Study Objectives Multisensor wearable consumer devices allowing the collection of multiple data sources, such as heart rate and motion, for the evaluation of sleep in the home environment, are increasingly ubiquitous. However, the validity of such devices for sleep assessment has not been directly compared to alternatives such as wrist actigraphy or polysomnography (PSG). Methods Eight participants each completed four nights in a sleep laboratory, equipped with PSG and several wearable devices. Registered polysomnographic technologist-scored PSG served as ground truth for sleep–wake state. Wearable devices providing sleep–wake classification data were compared to PSG at both an epoch-by-epoch and night level. Data from multisensor wearables (Apple Watch and Oura Ring) were compared to data available from electrocardiography and a triaxial wrist actigraph to evaluate the quality and utility of heart rate and motion data. Machine learning methods were used to train and test sleep–wake classifiers, using data from consumer wearables. The quality of classifications derived from devices was compared. Results For epoch-by-epoch sleep–wake performance, research devices ranged in d′ between 1.771 and 1.874, with sensitivity between 0.912 and 0.982, and specificity between 0.366 and 0.647. Data from multisensor wearables were strongly correlated at an epoch-by-epoch level with reference data sources. Classifiers developed from the multisensor wearable data ranged in d′ between 1.827 and 2.347, with sensitivity between 0.883 and 0.977, and specificity between 0.407 and 0.821. Conclusions Data from multisensor consumer wearables are strongly correlated with reference devices at the epoch level and can be used to develop epoch-by-epoch models of sleep–wake rivaling existing research devices.

There is a lack of research on associations of social jetlag with eating behaviours and obesity among adolescents. We examined the associations of social jetlag with eating behaviours and BMI in adolescents before and after adjustment for potential confounders. Self-report data were collected from 3060 adolescents (48·1 % female, mean age 15·59 (sd 0·77) years) from the Fragile Families and Child Wellbeing Study. In regression models, social jetlag predicted odds of consumption of breakfast, fruits/vegetables, fast food and sweetened drinks and BMI percentile. Primary models adjusted for school night sleep duration, sex, age, household income and youth living arrangements; secondary models further adjusted for race/ethnicity. In fully adjusted models, greater social jetlag was associated with lower odds of consumption of breakfast (OR = 0·92, P = 0·003) and fruits/vegetables (OR = 0·92, P = 0·009) and higher odds of consumption of fast food (OR = 1·18, P < 0·001) and sweetened drinks (OR = 1·18, P < 0·001). Social jetlag was positively associated with BMI percentile after additional adjustment for eating behaviours (b = 0·84, P = 0·037), but this relationship was attenuated after adjustment for race/ethnicity (b = 0·72, P = 0·072). Ethnoracial differences in social jetlag may attenuate the association of social jetlag with BMI and should be considered in future studies of circadian misalignment, eating behaviours and obesity markers.

BACKGROUND AND OBJECTIVES: Diagnostic codes are used widely within health care for billing, quality assessment, and to measure clinical outcomes. The US health care system will transition to the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM), in October 2015. Little is known about how this transition will affect pediatric practices. The objective of this study was to examine how the transition to ICD-10-CM may result in ambiguity of clinical information and financial disruption for pediatricians. METHODS: Using a statewide data set from Illinois Medicaid specified for pediatricians, 2708 International Classification of Diseases, Ninth Revision, Clinical Modification, diagnosis codes were identified. Diagnosis codes were categorized into 1 of 5 categories: identity, class-to-subclass, subclass-to-class, convoluted, and no translation. The convoluted and high-cost diagnostic codes (n = 636) were analyzed for accuracy and categorized into “information loss,” “overlapping categories,” “inconsistent,” and “consistent.” Finally, reimbursement by Medicaid was calculated for each category. RESULTS: Twenty-six percent of pediatric diagnosis codes are convoluted, which represents 21% of Illinois Medicaid pediatric patient encounters and 16% of reimbursement. The diagnosis codes represented by information loss (3.6%), overlapping categories (3.2%), and inconsistent (1.2%) represent 8% of Medicaid pediatric reimbursement. CONCLUSIONS: The potential for financial disruption and administrative errors from 8% of reimbursement diagnosis codes necessitates special attention to these codes in preparing for the transition to ICD-10-CM for pediatric practices.

Social jetlag, a misalignment between sleep timing on the weekend and work week, is associated with depressive symptoms among adults across both sexes. One prior study found that later sleep timing was associated with depressive symptoms in women but not men. To date, however, no research has investigated whether the association between social jetlag and depression varies by sex among adolescents. The current study assessed self-reported sleep, depressive symptoms, and demographic information from 3,058 adolescents (48% female, mean ± SD age 15.59 ± .77 years) from the age 15 wave of the Fragile Families and Child Wellbeing Study (FFCWS). Social jetlag was calculated as the absolute value of the midpoint of sleep on the weekend minus the midpoint of sleep during the school week. Depressive symptoms were measured through a modified 5-item version of the Center for Epidemiologic Studies Depression Scale (CES-D). We assessed whether the associations between sleep duration on school nights, social jetlag, and depressive symptoms were similar between male and female adolescents using multiple linear regression. In fully adjusted models, sex moderated the association between school night TST and depressive symptoms (p < .001) and between social jetlag and depressive symptoms (p = .037). In females, but not in males, school night TST was negatively associated with depressive symptoms (p <. 001), while social jetlag (p < .001) was positively and independently associated with depressive symptoms. The results indicate the importance of regular sleep timing across the week and adequate sleep duration for maintenance of optimal emotional health among female adolescents.

Although short total sleep time (TST) is associated with increased anxious symptoms in adolescents, it is unknown whether social jetlag, a misalignment between sleep timing on the weekend and school week, is independently associated with anxious symptoms. In the current study, sleep timing, anxious symptoms and demographic information were assessed from 3,097 adolescents (48% female, mean ± SD age 15.59 ± .77 years) from the age 15 wave of the Fragile Families and Child Wellbeing Study (FFCWS). Social jetlag was calculated as the absolute value of the midpoint of sleep on the weekend minus the midpoint of sleep during the school week. Anxious symptoms were measured through the 6-item anxiety subscale of the Brief Symptom Inventory 18. We assessed associations between sleep variables and anxious symptoms using multiple linear regression. Adjusted analyses controlled for sex, race/ethnicity, age in years, body mass index percentile, number of other children below the age of 18 in the household, and primary caregiver (PCG) married/cohabiting with youth's biological parent, PCG employment status, PCG household income, and PCG education level. In fully adjusted models (R 2 = .034), school night TST (b = −.04, ∆R 2 = .005, p < .001) was negatively associated with anxiety symptoms, while social jetlag (b = .04, ∆R 2 = .009, p < .001) was positively and independently associated with anxiety symptoms. Findings indicate small associations of school night TST and social jetlag with anxious symptoms. Thus, maintenance of optimal emotional health in adolescents may require both sufficient sleep duration and regularity of sleep timing across the week.