for participants in their 40s, short sleep duration was more strongly associated with cognitive decline, and as age increased, these relationships generally weakened. However, a sleep-by-race interaction was seen for older adults only, where the relationship between cognitive decline and both short and long sleep duration was stronger among Blacks/African-Americans compared to Non-Hispanic Whites. Further, secondary analyses among those who reported cognitive decline showed that those with ≤4h sleep duration were more likely to talk about it with a doctor (OR=1.67), and greater ordinal likelihood of cognitive decline interfering with social functioning was associated with both short and long sleep duration.

Conclusion

Sleep duration is related to cognitive decline and its social effects, though this depends on age and race/ethnicity, especially among older adults. Interventions should focus on effects of insufficient sleep in younger populations in general, and older Black/African-American groups.

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0271 Heterogeneities in Sleep Outcomes Among U.S. Immigrants from Different Racial and Ethnic Backgrounds
Authors: Liu Xiaoyue , Li Junxin , Cho Yeilim , Wu Bei
Published: April 2024

Introduction

Sleep plays an essential role in overall health and well-being. Although U.S. immigrants are considerably growing, few studies have examined sleep in this diverse population, particularly those from Asian backgrounds. It is also unclear how sleep differs by the length of residence (LOR) across immigrant groups. Using a nationally representative sample of U.S. immigrants, this study sought to address three questions: 1) Do sleep outcomes differ across racial/ethnic groups? 2) Is there an association between LOR and sleep outcomes? and 3) Does LOR moderate the association between race/ethnicity and sleep outcomes?

Methods

Data were pooled from the 2013-2018 National Health Interview Survey. The sample (N = 27,761; 14% ≥ 65 years old) included foreign-born adults from six racial/ethnic groups: non-Hispanic (NH) White, NH Black, NH Asian (Chinese, Filipino, Asian Indian), and Hispanic/Latino. LOR was categorized as < 5, 5-9, 10-14, and ≥15 years. Sleep outcomes included self-reported sleep duration (short < 7, normal 7-8, and long ≥ 9 hours) and sleep quality (trouble falling asleep, trouble staying asleep, and waking up feeling unrested).

Results

Over one-third of the sample reported either short or long sleep duration. The prevalence of poor sleep quality ranged from 15.6 to 40.2% among racial/ethnic groups. Compared to NH Whites, Filipinos (odds ratio [OR]=1.91, 95% confidence interval [CI]: 1.60-2.28), NH Blacks (OR=1.84, 95%CI: 1.58-2.15), and Hispanics/Latinos (OR=1.15, 95%CI: 1.03-1.29) were more likely to report short sleep, while Asian Indians were less likely to experience poor sleep quality (p < 0.05). Immigrants with LOR ≥ 15 years exhibited significantly worse sleep outcomes in comparison to those with LOR < 5 years, and LOR ≥ 15 years moderated White-Asian differences in sleep quality. Additionally, different immigrant groups showed variations in sleep patterns as they resided longer in the U.S.

Conclusion

Immigrants from different racial/ethnic backgrounds exhibited substantial heterogeneities in sleep outcomes. Future research should investigate the factors contributing to the variations in sleep patterns, both between racial/ethnic groups and within the same group of immigrants. More importantly, routine sleep assessments should be conducted for this population to promptly identify sleep problems and initiate tailored interventions.

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0272 Associations Between Sleep Architecture, Appetite and Food Reward over 6 Months in Black Emerging Adults
Authors: McNeil Jessica , Koch Hannah , Sims Jesse , Finlayson Graham , Pickett Stephanie , Wideman Laurie
Published: April 2024

Introduction

Short sleep duration is associated with increased feelings of appetite and food reward, though few studies have assessed associations between sleep architecture with appetite and food reward measures. Additionally, no data exists on these measures in Black emerging adults (ages 18-28 years old), despite higher risks of poor sleep and obesity in this population. This analysis aims to examine relationships between sleep architecture with appetite and food reward over 6 months in Black emerging adults.

Methods

In a repeated measures design, 15 Black emerging adults (12 females; age, 21±2.4 years; height, 168±11.1 cm; weight, 72.4±12.6 kg; body fat, 25.8±11.9%) completed a baseline (BLN) and 6-month follow-up (6MO) visit. In-home sleep over 2 nights was measured with polysomnography. Outcome measures included fasting and post-standard breakfast appetite sensations over 180 minutes (desire to eat, hunger, fullness, and prospective food consumption; visual analogue scales) and food reward (implicit wanting, explicit liking and explicit wanting; Leeds Food Preference Questionnaire). Linear mixed models using a restricted maximum likelihood estimation with a Kenward-Roger correction for small samples were used to assess associations between sleep stage duration (minutes of stage 2, slow-wave sleep (SWS) and rapid eye movement (REM) sleep) with fasting appetite sensations, post-meal appetite area under the curve (AUC) and food reward measures. Covariates included time (BLN vs. 6MO) and body weight. Participant ID was used as a grouping variable.

Results

No significant associations were noted between sleep stage duration with fasting appetite sensations and post-breakfast appetite AUC. Lower stage 2 sleep duration was associated with greater explicit wanting (β= -0.13, 95%CI [-0.23, -0.04], p=0.01) and explicit liking (β= -0.19, 95%CI [-0.28, -0.11], p< 0.0001) for sweet relative to savory foods.

Conclusion

These findings suggest that habitual, in-home measures of sleep stage duration are not associated with appetite sensations in Black emerging adults. However, greater explicit wanting and liking for sweet relative to savory foods in response to lower stage 2 sleep duration may be a mechanism by which short sleep duration leads to an increased risk of positive energy balance and obesity over time.

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0274 Associations Between Sleep Architecture and Energy Balance in Black Emerging Adults
Authors: Koch Hannah , Sims Jesse , Pickett Stephanie , Wideman Laurie , McNeil Jessica
Published: April 2024

Introduction

Body weight is determined by sustained changes in energy balance (EB), reflecting the difference between energy intake (EI) and energy expenditure (EE). Insufficient sleep negatively impacts EB to favor weight gain. Black emerging adults have a higher risk for insufficient sleep and obesity, but little data exists on these measures in this population. This analysis aims to examine relationships between sleep architecture with parameters of energy balance (EI and EE) in Black emerging adults.

Methods

In a repeated measures design, 15 Black emerging adults (12 females; age, 21±2.5 years; height, 168±11.1 cm; body mass, 72.4±12.6 kg; body fat, 25.8±11.9%) completed an initial (BLN) and 6-month follow-up (6MO) visit. In-home sleep over 2 nights was captured with polysomnography. Physical activity EE (PAEE) and moderate-to-vigorous physical activity (MVPA) were measured over seven days via actigraphy and calculated using the Freedson VM3 Combination and Freedson (1998) algorithms, respectively. Resting metabolic rate (RMR) and thermic effect of food were measured via indirect calorimetry. Ad libitum EI was measured using 3 days of provided meals. Spearman’s Rank correlations assessed relationships between changes in sleep measures (minutes and percentage of stage 2, slow wave sleep (SWS), and REM) with changes in parameters of EB. Linear mixed models assessed relationships between sleep variables and EB variables, with participant ID as a grouping variable and body weight as a covariate.

Results

There were no significant associations between changes in sleep architecture with changes in EB variables. SWS duration was positively related to EI (Beta = 9.11, 95%CI [0.486, 17.734], p = 0.049). RMR was inversely related to stage 2 percentage (Beta = -63.3, 95%CI [-101.48, -25.12], p < 0.01), SWS percentage (Beta = -52.63, SE: 18.85, p = 0.01), and REM percentage (Beta = -55.36, 95%CI [-92.84, -17.88], p = 0.01).

Conclusion

These results suggest that greater SWS duration was related to higher EI, and that relative time spent in stage 2 sleep, SWS, and REM sleep were inversely related to RMR. Therefore, habitual measures of sleep architecture may impact obesity risk via modifications in EB parameters in Black emerging adults.

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0275 Associations Between Sleep Architecture, Cortisol, and Body Composition over 6 Months in Black Emerging Adults
Authors: Koch Hannah , Sims Jesse , Pickett Stephanie , Wideman Laurie , McNeil Jessica
Published: April 2024

Introduction

Cortisol awakening response (CAR), diurnal slope (DS), and total daily output (TDO) are metrics of the hormone, cortisol. Emerging adults (ages 18-28 years old) experience poor sleep, which is linked to a blunted CAR, flatter DS, and obesity risk. Little data exists on these measures in Black emerging adults, despite higher risks of poor sleep and obesity. This analysis aims to examine relationships between sleep architecture, cortisol metrics, and body mass and composition changes over 6 months in Black emerging adults.

Methods

In a repeated measures design, 14 Black emerging adults (12 females; age, 21±2.5 years; height, 166±9.3 cm; body mass, 73.0±12.9 kg; body fat, 27.4±10.8%) completed an initial (BLN) and 6-month follow-up (6MO) visit. In-home sleep over 2 nights was captured with polysomnography. Salivary cortisol was collected at wake, 30-, 45-min post-wake, 12pm, and 7pm on 2 days. CAR area under the curve (AUC) was calculated with the wake, 30-, and 45-min post-wake samples with respect to wake (AUCi) and to ground (AUCg). DS was calculated as the slope using wake, 12pm, and 7pm samples. TDO AUC was calculated using all samples with respect to ground. Body mass and composition were assessed with BodPod. Paired t-tests evaluated differences in all variables between BLN and 6MO. Pearson correlations assessed relationships between sleep stage duration, cortisol metrics, and body mass and composition at each timepoint, and 6-month changes in these variables.

Results

There was an increase in body mass (MD: 2.7 kg, 95%CI [1.0, 4.4], p< 0.01), but not fat mass (p>0.05). REM sleep duration was positively associated with TDO at BLN (r = 0.57, p=0.03) but not at 6MO. REM sleep duration at BLN was also positively associated with 6-month changes in body mass (r=0.55; p=0.03). Greater increases in slow-wave sleep (SWS) duration were associated with a more positive DS (r = 0.73; p< 0.01).

Conclusion

These results suggest that greater amounts of REM sleep are associated with greater cortisol output and body weight changes, whereas greater amounts of SWS are associated with better DS profiles.

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0276 Sex Influences the Relationship Between Sleep-Related Impairment Score and Blood Chloride Among Blacks
Authors: Scott Sadeaqua , Blanc Judite , Gallop Erin-Leigh , Oliveira Bruno , Thompson Michelle , Locklear Clarence , Moise Rhoda , Nicholson Nadine , Seixas Azizi , Jean-Louis Girardin
Published: April 2024

Introduction

Sleep inefficiency is associated with increased risk of cardiovascular disease (CVD) and kidney disease. CVD and kidney disease have a bidirectional relationship, with one enhancing the disease progression of the other, and sharing biomarkers of inflammation and infection such as blood urea nitrogen (BUN) and chloride, respectively. Although Blacks have disproportionately higher rates of sleep inefficiency associated with cardiovascular, kidney, and inflammatory disease, data is limited concerning whether sleep-related impairment (SRI) is associated with these disease biomarkers, and sex in Blacks. This study investigated the association between SRI, sex and biomarkers of cardiometabolic, kidney and inflammatory disease including chloride and BUN within Blacks.

Methods

Data were extracted from 104 Blacks, aged 36 to 73 years, who were enrolled in two NIH-funded community-based sleep studies, ESSENTIAL and MOSAIC, from January 2020 until October 2023. Of the participants, 34.6% (n=36) were male and 65.4% (n=68) were female. The PROMIS Sleep-Related Impairment (SRI) 8a short form questionnaire was completed by all participants to determine subjective sleep efficiency. An independent t-test and multilinear regression analysis were conducted to explore associations between sleep-related impairment scores, chloride, BUN, and sex. Interaction effects between SRI score and potential moderators (sex, chloride and BUN) were conducted to examine which variables displayed a significant effect on SRI score.

Results

Black women reported higher sleep inefficiency compared to men (t(77.67) =-2.3, p ≤ 0.023). Controlling for age and sex, linear regression analysis showed that significant variables associated with (SRI) among participants were blood chloride (p ≤ 0.016) and sex (p ≤ 0.012). A moderation analysis showed a significant relationship between blood urea nitrogen, blood chloride and sex (p = 0.003), and that sex influences the relationship between SRI score and blood chloride. Regression analysis showed that all variables are significant predictors of SRI score.

Conclusion

The association of SRI to chloride, and its moderation by sex, with women scoring higher than males, suggests further investigations should be performed to analyze how these associations play a role in accounting for greater sleep inefficiency and CVD in Black women as compared to Black men.

Support (if any)

NIH (R01AG067523, R01HL142066, T32HL166609)
0277 Robust Identification of Sleep States and Their Transitions Using Whole-Night fMRI Data
Authors: Yang Nils , Picchioni Dante , de Zwart Jacco , Wang Yicun , van Gelderen Peter , Duyn Jeff
Published: April 2024

Introduction

Polysomnography (PSG)-based sleep staging has a relatively poor (30s) temporal resolution, and as a result does not capture any sleep structure that may exist on finer time-scales. For example, brain activity patterns involved with transitions or changes within and between classical sleep stages are not captured. Here we used whole-night functional magnetic resonance imaging (fMRI) to address this shortcoming.

Methods

Data acquisition was conducted as part of a well-controlled sleep experiment with two consecutive nights of concurrent fMRI-EEG recording from 23:00 to 7:00. Twelve participants (18-35 years old, 8 females) had at least one complete sleep cycle during both Night 1 and 2. We analyzed the fMRI data using an unsupervised learning approach - Hidden Markov Model (HMM) to reveal recurrent structure (“states”). The HMM, applied to Night 2 data, encompassed 21 whole-brain states based on various model evaluation indexes. Each state was characterized as a multivariate Gaussian distribution including a mean fMRI activation distribution,a functional connectivity (FC) matrix, and a transition probability matrix.

Results

Modular analysis of the extracted transition probability matrix (between each pair of states) revealed five modules, each containing a set of states that had similar preferences to occur during a specific sleep stage or part thereof. Remarkably, the trained HMM predicted brain sleep states during Night 1 that had highly similar sleep stage preference (r = 0.94, p < 0.001). In Wake-related HMM states, the FCs between DMN and Salience Network (SAL) / Control Network (CON) were negative, while during N3-related HMM states, these FCs were positive. Similar patterns were found for mean fMRI activation.

Conclusion

These observations suggest that HMM may provide valuable information about sleep-state-specific brain activity patterns that extend well beyond the information provided by classical sleep staging. For example, cursory inspection of the HMM results suggests a subdivision of N2 in two groups of multiple states with different transition probabilities to Wake; analysis of brain activation and FC patterns of HMM states indicated that the connections between DMN and SAL/CON may play a critical role in the transition from wake to light sleep and, to deep sleep.

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0280 Effect of Daily Transcutaneous Vagal Nerve Stimulation on Objective and Subjective Sleep Features in Healthy Adults
Authors: Subramoniam Anjana , Silva-Jones Jillian , Crosswell Alexandra , Whitehurst Lauren
Published: April 2024

Introduction

One key pathway through which the autonomic nervous system modulates sleep is via the vagus nerve. No study to date has examined the impact of daily vagal modulation on nightly sleep activity. Here, in a two-week, within-subject sham-controlled and counterbalanced study, we investigated the impact of daily, non-invasive vagal nerve stimulation on subjective and objective sleep features.

Methods

The Institutional Review Board of the University of Kentucky approved experimental procedures. Twenty healthy adults, aged between 18-65, were given ambulatory vagal nerve stimulators to wear at home for one week of active and one week of sham stimulation. Stimulation conditions were counterbalanced across participants. The device was worn for 15 minutes between 9 PM-11 PM each day before bedtime. Before and after sleep, participants completed the Karolinska Sleepiness Scale (KSS) to measure subjective sleepiness and completed daily diaries to gather subjective sleep outcomes. Participants also wore wrist actigraphs to objectively characterize behavioral sleep/wake patterns. Linear mixed effect models assessed the effect of tVNS on subjective and objective measures of sleep.

Results

tVNS had a significant impact on actigraphy indices of sleep behavior. Compared to sham stimulation nights, there was a significant reduction in wake after sleep onset (b=-17.12, p=.004), a significant improvement in amount of time spent asleep during the night (b=2.87, p=.01) and higher sleep efficiencies (b = 2.05, p=.01) on stimulation nights. No significant differences were found in KSS ratings before and after sleep or in subjective sleep assessments measured with daily diaries.

Conclusion

The results suggest that the use of daily tVNS may improve behavioral indices of sleep, highlighting the important role that autonomic activity may play in regulating nighttime sleep/wake function. Future studies should examine tVNS impacts on polysomnographically-measured sleep

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0282 Associations Between EEG Sleep Characteristics and Alcohol Use Behaviors in Young Adults
Authors: Harris Nicholas , Oryshkewych Nina , Buysse Daniel , Pedersen Sarah , Wallace Meredith , Hasler Brant
Published: April 2024

Introduction

Alcohol use disorder (AUD) is characterized by sleep disturbances, but differentiating the effects of acute alcohol exposure, withdrawal, and chronic consumption remains an unsolved problem. This study takes a unique approach to examine proximate alcohol consumption effects on sleep electroencephalography (EEG) in young adults who engage in heavy episodic drinking. We aim to relate sleep physiology to progression from binge drinking towards AUD.

Methods

Young adults aged 21-30 years (N=88) who report weekly binge drinking (4+/5+ drinks per occasion for female/male assigned at birth) completed two nine-day ecological momentary assessment (EMA) protocols, each followed by overnight in-lab polysomnography (PSG) after negative alcohol breath test. Drinking events were recorded by EMA. EEG sleep analyses (AASM criteria) assessed sleep-wake staging and power spectral analysis. Linear mixed effect modeling examined the effects of drink number during the EMA period on measures of sleep continuity, architecture, and spectral power, adjusting for sociodemographic and behavioral covariates.

Results

Participants reported an average of 17.5+/-1.0 drinks over 3.0+/-0.1 days in each 9-day EMA period. Unexpectedly, higher drink counts were associated with lower time spent awake after sleep onset (WASO, log-transformed, BETA-STD=-0.17, p=0.028) without significant changes in sleep efficiency (p=0.06) or sleep onset latency (SOL, p=0.656). More drinks also correlated with higher number of REM periods (log-transformed, BETA-STD=0.17, p=0.022) and less REM fragmentation (log-transformed, BETA-STD=-0.21, p=0.005) without correlating with REM latency (p=0.058). Finally, consumption of more drinks was associated with decreased alpha power (8-12 Hz, log-transformed, BETA-STD=-0.1, p=0.03) but not associated with other aspects of sleep architecture or spectral power (p>0.05).

Conclusion

Contrary to our expectation of worse sleep in those with higher drinking frequency, we found that greater drink consumption was actually associated with better sleep based on parameters assessing continuity (WASO), REM sleep (number of periods, fragmentation), and spectral power (alpha power). Possible explanations include effects from binge drinking pattern, sleep improvement after alcohol detoxification, age-related resilience, or differential effects across the night. Future analyses will investigate sex differences, day-to-day drinking and sleeping relationships during EMA study period, subjective sleep quality, sleep changes across the night, and other putative covariates.

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NAH T32HL082610, BPH/SLP R01AA026249
0283 Urinary Thallium Concentration and Objective Sleep: An Examination in Multi-Ethnic Study of Atherosclerosis (MESA)
Authors: Paquet Caitlin , Bertisch Suzanne , Glabonjat Ronald , Sanchez Tiffany , Domingo-Relloso Arce , Navas-Acien Ana , Schilling Kathrin , Purcell Shaun M · , Redline Susan
Published: April 2024

Introduction

Thallium (Tl), a toxic metal abundant in the Earth’s crust, is a neurotoxicant that crosses the blood brain barrier and disrupts potassium-dependent neural communication. Tl’s neurotoxic effects have been linked to sleep disturbance. Prior research on the relationship between Tl and sleep relied on self-reported sleep measures or were isolated to specific populations (e.g., occupational, regional). We examined the relationship between Tl and sleep by analyzing the long-term impacts of Tl exposure on actigraphy- and polysomnography (PSG)-derived sleep outcomes in a large multiethnic cohort across the United States.

Methods

We used data from Multi-Ethnic Study of Atherosclerosis (MESA). Spot urinary measurements of Tl concentration were measured at Exam 1 (2000-2002) and overnight in-home PSG with seven days of wrist-worn actigraphy were collected between 2010-2013. We employed nonparametric partial correlations to examine the relationship between log-transformed Tl and sleep outcomes, adjusting for demographics, site and urinary creatinine.

Results

1822 adults were included (mean age 59.3 (45-84) years, 53.5% female, and 37.5% White, 27.9% Black/African American, 23.3% Hispanic, and 11.2% Chinese). Higher Tl levels were associated with actigraphy-based shorter sleep duration (rs = -.05, p < .05), higher wake after sleep onset (rs = .07, p <.01), shorter sleep maintenance efficiency (rs = -.08, p < .01), and higher activity during sleep (L5, rs = .05, p < .05). In contrast, higher Tl was related to favorable PSG-derived metrics: less %N1 (rs = -.05, p < .05), greater N3 (rs = .06, p < .05), and greater REM duration (rs = .06, p < .05). Higher Tl also was associated with higher sleep regularity (lower sleep duration SD; rs = -.06, p < .01; and Inter-day Stability: rs = .05, p < .05).

Conclusion

Tl was associated with more fragmented sleep measured at home with actigraphy, but with higher sleep regularity, and deeper sleep by PSG. The discordance of associations across sleep domains may indicate a complex effect of metal exposure and requires further investigation. Such findings may contribute to understanding the potential role of heavy metals on neurological process and sleep.

Support (if any)

The MESA Sleep studies were supported by NHLBI HL56984 and NIA R01AG070867.
0285 Measuring Sleep with the Apple Watch: A Comparison of a Machine Learning versus Traditional Algorithms to Actiwatch
Authors: Caputo Dominick , Hirata Mika , Moreno Jennette , Drake Christopher , Walch Olivia , Cheng Philip
Published: April 2024

Introduction

Consumer-based actigraphy has seen rapid adoption in the United States and presents an underutilized opportunity and resource for ecologically valid sleep-wake monitoring. Furthermore, with the discontinuation of Philips Actiwatch, a reliable and scalable alternative is required. Apple Watch may be a promising solution, with prior data indicating strong concordance for activity counts derived from the Apple Watch compared to the Actiwtach. The present study extends previous findings to sleep periods as an outcome of interest.

Methods

A community sample of 40 adults wore an Actiwatch and Apple Watch for 7 to 14 days with daily completion of the consensus sleep diary. Sleep periods from both wrist-worn devices were calculated and compared with sleep periods reported on the sleep diary. Sleep based on Apple Watch was derived using two approaches: one that mirrored traditional actigraphy (ie, sleep-wake classification using the Cole-Kripke model), and another than utilized machine learning with steps and heart rate as inputs. Agreement of sleep periods between the wrist-worn device and the sleep diary was operationalized as percent overlap. Performance of Apple Watch compared to the Actiwatch was then evaluated using the ratio of percentage overlap with sleep diary. A ratio of 1.00 represents perfect agreement.

Results

The agreement between Apple Watch derived sleep periods and sleep diary was comparable to that with Actiwatches. The ratio of percentage overlap between the two devices was 1.00 when using the machine learning algorithm, and 0.97 when using the traditional actigraphy approach. When averaged across the sample, sleep periods derived from Actiwatch overlapped by 80.7% (95% CI [84.1% - 77.3%]) with sleep diary periods, and sleep periods derived from Apple Watch overlapped by 82.0% (95% CI [84.7% - 79.4%]) and 81.2% (95% CI [84.9% - 77.5%]) for the machine learning and traditional actigraphy approaches, respectively. Total sleep period from the Apple Watch produced lower mean absolute errors compared to Actiwatch (machine learning: 24.8 minutes, traditional actigraphy approach: 19.1 minutes).

Conclusion

Sleep periods derived from Apple Watch data showed strong agreement with Actiwatch data, with the machine learning algorithm showing slightly stronger performance compared to the Cole-Kripke algorithm.

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0287 SAFTEr: An R Package for the SAFTE Model
Authors: Choynowski Jake , Devine Jaime , Hursh Steven
Published: April 2024

Introduction

The Sleep, Activity, Fatigue, and Task Effectiveness (SAFTE) model is a framework that predicts individual performance changes based on variations in circadian phase and sleep/wake schedules. The SAFTE model is used by industries in which fatigue risk is relevant to safety through licensed software like SAFTE-FAST. The SAFTE model may provide helpful context during the analysis of objective and performance sleep data but a full software license may be cost-prohibitive. SAFTEr was created as an open-source R package to allow the use of the original patented SAFTE model as a freely available research tool.

Methods

The SAFTE algorithm was rebuilt from patent equations in collaboration with SAFTE inventor Steven Hursh using the R-coding language. The R package was broken down into three primary steps: 1) formatting data into 1-minute epochs; 2) fitting SAFTE model predictions to the data; and 3) graphing the dataset. SAFTEr includes 17 constants identified in the model and 20 output variables that can be computed on an epoch-by-epoch basis. SAFTEr is best suited for schedules that do not induce a phase change, because the simplified model does not detect and automatically shift circadian phase.

Results

The current version of the SAFTEr package (0.1.2) consists of six functions that model and graph time-based datasets of sleep/wake data and include the ability to customize bedtimes, study start and end times, and events markers. The six functions include: 1) formatting data; 2) identification of possible missing data; 3) modeling; 4) generation of individual graphs with graphic overlay of event markers against the modeled data; 5) graph overlay to compare variables of interest against the SAFTE model as a line chart or; 6) as a scatter plot.

Conclusion

The SAFTEr package is freely available for use by researchers who wish to predict cognitive performance as a function of objective sleep data. The SAFTEr package is an open-source recreation of the SAFTE model that gives anyone with a basic knowledge of R the ability to apply the model to their own data as well as graph it against other measurable tests.

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N/A