Variable Selection for Skewed Model-Based Clustering: Application to the Identification of Novel Sleep Phenotypes

Ten-Year Stability of an Insomnia Sleeper Phenotype and Its Association With Chronic Conditions

OBJECTIVE

To identify distinct sleep health phenotypes in adults, examine transitions in sleep health phenotypes over time, and subsequently relate these to the risk of chronic conditions.

METHODS

A national sample of adults from the Midlife in the United States study ( N = 3683) provided longitudinal data with two time points (T1: 2004-2006, T2: 2013-2017). Participants self-reported on sleep health (regularity, satisfaction, alertness, efficiency, duration) and the number and type of chronic conditions. Covariates included age, sex, race, education, education, partnered status, number of children, work status, smoking, alcohol, and physical activity.

RESULTS

Latent transition analysis identified four sleep health phenotypes across both time points: good sleepers, insomnia sleepers, weekend catch-up sleepers, and nappers. Between T1 and T2, the majority (77%) maintained their phenotype, with the nappers and insomnia sleepers being the most stable. In fully adjusted models with good sleepers at both time points as the reference, being an insomnia sleeper at either time point was related to having an increased number of total chronic conditions by 28%-81% at T2, adjusting for T1 conditions. Insomnia sleepers at both time points were at 72%-188% higher risk for cardiovascular disease, diabetes, depression, and frailty. Being a napper at any time point related to increased risks for diabetes, cancer, and frailty. Being a weekend catch-up sleeper was not associated with chronic conditions. Those with lower education and unemployed were more likely to be insomnia sleepers; older adults and retirees were more likely to be nappers.

CONCLUSION

Findings indicate a heightened risk of chronic conditions involved in suboptimal sleep health phenotypes, mainly insomnia sleepers.

Neurobehavioral Reward and Sleep-Circadian Profiles Predict Present and Next-Year Mania/Hypomania Symptoms

BACKGROUND

Heightened reward sensitivity/impulsivity, related neural activity, and sleep-circadian disruption are important risk factors for bipolar spectrum disorders, the defining feature of which is mania/hypomania. Our goal was to identify neurobehavioral profiles based on reward and sleep-circadian features and examine their specificity to mania/hypomania versus depression vulnerability.

METHODS

At baseline, a transdiagnostic sample of 324 adults (18-25 years) completed trait measures of reward sensitivity (Behavioral Activation Scale), impulsivity (UPPS-P-Negative Urgency), and a functional magnetic resonance imaging card-guessing reward task (left ventrolateral prefrontal activity to reward expectancy, a neural correlate of reward motivation and impulsivity, was extracted). At baseline, 6-month follow-up, and 12-month follow-up, the Mood Spectrum Self-Report Measure - Lifetime Version assessed lifetime predisposition to subthreshold-syndromal mania/hypomania, depression, and sleep-circadian disturbances (insomnia, sleepiness, reduced sleep need, rhythm disruption). Mixture models derived profiles from baseline reward, impulsivity, and sleep-circadian variables.

RESULTS

Three profiles were identified: 1) healthy (no reward or sleep-circadian disruption; n = 162); 2) moderate-risk (moderate reward and sleep-circadian disruption; n = 109); and 3) high-risk (high impulsivity and sleep-circadian disruption; n = 53). At baseline, the high-risk group had significantly higher mania/hypomania scores than the other groups but did not differ from the moderate-risk group in depression scores. Over the follow-up period, the high-risk and moderate-risk groups exhibited elevated mania/hypomania scores, whereas depression scores increased at a faster rate in the healthy group than in the other groups.

CONCLUSIONS

Cross-sectional and next-year predisposition to mania/hypomania is associated with a combination of heightened reward sensitivity and impulsivity, related reward circuitry activity, and sleep-circadian disturbances. These measures can be used to detect mania/hypomania risk and provide targets to guide and monitor interventions.

Quantifying Distances Between Non-Elliptical Clusters to Enhance the Identification of Meaningful Emotional Reactivity Subtypes

Coordinated emotional responses across psychophysiological and subjective indices is a cornerstone of adaptive emotional functioning. Using clustering to identify cross-diagnostic subgroups with similar emotion response profiles may suggest novel underlying mechanisms and treatments.However, many psychophysiological measures are non-normal even in homogenous samples, and over-reliance on traditional elliptical clustering approaches may inhibit the identification of meaningful subgroups. Finite mixture models that allow for non-elliptical cluster distributions is an emerging methodological field that may overcome this hurdle. Furthermore, succinctly quantifying pairwise cluster separation could enhance the clinical utility of the clustering solutions. However, a comprehensive examination of distance measures in the context of elliptical and non-elliptical model-based clustering is needed to provide practical guidance on the computation, benefits, and disadvantages of existing measures. We summarize several measures that can quantify the multivariate distance between two clusters and suggest practical computational tools. Through a simulation study, we evaluate the measures across three scenarios that allow for clusters to differ in location, scale, skewness, and rotation. We then demonstrate our approaches using psychophysiological and subjective responses to emotional imagery captured through the Transdiagnostic Anxiety Study. Finally, we synthesize findings to provide guidance on how to use distance measures in clustering applications.

Actigraphy-derived sleep health profiles and mortality in older men and women

STUDY OBJECTIVES

To identify actigraphy sleep health profiles in older men (Osteoporotic Fractures in Men Study; N = 2640) and women (Study of Osteoporotic Fractures; N = 2430), and to determine whether profile predicts mortality.

METHODS

We applied a novel and flexible clustering approach (Multiple Coalesced Generalized Hyperbolic mixture modeling) to identify sleep health profiles based on actigraphy midpoint timing, midpoint variability, sleep interval length, maintenance, and napping/inactivity. Adjusted Cox models were used to determine whether profile predicts time to all-cause mortality.

RESULTS

We identified similar profiles in men and women: High Sleep Propensity [HSP] (20% of women; 39% of men; high napping and high maintenance); Adequate Sleep [AS] (74% of women; 31% of men; typical actigraphy levels); and Inadequate Sleep [IS] (6% of women; 30% of men; low maintenance and late/variable midpoint). In women, IS was associated with increased mortality risk (Hazard Ratio [HR] = 1.59 for IS vs. AS; 1.75 for IS vs. HSP). In men, AS and IS were associated with increased mortality risk (1.19 for IS vs. HSP; 1.22 for AS vs. HSP).

CONCLUSIONS

These findings suggest several considerations for sleep-related interventions in older adults. Low maintenance with late/variable midpoint is associated with increased mortality risk and may constitute a specific target for sleep health interventions. High napping/inactivity co-occurs with high sleep maintenance in some older adults. Although high napping/inactivity is typically considered a risk factor for deleterious health outcomes, our findings suggest that it may not increase risk when it occurs in combination with high sleep maintenance.

Multidimensional sleep health in a diverse, aging adult cohort: Concepts, advances, and implications for research and intervention

PURPOSE

To illustrate 2 frameshifts of multidimensional sleep health: i) use of composite sleep metrics; and ii) the correlations among sleep dimensions.

PARTICIPANTS

735 adults of diverse backgrounds aged <65 years who participated in the Multi-Ethnic Study of Atherosclerosis.

MEASURES

In-home polysomnography, 7-day wrist actigraphy, and validated questionnaires.

METHODS

The Buysse Ru SATED model-sleep regularity, satisfaction, alertness, timing, efficiency, duration-was operationalized, then extended by including additional measures of sleep architecture and sleep apnea from polysomnography and difficulties initiating sleep from questionnaire and sleep onset latency and duration [ir]regularity from actigraphy. We dichotomized sleep variables, operationalizing optimal and nonoptimal ranges as 1 and 0, respectively, summed into a sleep health score, and computed global sleep health scores via principal components analysis.

FINDINGS

Participants showed low prevalence of sleep regularity in timing (<30 minutes standard deviation [SD]; 21.4% favorable) and duration (<60 minutes SD; 36.9%). Although 62.7% of participants demonstrated favorable sleep duration by actigraphy, few met criteria for favorable levels of % N3 (11.4%) or %R (34.1%). The average Sleep Health Score was 5.6 of 13 (higher is better). Sleep variables were variably intercorrelated (r = 0 to r = -0.72). The first principal component for each operationalization of sleep health was interpretable as a "health" score; all summary scores captured variable but systematic shifts towards more favorable sleep in each sleep variable.

CONCLUSIONS

Multidimensional sleep health can be measured by complementary composite scores as well as consideration of multiple individual dimensions.

Multidimensional sleep health domains in older men and women: an actigraphy factor analysis

The multidimensional sleep health framework emphasizes that sleep can be characterized across several domains, with implications for developing novel sleep treatments and improved prediction and health screening. However, empirical evidence regarding the domains and representative measures that exist in actigraphy-assessed sleep is lacking. We aimed to establish these domains and representative measures in older adults by examining the factor structure of 28 actigraphy-derived sleep measures from 2,841 older men from the Osteoporotic Fractures in Men Sleep Study and, separately, from 2,719 older women from the Study of Osteoporotic Fractures. Measures included means and standard deviations of actigraphy summary measures and estimates from extended cosine models of the raw actigraphy data. Exploratory factor analyses revealed the same five factors in both sexes: Timing (e.g. mean midpoint from sleep onset to wake-up), Efficiency (e.g. mean sleep efficiency), Duration (e.g. mean minutes from sleep onset to wake-up), Sleepiness/Wakefulness (e.g. mean minutes napping and amplitude of rhythm), and Regularity (e.g. standard deviation of the midpoint). Within each sex, confirmatory factor analyses confirmed the one-factor structure of each factor and the entire five-factor structure (Comparative Fit Index and Tucker-Lewis Index ≥ 0.95; Root Mean Square Error of Approximation 0.08-0.38). Correlation magnitudes among factors ranged from 0.01 to 0.34. These findings demonstrate the validity of conceptualizing actigraphy sleep as multidimensional, provide a framework for selecting sleep health domains and representative measures, and suggest targets for behavioral interventions. Similar analyses should be performed with additional measures of rhythmicity, other age ranges, and more racially/ethnically diverse samples.

Beyond single sleep measures: A composite measure of sleep health and its associations with psychological and physical well-being in adulthood

RATIONALE

Sleep is important for many functions including body and mind restoration. Studies report the association of sleep with stress and physical deterioration, often focusing only on sleep duration; yet, sleep health needs to be understood by multiple dimensions to comprehensively capture its impact on well-being.

OBJECTIVE

This study examined cross-sectional and longitudinal associations of multidimensional sleep health with perceived stress and chronic physical conditions.

METHODS

We used a sample of 441 adults (M age = 57 years) who participated in the biomarker project of the Midlife in the United States Study. Participants provided self-report and actigraphy sleep data in 2004-2009 (T1). We created a composite score of sleep health (Range = 0-6; higher indicating more sleep problems) encompassing: actigraphy-measured regularity, timing, efficiency, duration, and self-reported satisfaction and alertness. Participants responded to the perceived stress scale and chronic physical conditions checklist at T1; chronic physical conditions were reassessed in 2013-2015 (T2).

RESULTS

Cross-sectionally, a composite score of sleep health problems was uniquely associated with higher perceived stress and more chronic conditions, explaining additional variance that each individual sleep variable did not explain. Sleep duration - one of the most commonly researched dimensions of sleep - was not associated with either perceived stress or chronic conditions. Longitudinally, for individuals who had fewer chronic conditions at T1, having more sleep health problems was associated with an increase in chronic conditions at T2. Among the multiple dimensions, sleep satisfaction was most consistently and strongly associated with the outcomes.

CONCLUSION

Findings suggest the importance of considering multiple sleep dimensions concerning psychological and physical well-being in adulthood.