Unobtrusive Skin Temperature Estimation on a Smart Bed.

The transition from wakefulness to sleep occurs when the core body temperature decreases. The latter is facilitated by an increase in the cutaneous blood flow, which dissipates internal heat into the micro-environment surrounding the sleeper's body. The rise in cutaneous blood flow near sleep onset causes the distal (hands and feet) and proximal (abdomen) temperatures to increase by about 1 °C and 0.5 °C, respectively. Characterizing the dynamics of skin temperature changes throughout sleep phases and understanding its relationship with sleep quality requires a means to unobtrusively and longitudinally estimate the skin temperature. Leveraging the data from a temperature sensor strip (TSS) with five individual temperature sensors embedded near the surface of a smart bed's mattress, we have developed an algorithm to estimate the distal skin temperature with a minute-long temporal resolution. The data from 18 participants who recorded TSS and ground-truth temperature data from sleep during 14 nights at home and 2 nights in a lab were used to develop an algorithm that uses a two-stage regression model (gradient boosted tree followed by a random forest) to estimate the distal skin temperature. A five-fold cross-validation procedure was applied to train and validate the model such that the data from a participant could only be either in the training or validation set but not in both. The algorithm verification was performed with the in-lab data. The algorithm presented in this research can estimate the distal skin temperature at a minute-level resolution, with accuracy characterized by the mean limits of agreement [-0.79 to +0.79 °C] and mean coefficient of determination R2=0.87. This method may enable the unobtrusive, longitudinal and ecologically valid collection of distal skin temperature values during sleep. Therelatively small sample size motivates the need for further validation efforts.

A Protocol to Determine Circadian Phase by At-Home Salivary Dim Light Melatonin Onset Assessment.

Internal circadian phase assessment is increasingly acknowledged as a critical clinical tool for the diagnosis, monitoring, and treatment of circadian rhythm sleep-wake disorders and for investigating circadian timing in other medical disorders. The widespread use of in-laboratory circadian phase assessments in routine practice has been limited, most likely because circadian phase assessment is not required by formal diagnostic nosologies, and is not generally covered by insurance. At-home assessment of salivary dim light melatonin onset (DLMO, a validated circadian phase marker) is an increasingly accepted approach to assess circadian phase. This approach may help meet the increased demand for assessments and has the advantages of lower cost and greater patient convenience. We reviewed the literature describing at-home salivary DLMO assessment methods and identified factors deemed to be important to successful implementation. Here, we provide specific protocol recommendations for conducting at-home salivary DLMO assessments to facilitate a standardized approach for clinical and research purposes. Key factors include control of lighting, sampling rate, and timing, and measures of patient compliance. We include findings from implementation of an optimization algorithm to determine the most efficient number and timing of samples in patients with Delayed Sleep-Wake Phase Disorder. We also provide recommendations for assay methods and interpretation. Providing definitive criteria for each factor, along with detailed instructions for protocol implementation, will enable more widespread adoption of at-home circadian phase assessments as a standardized clinical diagnostic, monitoring, and treatment tool.

Characterization of sleep disturbance in established rheumatoid arthritis patients: exploring the relationship with central nervous system pain regulation.

BACKGROUND: To characterize sleep disturbance in patients with established rheumatoid arthritis (RA) and explore the relationship between sleep and mechanisms of central nervous system pain regulation. METHODS: Forty-eight RA participants completed wrist-worn actigraphy monitoring and daily sleep diaries for 14 days to assess sleep-wake parameters. Participants underwent quantitative sensory testing to assess pressure pain thresholds, temporal summation, and conditioned pain modulation. Data were analyzed using descriptive statistics, Spearman's correlation, and multivariable median regression analyses. RESULTS: Median actigraphy and sleep diary derived sleep duration was 7.6 h (interquartile range (IQR) 7.0, 8.2) and 7.1 h (IQR 6.7, 7.6), respectively. Actigraphy based sleep fragmentation (rho = 0.34), wake after sleep onset (rho = 0.36), and sleep efficiency (rho = -0.32) were each related to higher temporal summation values in unadjusted analyses, but these relationships did not persist after controlling for age, body mass index, disease duration, and swollen joint count. No significant relationships were observed between sleep with pressure pain thresholds and conditioned pain modulation. CONCLUSION: Actigraphy and sleep diary monitoring are well tolerated in established RA patients. Future investigations should include both subjective and objective assessments, as they may provide information relating to different components and mechanisms.

Impact of sleep disruption on cognitive function in patients with postacute sequelae of SARS-CoV-2 infection: initial findings from a Neuro-COVID-19 clinic.

Introduction: Fatigue, brain fog, and sleep disturbance are among the most common symptoms of postacute sequelae of SARS-CoV-2 infection (PASC). We sought to determine the impact of sleep disruption on cognition and quality of life in patients with neurologic manifestations of PASC (Neuro-PASC). Methods: Thirty-nine patients were recruited from Neuro-COVID-19 clinic. Mean age was 48.1 years, 71.8% were female, and 82% were never hospitalized for COVID-19. Patients were evaluated via clinical assessment, quality-of-life measures in domains of cognitive function, fatigue, sleep disturbance, anxiety, and depression, NIH Toolbox cognitive tests, and 7 days of wrist actigraphy. Results: The median number of neurologic symptoms attributed to PASC was 6, with brain fog being the most common in 89.7%. Regarding non-neurologic symptoms, 94.9% complained of fatigue and 74.4% of insomnia. Patients reported significant impairment in all quality-of-life domains and performed worse in a task of attention compared to a normative US population. Actigraphy showed Neuro-PASC patients had lower sleep efficiency, longer sleep latency (both p < 0.001), and later sleep midpoint (p = 0.039) compared to 71 age-matched healthy controls with no PASC history. Self-reported cognitive symptoms correlated with the severity of fatigue (p < 0.001), anxiety (p = 0.05), and depression (p < 0.01). Objective evidence of sleep disruption measured by wakefulness after sleep onset, sleep efficiency, and latency were associated with decreased performance in attention and processing speed. Conclusion: Prospective studies including larger populations of patients are needed to fully determine the interplay of sleep disruption on the cognitive function and quality of life of patients with PASC.

The association between multidimensional sleep health and gestational weight gain.

BACKGROUND: Although poor sleep health is associated with weight gain and obesity in the non-pregnant population, research on the impact of sleep health on weight change among pregnant people using a multidimensional sleep health framework is needed. OBJECTIVES: This secondary data analysis of the Nulliparous Pregnancy Outcome Study: Monitoring Mothers-to-be Sleep Duration and Continuity Study (n = 745) examined associations between mid-pregnancy sleep health indicators, multidimensional sleep health and gestational weight gain (GWG). METHODS: Sleep domains (i.e. regularity, nap duration, timing, efficiency and duration) were assessed via actigraphy between 16 and 21 weeks of gestation. We defined 'healthy' sleep in each domain with empirical thresholds. Multidimensional sleep health was based on sleep profiles derived from latent class analysis and composite score defined as the sum of healthy sleep domains. Total GWG, the difference between self-reported pre-pregnancy weight and the last measured weight before delivery, was converted to z-scores using gestational age- and BMI-specific charts. GWG was defined as low (<-1 SD), moderate (-1 or +1 SD) and high (>+1 SD). RESULTS: Nearly 50% of the participants had a healthy sleep profile (i.e. healthy sleep in most domains), whereas others had a sleep profile defined as having varying degrees of unhealthy sleep in each domain. The individual sleep domains were associated with a 20%-30% lower risk of low or high GWG. Each additional healthy sleep indicator was associated with a 10% lower risk of low (vs. moderate), but not high, GWG. Participants with late timing, long duration and low efficiency (vs. healthy) profiles had the strongest risk of low GWG (relative risk 1.5, 95% confidence interval 0.9, 2.4). Probabilistic bias analysis suggested that most associations between individual sleep health indicators, sleep health profiles and GWG were biased towards the null. CONCLUSIONS: Future research should determine whether sleep health is an intervention target for healthy GWG.

Work-Related Sleep Disorders: Causes and Impacts.

Insufficient sleep syndrome, shift work disorder, and obstructive sleep apnea (OSA) not only significantly impact the health of affected individuals, but also pose a threat to public safety. This article describes the clinical manifestations and impact of these sleep disorders, particularly as they pertain to workers' health and those with safety-sensitive positions. Sleep deprivation, circadian rhythm disruptions, and excessive daytime sleepiness-hallmarks of insufficient sleep, shift work disorder, and OSA, respectively-all lead to a series of cognitive deficits and impaired concentration that affect workers in a wide variety of fields. We describe the health consequences of these disorders along with treatment strategies, with a focus on current regulatory standards and the under-recognition of OSA in commercial drivers. Given its large scale, there is a need for improved guidelines and regulations for the screening, diagnosis, treatment, and long-term follow-up of OSA in commercial motor vehicle drivers. Increased recognition of the ways in which these sleep disorders impact workers will pave the way for significant improvements in occupational health and safety.

The association between multidimensional sleep health and gestational weight gain: nuMoM2b Sleep Duration and Continuity Study.

Background: Although poor sleep health is associated with weight gain and obesity in the non-pregnant population, research on the impact of sleep health on weight change among pregnant people using a multidimensional sleep-health framework is needed. This study examined associations among mid-pregnancy sleep health indicators, multidimensional sleep health, and gestational weight gain (GWG). Methods: We conducted a secondary data analysis of the Nulliparous Pregnancy Outcome Study: Monitoring Mothers-to-be Sleep Duration and Continuity Study (n=745). Indicators of individual sleep domains (i.e., regularity, nap duration, timing, efficiency, and duration) were assessed via actigraphy between 16 and 21 weeks of gestation. We defined "healthy" sleep in each domain based on empirical thresholds. Multidimensional sleep health was based on sleep profiles derived from latent class analysis. Total GWG, the difference between self-reported pre-pregnancy weight and the last measured weight before delivery, was converted to z-scores using gestational age- and BMI-specific charts. GWG was defined as low (<-1 SD), moderate (-1 or +1 SD), and high (>+1 SD). Results: Nearly 50% of the participants had a healthy sleep profile (i.e., healthy sleep in most domains), whereas others had a sleep profile defined as having varying degrees of poor health in each domain. While indicators of individual sleep domains were not associated with GWG, multidimensional sleep health was related to low and high GWG. Participants with a sleep profile characterized as having low efficiency, late timing, and long sleep duration (vs. healthy sleep profile) had a higher risk (RR 1.7; 95% CI 1.0, 3.1) of low GWG a lower risk of high GWG (RR 0.5 95% CI 0.2, 1.1) (vs. moderate GWG). Conclusions: Multidimensional sleep health was more strongly associated with GWG than individual sleep domains. Future research should determine whether sleep health is a valuable intervention target for optimizing GWG. Synopsis: Study question: What is the association between mid-pregnancy multidimensional sleep health and gestational weight gain?What's already known?: Sleep is associated with weight and weight gain outside of pregnancyWhat does this study add?: We identified patterns of sleep behaviors associated with an increased risk of low gestational weight gain.

Light at night in older age is associated with obesity, diabetes, and hypertension.

Light at night (LAN) has been associated with negative health consequences and metabolic risk factors. Little is known about the prevalence of LAN in older adults in the United States and its association with CVD risk factors. We tested the hypothesis that LAN in older age is associated with higher prevalence of individual CVD risk factors. Five hundred and fifty-two community-dwelling adults aged 63-84 years underwent an examination of CVD risk factor profiles and 7-day actigraphy recording for activity and light measures. Associations between actigraphy-measured LAN, defined as no light vs. light within the 5-hour nadir (L5), and CVD risk factors, including obesity, diabetes, hypertension, and hypercholesterolemia, were examined, after adjusting for age, sex, race, season of recording, and sleep variables. LAN exposure was associated with a higher prevalence of obesity (multivariable-adjusted odds ratio [OR] 1.82 [95% CI 1.26-2.65]), diabetes (OR 2.00 [1.19-3.43]), and hypertension (OR 1.74 [1.21-2.52]) but not with hypercholesterolemia. LAN was also associated with (1) later timing of lowest light exposure (L5-light) and lowest activity (L5-activity), (2) lower inter-daily stability and amplitude of light exposure and activity, and (3) higher wake after sleep onset. Habitual LAN in older age is associated with concurrent obesity, diabetes, and hypertension. Further research is needed to understand long-term effects of LAN on cardiometabolic risks.

Night-to-night associations between light exposure and sleep health.

Previous research has demonstrated that exposure to light preceding and during sleep is associated with poor sleep, but most research to date has utilized either experimental or cross-sectional designs. The current study expands upon prior studies by using a microlongitudinal design that examines the night-to-night associations between light and sleep health in a diverse sample of adults (pre-registered at osf.io/k5zgv). US adults aged 18-87 years from two parent studies (N = 124) wore an actiwatch for up to 10 nights. Light variables estimated from actigraphy include both average exposure and time above light threshold of 10 (TALT10 ) and 40 (TALT40 ) lux both during sleep and for the 1-hr preceding sleep. Actigraphy-based sleep variables included sleep offset, duration, percentage and fragmentation index. Higher average light exposure during sleep was associated with a later sleep-offset time, lower sleep percentage and higher fragmentation index (all p < 0.01). More minutes of TALT10 during sleep was associated with later sleep timing, lower sleep percentage and higher fragmentation index (all p < 0.01), and greater TALT40 during sleep was associated with lower sleep percentage. Light exposure was not related to sleep duration. In summary, greater light exposure during sleep was related to poorer sleep continuity and later wake time. The lack of association between light and sleep duration may be the result of compensating for sleep disruption by delaying wake time. Multi-level interventions to consistently reduce light levels during sleep should be considered.

Sleep, cardiovascular risk factors, and kidney function: The Multi-Ethnic Study of Atherosclerosis (MESA).

OBJECTIVES: Examine the associations of sleep measures with kidney function changes over time among individuals from a community-based study. METHODS: The sample includes 1657 participants (287 with chronic kidney disease [CKD]) in the Multi-Ethnic Study of Atherosclerosis Sleep Cohort (mean age: 57.7 years, male: 46.0%). We examined associations between a large set of sleep variables (polysomnography, actigraphy, and questionnaires) and cardiovascular disease risk factors and changes in estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio over approximately 5 years using high-dimensional regression. We investigated the modifying effect of sleep on the associations between cardiovascular disease risk factors and kidney function. RESULTS: Sleep metrics predicted kidney function decline only among individuals with baseline CKD. Among this group, eGFR decline was associated with decreased stage N3 sleep (0.32 mL/min/1.73 m2/y per 10% decrease in N3, p < .001); increased actigraphy napping frequency (beta: -0.20 [-0.30, -0.07]); and actigraphy sleep midpoint trajectory in early morning (ref: midnight, beta: -0.84 [-1.19, -0.50]). Urinary albumin-to-creatinine ratio increase was associated with high wake bouts trajectory (ref: low, beta: 0.97 [0.28, 1.67]) and increased sleep-related hypoxemia (oxygen saturation %time<90 [≥5%], beta: 2.17 [1.26, 3.08]). Sleep metrics--N3 sleep, naps, and midpoint trajectory--significantly modified associations between hemoglobin A1C and eGFR decline. CONCLUSIONS: Reduced deep sleep, daytime napping, increased wake bouts, delayed sleep rhythms, and overnight hypoxemia are associated with longitudinal kidney function decline, with effects most apparent in individuals with CKD. Deep sleep, napping, and sleep timing modified the association between hemoglobin A1C and kidney function.

Examining the Efficacy of Bright Light Therapy on Cognitive Function in Hematopoietic Stem Cell Transplant Survivors.

Patients who have undergone hematopoietic stem cell transplant (HSCT) may experience cognitive impairment that can persist after treatment. Several studies have shown that bright light therapy may improve cognition, potentially due to its effects on the circadian system via brain regions that respond preferentially to light. In this double-blind randomized controlled trial, the efficacy of bright light therapy on cognition was examined in HSCT survivors. Forty-seven HSCT survivors at an urban hospital in the United States were screened for mild cognitive impairment, randomized to either bright white light (BWL) or comparison dim red light (DRL) conditions using a block randomization approach, and instructed to use their assigned light box every morning upon awakening for 30 min for 4 weeks. Assessments occurred at baseline, the end of the second week of the intervention, the end of the intervention, and at follow-up (8 weeks later). The primary outcome was objective cognitive function as measured by a global composite score on neuropsychological tests. Secondary outcomes included cognitive performance in individual domains, self-reported cognitive function, fatigue, sleep and sleep quality, and circadian rhythm robustness. Repeated-measures linear mixed models for both objective and self-reported cognitive function indicated significant main effects for time (ps < 0.05) suggesting significant improvements in both conditions over time. Time by light condition interaction effects were not significant. Models focused on secondary outcomes yielded no significant effects. Both BWL and DRL groups demonstrated significant improvements in objective cognitive and self-reported cognitive function over time, but there was no hypothesized effect of BWL over DRL nor associations with circadian rhythm robustness. Therapeutic effects of both light conditions, practice effects, and/or placebo effects may account for the findings.Trial registration: ClinicalTrials.gov Identifier: NCT02677987 (9 February 2016).

Associations of chronotype and sleep patterns with metabolic syndrome in the Hispanic community health study/study of Latinos.

Sleep duration, sleep efficiency, and sleep timing have been shown to have potential effects on metabolic functions relevant to circadian rhythms. It is not clear if the impact of sleep patterns on metabolic risk factors is through sociocultural and environmental factors or circadian misalignment. We investigated the associations of sleep patterns, chronotype, and social jet lag with metabolic syndrome among non-shift worker Hispanic/Latino adults. We used cross-sectional data from the Sueño Ancillary Study of The Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Data from a subsample of 2189 participants aged 18-64 years were used in the analysis. Mean nightly sleep duration, mean sleep onset time, mean sleep offset time, mean sleep midpoint time, sleep efficiency, sleep variability (standard deviation (SD) of sleep duration, and SD of sleep midpoint), and time spent above light exposure threshold (1000 lux) in a day were assessed by wrist actigraphy (Acti-watch Spectrum). Chronotype was determined by the reduced Morningness-Eveningness Questionnaire. Medical conditions including dyslipidemia, hypertension, and diabetes mellitus were determined from a fasting blood specimen and physical exam at the baseline visit. To determine whether sleep patterns, light levels, chronotype, and social jetlag are associated with metabolic syndrome, multivariable logistic regression models were fitted, including variables with P < .15 in the univariate analysis. The results of the multivariable analysis demonstrated that in participants older than 40 years, intermediate chronotype (vs early) was significantly associated with a higher risk of metabolic syndrome (Odds ratio (95%CI): 1.33 (1.04,1.7)), while later chronotype (vs. early) in participants younger than 40 years was significantly associated with a lower risk of metabolic syndrome (Odds ratio (95%CI): 0.37 (0.14, 0.96)). Also, higher sleep efficiency was significantly associated with decreased odds of metabolic syndrome (Odds ratio (95%CI): 0.98 (0.96, 0.99)). Nightly sleep duration was not significantly different between two groups of participants with and without metabolic syndrome in multivariable analyses. There was no significant association between social jet lag and metabolic syndrome in multivariable analysis (p = .286). Moreover, there was no significant association between chronotype and social jet lag in multivariable analysis. The association between metabolic syndrome and chronotype is age-dependent. While early chronotype is associated with metabolic syndrome in younger individuals, it tended to be associated with lower odds for metabolic syndrome in older individuals.

Optimizing a Behavioral Sleep Intervention for Gynecologic Cancer Survivors: Study Design and Protocol.

Sleep difficulties, particularly symptoms of insomnia and circadian disruption, are among the primary complaints of gynecologic cancer survivors before, during, and after treatment. Moreover, difficulty sleeping has been linked to poorer health-related quality of life and elevated symptom burden in this population. Although leading behavioral sleep interventions have demonstrated efficacy among cancer survivors, up to 50% of survivors are non-adherent to these treatments, likely because these interventions require labor-intensive behavior and lifestyle changes. Therefore, there is a need for more effective and acceptable approaches to diminish sleep disturbance among cancer survivors. This manuscript describes the methodology of a two-part study guided by the Multiphase Optimization Strategy (MOST) framework to identify a streamlined behavioral sleep intervention for gynecologic cancer survivors. Three candidate intervention components previously shown to decrease sleep disturbance will be evaluated, including sleep restriction, stimulus control, and systematic bright light exposure. Participants will be adult women with a history of non-metastatic gynecologic cancer who have completed primary treatment and who report current poor sleep quality. Fifteen participants will be recruited for Part 1 of the study, which will utilize qualitative methods to identify barriers to and facilitators of intervention adherence. Results will inform changes to the delivery of the candidate intervention components to promote adherence in Part 2, where 80 participants will be recruited and randomized to one of eight conditions reflecting every possible combination of the three candidate intervention components in a full factorial design. Participants will complete assessments at baseline, post-intervention, and 3-months post-intervention. Part 2 results will identify the combination of candidate intervention components that yields the most efficacious yet efficient 6-week intervention for diminishing sleep disturbance. This is the first known study to apply the MOST framework to optimize a behavioral sleep intervention and will yield a resource-efficient treatment to diminish sleep disturbance, improve health-related quality of life, and decrease symptom burden among gynecologic cancer survivors. ClinicalTrials.gov Identifier: NCT05044975.

Light exposure during sleep impairs cardiometabolic function.

SignificanceAmbient nighttime light exposure is implicated as a risk factor for adverse health outcomes, including cardiometabolic disease. However, the effects of nighttime light exposure during sleep on cardiometabolic outcomes and the related mechanisms are unclear. This laboratory study shows that, in healthy adults, one night of moderate (100 lx) light exposure during sleep increases nighttime heart rate, decreases heart rate variability (higher sympathovagal balance), and increases next-morning insulin resistance when compared to sleep in a dimly lit (<3 lx) environment. Moreover, a positive relationship between higher sympathovagal balance and insulin levels suggests that sympathetic activation may play a role in the observed light-induced changes in insulin sensitivity.

Guiding principles for determining work shift duration and addressing the effects of work shift duration on performance, safety, and health: guidance from the American Academy of Sleep Medicine and the Sleep Research Society.

CITATION: Risks associated with fatigue that accumulates during work shifts have historically been managed through working time arrangements that specify fixed maximum durations of work shifts and minimum durations of time off. By themselves, such arrangements are not sufficient to curb risks to performance, safety, and health caused by misalignment between work schedules and the biological regulation of waking alertness and sleep. Science-based approaches for determining shift duration and mitigating associated risks, while addressing operational needs, require: (1) a recognition of the factors contributing to fatigue and fatigue-related risks; (2) an understanding of evidence-based countermeasures that may reduce fatigue and/or fatigue-related risks; and (3) an informed approach to selecting workplace-specific strategies for managing work hours. We propose a series of guiding principles to assist stakeholders with designing a shift duration decision-making process that effectively balances the need to meet operational demands with the need to manage fatigue-related risks.

Guiding principles for determining work shift duration and addressing the effects of work shift duration on performance, safety, and health: guidance from the American Academy of Sleep Medicine and the Sleep Research Society.

Risks associated with fatigue that accumulates during work shifts have historically been managed through working time arrangements that specify fixed maximum durations of work shifts and minimum durations of time off. By themselves, such arrangements are not sufficient to curb risks to performance, safety, and health caused by misalignment between work schedules and the biological regulation of waking alertness and sleep. Science-based approaches for determining shift duration and mitigating associated risks, while addressing operational needs, require: (1) a recognition of the factors contributing to fatigue and fatigue-related risks; (2) an understanding of evidence-based countermeasures that may reduce fatigue and/or fatigue-related risks; and (3) an informed approach to selecting workplace-specific strategies for managing work hours. We propose a series of guiding principles to assist stakeholders with designing a shift duration decision-making process that effectively balances the need to meet operational demands with the need to manage fatigue-related risks.

Effects of manipulating body temperature on sleep in postmenopausal women.

STUDY OBJECTIVES: A decline in sleep quality, slow wave sleep (SWS) and slow wave activity (SWA) are common in older adults. Prior studies have shown that manipulating body temperature during sleep can increase SWS/SWA. The aim of this study was to determine the effects of manipulation of body temperatures during sleep, using a high heat capacity mattress, on SWS/SWA and heart rate in post-menopausal women. METHODS: Twenty-four healthy postmenopausal women between 40 and 75 years of age (mean age 62.4 ± 8.2 years, mean BMI 25.4 ± 3.5 kg/m2) were randomized in a single-blind, counterbalanced, cross-over manner to sleep on either a high heat capacity mattress (HHCM) or a low heat capacity mattress (LHCM) a week apart. Sleep was recorded using polysomnography during an 8-h sleep opportunity. Core and peripheral temperature were recorded using an ingestible capsule and thermochron respectively. RESULTS: In comparison to the LHCM, sleep on HHCM exhibited a selective increase in SWS (average increase in Stage N3 of 9.6 min (2.1%), p = 0.04) and in slow oscillatory (SO) activity (0.5-1 Hz) in the first NREM/REM cycle (p = 0.04). In addition, the HHCM induced a greater reduction in core body temperature (p = 0.002). The reduction in core body temperature (first 180 min after lights out) from LHCM to HHCM was associated (r = 0.5, p = 0.012) with the increase in SO activity (SO cycle 1 and 2/cycle 3 and 4). Average heart rate was 1.6 beats/minute lower across the night on the HHCM compared to the LHCM (p = 0.001). CONCLUSIONS: The results of this study indicate that manipulation of body temperature during sleep may be a useful approach to enhance SWS sleep in postmenopausal women.

Meal timing relative to DLMO: Associations with BMI and body fat.

BACKGROUND: Timing of eating relative to the dim light melatonin onset (DLMO) may serve as a modifiable risk factor for adverse cardiometabolic outcomes. The primary aim of this study was to examine whether the timing of eating relative to DLMO is associated with body mass index (BMI), body fat, and diet in healthy adults without the confound of sleep deprivation. METHODS: Healthy men and women (N = 97), ages 18-50, with a habitual sleep duration of ≥6.5 hours and ≤8.5 hours completed 7 days of actigraphy and daily sleep and food diaries. Participants underwent a dual-energy X-ray absorptiometry scan and blood draws to assess DLMO in the clinical research unit. RESULTS: A shorter duration between DLMO and the average clock time of the last meal (last meal-DLMO) was related to a higher number of meals consumed, b = 0.25, SEb = 0.06, P< .001, longer feeding duration, b = 0.84, SEb = 0.06, P< .001, greater carbohydrate intake, b = 9.08, SEb = 3.55, P= .01, and greater sugar intake, b = 4.73, SEb = 1.83, P= .01. Last meal-DLMO was not associated with BMI in the full sample; however, among those with later DLMO (after 10:30 PM) last meal-DLMO was related to higher BMI, b = 0.92, SEb = 0.36, P= .02. CONCLUSION: These results suggest that timing of last meal relative to DLMO may serve as a marker of circadian misalignment and that eating the last meal closer to DLMO may negatively impact dietary habits.